Dataset Information

Impact of Gender Inequalities in the Causes of Mortality on the Competitiveness of OECD Countries.

ABSTRACT: The aim of the present study is to quantify the relations between gender inequalities in mortality by selected causes of mortality and between competitiveness of Organisation for Economic Co-operation and Development (OECD) countries. Data for the analyses were obtained from OECD databases and the World Economic Forum (Global Competitiveness Index), for the years 2011-2016, for all 36 countries. The methods of descriptive analysis, analysis of differences in causes of mortality by gender characteristics, regression analysis, relationship analysis of gender inequalities in causes of mortality and competitiveness, and cluster analysis were used for the statistical data processing. Based on the research findings, it can be concluded that gender inequality occurs in most of the examined mortality groups of diagnoses, while it was most significant in the case of mortality due to neoplasms. The impacts of mortality on competitiveness are significant. In assessing gender inequalities in causes of mortality, significant impacts were seen in most mortality causes, but the most significant impact was identified within mortality due to neoplasms. Emphasis should be placed on men when reducing inequalities. Health and health equity should be supported by national governments, and health equity should be one of the key performance indicators of the country.

SUBMITTER: Gavurova B

PROVIDER: S-EPMC7277152 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Impact of Gender Inequalities in the Causes of Mortality on the Competitiveness of OECD Countries.

Gavurova Beata B Ivankova Viera V Rigelsky Martin M Suhanyi Ladislav L

International journal of environmental research and public health 20200524 10

The aim of the present study is to quantify the relations between gender inequalities in mortality by selected causes of mortality and between competitiveness of Organisation for Economic Co-operation and Development (OECD) countries. Data for the analyses were obtained from OECD databases and the World Economic Forum (Global Competitiveness Index), for the years 2011-2016, for all 36 countries. The methods of descriptive analysis, analysis of differences in causes of mortality by gender charact ...[more]

PMID: 32456300

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Project description:ObjectivesRecent studies have demonstrated worsened mental health in relatively highly developed countries impacted by social inequalities and unemployment. Here, we investigate (1) whether mental health issues are differently or similarly affected by these social factors and (2) whether their effects on mental health are related or unrelated to each other.SettingAnalysis at the country level among Organization for Economic Cooperation and Development (OECD) countries (n=36). Data on social indicators were collected from OECD and the United Nations Development Programme databases. Data on the prevalence of mental issues were obtained from the Institute for Health Metrics and Evaluation's Global Burden of Disease study 2017.ParticipantsNo involvement of participants.Primary and secondary outcome measuresUsing linear regression models, we investigated the relative contribution played by human development (as measured by the Human Development Index (HDI)), social inequalities (Gini index) and unemployment (unemployment rate) on the prevalence of 10 mental health issues. We then measured the relationship between the socioeconomic factors' effects on mental issues using 2×2 Pearson's correlation test and principal component analysis.ResultsFirst, the overall effect of each socioeconomic factor on a combination of mental health disorders was large (r range: 0.51 to 0.76; p<0.002). However, the influence of social factors on mental health was relative to each mental issue (r range: -0.34 to 0.74). Second, the socioeconomic factors' effects on mental health showed strong interdependence (rHDI-Gini=0.93, rHDI-unemploy=0.81, runemploy-Gini=0.84; p<0.001. Principal component analysis demonstrated that the first principal component of the three variables (rHDI, rGini, runemploy) explained 91.5% of the variance.ConclusionThese results implore a reanalysis of the socioeconomic determinants of mental health where (1) the heterogeneity of mental health issues would be taken into account and (2) each socioeconomic indicator's effect would be analysed and interpreted in conjunction with the others.

Project description:PurposeThe aims of this study were to (a) describe gender inequalities in physical activity (PA) among adolescents from Global South countries, and (b) investigate the relationship between gender inequalities in PA and contextual factors, such as geographic region, human development index, gender inequality index, and unemployment rates.MethodsWe analyzed cross-sectional data from the Global School-Based Student Health Survey conducted in Global South countries between 2010 and 2020 among 13- to 17-year-old adolescents. Country-context variables were retrieved from secondary data sources (World Health Organization, World Bank, and Human Development Reports). PA was assessed by a self-administered questionnaire querying the number of days in the past week in which participants were physically active for a total of at least 60 min. PA absolute gender inequalities were evaluated by the differences in the prevalence between boys and girls, 95% confidence intervals (95%CIs) were estimated using the bootstrap method. Relative inequalities were obtained through Poisson regression. Meta-analyses with random effects were used to calculate pooled estimates of absolute and relative inequalities.ResultsBased on 64 Global South countries/surveys, the prevalence of PA was 6.7 percentage points (p.p.) higher in boys than in girls, ranging from 0.5 p.p. in Afghanistan to 15.6 p.p. in Laos (I2= 85.1%). The pooled ratio for all countries showed that boys presented a PA prevalence 1.58 times higher than girls (95%CI: 1.47-1.70) on average. The highest absolute and relative inequalities were observed in high income countries. Countries with higher Human Development Index rankings and lower Gender Inequality Index rankings also presented greater gender differences.ConclusionGiven that girls are overall less active than boys across the globe, the findings of this study reinforce that macro- and micro-level changes should be actively sought if we aim to increase population levels of PA in adolescents and promote equity in PA.

Dataset Information

Impact of Gender Inequalities in the Causes of Mortality on the Competitiveness of OECD Countries.

Publications

Impact of Gender Inequalities in the Causes of Mortality on the Competitiveness of OECD Countries.

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