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Silventoinen K, Lahtinen H, Korhonen K, Smith GD, Ripatti S, Morris T, Martikainen P. Marital status and genetic liability independently predict coronary heart disease incidence. Scand J Public Health 2024; 52:1-4. [PMID: 36071625 PMCID: PMC10845822 DOI: 10.1177/14034948221119634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 06/27/2022] [Accepted: 06/30/2022] [Indexed: 11/16/2022]
Abstract
AIMS Married individuals have a lower coronary heart disease (CHD) risk than non-married, but the mechanisms behind this are not fully understood. We analyzed whether genetic liability to CHD may affect these associations. METHODS Marital status, a polygenic score of CHD (PGS-CHD), and other risk factors for CHD were measured from 35,444 participants (53% female) in Finnish population-based surveys conducted between 1992 and 2012. During the register-based follow-up until 2020, there were 2439 fatal and non-fatal incident CHD cases. The data were analyzed using linear and Cox regression models. RESULTS Divorced and cohabiting men and women had a higher genetic risk of CHD than married individuals, but the difference was very small (0.023-0.058 standard deviation of PGS-CHD, p-values 0.011-0.429). Both marital status and PGS-CHD were associated with CHD incidence, but the associations were largely independent. Adjusting for behavioral and metabolic risk factors for CHD explained part of these associations (11-20%). No interaction was found between marital status and PGS-CHD for CHD incidence. CONCLUSIONS We showed minor differences between the marital status categories in PGS-CHD and demonstrated that marital status and genetic liability predicted CHD incidence largely independently. This emphasizes the need to measure multiple risk factors when predicting CHD risk.
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Affiliation(s)
- Karri Silventoinen
- Faculty of Social Sciences, University of Helsinki, Finland
- Faculty of Medicine, University of Helsinki, Finland
| | - Hannu Lahtinen
- Faculty of Social Sciences, University of Helsinki, Finland
| | | | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, UK
| | - Samuli Ripatti
- Faculty of Medicine, University of Helsinki, Finland
- Institute for Molecular Medicine Finland, Finland
- Broad Institute of MIT and Harvard, USA
| | - Tim Morris
- Population Health Sciences, Bristol Medical School, University of Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, UK
| | - Pekka Martikainen
- Faculty of Social Sciences, University of Helsinki, Finland
- Centre for Health Equity Studies, Stockholm University, Sweden
- Max-Planck-Institute for Demographic Research, Germany
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Silventoinen K, Lahtinen H, Kilpi F, Morris TT, Davey Smith G, Martikainen P. Socio-economic differences in body mass index: the contribution of genetic factors. Int J Obes (Lond) 2024:10.1038/s41366-024-01459-w. [PMID: 38200145 DOI: 10.1038/s41366-024-01459-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 12/17/2023] [Accepted: 01/02/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND Higher mean body mass index (BMI) among lower socioeconomic position (SEP) groups is well established in Western societies, but the influence of genetic factors on these differences is not well characterized. METHODS We analyzed these associations using Finnish health surveys conducted between 1992 and 2017 (N = 33 523; 53% women) with information on measured weight and height, polygenic risk scores of BMI (PGS-BMI) and linked data from administrative registers to measure educational attainment, occupation-based social class and personal income. RESULTS In linear regressions, largest adjusted BMI differences were found between basic and tertiary educated men (1.4 kg/m2, 95% confidence interval [CI] 1.2; 1.6) and women (2.5 kg/m2, 95% CI 2.3; 2.8), and inverse BMI gradients were also found for social class and income. These SEP differences arose partly because mean PGS-BMI was higher and partly because PGS-BMI predicted BMI more strongly in lower SEP groups. The inverse SEP gradients of BMI were steeper in women than in men, but sex differences were not found in the genetic contributions to these differences. CONCLUSIONS Better understanding of the interplay between genes and environment provides insight into the mechanisms explaining SEP differences in BMI.
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Affiliation(s)
- Karri Silventoinen
- University of Helsinki, Faculty of Social Sciences, Population Research Unit, Helsinki, Finland.
| | - Hannu Lahtinen
- University of Helsinki, Faculty of Social Sciences, Population Research Unit, Helsinki, Finland
- Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
| | - Fanny Kilpi
- Bristol Medical School, University of Bristol, Population Health Sciences, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Tim T Morris
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - George Davey Smith
- Bristol Medical School, University of Bristol, Population Health Sciences, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Pekka Martikainen
- University of Helsinki, Faculty of Social Sciences, Population Research Unit, Helsinki, Finland
- Max Planck - University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
- Max-Planck-Institute for Demographic Research, Rostock, Germany
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Aaltonen S, Urjansson M, Varjonen A, Vähä-Ypyä H, Iso-Markku P, Kaartinen S, Vasankari T, Kujala UM, Silventoinen K, Kaprio J, Vuoksimaa E. Accelerometer-measured physical activity and sedentary behavior in nonagenarians: Associations with self-reported physical activity, anthropometric, sociodemographic, health and cognitive characteristics. PLoS One 2023; 18:e0294817. [PMID: 38055660 DOI: 10.1371/journal.pone.0294817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/09/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Research on device-based physical activity in the oldest-old adults is scarce. We examined accelerometer-measured physical activity and sedentary behavior in nonagenarians. We also investigated how the accelerometer characteristics associate with nonagenarians' self-reported physical activity, anthropometric, sociodemographic, health and cognitive characteristics. METHODS Nonagenarians from a population-based cohort study (N = 38, mean age 91.2) used accelerometers during the waking hours for seven days. They also participated in a health survey and cognitive telephone interview. The Wald test and Pearson and polyserial correlations were used to analyze the data. RESULTS The participants' average day consisted of 2931 steps, 11 minutes of moderate-to-vigorous physical activity and 13.6 hours of sedentary time. Physical activity bouts less than 3 minutes per day and sedentary time bouts of 20-60 minutes per day were the most common. No sex differences were found. Many accelerometer-measured and self-reported physical activity characteristics correlated positively (correlations ≥0.34, p-values <0.05). The low levels of many accelerometer-measured physical activity characteristics associated with low education (correlations ≥0.25, p-values <0.05), dizziness (correlations ≤-0.42, p-values <0.01) and fear of falling (correlations ≤-0.45, p-values <0.01). Fear of falling was also associated with accelerometer-measured sedentary behavior characteristics (correlations -0.42 or ≥0.43). CONCLUSIONS Nonagenarians were mostly sedentary and low in physical activity, but individual variability existed. Accelerometer-measured and self-reported physical activity had a good consistency. Education, dizziness and fear of falling were consistently related to accelerometer-measured characteristics in nonagenarians.
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Affiliation(s)
- Sari Aaltonen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Mia Urjansson
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Anni Varjonen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Henri Vähä-Ypyä
- UKK Institute for Health Promotion Research, Tampere, Finland
| | - Paula Iso-Markku
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- HUS Diagnostic Center, Clinical Physiology and Nuclear Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Sara Kaartinen
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Physical Medicine and Rehabilitation, HUS Hyvinkää Hospital, Hyvinkää, Finland
| | - Tommi Vasankari
- UKK Institute for Health Promotion Research, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | | | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
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Silventoinen K, Luukkonen J, Myrskylä M, Martikainen P. Birth size, school performance and family social position: a study of 650,000 children. Pediatr Res 2023; 94:2105-2114. [PMID: 37516757 PMCID: PMC10665183 DOI: 10.1038/s41390-023-02757-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 06/15/2023] [Accepted: 06/19/2023] [Indexed: 07/31/2023]
Abstract
BACKGROUND Low birth weight (BW) is associated with lower cognitive functioning, but less is known of these associations across the full range of the BW distribution and its components. We analyzed how BW, birth length (BL) and birth ponderal index (BPI, kg/m3) are associated with school performance and how childhood family social position modifies these associations. METHODS Medical birth records of all Finnish children born in 1987-1997 were linked to school performance records at 16 years of age (N = 642,425). We used population averaged and within-siblings fixed-effects linear regression models. RESULTS BL showed a linear and BW a curvilinear association with school performance whereas for BPI the association was weak. The strongest association was found for BL explaining 0.08% of the variation in school performance in boys and 0.14% in girls. Demographic, gestational and social factors partly explained these associations. Similar but weaker associations were found within sibships. The association of BL with school performance was stronger at lower levels of family social position. CONCLUSION BL shows a linear association with school performance and can explain more school performance variation than BW. At the population level, BL can offer useful information on intrauterine environmental factors relevant for cognitive performance. IMPACT Birth length is linearly associated with school performance in late adolescence and explains a larger proportion of school performance variation than birth weight. The association between birth length and school performance is stronger in families with lower socio-economic position. At the population level, birth length can offer information on the intrauterine environment relevant for later cognitive performance.
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Affiliation(s)
- Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland.
- Research Institute of Human Development, Kyoto International Social Welfare Exchange Centre, Kyoto, Japan.
| | - Juha Luukkonen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Mikko Myrskylä
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Max Planck Institute for Demographic Research, Rostock, Germany
- Max Planck-University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany
- Max Planck-University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
| | - Pekka Martikainen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Max Planck Institute for Demographic Research, Rostock, Germany
- Max Planck-University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany
- Max Planck-University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
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Berntzen BJ, Palviainen T, Silventoinen K, Pietiläinen KH, Kaprio J. Polygenic risk of obesity and BMI trajectories over 36 years: A longitudinal study of adult Finnish twins. Obesity (Silver Spring) 2023; 31:3086-3094. [PMID: 37987187 PMCID: PMC10947257 DOI: 10.1002/oby.23906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/04/2023] [Accepted: 08/06/2023] [Indexed: 11/22/2023]
Abstract
OBJECTIVE This study investigated 36-year BMI trajectories in twins whose BMI in young adulthood was below, within, or above their genetically predicted BMI, with a focus on twin pairs with large intrapair BMI differences (within-pair ΔBMI ≥ 3 kg/m2 ). METHODS Together, 3227 like-sexed twin pairs (34% monozygotic) were examined at age ~30 years in 1975 and followed up in 1981, 1990, and 2011. An individual's observed BMI in 1975 was considered within (±2.0), below (<-2.0), or above (>+2.0) genetically predicted BMI, measured by a polygenic risk score of 996,919 single nucleotide polymorphisms. RESULTS In monozygotic and dizygotic twin pairs with large intrapair BMI differences, the co-twin with a higher observed BMI in 1975 deviated above predicted BMI more frequently (~2/3) than the co-twin with a lower BMI deviated below prediction (~1/3). Individuals below, within, and above prediction in 1975 reached, respectively, normal weight, overweight, and obesity by 2011, with a mean BMI increase of 4.5 (95% CI: 4.3-4.8). CONCLUSIONS Categorizing BMI as below, within, or above polygenic risk score-predicted BMI helps identifying individuals who have been resistant or susceptible to weight gain. This may provide new insights into determinants and consequences of obesity.
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Affiliation(s)
- Bram J. Berntzen
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
| | - Karri Silventoinen
- Faculty of Social Sciences, Population Research UnitUniversity of HelsinkiHelsinkiFinland
| | - Kirsi H. Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
- HealthyWeightHub, Endocrinology, Abdominal CenterHelsinki University Hospital and University of HelsinkiHelsinkiFinland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
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Howe LJ, Rasheed H, Jones PR, Boomsma DI, Evans DM, Giannelis A, Hayward C, Hopper JL, Hughes A, Lahtinen H, Li S, Lind PA, Martin NG, Martikainen P, Medland SE, Morris TT, Nivard MG, Pingault JB, Silventoinen K, Smith JA, Willoughby EA, Wilson JF. Educational attainment, health outcomes and mortality: a within-sibship Mendelian randomization study. Int J Epidemiol 2023; 52:1579-1591. [PMID: 37295953 PMCID: PMC10555788 DOI: 10.1093/ije/dyad079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 05/12/2023] [Indexed: 06/12/2023] Open
Abstract
BACKGROUND Previous Mendelian randomization (MR) studies using population samples (population MR) have provided evidence for beneficial effects of educational attainment on health outcomes in adulthood. However, estimates from these studies may have been susceptible to bias from population stratification, assortative mating and indirect genetic effects due to unadjusted parental genotypes. MR using genetic association estimates derived from within-sibship models (within-sibship MR) can avoid these potential biases because genetic differences between siblings are due to random segregation at meiosis. METHODS Applying both population and within-sibship MR, we estimated the effects of genetic liability to educational attainment on body mass index (BMI), cigarette smoking, systolic blood pressure (SBP) and all-cause mortality. MR analyses used individual-level data on 72 932 siblings from UK Biobank and the Norwegian HUNT study, and summary-level data from a within-sibship Genome-wide Association Study including >140 000 individuals. RESULTS Both population and within-sibship MR estimates provided evidence that educational attainment decreased BMI, cigarette smoking and SBP. Genetic variant-outcome associations attenuated in the within-sibship model, but genetic variant-educational attainment associations also attenuated to a similar extent. Thus, within-sibship and population MR estimates were largely consistent. The within-sibship MR estimate of education on mortality was imprecise but consistent with a putative effect. CONCLUSIONS These results provide evidence of beneficial individual-level effects of education (or liability to education) on adulthood health, independently of potential demographic and family-level confounders.
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Affiliation(s)
- Laurence J Howe
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Humaira Rasheed
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
| | - Paul R Jones
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Registry, Vrije Universiteit, Amsterdam, Netherlands
- Amsterdam Public Health (APH) and Amsterdam Reproduction and Development (AR&D)
| | - David M Evans
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
| | | | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Amanda Hughes
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Hannu Lahtinen
- Population Research Unit, University of Helsinki, Helsinki, Finland
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Pekka Martikainen
- Population Research Unit, University of Helsinki, Helsinki, Finland
- The Max Planck Institute for Demographic Research, Germany
- Department of Public Health Sciences, Stockholm University, Sweden
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Australia
- School of Psychology, University of Queensland, Brisbane, Australia
| | - Tim T Morris
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Michel G Nivard
- Department of Biological Psychology, Netherlands Twin Registry, Vrije Universiteit, Amsterdam, Netherlands
| | - Jean-Baptiste Pingault
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | | | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | | | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, UK
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Wang M, Raza A, Narusyte J, Silventoinen K, Böckerman P, Svedberg P, Ropponen A. Family-Related Life Events as Predictors of Labor Market Marginalization Trajectories: A Cohort Study of Swedish Twins. J Occup Environ Med 2023; 65:627-634. [PMID: 37143233 PMCID: PMC10417248 DOI: 10.1097/jom.0000000000002869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
OBJECTIVES The aims of the study are to investigate trajectories of labor market marginalization (LMM) and to examine the associations between family-related life events and LMM trajectories while accounting for familial factors. METHODS This is a prospective cohort study of 37,867 Swedish twins. Data were analyzed by group-based trajectory modeling. Associations of family-related life events with trajectory groups were estimated by multinomial logistic regression. RESULTS Most participants had no or low levels of LMM. Individuals who stayed married over time or changed from single without children to married with children had a decreased risk of LMM. The risk of LMM over time was higher among individuals who changed from married to being single. CONCLUSIONS Being or getting married as well as having children decreases the risk of LMM while divorce is a risk factor for LMM.
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Ropponen A, Narusyte J, Wang M, Silventoinen K, Böckerman P, Svedberg P. Genetic and environmental contributions to individual differences in sustainable working life-A Swedish twin cohort study. PLoS One 2023; 18:e0289074. [PMID: 37498854 PMCID: PMC10374081 DOI: 10.1371/journal.pone.0289074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 07/10/2023] [Indexed: 07/29/2023] Open
Abstract
Although genetics is known to have a role in sickness absences (SA), disability pensions (DP) and in their mutual associations, the empirical knowledge is scarce on not having these interruptions, i.e., sustainable working life. Hence, we aimed to investigate how genetic and environmental factors affect individual variation in sustainable working life in short-term (two consecutive years) and in long-term (22 years of follow-up) using the classical twin modeling based on different genetic relatedness of mono- and dizygotic twins. The final sample (n = 51 071) included Swedish same-sex twins with known zygosity born between 1930 and 1990 (53% women) with complete national register data of employment, SA, DP, unemployment, old-age pension, emigration, and death. For the short-term sustainable working life, genetic factors explained 36% (95% confidence intervals (CI) 31-41%), environmental factors shared by co-twins such as family background 8% (95% CI 5-14%) and environmental factors unique to each twin individual 56% (95% CI 56-56%) on the individual differences. For the long-term sustainable working life, the largest proportions on individual differences were explained by environmental factors shared by co-twins (46%, 95% CI 44-48%) and unique to each twin individual (37% 95% CI 36-38%) whereas a small proportion was explained by genetic factors (18%, 95%CI 14-22%). To conclude, short-term sustainable working life was explained to a large extent by unique environment and to lesser extent by genetic factors whereas long-term (22 years) sustainable working life had both moderate unique and common environmental effect, and to lower extent genetic effects contributing to individual differences. These findings suggest that sustainable working life have different short- and long-term predictors.
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Affiliation(s)
- Annina Ropponen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Finnish Institute of Occupational Health, Helsinki, Finland
| | - Jurgita Narusyte
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Mo Wang
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Karri Silventoinen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Petri Böckerman
- School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
- Labour Institute for Economic Research LABORE, Helsinki, Finland
- IZA Institute of Labor Economics, Bonn, Germany
| | - Pia Svedberg
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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Gonggrijp BMA, Silventoinen K, Dolan CV, Boomsma DI, Kaprio J, Willemsen G. The mechanism of assortative mating for educational attainment: a study of Finnish and Dutch twins and their spouses. Front Genet 2023; 14:1150697. [PMID: 37396041 PMCID: PMC10311485 DOI: 10.3389/fgene.2023.1150697] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 05/31/2023] [Indexed: 07/04/2023] Open
Abstract
Introduction: Assortative mating refers describes a phenomenon in which individuals with similar phenotypic traits are more likely to mate and reproduce with each other; i.e. assortative mating occurs when individuals choose partners based on their similarity or dissimilarity in certain traits.to patterns of non-random mating of spouses leading to phenotypic resemblance. There are various theories about the its underlying mechanisms, which have different genetic consequences. Methods: We analyzed examined two possible mechanisms underlying assortative mating - phenotypic assortment and social homogamy - for educational attainment in two countries utilizing data of mono- and dizygotic twins and their spouses (1,451 Finnish and 1,616 Dutch twin-spouse pairs). Results: The spousal correlations were 0.51 in Finland and 0.45 in the Netherlands, to which phenotypic assortment contributed 0.35 and 0.30, and social homogamy 0.16 and 0.15, respectively. Conclusion: Both social homogamy and phenotypic assortment are important processes in spouse selection in Finland and the Netherlands. In both countries, phenotypic assortment contributes to a greater degree to the similarity of spouses than social homogamy.
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Affiliation(s)
- Bodine M. A. Gonggrijp
- Netherlands Institute for the Study of Crime and Law Enforcement (NSCR), Amsterdam, Netherlands
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, VU Amsterdam, Amsterdam, Netherlands, Netherlands
| | - Karri Silventoinen
- Faculty of Social Sciences, University of Helsinki, Helsinki, Uusimaa, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Uusimaa, Finland
| | - Conor V. Dolan
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, VU Amsterdam, Amsterdam, Netherlands, Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, VU Amsterdam, Amsterdam, Netherlands, Netherlands
- Amsterdam Public Health Research Institute, VU Medical Center, Amsterdam, Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Uusimaa, Finland
| | - Gonneke Willemsen
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, VU Amsterdam, Amsterdam, Netherlands, Netherlands
- Amsterdam Public Health Research Institute, VU Medical Center, Amsterdam, Netherlands
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10
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Silventoinen K, Lahtinen H, Davey Smith G, Morris TT, Martikainen P. Height, social position and coronary heart disease incidence: the contribution of genetic and environmental factors. J Epidemiol Community Health 2023; 77:384-390. [PMID: 36963814 DOI: 10.1136/jech-2022-219907] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/13/2023] [Indexed: 03/26/2023]
Abstract
BACKGROUND The associations between height, socioeconomic position (SEP) and coronary heart disease (CHD) incidence are well established, but the contribution of genetic factors to these associations is still poorly understood. We used a polygenic score (PGS) for height to shed light on these associations. METHODS Finnish population-based health surveys in 1992-2011 (response rates 65-93%) were linked to population registers providing information on SEP and CHD incidence up to 2019. The participants (N=29 996; 54% women) were aged 25-75 at baseline, and there were 1767 CHD incident cases (32% in women) during 472 973 person years of follow-up. PGS-height was calculated based on 33 938 single-nucleotide polymorphisms, and residual height was defined as the residual of height after adjusting for PGS-height in a linear regression model. HRs of CHD incidence were calculated using Cox regression. RESULTS PGS-height and residual height showed clear gradients for education, social class and income, with a larger association for residual height. Residual height also showed larger associations with CHD incidence (HRs per 1 SD 0.94 in men and 0.87 in women) than PGS-height (HRs per 1 SD 0.99 and 0.97, respectively). Only a small proportion of the associations between SEP and CHD incidence was statistically explained by the height indicators (6% or less). CONCLUSIONS Residual height associations with SEP and CHD incidence were larger than for PGS-height. This supports the role of material and social living conditions in childhood as contributing factors to the association of height with both SEP and CHD risk.
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Affiliation(s)
- Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Hannu Lahtinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - George Davey Smith
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Tim T Morris
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Pekka Martikainen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Centre for Health Equity Studies, Stockholm University, Stockholm, Sweden
- Max-Planck-Institute for Demographic Research, Rostock, Germany
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11
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Drouard G, Silventoinen K, Latvala A, Kaprio J. Genetic and Environmental Factors Underlying Parallel Changes in Body Mass Index and Alcohol Consumption: A 36-Year Longitudinal Study of Adult Twins. Obes Facts 2023; 16:224-236. [PMID: 36882010 PMCID: PMC10826601 DOI: 10.1159/000529835] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 02/17/2023] [Indexed: 03/09/2023] Open
Abstract
INTRODUCTION While the genetic and environmental underpinnings of body weight and alcohol use are fairly well-known, determinants of simultaneous changes in these traits are still poorly known. We sought to quantify the environmental and genetic components underlying parallel changes in weight and alcohol consumption and to investigate potential covariation between them. METHODS The analysis comprised 4,461 adult participants (58% women) from the Finnish Twin Cohort with four measures of alcohol consumption and body mass index (BMI) over a 36-year follow-up. Trajectories of each trait were described by growth factors, defined as intercepts (i.e., baseline) and slopes (i.e., change over follow-up), using latent growth curve modeling. Growth values were used for male (190 monozygotic pairs, 293 dizygotic pairs) and female (316 monozygotic pairs, 487 dizygotic pairs) same-sex complete twin pairs in multivariate twin modeling. The variances and covariances of growth factors were then decomposed into genetic and environmental components. RESULTS The baseline heritabilities were similar in men (BMI: h2 = 79% [95% confidence interval: 74, 83]; alcohol consumption: h2 = 49% [32, 67]) and women (h2 = 77% [73, 81]; h2 = 45% [29, 61]). Heritabilities of BMI change were similar in men (h2 = 52% [42, 61]) and women (h2 = 57% [50, 63]), but the heritability of change in alcohol consumption was significantly higher (p = 0.03) in men (h2 = 45% [34, 54]) than in women (h2 = 31% [22, 38]). Significant additive genetic correlations between BMI at baseline and change in alcohol consumption were observed in both men (rA = -0.17 [-0.29, -0.04]) and women (rA = -0.18 [-0.31, -0.06]). Non-shared environmental factors affecting changes in alcohol consumption and BMI were correlated in men (rE = 0.18 [0.06, 0.30]). Among women, non-shared environmental factors affecting baseline alcohol consumption and the change in BMI were inversely correlated (rE = -0.11 [-0.20, -0.01]). CONCLUSIONS Based on genetic correlations, genetic variation underlying BMI may affect changes in alcohol consumption. Independent of genetic effects, change in BMI correlates with change in alcohol consumption in men, suggesting direct effects between them.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Antti Latvala
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Institute of Criminology and Legal Policy, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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12
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Silventoinen K, Maia J, Li W, Sund R, Gouveia ÉR, Antunes A, Marques G, Thomis M, Jelenkovic A, Kaprio J, Freitas D. Genetic regulation of body size and morphology in children: a twin study of 22 anthropometric traits. Int J Obes (Lond) 2023; 47:181-189. [PMID: 36635383 PMCID: PMC10023566 DOI: 10.1038/s41366-023-01253-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 01/02/2023] [Accepted: 01/04/2023] [Indexed: 01/13/2023]
Abstract
BACKGROUND Anthropometric measures show high heritability, and genetic correlations have been found between obesity-related traits. However, we lack a comprehensive analysis of the genetic background of human body morphology using detailed anthropometric measures. METHODS Height, weight, 7 skinfold thicknesses, 7 body circumferences and 4 body diameters (skeletal breaths) were measured in 214 pairs of twin children aged 3-18 years (87 monozygotic pairs) in the Autonomous Region of Madeira, Portugal. Factor analysis (Varimax rotation) was used to analyze the underlying structure of body physique. Genetic twin modeling was used to estimate genetic and environmental contributions to the variation and co-variation of the anthropometric traits. RESULTS Together, two factors explained 80% of the variation of all 22 anthropometric traits in boys and 73% in girls. Obesity measures (body mass index, skinfold thickness measures, as well as waist and hip circumferences) and limb circumferences loaded most strongly on the first factor, whereas height and body diameters loaded especially on the second factor. These factors as well as all anthropometric measures showed high heritability (80% or more for most of the traits), whereas the rest of the variation was explained by environmental factors not shared by co-twins. Obesity measures showed high genetic correlations (0.75-0.98). Height showed the highest genetic correlations with body diameter measures (0.58-0.76). Correlations between environmental factors not shared by co-twins were weaker than the genetic correlations but still substantial. The correlation patterns were roughly similar in boys and girls. CONCLUSIONS Our results show high genetic correlations underlying the human body physique, suggesting that there are sets of genes widely affecting anthropometric traits. Better knowledge of these genetic variants can help to understand the development of obesity and other features of the human physique.
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Affiliation(s)
- Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland.
| | - José Maia
- Center of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, Porto, Portugal
| | - Weilong Li
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Reijo Sund
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Élvio R Gouveia
- Department of Physical Education and Sport, University of Madeira, Funchal, Portugal
- LARSYS, Interactive Technologies Institute, Funchal, Portugal
| | - António Antunes
- Department of Physical Education and Sport, University of Madeira, Funchal, Portugal
| | - Gonçalo Marques
- Department of Physical Education and Sport, University of Madeira, Funchal, Portugal
| | - Martine Thomis
- Physical Activity, Sports & Health Research Group, Department of Movement Sciences, Faculty of Movement and Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Aline Jelenkovic
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country, Bilbao, Spain
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Duarte Freitas
- Center of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, Porto, Portugal
- Department of Physical Education and Sport, University of Madeira, Funchal, Portugal
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13
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Wang M, Raza A, Narusyte J, Silventoinen K, Böckerman P, Svedberg P, Ropponen A. Life events as predictors of unsustainable working life trajectories from a life course perspective. Eur J Public Health 2022. [DOI: 10.1093/eurpub/ckac129.093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
The association between family-related life events (e.g., getting married or having children) and unsustainable working life in terms of unemployment, sickness absence and disability pension (SA/DP) are rarely studied from a life-course perspective although having public health importance. We investigated trajectories of unsustainable working life, and the associations between change in family-related life events and unsustainable working life trajectories by controlling for familial factors.
Methods
This is a prospective cohort study of 37,867 Swedish twins aged between 20-40 years on 31st December 1994. Data on trajectories of annual unemployment, SA/DP, and a combined measure of unsustainable working life months was collected from the Swedish national registers. The trajectories over a 23-year period were analysed by group-based trajectory modelling. Associations of change in family-related life events with trajectory groups in the whole sample were estimated by multinomial logistic regression and in discordant twin pairs (n = 4,647 pairs) with conditional models.
Results
Most participants had no or low levels of unemployment, SA/DP or combined unsustainable working life during 1994-2016. Individuals who were stably married or changed from being single living without children to married living with children had a decreased risk of unsustainable working life compared to individuals with stable family-related life events. The risk of unsustainable working life months over time was higher among individuals who changed from married to single status regardless of having children (range of HRs:1.31-4.44).
Conclusions
Family-related life events such as maintaining the relationship or getting married and having children decreases the risk of unsustainable working life while divorce is a risk factor for unsustainable working life. From a public health perspective, actions to support family formation or life would consequently promote a sustainable working life.
Key messages
• Unsustainable working life was less likely among married and among those who changed from single living without children to married with children compared to those with stable family life events.
• Individuals who changed from being married to divorced status had an increased risk of unsustainable working life over time and therefore being potentially an important group for public health.
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Affiliation(s)
- M Wang
- Department of Clinical Neuroscience, Karolinska Institutet , Stockholm, Sweden
| | - A Raza
- Department of Clinical Neuroscience, Karolinska Institutet , Stockholm, Sweden
| | - J Narusyte
- Department of Clinical Neuroscience, Karolinska Institutet , Stockholm, Sweden
- Center of Epidemiology and Community Medicine, Stockholm County Council , Stockholm, Sweden
| | - K Silventoinen
- Department of Clinical Neuroscience, Karolinska Institutet , Stockholm, Sweden
- Population Research Unit, Faculty of Social Sciences, University of Helsinki , Helsinki, Finland
| | - P Böckerman
- School of Business and Economics, University of Jyväskylä , Jyväskylä, Finland
- Labour Institute for Economic Research , Helsinki, Finland
- IZA Institute of Labor Economics , Bonn, Germany
| | - P Svedberg
- Department of Clinical Neuroscience, Karolinska Institutet , Stockholm, Sweden
| | - A Ropponen
- Department of Clinical Neuroscience, Karolinska Institutet , Stockholm, Sweden
- Finnish Institute of Occupational Health , Helsinki, Finland
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14
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Ropponen A, Josefsson P, Böckerman P, Silventoinen K, Narusyte J, Wang M, Svedberg P. Sustainable Working Life Patterns in a Swedish Twin Cohort: Age-Related Sequences of Sickness Absence, Disability Pension, Unemployment, and Premature Death during Working Life. Int J Environ Res Public Health 2022; 19:10549. [PMID: 36078264 PMCID: PMC9517844 DOI: 10.3390/ijerph191710549] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 08/17/2022] [Accepted: 08/19/2022] [Indexed: 06/15/2023]
Abstract
We aimed to investigate sustainable working life via age-related sequences of sickness absence (SA), disability pension (DP), unemployment (UE), premature death, and the influence of individual characteristics, accounting for familial confounding. The sample included monozygotic (MZ) and dizygotic (DZ) same-sexed twin pairs with register data (n = 47,450) that were followed for 10 years in four age cohorts: 26-35 (n = 9892), 36-45 (n = 10,620), 46-55 (n = 12,964) and 56-65 (n = 13,974). A sequence analysis was done in a 7-element state space: 1. "Sustainable working life": SA/DP 0-30 days and UE 0-90 days; 2. "Unemployment >90 days": SA/DP 0-30 days and UE > 90 days; 3. "Moderate SA/DP": SA/DP 30-180 days; 4. "Almost full year of SA/DP": SA/DP 180-365 days; 5. "Full year of SA/DP": SA/DP ≥ 365 days; 6. Death; 7. Old-age pension. The largest cluster had a sustainable working life and never experienced states 2-6 (34-59%). Higher education and being married predicted a lower likelihood of experiencing states 2-6. The MZ twin pairs (vs. DZ) were more often in the same cluster suggesting the role of genetic factors. To conclude, the sustainable working life was the largest cluster group. Few individuals had prolonged periods of interruptions of sustainable working life meriting actions, especially in early adulthood for interventions to support workability.
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Affiliation(s)
- Annina Ropponen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
- Finnish Institute of Occupational Health, 00032 Työterveyslaitos, Finland
| | - Pontus Josefsson
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Petri Böckerman
- IZA Institute of Labor Economics, 53113 Bonn, Germany
- School of Business and Economics, University of Jyväskylä, 40014 Jyväskylä, Finland
- Labour Institute for Economic Research LABORE, 00100 Helsinki, Finland
| | - Karri Silventoinen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, 00014 Helsinki, Finland
| | - Jurgita Narusyte
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
- Center of Epidemiology and Community Medicine, Stockholm County Council, 104 31 Stockholm, Sweden
| | - Mo Wang
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Pia Svedberg
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
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15
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Silventoinen K, Li W, Jelenkovic A, Sund R, Yokoyama Y, Aaltonen S, Piirtola M, Sugawara M, Tanaka M, Matsumoto S, Baker LA, Tuvblad C, Tynelius P, Rasmussen F, Craig JM, Saffery R, Willemsen G, Bartels M, van Beijsterveldt CEM, Martin NG, Medland SE, Montgomery GW, Lichtenstein P, Krueger RF, McGue M, Pahlen S, Christensen K, Skytthe A, Kyvik KO, Saudino KJ, Dubois L, Boivin M, Brendgen M, Dionne G, Vitaro F, Ullemar V, Almqvist C, Magnusson PKE, Corley RP, Huibregtse BM, Knafo-Noam A, Mankuta D, Abramson L, Haworth CMA, Plomin R, Bjerregaard-Andersen M, Beck-Nielsen H, Sodemann M, Duncan GE, Buchwald D, Burt SA, Klump KL, Llewellyn CH, Fisher A, Boomsma DI, Sørensen TIA, Kaprio J. Changing genetic architecture of body mass index from infancy to early adulthood: an individual based pooled analysis of 25 twin cohorts. Int J Obes (Lond) 2022; 46:1901-1909. [PMID: 35945263 PMCID: PMC9492534 DOI: 10.1038/s41366-022-01202-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 07/22/2022] [Accepted: 07/25/2022] [Indexed: 11/09/2022]
Abstract
Background Body mass index (BMI) shows strong continuity over childhood and adolescence and high childhood BMI is the strongest predictor of adult obesity. Genetic factors strongly contribute to this continuity, but it is still poorly known how their contribution changes over childhood and adolescence. Thus, we used the genetic twin design to estimate the genetic correlations of BMI from infancy to adulthood and compared them to the genetic correlations of height. Methods We pooled individual level data from 25 longitudinal twin cohorts including 38,530 complete twin pairs and having 283,766 longitudinal height and weight measures. The data were analyzed using Cholesky decomposition offering genetic and environmental correlations of BMI and height between all age combinations from 1 to 19 years of age. Results The genetic correlations of BMI and height were stronger than the trait correlations. For BMI, we found that genetic correlations decreased as the age between the assessments increased, a trend that was especially visible from early to middle childhood. In contrast, for height, the genetic correlations were strong between all ages. Age-to-age correlations between environmental factors shared by co-twins were found for BMI in early childhood but disappeared altogether by middle childhood. For height, shared environmental correlations persisted from infancy to adulthood. Conclusions Our results suggest that the genes affecting BMI change over childhood and adolescence leading to decreasing age-to-age genetic correlations. This change is especially visible from early to middle childhood indicating that new genetic factors start to affect BMI in middle childhood. Identifying mediating pathways of these genetic factors can open possibilities for interventions, especially for those children with high genetic predisposition to adult obesity.
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Affiliation(s)
- Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland. .,Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan.
| | - Weilong Li
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Aline Jelenkovic
- Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country, Leioa, Spain.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Reijo Sund
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Yoshie Yokoyama
- Department of Public Health Nursing, Osaka Metropolitan University, Osaka, Japan
| | - Sari Aaltonen
- Institute for Molecular Medicine Finland FIMM, Helsinki, Finland
| | - Maarit Piirtola
- Institute for Molecular Medicine Finland FIMM, Helsinki, Finland.,UKK Institute - Centre for Health Promotion Research, Tampere, Finland
| | - Masumi Sugawara
- Faculty of Human Studies, Shirayuri University, Tokyo, Japan
| | - Mami Tanaka
- Center for Forensic Mental Health, Chiba University, Chiba, Japan
| | - Satoko Matsumoto
- Institute for Education and Human Development, Ochanomizu University, Tokyo, Japan
| | - Laura A Baker
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Catherine Tuvblad
- Department of Psychology, University of Southern California, Los Angeles, CA, USA.,School of Law, Psychology and Social Work, Örebro University, Örebro, Sweden
| | - Per Tynelius
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Finn Rasmussen
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Jeffrey M Craig
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), Deakin University School of Medicine, Geelong, Australia.,Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.,Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Richard Saffery
- Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.,Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Gonneke Willemsen
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, Amsterdam, Netherlands
| | - Meike Bartels
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, Amsterdam, Netherlands
| | | | - Nicholas G Martin
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Sarah E Medland
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, Riverside, CA, 92521, USA
| | - Kaare Christensen
- The Danish Twin Registry, Department of Public Health, Epidemiology, Biostatistics & Biodemography, University of Southern Denmark Odense, Odense, Denmark.,Department of Clinical Biochemistry and Pharmacology and Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | - Axel Skytthe
- The Danish Twin Registry, Department of Public Health, Epidemiology, Biostatistics & Biodemography, University of Southern Denmark Odense, Odense, Denmark
| | - Kirsten O Kyvik
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark.,Odense Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Kimberly J Saudino
- Boston University, Department of Psychological and Brain Sciencies, Boston, MA, USA
| | - Lise Dubois
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Michel Boivin
- École de psychologie, Université Laval, Québec, Canada
| | - Mara Brendgen
- Département de psychologie, Université du Québec à Montréal, Montréal, Québec, Canada
| | | | - Frank Vitaro
- École de psychoéducation, Université de Montréal, Montréal, Québec, Canada
| | - Vilhelmina Ullemar
- Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden.,Theme Women's Health, Karolinska University Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Pediatric Allergy and Pulmonology Unit at Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado, USA
| | - Brooke M Huibregtse
- Department of Psychology and Neuroscience, University of Colorado, Boulder, Colorado, USA
| | | | - David Mankuta
- Hadassah Hospital Obstetrics and Gynecology Department, Hebrew University Medical School, Jerusalem, Israel
| | - Lior Abramson
- The Hebrew University of Jerusalem, Jerusalem, Israel
| | | | - Robert Plomin
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Morten Bjerregaard-Andersen
- Bandim Health Project, INDEPTH Network, Bissau, Guinea-Bissau.,Department of Endocrinology, Hospital of Southwest Jutland, Esbjerg, Denmark.,Department of Endocrinology, Odense University Hospital, Odense, Denmark
| | | | - Morten Sodemann
- Department of Infectious Diseases, Odense University Hospital, Odense, Denmark
| | - Glen E Duncan
- Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Dedra Buchwald
- Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - S Alexandra Burt
- Department of Psychology, Michigan State University, East Lansing, Michigan, USA
| | - Kelly L Klump
- Department of Psychology, Michigan State University, East Lansing, Michigan, USA
| | - Clare H Llewellyn
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Abigail Fisher
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, Amsterdam, Netherlands
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Centre for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Public Health (Section of Epidemiology), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Institute for Molecular Medicine Finland FIMM, Helsinki, Finland
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16
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Rose RJ, Latvala A, Silventoinen K, Kaprio J. Alcohol consumption at age 18-25 and number of children at a 33-year follow-up: Individual and within-pair analyses of Finnish twins. Alcohol Clin Exp Res 2022; 46:1552-1564. [PMID: 35719054 PMCID: PMC9545724 DOI: 10.1111/acer.14886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 05/14/2022] [Accepted: 06/13/2022] [Indexed: 01/31/2023]
Abstract
BACKGROUND Do drinking patterns in late adolescence/early adulthood predict lifetime childlessness and number of children? Research on this question has been only tangentially relevant and the results inconsistent. The designs used to date have been compromised by genetic and environmental confounds that are poorly controlled; covariate effects of smoking and education that are often ignored; males being understudied; population-based sampling rare, and long-term prospective studies with genetically informative designs yet to be reported. METHOD In a 33-year follow-up, we linked the drinking patterns of >3500 Finnish twin pairs, assessed at ages 18-25, to registry data on their eventual number of children. Analyses distinguished associations of early drinking patterns with lifetime childlessness from those predictive of family size. Within-twin pair analyses used fixed-effects regression models to account for shared familial confounds and genetic liabilities. Childlessness was analyzed with Cox proportional hazards models and family size with Poisson regression. Analyses within-pairs and of twins as individuals were run before and after adjustment for smoking and education, and for oral contraceptive (OC) use in individual-level analyses of female twins. RESULTS Baseline abstinence and heavier drinking both significantly predicted lifetime childlessness in individual-level analyses. Few abstinent women used OCs, but they were nonetheless more often eventually childless; adjusting for smoking and education did not affect this finding. Excluding childless twins, Poisson models of family size showed heavier drinking at 18-25 to be predictive of fewer children in both men and women. Those associations were replicated in within-pair analyses of dizygotic twins, each level of heavier drinking being associated with smaller families. Among monozygotic twins, associations of drinking with completed family size yielded effects of similar magnitude, reaching significance at the highest levels of consumption, ruling out familial confounds. CONCLUSIONS Compared to moderate levels of drinking, both abstinence and heavier drinking in late adolescence/early adulthood predicted a greater likelihood of lifetime childlessness and eventual number of children. Familial confounds do not fully explain these associations.
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Affiliation(s)
- Richard J. Rose
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
| | - Antti Latvala
- Institute of Criminology and Legal PolicyFaculty of Social Sciences, University of HelsinkiHelsinkiFinland
| | - Karri Silventoinen
- Population Research Unit, Faculty of Social SciencesUniversity of HelsinkiHelsinkiFinland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
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17
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Silventoinen K, Jelenkovic A, Palviainen T, Dunkel L, Kaprio J. The Association Between Puberty Timing and Body Mass Index in a Longitudinal Setting: The Contribution of Genetic Factors. Behav Genet 2022; 52:186-194. [PMID: 35381915 PMCID: PMC9135891 DOI: 10.1007/s10519-022-10100-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 03/17/2022] [Indexed: 12/11/2022]
Abstract
We analyzed the contribution of genetic factors on the association between puberty timing and body mass index (BMI) using longitudinal data and two approaches: (i) genetic twin design and (ii) polygenic scores (PGS) of obesity indices. Our data were derived from Finnish cohorts: 9080 twins had information on puberty timing and BMI and 2468 twins also had genetic data. Early puberty timing was moderately associated with higher BMI in childhood in both boys and girls; in adulthood these correlations were weaker and largely disappeared after adjusting for childhood BMI. The largest proportion of these correlations was attributable to genetic factors. The higher PGSs of BMI and waist circumference were associated with earlier timing of puberty in girls, whereas weaker associations were found in boys. Early puberty is not an independent risk factor for adult obesity but rather reflects the association between puberty timing and childhood BMI contributed by genetic predisposition.
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Affiliation(s)
- Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014, Helsinki, Finland.
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| | - Aline Jelenkovic
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Bilbao, Spain
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Leo Dunkel
- Barts & the London Medical School, William Harvey Research Institute, London, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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18
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Howe LJ, Nivard MG, Morris TT, Hansen AF, Rasheed H, Cho Y, Chittoor G, Ahlskog R, Lind PA, Palviainen T, van der Zee MD, Cheesman R, Mangino M, Wang Y, Li S, Klaric L, Ratliff SM, Bielak LF, Nygaard M, Giannelis A, Willoughby EA, Reynolds CA, Balbona JV, Andreassen OA, Ask H, Baras A, Bauer CR, Boomsma DI, Campbell A, Campbell H, Chen Z, Christofidou P, Corfield E, Dahm CC, Dokuru DR, Evans LM, de Geus EJC, Giddaluru S, Gordon SD, Harden KP, Hill WD, Hughes A, Kerr SM, Kim Y, Kweon H, Latvala A, Lawlor DA, Li L, Lin K, Magnus P, Magnusson PKE, Mallard TT, Martikainen P, Mills MC, Njølstad PR, Overton JD, Pedersen NL, Porteous DJ, Reid J, Silventoinen K, Southey MC, Stoltenberg C, Tucker-Drob EM, Wright MJ, Hewitt JK, Keller MC, Stallings MC, Lee JJ, Christensen K, Kardia SLR, Peyser PA, Smith JA, Wilson JF, Hopper JL, Hägg S, Spector TD, Pingault JB, Plomin R, Havdahl A, Bartels M, Martin NG, Oskarsson S, Justice AE, Millwood IY, Hveem K, Naess Ø, Willer CJ, Åsvold BO, Koellinger PD, Kaprio J, Medland SE, Walters RG, Benjamin DJ, Turley P, Evans DM, Davey Smith G, Hayward C, Brumpton B, Hemani G, Davies NM. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects. Nat Genet 2022; 54:581-592. [PMID: 35534559 PMCID: PMC9110300 DOI: 10.1038/s41588-022-01062-7] [Citation(s) in RCA: 95] [Impact Index Per Article: 47.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 03/25/2022] [Indexed: 02/01/2023]
Abstract
Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.
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Affiliation(s)
- Laurence J Howe
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Michel G Nivard
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, the Netherlands
| | - Tim T Morris
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ailin F Hansen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Humaira Rasheed
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Yoonsu Cho
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Geetha Chittoor
- Department of Population Health Sciences, Geisinger Health, Danville, PA, USA
| | - Rafael Ahlskog
- Department of Government, Uppsala University, Uppsala, Sweden
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Teemu Palviainen
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
| | - Matthijs D van der Zee
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, the Netherlands
| | - Rosa Cheesman
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, UK
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Scott M Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Marianne Nygaard
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | | | | | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Jared V Balbona
- Department of Psychology & Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Helga Ask
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Christopher R Bauer
- BioMarin Pharmaceutical Inc., Novato, CA, USA
- Biomedical and Translational Informatics, Geisinger Health, Danville, PA, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health (APH) and Amsterdam Reproduction and Development (AR&D), Amsterdam, the Netherlands
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Harry Campbell
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | | | - Elizabeth Corfield
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
| | | | - Deepika R Dokuru
- Department of Psychology & Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Luke M Evans
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
- Department of Ecology & Evolutionary Biology, University of Colorado at Boulder, Boulder, CO, USA
| | - Eco J C de Geus
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Sudheer Giddaluru
- Institute of Health and Society, University of Oslo, Oslo, Norway
- Norwegian Institute of Public Health, Oslo, Norway
| | - Scott D Gordon
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - K Paige Harden
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - W David Hill
- Lothian Birth Cohorts Group, Department of Psychology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Amanda Hughes
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Shona M Kerr
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Yongkang Kim
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Antti Latvala
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
- Institute of Criminology and Legal Policy, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Deborah A Lawlor
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol NIHR Biomedical Research Centre, Bristol, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Skøyen, Oslo, Norway
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Travis T Mallard
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Pekka Martikainen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- The Max Planck Institute for Demographic Research, Rostock, Germany
- Department of Public Health Sciences, Stockholm University, Stockholm, Sweden
| | - Melinda C Mills
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK
| | - Pål Rasmus Njølstad
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | | | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | | | - Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Camilla Stoltenberg
- Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Elliot M Tucker-Drob
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | | | | | - John K Hewitt
- Department of Psychology & Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Matthew C Keller
- Department of Psychology & Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Michael C Stallings
- Department of Psychology & Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - James J Lee
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Kaare Christensen
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
- Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jean-Baptiste Pingault
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Robert Plomin
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Alexandra Havdahl
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Meike Bartels
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, the Netherlands
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Sven Oskarsson
- Department of Government, Uppsala University, Uppsala, Sweden
| | - Anne E Justice
- Department of Population Health Sciences, Geisinger Health, Danville, PA, USA
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
| | - Øyvind Naess
- Institute of Health and Society, University of Oslo, Oslo, Norway
- Norwegian Institute of Public Health, Oslo, Norway
| | - Cristen J Willer
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Internal Medicine: Cardiology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Philipp D Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Daniel J Benjamin
- UCLA Anderson School of Management, Los Angeles, CA, USA
- Human Genetics Department, UCLA David Geffen School of Medicine, Gonda (Goldschmied) Neuroscience and Genetics Research Center, Los Angeles, CA, USA
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Patrick Turley
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
- Department of Economics, University of Southern California, Los Angeles, CA, USA
| | - David M Evans
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Ben Brumpton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
- HUNT Research Center, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway.
| | - Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
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Silventoinen K, Korhonen K, Lahtinen H, Jelenkovic A, Havulinna AS, Ripatti S, Salomaa V, Davey Smith G, Martikainen P. Joint associations of depression, genetic susceptibility and the area of residence for coronary heart disease incidence. J Epidemiol Community Health 2022; 76:281-284. [PMID: 34407993 PMCID: PMC7615472 DOI: 10.1136/jech-2021-216451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 08/08/2021] [Indexed: 11/04/2022]
Abstract
BACKGROUND Depression is a risk factor for coronary heart disease (CHD), but less is known whether genetic susceptibility to CHD or regional-level social indicators modify this association. METHODS Risk factors of CHD including a Polygenic Risk Score (PRS) were measured for 19 999 individuals residing in Finland in 1997, 2002, 2007 and 2012 (response rates 60%-75%). During the register-based follow-up until 2015, there were 1381 fatal and non-fatal incident CHD events. Unemployment rate, degree of urbanisation and crime rate of the municipality of residence were used as regional level social indicators. HRs were calculated using register-based antidepressant purchases as a non-reversible time-dependent covariate. RESULTS Those having depression and in the highest quartile of PRS had somewhat higher CHD risk than predicted only by the main effects of depression and PRS (HR for interaction 1.53, 95% CI 0.95 to 2.45). Depression was moderately associated with CHD in high crime (HR 1.51, 95% CI 1.20 to 1.90) and weakly in low crime regions (HR 1.07, 95% CI 0.86 to 1.33; p value of interaction=0.087). Otherwise, we did not found evidence for interactions. CONCLUSIONS Those having both depression and high genetic susceptibility need a special attention in healthcare for CHD.
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Affiliation(s)
- Karri Silventoinen
- Department of Social Research, Population Research Unit, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Kaarina Korhonen
- Department of Social Research, Population Research Unit, University of Helsinki, Helsinki, Finland
| | - Hannu Lahtinen
- Department of Social Research, Population Research Unit, University of Helsinki, Helsinki, Finland
| | - Aline Jelenkovic
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Faculty of Medicine and Nursing, Department of Physiology, University of the Basque Country, Bilbao, Spain
| | - Aki S Havulinna
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, Helsinki, Finland
| | - Samuli Ripatti
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Veikko Salomaa
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - George Davey Smith
- Bristol Medical School, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Pekka Martikainen
- Department of Social Research, Population Research Unit, University of Helsinki, Helsinki, Finland
- Centre for Health Equity Studies, Stockholm University, Stockholm, Sweden
- Max-Planck-Institute for Demographic Research, Rostock, Germany
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20
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Kaartinen S, Silventoinen K, Korhonen T, Kujala UM, Kaprio J, Aaltonen S. Genetic and Environmental Effects on the Individual Variation and Continuity of Participation in Diverse Physical Activities. Med Sci Sports Exerc 2021; 53:2495-2502. [PMID: 34649261 DOI: 10.1249/mss.0000000000002744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
INTRODUCTION Participation in diverse physical activities has beneficial health effects. However, little is known on how genetic and environmental factors affect this trait. Thus, we examined to what extent these factors explain participation in diverse leisure-time physical activities from late adolescence to adulthood using a twin study design. METHODS The participants were Finnish twins who reported their participation in diverse leisure-time physical activities at ages 17 (n = 5429) and 34 yr (n = 4246). The number of physical activities engaged in was analyzed using applications of structural linear modeling for twin data. RESULTS On average, the total number of physical activities engaged in during leisure time was slightly over three at both ages and in both sexes, with moderate heritability estimates (40%-58%) from adolescence to adulthood. Environmental factors shared by co-twins (e.g., childhood family environment) influenced only in adolescence, being higher for women. Environmental influences unique to each co-twin explained the remaining variances (34%-57%), being higher at age 34 yr. Participation in diverse leisure-time physical activities correlated moderately between ages 17 and 34 yr (men: rtrait = 0.30, 95% confidence interval [CI] = 0.25-0.35; women: rtrait = 0.26, 95% CI = 0.22-0.31). In addition, genetic influences on participation in physical activities correlated moderately between adolescence and adulthood (rA = 0.51, 95% CI = 0.39-0.64, and 0.44, 95% CI = 0.34-0.55, respectively). These common genetic influences explained 93% of the trait correlations found in men and 85% in women. CONCLUSIONS Genetic and unique environmental influences explain a large proportion of variation in the number of leisure-time physical activities. However, the estimates vary by age and sex. Common genetic background mainly explains the continuity of the participation in diverse leisure-time physical activities between adolescence and adulthood.
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Affiliation(s)
- Sara Kaartinen
- Department of Public Health, University of Helsinki, Helsinki, FINLAND
| | | | - Tellervo Korhonen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, FINLAND
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | | | - Sari Aaltonen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, FINLAND
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21
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Masip G, Foraita R, Silventoinen K, Adan RAH, Ahrens W, De Henauw S, Hebestreit A, Keski-Rahkonen A, Lissner L, Mehlig K, Molnar D, Moreno LA, Pigeot I, Russo P, Veidebaum T, Bogl LH, Kaprio J. The temporal relationship between parental concern of overeating and childhood obesity considering genetic susceptibility: longitudinal results from the IDEFICS/I.Family study. Int J Behav Nutr Phys Act 2021; 18:139. [PMID: 34732214 PMCID: PMC8567680 DOI: 10.1186/s12966-021-01205-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 09/28/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Many genes and molecular pathways are associated with obesity, but the mechanisms from genes to obesity are less well known. Eating behaviors represent a plausible pathway, but because the relationships of eating behaviors and obesity may be bi-directional, it remains challenging to resolve the underlying pathways. A longitudinal approach is needed to assess the contribution of genetic risk during the development of obesity in childhood. In this study we aim to examine the relationships between the polygenic risk score for body mass index (PRS-BMI), parental concern of overeating and obesity indices during childhood. METHODS The IDEFICS/I.Family study is a school-based multicenter pan-European cohort of children observed for 6 years (mean ± SD follow-up 5.8 ± 0.4). Children examined in 2007/2008 (wave 1) (mean ± SD age: 4.4 ± 1.1, range: 2-9 years), in 2009/2010 (wave 2) and in 2013/2014 (wave 3) were included. A total of 5112 children (49% girls) participated at waves 1, 2 and 3. For 2656 children with genome-wide data we constructed a PRS based on 2.1 million single nucleotide polymorphisms. Z-score BMI and z-score waist circumference (WC) were assessed and eating behaviors and relevant confounders were reported by parents via questionnaires. Parental concern of overeating was derived from principal component analyses from an eating behavior questionnaire. RESULTS In cross-lagged models, the prospective associations between z-score obesity indices and parental concern of overeating were bi-directional. In mediation models, the association between the PRS-BMI and parental concern of overeating at wave 3 was mediated by baseline z-BMI (β = 0.16, 95% CI: 0.10, 0.21) and baseline z-WC (β = 0.17, 95% CI: 0.11, 0.23). To a lesser extent, baseline parental concern of overeating also mediated the association between the PRS-BMI and z-BMI at wave 3 (β = 0.10, 95% CI: 0.07, 0.13) and z-WC at wave 3 (β = 0.09, 95% CI: 0.07, 0.12). CONCLUSIONS The findings suggest that the prospective associations between obesity indices and parental concern of overeating are likely bi-directional, but obesity indices have a stronger association with future parental concern of overeating than vice versa. The findings suggest parental concern of overeating as a possible mediator in the genetic susceptibility to obesity and further highlight that other pathways are also involved. A better understanding of the genetic pathways that lead to childhood obesity can help to prevent weight gain. TRIAL REGISTRATION Registry number: ISRCTN62310987 Retrospectively registered 17 September 2018.
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Affiliation(s)
- Guiomar Masip
- Department of Public Health, University of Helsinki, Helsinki, Finland.
| | - Ronja Foraita
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Karri Silventoinen
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Roger A H Adan
- Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Wolfgang Ahrens
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
- Faculty of Mathematics and Computer Science, University of Bremen, Bremen, Germany
| | - Stefaan De Henauw
- Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Antje Hebestreit
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | | | - Lauren Lissner
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Kirsten Mehlig
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Dénés Molnar
- Department of Paediatrics, Medical School, University of Pécs, Pécs, Hungary
| | - Luis A Moreno
- GENUD (Growth, Exercise, Nutrition and Development) Research Group, Faculty of Health Sciences, University of Zaragoza Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria de Aragón, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición CIBEROBN, Instituto de Salud Carlos III, Madrid, Spain
| | - Iris Pigeot
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
- Faculty of Mathematics and Computer Science, University of Bremen, Bremen, Germany
| | - Paola Russo
- Institute of Food Sciences, National Research Council, Avellino, Italy
| | - Toomas Veidebaum
- Department of Chronic Diseases, National Institute for Health Development, Tallinn, Estonia
| | - Leonie H Bogl
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
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22
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Silventoinen K, Bogl LH, Jelenkovic A, Vuoksimaa E, Latvala A, Li W, Tan Q, Zhang D, Pang Z, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Willemsen G, Bartels M, van Beijsterveldt CEM, Rebato E, Corley RP, Huibregtse BM, Hopper JL, Tyler J, Duncan GE, Buchwald D, Silberg JL, Maes HH, Kandler C, Cozen W, Hwang AE, Mack TM, Nelson TL, Whitfield KE, Medda E, Nisticò L, Toccaceli V, Krueger RF, McGue M, Pahlen S, Martin NG, Medland SE, Montgomery GW, Heikkilä K, Derom CA, Vlietinck RF, Loos RJF, Magnusson PKE, Pedersen NL, Dahl Aslan AK, Hotopf M, Sumathipala A, Rijsdijk F, Siribaddana SH, Rose RJ, Sørensen TIA, Boomsma DI, Kaprio J. Educational attainment of same-sex and opposite-sex dizygotic twins: An individual-level pooled study of 19 twin cohorts. Horm Behav 2021; 136:105054. [PMID: 34488063 DOI: 10.1016/j.yhbeh.2021.105054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 08/16/2021] [Accepted: 08/17/2021] [Indexed: 11/15/2022]
Abstract
Comparing twins from same- and opposite-sex pairs can provide information on potential sex differences in a variety of outcomes, including socioeconomic-related outcomes such as educational attainment. It has been suggested that this design can be applied to examine the putative role of intrauterine exposure to testosterone for educational attainment, but the evidence is still disputed. Thus, we established an international database of twin data from 11 countries with 88,290 individual dizygotic twins born over 100 years and tested for differences between twins from same- and opposite-sex dizygotic pairs in educational attainment. Effect sizes with 95% confidence intervals (CI) were estimated by linear regression models after adjusting for birth year and twin study cohort. In contrast to the hypothesis, no difference was found in women (β = -0.05 educational years, 95% CI -0.11, 0.02). However, men with a same-sex co-twin were slightly more educated than men having an opposite-sex co-twin (β = 0.14 educational years, 95% CI 0.07, 0.21). No consistent differences in effect sizes were found between individual twin study cohorts representing Europe, the USA, and Australia or over the cohorts born during the 20th century, during which period the sex differences in education reversed favoring women in the latest birth cohorts. Further, no interaction was found with maternal or paternal education. Our results contradict the hypothesis that there would be differences in the intrauterine testosterone levels between same-sex and opposite-sex female twins affecting education. Our findings in men may point to social dynamics within same-sex twin pairs that may benefit men in their educational careers.
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Affiliation(s)
- Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland; Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan.
| | - Leonie H Bogl
- Institute for Molecular Medicine FIMM, Helsinki, Finland; Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
| | - Aline Jelenkovic
- Department of Physiology, University of the Basque Country (UPV/EHU), Bilbao, Spain; Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine FIMM, Helsinki, Finland
| | - Antti Latvala
- Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Weilong Li
- Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Qihua Tan
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Department of Public Health, Qingdao University Medical College, Qingdao, China
| | - Zengchang Pang
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Juan R Ordoñana
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain; IMIB-Arrixaca, Murcia, Spain
| | - Juan F Sánchez-Romera
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain; IMIB-Arrixaca, Murcia, Spain
| | - Lucia Colodro-Conde
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain; QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands
| | - Meike Bartels
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands
| | | | - Esther Rebato
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Bilbao, Spain
| | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA
| | | | - John L Hopper
- Twin Research Australia, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Victoria, Australia; Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Republic of Korea
| | - Jessica Tyler
- Twin Research Australia, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Glen E Duncan
- Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Dedra Buchwald
- Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Judy L Silberg
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Hermine H Maes
- Department of Human and Molecular Genetics, Psychiatry & Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Wendy Cozen
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA; USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Amie E Hwang
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Thomas M Mack
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA; USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Tracy L Nelson
- Department of Health and Exercise Sciences and Colorado School of Public Health, Colorado State University, USA
| | | | - Emanuela Medda
- Istituto Superiore di Sanità Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Lorenza Nisticò
- Istituto Superiore di Sanità Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Virgilia Toccaceli
- Istituto Superiore di Sanità Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Nicholas G Martin
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Sarah E Medland
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Grant W Montgomery
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Kauko Heikkilä
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Catherine A Derom
- Centre of Human Genetics, University Hospitals Leuven, Leuven, Belgium; Department of Obstetrics and Gynaecology, Ghent University Hospitals, Ghent, Belgium
| | | | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna K Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; School of Health Sciences, University of Skövde, Skövde, Sweden; Institute of Gerontology and Aging Research Network-Jönköping (ARN-J), School of Health and Welfare Jönköping University, Jönköping, Sweden
| | - Matthew Hotopf
- NIHR Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, UK
| | - Athula Sumathipala
- Institute of Research & Development, Battaramulla, Sri Lanka; Research Institute for Primary Care and Health Sciences, School for Primary Care Research (SPCR), Faculty of Health, Keele University, Staffordshire, UK
| | - Fruhling Rijsdijk
- King's College London, MRC Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Sisira H Siribaddana
- Institute of Research & Development, Battaramulla, Sri Lanka; Faculty of Medicine & Allied Sciences, Rajarata University of Sri Lanka Saliyapura, Sri Lanka
| | - Richard J Rose
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Centre for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Public Health (Section of Epidemiology), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, Helsinki, Finland; Department of Public Health, University of Helsinki, Helsinki, Finland
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23
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Wang M, Svedberg P, Narusyte J, Silventoinen K, Ropponen A. The role of familial confounding in the associations of physical activity, smoking and alcohol consumption with early exit from the labour market. Prev Med 2021; 150:106717. [PMID: 34242665 DOI: 10.1016/j.ypmed.2021.106717] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 06/28/2021] [Accepted: 07/03/2021] [Indexed: 10/20/2022]
Abstract
We investigated the associations between health behaviors and sustainable working life outcomes including all-cause disability pension, disability pensions due to musculoskeletal and mental diagnoses and unemployment. The role of familial factors behind these associations was studied by analysing discordant twin pairs. Our data included Swedish twins born in 1925-1986 (51891 twin individuals). Baseline data based on two independent surveys in 1998-2003 and 2005-2006 for health behaviors were linked to national registers on disability pension and unemployment until 2016. Cox proportional hazards models for hazard ratios (HR) with 95% confidence intervals (CI) were estimated for the whole sample adjusting for covariates. Analyses of health behavior discordant twin pairs (n = 5903 pairs) were conducted using conditional Cox models. In the whole cohort, the combination of healthy behaviors was associated with lower risk for all-cause disability pension, disability pension due to musculoskeletal diagnoses or mental diagnoses, and for unemployment (HRs 0.56-0.86, 95% CIs 0.51-0.92) as did being physically active (HRs 0.69-0.87, 95% CI 0.65-0.92). The discordant pair analyses confirmed the lower risk among those having healthy behaviors (HR 0.70-0.86) or being physically active (HR 0.86-0.87) for all-cause disability pension, disability pension due to musculoskeletal diagnoses, and for unemployment. To conclude, controlling the effects of covariates or familial confounding (i.e. discordant twin pair analyses) shows that being physically active or having several healthy behaviors predict better working life outcomes. This points towards independent association between healthy behavior and longer working life.
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Affiliation(s)
- Mo Wang
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Pia Svedberg
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jurgita Narusyte
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Center of Epidemiology and Community Medicine, Stockholm County Council, Sweden
| | - Karri Silventoinen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Annina Ropponen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Finnish Institute of Occupational Health, Helsinki, Finland.
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24
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Torvik FA, Flatø M, McAdams TA, Colman I, Silventoinen K, Stoltenberg C. Early Puberty Is Associated With Higher Academic Achievement in Boys and Girls and Partially Explains Academic Sex Differences. J Adolesc Health 2021; 69:503-510. [PMID: 33795203 DOI: 10.1016/j.jadohealth.2021.02.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 01/21/2021] [Accepted: 02/04/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE On average, boys have lower academic achievement than girls. We investigated whether the timing of puberty is associated with academic achievement, and whether later puberty among boys contributes to the sex difference in academic achievement. METHOD Examination scores at age 16 were studied among 13,477 British twins participating in the population-based Twins Early Development Study. A pubertal development scale, a height-based proxy of growth spurt, and age at menarche were used as indicators of puberty. Associations between puberty, sex, and academic achievement were estimated in phenotypic mediation models and biometric twin models. RESULTS Earlier puberty was associated with higher academic achievement both in boys and girls. The exception was early age at menarche in girls, which associated with lower academic achievement. More than half of the sex differences in academic achievement could be linked to sex differences in pubertal development, but part of this association appeared to be rooted in prepubertal differences. The biometric twin modelling indicated that the association between puberty and academic achievement was due to shared genetic risk factors. Genetic influences on pubertal development accounted for 7%-8% of the phenotypic variation in academic achievement. CONCLUSIONS Pubertal maturation relates to the examination scores of boys and of girls. This can give genes related to pubertal maturation an influence on outcomes in education and beyond. Sex differences in pubertal maturation can explain parts of the sex difference in academic achievement. Grading students when they are immature may not accurately measure their academic potential.
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Affiliation(s)
- Fartein Ask Torvik
- Centre For Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway.
| | - Martin Flatø
- Centre For Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Tom A McAdams
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Promenta Research Centre, University of Oslo, Oslo, Norway
| | - Ian Colman
- Centre For Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Karri Silventoinen
- Demographic Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Camilla Stoltenberg
- Norwegian Institute of Public Health, Oslo, Norway; Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
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25
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Martikainen P, Korhonen K, Jelenkovic A, Lahtinen H, Havulinna A, Ripatti S, Borodulin K, Salomaa V, Davey Smith G, Silventoinen K. Joint association between education and polygenic risk score for incident coronary heart disease events: a longitudinal population-based study of 26 203 men and women. J Epidemiol Community Health 2021; 75:651-657. [PMID: 33408166 DOI: 10.1136/jech-2020-214358] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 11/03/2020] [Accepted: 12/16/2020] [Indexed: 12/28/2022]
Abstract
BACKGROUND Genetic vulnerability to coronary heart disease (CHD) is well established, but little is known whether these effects are mediated or modified by equally well-established social determinants of CHD. We estimate the joint associations of the polygenetic risk score (PRS) for CHD and education on CHD events. METHODS The data are from the 1992, 1997, 2002, 2007 and 2012 surveys of the population-based FINRISK Study including measures of social, behavioural and metabolic factors and genome-wide genotypes (N=26 203). Follow-up of fatal and non-fatal incident CHD events (N=2063) was based on nationwide registers. RESULTS Allowing for age, sex, study year, region of residence, study batch and principal components, those in the highest quartile of PRS for CHD had strongly increased risk of CHD events compared with the lowest quartile (HR=2.26; 95% CI: 1.97 to 2.59); associations were also observed for low education (HR=1.58; 95% CI: 1.32 to 1.89). These effects were largely independent of each other. Adjustment for baseline smoking, alcohol use, body mass index, igh-density lipoprotein (HDL) and total cholesterol, blood pressure and diabetes attenuated the PRS associations by 10% and the education associations by 50%. We do not find strong evidence of interactions between PRS and education. CONCLUSIONS PRS and education predict CHD events, and these associations are independent of each other. Both can improve CHD prediction beyond behavioural risks. The results imply that observational studies that do not have information on genetic risk factors for CHD do not provide confounded estimates for the association between education and CHD.
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Affiliation(s)
- Pekka Martikainen
- Population Research Unit, University of Helsinki Faculty of Social Sciences, Helsinki, Finland
- Centre for Health Equity Studies, Stockholm University, Stockholm, Sweden
- Max Planck Institute for Demographic Research, Rostock, Germany
| | - Kaarina Korhonen
- Population Research Unit, University of Helsinki Faculty of Social Sciences, Helsinki, Finland
| | - Aline Jelenkovic
- Department of Physiology, University of the Basque Country, Bilbao, País Vasco, Spain
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Hannu Lahtinen
- Population Research Unit, University of Helsinki Faculty of Social Sciences, Helsinki, Finland
| | - Aki Havulinna
- Institute for Molecular Medicine Finland, Helsinki, Finland
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Uusimaa, Finland
| | - Samuli Ripatti
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Katja Borodulin
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Uusimaa, Finland
- Age Institute, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Uusimaa, Finland
| | - George Davey Smith
- Department of Social Medicine, University of Bristol, Bristol, Bristol, UK
| | - Karri Silventoinen
- Population Research Unit, University of Helsinki Faculty of Social Sciences, Helsinki, Finland
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26
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Carslake D, Fraser A, May MT, Palmer T, Silventoinen K, Tynelius P, Lawlor DA, Davey Smith G. Author Correction: Associations of mortality with own blood pressure using son's blood pressure as an instrumental variable. Sci Rep 2021; 11:5470. [PMID: 33658539 PMCID: PMC7930109 DOI: 10.1038/s41598-021-84494-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Affiliation(s)
- David Carslake
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK. .,Bristol Medical School, Population Health Sciences, Bristol, UK.
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Bristol Medical School, Population Health Sciences, Bristol, UK
| | - Margaret T May
- Bristol Medical School, Population Health Sciences, Bristol, UK
| | - Tom Palmer
- Department of Mathematics and Statistics, University of Lancaster, Lancaster, UK
| | - Karri Silventoinen
- Population Research Unit, Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Per Tynelius
- Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Bristol Medical School, Population Health Sciences, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Bristol Medical School, Population Health Sciences, Bristol, UK
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27
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Silventoinen K, Konttinen H. Obesity and eating behavior from the perspective of twin and genetic research. Neurosci Biobehav Rev 2021; 109:150-165. [PMID: 31959301 DOI: 10.1016/j.neubiorev.2019.12.012] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 11/11/2019] [Accepted: 12/09/2019] [Indexed: 12/21/2022]
Abstract
Obesity has dramatically increased during the last decades and is currently one of the most serious global health problems. We present a hypothesis that obesity is a neuro-behavioral disease having a strong genetic background mediated largely by eating behavior and is sensitive to the macro-environment; we study this hypothesis from the perspective of genetic research. Genetic family and genome-wide-association studies have shown well that body mass index (BMI, kg/m2) is a highly heritable and polygenic trait. New genetic variation of BMI emerges after early childhood. Candidate genes of BMI notably express in brain tissue, supporting that this new variation is related to behavior. Obesogenic environments at both childhood family and societal levels reinforce the genetic susceptibility to obesity. Genetic factors have a clear influence on macro-nutrient intake and appetite-related eating behavior traits. Results on the gene-by-diet interactions in obesity are mixed, but emerging evidence suggests that eating behavior traits partly mediate the effect of genes on BMI. However, more rigorous prospective study designs controlling for measurement bias are still needed.
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Affiliation(s)
- Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland; Department of Public Health, University of Helsinki, Helsinki, Finland.
| | - Hanna Konttinen
- Department of Social Research, University of Helsinki, Helsinki, Finland
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28
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Yang L, Hu Y, Silventoinen K, Martikainen P. Childhood adversity and trajectories of multimorbidity in mid-late life: China health and longitudinal retirement study. J Epidemiol Community Health 2020; 75:jech-2020-214633. [PMID: 33293288 DOI: 10.1136/jech-2020-214633] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Revised: 10/28/2020] [Accepted: 11/23/2020] [Indexed: 11/04/2022]
Abstract
BACKGROUND The association between childhood adversity and an individual's health in later life has been extensively studied in Western societies; however, little is known about this association for the development of multimorbidity in China. METHODS Three waves (2011-2012, 2013 and 2015) of the China Health and Retirement Longitudinal Study were used for adults aged 45-101 years. Multimorbidity was assessed by the summed scores of self-reported physician diagnoses of 14 chronic diseases. Childhood adversity was measured by the incidence of childhood abuse and neglect, negative caregiver's characteristics and low socioeconomic status. Latent growth curve modelling was used to investigate the trajectory of multimorbidity by childhood adversity. RESULTS Parental physical abuse was associated with increased number of chronic diseases (intercept: 0.119; 95% CI: 0.033 to 0.205 for men and 0.268: 95% CI: 0.188 to 0.348 for women) and a higher rate of increase (slope: 0.013: 95% CI: 0.000 to 0.027 for men and 0.022: 95% CI: 0.008 to 0.036 for women) in multimorbidity. Adequacy of food was associated with a lower number chronic diseases at baseline (men: -0.171: 95% CI: -0.245 to -0.097; women: -0.223: 95% CI: -0.294 to -0.152) and a slower rate of change in multimorbidity (men: -0.015 per year: 95% CI: -0.027 to -0.003; women: -0.012 per year: 95% CI: -0.024 to -0.001). CONCLUSIONS The results demonstrate that childhood adversity exerts long-lasting effects on multimorbidity among older adults in China. Prevention of childhood maltreatment may delay or even avert the emergence of multimorbidity in later life.
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Affiliation(s)
- Lei Yang
- School of Ethnology and Sociology, Minzu University of China, Beijing, China
| | - Yaoyue Hu
- School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Pekka Martikainen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Laboratory of Population Health, Max-Planck-Institute for Demographic Research, Rostock, Germany
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Matsumoto D, Inui F, Honda C, Tomizawa R, Watanabe M, Silventoinen K, Sakai N. Heritability and Environmental Correlation of Phase Angle with Anthropometric Measurements: A Twin Study. Int J Environ Res Public Health 2020; 17:ijerph17217810. [PMID: 33114521 PMCID: PMC7662672 DOI: 10.3390/ijerph17217810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 10/21/2020] [Accepted: 10/22/2020] [Indexed: 11/04/2022]
Abstract
Bioelectrical impedance analysis (BIA)-derived phase angle (PhA) is a valuable parameter to assess physical health. However, the genetic and environmental aspects of PhA are not yet well understood. The present study aimed to estimate the heritability of PhA and investigate the relationships between PhA and anthropometric measurements. PhA and skeletal muscle mass index (SMI) were examined using multi-frequency BIA in 168 Japanese twin volunteers (54 males and 114 females; mean age = 61.0 ± 16.5 years). We estimated the narrow-sense heritability of these parameters and the genetic and environmental relationships between them using a genetic twin modeling. For the PhA, 51% (95% confidence interval: 0.33, 0.64) of the variance was explained by additive genetic effects, and 49% (95% confidence interval: 0.36, 0.67) was explained by unique environmental effects. The heritability of PhA was lower than the height, body weight, and body mass index. PhA shared almost no genetic variation with anthropometric measurements and SMI but shared an environmental variation (14%) with SMI. These findings suggest that the genes affecting PhA are different than those affecting anthropometric measurements and SMI. The correlation between PhA and SMI is caused by common environmental factors.
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Affiliation(s)
- Daisuke Matsumoto
- Department of Physical Therapy, Faculty of Health Sciences, Kio University, 4-2-2 Umaminaka, Koryo-cho, Kitakatsuragi-gun, Nara 635-0832, Japan
- Health Promotion Center, Kio University, 4-2-2 Umaminaka, Koryo-cho, Kitakatsuragi-gun, Nara 635-0832, Japan;
- Center for Twin Research, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; (C.H.); (R.T.); (M.W.); (K.S.); (N.S.)
- Correspondence: ; Tel.: +81-745-54-1601
| | - Fujio Inui
- Health Promotion Center, Kio University, 4-2-2 Umaminaka, Koryo-cho, Kitakatsuragi-gun, Nara 635-0832, Japan;
- Center for Twin Research, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; (C.H.); (R.T.); (M.W.); (K.S.); (N.S.)
- Department of Nursing, Faculty of Health Sciences, Kio University, 4-2-2 Umaminaka, Koryo-cho, Kitakatsuragi-gun, Nara 635-0832, Japan
| | - Chika Honda
- Center for Twin Research, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; (C.H.); (R.T.); (M.W.); (K.S.); (N.S.)
- Faculty of Nursing, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
| | - Rie Tomizawa
- Center for Twin Research, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; (C.H.); (R.T.); (M.W.); (K.S.); (N.S.)
| | - Mikio Watanabe
- Center for Twin Research, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; (C.H.); (R.T.); (M.W.); (K.S.); (N.S.)
- Department of Clinical Laboratory and Biomedical Sciences, Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan
| | - Karri Silventoinen
- Center for Twin Research, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; (C.H.); (R.T.); (M.W.); (K.S.); (N.S.)
- Department of Social Research, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014 Helsinki, Finland
| | - Norio Sakai
- Center for Twin Research, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; (C.H.); (R.T.); (M.W.); (K.S.); (N.S.)
- Child Healthcare and Genetic Science Laboratory, Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan
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Ropponen A, Narusyte J, Silventoinen K, Svedberg P. Health behaviours and psychosocial working conditions as predictors of disability pension due to different diagnoses: a population-based study. BMC Public Health 2020; 20:1507. [PMID: 33023556 PMCID: PMC7541297 DOI: 10.1186/s12889-020-09567-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 09/18/2020] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND To investigate whether the clustering of different health behaviours (i.e. physical activity, tobacco use and alcohol consumption) influences the associations between psychosocial working conditions and disability pension due to different diagnoses. METHODS A population-based sample of 24,987 Swedish twins born before 1958 were followed from national registers for disability pension until 2013. Baseline survey data in 1998-2003 were used to assess health behaviours and psychosocial Job Exposure Matrix for job control, job demands and social support. Cox proportional hazards models were used to calculate hazard ratios (HR) with 95% confidence intervals (CI). RESULTS During follow-up, 1252 disability pensions due to musculoskeletal disorders (5%), 601 due to mental diagnoses (2%) and 1162 due to other diagnoses (5%) occurred. In the models controlling for covariates, each one-unit increase in job demands was associated with higher (HR 1.16, 95%CI 1.01-1.33) and in job control with lower (HR 0.87, 95%CI 0.80-0.94) risk of disability pension due to musculoskeletal disorders among those with unhealthy behaviours. Among those with healthy behaviours, one-unit increase of social support was associated with a higher risk of disability pension due to mental and due to other diagnoses (HRs 1.29-1.30, 95%CI 1.04-1.63). CONCLUSIONS Job control and job demands were associated with the risk of disability pension due to musculoskeletal disorders only among those with unhealthy behaviours. Social support was a risk factor for disability pension due to mental or other diagnoses among those with healthy behaviours. Workplaces and occupational health care should acknowledge these simultaneous circumstances in order to prevent disability pension.
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Affiliation(s)
- Annina Ropponen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden. .,Finnish Institute of Occupational Health, Helsinki, Finland.
| | - Jurgita Narusyte
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden.,Center of Epidemiology and Community Medicine, Stockholm County Council, Stockholm, Sweden
| | - Karri Silventoinen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden.,Department of Social Research, Population Research Unit, University of Helsinki, Helsinki, Finland
| | - Pia Svedberg
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden
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31
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Masip G, Silventoinen K, Keski-Rahkonen A, Palviainen T, Sipilä PN, Kaprio J, Bogl LH. The genetic architecture of the association between eating behaviors and obesity: combining genetic twin modeling and polygenic risk scores. Am J Clin Nutr 2020; 112:956-966. [PMID: 32685959 PMCID: PMC7528566 DOI: 10.1093/ajcn/nqaa181] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 06/12/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Obesity susceptibility genes are highly expressed in the brain suggesting that they might exert their influence on body weight through eating-related behaviors. OBJECTIVES To examine whether the genetic susceptibility to obesity is mediated by eating behavior patterns. METHODS Participants were 3977 twins (33% monozygotic, 56% females), aged 31-37 y, from wave 5 of the FinnTwin16 study. They self-reported their height and weight, eating behaviors (15 items), diet quality, and self-measured their waist circumference (WC). For 1055 twins with genome-wide data, we constructed a polygenic risk score for BMI (PRSBMI) using almost 1 million single nucleotide polymorphisms. We used principal component analyses to identify eating behavior patterns, twin modeling to decompose correlations into genetic and environmental components, and structural equation modeling to test mediation models between the PRSBMI, eating behavior patterns, and obesity measures. RESULTS We identified 4 moderately heritable (h2 = 36-48%) eating behavior patterns labeled "snacking," "infrequent and unhealthy eating," "avoidant eating," and "emotional and external eating." The highest phenotypic correlation with obesity measures was found for the snacking behavior pattern (r = 0.35 for BMI and r = 0.32 for WC; P < 0.001 for both), largely due to genetic factors in common (bivariate h2 > 70%). The snacking behavior pattern partially mediated the association between the PRSBMI and obesity measures (βindirect = 0.06; 95% CI: 0.02, 0.09; P = 0.002 for BMI; and βindirect = 0.05; 95% CI: 0.02, 0.08; P = 0.003 for WC). CONCLUSIONS Eating behavior patterns share a common genetic liability with obesity measures and are moderately heritable. Genetic susceptibility to obesity can be partly mediated by an eating pattern characterized by frequent snacking. Obesity prevention efforts might therefore benefit from focusing on eating behavior change, particularly in genetically susceptible individuals.
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Affiliation(s)
- Guiomar Masip
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Karri Silventoinen
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | | | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Pyry N Sipilä
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Leonie H Bogl
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
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32
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Aaltonen S, Latvala A, Jelenkovic A, Rose RJ, Kujala UM, Kaprio J, Silventoinen K. Physical Activity and Academic Performance: Genetic and Environmental Associations. Med Sci Sports Exerc 2020; 52:381-390. [PMID: 31425387 DOI: 10.1249/mss.0000000000002124] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
INTRODUCTION Physical activity and academic performance are believed to be associated. Though both traits are partially heritable, it remains unclear whether these traits also share a genetic and/or environmental background in common. We aimed to examine to what extent leisure time physical activity and academic performance share genetic and environmental effects from early adolescence to young adulthood. METHODS Participants were Finnish twins (2543-2693 individuals/study wave) who reported their leisure-time physical activity at ages 12, 14, 17, and 24 yr. Academic performance was assessed with teacher-reported grade point averages at ages 12 and 14 yr and by self-reported educational levels at ages 17 and 24 yr. Bivariate quantitative genetic modeling at each age and between different ages was performed to decompose the trait correlation between academic performance and physical activity into genetic and environmental components. RESULTS The trait correlations between leisure-time physical activity and academic performance were positive, but modest at most (rtrait = 0.08-0.22 in males, and 0.07-0.18 in females). The genetic correlations between leisure-time physical activity and academic performance were higher than the trait correlations (rA = 0.17-0.43 in males, and 0.15-0.25 in females). Common genetic influences explained 43% to 100% of the trait correlations. Environmental influences shared by cotwins between leisure-time physical activity and academic performance were also correlated (rC = 0.27-0.54 in males, and 0.21-0.69 in females) explaining 41% to 100% of the trait correlations. Unique environmental influences were correlated only in females (rE = 0.10-0.15). CONCLUSIONS Both common genetic background and shared family environment (i.e., familial background) partially account for the associations observed between leisure-time physical activity and academic performance. However, the estimates vary in magnitude by age.
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Affiliation(s)
| | - Antti Latvala
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, FINLAND
| | | | - Richard J Rose
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | | | - Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, FINLAND
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33
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Silventoinen K, Jelenkovic A, Sund R, Latvala A, Honda C, Inui F, Tomizawa R, Watanabe M, Sakai N, Rebato E, Busjahn A, Tyler J, Hopper JL, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Calais-Ferreira L, Oliveira VC, Ferreira PH, Medda E, Nisticò L, Toccaceli V, Derom CA, Vlietinck RF, Loos RJF, Siribaddana SH, Hotopf M, Sumathipala A, Rijsdijk F, Duncan GE, Buchwald D, Tynelius P, Rasmussen F, Tan Q, Zhang D, Pang Z, Magnusson PKE, Pedersen NL, Dahl Aslan AK, Hwang AE, Mack TM, Krueger RF, McGue M, Pahlen S, Brandt I, Nilsen TS, Harris JR, Martin NG, Medland SE, Montgomery GW, Willemsen G, Bartels M, van Beijsterveldt CEM, Franz CE, Kremen WS, Lyons MJ, Silberg JL, Maes HH, Kandler C, Nelson TL, Whitfield KE, Corley RP, Huibregtse BM, Gatz M, Butler DA, Tarnoki AD, Tarnoki DL, Park HA, Lee J, Lee SJ, Sung J, Yokoyama Y, Sørensen TIA, Boomsma DI, Kaprio J. Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts. Sci Rep 2020; 10:12681. [PMID: 32728164 PMCID: PMC7391756 DOI: 10.1038/s41598-020-69526-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 07/10/2020] [Indexed: 01/07/2023] Open
Abstract
We investigated the heritability of educational attainment and how it differed between birth cohorts and cultural–geographic regions. A classical twin design was applied to pooled data from 28 cohorts representing 16 countries and including 193,518 twins with information on educational attainment at 25 years of age or older. Genetic factors explained the major part of individual differences in educational attainment (heritability: a2 = 0.43; 0.41–0.44), but also environmental variation shared by co-twins was substantial (c2 = 0.31; 0.30–0.33). The proportions of educational variation explained by genetic and shared environmental factors did not differ between Europe, North America and Australia, and East Asia. When restricted to twins 30 years or older to confirm finalized education, the heritability was higher in the older cohorts born in 1900–1949 (a2 = 0.44; 0.41–0.46) than in the later cohorts born in 1950–1989 (a2 = 0.38; 0.36–0.40), with a corresponding lower influence of common environmental factors (c2 = 0.31; 0.29–0.33 and c2 = 0.34; 0.32–0.36, respectively). In conclusion, both genetic and environmental factors shared by co-twins have an important influence on individual differences in educational attainment. The effect of genetic factors on educational attainment has decreased from the cohorts born before to those born after the 1950s.
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Affiliation(s)
- Karri Silventoinen
- Department of Social Research, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014, Helsinki, Finland. .,Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan.
| | - Aline Jelenkovic
- Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country, Leioa, Spain.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Reijo Sund
- Department of Social Research, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014, Helsinki, Finland.,Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Antti Latvala
- Department of Social Research, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014, Helsinki, Finland
| | - Chika Honda
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Fujio Inui
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan.,Faculty of Health Science, Kio University, Nara, Japan
| | - Rie Tomizawa
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Mikio Watanabe
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Norio Sakai
- Center for Twin Research, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Esther Rebato
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | | | - Jessica Tyler
- Twins Research Australia, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, VIC, Australia
| | - John L Hopper
- Twins Research Australia, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, VIC, Australia.,Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Juan R Ordoñana
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain.,IMIB-Arrixaca, Murcia, Spain
| | - Juan F Sánchez-Romera
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain.,IMIB-Arrixaca, Murcia, Spain
| | - Lucia Colodro-Conde
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain.,Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Lucas Calais-Ferreira
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Vinicius C Oliveira
- Pós-Graduação em Reabilitação e Desempenho Funcional, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, Brazil
| | - Paulo H Ferreira
- Musculoskeletal Health Research Group, Faculty of Health Sciences, The University of Sydney, Sydney, Australia
| | - Emanuela Medda
- Istituto Superiore di Sanità - Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Lorenza Nisticò
- Istituto Superiore di Sanità - Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Virgilia Toccaceli
- Istituto Superiore di Sanità - Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Catherine A Derom
- Centre of Human Genetics, University Hospitals Leuven, Leuven, Belgium.,Department of Obstetrics and Gynaecology, Ghent University Hospitals, Ghent, Belgium
| | | | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, Icahn School of Medicine At Mount Sinai, New York, NY, USA
| | - Sisira H Siribaddana
- Institute of Research and Development, Battaramulla, Sri Lanka.,Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka Saliyapura, Anuradhapura, Sri Lanka
| | - Matthew Hotopf
- Institute of Psychiatry Psychology and Neuroscience, King's College London, London, UK.,South London and Maudsley NHS Foundation Trust, London, UK
| | - Athula Sumathipala
- Institute of Research and Development, Battaramulla, Sri Lanka.,Research Institute for Primary Care and Health Sciences, School for Primary Care Research (SPCR), Faculty of Health, Keele University, Staffordshire, UK
| | - Fruhling Rijsdijk
- Social Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Glen E Duncan
- Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Dedra Buchwald
- Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Per Tynelius
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Finn Rasmussen
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Qihua Tan
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Department of Public Health, Qingdao University Medical College, Qingdao, China
| | - Zengchang Pang
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna K Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Amie E Hwang
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.,USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Thomas M Mack
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.,USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, Riverside, CA, 92521, USA
| | - Ingunn Brandt
- Division of Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Thomas S Nilsen
- Division of Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Jennifer R Harris
- Division of Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Nicholas G Martin
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Sarah E Medland
- Genetic Epidemiology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Gonneke Willemsen
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, Amsterdam, The Netherlands
| | | | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, CA, USA.,VA San Diego Center of Excellence for Stress and Mental Health, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Judy L Silberg
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Hermine H Maes
- Department of Human and Molecular Genetics, Psychiatry and Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Tracy L Nelson
- Department of Health and Exercise Sciences and Colorado School of Public Health, Colorado State University, Fort Collins, USA
| | | | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA
| | | | - Margaret Gatz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - David A Butler
- Health and Medicine Division, The National Academies of Sciences, Engineering, and Medicine, Washington, DC, USA
| | - Adam D Tarnoki
- Medical Imaging Centre, Semmelweis University, Budapest, Hungary.,Hungarian Twin Registry, Budapest, Hungary
| | - David L Tarnoki
- Medical Imaging Centre, Semmelweis University, Budapest, Hungary.,Hungarian Twin Registry, Budapest, Hungary
| | - Hang A Park
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea.,Department of Emergency Medicine, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea
| | - Jooyeon Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Soo Ji Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea.,Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Joohon Sung
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea.,Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Yoshie Yokoyama
- Department of Public Health Nursing, Osaka City University, Osaka, Japan
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Centre for Basic Metabolic Research (Section of Metabolic Genetics), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Public Health (Section of Epidemiology), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
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Silventoinen K, Maia J, Jelenkovic A, Pereira S, Gouveia É, Antunes A, Thomis M, Lefevre J, Kaprio J, Freitas D. Genetics of somatotype and physical fitness in children and adolescents. Am J Hum Biol 2020; 33:e23470. [PMID: 32638469 DOI: 10.1002/ajhb.23470] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 05/28/2020] [Accepted: 06/24/2020] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVES To analyze the influence of genetic and environmental factors on the variation in somatotype, physical fitness, and their mutual associations. METHODS Twins from 214 pairs (87 monozygotic) of the Autonomous Region of Madeira, Portugal, from 3 to 18 years of age (51% girls) were assessed in anthropometry and physical fitness tests. We estimated endomorphy, mesomorphy, and ectomorphy based on anthropometric measures and physical fitness using the Eurofit test battery. Two age categories were analyzed: children (3-11 years) and adolescents (12-18 years). Genetic and environmental variations were estimated using quantitative genetic twin modeling. RESULTS No genetic sex differences were found, thus boys and girls were pooled in all genetic analyses. Heritability estimates were high for somatotype (a2 = 0.80-0.93), physical fitness traits (a2 = 0.67-0.83), and largely similar in children and adolescents. Positive correlations were found for ectomorphy with motor ability and cardiorespiratory endurance as well as for endomorphy and mesomorphy with muscular strength (r = 0.25-0.37). In contrast, negative associations were found for ectomorphy with muscular strength, as well as for endomorphy and mesomorphy with motor ability and cardiorespiratory endurance (-0.46 to -0.26). Twin modeling indicated that these associations were explained mostly by genetic factors in common to the two associated traits (84% or more). CONCLUSIONS Associations between somatotype and physical fitness tests are mainly explained by common genetic background in children and adolescents. Therefore, interventions in youth should consider that a child's performance in physical fitness tests partly reflects their inherited physique.
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Affiliation(s)
- Karri Silventoinen
- Population Research Unit, Department of Social Research, University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - José Maia
- Centre of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, Porto, Portugal
| | - Aline Jelenkovic
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Bilbao, Spain
| | - Sara Pereira
- Centre of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, Porto, Portugal
| | - Élvio Gouveia
- Department of Physical Education and Sport, University of Madeira, Funchal, Portugal.,Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Geneva, Switzerland.,LARSYS, Interactive Technologies Institute, Funchal, Portugal
| | - António Antunes
- Department of Physical Education and Sport, University of Madeira, Funchal, Portugal
| | - Martine Thomis
- Physical Activity, Sports & Health Research Group, Department of Movement Sciences, Faculty of Movement and Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Johan Lefevre
- Physical Activity, Sports & Health Research Group, Department of Movement Sciences, Faculty of Movement and Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Duarte Freitas
- Centre of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, Porto, Portugal.,Department of Physical Education and Sport, University of Madeira, Funchal, Portugal.,Department of Mathematical Sciences, University of Essex, Colchester, UK
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35
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Yang L, Hu Y, Silventoinen K, Martikainen P. Childhood adversity and depressive symptoms among middle-aged and older Chinese: results from China health and retirement longitudinal study. Aging Ment Health 2020; 24:923-931. [PMID: 30700138 DOI: 10.1080/13607863.2019.1569589] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Objectives: A number of studies have established the link between childhood adversity (CA) and depression across the life span. This association can be culturally specific, and it remains unclear whether and how different aspects of CA affect depressive symptoms in later life in non-Western societies.Method: Data were from the China Health and Retirement Longitudinal Study in 2011, 2013, 2014 (Life Event History survey) and 2015 (N = 13,710). Depressive symptoms were measured repeatedly in 2011, 2013, and 2015 using the ten-item Centre for Epidemiologic Studies Depression Scale (CES-D-10). CA was assessed in 2014 by parental physical abuse, maternal emotional neglect, early parental death, parental mental health problems, poor quality of parental relationship, and childhood socioeconomic disadvantage. Multilevel linear models were used to analyse the data.Results: Parental physical abuse was associated with 0.51 (95% confidence interval [CI]: 0.28, 0.74) and 0.59 (95% CI: 0.31, 0.88) higher CES-D-10 scores compared to those without such abuse experience for men and women, respectively. Emotional neglect predicted 0.30 (95% CI: 0.07, 0.51) and 0.33 (95% CI: 0.08, 0.58) higher CES-D-10 scores for men and women. Elevated CES-D-10 scores were also found among men and women whose parents had poor mental health and poor relationship, and those who experienced food inadequacy (men: 0.78, 95% CI: 0.54, 1.01; women: 1.15, 95% CI: 0.90, 1.41). Early parental death nevertheless was not associated with CES-D-10 scores.Conclusion: CA exerts long-term detrimental effects on mental health in mid- and late-life among Chinese adults. The findings are consistent with those from Western societies, except for early parental death.
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Affiliation(s)
- Lei Yang
- Department of Sociology, School of Ethnology and Sociology, Minzu University of China, Beijing, China
| | - Yaoyue Hu
- Laboratory of Population Health, Max Planck Institute for Demographic Research, Rostock, Germany
| | - Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Pekka Martikainen
- Laboratory of Population Health, Max Planck Institute for Demographic Research, Rostock, Germany.,Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland.,Centre for Health Equity Studies (CHESS), Stockholm University and Karolinska Institutet, Stockholm, Sweden
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36
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Aaltonen S, Waller K, Vähä-Ypyä H, Rinne J, Sievänen H, Silventoinen K, Kaprio J, Kujala UM. Motives for physical activity in older men and women: A twin study using accelerometer-measured physical activity. Scand J Med Sci Sports 2020; 30:1409-1422. [PMID: 32259351 DOI: 10.1111/sms.13673] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 03/10/2020] [Accepted: 03/25/2020] [Indexed: 12/30/2022]
Abstract
Motives for physical activity may vary considerably by age, sex, and the level of physical activity. We aimed to examine motives for physical activity in older men and women with different physical activity levels as well as whether genetic and/or environmental factors explain those motives. Finnish twins (mean age 72.9 years, 262 full twin pairs) self-reported their motives for physical activity. Time spent on moderate-to-vigorous physical activity was monitored using a hip-worn accelerometer. Comparisons between the different physical activity groups of older twins (n = 764-791/motive dimension) were analyzed using the Wald test, and effect sizes were calculated as Cohen's d. Quantitative genetic modeling was used to estimate genetic and environmental contributions. For both sexes, the most frequently reported motives for physical activity were physical fitness, health maintenance, and psychological well-being. Conforming to others' expectations was more important for men than for women (P < .001, Cohen's d = 0.38), while appearance (P = .001 Cohen's d = -0.24) and psychological well-being (P = .02, Cohen's d = -0.17) were highlighted by women. Most of the motive dimensions differed significantly between the physically active and inactive individuals. It was estimated that 5%-42% of the variation in motives was contributed by genetic factors and 58%-95% by environmental factors. The result that environmental factors contribute in a great deal to motives indicates that interventions to motivate physically inactive older individuals to be physically active can be successful. However, personalized interventions are needed because sex and the level of physical activity were found to be associated with older individuals' motives for physical activity.
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Affiliation(s)
- Sari Aaltonen
- Institute for Molecular Medicine (FIMM), University of Helsinki, University of Helsinki, Helsinki, Finland
| | - Katja Waller
- Faculty of Sport and Health Sciences, University of Jyväskylä, University of Jyväskylä, Jyväskylä, Finland
| | - Henri Vähä-Ypyä
- The UKK Institute for Health Promotion Research, Tampere, Finland
| | - Juha Rinne
- Clinical Neurology, Turku PET Centre, Turku University Hospital, Turku, Finland
| | - Harri Sievänen
- The UKK Institute for Health Promotion Research, Tampere, Finland
| | - Karri Silventoinen
- Department of Social Research, University of Helsinki, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine (FIMM), University of Helsinki, University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, University of Helsinki, Helsinki, Finland
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, University of Jyväskylä, Jyväskylä, Finland
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37
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Kärkkäinen S, Silventoinen K, Svedberg P, Ropponen A. Life events as predictors for disability pension due to musculoskeletal diagnoses: a cohort study of Finnish twins. Int Arch Occup Environ Health 2019; 93:469-478. [PMID: 31828421 PMCID: PMC7118032 DOI: 10.1007/s00420-019-01505-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 12/03/2019] [Indexed: 11/24/2022]
Abstract
Purpose Musculoskeletal diagnoses (MSD) are one of the largest diagnostic groups for disability pensions (DP). This study investigated the associations between life events and DP due to MSD, considering sociodemographic, health, and familial factors. Methods The study sample included 18,530 Finnish twins, 24–64 years old at baseline, who responded to a questionnaire in 1981 including a 21-item life event inventory. Information on DP with diagnosis codes (ICD codes: M00–M99) were obtained from the official national pension registers. Life events were divided into family- and work-related events. “Positive change in life” was analyzed separately. Cox proportional hazards models were used to calculate hazard ratios (HR) with 95% confidence intervals (CI). Results During the follow-up of 23 years, 1273 (7%) individuals were granted DP due to MSD. In discordant pair analysis, family-related events (≥ 4 events) increased (HR 1.63, 95% CI 1.31, 2.03) and the absence of such events decreased (HR 0.68, 95% CI 0.48, 0.95) the risk of DP due to MSD. For work-related events (≥ 3 events), the risk estimates were non-significant when controlling for familial factors. Having had a positive change in life decreased the risk of DP due to MSD (HR 0.79, 95% CI 0.65, 0.96) while controlling for familial confounding, but were non-significant in the full model controlling for various covariates (HR 0.91, 95% CI 0.75, 1.12). Conclusions The associations between life events and the risk of DP due to MSD are complex and potentially affected by familial and other confounding factors including sociodemographics and health.
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Affiliation(s)
- Sanna Kärkkäinen
- Institute of Public Health and Clinical Nutrition, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland. .,Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland.,Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Pia Svedberg
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Annina Ropponen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Finnish Institute of Occupational Health, Helsinki, Finland
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38
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Tuomela J, Kaprio J, Sipilä P, Silventoinen K, Wang X, Ollikainen M, Piirtola M. Accuracy of self-reported anthropometric measures — Findings from the Finnish Twin Study. Obes Res Clin Pract 2019; 13:522-528. [PMID: 31761633 PMCID: PMC9234778 DOI: 10.1016/j.orcp.2019.10.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 08/21/2019] [Accepted: 10/28/2019] [Indexed: 12/25/2022]
Abstract
Objective: To determine the accuracy of self-reported height, weight, body mass index (BMI) and waist circumference (WC) compared to the measured values, and to assess the similarity between self-reported and measured values within dizygotic (DZ) and monozygotic (MZ) twin pairs. Methods: The data on self-reported and measured height, weight and WC values as well as measured hip circumference (HC) were collected from 444 twin individuals (53–67 years old, 60% women). Accuracies between self-reported and measured values were assessed by Pearson’s correlation coefficients, Cohen’s kappa coefficients and Bland-Altman 95% limits of agreement. Intra-class correlation was used in within-pair analyses. Results: The correlations between self-reported and measured values were high for all variables (r = 0.86–0.98), although the agreement assessed by Bland-Altman 95% limits had relatively wide variation. The degree of overestimating height was similar in both sexes, whereas women tended to underestimate and men overestimate their weight. Cohen’s kappa coefficients between self-reported and measured BMI categories were high: 0.71 in men and 0.70 in women. Further, the mean self-reported WC was less than the mean measured WC (difference in men 2.5 cm and women 2.6 cm). The within-pair correlations indicated a tendency of MZ co-twins to report anthropometric measures more similarly than DZ co-twins. Conclusions: Self-reported anthropometric measures are reasonably accurate indicators for obesity in large cohort studies. However, the possibility of more similar reporting among MZ pairs should be taken into account in twin studies exploring the heritability of different phenotypes.
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39
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Piirtola M, Kaprio J, Svedberg P, Silventoinen K, Ropponen A. Associations of sitting time with leisure-time physical inactivity, education, and body mass index change. Scand J Med Sci Sports 2019; 30:322-331. [PMID: 31605629 DOI: 10.1111/sms.13575] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 10/04/2019] [Accepted: 10/08/2019] [Indexed: 01/15/2023]
Abstract
We aimed to investigate the associations of long-term leisure-time physical inactivity, body mass index (BMI) change, and education with sitting time in a 35-year follow-up based on self-reports in surveys. Influences of working status in 2011 and familial confounding on the associations were tested. Data were based on the population-based Finnish Twin Cohort of 5232 twins (53-67-year-old, 41% men) with four surveys in 1975-2011. Statistical analyses were performed using linear regression with several covariates. The effect of familial confounding (genetics and shared environment) was analyzed using a co-twin control design which should be interpreted as if familial confounding plays a role, an association should be seen among all individuals but not in discordant twin pairs. Compared to those not at work, those at work had a longer total sitting time/d. For those at work, higher education was associated with more total sitting but with less non-work sitting. Long-term leisure-time physical inactivity was associated with more non-work sitting among those at work, whereas long-term weight gain with more total and non-work sitting regardless of working status. Familial confounding attenuated the associations, except for the association of increasing BMI with total and non-work sitting among women at work. To conclude, total sitting time was longer among those still at work, but it was also influenced by long-term leisure-time physical inactivity, higher education, and an increase of BMI over the years. Public health efforts should be targeted to reduce sedentary behavior by promoting life-long leisure-time physical activity and weight control.
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Affiliation(s)
- Maarit Piirtola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Pia Svedberg
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Karri Silventoinen
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Annina Ropponen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Finnish Institute of Occupational Health, Helsinki, Finland
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40
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Silventoinen K, Su J, Pulkkinen L, Barr P, Rose RJ, Dick DM, Kaprio J. Correction to: Genetics of Perceived Family Interaction From 12 to 17 Years of Age. Behav Genet 2019; 49:484. [PMID: 31263991 PMCID: PMC6768905 DOI: 10.1007/s10519-019-09963-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Karri Silventoinen
- Department of Social Research, University of Helsinki, P.O. Box 18, FIN-00014, Helsinki, Finland.
| | - Jinni Su
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Lea Pulkkinen
- Department of Psychology, University of Jyvaskyla, Jyvaskyla, Finland
| | - Peter Barr
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Richard J Rose
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA.,Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA.,College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
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41
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Carslake D, Fraser A, May MT, Palmer T, Silventoinen K, Tynelius P, Lawlor DA, Davey Smith G. Associations of mortality with own blood pressure using son's blood pressure as an instrumental variable. Sci Rep 2019; 9:8986. [PMID: 31222129 PMCID: PMC6586810 DOI: 10.1038/s41598-019-45391-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 05/28/2019] [Indexed: 11/09/2022] Open
Abstract
High systolic blood pressure (SBP) causes cardiovascular disease (CVD) and is associated with mortality from other causes, but conventional multivariably-adjusted results may be confounded. Here we used a son’s SBP (>1 million Swedish men) as an instrumental variable for parental SBP and examined associations with parents’ cause-specific mortality, avoiding reverse causation. The hazard ratio for CVD mortality per SD (10.80 mmHg) of SBP was 1.49 (95% CI: 1.43, 1.56); SBP was positively associated with coronary heart disease and stroke. SBP was also associated positively with all-cause, diabetes and kidney cancer mortality, and negatively with external causes. Negative associations with respiratory-related mortality were probably confounded by smoking. Hazard ratios for other causes were imprecise or null. Diastolic blood pressure gave similar results to SBP. CVD hazard ratios were intermediate between those from conventional multivariable studies and Mendelian randomization and stronger than those from clinical trials, approximately consistent with an effect of exposure duration on effect sizes. Plots of parental mortality against offspring SBP were approximately linear, supporting calls for lower SBP targets. Results suggest that conventional multivariable analyses of mortality and SBP are not substantially confounded by reverse causation and confirm positive effects of SBP on all-cause, CVD and diabetes mortality.
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Affiliation(s)
- David Carslake
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK. .,Population Health Sciences, Bristol Medical School, Bristol, UK.
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Margaret T May
- Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Tom Palmer
- Department of Mathematics and Statistics, University of Lancaster, Lancaster, UK
| | - Karri Silventoinen
- Population Research Unit, Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Per Tynelius
- Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, Bristol, UK
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42
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Silventoinen K, Su J, Pulkkinen L, Barr P, Rose RJ, Dick DM, Kaprio J. Genetics of Perceived Family Interaction From 12 to 17 Years of Age. Behav Genet 2019; 49:366-375. [PMID: 31127448 PMCID: PMC6554250 DOI: 10.1007/s10519-019-09960-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Accepted: 05/13/2019] [Indexed: 12/29/2022]
Abstract
We analyzed how the effects of genetic and environmental factors on the perceptions of family interaction change from early to late adolescence. The data were collected by postal surveys on Finnish twins (N = 4808) at 12, 14 and 17 years of age and analyzed using genetic twin modeling. Additive genetic factors explained a modest share of the variation in perceived relational support (a2 = 0.30 in boys and 0.18 in girls) and relational tensions (a2 = 0.13 and 0.14, respectively) at 12 years of age, with the proportions becoming larger through 17 years of age (a2 = 0.53 in boys and 0.49 in girls for relational support; a2 = 0.35 in boys and 0.33 in girls for relational tensions). Simultaneously, the role of environment shared by co-twins decreased. These findings suggest that the associations between perceived family interaction and other factors in adulthood should be interpreted with caution, because they partly reflect genetic background, whereas in childhood, they may provide more reliable information on parental characteristics.
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Affiliation(s)
- Karri Silventoinen
- Department of Social Research, University of Helsinki, P.O. Box 18, FIN-00014, Helsinki, Finland.
| | - Jinni Su
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Lea Pulkkinen
- Department of Psychology, University of Jyvaskyla, Jyvaskyla, Finland
| | - Peter Barr
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Richard J Rose
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
- College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
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43
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Yokoyama Y, Jelenkovic A, Hur YM, Sund R, Fagnani C, Stazi MA, Brescianini S, Ji F, Ning F, Pang Z, Knafo-Noam A, Mankuta D, Abramson L, Rebato E, Hopper JL, Cutler TL, Saudino KJ, Nelson TL, Whitfield KE, Corley RP, Huibregtse BM, Derom CA, Vlietinck RF, Loos RJF, Llewellyn CH, Fisher A, Bjerregaard-Andersen M, Beck-Nielsen H, Sodemann M, Krueger RF, McGue M, Pahlen S, Bartels M, van Beijsterveldt CEM, Willemsen G, Harris JR, Brandt I, Nilsen TS, Craig JM, Saffery R, Dubois L, Boivin M, Brendgen M, Dionne G, Vitaro F, Haworth CMA, Plomin R, Bayasgalan G, Narandalai D, Rasmussen F, Tynelius P, Tarnoki AD, Tarnoki DL, Ooki S, Rose RJ, Pietiläinen KH, Sørensen TIA, Boomsma DI, Kaprio J, Silventoinen K. Genetic and environmental factors affecting birth size variation: a pooled individual-based analysis of secular trends and global geographical differences using 26 twin cohorts. Int J Epidemiol 2019; 47:1195-1206. [PMID: 29788280 DOI: 10.1093/ije/dyy081] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 04/24/2018] [Indexed: 11/13/2022] Open
Abstract
Background The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birthweight, length and ponderal index (PI) across geographical-cultural regions (Europe, North America and Australia, and East Asia) and across birth cohorts, and how gestational age modifies these effects. Methods Data from 26 twin cohorts in 16 countries including 57 613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modelling. Results The variance of birthweight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased the proportions of shared environmental variance and increased the propositions of unique environmental variance. Genetic variance was similar in the geographical-cultural regions, but shared environmental variance was smaller in East Asia than in Europe and North America and Australia. The total variance and shared environmental variance of birth length and PI were greater from the birth cohort 1990-99 onwards compared with the birth cohorts from 1970-79 to 1980-89. Conclusions The contribution of genetic factors to birth size is smaller than that of shared environmental factors, which is partly explained by gestational age. Shared environmental variances of birth length and PI were greater in the latest birth cohorts and differed also across geographical-cultural regions. Shared environmental factors are important when explaining differences in the variation of birth size globally and over time.
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Affiliation(s)
- Yoshie Yokoyama
- Department of Public Health Nursing, Osaka City University, Osaka, Japan
| | - Aline Jelenkovic
- Department of Social Research, University of Helsinki, Helsinki, Finland.,Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Yoon-Mi Hur
- Department of Education, Mokpo National University, Jeonnam, South Korea
| | - Reijo Sund
- Department of Social Research, University of Helsinki, Helsinki, Finland.,Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Corrado Fagnani
- Istituto Superiore di Sanità - National Center for Epidemiology, Surveillance and Health Promotion, Rome, Italy
| | - Maria A Stazi
- Istituto Superiore di Sanità - National Center for Epidemiology, Surveillance and Health Promotion, Rome, Italy
| | - Sonia Brescianini
- Istituto Superiore di Sanità - National Center for Epidemiology, Surveillance and Health Promotion, Rome, Italy
| | - Fuling Ji
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Feng Ning
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Zengchang Pang
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Ariel Knafo-Noam
- Department of Psychology, Hebrew University of Jerusalem, Jerusalem, Israel
| | - David Mankuta
- Hadassah Hospital Obstetrics and Gynecology Department, Hebrew University Medical School, Jerusalem, Israel
| | - Lior Abramson
- Department of Psychology, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Esther Rebato
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | - John L Hopper
- Australian Twin Registry, Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia.,Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Tessa L Cutler
- Australian Twin Registry, Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia
| | - Kimberly J Saudino
- Department of Psychological and Brain Sciencies, Boston University, Boston, MA, USA
| | - Tracy L Nelson
- Department of Health and Exercise Sciencies and Colorado School of Public Health, Colorado State University, Fort Collins, CO, USA
| | | | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA
| | | | - Catherine A Derom
- Centre of Human Genetics, University Hospitals Leuven, Leuven, Belgium.,Department of Obstetrics and Gynaecology, Ghent University Hospitals, Ghent, Belgium
| | | | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Clare H Llewellyn
- Department of Epidemiology and Public Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Abigail Fisher
- Department of Epidemiology and Public Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Morten Bjerregaard-Andersen
- Bandim Health Project, INDEPTH Network, Bissau, Guinea-Bissau.,Research Center for Vitamins and Vaccines, Statens Serum Institute, Copenhagen, Denmark.,Department of Endocrinology
| | | | - Morten Sodemann
- Department of Infectious Diseases, Odense University Hospital, Odense, Denmark
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Shandell Pahlen
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Meike Bartels
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | | | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Jennifer R Harris
- Department of Genetic Research and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway
| | - Ingunn Brandt
- Department of Genetic Research and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway
| | - Thomas S Nilsen
- Department of Genetic Research and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway
| | - Jeffrey M Craig
- Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, VIC, Australia.,Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Richard Saffery
- Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, VIC, Australia.,Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Lise Dubois
- School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Michel Boivin
- École de psychologie, Université Laval, Québec, QC, Canada.,Institute of Genetic, Neurobiological, and Social Foundations of Child Development, Tomsk State University, Tomsk, Tomskaya oblast', Russian Federation
| | - Mara Brendgen
- Département de psychologie, Université du Québec à Montréal, Montréal, QC, Canada
| | - Ginette Dionne
- École de psychologie, Université Laval, Québec, QC, Canada
| | - Frank Vitaro
- École de psychoéducation, Université de Montréal, Montréal, QC, Canada
| | | | - Robert Plomin
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | | | - Danshiitsoodol Narandalai
- Healthy Twin Association of Mongolia, Ulaanbaatar, Mongolia.,Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Finn Rasmussen
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.,Department of Health Sciences, Lund University, Lund, Sweden
| | - Per Tynelius
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Adam D Tarnoki
- Department of Radiology and Oncotherapy, Semmelweis University, Budapest, Hungary.,Hungarian Twin Registry, Budapest, Hungary
| | - David L Tarnoki
- Department of Radiology and Oncotherapy, Semmelweis University, Budapest, Hungary.,Hungarian Twin Registry, Budapest, Hungary
| | - Syuichi Ooki
- Department of Health Science, Ishikawa Prefectural Nursing University, Kahoku, Ishikawa, Japan
| | - Richard J Rose
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Kirsi H Pietiläinen
- Obesity Research Unit, University of Helsinki, Helsinki, Finland.,Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Centre for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.,Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Institute for Molecular Medicine FIMM, Helsinki, Finland?>
| | - Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland.,Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
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44
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Silventoinen K, Jelenkovic A, Latvala A, Yokoyama Y, Sund R, Sugawara M, Tanaka M, Matsumoto S, Aaltonen S, Piirtola M, Freitas DL, Maia JA, Öncel SY, Aliev F, Ji F, Ning F, Pang Z, Rebato E, Saudino KJ, Cutler TL, Hopper JL, Ullemar V, Almqvist C, Magnusson PKE, Cozen W, Hwang AE, Mack TM, Willemsen G, Bartels M, van Beijsterveldt CEM, Nelson TL, Whitfield KE, Sung J, Kim J, Lee J, Lee S, Llewellyn CH, Fisher A, Medda E, Nisticò L, Toccaceli V, Baker LA, Tuvblad C, Corley RP, Huibregtse BM, Derom CA, Vlietinck RF, Loos RJF, Knafo-Noam A, Mankuta D, Abramson L, Burt SA, Klump KL, Silberg JL, Maes HH, Krueger RF, McGue M, Pahlen S, Gatz M, Butler DA, Harris JR, Nilsen TS, Harden KP, Tucker-Drob EM, Franz CE, Kremen WS, Lyons MJ, Lichtenstein P, Jeong HU, Hur YM, Boomsma DI, Sørensen TIA, Kaprio J. Parental Education and Genetics of BMI from Infancy to Old Age: A Pooled Analysis of 29 Twin Cohorts. Obesity (Silver Spring) 2019; 27:855-865. [PMID: 30950584 PMCID: PMC6478550 DOI: 10.1002/oby.22451] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 01/31/2019] [Indexed: 01/30/2023]
Abstract
OBJECTIVE The objective of this study was to analyze how parental education modifies the genetic and environmental variances of BMI from infancy to old age in three geographic-cultural regions. METHODS A pooled sample of 29 cohorts including 143,499 twin individuals with information on parental education and BMI from age 1 to 79 years (299,201 BMI measures) was analyzed by genetic twin modeling. RESULTS Until 4 years of age, parental education was not consistently associated with BMI. Thereafter, higher parental education level was associated with lower BMI in males and females. Total and additive genetic variances of BMI were smaller in the offspring of highly educated parents than in those whose parents had low education levels. Especially in North American and Australian children, environmental factors shared by co-twins also contributed to the higher BMI variation in the low education level category. In Europe and East Asia, the associations of parental education with mean BMI and BMI variance were weaker than in North America and Australia. CONCLUSIONS Lower parental education level is associated with higher mean BMI and larger genetic variance of BMI after early childhood, especially in the obesogenic macro-environment. The interplay among genetic predisposition, childhood social environment, and macro-social context is important for socioeconomic differences in BMI.
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Affiliation(s)
- Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Aline Jelenkovic
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Antti Latvala
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Yoshie Yokoyama
- Department of Public Health Nursing, Osaka City University, Osaka, Japan
| | - Reijo Sund
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Masumi Sugawara
- Department of Psychology, Ochanomizu University, Tokyo, Japan
| | - Mami Tanaka
- Center for Forensic Mental Health, Chiba University, Chiba, Japan
| | - Satoko Matsumoto
- Institute for Education and Human Development, Ochanomizu University, Tokyo
| | - Sari Aaltonen
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Maarit Piirtola
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Duarte L Freitas
- Department of Physical Education and Sport, University of Madeira, Funchal, Portugal
| | - José A Maia
- CIFI2D, Faculty of Sport, Porto, University of Porto, Portugal
| | - Sevgi Y Öncel
- Department of Statistics, Faculty of Arts and Sciences, Kirikkale University, Kirikkale, Turkey
| | - Fazil Aliev
- Psychology and African American Studies, Viginia Commonwealth University, Richmond, VA, USA
| | - Fuling Ji
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Feng Ning
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Zengchang Pang
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Esther Rebato
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Kimberly J Saudino
- Boston University, Department of Psychological and Brain Sciencies, Boston, MA, USA
| | - Tessa L Cutler
- The Australian Twin Registry, Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Victoria, Australia
| | - John L Hopper
- The Australian Twin Registry, Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Victoria, Australia
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Vilhelmina Ullemar
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pediatric Allergy and Pulmonology Unit at Astrid Lindgren Children’s Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Patrik KE Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Wendy Cozen
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
- USC Norris Comprehensive Cancer Center, Los Angeles, California, USA
| | - Amie E Hwang
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Thomas M Mack
- Department of Preventive Medicine, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
- USC Norris Comprehensive Cancer Center, Los Angeles, California, USA
| | - Gonneke Willemsen
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Meike Bartels
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | | | - Tracy L Nelson
- Department of Health and Exercise Sciences and Colorado School of Public Health, Colorado State University, Fort Collins, Colorado, USA
| | | | - Joohon Sung
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
- Institute of Health and Environment, Seoul National University, Seoul, South-Korea
| | - Jina Kim
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Jooyeon Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Sooji Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea
| | - Clare H Llewellyn
- Health Behaviour Research Centre, Department of Epidemiology and Public Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Abigail Fisher
- Health Behaviour Research Centre, Department of Epidemiology and Public Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Emanuela Medda
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità - Rome, Italy
| | - Lorenza Nisticò
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità - Rome, Italy
| | - Virgilia Toccaceli
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità - Rome, Italy
| | - Laura A Baker
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Catherine Tuvblad
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
- School of Law, Psychology and Social Work, Örebro University, Örebro, Sweden
| | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado, USA
| | - Brooke M Huibregtse
- Institute of Behavioral Science, University of Colorado, Boulder, Colorado, USA
| | - Catherine A Derom
- Centre of Human Genetics, University Hospitals Leuven, Leuven, Belgium
- Department of Obstetrics and Gynaecology, Ghent University Hospitals, Ghent, Belgium
| | | | - Ruth JF Loos
- The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - David Mankuta
- Hadassah Hospital Obstetrics and Gynecology Department, Hebrew University Medical School, Jerusalem, Israel
| | - Lior Abramson
- The Hebrew University of Jerusalem, Jerusalem, Israel
| | | | - Kelly L Klump
- Michigan State University, East Lansing, Michigan, USA
| | - Judy L Silberg
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Hermine H Maes
- Department of Human and Molecular Genetics, Psychiatry & Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Shandell Pahlen
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Margaret Gatz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - David A Butler
- Health and Medicine Division, The National Academies of Sciences, Engineering, and Medicine Washington, DC, USA
| | | | | | - K Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | | | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, CA, USA
- VA San Diego Center of Excellence for Stress and Mental Health, La Jolla, CA, USA
| | - Michael J Lyons
- Boston University, Department of Psychology, Boston, MA, USA
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hoe-Uk Jeong
- Department of Education, Mokpo National University, Jeonnam, South Korea
| | - Yoon-Mi Hur
- Department of Education, Mokpo National University, Jeonnam, South Korea
| | - Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Thorkild IA Sørensen
- Novo Nordisk Foundation Centre for Basic Metabolic Research (Section of Metabolic Genetics), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health (Section of Epidemiology), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
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45
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Yokoyama Y, Hakulinen T, Sugimoto M, Silventoinen K, Kalland M. Maternal subjective well-being and preventive health care system in Japan and Finland. Eur J Public Health 2019; 28:652-657. [PMID: 29272457 DOI: 10.1093/eurpub/ckx211] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Background Maternal well-being is an important issue not only for mothers but also for their offspring and whole families. This study aims to clarify differences in subjective well-being for mothers with infants and associated factors by comparing Japanese and Finnish mothers. Methods In Finland, 101 mothers with infants who received health check-ups at child's age 4 months participated in the study. In Japan, 505 mothers with infants who should receive health check-ups at child's age 4 months and, whose age, age of the infant and number of children matched with the Finnish mothers were selected. The factors associated with maternal subjective well-being were explored by the linear regression analysis. All Finnish mothers had individual infant health check-ups by nurses in Child Health Clinics nearly monthly. The same nurse was responsible for following up the family throughout the years. All Japanese participants received group health check-up once at child's age 3 to 4 months, and a nurse did not cover same child and their mother. Results Finnish mothers showed significantly better subjective well-being compared with Japanese mothers. Whereas 85% of Finnish mothers responded that they had obtained childcare information from public health nurses, significantly fewer Japanese mothers indicated the same response (8%). Linear regression analyses disclosed that mothers' subjective well-being was associated with country, mothers' stress and age. Conclusion Finnish mothers had better subjective well-being than Japanese mothers. Our results may indicate that the Finnish health care system supports mothers better than the Japanese health care system does.
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Affiliation(s)
- Yoshie Yokoyama
- Department of Public Health Nursing, Osaka City University, Osaka, Japan
| | - Tuovi Hakulinen
- Children, Adolescence and Families Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Masako Sugimoto
- Department of Public Health Nursing, Osaka City University, Osaka, Japan
| | - Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Mirjam Kalland
- Swedish School of Social Science, University of Helsinki, Helsinki, Finland
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46
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Yang L, Konttinen H, Martikainen P, Silventoinen K. Socioeconomic Status and Physical Functioning: A Longitudinal Study of Older Chinese People. J Gerontol B Psychol Sci Soc Sci 2018; 73:1315-1329. [PMID: 28329825 DOI: 10.1093/geronb/gbx010] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Indexed: 01/20/2023] Open
Abstract
Objectives We aimed to assess the longitudinal associations of socioeconomic status and physical functioning using a large population-based survey data in China. Method We used four waves of the Chinese Longitudinal Healthy Longevity Survey (2002-2011). Physical functioning was assessed by activities of daily living (ADL) and instrumental activities of daily living (IADL) measures. Socioeconomic status was assessed using educational attainment, occupational status, household income, financial resources, and access to health services. Latent growth curve model combined with selection model was utilized. Results High education was not associated with the baseline level or the rate of change in ADL score but predicted better baseline IADL functioning. High income was related to better IADL functioning but had no effect on the rate of change in IADL. Inadequate financial resources and unavailability of health services were mainly associated with poorer ADL and IADL functioning at baseline. White-collar occupation was unrelated to the trajectory of physical functioning. Discussion This study provides no support either for the cumulative disadvantage or age-as-leveler theory. Improving financial status and accessibility of health care services, especially in lower social classes, may help to improve the overall level of physical functioning of the older adults.
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Affiliation(s)
- Lei Yang
- Population Research Unit, University of Helsinki, Finland
| | - Hanna Konttinen
- Social Psychology, Department of Social Research, University of Helsinki, Finland
| | - Pekka Martikainen
- Population Research Unit, University of Helsinki, Finland.,Centre for Health Equity Studies (CHESS), Stockholm University and Karolinska Institutet, Sweden.,Max Planck Institute for Demographic Research, Rostock, Germany
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47
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Nisén J, Martikainen P, Myrskylä M, Silventoinen K. Education, Other Socioeconomic Characteristics Across the Life Course, and Fertility Among Finnish Men. Eur J Popul 2018; 34:337-366. [PMID: 30147207 PMCID: PMC6096873 DOI: 10.1007/s10680-017-9430-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Accepted: 05/01/2017] [Indexed: 11/25/2022]
Abstract
The level of education and other adult socioeconomic characteristics of men are known to associate with their fertility, but early-life socioeconomic characteristics may also be related. We studied how men’s adult and early-life socioeconomic characteristics are associated with their eventual fertility and whether the differences therein by educational level are explained or mediated by other socioeconomic characteristics. The data on men born in 1940–1950 (N = 37,082) were derived from the 1950 Finnish census, which is linked to later registers. Standard and sibling fixed-effects Poisson and logistic regression models were used. Education and other characteristics were positively associated with the number of children, largely stemming from a higher likelihood of a first birth among the more socioeconomically advantaged men. The educational gradient in the number of children was not explained by early socioeconomic or other characteristics shared by brothers, but occupational position and income in adulthood mediated approximately half of the association. Parity-specific differences existed: education and many other socioeconomic characteristics predicted the likelihood of a first birth more strongly than that of a second birth, and the mediating role of occupational position and income was also strongest for first births. Relatively small differences were found in the likelihood of a third birth. In men, education is positively associated with eventual fertility after controlling for early socioeconomic and other characteristics shared by brothers. Selective entry into fatherhood based on economic provider potential may contribute considerably to educational differentials in the number of children among men.
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Affiliation(s)
- Jessica Nisén
- Population Research Unit, Department of Social Research, University of Helsinki, P.O. Box 18 (Unioninkatu 35), 00014 Helsinki, Finland
- Max Planck Institute for Demographic Research, Konrad-Zuse-Straße 1, 18057 Rostock, Germany
| | - Pekka Martikainen
- Population Research Unit, Department of Social Research, University of Helsinki, P.O. Box 18 (Unioninkatu 35), 00014 Helsinki, Finland
- Max Planck Institute for Demographic Research, Konrad-Zuse-Straße 1, 18057 Rostock, Germany
- Centre for Health Equity Studies (CHESS), Stockholm University, Stockholm, Sweden
- Karolinska Institutet, Stockholm, Sweden
| | - Mikko Myrskylä
- Population Research Unit, Department of Social Research, University of Helsinki, P.O. Box 18 (Unioninkatu 35), 00014 Helsinki, Finland
- Max Planck Institute for Demographic Research, Konrad-Zuse-Straße 1, 18057 Rostock, Germany
- Department of Social Policy, London School of Economics, London, UK
| | - Karri Silventoinen
- Population Research Unit, Department of Social Research, University of Helsinki, P.O. Box 18 (Unioninkatu 35), 00014 Helsinki, Finland
- School of Medicine, Osaka University, Suita, Japan
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48
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Piirtola M, Jelenkovic A, Latvala A, Sund R, Honda C, Inui F, Watanabe M, Tomizawa R, Iwatani Y, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Tarnoki AD, Tarnoki DL, Martin NG, Montgomery GW, Medland SE, Rasmussen F, Tynelius P, Tan Q, Zhang D, Pang Z, Rebato E, Stazi MA, Fagnani C, Brescianini S, Busjahn A, Harris JR, Brandt I, Nilsen TS, Cutler TL, Hopper JL, Corley RP, Huibregtse BM, Sung J, Kim J, Lee J, Lee S, Gatz M, Butler DA, Franz CE, Kremen WS, Lyons MJ, Magnusson PKE, Pedersen NL, Dahl Aslan AK, Öncel SY, Aliev F, Derom CA, Vlietinck RF, Loos RJF, Silberg JL, Maes HH, Boomsma DI, Sørensen TIA, Korhonen T, Kaprio J, Silventoinen K. Association of current and former smoking with body mass index: A study of smoking discordant twin pairs from 21 twin cohorts. PLoS One 2018; 13:e0200140. [PMID: 30001359 PMCID: PMC6042712 DOI: 10.1371/journal.pone.0200140] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Accepted: 06/20/2018] [Indexed: 11/21/2022] Open
Abstract
Background Smokers tend to weigh less than never smokers, while successful quitting leads to an increase in body weight. Because smokers and non-smokers may differ in genetic and environmental family background, we analysed data from twin pairs in which the co-twins differed by their smoking behaviour to evaluate if the association between smoking and body mass index (BMI) remains after controlling for family background. Methods and findings The international CODATwins database includes information on smoking and BMI measured between 1960 and 2012 from 156,593 twin individuals 18–69 years of age. Individual-based data (230,378 measurements) and data of smoking discordant twin pairs (altogether 30,014 pairwise measurements, 36% from monozygotic [MZ] pairs) were analysed with linear fixed-effects regression models by 10-year periods. In MZ pairs, the smoking co-twin had, on average, 0.57 kg/m2 lower BMI in men (95% confidence interval (CI): 0.49, 0.70) and 0.65 kg/m2 lower BMI in women (95% CI: 0.52, 0.79) than the never smoking co-twin. Former smokers had 0.70 kg/m2 higher BMI among men (95% CI: 0.63, 0.78) and 0.62 kg/m2 higher BMI among women (95% CI: 0.51, 0.73) than their currently smoking MZ co-twins. Little difference in BMI was observed when comparing former smoking co-twins with their never smoking MZ co-twins (0.13 kg/m2, 95% CI 0.04, 0.23 among men; -0.04 kg/m2, 95% CI -0.16, 0.09 among women). The associations were similar within dizygotic pairs and when analysing twins as individuals. The observed series of cross-sectional associations were independent of sex, age, and measurement decade. Conclusions Smoking is associated with lower BMI and smoking cessation with higher BMI. However, the net effect of smoking and subsequent cessation on weight development appears to be minimal, i.e. never more than an average of 0.7 kg/m2.
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Affiliation(s)
- Maarit Piirtola
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- * E-mail:
| | - Aline Jelenkovic
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Antti Latvala
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Reijo Sund
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Chika Honda
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Fujio Inui
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
- Faculty of Health Science, Kio University, Nara, Japan
| | - Mikio Watanabe
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Rie Tomizawa
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Yoshinori Iwatani
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Juan R. Ordoñana
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain
- IMIB-Arrixaca, Murcia, Spain
| | - Juan F. Sánchez-Romera
- IMIB-Arrixaca, Murcia, Spain
- Department of Developmental and Educational Psychology, University of Murcia, Murcia, Spain
| | - Lucia Colodro-Conde
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Adam D. Tarnoki
- Department of Radiology, Semmelweis University, Budapest, Hungary
- Hungarian Twin Registry, Budapest, Hungary
| | - David L. Tarnoki
- Department of Radiology, Semmelweis University, Budapest, Hungary
- Hungarian Twin Registry, Budapest, Hungary
| | | | | | | | - Finn Rasmussen
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Per Tynelius
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Qihua Tan
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Department of Public Health, Qingdao University Medical College, Qingdao, China
| | - Zengchang Pang
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Esther Rebato
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Maria A. Stazi
- Istituto Superiore di Sanità—Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Corrado Fagnani
- Istituto Superiore di Sanità—Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | - Sonia Brescianini
- Istituto Superiore di Sanità—Centre for Behavioural Sciences and Mental Health, Rome, Italy
| | | | | | | | | | - Tessa L. Cutler
- Twins Research Australia, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Victoria, Australia
| | - John L. Hopper
- Twins Research Australia, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, South Korea
| | - Robin P. Corley
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, United States of America
| | - Brooke M. Huibregtse
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, United States of America
| | - Joohon Sung
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, South Korea
- Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Jina Kim
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, South Korea
| | - Jooyeon Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, South Korea
| | - Sooji Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, South Korea
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, United States of America
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - David A. Butler
- Health and Medicine Division, The National Academies of Sciences, Engineering, and Medicine, Washington, DC, United States of America
| | - Carol E. Franz
- Department of Psychiatry, University of California, San Diego, CA, United States of America
| | - William S. Kremen
- Department of Psychiatry, University of California, San Diego, CA, United States of America
- VA San Diego Center of Excellence for Stress and Mental Health, La Jolla, CA, United States of America
| | - Michael J. Lyons
- Department of Psychology, Boston University, Boston, MA, United States of America
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna K. Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Gerontology and Aging Research Network–Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Sevgi Y. Öncel
- Department of Statistics, Faculty of Arts and Sciences, Kırıkkale University, Kırıkkale, Turkey
| | - Fazil Aliev
- Psychology and African American Studies, Virginia Commonwealth University, Richmond, VA, United States of America
- Faculty of Business, Karabuk University, Karabuk, Turkey
| | - Catherine A. Derom
- Centre of Human Genetics, University Hospitals Leuven, Leuven, Belgium
- Department of Obstetrics and Gynaecology, Ghent University Hospitals, Ghent, Belgium
| | | | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Judy L. Silberg
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States of America
| | - Hermine H. Maes
- Department of Human and Molecular Genetics, Psychiatry & Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, United States of America
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands
| | - Thorkild I. A. Sørensen
- Novo Nordisk Foundation Centre for Basic Metabolic Research (Section for Metabolic Genetics), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health (Section of Epidemiology), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
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Jelenkovic A, Mikkonen J, Martikainen P, Latvala A, Yokoyama Y, Sund R, Vuoksimaa E, Rebato E, Sung J, Kim J, Lee J, Lee S, Stazi MA, Fagnani C, Brescianini S, Derom CA, Vlietinck RF, Loos RJF, Krueger RF, McGue M, Pahlen S, Nelson TL, Whitfield KE, Brandt I, Nilsen TS, Harris JR, Cutler TL, Hopper JL, Tarnoki AD, Tarnoki DL, Sørensen TIA, Kaprio J, Silventoinen K. Association between birth weight and educational attainment: an individual-based pooled analysis of nine twin cohorts. J Epidemiol Community Health 2018; 72:832-837. [PMID: 29848580 DOI: 10.1136/jech-2017-210403] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Revised: 05/07/2018] [Accepted: 05/09/2018] [Indexed: 11/04/2022]
Abstract
BACKGROUND There is evidence that birth weight is positively associated with education, but it remains unclear whether this association is explained by familial environmental factors, genetic factors or the intrauterine environment. We analysed the association between birth weight and educational years within twin pairs, which controls for genetic factors and the environment shared between co-twins. METHODS The data were derived from nine twin cohorts in eight countries including 6116 complete twin pairs. The association between birth weight and educational attainment was analysed both between individuals and within pairs using linear regression analyses. RESULTS In between-individual analyses, birth weight was not associated with educational years. Within-pairs analyses revealed positive but modest associations for some sex, zygosity and birth year groups. The greatest association was found in dizygotic (DZ) men (0.65 educational years/kg birth weight, p=0.006); smaller effects of 0.3 educational years/kg birth weight were found within monozygotic (MZ) twins of both sexes and opposite-sex DZ twins. The magnitude of the associations differed by birth year in MZ women and opposite-sex DZ twins, showing a positive association in the 1915-1959 birth cohort but no association in the 1960-1984 birth cohort. CONCLUSION Although associations are weak and somewhat inconsistent, our results suggest that intrauterine environment may play a role when explaining the association between birth weight and educational attainment.
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Affiliation(s)
- Aline Jelenkovic
- Department of Social Research, University of Helsinki, Helsinki, Finland.,Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Janne Mikkonen
- Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Pekka Martikainen
- Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Antti Latvala
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Yoshie Yokoyama
- Department of Public Health Nursing, Osaka City University, Osaka, Japan
| | - Reijo Sund
- Department of Social Research, University of Helsinki, Helsinki, Finland.,Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Esther Rebato
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Joohon Sung
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, The Republic of Korea.,Institute of Health and Environment, Seoul National University, Seoul, The Republic of Korea
| | - Jina Kim
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, The Republic of Korea
| | - Jooyeon Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, The Republic of Korea
| | - Sooji Lee
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, The Republic of Korea
| | - Maria A Stazi
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy
| | - Corrado Fagnani
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy
| | - Sonia Brescianini
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy
| | - Catherine A Derom
- Centre of Human Genetics, University Hospitals Leuven, Leuven, Belgium.,Department of Obstetrics and Gynaecology, Ghent University Hospitals, Ghent, Belgium
| | | | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Shandell Pahlen
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Tracy L Nelson
- Department of Health and Exercise Sciencies and Colorado School of Public Health, Colorado State University, Fort Collins, Colorado, USA
| | - Keith E Whitfield
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina, USA
| | - Ingunn Brandt
- Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway
| | - Thomas S Nilsen
- Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway
| | - Jennifer R Harris
- Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway
| | - Tessa L Cutler
- The Australian Twin Registry, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Victoria, Australia
| | - John L Hopper
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, The Republic of Korea.,The Australian Twin Registry, Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Adam D Tarnoki
- Department of Radiology, Semmelweis University, Budapest, Hungary.,Hungarian Twin Registry, Budapest, Hungary
| | - David L Tarnoki
- Department of Radiology, Semmelweis University, Budapest, Hungary.,Hungarian Twin Registry, Budapest, Hungary
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Centre for Basic Metabolic Research (Section of Metabolic Genetics), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Public Health (Section of Epidemiology), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland.,Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
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50
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Aaltonen S, Kaprio J, Kujala UM, Pulkkinen L, Rose RJ, Silventoinen K. The Interplay between Genes and Psychosocial Home Environment on Leisure-time Physical Activity. Med Sci Sports Exerc 2018. [DOI: 10.1249/01.mss.0000536228.27516.f6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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