scholarly journals Body Mass Index and Healthcare Costs: Using Genetic Variants from the HUNT Study as Instrumental Variables

2021 ◽  
Author(s):  
Christina Hansen Edwards ◽  
Gunnhild Åberge Vie ◽  
Christina Hansen Edwards
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Genetic Variants ◽  
Healthcare Costs ◽  
Sociodemographic Factors ◽  
Ordinary Least Squares ◽  
Effect Estimate ◽  
Omitted Variables ◽  
Reverse Causality ◽  
Individual Level

Abstract Background: Past studies have found associations between obesity and healthcare costs, however, these studies have suffered from bias due to omitted variables, reverse causality, and omitted variables. Methods: We used genetic variants related to body mass index (BMI) as instruments for BMI; thereby exploiting the natural randomization of genetic variants that occurs at conception. We used data on measured height and weight, genetic information, and sociodemographic factors from the Nord-Trøndelag Health Studies (HUNT), and individual-level registry data on healthcare costs, educational level, registration status, and biological relatives. We studied associations between BMI and general practitioner (GP)-, specialist-, and total healthcare costs in the Norwegian setting using instrumental variable (IV) regressions, and compared our findings with effect estimates from ordinary least squares (OLS) regressions. The sensitivity of our findings to underlying IV-assumptions was explored using two-sample Mendelian randomization methods, non-linear analyses, sex-, healthcare provider-, and age-specific analyses, within-family analyses, and outlier removal. We also conducted power calculations to assess the likelihood of detecting an effect given our sample 60 786 individuals.Results: We found that increased BMI resulted in significantly higher GP costs; however, the IV-based effect estimate was smaller than the OLS-based estimate. We found no evidence of an association between BMI and specialist or total healthcare costs. Conclusions: The effect of obesity on GP- and specialist costs may have been overestimated in previous studies.

scholarly journals Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index

2016 ◽  
Vol 14 (4) ◽  
pp. 149 ◽  
Author(s):  
Sunghwan Bae ◽  
Sungkyoung Choi ◽  
Sung Min Kim ◽  
Taesung Park
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Genetic Variants ◽  
Quantitative Traits ◽  
Common Genetic Variants

Morbid obesity in the UK: A modelling projection study to 2035

2018 ◽  
Vol 48 (4) ◽  
pp. 422-427 ◽  
Author(s):  
Laura Keaver ◽  
Benshuai Xu ◽  
Abbygail Jaccard ◽  
Laura Webber
Keyword(s):  
Body Mass Index ◽  
Morbid Obesity ◽  
Body Mass ◽  
Communicable Disease ◽  
Age Groups ◽  
Morbidly Obese ◽  
Healthy Weight ◽  
Individual Level ◽  
Annual Distribution ◽  
The Uk

Background: Morbid obesity (body mass index ⩾40 kg/m2) carries a higher risk of non-communicable disease and is associated with more complex health issues and challenges than obesity body mass index ≥30kg/m2 and <40kg/m2, resulting in much higher financial implications for health systems. Although obesity trends have previously been projected to 2035, these projections do not separate morbid obesity from obesity. This study therefore complements these projections and looks at the prevalence and development of morbid obesity in the UK. Methods: Individual level body mass index data for people aged >15 years in England, Wales (2004–2014) and Scotland (2008–2014) were collated from national surveys and stratified by sex and five-year age groups (e.g. 15–19 years), then aggregated to calculate the annual distribution of healthy weight, overweight, obesity and morbid obesity for each age and sex group. A categorical multi-variate non-linear regression model was fitted to these distributions to project trends to 2035. Results: The prevalence of morbid obesity was predicted to increase to 5, 8 and 11% in Scotland, England and Wales, respectively, by 2035. Welsh women aged 55–64 years had the highest projected prevalence of 20%. In total, almost five million people are forecast to be classified as morbidly obese across the three countries in 2035. Conclusions: The prevalence of morbid obesity is predicted to increase by 2035 across the three UK countries, with Wales projected to have the highest rates. This is likely to have serious health and financial implications for society and the UK health system.

scholarly journals Application of Mendelian Randomization to Investigate the Association of Body Mass Index with Health Care Costs

2020 ◽  
Vol 40 (2) ◽  
pp. 156-169 ◽  
Author(s):  
Christoph F. Kurz ◽  
Michael Laxy
Keyword(s):  
Health Care ◽  
Body Mass Index ◽  
Body Mass ◽  
Health Care Costs ◽  
Instrumental Variables ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Omitted Variables ◽  
Care Costs ◽  
Genetic Instruments

Causal effect estimates for the association of obesity with health care costs can be biased by reversed causation and omitted variables. In this study, we use genetic variants as instrumental variables to overcome these limitations, a method that is often called Mendelian randomization (MR). We describe the assumptions, available methods, and potential pitfalls of using genetic information and how to address them. We estimate the effect of body mass index (BMI) on total health care costs using data from a German observational study and from published large-scale data. In a meta-analysis of several MR approaches, we find that models using genetic instruments identify additional annual costs of €280 for a 1-unit increase in BMI. This is more than 3 times higher than estimates from linear regression without instrumental variables (€75). We found little evidence of a nonlinear relationship between BMI and health care costs. Our results suggest that the use of genetic instruments can be a powerful tool for estimating causal effects in health economic evaluation that might be superior to other types of instruments where there is a strong association with a modifiable risk factor.

scholarly journals Associations of genetic variants in/near body mass index-associated genes with type 2 diabetes: a systematic meta-analysis

2014 ◽  
Vol 81 (5) ◽  
pp. 702-710 ◽  
Author(s):  
Bo Xi ◽  
Fumihiko Takeuchi ◽  
Aline Meirhaeghe ◽  
Norihiro Kato ◽  
John C. Chambers ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Body Mass Index ◽  
Body Mass ◽  
Genetic Variants ◽  
Meta Analysis

scholarly journals Polygenic Score for Body Mass Index Is Associated with Disordered Eating in a General Population Cohort

2020 ◽  
Vol 9 (4) ◽  
pp. 1187 ◽  
Author(s):  
Mohamed Abdulkadir ◽  
Moritz Herle ◽  
Bianca L. De Stavola ◽  
Christopher Hübel ◽  
Diana L. Santos Ferreira ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Binge Eating ◽  
Body Dissatisfaction ◽  
Disordered Eating ◽  
Body Mass ◽  
Genetic Variants ◽  
Emotional Eating ◽  
Mediation Analyses ◽  
Parents And Children ◽  
Polygenic Scores

Background: Disordered eating (DE) is common and is associated with body mass index (BMI). We investigated whether genetic variants for BMI were associated with DE. Methods: BMI polygenic scores (PGS) were calculated for participants of the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 8654) and their association with DE tested. Data on DE behaviors (e.g., binge eating and compensatory behaviors) were collected at ages 14, 16, 18 years, and DE cognitions (e.g., body dissatisfaction) at 14 years. Mediation analyses determined whether BMI mediated the association between the BMI-PGS and DE. Results: The BMI-PGS was positively associated with fasting (OR = 1.42, 95% CI = 1.25, 1.61), binge eating (OR = 1.28, 95% CI = 1.12, 1.46), purging (OR = 1.20, 95% CI = 1.02, 1.42), body dissatisfaction (Beta = 0.99, 95% CI = 0.77, 1.22), restrained eating (Beta = 0.14, 95% CI = 0.10, 1.17), emotional eating (Beta = 0.21, 95% CI = 0.052, 0.38), and negatively associated with thin ideal internalization (Beta = −0.15, 95% CI = −0.23, −0.07) and external eating (Beta = −0.19, 95% CI = −0.30, −0.09). These associations were mainly mediated by BMI. Conclusions: Genetic variants associated with BMI are also associated with DE. This association was mediated through BMI suggesting that weight potentially sits on the pathway from genetic liability to DE.

scholarly journals Associations between body mass index-related genetic variants and adult body composition: The Fenland cohort study

2017 ◽  
Vol 41 (4) ◽  
pp. 613-619 ◽  
Author(s):  
E A D Clifton ◽  
F R Day ◽  
E De Lucia Rolfe ◽  
N G Forouhi ◽  
S Brage ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Cohort Study ◽  
Body Mass ◽  
Genetic Variants ◽  
Adult Body

scholarly journals Influence of genetic variants associated with body mass index on eating behavior in childhood

Obesity ◽  
2017 ◽  
Vol 25 (4) ◽  
pp. 765-772 ◽  
Author(s):  
Claire Monnereau ◽  
Pauline W. Jansen ◽  
Henning Tiemeier ◽  
Vincent W.V. Jaddoe ◽  
Janine F. Felix
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Eating Behavior ◽  
Genetic Variants

scholarly journals Rare and Common Genetic Variants, Smoking and Higher Body Mass Index Are Associated with Earlier Age of Progression to Geographic Atrophy and Neovascular Advanced Stages of Macular Degeneration in a Prospective Analysis

2020 ◽  
Author(s):  
Johanna Seddon ◽  
Rafael Widjajahakim ◽  
Bernard Rosner
Keyword(s):  
Body Mass Index ◽  
Macular Degeneration ◽  
Body Mass ◽  
Genetic Variants ◽  
Geographic Atrophy ◽  
Smoking History ◽  
Behavioral Factors ◽  
Severity Scale ◽  
Age Related ◽  
The Impact

IMPORTANCE Genes and lifestyle factors influence progression to advanced age-related macular degeneration (AAMD). However, the impact of genetic and behavioral factors on age when this transition occurs has not been evaluated prospectively. OBJECTIVE To determine whether genetic and environmental factors are associated with age of progression to AAMD and to quantify the effect on age. DESIGN, SETTING, AND PARTICIPANTS Longitudinal progression to AAMD was based on the severity scale in the Age-Related Eye Disease Study database. Progression was defined as an eye that transitioned from non-advanced dry AMD without any evidence of geographic atrophy (GA) (levels 1-8) to any GA or evidence of neovascularization (NV) or both (levels ≥9) during 13 years follow up. Genotypes were determined from DNA samples. MAIN OUTCOME AND MEASURES A stepwise selection of genetic variants with the eye as the unit of analysis, using age as the time scale, yielded 11 genetic variants associated with overall progression, adjusting for sex, education, smoking history, BMI, baseline severity scale, and AREDS treatment. Multivariate analysis was also performed to calculate the effect of genetic and behavioral factors on age of progression. RESULTS Among 5421 eyes, 1206 progressed. Genetic variants associated with progression to AAMD were in the complement, immune, inflammatory, lipid, extracellular matrix, DNA repair and protein binding pathways. Three of these variants were significantly associated with earlier age of progression, adjusting for other covariates: CFH R1210C (P=0.019) with 4.7 years earlier age at progression among carriers of this mutation, C3 K155Q (P=0.011) with 2.44 years earlier for carriers, and ARMS2/HTRA1 A69S (P=0.012) with 0.67 years earlier per allele. Subjects who were smokers (P<.001) or had high BMI (P=0.006) also had an earlier age at progression (4.1 years and 1.4 years, respectively). CONCLUSIONS Carriers of rare variants in the complement pathway and a common risk allele in ARMS2/HTRA1 develop advanced AMD at an earlier age, and unhealthy behaviors including smoking and higher body mass index lead to earlier age of progression to AAMD.

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