What explains gender inequality in HIV infection among high-risk people? A Blinder-Oaxaca decomposition

Background Despite clear evidence on role of gender in vulnerability and exposure to HIV infection, information on gender-related inequalities in HIV and related factors are rarely documented. The aim of this study was to measure gender inequality in HIV infection and its determinates in Tehran city, the capital of Iran. Methods The study used the data of 20,156 medical records of high-risk people who were admitted to Imam Khomeini Voluntary Counseling and Testing site in Tehran from 2004 to 2018. The Blinder-Oaxaca decomposition was used to quantify the contribution of explanatory variables to the gap in the prevalence of HIV infection between female and male. Results The age-adjusted proportion of HIV infection was 9.45% (95%Cl: 9.02, 9.87). The absolute gap in the prevalence of HIV infection between male and female was 4.50% (95% CI: − 5.33, − 3.70%). The Blinder-Oaxaca decomposition indicated that most explanatory factors affecting the differences in HIV infection were job exposure, drug abuse, history of imprisonment, injection drug, heterosexual unsafe sex, and having an HIV-positive spouse. Conclusion The results can provide evidence for health policymakers to better planning and conducting gender-based preventive and screening programs. Policies aiming at promoting HIV preventive behaviors among male may reduce the gap in HIV infection between female and male in Iran.

A detailed explanation and graphical representation of the Blinder-Oaxaca decomposition method with its application in health inequalities

This paper introduces the Blinder-Oaxaca decomposition method to be applied in explaining inequality in health outcome across any two groups. In order to understand every aspect of the inequality, multiple regression model can be used in a way to decompose the inequality into contributing factors. The method can therefore be indicated to what extent of the difference in mean predicted outcome between two groups is due to differences in the levels of observable characteristics (acceptable and fair). Assuming the identical characteristics in the two groups, the remaining inequality can be due to differential effects of the characteristics, maybe discrimination, and unobserved factors that not included in the model. Thus, using the decomposition methods can identify the contribution of each particular factor in moderating the current inequality. Accordingly, more detailed information can be provided for policy-makers, especially concerning modifiable factors. The method is theoretically described in detail and schematically presented. In the following, some criticisms of the model are reviewed, and several statistical commands are represented for performing the method, as well. Furthermore, the application of it in the health inequality with an applied example is presented.

The innovation gender gap in transition countries

This paper investigates the sources of the possible gender ownership gap in innovativeness in a set of Transition economies by means of firm-level data coming from the Business Environment and Enterprise Performance Survey (BEEPS V) conducted in 2012–2014. Through the Blinder-Oaxaca decomposition we highlight the factors explaining the differences in the propensity to innovate between female-owned and male-owned firms. We find that the innovation disparity between firms with females among their owners and those having only male owners is mainly due to the differences in endowment effects. Tangible and intangible assets affect the innovation gap between the two groups of firms.

Urban-rural disparities in institutional delivery among women in East Africa: A decomposition analysis

Background Though institutional delivery plays a significant role in maternal and child health, there is substantial evidence that the majority of rural women have lower health facility delivery than urban women. So, identifying the drivers of these disparities will help policy-makers and programmers with the reduction of maternal and child death. Methods The study used the data on a nationwide representative sample from the most recent rounds of the Demographic and Health Survey (DHS) of four East African countries. A Blinder-Oaxaca decomposition analysis and its extensions was conducted to see the urban-rural differences in institutional delivery into two components: one that is explained by residence difference in the level of the determinants (covariate effects), and the other components was explained by differences in the effect of the covariates on the outcome (coefficient effects). Results The findings showed that institutional delivery rates were 21.00% in Ethiopia, 62.61% in Kenya, 65.29% in Tanzania and 74.64% in Uganda. The urban-rural difference in institutional delivery was higher in the case of Ethiopia (61%), Kenya (32%) and Tanzania (30.3%), while the gap was relatively lower in the case of Uganda (19.2%). Findings of the Blinder-Oaxaca decomposition and its extension showed that the covariate effect was dominant in all study countries. The results were robust to the different decomposition weighting schemes. The frequency of antenatal care, wealth and parity inequality between urban and rural households explains most of the institutional delivery gap. Conclusions The urban-rural institutional delivery disparities were high in study countries. By identifying the underlying factors behind the urban-rural institutional birth disparities, the findings of this study help in designing effective intervention measures targeted at reducing residential inequalities and improving population health outcomes. Future interventions to encourage institutional deliveries to rural women of these countries should therefore emphasize increasing rural women’s income, access to health care facilities to increase the frequency of antenatal care utilization.

Socioeconomic inequality in prevalence of cigarette and Water-pipe smoking among Iranian adults: A blinder- Oaxaca decomposition Analysis

Background: To assess the association between socioeconomic inequality and the prevalence of tobacco smoking among Iranian adults in 2010. Methods: Data from the fifth national STEPS survey (WHO STEPwise approach to NCD Surveillance) were analyzed. A Blinder-Oaxaca decomposition method was applied to assess the association between socioeconomic inequality and the prevalence of daily cigarette and water pipe (WP) smoking among Iranian men and women. Results: From 10,615 participants in the survey, 4,203 (39.5%) participants appeared to be in the first and fifth quintiles of socioeconomic status (SES). For men, the prevalence of daily cigarette smoking was higher among those with low SES (23.1%) than those with high SES (11.1%) (P<0.001). The observed difference was mainly attributed to the educational level (8.6%). We found no significant difference in high compared to low SES women for cigarette smoking (P value= 0.881). Although there was no difference between high and low SES men for daily WP smoking, low SES women had a higher prevalence of WP smoking (4.4%) than high SES women (1.3%) (P value=0.027). Education level was the major factor (3.3%) to explain the corresponding difference. The difference in WP smoking in high and low SES men was not statistically significant (P value= 0.199). Conclusion: Cigarette smoking in men and WP smoking in women are associated with SES in Iran. Education was the main factor explaining the differences in the prevalence of cigarette and WP smoking in Iranian men and women. Results from this study must be considered as a pivotal basis for designing a tobacco control program at national and sub-national levels.

Black Lives Matter: A Decomposition of Racial Inequalities in Oral Cancer Screening

(1) Background: The Black Lives Matter movement has highlighted the discrepancies in public health in regard to race. This study aims to investigate tools that can be used to analyze and investigate this discrepancy, which can be applied to policymaking. (2) Methods: National Health and Nutrition Examination Survey (NHANES) data from 2011–2018 was combined (N = 22,617) to investigate discrepancies of oral cancer screening in Black Americans. We give examples of counterfactual techniques that can be used to guide policy. Inverse probability treatment weighting (IPTW) was used to remove all measured confounding in an interaction analysis to assess the combined effect of socioeconomic status and race. Blinder–Oaxaca decomposition was then used to investigate the intervenable factors associated with differences in race. (3) Results: Sub-additive interaction was found on additive and multiplicative scales when all measured confounding was removed via IPTW (relative excess risk due to interaction (RERI)(OR) = −0.55 (−0.67–−0.42)). Decomposition analysis found that 32% of the discrepancy could be explained by characteristics of higher education and poverty status. (4) Conclusions: Black Americans in poverty are less likely to seek oral cancer screening than the additive likelihood would suggest. Blinder–Oaxaca decomposition is a strong tool to use for guiding policy as it quantifies clear breakdowns of what intervenable factors there are that would improve the discrepancy the most.

Determinants of financial performance of listed firms manufacturing food products in Vietnam: regression analysis and Blinder–Oaxaca decomposition analysis

PurposeThis article studies the impact of micro and macro factors on firm performance in the context of an emerging economy just changed from a subsidized economy to a market economy.Design/methodology/approachThe authors carried out an investigation into 30 listed food processing companies in Vietnam from 2014 to 2019. The data are analyzed by using STATA software. In this study, beside the regression analytical technique, the Blinder–Oaxaca decomposition analysis is used to study more deeply the effect of variables on financial performance of food processing companies, so its results are reliable base to give suggestions.FindingsThe results of empirical research help us to have some following conclusion. First, two variables consisting of total assets turnover ratio (ATR) and growth in sales significantly influence financial performance, when it is measured by return on equity (ROE) or return on sales (ROS). Second, leverage significantly negatively impacts return on sale. Third, there are difference in financial performance and the effect of predictors on dependent variable “ROS” between state-owned enterprises (SOEs) and non SOEs, and the causes come from the component effect.Originality/valueIn fact, although a range of previous researches on that topic have been carried out, none of them dig deeper reasons resulting to the differences in financial performance between SOEs and non SOEs, whereas Vietnamese economy has just changed to a market economy since 1986, making impacts of State ownership totally different from other countries. In this study, the authors use the t-test and analysis to have more accurate conclusions about that problem.