Urban-Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression

Prevalence of Multimorbidity Among School-Aged Children in the Yangzhou District of China

Background: Health issues among school-age children have emerged as a global public health concern. These conditions often do not occur in isolation but tend to cluster, indicating a widespread issue of multimorbidity among this population. This study examined the prevalence and clustering of multimorbidity among school-aged school students in the Yangzhou district. Methods: A repeated cross-sectional analysis was conducted from 2019 to 2024, including 22,512 students aged 6-18 years. Common diseases, under national key monitoring, including myopia, dental caries, obesity, elevated blood pressure, and growth disorders, were assessed. Multimorbidity patterns were identified using association rule mining (Apriori algorithm) with predefined thresholds (support ≥ 2.0%, confidence ≥ 20.0% and lift > 1). Results: The multimorbidity prevalence among school-age students in the Yangzhou district is 53.95%. The most frequent multimorbidity was found in dental caries and myopia, while the most common ternary pattern was found in obesity, dental caries, and myopia. The following gender differences were observed: boys had a higher multimorbidity prevalence (56.4%) compared to girls (51.2%), with boys more likely to exhibit obesity and dental caries, while girls showed a higher prevalence of myopia-related multimorbidity. By educational stage, primary school students showed a multimorbidity rate of 50.3%, junior high showed a rate of 54.6%, and senior high showed a rate of 57.9%, indicating a rising trend across age groups. Patterns of multimorbidity varied but were interrelated. Conclusions: From 2019 to 2024, the prevalence of multimorbidity among school-aged children in Yangzhou remained relatively high, primarily manifesting as co-occurring myopia and other health issues. Patterns of multimorbidity across gender and educational stage varied but were interrelated.

Prevalence of multimorbidity among urban-rural older adults in Mongolia: a cross-sectional study

BACKGROUND

Multimorbidity presents medical challenges, incurs high medical costs, burdens the economy, and increases mortality risk among adults. Despite its impact, recent surveys identifying risk factors for multimorbidity and its association with quality of life in Mongolia are lacking. This study aimed to investigate the prevalence of multimorbidity and its risk factors for multimorbidity among older adults (aged sixty years and above) in urban and rural areas in Mongolia.

METHODS

A face-to-face, questionnaire-based cross-sectional study was conducted with 720 valid participants aged ≥ 60 years in Mongolia from June to September 2023.

RESULTS

The study revealed that (1) the prevalence of multimorbidity among older adults was 66.94%, with 51.87% of rural respondents and 48.13% of urban respondents affected; (2) the multimorbidity rate was significantly higher among low-income older adults (80.68%) than among middle-income older adults (58.24%), with a significant difference (χ² = 35.94, P < 0.001); (3) the multimorbidity rates were 4.72% for two chronic diseases, 12.50% for three, 15.42% for four, and 10.83% for five chronic diseases; and (4) seven patterns of multimorbidity associated with rheumatoid arthritis were identified in rural older adults, whereas six patterns related to hypertension were observed in urban older adults.

CONCLUSION

The prevalence of multimorbidity is notably high among older adults in both rural and urban Mongolia, with distinct differences in chronic disease patterns and risk factors. The implementation of systemic transformations may help reduce multimorbidity rates and increase the overall health of older adults across various settings.

Advanced applications in chronic disease monitoring using IoT mobile sensing device data, machine learning algorithms and frame theory: a systematic review

The escalating demand for chronic disease management has presented substantial challenges to traditional methods. However, the emergence of Internet of Things (IoT) and artificial intelligence (AI) technologies offers a potential resolution by facilitating more precise chronic disease management through data-driven strategies. This review concentrates on the utilization of IoT mobile sensing devices in managing major chronic diseases such as cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes. It scrutinizes their efficacy in disease diagnosis and management when integrated with machine learning algorithms, such as ANN, SVM, RF, and deep learning models. Through an exhaustive literature review, this study dissects how these technologies aid in risk assessment, personalized treatment planning, and disease management. This research addresses a gap in the existing literature concerning the application of IoT and AI technologies in the management of specific chronic diseases. It particularly demonstrates methodological novelty by introducing advanced models based on deep learning, tight frame-based methodologies and real-time monitoring systems. This review employs a rigorous examination method, which includes systematically searching relevant databases, filtering literature that meets specific inclusion and exclusion criteria, and adopting quality assessment tools to ensure the rigor of selected studies. This study identifies potential biases and weaknesses related to data collection, algorithm selection, and user interaction. The research demonstrates that platforms integrating IoT and machine learning algorithms for chronic disease monitoring and management are not only technically viable but also yield substantial economic and social advantages in real-world applications. Future studies could investigate the use of quantum computing for processing vast medical datasets and novel techniques that merge biosensors with nanotechnology for drug delivery and disease surveillance. Furthermore, this paper examines recent progress in medical image reconstruction, emphasizing tight frame-based methodologies. We discuss the principles, benefits, and constraints of these methods, assessing their efficacy across diverse application contexts.

Multimorbidity patterns and influencing factors in older Chinese adults: a national population-based cross-sectional survey

Background

This study aims to develop specific multimorbidity relationships among the elderly and to explore the association of multidimensional factors with these relationships, thereby facilitating the formulation of personalised strategies for multimorbidity management.

Methods

Cluster analysis identified chronic conditions that tend to cluster together, and then association rule mining was used to investigate relationships within these identified clusters more closely. Stepwise logistic regression analysis was conducted to explore the relationship between influencing factors and different health statuses in older adults. The results of this study were presented by network graph visualisation.

Results

A total of 15 045 individuals were included in this study. The average age was 73.0 ± 6.8 years. The number of patients with multimorbidity was 7426 (49.4%). The most common binary disease combination was hypertension and depression. The four major multimorbidity clusters identified were the tumour-digestive disease cluster, the metabolic-circulatory disease cluster, the metal-psychological disease cluster, and the age-related degenerative disease cluster. Cluster analysis by sex and region revealed similar numbers and types of conditions in each cluster, with some variations. Gender and number of medications had a consistent effect across all disease clusters, while aging, body mass index (BMI), waist-to-hip ratio (WHR), cognitive impairment, plant-based foods, animal-based foods, highly processed foods and marital status had varying effects across different disease clusters.

Conclusions

Multimorbidity is highly prevalent in the older population. The impact of lifestyle varies between different clusters of multimorbidity, and there is a need to implement different strategies according to different clusters of multimorbidity rather than an integrated approach to multimorbidity management.

Fracture risk prediction & kidney function at different stages of chronic kidney disease: A correlation study

Background & objectives Mineral bone disease commonly occurs in individuals with chronic kidney disease (CKD) and increases fracture risk due to deficiency in bone quality and quantity. The FRAX score attempts to estimate fracture risk better. The primary aim of this study was to evaluate the prediction and correlation of fracture risk with different stages of CKD. Methods This was a correlational study. Data were collected from 95 individuals at different stages of CKD using non-probability consecutive sampling. The clinical and laboratory parameters were compared with the FRAX score in all CKD patients. Results A total of 95 CKD patients with a mean age of 51.42±9.95 yr were selected. Of these, 66.3 per cent between 40-55 yr, 25.3 per cent were 56-70 yr, and 8.4 per cent were ≥70 yr. There were 62 (65.3%) males and 33 (34.7%) females, and more than half (60%) were from rural areas. Age (P<0.001), occupation (P<0.005), and area of residence (P<0.003) showed a significant association with the FRAX score for major osteoporotic fracture risk. The FRAX score for predicting hip fracture risk showed a significant association with factors such as age, occupation, and area of residence, with P values of <0.001, 0.003, and 0.031, respectively. Additionally, the FRAX score for assessing the risk of major osteoporotic fractures demonstrated a significant association with various stages of CKD (P=0.018). Similarly, for hip fracture, there was a significant increase in the risk between stage III and V CKD patients (P=0.038). Interpretation & conclusions Based on the study findings it was found that the FRAX score was significantly associated with different stages of CKD, both for major osteoporotic as well as hip fracture risk.

Health insurance and clinical outcomes in patients with chronic heart failure in Latin America: an observational study of the Colombian Heart Failure Registry (RECOLFACA)

The effect of the health insurance type on the prognosis of heart failure (HF) patients in Colombia and Latin America is poorly known. We aimed to analyze the characteristics of HF patients that participated in the Colombian Heart Failure Registry (RECOLFACA) as stated by their health insurance type and their relationship with the immediate prognosis of these patients. Patients with HF diagnosis were included in the RECOLFACA registry between 2017-2019. The registry was conducted in 60 centers in Colombia. All-cause mortality was the principal outcome. To evaluate the impact of health insurance on mortality, a Cox proportional hazards regression model was used. The Kaplan-Meier analysis was performed to compare survival probabilities according to insurance type. All statistical analyses were two-tailed and were considered significant with a p value < 0.05. Of the 2,528 participants enrolled in the registry, 99% held details about their health insurance. Of those, 897 patients (35.6%) were covered by public insurance. These patients were significantly younger, with a lower proportion of men, more frequently from rural origin, and lower prevalence of most comorbidities (omitting hypertension, chronic obstructive pulmonary disease (COPD), and Chagas disease) than those with private insurance. Furthermore, patients with public insurance had a worse functional class, as well as a poorer quality of life, and lower frequency of use of implantable devices, while exhibiting similar prescription rates of triple medical therapy for HF. Finally, no differences in short-term mortality were observed between the two groups (HR 1.09; 95% CI 0.79, 1.51). The type of health insurance represents a condition related with relevant differences in the profile of patients with HF in Colombia. Despite this, no significant differences were detected in the short-term prognosis of these patients based on the type of health insurance.

Does high-frequency resistance exercise offer additional benefits to older adults? learnings from a randomized controlled trial

OBJECTIVE

Resistance exercise is an effective strategy to improve muscle strength in older adults. A limited-load resistance would be flexible and suitable for community-based training. It was unclear whether high-frequency resistance exercise offer additional benefits to older adults. Here, we aimed to examine the effect of limited-load resistance exercise among different frequency on muscle parameters in older adults.

METHODS

The current study was a single-blind, randomized controlled trial comparing the effectiveness of different-frequency resistance exercise in older adults. Change in skeletal muscle was estimated with a multi-frequency bioelectrical impedance analyzer. Demographics, physical examination, nutritional assessment, prealbumin and lymphocytes were also measured. Fisher's precision probability test and baseline-adjusted generalized linear models were applied accordingly to analyze the influence of dose-different exercise on prevalence of sarcopenia, muscle parameters and body composition. A two-sided p value of < 0.05 was defined statistical significance.

RESULTS

The participants had a mean age of 71.96 years and close gender ratio. One hundred and twenty-seven participants (control 40; low-dose 46; high-dose 41) completed the 6-month exercise intervention. In contrast to control group, only high-dose exercise groups experienced improvements in muscle mass (0.66 kg, p < 0.001) and max grip strength (+ 2.17 kg, p < 0.001). There were significant dose-response effects of muscle mass (index), fat mass (index), max grip strength, 5-times sit to stand test, 6-minute walking test and visceral fat area (all ptrend <0.01).

CONCLUSIONS

As the proved dose-dependent effect, current findings supported high-frequency limited-load resistance exercise applied and extended among older adults in community.

TRIAL REGISTRATION

This study was registered at Chinese Clinical Trial Registry Network (ChiCTR2200062007, Registered on 19 July 2022).

Multimorbidity, cognitive phenotypes, and Alzheimer's disease plasma biomarkers in older adults: A population-based study

INTRODUCTION

To examine the burden and clusters of multimorbidity in association with mild cognitive impairment (MCI), dementia, and Alzheimer's disease (AD)-related plasma biomarkers among older adults.

METHODS

This population-based study included 5432 participants (age ≥60 years); of these, plasma amyloid beta (Aβ), total tau, and neurofilament light chain (NfL) were measured in a subsample (n = 1412). We used hierarchical clustering to generate five multimorbidity clusters from 23 chronic diseases. We diagnosed dementia and MCI following international criteria. Data were analyzed using logistic and linear regression models.

RESULTS

The number of chronic diseases was associated with dementia (multivariable-adjusted odds ratio = 1.22; 95% confidence interval [CI] = 1.11 to 1.33), AD (1.13; 1.01 to 1.26), vascular dementia (VaD) (1.44; 1.25 to 1.64), and non-amnestic MCI (1.25; 1.13 to 1.37). Metabolic cluster was associated with VaD and non-amnestic MCI, whereas degenerative ocular cluster was associated with AD (p < 0.05). The number of chronic diseases was associated with increased plasma Aβ and NfL (p < 0.05).

DISCUSSION

Multimorbidity burden and clusters are differentially associated with subtypes of dementia and MCI and AD-related plasma biomarkers in older adults.

HIGHLIGHTS

We used hierarchical clustering to generate five clusters of multimorbidity. The presence and load of multimorbidity were associated with dementia and mild cognitive impairment. Multimorbidity clusters were differentially associated with subtypes of dementia and Alzheimer's disease plasma biomarkers.

Urban-rural differences in associations among perceived stress, resilience and self-care in Chinese older adults with multiple chronic conditions

BACKGROUND

Social determinants of health (SDH) are mainly comprised of structural and intermediary domains. Emerging evidence suggests that the burden of multiple chronic conditions (MCCs) in older adults is exacerbated by structural determinants (e.g. low income and low education). However, less attention was paid to the intermediary determinants (i.e. material circumstances, psychosocial factors and behavioural factors) of MCCs.

OBJECTIVES

To investigate the associations among perceived stress, resilience and self-care in Chinese older adults with MCCs by comparing urban and rural groups.

METHODS

A convenience sample (125 and 115 participants from urban and rural settings, respectively) of Chinese older adults with MCCs was enrolled between January and April 2022. Hierarchical multiple regression analyses and propensity score weights were used to determine the associations among perceived stress, resilience and self-care.

RESULTS

Hypothesis 1 regarding the negative associations between perceived stress and self-care was fully supported in the rural group. However, for the urban group, the negative association was only supported for the relationship between MCCs-related perceived stress and self-care maintenance. Hypothesis 2 was fully supported regarding the positive associations between resilience and the three components of self-care in both groups, although the relationship between resilience and self-care monitoring was marginally significant in the urban group. Hypothesis 3 regarding the moderating effect of resilience was only supported in the relationship between general perceived stress and self-care monitoring in the rural group. After adding the propensity score weights, the moderating effect was no longer statistically significant in the rural group.

CONCLUSIONS

The urban-rural disparities in the Chinese context might largely be attributed to the complex interactions of the structural determinants and intermediary determinants. Findings can inform the development of culturally tailored interventions to promote self-care and reduce urban-rural disparities for Chinese older adults with MCCs.

IMPLICATIONS FOR PRACTICE

With the increasing number of older adults in China who are living with multiple chronic conditions and the call for effective interventions to improve their health outcomes, current findings can inform the development and implementation of nurse-led culturally tailored interventions to promote self-care and reduce urban-rural disparities for Chinese older adults with MCCs.

Differences in the influence of daily behavior on health among older adults in urban and rural areas: evidence from China

Background

As the population of older adult in China keeps growing, the degree of aging is becoming increasingly serious and the health of older adults is a growing concern. Comparing the personal characteristics and health levels of urban and rural older adults and determining the relationship between these factors are of great significance in maintaining their health. In addition, exploring how these relationships differ between urban and rural areas is important.

Method

This study conducted a literature review to examine the impact of various factors on the physical and mental health of older adults in urban and rural areas in China. Moreover, based on cross-sectional data from the 2017 Chinese General Social Survey (CGSS), urban-rural differences in the factors' degree of influence on the perceived health of older adults were studied using multiple logistic regression.

Results

Regular physical exercise had a powerful protective effect on urban older adults' physical and mental health, whereas regular participation in social activities had a positive impact on rural older adults' health. Low income, low educational level, low social trust, lack of a partner, and having more than one child negatively affected the physical health of rural older people. Low socioeconomic status had a negative impact on rural people's health both in mind and body. Overall, the rural adults' health status was found to be relatively low and deserves more attention.

Conclusion

This study demonstrated that older people's physical and mental health levels can be significantly affected by the frequency of daily activities and individual and family characteristics. Furthermore, urban-rural differences were observed. These findings could provide feasible suggestions for governments, communities, and older adults' family members to help alleviate health inequality.

Ethnic disparities in prevalence of chronic non-communicable diseases and its multimorbidity among older adults in rural southwest China

BACKGROUND

As the population ages, chronic non-communicable diseases (NCDs) multimorbidity has emerged as a major public health issue globally. This study examines ethnic disparities in prevalence of NCDs and its multimorbidity among rural southwest Chinese older adults.

METHODS

A cross-sectional survey was conducted in rural southwest population aged ≥ 60 years consisting of 5,642 consenting participants of Han and three ethnic minority groups (Dai, Ha Ni, and Bai). Information about participants' demographic characteristics and lifestyle behaviors was obtained using a standard questionnaire. Anthropometric measurements including height, weight, and waist circumference, fasting blood sugar and blood pressure measurement, as well as post-bronchodilator spirometry test were recorded for each participant.

RESULTS

The age-standardized prevalence of five common chronic NCDs- hypertension, diabetes, coronary heart disease (CHD), stroke, chronic obstructive pulmonary disease (COPD) - and its multimorbidity was 72.8%, 15.9%, 4.0%, 10.0%, 9.8%, and 27.6%, respectively. Bai participants had both the highest overall and sex-specific prevalence rates of hypertension, diabetes, stroke, and COPD, whereas Han participants had the highest rates of CHD (P < 0.01). The results of multivariate logistic regression analysis indicated that female and older participants had a higher probability of chronic NCDs multimorbidity than their counterparts (P < 0.01). Bai ethnic minority participants were more likely to have NCDs multimorbidity while Ha Ni and Dai ethnic minority participants were less likely to have NCD multimorbidity relative to the Han participants (P < 0.05). Older adults with a higher level of education and family history of chronic NCDs, and who were also current smokers, current drinkers, obese, centrally obese, and physically inactive had a greater probability of developing chronic NCDs multimorbidity (P < 0.01).

CONCLUSIONS

Ethnicity and individual demographic and lifestyle factors significantly impact prevalence of chronic NCDs multimorbidity. Future chronic NCDs prevention and control strategies must be tailored to address ethnicity, and culturally tailored lifestyle interventions may reduce the prevalence of chronic NCDs multimorbidity in rural southwest China.

Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis

BACKGROUND

Knowing the prevalence of multimorbidity among adults across continents is a crucial piece of information for achieving Sustainable Development Goal 3.4, which calls for reducing premature death due to non-communicable diseases. A high prevalence of multimorbidity indicates high mortality and increased healthcare utilization. We aimed to understand the prevalence of multimorbidity across WHO geographic regions among adults.

METHODS

We performed a systematic review and meta-analysis of surveys designed to estimate the prevalence of multimorbidity among adults in community settings. We searched PubMed, ScienceDirect, Embase and Google Scholar databases for studies published between January 1, 2000, and December 31, 2021. The random-effects model estimated the pooled proportion of multimorbidity in adults. Heterogeneity was quantified using I² statistics. We performed subgroup analyses and sensitivity analyses based on continents, age, gender, multimorbidity definition, study periods and sample size. The study protocol was registered with PROSPERO (CRD42020150945).

FINDINGS

We analyzed data from 126 peer-reviewed studies that included nearly 15.4 million people (32.1% were male) with a weighted mean age of 56.94 years (standard deviation of 10.84 years) from 54 countries around the world. The overall global prevalence of multimorbidity was 37.2% (95% CI = 34.9-39.4%). South America (45.7%, 95% CI = 39.0-52.5) had the highest prevalence of multimorbidity, followed by North America (43.1%, 95% CI = 32.3-53.8%), Europe (39.2%, 95% CI = 33.2-45.2%), and Asia (35%, 95% CI = 31.4-38.5%). The subgroup study highlights that multimorbidity is more prevalent in females (39.4%, 95% CI = 36.4-42.4%) than males (32.8%, 95% CI = 30.0-35.6%). More than half of the adult population worldwide above 60 years of age had multimorbid conditions (51.0%, 95% CI = 44.1-58.0%). Multimorbidity has become increasingly prevalent in the last two decades, while the prevalence appears to have stayed stable in the recent decade among adults globally.

INTERPRETATION

The multimorbidity patterns by geographic regions, time, age, and gender suggest noticeable demographic and regional differences in the burden of multimorbidity. According to insights about prevalence among adults, priority is required for effective and integrative interventions for older adults from South America, Europe, and North America. A high prevalence of multimorbidity among adults from South America suggests immediate interventions are needed to reduce the burden of morbidity. Furthermore, the high prevalence trend in the last two decades indicates that the global burden of multimorbidity continues at the same pace. The low prevalence in Africa suggests that there may be many undiagnosed chronic illness patients in Africa.

FUNDING

None.

Multimorbidity and Sleep Patterns among Adults in a Peruvian Semi-Urban Area

Objective  To assess if the duration and quality of sleep vary due to the presence of multimorbidity. Materials and Methods  We performed a secondary analysis using data from a population-based study involving adult subjects aged between 30 and 69 years residing in a semi-urban area of Tumbes, Peru. The duration (normal, short or prolonged) and quality (good or poor) of sleep were our outcome variables, whereas the exposure was multimorbidity (two or more chronic conditions). Crude and adjusted Poisson regression models were built to assess the association of interest, and prevalence ratios (PRs) and 95% confidence intervals (95%CIs) were reported. Results  We analyzed data from 1,607 subjects with a mean age of 48.2 (standard deviation [SD]: ± 10.6) years, 809 (50.3%) of whom were women. Multimorbidity was present in 634 (39.5%; 95%CI: 37.1-41.9%) subjects, and 193 (12.1%; 95%CI: 10.5-13.7%) were short sleepers, 131 (8.2%; 95%CI: 6.9-9.6%) were long sleepers, and 312 (19.5%; 95%CI: 17.5-21.5%) had poor sleep quality. In the multivariable model, multimorbidity was associated with prolonged sleep duration (PR = 1.45; 95%CI: 1.03-2.04) and poor sleep quality (PR = 2.04; 95%CI: 1.65-2.52). Conclusions  Multimorbidity was associated with prolonged, but not short, sleep duration, as well as with poor sleep quality. Our results suggest the need of assessing sleep patterns among adults with multimorbidity.

Gender and Socioeconomic Differences in the Prevalence and Patterns of Multimorbidity among Middle-Aged and Older Adults in China

BACKGROUND

Multimorbidity has become a global public health concern. Knowledge about the prevalence and patterns of multimorbidity will provide essential information for public intervention and clinical management. This study aimed to examine gender and socioeconomic differences in the prevalence and patterns of multimorbidity among a nationally representative sample of middle-aged and older Chinese individuals.

METHODS

Data were obtained from the 2018 wave of the China Health and Retirement Longitudinal Study. Latent class analysis was conducted to discriminate among the multimorbidity patterns. Multinomial logit analysis was performed to explore gender and socioeconomic factors associated with various multimorbidity patterns.

RESULTS

A total of 19,559 respondents over 45 years old were included in the study. The findings showed that 56.73% of the respondents reported multimorbidity, with significantly higher proportions among women. Four patterns, namely "relatively healthy class", "respiratory class", "stomach-arthritis class" and "vascular class", were identified. The women were more likely to be in the stomach-arthritis class. Respondents with a higher SES, including higher education, urban residence, higher consumption, and medical insurance, had a higher probability of being in the vascular class. Conclusions: Significant gender and socioeconomic differences were observed in the prevalence and patterns of multimorbidity. The examination of gender and socioeconomic differences for multimorbidity patterns has great implications for clinical practice and health policy. The results may provide insights to aid in the management of multimorbidity patients and improve health resource allocation.

Patterns and Determinants of Multimorbidity in Older Adults: Study in Health-Ecological Perspective

(1) Background: Multimorbidity has become one of the key issues in the public health sector. This study aims to explore the patterns and health-ecological factors of multimorbidity in China to propose policy recommendations for the management of chronic diseases in the elderly. (2) Methods: A multi-stage random sampling method was used to conduct a questionnaire survey on 3637 older adults aged 60 and older in Shanxi, China. Association rule mining analysis (ARM) and network analysis were applied to analyze the patterns of multimorbidity. The health-ecological model was adopted to explore the potential associated factors of multimorbidity in a multidimensional perspective. A hierarchical multiple logistic model was employed to investigate the association strengths reflected by adjusted odds ratios and 95% confidence. (3) Results: Multimorbidity occurred in 20.95% of the respondents. The graph of network analysis showed that there were 6 combinations of chronic diseases with strong association strengths and 14 with moderate association strengths. The results of the ARM were similar to the network analysis; six dyadic chronic disease combinations and six triadic ones were obtained. Hierarchical multiple logistic regression indicated that innate personal traits (age, history of genetics, and body mass index), behavioral lifestyle (physical activity levels and medication adherence), interpersonal network (marital status), and socioeconomic status (educational level) were the common predictors of multimorbidity for older adults, among which, having no family history was found to be a relative determinant as a protective factor for multimorbidity after controlling the other covariates. (4) Conclusions: multimorbidity was prevalent in older adults and most disease combinations are associated with hypertension, followed by diabetes. This shows that diabetes and hypertension have a high prevalence among older adults and have a wide range of associations with other chronic diseases. Exploring the patterns and associated factors of multimorbidity will help the country prevent complications and avoid the unnecessary use of the health service, adopting an integrated approach to managing multimorbidity rather than an individual disease-specific approach and implementing different strategies according to the location of residence.

Variance Analysis in China's Coal Mine Accident Studies Based on Data Mining

The risk of coal mine accidents rises significantly with mining depth, making it urgent for accident prevention to be supported by both scientific analysis and advanced technologies. Hence, a comprehensive grasp of the research progress and differences in hotspots of coal mine accidents in China serves as a guide to find the shortcomings of studies in the field, promote the effectiveness of coal mine disaster management, and enhance the prevention and control ability of coal mine accidents. This paper analyzes Chinese and foreign literature based on data mining algorithms (LSI + Apriori), and the findings indicate that: (1) 99% of the available achievements are published in Chinese or English-language journals, with the research history conforming to the stage of Chinese coal industry development, which is characterized by "statistical description, risk evaluation, mechanism research, and intelligent reasoning". (2) Chinese authors are the primary contributors that lead and contribute to the continued development of coal mine accident research in China globally. Over 81% of the authors and over 60% of the new authors annually are from China. (3) The emphasis of the Chinese and English studies is different. Specifically, the Chinese studies focus on the analysis of accident patterns and causes at the macroscale, while the English studies concentrate on the occupational injuries of miners at the small-scale and the mechanism of typical coal mine disasters (gas and coal spontaneous combustion). (4) The research process in Chinese is generally later than that in English due to the joint influence of the target audience, industrial policy, and scientific research evaluation system. After 2018, the Chinese studies focus significantly on AI technology in deep mining regarding accident rules, regional variation analysis, risk monitoring and early warning, as well as knowledge intelligence services, while the hotspots of English studies remain unchanged. Furthermore, both Chinese and English studies around 2019 focus on "public opinion", with Chinese ones focusing on serving the government to guide the correct direction of public opinion while English studies focus on critical research of news authenticity and China's safety strategy.

Psychological factors substantially contribute to biological aging: evidence from the aging rate in Chinese older adults

We have developed a deep learning aging clock using blood test data from the China Health and Retirement Longitudinal Study, which has a mean absolute error of 5.68 years. We used the aging clock to demonstrate the connection between the physical and psychological aspects of aging. The clock detects accelerated aging in people with heart, liver, and lung conditions. We demonstrate that psychological factors, such as feeling unhappy or being lonely, add up to 1.65 years to one's biological age, and the aggregate effect exceeds the effects of biological sex, living area, marital status, and smoking status. We conclude that the psychological component should not be ignored in aging studies due to its significant impact on biological age.

The impact of socioeconomic status and sleep quality on the prevalence of multimorbidity in older adults

Introduction

Multimorbidity has become a global public health concern that can cause serious damage to the health status of older adults. This study aimed to investigate the impact of socioeconomic status (SES) and sleep quality on the prevalence of multimorbidity in older adults, thus providing a reference for reducing the risk of the prevalence of multimorbidity and improving the health of older adults.

Methods

A multi-stage random sampling method was used to conduct a questionnaire survey on 3,250 older adults aged 60 years and above in Shanxi Province, China. The chi-square test and multiple logistic regression models were used to analyze the association of SES and sleep quality with the prevalence of multimorbidity of older adults.

Results

The prevalence of multimorbidity was 30.31% in older adults aged 60 years and above in Shanxi Province, China. After adjusting for confounders, very low SES (OR = 1.440, 95% CI: 1.083-1.913) and poor sleep quality (OR = 2.445, 95% CI: 2.043-2.927) were associated with the prevalence of multimorbidity. Older adults with low SES and poor sleep quality had the highest risk of the prevalence of multimorbidity (OR = 3.139, 95% CI: 2.288-4.307).

Conclusions

SES and sleep quality are associated with the prevalence of multimorbidity in older adults, and older adults with lower SES and poorer sleep quality are at higher risk for the prevalence of multimorbidity.

Work Content of General Practitioners in Beijing, China: A Multi-method Study

Background

Despite the dramatic growth of primary care in China, little evidence showed what general practitioner (GP) do and how GP provided medical service in Beijing.

Objective

This study aimed to explore the work content of GPs in primary care in Beijing.

Methods

A multi-method study was conducted in five community health service institutions using non-participant observation and critical incident technique interview. Eleven GPs was recruited by purpose sampling, with each GP recording details of 100 patient encounters. Health problems of patients and activities of GPs were observed in consultations. Then, critical incident technique interviews were conducted focusing on GPs' works out of clinics and challenge.

Results

A total of 1, 100 patients encounters and 1,897 reasons for encounter (RFEs) were recorded from 11 GPs. There were 1897 RFEs (1.72 per encounter) and 2,762 health problems (2.51 per encounter) from 1,100 encounters during our observation. GPs' work related to consultation was focus on disease diagnoses and treatment. Physical examination and investigations were performed in only 15.5 and 17.1% consultations, respectively. Procedures for chronic disease management were infrequently provided to patients (0.4–26.6%). Time spent in each work process in consultations ranged from 0.68 ± 0.27 min for reservation to 4.00 ± 2.45 min for surgical treatment. In addition to clinical work, there were tasks about health files, contracted family doctor services, health education, teaching students, and scientific research.

Conclusion

This study illustrated the complexity of GPs' work and heavy workload in Beijing, China. More attention and effort are needed to develop GPs performance and release GPs' work workload in primary care.

The association between sleep quality and psychological distress among older Chinese adults: a moderated mediation model

BACKGROUND

Previous research has found a link between sleep quality and psychological distress. However, the underlying mechanisms of this connection have still not been well explored. The aim of this study was to examine the roles of activities of daily living (ADL), physical activity, and perceived social support in the link between sleep quality and psychological distress among older adults.

METHODS

Three thousand two hundred fifty valid individuals (aged 60 years or above) participated in face-to-face questionnaire-based surveys. Older individuals were assessed using the Pittsburgh Sleep Quality Index, Barthel Index, International Physical Activity Questionnaire, Perceived Social Support Scale, and Depression Anxiety Stress Scale-21. The PROCESS macro developed by Hayes was used to conduct moderated mediation analysis.

RESULTS

In older adults, sleep quality had a substantial direct influence on psychological distress. ADL mediated the association between sleep quality and psychological distress. Physical activity significantly reduced ADL's mediating influence on the relationship between sleep quality and psychological distress. Furthermore, perceived social support moderated the direct relationship between sleep quality and psychological distress, as well as the second half of the mediating effect of the ADL. Moreover, physical activity and perceived social support were preventive factors that might successfully mitigate the detrimental effects of poor sleep quality on ADL and psychological distress.

CONCLUSIONS

The findings contribute to existing understanding by clarifying the fundamental mechanisms that link sleep quality and psychological distress. These results may provide a valuable reference to the Chinese government for improving mental health in older individuals.