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The purpose of this study was to explore the relationship between total physical activity and different dimensions of cognitive function (orientation, attention, and memory) among older adults in rural Sichuan, China. This cross-sectional study involved 715 older adults (average age of 72 years). Total PA was measured by the Physical Activity Scale for the Elderly, and cognitive function was assessed by the Telephone Interview for Cognitive Status (TICS) questionnaire. The multivariate linear regression analysis indicated that total PA and household PA were significantly associated with the overall Telephone Interview for Cognitive Status score (β = 0.143, p <.001; β = 0.115, p =.002, respectively), the orientation dimension (β = 0.142, p <.001; β = 0.131, p =.001, respectively), and the memory dimension (β = 0.179, p <.001; β = 0.134, p =.001, respectively). The study showed a positive association between total PA, household PA, and cognitive function in older adults, especially in the orientation dimension and the memory dimension of cognitive function. [ABSTRACT FROM AUTHOR]

Yufei Wang, Qiong Meng, Jin Zhang, Bing Guo, Nanyan Li, Qian Deng, Julinling Hu, Deji Quzong, Han Guan, Danzhen Wangjiu, Hui Yu, Zhifeng Li, and Junmin Zhou. Altitude and metabolic dysfunction-associated fatty liver disease (MAFLD) in China: a population-based study. High Alt Med Biol. 00:00-00, 2024. Objectives: The epidemiological evidence for the relationship between altitude and metabolic dysfunction-associated fatty liver disease (MAFLD) is scarce. This study aims to examine the altitude-MAFLD relationship and explore the potential mediators explaining the relationship. Methods: Data were derived from the China Multi-Ethnic Cohort. The participants' altitude information was extracted from their residential addresses. MAFLD was diagnosed based on radiographically confirmed hepatic steatosis and any one of the following three items: overweight/obese status, diabetes mellitus, or metabolic dysregulation. We performed multivariable logistic regression and mediation analyses to assess the altitude-MAFLD associations and potential mediators, respectively. In the mediation analysis, mediation proportion is an estimate of the extent to which the total effect (altitude-MAFLD association) is accounted for by the pathway through the mediators. Results: In total, 87,679 participants (female: 60.7%, mean age: 51.36 years) were included. The odds ratio of MAFLD was 1.61 (95% confidence interval [CI]: 1.52-1.71) between high and low altitudes, 1.52 (95% CI: 1.43-1.62) between high and middle altitudes, and 1.06 (95% CI: 1.01-1.10) between middle and low altitudes. Of the total estimated effect between high and low altitude, physical activity and vegetable intake accounted for 15.7% (95% CI: 12.8-19.1) and 3.8% (95% CI: 1.2-6.6), respectively. Of the total estimated effect between high and middle altitude, physical activity and vegetable intake accounted for 31.4% (95% CI: 26.2-34.8) and 2.3% (95% CI: 0.6-3.8), respectively. Of the total estimated effect between middle and low altitude, vegetable intake accounted for 11.8% (95% CI: 3.2-61.5). Conclusion: Higher altitude was associated with increased odds of MAFLD, and physical activity and vegetable intake mediated such association. Multifaceted efforts should be taken in public health to promote healthy lifestyles among higher altitude residents.

Background: Current randomized trial evidence for the effects of physical activity intervention on weight change in adults was mainly from western countries, with little reliable evidence from low- and middle-income countries, such as China, where lifestyle factors and obesity patterns differ substantially from those in western countries. We examined the effects of physical activity intervention on weight change using cluster randomized trial data among Chinese older adults., Methods: The cluster randomized controlled trial included an 8-week physical activity intervention period and was followed up to 24 months. Eight villages were randomly assigned to the intervention group (4 villages, n = 240) or the control group (4 villages, n = 268). The intervention group received physical activity intervention based on the socio-ecological model, while the control group did not. The intervention involved three levels: individual, interpersonal, and community levels, which aimed to promote leisure-time physical activity of participants. The primary outcome of the present study was the difference in percentage weight change at 24 months from baseline. We used Tanita BC-601 analyzer scales to measure weight and recorded it to the nearest 0.1 kg., Results: Among the 508 participants, the mean age was 70.93 (SD, 5.69) years, and 55.5% were female. There were significant differences in percentage weight change between the intervention group and the control group with a mean change of -1.78% (95% CI, -2.67% to -0.90%; p < 0.001) in the total sample, -1.94% (95% CI, -3.14% to -0.73%; p = 0.002) in participants with overweight/obesity, and -1.45% (95% CI, -2.73% to -0.18%; p = 0.027) among participants with underweight/healthy weight in favor of the intervention group at 24 months., Conclusions: Physical activity intervention resulted in weight loss in rural older sample at 24 months. This suggested that physical activity interventions are feasible for weight loss among older adults, especially for those with overweight/obesity or aged under 80., Trial Registration: The study has been registered on the Chinese Clinical Trial Registry on April 20, 2021 (ChiCTR2100045653), https://www.chictr.org.cn/showproj.html?proj=123704 ., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Study Objectives: To examine the longer-term effect of physical activity (PA) intervention on sleep quality and whether the effect was heterogeneous between daytime nappers and non-nappers., Methods: This study was a secondary analysis of a cluster randomized controlled trial in China. Eight villages were randomized 1:1 to intervention or control group. The intervention group received an 8-week PA intervention, while the control group did not. The primary outcome of this study was the change in the Pittsburgh Sleep Quality Index (PSQI) global score at 24 months., Results: The 511 participants had a mean age of 70.94 years (SD 5.73) and 55.6% were female. The intervention showed improvements in the PSQI global score at 8 weeks (adjusted mean difference -1.05; P=0.002), and the effect diminished at 24 months (-0.64; P=0.06). There were statistically significant improvements in the PSQI global score for daytime nappers, but not for non-nappers at 8 weeks (adjusted mean difference -0.98; P=0.01 vs -1.27; P=0.05), 12 months (-0.86; P=0.03 vs -0.84; P=0.21), and 24 months (-0.80; P=0.04 vs -0.14; P=0.84), although these improvements were below the minimum detectible level of the PSQI which is 1 point., Conclusion: The 8-week PA intervention was effective in improving sleep quality, while the effect was diminished and below the minimum detectible level of the PSQI which is 1 point after 24 months. The effect of PA intervention on sleep quality was more pronounced in daytime nappers. Additional interventions (e.g., focusing on multiple behavioral interventions such as PA and healthy diet) are needed to maintain the beneficial effect of PA on sleep quality in the general older populations. Further research is required to confirm the mechanisms of the effect of napping and develop tailored interventions., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Introduction: How education affects the relationship between sedentary behavior and cognitive function remains unclear. The aim of this study was to investigate the relationship between mentally active sedentary behavior and cognitive function in rural older Chinese across different levels of education., Methods: Data from 517 participants aged 60 years and older in rural China at baseline, 4 weeks, 8 weeks, 6 months, 12 months, and 24 months were analyzed. Univariate analysis was carried out using descriptive statistical techniques and bivariate analysis was performed using linear mixed effects models., Results: Total mentally active sedentary behavior time and playing cards/mahjong time were significantly associated with global cognition (0.25 points [95% CI, 0.15-0.35], p &lt; 0.001; 0.27 points [95% CI, 0.16-0.37], p &lt; 0.001, respectively), the attention dimension (0.07 points [95% CI, 0.01-0.12], p = 0.025; 0.08 points [95% CI, 0.02-0.14], p = 0.011, respectively), and the memory dimension (0.20 points [95% CI, 0.13-0.26], p &lt; 0.001; 0.18 points [95% CI, 0.12-0.25], p &lt; 0.001, respectively). Such associations were more pronounced in illiterate participants., Conclusion: Our study suggested a positive association between mentally active sedentary behavior and cognitive function, with the association being more pronounced among illiterate older adults compared to the relatively well-educated. Future cognitive interventions should focus more on mentally active behavior. In addition, education-specific intervention strategy may be considered in cognitive interventions., (© 2024 S. Karger AG, Basel.)

The purpose of this study was to explore the relationship between total physical activity and different dimensions of cognitive function (orientation, attention, and memory) among older adults in rural Sichuan, China. This cross-sectional study involved 715 older adults (average age of 72 years). Total PA was measured by the Physical Activity Scale for the Elderly, and cognitive function was assessed by the Telephone Interview for Cognitive Status (TICS) questionnaire. The multivariate linear regression analysis indicated that total PA and household PA were significantly associated with the overall Telephone Interview for Cognitive Status score (β = 0.143, p < .001; β = 0.115, p = .002, respectively), the orientation dimension (β = 0.142, p < .001; β = 0.131, p = .001, respectively), and the memory dimension (β = 0.179, p < .001; β = 0.134, p = .001, respectively). The study showed a positive association between total PA, household PA, and cognitive function in older adults, especially in the orientation dimension and the memory dimension of cognitive function.