Furong Xu

Background: This study examined associations of body mass index (BMI) category and waist circumference (WC) independently and in tandem on all‐cause mortality risk among US adults aged ≥ 65 years. Methods: The present study utilized 14 years of longitudinal data (2011–2024) from 6905 participants in the National Health and Aging Trends Study. Cox proportional hazards models were used to estimate the hazard ratios (HRs), adjusted for baseline age, race, education, annual income, smoking status, and homebound status. Results: Compared with normal weight, overweight males (HR, 0.54 [95% CI, 0.45–0.66]) and males with class I and II obesity (HR, 0.49 [95% CI, 0.37–0.65]) had lower mortality risk. High WC was associated with greater mortality risk in males (HR, 1.24 [95% CI, 1.07–1.44]). Similar patterns were observed in females. In joint BMI‐WC analyses, overweight regardless of WC status and class I and II obesity with high WC were associated with lower mortality risk among males. Being underweight, regardless of WC status, and having normal weight with high WC were both associated with higher mortality risk in both sexes. Conclusions: These findings highlight the adverse association of central adiposity and the limitations of BMI‐only classification for mortality risk stratification in older adults.

Introduction: Longitudinal anthropometric changes may provide prognostic information beyond single timepoint measurements in older adults. We tested whether the annual percentage change (APC) in five anthropometric metrics (body mass index [BMI], waist circumference [WC], weight-adjusted waist index [WWI], waist-to-height ratio [WHtR], and waist-to-height^0.5 [WHT.5R]) were associated with all-cause mortality in a 14-year U.S. cohort of older adults. Methods: Using data from the National Health and Aging Trends Study (NHATS) 2011–2024 ( N = 5,245 after excluding deaths < 2 years), we calculated APC in BMI, WC, WWI, WHtR, WHT.5R using participant specific log-linear models. Survey-weighted Cox proportional hazard models were used to examine APC categories (stable [≤ 2% change] vs. larger gain/loss [> 2% change]) in relation to all-cause mortality, adjusted for baseline age, sex, race, education, annual income, smoking status, homebound status, major chronic disease status, physical frailty, functional status, and cognitive impairment. To ensure the robustness of study findings across all five indices, supplementary restricted cubic spline analyses were performed to validate our primary categorization analysis. Sensitivity analyses included 3- and 5-year lags to minimize reverse causation, explore sex-specific differences, and a two-point APC to confirm findings were not a modeling artifact. Results: Compared to stable (≤ 2% change) measures, fluctuations in all five anthropometric indices were associated with an elevated mortality risk (pooled HR range: 2.15–9.74; 95% CI boundaries ranged from 1.68 to 17.49; p < 0.001). Restricted cubic splines analyses supported a generally V-shaped association between anthropometric changes and mortality (all p _{non-linearity} < 0.05). Lagged sensitivity analyses produced findings generally consistent with the primary models (all p < 0.05). This elevated risk was observed for both gain and loss categories and were generally consistent across sex-stratified and two-point APC sensitivity analyses. Conclusion: These findings suggest that stability in anthropometric metrics may reflect a lower-risk physiological profile in older adults. Fluctuations (gain or loss) in the examined anthropometric metrics were associated with higher mortality risk, with generally consistent findings across sensitivity analyses. However, these associations should be interpreted cautiously as anthropometric changes may reflect underlying illness, frailty, or other unmeasured factors.

Background: Lifestyle behaviors are a potential adjunctive treatment for depression in emerging adults (18-25 years), but the combination of behaviors associated with depression remains unclear. Methods: 2,019 emerging adults from the National Health and Nutrition Examination Survey between 2011 and 2018 were selected. Latent class analysis (LCA) identified patterns of lifestyle behaviors (diet [Dietary Inflammatory Index], sleep [quantity/quality], physical activity, sedentary behavior, substance use [alcohol/smoking]). Multiple logistic regression examined associations between lifestyle patterns and depression. Results: LCA identified 6 male classes and 5 female classes. Compared to the Healthy reference group, males in the Poor Sleep Sedentary Drinkers (aOR [95% CI]: 4.40 [1.10, 17.55], P = 0.032) and Pro-inflammatory Diet (PID) Smokers Drinkers (aOR [95% CI]: 6.11 [1.94, 19.25], P = 0.002) groups and females in the PID Smokers Drinkers (aOR [95% CI]: 4.96 [2.07, 11.89], P < 0.001), Trouble Sleeping (aOR [95% CI]: 6.65 [2.17, 20.33], P < 0.001), and PID Sedentary (aOR [95% CI]: 4.74 [1.37, 16.35], P = 0.012) groups had increased odds of depression. Conclusions: We found unique sex-specific lifestyle patterns associated with depression (males: diet, sleep [quantity/quality], sedentary behavior, substance use; females: sleep quality). Lifestyle behaviors should be comprehensively targeted to prevent and treat depression in emerging adults.

Introduction: This study examined the relationship between fat distribution and diabetes by sex-specific racial/ethnic groups.Methods: A secondary data analysis of National Health and Nutrition Examination Survey 2011–2018 data (n = 11,972) was completed. Key variables examined were visceral adipose tissue area (VATA), subcutaneous fat area (SFA), diabetes prevalence, and race/ethnicity. The association of VATA and SFA and diabetes prevalence was examined separately and simultaneously using multiple logistic regression. Bonferroni corrections were applied to all multiple comparisons between racial/ethnic groups. All analyses were adjusted for demographics and muscle mass.Results: VATA was positively associated with diabetes in both sexes (p < 0.001) and across all racial/ethnic groups (p < 0.05) except Black females. No statistically significant relationships were observed between SFA and diabetes while accounting for VATA with the exception of White females (p = 0.032). When comparing racial/ethnic groups, the relationship between VATA and diabetes was stronger in White and Hispanic females than in Black females (p < 0.005) while the relationship between SFA and diabetes did not differ between any racial/ethnic groups.Conclusion: This study found that VATA is associated with diabetes for both sexes across almost all racial/ethnic groups independent of SFA whereas the only significant relationship between SFA and diabetes, independent of VATA, was observed in White females. The findings indicated that visceral fat was more strongly associated with diabetes than subcutaneous. Additionally, there are health disparities in sex-specific racial/ethnic groups thus further study is warranted.