Purpose We examined total, light, and moderate-to-vigorous physical activity (MVPA) as predictors of mortality in a nationally representative sample of older adults. Then, we explored the theoretical consequences of replacing sedentary time with the same duration of light activity or MVPA. Methods Using accelerometer measured activity, the associations between total, light (100 to 2019 counts per minute), and moderate-to-vigorous (>2019 counts per minute) activity counts and mortality were examined in adults aged 50 to 79 in the National Health and Nutrition Examination Survey, 2003-2006 (n=3,029), with mortality follow-up through December 2011. Cox proportional hazards models were fitted to estimate mortality risks. An isotemporal substitution model was used to examine the theoretical consequences of replacing sedentary time with light activity or MVPA on mortality. Results After adjusting for potential confounders, including age, sex, race/ethnicity, education, body mass index, and the presence of comorbid conditions, those in the highest tertile of total activity counts had one fifth the risk of death of those in the lowest tertile (HR: 0.21, 95% CI: 0.12, 0.38), and those in the middle tertile had one third the risk of death (HR: 0.36, 95% CI: 0.30, 0.44). In addition, replacing thirty minutes of sedentary time with light activity was associated with significant reduction in mortality risk (After 5 years of follow-up: HR = 0.80, 95% CI: 0.75, 0.85). Replacing thirty minutes of sedentary time with MVPA was also associated with reduction in mortality risk (HR = 0.49, 95% CI: 0.25, 0.97). Conclusions Greater total activity is associated with lower all-cause mortality risk. Replacing sedentary time with light activity or MVPA may reduce mortality risk for older adults.
Purpose The health consequences of obesity are often assessed using categorical, self-reported data on body mass index (BMI). This paper investigates the combined effects of categorization and self-report bias on the estimated association between obesity and mortality. Methods We used the National Health and Nutrition Examination Survey (1988–2008) linked to death records through 2011. Cox models and age-standardized death rates were used to evaluate the effects of categorization and self-report bias on the mortality risks and percent of deaths attributable to obesity. Results Despite a correlation between measured and self-reported BMI of 0.96, self-reports miscategorized 20% of adults. Hazard ratios using self-reports were overstated for the obese 1 (BMI 30–35 kg/m2) and obese 2 (BMI ≥30 kg/m2) categories. The bias was much smaller using a continuous measure of BMI. In contrast, the percent of deaths attributable to excess weight was lower using self-reported versus measured data because self-reports led to systematic downward bias in the BMI distribution. Conclusions Categorization of BMI and self-report bias combine to produce substantial error in the estimated hazard ratios and percent of deaths attributable to obesity. Future studies should use caution when estimating the association between obesity and mortality using categorical self-reported data.
Dementia is increasingly recognized as a major source of disease burden in the United States, yet little research has evaluated the lifecycle implications of dementia. To address this research gap, this article uses the Aging, Demographics, and Memory Study (ADAMS) to provide the first nationally representative, longitudinal estimates of the probability that a dementia-free person will develop dementia later in life. For the 1920 birth cohort, the average dementia-free 70-year-old male had an estimated 26.9 % (SE = 3.2 %) probability of developing dementia, and the average dementia-free 70-year-old female had an estimated 34.7 % (SE = 3.7 %) probability. These estimates of risk of dementia are higher for younger, lower-mortality cohorts and are substantially higher than those found in local epidemiological studies in the United States, suggesting a widespread need to prepare for a life stage with dementia.Electronic supplementary materialThe online version of this article (doi:10.1007/s13524-017-0598-7) contains supplementary material, which is available to authorized users.
OBJECTIVEUsing a nationally representative sample of the civilian noninstitutionalized U.S. population, we estimated trends in diabetes prevalence across cohorts born 1910–1989 and provide the first estimates of age-specific diabetes incidence using nationally representative, measured data.RESEARCH DESIGN AND METHODSData were from 40,130 nonpregnant individuals aged 20–79 years who participated in the third National Health and Nutrition Examination Survey (NHANES III), 1988–1994, and the continuous 1999–2010 NHANES. We defined diabetes as HbA1c ≥6.5% (48 mmol/mol) or taking diabetes medication. We estimated age-specific diabetes prevalence for the 5-year age-groups 20–24 through 75–79 for cohorts born 1910–1919 through 1980–1989 and calendar periods 1988–1994, 1999–2002, 2003–2006, and 2007–2010. We modeled diabetes prevalence as a function of age, calendar year, and birth cohort, and used our cohort model to estimate age-specific diabetes incidence.RESULTSAge-adjusted diabetes prevalence rose by a factor of 4.9 between the birth cohorts of 1910–1919 and 1980–1989. Diabetes prevalence rose with age within each birth cohort. Models based on birth cohorts show a steeper age pattern of diabetes prevalence than those based on calendar years. Diabetes incidence peaks at 55–64 years of age.CONCLUSIONSDiabetes prevalence has risen across cohorts born through the 20th century. Changes across birth cohorts explain the majority of observed increases in prevalence over time. Incidence peaks between 55 and 64 years of age and then declines at older ages.
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