Exploration of Confounding Due to Poor Health in an Accelerometer-Mortality Study

Confounding due to poor health is a concern in accelerometer-based studies of physical activity and health, but detailed investigations of this source of bias are lacking. US adults (n = 4840) from the National Health and Nutrition Examination Survey (2003 to 2006) wore an accelerometer for 1 to 7 d...

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Vydané v:Medicine and science in sports and exercise Ročník 52; číslo 12; s. 2546
Hlavní autori: Matthews, Charles E, Troiano, Richard P, Salerno, Elizabeth A, Berrigan, David, Patel, Shreya B, Shiroma, Eric J, Saint-Maurice, Pedro F
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 01.12.2020
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Abstract Confounding due to poor health is a concern in accelerometer-based studies of physical activity and health, but detailed investigations of this source of bias are lacking. US adults (n = 4840) from the National Health and Nutrition Examination Survey (2003 to 2006) wore an accelerometer for 1 to 7 d (mean = 5.7 d) and were followed for mortality through 2015. Logistic regression was used to examine odds ratios between poor health (chronic conditions, self-reported health, mobility limitations, frailty) and low physical activity levels; Cox models were used to estimate adjusted hazard ratios (HR) and 95% CI for mortality associations for a 1 h·d increase in moderate-to-vigorous-intensity physical activity (MVPA) using two commonly used cut-points (MVPA760, MVPA2020). Modeling scenarios with shorter and longer follow-up time, increasing adjustment for poor health, by age group, and after excluding early years of follow-up were used to assess bias. Over a mean of 10.1 yr of follow-up, 1165 deaths occurred. Poor health was associated with low MVPA760 levels and increased mortality risk. In fully adjusted MVPA760 models, HR was 26% stronger comparing 0 to 4 yr (HR = 0.46) with 0 to 12 yr of follow-up (HR = 0.62), particularly in older adults (65 yr and older). Increasing statistical adjustment for poor health attenuated MVPA760 associations by 13% to 15%, and exclusion of the first 2 yr of follow-up had limited effects. Comparable results were obtained with the MVPA2020 cut-point. We did not find evidence that confounding by health status resulted in entirely spurious MVPA-mortality associations; however, potential bias was appreciable in modeling scenarios involving shorter follow-up (<6 yr), older adults, and more limited statistical adjustment for poor health. The strength of MVPA-mortality associations in studies reflecting these scenarios should be interpreted cautiously.
AbstractList Confounding due to poor health is a concern in accelerometer-based studies of physical activity and health, but detailed investigations of this source of bias are lacking.PURPOSEConfounding due to poor health is a concern in accelerometer-based studies of physical activity and health, but detailed investigations of this source of bias are lacking.US adults (n = 4840) from the National Health and Nutrition Examination Survey (2003 to 2006) wore an accelerometer for 1 to 7 d (mean = 5.7 d) and were followed for mortality through 2015. Logistic regression was used to examine odds ratios between poor health (chronic conditions, self-reported health, mobility limitations, frailty) and low physical activity levels; Cox models were used to estimate adjusted hazard ratios (HR) and 95% CI for mortality associations for a 1 h·d increase in moderate-to-vigorous-intensity physical activity (MVPA) using two commonly used cut-points (MVPA760, MVPA2020). Modeling scenarios with shorter and longer follow-up time, increasing adjustment for poor health, by age group, and after excluding early years of follow-up were used to assess bias.METHODSUS adults (n = 4840) from the National Health and Nutrition Examination Survey (2003 to 2006) wore an accelerometer for 1 to 7 d (mean = 5.7 d) and were followed for mortality through 2015. Logistic regression was used to examine odds ratios between poor health (chronic conditions, self-reported health, mobility limitations, frailty) and low physical activity levels; Cox models were used to estimate adjusted hazard ratios (HR) and 95% CI for mortality associations for a 1 h·d increase in moderate-to-vigorous-intensity physical activity (MVPA) using two commonly used cut-points (MVPA760, MVPA2020). Modeling scenarios with shorter and longer follow-up time, increasing adjustment for poor health, by age group, and after excluding early years of follow-up were used to assess bias.Over a mean of 10.1 yr of follow-up, 1165 deaths occurred. Poor health was associated with low MVPA760 levels and increased mortality risk. In fully adjusted MVPA760 models, HR was 26% stronger comparing 0 to 4 yr (HR = 0.46) with 0 to 12 yr of follow-up (HR = 0.62), particularly in older adults (65 yr and older). Increasing statistical adjustment for poor health attenuated MVPA760 associations by 13% to 15%, and exclusion of the first 2 yr of follow-up had limited effects. Comparable results were obtained with the MVPA2020 cut-point.RESULTSOver a mean of 10.1 yr of follow-up, 1165 deaths occurred. Poor health was associated with low MVPA760 levels and increased mortality risk. In fully adjusted MVPA760 models, HR was 26% stronger comparing 0 to 4 yr (HR = 0.46) with 0 to 12 yr of follow-up (HR = 0.62), particularly in older adults (65 yr and older). Increasing statistical adjustment for poor health attenuated MVPA760 associations by 13% to 15%, and exclusion of the first 2 yr of follow-up had limited effects. Comparable results were obtained with the MVPA2020 cut-point.We did not find evidence that confounding by health status resulted in entirely spurious MVPA-mortality associations; however, potential bias was appreciable in modeling scenarios involving shorter follow-up (<6 yr), older adults, and more limited statistical adjustment for poor health. The strength of MVPA-mortality associations in studies reflecting these scenarios should be interpreted cautiously.CONCLUSIONSWe did not find evidence that confounding by health status resulted in entirely spurious MVPA-mortality associations; however, potential bias was appreciable in modeling scenarios involving shorter follow-up (<6 yr), older adults, and more limited statistical adjustment for poor health. The strength of MVPA-mortality associations in studies reflecting these scenarios should be interpreted cautiously.
Confounding due to poor health is a concern in accelerometer-based studies of physical activity and health, but detailed investigations of this source of bias are lacking. US adults (n = 4840) from the National Health and Nutrition Examination Survey (2003 to 2006) wore an accelerometer for 1 to 7 d (mean = 5.7 d) and were followed for mortality through 2015. Logistic regression was used to examine odds ratios between poor health (chronic conditions, self-reported health, mobility limitations, frailty) and low physical activity levels; Cox models were used to estimate adjusted hazard ratios (HR) and 95% CI for mortality associations for a 1 h·d increase in moderate-to-vigorous-intensity physical activity (MVPA) using two commonly used cut-points (MVPA760, MVPA2020). Modeling scenarios with shorter and longer follow-up time, increasing adjustment for poor health, by age group, and after excluding early years of follow-up were used to assess bias. Over a mean of 10.1 yr of follow-up, 1165 deaths occurred. Poor health was associated with low MVPA760 levels and increased mortality risk. In fully adjusted MVPA760 models, HR was 26% stronger comparing 0 to 4 yr (HR = 0.46) with 0 to 12 yr of follow-up (HR = 0.62), particularly in older adults (65 yr and older). Increasing statistical adjustment for poor health attenuated MVPA760 associations by 13% to 15%, and exclusion of the first 2 yr of follow-up had limited effects. Comparable results were obtained with the MVPA2020 cut-point. We did not find evidence that confounding by health status resulted in entirely spurious MVPA-mortality associations; however, potential bias was appreciable in modeling scenarios involving shorter follow-up (<6 yr), older adults, and more limited statistical adjustment for poor health. The strength of MVPA-mortality associations in studies reflecting these scenarios should be interpreted cautiously.
Author Patel, Shreya B
Salerno, Elizabeth A
Troiano, Richard P
Saint-Maurice, Pedro F
Berrigan, David
Matthews, Charles E
Shiroma, Eric J
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  givenname: Pedro F
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  fullname: Saint-Maurice, Pedro F
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Snippet Confounding due to poor health is a concern in accelerometer-based studies of physical activity and health, but detailed investigations of this source of bias...
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StartPage 2546
SubjectTerms Accelerometry - mortality
Adult
Age Factors
Aged
Bias
Confounding Factors, Epidemiologic
Exercise
Female
Follow-Up Studies
Frailty
Health Status
Humans
Logistic Models
Male
Middle Aged
Mobility Limitation
Nutrition Surveys - statistics & numerical data
Odds Ratio
Proportional Hazards Models
Sedentary Behavior
Self Report
Time Factors
Title Exploration of Confounding Due to Poor Health in an Accelerometer-Mortality Study
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