Objectives Examination of the prevalence, influence factors and patterns of multimorbidity among the elderly people in Guangzhou, China. Design Cross-sectional study. Participants 31 708 community-dwelling elderly people aged 65 and over. Primary and secondary outcome measures Prevalence, influence factors and patterns of multimorbidity in seven chronic conditions among the participants. A multistage, stratified random sampling was adopted for selection of health records in the residents’ health records system of Guangzhou. Data mining by association rule mining analysis was used to explore the correlations and multimorbidity patterns between seven chronic diseases. Results The prevalence of morbidity was 55.0% (95% CI 40.1% to 60.1%) and the multimorbidity was 15.2% (95% CI 12.4% to 18.4%) among the participants. Elderly, women, higher education level, being single, living in urban areas and having medical insurance were more likely to have chronic diseases and multimorbidity. Data mining by association rule mining analysis reveals patterns of multimorbidity among the participants, including coexistence of hypertension and diabetes (support: 12.5%, confidence: 17.6%), hypertension and coronary heart disease (support: 4.4%, confidence: 5.7%), diabetes and coronary heart disease (support: 1.6%, confidence: 5.7%), diabetes, coronary heart disease and hypertension (support: 1.4%, confidence: 4.4%). Conclusions A high prevalence of morbidity (especially on hypertension and diabetes) and a relatively low multimorbidity of chronic diseases exist in elderly people. Data mining of residents’ health records will help for strengthening the management of residents’ health records in community health service centres of Guangzhou, China.

Introduction: As a developing country with the largest older adult population in the world, strengthening the research on falls among the older adults is undoubtedly an urgent item in China. This study aimed to explore the prevalence and risk factors associated with falls and injury from falls among community-dwelling older adults in Guangzhou, China, particularly focusing on their associations with chronic diseases.Methods: A total of 1,629 participants aged 65 years and above were selected from 11 counties in Guangzhou by the multi-stage stratified random sampling method in 2021. Socio-demographic characteristics, health and lifestyle factors, the status of falls, and injury from falls were measured by structured questionnaires through face-to-face interviews. Chi-square tests and logistic regression analysis were used to identify factors associated with falls and injury from falls. Chord diagrams were used to explore their associations with chronic diseases.Results: A total of 251 participants (15.41%, 95% CI: 13.98%−17.25%) reported falls, and 162 participants (9.46%, 95% CI:7.72%−11.55%) indicated an injury from falls. Logistic regression analysis showed the results as follows: female patients (adjusted OR = 1.721, 95% CI: 1.681–1.761) aged ≥80 years (1.910, 1.847–1.975), unemployed (1.226, 1.171–1.284), uninsured (1.555, 1.448–1.671), average monthly household income of 2,001–4,000 CNY (1.878, 1.827–1.930), number of services provided by the community health center ≥13 times per year (1.428, 1.383–1.475), illness within 2 weeks (1.633, 1.595–1.672), high-intensity physical activity (2.254, 2.191–2.32), sedentary (1.094, 1.070–1.117), and number of chronic disease illnesses ≥3 (1.930, 1.870–1.993). Meanwhile, those risk factors were also associated with injury from falls. The older adults with medium-intensity physical activity were at lower risk (0.721, 0.705–0.737) of falls and higher risk (1.086, 1.057–1.117) of being injured from falls. Chord diagrams showed the correlations between chronic diseases and falls and injury from falls among community-dwelling older adults in Guangzhou, China.Conclusion: The high prevalence of falls is found among community-dwelling older adults in Guangzhou, China, which is related to multiple factors such as demographic variables, lifestyle, and health status, especially for chronic diseases. Therefore, targeted interventions should be developed and implemented urgently.

Multimorbidity, individuals suffering from two or more chronic diseases, has become a major health challenge worldwide, especially in populous and prosperous cities, where studies of this phenomenon in China are limited. We examined the prevalence, trends, patterns, and associated factors of multimorbidity from 2009 to 2018 among community-dwelling adults in Guangzhou, China. We conducted serial cross-sectional surveys for chronic diseases in Guangzhou, China, in 2009, 2013, and 2018. General and stratified prevalence were standardized using demographic data. Multivariable logistic regression and hierarchical cluster analysis were applied to identify associated factors and to assess the correlations and patterns of multimorbidity, respectively. This study included 23,284 adults aged 18 and over in 2009, 18,551 in 2013, and 15,727 in 2018. The standardized prevalence of multimorbidity increased substantially, with 12.69% (95% CI: 10.45-15.33) in 2009, 25.44% (95% CI: 23.47-27.52) in 2013, and 35.13% (95% CI:32.64-37.70) in 2018 (P for trend <0.001). The highest bi- and triple-conditions of multimorbidity were dyslipidemia (DP) and overweight or obesity (OO) (12.54%, 95% CI: 11.68-13.46), and DP, OO, and Hypertension (HT) (3.99%, 95% CI: 3.47-4.58) in 2018. From 2009 to 2018, (1) The majority of multimorbidity patterns showed a high prevalence; (2) The percentage of participants with only one chronic condition was found lower, while the percentage with multiple conditions was higher. The prevalence of chronic disease multimorbidity in Guangzhou China, has increased substantially among adults. Effective policies targeting multimorbidity are urgently needed, especially for the health management of primary medical institutions.

Several studies have demonstrated that older adults with type 2 diabetes mellitus (T2DM) have a higher risk of falls compared to those without T2DM, which may lead to disability and a lower quality of life. While, limited prospective studies have quantified the associations in southern China. We conducted a longitudinal cohort study to quantify the associations between T2DM and falls and investigate the risk factors of falls among community-dwelling elderly people in Guangzhou, China. The population-based study included 8800 residents aged 65 and over in 11 counties of Guangzhou at baseline in 2020 and then prospectively followed up through 2022. Of 6169 participants had complete follow-up and were included in the present study. A fall event was identified by self-reported. The Cox regression was applied to quantify the associations between T2DM and falls, and hazard ratios (HRs) were calculated to the factors associated with falls among participants. The median follow-up time for participants was 2.42 years. During the follow-up period, the incidence of falls among all participants was 21.96%. After adjusting for covariates in Cox regression models, T2DM remained a significant risk factor for falls, with HR of 1.781 (95% CI: 1.600-1.983) in the unadjusted covariates model and 1.757 (1.577–1.957) in the adjusted covariates model. Female (1.286, 1.136–1.457), older age (≥ 80: 1.448, 1.214–1.729), single marital status (1.239, 1.039–1.477), lower education level (primary school and below: 1.619, 1.004–1.361), hypertension (1.149, 1.026–1.286) and stroke (1.619, 1.176–2.228) were associated with a higher risk of falls, whereas everyday physical exercise (0.793, 0.686–0.918) was associated with a lower risk of falls. Falls are common, with risks between T2DM and falls quantified and several factors investigated in the longitudinal cohort study among community-dwelling elderly people in Guangzhou, China. Targeted action on the risk factors may reduce the burden of falls in elderly people with T2DM in the future.

With rapid increase in the aging population, falls injuries have become an important public health problem. However, limited data have been reported on the associations between meteorological factors and falls injuries in the elderly. This study assessed the epidemiology of falls injuries and explored this association in the elderly in Guangzhou, China. Data on elderly falls injury cases and meteorological variables from 2014 to 2018 in Guangzhou were collected from the Guangzhou Injury Monitoring System and Guangzhou Meteorological Bureau, respectively. The monthly average data on falls injuries and meteorological factors were applied to the data analysis. These correlations were conducted using Pearson correlation analysis. A multiple linear regression model was used to estimate the effects of meteorological factors on falls injuries in the elderly in Guangzhou, China. Accounting for 49.41% of causes of elderly injury were falls in the Guangzhou Injury Monitoring System from 2014 to 2018, which occupied first place for five consecutive years. The monthly number of elderly falls injury cases was lowest in April and highest in December, and had a positive correlation with monthly mean wind speed (r = 0.187, P < 0.01) and a negative correlation with monthly atmospheric pressure (r = -0.142, P < 0.05). A multiple linear regression model was constructed (F = 10.176, P < 0.01), which explained 23.7% of the variances (R² = 0.237). Monthly mean wind speed (β = 76.85, P < 0.01) and monthly mean atmospheric pressure (β = −3.162, P < 0.01) were independent factors affecting monthly elderly falls injuries. Falls are the primary cause of injury among elderly people in Guangzhou, China. Meteorological factors are related to falls injuries in the elderly population. Decreasing activity during high wind and low atmospheric pressure weather may help reduce the number of elderly falls injury cases.