Based on longitudinal survey data, this study aimed to explore the associations between Activities of Daily Living (ADL), depressive symptoms, and cognitive function among rural elderly individuals in Guizhou Province, so as to provide scientific evidence for promoting the health of rural elderly populations.

A multi-stage cluster sampling method was adopted to select rural elderly individuals aged 60 years and above from 12 villages in 5 townships (towns) of 2 counties (districts) in Guizhou Province. A baseline survey (T1) was conducted in 2019, and a follow-up survey (T2) was carried out in 2022. Generalized Estimating Equations (GEE) were used to analyze the associations and interaction effects between ADL, depressive symptoms, and cognitive function.

A total of 763 elderly individuals were included as participants in this study. The results showed that both ADL scores (β=-0.57, 95%CI: -0.68 - -0.47) and depression scores (β=-0.20 95%CI: -0.33 - -0.06) were negatively associated with cognitive function (assessed by Mini-Mental State Examination ［MMSE］ scores). Furthermore, a significant interaction effect was observed between these two factors on cognitive function (β=0.11, 95%CI: 0.08-0.15). Stratified analysis by depression score levels revealed that ADL scores remained negatively associated with cognitive function across all strata (all P<0.05). When stratified by ADL score levels, depression scores were negatively associated with cognitive function in the low ADL group (P<0.05), whereas no statistically significant association was found in the high ADL group (β=-0.06, 95%CI: -0.28-0.17).

Impaired ADL and depressive symptoms increase the risk of cognitive decline in elderly individuals in rural areas. Depression can moderate the association between ADL and cognitive function: elderly individuals with unimpaired ADL may be more vulnerable to the impact of depression on cognitive function. Strengthening the monitoring and intervention of ADL and depressive symptoms in the elderly is conducive to preventing or delaying cognitive decline among elderly individuals in rural areas.

To understand the current status of chronic comorbidities and impaired activities of daily living in elderly OP patients, explore the association between different comorbidity combinations and daily ADL, and provide theoretical basis for improving the quality of life of elderly OP comorbidities.

In April 2025, a stratified cluster random sampling method was used to select research subjects from two townships in Yanchi County, Ningxia, to conduct a questionnaire survey and measure bone density. Obtain association rules for chronic disease combinations in elderly OP patients through association rules, and use binary logistic regression to analyze the magnitude of the association between comorbidities in elderly OP and ADL impairment.

This study included 685 elderly OP patients, with a chronic disease comorbidity rate of 66.72%. The rates of BADL, IADL, and ADL impairment were 10.66%, 11.97%, and 16.79%, respectively. Through the Apriori algorithm, a total of 12 association rules were identified, with “hypertension and osteoporosis” being the most common comorbidity among all combinations (47.445%). Single factor logistic regression analysis shows that the comorbidity combination of “hypertension, lumbar disc disease, and osteoporosis” was significantly associated with increased impairment in BADL and ADL compared to elderly OP patients ［(OR=3.69, 95%CI：1.80-7.55), (OR=3.25, 95%CI：1.69-6.25)］. The comorbidity combination of “hypertension, heart disease, and osteoporosis” was associated with a higher likelihood of impaired IADL (OR=3.73, 95%CI：2.08-6.69). The results of multiple logistic regression showed that compared with elderly OP patients, the comorbid combination of “lumbar disc disease and osteoporosis” increased the likelihood of impaired BADL and ADL ［(OR=4.27, 95%CI：2.28-7.99), (OR=3.62, 95%CI：2.06-6.38)］, while the “hypertension, heart disease, and osteoporosis” combination was associated with a higher likelihood of IADL impairment (OR=3.02, 95%CI：1.57-5.80).

Elderly OP patients have impaired activities of daily living, and hypertension plays an important comorbidity center in elderly OP patients. Multiple comorbidity combinations significantly increase the risk of ADL impairment. The healthcare system should focus on the elderly population with comorbidities, develop effective long-term care policies for different comorbidities, and enhance the elderly’s sense of health and quality of life.

To explore the mediating role of sleep quality in the relationship between multimorbidity and depressive symptoms in patients with pneumoconiosis.

Based on the baseline data from the West China Pneumoconiosis Prospective Specialized Disease Cohort, latent class analysis was employed to categorize nine common multimorbidities among pneumoconiosis patients. Logistic regression models were used to analyze the associations between the number of multimorbidities, multimorbidity patterns, and depressive symptoms. The Bootstrap method was employed to examine the mediating effect of sleep quality.

40.97% patients with pneumoconiosis exhibited depressive symptoms. Latent class analysis identified four multimorbidity patterns: relatively healthy, cardiovascular-metabolic, respiratory system, and multimorbidity. Logistic regression showed that the number of multimorbidities (OR=1.34, 95%CI: 1.23-1.46), the cardiovascular-metabolic pattern (OR=1.82, 95%CI: 1.02-3.25), and the multimorbidity pattern (OR=3.16, 95%CI: 1.97-5.06) were positively associated with depressive symptoms. Mediation analysis indicated that sleep quality partially mediated the relationship between the number of multimorbidities and depressive symptoms (β=0.53, 95%CI: 0.41-0.66), with a mediation effect proportion of 61.63%. Regarding the multimorbidity pattern, sleep quality fully mediated the relationship with depressive symptoms, with a mediation effect value of 2.11(95%CI:1.46-2.78) and an effect proportion of 69.41%.

The number of multimorbidities, cardiovascular-metabolic pattern, and multimorbidity pattern are associated with a higher risk of depression in pneumoconiosis patients. Sleep quality partially mediates the relationship between the number of multimorbidities and depressive symptoms, while it fully mediates the relationship between the multimorbidity pattern and depressive symptoms.

To explore the mediating role of frailty between grip strength and cognitive function in community-dwelling older adults and the moderating effect of age.

A convenience sample of 818 community-dwelling older adults was recruited from Qixia District, Nanjing, Jiangsu Province, between July and August 2024. Cognitive function was assessed using the Beijing version of the Montreal Cognitive Assessment (MoCA), frailty status was assessed using the FRAIL Scale (The FRAIL Scale, FRAIL), and grip strength was measured using an electronic handgrip dynamometer. Moderated mediation analysis was conducted using PROCESS 4.1 (Model 4 and Model 59).

Grip strength was negatively correlated with frailty scale scores (r=-0.252, P<0.001) and positively correlated with cognitive function scale scores (r=0.216, P<0.001). Frailty partially mediated the association between grip strength and cognitive function, with a mediation effect of 0.014 (95%CI: 0.006-0.024), accounting for 21.9% of the total effect. In the age-moderated mediation model, the interaction terms for the first path (grip strength×age group→frailty) and the second path (frailty×age group→cognitive function) were both significant (both P<0.05).

Grip strength influences cognitive function indirectly through frailty, and this mediation pathway is moderated by age. Early screening for frailty and age-specific interventions should be emphasized to preserve cognitive function.

To investigate the factors associated with intergenerational transmission of weight status in low-income families in China and to provide evidence for policies aimed at interrupting the vertical inequality in health.

Utilizing data from the 2022 China Family Panel Studies (CFPS), we employed Multinomial Logistic Regression Model(MLOGIT) models to analyze the associations.

Maternal weight status showed significant effects on offspring weight. Compared to mothers with normal weight, underweight mothers were associated with a 56.7% higher risk of offspring being underweight (OR=1.567, P<0.05) and a 41.9% lower risk of offspring obesity (OR=0.581, P<0.05). Obese mothers were associated with a 55.5% increased risk of offspring obesity (OR=1.555, P<0.05). Paternal weight status had a limited influence on offspring weight outcomes, with no significant association observed between paternal obesity and offspring obesity. Male offspring and children of younger age exhibited a higher likelihood of being overweight or obese. Higher educational attainment of both parents was significantly associated with a reduced risk of offspring overweight or obesity. Furthermore, maternal rural residency was linked to a complex pattern, potentially associated with a decreased risk of offspring underweight yet an increased risk of obesity.

In low-income families, parental weight status is strongly correlated with offspring weight status. Mothers serve as more comprehensive and direct influencers on offspring health, whereas the influence of fathers is relatively limited. Offspring characteristics and household economic factors are also important determinants of offspring health. Therefore, breaking the intergenerational transmission of weight disadvantages in low-income families requires differentiated strategies.

To identify multimorbidity phenotypes in middle-aged and older adults, examine their long-term health trajectories, and develop a predictive model for functional dependency.

This longitudinal analysis used five waves(2011-2020) of the China Health and Retirement Longitudinal Study(CHARLS) and included 298 participants with complete follow-up. Phenotype subgroups were derived by Kmeans clustering based on baseline disease count. Generalized Estimating Equations(GEE) were applied to assess health differences and trajectories across phenotypes. A care-needs prediction model was developed by integrating prior health status(2018) and pre-2018 dynamic slopes.

Three multimorbidity burden phenotypes were identified: high, moderate, and low. A higher baseline disease count was independently associated with increased risks of functional dependency(ADL: OR=2.398; IADL: OR=2.346), depression, and pain(all P<0.001). The high-burden phenotype showed faster rates of decline in cognitive function, pain accumulation, and life satisfaction(all P<0.01). The prediction model, incorporating prior functional status, depressive symptoms, phenotype, and rate of pain progression, demonstrated good discrimination(AUC for ADL dependency=0.807, 95%CI: 0.740-0.874; AUC for IADL dependency=0.765, 95%CI: 0.678-0.851).

Multimorbidity phenotypes are associated with distinct long-term health trajectories. A model combining static phenotypes and dynamic health indicators can help identify individuals at high risk of functional dependency, supporting targeted prevention and care planning.

To explore the association between accelerated phenotypic aging(PAA) and risk of osteoarthritis(OA), and to assess the modifying effect of genetic susceptibility, as well as the mediating effect of body mass index(BMI) on the PAA-OA association.

Using baseline survey, diagnostic, and genetic data from the UK Biobank(UKB), Cox proportional hazards regression models was employedto analyze the association between PAA and OA, and pathway analysis was employed to explore the mediating effect of BMI.

With an average follow-up of 13.7 years, a total of 42 977 incident OA cases were recorded. PAA acceleration was significantly associated with an increased risk of OA(HR=2.13, 95%CI:2.11-2.15). BMI mediated 77.1%(95%CI:65.5%-92.1%) of the total effect. Further subgroup analyses revealed that the PAA-OA association was significant across all subgroups, including different sex, age, and BMI levels. No gene-PAA interaction was identified for OA risk.

PAA is an independent risk factor for OA, and BMI is an important mediating variable in the PAA-OA association. This study provides novel insights and public health implications for delaying aging and preventing OA.

To explore the impact of temperature on the number of hospital admissions for stroke in Hengshui City, Hebei Province, and to provide scientific support for relevant prevention and control efforts.

We collected data on the number of hospital admissions for stroke in a region of Hebei Province, daily meteorological data, and air quality data. A distributed lag non-linear model (DLNM) was employed to analyze the effects of temperature on hospital admissions among different genders, age groups, and subgroups.

During the warm season (May to October), temperature had a significant impact on the number of hospital admissions for stroke across various populations. With a cumulative lag of 15 days, the cumulative relative risk (RR) of hospital admission for stroke at a relatively low temperature of 20 ℃ in the warm season was 1.291 (95%CI: 1.030-1.619), at 21 ℃ it was 1.216 (95%CI: 1.016-1.456), and at 22 ℃ it was 1.154(95%CI: 1.003-1.327). For females, the RR was 6.422 (95%CI: 1.910-21.588) at 10 ℃. For the population aged ≥ 65 years, the RR was 4.286 (95%CI: 1.401-13.112) at 10 ℃ and 1.117 (95%CI: 1.016-1.228) at 24 ℃. The relatively low temperature range of 20 ℃-26 ℃ in warm seasons could significantly increase the hospitalization risk of cerebral ischemia subtype (RR: 1.09-2.31). The risk peaked at 20℃, when RR was 2.315 (95%CI: 1.338-4.003).

Temperature during the warm season influences the number of hospital admissions for stroke, with relatively low temperatures (20-22 ℃) in the warm season identified as potential risk factors for stroke patient admissions. Moreover, temperature has specific impacts on females, individuals aged 65 and above, and those with cerebral ischemia.

To explore the impact of extreme temperature on the risk of non-accidental mortality in Zhangjiakou city, and to identify susceptible subpopulations.

Data on non-accidental mortality among residents in Zhangjiakou City from 2019 to 2024, as well as concurrent meteorological and air pollution data, were obtained from the Air Pollution and Health Effects Monitoring Information System. The distributed lag non-linear model (DLNM) was employed to analyze the exposure-lag-response relationships between extreme temperatures and both non-accidental mortality and cardiovascular disease mortality, with stratified analyses conducted by sex and age group.

The exposure-response relationship between daily mean temperature and both non-accidental and cardiovascular mortality exhibited a U-shaped curve. The effects of extreme cold showed persistent lag patterns, with the cumulative relative risks (cumulative RRs) peaking at lag 21 days for both non-accidental mortality (CRR=2.470, 95%CI: 1.746-3.494) and cardiovascular mortality (CRR=2.163, 95%CI: 1.379-3.394). In contrast, the effects of extreme heat were acute and short-lived, with cumulative RRs peaking at lag 6 days (CRR=1.483, 95%CI: 1.316-1.672) and lag 5 days (CRR=1.462, 95%CI: 1.236-1.729) for non-accidental and cardiovascular mortality, respectively. Stratified analysis revealed that males and individuals aged ≥65 years were at higher risk, with greater cumulative RRs during extreme temperature events.

Extreme temperatures significantly increase the risk of cardiovascular mortality in Zhangjiakou. Males and the elderly (≥65 years) are particularly vulnerable.