A Comparison of the Nutritional Outcomes of the Children of Labour Migrants and the Children of Non-Migrants, Based on Height-for-Age Measurements in Kenya

Background and AimHealth is viewed as a form of human capital and a necessary basis for people to realize capabilities. Moreover, socioeconomic inequality in health outcome widens income inequality and exacerbates social inequality. The aim of this study is to measure socioeconomic inequality in health outcomes among the elderly in China.MethodsThe data used in this study were sourced from China Health and Retirement Longitudinal Study in 2015, including 5643 participants aged 60 and above. Concentration curve and concentration index were applied to measure the extent of socioeconomic inequality in health outcomes among older adults. Furthermore, the decomposition method of concentration index proposed by Wagstaff was employed to quantify each determinant’s contribution to the measured socioeconomic inequality in health outcomes.ResultsThe concentration index of Activity of Daily Living Scale and Center of Epidemiological Survey-Depression Scale score were −0.0064 and −0.0158, respectively, indicating pro-rich inequality in physical and mental health among the elderly. The decomposition analysis revealed that household income (41.15%), aged 70–79 (17.37%), being male (8.38%), and living in urban area (5.78%) were key factors to explain the pro-rich inequality in physical health. Furthermore, the results also suggested that household income (68.41%), being male (17.55%), having junior high school education (10.67%), and living in urban area (6.49%) were key factors to explain the pro-rich inequality in mental health.ConclusionThis study revealed that there are pro-rich inequalities in physical and mental health among the elderly in China, and the degree of pro-rich inequality in mental health is higher than that in physical health. Moreover, the results also suggested that household income is the biggest contributor to socioeconomic inequality in physical and mental health. Furthermore, this study found that educational attainment makes a substantial contribution to socioeconomic inequality in health outcomes, while the contribution of health insurance to health inequality is limited.

BackgroundMental health is of special importance regarding socioeconomic inequalities in health. On the one hand, mental health status mediates the relationship between economic inequality and health; on the other hand, mental health as an "end state" is affected by social factors and socioeconomic inequality. In spite of this, in examining socioeconomic inequalities in health, mental health has attracted less attention than physical health. As a first attempt in Iran, the objectives of this paper were to measure socioeconomic inequality in mental health, and then to untangle and quantify the contributions of potential determinants of mental health to the measured socioeconomic inequality.MethodsIn a cross-sectional observational study, mental health data were taken from an Urban Health Equity Assessment and Response Tool (Urban HEART) survey, conducted on 22 300 Tehran households in 2007 and covering people aged 15 and above. Principal component analysis was used to measure the economic status of households. As a measure of socioeconomic inequality, a concentration index of mental health was applied and decomposed into its determinants.ResultsThe overall concentration index of mental health in Tehran was -0.0673 (95% CI = -0.070 - -0.057). Decomposition of the concentration index revealed that economic status made the largest contribution (44.7%) to socioeconomic inequality in mental health. Educational status (13.4%), age group (13.1%), district of residence (12.5%) and employment status (6.5%) also proved further important contributors to the inequality.ConclusionsSocioeconomic inequalities exist in mental health status in Iran's capital, Tehran. Since the root of this avoidable inequality is in sectors outside the health system, a holistic mental health policy approach which includes social and economic determinants should be adopted to redress the inequitable distribution of mental health.

BackgroundInterest in applying a complex systems approach to understanding socioeconomic inequalities in health is growing, but an overview of existing research on this topic is lacking. In this systematic scoping review, we summarize the current state of the literature, identify shared drivers of multiple health and health behavior outcomes, and highlight areas ripe for future research.MethodsSCOPUS, Web of Science, and PubMed databases were searched in April 2023 for peer-reviewed, English-language studies in high-income OECD countries containing a conceptual systems model or simulation model of socioeconomic inequalities in health or health behavior in the adult general population. Two independent reviewers screened abstracts and full texts. Data on study aim, type of model, all model elements, and all relationships were extracted. Model elements were categorized based on the Commission on Social Determinants of Health framework, and relationships between grouped elements were visualized in a summary conceptual systems map.ResultsA total of 42 publications were included; 18 only contained a simulation model, 20 only contained a conceptual model, and 4 contained both types of models. General health outcomes (e.g., health status, well-being) were modeled more often than specific outcomes like obesity. Dietary behavior and physical activity were by far the most commonly modeled health behaviors. Intermediary determinants of health (e.g., material circumstances, social cohesion) were included in nearly all models, whereas structural determinants (e.g., policies, societal values) were included in about a third of models. Using the summary conceptual systems map, we identified 15 shared drivers of socioeconomic inequalities in multiple health and health behavior outcomes.ConclusionsThe interconnectedness of socioeconomic position, multiple health and health behavior outcomes, and determinants of socioeconomic inequalities in health is clear from this review. Factors central to the complex system as it is currently understood in the literature (e.g., financial strain) may be both efficient and effective policy levers, and factors less well represented in the literature (e.g., sleep, structural determinants) may warrant more research. Our systematic, comprehensive synthesis of the literature may serve as a basis for, among other things, a complex systems framework for socioeconomic inequalities in health.

Socio-economic inequalities in health may change over time, and monitoring such change is relevant to inform adequate policy responses. We aimed to quantify socio-economic inequalities in health among people with direct, indirect and without migration background in Germany and to assess temporal trends and changes between 1995 and 2017. Using nationally representative survey data from the Socio-Economic Panel (SOEP), we quantified absolute and relative socio-economic inequalities in self-reported general health by calculating the slope (SII) and relative index of inequality (RII) with 95% confidence intervals (CI) among each group and year (1995–2017) in a repeated cross-sectional design. Temporal trends were assessed using a GLM regression over the SII and RII, respectively. The total sample size comprised 492,489 observations, including 108,842 (22.23%) among people with migration background. About 31% of the population with and 15% of the population without migration background had a low socio-economic status. Socio-economic inequalities in health persisted in the group with migration background (1995 to 2017), while inequalities in the non-migrant population increased (SII: = 0.04, p < 0.01) and were on a higher level. The highest socio-economic inequalities in health were found among those with direct migration background ( = −0.23, p< 0.01; = −0.33, p < 0.01). The results show that the magnitude and temporal dynamics of inequalities differ among populations with direct, indirect and without migration background. Monitoring systems can capture and investigate these inequalities if migrant populations are adequately integrated into the respective systems.

Neighbourhood greenspace quantity, quality and socioeconomic inequalities in mental health

BackgroundMaterial, psychosocial and behavioural factors are important explanatory pathways for socioeconomic inequalities in health. The aim of this systematic review was to summarise the available evidence on empirical studies and...

Background Sugar-Sweetened Beverages (SSBs) taxes have been implemented in several countries, however, little is known on how an SSBs tax may impact on low and high socioeconomic groups differently. Therefore, the aim of this study was to gain insight into the perceptions of different stakeholder groups in the Netherlands on (1) the contribution of an SSBs tax to socioeconomic inequalities in diet and health and (2) the mechanisms via which an SSBs tax may influence these inequalities. Methods Semi-structured interviews were held in the Netherlands in March-May 2019 with 27 participants from the following stakeholder groups: health and consumer organisations, health professional associations, advisory bodies, scientists, trade organisations, policy makers, and politicians. Interview transcripts were analysed following a thematic content approach. Results Participants from all stakeholder groups indicated that an SSBs tax would have a larger impact on the budget and SSB consumption of lower socioeconomic groups. With that, an SSBs tax could have larger health benefits among lower socioeconomic groups as a result of cutting down on SSBs. A few participants - from science and a health professional association - discussed possible unwanted effects of an SSBs tax (e.g. lower socioeconomic groups may compensate their lower SSB consumption with other unhealthy behaviour). Some participants emphasised that an SSB tax should only be introduced when accompanied by other measures (e.g. educational efforts, offering healthy alternatives). Conclusions Our results imply that most stakeholders agree that an SSBs tax could contribute to a reduction of socioeconomic inequalities in diet and health. However, in order to be effective and to prevent that an SSBs tax leads to a widening of inequalities, it is important to carefully monitor behavioural changes of socioeconomic groups in response to an SSBs tax, and to implement an SSBs tax as part of a comprehensive policy approach. Key messages An SSBs tax could contribute to a reduction of socioeconomic inequalities in health, according to Dutch stakeholders. It is important to carefully monitor behavioural changes of socioeconomic groups in response to an SSBs tax, and to implement an SSBs tax as part of a comprehensive policy approach.

Socioeconomic inequality in health in older adults in Brazil.

An evolution of socioeconomic inequalities in self-rated health in Korea: Evidence from Korea National Health and Nutrition Examination Survey (KNHANES) 1998–2018

Changes over time in inequalities in self-reported health are studied for increasingly more countries, but a comprehensive overview encompassing several countries is still lacking. The general aim of this article is to determine whether inequalities in self-assessed health in 10 European countries showed a general tendency either to increase or to decrease between the 1980s and the 1990s and whether trends varied among countries. Data were obtained from nationally representative interview surveys held in Finland, Sweden, Norway, Denmark, England, The Netherlands, West Germany, Austria, Italy, and Spain. The proportion of respondents with self-assessed health less than 'good' was measured in relation to educational level and income level. Inequalities were measured by means of age-standardized prevalence rates and odds ratios (ORs). Socioeconomic inequalities in self-assessed health showed a high degree of stability in European countries. For all countries together, the ORs comparing low with high educational levels remained stable for men (2.61 in the 1980s and 2.54 in the 1990s) but increased slightly for women (from 2.48 to 2.70). The ORs comparing extreme income quintiles increased from 3.13 to 3.37 for men and from 2.43 to 2.86 for women. Increases could be demonstrated most clearly for Italian and Spanish men and women, and for Dutch women, whereas inequalities in health in the Nordic countries showed no tendency to increase. The results underscore the persistent nature of socioeconomic inequalities in health in modern societies. The relatively favourable trends in the Nordic countries suggest that these countries' welfare states were able to buffer many of the adverse effects of economic crises on the health of disadvantaged groups.

Socioeconomic inequalities in ageing and health

Socioeconomic inequalities in self-assessed health and mental health in Barcelona, 2001-2016

The present study aimed to assess socioeconomic inequalities in general and mental health, depression and substance use disorders (daily tobacco use, hazardous alcohol use). Data from the 2010 SIRS (French acronym for Health, Inequalities, and Social Ruptures) study, which is deemed to be representative of the French-speaking adult population living in the Paris Metropolitan Area, were analysed. Different socioeconomic position indicators were selected: education, income and perceived financial status. Absolute measures (the slope index of inequality (SII)) and relative measures (the odds ratio (OR) and relative index of inequality (RII)) of health inequalities were used. The OR, RII and SII were adjusted for age, household type and migration characteristics and all analyses were performed separately for men and women. The study included 3,006 adults. The results showed significant relative and absolute socioeconomic inequalities in general, mental health and depression for all socioeconomic position indicators considered (education, income, and perceived financial status). The absolute inequalities were greater for women than for men. Strongest inequalities were observed by perceived financial status for men and women. Education seemed to play a stronger role in inequalities for women, whereas, for men, income seemed to play a stronger role. Only few socioeconomic inequalities were found in daily tobacco use, while a reversed gradient was observed for hazardous alcohol use. We hope that these results will be regularly re-evaluated and compared across time in order to monitor socioeconomic inequalities in health.

Adult health inequalities are a persistent public health problem. Explanations are usually sought in behaviours and environments in adulthood, despite evidence on the importance of early life conditions for life...

A low socioeconomic position (SEP) adversely affects health outcomes and is associated with a lower perceived importance of health. It has been suggested that people with a low SEP disproportionately face daily hassles, as a result of which health may be perceived as less important for those with a low SEP compared to those with a high SEP. A lower perceived importance of health likely influences health-related behaviours that affect health outcomes. This study examines whether socioeconomic inequalities in self-assessed health are mediated by daily hassles and/or the perceived importance of health, and whether there is sequential mediation of daily hassles and perceived importance of health. A cross-sectional survey was conducted in 2019 among N = 1,334 Dutch adults. Participants rated the extent of eleven commonly experienced daily hassles (e.g., financial hassles, legal issues), and indicated the perceived importance of two health-related domains (not being ill, living a long life). Inequalities in self-assessed health according to SEP (indicated by income and education) were examined using structural equation modelling, with daily hassles and perceived importance of not being ill or living long a life either as single or sequential mediators. Daily hassles and perceived importance of health individually mediated the relationship between SEP and self-assessed health, but importance of health did not mediate the association between by daily hassles self-assessed health. Socioeconomic inequalities in self-assessed health were explained by the experience of daily hassles, and by differences in the perceived importance of health individually, but the perceived importance of health did not explain the influence of the experience of daily hassles. Addressing the challenging circumstances (e.g., financial or housing hassles) associated with a low SEP, may contribute to improving self-assessed health. Further research should examine how daily hassles affect health. Key messages Daily hassles and the perceived importance of health mediated the relationship between socioeconomic position and health. There was no association between daily hassles and the perceived importance of health.