Erreygers Concentration Index Research Articles

An analysis of predictors and wealth-based inequality in internet use among women in India: aiming for better digital health outcomes

BackgroundDigital health, aiming to boost healthcare accessibility, is an emerging concept in the domain of healthcare administration and delivery in developing countries. In India, according to the National Family Health Survey (NFHS-5), more than half (55%) of the men have reported ever using the internet, while only one-third (33%) of the women have done so. This gendered digital divide is further complicated and worsened by the fact that individuals in the lowest wealth quintile exhibit significantly lower internet usage rates, with only 9% of women and 26% of men. Such intersectionality of the gendered digital divide might prove a barrier to realizing the full potential of digital health in India. Eliminating digital inequalities in all forms and ensuring universal digitalization is essential for desired digital health outcomes.MethodsThis study aims to explore India’s readiness for digital health in terms of access to basic digital infrastructure, i.e., the internet. We analyze access to the Internet among Indian women of reproductive age using pan-India survey data from the fifth round of the National Family Health Survey (2019–21). We investigate predictors of Internet use in a regression model and apply the Erreygers Concentration Index (ECI) to examine inequalities in Internet access. Using decomposition analyses, we analyze factors contributing to digital inequality in terms of internet use.ResultsOur inequality analysis based on the ECI [ECI- 0.4444 (p < 0.001)] suggests that a significant inequality exists in internet access. Furthermore, the decomposition analyses in the study find women’s educational level to be the most prominent (28.19%) contributing factor to internet inequality, followed by wealth (25.67%), place of residence (23.16%), and caste (1.10%).RecommendationWe suggest a comprehensive readiness and need assessment, revamping of digital infrastructure, and moving with caution in implementing digital health innovation in the country as it may further exacerbate the existing healthcare access inequities.

Explaining changes in educational disparities in competent maternal health care services in urban and rural areas in Ethiopia.

Aggregate statistics of maternal health care services have improved in Ethiopia. Nevertheless, the country has one of the lowest Universal Health Coverage (UHC) service coverage indices, with slight improvement between 2000 and 2019. There are disparity studies that focus on a single dimension of inequality. However, studies that combine multiple dimensions of inequality simultaneously may have important policy implications for closing inequalities. In this study, we investigated education inequalities in the receipt of maternal health care services in rural and urban areas separately, and we examined whether these inequalities decreased, increased, or remained unchanged. The data for the study came from the 2011 and 2016 Ethiopia Demographic and Health Surveys. Using women's education as a dimension of inequality, we separately analyzed inequalities in maternal health care services in urban and rural settings. Inequalities were measured through the Erreygers concentration index, second differences, and Relative Index of Inequality (RII). Whether inequalities changed over time was analyzed by relative and absolute measures. An Oaxaca-type decomposition approach was applied to explain changes in absolute disparities over time. There were glaring educational disparities in maternal health care services in urban and rural areas, where the services were more concentrated among women with better schooling. The disparities were more severe in urban than in rural areas. In urban areas, skilled birth service was the most unequal in both periods. Disparities in rural places were roughly similar for all services except that in 2011, postnatal care was the least unequal, and in 2016, skilled birth was the most unequal services. Trend analyses revealed that disparities significantly dropped in urban by absolute and relative measures. Conversely, in rural regions, the disparities grew by the concentration index measure for most services. The RII and second differences presented conflicting results regarding whether the gaps were increasing, shrinking, or remaining the same. Substantial disparities in maternal health care services remained and even increased, as in rural areas. Different and targeted strategies are needed for urban and rural places to close the observed educational inequalities in these areas.

Socioeconomic inequality and urban-rural disparity of antenatal care visits in Bangladesh: A trend and decomposition analysis.

Socioeconomic inequality in antenatal care visits is a great concern in developing countries including Bangladesh; however, there is a scarcity of investigation to assess the factors of inequality and these changes over time. In this study, we investigated the trend of socioeconomic inequalities (2004-2017) in 1+ANC and 4+ANC visits, and extracted determinants contributions to the observed inequalities and urban-rural disparities in Bangladesh over the period from 2011 to 2017. The data from the Bangladesh Demographic and Health Surveys (BDHS) conducted in 2004, 2007, 2011 and 2017 were analyzed in this study. The analysis began with exploratory and bivariate analysis, followed by the application of logistic regression models. To measure the inequalities, the Erreygers concentration index was used, and regression-based decomposition analyses were utilized to unravel the determinant's contribution to the observed inequalities. The Blinder-Oaxaca type decomposition is also used to decompose the urban-rural disparity into the factors. Our analysis results showed that the prevalence of 1+ANC and 4+ANC visits has increased across all the determinants, although the rate of 4+ANC visits remains notably low. The magnitudes of socioeconomic inequality in 4+ANC visits represented an irregular pattern at both the national and urban levels, whereas it increased gradually in rural Bangladesh. However, inequalities in 1+ANC visits declined substantially after 2011 across the national, rural and urban areas of Bangladesh. Decomposition analyses have suggested that wealth status, women's education, place of residence (only for 4+ANC visits), caesarean delivery, husband education, and watching television (TV) are the main determinants to attribute and changes in the level of inequality and urban-rural disparity between the years 2011 and 2017. According to the findings of our study, it is imperative for authorities to ensure antenatal care visits are more accessible for rural and underprivileged women. Additionally, should focus on delivering high-quality education, ensuring the completion of education, reducing income disparity as well as launching a program to enhance awareness about health facilities, and the impact of caesarean delivery.

Income-related inequality in health outcomes among older individuals in China: A measurement and decomposition analysis

Population aging in China presents a significant challenge, with projections indicating that individuals aged 65 and above will exceed 30% of the total population by 2050, thereby increasing health-care and long-term care (LTC) demands. Therefore, this study aimed to examine income-related inequality in self-rated health (SRH) and functional ability among older individuals in China while also examining the contribution of socioeconomic factors to health inequality. Data were drawn from the 2018 wave of the Chinese Longitudinal Healthy Longevity Survey. Well-established tools, such as concentration curves, the Erreygers concentration index (EI), and decomposition analysis, were employed to elucidate income-related inequality in health within the sample. The results revealed that for SRH, both unstandardized and standardized concentration curves were observed below the 45&amp;deg; line, with unstandardized EI at 0.068 and standardized EI at 0.033. For functional ability, both unstandardized and standardized concentration curves were observed above the 45&amp;deg; line, with unstandardized EI at &amp;minus;0.016 and standardized EI at &amp;minus;0.003. These results suggest that, after controlling for demographic factors, the better-off group is more likely to report better SRH and less likely to experience functional limitations compared to the worse-off group. Furthermore, this inequality in health outcomes is predominantly driven by socioeconomic factors rather than demographic factors. For SRH, income emerges as the primary contributor to total inequality. Similarly, for functional ability, income emerges as the key factor driving inequality, disproportionately affecting the less affluent population. Consequently, it is crucial for the government to protect older individuals with lower socioeconomic status to mitigate income-related inequality in health by directly providing cash aids and formal LTC, which could contribute to promoting healthy aging in the context of global aging.

An Examination of Inter-State Variation in Utilization of Healthcare Services, Associated Financial Burden and Inequality: Evidence from Nationally Representative Survey in India.

This study examines the health care utilization pattern, associated financial catastrophes, and inequality across Indian states to understand the subnational variations and aid the policy makers in this regard. Data from recent National Sample Survey (2017-2018), titled, "Household Social Consumption: Health," covering 113,823 households, was employed in the study. Descriptive statistics, Erreygers concentration index (CI), and recentered influence function decomposition were applied in the study. We found that, in India, 7 percent of households experienced catastrophic health expenditure (CHE) and 1.9 percent of households were pushed below poverty line due to out-of-pocket expenditure on hospitalization. Notably, outpatient care was more burdensome (CHE: 12.1%; impoverishment: 4%). Substantial interstate variations were observed, with high financial burden in poorer states. Utilization of health care services from private health care providers was pro-rich (hospitalization CI 0.31; outpatient CI 0.10), while the occurrence of CHE incidence was pro-poor (hospitalization CI -0.10; outpatient CI -0.14). Education level, economic status, health insurance, and area of residence contributed significantly to inequalities in utilization of health care services from private providers and financial burden. The high financial burden of seeking health care necessitates the need to increase public health spending and strengthen public health infrastructure. Also, concerted efforts directed towards increasing awareness about health insurance and introducing comprehensive health insurance products (covering both inpatient and outpatient services) are imperative to augment financial risk protection in India.

Socioeconomic and geographic variations of disabilities in India: evidence from the National Family Health Survey, 2019–21

BackgroundIncreasing disability is of global and national concern. Lack of evidence on disability across socioeconomic groups and geographic levels (especially small areas) impeded interventions for these disadvantaged subgroups. We aimed to examine the socioeconomic and geographic variations in disabilities, namely hearing, speech, visual, mental, and locomotor, in Indian participants using cross-sectional data from the National Family Health Survey 2019–2021.MethodsUsing data from 27,93,971 individuals, we estimated age-sex-adjusted disability rates at the national and sub-national levels. The extent of socioeconomic variations in disabilities was explored using the Erreygers Concentration Index and presented graphically through a concentration curve. We adopted a four-level random intercept logit model to compute the variance partitioning coefficient (VPC) to assess the significance of each geographical unit in total variability. We also calculated precision-weighted disability estimates of individuals across 707 districts and showed their correlation with within-district or between-cluster standard deviation.ResultsWe estimated the prevalence of any disability of 10 per 1000 population. The locomotor disability was common, followed by mental, speech, hearing, and visual. The concentration index of each type of disability was highest in the poorest wealth quintile households and illiterate 18 + individuals, confirming higher socioeconomic variations in disability rates. Clusters share the largest source of geographic variation for any disability (6.5%), hearing (5.8%), visual (24.3%), and locomotor (17.4%). However, States/Union Territories (UTs) account for the highest variation in speech (3.7%) and mental (6.5%) disabilities, where the variation at the cluster level becomes negligible. Districts with the highest disability rates were clustered in Madhya Pradesh, Maharashtra, Karnataka, Tamil Nadu, Telangana, and Punjab. Further, we found positive correlations between the district rates and cluster standard deviations (SDs) for disabilities.ConclusionsThough the growing disability condition in India is itself a concerning issue, wide variations across socioeconomic groups and geographic locations indicate the implementation of several policy-relevant implications focusing on these vulnerable chunks of the population. Further, the critical importance of small-area variations within districts suggests the design of strategies targeting these high-burden areas of disabilities.

Socioeconomic inequality in adults undertaking HIV testing over time in Ethiopia based on data from demographic and health surveys.

HIV testing is the entry point to HIV prevention, care and treatment and needs continuous evaluation to understand whether all social groups have accessed services equally. Addressing disparities in HIV testing between social groups results in effective and efficient response against HIV prevention. Despite these benefits, there was no previous study on inequality and determinants over time in Ethiopia. Thus, the objective of this research was to examine socioeconomic inequality in individuals undertaking HIV testing over time, allowing for the identification of persistent and emerging determinants. Data sources for the current study were the 2011 and 2016 Ethiopian Demographic Health Surveys. The 2016 population health survey is the one that Ethiopia used to set national AIDS response strategies; there was no other recent survey with HIV/AIDS-related indicators in Ethiopia. The final sample size for the current study was 28,478 for the year 2011 and 25,542 for the year 2016. The concentration curve and Erreygers' concentration index were used to estimate socioeconomic inequality in HIV testing. Subsequently, decomposition analysis was performed to identify persistent and emerging contributors of socioeconomic inequality. Generalized linear regression model with the logit link function was employed to estimate the marginal effect, elasticity, Erreygers' concentration index (ECI), and absolute and percentage contributions of each covariate. The concentration curve was below the line of equality over time, revealing the pro-rich inequality in HIV testing. The inequality was observed in both 2011 (ECI = 0.200) and 2016 (ECI = 0.213). A household wealth rank had the highest percentage contribution (49.2%) for inequality in HIV testing in 2011, which increased to 61.1% in 2016. Additional markers include listening to the radio (13.4% in 2011 and 12.1% in 2016), education status (8.1% in 2011 and 6.8% in 2016), and resident (-2.0% in 2011 and 6.3% in 2016). Persistent determinants of individuals undertaking HIV testing were age 20-34 years, geographic region, education status, marital status, religion, income, media exposure (listening to the radio, reading newspaper, watching television), knowledge about HIV/AIDS, and attitudes towards people living with HIV. Age between 35 and 44 years and urban residence emerged as new associated factors in 2016. The higher HIV testing coverage was among individuals with higher socioeconomic status in Ethiopia. Socioeconomic inequality amongst individuals undertaking HIV testing was diverging over time. Household wealth rank, mass media exposure, education status, and resident took the largest share in explaining the disparity in individuals undertaking HIV testing between the lower and higher income groups. Therefore, interventions to equalise HIV testing coverage should take account of these determinants.

Oral Health Service Use in Older Peruvians Before and During the COVID-19 Pandemic

The aim of this work was to analyse inequalities in oral health services utilisation (OHSU) in older Peruvian adults through comparative analysis of the years 2019 and 2021. We conducted a secondary analysis of data from the 2019 and 2021 Demographic and Health Survey (ENDES). The outcome variable was OHSU by older Peruvian adults in the past year. We used Poisson generalised linear models adjusted for age and sex to assess changes in OHSU by sociodemographic characteristics. The Erreygers concentration index was used to describe the socioeconomic inequalities in OHSU. The contribution of each variable to inequalities was estimated by a decomposition analysis. In 2021, OHSU probability amongst older Peruvian adults decreased by 37% compared to 2019. The decline was greatest in those aged 80 or older (51%), the lowest wealth quintile (47%), those with functional limitations (53%), and those whose native language is Quechua or other indigenous languages (47%). Surprisingly, we observed a reduction in OHSU inequalities (difference: -0.1074; P = .003) during the COVID-19 pandemic, particularly amongst rural residents (difference: -0.0771; P = .030), the lowest wealth quintile (difference: -0.0764; P = .020), and those with functional limitations (difference: -0.3665; P < .001). Poverty accounted for 73% of the inequality in 2021. The probability of OHSU has significantly decreased likely due to the COVID-19 pandemic. Paradoxically, we observed a reduction in OHSU inequalities during the pandemic, despite the known socioeconomic impact. However, further research is required to gain deeper understanding of this phenomenon.

Explaining the rise of economic and rural-urban inequality in clean cooking fuel use in Tanzania

Despite the high rate of economic growth and electrification in the last two decades in Tanzania, only 6.9 % of the nation's households have access to clean cooking fuel technology which is concentrated among the rich urban households. Analysing data from two waves of the Tanzania National Panel Survey (2014/15 and 2020/21), we estimate the economic and rural-urban inequalities in the use of clean cooking fuel. Using the concentration curve, Erreygers concentration index and non-linear Fairlie decomposition, we find an increase in economic inequality and rural-urban inequality in the use of clean cooking fuel. Based on our analysis, factors such as the household head's education, household economic status and household connection to electricity contribute to the rural-urban inequality in the use of clean cooking fuel. Policy changes are vital for ensuring both rural and urban households have equitable access to education, electricity connection and household economic status to address inequality in the use of clean cooking fuel.

Socioeconomic inequality and contributors in accepting attitudes toward people living with HIV among adults in Ethiopia from 2005 to 2016: a population-based cross-sectional study

IntroductionThe public’s accepting attitude toward people living with HIV is crucial in reducing HIV-related stigma and discrimination, increasing people’s access to HIV service. This study examines the inequalities in accepting...

Spatiotemporal change in wealth-based inequalities in overweight/obesity among women of reproductive age in India, 2015–2021

BackgroundOverweight/obesity poses significant global health concerns, especially affecting women. This study aimed to measure changes in wealth-based inequality in overweight/obesity among women of reproductive age (WRA) across states of India from 2015 to 2021 and identify the contributing factors to this inequality. MethodsThe study used information on 582,851 and 587,435 women aged 15–49 from National Family Health Survey (NFHS)-4 (2015-16) and NFHS-5 (2019-21), respectively. Erreygers Concentration Index (ECI) was employed to measure the change in inequality over time. Further, ECI was decomposed to unravel the contributing factors to this inequality. ResultsOverweight/obesity among WRA in India increased from 20.3 % in NFHS-4 to 23.7 % in NFHS-5. A significant pro-rich inequality in overweight/obesity was observed at the national level and across all 28 states of India during both NFHS-4 and NFHS-5. The national wealth-based inequality reduced marginally over the study period (ECI: 0.25 in NFHS-4, ECI: 0.23 in NFHS-5), but at the state level, it rose in 8 states and declined in 16 states. Punjab witnessed the most significant increase (ECI: 0.10 in NFHS-4, ECI: 0.18 in NFHS-5) in inequality, while Maharashtra (ECI: 0.24 in NFHS-4, ECI: 0.16 in NFHS-5) saw the most significant decrease in inequality. The decomposition analysis results revealed that women's education, mass media exposure, and place of residence were major contributors, contributing more than 80 % to wealth-based inequality in overweight/obesity. ConclusionThe study highlights the growing prevalence of overweight/obesity among WRA in India, emphasizing that wealth-related inequalities in the prevalence of overweight/obesity represent a significant public health concern both at the national and state levels in India.

Frequency, inequalities and spatial distribution of oral health services utilization in Peruvian children under twelve years of age: a population-based comparative analysis of the years 2017 and 2021

BackgroundOral diseases pose a significant public health challenge among Peruvian children. However, oral health services utilization among them is marked by inequalities, which may have been exacerbated by the COVID-19 pandemic. The objective was to compare the frequency, inequalities, determinants of inequality, and spatial distribution in oral health services utilization in Peruvian children under 12 years of age in 2017 and 2021.MethodsComparative secondary data analysis from the Demographic and Family Health Survey (ENDES) for the years 2017 (38,787 minors) and 2021 (36,729 minors). Age-adjusted prevalence ratios (PR) with 95% confidence intervals (CI) were calculated to assess the change in oral health services utilization in the last 12 months between the years 2017 and 2021, stratifying by demographic and socioeconomic covariates. Inequality was assessed by decomposing the Erreygers Concentration Index (ECI) and calculating the percentage contribution to inequality of the independent variables. Spatial analysis was performed using spatial autocorrelation methods, Hot Spot Analysis, Cluster and Outlier analysis, Inverse Distance Weighting, ordinary Kriging, and Kulldorff analysis.ResultsThe probability of Peruvian children under 12 years of age using oral health services in the last 12 months was reduced by 45% in 2021 compared to 2017. The ECI identified a significant reduction in oral health services utilization inequalities at the national level (Diff: -0.0963; p < 0.001). The main contributor to inequality was higher tutor education level (55.2% in 2017 and 82.7% in 2021). In the comparison of spatial distribution, there was a greater dispersion of the conglomerates in which the use of oral health services is concentrated in 2021.ConclusionsThe frequency of oral health services utilization in the Peruvian children under 12 years of age was halved between 2017 and 2021. This problem is transversal to the entire population at the demographic and socioeconomic level. The key factor contributing to inequalities in the utilization of oral health services was the higher educational attainment of caregivers or guardians. Despite the improvement observed in inequalities and spatial distribution of the concentration of oral health services utilization, it is necessary to keep monitoring these patterns to guide decision-making.

Spatiotemporal change in socioeconomic inequality in hygienic menstrual product use among adolescent girls in India during 2015–2019

BackgroundThe use of hygienic products, such as sanitary napkins, tampons, and menstrual cups, to absorb menstrual blood is vital for the health and well-being of adolescent girls in India. However, the degree of inequity in the use of such products among this subpopulation remains inadequately explored. To fill this critical knowledge gap, this study aims to investigate the spatiotemporal dynamics of hygienic product use among adolescent girls in India from 2015 to 2020.MethodsIn this cross-sectional study, we analyzed data from 117,749 to 114,839 adolescent girls aged 15–19, obtained from two consecutive rounds of the National Family Health Survey (NFHS) conducted in India during 2015-16 and 2019-21. Our approach involved utilizing Erreygers’ Concentration Index (ECI) and Concentration Curve to quantitatively assess and visually represent socioeconomic inequality in hygienic product usage. Additionally, we investigated the spatiotemporal variation in this inequality over the study period and decomposed the ECI to identify the key contributing factors.ResultsThe findings reveal that hygienic product usage among adolescent girls in India has increased by 13 percentage points (PP), from 37% in 2015-16 to 50% in 2019-21. This increase is also visible across all household wealth quintiles. However, the bottom quintiles experienced a greater rise (+ 15 to 16 PP) than the top quintile (+ 8 PP). During the study period, the ECI reduced marginally, from 0.48 in 2015-16 to 0.43 in 2019-21. However, the extent of this reduction varied across different states. The greatest reduction in ECI was recorded in Punjab (-0.23 points), Telangana (-0.16 points), and West Bengal (-0.14 points). In contrast, there were a number of states with high socioeconomic inequality (ECI > 0.30) in 2015-16, where inequality reduction was minimal (< 0.05 points) over the study period. This included more developed states of Kerala, Karnataka, Maharashtra and Gujarat and relatively less developed states of Odisha, Jharkhand, Chhattisgarh, Uttar Pradesh, and Assam. Some states, such as Bihar and Madhya Pradesh, recorded an increase in socioeconomic inequality over the study period, with ECI rising to 0.31 and 0.46 (highest in the country) in 2019-21. The decomposition analysis revealed that the inequality in using hygienic products was primarily explained by place of residence, exposure to mass-media, education, and region of residence.ConclusionsThe findings suggest the need for targeted policies to reduce existing socioeconomic inequality in the usage of hygienic products among adolescent girls in India. Specifically, interventions should target regions with low use of hygienic products, economically disadvantaged groups, and poor and vulnerable populations. State-specific policies and programs are also necessary to address the disparities in socioeconomic inequality. Additionally, efforts to reduce inequality should address the underlying factors contributing to inequality.

Determinants, inequalities, and spatial patterns of diarrhea in the Peruvian under-five population: findings from nationally representative survey data.

To determine the associated factors, decompose the socioeconomic inequalities, and analyze the spatial distribution of childhood diarrhea in Peru. A cross-sectional analytical study was conducted using data from the National Demographic and Family Health Survey 2021. The dependent variable was the presence of diarrhea in the last two weeks. Three types of analysis were performed: (i) to evaluate the associated factors, generalized linear models of the Poisson family with logarithmic link were applied and prevalence ratios with their 95% confidence intervals were reported; (ii) for the analysis of inequalities, a decomposition of the Erreygers concentration index was performed using a generalized linear model; and (ii) a spatial autocorrelation analysis, hot spot analysis and cluster and outlier analysis were performed. A total of 18,871 children under 5 years of age were included. The prevalence of diarrhea in this population was 10.0%. Determinants such as being aged 0-23 months, being male, belonging to the poorest, poorer and rich wealth index, and residing in the Highlands and Jungle increased the probability of presenting diarrhea. In the decomposition analysis, diarrhea had a pro-poor orientation, with the greatest contributors were age 0-23 months, belonging to the poorest and poorer wealth indexes, and residing in the Highlands and Jungle. Spatial analysis showed that the highest concentrations and occurrence of this event were observed in departments of the Highlands and Jungle. Government institutions seeking to reduce the numbers and burden of childhood diarrhea should focus their strategies on promoting hygiene measures and improving access to water and sanitation services, especially in poor populations living in the Peruvian Highlands and Jungle.

Inequalities in anemia among Peruvian children aged 6-59 months: A decomposition analysis.

To quantify the inequalities of anemia in Peruvian children aged 6-59 months and uncover its contributing factors. We conducted a cross-sectional study based on the secondary data analysis of the 2021 Peruvian Demographic and Health Survey (DHS). Our sample included Peruvian children aged 6-59 months with complete data for the variables of interest. Anemia was defined as having a hemoglobin level of less than 11 g/dL, adjusted by altitude. Erreygers Concentration Index (ECI) and concentration curves were computed to estimate the socio-economic inequality in anemia among Peruvian children. Moreover, ECI was decomposed to figure out the contributing factors to the inequality of anemia and the residual variation. Nationwide, the prevalence of anemia in Peruvian children was 29.47%. We found a pro-poor inequality regarding anemia at the national level (ECI = -0.1848). The determinants included in the model explained 81.85% of the overall socio-economic inequality in anemia. The largest contribution to inequality was from household- and community-related factors. Having a higher mother's education level (26.26%) and being from the highlands (24.91%) were the major significant contributors to the overall health inequality. Almost one-third of Peruvian children have anemia. A pro-poor inequality of anemia in Peruvian children was found. Public policies ought to address the major contributing factors of anemia inequality.

Socio-economic and education related inequities in use of modern contraceptive in seven sub-regions in Uganda

BackgroundAdvocacy for equity in health service utilization and access, including Family Planning (FP) continues to be a cornerstone in increasing universal health coverage. Inequities in Family planning are highlighted by the differences in reproductive health outcomes or in the distribution of resources among different population groups. In this study we examine inequities in use of modern contraceptives with respect to Socio-economic and Education dimensions in seven sub-regions in Uganda.MethodsThe data were obtained from a baseline cross-sectional study in seven statistical regions where a program entitled “Reducing High Fertility Rates and Improving Sexual Reproductive Health Outcomes in Uganda, (RISE)” is implemented in Uganda. There was a total of 3,607 respondents, half of whom were women of reproductive age (15-49 years) and the other half men (18-54 years). Equity in family planning utilization was assessed by geography, wealth/economic and social-demographics. The use of modern family planning was measured as; using or not using modern FP. Concentration indices were used to measure the degree of Inequality in the use of modern contraceptives. Prevalence Ratios to compare use of modern FP were computed using modified Poisson regression run in STATA V15.ResultsThree-quarters (75.6%) of the participants in rural areas were married compared to only 63% in the urban. Overall use of modern contraceptives was 34.2% [CI:30.9, 37.6], without significant variation by rural/urban settings. Women in the higher socio-economic status (SES) were more advantaged in use of modern contraceptives compared to lower SES women. The overall Erreygers Concentration Index, as a measure of inequity, was 0.172, p<0.001. Overall, inequity in use of modern contraceptives by education was highest in favor of women with higher education (ECI=0.146, p=0.0001), and the concentration of use of modern contraceptives in women with higher education was significant in the rural but not urban areasConclusionInequities in the use of modern contraceptives still exist in favor of women with more education or higher socio-economic status, mainly in the rural settings. Focused programmatic interventions in rural settings should be delivered if universal Family Planning uptake is to be improved.

Inequality and disparities in health insurance enrolment in India

BackgroundOver the years, several health insurance programmes have been launched in India to provide financial risk protection against burgeoning health expenditure. Therefore, it is essential to examine variation and inequality in health insurance enrolment over the years to identify “who is still left to be covered” and areas that require greater policy attention. Data and methodologyThe study used data from three rounds of the National Sample Survey (2004, 2014, and 2018). Descriptive statistics, bivariate and multivariable analysis, and concentration index (CI) were employed. ResultsIn India, enrolment under health insurance increased from nearly 1% in 2004 to 15% in 2014 and 2018. It varied substantially across states/union territories, ranging from 0.38% in Bihar to 78.57% in Mizoram in 2018. The enrolment was consistently higher in urban areas than rural areas in 2004 (3.13% versus 0.36%), 2014 (18.02% versus 14.06%), and 2018 (19.06% versus 14.07%). Notably, enrolment under health insurance was statistically significantly concentrated among wealthier individuals in India (Erreygers CI: 0.12; Wagstaff CI: 0.22) as well as in 22/36 states/union territories in 2018. Moreover, individuals with higher educational levels, belonging to higher economic quintiles, scheduled tribes, urban areas, aged > 40 years, those earning regular wages and salaries, and following Hinduism were more likely to enrol under health insurance. ConclusionThe wide variations in health insurance enrolment (at inter-state, intra-state, and socio-economic levels) and the existence of inequality in insurance enrolment, emphasize the need for raising awareness, improving implementation processes, and taking into account contextual differences to increase enrolment in India.

Explanation of Socio-economic Inequality in Medicine Use: A Cross-sectional Analysis from Iran.

Despite the favorable progress in the production of medicines, there is no significant access to these important health inputs among different socio-economic groups. This study aimed to measure and explain socio-economic inequality in prescribed and non-prescribed medicine use in Iran. Data were obtained from a recent household survey on health services in Iran conducted in 2016. The Erreygers concentration index (ECI) was used to measure socio-economic inequality in the use of prescribed and non-prescribed medicines. In addition, Decomposition analysis was conducted to explain socio-economic inequality. The ECI revealed pro-rich socio-economic inequality in prescribed medicine use (ECI = 0.067, SE = 0.010), indicating that prescribed medicine use was concentrated on the better-offs. On the other hand, this index showed pro-poor inequality in non-prescribed medicine use (ECI = -0.064, SE = 0.009). Decomposition analysis showed that economic status and place of residence were the main determinants of socio-economic inequality in prescribing medicines. These factors and the number of health care needs explained the majority of socio-economic inequality in non-prescribed medicine use. Despite previous positive beliefs, we found remarkable socio-economic inequality in the use of medicines in Iran. Facilitating access to pharmaceutical services for disadvantaged households and rural residents and promoting of national essential medicines list could be recommended against socio-economic inequality in the pharmaceutical market of Iran.

Socioeconomic determinants and inequalities in exclusive breastfeeding among children in Peru.

Although Latin America and the Caribbean have one of the highest prevalences of exclusive breastfeeding (EBF), the countries in this region have socioeconomic determinants that influence the frequency of this practice and do not allow achieving the 70% target recommended by the World Health Organization. Therefore, the objective of the study was to examine the socioeconomic determinants and perform a decomposition analysis of socioeconomic inequalities in EBF in Peruvian children 6 to 59 months of age. A cross-sectional study was carried out using the 2021 Demographic and Family Health Survey. The dependent variable for the study was EBF up to 6 months of age and the wealth index variable was used to perform the inequality analysis. Poisson log generalized linear regression models were fitted to evaluate the association between EBF and the independent variables, and concentration curves and Erreygers concentration index decomposition were used to analyze inequalities in EBF. A total of 9926 surveyed participants were included. The prevalence of EBF was 70.5% (95% confidence interval: 69.2-71.8). Women who were married, self-identified as native, received EBF training, resided in the highlands and jungle, and their child was the second or older showed a higher likelihood of EBF. In the inequality analysis, EBF was concentrated among the poorest mothers and the major contributors were residing in the highlands and jungle and belonging to the middle and wealthy quintiles. Our findings suggest that the main strategies to encourage the practice of EBF should be focused on all mothers regardless of their socioeconomic status in order to reduce the EBF gap between richer and poorer women.

Chronic disease relapses: A cross-sectional study of the associated factors and socioeconomic inequalities during the COVID-19 pandemic in Peru.

ObjectivesTo investigate the prevalence, associated factors and socioeconomic inequalities in chronic disease relapses (CDR) during 2020 in Peru.MethodsA secondary analysis was made of the National Household Survey on Living Conditions and Poverty (ENAHO) 2020. Participants older than 18 years who suffered from a chronic disease and with information about the occurrence of a CDR in the last 4 weeks prior to the survey were included. Adjusted prevalence ratios (aPRs) were estimated to determine the associated factors. Socioeconomic inequality in CDR was estimated using concentration curves (CC) and the Erreygers concentration index (ECI).ResultsData from 38,662 participants were analyzed; the prevalence of CDR in the last 4 weeks prior to the survey was 16.5% (95% CI: 15.8–17.2). Being female (aPR 1.29; 95% CI: 1.21–1.37), with regards to being male; being 30–39 (aPR 1.22; 95% CI: 1.05–1.42), 40–49 (aPR 1.29; 95% CI: 1.12–1.48), 50–59 (aPR 1.60; 95% CI: 1.41–1.82), and 60 years or older (aPR 1.80; 95% CI: 1.58–2.04), compared to 18–29; reaching up to primary (aPR 1.18; 95% CI: 1.07–1.31), or secondary education (aPR 1.13; 95% CI: 1.02–1.24), in contrast to tertiary education; presenting some physical, psychological or cognitive limitation (aPR 1.33; 95% CI: 1.21–1.46), with respect to experiencing no limitations; and being affiliated to a health insurance (aPR 1.18; CI 95%: 1.09–1.29), opposed to not having health insurance; were associated with a higher probability of CDR. Residing in the natural region of the coastal area (aPR 0.83; 95% CI: 0.74–0.92) was associated with a lower probability of relapse compared to residing in the jungle area. In people with limitations and residents of the jungle areas, the prevalence of CDR was concentrated in those with higher per capita spending.ConclusionsApproximately 1 in 6 Peruvians with chronic diseases had a relapse within the last 4 weeks prior to the survey of 2020 and certain geographic and sociodemographic factors were found to be associated with CDR. It was also found that a higher concentration of CDR was observed in the population with the highest per capita spending with some limitations, as well as in residents of the jungle, implying the need for appropriate policy interventions that address CDR with a special focus on these populations.