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Huider F, Milaneschi Y, Hottenga JJ, Bot M, Rietman ML, Kok AAL, Galesloot TE, 't Hart LM, Rutters F, Blom MT, Rhebergen D, Visser M, Brouwer I, Feskens E, Hartman CA, Oldehinkel AJ, de Geus EJC, Kiemeney LA, Huisman M, Picavet HSJ, Verschuren WMM, van Loo HM, Penninx BWJH, Boomsma DI. Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project. Twin Res Hum Genet 2024:1-11. [PMID: 38497097 DOI: 10.1017/thg.2024.4] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.
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Affiliation(s)
- Floris Huider
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | - Yuri Milaneschi
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | - Mariska Bot
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - M Liset Rietman
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
| | - Almar A L Kok
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit, 1081 Amsterdam, the Netherlands
| | | | | | | | | | - Didi Rhebergen
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Mental health Institute GGZ Centraal, Amersfoort, the Netherlands
| | - Marjolein Visser
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Ingeborg Brouwer
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Edith Feskens
- Division of Human Nutrition and Health, Wageningen University & Research, 6700 Wageningen, the Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Albertine J Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | | | - Martijn Huisman
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit, 1081 Amsterdam, the Netherlands
- Department of Sociology, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - H Susan J Picavet
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
| | - W M Monique Verschuren
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 Utrecht, the Netherlands
| | - Hanna M van Loo
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Brenda W J H Penninx
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
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Bogaardt L, van Giessen A, Picavet HSJ, Boshuizen HC. A Model of Individual BMI Trajectories. Math Med Biol 2024; 41:1-18. [PMID: 38167965 DOI: 10.1093/imammb/dqad009] [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] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 09/24/2023] [Accepted: 12/21/2023] [Indexed: 01/05/2024]
Abstract
A risk factor model of body mass index (BMI) is an important building block of health simulations aimed at estimating government policy effects with regard to overweight and obesity. We created a model that generates representative population level distributions and that also mimics realistic BMI trajectories at an individual level so that policies aimed at individuals can be simulated. The model is constructed by combining several datasets. First, the population level distribution is extracted from a large, cross-sectional dataset. The trend in this distribution is estimated from historical data. In addition, longitudinal data are used to model how individuals move along typical trajectories over time. The model faithfully describes the population level distribution of BMI, stratified by sex, level of education and age. It is able to generate life course trajectories for individuals which seem plausible, but it does not capture extreme fluctuations, such as rapid weight loss.
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Affiliation(s)
- Laurens Bogaardt
- National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3721MA Bilthoven, The Netherlands
| | - Anoukh van Giessen
- National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3721MA Bilthoven, The Netherlands
| | - H Susan J Picavet
- National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3721MA Bilthoven, The Netherlands
| | - Hendriek C Boshuizen
- National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3721MA Bilthoven, The Netherlands
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Smit AP, Herber GCM, Kuiper LM, Loef B, Picavet HSJ, Verschuren WMM. Past or Present; Which Exposures Predict Metabolomic Aging Better? The Doetinchem Cohort Study. J Gerontol A Biol Sci Med Sci 2024; 79:glad202. [PMID: 37642222 PMCID: PMC10799759 DOI: 10.1093/gerona/glad202] [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: 05/08/2023] [Indexed: 08/31/2023] Open
Abstract
People age differently. Differences in aging might be reflected by metabolites, also known as metabolomic aging. Predicting metabolomic aging is of interest in public health research. However, the added value of longitudinal over cross-sectional predictors of metabolomic aging is unknown. We studied exposome-related exposures as potential predictors of metabolomic aging, both cross-sectionally and longitudinally in men and women. We used data from 4 459 participants, aged 36-75 of Round 4 (2003-2008) of the long-running Doetinchem Cohort Study (DCS). Metabolomic age was calculated with the MetaboHealth algorithm. Cross-sectional exposures were demographic, biological, lifestyle, and environmental at Round 4. Longitudinal exposures were based on the average exposure over 15 years (Round 1 [1987-1991] to 4), and trend in these exposure over time. Random Forest was performed to identify model performance and important predictors. Prediction performances were similar for cross-sectional and longitudinal exposures in both men (R2 6.8 and 5.8, respectively) and women (R2 14.8 and 14.4, respectively). Biological and diet exposures were most predictive for metabolomic aging in both men and women. Other important predictors were smoking behavior for men and contraceptive use and menopausal status for women. Taking into account history of exposure levels (longitudinal) had no added value over cross-sectionally measured exposures in predicting metabolomic aging in the current study. However, the prediction performances of both models were rather low. The most important predictors for metabolomic aging were from the biological and lifestyle domain and differed slightly between men and women.
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Affiliation(s)
- Annelot P Smit
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Gerrie-Cor M Herber
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Lieke M Kuiper
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Bette Loef
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - H Susan J Picavet
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - W M Monique Verschuren
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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Sialino LD, Wijnhoven HAH, van Oostrom SH, Picavet HSJ, Visser M, Schaap LA. The sex difference in self-rated health among older Turkish and Moroccan migrants in the Netherlands: an exploratory study of contributing determinants. BMC Public Health 2024; 24:248. [PMID: 38254057 PMCID: PMC10801924 DOI: 10.1186/s12889-023-17479-6] [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: 07/14/2023] [Accepted: 12/13/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Although being a woman and having a migration background are strong predictors of poor self-rated health among (older) adults, research on the sex difference in self-rated health among (older) migrants remains limited. This study therefore aims to investigate this topic and explore the contributing role of determinants of self-rated health. METHODS Cross-sectional data from 360 Turkish-Dutch and Moroccan-Dutch adults aged 55-65 as part of the Longitudinal Aging Study Amsterdam (LASA) were used. Self-rated health (good versus poor) was measured by a single item question. Univariate age-adjusted logistic regression analysis was used to investigate the sex difference in self-rated health and the contribution of sex differences in sensitivity (strength of the association) and/or exposure (prevalence) to socio-demographic, social, lifestyle or health-related determinants of self-rated health. RESULTS Women had a 0.53 times lower odds (95%CI:0.40-0.82, p = 0.004) on good self-rated health compared to men. Women more often having a lower education level, living alone and having a higher prevalence of depressive symptoms, chronic diseases and especially functional limitations contributed to the lower self-rated health among women. In contrast, men were more sensitive to the impact of memory complaints, depressive symptoms, visual difficulties and functional limitations. CONCLUSIONS Older Turkish-Dutch and Moroccan-Dutch women have a significant lower self-rated health compared to men. Women having a higher exposure to both socio-demographic and health-related determinants of self-rated health, which contributed to the sex difference. Future research should take these differences in self-rated health and determinants between women and men into account when investigating health among older migrants.
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Affiliation(s)
- Lena D Sialino
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
| | - H A H Wijnhoven
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - S H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - H S J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - M Visser
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - L A Schaap
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
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Kuijpers Y, Picavet HSJ, de Rond L, de Zeeuw-Brouwer ML, Rutkens R, Gijsbers E, Slits I, Engelfriet P, Buisman AM, Verschuren WMM. Potential determinants of antibody responses after vaccination against SARS-CoV-2 in older persons: the Doetinchem Cohort Study. Immun Ageing 2023; 20:57. [PMID: 37880758 PMCID: PMC10599057 DOI: 10.1186/s12979-023-00382-4] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 10/13/2023] [Indexed: 10/27/2023]
Abstract
BACKGROUND Immune responses to vaccination vary widely between individuals. The aim of this study was to identify health-related variables potentially underlying the antibody responses to SARS-CoV-2 vaccination in older persons. We recruited participants in the long-running Doetinchem Cohort Study (DCS) who underwent vaccination as part of the national COVID-19 program, and measured antibody concentrations to SARS-CoV-2 Spike protein (S1) and Nucleoprotein (N) at baseline (T0), and a month after both the first vaccination (T1), and the second vaccination (T2). Associations between the antibody concentrations and demographic variables, including age, sex, socio-economic status (SES), comorbidities (cardiovascular diseases and immune mediated diseases), various health parameters (cardiometabolic markers, inflammation markers, kidney- and lung function) and a composite measure of frailty ('frailty index', ranging from 0 to 1) were tested using multivariate models. RESULTS We included 1457 persons aged 50 to 92 years old. Of these persons 1257 were infection naïve after their primary vaccination series. The majority (N = 954) of these individuals were vaccinated with two doses of BNT162b2 (Pfizer) and their data were used for further analysis. A higher frailty index was associated with lower anti-S1 antibody responses at T1 and T2 for both men (RT1 = -0.095, PT1 = 0.05; RT2 = -0.11, PT2 = 0.02) and women (RT1 = -0.24, PT1 < 0.01; RT2 = -0.15, PT2 < 0.01). After correcting for age and sex the frailty index was also associated with the relative increase in anti-S1 IgG concentrations between the two vaccinations (β = 1.6, P < 0.01). Within the construct of frailty, history of a cardiac catheterization, diabetes, gastrointestinal disease, a cognitive speed in the lowest decile of the population distribution, and impaired lung function were associated with lower antibody responses after both vaccinations. CONCLUSIONS Components of frailty play a key role in the primary vaccination response to the BNT162b2 vaccine within an ageing population. Older persons with various comorbidities have a lowered immune response after their first vaccination, and while frail and sick older persons see a stronger increase after their second vaccination compared to healthy people, they still have a lower antibody response after their second vaccination.
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Affiliation(s)
- Yunus Kuijpers
- Centre for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands.
| | - H Susan J Picavet
- Centre for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
| | - Lia de Rond
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
| | - Mary-Lène de Zeeuw-Brouwer
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
| | - Ryanne Rutkens
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
| | - Esther Gijsbers
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
| | - Irene Slits
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
| | - Peter Engelfriet
- Centre for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
| | - Anne-Marie Buisman
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
| | - W M Monique Verschuren
- Centre for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3721 MA, The Netherlands
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, 3508 TC, The Netherlands
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Sialino LD, Wijnhoven HAH, van Oostrom SH, Picavet HSJ, Verschuren WMM, Visser M, Vader S, Schaap LA. Perspectives of older women in the Netherlands: identifying motivators and barriers for healthy lifestyles and determinants of healthy aging. BMC Public Health 2023; 23:664. [PMID: 37041507 PMCID: PMC10088167 DOI: 10.1186/s12889-023-15611-0] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 04/05/2023] [Indexed: 04/13/2023] Open
Abstract
BACKGROUND Women have a higher life expectancy than men but experience more years with physical disabilities in daily life at older ages, especially women with a migration background. This pinpoints older women as an important target group for strategies that stimulate healthy lifestyle, which benefits healthy aging. Our study investigates motivators and barriers for healthy lifestyles and perspectives on determinants of healthy aging of older women. This provides essential information for developing targeted strategies. METHODS Data was collected by semi-structured digital interviews from February till June 2021. Women aged 55 years and older living in the Netherlands (n = 34) with a native Dutch (n = 24), Turkish (n = 6) or Moroccan (n = 4) migration background were included. Two main subjects were investigated: (1) motivators and barriers on their current lifestyles regarding smoking, alcohol consumption, physical activity, diet and sleep and (2) perspectives on determinants of healthy aging. Interviews were analyzed using Krueger's framework. RESULTS Personal health was the most common motivator for a healthy lifestyle. In addition, peer pressure and being outdoors were specific motivators for physical activity. Bad weather conditions and personal dislike to be active were specific barriers. The social environment, personal preferences and personal belief to compensate with other healthy lifestyle behaviors were barriers for low alcohol consumption. Personal preferences (liking unhealthy food and not making time) were the main barriers for a healthy diet. Sleep was not perceived as a form of lifestyle behavior, but rather as a personal trait. Since there were no smokers, specific barriers were not mentioned. For Turkish-Dutch and Moroccan-Dutch women, additional barriers and motivators were culture and religion. These were strong motivators to abstain from alcohol consumption and smoking, but a barrier for a healthy diet. With regard to perspectives on determinants of healthy aging, positive views on aging and being physically active were perceived as most important. Women often wanted to increase their physical activity or healthy diet to stimulate healthy aging. Among Turkish-Dutch and Moroccan-Dutch women, healthy aging was also perceived as something in the hands of God. CONCLUSIONS Although motivators and barriers for a healthy lifestyle and perspectives on healthy aging vary for distinct lifestyles, personal health is a common motivator across all lifestyles. Having a migration background added culture and religion as distinct barriers and motivations. Strategies to improve lifestyle among older women should therefore have a tailored, culture sensitive approach (if applicable) for distinct lifestyle factors.
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Affiliation(s)
- L D Sialino
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, De Boelelaan 1105, North-Holland, 1081HV, Amsterdam, the Netherlands.
| | - H A H Wijnhoven
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, De Boelelaan 1105, North-Holland, 1081HV, Amsterdam, the Netherlands
| | - S H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - H S J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - W M M Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
- Julius Centre for Health Sciences and Primary Care, University Medical Centre, Utrecht, the Netherlands
| | - M Visser
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, De Boelelaan 1105, North-Holland, 1081HV, Amsterdam, the Netherlands
| | - S Vader
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - L A Schaap
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, De Boelelaan 1105, North-Holland, 1081HV, Amsterdam, the Netherlands
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Vader SS, Lewis SM, Verdonk P, Verschuren WM, Picavet HSJ. Masculine gender affects sex differences in the prevalence of chronic health problems - the Doetinchem Cohort Study. Prev Med Rep 2023; 33:102202. [DOI: 10.1016/j.pmedr.2023.102202] [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] [Received: 08/18/2022] [Revised: 03/01/2023] [Accepted: 04/04/2023] [Indexed: 04/09/2023] Open
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Loef B, Herber GCM, Wong A, Janssen NAH, Hoekstra J, Picavet HSJ, Verschuren WMM. Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study. BMC Geriatr 2023; 23:107. [PMID: 36823523 PMCID: PMC9948415 DOI: 10.1186/s12877-023-03789-2] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 02/01/2023] [Indexed: 02/25/2023] Open
Abstract
BACKGROUND Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most important exposome-related predictors of healthy physiological aging over the life course and across generations. METHODS Data were used from 2815 participants from four generations (generation 1960s/1950s/1940s/1930s aged respectively 20-29/30-39/40-49/50-59 years old at baseline, wave 1) of the Doetinchem Cohort Study who were measured every 5 years for 30 years. The Healthy Aging Index, a physiological aging index consisting of blood pressure, glucose, creatinine, lung function, and cognitive functioning, was measured at age 46-85 years (wave 6). The average exposure and trend of exposure over time of demographic, lifestyle, environmental, and biological exposures were included, resulting in 86 exposures. Random forest was used to identify important predictors. RESULTS The most important predictors of healthy physiological aging were overweight-related (BMI, waist circumference, waist/hip ratio) and cholesterol-related (using cholesterol lowering medication, HDL and total cholesterol) measures. Diet and educational level also ranked in the top of important exposures. No substantial differences were observed in the predictors of healthy physiological aging across generations. The final prediction model's performance was modest with an R2 of 17%. CONCLUSIONS Taken together, our findings suggest that longitudinal cardiometabolic exposures (i.e. overweight- and cholesterol-related measures) are most important in predicting healthy physiological aging. This finding was similar across generations. More work is needed to confirm our findings in other study populations.
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Affiliation(s)
- Bette Loef
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
| | - Gerrie-Cor M. Herber
- grid.31147.300000 0001 2208 0118Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Albert Wong
- grid.31147.300000 0001 2208 0118Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Nicole A. H. Janssen
- grid.31147.300000 0001 2208 0118Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Jurriaan Hoekstra
- grid.31147.300000 0001 2208 0118Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - H. Susan J. Picavet
- grid.31147.300000 0001 2208 0118Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - W. M. Monique Verschuren
- grid.31147.300000 0001 2208 0118Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands ,grid.5477.10000000120346234Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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Klokgieters SS, Picavet HSJ, Huisman M, Monique Verschuren WM, Uiters EAH, Kok AA. Differences in the Mediating Role of HL in Socioeconomic Inequalities in Health Across Age Groups: Results from the Dutch Doetinchem Cohort Study. Health Lit Res Pract 2023; 7:e26-e38. [PMID: 36779930 PMCID: PMC9918305 DOI: 10.3928/24748307-20230124-01] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/14/2023] Open
Abstract
BACKGROUND Although it is known that health literacy (HL) plays an explanatory role in educational inequalities in health, it is unknown whether this role varies across age groups. OBJECTIVE The purpose of this study was to investigate whether the mediating role of HL in educational inequalities in four health outcomes varies across age groups: age 46 to 58 years, age 59 to 71 years, and age 72 to 84 years. METHODS We used data from the Dutch Doetinchem Cohort Study, which included 3,448 participants. We included years of education as predictor, chronic illness prevalence and incidence, mental and self-perceived health as outcomes, and HL, based on self-report, as mediator. We used multiple-group mediation models to compare indirect effects across age groups. KEY RESULTS In the complete sample without age stratification, HL partly mediated the effect of education on all health outcomes except for incidence of chronic diseases. These indirect effect estimates were larger for subjective (self-perceived health, proportion mediated [PM] = 37%, and mental health, PM = 37%) than for objective health outcomes (prevalence of chronic disease, PM = 17%). For the prevalence of chronic disease, the indirect effect estimate was significantly larger among individuals age 46 to 58 years compared to individuals age 59 to 71 years and for incidence of chronic disease also compared to individuals age 72 to 84 years. All other indirect effect estimates did not differ significantly between age groups. Using an alternative cut-off point for HL or adjusting for cognitive functioning did not meaningfully change the results. CONCLUSIONS Overall, we found that the explanatory role of HL in educational inequalities in mental and subjective health was stable but that it varied across age groups for chronic diseases, where it was largest among individuals age 46 to 58 years. Future studies may investigate the benefits of starting to intervene on HL from a younger age but means to improve HL may also benefit the subjective health of older adults with lower education. [HLRP: HL Research and Practice. 2023;7(1):e26-e38.] Plain Language Summary: This study examined age-group differences in the mediating role of HL in the relationship between education and health. Overall, we found that the explanatory role of HL in educational inequalities in mental and subjective health was stable but that it varied across age groups for chronic diseases, where it was largest among individuals age 46 to 58 years compared to individuals age 59 to 71 years and individuals age 72 to 84 years.
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Affiliation(s)
- Silvia S. Klokgieters
- Address correspondence Silvia S. Klokgieters, PhD, Department of Epidemiology and Data Science, Amsterdam UMC, Location VUmc, Amsterdam Public Health, de Boelelaan 1117, Amsterdam, Netherlands;
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Schermer EE, Engelfriet PM, Blokstra A, Verschuren WMM, Picavet HSJ. Healthy lifestyle over the life course: Population trends and individual changes over 30 years of the Doetinchem Cohort Study. Front Public Health 2022; 10:966155. [PMID: 36159268 PMCID: PMC9500162 DOI: 10.3389/fpubh.2022.966155] [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: 06/10/2022] [Accepted: 08/22/2022] [Indexed: 01/24/2023] Open
Abstract
For five health-related lifestyle factors (physical activity, weight, smoking, sleep, and alcohol consumption) we describe both population trends and individual changes over a period of 30 years in the same adult population. Dichotomous indicators (healthy/unhealthy) of lifestyle were analyzed for 3,139 participants measured every 5 years in the Doetinchem Cohort Study (1987-2017). Population trends over 30 years in physical inactivity and "unhealthy" alcohol consumption were flat (i.e., stable); overweight and unhealthy sleep prevalence increased; smoking prevalence decreased. The proportion of the population being healthy on all five lifestyle factors declined from 17% in the round 1 to 10.8% in round 6. Underlying these trends a dynamic pattern of changes at the individual level was seen: sleep duration and physical activity level changed in almost half of the individuals; Body Mass Index (BMI) and alcohol consumption in one-third; smoking in one-fourth. Population trends don't give insight into change at the individual level. In order to be able to gauge the potential for change of health-related lifestyle, it is important to take changes at the individual level into account.
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Affiliation(s)
- Edith E. Schermer
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Peter M. Engelfriet
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Anneke Blokstra
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - W. M. Monique Verschuren
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, Netherlands,Julius Centre for Health Sciences and Primary Care, University Medical Centre, Utrecht, Netherlands
| | - H. Susan J. Picavet
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, Netherlands,*Correspondence: H. Susan J. Picavet
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van den Hoogen LL, Boer M, Postema A, de Rond L, de Zeeuw-Brouwer ML, Pronk I, Wijmenga-Monsuur AJ, Bijvank E, Kruiper C, Beckers L, Maurik MBV, Zutt I, van Vliet J, van Bergen R, Kuijer M, Smits G, Verschuren WMM, Picavet HSJ, van der Klis FRM, den Hartog G, van Binnendijk RS, Buisman AM. Reduced Antibody Acquisition with Increasing Age following Vaccination with BNT162b2: Results from Two Longitudinal Cohort Studies in The Netherlands. Vaccines (Basel) 2022; 10:vaccines10091480. [PMID: 36146557 PMCID: PMC9504637 DOI: 10.3390/vaccines10091480] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [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: 07/19/2022] [Revised: 08/25/2022] [Accepted: 08/30/2022] [Indexed: 11/16/2022] Open
Abstract
Vaccine-induced protection against severe COVID-19, hospitalization, and death is of the utmost importance, especially in the elderly. However, limited data are available on humoral immune responses following COVID-19 vaccination in the general population across a broad age range. We performed an integrated analysis of the effect of age, sex, and prior SARS-CoV-2 infection on Spike S1-specific (S1) IgG concentrations up to three months post-BNT162b2 (Pfizer/BioNTech; Comirnaty) vaccination. In total, 1735 persons, eligible for COVID-19 vaccination through the national program, were recruited from the general population (12 to 92 years old). Sixty percent were female, and the median vaccination interval was 35 days (interquartile range, IQR: 35−35). All participants had seroconverted to S1 one month after two vaccine doses. S1 IgG was higher in participants with a history of SARS-CoV-2 infection (median: 4535 BAU/mL, IQR: 2341−7205) compared to infection-naive persons (1842 BAU/mL, 1019−3116), p < 0.001. In infection-naive persons, linear mixed effects regression showed a strong negative association between age and S1 IgG (p < 0.001) across the entire age range. Females had higher S1 IgG than males (p < 0.001). In persons with an infection history, age nor sex was associated with S1 IgG concentrations. The lower magnitude of S1 antibodies in older persons following COVID-19 vaccination will affect long-term protection.
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Affiliation(s)
- Lotus Leonie van den Hoogen
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
- Correspondence:
| | - Mardi Boer
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Abigail Postema
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Lia de Rond
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Mary-lène de Zeeuw-Brouwer
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Inge Pronk
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Alienke Jentien Wijmenga-Monsuur
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Elske Bijvank
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Caitlyn Kruiper
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Lisa Beckers
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Marjan Bogaard-van Maurik
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Ilse Zutt
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Jeffrey van Vliet
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Rianne van Bergen
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Marjan Kuijer
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Gaby Smits
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - W. M. Monique Verschuren
- Centre for Prevention and Health Services Research, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, 3508 TC Utrecht, The Netherlands
| | - H. Susan J. Picavet
- Centre for Prevention and Health Services Research, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Fiona Regina Maria van der Klis
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Gerco den Hartog
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Robert Samuel van Binnendijk
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
| | - Anne-Marie Buisman
- Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment (RIVM), 3721 MA Bilthoven, The Netherlands
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12
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Sialino LD, Picavet HSJ, Wijnhoven HAH, Loyen A, Verschuren WMM, Visser M, Schaap LS, van Oostrom SH. Exploring the difference between men and women in physical functioning: How do sociodemographic, lifestyle- and health-related determinants contribute? BMC Geriatr 2022; 22:610. [PMID: 35864451 PMCID: PMC9306105 DOI: 10.1186/s12877-022-03216-y] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 06/13/2022] [Indexed: 11/17/2022] Open
Abstract
Background To explore whether differences between men and women in the sensitivity to (strength of the association) and/or in the exposure to determinants (prevalence) contribute to the difference in physical functioning, with women reporting more limitations. Methods Data of the Doetinchem Cohort Study was used (n = 5856, initial ages 26–70 years), with follow-up measurements every 5 years (up to 20). Physical functioning (subscale SF-36, range:0–100), sex (men or women) and a number of socio-demographic, lifestyle- and health-related determinants were assessed. Mixed-model multivariable analysis was used to investigate differences between men and women in sensitivity (interaction term with sex) and in exposure (change of the sex difference when adjusting) to determinants of physical functioning. Results The physical functioning score among women was 6.55 (95%CI:5.48,7.61) points lower than among men. In general, men and women had similar determinants, but pain was more strongly associated with physical functioning (higher sensitivity), and also more prevalent among women (higher exposure). The higher exposure to low educational level and not having a paid job also contributed to the lower physical functioning score among women. In contrast, current smoking, mental health problems and a low educational level were more strongly associated with a lower physical functioning score among men and lower physical activity and higher BMI were more prevalent among men. Conclusions Although important for physical functioning among both men and women, our findings provide no indications for reducing the difference in physical functioning by promoting a healthy lifestyle but stress the importance of differences in pain, work and education.
Supplementary Information The online version contains supplementary material available at 10.1186/s12877-022-03216-y.
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Affiliation(s)
- Lena Dirkje Sialino
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. .,Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Hanneke A H Wijnhoven
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anne Loyen
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.,Julius Centre for Health Sciences and Primary Care, University Medical Centre, Utrecht, The Netherlands
| | - Marjolein Visser
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Laura S Schaap
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
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13
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Loef B, Wong A, Janssen NAH, Strak M, Hoekstra J, Picavet HSJ, Boshuizen HCH, Verschuren WMM, Herber GCM. Using random forest to identify longitudinal predictors of health in a 30-year cohort study. Sci Rep 2022; 12:10372. [PMID: 35725920 PMCID: PMC9209521 DOI: 10.1038/s41598-022-14632-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [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: 10/27/2021] [Accepted: 06/09/2022] [Indexed: 11/09/2022] Open
Abstract
Due to the wealth of exposome data from longitudinal cohort studies that is currently available, the need for methods to adequately analyze these data is growing. We propose an approach in which machine learning is used to identify longitudinal exposome-related predictors of health, and illustrate its potential through an application. Our application involves studying the relation between exposome and self-perceived health based on the 30-year running Doetinchem Cohort Study. Random Forest (RF) was used to identify the strongest predictors due to its favorable prediction performance in prior research. The relation between predictors and outcome was visualized with partial dependence and accumulated local effects plots. To facilitate interpretation, exposures were summarized by expressing them as the average exposure and average trend over time. The RF model's ability to discriminate poor from good self-perceived health was acceptable (Area-Under-the-Curve = 0.707). Nine exposures from different exposome-related domains were largely responsible for the model's performance, while 87 exposures seemed to contribute little to the performance. Our approach demonstrates that ML can be interpreted more than widely believed, and can be applied to identify important longitudinal predictors of health over the life course in studies with repeated measures of exposure. The approach is context-independent and broadly applicable.
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Affiliation(s)
- Bette Loef
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands.
| | - Albert Wong
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
| | - Nicole A H Janssen
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
| | - Maciek Strak
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
| | - Jurriaan Hoekstra
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
| | - H Susan J Picavet
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
| | - H C Hendriek Boshuizen
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
- Wageningen University and Research, Wageningen, The Netherlands
| | - W M Monique Verschuren
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Gerrie-Cor M Herber
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
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Fraszczyk E, Spijkerman AMW, Zhang Y, Brandmaier S, Day FR, Zhou L, Wackers P, Dollé MET, Bloks VW, Gào X, Gieger C, Kooner J, Kriebel J, Picavet HSJ, Rathmann W, Schöttker B, Loh M, Verschuren WMM, van Vliet-Ostaptchouk JV, Wareham NJ, Chambers JC, Ong KK, Grallert H, Brenner H, Luijten M, Snieder H. Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts. Diabetologia 2022; 65:763-776. [PMID: 35169870 PMCID: PMC8960572 DOI: 10.1007/s00125-022-05652-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 11/15/2021] [Indexed: 02/02/2023]
Abstract
AIMS/HYPOTHESIS Type 2 diabetes is a complex metabolic disease with increasing prevalence worldwide. Improving the prediction of incident type 2 diabetes using epigenetic markers could help tailor prevention efforts to those at the highest risk. The aim of this study was to identify predictive methylation markers for incident type 2 diabetes by combining epigenome-wide association study (EWAS) results from five prospective European cohorts. METHODS We conducted a meta-analysis of EWASs in blood collected 7-10 years prior to type 2 diabetes diagnosis. DNA methylation was measured with Illumina Infinium Methylation arrays. A total of 1250 cases and 1950 controls from five longitudinal cohorts were included: Doetinchem, ESTHER, KORA1, KORA2 and EPIC-Norfolk. Associations between DNA methylation and incident type 2 diabetes were examined using robust linear regression with adjustment for potential confounders. Inverse-variance fixed-effects meta-analysis of cohort-level individual CpG EWAS estimates was performed using METAL. The methylGSA R package was used for gene set enrichment analysis. Confirmation of genome-wide significant CpG sites was performed in a cohort of Indian Asians (LOLIPOP, UK). RESULTS The meta-analysis identified 76 CpG sites that were differentially methylated in individuals with incident type 2 diabetes compared with control individuals (p values <1.1 × 10-7). Sixty-four out of 76 (84.2%) CpG sites were confirmed by directionally consistent effects and p values <0.05 in an independent cohort of Indian Asians. However, on adjustment for baseline BMI only four CpG sites remained genome-wide significant, and addition of the 76 CpG methylation risk score to a prediction model including established predictors of type 2 diabetes (age, sex, BMI and HbA1c) showed no improvement (AUC 0.757 vs 0.753). Gene set enrichment analysis of the full epigenome-wide results clearly showed enrichment of processes linked to insulin signalling, lipid homeostasis and inflammation. CONCLUSIONS/INTERPRETATION By combining results from five European cohorts, and thus significantly increasing study sample size, we identified 76 CpG sites associated with incident type 2 diabetes. Replication of 64 CpGs in an independent cohort of Indian Asians suggests that the association between DNA methylation levels and incident type 2 diabetes is robust and independent of ethnicity. Our data also indicate that BMI partly explains the association between DNA methylation and incident type 2 diabetes. Further studies are required to elucidate the underlying biological mechanisms and to determine potential causal roles of the differentially methylated CpG sites in type 2 diabetes development.
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Affiliation(s)
- Eliza Fraszczyk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Annemieke M W Spijkerman
- Centre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Stefan Brandmaier
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Li Zhou
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Paul Wackers
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Martijn E T Dollé
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Vincent W Bloks
- Department of Pediatrics, Section of Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Xīn Gào
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Jaspal Kooner
- Department of Cardiology, Ealing Hospital, Ealing, UK
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jennifer Kriebel
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Auf'm Hennekamp, Duesseldorf, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Jana V van Vliet-Ostaptchouk
- Genomics Coordination Center, Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Ken K Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Department of Paediatrics, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Mirjam Luijten
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
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Loyen A, Wendel-Vos GCW, Shekoh MI, Verschuren WMM, Picavet HSJ. 20-year individual physical activity patterns and related characteristics. BMC Public Health 2022; 22:437. [PMID: 35246085 PMCID: PMC8897943 DOI: 10.1186/s12889-022-12862-1] [Citation(s) in RCA: 2] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 02/18/2022] [Indexed: 12/25/2022] Open
Abstract
Background This study aims to describe individual leisure-time physical activity patterns among Dutch adults over a 20-year period, and to compare baseline characteristics of participants with different patterns. Methods The study population consisted of 2,518 adults (53% women) aged 26–65 years at baseline, measured every 5 years over a 20-year period. Self-reported physical activity measurements (from 1994 to 2017) were used to compose five (predefined) patterns: stable active, becoming active, becoming inactive, stable inactive, and varying physical activity. Multivariate logistic regression analyses were used to compare baseline socio-demographic, lifestyle, and health-related characteristics of these patterns. Results The total population shows a stable percentage being active in each round (between 55 and 58%). However over a period of 20 years, 32.6% of the participants were stable active, 19.9% were stable inactive, 15.2% became active, 11.6% became inactive, and 20.8% had varying physical activity behaviour. Compared to participants who were stable active, becoming active was associated with being 46–55 years old, having an intermediate level of education, and smoking, at baseline. Participants who became inactive were less likely to be 46–55 years old and more likely to be obese. Stable inactivity was associated with an intermediate level of education, low adherence to dietary guidelines, smoking, low levels of alcohol use and a moderate/poor perceived health. Participants with a varying physical activity level were more likely to have low adherence to dietary guidelines and to smoke. Conclusions Almost half of the participants changed their physical activity behaviour over 20 years. Baseline age, level of education, smoking, alcohol consumption, adherence to dietary guidelines, weight status and perceived health were associated with different physical activity patterns.
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Affiliation(s)
- Anne Loyen
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - G C Wanda Wendel-Vos
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | | | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
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DiCorpo D, LeClair J, Cole JB, Sarnowski C, Ahmadizar F, Bielak LF, Blokstra A, Bottinger EP, Chaker L, Chen YDI, Chen Y, de Vries PS, Faquih T, Ghanbari M, Gudmundsdottir V, Guo X, Hasbani NR, Ibi D, Ikram MA, Kavousi M, Leonard HL, Leong A, Mercader JM, Morrison AC, Nadkarni GN, Nalls MA, Noordam R, Preuss M, Smith JA, Trompet S, Vissink P, Yao J, Zhao W, Boerwinkle E, Goodarzi MO, Gudnason V, Jukema JW, Kardia SL, Loos RJ, Liu CT, Manning AK, Mook-Kanamori D, Pankow JS, Picavet HSJ, Sattar N, Simonsick EM, Verschuren WM, Willems van Dijk K, Florez JC, Rotter JI, Meigs JB, Dupuis J, Udler MS. Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts. Diabetes Care 2022; 45:674-683. [PMID: 35085396 PMCID: PMC8918228 DOI: 10.2337/dc21-1395] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 12/15/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.
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Affiliation(s)
- Daniel DiCorpo
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jessica LeClair
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Joanne B. Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Division of Endocrinology, Boston Children’s Hospital, Boston, MA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Julius Global Health, University Utrecht Medical Center, Utrecht, the Netherlands
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Anneke Blokstra
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Erwin P. Bottinger
- Hasso Plattner Institute Digital Health, Potsdam, Germany
- Mount Sinai Health System, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Layal Chaker
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Division of Endocrinology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Yii-Der I. Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Ye Chen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Tariq Faquih
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Natalie R. Hasbani
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Dorina Ibi
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Hampton L. Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
- Data Tecnica International, Glen Echo, MD
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Josep M. Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Alanna C. Morrison
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Girish N. Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Mike A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
- Data Tecnica International, Glen Echo, MD
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Michael Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI
| | - Stella Trompet
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Petra Vissink
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - J. Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Ruth J.F. Loos
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Dennis Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - H. Susan J. Picavet
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, U.K
| | - Eleanor M. Simonsick
- Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - W.M. Monique Verschuren
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, MA
- Endocrine Division, Massachusetts General Hospital, Boston, MA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - James B. Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Miriam S. Udler
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Endocrine Division, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
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17
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Samson LD, Buisman A, Ferreira JA, Picavet HSJ, Verschuren WMM, Boots AMH, Engelfriet P. Inflammatory marker trajectories associated with frailty and ageing in a 20‐year longitudinal study. Clin Transl Immunology 2022; 11:e1374. [PMID: 35154709 PMCID: PMC8826353 DOI: 10.1002/cti2.1374] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [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: 04/12/2021] [Revised: 01/06/2022] [Accepted: 01/18/2022] [Indexed: 12/24/2022] Open
Abstract
Objective The aim of this exploratory study was to investigate the development of low‐grade inflammation during ageing and its relationship with frailty. Methods The trajectories of 18 inflammatory markers measured in blood samples, collected at 5‐year intervals over a period of 20 years from 144 individuals aged 65–75 years at the study endpoint, were related to the degree of frailty later in life. Results IFN‐γ‐related markers and platelet activation markers were found to change in synchrony. Chronically elevated levels of IL‐6 pathway markers, such as CRP and sIL‐6R, were associated with more frailty, poorer lung function and reduced physical strength. Being overweight was a possible driver of these associations. More and stronger associations were detected in women, such as a relation between increasing sCD14 levels and frailty, indicating a possible role for monocyte overactivation. Multivariate prediction of frailty confirmed the main results, but predictive accuracy was low. Conclusion In summary, we documented temporal changes in and between inflammatory markers in an ageing population over a period of 20 years, and related these to clinically relevant health outcomes.
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Affiliation(s)
- Leonard Daniël Samson
- National Institute of Public Health and the Environment Bilthoven The Netherlands
- Department of Rheumatology and Clinical Immunology University of Groningen University Medical Center Groningen The Netherlands
| | - Anne‐Marie Buisman
- National Institute of Public Health and the Environment Bilthoven The Netherlands
| | - José A Ferreira
- National Institute of Public Health and the Environment Bilthoven The Netherlands
| | - H Susan J Picavet
- National Institute of Public Health and the Environment Bilthoven The Netherlands
| | - W M Monique Verschuren
- National Institute of Public Health and the Environment Bilthoven The Netherlands
- Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht University Utrecht The Netherlands
| | - Annemieke MH Boots
- Department of Rheumatology and Clinical Immunology University of Groningen University Medical Center Groningen The Netherlands
| | - Peter Engelfriet
- National Institute of Public Health and the Environment Bilthoven The Netherlands
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18
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Samson LD, Engelfriet P, Verschuren WMM, Picavet HSJ, Ferreira JA, de Zeeuw-Brouwer ML, Buisman AM, Boots AMH. Impaired JAK-STAT pathway signaling in leukocytes of the frail elderly. Immun Ageing 2022; 19:5. [PMID: 35039055 PMCID: PMC8762193 DOI: 10.1186/s12979-021-00261-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [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: 10/15/2021] [Accepted: 12/23/2021] [Indexed: 12/30/2022]
Abstract
Background Elderly often show reduced immune functioning and can develop chronic low-grade inflammation. Why some elderly are more prone to become frail is unknown. We investigated whether frailty is associated with altered cytokine signaling through the JAK-STAT pathway in leukocytes of 34 individuals aged 65–74 years. In addition, we investigated how this relation is affected by chronic low-grade inflammation during the previous 20 years. Cytokine signaling was quantified by measuring intracellular STAT1, STAT3, and STAT5 phosphorylation in monocytes, B cells, CD4+ T cells and CD8+ T cells upon stimulation with IL-2, IL-6, IL-10, IFNα and IFNγ, using phospho-flow cytometry. Presence of chronic low-grade inflammation was investigated by evaluating 18 different plasma inflammatory markers that had been measured repeatedly in the same individuals over the previous 20 years. Frailty was assessed as a score on a frailty index. Results We found that lower cytokine-induced pSTAT responsiveness in the various cell subsets was seen with higher frailty scores in both men and women, indicative of dysfunctional pSTAT responses in frailer individuals. Associations differed between men and women, with frailer women showing lower pSTAT1 responses in monocytes and frailer men showing lower pSTAT5 responses in CD4+ and CD8+ T cells. Notably, lower IL-10-induced pSTAT3 responses in men were related to both higher frailty scores and higher CRP levels over the past 20 years. This might indicate poor resolution of low-grade inflammation due to defective regulatory pSTAT signaling in older men. Conclusions Our results emphasize the importance of preserved JAK-STAT pathway signaling in healthy aging and reveal cellular pSTAT levels as a candidate biomarker of frailty. Supplementary Information The online version contains supplementary material available at 10.1186/s12979-021-00261-w.
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Affiliation(s)
- Leonard Daniël Samson
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands. .,Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| | - Peter Engelfriet
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | - W M Monique Verschuren
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - H Susan J Picavet
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | - José A Ferreira
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | | | - Anne-Marie Buisman
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | - A Mieke H Boots
- Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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19
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Nooyens ACJ, Wijnhoven HAH, Schaap LS, Sialino LD, Kok AAL, Visser M, Verschuren WMM, Picavet HSJ, van Oostrom SH. Sex Differences in Cognitive Functioning with Aging in the Netherlands. Gerontology 2022; 68:999-1009. [PMID: 34983049 PMCID: PMC9501735 DOI: 10.1159/000520318] [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] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 10/14/2021] [Indexed: 11/19/2022] Open
Abstract
Introduction Dementia prevalence in older women is higher than that in men. The purpose of the present study was to investigate whether there is a female disadvantage in cognitive functioning at adult age and/or whether a female disadvantage develops with age. Methods Data of 5,135 women and 4,756 men from the Longitudinal Aging Study Amsterdam (LASA) and the Doetinchem Cohort Study (DCS) were used. In the LASA, memory, processing speed, fluid intelligence, and global cognitive function were measured every 3–4 years since 1992 in persons aged 55+ years for up to 23 years. In the DCS, memory, processing speed, cognitive flexibility, and global cognitive function were measured every 5 years since 1995 in persons aged 45+ years for up to 20 years. Sex differences in cognitive aging were analyzed using linear mixed models and also examined by the 10-year birth cohort or level of education. Results Women had a better memory, processing speed, flexibility, and, in the DCS only, global cognitive function than men (p's < 0.01). However, women showed up to 10% faster decline in these cognitive domains, except for flexibility, where women showed 9% slower decline. In the LASA, women scored poorer on fluid intelligence (p < 0.01), but their decline was 10% slower than that in men. Female advantage was larger in later born cohorts; adjustment for the educational level increased the female advantage. Conclusion Women have better memory and processing speed than men at middle age. This female advantage becomes smaller with aging and has increased in more recent birth cohorts.
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Affiliation(s)
- Astrid C J Nooyens
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Hanneke A H Wijnhoven
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Laura S Schaap
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Lena D Sialino
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.,Department of Health Sciences, Faculty of Science, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Almar A L Kok
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology & Biostatistics, Amsterdam Public Health, Amsterdam, The Netherlands
| | - Marjolein Visser
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
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20
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Proper KI, Jaarsma E, Robroek SJW, Schram JLD, Boshuizen H, Picavet HSJ, Verschuren WMM, van Oostrom SH. The mediating role of unhealthy behavior in the relationship between shift work and perceived health. BMC Public Health 2021; 21:1300. [PMID: 34215233 PMCID: PMC8254208 DOI: 10.1186/s12889-021-11350-2] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 06/21/2021] [Indexed: 11/19/2022] Open
Abstract
Background Little is known about the relationship between shift work and perceived health, including potential underlying mechanisms such as unhealthy behaviors. The aim of this study was to investigate whether unhealthy behaviors mediate the relationship between shift work and perceived mental and physical health, taking into account potential differences by level of education. Methods Data from 1633 workers participating in the Doetinchem Cohort Study during 1995–2016 were used. Being engaged in shift work was determined at 1 year preceding the assessment of health behaviors. Mental and physical health were assessed after 5 years of follow-up by the 5-item Mental Health Inventory and the physical functioning scale of the 36-item Short Form Health Survey. Smoking, physical inactivity, alcohol consumption, and overweight were considered as potential mediators and education was treated as moderator. Moderated mediation analyses using generalized estimated equations were performed. Results Shift work was not statistically significantly related to either mental or physical health. Despite this, statistically significant mediation effects of smoking (Beta − 0.09; 95% Confidence Interval − 0.20 - -0.01, respectively B -0.09; 95%CI -0.21 - -0.01) and physical inactivity (B 0.11; 95%CI 0.03–0.23, respectively B 0.08; 95%CI 0.01–0.18) were found in the relationship between shift work and mental or physical health. Direct and indirect effects outweighed each other in the relationship between shift work and mental health, since the direction of these effects was opposite. The relationship between shift work, unhealthy behavior, and health was not different by educational level. Conclusion Shift workers did not report lower mental or physical health than non-shift workers. Though mediation effects of unhealthy behavior were observed in the relationship between shift work and perceived health, these small effects had minor public health relevance.
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Affiliation(s)
- Karin I Proper
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.,Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, The Netherlands
| | - Eva Jaarsma
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, the Netherlands
| | - Suzan J W Robroek
- Department of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jolinda L D Schram
- Department of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Hendriek Boshuizen
- Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, the Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.
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21
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Sialino LD, Schaap LA, van Oostrom SH, Picavet HSJ, Twisk JWR, Verschuren WMM, Visser M, Wijnhoven HAH. The sex difference in gait speed among older adults: how do sociodemographic, lifestyle, social and health determinants contribute? BMC Geriatr 2021; 21:340. [PMID: 34078276 PMCID: PMC8173843 DOI: 10.1186/s12877-021-02279-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [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: 02/22/2021] [Accepted: 05/04/2021] [Indexed: 12/25/2022] Open
Abstract
Background This study explores whether a sex difference in sensitivity to (strength of the association) and/or in exposure to (prevalence) determinants of gait speed contributes to the observed lower gait speed among older women compared to men. Methods Data from the Longitudinal Aging Study Amsterdam (LASA) were used. In total 2407 men and women aged 55–81 years were included, with baseline measurements in 1992/2002 and follow-up measurements every 3–4 years for 15/25 years. Multivariable mixed model analysis was used to investigate sex differences in sensitivity (interaction term with sex) and in exposure to (change of the sex difference when adjusted) socio-demographic, lifestyle, social and health determinants of gait speed. Results Women had a 0.054 m/s (95 % CI: 0.076 − 0.033, adjusted for height and age) lower mean gait speed compared to men. In general, men and women had similar determinants of gait speed. However, higher BMI and lower physical activity were more strongly associated with lower gait speed in women compared to men (i.e. higher sensitivity). More often having a lower educational level, living alone and having more chronic diseases, pain and depressive symptoms among women compared to men also contributed to observed lower gait speed in women (i.e. higher exposure). In contrast, men more often being a smoker, having a lower physical activity and a smaller personal network size compared to women contributed to a lower gait speed among men (i.e. higher exposure). Conclusions Both a higher sensitivity and higher exposure to determinants of gait speed among women compared to men contributes to the observed lower gait speed among older women. The identified (modifiable) contributing factors should be taken into account when developing prevention and/or treatment strategies aimed to enhance healthy physical aging. This might require a sex-specific approach in both research and clinical practice, which is currently often lacking. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-021-02279-7.
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Affiliation(s)
- Lena D Sialino
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
| | - Laura A Schaap
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Johannes W R Twisk
- Department of Clinical Epidemiology and Biostatistics, Amsterdam University Medical Centre, Amsterdam, the Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.,Julius Centre for Health Sciences and Primary Care, University Medical Centre, Utrecht, The Netherlands
| | - Marjolein Visser
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Hanneke A H Wijnhoven
- Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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22
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Nooyens ACJ, Yildiz B, Hendriks LG, Bas S, van Boxtel MPJ, Picavet HSJ, Boer JMA, Verschuren WMM. Adherence to dietary guidelines and cognitive decline from middle age: the Doetinchem Cohort Study. Am J Clin Nutr 2021; 114:871-881. [PMID: 34004676 PMCID: PMC8408878 DOI: 10.1093/ajcn/nqab109] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 03/11/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Diet, in particular the Mediterranean diet, has been associated with better cognitive function and less cognitive decline in older populations. OBJECTIVES To quantify associations of a healthy diet, defined by adherence to either the Mediterranean diet, the WHO guidelines, or Dutch Health Council dietary guidelines, with cognitive function and cognitive decline from middle age into old age. METHODS From the Doetinchem Cohort Study, a large population-based longitudinal study, 3644 participants (51% females) aged 45-75 y at baseline, were included. Global cognitive function, memory, processing speed, and cognitive flexibility were assessed at 5-y time intervals up to 20-y follow-up. Adherence to the Mediterranean diet was measured with the modified Mediterranean Diet Score (mMDS), adherence to the WHO dietary guidelines with the Healthy Diet Indicator (HDI), and adherence to the Dutch Health Council dietary guidelines 2015 with the modified Dutch Healthy Diet 2015 index (mDHD15-index). The scores on the dietary indices were classified in tertiles (low, medium, high adherence). Linear mixed models were used to model level and change in cognitive function by adherence to healthy diets. RESULTS The highest tertiles of the mMDS, HDI, and mDHD15-index were associated with better cognitive function compared with the lowest tertiles (P values <0.01), for instance at age 65 y equal to being 2 y cognitively younger in global cognition. In addition, compared with the lowest tertiles, the highest tertiles of the mMDS, HDI, and mDHD15-index were statistically significantly associated with 6-7% slower global cognitive decline from age 55 to 75 y, but also slower decline in processing speed (for mMDS: 10%; 95% CI: 2, 18%; for mDHD15: 12%; 95% CI: 6, 21%) and cognitive flexibility (for mDHD15: 10%; 95% CI: 4, 18%). CONCLUSIONS Healthier dietary habits, determined by higher adherence to dietary guidelines, are associated with better cognitive function and slower cognitive decline with aging from middle age onwards.
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Affiliation(s)
| | - Berivan Yildiz
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands,Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lisa G Hendriks
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Sharell Bas
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Martin P J van Boxtel
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Jolanda M A Boer
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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Wijga AH, Gehring U, van de Putte EM, Koppelman GH, Vader S, Schmits RJ, van der Wouden JC, Picavet HSJ. Headache in girls and boys growing up from age 11 to 20 years: the Prevention and Incidence of Asthma and Mite Allergy birth cohort study. Pain 2021; 162:1449-1456. [PMID: 33230003 PMCID: PMC8054541 DOI: 10.1097/j.pain.0000000000002141] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 10/19/2020] [Accepted: 11/02/2020] [Indexed: 01/18/2023]
Abstract
ABSTRACT The striking difference between men and women in headache prevalence is suggested to develop in adolescence. Although headaches are common and affect quality of life and daily functioning, the evidence needed to develop effective counselling and preventive approaches is still limited. Using data collected at age 11, 14, 17, and 20 years in the Dutch Prevention and Incidence of Asthma and Mite Allergy birth cohort study (n = 3064 with ≥ 1 questionnaire), we assessed headache prevalence and incidence in girls and boys and explored associations with early life, environmental, lifestyle, health, and psychosocial factors. Associations were analysed longitudinally with generalized linear mixed models and discrete time hazard models. From age 11 to 20 years, the prevalence of headache increased from 9.4% to 19.8% in girls and hardly changed in boys (7.6%-6.1%). Headache commonly co-occurred with other unfavorable health and psychosocial conditions. Eighty-eight percent of the girls and 76% of boys with headache also reported at least one of the following at age 17: sleeping problems, asthma, hay fever, musculoskeletal complaints, fatigue, low mental health, or worrying. Results suggest higher headache prevalence in adolescents following lower educational tracks, in those who skip breakfast ≥2 days per week, and in boys exposed to tobacco smoke in infancy. In girls, sleeping problems and musculoskeletal complaints were associated with higher odds of incident headache and residential greenness with lower odds of incident headache. The high prevalence and strong female predominance of headache, already in adolescence and often with comorbidities, deserve recognition by professionals in (preventive) health care settings and schools.
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Affiliation(s)
- Alet H. Wijga
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Ulrike Gehring
- Institute for Risk Assessment Sciences, Utrecht University, the Netherlands
| | | | - Gerard H. Koppelman
- Department of Pediatric Pulmonology and Pediatric Allergology, University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, GRIAC Research Institute, Groningen, the Netherlands
| | - Sarah Vader
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Ruben J.H. Schmits
- Division Preventive Youth Health Care, Public Health Services Region Utrecht (GGD Regio Utrecht), the Netherlands
| | - Johannes C. van der Wouden
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - H. Susan J. Picavet
- Centre for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
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24
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Verdiesen RMG, Onland-Moret NC, van Gils CH, Stellato RK, Spijkerman AMW, Picavet HSJ, Broekmans FJM, Verschuren WMM, van der Schouw YT. Anti-Müllerian hormone levels and risk of type 2 diabetes in women. Diabetologia 2021; 64:375-384. [PMID: 33048171 PMCID: PMC7801305 DOI: 10.1007/s00125-020-05302-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [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: 05/05/2020] [Accepted: 09/02/2020] [Indexed: 11/04/2022]
Abstract
AIMS/HYPOTHESIS Given its role in ovarian follicle development, circulating anti-Müllerian hormone (AMH) is considered to be a marker of reproductive ageing. Although accelerated reproductive ageing has been associated with a higher risk of type 2 diabetes, research on the relationship between AMH and type 2 diabetes risk is scarce. Therefore, we aimed to investigate whether age-specific AMH levels and age-related AMH trajectories are associated with type 2 diabetes risk in women. METHODS We measured AMH in repeated plasma samples from 3293 female participants (12,460 samples in total), aged 20-59 years at recruitment, from the Doetinchem Cohort Study, a longitudinal study with follow-up visits every 5 years. We calculated age-specific AMH tertiles at baseline to account for the strong AMH-age correlation. Cox proportional hazards models adjusted for confounders were used to assess the association between baseline age-specific AMH tertiles and incident type 2 diabetes. We applied linear mixed models to compare age-related AMH trajectories for women who developed type 2 diabetes with trajectories for women who did not develop diabetes. RESULTS During a median follow-up of 20 years, 163 women developed type 2 diabetes. Lower baseline age-specific AMH levels were associated with a higher type 2 diabetes risk (HRT2vsT3 1.24 [95% CI 0.81, 1.92]; HRT1vsT3 1.62 [95% CI 1.06, 2.48]; ptrend = 0.02). These findings seem to be supported by predicted AMH trajectories, which suggested that plasma AMH levels were lower at younger ages in women who developed type 2 diabetes compared with women who did not. The trajectories also suggested that AMH levels declined at a slower rate in women who developed type 2 diabetes, although differences in trajectories were not statistically significant. CONCLUSIONS/INTERPRETATION We observed that lower age-specific AMH levels were associated with a higher risk of type 2 diabetes in women. Longitudinal analyses did not show clear evidence of differing AMH trajectories between women who developed type 2 diabetes compared with women who did not, possibly because these analyses were underpowered. Further research is needed to investigate whether AMH is part of the biological mechanism explaining the association between reproductive ageing and type 2 diabetes. Graphical abstract.
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Affiliation(s)
- Renée M G Verdiesen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - N Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Carla H van Gils
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Rebecca K Stellato
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Annemieke M W Spijkerman
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Frank J M Broekmans
- Department of Reproductive Medicine and Gynecology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - W M Monique Verschuren
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Yvonne T van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
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Picavet HSJ, Gehring U, van Haselen A, Koppelman GH, van de Putte EM, Vader S, van der Wouden JHC, Schmits RJH, Smit HA, Wijga A. A widening gap between boys and girls in musculoskeletal complaints, while growing up from age 11 to age 20 - the PIAMA birth Cohort study. Eur J Pain 2021; 25:902-912. [PMID: 33405263 PMCID: PMC8048429 DOI: 10.1002/ejp.1719] [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] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
INTRODUCTION The adolescent years represent a key period for the development of musculoskeletal complaints (MSC) and the differences between boys and girls. We evaluated the prevalence and course of MSC and factors associated with MSC while growing up from age 11 to age 20. METHODS Questionnaire-based data at age 11 (n = 2,638), age 14 (n = 2,517), age 17 (n = 2,094) and at age 20 (n = 2,206) from the ongoing Prevention and Incidence of Asthma and Mite Allergy (PIAMA) birth cohort were analyzed. MSC refers to pain of lower back, upper- and/or lower extremities. A multivariable logistic regression analysis was used to evaluate a number of factors in relation to persistent pain (pain reported at three out of four measurements). RESULTS Prevalence of MSC increased from 14.2% at age 11 to 22.1% at age 20 for boys, and from 17.4% at age 11 to 37.9% at age 20 for girls. Persistent pain was found among 5.1% of the boys and 16.5% of the girls. Being bullied, sleeping problems and tiredness during the day were significantly associated with persistent pain, in both boys and girls, while the latter two were more prevalent among girls. Self-reported (sports-) accidents, and among girls also early onset of puberty, were also significantly associated with persistent pain, but lifestyle factors, such as physical activity and smoking, were not. CONCLUSION The prevalence of MSC increases during adolescence, with a widening gap between boys and girls. The factors associated with MSC are similar in boys and girls, though the prevalence of some of these differ by sex. SIGNIFICANCE Measuring a group of youngsters 4 times between age 11 and 20 shows an increase in the percentage reporting musculoskeletal complaints (MSC) with a widening gap between girls and boys, with more pain among girls. Boys and girls do hardly differ with respect to factors associated with MSC, being mainly psychosocial factors and (sports) accidents.
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Affiliation(s)
- H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Ulrike Gehring
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Amanda van Haselen
- Department of Health Sciences and Amsterdam Public Health research institute, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands
| | - Gerard H Koppelman
- Department of Pediatric Pulmonology and Pediatric Allergology, and GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Groningen, The Netherlands
| | - Elise M van de Putte
- Division Paediatrics, Wilhelmina Children's Hospital (UMC Utrecht), Utrecht, The Netherlands
| | - Sarah Vader
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - J Hans C van der Wouden
- Department of General Practice and Elderly Care Medicine and Amsterdam Public Health research institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Ruben J H Schmits
- Division Preventive Youth Health Care, Public Health Services region Utrecht (GGD Regio Utrecht), Utrecht, The Netherlands
| | - Henriette A Smit
- Division Julius Center, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Alet Wijga
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
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Dieteren CM, Samson LD, Schipper M, van Exel J, Brouwer WBF, Verschuren WMM, Picavet HSJ. The Healthy Aging Index analyzed over 15 years in the general population: The Doetinchem Cohort Study. Prev Med 2020; 139:106193. [PMID: 32653354 DOI: 10.1016/j.ypmed.2020.106193] [Citation(s) in RCA: 4] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 05/30/2020] [Accepted: 07/05/2020] [Indexed: 12/12/2022]
Abstract
The Healthy Aging Index (HAI), an index of physiological aging, has been demonstrated to predicts mortality, morbidity and disability. We studied the longitudinal development of the HAI to identify aging trajectories and evaluated the role of baseline sociodemographic characteristics and lifestyle factors of the trajectories. Four measurements with intervals of 5 years were included from the Doetinchem Cohort Study. The HAI reflects levels of systolic blood pressure, non-fasting plasma glucose levels, global cognitive functioning, plasma creatinine levels and lung functioning. The HAI score ranges from 0 to 10: higher scores indicate a better health profile. Latent class mixture modelling was used to model within-person change and to identify aging trajectories. Area under the curve was calculated per trajectory to estimate total healthy years. In total, 2324 women and 2013 men were included. One HAI trajectory was identified for women, and two trajectories for men, labelled 'gradual' aging (76%) and 'early' aging (24%). Men who were medium/high educated, below 36 years at baseline, complied with guidelines on physical activity and were not obese in any round were associated with increased odds to 'gradual' aging of 1.46 (CI: 1.18-1.81), 1.93 (CI: 1.42-2.62), 1.26 (1.02-1.57) and 1.76 (1.32-2.35), respectively. Between 30 and 70 years of age, men in the 'early' aging trajectory had the least healthy years (29.6 years), followed by women (30.1 years), and 'gradual' aging men (34.7 years). This study emphasizes that 'physiological aging' is not only an issue of older ages. Between 30 and 70 years of age, 'early' aging men and women had approximately five healthy years less compared to 'gradual' aging men. Lifestyle factors (e.g. nutrition and physical activity) seem to play an important role in optimal aging.
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Affiliation(s)
- Charlotte M Dieteren
- Erasmus University Rotterdam, Erasmus School of Health Policy & Management, Rotterdam, the Netherlands.
| | - Leonard D Samson
- National Institute of Public Health and the Environment, Bilthoven, the Netherlands; Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Maarten Schipper
- National Institute of Public Health and the Environment, Bilthoven, the Netherlands
| | - Job van Exel
- Erasmus University Rotterdam, Erasmus School of Health Policy & Management, Rotterdam, the Netherlands; Erasmus University Rotterdam, Erasmus School of Economics, Rotterdam, the Netherlands
| | - Werner B F Brouwer
- Erasmus University Rotterdam, Erasmus School of Health Policy & Management, Rotterdam, the Netherlands; Erasmus University Rotterdam, Erasmus School of Economics, Rotterdam, the Netherlands
| | - W M Monique Verschuren
- National Institute of Public Health and the Environment, Bilthoven, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - H Susan J Picavet
- National Institute of Public Health and the Environment, Bilthoven, the Netherlands
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Samson LD, H Boots AM, Ferreira JA, J Picavet HS, de Rond LGH, de Zeeuw-Brouwer ML, Monique Verschuren WM, Buisman AM, Engelfriet P. In-depth immune cellular profiling reveals sex-specific associations with frailty. Immun Ageing 2020; 17:20. [PMID: 32582361 PMCID: PMC7310472 DOI: 10.1186/s12979-020-00191-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 06/11/2020] [Indexed: 01/12/2023]
Abstract
Background With advancing age, the composition of leukocyte subpopulations in peripheral blood is known to change, but how this change differs between men and women and how it relates to frailty is poorly understood. Our aim in this exploratory study was to investigate whether frailty is associated with changes in immune cell subpopulations and whether this differs between men and women. Therefore, we performed in-depth immune cellular profiling by enumerating a total of 37 subpopulations of T cells, B cells, NK cells, monocytes, and neutrophils in peripheral blood of 289 elderly people between 60-87 years of age. Associations between frailty and each immune cell subpopulation were tested separately in men and women and were adjusted for age and CMV serostatus. In addition, a random forest algorithm was used to predict a participant’s frailty score based on enumeration of immune cell subpopulations. Results In the association study, frailty was found to be associated with increased numbers of neutrophils in both men and in women. Frailer women, but not men, showed higher numbers of total and CD16- monocytes, and lower numbers of both CD56+ T cells and late differentiated CD4+ TemRA cells. The random forest algorithm confirmed all the findings of the association studies in men and women. In men, the predictive accuracy of the algorithm was too low (5.5%) to warrant additional conclusions on top of the ones derived from the association study. In women however, the predictive accuracy was higher (23.1%), additionally revealing that total T cell numbers and total lymphocyte numbers also contribute in predicting frailty. Conclusions In-depth immune cellular profiling revealed consistent associations of frailty with elevated numbers of myeloid cell subpopulations in both men and women. Furthermore, additional associations were found between frailty and lower numbers of some T cell subpopulations, in women only. Thus, our study indicates sex-specific associations of immune subpopulations with frailty. We hope that our study will prompt further investigation into the sex-specific immune mechanisms associated with the development of frailty.
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Affiliation(s)
- Leonard Daniël Samson
- National Institute of Public Health and the Environment, Bilthoven, 3722 BA Netherlands.,Department of Rheumatology and Clinical Immunology, University Medical Center Groningen, University of Groningen, Groningen, 9727 Netherlands
| | - A Mieke H Boots
- Department of Rheumatology and Clinical Immunology, University Medical Center Groningen, University of Groningen, Groningen, 9727 Netherlands
| | - José A Ferreira
- National Institute of Public Health and the Environment, Bilthoven, 3722 BA Netherlands
| | - H Susan J Picavet
- National Institute of Public Health and the Environment, Bilthoven, 3722 BA Netherlands
| | - Lia G H de Rond
- National Institute of Public Health and the Environment, Bilthoven, 3722 BA Netherlands
| | | | - W M Monique Verschuren
- National Institute of Public Health and the Environment, Bilthoven, 3722 BA Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, 3553 Netherlands
| | - Anne-Marie Buisman
- National Institute of Public Health and the Environment, Bilthoven, 3722 BA Netherlands
| | - Peter Engelfriet
- National Institute of Public Health and the Environment, Bilthoven, 3722 BA Netherlands
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Fedko IO, Hottenga JJ, Helmer Q, Mbarek H, Huider F, Amin N, Beulens JW, Bremmer MA, Elders PJ, Galesloot TE, Kiemeney LA, van Loo HM, Picavet HSJ, Rutters F, van der Spek A, van de Wiel AM, van Duijn C, de Geus EJC, Feskens EJM, Hartman CA, Oldehinkel AJ, Smit JH, Verschuren WMM, Penninx BWJH, Boomsma DI, Bot M. Measurement and genetic architecture of lifetime depression in the Netherlands as assessed by LIDAS (Lifetime Depression Assessment Self-report). Psychol Med 2020; 51:1-10. [PMID: 32102724 PMCID: PMC8223240 DOI: 10.1017/s0033291720000100] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 10/09/2019] [Accepted: 01/13/2020] [Indexed: 11/25/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is a common mood disorder, with a heritability of around 34%. Molecular genetic studies made significant progress and identified genetic markers associated with the risk of MDD; however, progress is slowed down by substantial heterogeneity as MDD is assessed differently across international cohorts. Here, we used a standardized online approach to measure MDD in multiple cohorts in the Netherlands and evaluated whether this approach can be used in epidemiological and genetic association studies of depression. METHODS Within the Biobank Netherlands Internet Collaboration (BIONIC) project, we collected MDD data in eight cohorts involving 31 936 participants, using the online Lifetime Depression Assessment Self-report (LIDAS), and estimated the prevalence of current and lifetime MDD in 22 623 unrelated individuals. In a large Netherlands Twin Register (NTR) twin-family dataset (n ≈ 18 000), we estimated the heritability of MDD, and the prediction of MDD in a subset (n = 4782) through Polygenic Risk Score (PRS). RESULTS Estimates of current and lifetime MDD prevalence were 6.7% and 18.1%, respectively, in line with population estimates based on validated psychiatric interviews. In the NTR heritability estimates were 0.34/0.30 (s.e. = 0.02/0.02) for current/lifetime MDD, respectively, showing that the LIDAS gives similar heritability rates for MDD as reported in the literature. The PRS predicted risk of MDD (OR 1.23, 95% CI 1.15-1.32, R2 = 1.47%). CONCLUSIONS By assessing MDD status in the Netherlands using the LIDAS instrument, we were able to confirm previously reported MDD prevalence and heritability estimates, which suggests that this instrument can be used in epidemiological and genetic association studies of depression.
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Affiliation(s)
- Iryna O. Fedko
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Quinta Helmer
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Hamdi Mbarek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Floris Huider
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Joline W. Beulens
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Centres, location VUMC, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Petra J. Elders
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of General Practice, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Tessel E. Galesloot
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Lambertus A. Kiemeney
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Hanna M. van Loo
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - H. Susan J. Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Femke Rutters
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Centres, location VUMC, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Ashley van der Spek
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Anne M. van de Wiel
- Division of Human Nutrition and Health, Wageningen University, Wageningen, The Netherlands
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Edith J. M. Feskens
- Division of Human Nutrition and Health, Wageningen University, Wageningen, The Netherlands
| | - Catharina A. Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Albertine J. Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jan H. Smit
- Amsterdam UMC, Vrije Universiteit Amsterdam, Psychiatry, Amsterdam, The Netherlands
| | - W. M. Monique Verschuren
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Brenda W. J. H. Penninx
- Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam, The Netherlands
- Amsterdam UMC, Vrije Universiteit Amsterdam, Psychiatry, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Mariska Bot
- Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam, The Netherlands
- Amsterdam UMC, Vrije Universiteit Amsterdam, Psychiatry, Amsterdam, The Netherlands
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Freisling H, Viallon V, Lennon H, Bagnardi V, Ricci C, Butterworth AS, Sweeting M, Muller D, Romieu I, Bazelle P, Kvaskoff M, Arveux P, Severi G, Bamia C, Kühn T, Kaaks R, Bergmann M, Boeing H, Tjønneland A, Olsen A, Overvad K, Dahm CC, Menéndez V, Agudo A, Sánchez MJ, Amiano P, Santiuste C, Gurrea AB, Tong TYN, Schmidt JA, Tzoulaki I, Tsilidis KK, Ward H, Palli D, Agnoli C, Tumino R, Ricceri F, Panico S, Picavet HSJ, Bakker M, Monninkhof E, Nilsson P, Manjer J, Rolandsson O, Thysell E, Weiderpass E, Jenab M, Riboli E, Vineis P, Danesh J, Wareham NJ, Gunter MJ, Ferrari P. Lifestyle factors and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study. BMC Med 2020; 18:5. [PMID: 31918762 PMCID: PMC6953215 DOI: 10.1186/s12916-019-1474-7] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2019] [Accepted: 11/26/2019] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. METHODS In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. RESULTS During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. CONCLUSION Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.
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Affiliation(s)
- Heinz Freisling
- Nutritional Methodology and Biostatistics Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France.
| | - Vivian Viallon
- Nutritional Methodology and Biostatistics Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Hannah Lennon
- Nutritional Methodology and Biostatistics Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Vincenzo Bagnardi
- Department of Statistics and Quantitative Methods, University of Milan Bicocca, Milan, Italy
| | - Cristian Ricci
- Centre of Excellence for Nutrition (CEN), North-West University, Potchefstroom, South Africa
| | - Adam S Butterworth
- Medical Research Council, British Heart Foundation, Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Michael Sweeting
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - David Muller
- Department Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Isabelle Romieu
- Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Pauline Bazelle
- Nutritional Methodology and Biostatistics Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
| | - Marina Kvaskoff
- Centre for Research in Epidemiology and Population Health (CESP), Inserm, Facultés de Médecine Universités Paris Sud, UVSQ, Université Paris Saclay, Gustave Roussy, Villejuif, France
| | - Patrick Arveux
- Centre for Research in Epidemiology and Population Health (CESP), Inserm, Facultés de Médecine Universités Paris Sud, UVSQ, Université Paris Saclay, Gustave Roussy, Villejuif, France
- Breast and Gynaecologic Cancer Registry of Côte d'Or, Georges François Leclerc Comprehensive Cancer Care Centre, Dijon, France
| | - Gianluca Severi
- Centre for Research in Epidemiology and Population Health (CESP), Inserm, Facultés de Médecine Universités Paris Sud, UVSQ, Université Paris Saclay, Gustave Roussy, Villejuif, France
- Molecular and Genetic Epidemiology Unit, Human Genetics Foundation, Torino, Italy
| | - Christina Bamia
- WHO Collaborating Center for Nutrition and Health, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
- Hellenic Health Foundation, Athens, Greece
| | - Tilman Kühn
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Manuela Bergmann
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbrücke, Nuthetal, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbrücke, Nuthetal, Germany
| | | | - Anja Olsen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Kim Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | | | | | - Antonio Agudo
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - Maria-Jose Sánchez
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Andalusian School of Public Health and Instituto de Investigación Biosanitaria de Granada ibs, Servicio Andaluz de Salud/Universidad de Granada, Granada, Spain
| | - Pilar Amiano
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Public Health Division of Gipuzkoa, BioDonostia Research Institute, San Sebastian, Spain
| | - Carmen Santiuste
- Department of Epidemiology, Murcia Regional Health Council, IMIB Arrixaca, Murcia, Spain
| | | | - Tammy Y N Tong
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ioanna Tzoulaki
- Department Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Konstantinos K Tsilidis
- Department Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Heather Ward
- Department Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy
| | - Claudia Agnoli
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | | | - Fulvio Ricceri
- Città della Salute e della Scienza di Torino Hospital, Turin, Italy
| | - Salvatore Panico
- Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Marije Bakker
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Evelyn Monninkhof
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Peter Nilsson
- Public Health and Clinical Medicine, Nutritional Research, Umeå University, and Arctic Research Centre at Umeå University, Umeå, Sweden
| | - Jonas Manjer
- Department of Surgery, Skåne University Hospital Malmö, Lund University, Malmö, Sweden
| | - Olov Rolandsson
- Department of Public Health and Clinical Medicine, Section of Family Medicine, Umeå University, Umeå, Sweden
| | - Elin Thysell
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | | | - Mazda Jenab
- Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Elio Riboli
- Department Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Paolo Vineis
- Department Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - John Danesh
- Medical Research Council, British Heart Foundation, Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Nick J Wareham
- MRC Epidemiology Unit, School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Marc J Gunter
- Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Pietro Ferrari
- Nutritional Methodology and Biostatistics Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon CEDEX 08, France
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Picavet HSJ, Monique Verschuren WM, Groot L, Schaap L, van Oostrom SH. Pain over the adult life course: 15-year pain trajectories-The Doetinchem Cohort Study. Eur J Pain 2019; 23:1723-1732. [PMID: 31257661 PMCID: PMC6790708 DOI: 10.1002/ejp.1450] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 06/24/2019] [Accepted: 06/25/2019] [Indexed: 12/20/2022]
Abstract
BACKGROUND Pain at any age is related to pain experienced at younger ages, but not much is known on how pain develops over the adult life course. We studied long-term individual trajectories of pain over 15 years of the life course and evaluated the role of baseline sociodemographic factors, lifestyle factors and health characteristics. METHODS Longitudinal data from the Doetinchem Cohort Study was used with 3,485 adults aged 25-71 years at baseline who were measured every 5 years, until the age of 40-86 years. Four measurements of self-reported pain were used to distinguish 15-year trajectories of pain, that were summarized in five pre-definedpatterns. RESULTS The typical pain trajectory patterns were (prevalence): never pain (32.2%), persistent pain (19.5%), development of pain (19.2%), diminishing pain (11.1%) and fluctuating pain (18.0%). Multinomial logistic regression analyses showed that the trajectory characterized by never pain was more often found among: men, non-smokers, those reporting a normal sleep duration and those without obesity, chronic disease, a poor mental health, a poor perceived health, or musculoskeletal complaints. CONCLUSIONS A substantial part of the population reports pain over a long period of their life course and long-term trajectories of pain may reflect phenotypes that may be relevant to take into account in pain management. Several risk factors, such as short-sleep duration, smoking, obesity and poor perceived or mental health may be relevant in recognizing those with pain, and tackling these may contribute to the prevention of pain over the life course. SIGNIFICANCE Asking adults about pain every 5 years over a 15-year period shows that almost one-third never reported pain and one-fifth persistent pain. "Persistent" and "developing" pain is associated with smoking, obesity and short sleep duration. Long-term pain trajectories may reflect relevant pain phenotypes.
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Affiliation(s)
- H. Susan J. Picavet
- Centre for Nutrition, Prevention and Health ServicesNational Institute for Public Health and the EnvironmentBilthoventhe Netherlands
| | - W. M. Monique Verschuren
- Centre for Nutrition, Prevention and Health ServicesNational Institute for Public Health and the EnvironmentBilthoventhe Netherlands
- Julius Center for Health Sciences and Primary CareUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Lichelle Groot
- Centre for Nutrition, Prevention and Health ServicesNational Institute for Public Health and the EnvironmentBilthoventhe Netherlands
- Health SciencesVU UniversityAmsterdamthe Netherlands
| | - Laura Schaap
- Health SciencesVU UniversityAmsterdamthe Netherlands
| | - Sandra H. van Oostrom
- Centre for Nutrition, Prevention and Health ServicesNational Institute for Public Health and the EnvironmentBilthoventhe Netherlands
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Rietman ML, Hulsegge G, Nooyens ACJ, Dollé MET, Picavet HSJ, Bakker SJL, Gansevoort RT, Spijkerman AMW, Verschuren WMM. Trajectories of (Bio)markers During the Development of Cognitive Frailty in the Doetinchem Cohort Study. Front Neurol 2019; 10:497. [PMID: 31214102 PMCID: PMC6555275 DOI: 10.3389/fneur.2019.00497] [Citation(s) in RCA: 5] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 04/24/2019] [Indexed: 01/31/2023] Open
Abstract
Background: Long-term changes in (bio)markers for cognitive frailty are not well characterized. Therefore, our aim is to explore (bio)marker trajectories in adults who became cognitively frail compared to age- and sex-matched controls who did not become cognitively frail over a 15 year follow-up. We hypothesize that those who become cognitively frail have more unfavorable trajectories of (bio)markers compared to controls. Methods: The Doetinchem Cohort Study is a longitudinal population-based study that started in 1987-1991 in men and women aged 20-59 years, with follow-up examinations every 5 years. For the current analyses, we used data of 17 potentially relevant (bio)markers (e.g., body mass index (BMI), urea) from rounds 2 to 5 (1993-2012). A global cognitive functioning score (based on memory, speed, and flexibility) was calculated for each round and transformed into education and examination round-adjusted z-scores. The z-score that corresponded to the 10th percentile in round 5 (z-score = -0.77) was applied as cut-off point for incident cognitive frailty in rounds 2-5. In total, 455 incident cognitively frail cases were identified retrospectively and were compared with 910 age- and sex-matched controls. Trajectories up to 15 years before and 10 years after incident cognitive frailty were analyzed using generalized estimating equations with stratification for sex and adjustment for age and, if appropriate, medication use. Results were further adjusted for level of education, depressive symptoms, BMI, and lifestyle factors. Results: In men, (bio)marker trajectories did not differ as they ran parallel and the difference in levels was not statistically significant between those who became cognitively frail compared to controls. In women, total cholesterol trajectories first increased and thereafter decreased in cognitively frail women and steadily increased in controls, gamma-glutamyltransferase trajectories were more or less stable in cognitively frail women and increased in controls, and urea trajectories increased in cognitively frail women and remained more or less stable in controls. Results were similar after additional adjustment for potential confounders. Conclusions: Out of the 17 (bio)markers included in this explorative study, differential trajectories for three biomarkers were observed in women. We do not yet consider any of the studied (bio)markers as promising biomarkers for cognitive frailty.
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Affiliation(s)
- M Liset Rietman
- National Institute for Public Health and the Environment, Bilthoven, Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Gerben Hulsegge
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Astrid C J Nooyens
- National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Martijn E T Dollé
- National Institute for Public Health and the Environment, Bilthoven, Netherlands.,Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
| | - H Susan J Picavet
- National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Stephan J L Bakker
- Department of Internal Medicine, University Medical Center Groningen and University of Groningen, Groningen, Netherlands
| | - Ron T Gansevoort
- Department of Internal Medicine, University Medical Center Groningen and University of Groningen, Groningen, Netherlands
| | | | - W M Monique Verschuren
- National Institute for Public Health and the Environment, Bilthoven, Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
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van Oostrom SH, Slobbe LCJ, van den Berg SW, Verschuren WMM, Picavet HSJ. Do generations differ in sports participation and physical activity over the life course? Evidence from multiple datasets. Eur J Sport Sci 2019; 19:1395-1403. [PMID: 30978151 DOI: 10.1080/17461391.2019.1600587] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Generational differences in health-related factors will affect forecasts of future disease patterns and health care needs. We studied whether participation in sports activity and being physically active are different between 10-year generations over a part of their life course. We used three different datasets on Dutch adults: a cohort study running for 20 years, the Doetinchem Cohort Study (DCS), multiple yearly databases (2001-2015) from the Netherlands health interview study (HIS), and a retrospective cohort study on life time sports careers, the Sports Participation Monitor (SPM). Based on a different questionnaire in each study, frequencies of weekly sport participation and being physically active according to recommended levels were determined by generation and sex. All data sets showed that self-reported sport participation has been increasing with every 10-year generation already for many decades. Especially for those generations born in the 1930s up to the 1960s, sport participation is higher compared to their predecessors. For instance at age 50, 43% of those born in the 1940s engaged in sports activities compared to 55% of those born in the 1950s (DCS data). Physical activity according to recommended levels showed no systematic differences by generation. In conclusion, favourable generation-specific trends in participation in sports activities are found: recent generations are doing better than the older generations. It is unclear whether this also reflects higher levels of physical activity or lower levels of inactivity. Future research may reveal whether these developments also hold for other countries, and whether these developments continue for the younger generations.
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Affiliation(s)
- Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment , Bilthoven , Netherlands
| | - Lany C J Slobbe
- Centre for Health and Society, National Institute for Public Health and the Environment , Bilthoven , Netherlands
| | - Saskia W van den Berg
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment , Bilthoven , Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment , Bilthoven , Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment , Bilthoven , Netherlands
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Hulsegge G, Picavet HSJ, van der Beek AJ, Verschuren WMM, Twisk JW, Proper KI. Shift work, chronotype and the risk of cardiometabolic risk factors. Eur J Public Health 2018; 29:128-134. [DOI: 10.1093/eurpub/cky092] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Affiliation(s)
- Gerben Hulsegge
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Allard J van der Beek
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jos W Twisk
- Department of Epidemiology & Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - Karin I Proper
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
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van Oostrom SH, Engelfriet PM, Verschuren WMM, Schipper M, Wouters IM, Boezen M, Smit HA, Kerstjens HAM, Picavet HSJ. Aging-related trajectories of lung function in the general population-The Doetinchem Cohort Study. PLoS One 2018; 13:e0197250. [PMID: 29768509 PMCID: PMC5955530 DOI: 10.1371/journal.pone.0197250] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Accepted: 04/30/2018] [Indexed: 01/07/2023] Open
Abstract
The objective of this study was to explore trajectories of lung function decline with age in the general population, and to study the effect of sociodemographic and life style related risk factors, in particular smoking and BMI. For this purpose, we used data from the Doetinchem Cohort Study (DCS) of men and women, selected randomly from the general population and aged 20–59 years at inclusion in 1987–1991, and followed until the present. Participants in the DCS are assessed every five years. Spirometry has been performed as part of this assessment from 1994 onwards. Participants were included in this study if spirometric measurement of FEV1, which in this study was the main parameter of interest, was acceptable and reproducible on at least one measurement round, leading to the inclusion of 5727 individuals (3008 females). Statistical analysis revealed three typical trajectories. The majority of participants followed a trajectory that closely adhered to the Global Lung Initiative Reference values (94.9% of men and 96.4% of women). Two other trajectories showed a more pronounced decline. Smoking and the presence of respiratory complaints were the best predictors of a trajectory with stronger decline. A greater BMI over the follow-up period was associated with a more unfavorable FEV1 course both in men (β = -0.027 (SD = 0.002); P < 0.001) and in women (β = -0.008 (SD = 0.001); P < 0.001). Smokers at baseline who quit the habit during follow-up, showed smaller decline in FEV1 in comparison to persistent smokers, independent of BMI change (In men β = -0.074 (SD = 0.020); P < 0.001. In women β = -0.277 (SD = 0.068); P < 0.001). In conclusion, three typical trajectories of age-related FEV1 decline could be distinguished. Change in the lifestyle related risk factors, BMI and smoking, significantly impact aging-related decline of lung function. Identifying deviant trajectories may help in early recognition of those at risk of a diagnosis of lung disease later in life.
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Affiliation(s)
- Sandra H. van Oostrom
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Peter M. Engelfriet
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
- * E-mail:
| | - W. M. Monique Verschuren
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Maarten Schipper
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Inge M. Wouters
- Division of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands
| | - Marike Boezen
- Department of Epidemiology, UMCG, Groningen, the Netherlands
| | - Henriëtte A. Smit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | - H. Susan J. Picavet
- Center for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
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Geboers B, Uiters E, Reijneveld SA, Jansen CJM, Almansa J, Nooyens ACJ, Verschuren WMM, de Winter AF, Picavet HSJ. Health literacy among older adults is associated with their 10-years' cognitive functioning and decline - the Doetinchem Cohort Study. BMC Geriatr 2018; 18:77. [PMID: 29558890 PMCID: PMC5859753 DOI: 10.1186/s12877-018-0766-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [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: 10/16/2017] [Accepted: 03/12/2018] [Indexed: 11/11/2022] Open
Abstract
Background Many older adults have low levels of health literacy which affects their ability to participate optimally in healthcare. It is unclear how cognitive decline contributes to health literacy. To study this, longitudinal data are needed. The aim of this study was therefore to assess the associations of cognitive functioning and 10-years’ cognitive decline with health literacy in older adults. Methods Data from 988 participants (mean age = 65.3) of the Doetinchem Cohort Study were analyzed. Health literacy was measured by the Brief Health Literacy Screening. Memory, mental flexibility, information processing speed, and global cognitive functioning were assessed at the same time as health literacy and also 10 years earlier. Logistic regression analyses were performed, adjusted for age, gender, and educational level. Results Higher scores on tests in all cognitive domains were associated with a lower likelihood of having low health literacy after adjustment for confounders (all ORs < 0.70, p-values<.001). Similar associations were found for past cognitive functioning (all ORs < 0.75, p-values<.05). Before adjustment, stronger cognitive decline was associated with a greater likelihood of having low health literacy (all ORs > 1.37, p-values<.05). These associations lost significance after adjustment for educational level, except for the association of memory decline (OR = 1.40, p = .023, 95% CI: 1.05 to 1.88). Conclusion Older adults with poorer cognitive functioning and stronger cognitive decline are at risk for having low health literacy, which can affect their abilities to promote health and self-manage disease. Low health literacy and declining cognitive functioning might be a barrier for person-centered care, even in relatively young older adults.
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Affiliation(s)
- Bas Geboers
- Department of Health Sciences, University Medical Center Groningen, University of Groningen, Hanzeplein 1, FA10, P.O. Box 30.001, 9700 RB, Groningen, the Netherlands.
| | - Ellen Uiters
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Sijmen A Reijneveld
- Department of Health Sciences, University Medical Center Groningen, University of Groningen, Hanzeplein 1, FA10, P.O. Box 30.001, 9700 RB, Groningen, the Netherlands
| | - Carel J M Jansen
- Department of Communication and Information Studies, Faculty of Arts, University of Groningen, Groningen, the Netherlands
| | - Josué Almansa
- Department of Health Sciences, University Medical Center Groningen, University of Groningen, Hanzeplein 1, FA10, P.O. Box 30.001, 9700 RB, Groningen, the Netherlands
| | - Astrid C J Nooyens
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Andrea F de Winter
- Department of Health Sciences, University Medical Center Groningen, University of Groningen, Hanzeplein 1, FA10, P.O. Box 30.001, 9700 RB, Groningen, the Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
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Rietman ML, van der A DL, van Oostrom SH, Picavet HSJ, Dollé MET, van Steeg H, Verschuren WMM, Spijkerman AMW. The Association between BMI and Different Frailty Domains: A U-Shaped Curve? J Nutr Health Aging 2018; 22:8-15. [PMID: 29300416 DOI: 10.1007/s12603-016-0854-3] [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] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVES Previous studies showed a U-shaped association between BMI and (physical) frailty. We studied the association between BMI and physical, cognitive, psychological, and social frailty. Furthermore, the overlap between and prevalence of these frailty domains was examined. DESIGN Cross-sectional study. SETTING The Doetinchem Cohort Study is a longitudinal population-based study starting in 1987-1991 examining men and women aged 20-59 with follow-up examinations every 5 yrs. PARTICIPANTS For the current analyses, we used data from round 5 (2008-2012) with 4019 participants aged 41-81 yrs. MEASUREMENTS Physical frailty was defined as having ≥ 2 of 4 frailty criteria from the Frailty Phenotype (unintentional weight loss, exhaustion, physical activity, handgrip strength). Cognitive frailty was defined as the < 10th percentile on global cognitive functioning (based on memory, speed, flexibility). Psychological frailty was defined as having 2 out of 2 criteria (depression, mental health). Social frailty was defined as having ≥ 2 of 3 criteria (loneliness, social support, social participation). BMI was divided into four classes. Analyses were adjusted for sex, age, level of education, and smoking. RESULTS A U-shaped association was observed between BMI and physical frailty, a small linear association for BMI and cognitive frailty and no association between BMI and psychological and social frailty. The four frailty domains showed only a small proportion of overlap. The prevalence of physical, cognitive and social frailty increased with age, whereas psychological frailty did not. CONCLUSION We confirm that not only underweight but also obesity is associated with physical frailty. Obesity also seems to be associated with cognitive frailty. Further, frailty prevention should focus on multiple domains and target individuals at a younger age (<65yrs).
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Affiliation(s)
- M L Rietman
- M. Liset Rietman, MSc, National Institute for Public Health and the Environment, Bilthoven, the Netherlands, E-mail address: , Telephone number: +31302742709
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Picavet HSJ, Blokstra A, Spijkerman AMW, Verschuren WMM. Cohort Profile Update: The Doetinchem Cohort Study 1987-2017: lifestyle, health and chronic diseases in a life course and ageing perspective. Int J Epidemiol 2017; 46:1751-1751g. [PMID: 29040549 PMCID: PMC5837330 DOI: 10.1093/ije/dyx103] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 05/16/2017] [Accepted: 05/22/2017] [Indexed: 12/26/2022] Open
Affiliation(s)
- H S J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands and
| | - Anneke Blokstra
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands and
| | - Annemieke MW Spijkerman
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands and
| | - WM Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands and
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
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Zomers ML, Hulsegge G, van Oostrom SH, Proper KI, Verschuren WMM, Picavet HSJ. Characterizing Adult Sleep Behavior Over 20 Years-The Population-Based Doetinchem Cohort Study. Sleep 2017; 40:3836088. [PMID: 28525637 PMCID: PMC5805248 DOI: 10.1093/sleep/zsx085] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [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] [Indexed: 01/19/2023] Open
Abstract
Study Objectives: To describe sleep duration patterns of adults over a 20-year period; to compare sociodemographic, lifestyle, and health characteristics across these patterns; and to relate the patterns to sleep quality. Methods: The study population consisted of 3695 adults aged 20 to 59 years at baseline. Five measurements of self-reported sleep duration were used to compose seven patterns from 1987 to 2012: persistent short (≤6 hours), moderate (7–8 hours), or long (≥9 hours) sleep duration and several changing patterns (varying and became short, moderate, or long sleepers). Multinomial logistic regression analyses were used to compare characteristics across sleep duration patterns. Results: About 56% of the adults had persistent moderate sleep duration over 20 years. This group had a better sleep quality than the other groups. Of the adults who changed in their sleep duration (40%), 43% became a short sleeper. Sleep duration patterns that deviate from persistent moderate sleep duration were associated with physical inactivity during leisure time (odds ratios [ORs] and 95% confidence intervals [95% CIs] varied between 1.26 [1.04–1.53] and 1.58 [1.06–2.37]) and with poor self-rated health (ORs [95% CIs] varied between 1.50 [1.20–1.87] and 2.15 [1.48–3.12]). Conclusions: Nearly half of the adults did not have persistent moderate sleep duration over a 20-year period and more than one-sixth became short sleeper. This is reason for concern considering the adverse health status associated with short and long sleep duration. Leisure-time physical activity is a potential important target to prevent unfavorable changes in sleep duration over the life course.
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Affiliation(s)
- Margot L Zomers
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Gerben Hulsegge
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.,Department of Public and Occupational Health, EMGO+ Institute for Health and Care Research, VU University Medical Centre, Amsterdam, The Netherlands
| | - Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Karin I Proper
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.,Department of Public and Occupational Health, EMGO+ Institute for Health and Care Research, VU University Medical Centre, Amsterdam, The Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.,Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
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van Oostrom SH, van der A DL, Rietman ML, Picavet HSJ, Lette M, Verschuren WMM, de Bruin SR, Spijkerman AMW. A four-domain approach of frailty explored in the Doetinchem Cohort Study. BMC Geriatr 2017; 17:196. [PMID: 28854882 PMCID: PMC5577839 DOI: 10.1186/s12877-017-0595-0] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [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: 01/10/2017] [Accepted: 08/22/2017] [Indexed: 11/24/2022] Open
Abstract
Background Accumulation of problems in physical, psychological, cognitive, or social functioning is characteristic for frail individuals. Using a four-domain approach of frailty, this study explored how sociodemographic and lifestyle factors, life events and health are associated with frailty. Methods The study sample included 4019 men and women (aged 40–81 years) examined during the fifth round (2008–2012) of the Doetinchem Cohort Study. Four domains of frailty were considered: physical (≥4 of 8 criteria: unintentional weight loss, exhaustion, strength, perceived health, walking, balance, hearing and vision impairments), psychological (2 criteria: depressive symptoms, mental health), cognitive (<10th percentile on global cognitive functioning), and social frailty (≥2 of 3 criteria: loneliness, social support, social participation). Logistic regression was used to study the cross-sectional association of sociodemographic factors, lifestyle, life events and chronic diseases with frailty domains. Results About 17% of the population was frail on one or more domains. Overlap between the frailty domains was limited since 82% of the frail population was frail on one domain only. Low educated respondents were at higher risk of being psychologically and socially frail. Having multiple diseases was associated with a higher risk of being physically and psychologically frail. Being physically active was consistently associated with a lower risk of frailty on each of the four domains. Short or long sleep duration was associated with a higher risk of being physically, psychologically, and socially frail. Conclusions Sociodemographic factors, lifestyle and multimorbidity contributed differently to the four frailty domains. It is important to consider multiple frailty domains since this helps to identify different groups of frail people, and as such to provide tailored care and support. Lifestyle factors including physical activity, smoking and sleep duration were associated with multiple domains of frailty. Electronic supplementary material The online version of this article doi: 10.1186/s12877-017-0595-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, P.O. Box 1, 3720, Bilthoven, BA, The Netherlands.
| | - Daphne L van der A
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, P.O. Box 1, 3720, Bilthoven, BA, The Netherlands
| | - M Liset Rietman
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, P.O. Box 1, 3720, Bilthoven, BA, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, P.O. Box 1, 3720, Bilthoven, BA, The Netherlands
| | - Manon Lette
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, P.O. Box 1, 3720, Bilthoven, BA, The Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, P.O. Box 1, 3720, Bilthoven, BA, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Simone R de Bruin
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, P.O. Box 1, 3720, Bilthoven, BA, The Netherlands
| | - Annemieke M W Spijkerman
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, P.O. Box 1, 3720, Bilthoven, BA, The Netherlands
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van Oostrom SH, Gijssen R, Stirbu I, Korevaar JC, Schellevis FG, Picavet HSJ, Hoeymans N. [Time trends in prevalence of chronic diseases and multimorbidity not only due to aging: data from general practices and health surveys]. Ned Tijdschr Geneeskd 2017; 161:D1429. [PMID: 28854986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
INTRODUCTION Chronic diseases and multimorbidity are common and expected to rise over the coming years. The objective of this study is to examine the time trend in the prevalence of chronic diseases and multimorbidity over the period 2001 till 2011 in the Netherlands, and the extent to which this can be ascribed to the aging of the population. METHODS Monitoring study, using two data sources: 1) medical records of patients listed in a nationally representative network of general practices over the period 2002-2011, and 2) national health interview surveys over the period 2001-2011. Regression models were used to study trends in the prevalence-rates over time, with and without standardization for age. RESULTS An increase from 34.9% to 41.8% (p<0.01) in the prevalence of chronic diseases was observed in the general practice registration over the period 2004-2011 and from 41.0% to 46.6% (p<0.01) based on self-reported diseases over the period 2001-2011. Multimorbidity increased from 12.7% to 16.2% (p<0.01) and from 14.3% to 17.5% (p<0.01), respectively. Aging of the population explained part of these trends: about one-fifth based on general practice data, and one-third for chronic diseases and half of the trend for multimorbidity based on health surveys. CONCLUSIONS The prevalence of chronic diseases and multimorbidity increased over the period 2001-2011. Aging of the population only explained part of the increase, implying that other factors such as health care and society-related developments are responsible for a substantial part of this rise.
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Affiliation(s)
- S H van Oostrom
- *Dit onderzoek werd eerder gepubliceerd in PLoS One (2016;11:e0160264) met als titel 'Time trends in prevalence of chronic diseases and multimorbidity not only due to aging: data from general practices and health surveys'. Afgedrukt met toestemming
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Picavet HSJ, Milder I, Kruize H, de Vries S, Hermans T, Wendel-Vos W. Greener living environment healthier people?: Exploring green space, physical activity and health in the Doetinchem Cohort Study. Prev Med 2016; 89:7-14. [PMID: 27154351 DOI: 10.1016/j.ypmed.2016.04.021] [Citation(s) in RCA: 80] [Impact Index Per Article: 10.0] [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: 08/13/2015] [Revised: 04/18/2016] [Accepted: 04/29/2016] [Indexed: 11/18/2022]
Abstract
BACKGROUND Evidence is emerging that more green space in the living environment is associated with better health, partly via the pathway of physical activity. OBJECTIVES We explored the cross-sectional and longitudinal associations between green space and physical activity and several health indicators in the Doetinchem Cohort Study. METHODS A random sample of men and women aged 20-59years at baseline was measured max 5 times with 5year-intervals in the period 1987-2012. Data of round 3-5 were used. Measurements were based on examinations (height, weight, blood pressure) or questionnaires (physical activity, perceived health, depressive symptoms, chronic conditions). The percentage of green space (mainly urban and agricultural green) around the home address (125m and 1km) was calculated using satellite data. RESULTS More agricultural green was associated with less time spent on bicycling (β1km=-0.15, 95%CL -0.13; -0.04) and sports (β1km=-0.04, 95%CL -0.07; -0.01) and more time spent on gardening (β1km=0.16, 95%CL 0.12; 0.19) and odd jobs (β1km=0.10, 95%CL 0.05; 0.15), and this was in the other direction for urban green. For only a few of the many health indicators a positive association with green was found, and mainly for total green within 1km radius. Longstanding green or a transition to more green did not show more pronounced associations with health. CONCLUSIONS For the green space range of the Doetinchem area the findings do not strongly support the hypothesis that the percentage of green in the living environment affects health positively. The distinction by type of green may, however, be relevant for physical activity.
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Affiliation(s)
- H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, The Netherlands.
| | - Ivon Milder
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, The Netherlands
| | - Hanneke Kruize
- Centre for Sustainability, Environment and Health, National Institute of Public Health and the Environment, The Netherlands
| | - Sjerp de Vries
- Alterra, Wageningen UR, Wageningen, The Netherlands; Cultural Geography, Wageningen UR, Wageningen, The Netherlands
| | - Tia Hermans
- Alterra, Wageningen UR, Wageningen, The Netherlands
| | - Wanda Wendel-Vos
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, The Netherlands
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Rooth V, van Oostrom SH, Deeg DJH, Verschuren WMM, Picavet HSJ. Common trajectories of physical functioning in the Doetinchem Cohort Study. Age Ageing 2016; 45:382-8. [PMID: 26892339 DOI: 10.1093/ageing/afw018] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2015] [Accepted: 10/21/2015] [Indexed: 11/14/2022] Open
Abstract
PURPOSE to describe common trajectories of physical functioning and their determinants among an adult cohort, followed over a period of 15 years. METHODS the study sample consisted of 4,123 participants (initial ages 26-70 years) from the Doetinchem Cohort Study, who participated in three or four measurement cycles. Physical functioning was measured with the Dutch version of the SF-36. Using a group-based modelling strategy, trajectories of physical functioning were determined. Weighted multinomial logistic regression analyses were performed to identify socio-demographic, lifestyle and health characteristics that differentiate between the trajectories at baseline. RESULTS five common physical functioning trajectories were distinguished, labelled as 'stable not limited' (27% of the population), 'stable slightly limited' (54%), 'slightly limited substantial deterioration' (7%), 'moderately limited gradual improvement' (9%) and 'stable severely limited' (3%). The characteristics that differentiate between the trajectories with limitations and the trajectory 'stable not limited' were being female, older, physically inactive, overweight or obese, having one or more chronic conditions, poor mental health and poor self-perceived health at baseline. Being younger, physically active, less obese, living with a partner and a good perceived health were characteristics of the trajectory 'moderately limited gradual improvement' compared with 'stable severely limited'. CONCLUSION five common trajectories of physical functioning were distinguished in an adult cohort, with most individuals following a stable but slightly limited course of physical functioning. Some early risk indicators were found that in the future might be used to early identify those with limitations in physical functioning.
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Affiliation(s)
- Vera Rooth
- National Institute for Public Health and the Environment-Centre for Nutrition, Prevention and Health Services, Bilthoven, The Netherlands
| | - Sandra H van Oostrom
- National Institute for Public Health and the Environment-Centre for Nutrition, Prevention and Health Services, Bilthoven, The Netherlands
| | - Dorly J H Deeg
- VU University Medical Centre-Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, Amsterdam, The Netherlands
| | - W M Monique Verschuren
- National Institute for Public Health and the Environment-Centre for Nutrition, Prevention and Health Services, Bilthoven, The Netherlands Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - H Susan J Picavet
- National Institute for Public Health and the Environment-Centre for Nutrition, Prevention and Health Services, Bilthoven, The Netherlands
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Picavet HSJ, Pas LW, van Oostrom SH, van der Ploeg HP, Verschuren WMM, Proper KI. The Relation between Occupational Sitting and Mental, Cardiometabolic, and Musculoskeletal Health over a Period of 15 Years--The Doetinchem Cohort Study. PLoS One 2016; 11:e0146639. [PMID: 26752695 PMCID: PMC4713474 DOI: 10.1371/journal.pone.0146639] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Accepted: 12/21/2015] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE Sedentary behaviors are reported to impose health risks. Since occupational exposure is a major proportion of total sedentary time, we studied the association between occupational sitting and a number of health problems. METHODS From the longitudinal Doetinchem Cohort Study, we selected those working at baseline with complete data (n = 1,509). Participants were examined four times at 5 year-intervals between 1993 and 2012. We characterized occupational sitting as follows: 1) stable sitters and stable non sitters over a 15-year period, based on job characteristics and (2) having a job with a low, moderate or high amount of sitting, based on tertiles of self-reported number of hours per week of occupational sitting, measured at wave 5. Linear and logistic regression models were used. Outcomes were self-reported mental health, low-back or upper extremity pain, and objectively measured cardiometabolic health (overweight, hypertension, hypercholesterolemia). RESULTS Compared to stable non sitters, a lower risk of chronic upper extremity pain was observed for stable sitters (OR 0.75, 95% CI: 0.57; 1.00) as well as for those in the two upper tertiles for hours of occupational sitting (>4 hr/wk) (OR 0.65; 95%CI 0.50-0.86). For the other health outcomes studied, no significant associations were found with occupational sitting. CONCLUSION Our findings do not support the hypothesis that occupational sitting is associated with health problems. The finding that occupational sitting is associated with less upper extremity pain might be due to the association of occupational sitting with less physical load.
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Affiliation(s)
- H. Susan J. Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - L. Willemijn Pas
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Sandra H. van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Hidde P. van der Ploeg
- Department of Public and Occupational Health, EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - W. M. Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Karin I. Proper
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
- Department of Public and Occupational Health, EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
- * E-mail:
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Cloostermans L, Picavet HSJ, Bemelmans WJE, Verschuren WMM, Proper KI. Psychological distress as a determinant of changes in body mass index over a period of 10years. Prev Med 2015; 77:17-22. [PMID: 25937590 DOI: 10.1016/j.ypmed.2015.04.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [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: 11/24/2014] [Revised: 04/19/2015] [Accepted: 04/26/2015] [Indexed: 10/23/2022]
Abstract
OBJECTIVE To examine the longitudinal relationship between psychological distress and body mass index (BMI) changes over a period of five and ten years. METHOD Data were used from the Dutch, prospective, population based Doetinchem Cohort study over the period 1995/1999 until 2005/2009 (N=5504). Psychological distress was assessed using the Mental Health Inventory (MHI-5). BMI (kg/m(2)) was calculated from measured body height and body weight. GEE analyses were used to examine the relationship between psychological distress at baseline and BMI change, and the development of overweight over five years. Linear and logistic regression analyses were used to examine these relations over ten years. RESULTS Psychological distress predicted an extra overall increase in BMI of 0.14kg/m(2) (95% CI 0.03-0.25) over five years and an increase of 0.18kg/m(2) (95% CI 0.01-0.35) over ten years, when comparing psychologically distressed participants to psychologically healthy participants. This was especially the case among persons with normal weight (five years; B=0.26kg/m(2), 95% CI=0.12-0.40/ten years; B=0.32kg/m(2) 95% CI=0.11-0.53) and moderate overweight (five years: B=0.18kg/m(2), 95% CI=0.02-0.35) at baseline. Psychological distress did not predict the development of overweight five and ten years later. CONCLUSION The results in this study indicated that psychological distress predicted an increased risk in gaining weight, but did not result in an increased risk for developing overweight.
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Affiliation(s)
- Laura Cloostermans
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Wanda J E Bemelmans
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Karin I Proper
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; Department of Public and Occupational Health Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands.
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Dijkstra AE, Smolonska J, van den Berge M, Wijmenga C, Zanen P, Luinge MA, Platteel M, Lammers JW, Dahlback M, Tosh K, Hiemstra PS, Sterk PJ, Spira A, Vestbo J, Nordestgaard BG, Benn M, Nielsen SF, Dahl M, Verschuren WM, Picavet HSJ, Smit HA, Owsijewitsch M, Kauczor HU, de Koning HJ, Nizankowska-Mogilnicka E, Mejza F, Nastalek P, van Diemen CC, Cho MH, Silverman EK, Crapo JD, Beaty TH, Lomas DA, Bakke P, Gulsvik A, Bossé Y, Obeidat M, Loth DW, Lahousse L, Rivadeneira F, Uitterlinden AG, Hofman A, Stricker BH, Brusselle GG, van Duijn CM, Brouwer U, Koppelman GH, Vonk JM, Nawijn MC, Groen HJM, Timens W, Boezen HM, Postma DS. Correction: Susceptibility to chronic mucus hypersecretion, a genome wide association study. PLoS One 2015; 10:e0129524. [PMID: 26024482 PMCID: PMC4449226 DOI: 10.1371/journal.pone.0129524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Raho E, van Oostrom SH, Visser M, Huisman M, Zantinge EM, Smit HA, Verschuren WMM, Hulsegge G, Picavet HSJ. Generation shifts in smoking over 20 years in two Dutch population-based cohorts aged 20-100 years. BMC Public Health 2015; 15:142. [PMID: 25884440 PMCID: PMC4340284 DOI: 10.1186/s12889-015-1481-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [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: 08/21/2014] [Accepted: 01/27/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Younger and older generations may differ substantially in their lifetime smoking habits, which may result in generation-specific health challenges. We aimed to quantify generation shifts in smoking over a period of 25 years. METHODS We used the Doetinchem Cohort Study (baseline 1987-1991; 7768 individuals; 20-60 years; follow-up 1993-2012) and the Longitudinal Aging Study Amsterdam (baseline 1992-1993; 3017 individuals; 55-85 years; follow-up 1995-2009). Generation shifts were studied between 10-year generations (age range: 20-100 years). Generation shifts were examined graphically and by using logistic random effect models for men and women. RESULTS Among men, significant generation shifts in current smoking were found between two non-successive generations: for instance men in their 40s at baseline smoked much more than men in their 40s at follow-up (33.6% vs. 23.1%, p < 0.05). Among women, the most recently born generation showed a favourable significant generation shift in current smoking (-7.3%) and ever smoking (-10.1%). For all other generations, the prevalence of ever smoking among women was significantly higher in every more recently born generation, whereas no other generation shifts were observed for current smoking. The unfavourable generation shifts were mainly found among the lower educated. CONCLUSIONS The future burden of disease due to smoking is expected to be reduced among men, but not yet among women. Educational differences in smoking-related health problems are expected to increase.
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Affiliation(s)
- Enrico Raho
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
| | - Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
| | - Marjolein Visser
- Department of Health Sciences, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands. .,EMGO+ Institute for Health and Care Research, Department of Epidemiology & Biostatistics, VU University Medical Center, Amsterdam, The Netherlands.
| | - Martijn Huisman
- EMGO+ Institute for Health and Care Research, Department of Epidemiology & Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. .,Department of Sociology, VU University, Amsterdam, The Netherlands.
| | - Else M Zantinge
- Centre for Health and Society, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
| | - Henriette A Smit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands. .,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Gerben Hulsegge
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands. .,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
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van Oostrom SH, Picavet HSJ, de Bruin SR, Stirbu I, Korevaar JC, Schellevis FG, Baan CA. Multimorbidity of chronic diseases and health care utilization in general practice. BMC Fam Pract 2014; 15:61. [PMID: 24708798 PMCID: PMC4021063 DOI: 10.1186/1471-2296-15-61] [Citation(s) in RCA: 159] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2013] [Accepted: 03/25/2014] [Indexed: 11/16/2022]
Abstract
Background Multimorbidity is common among ageing populations and it affects the demand for health services. The objective of this study was to examine the relationship between multimorbidity (i.e. the number of diseases and specific combinations of diseases) and the use of general practice services in the Dutch population of 55 years and older. Methods Data on diagnosed chronic diseases, contacts (including face-to-face consultations, phone contacts, and home visits), drug prescription rates, and referral rates to specialised care were derived from the Netherlands Information Network of General Practice (LINH), limited to patients whose data were available from 2006 to 2008 (N = 32,583). Multimorbidity was defined as having two or more out of 28 chronic diseases. Multilevel analyses adjusted for age, gender, and clustering of patients in general practices were used to assess the association between multimorbidity and service utilization in 2008. Results Patients diagnosed with multiple chronic diseases had on average 18.3 contacts (95% CI 16.8 19.9) per year. This was significantly higher than patients with one chronic disease (11.7 contacts (10.8 12.6)) or without any (6.1 contacts (5.6 6.6)). A higher number of chronic diseases was associated with more contacts, more prescriptions, and more referrals to specialized care. However, the number of contacts per disease decreased with an increasing number of diseases; patients with a single disease had between 9 to 17 contacts a year and patients with five or more diseases had 5 or 6 contacts per disease per year. Contact rates for specific combinations of diseases were lower than what would be expected on the basis of contact rates of the separate diseases. Conclusion Multimorbidity is associated with increased health care utilization in general practice, yet the increase declines per additional disease. Still, with the expected rise in multimorbidity in the coming decades more extensive health resources are required.
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Affiliation(s)
- Sandra H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
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Manschot A, van Oostrom SH, Smit HA, Verschuren WMM, Picavet HSJ. Diagnosis of diabetes mellitus or cardiovascular disease and lifestyle changes - the Doetinchem cohort study. Prev Med 2014; 59:42-6. [PMID: 24275227 DOI: 10.1016/j.ypmed.2013.11.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [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: 06/24/2013] [Revised: 11/15/2013] [Accepted: 11/16/2013] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To study whether being diagnosed with a cardiovascular disease (CVD) or diabetes mellitus (DM) is associated with improvements in lifestyles. METHODS We used data from the Doetinchem Cohort Study, a prospective study among 6386 Dutch men and women initially aged 20-59years who were examined four times over 15years (1987-2007). Logistic and linear regression models were used to assess the effect of a self-reported diagnosis of CVD (n=403) or DM (n=221) on smoking, alcohol consumption, weight, diet and physical activity. RESULTS Self-reported diagnosis of CVD increased rates of smoking cessation (OR=2.2, 95%CI 1.6 - 3.1). Adults reporting a diagnosis of DM (relatively) decreased weight (3.2%, 95%CI 2.2 - 4.2), (relatively) decreased energy intake (4.2%, 95%CI 0.7 - 7.7), decreased energy percentage from saturated fat (0.4%, 95%CI 0.0 - 0.9) and increased fish consumption (2.8 g/day, 95%CI 0.4 - 5.1). A self-reported diagnosis of CVD or DM was not associated with changes in physical activity. CONCLUSION A diagnosis of CVD or DM may act, along with possible effects of medical treatment, as a trigger to adopt a healthier lifestyle in terms of smoking cessation, healthier diet and weight loss.
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Affiliation(s)
- A Manschot
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands; University of Utrecht, The Netherlands.
| | - S H van Oostrom
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands.
| | - H A Smit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands.
| | - W M M Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands.
| | - H S J Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands.
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Super S, Verschuren WMM, Zantinge EM, Wagemakers MAE, Picavet HSJ. A weak sense of coherence is associated with a higher mortality risk. J Epidemiol Community Health 2014; 68:411-7. [DOI: 10.1136/jech-2013-203085] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Zantinge EM, van den Berg M, Smit HA, Picavet HSJ. Retirement and a healthy lifestyle: opportunity or pitfall? A narrative review of the literature. Eur J Public Health 2013; 24:433-9. [PMID: 24148557 DOI: 10.1093/eurpub/ckt157] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Retirement is a life-course transition in late adult life that is marked by major changes that may affect healthy lifestyles. Our aim is to give an overview of the current knowledge on changes in smoking, alcohol consumption, physical activity and dietary habits during the transition to retirement. This may provide clues to a better targeting and timing of preventive activities at older age. METHODS Literature search in Medline, Scopus, Embase, PsycInfo, Social SciSearch and SciSearch limited to English-language papers published between 2001 and May 2013. Results of 20 original papers are summarized in a narrative review. RESULTS Some studies report an increase in alcohol consumption after retirement, whereas others found a decrease or no change at all. Those who retired involuntarily tended to increase their alcohol consumption, whereas retirees who quit voluntarily did not change their alcohol consumption. Leisure-time physical activity seems to increase slightly after retirement, especially moderately intensive physical activity. This increase does not compensate the loss of work-related physical activity such as the work itself or work-related transportation. The studies on changes in smoking and dietary habits were too limited to draw conclusions. CONCLUSIONS The transition to retirement is accompanied with both favourable and unfavourable lifestyle changes, depending on the type of lifestyle, lifestyle indicator and the personal situation of the retiree. The (pre-)retirement period may well offer a suitable opportunity for preventive action, for example in pre-retirement programmes, planning or other retirement-related support.
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Affiliation(s)
- Else M Zantinge
- 1 Centre for Health and Society, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Matthijs van den Berg
- 2 Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Henriëtte A Smit
- 3 Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands
| | - H Susan J Picavet
- 2 Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
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