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Glorioso, Valeria, and Maurizio Pisati. "Socioeconomic inequality in health-related behaviors: a lifestyle approach." Quality & Quantity 48, no. 5 (October 1, 2013): 2859–79. http://dx.doi.org/10.1007/s11135-013-9929-y.
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Baigi, Vali, Saharnaz Nedjat, Ahmad Reza Hosseinpoor, Majid Sartipi, Yahya Salimi, and Akbar Fotouhi. "Socioeconomic inequality in health domains in Tehran: a population-based cross-sectional study." BMJ Open 8, no. 2 (February 2018): e018298. http://dx.doi.org/10.1136/bmjopen-2017-018298.
Повний текст джерелаАнотація:
ObjectiveReduction of socioeconomic inequality in health requires appropriate evidence on health and its distribution based on socioeconomic indicators. The objective of this study was to assess socioeconomic inequality in various health domains and self-rated health (SRH).MethodsThis study was conducted using data collected in a survey in 2014 on a random sample of individuals aged 18 and above in the city of Tehran. The standardised World Health Survey Individual Questionnaire was used to assess different health domains. The age-adjusted prevalence of poor health was calculated for each health domain and SRH based on levels of education and wealth quintiles. Furthermore, the Slope Index of Inequality (SII) and the Relative Index of Inequality (RII) were applied to assess socioeconomic inequality in each of the health domains and SRH.ResultsThe age-adjusted prevalence of poor health was observed in a descending order from the lowest to the highest wealth quintiles, and from the lowest level of education to the highest. RII also showed varying values of inequality among different domains, favouring rich subgroups. The highest wealth-related RII was observed in the ‘Mobility’ domain with a value of 4.16 (95% CI 2.01 to 8.62), and the highest education-related RII was observed in the ‘Interpersonal Activities’ domain with a value of 6.40 (95% CI 1.91 to 21.36).ConclusionsSubstantial socioeconomic inequalities were observed in different health domains in favour of groups of better socioeconomic status. Based on these results, policymaking aimed at tackling inequalities should pay attention to different health domains as well as to overall health.
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Wang, Yixiao. "Income-related inequality in health outcomes among older individuals in China: A measurement and decomposition analysis." Global Health Economics and Sustainability 2, no. 1 (March 20, 2024): 2243. http://dx.doi.org/10.36922/ghes.2243.
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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° 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° line, with unstandardized EI at −0.016 and standardized EI at −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.
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Panigrahi, Priyanca, Dharmashree Satyarup, and Jagruti Nanda. "A Review on Socioeconomic Divide: Implications for Health Outcomes and Oral Health." International Journal of Medical Sciences and Pharma Research 10, no. 4 (December 15, 2024): 9–15. https://doi.org/10.22270/ijmspr.v10i4.118.
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Social inequality has a substantial influence on oral health and health outcomes in general. It takes many different forms, including differences in wealth and educational attainment. Prominent health inequalities are caused by the unequal distribution of opportunities and resources, which is influenced by socioeconomic, racial, and geographic variables. Unfair health disparities are caused by a variety of factors, including as living circumstances, health-related behaviours, and biological variance. These differences, which mostly impact lower socioeconomic groups, threaten social cohesiveness, impair economic stability, and intensify emotional stress. In order to address these problems, more inclusive definitions of health are needed, along with fair policy. Addressing these gaps requires comprehensive efforts to enhance general health and eliminate inequities, including those in dental treatment. Public health plays a vital role in this regard. Keywords: Health, Inequality, Perspective, Social inequality
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Safaei, Jalil. "Global income related health inequalities." Social Medicine 2, no. 1 (January 15, 2007): 19–33. https://doi.org/10.71164/socialmedicine.v2i1.2007.31.
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Income related health inequalities have been estimated for various groups of individuals at local, state, or national levels. Almost all of theses estimates are based on individual data from sample surveys. Lack of consistent individual data worldwide has prevented estimates of international income related health inequalities. This paper uses the (population weighted) aggregate data available from many countries around the world to estimate worldwide income related health inequalities. Since the intra-country inequalities are subdued by the aggregate nature of the data, the estimates would be those of the inter-country or international health inequalities. As well, the study estimates the contribution of major socioeconomic variables to the overall health inequalities. The findings of the study strongly support the existence of worldwide income related health inequalities that favor the higher income countries. Decompositions of health inequalities identify inequalities in both the level and distribution of income as the main source of health inequality along with inequalities in education and degree of urbanization as other contributing determinants. Since income related health inequalities are preventable, policies to reduce the income gaps between the poor and rich nations could greatly improve the health of hundreds of millions of people and promote global justice. Keywords: global, income, health inequality, socioeconomic determinants of health
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Andrade, Fabíola Bof de, José Leopoldo Ferreira Antunes, Paulo Roberto Borges de Souza Junior, Maria Fernanda Lima-Costa, and Cesar De Oliveira. "Life course socioeconomic inequalities and oral health status in later life." Revista de Saúde Pública 52, Suppl 2 (January 24, 2019): 7s. http://dx.doi.org/10.11606/s1518-8787.2018052000628.
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OBJECTIVE: To investigate the association between life course socioeconomic conditions and two oral health outcomes (edentulism and use of dental prostheses among individuals with severe tooth loss) among older Brazilian adults. METHODS: This was a cross-sectional study with data from the Brazilian Longitudinal Study of Aging (ELSI-Brazil) which includes information on persons aged 50 years or older residing in 70 municipalities across the five great Brazilian regions. Regression models using life history information were used to investigate the relation between childhood (parental education) and adulthood (own education and wealth) socioeconomic circumstances and edentulism and use of dental prostheses. Slope index of inequality and relative index of inequality for edentulism and use of dental prostheses assessed socioeconomic inequalities in both outcomes. RESULTS: Approximately 28.8% of the individuals were edentulous and among those with severe tooth loss 80% used dental prostheses. Significant absolute and relative inequalities were found for edentulism and use of dental prostheses. The magnitude of edentulism was higher among individuals with lower levels of socioeconomic position during childhood, irrespective of their current socioeconomic position. Absolute and relative inequalities related to the use of dental prostheses were not related to childhood socioeconomic position. CONCLUSIONS: These findings substantiate the association between life course socioeconomic circumstances and oral health in older adulthood, although use of dental prostheses was not related to childhood socioeconomic position. The study also highlights the long-lasting relation between childhood socioeconomic inequalities and oral health through the life course.
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Ataguba, John E., James Akazili, and Di McIntyre. "Socioeconomic-related health inequality in South Africa: evidence from General Household Surveys." International Journal for Equity in Health 10, no. 1 (2011): 48. http://dx.doi.org/10.1186/1475-9276-10-48.
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Lumme, Sonja, Kristiina Manderbacka, Sakari Karvonen, and Ilmo Keskimäki. "Trends of socioeconomic equality in mortality amenable to healthcare and health policy in 1992–2013 in Finland: a population-based register study." BMJ Open 8, no. 12 (December 2018): e023680. http://dx.doi.org/10.1136/bmjopen-2018-023680.
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ObjectiveTo study trends in socioeconomic equality in mortality amenable to healthcare and health policy interventions.DesignA population-based register study.SettingNationwide data on mortality from the Causes of Death statistics for the years 1992–2013.ParticipantsAll deaths of Finnish inhabitants aged 25–74.Outcome measuresYearly age-standardised rates of mortality amenable to healthcare interventions, alcohol-related mortality, ischaemic heart disease mortality and mortality due to all the other causes by income. Concentration index (C) was used to evaluate the magnitude and changes in income group differences.ResultsSignificant socioeconomic inequalities favouring the better-off were observed in each mortality category among younger (25–64) and older (65–74) age groups. Inequality was highest in alcohol-related mortality, C was −0.58 (95% CI −0.62 to −0.54) among younger men in 2008 and −0.62 (−0.72 to −0.53) among younger women in 2013. Socioeconomic inequality increased significantly during the study period except for alcohol-related mortality among older women.ConclusionsThe increase in socioeconomic inequality in mortality amenable to healthcare and health policy interventions between 1992 and 2013 suggests that either the means or the implementation of the health policies have been inadequate.
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Bof de Andrade, Fabíola, and Flavia Drumond Andrade. "Socioeconomic Inequalities in Oral Health-Related Quality of Life among Brazilians: A Cross-Sectional Study." Dentistry Journal 7, no. 2 (April 2, 2019): 39. http://dx.doi.org/10.3390/dj7020039.
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Objective: Assess the magnitude of the socioeconomic inequalities related to the impact of oral health on quality of life among adults and elderly individuals. Methods: This was a cross-sectional study with data from the most recent oral health survey from the state of Minas Gerais, Brazil. The sample included data on 2288 individuals—1159 adults in the 35–44 age group and 1129 adults in the 65–74 age group. Socioeconomic inequalities in Oral Impacts on Daily Performance ratings were measured using two inequality measures: the slope index of inequality (SII) and the relative index of inequality (RII). Results: The prevalence of negative impact of oral health on quality of life was 42.2% for the total sample, 44.9% among adults and 37.5% among elderly individuals. Significant absolute and relative income inequalities were found for the total sample (SII −27.8; RII 0.52) and both age groups (adults: SII −32.4; RII 0.49; elderly: SII −18.3; RI 0.63), meaning that individuals in the lowest income level had the highest prevalence of negative impacts. Regarding schooling, no significant differences were observed among the elderly. Conclusion: There were significant socioeconomic inequalities related to the negative impact of oral health-related quality of life in Brazil among both age groups.
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Wondimu, Abrham, Jurjen van der Schans, Marinus van Hulst, and Maarten J. Postma. "Inequalities in Rotavirus Vaccine Uptake in Ethiopia: A Decomposition Analysis." International Journal of Environmental Research and Public Health 17, no. 8 (April 14, 2020): 2696. http://dx.doi.org/10.3390/ijerph17082696.
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A previous study in Ethiopia reported significant variation in rotavirus vaccine uptake across socioeconomic strata. This study aims to quantify socioeconomic inequality of rotavirus vaccine uptake in Ethiopia and to identify the contributing factors for the inequality. The concentration curve (CC) and the Erreygers Normalized Concentration Index (ECI) were used to assess the socioeconomic related inequality in rotavirus vaccine uptake using data from the 2016 Ethiopian Demographic and Health Survey. Decomposition analysis was conducted to identify the drivers of inequalities. The CC for rotavirus vaccine uptake lay below the line of equality and the ECI was 0.270 (p < 0.001) indicating that uptake of rotavirus vaccine in Ethiopia was significantly concentrated among children from families with better socioeconomic status. The decomposition analysis showed that underlining inequalities in maternal health care services utilization, including antenatal care use (18.4%) and institutional delivery (8.1%), exposure to media (12.8%), and maternal educational level (9.7%) were responsible for the majority of observed inequalities in the uptake of rotavirus vaccine. The findings suggested that there is significant socioeconomic inequality in rotavirus vaccine uptake in Ethiopia. Multi-sectoral actions are required to reduce the inequalities, inclusive increasing maternal health care services, and educational attainments among economically disadvantaged mothers.
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Andrade, Fabíola Bof de, and Flávia Cristina Drumond Andrade. "Socioeconomic inequalities related to dental care needs among adolescents and adults living in the state of Minas Gerais, Brazil." Cadernos Saúde Coletiva 29, no. 3 (September 2021): 322–29. http://dx.doi.org/10.1590/1414-462x202129030186.
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Abstract Background There is significant evidence of inequalities in the need for dental treatment, and their monitoring is essential for public health planning. Objective To measure the extent of the association between socioeconomic inequality and need for dental care. Method This study used data from the 2011 Survey of Oral Health Conditions, including a representative sample of adolescents (n=2,310) and adults (n=1,188) from the state of Minas Gerais, Brazil. Need for dental treatment was evaluated according to criteria of the World Health Organization (WHO). Family income was used as a measure of socioeconomic status. The magnitude of socioeconomic inequalities related to the need for treatment was assessed using the slope index of inequality (SII) and the relative index of inequality (RII). Results Among adolescents, the SII was -22.9% (95% CI -34.8; -11.0) and the estimated RII was 0.61 (95% CI 0.47; 0.79). Among adults, the SII was -28.0% (95% CI -39.8; -16.3) and the RII was 0.58 (95% CI 0.45; 0.74). Conclusion There are socioeconomic inequalities regarding the need for dental treatment, and individuals with lower family income present a higher prevalence of need.
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Shibalkov, Ivan P., Irina A. Pavlova, Olga P. Nedospasova, and Ekaterina K. Tagina. "Systematization of Socioeconomic Factors that Determine Health Inequality: A Literature Review." Vestnik Tomskogo gosudarstvennogo universiteta, no. 468 (2021): 101–14. http://dx.doi.org/10.17223/15617793/468/12.
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Academic and expert community is continuously researching all aspects of inequality. However, problems of inequality in healthcare (due to objective circumstances (ethnicity, gender, etc.) and settings in which people are born, grow up, work, and age) have been studied to a lesser extent. The study aims to summarize and analyze literature on the identification and systematization of socioeconomic factors affecting inequality in health on individual and population levels. Health factors are primarily determined by a person's socioeconomic position (SEP), including education, income, and occupation. Socio-economic factors that determine inequality in health are all factors that affect the absolute and relative (relative to other members of the society in which the individual lives) social and economic situation of a person. In addition to them, the analysis includes institutions that potentially influence a person's health: a person, at their own free will or in connection with established norms, interacts with these institutions regularly during their life. A literature review using the PubMed, Web of Science, Scopus, Russian Science Citation Index databases was carried out. The search depth by the time parameter had no restrictions. The keywords “socioeconomic status”, “socioeconomic position”, “inequality in health”, “health factors” were used to analyze more than 350 publications. The analysis allowed us to divide socioeconomic factors into the following categories and subcategories related to education (level of education of a person, level of education of a partner, gender differences in education, medical awareness), welfare and financial security (level of income, income inequality in society, macroeconomic parameters), employment and labor relations (nature and conditions of work, support of employment by the state), environmental factors (ecology and climate, physical habitat, social environment, health care). The factors are also systematized according to the levels of influence: individual level (micro-level), a person's inner circle (meso-level), and society as a whole (macro-level). The study identifies the relationship between various aspects of a person's SEP and their health for the majority of the factor groups for both developed and developing countries. The study results amend and strengthen arguments confirming the importance of the effective functioning of institutions responsible for the health of the population and explain their institutional roles for improving the quality of life and well-being of citizens throughout their life trajectories. In this regard, a systematic study of the factors that determine inequality in health creates conditions for improving the quality of the institutional framework and substantiating the effectiveness of measures aimed at minimizing inequality in health at the micro-, meso-, macro-levels for increasing the well-being of the entire socioeconomic system.
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Muhammad, T., Anjali Elsa Skariah, Manish Kumar, and Shobhit Srivastava. "Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018." BMJ Open 12, no. 6 (June 2022): e054730. http://dx.doi.org/10.1136/bmjopen-2021-054730.
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ObjectivesTo find out the association between socioeconomic and health status and depression among older adults and explore the contributing factors in the socioeconomic and health-related inequalities in late-life depression.DesignA cross-sectional study was conducted using large representative survey data.Setting and participantsData for this study were derived from the baseline wave of the Longitudinal Ageing Study in India conducted during 2017–2018. The effective sample size was 30 888 older adults aged 60 years and above.Primary and secondary outcome measuresThe outcome variable in this study was depression among older adults. Descriptive statistics along with bivariate analysis was conducted to report the preliminary results. Multivariable binary logistic regression analysis and Wagstaff’s decomposition were used to fulfil the objectives of the study.ResultsThere was a significant difference for the prevalence of depression (4.3%; p<0.05) among older adults from poor (11.2%) and non-poor categories (6.8%). The value of the Concentration Index was −0.179 which also confirms that the major depression was more concentrated among poor older adults. About 38.4% of the socioeconomic and health-related inequality was explained by the wealth quintile for major depression among older adults. Moreover, about 26.6% of the inequality in major depression was explained by psychological distress. Self-rated health (SRH), difficulty in activities of daily living (ADL) and instrumental ADL (IADL) contributed 8.7%, 3.3% and 4.8% to the inequality, respectively. Additionally, region explained about 23.1% of inequality followed by life satisfaction (11.2) and working status (9.8%) for major depression among older adults.ConclusionsFindings revealed large socioeconomic and health-related inequalities in depression in older adults which were especially pronounced by poor household economy, widowhood, poor SRH, ADL and IADL difficulty, and psychological distress. In designing prevention programmes, detection and management of older adults with depression should be a high priority, especially for those who are more vulnerable.
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Gagné, Thierry, and Adrian E. Ghenadenik. "Rethinking the relationship between socioeconomic status and health: Challenging how socioeconomic status is currently used in health inequality research." Scandinavian Journal of Public Health 46, no. 1 (December 4, 2017): 53–56. http://dx.doi.org/10.1177/1403494817744987.
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Aims: The Scandinavian Journal of Public Health recently reiterated the importance of addressing social justice and health inequalities in its new editorial policy announcement. One of the related challenges highlighted in that issue was the limited use of sociological theories able to inform the complexity linking the resources and mechanisms captured by the concept of socioeconomic status. This debate article argues that part of the problem lies in the often unchallenged reliance on a generic conceptualization and operationalization of socioeconomic status. These practices hinder researchers’ capacity to examine in finer detail how resources and circumstances promote the unequal distribution of health through distinct yet intertwined pathways. As a potential way forward, this commentary explores how research practices can be challenged through concrete publication policies and guidelines. To this end, we propose a set of recommendations as a tool to strengthen the study of socioeconomic status and, ultimately, the quality of health inequality research. Conclusions: Authors, reviewers, and editors can become champions of change toward the implementation of sociological theory by holding higher standards regarding the conceptualization, operationalization, analysis, and interpretation of results in health inequality research.
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Endalamaw, Aklilu, Charles F. Gilks, Fentie Ambaw, Resham B. Khatri, and Yibeltal Assefa. "Socioeconomic inequality in knowledge about HIV/AIDS over time in Ethiopia: A population-based study." PLOS Global Public Health 3, no. 10 (October 31, 2023): e0002484. http://dx.doi.org/10.1371/journal.pgph.0002484.
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Socioeconomic inequality in comprehensive knowledge about HIV/AIDS can hinder progress towards ending the epidemic threat of this disease. To address the knowledge gap, it is essential to investigate inequality in HIV/AIDS services. This study aimed to investigate socioeconomic inequality, identify contributors, and analyze the trends in inequality in comprehensive knowledge about HIV/AIDS among adults in Ethiopia. A cross-sectional study was conducted using 2005, 2011, and 2016 population-based health survey data. The sample size was 18,818 in 2005, 29,264 in 2011, and 27,261 in 2016. Socioeconomic inequality in comprehensive knowledge about HIV/AIDS was quantified by using a concentration curve and index. Subsequently, the decomposition of the concentration index was conducted using generalised linear regression with a logit link function to quantify covariates’ contribution to wealth-based inequality. The Erreygers’ concentration index was 0.251, 0.239, and 0.201 in 2005, 2011, and 2016, respectively. Watching television (24.2%), household wealth rank (21.4%), ever having been tested for HIV (15.3%), and education status (14.3%) took the significant share of socioeconomic inequality. The percentage contribution of watching television increased from 4.3% in 2005 to 24.2% in 2016. The household wealth rank contribution increased from 14.6% in 2005 to 21.38% in 2016. Education status contribution decreased from 16.2% to 14.3%. The percentage contribution of listening to the radio decreased from 16.9% in 2005 to -2.4% in 2016. The percentage contribution of residence decreased from 7.8% in 2005 to -0.5% in 2016. This study shows comprehensive knowledge about HIV/AIDS was concentrated among individuals with a higher socioeconomic status. Socioeconomic-related inequality in comprehensive knowledge about HIV/AIDS is woven deeply in Ethiopia, though this disparity has been decreased minimally. A combination of individual and public health approaches entangled in a societal system are crucial remedies for the general population and disadvantaged groups. This requires comprehensive interventions according to the primary health care approach.
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CRAIG, PETER, and JOHN FORBES. "SOCIAL POSITION AND HEALTH: ARE OLD AND NEW OCCUPATIONAL CLASSIFICATIONS INTERCHANGEABLE?" Journal of Biosocial Science 37, no. 1 (December 8, 2004): 89–106. http://dx.doi.org/10.1017/s0021932003006424.
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There is growing international interest in the choice of socioeconomic indicators for health research. This study used a combination of standard and novel methods to compare three occupation-based measures of social position in terms of their ability to explain variation and measure inequality in self-assessed health. The recently developed National Statistics Socioeconomic Classification (NS-SEC) is compared with its predecessor, the Registrar General’s Social Class schema (RGSC), and with another occupation-based measure, the Cambridge Social Interaction and Stratification Scale (CAMSIS). With data from two large, independent, nationally representative samples of adults aged 16–64 living in private households in Scotland, logistic regression models are used to compare the classifications' ability to predict self-assessed health. Concentration indices are estimated to compare how well they capture inequality in self-assessed health. The study shows that all three classifications are strongly associated with self-assessed health, though the associations are heavily attenuated by adjustment for one another and for other measures of social position. Despite their differing theoretical bases, the three are closely related. No evidence is found that any of them systematically under- or overstate the extent of inequality in self-assessed health in either men or women, and the extent to which they measure independent dimensions of social inequality is questioned. It is concluded that the availability of the new classifications is unlikely to transform our understanding of the extent or the causes of socioeconomic inequality in health, but provides useful opportunities for sensitivity analysis.
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Annapurna, Afifa Aftab, Sangeeta Kansal, and Alok Kumar. "Socioeconomic Disparity and Risk Factors of Non-communicable Diseases: Analysis of Longitudinal Ageing Study in India using a Decomposition Approach." Indian Journal of Public Health 67, Suppl 1 (January 2023): S18—S26. http://dx.doi.org/10.4103/ijph.ijph_691_23.
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Abstract Introduction: Many countries prioritize health-related research and policy around socioeconomic inequality. In India, data on socioeconomic disparity and risk factors for noncommunicable diseases (NCDs) are limited. The study provides empirical information on socioeconomic disparities in NCD risk factors in India as part of a preventative and policy initiative. Methods: The study used nationally representative data from wave 1 of the Longitudinal Ageing Study in India which adopted a multistage random sampling design. To achieve the objectives of the study, binary logistic regression was used to demonstrate the association between socioeconomic status and NCD risk factors, and further analysis was conducted employing the decomposition method approach using STATA 14 software to assess socioeconomic disparity. Results: Concentration Indices (CIs) revealed that overweight/obesity (CI = 0.157) was more prevalent among the nonpoor, whereas smoking (CI = −0.067) and alcohol consumption (CI = −0.014) were more prevalent among the poor. Wealth status was identified as the primary contributor to socioeconomic inequality for all of the risk factors of NCDs. Education was also the leading cause of socioeconomic inequality with respect to alcohol, smoking, high blood pressure, and obesity. Conclusion: Identifying the specific needs of impoverished and nonpoor populations is necessary for addressing NCD risk factors and inequalities. It is essential to implement interventions that address the underlying social determinants of health and promote health equality to reduce the burden of NCDs and enhance health outcomes for all.
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Ankara, Hasan Giray. "SOCIOECONOMIC VARIATIONS IN INDUCED ABORTION IN TURKEY." Journal of Biosocial Science 49, no. 1 (April 22, 2016): 99–122. http://dx.doi.org/10.1017/s0021932016000158.
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SummaryThis study aimed to identify the levels of, and socioeconomic variations in, income-related inequality in induced abortion among Turkish women. The study included 15,480 ever-married women of reproductive age (15–49) from the 2003 and 2008 waves of the Turkish Demographic and Health Survey. The measured inequalities in abortion levels and their changes over time were decomposed into the percentage contributions of selected socioeconomic factors using ordinary least square analysis and concentration indices were calculated. The inequalities and their first difference (difference in inequalities between 2003 and 2008) were decomposed using the approaches of Wagstaffet al.(2003). Higher socioeconomic characteristics (such as higher levels of wealth and education and better neighbourhood) were found to be associated with higher rates of abortion. Inequality analyses indicated that although deprived women become more familiar with abortion over time, abortion was still more concentrated among affluent women in the 2008 survey. The decomposition analyses suggested that wealth, age, education and level of regional development were the most important contributors to income-related inequality in abortion. Therefore policies that (i) increase the level of wealth and education of deprived women, (ii) develop deprived regions of Turkey, (iii) improve knowledge about family planning and, especially (iv) enhance the accessibility of family planning services for deprived and/or rural women, may be beneficial for reducing socioeconomic variations in abortion in the country.
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Amare, Tsegaw, Endalkachew Dellie, and Getasew Amare. "Trends of Inequalities in Early Initiation of Breastfeeding in Ethiopia: Evidence from Ethiopian Demographic and Health Surveys, 2000-2016." BioMed Research International 2022 (February 27, 2022): 1–8. http://dx.doi.org/10.1155/2022/5533668.
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Background. Early initiation of breastfeeding (EIBF) is a costless practice with numerous neonates’ survival benefits. Thus, any disparity results in an unacceptably high neonatal death rate but socioeconomic disparities on EIBF have not been well explored in Ethiopia. Therefore, this study is aimed at assessing the socioeconomic inequalities of EIBF in Ethiopia from 2000 to 2016. Methods. The Ethiopian demographic and health survey data and the World Health Organization’s Health Equity Assessment Toolkit were used to investigate the inequalities in EIBF across the wealth quintile, education, residence, and subnational region. Difference, ratio, slope index inequality (SII), relative index inequality (RII), and population attributable risk (PAR) were used as equity summary measures. Results. In Ethiopia, EIBF practice was 47.4% in 2000, 66.2% in 2005, 51.5% in 2011, and 73.3% in 2016. Wealth-related inequality was observed in the 2000, 2005, and 2011 survey years with SII of -7.1%, -8.8%, and 8.7%, respectively, whereas educational-related inequality was observed in 2005 and 2011 with SII of -11.7% and 6.5%, respectively. However, significant change in wealth-, education-, and residence-related inequalities was detected in 2011. Regional inequality on EIBF was observed in all survey years with a difference of 35.7%, 38.0%, 29.1%, and 48.5% in the 2000, 2005, 2011, and 2016 survey years, respectively. But a significant change in regional inequality was noted in 2016 with a PAR of 17.2%. Conclusions. In Ethiopia, the wealth-, residence-, and educational-related inequalities of EIBF increased significantly between the years 2000 and 2011. However, regional inequality persistently increased from 2000 to 2016. Overall, one-sixth of the national level EIBF was decreased due to regional disparity in 2016. The northern regions of Ethiopia (Tigray, Afar, and Amhara) poorly performed compared to the peer regions. Therefore, interventions targeting them would significantly improve the national level of EIBF.
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Somkotra, T. "P1-523 Socioeconomic-related inequality in oral health risk behaviours among adolescents in Thailand." Journal of Epidemiology & Community Health 65, Suppl 1 (August 1, 2011): A211. http://dx.doi.org/10.1136/jech.2011.142976h.11.
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Amornsuradech, Sirinthip, and Warangkana Vejvithee. "Socioeconomic inequality and dental caries among Thai working age population." Journal of Health Research 33, no. 6 (November 11, 2019): 517–28. http://dx.doi.org/10.1108/jhr-03-2019-0060.
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Purpose The purpose of this paper is to determine the relationship between socioeconomic status (SES) and oral health among Thai adults. Design/methodology/approach This study is a cross-sectional analytical study using secondary data from the 7th Thailand National Oral Health Survey (2012). Age group 35–44 years old samples were used to represent the working age population. Oral health outcome was determined by untreated dental caries. SES was indicated by income, education and occupational groups. Demographic background, oral health-related behavior and access to dental service were adjusted for analysis. Binary logistic regression analysis was performed to determine the relationship between independent variables and oral health outcome. Findings People with lower education showed a higher odds ratio for having untreated dental caries before and after controlling for related variables. Those living in the north and northeast, using additional cleaning tools and going to the public provider for dental service also showed better oral health. Research limitations/implications The limitation of this study is that the cross-sectional study cannot indicate casual relationships. The national oral health survey was not designed to find relationships between factors. The access to data and measurement of SES was limited. The policy maker should emphasize on people with lower education which have a higher risk for dental caries to improve oral health in disadvantaged groups. Future research should include all related factors in the study including diet and knowledge about oral health. Moreover, oral health outcome is a long-term effect which accumulated through a lifetime. The social class might change over time and so do behaviors. Originality/value There is socioeconomic inequality in dental caries of Thai working age population.
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Teni, Fitsum Sebsibe, Ulf-G. Gerdtham, Reiner Leidl, Martin Henriksson, Mimmi Åström, Sun Sun, and Kristina Burström. "Inequality and heterogeneity in health-related quality of life: findings based on a large sample of cross-sectional EQ-5D-5L data from the Swedish general population." Quality of Life Research 31, no. 3 (October 10, 2021): 697–712. http://dx.doi.org/10.1007/s11136-021-02982-3.
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Abstract Purpose This study aimed to investigate inequality and heterogeneity in health-related quality of life (HRQoL) and to provide EQ-5D-5L population reference data for Sweden. Methods Based on a large Swedish population-based survey, 25,867 respondents aged 30‒104 years, HRQoL is described by sex, age, education, income, economic activity, health-related behaviours, self-reported diseases and conditions. Results are presented by EQ-5D-5L dimensions, respondents rating of their overall health on the EQ visual analogue scale (EQ VAS), VAS index value and TTO (time trade-off) index value allowing for calculation of quality-adjusted life years (QALYs). Ordinary Least Squares and multivariable logistic regression analyses were used to study inequalities in observed EQ VAS score between socioeconomic groups and the likelihood to report problems on the dimensions, respectively, adjusted for confounders. Results In total, 896 different health states were reported; 24.1% did not report any problems. Most problems were reported with pain/discomfort. Women reported worse HRQoL than men, and health deteriorated with age. The strongest association between diseases and conditions and EQ VAS score was seen for depression and mental health problems. There was a socioeconomic gradient in HRQoL; adjusting for health-related behaviours, diseases and conditions slightly reduced the differences between educational groups and income groups, but socioeconomic inequalities largely remained. Conclusion EQ-5D-5L population reference (norms) data are now available for Sweden, including socioeconomic differentials. Results may be used for comparisons with disease-specific populations and in health economic evaluations. The observed socioeconomic inequality in HRQoL should be of great importance for policy makers concerned with equity aspects.
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Khoramrooz, Maryam, Fariba Zare, Farideh Sadeghian, Ali Dadgari, Reza Chaman, and Seyed Mohammad Mirrezaie. "Socioeconomic inequalities in employees’ health-enhancing physical activity: Evidence from the SHAHWAR cohort study in Iran." PLOS ONE 18, no. 5 (May 15, 2023): e0285620. http://dx.doi.org/10.1371/journal.pone.0285620.
Повний текст джерелаАнотація:
Background Increasing level of physical activity (PA) among working population is of particular importance, because of the high return of investment on employees’ PA. This study was aimed to investigate socioeconomic inequalities in Health-Enhancing Physical Activity (HEPA) among employees of a Medical Sciences University in Iran. Methods Data were extracted from the SHAHWAR Cohort study in Iran. Concentration index (C) and Wagstaff decomposition techniques were applied to determine socioeconomic inequality in the study outcomes and its contributors, respectively. Results Nearly half of the university employees (44.6%) had poor HEPA, and employees with high socioeconomic status (SES) suffered more from it (C = 0.109; 95% CI: 0.075, 0.143). Also, we found while poor work-related PA (C = 0.175; 95% CI: 0.142, 0.209) and poor transport-related PA (C = 0.081, 95% CI: 0.047, 0.115) were more concentrated among high-SES employees, low-SES employees more affected by the poor PA at leisure time (C = -0.180; 95% CI: -0.213, -0.146). Shift working, and having higher SES and subjective social status were the main factors that positively contributed to the measured inequality in employees’ poor HEPA by 33%, 31.7%, and 29%, respectively, whereas, having a married life had a negative contribution of -39.1%. The measured inequality in poor leisure-time PA was mainly attributable to SES, having a married life, urban residency, and female gender by 58.1%, 32.5%, 28.5%, and -32.6%, respectively. SES, urban residency, shift working, and female gender, with the contributions of 42%, 33.5%, 21.6%, and -17.3%, respectively, were the main contributors of poor work-related PA inequality. Urban residency, having a married life, SES, and subjective social status mainly contributed to the inequality of poor transport-related PA by 82.9%, -58.7%, 36.3%, and 33.5%, respectively, followed by using a personal car (12.3%) and female gender (11.3%). Conclusions To reduce the measured inequalities in employees’ PA, workplace health promotion programs should aim to educate and support male, urban resident, high-SES, high-social-class, and non-shift work employees to increase their PA at workplace, and female, married, rural resident, and low-SES employees to increase their leisure-time PA. Active transportation can be promoted among female, married, urban resident, high-SES, and high-social-class employees and those use a personal car.
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Devkota, Satis C., and Mukti P. Upadhyay. "How does education inequality respond to policy? A method and application to survey data from Albania and Nepal." Journal of Economic Studies 43, no. 2 (May 9, 2016): 166–77. http://dx.doi.org/10.1108/jes-09-2014-0156.
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Purpose – The purpose of this paper is to measure inequality in education and examine how socioeconomic factors affect education inequality in Albania and Nepal. Design/methodology/approach – Using large household survey data sets the authors calculate income-related inequality in education and decompose the inequality into factors that determine educational attainment. The decomposition procedure establishes the role played by two sets of factors: elasticities of education demand with respect to its determinants; and inequalities in those determinants. The paper then proposes a new mechanism to quantify the effects of policy simulations regarding income, urbanization, and distance to school on education inequality. Findings – Both the countries show significant inequality in education. Educational attainment in Albania and Nepal is determined by socioeconomic, demographic and geographic factors of which three are particularly significant in affecting inequality – income, urbanization and distance to school. Research limitations/implications – While schooling for most individuals is largely financed by public subsidy in the countries, attainment is also likely affected by the price of education services and cost of health care. Identification of those factors in the context of more comprehensive data will enable researchers in future to draw firmer conclusions. Practical implications – The proposed method can help to identify cost-effective and sustainable policies to reduce socioeconomic inequality in education in developing countries. Social implications – Reduction in education inequality can lead to higher income and better health which are instrumental in uplifting the poor in developing countries. Originality/value – This is the first paper to measure education inequality using a concentration index and to propose a new mechanism to show the effect of simulated policies on education inequality.
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Nglazi, Mweete D., and John E. Ataguba. "Did socioeconomic inequalities in overweight and obesity in South African women of childbearing age improve between 1998 and 2016? A decomposition analysis." PLOS Global Public Health 4, no. 11 (November 14, 2024): e0003719. http://dx.doi.org/10.1371/journal.pgph.0003719.
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Overweight and obesity in adult women contribute to deaths and disability from non-communicable diseases (NCDs) and obesity-related health problems in their offspring. Globally, overweight and obesity prevalence among women of childbearing age (WCBA) has increased, but associated socioeconomic inequality remains unclear. This study, therefore, assesses the changing patterns in the socioeconomic inequality in overweight and obesity among South African non-pregnant WCBA between 1998 and 2016. It uses data from the 1998 and 2016 Demographic and Health Surveys. Socioeconomic inequality in overweight and obesity was assessed using the concentration index (C). The index was decomposed to identify contributing factors to obesity and overweight inequalities. Factors contributing to changes in inequalities between 1998 and 2016 were assessed using the Oaxaca-type decomposition approach. Socioeconomic inequalities in overweight and obesity among WCBA in South Africa increased between 1998 (C of 0.02 and 0.06, respectively) and 2016 (C of 0.04 and 0.08, respectively). Socioeconomic status was the biggest contributor to overweight and obesity inequalities for both years. The Oaxaca-type decomposition showed that race and urban residence are major contributors to changes in overweight and obesity inequalities. Policies such as the current tax on sugar-sweetened beverages and subsidising fruits and vegetables, among others, are needed to prioritise WCBA, especially for those from disadvantaged socioeconomic backgrounds, in addressing inequalities in overweight and obesity in South Africa.
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Houghton, Natalia, Ernesto Bascolo, and Amalia del Riego. "Socioeconomic inequalities in access barriers to seeking health services in four Latin American countries." Revista Panamericana de Salud Pública 44 (March 4, 2020): 1. http://dx.doi.org/10.26633/rpsp.2020.11.
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Objective. To present summary measures of socioeconomic inequalities in access barriers to health services in Colombia, El Salvador, Paraguay, and Peru. Methods. This cross-sectional study used data from nationally - representative household surveys in Colombia, El Salvador, Peru, and Paraguay to analyze income-related inequalities in barriers to seeking health services. Households that reported having a health problem (disease/accident) and not seeking professional health care were considered to be facing access barriers. The measures of inequality were the slope index of inequality and relative index of inequality. Results. Inequality trends were mixed across the four countries. All showed improvement, but large inequality gaps persisted between the highest and lowest income quintiles, despite health care reforms. Relative inequality gaps were highest in Colombia (60%), followed by Paraguay (30%), Peru (20%), and El Salvador (20%). Conclusions. The effect of national policy initiatives on equity to accessing health services should be the object of future analysis. There is also a need for research on national and regional monitoring of access barriers and explanatory factors for why people do not seek care, even when having a health problem.
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Cuadrado, Cristóbal, Pedro Zitko, Trinidad Covarrubias, Dunia Hernandez, Cristina Sade, Carolina Klein, and Alejandro Gomez. "Association Between Adolescent Suicide and Sociodemographic Factors in Chile." Crisis 36, no. 4 (July 2015): 281–90. http://dx.doi.org/10.1027/0227-5910/a000324.
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Abstract. Background: Adolescent suicide rates (ASR) are a matter of concern worldwide. Causes of this trend are not understood and could correspond to socioeconomic factors such as inequality. Aim: To investigate sociodemographic variables related to ASR, particularly the potential association with indicators of socioeconomic inequality. Method: Cross-sectional ecological study analyzing data from 29 health districts with univariate and multivariable multilevel Poisson models. Results: ASR were higher in male adolescents and at increasing age. No association was found between ASR and inequality (Gini coefficient and 20/20 ratio). Analysis revealed that living in a single-parent family is associated with ASR. Conclusions: The usual demographic patterns of adolescent suicide apply in Chile. An emerging variable of interest is single-parent family. No cross-sectional association between social inequality and ASR was found based on conflicting evidence. These results should be explored in future prospective population studies to further understand associated social factors.
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Armanmehr, Vajihe, Zohreh Shahghasemi, Ali Alami, Sahar Babasafari, and Shahab Rezaeian. "Regional Mental Health Inequality in a Limited Data Region in the Northeast of Iran: A Decomposition Analysis." Journal of Research & Health 13, no. 1 (January 1, 2023): 11–18. http://dx.doi.org/10.32598/jrh.13.1.100.7.
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Background: Limited information still exists about the distribution of mental health (MH) in small districts. Considering the diversity in cultural specifications of entities in different societies, the current study aimed-assess the inequality of poor MH and corresponding socio-demographic components in a general population. Methods: This population-based cross-sectional study was conducted in Gonabad City, North Eastern Iran. Data were collected by a general health questionnaire-28 (GHQ-28) assess MH status, considering a cut-off point of 23. The concentration index defines the inequality in the MH. Decomposition analysis was done-identify the contribution of each explanatory variable-the socioeconomic inequality in MH prevalence. Results: Eight hundred subjects were recruited (response rate=98%); approximately 41.6% were aged 30 years or younger, half of whom were females. The overall prevalence of poor MH was 24.7% (95% CI: 21.8-27.9%) and the age-adjusted prevalence of poor MH was 27.5% (95% CI: 24.2-31.2%). A concentration of poor MH prevalence was observed among the poorest people (concentration index: -0.15). Socioeconomic Status (SES) (59.7%), age (24.1%), and gender (4.7%) were identified as the main contributors-socioeconomic-related inequality in poor MH prevalence. Conclusion: Poor MH is significantly concentrated among the poorest people. Therefore, SES appeared-play a key role in improving the health of individuals, which can lead-improved health status in a community. Furthermore, these data suggest that the MH initiative should target the elderly and women via a recently determined family physician plan in Iran.
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Ravaghi, V., D. S. Hargreaves, and A. J. Morris. "Persistent Socioeconomic Inequality in Child Dental Caries in England despite Equal Attendance." JDR Clinical & Translational Research 5, no. 2 (September 5, 2019): 185–94. http://dx.doi.org/10.1177/2380084419872136.
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Introduction: Despite a decline in the prevalence of dental caries among children in England and ongoing arrangements for the provision of free dental care up to the age of 18 y, there is limited information on the pattern and trend of socioeconomic inequalities in dental caries and dental attendance. Methods: We estimated the magnitude of deprivation-related inequalities for dental caries and dental attendance in young children, using publicly available data and 2 regression-based summary measures of inequalities: slope index of inequality and relative index of inequality. Results: We found no significant absolute or relative inequalities in dental attendance across English areas in the past decade, while there were persistent absolute and relative inequalities in dental caries. Socioeconomic inequalities in dental caries decreased between 2007 and 2012; thereafter, the relative inequalities increased. Conclusions: The apparent widening inequality in child dental caries in England despite equal access to dental care is a challenge for policy makers. Knowledge Transfer Statement: While caries prevalence among English children has declined over the past decade, there has been an increase in socioeconomic inequalities in oral health despite there being no inequality in dental attendance. This has implications for the development of oral health strategy and planning dental services.
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Bintabara, Deogratius, and Namanya Basinda. "Twelve-year persistence of inequalities in antenatal care utilisation among women in Tanzania: a decomposition analysis of population-based cross-sectional surveys." BMJ Open 11, no. 4 (April 2021): e040450. http://dx.doi.org/10.1136/bmjopen-2020-040450.
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ObjectiveThis study was undertaken to assess the trend and contributors of socioeconomic inequalities in antenatal care (ANC) utilisation among women of reproductive age in Tanzania from 2004 to 2016.DesignPopulation-based cross-sectional surveys.SettingThis study analysed nationally representative data for women of reproductive age obtained from the 2004–2016 Tanzania Demographic Health Surveys.Primary outcome measureThe outcome variables analysed in this study are: (1) attendance of ANC and (2) accessing adequate antenatal care.Analytical methodsThe concentration curve and the concentration index were used to measure socioeconomic inequality in attending and accessing adequate ANC. The concentration index was decomposed to identify the factors explaining the observed socioeconomic inequality of these two outcomes.ResultsThe concentration index for attending at least four ANC visits increased from 0.169 in 2004 to 0.243 in 2016 (p<0.01). Similarly, for accessing adequate care, the index increased from 0.147 in 2004 to 0.355 in 2016 (p<0.01). This indicates the significant increase in socioeconomic inequalities (favouring wealthier women) for these two outcomes over time. Furthermore, the results show that wealth status was the largest contributor to inequality in both attending at least four visits (71%, 50% and 70%) and accessing adequate ANC (50%, 42% and 51%) in 2004, 2010 and 2016, respectively, in favour of wealthier women (p<0.05). The other contributors to socioeconomic inequalities in ANC utilisation were maternal education and type of residence.ConclusionOver the 12 years of surveys, there was no reduction in socioeconomic inequalities in ANC utilisation in Tanzania. Therefore, the efforts of achieving universal health coverage should focus on reducing wealth-related inequality and improving women’s education from poor households.
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Hasan, Mohammad Monirul, Jalal Uddin, Mohammad Habibullah Pulok, Nabila Zaman, and Mohammad Hajizadeh. "Socioeconomic Inequalities in Child Malnutrition in Bangladesh: Do They Differ by Region?" International Journal of Environmental Research and Public Health 17, no. 3 (February 8, 2020): 1079. http://dx.doi.org/10.3390/ijerph17031079.
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Socioeconomic inequality in child malnutrition is well-evident in Bangladesh. However, little is known about whether this inequality differs by regional contexts. We used pooled data from the 2011 and 2014 Bangladesh Demographic and Health Survey to examine regional differences in socioeconomic inequalities in stunting and underweight among children under five. The analysis included 14,602 children aged 0–59 months. We used logistic regression models and the Concentration index to assess and quantify wealth- and education-related inequalities in child malnutrition. We found stunting and underweight to be more concentrated among children from poorer households and born to less-educated mothers. Although the poverty level was low in the eastern regions, socioeconomic inequalities were greater in these regions compared to the western regions. The extent of socioeconomic inequality was the highest in Sylhet and Chittagong for stunting and underweight, respectively, while it was the lowest in Khulna. Regression results demonstrated the protective effects of socioeconomic status (SES) on child malnutrition. The regional differences in the effects of SES tend to diverge at the lower levels of SES, while they converge or attenuate at the highest levels. Our findings have policy implications for developing programs and interventions targeted to reduce socioeconomic inequalities in child malnutrition in subnational regions of Bangladesh.
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Endalamaw, Aklilu, Charles F. Gilks, and Yibeltal Assefa. "Socioeconomic inequality in adults undertaking HIV testing over time in Ethiopia based on data from demographic and health surveys." PLOS ONE 19, no. 2 (February 14, 2024): e0296869. http://dx.doi.org/10.1371/journal.pone.0296869.
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Introduction 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. Methods 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. Results 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. Conclusions 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.
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Shibre, Gebretsadik, Betregiorgis Zegeye, Gorems Lemma, Birhan Abebe, and Gashaw Garedew Woldeamanuel. "Socioeconomic, sex and area related inequalities in childhood stunting in Mauritania: Evidence from the Mauritania Multiple Indicator Cluster Surveys (2007–2015)." PLOS ONE 16, no. 10 (October 18, 2021): e0258461. http://dx.doi.org/10.1371/journal.pone.0258461.
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Introduction The prevalence of stunting in under five children is high in Mauritania. However, there is a paucity of evidence on the extent and the overtime alteration of inequality in stunting. To this end, we did this study to investigate stunting inequality and the change with time using three rounds of Mauritania Multiple Indicator Cluster Surveys. The evidence is important to inform implementation of equitable nutrition interventions to help narrow inequality in stunting between population groups. Methods World Health Organization’s (WHO) Health Equity Assessment Toolkit (HEAT) was used in the analysis of stunting inequality. Following standard equity analysis methods recommended by the WHO, we performed disaggregated analysis of stunting across five equity stratfiers: Wealth, education, residence, sex and sub-national regions. Then, we summarized stunting inequality through four measures of inequality: Difference, Ratio, Population Attributable Fraction and Population Attributable Risk. The point estimates of stunting were accompanied by 95% confidence intervals to measure the statistical significance of the findings. Results The national average of childhood stunting in 2007, 2011 and 2015 was 31.3%, 29.7% and 28.2%, respectively. Glaring inequalities in stunting around the five equity stratifiers were observed in all the studied periods. In the most recent survey included in our study (2015), for instance, we recorded substantial wealth (PAF = -33.60; 95% CI: -39.79, -27.42) and education (PAF = -5.60; 95% CI: -9.68, -1.52) related stunting inequalities. Overall, no substantial improvement was documented in wealth and sex related inequality in stunting between 2007 and 2011 while region-based inequality worsened during the same time periods. Conclusions The burden of stunting appeared to be heavily concentrated among children born to socioeconomically worse-off women, women who live in rural settings and certain subnational regions. Targeted nutrition interventions are required to address drivers of stunting embedded within geographic and socioeconomic contexts.
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Choi, Eunji, Ha Na Cho, Da Hea Seo, Boyoung Park, Sohee Park, Juhee Cho, Sue Kim, Yeong-Ran Park, Kui Son Choi, and Yumie Rhee. "Socioeconomic inequalities in obesity among Korean women aged 19-79 years: the 2016 Korean Study of Women’s Health-Related Issues." Epidemiology and Health 41 (February 13, 2019): e2019005. http://dx.doi.org/10.4178/epih.e2019005.
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OBJECTIVES: While the prevalence of obesity in Asian women has remained stagnant, studies of socioeconomic inequalities in obesity among Asian women are scarce. This study aimed to examine the recent prevalence of obesity in Korean women aged between 19 years and 79 years and to analyze socioeconomic inequalities in obesity.METHODS: Data were derived from the 2016 Korean Study of Women’s Health-Related Issues. The chi-square test and logistic regression analysis were used to analyze the associations between socioeconomic factors and obesity using Asian standard body mass index (BMI) categories: low (<18.5 kg/m2 ), normal (18.5-22.9 kg/m2 ), overweight (23.0-24.9 kg/m2 ), and obese (≥25.0 kg/ m2 ). As inequality-specific indicators, the slope index of inequality (SII) and relative index of inequality (RII) were calculated, with adjustment for age and self-reported health status.RESULTS: Korean women were classified into the following BMI categories: underweight (5.3%), normal weight (59.1%), overweight (21.2%), and obese (14.4%). The SII and RII revealed substantial inequalities in obesity in favor of more urbanized women (SII, 4.5; RII, 1.4) and against of women who were highly educated (SII, -16.7; RII, 0.3). Subgroup analysis revealed inequalities in obesity according to household income among younger women and according to urbanization among women aged 65-79 years.CONCLUSIONS: Clear educational inequalities in obesity existed in Korean women. Reverse inequalities in urbanization were also apparent in older women. Developing strategies to address the multiple observed inequalities in obesity among Korean women may prove essential for effectively reducing the burden of this disease.
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Nguyen, Thi Phuoc Lai, Salvatore G. P. Virdis, and Ekbordin Winjikul. "Inequality of Low Air Quality-Related Health Impacts among Socioeconomic Groups in the World of Work." International Journal of Environmental Research and Public Health 19, no. 19 (October 10, 2022): 12980. http://dx.doi.org/10.3390/ijerph191912980.
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This research aimed to assess the perceptions of air quality and health symptoms caused by low urban air quality among vulnerable socio-economic groups in the world of work in Bangkok, Thailand through a questionnaire survey of 400 workers of both formal and informal sectors in the five districts with different socio-economic characteristics and levels of air pollution. The findings showed symmetry between air quality-monitoring data and health symptoms of different socio-economic groups but asymmetry between air quality-monitoring data and people’s perceptions of air quality in their areas. It also showed inequalities of low air quality-related health impacts on socio-economic groups in the world of work. People working near the streets, highways, and industrial zones tended to have more health symptoms related to low air quality, and informal sector workers faced more health risks than formal sector workers. The study appeals for effective air pollution communication to enhance the public and informal sector worker population’s literacy of air pollution, the sources of air pollution and its critical health impacts, and the available and sufficient primary care organizations and community health care centers to address work-related health needs to reach the informal sector worker population.
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Asaria, Miqdad, Sumit Mazumdar, Samik Chowdhury, Papiya Mazumdar, Abhiroop Mukhopadhyay, and Indrani Gupta. "Socioeconomic inequality in life expectancy in India." BMJ Global Health 4, no. 3 (May 2019): e001445. http://dx.doi.org/10.1136/bmjgh-2019-001445.
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IntroductionConcern for health inequalities is an important driver of health policy in India; however, much of the empirical evidence regarding health inequalities in the country is piecemeal focusing only on specific diseases or on access to particular treatments. This study estimates inequalities in health across the whole life course for the entire Indian population. These estimates are used to calculate the socioeconomic disparities in life expectancy at birth in the population.MethodsPopulation mortality data from the Indian Sample Registration System were combined with data on mortality rates by wealth quintile from the National Family Health Survey to calculate wealth quintile specific mortality rates. Results were calculated separately for males and females as well as for urban and rural populations. Life tables were constructed for each subpopulation and used to calculate distributions of life expectancy at birth by wealth quintile. Absolute gap and relative gap indices of inequality were used to quantify the health disparity in terms of life expectancy at birth between the richest and poorest fifths of households.ResultsLife expectancy at birth was 65.1 years for the poorest fifth of households in India as compared with 72.7 years for the richest fifth of households. This constituted an absolute gap of 7.6 years and a relative gap of 11.7 %. Women had both higher life expectancy at birth and narrower wealth-related disparities in life expectancy than men. Life expectancy at birth was higher across the wealth distribution in urban households as compared with rural households with inequalities in life expectancy widest for men living in urban areas and narrowest for women living in urban areas.ConclusionAs India progresses towards Universal Health Coverage, the baseline social distributions of health estimated in this study will allow policy makers to target and monitor the health equity impacts of health policies introduced.
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Xu, Yongjian, Siyu Zhu, Tao Zhang, Duolao Wang, Junteng Hu, Jianmin Gao, and Zhongliang Zhou. "Explaining Income-Related Inequalities in Dietary Knowledge: Evidence from the China Health and Nutrition Survey." International Journal of Environmental Research and Public Health 17, no. 2 (January 15, 2020): 532. http://dx.doi.org/10.3390/ijerph17020532.
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Lack of adequate dietary knowledge may result in poor health conditions. This study aims to measure income-related inequality in dietary knowledge, and to explain the sources of the inequality. Data were from the China Health and Nutrition Survey (CHNS) conducted in 2015. A summary of the dietary knowledge score and dietary guideline awareness was used to measure the dietary knowledge of respondents. The concentration index was employed as a measure of socioeconomic inequality and was decomposed into its determining factors. The study found that the proportion of respondents who correctly answered questions on dietary knowledge was significantly low for some questions. Compared to rural residents, urban residents had a higher proportion of correctly answered dietary knowledge questions. In addition, there are pro-rich inequalities in dietary knowledge. This observed inequality is determined not only by individual factors but also high-level area factors. Our study recommends that future dietary education programs could take different strategies for individuals with different educational levels and focus more on disadvantaged people. It would be beneficial to consider local dietary habits in developing education materials.
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Högberg, Pi, Göran Henriksson, Carme Borrell, Marius Ciutan, Giuseppe Costa, Irene Georgiou, Rafal Halik, et al. "Monitoring Health Inequalities in 12 European Countries: Lessons Learned from the Joint Action Health Equity Europe." International Journal of Environmental Research and Public Health 19, no. 13 (June 23, 2022): 7663. http://dx.doi.org/10.3390/ijerph19137663.
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To raise awareness about health inequalities, a well-functioning health inequality monitoring system (HIMS) is crucial. Drawing on work conducted under the Joint Action Health Equity Europe, the aim of this paper is to illustrate the strengths and weaknesses in current health inequality monitoring based on lessons learned from 12 European countries and to discuss what can be done to strengthen their capacities. Fifty-five statements were used to collect information about the status of the capacities at different steps of the monitoring process. The results indicate that the preconditions for monitoring vary greatly between countries. The availability and quality of data are generally regarded as strong, as is the ability to disaggregate data by age and gender. Regarded as poorer is the ability to disaggregate data by socioeconomic factors, such as education and income, or by other measures of social position, such as ethnicity. Few countries have a proper health inequality monitoring strategy in place and, where in place, it is often regarded as poorly up to date with policymakers’ needs. These findings suggest that non-data-related issues might be overlooked aspects of health inequality monitoring. Structures for stakeholder involvement and communication that attracts attention from policymakers are examples of aspects that deserve more effort.
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Santos, Joana, Irina Kislaya, Liliana Antunes, Ana João Santos, Ana Paula Rodrigues, Mariana Neto, and Carlos Matias Dias. "Diabetes: Socioeconomic Inequalities in the Portuguese Population in 2014." Acta Médica Portuguesa 30, no. 7-8 (August 31, 2017): 561. http://dx.doi.org/10.20344/amp.8235.
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Introduction: Diabetes is a major public health problem and it is related to socioeconomic factors. The aim of this study is to describe socioeconomic inequalities in the distribution of diabetes in the population with 25 years or more, resident in Portugal in 2014.Material and Methods: Data from the Health National Survey 2014 was analysed, n = 16 786. We estimated the prevalence of diabetes in the population and stratified by socioeconomic variables namely educational level and income. The extent of socioeconomic inequalities was assessed using concentration index and the relative index of inequality.Results: Diabetes was found to be concentrated among the people with lower educational levels (concentration index = -0.26) and lower income quintiles (concentration index = -0.14). Relative index of inequality also showed a lower degree of inequality among the most educated (0,20; CI 95% = [0,12; 0,32]) and with higher income (0,59; CI 95% = [0,48; 0,74]).Discussion: Distribution of diabetes is associated with education and income. Previous studies have shown that although income might reflect lifestyle patterns, education reflects better social factors that are important for establishing healthier behaviours. Also, the National Health Service, of universal coverage and free of charge, might have contributed to reduce inequalities in the access to health by those with the lowest income.Conclusion: Supporting ‘Health in All Policies’ might reduce inequalities, namely by improving population educational level and actions that promote health literacy.
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Boyd, Jennifer, Clare Bambra, Robin C. Purshouse, and John Holmes. "Beyond Behaviour: How Health Inequality Theory Can Enhance Our Understanding of the ‘Alcohol-Harm Paradox’." International Journal of Environmental Research and Public Health 18, no. 11 (June 3, 2021): 6025. http://dx.doi.org/10.3390/ijerph18116025.
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There are large socioeconomic inequalities in alcohol-related harm. The alcohol harm paradox (AHP) is the consistent finding that lower socioeconomic groups consume the same or less as higher socioeconomic groups yet experience greater rates of harm. To date, alcohol researchers have predominantly taken an individualised behavioural approach to understand the AHP. This paper calls for a new approach which draws on theories of health inequality, specifically the social determinants of health, fundamental cause theory, political economy of health and eco-social models. These theories consist of several interwoven causal mechanisms, including genetic inheritance, the role of social networks, the unequal availability of wealth and other resources, the psychosocial experience of lower socioeconomic position, and the accumulation of these experiences over time. To date, research exploring the causes of the AHP has often lacked clear theoretical underpinning. Drawing on these theoretical approaches in alcohol research would not only address this gap but would also result in a structured effort to identify the causes of the AHP. Given the present lack of clear evidence in favour of any specific theory, it is difficult to conclude whether one theory should take primacy in future research efforts. However, drawing on any of these theories would shift how we think about the causes of the paradox, from health behaviour in isolation to the wider context of complex interacting mechanisms between individuals and their environment. Meanwhile, computer simulations have the potential to test the competing theoretical perspectives, both in the abstract and empirically via synthesis of the disparate existing evidence base. Overall, making greater use of existing theoretical frameworks in alcohol epidemiology would offer novel insights into the AHP and generate knowledge of how to intervene to mitigate inequalities in alcohol-related harm.
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Chen, Yiqun, Petra Persson, and Maria Polyakova. "The Roots of Health Inequality and the Value of Intrafamily Expertise." American Economic Journal: Applied Economics 14, no. 3 (July 1, 2022): 185–223. http://dx.doi.org/10.1257/app.20200405.
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In the context of Sweden, we show that having a doctor in the family raises preventive health investments throughout the life cycle, improves physical health, and prolongs life. Two quasi-experimental research designs—medical school admission lotteries and variation in the timing of medical degrees—support a causal interpretation of these effects. A hypothetical policy that would bring the same health behavior changes and benefits to all Swedes would close 18 percent of the mortality-income gradient. Our results suggest that socioeconomic differences in exposure to health-related expertise may meaningfully contribute to health inequality. (JEL D15, G22, I12, I13, I14, I18)
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Debesay, Jonas, Line Nortvedt, and Birgitta Langhammer. "Social Inequalities and Health among Older Immigrant Women in the Nordic Countries: An Integrative Review." SAGE Open Nursing 8 (January 2022): 237796082210849. http://dx.doi.org/10.1177/23779608221084962.
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Introduction The Nordic countries have a surprisingly strong relative socioeconomic health inequality. Immigrants seem to be disproportionately affected due to their social economic position in the host countries. Healthcare professionals, including nurses, have a professional obligation to adhere to fairness and social equity in healthcare. The aim of this review was to identify and synthesize research on health status and the impact of social inequalities in older immigrant women in the Nordic countries. Methods We conducted an integrative review guided by the Whittemore and Knafl integrative review method. We searched multiple research databases using the keywords immigrant, older, women, socioeconomic inequality, health inequality, and Nordic countries. The results were limited to research published between 1990 and 2021. The retrieved articles were screened and assessed by two independent reviewers. Results Based on the few studies on older immigrant women in the Nordic countries, the review findings indicate that they fare worse in many health indicators compared to immigrant men and the majority population. These differences are related to various health issues, such as anxiety, depression, diabetes, multimorbidity, sedentary lifestyle, and quality of life. Lower participation in cancer screening programs is also a distinctive feature among immigrant women, which could be related to the immigrant women's help-seeking behavior. Transnational family obligations and responsibilities locally leave little room for prioritizing self-care, but differing views of health conditions might also contribute to avoidance of healthcare services. Conclusion This integrative review shows that there is a paucity of studies on the impact of social inequalities on the health status of older immigrant women in the Nordic countries. There is a need for not only research focused on the experiences of health status and inequality but also larger studies mapping the connection between older immigrant women's economic and health status and access to healthcare services.
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Rezaei, Satar, Mohammad Hajizadeh, Yahya Salimi, Ghobad Moradi, and Bijan Nouri. "What Explains Socioeconomic Inequality in Health-related Quality of Life in Iran? A Blinder-Oaxaca Decomposition." Journal of Preventive Medicine and Public Health 51, no. 5 (September 30, 2018): 219–26. http://dx.doi.org/10.3961/jpmph.18.012.
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Xu, Mengru, Xiaoli Gao, Huijing Wu, Min Ding, Chunzi Zhang, Shuo Du, Xing Wang, et al. "Measuring and decomposing socioeconomic‐related inequality in the use of oral health services among Chinese adults." Community Dentistry and Oral Epidemiology 49, no. 1 (September 21, 2020): 47–54. http://dx.doi.org/10.1111/cdoe.12575.
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Jiang, Jinqi, Wanzhen Huang, Yunru Liu, and Zhenhua Wang. "The Temporal and Spatial Changes of Health Inequality in Rural China." Frontiers in Public Health 10 (February 10, 2022). http://dx.doi.org/10.3389/fpubh.2022.821384.
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This article estimates the temporal and spatial changes of health inequality in rural China from 2010 to 2018. Based on a panel database of 29,616 rural residents, the Health Utility Index (HUI) and a spatial econometric model are used for analysis. The results show that, on the temporal dimension, the health inequality of rural China first expands and then deflates. On the spatial dimension, the health inequality gradually deflates from eastern to western China. Furthermore, from 2010 to 2018, the high and low-value areas constantly changed among different provinces. After decomposing the causes of health inequality, it is found that behind the health inequality is the difference of socioeconomic-related status. Moreover, narrowing the difference in socioeconomic-related status is the key to improving health inequality.
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Dorjdagva, J., E. Batbaatar, B. Dorjsuren, and J. Kauhanen. "Socioeconomic Inequalities in Mental Health in Mongolia." European Journal of Public Health 30, Supplement_5 (September 1, 2020). http://dx.doi.org/10.1093/eurpub/ckaa166.1062.
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Abstract Background Promotion of mental health and well-being is recently recognized as a health priority at the global level. In Mongolia, mental health issues have been on the rise. However, less is known on socioeconomic inequality in mental health in the country. The aim of this study is to examine socioeconomic inequality in mental health in the adult population in Mongolia. Methods This study analyzed the data of 30,567 adults from the Household Socio-Economic Survey, collected in 2012 by the National Statistical Office of Mongolia. Self-reported mental health was used as a health outcome variable. Socioeconomic status was measured by household income. We employed the Wagstaff's concentration index to assess the degree of socioeconomic inequality in mental health. Results The results show that the prevalence of self-reported mental health was 1.17% among the respondents. The adults living in urban areas suffer significantly more with mental illness compared to the adults living in rural settlements. The Wagstaff's concentration index for mental health was significantly negative (-0.243), indicating that mental health problems were concentrated among the lower-income groups. The decomposition results show that education, economic activity status and marital status were the main contributors to socioeconomic inequalities in mental health after removing age-sex related contributions. Conclusions Socioeconomic inequality in mental health exists in the adult population in Mongolia, which was mainly explained by the education level, employment and marital status. Prospective policies are needed to reduce socioeconomic inequality in mental health in the country. Key messages Socioeconomic inequality in mental health exists in Mongolia. It calls for further policy actions.
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Shifti, Desalegn Markos, Catherine Chojenta, Elizabeth G. Holliday, and Deborah Loxton. "Socioeconomic inequality in short birth interval in Ethiopia: a decomposition analysis." BMC Public Health 20, no. 1 (October 6, 2020). http://dx.doi.org/10.1186/s12889-020-09537-0.
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Abstract Background Short birth interval, defined as a birth-to-birth interval less than 33 months, is associated with adverse maternal and child outcomes. Evidence regarding the association of maternal socioeconomic status and short birth interval is inconclusive. Factors contributing to the socioeconomic inequality of short birth interval have also not been investigated. The current study assessed socioeconomic inequality in short birth interval and its contributing factors in Ethiopia. Methods Data from 8448 women collected in the 2016 Ethiopia Demographic and Health survey were included in the study. Socioeconomic inequality in short birth interval was the outcome variable. Erreygers normalized concentration index (ECI) and concentration curves were used to measure and illustrate socioeconomic-related inequality in short birth interval, respectively. Decomposition analysis was performed to identify factors explaining the socioeconomic-related inequality in short birth interval. Results The Erreygers normalized concentration index for short birth interval was − 0.0478 (SE = 0.0062) and differed significantly from zero (P < 0.0001); indicating that short birth interval was more concentrated among the poor. Decomposition analysis indicated that wealth quintiles (74.2%), administrative regions (26.4%), and not listening to the radio (5.6%) were the major contributors to the pro-poor socioeconomic inequalities in short birth interval. Conclusion There was a pro-poor inequality of short birth interval in Ethiopia. Strengthening the implementation of poverty alleviation programs may improve the population’s socioeconomic status and reduce the associated inequality in short birth interval.
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Alamneh, Tesfa Sewunet, Achamyeleh Birhanu Teshale, Yigizie Yeshaw, Adugnaw Zeleke Alem, Hiwotie Getaneh Ayalew, Alemneh Mekuriaw Liyew, Zemenu Tadesse Tessema, Getayeneh Antehunegn Tesema, and Misganaw Gebrie Worku. "Socioeconomic inequality in barriers for accessing health care among married reproductive aged women in sub-Saharan African countries: a decomposition analysis." BMC Women's Health 22, no. 1 (April 25, 2022). http://dx.doi.org/10.1186/s12905-022-01716-y.
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Abstract Background Accessibility of health care is an essential for promoting healthy life, preventing diseases and deaths, and enhancing health equity for all. Barriers in accessing health care among reproductive-age women creates the first and the third delay for maternal mortality and leads to the occurrence of preventable complications related to pregnancy and childbirth. Studies revealed that barriers for accessing health care are concentrated among individuals with poor socioeconomic status which creates health inequality despite many international organizations top priority is enhancing universal health coverage. Therefore, this study aimed to assess the presence of socioeconomic inequality in barriers for accessing health care and its contributors in Sub-Saharan African countries. Methods The most recent DHS data of 33 sub-Saharan African countries from 2010 to 2020 were used. A total sample of 278,501 married reproductive aged were included in the study. Erreygers normalized concentration index (ECI) and its concentration curve were used while assessing the socioeconomic-related inequality in barriers for accessing health care. A decomposition analysis was performed to identify factors contributing for the socioeconomic-related inequality. Results The weighted Erreygers normalized Concentration Index (ECI) for barriers in accessing health care was − 0.289 with Standard error = 0.005 (P value < 0.0001); indicating that barriers in accessing health care was disproportionately concentrated among the poor. The decomposition analysis revealed that wealth index (42.58%), place of residency (36.42%), husband educational level (5.98%), women educational level (6.34%), and mass media exposure (3.07%) were the major contributors for the pro-poor socioeconomic inequalities in barriers for accessing health care. Conclusion In this study, there is a pro-poor inequality in barriers for accessing health care. There is a need to intensify programs that improve wealth status, education level of the population, and mass media coverage to tackle the barriers for accessing health care among the poor.
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Alamneh, Tesfa Sewunet, Achamyeleh Birhanu Teshale, Yigizie Yeshaw, Adugnaw Zeleke Alem, Hiwotie Getaneh Ayalew, Alemneh Mekuriaw Liyew, Zemenu Tadesse Tessema, Getayeneh Antehunegn Tesema, and Misganaw Gebrie Worku. "Socioeconomic inequality in barriers for accessing health care among married reproductive aged women in sub-Saharan African countries: a decomposition analysis." BMC Women's Health 22, no. 1 (April 25, 2022). http://dx.doi.org/10.1186/s12905-022-01716-y.
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Abstract Background Accessibility of health care is an essential for promoting healthy life, preventing diseases and deaths, and enhancing health equity for all. Barriers in accessing health care among reproductive-age women creates the first and the third delay for maternal mortality and leads to the occurrence of preventable complications related to pregnancy and childbirth. Studies revealed that barriers for accessing health care are concentrated among individuals with poor socioeconomic status which creates health inequality despite many international organizations top priority is enhancing universal health coverage. Therefore, this study aimed to assess the presence of socioeconomic inequality in barriers for accessing health care and its contributors in Sub-Saharan African countries. Methods The most recent DHS data of 33 sub-Saharan African countries from 2010 to 2020 were used. A total sample of 278,501 married reproductive aged were included in the study. Erreygers normalized concentration index (ECI) and its concentration curve were used while assessing the socioeconomic-related inequality in barriers for accessing health care. A decomposition analysis was performed to identify factors contributing for the socioeconomic-related inequality. Results The weighted Erreygers normalized Concentration Index (ECI) for barriers in accessing health care was − 0.289 with Standard error = 0.005 (P value < 0.0001); indicating that barriers in accessing health care was disproportionately concentrated among the poor. The decomposition analysis revealed that wealth index (42.58%), place of residency (36.42%), husband educational level (5.98%), women educational level (6.34%), and mass media exposure (3.07%) were the major contributors for the pro-poor socioeconomic inequalities in barriers for accessing health care. Conclusion In this study, there is a pro-poor inequality in barriers for accessing health care. There is a need to intensify programs that improve wealth status, education level of the population, and mass media coverage to tackle the barriers for accessing health care among the poor.
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Zubair, Muhammad, Lubna Naz, and Shyamkumar Sriram. "Decomposing socioeconomic inequality in household out of pocket health expenditures in Pakistan (2010-11–2018-19)." BMC Health Services Research 24, no. 1 (July 24, 2024). http://dx.doi.org/10.1186/s12913-024-11203-9.
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Abstract Background The increased socioeconomic inequality in catastrophic health expenditure (CHE) disproportionately affects disadvantaged populations, subjecting them to financial hardships, limiting their access to healthcare, and exacerbating their vulnerability to morbidity. Objectives This study examines changes in socioeconomic inequality related to CHE and analyzes the contributing factors responsible for these changes in Pakistan between 2010-11 and 2018-19. Methods This paper extracted the data on out-of-pocket health expenditures from the National Health Accounts for 2009-10 and 2017-18. Sociodemographic information was gathered from the Household Integrated Economic Surveys of 2010-11 and 2018-19. CHE was calculated using budget share and the ability-to-pay approaches. To assess socioeconomic inequality in CHE in 2010-11 and 2018-19, both generalized and standard concentration indices were used, and Wagstaff inequality decomposition analysis was employed to explore the causes of socioeconomic inequality in each year. Further, an Oaxaca-type decomposition was applied to assess changes in socioeconomic inequality in CHE over time. Results The concentration index reveals that socioeconomic inequality in CHE decreased in 2018-19 compared to 2010-11 in Pakistan. Despite the reduction in inequality, CHE was concentrated among the poor in Pakistan in 2010-11 and 2018-19. The inequality decomposition analysis revealed that wealth status was the main cause of inequality in CHE over time. The upper wealth quantiles indicated a positive contribution, whereas lower quantiles showed a negative contribution to inequality in CHE. Furthermore, urban residence contributed to pro-rich inequality, whereas employed household heads, private healthcare provider, and inpatient healthcare utilization contributed to pro-poor inequality. A noticeable decline in socioeconomic inequality in CHE was observed between 2010 and 2018. However, inequality remained predominantly concentrated among the lower socio-economic strata. Conclusion These results underscore the need to improve the outreach of subsidized healthcare and expand social safety nets.