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Social determinants of the Latinx diabetes health disparity: A Oaxaca-Blinder decomposition analysis.

ABSTRACT: Latinx people living in the U.S. report a disproportionately high prevalence of diabetes. This project builds on the existing social determinants of diabetes literature by examining factors associated with a greater likelihood of diabetes and investigates factors correlated with the Latinx/non-Latinx disparity. This project studies the adult sample (18 and older) from the 2010-2018 IPUMS Health: National Health Interview Survey (NHIS) data. Logistic regression analyses are used to examine the patterns between reporting Latinx identity and reporting diabetes with additional subgroup analyses of the Latinx and non-Latinx groups. Then, Oaxaca-Blinder decomposition is used to examine the patterns explaining the difference in self-reported diabetes between the Latinx and non-Latinx population for the whole sample and by age group. The logistic regression analyses show that after adjusting for age and other key social determinants of health, Latinx individuals are approximately 64.5% (OR 1.645, [95% CI, 1.536-1.760]) more likely to report being diagnosed with diabetes than non-Latinx individuals. Individual characteristics of age, race, and smoking behaviors are identified as suppressors of the gap, and conversely, characteristics of income, education, and BMI all contribute to the Latinx diabetes disparity gap. The Oaxaca-Blinder decomposition results show that the measured social determinants of health characteristics explain a meaningful amount of the Latinx diabetes gap. Importantly, differences in education and income (which are more immediately actionable policy areas) make larger contributions to the gap than BMI or other health behaviors.

SUBMITTER: Cartwright K

PROVIDER: S-EPMC8350406 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThroughout Wales and the world, health inequality remains a problem that is interconnected with a wider and complex social, economic and environmental dynamic. Subsequently, action to tackle inequality in health needs to take place at a structural level, acknowledging the constraints affecting an individual's (or community's) capability and opportunity to enable change. While the 'social determinants of health' is an established concept, fully understanding the composition of the health gap is dependent on capturing the relative contributions of a myriad of social, economic and environmental factors within a quantitative analysis.MethodThe decomposition analysis sought to explain the differences in the prevalence of these outcomes in groups stratified by their ability to save at least £10 a month, whether they were in material deprivation, and the presence of a limiting long-standing illness, disability of infirmity. Responses to over 4,200 questions within the National Survey for Wales (n = 46,189; 2016-17 to 2019-20) were considered for analysis. Variables were included based on (1) their alignment to a World Health Organization (WHO) health equity framework ("Health Equity Status Report initiative") and (2) their ability to allow for stratification of the survey sample into distinct groups where considerable gaps in health outcomes existed. A pooled Blinder-Oaxaca model was used to analyse inequalities in self-reported health (fair/poor health, low mental well-being and low life satisfaction) and were stratified by the variables relating to financial security, material deprivation and disability status.ResultsThe prevalence of fair/poor health was 75% higher in those who were financially insecure and 95% higher in those who are materially deprived. Decomposition of the outcome revealed that just under half of the health gap was "explained" i.e., 45.5% when stratifying by the respondent's ability to save and 46% when stratifying by material deprivation status. Further analysis of the explained component showed that "Social/Human Capital" and "Income Security/Social Protection" determinants accounted the most for disparities observed; it also showed that "Health Services" determinants accounted the least. These findings were consistent across the majority of scenarios modeled.ConclusionThe analysis not only quantified the significant health gaps that existed in the years leading up to the COVID-19 pandemic but it has also shown what determinants of health were most influential. Understanding the factors most closely associated with disparities in health is key in identifying policy levers to reduce health inequalities and improve the health and well-being across populations.

Project description:Objectives:The present research was conducted aiming at assessing the association of socioeconomic inequality in the prevalence of risk factors associated with cardio-metabolic disorders in a sample population of nationally representative Iranian adolescents and to identify its influencing factors. Methods:This study was conducted as part of a national-based surveillance program performed on 5625 individuals aged 10-18 years in 27 provinces in Iran. To determine the socioeconomic status (SES) of participants, we defined a new variable by applying the principal component analysis. Doing so, the socioeconomic inequality in cardio-metabolic risk factors was examined over the tertiles of SES using concentration index (C). Then, Oaxaca-Blinder decomposition analysis was carried out in order to decide upon the roots of inequality in the health system. Results:The mean (standard deviation) age of participants was 14.73 (2.41) years. The prevalence of cardio-metabolic parameters had considerable difference across SES tertiles. Elevated fasting blood glucose (FBG), elevated triglycerides (TG), abdominal obesity, elevated total cholesterol (TC), and metabolic syndrome (MetS) increased linearly by increasing SES tertiles. C index for depressed high density lipoprotein- cholesterol (HDL-C) was negative, which was suggestive of inequality in favor of high SES groups and for other cardio-metabolic parameters, it was positive, which indicate inequality was in favor of the lowest SES groups. The highest gap between the first and third tertiles of socioeconomic was for frequency of abdominal obesity; 13.18% of the lowest SES groups and 20.11% of the highest SES groups had abdominal obesity which accounts 6.93% gap in favor of the highest SES groups. The living area could be named as the main variables standing for the inequality of elevated FBS, elevated LDL-c, low HDL-c and abdominal obesity frequency between the first and the last SES group. In addition, BMI could stand as the main independent variable explaining the gap in elevated TG, elevated TC, elevated BP and MetS prevalence across the lowest and the highest SES group. Conclusions:The study revealed the considerable inequality in the prevalence of cardio-metabolic risk factors between the highest and the lowest SES groups of Iranian adolescents. Living area and BMI are the two main factors which explained inequality in prevalence of cardio metabolic risk factors between SES groups. These estimations could provide health policy markers with practical information for future complementary analyses.

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Social determinants of the Latinx diabetes health disparity: A Oaxaca-Blinder decomposition analysis.

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