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Dixon P, Martin RM, Harrison S. Causal Estimation of Long-term Intervention Cost-effectiveness Using Genetic Instrumental Variables: An Application to Cancer. Med Decis Making 2024; 44:283-295. [PMID: 38426435 PMCID: PMC10988994 DOI: 10.1177/0272989x241232607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Accepted: 01/23/2024] [Indexed: 03/02/2024]
Abstract
BACKGROUND This article demonstrates a means of assessing long-term intervention cost-effectiveness in the absence of data from randomized controlled trials and without recourse to Markov simulation or similar types of cohort simulation. METHODS Using a Mendelian randomization study design, we developed causal estimates of the genetically predicted effect of bladder, breast, colorectal, lung, multiple myeloma, ovarian, prostate, and thyroid cancers on health care costs and quality-adjusted life-years (QALYs) using outcome data drawn from the UK Biobank cohort. We then used these estimates in a simulation model to estimate the cost-effectiveness of a hypothetical population-wide preventative intervention based on a repurposed class of antidiabetic drugs known as sodium-glucose cotransporter-2 (SGLT2) inhibitors very recently shown to reduce the odds of incident prostate cancer. RESULTS Genetic liability to prostate cancer and breast cancer had material causal impacts on either or both health care costs and QALYs. Mendelian randomization results for the less common cancers were associated with considerable uncertainty. SGLT2 inhibition was unlikely to be a cost-effective preventative intervention for prostate cancer, although this conclusion depended on the price at which these drugs would be offered for a novel anticancer indication. IMPLICATIONS Our new causal estimates of cancer exposures on health economic outcomes may be used as inputs into decision-analytic models of cancer interventions such as screening programs or simulations of longer-term outcomes associated with therapies investigated in randomized controlled trials with short follow-ups. Our method allowed us to rapidly and efficiently estimate the cost-effectiveness of a hypothetical population-scale anticancer intervention to inform and complement other means of assessing long-term intervention value. HIGHLIGHTS The article demonstrates a novel method of assessing long-term intervention cost-effectiveness without relying on randomized controlled trials or cohort simulations.Mendelian randomization was used to estimate the causal effects of certain cancers on health care costs and quality-adjusted life-years (QALYs) using data from the UK Biobank cohort.Given causal data on the association of different cancer exposures on costs and QALYs, it was possible to simulate the cost-effectiveness of an anticancer intervention.Genetic liability to prostate cancer and breast cancer significantly affected health care costs and QALYs, but the hypothetical intervention using SGLT2 inhibitors for prostate cancer may not be cost-effective, depending on the drug's price for the new anticancer indication. The methods we propose and implement can be used to efficiently estimate intervention cost-effectiveness and to inform decision making in all manner of preventative and therapeutic contexts.
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Affiliation(s)
- Padraig Dixon
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Richard M. Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Sean Harrison
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- UK Health Security Agency
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2
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Abstract
Obesity is a common complex trait that elevates the risk for various diseases, including type 2 diabetes and cardiovascular disease. A combination of environmental and genetic factors influences the pathogenesis of obesity. Advances in genomic technologies have driven the identification of multiple genetic loci associated with this disease, ranging from studying severe onset cases to investigating common multifactorial polygenic forms. Additionally, findings from epigenetic analyses of modifications to the genome that do not involve changes to the underlying DNA sequence have emerged as key signatures in the development of obesity. Such modifications can mediate the effects of environmental factors, including diet and lifestyle, on gene expression and clinical presentation. This review outlines what is known about the genetic and epigenetic contributors to obesity susceptibility, along with the albeit limited therapeutic options currently available. Furthermore, we delineate the potential mechanisms of actions through which epigenetic changes can mediate environmental influences and the related opportunities they present for future interventions in the management of obesity.
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Affiliation(s)
- Khanh Trang
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
- Division of Diabetes and Endocrinology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104 USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104 USA
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3
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Johnson W, Pereira SMP, Costa S, Baker JL, Norris T. The associations of maternal and paternal obesity with latent patterns of offspring BMI development between 7 and 17 years of age: pooled analyses of cohorts born in 1958 and 2001 in the United Kingdom. Int J Obes (Lond) 2023; 47:39-50. [PMID: 36357563 PMCID: PMC9834052 DOI: 10.1038/s41366-022-01237-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/31/2022] [Accepted: 11/01/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE We aimed to 1) describe how the UK obesity epidemic reflects a change over time in the proportion of the population demonstrating adverse latent patterns of BMI development and 2) investigate the potential roles of maternal and paternal BMI in this secular process. METHODS We used serial BMI data between 7 and 17 years of age from 13220 boys and 12711 girls. Half the sample was born in 1958 and half in 2001. Sex-specific growth mixture models were developed. The relationships of maternal and paternal BMI and weight status with class membership were estimated using the 3-step BCH approach, with covariate adjustment. RESULTS The selected models had five classes. For each sex, in addition to the two largest normal weight classes, there were "normal weight increasing to overweight" (17% of boys and 20% of girls), "overweight increasing to obesity" (8% and 6%), and "overweight decreasing to normal weight" (3% and 6%) classes. More than 1-in-10 children from the 2001 birth cohort were in the "overweight increasing to obesity" class, compared to less than 1-in-30 from the 1958 birth cohort. Approximately 75% of the mothers and fathers of this class had overweight or obesity. When considered together, both maternal and paternal BMI were associated with latent class membership, with evidence of negative departure from additivity (i.e., the combined effect of maternal and paternal BMI was smaller than the sum of the individual effects). The odds of a girl belonging to the "overweight increasing to obesity" class (compared to the largest normal weight class) was 13.11 (8.74, 19.66) times higher if both parents had overweight or obesity (compared to both parents having normal weight); the equivalent estimate for boys was 9.01 (6.37, 12.75). CONCLUSIONS The increase in obesity rates in the UK over more than 40 years has been partly driven by the growth of a sub-population demonstrating excess BMI gain during adolescence. Our results implicate both maternal and paternal BMI as correlates of this secular process.
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Affiliation(s)
- William Johnson
- grid.6571.50000 0004 1936 8542School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Snehal M. Pinto Pereira
- grid.83440.3b0000000121901201UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Silvia Costa
- grid.6571.50000 0004 1936 8542School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Jennifer L. Baker
- grid.411702.10000 0000 9350 8874Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark
| | - Tom Norris
- grid.83440.3b0000000121901201UCL Division of Surgery & Interventional Science, University College London, London, UK
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4
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Genetic footprints of assortative mating in the Japanese population. Nat Hum Behav 2023; 7:65-73. [PMID: 36138222 PMCID: PMC9883156 DOI: 10.1038/s41562-022-01438-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 07/20/2022] [Indexed: 02/03/2023]
Abstract
Assortative mating (AM) is a pattern characterized by phenotypic similarities between mating partners. Detecting the evidence of AM has been challenging due to the lack of large-scale datasets that include phenotypic data on both partners, especially in populations of non-European ancestries. Gametic phase disequilibrium between trait-associated alleles is a signature of parental AM on a polygenic trait, which can be detected even without partner data. Here, using polygenic scores for 81 traits in the Japanese population using BioBank Japan Project genome-wide association studies data (n = 172,270), we found evidence of AM on the liability to type 2 diabetes and coronary artery disease, as well as on dietary habits. In cross-population comparison using United Kingdom Biobank data (n = 337,139) we found shared but heterogeneous impacts of AM between populations.
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5
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Lee DS, Nitsche N, Barclay K. Body mass index in early adulthood and transition to first birth: Racial/ethnic and sex differences in the United States NLSY79 Cohort. POPULATION STUDIES 2022:1-21. [DOI: 10.1080/00324728.2022.2128396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
| | | | - Kieron Barclay
- Max Planck Institute for Demographic Research
- Swedish Collegium for Advanced Study
- Stockholm University
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6
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Dixon P, Harrison S, Hollingworth W, Davies NM, Davey Smith G. Estimating the causal effect of liability to disease on healthcare costs using Mendelian Randomization. ECONOMICS AND HUMAN BIOLOGY 2022; 46:101154. [PMID: 35803012 DOI: 10.1016/j.ehb.2022.101154] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 06/15/2022] [Accepted: 06/28/2022] [Indexed: 05/27/2023]
Abstract
Accurate measurement of the effects of disease status on healthcare costs is important in the pragmatic evaluation of interventions but is complicated by endogeneity bias. Mendelian Randomization, the use of random perturbations in germline genetic variation as instrumental variables, can avoid these limitations. We used a novel Mendelian Randomization analysis to model the causal impact on inpatient hospital costs of liability to six prevalent diseases and health conditions: asthma, eczema, migraine, coronary heart disease, Type 2 diabetes, and depression. We identified genetic variants from replicated genome-wide associations studies and estimated their association with inpatient hospital costs on over 300,000 individuals. There was concordance of findings across varieties of sensitivity analyses, including stratification by sex and methods robust to violations of the exclusion restriction. Results overall were imprecise and we could not rule out large effects of liability to disease on healthcare costs. In particular, genetic liability to coronary heart disease had substantial impacts on costs.
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Affiliation(s)
- Padraig Dixon
- Nuffield Department of Primary Care Health Sciences, University of Oxford, United Kingdom; MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom.
| | - Sean Harrison
- MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom; Population Health Sciences, University of Bristol, United Kingdom
| | | | - Neil M Davies
- MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom; Population Health Sciences, University of Bristol, United Kingdom; K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Norway
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom; Population Health Sciences, University of Bristol, United Kingdom; NIHR Biomedical Research Centre, University of Bristol, United Kingdom
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7
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Time to Consider the “Exposome Hypothesis” in the Development of the Obesity Pandemic. Nutrients 2022; 14:nu14081597. [PMID: 35458158 PMCID: PMC9032727 DOI: 10.3390/nu14081597] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 04/04/2022] [Accepted: 04/08/2022] [Indexed: 02/04/2023] Open
Abstract
The obesity epidemic shows no signs of abatement. Genetics and overnutrition together with a dramatic decline in physical activity are the alleged main causes for this pandemic. While they undoubtedly represent the main contributors to the obesity problem, they are not able to fully explain all cases and current trends. In this context, a body of knowledge related to exposure to as yet underappreciated obesogenic factors, which can be referred to as the “exposome”, merits detailed analysis. Contrarily to the genome, the “exposome” is subject to a great dynamism and variability, which unfolds throughout the individual’s lifetime. The development of precise ways of capturing the full exposure spectrum of a person is extraordinarily demanding. Data derived from epidemiological studies linking excess weight with elevated ambient temperatures, in utero, and intergenerational effects as well as epigenetics, microorganisms, microbiota, sleep curtailment, and endocrine disruptors, among others, suggests the possibility that they may work alone or synergistically as several alternative putative contributors to this global epidemic. This narrative review reports the available evidence on as yet underappreciated drivers of the obesity epidemic. Broadly based interventions are needed to better identify these drivers at the same time as stimulating reflection on the potential relevance of the “exposome” in the development and perpetuation of the obesity epidemic.
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8
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Bouchard C. Genetics of Obesity: What We Have Learned Over Decades of Research. Obesity (Silver Spring) 2021; 29:802-820. [PMID: 33899337 DOI: 10.1002/oby.23116] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/15/2020] [Accepted: 12/16/2020] [Indexed: 12/14/2022]
Abstract
There is a genetic component to human obesity that accounts for 40% to 50% of the variability in body weight status but that is lower among normal weight individuals (about 30%) and substantially higher in the subpopulation of individuals with obesity and severe obesity (about 60%-80%). The appreciation that heritability varies across classes of BMI represents an important advance. After controlling for BMI, ectopic fat and fat distribution traits are characterized by heritability levels ranging from 30% to 55%. Defects in at least 15 genes are the cause of monogenic obesity cases, resulting mostly from deficiencies in the leptin-melanocortin signaling pathway. Approximately two-thirds of the BMI heritability can be imputed to common DNA variants, whereas low-frequency and rare variants explain the remaining fraction. Diminishing allele effect size is observed as the number of obesity-associated variants expands, with most BMI-increasing or -decreasing alleles contributing only a few grams or less to body weight. Obesity-promoting alleles exert minimal effects in normal weight individuals but have larger effects in individuals with a proneness to obesity, suggesting a higher penetrance; however, it is not known whether these larger effect sizes precede obesity or are caused by an obese state. The obesity genetic risk is conditioned by thousands of DNA variants that make genetically based obesity prevention and treatment a major challenge.
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Affiliation(s)
- Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
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9
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Magnus MC, Fraser A, Rich-Edwards JW, Magnus P, Lawlor DA, Håberg SE. Time-to-pregnancy and risk of cardiovascular disease among men and women. Eur J Epidemiol 2021; 36:383-391. [PMID: 33492547 PMCID: PMC8076115 DOI: 10.1007/s10654-021-00718-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 01/05/2021] [Indexed: 01/01/2023]
Abstract
A few studies indicate that women with prolonged time-to-pregnancy (TTP) have an increased risk of cardiovascular disease (CVD). This has not been studied in men. We evaluated CVD risk by self-reported TTP among parous women (n = 64,064) and men (n = 50,533) participating in the Norwegian Mother, Father and Child Cohort Study. TTP was categorized as 0–3 (reference), 4–12 and > 12 months. CVD diagnosed between 2008 and 2017 were available from the national patient and general practitioner databases. Risk of CVD by TTP was estimated using Cox regression adjusting for baseline age, education, BMI, smoking, diabetes, and number of offspring in both sexes, and history of endometriosis, ovarian cysts, preterm birth and pre-eclampsia for women. Mean age was 33 for women and 35 for men at baseline (years). The rate of any CVD was 24 per 1000 person years among women and 22 per 1000 person years among men. Longer TTP was associated with increased rate of CVD among women, with adjusted hazard ratios (HRs) of 1.07 (95% CI: 1.03, 1.09) for TTP 4–12 months and 1.14 (1.08, 1.20) for TTP > 12 months. Among men, respective HRs for CVD were 1.06 (1.00, 1.10) for TTP 4–12 months and 1.07 (1.01, 1.14) for TTP > 12 months. We observed sex-differences in the relationship with CVD subtypes but none were statistically significant. In conclusion, both men and women with a prolonged TTP had a small increased risk of CVD, clinical significance of which is unclear. Further studies are necessary to investigate in detail what underlying causes of prolonged TTP might be reflected in the increased risk of CVD. Longer follow-up is required to confirm these preliminary findings.
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Affiliation(s)
- Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, P.O. Box 222, 0213, Skøyen, Oslo, Norway. .,MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK. .,Population Health Sciences, Bristol Medical School, Bristol, UK.
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, Bristol, UK.,Bristol NIHR Biomedical Research Centre, Bristol, UK
| | - Janet W Rich-Edwards
- Division of Women's Health, Department of Medicine, Brigham and Women's Hospital, Boston, USA.,Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, USA
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, P.O. Box 222, 0213, Skøyen, Oslo, Norway
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, Bristol, UK.,Bristol NIHR Biomedical Research Centre, Bristol, UK
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, P.O. Box 222, 0213, Skøyen, Oslo, Norway
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10
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The influence of transmitted and non-transmitted parental BMI-associated alleles on the risk of overweight in childhood. Sci Rep 2020; 10:4806. [PMID: 32179833 PMCID: PMC7075975 DOI: 10.1038/s41598-020-61719-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 02/24/2020] [Indexed: 12/20/2022] Open
Abstract
Overweight in children is strongly associated with parental body mass index (BMI) and overweight. We assessed parental transmitted and non-transmitted genetic contributions to overweight in children from the Danish National Birth Cohort by constructing genetic risk scores (GRSs) from 941 common genetic variants associated with adult BMI and estimating associations of transmitted maternal/paternal and non-transmitted maternal GRS with child overweight. Maternal and paternal BMI (standard deviation (SD) units) had a strong association with childhood overweight [Odds ratio (OR): 2.01 (95% confidence interval (CI) 1.74; 2.34) and 1.64 (95% CI 1.43; 1.89)]. Maternal and paternal transmitted GRSs (SD-units) increased odds for child overweight equally [OR: 1.30 (95% CI 1.16; 1.46) and 1.30 (95% CI 1.16; 1.47)]. However, both the parental phenotypic and the GRS associations may depend on maternal BMI, being weaker among mothers with overweight. Maternal non-transmitted GRS was not associated with child overweight [OR 0.98 (95% CI 0.88; 1.10)] suggesting no specific influence of maternal adiposity as such. In conclusion, parental transmitted GRSs, based on adult BMI, contribute to child overweight, but in overweight mothers other genetic and environmental factors may play a greater role.
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11
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Silverman-Retana O, Hulman A, Simmons RK, Nielsen J, Witte DR. Trajectories of obesity by spousal diabetes status in the English Longitudinal Study of Ageing. Diabet Med 2019; 36:105-109. [PMID: 30175888 DOI: 10.1111/dme.13811] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/29/2018] [Indexed: 12/18/2022]
Abstract
AIMS To examine whether the development of obesity with age was different for individuals with and without a spouse with diabetes. METHODS We analysed data from the English Longitudinal Study of Ageing [n= 7123, median (interquartile range) age 59 (53-67) years, 51% men], which included four clinical examination waves between 1998 and 2012. The main exposure was having a spouse with diabetes. Outcomes of interest were BMI and waist circumference. We fitted quadratic age-related trajectories using mixed-effect models stratified by sex and adjusted for education, smoking and the corresponding interaction terms between age and spousal diabetes status. RESULTS The baseline spousal diabetes prevalence was 4.4%. Men with a wife with diabetes experienced a steeper increase in BMI (1.6 kg/m2 ) between ages 50 to 65 years than men with a wife without diabetes (0.9 kg/m2 ). Women with a husband with diabetes had a similarly shaped BMI trajectory to women with a husband without diabetes, but their average BMI levels were higher between ages 55 and 65 years. Waist circumference trajectories showed a similar shape by spousal diabetes status for men and women, although individuals with a spouse with diabetes had higher waist circumference values throughout follow-up. CONCLUSIONS We found a positive association between spousal diabetes status and obesity development, which differed by sex among middle-aged individuals. Evidence from couple-based interventions is needed to test whether the latter could improve the current individual-focused public health strategies for obesity prevention.
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Affiliation(s)
- O Silverman-Retana
- Department of Public Health, Aarhus University, Aarhus
- Danish Diabetes Academy, Odense University Hospital, Odense
| | - A Hulman
- Department of Public Health, Aarhus University, Aarhus
- Danish Diabetes Academy, Odense University Hospital, Odense
| | - R K Simmons
- Healthcare Improvement Studies (THIS) Institute, University of Cambridge, Cambridge, UK
| | - J Nielsen
- Global Health Section, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - D R Witte
- Department of Public Health, Aarhus University, Aarhus
- Danish Diabetes Academy, Odense University Hospital, Odense
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12
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Yengo L, Robinson MR, Keller MC, Kemper KE, Yang Y, Trzaskowski M, Gratten J, Turley P, Cesarini D, Benjamin DJ, Wray NR, Goddard ME, Yang J, Visscher PM. Imprint of assortative mating on the human genome. Nat Hum Behav 2018; 2:948-954. [PMID: 30988446 PMCID: PMC6705135 DOI: 10.1038/s41562-018-0476-3] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Accepted: 10/22/2018] [Indexed: 11/09/2022]
Abstract
Preference for mates with similar phenotypes; that is, assortative mating, is widely observed in humans1-5 and has evolutionary consequences6-8. Under Fisher's classical theory6, assortative mating is predicted to induce a signature in the genome at trait-associated loci that can be detected and quantified. Here, we develop and apply a method to quantify assortative mating on a specific trait by estimating the correlation (θ) between genetic predictors of the trait from single nucleotide polymorphisms on odd- versus even-numbered chromosomes. We show by theory and simulation that the effect of assortative mating can be quantified in the presence of population stratification. We applied this approach to 32 complex traits and diseases using single nucleotide polymorphism data from ~400,000 unrelated individuals of European ancestry. We found significant evidence of assortative mating for height (θ = 3.2%) and educational attainment (θ = 2.7%), both of which were consistent with theoretical predictions. Overall, our results imply that assortative mating involves multiple traits and affects the genomic architecture of loci that are associated with these traits, and that the consequence of mate choice can be detected from a random sample of genomes.
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Affiliation(s)
- Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
| | - Matthew R Robinson
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Matthew C Keller
- Department of Psychology and Neuroscience, Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Kathryn E Kemper
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Yuanhao Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Maciej Trzaskowski
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Jacob Gratten
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Mater Research, Translational Research Institute, Brisbane, Queensland, Australia
| | - Patrick Turley
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Centre for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - David Cesarini
- National Bureau of Economic Research, Cambridge, MA, USA
- Department of Economics, New York University, New York, NY, USA
- Center for Experimental Social Science, New York University, New York, NY, USA
| | - Daniel J Benjamin
- National Bureau of Economic Research, Cambridge, MA, USA
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
- Department of Economics, University of Southern California, Los Angeles, CA, USA
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Michael E Goddard
- Faculty of Veterinary and Agricultural Science, University of Melbourne, Melbourne, Victoria, Australia
- Biosciences Research Division, Department of Economic Development, Jobs, Transport and Resources Government of Victoria, Bundoora, Victoria, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.
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13
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Qasim A, Turcotte M, de Souza RJ, Samaan MC, Champredon D, Dushoff J, Speakman JR, Meyre D. On the origin of obesity: identifying the biological, environmental and cultural drivers of genetic risk among human populations. Obes Rev 2018; 19:121-149. [PMID: 29144594 DOI: 10.1111/obr.12625] [Citation(s) in RCA: 125] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 08/28/2017] [Accepted: 09/08/2017] [Indexed: 12/12/2022]
Abstract
Genetic predisposition to obesity presents a paradox: how do genetic variants with a detrimental impact on human health persist through evolutionary time? Numerous hypotheses, such as the thrifty genotype hypothesis, attempt to explain this phenomenon yet fail to provide a justification for the modern obesity epidemic. In this critical review, we appraise existing theories explaining the evolutionary origins of obesity and explore novel biological and sociocultural agents of evolutionary change to help explain the modern-day distribution of obesity-predisposing variants. Genetic drift, acting as a form of 'blind justice,' may randomly affect allele frequencies across generations while gene pleiotropy and adaptations to diverse environments may explain the rise and subsequent selection of obesity risk alleles. As an adaptive response, epigenetic regulation of gene expression may impact the manifestation of genetic predisposition to obesity. Finally, exposure to malnutrition and disease epidemics in the wake of oppressive social systems, culturally mediated notions of attractiveness and desirability, and diverse mating systems may play a role in shaping the human genome. As an important first step towards the identification of important drivers of obesity gene evolution, this review may inform empirical research focused on testing evolutionary theories by way of population genetics and mathematical modelling.
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Affiliation(s)
- A Qasim
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - M Turcotte
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - R J de Souza
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - M C Samaan
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pediatrics, McMaster University, Hamilton, ON, Canada.,Division of Pediatric Endocrinology, McMaster Children's Hospital, Hamilton, ON, Canada
| | - D Champredon
- Department of Biology, McMaster University, Hamilton, ON, Canada.,Agent-Based Modelling Laboratory, York University, Toronto, ON, Canada
| | - J Dushoff
- Department of Biology, McMaster University, Hamilton, ON, Canada
| | - J R Speakman
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, UK.,State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - D Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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14
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Nielsen J, Bahendeka SK, Whyte SR, Meyrowitsch DW, Bygbjerg IC, Witte DR. Household and familial resemblance in risk factors for type 2 diabetes and related cardiometabolic diseases in rural Uganda: a cross-sectional community sample. BMJ Open 2017; 7:e015214. [PMID: 28939566 PMCID: PMC5623496 DOI: 10.1136/bmjopen-2016-015214] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Revised: 07/21/2017] [Accepted: 07/26/2017] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVES Prevention of type 2 diabetes (T2D) has been successfully established in randomised clinical trials. However, the best methods for the translation of this evidence into effective population-wide interventions remain unclear. To assess whether households could be a target for T2D prevention and screening, we investigated the resemblance of T2D risk factors at household level and by type of familial dyadic relationship in a rural Ugandan community. METHODS This cross-sectional household-based study included 437 individuals ≥13 years of age from 90 rural households in south-western Uganda. Resemblance in glycosylated haemoglobin (HbA1c), anthropometry, blood pressure, fitness status and sitting time were analysed using a general mixed model with random effects (by household or dyad) to calculate household intraclass correlation coefficients (ICCs) and dyadic regression coefficients. Logistic regression with household as a random effect was used to calculate the ORs for individuals having a condition or risk factor if another household member had the same condition. RESULTS The strongest degree of household member resemblances in T2D risk factors was seen in relation to fitness status (ICC=0.24), HbA1c (ICC=0.18) and systolic blood pressure (ICC=0.11). Regarding dyadic resemblance, the highest standardised regression coefficient was seen in fitness status for spouses (0.54, 95% CI 0.32 to 0.76), parent-offspring (0.41, 95% CI 0.28 0.54) and siblings (0.41, 95% CI 0.25 to 0.57). Overall, parent-offspring and sibling pairs were the dyads with strongest resemblance, followed by spouses. CONCLUSIONS The marked degree of resemblance in T2D risk factors at household level and between spouses, parent-offspring and sibling dyads suggest that shared behavioural and environmental factors may influence risk factor levels among cohabiting individuals, which point to the potential of the household setting for screening and prevention of T2D.
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Affiliation(s)
- Jannie Nielsen
- Department of Public Health, Global Health Section, University of Copenhagen, Copenhagen, Denmark
| | | | - Susan R Whyte
- Department of Anthropology, University of Copenhagen, Copenhagen, Denmark
| | - Dan W Meyrowitsch
- Department of Public Health, Global Health Section, University of Copenhagen, Copenhagen, Denmark
| | - Ib C Bygbjerg
- Department of Public Health, Global Health Section, University of Copenhagen, Copenhagen, Denmark
| | - Daniel R Witte
- Department of Public Health, University of Aarhus, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
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15
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Silventoinen K, Jelenkovic A, Sund R, Yokoyama Y, Hur YM, Cozen W, Hwang AE, Mack TM, Honda C, Inui F, Iwatani Y, Watanabe M, Tomizawa R, Pietiläinen KH, Rissanen A, Siribaddana SH, Hotopf M, Sumathipala A, Rijsdijk F, Tan Q, Zhang D, Pang Z, Piirtola M, Aaltonen S, Öncel SY, Aliev F, Rebato E, Hjelmborg JB, Christensen K, Skytthe A, Kyvik KO, Silberg JL, Eaves LJ, Cutler TL, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Song YM, Yang S, Lee K, Franz CE, Kremen WS, Lyons MJ, Busjahn A, Nelson TL, Whitfield KE, Kandler C, Jang KL, Gatz M, Butler DA, Stazi MA, Fagnani C, D’Ippolito C, Duncan GE, Buchwald D, Martin NG, Medland SE, Montgomery GW, Jeong HU, Swan GE, Krasnow R, Magnusson PKE, Pedersen NL, Dahl Aslan AK, McAdams TA, Eley TC, Gregory AM, Tynelius P, Baker LA, Tuvblad C, Bayasgalan G, Narandalai D, Spector TD, Mangino M, Lachance G, Burt SA, Klump KL, Harris JR, Brandt I, Nilsen TS, Krueger RF, McGue M, Pahlen S, Corley RP, Huibregtse BM, Bartels M, van Beijsterveldt CEM, Willemsen G, Goldberg JH, Rasmussen F, Tarnoki AD, Tarnoki DL, Derom CA, Vlietinck RF, Loos RJF, Hopper JL, Sung J, Maes HH, Turkheimer E, Boomsma DI, Sørensen TIA, Kaprio J. Differences in genetic and environmental variation in adult BMI by sex, age, time period, and region: an individual-based pooled analysis of 40 twin cohorts. Am J Clin Nutr 2017; 106:457-466. [PMID: 28679550 PMCID: PMC5525120 DOI: 10.3945/ajcn.117.153643] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Accepted: 06/08/2017] [Indexed: 12/20/2022] Open
Abstract
Background: Genes and the environment contribute to variation in adult body mass index [BMI (in kg/m2)], but factors modifying these variance components are poorly understood.Objective: We analyzed genetic and environmental variation in BMI between men and women from young adulthood to old age from the 1940s to the 2000s and between cultural-geographic regions representing high (North America and Australia), moderate (Europe), and low (East Asia) prevalence of obesity.Design: We used genetic structural equation modeling to analyze BMI in twins ≥20 y of age from 40 cohorts representing 20 countries (140,379 complete twin pairs).Results: The heritability of BMI decreased from 0.77 (95% CI: 0.77, 0.78) and 0.75 (95% CI: 0.74, 0.75) in men and women 20-29 y of age to 0.57 (95% CI: 0.54, 0.60) and 0.59 (95% CI: 0.53, 0.65) in men 70-79 y of age and women 80 y of age, respectively. The relative influence of unique environmental factors correspondingly increased. Differences in the sets of genes affecting BMI in men and women increased from 20-29 to 60-69 y of age. Mean BMI and variances in BMI increased from the 1940s to the 2000s and were greatest in North America and Australia, followed by Europe and East Asia. However, heritability estimates were largely similar over measurement years and between regions. There was no evidence of environmental factors shared by co-twins affecting BMI.Conclusions: The heritability of BMI decreased and differences in the sets of genes affecting BMI in men and women increased from young adulthood to old age. The heritability of BMI was largely similar between cultural-geographic regions and measurement years, despite large differences in mean BMI and variances in BMI. Our results show a strong influence of genetic factors on BMI, especially in early adulthood, regardless of the obesity level in the population.
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Affiliation(s)
- Karri Silventoinen
- Departments of Social Research and .,Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Aline Jelenkovic
- Departments of Social Research and,Department of Genetics, Physical Anthropology, and Animal Physiology, University of the Basque Country, Leioa, Spain
| | - Reijo Sund
- Departments of Social Research and,Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Yoshie Yokoyama
- Department of Public Health Nursing, Osaka City University, Osaka, Japan
| | - Yoon-Mi Hur
- Department of Education, Mokpo National University, Jeonnam, South Korea
| | - Wendy Cozen
- Department of Preventive Medicine, Keck School of Medicine,,Norris Comprehensive Cancer Center, and
| | - Amie E Hwang
- Department of Preventive Medicine, Keck School of Medicine
| | - Thomas M Mack
- Department of Preventive Medicine, Keck School of Medicine,,Norris Comprehensive Cancer Center, and
| | - Chika Honda
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Fujio Inui
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan;,Faculty of Health Science, Kio University, Nara, Japan
| | - Yoshinori Iwatani
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Mikio Watanabe
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Rie Tomizawa
- Osaka University Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Programs Unit, University of Helsinki, Helsinki, Finland;,Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Aila Rissanen
- Obesity Research Unit, Research Programs Unit, University of Helsinki, Helsinki, Finland;,Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Sisira H Siribaddana
- Institute of Research and Development, Battaramulla, Sri Lanka;,Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, Sri Lanka
| | - Matthew Hotopf
- National Institute for Health Research Mental Health Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, Institute of Psychiatry Psychology and Neuroscience
| | - Athula Sumathipala
- Institute of Research and Development, Battaramulla, Sri Lanka;,Research Institute for Primary Care and Health Sciences, School for Primary Care Research, Faculty of Health, Keele University, Staffordshire, United Kingdom
| | - Fruhling Rijsdijk
- Medical Research Council Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, and
| | - Qihua Tan
- Unit of Epidemiology, Biostatistics, and Biodemography, Departments of Public Health and
| | - Dongfeng Zhang
- Department of Public Health, Qingdao University Medical College, Qingdao, China
| | - Zengchang Pang
- Department of Noncommunicable Diseases Prevention, Qingdao Centers for Disease Control and Prevention, Qingdao, China
| | - Maarit Piirtola
- Departments of Social Research and,Institute for Molecular Medicine, Helsinki, Finland
| | - Sari Aaltonen
- Departments of Social Research and,Public Health, and
| | - Sevgi Y Öncel
- Department of Statistics, Faculty of Arts and Sciences, Kırıkkale University, Kırıkkale, Turkey
| | - Fazil Aliev
- Faculty of Business, Karabuk University, Karabuk, Turkey;,Departments of Psychology and,African American Studies
| | - Esther Rebato
- Department of Genetics, Physical Anthropology, and Animal Physiology, University of the Basque Country, Leioa, Spain
| | | | - Kaare Christensen
- The Danish Twin Registry,,Departments of Clinical Biochemistry and Pharmacology and Clinical Genetics, and
| | | | - Kirsten O Kyvik
- Clinical Research, University of Southern Denmark, Odense, Denmark;,Odense Patient Data Explorative Network, Odense University Hospital, Odense, Denmark
| | - Judy L Silberg
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, and
| | - Lindon J Eaves
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, and
| | - Tessa L Cutler
- The Australian Twin Registry, Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Victoria, Australia
| | - Juan R Ordoñana
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain;,Biomedical Research Institute of Murcia (IMIB)-Arrixaca, Murcia, Spain
| | - Juan F Sánchez-Romera
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain;,Biomedical Research Institute of Murcia (IMIB)-Arrixaca, Murcia, Spain
| | - Lucia Colodro-Conde
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain;,Quantitative Genetics Laboratory and
| | - Yun-Mi Song
- Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sarah Yang
- Department of Epidemiology, School of Public Health, and,Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Kayoung Lee
- Department of Family Medicine, Busan Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, CA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, CA;,US Department of Veterans Affairs San Diego Center of Excellence for Stress and Mental Health, La Jolla, CA
| | | | | | - Tracy L Nelson
- Department of Health and Exercise Sciences, Colorado School of Public Health, Colorado State University, Aurora, CO
| | | | | | - Kerry L Jang
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada; Departments of
| | - Margaret Gatz
- Department of Psychology, University of Southern California, Los Angeles, CA;,Medical Epidemiology and Biostatistics and
| | - David A Butler
- Health and Medicine Division, National Academies of Sciences, Engineering, and Medicine, Washington, DC
| | - Maria A Stazi
- Italian National Institute of Health National Center for Epidemiology, Surveillance, and Health Promotion, Rome, Italy
| | - Corrado Fagnani
- Italian National Institute of Health National Center for Epidemiology, Surveillance, and Health Promotion, Rome, Italy
| | - Cristina D’Ippolito
- Italian National Institute of Health National Center for Epidemiology, Surveillance, and Health Promotion, Rome, Italy
| | - Glen E Duncan
- Washington State Twin Registry, Health Sciences, Washington State University, Spokane, WA
| | - Dedra Buchwald
- Washington State Twin Registry, Health Sciences, Washington State University, Spokane, WA
| | - Nicholas G Martin
- Genetic Epidemiology Department, Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, Australia
| | - Sarah E Medland
- Genetic Epidemiology Department, Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, Australia
| | - Grant W Montgomery
- Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Hoe-Uk Jeong
- Department of Education, Mokpo National University, Jeonnam, South Korea
| | - Gary E Swan
- Department of Medicine, Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA
| | - Ruth Krasnow
- Center for Health Sciences, SRI International, Menlo Park, CA
| | | | | | - Anna K Dahl Aslan
- Medical Epidemiology and Biostatistics and,Institute of Gerontology and Aging Research Network, School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Tom A McAdams
- Medical Research Council Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, and
| | - Thalia C Eley
- Medical Research Council Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, and
| | - Alice M Gregory
- Department of Psychology, Goldsmiths, University of London, London, United Kingdom
| | - Per Tynelius
- Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Laura A Baker
- Department of Psychology, University of Southern California, Los Angeles, CA
| | - Catherine Tuvblad
- Department of Psychology, University of Southern California, Los Angeles, CA;,School of Law, Psychology, and Social Work, Örebro University, Örebro, Sweden
| | | | - Danshiitsoodol Narandalai
- Healthy Twin Association of Mongolia, Ulaanbaatar, Mongolia;,Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Timothy D Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom;,National Institute for Health Research Biomedical Research Centre at Guy’s and St. Thomas’ Foundation Trust, London, United Kingdom
| | - Genevieve Lachance
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom
| | | | | | | | | | | | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN
| | - Shandell Pahlen
- Department of Psychology, University of Minnesota, Minneapolis, MN
| | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado
| | - Brooke M Huibregtse
- Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado
| | - Meike Bartels
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands
| | | | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands
| | - Jack H Goldberg
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA
| | - Finn Rasmussen
- Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Adam D Tarnoki
- Department of Radiology, Semmelweis University, Budapest, Hungary;,Hungarian Twin Registry, Budapest, Hungary
| | - David L Tarnoki
- Department of Radiology, Semmelweis University, Budapest, Hungary;,Hungarian Twin Registry, Budapest, Hungary
| | - Catherine A Derom
- Centre of Human Genetics, University Hospitals Leuven, Leuven, Belgium;,Department of Obstetrics and Gynaecology, Ghent University Hospitals, Ghent, Belgium
| | | | - Ruth JF Loos
- Charles Bronfman Institute for Personalized Medicine, Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - John L Hopper
- Department of Epidemiology, School of Public Health, and,The Australian Twin Registry, Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Victoria, Australia
| | - Joohon Sung
- Department of Epidemiology, School of Public Health, and,Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Hermine H Maes
- Departments of Human and Molecular Genetics and Psychiatry, Massey Cancer Center, Virginia Commonwealth University, Richmond, VA
| | - Eric Turkheimer
- Department of Psychology, University of Virginia, Charlottesville, VA
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands
| | - Thorkild IA Sørensen
- Section on Metabolic Genetics, Novo Nordisk Foundation Centre for Basic Metabolic Research, Copenhagen, Denmark;,Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; and,Department of Clinical Epidemiology, Bispebjerg and Frederiksberg Hospitals, Copenhagen, Denmark
| | - Jaakko Kaprio
- Public Health, and,Institute for Molecular Medicine, Helsinki, Finland
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16
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17
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Cobb LK, McAdams-DeMarco MA, Gudzune KA, Anderson CAM, Demerath E, Woodward M, Selvin E, Coresh J. Changes in Body Mass Index and Obesity Risk in Married Couples Over 25 Years: The ARIC Cohort Study. Am J Epidemiol 2016; 183:435-43. [PMID: 26405117 DOI: 10.1093/aje/kwv112] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 04/23/2015] [Indexed: 12/16/2022] Open
Abstract
Married couples might be an appropriate target for obesity prevention interventions. In the present study, we aimed to evaluate whether an individual's risk of obesity is associated with spousal risk of obesity and whether an individual's change in body mass index (BMI; weight in kilograms divided by height in meters squared) is associated with spousal BMI change. We analyzed data from 3,889 spouse pairs in the Atherosclerosis Risk in Communities Study cohort who were sampled at ages 45-65 years from 1986 to 1989 and followed for up to 25 years. We estimated hazard ratios for incident obesity by whether spouses remained nonobese, became obese, remained obese, or became nonobese. We estimated the association of participants' BMI changes with concurrent spousal BMI changes using linear mixed models. Analyses were stratified by sex. At baseline, 22.6% of men and 24.7% of women were obese. Nonobese participants whose spouses became obese were more likely to become obese themselves (for men, hazard ratio = 1.78, 95% confidence interval: 1.30, 2.43; for women, hazard ratio = 1.89, 95% confidence interval: 1.39, 2.57). With each 1-unit increase in spousal BMI change, women's BMI change increased by 0.15 (95% confidence interval: 0.13, 0.18) and men's BMI change increased by 0.10 (95% confidence interval: 0.09, 0.12). Having a spouse become obese nearly doubles one's risk of becoming obese. Future research should consider exploring the efficacy of obesity prevention interventions in couples.
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18
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Ajslev TA, Ängquist L, Silventoinen K, Baker JL, Sørensen TIA. Stable intergenerational associations of childhood overweight during the development of the obesity epidemic. Obesity (Silver Spring) 2015; 23:1279-87. [PMID: 25959297 DOI: 10.1002/oby.21060] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2014] [Accepted: 01/25/2015] [Indexed: 12/22/2022]
Abstract
OBJECTIVE The obesity epidemic may have developed as a response to the obesogenic environment among the genetically predisposed. This investigation examined whether the intergenerational resemblances in childhood overweight changed across the development of the obesity epidemic in groups of children born to parents with and without childhood overweight. METHODS The study population was from the Copenhagen School Health Records Register, which includes age- and sex-specific body mass index (BMI; kg/m(2) ) of children. This study used BMI values from 7-year-old children born 1952-1989 and from their parents at ages 7 and 13 years. The available number of parent-child pairs ranged from 17,926 through 42,184. The odds ratios of childhood overweight (BMI z-score >90th percentile) were calculated using logistic regression by parental BMI groups (BMI > or ≤90th percentile) and child birth year intervals. RESULTS Stable levels in parent-child overweight associations were observed across child BMI groups born to parents with and without childhood overweight. A slight upward odds ratio trend was observed across time in children born to two overweight parents at age 13, but not at age 7 years. CONCLUSIONS Parent-child resemblance in childhood overweight showed small changes during the development of the obesity epidemic, suggesting that the obesogenic environment inducing the epidemic in Denmark influenced children irrespective of their familial predisposition.
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Affiliation(s)
- Teresa A Ajslev
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg University Hospital, The Capital Region, Copenhagen, Denmark
| | - Lars Ängquist
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg University Hospital, The Capital Region, Copenhagen, Denmark
| | - Karri Silventoinen
- Population Research Unit, Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Jennifer L Baker
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg University Hospital, The Capital Region, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Thorkild I A Sørensen
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg University Hospital, The Capital Region, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
- MRC Integrative Epidemiology Unit, Bristol University, Bristol, UK
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How Has the Age-Related Process of Overweight or Obesity Development Changed over Time? Co-ordinated Analyses of Individual Participant Data from Five United Kingdom Birth Cohorts. PLoS Med 2015; 12:e1001828; discussion e1001828. [PMID: 25993005 PMCID: PMC4437909 DOI: 10.1371/journal.pmed.1001828] [Citation(s) in RCA: 129] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2014] [Accepted: 04/10/2015] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND There is a paucity of information on secular trends in the age-related process by which people develop overweight or obesity. Utilizing longitudinal data in the United Kingdom birth cohort studies, we investigated shifts over the past nearly 70 years in the distribution of body mass index (BMI) and development of overweight or obesity across childhood and adulthood. METHODS AND FINDINGS The sample comprised 56,632 participants with 273,843 BMI observations in the 1946 Medical Research Council National Survey of Health and Development (NSHD; ages 2-64 years), 1958 National Child Development Study (NCDS; 7-50), 1970 British Cohort Study (BCS; 10-42), 1991 Avon Longitudinal Study of Parents and Children (ALSPAC; 7-18), or 2001 Millennium Cohort Study (MCS; 3-11). Growth references showed a secular trend toward positive skewing of the BMI distribution at younger ages. During childhood, the 50th centiles for all studies lay in the middle of the International Obesity Task Force normal weight range, but during adulthood, the age when a 50th centile first entered the overweight range (i.e., 25-29.9 kg/m2) decreased across NSHD, NCDS, and BCS from 41 to 33 to 30 years in males and 48 to 44 to 41 years in females. Trajectories of overweight or obesity showed that more recently born cohorts developed greater probabilities of overweight or obesity at younger ages. Overweight or obesity became more probable in NCDS than NSHD in early adulthood, but more probable in BCS than NCDS and NSHD in adolescence, for example. By age 10 years, the estimated probabilities of overweight or obesity in cohorts born after the 1980s were 2-3 times greater than those born before the 1980s (e.g., 0.229 [95% CI 0.219-0.240] in MCS males; 0.071 [0.065-0.078] in NSHD males). It was not possible to (1) model separate trajectories for overweight and obesity, because there were few obesity cases at young ages in the earliest-born cohorts, or (2) consider ethnic minority groups. The end date for analyses was August 2014. CONCLUSIONS Our results demonstrate how younger generations are likely to accumulate greater exposure to overweight or obesity throughout their lives and, thus, increased risk for chronic health conditions such as coronary heart disease and type 2 diabetes mellitus. In the absence of effective intervention, overweight and obesity will have severe public health consequences in decades to come.
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20
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Casazza K, Brown A, Astrup A, Bertz F, Baum C, Brown MB, Dawson J, Durant N, Dutton G, Fields DA, Fontaine KR, Heymsfield S, Levitsky D, Mehta T, Menachemi N, Newby PK, Pate R, Raynor H, Rolls BJ, Sen B, Smith DL, Thomas D, Wansink B, Allison DB. Weighing the Evidence of Common Beliefs in Obesity Research. Crit Rev Food Sci Nutr 2015; 55:2014-53. [PMID: 24950157 PMCID: PMC4272668 DOI: 10.1080/10408398.2014.922044] [Citation(s) in RCA: 73] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Obesity is a topic on which many views are strongly held in the absence of scientific evidence to support those views, and some views are strongly held despite evidence to contradict those views. We refer to the former as "presumptions" and the latter as "myths." Here, we present nine myths and 10 presumptions surrounding the effects of rapid weight loss; setting realistic goals in weight loss therapy; stage of change or readiness to lose weight; physical education classes; breastfeeding; daily self-weighing; genetic contribution to obesity; the "Freshman 15"; food deserts; regularly eating (versus skipping) breakfast; eating close to bedtime; eating more fruits and vegetables; weight cycling (i.e., yo-yo dieting); snacking; built environment; reducing screen time in childhood obesity; portion size; participation in family mealtime; and drinking water as a means of weight loss. For each of these, we describe the belief and present evidence that the belief is widely held or stated, reasons to support the conjecture that the belief might be true, evidence to directly support or refute the belief, and findings from randomized controlled trials, if available. We conclude with a discussion of the implications of these determinations, conjecture on why so many myths and presumptions exist, and suggestions for limiting the spread of these and other unsubstantiated beliefs about the obesity domain.
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Affiliation(s)
- Krista Casazza
- a Department of Nutrition Sciences , University of Alabama at Birmingham , Birmingham , Alabama USA
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21
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Ajslev TA, Ängquist L, Silventoinen K, Baker JL, Sørensen TIA. Trends in parent-child correlations of childhood body mass index during the development of the obesity epidemic. PLoS One 2014; 9:e109932. [PMID: 25329656 PMCID: PMC4201474 DOI: 10.1371/journal.pone.0109932] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Accepted: 09/12/2014] [Indexed: 01/19/2023] Open
Abstract
Background The intergenerational resemblance in body mass index may have increased during the development of the obesity epidemic due to changes in environment and/or expression of genetic predisposition. Objectives This study investigates trends in intergenerational correlations of childhood body mass index (BMI; kg/m2) during the emergence of the obesity epidemic. Methods The study population was derived from the Copenhagen School Health Records Register, which includes height and weight measurements since birth year 1930. Mothers and fathers with BMIs available at ages 7 (n = 25,923 and n = 20,972) or 13 years (n = 26,750 and n = 21,397), respectively, were linked through the civil registration system introduced in 1968 to their children with BMIs available at age 7 years. Age- and sex-specific BMI z-scores were calculated. Correlations were estimated across eight intervals of child birth years (1952–1989) separately by sex. Trends in these correlations were examined. Whereas the mother-child correlations reflected the biological relationship, a likely decline in the assignment of non-biological fathers through the registration system across time must be considered when interpreting the father-child correlations. Results The BMI correlations between mothers and sons ranged from 0.29–0.36 and they decreased marginally, albeit significantly across time at ages 7–7 years (−0.002/year, p = 0.006), whereas those at 13–7 years remained stable (<0.0004/year, p = 0.96). Mother-daughter correlations ranged from 0.30–0.34, and they were stable at ages 7–7 years (0.0001/year, p = 0.84) and at 13–7 years (0.0004/year, p = 0.56). In contrast, father-son correlations increased significantly during this period, both at ages 7–7 (0.002/year, p = 0.007) and at ages 13–7 years (0.003/year, p<0.001), whereas the increase in father-daughter correlations were insignificant both at ages 7–7 (0.001/year, p = 0.37) and at ages 13–7 years (0.001/year, p = 0.18). Conclusion During the obesity epidemics development, the intergenerational resemblance with mothers remained stable, whereas the father-child BMI resemblance increased, possibly reflecting changes in family relationships, and unlikely to have influenced the epidemic.
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Affiliation(s)
- Teresa A. Ajslev
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg Hospital, Frederiksberg, Denmark
- * E-mail:
| | - Lars Ängquist
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg Hospital, Frederiksberg, Denmark
| | - Karri Silventoinen
- Population Research Unit, Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Jennifer L. Baker
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg Hospital, Frederiksberg, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences University of Copenhagen, Copenhagen, Denmark
| | - Thorkild I. A. Sørensen
- Institute of Preventive Medicine, Frederiksberg and Bispebjerg Hospital, Frederiksberg, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences University of Copenhagen, Copenhagen, Denmark
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Danchin E, Pocheville A. Inheritance is where physiology meets evolution. J Physiol 2014; 592:2307-17. [PMID: 24882815 PMCID: PMC4048090 DOI: 10.1113/jphysiol.2014.272096] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2014] [Accepted: 04/08/2014] [Indexed: 01/05/2023] Open
Abstract
Physiology and evolutionary biology have developed as two separated disciplines, a separation that mirrored the hypothesis that the physiological and evolutionary processes could be decoupled. We argue that non-genetic inheritance shatters the frontier between physiology and evolution, and leads to the coupling of physiological and evolutionary processes to a point where there exists a continuum between accommodation by phenotypic plasticity and adaptation by natural selection. This approach is also profoundly affecting the definition of the concept of phenotypic plasticity, which should now be envisaged as a multi-scale concept. We further suggest that inclusive inheritance provides a quantitative way to help bridging infra-individual (i.e. physiology) with supra-individual (i.e. evolution) approaches, in a way that should help building the long sough inclusive evolutionary synthesis.
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Affiliation(s)
- Etienne Danchin
- CNRS, UPS, ENFA; EDB (Laboratoire Evolution & Diversité Biologique), UMR5174, 118 route de Narbonne, F-31062, Toulouse, France Université de Toulouse, UMR5174, F-31062, Toulouse, France
| | - Arnaud Pocheville
- Center for Philosophy of Science, University of Pittsburgh, 817 Cathedral of Learning, Pittsburgh, PA, 15260, USA
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Platte P, Vögele C, Meule A. Adipositas im Kindes- und Jugendalter: Risikofaktoren, Prävention und Behandlung. VERHALTENSTHERAPIE 2014. [DOI: 10.1159/000363397] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Min J, Chiu DT, Wang Y. Variation in the heritability of body mass index based on diverse twin studies: a systematic review. Obes Rev 2013; 14:871-82. [PMID: 23980914 PMCID: PMC4346225 DOI: 10.1111/obr.12065] [Citation(s) in RCA: 93] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2013] [Revised: 06/27/2013] [Accepted: 07/15/2013] [Indexed: 12/22/2022]
Abstract
OBJECTIVES Over the past three decades, twin studies have shown variation in the heritability of obesity. This study examined the difference of body mass index (BMI) heritability (BMI-H) by population characteristics, such as sex, age, time period of observation and average BMI, as well as by broad social-environmental factors as indicated by country-level gross domestic product (GDP) per capita and GDP growth rate. METHODS Twin studies that reported BMI-H and were published in English from January 1990 to February 2011 after excluding those with disease, special occupations or combined heritability estimates for country/ethnic groups were searched in PubMed. 32 studies were identified from Finland (7), the United Kingdom (6), the United States (3), Denmark (3), China (3), Netherlands (2), South Korea (2), Sweden (2) and four from other countries. Meta-regression models with random effects were used to assess variation in BMI-H. RESULTS Heterogeneity of BMI-H is significantly attributable to variations in age (<20, 20-55 and ≥56 years), time period of observation (i.e. year of data collection), average BMI and GDP (≤$20,000, $20,001-26,000 and >$26,000). BMI-H was higher in adolescents (<20 years), in studies done in past years, and in populations with higher average BMIs or higher GDP per capita (≥$26,000) than their counterparts. Consistent lowering effects of high GDP growth rate (>median) on BMI-H were shown through stratified analyses by GDP. BMI-H was lower in countries of mid-level GDP, particularly those experiencing rapid economic growth. CONCLUSIONS BMI-H is sensitive to age, time period of observation, average BMI, GDP and rapid economic growth.
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Affiliation(s)
- J Min
- Johns Hopkins Global Center on Childhood Obesity, Department of International Health Human Nutrition Program, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA; Department of Preventive Medicine, School of Medicine, Ewha Womans University, Seoul, Korea
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Dawson JA, Dhurandhar EJ, Vazquez AI, Peng B, Allison DB. Propagation of obesity across generations: the roles of differential realized fertility and assortative mating by body mass index. Hum Hered 2013; 75:204-12. [PMID: 24081235 DOI: 10.1159/000352007] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND/AIMS To quantify the extent to which the increase in obesity observed across recent generations of the American population is associated with the individual or combined effects of assortative mating (AM) for body mass index (BMI) and differential realized fertility by BMI. METHODS A Monte Carlo framework is formed and informed using data collected from the National Longitudinal Survey of Youth (NLSY). The model has 2 portions: one that generates childbirth events on an annual basis and another that produces a BMI for each child. Once the model is informed using the data, a reference distribution of offspring BMIs is simulated. We quantify the effects of our factors of interest by removing them from the model and comparing the resulting offspring BMI distributions with that of the baseline scenario. RESULTS An association between maternal BMI and number of offspring is evidenced in the NLSY data as well as the presence of AM. These 2 factors combined are associated with an increased mean BMI (+0.067, 95% CI: 0.056; 0.078), an increased BMI variance (+0.578, 95% CI: 0.418; 0.736) and an increased prevalence of obesity (RR 1.032, 95% CI: 1.023; 1.041) and BMIs >40 (RR 1.083, 95% CI: 1.053; 1.118) among offspring. CONCLUSION Our investigation suggests that both differential realized fertility and AM by BMI appear to play a role in the increasing prevalence of obesity in America.
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Affiliation(s)
- John A Dawson
- Office of Energetics, School of Public Health, University of Alabama at Birmingham, Birmingham, Ala., USA
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