Dataset Information

Findings from the Indonesian family life survey on patterns and factors associated with multimorbidity.

ABSTRACT: The prevalence of multimorbidity tends to increase with age, but it is now also reported in the middle-aged population, which has a negative impact on healthcare systems and health outcomes. This study aims to analyze the patterns and factors associated with multimorbidity in Indonesia. This national cross-sectional population-based survey used publicly available data from the Indonesian Family Life Survey (IFLS-5) for 2014 among middle-aged (40-59 years old) and elderly (≥ 60 years old) respondents. Information on all chronic diseases was assessed using a self-reported questionnaire. Sociodemographic and health-related behavioral factors were obtained from self-reported data. Binary logistic regression analysis was used to identify the factors associated with multimorbidity. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported. The study recruited 11,867 respondents. The prevalence of multimorbidity was 18.6% (95% CI 17.9-19.3) with which 15.6% among middle age (95% CI 14.95-16.25) and 24.9% among the elderly (95% CI 24.12-25.68). Hypertension was the most commonly reported disease (23.2%) in all combinations of multimorbidity and among all age groups. Socio-demographic factors: elderly (AOR: 1.66; 95% CI 1.46-1.89), female (AOR: 1.42; 95% CI 1.20-1.69), living in the urban area (AOR: 1.22; 95% CI 1.09-1.38), higher educational level (AOR: 2.49; 95% CI 1.91-3.26), unemployed (AOR: 1.63; 95% CI 1.44-1.84), and higher economic level (AOR: 1.41; 95% CI 1.18-1.68) were associated with multimorbidity. Poor health behavior factors: being former smokers (AOR: 2.03; 95% CI 1.65-2.51) and obesity (AOR: 1.53; 95% CI 1.35-1.75) were also associated with multimorbidity. The prevalence of multimorbidity in the middle-aged and elderly population in Indonesia is relatively high, particularly in populations with poor health behaviors. Therefore, healthcare professionals should integrate more patient-specific factors when designing and implementing tailored interventions to manage multimorbidity in Indonesia.

SUBMITTER: Griselda M

PROVIDER: S-EPMC10616186 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Findings from the Indonesian family life survey on patterns and factors associated with multimorbidity.

Griselda Meliana M Alfian Sofa D SD Wicaksono Imam A IA Wawruch Martin M Abdulah Rizky R

Scientific reports 20231030 1

The prevalence of multimorbidity tends to increase with age, but it is now also reported in the middle-aged population, which has a negative impact on healthcare systems and health outcomes. This study aims to analyze the patterns and factors associated with multimorbidity in Indonesia. This national cross-sectional population-based survey used publicly available data from the Indonesian Family Life Survey (IFLS-5) for 2014 among middle-aged (40-59 years old) and elderly (≥ 60 years old) respond ...[more]

PMID: 37903815

Similar Datasets

Project description:BackgroundDiabetes is increasing rapidly in South-East Asia. Studies have reported typical risk factors associated with all-age adult diabetes and highlighted the roles of economic transition and childhood development factors in diabetes in later life. However, little is known about whether these factors were associated with young adult diabetes risk.ObjectivesThe study has two main aims: (1) estimate diabetes prevalence among adult participants of the Indonesian Family Life Survey (IFLS), and (2) identify childhood development factors associated with early-onset adult diabetes (diagnosed between age 20 and 40) in Indonesia.MethodsData were taken from adults participating in 4th and 5th IFLS (in 2007 and 2014) and linked to childhood history from previous surveys. Diabetes was ascertained from self-report and HbA1c testing in a subsample. Diabetes prevalence rates were estimated by age and source of diagnosis. Cox regression analysis was applied to assess potential risk factors for early-onset adult diabetes.ResultsA total of 34,767 participants were included in the study. Crude total prevalence estimate from self-report was 2,3% and increased with age. Including HbA1c measurements yielded nearly eight times higher prevalence estimates, depending on age. The proportion of yet undiagnosed cases is considerably higher in young age groups. Regression analyses showed that urban childhood residence and high education increased early-onset diabetes risk by 50-70%. Sex, childhood general health, socio-economic level and starvation exposure were not associated with early-onset diabetes risk.ConclusionRemarkable differences between diabetes prevalence rates based on self-report and HbA1c measurement indicated the need for better diagnosis, especially in young adults. Urban childhood residence and high education increased early-onset adult diabetes risk. Incorporating these factors and diabetes awareness in existing child health programs, together with screening of individuals at risk, could improve early diabetes detection and prevention strategies among young urban Indonesian adults.

Project description:BackgroundSocial-economic factors and health behaviours may be driving variation in ethnic health inequalities in multimorbidity including among distinct ethnic groups.MethodsUsing the cross-sectional nationally representative Health Surveys for England 2011-18 (N = 54 438, aged 16+), we performed multivariable logistic regression on the odds of having general multimorbidity (≥2 longstanding conditions) by ethnicity [British White (reference group), White Irish, Other White, Indian, Pakistani, Bangladeshi, Chinese, African, Caribbean, White mixed, Other Mixed], adjusting for age, sex, education, area deprivation, obesity, smoking status and survey year. This was repeated for cardiovascular multimorbidity (N = 37 148, aged 40+: having ≥2 of the following: self-reported diabetes, hypertension, heart attack or stroke) and multiple cardiometabolic risk biomarkers (HbA1c ≥6.5%, raised blood pressure, total cholesterol ≥5mmol/L).ResultsTwenty percent of adults had general multimorbidity. In fully adjusted models, compared with the White British majority, Other White [odds ratio (OR) = 0.63; 95% confidence interval (CI) 0.53-0.74], Chinese (OR = 0.58, 95% CI 0.36-0.93) and African adults (OR = 0.54, 95% CI 0.42-0.69), had lower odds of general multimorbidity. Among adults aged 40+, Pakistani (OR = 1.27, 95% CI 0.97-1.66; P = 0.080) and Bangladeshi (OR = 1.75, 95% CI 1.16-2.65) had increased odds, and African adults had decreased odds (OR = 0.63, 95% CI 0.47-0.83) of general multimorbidity. Risk of cardiovascular multimorbidity was higher among Indian (OR = 3.31, 95% CI 2.56-4.28), Pakistani (OR = 3.48, 95% CI 2.52-4.80), Bangladeshi (OR = 3.67, 95% CI 1.98-6.78), African (OR = 1.61, 95% CI 1.05-2.47), Caribbean (OR = 2.18, 95% CI 1.59-2.99) and White mixed (OR = 1.98, 95% CI 1.14-3.44) adults. Indian adults were also at risk of having multiple cardiometabolic risk biomarkers.ConclusionEthnic inequalities in multimorbidity are independent of social-economic factors. Ethnic minority groups are particularly at risk of cardiovascular multimorbidity, which may be exacerbated by poorer management of cardiometabolic risk requiring further investigation.

Project description:BackgroundMalaria is still an important parasitic infectious disease that affecting poor and vulnerable communities in many developing countries, including Indonesia. During the period of 2010-2017, there have been approximately 2.2 million confirmed malaria cases reported across Indonesia. This study aimed to identify individual, household and village-level factors associated with self-reported malaria among adults more than 15 years of age in Maluku, West Papua and Papua province.MethodsThis study analysed a subset of the data from nationally representative population-based Indonesian National Basic Health Research (Riset Kesehatan Dasar) (N = 1,027,763 in 294,959 households in 33 provinces) in 2013. Total of 41,079 individuals (20,326 males and 20,753 females) aged ≥ 15 years in 19,269 households in Maluku, West Papua and Papua provinces were included. Participants were interviewed if they ever had been diagnosed and laboratory confirmed of having malaria by physician in the past 12 months. A mixed effects multilevel logistic regression models were developed to assess the associations between socio-demographical variables at individual, household and village level and self-reported malaria.ResultsIndividuals aged ≥ 15 years in 701 villages in Maluku (n = 11,919), West Papua (n = 8003) and Papua (n = 21,157) were analysed. In all provinces, gender distribution was equally-represented. The prevalence of self-reported malaria was 4.1% (Maluku), 12.4% (West Papua) and 18.8% (Papua). At the individual level, primary industry workers (OR 1.29, 95% CI 1.15-1.46 [Maluku]; OR 1.17, 95% CI 1.09-1.25 [Papua]) and having higher education were associated with self-reporting malaria (OR 0.67, 95% CI 0.53-0.83 [Maluku]; OR 1.27, 95% CI 1.15-1.40 [Papua]). Household level factors include having bed net and better off wealth index were associated with increased self-reporting malaria among West Papua (OR 1.21; 95% CI 1.09-1.34 and OR 1.38; 95% CI 1.17-1.65, respectively) and Papuan (OR 1.12; 95% CI 1.02-1.23 and OR 1.33; 95% CI 1.11-1.57, respectively) adults. Increased odds of self-reporting malaria was associated with time required to reach healthcare facility (OR 1.30, 95% CI 1.01-1.67 [Maluku]). Contextual village-level characteristics such as living in rural (OR 1.31, 95% CI 1.12-1.54 [Maluku]; OR 1.56, 95% CI 1.17-2.07 [West Papua]), higher community education level (OR 1.28, 95% CI 1.02-1.63 [West Papua]; OR 1.45, 95% CI 1.23-1.72 [Papua]), higher community bed net ownerships (OR 0.59 95% CI 0.45-0.77 [West Papua]) were associated with self-reported malaria.ConclusionsFactors associated with self-reported malaria were varied between provinces suggesting locally-specific determinants were exist at individual, household and community-level. This study highlights the need for specific interventions by taking into consideration the contextual factors within the region and involving multi-sectoral collaboration between health authorities and related stakeholders (e.g., bureau of education, bureau of public works and infrastructure) to improve designs in planning and intervention strategies to succesfully eliminate malaria in Maluku and Papua.

Dataset Information

Findings from the Indonesian family life survey on patterns and factors associated with multimorbidity.

Publications

Findings from the Indonesian family life survey on patterns and factors associated with multimorbidity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets