Urban-rural differences in multimorbidity and associated factors in China and Korea: A population-based survey study

Socioeconomic disparities in the postnatal growth of preterm infants: a systematic review

OBJECTIVE

To determine the effect of parental socioeconomic status (SES) on the postnatal growth of preterm infants.

METHODS

A systematic review (PROSPERO registration CRD42020225714) of original articles from Medline, Embase, CINAHL Plus and Web of Science published 1946-2023 was undertaken. Studies were included if they reported anthropometric growth outcomes for preterm infants according to parental SES. Data extraction and assessments of bias and health equity impact were conducted using custom-designed forms.

RESULTS

A narrative synthesis of twelve included studies was performed. Most infants were moderate to late preterm. The settings, growth outcomes, timings of growth measurement, and SES measures were heterogenous. Six studies demonstrated an adverse effect of low parental SES on the extrauterine growth of preterm infants, five studies showed no effect, and one study showed a potentially beneficial effect. All studies had a high risk of bias, especially confounding and selection bias. The health equity impact of included studies was largely negative.

CONCLUSION

Limited and low-quality evidence suggests that socioeconomic minoritisation may adversely impact the growth of preterm infants, thereby widening existing socioeconomic health inequities. Observational studies informed by theorisation of the mechanistic pathways linking socioeconomic minoritisation to adverse postnatal growth are required to identify targets for intervention.

IMPACT

Limited evidence suggests low parental socioeconomic status (SES) adversely affects the postnatal growth of preterm infants across different settings. Early growth of preterm infants predicts neurodevelopmental outcomes and the risk of cardiovascular and metabolic disease in adulthood. Systematic screening of over 15,000 articles identified only twelve studies which reported postnatal growth outcomes for preterm infants according to parental SES. The health equity impact of the included studies was systematically assessed, and found to be negative overall. This study highlights limitations in existing evidence on the association between parental SES and postnatal growth, and delineates avenues for future research.

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.

Sociodemographic and lifestyle determinants of multimorbidity among community-dwelling older adults: findings from 346,760 SHARE participants

BACKGROUND

This study aimed to investigate the prevalence of multimorbidity and its associated factors among the older population in China to propose policy recommendations for the management of chronic diseases in older adults.

METHODS

This study was conducted based on the 2021 Shenzhen Healthy Ageing Research (SHARE), and involved analysis of 346,760 participants aged 65 or older. Multimorbidity is defined as the presence of two or more clinically diagnosed or non self-reported chronic diseases among the eight chronic diseases surveyed in an individual. The Logistic analysis was adopted to explore the potential associated factors of multimorbidity.

RESULTS

The prevalences of obesity, hypertension, diabetes, anemia, chronic kidney disease, hyperuricemia, dyslipidemia and fatty liver disease were 10.41%, 62.09%, 24.21%, 12.78%, 6.14%, 20.52%, 44.32%, and 33.25%, respectively. The prevalence of multimorbidity was 63.46%. The mean count of chronic diseases per participant was 2.14. Logistic regression indicated that gender, age, marriage status, lifestyle (smoking status, drinking status, and physical activity), and socioeconomic status (household registration, education level, payment method of medical expenses) were the common predictors of multimorbidity for older adults, among which, being women, married, or engaged in physical activity was found to be a relative determinant as a protective factor for multimorbidity after the other covariates were controlled.

CONCLUSION

Multimorbidity is prevalent among older adults in Chinese. Guideline development, clinical management,and public intervention should target a group of diseases instead of a single condition.

Association of smoking status and nicotine dependence with multi-morbidity in China: A nationally representative crosssectional study

INTRODUCTION

Multi-morbidity is a public health priority as it is associated with an increased risk of mortality and a substantial healthcare burden. Smoking is considered a predisposing factor for multi-morbidity, but evidence for an association between multi-morbidity and nicotine dependence is insufficient. This study aimed to explore the association between smoking status, nicotine dependence, and multi-morbidity in China.

METHODS

We recruited 11031 Chinese citizens from 31 provinces in 2021 using a multistage stratified cluster sampling strategy to ensure the study population represented national population characteristics. The association between smoking status and multi-morbidity was analyzed using binary logistic regression and multinomial logit regression models. We then analyzed the associations between four kinds of smoking status (age at smoking initiation, cigarette consumption per day, smoking when ill in bed, and inability to control smoking in public places), nicotine dependence, and multi-morbidity among participants who were current smokers.

RESULTS

Compared with non-smokers, the odds of multi-morbidity were higher among ex-smokers (adjusted odd ratio, AOR=1.40, 95% CI: 1.07-1.85). The risk of multi-morbidity was greater in participants who were underweight/overweight/obese (AOR=1.90; 95% CI: 1.60-2.26) compared with those who were normal weight. and also greater for drinkers (AOR=1.34; 95% CI: 1.09-1.63) than non-drinkers. Compared with children who began smoking at the age of <15 years, participants aged >18 years had a lower likelihood of multi-morbidity (AOR=0.52; 95% CI: 0.32-0.83). People who consumed ≥31 cigarettes per day (AOR=3.77; 95% CI: 1.47-9.68) and those who smoked when ill in bed (AOR=1.70; 95% CI: 1.10-2.64) were more likely to have multi-morbidity.

CONCLUSIONS

Our findings show that smoking behavior, including initiation age, frequency of daily smoking, and still smoking during illness or in public, is a critical risk factor for multi-morbidity, especially when combined with alcohol consumption, physical inactivity, and abnormal weight (underweight, overweight, or obese). This highlights the crucial effect of smoking cessation in the prevention and control of multi-morbidity, especially in patients with three or more diseases. Implementing smoking and lifestyle interventions to promote health would both benefit adults and prevent the next generation from initiating habits that increase the risk of multi-morbidity.

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.

Prevalence of Non-Communicable Diseases and Its Associated Factors Among Urban Elderly of Six Indian States

Aims The aim of this study is to investigate the prevalence, impact of health determinants on non-communicable diseases (NCDs), and multimorbidity among urban elderly in India. Methods This is a cross-sectional study involving a total of 1,671 (870 male and 801 female) respondents aged 60-80 years. Multistage sampling was used for the recruitment of the participants. A total of 12 sample areas from 12 cities of six southern states of south India were selected. Through survey form, information regarding demographic characteristics, health-influencing lifestyle factors, and history of nine NCDs was collected. Results The mean age of participants was 68.5 ± 6.01 years.. The prevalence of hypertension was 40.4%, followed by diabetes (31.2%), arthritis (22.1%), sensory impairment (10.1%), heart diseases (7.8%), and dyslipidemia (7.0%). 74.1% of participants had at least one morbidity, and 40.0% of people had multimorbidity. Being overweight is the highest risk health determinant for hypertension, diabetes, heart disease, high cholesterol, stroke, and joint pain. Obese people have 64% more risk of hypertension than people with normal BMI. People with disturbed sleep have increased risk of hypertension, high cholesterol, and joint pain by more than 80% compared to people with proper sleep. Among the modifiable health determinants of obesity, disturbed sleep, constipation, and physical activity up to 30 minutes were positively associated with multimorbidity. Those in the age group of 70 to 80 years have a high risk for NCDs and multimorbidity compared to those in the age group of 60 to 70 years. Conclusions A healthy lifestyle is necessary to reduce the burden of NCDs among the elderly. Developing holistic health policies seems an urgent need.

A combination of moderate and vigorous physical activities reduces the burden of multimorbidity: findings from Longitudinal Ageing Study in India

Background

Physical inactivity is a significant factor contributing to the prevalence of non-communicable diseases (NCDs). The objective of this study is to examine the association between physical activity and multimorbidity among Indian adults aged 45 years and above by residence.

Methods

Data from Longitudinal Ageing Study in India (LASI) 2017–2018, wave 1, a nationally representative study, are used to examine the above objective. A total of 59,073 adults aged 45 years and above are enlisted in the study. Physical activities and other demographic and socioeconomic variables have been used to describe the distribution of multimorbidity and investigate their relationship. Logistic regression is employed to examine the adjusted impact of physical activity on multimorbidity among Indian adults (45 + years) by residence.

Results

The level of physical activity is inversely related to the prevalence of multimorbidity in India. The rate of multimorbidity ranges from 4 to 12% among moderately active individuals in rural areas, whereas it ranges from 9 to 34% in urban areas across the age groups of 45 to 75+ years. Notably, the individuals who engage in both moderate and vigorous activities have a lower prevalence of multimorbidity than those who engage in only moderate activities.

Conclusion

Our study shows that physical inactivity has an association with the rise in multimorbidity in both rural and urban areas; however, the intensity of multimorbidity is higher in urban areas. The policymakers should consider the influence of moderate and vigorous physical activity as a key prevention measure of non-communicable disease and multimorbidity.

Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review

BACKGROUND

Driven by the increasing life expectancy, China and India, the two most populous countries in the world are experiencing a rising burden of multimorbidity. This study aims to explore community prevalence and dyad patterns of multimorbidity in China and India.

METHODS

We conducted a systematic review of five English and Chinese electronic databases. Studies involving adults 18 years or older at a community level, which reported multimorbidity prevalence and/or patterns were included. A modified Newcastle-Ottawa Scale was used for quality assessment. Despite large heterogeneity among reported studies, a systematic synthesis of the results was conducted to report the findings.

RESULTS

From 13 996 studies retrieved, 59 studies met the inclusion criteria (46 in China, 9 in India and 4 in both). The median prevalence of multimorbidity was 30.7% (IQR 17.1, 49.4), ranging from 1.5% to 90.5%. There was a large difference in multimorbidity prevalence between China and India, with median prevalence being 36.1% (IQR 19.6, 48.8) and 28.3% (IQR 8.9, 56.8), respectively. Among 27 studies that reported age-specific prevalence, 19 studies found multimorbidity prevalence increased with age, while 8 studies observed a paradoxical reduction in the oldest age group. Of the 34 studies that reported sex-specific prevalence, 86% (n=32) observed a higher prevalence in females. The most common multimorbidity patterns from 14 studies included hypertensive diseases combined with diabetes mellitus, arthropathies, heart diseases and metabolic disorders. All included studies were rated as fair or poor quality.

CONCLUSION

Multimorbidity is highly prevalent in China and India with hypertensive diseases and other comorbidities being the most observed patterns. The overall quality of the studies was low and there was a lack of representative samples in most studies. Large epidemiology studies, using a common definition of multimorbidity and national representative samples, with sex disaggregation are needed in both countries.

PROSPERO REGISTRATION NUMBER

CRD42020176774.

Multimorbidity patterns and associated factors in older Chinese: results from the China health and retirement longitudinal study

Background

This study aimed to investigate multimorbidity patterns and their associated factors among elderly population in China.

Methods

A total of 10,479 participants aged at least 60 years were drawn from the 2018 wave of the China Health and Retirement Longitudinal Study (CHARLS). Latent class analysis (LCA) was performed to identify distinct multimorbidity classes based on 14 self-reported chronic conditions. The multinomial logit model was used to analyze the associated factors of multimorbidity patterns, focusing on individuals' demographic characteristics, socioeconomic status (SES), and health behaviors.

Results

Among the 10,479 participants (mean age [SD]: 69.1 [7.1]), 65.6% were identified with multimorbidity. Five multimorbidity clusters were identified by LCA: relatively healthy class (49.8%), vascular class (24.7%), respiratory class (5.6%), stomach-arthritis class (14.5%), and multisystem morbidity class (5.4%). Multinomial logit analysis with the relatively healthy class as the reference showed that participants of older age and female sex were more likely to be in the vascular class and multisystem morbidity class. The probability of being in the vascular class was significantly higher for those with high SES. Ever smoking was associated with a higher probability of being in the respiratory class and multisystem morbidity class. Physical activity was associated with lower odds of being assigned to the vascular class, respiratory class, and multisystem class.

Conclusion

The distinct multimorbidity patterns imply that the prevention and care strategy should target a group of diseases instead of a single condition. Prevention interventions should be paid attention to for individuals with risk factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03154-9.

Life course socioeconomic conditions and multimorbidity in old age - A scoping review

Multimorbidity disproportionally affects individuals exposed to socioeconomic disadvantage. It is, however, unclear how adverse socioeconomic conditions (SEC) at different periods of the life course predict the occurrence of multimorbidity in later life. In this scoping review, we investigate the association between life course SEC and later-life multimorbidity, and assess to which extent it supports different life course causal models (critical period, sensitive period, accumulation, pathway, or social mobility). We identified four studies (25,209 participants) with the first measure of SEC in childhood (before age 18). In these four studies, childhood SEC was associated with multimorbidity in old age, and the associations were partially or fully attenuated upon adjustment for later-life SEC. These results are consistent with the sensitive period and the pathway models. We identified five studies (91,236 participants) with the first measure of SEC in young adulthood (after age 18), and the associations with multimorbidity in old age as well as the effects of adjustment for later-life SEC differed from one study to the other. Among the nine included studies, none tested the social mobility or the accumulation models. In conclusion, SEC in early life could have an effect on multimorbidity, attenuated at least partly by SEC in adulthood.

A comparison of health-related quality of life and personal, social, and environmental factors of older adults according to a residential area: a propensity score matching analysis

PURPOSE

This study identified individual, social, and environmental factors affecting the health-related quality of life (HRQoL) of older individuals living in urban and non-urban areas of the Republic of Korea and investigated their effects on HRQoL.

METHODS

A secondary data analysis study was conducted using raw data from Korea's 2017 Community Health Survey. Propensity score matching (PSM) was performed to compare the individual, social, and environmental characteristics of older individuals living in urban and non-urban areas (16,695 and 29,106 individuals, respectively). Statistical analyses were performed using R program 4.0.5. The differences between variables were analyzed using chi-squared and t-tests, whereas factors influencing HRQoL were analyzed using multiple regression analysis.

RESULTS

Among the individual factors, the living arrangement (p = 0.001, confidence interval [CI] = 0.00-0.02) was an influencing factor in urban areas, whereas it showed no statistical significance in non-urban areas. Moreover, Helping their neighbors (p = 0.001, CI = 0.00-0.01) among the social factors and satisfaction with the living environment (p = 0.011, CI = 0.00-0.02) and with healthcare services (p = 0.047, CI = 0.00-0.01) among the environmental factors were influencing factors in urban areas, whereas they showed no statistical significance in non-urban areas.

CONCLUSION

Satisfaction with the living environment and with healthcare services was positively associated with HRQoL among older individuals living in urban areas. Therefore, factors associated with regional health inequality should be identified, and health equality sought through the development of local government policies that consider diversity in population composition and health indicators by region.

Profiling Bispebjerg Acute Cohort: Database Formation, Acute Contact Characteristics of a Metropolitan Hospital, and Comparisons to Urban and Rural Hospitals in Denmark

Purpose

To present a metropolitan cohort, Bispebjerg acute cohort (BAC), and compare patient characteristics and outcomes with patients from urban and rural hospitals in Denmark.

Patients and Methods

We linked data from seven Danish nationwide registries and included all acute contacts to non-psychiatric hospitals in the years 2016–2018. Acute hospital contacts to Bispebjerg and Frederiksberg Hospital constituted BAC, representing a solely metropolitan/urban catchment area. Patient characteristics and outcomes were compared to the rest of Denmark in an urban cohort (UrC) and a rural cohort (RuC), stratified by visit and hospitalization contact types.

Results

We identified 4,063,420 acute hospital contacts in Denmark and BAC constituted 8.4% (n=343,200) of them. BAC had a higher proportion of visits (65.1%) compared with UrC (52.1%) and RuC (45.3%). Patients in BAC more often lived alone (visits: BAC: 34.8%, UrC: 30.6%, RuC: 29.2%; hospitalizations: BAC: 50.8%, UrC: 36.7%, RuC: 37.2%) and had temporary CPR number (visits: BAC: 4.4%, UrC: 1.9%, RuC: 1.6%; hospitalizations: BAC: 1.5%, UrC: 0.9%, RuC: 0.8%). Visit patients in BAC were younger (BAC: 36, UrC: 42, RuC: 45 years, median), more often students (BAC: 18.0%, UrC: 14.0%, RuC: 12.5%), and had more contacts due to infectious diseases (BAC: 19.8%, UrC: 14.1%, RuC: 6.2%) but less due to injuries (BAC: 40.0%, UrC: 43.8%, RuC: 60.7%). Hospitalized patients in BAC had higher median age (BAC: 64, UrC: 61, RuC: 64 years) and fewer were in employment than in UrC (BAC: 26.1%, UrC: 32.1%, RuC: 28.1%). BAC Hospitalizations had a lower death rate within 30 days than in RuC (BAC: 3.0% [2.9–3.1%], UrC: 3.1% [3.0–3.1%], RuC: 3.4% [3.3–3.4%]), but a higher readmission-rate (BAC: 20.5% [20.3–20.8%], UrC: 17.3% [17.2–17.4%], RuC: 17.5% [17.5–17.6%]).

Conclusion

Significant differences between BAC, urban, and rural cohorts may be explained by differences in healthcare structure and sociodemographics of the catchment areas.

Developing and validating a Chinese multimorbidity-weighted index for middle-aged and older community-dwelling individuals

OBJECTIVE

To develop and validate an index to quantify the multimorbidity burden in Chinese middle-aged and older community-dwelling individuals.

METHODS

We included 20,035 individuals aged 45 and older from the China Health and Retirement Longitudinal Study (CHARLS) and 19,297 individuals aged 65 and older from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Health outcomes of physical functioning (PF), basic and instrumental activities of daily living (ADL and IADL) and mortality were obtained. Based on self-reported disease status, we calculated five commonly used western multimorbidity indexes for CHARLS baseline participants. The one that predicted the health outcomes the best was selected and then modified through a linear mixed model using the repeated individual data in CHARLS. The performance of the modified index was internally and externally evaluated with CHARLS and CLHLS data.

RESULTS

The multimorbidity-weighted index (MWI) performed the best among the five indexes. In the modified Chinese multimorbidity-weighted index (CMWI), the weights of the diseases varied greatly (range 0.2-5.1). The top three diseases with the highest impact were stroke, memory-related diseases and cancer, corresponding to weights of 5.1, 4.3 and 3.4, respectively. Compared with the MWI, the CMWI showed better model fits for PF and IADL with larger R2 and smaller Akaike information criterion, and comparable prediction performances for ADL, IADL and mortality (e.g. the same predictive accuracy of 0.80 for ADL disability).

CONCLUSION

The CMWI is an adequate index to quantify the multimorbidity burden for Chinese middle-aged and older community-dwelling individuals. It can be directly computed via disease status examined in regular community health check-ups to facilitate health management.

Preventing Multimorbidity with Lifestyle Interventions in Sub-Saharan Africa: A New Challenge for Public Health in Low and Middle-Income Countries

Objectives: Low and Middle-Income Countries are experiencing a fast-paced epidemiological rise in clusters of non-communicable diseases such as diabetes and cardiovascular disease, forming an imminent rise in multimorbidity. However, preventing multimorbidity has received little attention in LMICs, especially in Sub-Saharan African Countries. Methods: Narrative review which scoped the most recent evidence in LMICs about multimorbidity determinants and appropriated them for potential multimorbidity prevention strategies. Results: MMD in LMICs is affected by several determinants including increased age, female sex, environment, lower socio-economic status, obesity, and lifestyle behaviours, especially poor nutrition, and physical inactivity. Multimorbidity public health interventions in LMICs, especially in Sub-Saharan Africa are currently impeded by local and regional economic disparity, underdeveloped healthcare systems, and concurrent prevalence of communicable and non-communicable diseases. However, lifestyle interventions that are targeted towards preventing highly prevalent multimorbidity clusters, especially hypertension, diabetes, and cardiovascular disease, can provide early prevention of multimorbidity, especially within Sub-Saharan African countries with emerging economies and socio-economic disparity. Conclusion: Future public health initiatives should consider targeted lifestyle interventions and appropriate policies and guidelines in preventing multimorbidity in LMICs.

Racial Disparities in End-of-Life Care Between Black and White Adults With Metastatic Cancer

CONTEXT

The comfort of patients with cancer near the end of life (EOL) is often undermined by unnecessary and burdensome treatments. There is a need for more research examining racial disparities in EOL care, especially in regions with a history of racial discrimination.

OBJECTIVES

To examine whether black adults received more burdensome EOL care than white adults in a population-based data set of cancer decedents in Louisiana, a state with a history of slavery and long-standing racial disparities.

METHODS

This was a retrospective analysis of EOL care from the Research Action for Health Network (REACHnet), a regional Patient-Centered Outcomes Research Institute-funded database. The sample consisted of 875 white and 415 black patients with metastatic cancer who died in Louisiana from 2011 to 2017. We used logistic regression to examine whether race was associated with five indicators of burdensome care in the last 30 days of life: chemotherapy use, inpatient hospitalization, intensive care unit admission, emergency department (ED) admission, and mechanical ventilation.

RESULTS

Most patients (85.0%) received at least one indicator of burdensome care: hospitalization (76.5%), intensive care unit admission (44.1%), chemotherapy (29.1%), mechanical ventilation (23.0%), and ED admission (18.3%). Odds ratios (ORs) indicated that black individuals were more likely than white individuals to be hospitalized (OR = 1.66; 95% CI = 1.21-2.28; P = 0.002) or admitted to the ED (OR = 1.57; 95% CI = 1.16-2.13; P = 0.004) during their last month of life.

CONCLUSION

Findings have implications for informing health care decision making near the EOL for patients, families, and clinicians, especially in regions with a history of racial discrimination and disparities.

Urban-rural disparity in prevalence of multimorbidity in China: a cross-sectional nationally representative study

BACKGROUND

To address the neglect of depression in multimorbidity measurement and the lack of focus on rural population in previous literature about China, this paper aimed to estimate the prevalence of multimorbidity (including depressive disorders) among the country's rural and urban population.

METHODS

We used a cross-sectional design and data from a nationally representative survey conducted in 2015-2016 among Chinese people aged 45 years or older involving 19 656 participants. Multimorbidity was measured with a cut-off point of having two or more among 14 chronic illnesses. In that 13 of them were based on self-reported physician diagnosis. In addition, depressive disorders were assessed with the 10-item Centre for Epidemiologic Studies Depression Scale. The weighted prevalence of multimorbidity was calculated, with a non-response adjustment. Multivariate logistic regression was applied to analyse the relation between covariates and multimorbidity.

FINDINGS

Multimorbidity was highly prevalent (54.3%) among the studied population. Contrary to previous studies, we found the prevalence of multimorbidity to be higher among the rural dwellers (58.3%) than among the urban population (50.4%). After adjustment for covariates, rural residents had 7.5% higher odds (95% CI of OR (1.003 to 1.151)) of having multimorbidity than their urban counterparts. Above 70% of patients with any of the 14 chronic illnesses above 45 years old had multimorbidity, while 80.6%-97.9% of chronic patients had multimorbidity.

INTERPRETATION

Future health system development in China should transform from preventing and controlling non-communicable diseases as individual diseases to addressing people's comprehensive health needs under multimorbidity. The rural population should be prioritised as they suffered more from multimorbidity than the urban population.

Neighborhood's locality, road types, and residents' multimorbidity: evidence from China's middle-aged and older adults

Background

Neighborhood factors have gained increasing attention, while the association between the neighborhood’s characteristics and multimorbidity has not been clarified. In this study, we aim to depict variations in the number of non-communicable chronic diseases (NCDs) as a function of urban vs. rural settings and road types.

Methods

The present cross-sectional study derived data from the China Health and Retirement Longitudinal Study 2011 National Baseline Survey. Negative binomial regression with clustered robust standard errors was performed to analyze variations in the number of NCDs among 13,414 Chinese middle-aged and older adults. Logistic regression models were employed to investigate the association between neighborhood-level characteristics and each NCD, respectively.

Results

First, over 65% of subjects had at least one NCDs, and over 35% had multimorbidity. Arthritis (33.08%), hypertension (24.54%), and digestive disease (21.98%) were the most prevalent NCDs. Urban vs. rural differences in multimorbidity were fully explained by neighborhood clustering variations (IRR = 1.02, 95% CI, 0.95–1.10). Living with paved roads was associated with a smaller number of NCDs relative to living with unpaved roads (IRR = 0.86, 95% CI, 0.78–0.95). Results from subgroup analyses suggested that in comparison with those living with unpaved roads, individuals living with paved roads respectively had lower odds of chronic lung disease (OR = 0.76, 95% CI, 0.63–0.93), chronic liver disease (OR = 0.74, 95% CI, 0.55–0.99), chronic kidney disease (OR = 0.68, 95% CI, 0.51–0.89), digestive disease (OR = 0.82, 95% CI, 0.69–0.97), arthritis or rheumatism (OR = 0.69, 95% CI, 0.55–0.87), and asthma (OR = 0.67, 95% CI, 0.51–0.88).

Conclusions

Urban vs. rural disparities in multimorbidity appeared to result from within-neighborhoods characteristics. The improvement in neighborhood-level characteristics, such as road pavement, holds promise to alleviate the increasing disease burden of chronic diseases.