To investigate the association between different domains of physical activity (PA) and adiposity-related indicators among rural older adults in Chengdu, offering empirical evidence to inform the design of tailored health intervention policies.
An observational analysis was conducted using data from a cluster randomized controlled trial performed in rural areas of Chengdu. The Physical Activity Scale for the Elderly was used to assess total physical activity, work-related physical activity, housework physical activity, and leisure-time physical activity levels. Body mass index (BMI), body fat percentage, waist-to-hip ratio (WHR), and waist-to-height ratio (WHTR) as adiposity-related indicators were measured. A linear mixed model was employed to analyze the relationship between different domains of PA and adiposity-related indicators. Sensitivity analyses were conducted in control group to assess the robustness of the findings.
Of the 508 enrolled participants (average age: 70.93 years), 282 were female, while the remaining 226 were male. Total PA, work-related PA, and household PA levels all showed significant negative correlations with BMI, body fat percentage, WHR, and WHTR (total PA: β=-0.004 9, P<0.001; β=-0.013 5, P<0.001; β=-0.000 1, P<0.001; β=-0.000 1, P<0.001; work-related PA: β=-0.003 1, P=0.006; β=-0.012 8, P=0.005; β=-0.000 1, P=0.007; β=-0.000 1, P<0.001; household PA: β=-0.008 4, P=0.006; β=-0.017 0, P<0.001; β=-0.000 2, P<0.001; β=-0.000 2, P<0.001). However, leisure-time PA was only significantly negatively associated with WHR and WHTR (β=-0.000 1, P=0.007; β=-0.000 1, P=0.011). Sensitivity analysis further confirmed the robustness of these associations.
Higher levels of total PA, work-related PA, and household PA were associated with lower BMI, body fat percentage, WHR, and WHTR in older adults. Higher leisure-time PA was only associated with lower WHR and WHTR. These findings suggest that future physical activity recommendations for older adults should be tailored based on adiposity-related indicators to develop precise and effective intervention strategies.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |