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Estimating the Effects of Obesity and Weight Change on Mortality Using a Dynamic Causal Model

BACKGROUND: A well-known challenge in estimating the mortality risks of obesity is reverse causality attributable to illness-associated and smoking-associated weight loss. Given that the likelihood of chronic and acute illnesses rises with age, reverse causality is most threatening to estimates deri...

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Autor principal: Cao, Bochen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481504/
https://www.ncbi.nlm.nih.gov/pubmed/26110432
http://dx.doi.org/10.1371/journal.pone.0129946
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author Cao, Bochen
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description BACKGROUND: A well-known challenge in estimating the mortality risks of obesity is reverse causality attributable to illness-associated and smoking-associated weight loss. Given that the likelihood of chronic and acute illnesses rises with age, reverse causality is most threatening to estimates derived from elderly populations. METHODS: I analyzed data from 12,523 respondents over 50 years old from a nationally representative longitudinal dataset, the Health and Retirement Study (HRS). The effects of both baseline body weight and time-varying weight change on mortality are estimated, adjusting for demographic and socio-economic variables, as well as time-varying confounders including illness and smoking. Body weight is measured by body mass index (BMI). In survival models for mortality, illness and smoking were lagged to minimize bias from reverse causality in estimates of the effect of weight change. Furthermore, because illness both causes and is caused by changes in BMI, I used a marginal structural model (MSM) rather than standard adjustment to control confounding by this and other time-dependent factors. RESULTS: Overall, relative to normal weight, underweight and Class II/III at baseline are associated with hazard ratios that are 2.07 (95% confidence interval (CI): 1.28–3.37) and 1.82 (1.54–2.16) respectively, whereas overweight and Class I obesity do not significantly lower or raise the mortality risks. Furthermore, relative to stable weight change, all types of weight change lead to significantly increased risk of mortality. Specifically, large weight loss results in a mortality risk that is nearly 3.86 (3.26–4.58) times of staying in the stable weight range and small weight loss is about 1.81 (1.55–2.11 ) times riskier. In contrast, large weight gain and small weight gain are associated with hazard ratios that are 1.98 (1.67–2.35) and 1.20 (1.02–1.41) respectively. CONCLUSIONS: Being underweight or severe obese at baseline is associated with excess mortality risk, and weight change tend to raise mortality risk. Both the confounding by illness and by smoking lead to overestimates of the effects of being underweight at baseline and of weight loss, but underestimates the effect of being obese at baseline.
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spelling pubmed-44815042015-07-01 Estimating the Effects of Obesity and Weight Change on Mortality Using a Dynamic Causal Model Cao, Bochen PLoS One Research Article BACKGROUND: A well-known challenge in estimating the mortality risks of obesity is reverse causality attributable to illness-associated and smoking-associated weight loss. Given that the likelihood of chronic and acute illnesses rises with age, reverse causality is most threatening to estimates derived from elderly populations. METHODS: I analyzed data from 12,523 respondents over 50 years old from a nationally representative longitudinal dataset, the Health and Retirement Study (HRS). The effects of both baseline body weight and time-varying weight change on mortality are estimated, adjusting for demographic and socio-economic variables, as well as time-varying confounders including illness and smoking. Body weight is measured by body mass index (BMI). In survival models for mortality, illness and smoking were lagged to minimize bias from reverse causality in estimates of the effect of weight change. Furthermore, because illness both causes and is caused by changes in BMI, I used a marginal structural model (MSM) rather than standard adjustment to control confounding by this and other time-dependent factors. RESULTS: Overall, relative to normal weight, underweight and Class II/III at baseline are associated with hazard ratios that are 2.07 (95% confidence interval (CI): 1.28–3.37) and 1.82 (1.54–2.16) respectively, whereas overweight and Class I obesity do not significantly lower or raise the mortality risks. Furthermore, relative to stable weight change, all types of weight change lead to significantly increased risk of mortality. Specifically, large weight loss results in a mortality risk that is nearly 3.86 (3.26–4.58) times of staying in the stable weight range and small weight loss is about 1.81 (1.55–2.11 ) times riskier. In contrast, large weight gain and small weight gain are associated with hazard ratios that are 1.98 (1.67–2.35) and 1.20 (1.02–1.41) respectively. CONCLUSIONS: Being underweight or severe obese at baseline is associated with excess mortality risk, and weight change tend to raise mortality risk. Both the confounding by illness and by smoking lead to overestimates of the effects of being underweight at baseline and of weight loss, but underestimates the effect of being obese at baseline. Public Library of Science 2015-06-25 /pmc/articles/PMC4481504/ /pubmed/26110432 http://dx.doi.org/10.1371/journal.pone.0129946 Text en © 2015 Bochen Cao http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Cao, Bochen
Estimating the Effects of Obesity and Weight Change on Mortality Using a Dynamic Causal Model
title Estimating the Effects of Obesity and Weight Change on Mortality Using a Dynamic Causal Model
title_full Estimating the Effects of Obesity and Weight Change on Mortality Using a Dynamic Causal Model
title_fullStr Estimating the Effects of Obesity and Weight Change on Mortality Using a Dynamic Causal Model
title_full_unstemmed Estimating the Effects of Obesity and Weight Change on Mortality Using a Dynamic Causal Model
title_short Estimating the Effects of Obesity and Weight Change on Mortality Using a Dynamic Causal Model
title_sort estimating the effects of obesity and weight change on mortality using a dynamic causal model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481504/
https://www.ncbi.nlm.nih.gov/pubmed/26110432
http://dx.doi.org/10.1371/journal.pone.0129946
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