Gender differences in the Prevalence and Pattern of Disease Combination of Chronic Multimorbidity among Indian Elderly

Sharma, Palak; Maurya, Priya

doi:10.1007/s12126-021-09419-9

Cited by 9 publications

(26 citation statements)

References 23 publications

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“…The findings are congruent with the literature in LMICs,15 27 28 but not with the findings of the Collaborative Research on Ageing in Europe study conducted in Finland, Poland and Spain,26 the HICs. This discrepancy could be attributed to shared effects of biological, social, psychological and environmental factors that generated inequalities in health status 29 30. Education level appears to be associated with a higher risk of multimorbidity in our study.…”

Section: Discussioncontrasting

confidence: 57%

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Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium

et al. 2022

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ObjectivesTo assess the prevalence and factors associated with multimorbidity in a community-dwelling general adult population on a large Health and Demographic Surveillance System (HDSS) scale.DesignPopulation-based cross-sectional study.SettingSouth East Asia Community Observatory HDSS site in Malaysia.ParticipantsOf 45 246 participants recruited from 13 431 households, 18 101 eligible adults aged 18–97 years (mean age 47 years, 55.6% female) were included.Main outcome measuresThe main outcome was prevalence of multimorbidity. Multimorbidity was defined as the coexistence of two or more chronic conditions per individual. A total of 13 chronic diseases were selected and were further classified into 11 medical conditions to account for multimorbidity. The conditions were heart disease, stroke, diabetes mellitus, hypertension, chronic kidney disease, musculoskeletal disorder, obesity, asthma, vision problem, hearing problem and physical mobility problem. Risk factors for multimorbidity were also analysed.ResultsOf the study cohort, 28.5% people lived with multimorbidity. The individual prevalence of the chronic conditions ranged from 1.0% to 24.7%, with musculoskeletal disorder (24.7%), obesity (20.7%) and hypertension (18.4%) as the most prevalent chronic conditions. The number of chronic conditions increased linearly with age (p<0.001). In the logistic regression model, multimorbidity is associated with female sex (adjusted OR 1.28, 95% CI 1.17 to 1.40, p<0.001), education levels (primary education compared with no education: adjusted OR 0.63, 95% CI 0.53 to 0.74; secondary education: adjusted OR 0.60, 95% CI 0.51 to 0.70; tertiary education: adjusted OR 0.65, 95% CI 0.54 to 0.80; p<0.001) and employment status (working adults compared with retirees: adjusted OR 0.70, 95% CI 0.60 to 0.82, p<0.001), in addition to age (adjusted OR 1.05, 95% CI 1.05 to 1.05, p<0.001).ConclusionsThe current single-disease services in primary and secondary care should be accompanied by strategies to address complexities associated with multimorbidity, taking into account the factors associated with multimorbidity identified. Future research is needed to identify the most commonly occurring clusters of chronic diseases and their risk factors to develop more efficient and effective multimorbidity prevention and treatment strategies.

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Section: Discussioncontrasting

confidence: 57%

“…30 Education level appears Numbers may not add up to totals due to missing data. Statistical significance testing by χ 2 test and independent t-test.…”

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confidence: 99%

Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium

et al. 2022

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“…Following the title and abstract screening, 93 records were left for the full‐text screening. Finally, 16 studies were included in this systematic review 1,18,19,50‐62 . Out of these 16 studies, 15 were included in the meta‐analysis 1,18,19,50,52‐62 .…”

Section: Resultsmentioning

confidence: 99%

Risk factors of multimorbidity among older adults in India: A systematic review and meta‐analysis

Goel,

Biswas,

Chattopadhyay

2024

Health Science Reports

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BackgroundMultimorbidity among older adults is a growing concern in India. Multimorbidity is defined as the coexistence of two or more chronic health conditions in an individual. Primary studies have been conducted on risk factors of multimorbidity in India, but no systematic review has been conducted on this topic. This systematic review aimed to synthesize the existing evidence on risk factors of multimorbidity among older adults in India.MethodsThe JBI and Preferred Reporting Items for Systematic Reviews and Meta‐Analysis guidelines were followed. Several databases were searched for published and unpublished studies until August 03, 2022. The screening of titles and abstracts and full texts, data extraction, and quality assessment were conducted by two independent reviewers. Any disagreements were resolved through discussion or by involving a third reviewer. Data synthesis was conducted using narrative synthesis and random effects meta‐analysis, where appropriate.ResultsOut of 8781 records identified from the literature search, 16 and 15 studies were included in the systematic review and meta‐analysis, respectively. All included studies were cross‐sectional, and 10 met a critical appraisal score of more than 70%. Broadly, sociodemographic, lifestyle, and health conditions‐related factors were explored in these studies. The pooled odds of multimorbidity were higher in people aged ≥70 years compared to 60‐69 years (odds ratio (OR) 1.51; 95% confidence interval (CI) 1.20–1.91), females compared to males (1.38; 1.09–1.75), single, divorced, separated, and widowed compared to married (1.29; 1.11–1.49), economically dependent compared to economically independent (1.54; 1.21–1.97), and smokers compared to non‐smokers (1.33; 1.16–1.52) and were lower in working compared to not working (0.51; 0.36–0.72).ConclusionThis systematic review and meta‐analysis provided a comprehensive picture of the problem by synthesizing the existing evidence on risk factors of multimorbidity among older adults in India. These synthesized sociodemographic and lifestyle factors should be taken into consideration when developing health interventions for addressing multimorbidity among older adults in India.

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“…Twenty studies were from low-income and middle-income countries12 34–52 and the remaining 45 studies were from high-income countries. The majority of articles were conducted among adults and only three study included children 53–55.…”

Section: Resultsmentioning

confidence: 99%

“…Educational attainment was the preferred measure of socioeconomic position (n=38/64), and 38 studies used multiple measures of socioeconomic position as exposures. The majority of studies (n=51/64) simply documented the presence of multimorbidity, and approximately one-third (n=13/64) additionally examined different patterns of multimorbidity9 40 41 45 47 53 55 67–70 72 75 77 78 (table 2).…”

Section: Resultsmentioning

confidence: 99%

Theoretical explanations for socioeconomic inequalities in multimorbidity: a scoping review

et al. 2022

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ObjectiveTo document socioepidemiological theories used to explain the relationship between socioeconomic disadvantage and multimorbidity.DesignScoping review.MethodsA search strategy was developed and then applied to multiple electronic databases including Medline, Embase, PsychInfo, Web of Science, Scielo, Applied Social Sciences, ERIC, Humanities Index and Sociological Abstracts. After the selection of studies, data were extracted using a data charting plan. The last search was performed on the 28 September 2021. Extracted data included: study design, country, population subgroups, measures of socioeconomic inequality, assessment of multimorbidity and conclusion on the association between socioeconomic variables and multimorbidity. Included studies were further assessed on their use of theory, type of theories used and context of application. Finally, we conducted a meta-narrative synthesis to summarise the results.ResultsA total of 64 studies were included in the review. Of these, 33 papers included theories as explanations for the association between socioeconomic position and multimorbidity. Within this group, 16 explicitly stated those theories and five tested at least one theory. Behavioural theories (health behaviours) were the most frequently used, followed by materialist (access to health resources) and psychosocial (stress pathways) theories. Most studies used theories as post hoc explanations for their findings or for study rationale. Supportive evidence was found for the role of material, behavioural and life course theories in explaining the relationship between social inequalities and multimorbidity.ConclusionGiven the widely reported social inequalities in multimorbidity and its increasing public health burden, there is a critical gap in evidence on pathways from socioeconomic disadvantage to multimorbidity. Generating evidence of these pathways will guide the development of intervention and public policies to prevent multimorbidity among people living in social disadvantage. Material, behavioural and life course pathways can be targeted to reduce the negative effect of low socioeconomic position on multimorbidity.

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Gender differences in the Prevalence and Pattern of Disease Combination of Chronic Multimorbidity among Indian Elderly

Cited by 9 publications

References 23 publications

Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium

Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium

Risk factors of multimorbidity among older adults in India: A systematic review and meta‐analysis

Theoretical explanations for socioeconomic inequalities in multimorbidity: a scoping review

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