Explaining mental health inequalities in Northern Sweden: a decomposition analysis

Abstract

Background: There has been a substantial increase of income inequalities in Sweden over the last 20 years, which also could be reflected in health inequalities, including mental health inequalities. Despite the growing body of literature focusing on health inequalities in Sweden, income-related inequalities in mental health have received little attention. Particularly scarce are research from Northern Sweden and examinations of the social determinants of health inequalities.Objectives: The present study seeks to provide evidence regarding inequalities in mental health in Northern Sweden. The specific aims were to (1) quantify the income-related inequality in mental health in Northern Sweden, and (2) determine the contribution of social determinants to the inequality.Methods: The study population comprised 25,646 participants of the 2014 Health on Equal Terms survey in the four northernmost counties of Sweden, aged 16 to 84 years old. Income-related inequalities in mental health were quantified by the concentration index and further decomposed by applying Wagstaff-type decomposition analysis.Results: The overall concentration index of mental health in Northern Sweden was−0.15 (95% CI: −0.17 to −0.13), indicating income inequalities in mental health disfavoring the less affluent population. The decomposition analysis results revealed that socio-economic conditions, including employment status (31%), income (22.6%), and cash margin (14%), made the largest contribution to the pro-rich inequalities in mental health. The second-largest contribution came from demographic factors, mainly age (11.3%) and gender (6%). Psychosocial factors were of smaller importance, with perceived discrimination (8%) and emotional support (3.4%) making moderate contributions to the health inequalities. Conclusions: The present study demonstrates substantial income-related mental health inequalities in Northern Sweden, and provides insights into their underpinnings. These findings suggest that addressing the root causes is essential for promoting mental health equity in this region.

Decomposing socioeconomic inequality in poor mental health among Iranian adult population: results from the PERSIAN cohort study

“…Except for the Mazandaran site, the E for all sites had negative sign, suggesting a higher concentration of poor mental health in socioeconomically disadvantaged people. This is in line with the previous reports around the world [24][25][26]. However, the different methods employed for inequality measurement in various studies made the comparison of the concentration indices difficult.…”

“…A study conducted by Morasae et al (2012) in Tehran, demonstrated a contribution of 13.1% for age to socioeconomic inequality in mental health in Tehran, Iran [26]. In contrast with a study by Amroussia et al [24], marital status had a small contribution to socioeconomic inequalities in poor mental health in Iran. Married people (compared to single, divorced and widowed) were found to have more contribution to socioeconomic inequality in poor mental health.…”

Modifiable Factors Explain Socioeconomic Inequalities in Children’s Dental Caries

“…The strengths of this study include a large representative sample of Australian children, the use of comprehensive questionnaires to collect the social data, the adequate examiner reliability measures for caries measures, the use of sophisticated socioeconomic inequalities measures, and the undertaking of a multilevel analysis taking individual and contextual socioeconomic factors into account as recommended (Singh et al 2018). In addition to that, we performed decomposition analyses, which are rarely found in dental literature but increasingly used in public health (Lauridsen et al 2006;Sözmen et al 2012;Amroussia et al 2017). The main limitation of the study was the cross-sectional design.…”

Decomposing gender inequalities in self-assessed health status in Liberia

“…Second, we use the SAH, a multidimensional and more encompassing measure of health [3,5]. Third, with the exception of [22][23][24] most of the empirical studies have not measured the degree to which the covariates contribute to disparities. While gender differences in the distribution of health risk factors might contribute to gender inequalities in health status, it is also possible that these characteristics have differential effects on health risk for men and women.…”

“…In this study, we used an extension of the Oaxaca-Blinder decomposition for non-linear models to investigate the relative contributions of variations in the distributions of health status versus their differential effects in producing gender inequalities in health status in Liberia [27,28]. Again, the recent few studies that have analysed the contribution of covariates to the health inequalities are mostly concentrated in developed countries [22,23] and little is known in developing countries [24]. This knowledge is crucial for designing more effective health policies and programmes in developing countries.…”