Longitudinal Sex‐Specific Physical Function Trends by Age, Race/Ethnicity, and Weight Status

Abstract

BACKGROUND: There is a need to assess longitudinal trends in physical function and to understand the prevalence of physical function status in the older population using objectively measured physical function. Therefore, the primary purpose of this study was to examine longitudinal sex-specific physical function trends and prevalence of physical function status by age, race/ethnicity, and weight status in older adults, aged 65 years and older. METHODS: The present study used longitudinal data from the National Health and Aging Trends Study. Physical function was measured annually from 2011 to 2018 using the Short Physical Performance Battery, and classified as poor (0-6), fair (7-9), or good (10-12). Mixed effect regression and generalized estimating equation models were used to estimate unadjusted trends and annual changes in physical function, adjusting for confounders and accounting for complex sampling. RESULTS: Respondents' physical function declined over time regardless of sex, age, race/ethnicity, and weight status (P < .001). Respondents aged 75 to 84 years (males: β = −.18; 95% confidence interval (CI) = −.22 to −.13; females: β = −.23; 95% CI = −.27 to −.20) and 85 years and older (males: β = −.39; 95% CI = −.47 to −.30; females: β = −.33; 95% CI = −.39 to −.28) had a greater annual physical function rate of decline than respondents aged 65 to 74 years. Respondents aged 75 years and older also had a greater annual increase in the proportion classified as having poor physical function than respondents aged 65 to 74 years (P < .001), regardless of sex. Compared with non-Hispanic whites, Hispanic females had a lower annual physical function rate of decline (β = .14; 95% CI = 0.07-0.20), and Hispanic and/or non-Hispanic blacks had slower annual changes in the proportion classified as having good physical function (P < .05). Compared with normal weight males, overweight males had lower annual changes in physical function (P = .003) and proportion of those with poor physical function (P = .004), but no differences between weight status were observed in females. CONCLUSIONS: Physical function declines with age, but temporal changes in physical function and physical function status varied by sex, age, race/ethnicity, and weight status.

Barriers to eating are associated with poor physical function in older women

“…The range of SPPB scores in this sample of women would be considered 'fair' 19 .A recent systematic review and meta-analysis 20 confirmed that SPPB scores of 7-9 and 4-6 were associated with an increased risk of all-cause mortality (OR=1.5 and 2.41, respectively) compared to scores of 10-12. Grip strength < 20 kg in women was recently shown to be highly predictive of mobility limitations in older women 21 as well as overall muscle weakness and predictor of sarcopenia.…”

Associations of Serum Albumin With Disability in Activities of Daily Living, Mobility and Objective Physical Functioning Regardless of Vitamin D: Cross-Sectional Findings From the Chinese Longitudinal Healthy Longevity Survey

“…According to previous studies, we found that some population characteristics (e.g., age, sex, ethnicity, and so on) (34)(35)(36)(37)(38)(39) and lifestyles (e.g., currently smoking, current consuming alcohol, and regular exercise) (40)(41)(42)(43) may confound the associations between serum albumin and physical functioning. Thus, as done in the previous study based on CLHLS (44), the following covariates were included in our analysis: age, sex, residence (rural vs. other), ethnicity (Han vs. other), education (≥1 year of education vs. no education), economic independence (yes vs. no), lifetime primary occupation (white-collar occupation vs. others), and being in receipt of adequate medications (yes vs. no); co-residence with children (yes vs. no) and current marital status (married vs. others) were used to assess participants' social support and contact; lifestyle consisted of consuming alcohol (yes vs. no), currently smoking (yes vs. no), and regular exercise (yes vs. no).…”

Trends in the prevalence of vision impairment among the oldest-old Chinese population from 1998 to 2018

“…We performed GEE models to assess temporal trends in the prevalence of vision impairment by examining higher-order terms of survey year [18]. The presence of vision impairment was modelled as a binomial outcome with a logit link in GEE models, with an exchangeable working correlation to account for repeated visual assessments of the same participant.…”