Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019

ObjectivesWe analysed predictors of health insurance enrolment in Nepal, measured wealth-related inequality and decomposed inequality into its contributing factors.DesignCross-sectional study.SettingWe used nationally representative data based on Nepal Multiple Indicator Cluster Survey 2019. Out of 10 958 households included in this study, 6.95% households were enroled in at least one health insurance scheme.Primary outcomemeasures health insurance (of any type) enrolment.ResultsHouseholds were more likely to have health insurance membership when household head have higher secondary education or above compared with households without formal education (adjusted OR 1.87; 95% CI: 1.32 to 2.64)). Households with mass media exposure were nearly three times more likely to get enroled into the schemes compared with their counterparts (adjusted OR 2.96; 95% CI 2.03 to 4.31). Hindus had greater odds of being enroled (adjusted OR 1.82; 95% CI 1.20 to 2.77) compared with non-Hindus. Dalits were less likely to get enroled compared with Brahmin, Chhetri and Madhesi (adjusted OR 0.66; 95% CI 0.47 to 0.94). Households from province 2, Bagmati and Sudurpaschim were less likely to have membership compared with households from province 1. Households from Richer and Richest wealth quintiles were more than two times more likely to have health insurance membership compared with households from the poorest wealth quintile. A positive concentration index 0.25 (95% CI 0.21 to 0.30; p<0.001) indicated disproportionately higher health insurance enrolment among wealthy households.ConclusionsEducation of household head, exposure to mass media, religious and ethnic background, geographical location (province) and wealth status were key predictors of health insurance enrolment in Nepal. There was a significant wealth-related inequality in health insurance affiliation. The study recommends regular monitoring of inequality in health insurance enrolment across demographic and socioeconomic groups to ensure progress towards Universal Health Coverage.

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Predictors of wealth-related inequality in institutional delivery: a decomposition analysis using Nepal Multiple Indicator Cluster Survey (MICS) 2019

10.21203/rs.3.rs-539128/v1 ◽

2021 ◽

Author(s):

Umesh Prasad Bhusal

Keyword(s):

Institutional Delivery ◽

Relative Concentration ◽

National Level ◽

Household Head ◽

Decomposition Analysis ◽

Cluster Survey ◽

Related Inequality ◽

Multiple Indicator Cluster Survey ◽

Multiple Indicator ◽

Status Of Women

Abstract Background Inequality in maternal healthcare use is a major concern for low-and middle-income countries (LMICs). Maternal health indicators at the national level have markedly improved in the last couple of decades in Nepal. However, the progress is not uniform across different population sub-groups. This study aims to identify the determinants of institutional delivery, measure the wealth-related inequality, and examine the key components that explain the inequality. Methods Most recent nationally representative Multiple Indicator Cluster Survey (MICS) 2019 was used to extract data about married women (15–49 years) with a live birth within two years preceding the survey. Logistic regression models were employed to assess the association of independent variables with the institutional delivery. The concentration curves (CC) and concentration indexe (CIX) were used to analyze the inequality in institutional delivery. Wealth index scores were used as a socio-economic variable to rank households. Decomposition was performed to identify the determinants that explain socio-economic inequality. Results The socio-economic status of households to which women belong was a significant predictor of institutional delivery, along with age, parity, four or more ANC visits, education status of women, area of residence, sex of household head, religious belief, and province. The concentration curve was below the line of equality and the relative concentration index (CIX) was 0.097 (p < 0.001), meaning the institutional delivery was disproportionately higher among women from wealthy groups. The decomposition analysis showed the following variables as the most significant contributor to the inequality: wealth status of women (53.2%), education of women (17 %), residence (8.64 %) and ANC visit (6.84 %). Conclusions The pro-poor strategies are urgent to reduce the existing inequality between wealthy and poorer women. The strategies should focus on raising the education level of women especially from the rural and relatively backward province (Province 2). Increasing antenatal care (ANC) coverage through out-reach campaigns is likely to increase facility-based delivery and decrease inequality. Monitoring of healthcare indicators at different sub-population level (for example wealth, residence, province) is key to ensure equitable improvement in health status and achieve universal health coverage (UHC).

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Determinants of health insurance enrolment in Ghana: evidence from three national household surveys

Health Policy and Planning ◽

10.1093/heapol/czz079 ◽

2019 ◽

Vol 34 (8) ◽

pp. 582-594 ◽

Cited By ~ 1

Author(s):

Paola Salari ◽

Patricia Akweongo ◽

Moses Aikins ◽

Fabrizio Tediosi

Keyword(s):

Health Insurance ◽

Complex Dynamics ◽

Living Standard ◽

Household Surveys ◽

Health Coverage ◽

Economic Determinants ◽

Logistic Regression Models ◽

Multiple Indicator Cluster Survey ◽

Multiple Indicator ◽

The Relationship

Abstract In 2003, Ghana implemented a National Health Insurance Scheme (NHIS) to move towards Universal Health Coverage. NHIS enrolment is mandatory for all Ghanaians, but the most recent estimates show that coverage stands under 40%. The evidence on the relationship between socio-economic characteristics and NHIS enrolment is mixed, and comes mainly from studies conducted in a few areas. Therefore, in this study we investigate the socio-economic determinants of NHIS enrolment using three recent national household surveys. We used data from the Ghanaian Demographic and Health Survey conducted in 2014, the Multiple Indicator Cluster Survey conducted in 2011 and the sixth wave of the Ghana Living Standard Survey conducted in 2012–13. Given the multilevel nature of the three databases, we use multilevel logistic regression models to estimate the probability of enrolment for women and men separately. We used three levels of analysis: geographical clusters, household and individual units. We found that education, wealth, marital status—and to some extent—age were positively associated with enrolment. Furthermore, we found that enrolment was correlated with the type of occupation. The analyses of three national household surveys highlight the challenges of understanding the complex dynamics of factors contributing to low NHIS enrolment rates. The results indicate that current policies aimed at identifying and subsidizing underprivileged population groups might insufficiently encourage health insurance enrolment.

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A multilevel analysis of the determinants of handwashing behavior among households in Eswatini: a secondary analysis of the 2014 multiple indicator cluster survey

African Health Sciences ◽

10.4314/ahs.v20i4.58 ◽

2020 ◽

Vol 20 (4) ◽

pp. 1996-2006

Author(s):

Maswati S Simelane

Keyword(s):

Logistic Regression ◽

Mass Media ◽

Secondary Analysis ◽

Multilevel Logistic Regression ◽

Cluster Survey ◽

Toilet Facility ◽

Multiple Indicator Cluster Survey ◽

Multiple Indicator ◽

Pit Latrine ◽

Handwashing With Soap

Introduction: Handwashing with soap has received considerable attention due to its importance in the prevention and inter- ruption of the transmission of diseases. Regardless of the positive effects of handwashing with soap, developing countries still have a low rate of handwashing. Objective: The study aimed to determine the individual, household and community-level factors associated with handwash- ing behavior among households in Eswatini. Methods: Using the Eswatini Multiple Indicator Cluster Survey conducted in 2014, a secondary analysis was done of the households surveyed. A total of 1,520 households nested in communities with complete data on handwashing practices were included in the analysis. Univariate, bivariate analysis and multivariate multilevel logistic regression were used to estab- lish the factors that were associated with handwashing behavior. Results: The prevalence of handwashing among households was 56% in 2014. Households whose heads were aged 35-54 and 55 years and older were more likely to practice handwashing (AOR=1.88, 95% CI:1.39, 2.54); and (AOR=1.77, 95% CI: 1.205, 2.62) compared to those aged 15-34 years. Households with a pit latrine or no toilet facility at all, were less likely to practice handwashing (AOR=0.24, 95% CI: 0.17, 0.35); (AOR=0.28, 95% CI: 0.11, 0.71) respectively compared to those with a flush toilet. Region of residence was a community-level variable associated with lower odds of handwashing, with those from the Hhohho (AOR=0.22, 95% CI: 0.14, 0.35) and Manzini region (AOR=0.42, 95% CI: 0.27, 0.67) compared to Lubombo region. Households from communities where access to mass media was high were more likely to practice handwashing (AOR =1.47, 95% CI: 1.05, 2.03) compared to those from communities where access to mass media was low. Conclusion: Households headed by young adults, with pit latrine or no toilet facility at all and lived in the Hhohho and Manzini regions and with low access to mass media, should be targeted for interventions aimed at improving handwashing practices. Keywords: Handwashing; factors; Eswatini; households; multilevel logistic regression.

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Multiple Indicator Cluster Survey 2003 in Afghanistan: Outdated Sampling Frame and the Effect of Sampling Weights on Estimates of Maternal and Child Health Coverage

Journal of Health Population and Nutrition ◽

10.3329/jhpn.v29i4.8456 ◽

2011 ◽

Vol 29 (4) ◽

Cited By ~ 2

Author(s):

Shivam Gupta ◽

Muhammad Shuaib ◽

Stan Becker ◽

Md Mokhlesur Rahman ◽

David H Peters

Keyword(s):

Child Health ◽

Maternal And Child Health ◽

Health Coverage ◽

Sampling Frame ◽

Sampling Weights ◽

Cluster Survey ◽

Multiple Indicator Cluster Survey ◽

Multiple Indicator ◽

And Child Health

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Fertility Determinan in Sudan: Analysis of Multiple Indicator Cluster Survey, 2014

Populasi ◽

10.22146/jp.44146 ◽

2019 ◽

Vol 26 (2) ◽

pp. 1

Author(s):

Mustafa Elnagi Elsamani Hassan ◽

Sukamdi Sukamdi ◽

Agus Joko Pitoyo

Keyword(s):

Urban Areas ◽

Post Partum ◽

Great Influence ◽

High Fertility ◽

Wealth Status ◽

Targeted Interventions ◽

Cluster Survey ◽

Multiple Indicator Cluster Survey ◽

Multiple Indicator ◽

Nationally Representative

Sudan has continuously reported high fertility rates. While the influence of both underlying and proximate determinants is well documented in various studies worldwide, there’s a lack of recent information on their influence on fertility in Sudan. Therefore, the objective of this study to examine the levels, patterns and determinants of fertility in Sudan. The analyses were based on 2014 Sudan Multiple Indicators Cluster Survey (SMICS) data. The SMICS data is nationally representative data. The survey sampled 18,302 women across the country, collecting information on females aged 15-49 years. The analysis was based on the Bongaarts Model. Results show that post-partum infecundability has the largest effect in reducing fertility in Sudan (30.7 per cent or 4.7 birth) followed by marriage (27.5 per cent or 4.3 birth) and contraceptive (7.8 per cent or 1.2 birth). The findings of study shown also that significant differences between education, wealth, and place of residence. This means that the increase in education, especially higher education, improve the wealth status and living in urban areas seem to have a great influence toward fertility education in Sudan. Also, it agreed that there is a regional fertility differential associated with social and economic development in the different region and states. Therefore, in order to manage fertility in Sudan, policies and programmes should consider the effects of marriage, postpartum infecundity, contraception, education, and wealth on fertility. Lack of such targeted interventions, population growth will remain a challenge in Sudan.

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Predictors of wealth-related inequality in institutional delivery: a decomposition analysis using Nepal multiple Indicator cluster survey (MICS) 2019

BMC Public Health ◽

10.1186/s12889-021-12287-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Umesh Prasad Bhusal

Keyword(s):

Concentration Index ◽

Institutional Delivery ◽

Economic Inequality ◽

Decomposition Analysis ◽

Concentration Curve ◽

Cluster Survey ◽

Related Inequality ◽

Multiple Indicator Cluster Survey ◽

Multiple Indicator ◽

Status Of Women

Abstract Background Inequality in maternal healthcare use is a major concern for low-and middle-income countries (LMICs). Maternal health indicators at the national level have markedly improved in the last couple of decades in Nepal. However, the progress is not uniform across different population sub-groups. This study aims to identify the determinants of institutional delivery, measure wealth-related inequality, and examine the key components that explain the inequality. Methods Most recent nationally representative Multiple Indicator Cluster Survey (MICS) 2019 was used to extract data about married women (15-49 years) with a live birth within two years preceding the survey. Logistic regression models were employed to assess the association of independent variables with the institutional delivery. The concentration curve (CC) and concentration index (CIX) were used to analyze the inequality in institutional delivery. Wealth index scores were used as a socio-economic variable to rank households. Decomposition was performed to identify the determinants that explain socio-economic inequality. Results The socio-economic status of households to which women belong was a significant predictor of institutional delivery, along with age, parity, four or more ANC visits, education status of women, area of residence, sex of household head, religious belief, and province. The concentration curve was below the line of equality and the relative concentration index (CIX) was 0.097 (p < 0.001), meaning the institutional delivery was disproportionately higher among women from wealthy groups. The decomposition analysis showed the following variables as the most significant contributor to the inequality: wealth status of women (53.20%), education of women (17.02%), residence (8.64%) and ANC visit (6.84%). Conclusions To reduce the existing socio-economic inequality in institutional delivery, health policies and strategies should focus more on poorest and poor quintiles of the population. The strategies should also focus on raising the education level of women especially from the rural and relatively backward province (Province 2). Increasing antenatal care (ANC) coverage through outreach campaigns is likely to increase facility-based delivery and decrease inequality. Monitoring of healthcare indicators at different sub-population levels (for example wealth, residence, province) is key to ensure equitable improvement in health status and achieve universal health coverage (UHC).

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Socioeconomic and demographic correlates of nonenrolment onto the national health insurance scheme among children in Ghana: Insight from the 2017/18 Multiple Indicator Cluster Survey

Preventive Medicine Reports ◽

10.1016/j.pmedr.2021.101385 ◽

2021 ◽

Vol 22 ◽

pp. 101385

Author(s):

Pascal Agbadi ◽

Joshua Okyere ◽

Alberta Lomotey ◽

Henry Ofori Duah ◽

Abdul-Aziz Seidu ◽

...

Keyword(s):

Health Insurance ◽

National Health Insurance ◽

National Health ◽

National Health Insurance Scheme ◽

Health Insurance Scheme ◽

Insurance Scheme ◽

Cluster Survey ◽

Multiple Indicator Cluster Survey ◽

Demographic Correlates ◽

Multiple Indicator

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ASSOCIATION OF SOCIO-DEMOGRAPHIC FACTORS WITH DIARRHEA IN CHILDREN LESS THAN FIVE YEARS: A SECONDARY ANALYSIS OF MULTIPLE INDICATOR CLUSTER SURVEY SINDH 2014

Pakistan Journal of Public Health ◽

10.32413/pjph.v7i2.39 ◽

1970 ◽

Vol 7 (2) ◽

pp. 85-89

Author(s):

Muhammad Irfan ◽

Syed Mustansir Hussain Zaidi ◽

Hira Fatima Waseem

Keyword(s):

Rural Areas ◽

Demographic Factors ◽

Wealth Index ◽

Household Wealth ◽

Cluster Survey ◽

Multiple Indicator Cluster Survey ◽

Increased Risk ◽

Multiple Indicator ◽

Mother Education ◽

Socio Demographic Factors

Background: Diarrhea founds to be the major cause of morbidity and mortality in children less than five years. Various factors are associated with diarrhea but socio-demographic factors are the main key elements, which associated with diarrhea. Methods: This study was examined association of socio-demographic factors with diarrhea in children less than five years of age of Sindh, Pakistan, using data from the Multiple Indicator Cluster Survey (MICS) conducted from January 2014 to August 2014. Data were collected for 18,108 children in whom 16,449 children had complete data of demographic variables being included in the analysis. Bivariate analysis was done using Pearson's Chi square test and multivariate analysis being done using binary logistic regression. Results: We found increased risk of diarrhea among children lives in rural areas while household wealth index quintile was also associated with diarrhea. Children in the poor, middle and fourth wealth index quintiles being at increased risk of diarrhea compared to children in the richest wealth index quintile. The highest risk of diarrhea was found for the child having mother with no education as well as children aged 12-23 months. Conclusion: Age of child, mother education and wealth index found significant with diarrhea while Male children, child aged 12-23 months, child with no mother education, child from rural areas and child from poor households found with high risk of diarrhea.

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