To analyze the life expectancy (LE) and healthy life expectancy (HLE) of the elderly living in different ways in China, as well as gender and urban-rural differences, thus providing data support for optimizing the living arrangements and improving the HLE of the elderly in China.

The data of 4 503 elderly people aged 65 years old and above in 2014 and 2018 of Chinese Longitudinal Healthy Longevity Survey (CLHLS) were collected. The LE, HLE, and HLE/LE ratio of the elderly living alone and living with their families were measured by the micro-simulation method and compared between different genders as well as between urban and rural areas.

The LE of 65–100 elderly living alone and living with their families in China were 20.12–4.72 years and 17.59–4.13 years, respectively. The HLE were 10.12–1.78 years and 9.26–1.70 years, respectively. The HLE/LE were 50.30%–37.71% and 52.24% –41.16 %, respectively. The LE of men living alone and living with their families for 65 years and 100 years old were 14.77–3.59 years, 16.61–4.12 years, respectively. The HLE were 7.04–1.10 years, 9.80–1.68 years, respectively. The HLE/LE were 47.66%–30.64%, 59.00%–40.78%, respectively. The LE of women living alone and living with their families for 65–100 years old were 23.93–5.21 years and 19.09–3.82 years, respectively. The HLE were 12.14–1.78 years and 8.96–1.29 years, respectively. The HLE/LE were 50.73%–34.17% and 46.96%–22.77%, respectively. The LE, HLE, HLE/LE of male elderly living alone and male elderly living with family were lower than those of female elderly. The HLE and HLE/LE of male elderly living with family were higher than those of female elderly. The LE, HLE and HLE/LE of male elderly living alone were lower than those of male elderly living with family. The LE, HLE and HLE/LE of female elderly living alone were higher than those of female elderly living with family. The LE of the elderly living alone in the city and living with their families for 65–100 years were 20.55–5.29 years and 18.52–5.13 years, respectively. The HLE were 10.02–2.85 years and 9.06–3.04 years, respectively. The HLE/LE were 48.76%–53.88% and 48.92–59.26%, respectively. The LE of the elderly living alone in rural areas and living with their families for 65–100 years were 20.13–4.53 years and 17.28–3.71 years, respectively. The HLE were 10.97–1.20 years and 9.67–0.92 years, respectively. The HLE/LE were 54.50%–26.49% and 55.96%–24.80%, respectively. The LE of the urban elderly at all ages was higher than that of the rural elderly. Except that the HLE of the urban elderly aged 65-68 and the elderly aged 65 and 66 living with their families was lower than that of the rural elderly, the HLE of the elderly at other ages was higher than that of the rural elderly. With the increase of age, the HLE/LE of the rural elderly gradually decreased, while the HLE/LE of the urban elderly gradually increased.

The LE and HLE of the elderly living alone are generally higher than those living with their families, while the HLE/LE ratio demonstrates an opposite trend. Female elderly and the elderly living alone in urban areas have higher LE and HLE, while the male elderly living with their families have higher LE and HLE than the male elderly living alone.

To analyze the relationship between social inclusion and cognitive function of older adults in China and provide a theoretical basis for future research on reducing the risk of cognitive impairment in older adults through social inclusion interventions.

Data were collected from the China Health and Retirement Longitudinal Study (CHARLS) in 2015 (T1), 2018 (T2), and 2020 (T3), which measured cognitive function and social inclusion (economic inclusion, relational inclusion, and community inclusion) of 5 464 elderly people aged of and above 60. A cross-lagged model was adopted to analyze the effect of social inclusion on changes in cognitive function of older adults from T1 to T3.

The 5 464 people aged of and above 60 included in the analysis showed the total cognitive function scores of (14.11 ± 5.26), (12.55 ± 6.17), and (12.14 ± 5.99) and total social inclusion scores of (2.15 ± 1.06), (1.73 ± 0.85), and (1.64 ± 0.87) in T1, T2, and T3 periods, respectively. After the control of confounding factors such as sex, age, and education, the total social inclusion scores in T1 and T2 could positively predict the total cognitive function scores in T2 and T3 (β′ = 0.019 and 0.017, both P < 0.01), respectively. The community inclusion scores in T1 and T2 could positively predict the total cognitive function scores in T2 and T3 (β′ = 0.016 and 0.016, both P < 0.05), respectively. The total cognitive function score in T1 could positively predict the total social inclusion score, economic inclusion score, relational inclusion score, and community inclusion score (β′ = 0.051, 0.023, 0.025, and 0.057, all P < 0.05) in T2. The total cognitive function score in T2 could positively predict the total social inclusion score, economic inclusion score, relational inclusion score, and community inclusion score (β′ = 0.063. 0.031, 0.027, and 0.075, all P < 0.05) in T3.

Good social inclusion of older adults can protect their cognitive function, especially community inclusion, and good cognitive function of older adults can promote social inclusion.

To understand the disability index and its influencing factors among Chinese older adults from 2011 to 2018 and provide a reference for the development and adjustment of disability prevention policies.

We collected the data related to the disability index of 17 928 older adults aged 60 years and above in the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018. We conducted the Mann-Kendall trend test to analyze the trend of disability index in Chinese older adults from 2011 to 2018 and adopted the generalized estimating equation (GEE) to analyze its influencing factors.

The median score of disability index was 29.17 (15.28, 44.17) among 17 928 older adults aged 60 years and above in China. The median scores of disability index in 2011, 2013, 2015, and 2018 were 28.89 (13.89, 44.44), 26.94 (14.44, 41.11), 27.22 (13.89, 43.68), and 32.22 (22.78, 46.11), respectively. From 2011 to 2018, the disability index of older adults first improved and then worsened (τ_b = 0.066, P < 0.001). The results of the GEE analysis showed that the disability index was higher among Chinese older adults with a survey time point of 2018, being female, aged ≥ 75 years, in central or western China, residing in rural areas, having no medical insurance, suffering from ≥ 1 chronic disease, and having a history of falls. Chinese older adults with a survey time point of 2013 or 2015, having a primary school education or above, being married, and having a self-rated memory as fair or good had a lower disability index.

The disability index of Chinese older adults showed a trend of first improvement and then deterioration from 2011 to 2018. The survey time point, gender, age, education background, marital status, region, residence place, medical insurance, chronic disease, history of falls, and self-rated memory were the main influencing factors of the disability index in Chinese older adults.

To understand the relationships of the number of pregnancies and lifestyle with the prevalence of cardiovascular diseases (CVD) among elderly female diabetic patients in Jiaxian county, Henan province and provide a scientific basis for developing individualized CVD prevention strategies.

From July 1 to August 31, 2023, a cluster sampling method was employed to conduct a questionnaire survey among 21 379 patients aged ≥ 65 years who had lived in Jiaxian county, Henan province for at least six months and treated in 15 township hospitals or community health service centers. After individuals with incomplete lifestyle information, males, and non-diabetic patients were excluded, a total of 4 133 elderly female diabetic patients were included in the final analysis. A multivariable unconditional logistic regression model was adopted to examine the associations of the number of pregnancies and lifestyle with the prevalence of CVD among these patients.

Among the 4 133 elderly female diabetic patients included in the analysis from Jiaxian county, Henan province, 1 712 were diagnosed with CVD, resulting in a CVD prevalence of 41.4%. A total of 1 099 (26.6%), 1 190 (28.8%), and 1 844 (44.6%) patients had ≤ 2, 3, and ≥ 4 pregnancies, respectively. Regarding lifestyle, 2 183 (52.8%) patients were classified as having an unhealthy lifestyle, while 1 950 (47.2%) had a healthy lifestyle. After adjustment for confounding factors such as age, ethnicity, education background, marital status, and annual household income, multivariable unconditional logistic regression analysis showed that the elderly female diabetic patients with an unhealthy lifestyle had a 1.521-fold higher risk of CVD compared to those with a healthy lifestyle (OR = 1.521, 95%CI: 1.341–1.726). Interaction analysis further revealed that compared to the patients with ≤ 2 pregnancies and a healthy lifestyle, those with ≤ 2 pregnancies and an unhealthy lifestyle had a 1.432-fold higher risk of CVD (OR = 1.432, 95%CI: 1.121–1.829), those with 3 pregnancies and an unhealthy lifestyle had a 1.571-fold higher risk (OR = 1.571, 95%CI: 1.237–1.996), and those with ≥ 4 pregnancies and an unhealthy lifestyle had a 1.674-fold higher risk (OR = 1.674, 95%CI: 1.340–2.091).

A multiplicative interaction was observed between the number of pregnancies and unhealthy lifestyle, contributing to an elevated risk of CVD among elderly female diabetic patients in Jiaxian county, Henan province.

To investigate the incidence and influencing factors of moderate and severe fall-related injuries among the elderly in Guangzhou, Guangdong, China, thus informing evidence-based interventions for fall prevention in the elderly population.

To analyze the incurrence of moderate and severe fall-related injuries and identify influencing factors among the elderly patients, we collected data from 13 898 injury surveillance reports between January 1, 2015 and December 31, 2021 across four National Injury Surveillance Sentinel hospitals in Guangzhou.

moderate and severe injuries accounted for 38.53% (n = 5 355) of cases. Multivariate unconditional logistic regression analysis identified the following risk factors: female, non-local household registration, age ≥ 70 years, history of falls, and activity-specific hazards emerged during walking (OR=1.118) and essential life activities, particularly in unspecified locations. Autumn occurrence and road/street environments of falls were the protective factors.

The incidence of moderate and severe fall-related injuries among elderly patients in Guangzhou is high. Key influencing factors include gender, age, household registration, history of falls, seasons, activities, and locations.

To analyze the sleep quality and associated factors among community-dwelling adults aged ≥ 60 years in the urban areas of Nanjing, China, thus providing evidence for optimizing sleep quality in this population.

From July to December 2023, a multi-stage stratified sampling method was used to randomly select 2 851 adults aged ≥ 60 years from urban communities in Nanjing. Face-to-face questionnaire surveys were conducted to systematically collect data on general demographic characteristics, daily lifestyle behaviors, and medical history. The Pittsburgh sleep quality index (PSQI) was adopted to assess sleep quality.

The older adults in the urban areas of Nanjing presented the mean PSQI score of 5.31 ± 3.27, with the poor sleep quality detection rate of 40.3%. Multivariate analysis revealed that the individuals aged 70–79 (OR = 1.24, 95%CI: 1.04–1.47) and ≥ 80 years (OR = 1.69, 95%CI: 1.30–2.19) had worse sleep quality than those aged 60–69 years. Additionally, the presence of cardiovascular diseases (OR = 1.50, 95%CI: 1.19–1.88), other chronic diseases (OR = 1.68, 95%CI: 1.19–2.38), depressive symptoms (OR = 2.04, 95%CI: 1.24–3.37), and anxiety symptoms (OR = 2.69, 95%CI: 1.88–3.86) were also significant influencing factors for poor sleep quality (all P < 0.05).

Poor sleep quality is common among older adults in the urban areas of Nanjing, and its occurrence is associated with age, cardiovascular diseases, other chronic diseases, depressive symptoms, and anxiety symptoms.

To investigate the incidence and influencing factors of falls in the elderly of Jilin province and provide a scientific basis for further prevention and control of falls among the elderly.

From July to December 2022, 800 permanent residents aged ≥ 60 years old were selected by multi-stage stratified random sampling from Nanguan district of Changchun city, Xi′an district of Liaoyuan city, Antu county of Yanbian prefecture, and Lishu county of Siping city in Jilin province. The main influencing factors of falls in the elderly in this area were analyzed by multivariate logistic regression.

Among the 800 permanent residents aged ≥ 60 years old in Jilin province, 166 fell in the past year, and thus the incidence of falls was 20.75%. The results of multivariate logistic regression showed that age ≥ 80 years old (OR = 2.555, 95%CI: 1.390–4.659), residence in rural areas (OR = 1.685, 95%CI: 1.048–2.710), cerebrovascular disease self-reported (OR = 1.947, 95%CI: 1.262–3.004), chronic obstructive pulmonary disease self-reported (OR = 1.815, 95%CI: 1.009–3.263) and osteoarthritis self-reported (OR = 1.783, 95%CI: 1.153–2.759) were more likely to fall. Those exercising regularly (OR = 0.641, 95%CI: 0.423–0.970), self-assessing general health condition (OR = 0.292, 95%CI: 0.184–0.464) or good health conditions (OR = 0.149, 95%CI: 0.080–0.276) were not likely to fall.

The incidence of falls is high among the elderly in Jilin province. Age, place of residence, regular physical exercise, self-assessment of health status, and whether suffering from cerebrovascular diseases, chronic obstructive pulmonary disease, or osteoarthritis are the main influencing factors of falls among the elderly in this area.

To compare the performance of back propagation artificial neural network (BP-ANN) and logistic regression models in predicting the risk of cumulative fatigue among petrochemical employees and evaluate the prediction models for early identification and intervention of cumulative fatigue in these employees.

A total of 4 066 employees of a petrochemical enterprise in Jiangsu province were selected by cluster sampling for a cross-sectional study from July to October 2021. A web-based questionnaire was designed to investigate the general information, work conditions, occupational stress, and prevalence of cumulative fatigue among employees. SPSS 23.0 was used to analyze the influencing factors of cumulative fatigue among petrochemical employees through non-parametric tests. BP-ANN and logistic regression models were established and receiver operating characteristic (ROC) curves were plotted to compare the prediction performance of models based on sensitivity, specificity, Youden index, and area under the curve (AUC) value.

A total of 3 763 valid questionnaires were collected, which showed that 63.2% (2 377/3 763) of petrochemical employees experienced cumulative fatigue. The comprehensive analysis of the two models indicated that age, weekly working hours, shift work, occupational stress, and regular exercise were the key factors influencing employees’ cumulative fatigue. Both models had AUC values > 0.7. Sensitivity was comparable between the BP-ANN and logistic models (BP 75.7%, logistic 75.6%). The BP-ANN model achieved higher specificity (BP 76.3%, logistic 69.3%), Youden index (BP 51.9%, logistic 44.9%), and AUC value (BP 84.4%, logistic 79.9%) than the logistic model. Both models can be used to predict the incidence of cumulative fatigue among petrochemical employees, while the overall prediction performance of the BP-ANN model was superior to that of the logistic model.

Both BP-ANN and logistic regression models can be adopted to predict cumulative fatigue among petrochemical employees, with the BP-ANN model showing better prediction performance.

To evaluate the effectiveness of a community-based management intervention based on the Information-Motivation-Behavioral Skills (IMB) model in ameliorating non-alcoholic fatty liver disease (NAFLD), providing a reference for exploring the health management pathways for NAFLD in primary health service centers.

Between January and April 2023, 714 NAFLD patients aged 50–69 years and diagnosed during physical examinations were recruited from the Community Health Service Center of Dongzha Street in Jiaxing, Zhejiang. The participants were randomly allocated into a control group (n = 357) and an intervention group (n = 357). The control group received health education manuals, while the intervention group additional received a comprehensive lifestyle intervention based on the IMB model. The controlled attenuation parameter (CAP), liver stiffness measurement (LSM), body weight, body mass index (BMI), waist circumference, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and fasting blood glucose (GLU) were compared between the two groups before and after the 1-year intervention.

The CAP, LSM, body weight, BMI, waist circumference, TC, TG, LDL-C, HDL-C, AST, ALT, and GLU in the control and intervention groups before intervention were (280.75 ± 35.45) and (287.07 ± 37.81) dB/m, (5.83 ± 2.00) and (5.66 ± 1.86) kPa, (67.85 ± 9.90) and (67.64 ± 9.61) kg, (25.99 ± 2.88) and (26.22 ± 2.98), (89.27 ± 8.12) and (88.85 ± 7.98) cm, (5.10 ± 0.97) and (5.18 ± 1.08) mmol/L, (2.35 ± 1.58) and (2.44 ± 2.45) mmol/L, (2.83 ± 0.73) and (2.88 ± 0.77) mmol/L, (1.28 ± 0.33) and (1.28 ± 0.33) mmol/L, (24.31 ± 9.39) and (24.88 ± 9.38) U/L, (26.47 ± 17.68) and (26.84 ± 15.04) U/L, and (6.29 ± 1.84) and (6.40 ± 2.27) mmol/L, respectively. After intervention, the values were (277.06 ± 43.59) and (265.34 ± 41.39) dB/m, (5.57 ± 1.76) and (5.30±1.75) kPa, (66.05 ± 9.79) and (64.11 ± 10.11) kg, (25.38 ± 2.91) and (25.10 ± 3.03), (88.01 ± 8.06) and (85.30 ± 8.93) cm, (5.17 ± 1.17) and (5.01 ± 1.08) mmol/L, (2.26 ± 1.90) and (1.98 ± 1.48) mmol/L, (2.97 ± 0.80) and (2.89 ± 0.79) mmol/L, (1.38 ± 0.34) and (1.44 ± 0.33) mmol/L, (22.80 ± 8.39) and (22.25 ± 6.74) U/L, (24.87 ± 13.52) and (23.85 ± 13.05) U/L, (6.21 ± 1.61) and (5.98 ± 1.51) mmol/L respectively. The control group of NAFLD patients showed differences in LSM, body weight, BMI, waist circumference, LDL-C, HDL-C, AST, and ALT before and after intervention (all P < 0.05). The intervention group of NAFLD patients showed differences in CAP, LSM, body weight, BMI, waist circumference, TC, TG, HDL-C, AST, ALT, and GLU before and after intervention (all P < 0.01). Before intervention, the two groups showed differences in CAP (t = −2.214, P = 0.027). After intervention, the two groups of NAFLD patients showed differences in CAP, body weight, waist circumference, TG, and HDL-C (all P < 0.05).

The community-based management intervention based on the IMB model effectively reduced hepatic steatosis, body weight, and waist circumference and recovered serum levels of lipids such as TG and HDL-C in NAFLD patients.

To investigate the willingness of middle-aged and elderly men in rural Sichuan province to undergo human immunodeficiency virus (HIV) testing and its associated factors, providing references for promoting voluntary testing.

A face-to-face questionnaire survey was conducted among 990 middle-aged and elderly men in rural Sichuan from July to August 2023. The data on demographic characteristics, HIV testing willingness, and HIV prevention protection motivation were collected. LASSO and Boruta methods were used to screen relevant variables. An XGBoost model was employed to predict HIV testing willingness, with SHapley Additive exPlanations (SHAP) for importance and interaction analyses.

The middle-aged and elderly men in rural Sichuan showed the HIV testing willingness rate of 53.13% and the HIV knowledge awareness rate of 35.56%. Among them, 62.02% held an attitude of relative stigma toward AIDS, and 6.36% had previously undergone HIV testing. Lasso and Boruta identified 10 key variables from 22 independent variable candidates. The XGBoost model achieved an area under the curve (AUC) value of 0.979 (95%CI: 0.963–0.995). SHAP importance analysis revealed the top five factors derived from protection motivation theory dimensions. The HIV testing willingness was positively associated with testing self-efficacy (SAV = 3.08), social support (SAV = 0.29), and awareness of HIV-related services (SAV = 0.27), and negatively associated with behavioral costs (SAV = 0.22) and external rewards (SAV = 0.20). Factors such as unmarried status, lack of HIV knowledge, and previous experience of HIV testing were primarily associated with willingness, while 45–49 years and high school/vocational school or above were mainly associated with unwillingness.

Middle-aged and elderly men in rural Sichuan exhibit low willingness to undergo HIV testing, which is primarily associated with insufficient HIV knowledge, inadequate social support, and prevalent AIDS-related stigma. Enhancing the awareness of testing experiences may encourage testing uptake.