Association Between Body Mass index and Prevalence of Multimorbidity in Low-and Middle-income Countries: A Cross-Sectional Study

Osteoarthritis burden and inequality from 1990 to 2021: a systematic analysis for the global burden of disease Study 2021

Osteoarthritis (OA) is a major global health burden, affecting millions and causing significant disability. Understanding its trends and determinants is crucial for effective management and prevention. We analyzed data from the Global Burden of Diseases (GBD) study 2021 to assess OA incidence, Years Lived with Disability (YLDs), and age-standardized rates (ASIR/ASYR) from 1990 to 2021. We explored trends and determinants across gender, region, and Socio-Demographic Index (SDI) quintiles using Joinpoint regression, Age-Period-Cohort (APC) modeling, decomposition, and inequality analyses. The global incidence of OA surged from 20.9 million in 1990 to 46.6 million cases in 2021, with an AAPC of 0.29%. Correspondingly, YLDs escalated from 8.92 million to 21.30 million, reflecting an AAPC of 0.30%. Disparities exist across SDI quintiles, with higher rates observed in high SDI countries. Women consistently experience a higher burden compared to men. Asian regions demonstrate the fastest rise in ASYR. High BMI contributes significantly to OA burden, particularly in high SDI countries. The rising burden of OA necessitates urgent attention. Interventions targeting modifiable risk factors, such as obesity, and early detection and management strategies are crucial. Addressing gender disparities and health inequalities, particularly in high SDI countries, is essential for effective OA prevention and control.

Global burden of early-onset osteoarthritis, 1990-2019: results from the Global Burden of Disease Study 2019

OBJECTIVES

Early-onset osteoarthritis (OA) is an emerging health issue amidst the escalating prevalence of overweight and obesity. However, there are scant data on its disease, economic burden and attributable burden due to high body mass index (BMI).

METHODS

Using data from the Global Burden of Diseases Study 2019, we examined the numbers of incident cases, prevalent cases, years lived with disability (YLDs) and corresponding age-standardised rates for early-onset OA (diagnosis before age 55) from 1990 to 2019. The case definition was symptomatic and radiographically confirmed OA in any joint. The average annual percentage changes (AAPCs) of the age-standardised rates were calculated to quantify changes. We estimated the economic burden of early-onset OA and attributable burden to high BMI.

RESULTS

From 1990 to 2019, the global incident cases, prevalent cases and YLDs of early-onset OA were doubled. 52.31% of incident OA cases in 2019 were under 55 years. The age-standardised rates of incidence, prevalence and YLDs increased globally and for countries in all Sociodemographic Index (SDI) quintiles (all AAPCs>0, p<0.05), with the fastest increases in low-middle SDI countries. 98.04% of countries exhibited increasing trends in all age-standardised rates. Early-onset OA accounts for US$46.17 billion in healthcare expenditure and US$60.70 billion in productivity loss cost in 2019. The attributable proportion of high BMI for early-onset OA increased globally from 9.41% (1990) to 15.29% (2019).

CONCLUSIONS

Early-onset OA is a developing global health problem, causing substantial economic costs in most countries. Targeted implementation of cost-effective policies and preventive intervention is required to address the growing health challenge.

Epidemiology and impact of chronic disease multimorbidity in India: a systematic review and meta-analysis

Objectives

This is the first systematic review and meta-analysis of the prevalence of multimorbidity, its risk factors including socioeconomic factors, and the consequences of multimorbidity on health systems and broader society in India.

Methods

A systematic review of both published and grey literature from five databases (Medline, Embase, EBSCO, Scopus, and ProQuest) was conducted including original studies documenting prevalence or patient outcomes associated with multimorbidity among adults in India. We excluded studies that did not explicitly mention multimorbidity. Three independent reviewers did primary screening based on titles and abstracts followed by full-text review for potential eligibility. The risk of bias was independently assessed by two reviewers following the Appraisal Tool for Cross-Sectional Studies. We presented both qualitative and quantitative (through meta-analysis) summaries of the evidence. The protocol for this study was prospectively registered with PROSPERO (CRD42021257281).

Results

The review identified 5442 articles out of which 35 articles were finally included in this study. Twenty-three studies were based on the primary data while 12 used secondary data. Eleven studies were conducted in hospital/primary care setting while 24 were community-based. The pooled prevalence of multimorbidity based on (n=19) studies included for meta-analysis was 20% (95% CI: 19% to 20%). The most frequent outcomes were increased healthcare utilization, reduced health-related quality of life, physical and mental functioning.

Conclusion

We identified a wide variance in the magnitude of multimorbidity across age groups and regions with most of the studies from eastern India. Nation-wide studies, studies on vulnerable populations and interventions are warranted.

Exploring multimorbidity profiles in middle-aged inpatients: a network-based comparative study of China and the United Kingdom

BACKGROUND

Multimorbidity is better prevented in younger ages than in older ages. This study aims to identify the differences in comorbidity patterns in middle-aged inpatients from China and the United Kingdom (UK).

METHODS

We utilized 184,133 and 180,497 baseline hospitalization records in middle-aged populations (40-59 years) from Shaanxi, China, and UK Biobank. Logistic regression was used to calculate odds ratios and P values for 43,110 unique comorbidity patterns in Chinese inpatients and 21,026 unique comorbidity patterns in UK inpatients. We included the statistically significant (P values adjusted by Bonferroni correction) and common comorbidity patterns (the pattern with prevalence > 1/10,000 in each dataset) and employed network analysis to construct multimorbidity networks and compare feature differences in multimorbidity networks for Chinese and UK inpatients, respectively. We defined hub diseases as diseases having the top 10 highest number of unique comorbidity patterns in the multimorbidity network.

RESULTS

We reported that 57.12% of Chinese inpatients had multimorbidity, substantially higher than 30.39% of UK inpatients. The complete multimorbidity network for Chinese inpatients consisted of 1367 comorbidities of 341 diseases and was 2.93 × more complex than that of 467 comorbidities of 215 diseases in the UK. In males, the complexity of the multimorbidity network in China was 2.69 × more than their UK counterparts, while the ratio was 2.63 × in females. Comorbidities associated with hub diseases represented 68.26% of comorbidity frequencies in the complete multimorbidity network in Chinese inpatients and 55.61% in UK inpatients. Essential hypertension, dyslipidemia, type 2 diabetes mellitus, and gastritis and duodenitis were the hub diseases in both populations. The Chinese inpatients consistently demonstrated a higher frequency of comorbidities related to circulatory and endocrine/nutritional/metabolic diseases. In the UK, aside from these comorbidities, comorbidities related to digestive and genitourinary diseases were also prevalent, particularly the latter among female inpatients.

CONCLUSIONS

Chinese inpatients exhibit higher multimorbidity prevalence and more complex networks compared to their UK counterparts. Multimorbidity with circulatory and endocrine/nutritional/metabolic diseases among both Chinese and UK inpatients necessitates tailored surveillance, prevention, and intervention approaches. Targeted interventions for digestive and genitourinary diseases are warranted for the UK.

The Multimorbidity and Lifestyle Correlates in Chinese Population Residing in Macau: Findings from a Community-Based Needs Assessment Study

Multimorbidity has become one of the most pressing public health concerns worldwide. The objectives of this study were to understand the prevalence of multimorbidity and its relationship with lifestyle factors among Chinese adults in Macau, and to investigate the combined contribution of common lifestyle factors in predicting multimorbidity. Data were collected through face-to-face interviews using a self-reported questionnaire on common chronic diseases, lifestyle factors and sociodemographics. BMI, physical activity, drinking status, smoking status and sleep quality were assessed, and a composite lifestyle score (0 to 9 points) was calculated, and the higher the score, the healthier the lifestyle. A total of 1443 participants were included in the analysis, of whom 55.2% were female, 51.8% were middle aged or elderly and 30.5% completed tertiary education or higher. The prevalence of multimorbidity was 10.3%. The combination of hypertension and hyperlipidaemia was the most common (22.2%) multimorbidity among the participants with multimorbidity. After the adjustment of the covariates, it was found that the participants who were overweight (OR: 1.95, 95% CI: 1.18-3.20, p = 0.009) or obese (OR: 3.76, 95% CI: 2.38-5.96, p < 0.001), former drinkers (OR: 2.43, 95% CI: 1.26-4.69, p = 0.008), and those who reported poor sleep quality (OR: 2.25, 95% CI: 1.49-3.40, p < 0.001) had a high risk of developing multimorbidity. A one-unit increase in the lifestyle score was associated with a 0.33-times reduction in the risk of developing multimorbidity (OR: 0.67; 95% CI: 0.59-0.77, p < 0.001). A combination of lifestyle factors can influence a variety of multimorbidity among the Chinese adults in Macau. Thus, comprehensively assessing the combined contribution of several lifestyle factors in predicting multimorbidity is important.

Quality of life and associated factors among community-dwelling adults with multimorbidity in Shanghai, China: A cross-sectional study

AIM

To compare the quality of life of patients with and without multimorbidity and investigate potential factors related to the quality of life in patients with multimorbidity.

DESIGN

A descriptive cross-sectional study.

METHODS

This study included 1778 residents with chronic diseases, including single disease (1255 people, average age: 60.78 ± 9.42) and multimorbidity (523 people, average age: 64.03 ± 8.91) groups, who were recruited from urban residents of Shanghai through a multistage, stratified, probability proportional to size sampling method. The quality of life was measured using the World Health Organization Quality of Life Questionnaire. The socio-demographic data and psychological states were measured using a self-made structured questionnaire, Self-rating Anxiety Scale, and Self-rating Depression Scale. Differences in demographic characteristics were estimated using Pearson's chi-squared test, and independent t-test or one-way ANOVA followed by S-N-K test was used to compare the mean quality of life. Multiple linear regression analysis was conducted to identify risk factors for multimorbidity.

RESULTS

There were differences in age, education, income, and BMI between single-disease and multimorbidity groups, but no differences in gender, marriage, and occupation. Multimorbidity had lower quality of life, reflected in all four domains. Multiple linear regression analyses showed that low level of education, low income, number of diseases, depression, and anxiety were negatively related to quality of life in all domains.

An analysis of socioeconomic factors on multiple chronic conditions and its economic burden: evidence from the National Health Service Survey in Yunnan Province, China

Background

The economic burden of multiple chronic conditions (MCCs) and its socio-economic influencing factors have widely raised public concerns. However, there are few large population-based studies on these problems in China. Our study aims at determining the economic burden of MCCs and associated factors specific to multimorbidity among middle-aged and older individuals.

Methods

As our study population, we extracted all 11,304 participants over 35 years old from the 2018 National Health Service Survey (NHSS) in Yunnan. Economic burden and socio-demographic characteristics were analyzed with descriptive statistics. Chi-square test and generalized estimating equations (GEE) regression models were used to identify influencing factors.

Results

The prevalence of chronic diseases was 35.93% in 11,304 participants and the prevalence of MCCs increased with age, was 10.12%. Residents who lived in rural areas were more likely to report MCCs than those who lived in urban areas (adjusted OR = 1.347, 97.5% CI: 1.116-1.626). Ethnic minority groups were less likely to report MCCs than those of Han (OR = 0.752, 97.5% CI: 0.601-0.942). Overweight or obese people were more likely to report MCCs than people with normal weight (OR = 1.317, 97.5% CI: 1.099-1.579). The per capita expenses of 2 weeks' illness, per capita hospitalization expenses, annual household income, annual household expenses, and annual household medical expenses of MCCs were ¥292.90 (±1427.80), ¥4804.22 (±11851.63), ¥51064.77 (±52158.76), ¥41933.50 (±39940.02) and ¥11724.94 (±11642.74), respectively. The per capita expenses of 2 weeks' illness, per capita hospitalization expenses, annual household income, annual household cost, and annual household medical expenses of hypertensive co-diabetic patients were more compared to those with other three comorbidity modes.

Conclusion

The prevalence of MCCs was relatively high among middle-aged and older individuals in Yunnan, China, which bought a heavy economic burden. This encourages policy makers and health providers to pay more attention to the behavioral/lifestyle factors, that contribute to multimorbidity to a great extent. Furthermore, health promotion and education in terms of MCCs need to be prioritized in Yunnan.

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.

Bidirectional association between functional disability and multimorbidity among middle-aged and older adults in Thailand

Objectives

The purpose of this study was to assess the bidirectional association between multimorbidity (MM) and functional disability among middle-aged and older adults in a longitudinal study in Thailand.

Methods

We analyzed longitudinal data of participants aged 45 years and older from two consecutive waves (in 2015 and 2017) of the Health, Aging, and Retirement in Thailand (HART). Functional disability was assessed with a 4-item activity of daily living (ADL) scale. Logistic regression analysis was conducted to assess the association between baseline functional disability and incident MM (≥2), and baseline morbidity and incident functional disability.

Results

The results indicate that a total of 1,716 individuals without morbidity at baseline and 3,529 without functional disability at baseline were included. At follow-up, 16.7 and 20.0% of functional disability cases and 7.1 and 3.6% of nonfunctional disability cases developed 2 morbidities and 3 or more morbidities, respectively, and 6.6% of MM cases and 4.0% of non-MM cases developed a functional disability. In the final logistic regression model adjusted for education, income, age, marital status, sex, smoking tobacco, body mass index (BMI), alcohol use, physical activity, and social engagement, functional disability at baseline was positively associated with incident MM (≥2) (adjusted odds ratio [aOR]: 2.58, 95% CI: 1.42-4.72), and MM (≥3) at baseline was positively associated with incident functional disability (aOR: 1.97, 95% CI: 1.13-3.43).

Conclusion

Multimorbidity and functional disability were bidirectionally associated.

Multiple chronic conditions among older adults in China: differences in socio-demographic characteristics

Objective

There are relatively few studies on multiple chronic conditions (MCC) among older adults in China. This study sought to assess the potential differences in the risk of MCC among different elderly populations, and thus to identify the most vulnerable populations at higher risk of developing the MCC.

Methods

A sample of 5320 adults aged 60 years or above from the China's Health-Related Quality of Life Survey for Older Adults 2018 (CHRQLS-OA 2018) were included in this study. Descriptive statistics frequencies and proportions were used to summarize the sample characteristics, and logistic regression models were conducted to identify the differences in the risk of having MCC among different populations.

Results

Overall, 52.6% of respondents had been clearly diagnosed with at least one chronic disease with 25.3% having MCC. The males ((adjusted odds ratio [AOR] = 0.84; 95% confidence interval [CI] = 0.73-0.98) were less likely to have MCC. This was also true among female elderly with a non-agricultural hukou (AOR = 0.75; 95% CI = 0.57-0.99). The elderly with a non-agricultural hukou aged 60-64 (AOR = 0.55; 95% CI = 0.34-0.88) had a lower risk of having MCC. Those whose average annual household income per capita were 15,000-30,000 RMB (AOR = 1.42; 95% CI = 1.03-1.96) were more likely to suffer from MCC. The odds ratios of having MCC were smaller as the personal savings increases in total samples (all P < 0.05).

Conclusions

The findings suggest that different policies or approaches should target these specific populations who are most in need and are most likely to suffer from MCC.

Self-rated health and multimorbidity in patients with type 2 diabetes

The relationship between multimorbidity and self-rated health is well established. This study examined self-rated health in relation to multimorbidity, glycaemia and body weight specifically in adults with type 2 diabetes. Bootstrapped hierarchical logistic regression and structural equation modelling (SEM) were used to analyse survey data from 280 adults with type 2 diabetes. The odds of 'fair/bad/very bad' self-rated health increased 10-fold in patients with three (OR = 10.11 (3.36-30.40)) and four conditions (OR = 10.58 (2.9-38.25)), irrespective of glycaemic control (p < 0.001). The relationship between multimorbidity and perceived health was more pronounced in male patients. SEM generated a model with good fit, χ2 (CMIN) = 5.10, df = 3, p = 0.164, χ2 (CMIN)/df = 1.70, RMSEA = 0.05, CFI = 0.97, TLI = 0.95 and NFI = 0.94; self-rated health mediated relations between multimorbidity and BMI. Overall, this study highlights the potential of self-rated health to mediate relationships between multimorbidity and BMI, but not glycaemic control, in adults with type 2 diabetes.

One in five South Africans are multimorbid: An analysis of the 2016 demographic and health survey

Multimorbidity is a global research priority, yet relatively little is known about it in low and middle income countries. South Africa has the largest burden of HIV worldwide but also has a growing burden of non-communicable diseases; potentially leading to uncommon disease combinations. Information about the prevalence of multimorbidity and factors associated with it can assist in healthcare planning and targeting groups of people for interventions. This study aimed to determine the prevalence of multimorbidity by age and sex, as well as factors associated with multimorbidity in people 15 years and older. This study analyses the nationally representative 2016 South African Demographic Health Survey. The sample included 10 336 people who participated in the Adult Health questionnaire and approximately 7 961 people who provided biomarkers. Multivariate logistic regression was used to measure the association of multimorbidity with age, sex, living in an urban or rural area, education level, wealth level, employment status, body mass index, current alcohol or tobacco use. All analyses were conducted using STATA 15. Multimorbidity was present in 20.7% (95% CI: 19.5%- 21.9%) of participants; in 14.8% (95% CI: 13.4% - 16.3%) of males and 26.2% (95% CI: 24.7-27.7%) of females. Multimorbidity increased with age; with the highest odds in the 55-64 years old age group (OR: 24.910, 95% CI: 14.901-41.641, p < 0.001) compared to those aged 15-24 years. The odds of multimorbidity was also higher in young females compared to young males (OR: 2.734, 95% CI: 1.50-4.99, p = 0.001). Possessing tertiary education (OR: 0.722, 95% CI: 0.537-0.97, p = 0.031), being employed (OR: 0.813, 95% CI: 0.675-0.979, p = 0.029) or currently using alcohol (OR: 0.815, 95% CI: 0.686-0.968, p = 0.02) was protective against multimorbidity. Multimorbidity is prevalent within the South African population, with females and older adults being most affected. However, multimorbidity is also observed in younger adults and most likely driven by the high prevalence of HIV and hypertension.

Association of multimorbidity and physical activity among older adults in India: an analysis from the Longitudinal Ageing Survey of India (2017-2018)

OBJECTIVE

To examine the association of multimorbidity and physical activity among older adults in India.

DESIGN

A cross-sectional study was conducted using large representative survey data.

SETTING AND PARTICIPANTS

The study used data from the nationally representative 'Longitudinal Ageing Study in India (LASI),' conducted during 2017-2018. The study included a total sample of 65 336 older adults aged 45 years and above in India.

METHODS

Moderate and vigorous physical activities were measured separately by self-reported questionnaires. Physical activity was calculated as minutes of metabolic equivalent tasks per week. The outcome variable was a categorical variable where 2=the prevalence of more than one morbidity, 1=presence of one morbidity and 0=none. Bivariate analysis and multinomial logistic regression were applied to fulfil the objectives.

RESULTS

27.39% of older adults in India had multimorbidity. 31.02% of older adults did not engage in any moderate physical activities. Also, 59.39% of older adults did not engage in any vigorous physical activities. Older adults reporting low (adjusted relative risk ratio (A RRR): 1.10, 95% CI 1.03 to 1.18) and moderate (A RRR): 1.05, 95% CI 0.98 to 1.13) level of moderate physical activity were significantly more likely to suffer from multimorbidity compared with no involvement in moderate physical activity. However, older adults who reported high (A RRR: 0.79, 95% CI 0.75 to 0.84), moderate (A RRR: 0.88, 95% CI 0.80 to 0.98) and low level of vigorous physical activity (A RRR: 0.94, 95% CI 0.86 to 1.02) had significantly less multimorbidity in comparison to those who never engaged in vigorous physical activity.

CONCLUSION

Lack of physical activity is associated with multimorbidity among older adults. Physical activity promotion should be adopted as a primary strategy in reducing the burden of morbidity and multimorbidity.

Lifestyle, high Body Mass Index, and markers of socioeconomic conditions associated with multimorbidity in women

OBJECTIVE

This study aimed to identify the prevalence of multimorbidity and its associated factors in women in southern Brazil.

METHODS

We conducted a cross-sectional, population-based study with a sample of 1,128 women (age 20-69 years), living in São Leopoldo, southern Brazil. Multimorbidity was defined as two or more chronic conditions measured using the therapeutic and chemical anatomical classification of continuous use medications prescribed by a physician. Poisson regression model with robust variance was used to assess the association between sociodemographic and lifestyle variables and multimorbidity.

RESULTS

The prevalence of multimorbidity was 21.7% (95%CI 19.3-24.2), and 26 chronic conditions were identified. A direct linear association was observed with age and income and an inverse association with education. Being unemployed was a risk factor for multimorbidity (PR 1.95; 95%CI 1.51-2.52). Alcohol consumption (moderate or excessive) had a protective effect. Overweight and obese women were 53% (PR 1.53; 95%CI 1.09-2.15) and 76% (PR 1.76; 95%CI 1.27-2.45) more likely to have multimorbidity than eutrophic women.

CONCLUSION

Over 20% of the adult women had multimorbidity, and its occurrence was strongly associated with socioeconomic characteristics, such as fewer years of schooling, higher income, and not having an occupation. The results regarding alcohol consumption are still insufficient to propose a public policy for the prevention of multimorbidity. Excess weight was an independent risk factor and should be addressed in public health policies for the prevention and management of multimorbidity.

Decomposing urban-rural differences in multimorbidity among older adults in India: a study based on LASI data

BACKGROUND

Multimorbidity is defined as the co-occurrence of two or more than two diseases in the same person. With rising longevity, multimorbidity has become a prominent concern among the older population. Evidence from both developed and developing countries shows that older people are at much higher risk of multimorbidity; however, urban-rural differential remained scarce. Therefore, this study examines urban-rural differential in multimorbidity among older adults by decomposing the risk factors of multimorbidity and identifying the covariates that contributed to the change in multimorbidity.

METHODS

The study utilized information from 31,464 older adults (rural-20,725 and urban-10,739) aged 60 years and above from the recent release cross-sectional data of the Longitudinal Ageing Study in India (LASI). Descriptive, bivariate, and multivariate decomposition analysis techniques were used.

RESULTS

Overall, significant urban-rural differences were found in the prevalence of multimorbidity among older adults (difference: 16.3; p < 0.001). The multivariate decomposition analysis revealed that about 51% of the overall differences (urban-rural) in the prevalence of multimorbidity among older adults was due to compositional characteristics (endowments). In contrast, the remaining 49% was due to the difference in the effect of characteristics (Coefficient). Moreover, obese/overweight and high-risk waist circumference were found to narrow the difference in the prevalence of multimorbidity among older adults between urban and rural areas by 8% and 9.1%, respectively. Work status and education were found to reduce the urban-rural gap in the prevalence of multimorbidity among older adults by 8% and 6%, respectively.

CONCLUSIONS

There is a need to substantially increase the public sector investment in healthcare to address the multimorbidity among older adults, more so in urban areas, without compromising the needs of older adults in rural areas.

Multimorbidity of non-communicable diseases in low-income and middle-income countries: a systematic review and meta-analysis

INTRODUCTION

Multimorbidity is a major public health challenge, with a rising prevalence in low/middle-income countries (LMICs). This review aims to systematically synthesise evidence on the prevalence, patterns and factors associated with multimorbidity of non-communicable diseases (NCDs) among adults residing in LMICs.

METHODS

We conducted a systematic review and meta-analysis of articles reporting prevalence, determinants, patterns of multimorbidity of NCDs among adults aged >18 years in LMICs. For the PROSPERO registered review, we searched PubMed, EMBASE and Cochrane libraries for articles published from 2009 till 30 May 2020. Studies were included if they reported original research on multimorbidity of NCDs among adults in LMICs.

RESULTS

The systematic search yielded 3272 articles; 39 articles were included, with a total of 1 220 309 participants. Most studies used self-reported data from health surveys. There was a large variation in the prevalence of multimorbidity; 0.7%-81.3% with a pooled prevalence of 36.4% (95% CI 32.2% to 40.6%). Prevalence of multimorbidity increased with age, and random effect meta-analyses showed that female sex, OR (95% CI): 1.48, 1.33 to 1.64, being well-off, 1.35 (1.02 to 1.80), and urban residence, 1.10 (1.01 to 1.20), respectively were associated with higher odds of NCD multimorbidity. The most common multimorbidity patterns included cardiometabolic and cardiorespiratory conditions.

CONCLUSION

Multimorbidity of NCDs is an important problem in LMICs with higher prevalence among the aged, women, people who are well-off and urban dwellers. There is the need for longitudinal data to access the true direction of multimorbidity and its determinants, establish causation and identify how trends and patterns change over time.

PROSPERO REGISTRATION NUMBER

CRD42019133453.

Multimorbidity and obesity in older adults from six low- and middle-income countries

Prevalence of multimorbidity (i.e., ≥2 chronic conditions), chronic diseases, and obesity is increasing in low- and middle-income countries (LMICs), posing a potential threat to the health of older adults living in these areas. This study hence investigates the unexplored association between obesity and multimorbidity among older adults from LMICs. Cross-sectional, community-based data from the WHO Study on global Ageing and adult health (SAGE) were analysed. The sample consisted of 20,198 individuals aged ≥60 years [Mean age (SD) = 69.3 (13.1) years; 54.1% female] from China, India, Ghana, Mexico, Russia, South Africa. Twelve chronic conditions were assessed. Multivariable logistic regression was conducted to assess the association between BMI ≥ 30 kg/m², high waist circumference (WC, cut-points > 102 cm for males and > 88 cm for females) and multimorbidity. After adjusting for potential confounders, overall, BMI ≥ 30 kg/m² was associated with 1.43 (95%CI = 1.21-1.69) times higher odds for multimorbidity, while this estimate for high WC was 1.50 (95%CI = 1.21-1.86). Significant associations emerged between obesity measures and five out of twelve chronic conditions. Results from this study underline the need to reduce obesity among older adults in areas where its prevalence is increasing, as it is associated with increased odds for multimorbidity. Future longitudinal research in this setting is required to assess the impact of obesity reduction on multimorbidity incidence.

Non-communicable diseases deaths attributable to high body mass index in Chile

We estimated the proportion and number of deaths from non-communicable diseases (NCD) attributable to high body mass index (BMI) in Chile in 2018. We used data from 5927 adults from a 2016-2017 Chilean National Health Survey to describe the distribution of BMI. We obtained the number of deaths from NCD from the Ministry of Health. Relative risks (RR) and 95% confidence intervals per 5 units higher BMI for cardiovascular disease, cancer, and respiratory disease were retrieved from the Global BMI Mortality Collaboration meta-analyses. The prevalences of overweight and obesity were 38.9% and 39.1%, respectively. We estimated that reducing population-wide BMI to a theoretical minimum risk exposure level (mean BMI: 22.0 kg/m²; standard deviation: 1) could prevent approximately 21,977 deaths per year (95%CI 13,981-29,928). These deaths represented about 31.6% of major NCD deaths (20.1-43.1) and 20.4% of all deaths (12.9-27.7) that occurred in 2018. Most of these preventable deaths were from cardiovascular diseases (11,474 deaths; 95% CI 7302-15,621), followed by cancer (5597 deaths; 95% CI 3560-7622) and respiratory disease (4906 deaths; 95% CI 3119-6684). A substantial burden of NCD deaths was attributable to high BMI in Chile. Policies and population-wide interventions are needed to reduce the burden of NCD due to high BMI in Chile.

Multimorbidity in Latin America and the Caribbean: a systematic review and meta-analysis

OBJECTIVE

To estimate the pooled prevalence of multimorbidity (≥2 non-communicable diseases in the same individual) among adults of the general population of Latin American and the Caribbean (LAC).

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE, Embase, Global Health, Scopus and LILACS up to 1 July 2020.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

The outcome was the prevalence of multimorbidity. Reports were selected whether they enrolled adult individuals (age ≥18 years) from the general population.

DATA EXTRACTION AND SYNTHESIS

Reviewers extracted relevant data and assessed risk of bias independently. A random-effects meta-analysis was conducted to report pooled prevalence estimates of multimorbidity; pooled estimates by pre-specified subgroups (eg, national studies) were also pursued.

RESULTS

From 5830 results, we selected 28 reports, mostly from Brazil and 16 were based on a nationally representative sample. From the 28 selected reports, 26 were further included in the meta-analysis revealing a pooled multimorbidity prevalence of 43% (95% CI: 35% to 51%; I²: 99.9%). When only reports with a nationally representative sample were combined, the pooled prevalence was 37% (95% CI: 27% to 47%; I²: 99.9%). When the ascertainment of multimorbidity was based on self-reports alone, the pooled prevalence was 40% (95% CI: 31% to 48%; I²: 99.9%); this raised to 52% (95% CI: 33% to 70%; I²: 99.9%) for reports including self-reported and objective diagnosis.

CONCLUSIONS

Our results complement and advance those from global efforts by incorporating much more reports from LAC. We revealed a larger presence of multimorbidity in LAC than previously reported.

PROSPERO REGISTRATION NUMBER

CRD42020196177.

An assessment of anthropometric indices and its association with NCDs among the older adults of India: evidence from LASI Wave-1

BACKGROUND

The purpose of this study is to assess the status of physical body indices such as body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) among the older adults aged 45 and above in India. Further, to explore the association of anthropometric indices with various non-communicable morbidities.

METHODS

The study uses secondary data of the Longitudinal Ageing Survey's first wave in India (2017-18). The national representative sample for older adults 45 and above (65,662) considered for the analysis. The prevalence of the non-communicable diseases (NCDs) included in the study is based on the self-reporting of the participants. Diseases included are among the top ten causes of death, such as cancer, hypertension, stroke, chronic heart diseases, diabetes, chronic respiratory diseases, and multi-morbidity. Multi-morbidity is a case of having more than one of the morbidities mentioned above. BMI-obese indicates an individual having a BMI ≥30, and the critical threshold value for high-risk WC for men is ≥102 cm while for women is ≥88 cm. The critical limit for the high-risk WHR for men and women is ≥0.90 and ≥ 0.85, respectively. Descriptive statistics and multiple logistic regressions are used to assess the association BMI, WC, and WHR with non-communicable morbidities.

RESULTS

Based on the multivariate-adjusted model, odds shows that an Indian older adult aged 45 and above is 2.3 times more likely (AOR: 2.33; 95% CI (2.2, 2.5)) by obesity, 61% more likely (AOR: 1.61; 95% CI (1.629, 1.631)) by high-risk WHR and 98% more likely (AOR: 1.98; 95% CI (1.9, 2.1)) by high-risk WC to develop CVDs than their normal counterparts. Similarly, significant positive associations of obesity, high-risk WC, and high-risk WHR were observed with other NCDs and multi-morbidity.

CONCLUSION

Our study shows that obesity, high-risk WC, and high-risk WHR are significant risks for developing NCDs and multi-morbidity among the older adults in India. There is a need for a multi-sectoral approach to reduce the share of the elderly population in high-risk groups of BMIs, WHR, and WC.

Chronic disease multimorbidity among the Canadian population: prevalence and associated lifestyle factors

Background

Chronic diseases is increasingly becoming one of the most pressing public health concerns in most part of the world, including the Canadian population. The purpose of this study was to estimate the prevalence of multimorbidity in the general population based on 14 major chronic diseases and examine associations with lifestyle/behavioral factors.

Methods

The data source was the 2015–2016 Canadian Community Health Survey (CCHS). The CCHS is a cross sectional, complex multi-stage survey based on information collected from 109,659 participants aged 12+, covering all provinces and territories. Multimorbidity was defined as the co-occurrence of two or more chronic diseases within a person. Multiple logistic regression was used to examine the key determinants of multimorbidity.

Results

The prevalence of multimorbidity was 33 %. Adjusting for sociodemographic variables, there was an increased odd of multimorbidity for those having a sedentary lifestyle (AOR = 1.06; CI:1.01–1.11) and being obese (AOR = 1.37; CI:1.32–1.43) or overweight (AOR = 2.65; CI: 2.54–2.76). There were two statistically significant interactions, between sex and smoking, and between immigration status and alcohol intake. Smoking was more strongly associated with multimorbidity in females than males. The association between alcohol intake and multimorbidity was also dependent upon immigration status.

Conclusions

Given the high prevalence of multimorbidity among the general Canadian population, policy makers and service providers should give more attention to the behavioral/lifestyle factors which significantly predicted multimorbidity. Policy and program efforts that promote a healthy lifestyle should be a priority.

Dementia and Adherence to Anti-Diabetic Medications: A Meta-Analysis

Introduction Diabetes mellitus (DM) and dementia (DN) are common morbid disorders with high mortality, the two disorders shared the pathogenesis of proinflammation and insulin resistance. Polypharmacy is expected when DM and DN co-exist and medication adherence is essential to an effective self-care and management plan. This meta-analysis aimed to assess medication persistence among patients with diabetes and cognitive impairment (CogImp). Methods We systematically searched the literature through PubMed, Medline, Cochrane library, and the first 100 articles published in Google Scholar. We included articles publishes in English and conducted on humans, no limitation was set to the date of publication, all the articles were approached from the first published up to March 15, 2021. The keywords used were Dementia, cognitive impairment, cognitive decline, cognitive dysfunction, diabetes self-care, compliance to anti-diabetic drugs, and medication adherence. One hundred-seventy-six were identified, the 12 full texts screened, only four fulfilled the inclusion and exclusion criteria. Results The studies were published in Europe, the United States, and Asia (all were observational). The results showed no effects of dementia on medication adherence, P-value of 0.41, odd ratio: 1.09, 95% CI: 0.89-1.32, Chi-square for heterogeneity: 12.15, I2 = 75%, and standard difference = 3. The P-value for heterogeneity was 0.007. The studies included 2,556 patients and 1,854 events. Conclusion No association was found between dementia and compliance to anti-diabetic medications. Further prospective studies are needed to solve the issue.

Burden of Elevated Body Mass Index and Its Association With Non-Communicable Diseases in Patients Presenting to an Endocrinology Clinic

Introduction In the last 45 years, the worldwide rate of obesity has risen by nearly three-folds. Globally, 650 million adults are obese and more than 1.9 billion are overweight. The estimated prevalence of overweight and obesity in Pakistan was found to be 25% and obesity prevalence alone was 10.3% using the Asian-specific body mass index (BMI) criteria. According to the World Health Organization, overweight and obesity increase the risk of non-communicable diseases (NCDs). Objectives The aim of this retrospective observational study was to determine the burden of elevated BMI and its association with NCDs among patients presenting to a private endocrinology clinic. Study design This was a retrospective observational study conducted at Medicell Institute of Diabetes, Endocrinology & Metabolism (MIDEM), and the study duration was two years. Methodology Medical records of the patients who visited MIDEM from January 2017 to December 2018 were reviewed. Patients' data such as age (in years), gender, height (in cm), and weight (in kg), along with primary complaints and comorbidities were retrieved. BMI was calculated by dividing weight (in kg) by squared height (in m²). Results A total of 613 records were reviewed. The median age and BMI were 38 years (IQR=18 - 80 years) and 28.8 kg/m² (IQR=24.6-33.05 kg/m²),respectively. Out of 613 patients, 10.6% were overweight and 72.6% were obese. Among 510 (83.2%) patients with elevated BMI (≥23 kg/m²), the most frequent associated NCDs were dyslipidemia (39.2%), diabetes (32.5%), hypertension (31.4%), thyroid disorders (28.6%), metabolic syndrome (25%), subfertility (14.9%), impaired glucose tolerance (12.7%) and autoimmune diseases (6.9%). On age- and gender-adjusted logistic regression model, the risk of dyslipidemia, hypertension, and diabetes was significantly higher in overweight and obese patients. Conclusion This study demonstrated a high prevalence of obesity in patients visiting the endocrinology clinic. Obesity was identified as an independent risk factor for dyslipidemia, hypertension, and diabetes. Future studies are suggested to determine the burden of obesity and establish its association with NCDs in the general population.

Health-Related Quality of Life and Health Service Use among Multimorbid Middle-Aged and Older-Aged Adults in China: A Cross-Sectional Study in Shandong Province

(1) Background: The management of multiple chronic diseases challenges China's health system, but current research has neglected how multimorbidity is associated with poor health-related quality of life (HRQOL) and high health service demands by middle-aged and older adults. (2) Methods: A cross-sectional study was conducted in Shandong province, China in 2018 across three age groups: Middle-aged (45 to 59 years), young-old (60 to 74 years), and old-old (75 or above years). The information about socio-economic, health-related behaviors, HRQOL, and health service utilization was collected via face-to-face structured questionnaires. The EQ-5D-3L instrument, comprising a health description system and a visual analog scale (VAS), was used to measure participants' HRQOL, and χ² tests and the one-way ANOVA test were used to analyze differences in socio-demographic factors and HRQOL among the different age groups. Logistic regression models estimated the associations between lifestyle factors, health service utilization, and multimorbidity across age groups. (3) Results: There were 17,867 adults aged 45 or above in our sample, with 9259 (51.82%) female and 65.60% living in rural areas. Compared with the middle-aged adults, the young-old and old-old were more likely to be single and to have a lower level of education and income, with the old-old having lower levels than the young-old (P < 0.001). We found that 2465 (13.80%) suffered multimorbidities of whom 75.21% were older persons (aged 60 or above). As age increased, both the mean values of EQ-5D utility and the VAS scale decreased, displaying an inverse trend to the increase in the number of chronic diseases (P < 0.05). Ex-smokers and physical check-ups for middle or young-old respondents and overweight/obesity for all participants (P < 0.05) were positively correlated with multimorbidity. Drinking within the past month for all participants (P < 0.001), and daily tooth-brushing for middle (P < 0.05) and young-old participants (P < 0.001), were negatively associated with multimorbidity. Multimorbidities increased service utilization including outpatient and inpatient visits and taking self-medicine; and the probability of health utilization was the lowest for the old-old multimorbid patients (P < 0.001). (4) Conclusions: The prevalence and decline in HRQOL of multimorbid middle-aged and older-aged people were severe in Shandong province. Old patients also faced limited access to health services. We recommend early prevention and intervention to address the prevalence of middle-aged and old-aged multimorbidity. Further, the government should set-up special treatment channels for multiple chronic disease sufferers, improve medical insurance policies for the older-aged groups, and set-up multiple chronic disease insurance to effectively alleviate the costs of medical utilization caused by economic pressure for outpatients and inpatients with chronic diseases.

The rising complexity and burden of multimorbidity in a middle-income country

BACKGROUND

The limited knowledge on aetiology, epidemiology and risk factors for multimorbidity especially evident from low and middle-income countries curtail the development and implementation of sustainable healthcare models. Sri Lanka, boasting for one of South Asia's most efficient public health systems that is accessible free-of-charge by the citizens is presently transitioning from lower-middle to upper-middle-income tier. Faced with the triple burden of disease, it is imperative for Sri Lanka to incorporate an integrated model to manage multimorbidity.

METHODS

A descriptive cross-sectional study was carried out in medical clinics of a tertiary care hospital and a University primary care department. Data were extracted on to a form from the clinical records of patients over the age of 20 years with at least one non-communicable disease (NCD) and analysed.

RESULTS

Multimorbidity was present among 64.1% of patients (n = 1600). Nearly 44.44% of the patients aged 20-35 years have a minimum of two disorders, and by the time they reach 50 years, nearly 64% of the patients have two or more non-communicable diseases. Nearly 7% of those aged over 65 years were diagnosed with four or more disorders. A fourth of the sample was affected by co-morbid diabetes mellitus and hypertension, whereas the combinations of coronary heart disease with hypertension and diabetes mellitus were also found to be significantly prevalent. A salient revelation of the binomial logistic regression analysis was that the number of disorders was positively correlated to the presence of mental disorders 7.25 (95% CI = 5.82-8.68).

CONCLUSION

Multimorbidity is highly prevalent among this population and seemingly has a detrimental effect on the psychological wellbeing of those affected. Therefore, the need for horizontal integration of all primary to tertiary care disciplines, including mental health, to manage multimorbidity by policymakers is emphasized as a priority task.

Prevalence and associated socioeconomic factors of multimorbidity in 10 regions of China: an analysis of 0.5 million adults

BACKGROUND

The epidemiology of multiple chronic conditions in China is poorly understood. We investigated the prevalence of multimorbidity among the middle-aged and elderly population in China and analyzed its demographic and socioeconomic correlates.

METHODS

Data were obtained from the baseline of the China Kadoorie Biobank Study, which recruited over 0.5 million participants between 2004 and 2008. We calculated the prevalence by the characteristics of multimorbidity. The demographic and socioeconomic correlates were analyzed using a multivariable logistic regression model.

RESULTS

15.9% of the participants were multimorbid. Although the prevalence of multimorbidity increased with age, the absolute number of people with multimorbidity was much higher among middle-aged adults (30-60 years, n = 42 041) than the elderly group (>60 years, n = 38 834). The odd of multimorbidity was higher in males (aOR =1.09, 95% CI: 1.07-1.11) and among those who were unemployed (aOR = 1.58, 95% CI: 1.55-1.62). Those who received the highest level of education were most likely to be multimorbid compared with those with no education (aOR = 1.14, 95% CI: 1.09-1.19). Such an association was similar when treating multimorbidity as multinomial variable.

CONCLUSIONS

Multimorbidity is a public health concern, with higher prevalence among the elderly, males and those who belong to a lower socioeconomic stratum. Actions are needed to curb multimorbidity epidemic in China.

Association between Overweight, Obesity and the Prevalence of Multimorbidity among the Elderly: Evidence from a Cross-Sectional Analysis in Shandong, China

(1) Background: Multimorbidity, defined as the occurrence of two or more chronic diseases, is a global public health problem which has a significant negative impact on individuals, families and the society. The aim of this study was to evaluate the association between overweight, obesity and the prevalence of multimorbidity among male and female older adults; (2) Methods: Cross-sectional data of the 7070 participants from China, aged 60 years and above included in 2017 the Shandong Elderly Family Health Service Survey were analyzed. Multivariate logistic regression analysis was used to examine the relationship between overweight, obesity and the prevalence of multimorbidity in males and females; (3) Results: Among the 7070 participants, of which 40.25% were males and 59.75% were females, the average age of all participants was (69.81 ± 6.45) years old. The prevalence of multimorbidity in older adults was 34.71%, and the overweight and obesity rates were 39.25% and 16.89%. Among the male elderly, the likelihood of multimorbidity was more than two times higher among the obese than the normal BMI population (OR: 2.14; 95%CI: 1.63–2.82). A less strong association was found in the overweight male older population (OR: 1.43; 95%CI: 1.18–1.74). In the females, compared with individuals with normal BMI, the risks for incident multimorbidity were high in the overweight and obese groups, with odds ratios of 1.42 (95%CI: 1.21–1.65) and 1.81 (95%CI: 1.51–2.17), respectively. (4) Conclusions: In this study, overweight and obesity had the strongest association with the prevalence of multimorbidity among Chinese older adults, and the associations were different between the male and female elderly. The prevalence of multimorbidity might be effectively prevented by controlling body mass index. Encouraging the elderly to eat the recommended amount of vegetables and fruits, walk at least 30 min a day and have enough sleep to maintain a healthy weight.

The burden of non-communicable diseases attributable to high BMI in Brazil, 1990-2017: findings from the Global Burden of Disease Study

BACKGROUND

The prevalence and burden of disease resulting from obesity have increased worldwide. In Brazil, more than half of the population is now overweight. However, the impact of this growing risk factor on disease burden remains inexact. Using the 2017 Global Burden of Disease (GBD) results, this study sought to estimate mortality and disability-adjusted life years (DALYs) lost to non-communicable diseases caused by high body mass index (BMI) in both sexes and across age categories. This study also aimed to describe the prevalence of overweight and obesity throughout the states of Brazil.

METHODS

Age-standardized prevalence of overweight and obesity were estimated between 1990 and 2017. A comparative risk assessment was applied to estimate DALYs and deaths for non-communicable diseases and for all causes linked to high BMI.

RESULTS

The prevalence of overweight and obesity increased during the period of analysis. Overall, age-standardized prevalence of obesity in Brazil was higher in females (29.8%) than in males (24.6%) in 2017; however, since 1990, males have presented greater rise in obesity (244.1%) than females (165.7%). Increases in prevalence burden were greatest in states from the North and Northeast regions of Brazil. Overall, burden due to high BMI also increased from 1990 to 2017. In 2017, high BMI was responsible for 12.3% (8.8-16.1%) of all deaths and 8.4% (6.3-10.7%) of total DALYs lost to non-communicable diseases, up from 7.2% (4.1-10.8%), and 4.6% (2.4-6.0%) in 1990, respectively. Change due to risk exposure is the leading contributor to the growth of BMI burden in Brazil. In 2017, high BMI was responsible for 165,954 deaths and 5,095,125 DALYs. Cardiovascular disease and diabetes have proven to be the most prevalent causes of deaths, along with DALYs caused by high BMI, regardless of sex or state.

CONCLUSIONS

This study demonstrates increasing age-standardized prevalence of obesity in all Brazilian states. High BMI plays an important role in disease burdens in terms of cardiovascular diseases, diabetes, and all causes of mortality. Assessing levels and trends in exposures to high BMI and the resulting disease burden highlights the current priority for primary prevention and public health action initiatives focused on obesity.

Association between obesity-related anthropometric indices and multimorbidity among older adults in Shandong, China: a cross-sectional study

OBJECTIVES

Whether the association between obesity-related anthropometric indices and multimorbidity differs by age among Chinese older adults (aged 65+) is unclear. We aimed to investigate the association between body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) with multimorbidity among the young-old (aged 65-79) and old-old (aged 80+) adults.

DESIGN

Cross-sectional population-based study.

SETTING

Shandong province on the eastern coast of China.

PARTICIPANTS

5493 subjects aged 65 years or above.

MEASUREMENTS

Details on sociodemographics, lifestyle characteristics and chronic conditions were collected using a structured questionnaire. The respondents were assessed with anthropometric measurements including height, weight, WC, hip circumference.

RESULTS

The overall prevalence of multimorbidity in older adults (aged 65+) was 35.2%. The BMI-obesity, WC-obesity and WHR-obesity rates were 7.4%, 57.5% and 80.4%, respectively. In the young-old adults (aged 65-79), the likelihood of multimorbidity was more than two times higher among the BMI-obese than the BMI-normal population (OR 2.08, 95% CI 1.66 to 2.60). Similar but less strong associations were found for the WC-obese and WHR-obese young-old population (OR 1.60, 95% CI 1.42 to 1.81; OR 1.31, 95% CI 1.10 to 1.56, respectively). For the old-old group (aged 80+), the BMI-obese, WC-obese and WHR-obese had a higher likelihood of having multimorbidity compared with the normal weight category (OR 2.10, 95% CI 0.96 to 4.57; OR 1.75, 95% CI 1.21 to 2.54; OR 2.15, 95% CI 1.18 to 3.93, respectively).

CONCLUSION

BMI-obesity, WC-obesity and WHR-obesity were associated with a greater risk of multimorbidity, and the associations were different between the young-old and the old-old adults. These age differences need to be considered in assessing healthy body weight in old age. These findings may be vital for public health surveillance, prevention and management strategies for multimorbidity in older adults.

Multimorbidity of chronic non-communicable diseases in low- and middle-income countries: A scoping review

BACKGROUND

Multimorbidity is rising in low- and middle-income countries (LMICs). However, the evidence on its epidemiology from LMICs settings is limited and the available literature has not been synthesized as yet.

OBJECTIVES

To review the available evidence on the epidemiology of multimorbidity in LMICs.

METHODS

PubMed, Scopus, PsycINFO and Grey literature databases were searched. We followed the PRISMA-ScR reporting guideline.

RESULTS

Of 33, 110 articles retrieved, 76 studies were eligible for the epidemiology of multimorbidity. Of these 76 studies, 66 (86.8%) were individual country studies. Fifty-two (78.8%) of which were confined to only six middle-income countries: Brazil, China, South Africa, India, Mexico and Iran. The majority (n = 68, 89.5%) of the studies were crosssectional in nature. The sample size varied from 103 to 242, 952. The largest proportion (n = 33, 43.4%) of the studies enrolled adults. Marked variations existed in defining and measuring multimorbidity. The prevalence of multimorbidity in LMICs ranged from 3.2% to 90.5%.

CONCLUSION AND RECOMMENDATIONS

Studies on the epidemiology of multimorbidity in LMICs are limited and the available ones are concentrated in few countries. Despite variations in measurement and definition, studies consistently reported high prevalence of multimorbidity. Further research is urgently required to better understand the epidemiology of multimorbidity and define the best possible interventions to improve outcomes of patients with multimorbidity in LMICs.

Association of obesity measures and multimorbidity in Pakistan: findings from the IMPACT study

OBJECTIVE

Obesity is a major factor leading to multimorbidity. However, the relative importance of obesity measures, including body mass index (BMI), body fat percentage (BF%) and visceral fat (VF), in relation to multimorbidity has not been extensively studied in Asia. Therefore, the objective of this study was to examine the relation of these measures of obesity with multimorbidity in a representative community sample in Pakistan.

STUDY DESIGN

This is a community-based cross-sectional study.

METHODS

This study was conducted among residents of Gulshan town, Karachi, Pakistan. Data on healthy individuals and individuals with chronic conditions were recorded. All self-reported chronic conditions were further assessed by physical examination, medical history of the participants and laboratory findings. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses of BMI, BF% and VF as predictors of obesity were used to examine the association with multimorbidity.

RESULTS

A total of 1500 participants (738 men and 762 women) were recruited, with a median age of 54.5 years. Multivariate logistic regression showed a significant association of BMI (odds ratio [OR] = 1.28, 95% confidence interval [CI] = 1.00-1.81, P-value 0.049) and BF% (OR = 2.28, 95% CI = 1.50-3.45, P-value <0.001) with multimorbidity. However, the ROC analysis for BMI, BF% and VF showed very similar results, even when the analysis was stratified by gender. In this exploratory analysis, increasing age and female gender were significantly associated with multimorbidity compared with their counterparts.

CONCLUSIONS

Adult populations with high BF% levels carry a higher risk of multimorbidity than those with high BMI scores. In a population with differing metabolic characteristics, BMI might be less precise than direct adiposity measurements. Additional studies are needed to confirm the potential use of measuring the anatomical location and metabolic characteristics of lean and fat mass to identify risk of diseases.

Multimorbidity and complex multimorbidity in Brazilian rural workers

OBJECTIVE

To estimate the prevalence of multimorbidity and complex multimorbidity in rural workers and their association with sociodemographic characteristics, occupational contact with pesticides, lifestyle and clinical condition.

METHODS

This is a cross-sectional epidemiological study with 806 farmers from the main agricultural municipality of the state of Espírito Santo/Brazil, conducted from December 2016 to April 2017. Multimorbidity was defined as the presence of two or more chronic diseases in the same individual, while complex multimorbidity was classified as the occurrence of three or more chronic conditions affecting three or more body systems. Socio-demographic data, occupational contact with pesticides, lifestyle data and clinical condition data were collected through a structured questionnaire. Binary logistic regression was conducted to identify risk factors for multimorbidity.

RESULTS

The prevalence of multimorbidity among farmers was 41.5% (n = 328), and complex multimorbidity was 16.7% (n = 132). More than 77% of farmers had at least one chronic illness. Hypertension, dyslipidemia and depression were the most prevalent morbidities. Being 40 years or older (OR 3.33, 95% CI 2.06-5.39), previous medical diagnosis of pesticide poisoning (OR 1.89, 95% CI 1.03-3.44), high waist circumference (OR 2.82, CI 95% 1.98-4.02) and worse health self-assessment (OR 2.10, 95% CI 1.52-2.91) significantly increased the chances of multimorbidity. The same associations were found for the diagnosis of complex multimorbidity.

CONCLUSION

We identified a high prevalence of multimorbidity and complex multimorbidity among the evaluated farmers. These results were associated with increased age, abdominal fat, pesticide poisoning, and poor or fair health self-assessment. Public policies are necessary to prevent, control and treat this condition in this population.

A Cross-National Study of the Gender Gap in Health Among Older Adults in India and China: Similarities and Disparities

Background and Objectives

The present cross-sectional study examines gender differences in three major health measures among older adults in India and in China, and investigates whether these differences can be explained by major sociodemographic and health risk characteristics.

Research Design and Methods

The study included 7,150 individuals in India and 13,367 individuals in China aged 50-plus who participated in the WHO Study on Global AGEing and Adult Health in 2007-2010. Logistic regression models for self-reported health (SRH) and ordinary least square regression models for grip strength and cognitive function were used to investigate gender differences in health.

Results

A consistent female disadvantage was found in India and in China for all three health measures. Compared to their male counterparts, women in the Indian and the Chinese samples had, respectively, 38% (95% confidence interval [CI]: 1.22, 1.56) and 36% (95% CI: 1.25, 1.48) higher risk of reporting poor SRH, 9.56 kg (95% CI: 9.91, 9.22) and 11.95 kg (95% CI: 12.29, 11.62) lower grip strength, and 3.64 (95% CI: 3.96, 3.32) and 1.99 (95% CI: 2.28, 1.71) lower cognitive scores. The magnitude of the female disadvantage in poor SRH and in grip strength changed very little when adjustments were made for marital status, education, place of residence, smoking status, height, and number of chronic conditions; but these characteristics accounted for about 50% of the gender gap in cognitive function.

Discussion and Implications

In these study populations, major sociodemographic and health risk characteristics accounted for very small parts of the gender differences in health, except in cognition.

Epidemiology of obesity and its related morbidities among rural population attending a primary health centre of Odisha, India

Context:

Overweight and obesity has become a major contributor to global burden of chronic diseases and disability. Obesity among rural India is emerging as a major health problem because of change in lifestyle and food habits, thereby increases the risk of multiple morbid conditions among rural population.

Aims:

This study aims to find out the association of overweight/obesity with different socio-demographic factors and explore the co-morbidities among overweight and obese in a rural setting.

Settings and Design:

A cross-sectional study was done in a randomly selected primary health centre of Khurda district, Odisha for 4 months.

Materials and Methods:

This study was done among 183 patients aged >20 years with BMI >25 kg/m² after taking their consent. Anthropometric measurements were done and data were collected using a semi-structured questionnaire.

Statistical Analysis Used:

Descriptive statistics such as proportion, mean and standard deviation were calculated and inferential statistics such as Chi-square test, univariate and multivariate regression was done using the SPSS version 20.0.

Results:

Mean age of participants was 45.7 (±13.8) years. About 93.4% were Grade II obese while 51.9% were at risk according to their waist–hip ratio. Around 53.6% of participants had multi-morbidity. Age, occupation and number of children were significantly associated with obesity. Morbidity was significantly associated with age, occupation, marital status and number of children. Increased grade in obesity the more is the probability of having morbidity.

Conclusions:

There is an urgent need to screen for obesity at rural health facility and early management for prevention from co-morbidities.

Multimorbidity in South Asian adults: prevalence, risk factors and mortality

BACKGROUND

We report the prevalence, risk factors and mortality associated with multimorbidity in urban South Asian adults.

METHODS

Hypertension, diabetes, heart disease, stroke and chronic kidney disease were measured at baseline in a sample of 16 287 adults ages ≥20 years in Delhi, Chennai and Karachi in 2010-11 followed for an average of 38 months. Multimorbidity was defined as having ≥2 chronic conditions at baseline. We identified correlates of multimorbidity at baseline using multinomial logistic models, and we assessed the prospective association between multimorbidity and mortality using Cox proportional hazards models.

RESULTS

The adjusted prevalence of multimorbidity was 9.4%; multimorbidity was highest in adults who were aged ≥60 years (37%), consumed alcohol (12.3%), body mass index ≥25 m/kg2 (14.1%), high waist circumference (17.1%) and had family history of a chronic condition (12.4%). Compared with adults with no chronic conditions, the fully adjusted relative hazard of death was twice as high in adults with two morbidities (hazard ratio [HR] = 2.3; 95% confidence interval [CI]: 1.6, 3.3) and thrice as high in adults with ≥3 morbidities (HR = 3.1; 95% CI: 1.9, 5.1).

CONCLUSION

Multimorbidity affects nearly 1 in 10 urban South Asians, and each additional morbidity carries a progressively higher risk of death. Identifying locally appropriate strategies for prevention and coordinated management of multimorbidity will benefit population health in the region.

Lifestyle factors and high body mass index are associated with different multimorbidity clusters in the Brazilian population

Multimorbidity patterns of a population can be influenced by socioeconomic and lifestyle-related factors. Some of these factors are preventable when healthy habits are promoted to the population. This study analyzed the main grouping patterns of chronic diseases and the relationship with socioeconomic and lifestyle-related factors of the Brazilian population (over the age of 18), based on a population-based survey (2013 National Health Survey). A total of 60,202 participants were included. Cluster analysis was carried out to identify the combinations of chronic diseases. Bivariate and multivariate analyses were carried out to verify the relationship between disease clusters and independent variables, utilizing Poisson's regression with robust variance, considering a 95% confidence interval. Cluster analysis revealed four disease clusters:cardiometabolic diseases/cancer, mental/occupational diseases, musculoskeletal diseases and respiratory diseases, all significantly associated with the female gender, current/past smoking habits and overweight/obesity in multivariate analyses. These aspects must be considered when planning health services and developing strategies and guidelines for the prevention and treatment of multiple chronic conditions.