Assessing Psychosocial Health Impacts of Climate Adaptation: A Critical Review.

The urgency of dealing with risks associated with climate change and the need for effective response measures to their impacts are increasing daily the world over. Literature abounds regarding the impacts of climate change on physical, psychosocial, and other health outcomes. In contrast, little research exists on the health impacts of response measures to climate change. This critical review seeks to contribute towards closing this gap through a synthesis of current literature on the psychosocial health outcomes of climate adaptation actions. Our results found both positive and negative outcomes associated with psychosocial health that may result from climate adaptation actions. We propose the utilization of well-developed conceptual frameworks and evaluation tools in assessment and analysis of these outcomes. Ultimately, there is need to expand similar and related areas of research more broadly and on psychosocial effects, specifically.

Is socioeconomic inequality in antenatal care coverage widening or reducing between- and within-socioeconomic groups? A case of 19 countries in sub-Saharan Africa.

Maternal health statistics have improved in many countries in sub-Saharan Africa (SSA). Still, progress remains slow in meeting the Sustainable Development Goals (SDG) targets. Accelerating antenatal care (ANC) coverage is critical to improving maternal health outcomes. To progress, countries should understand whether to target reducing health disparities between- or within-socioeconomic groups, as policies for achieving these may differ. This paper develops a framework for decomposing changes in socioeconomic inequalities in health into changes in between- and within-socioeconomic groups using the concentration index, a popular measure for assessing socioeconomic inequalities in health. It begins by noting the challenge in decomposing the concentration index into only between- and within-group components due to the possibility of an overlap created by overlapping distributions of socioeconomic status between groups. Using quantiles of socioeconomic status provides a convenient way to decompose the concentration index so that the overlap component disappears. In characterising the decomposition, a pro-poor shift occurs when socioeconomic inequality is reduced over time, including between- and within-socioeconomic groups, while a pro-rich shift or change occurs conversely. The framework is applied to data from two rounds of the Demographic and Health Survey of 19 countries in SSA conducted about ten years apart in each country. It assessed changes in socioeconomic inequalities in an indicator of at least four antenatal care visits (ANC4+) and the count of ANC visits (ANC intensity). The results show that many countries in SSA witnessed significant pro-poor shifts or reductions in socioeconomic inequalities in ANC coverage because pro-rich inequalities in ANC4+ and ANC intensity become less pro-rich. Changes in between-socioeconomic group inequalities drive the changes in ANC service coverage inequalities in all countries. Thus, policies addressing inequalities between-socioeconomic groups are vital to reducing overall disparities and closing the gap between the rich and the poor, a crucial objective for the SDGs.

Health indicators and poor health dynamics during COVID-19 pandemic.

It is expected that the coronavirus pandemic will exacerbate inequality in wellbeing compared to the pre-pandemic situation. However, there are theories (e.g., the Conservation of Resource (COR) theory) that acknowledge situation-specific lower wellbeing for individuals who typically have more resources. The argument is that perception of loss might occur differently across the socioeconomic spectrum such that individuals with higher socioeconomic status perceive that they experience more loss. Therefore, given the pandemic situation, it is possible that indicators of poor wellbeing (e.g., depression) becoming less concentrated among the poor, contrary to expectation. Given the above, we examine income-related inequality in self-assessed health and depressive symptoms in South Africa. This is done using both pre-pandemic data (i.e. National Income Dynamic Study) and data collected during the pandemic (National Income Dynamic Study-Coronavirus Rapid Mobile Survey). Consistent with expectation, we find that poor self-assessed health is not only disproportionately concentrated amongst the poor, but this concentration has increased compared to the pre-pandemic period. However, contrary to expectation, depressive symptoms have become less concentrated amongst the poor compared to the pre-pandemic period. We note that while there may be an alternative explanation for this change in trend, it may also be due to situation-specific lower wellbeing for individuals who typically have more resources. We argue that this has implication for tracking population health in a crisis.

Food insecurity and health outcomes during the coronavirus pandemic in South Africa: a longitudinal study.

BACKGROUND: Given that South Africa experienced significant food insecurity even before the COVID-19 pandemic, it is not surprising that the pandemic would result in even greater food insecurity in the country. This paper provides additional evidence on the relationship between food insecurity and health. METHODS: Data came from the National Income Dynamics Study-Coronavirus Rapid Mobile Survey, a longitudinal survey of adult South Africans. Health was a self-reported indicator of general health, while food insecurity was measured by household hunger, the frequency of household hunger, and households running out of money to buy food. We performed descriptive and econometric analyses. RESULTS: Food insecurity has remained high even in the face of greater re-opening of the economy. Moreover, among hunger-affected households, between a quarter and a third struggled with hunger almost daily or daily. Belonging to a hunger-affected household was associated with a 7-percentage point higher probability of worse health compared to not experiencing hunger. Compared to being unaffected by hunger, being hungry everyday was associated with a 15-percentage point higher probability of worse health in wave 1, an effect that became statistically insignificant by wave 4. CONCLUSIONS: These results show the enormity of the hunger problem in South Africa and its adverse effects on health. In the face of economic uncertainty and the removal of COVID-19 palliatives like the grant top-ups, we enjoin policy makers to protect the vulnerable from food insecurity by continuing the implementation of anti-hunger policies and other measures that enhance food security in the country.

Association Between ART Adherence and Mental Health: Results from a National HIV Sero-Behavioural Survey in South Africa.

This paper assesses the levels of antiretroviral treatment (ART) adherence and mental health distress among study participants in a national behavioural HIV-sero prevalence study South Africa. The study was a cross-sectional population-based multi-stage stratified cluster random survey, (SABSSM V, 2017). Structured questionnaires were used to collect information on socio-demographics, HIV knowledge, perceptions, HIV testing and HIV treatment history. Study participants were tested for HIV infection, antiretroviral use, viral suppression, and ART drug resistance. A total of 2155 PLHIV aged 15 years or older who were on ART were included in the study. Incidence of either moderate or severe mental health distress was 19.7%. Self-reported ART adherence among study participants with no, mild, moderate, or severe mental distress was 82%, 83%, 86% and 78%, respectively. The adjusted odds ratio for ART non-adherence was 0.58 (95% CI 0.24; 1.40) for mild mental distress, 0.82 (95% CI 0.35; 1.91) for moderate mental distress and 2.19 (95% CI 1.14; 4.19) for severe mental distress groups compared to the no mental health distress group. The other factors that were associated with ART non-adherence in adjusted models included education level, alcohol use and province/region of residence. The study revealed that mental health remains a challenge to ART adherence in South Africa. To improve ART adherence, HIV continuum of care programs should include screening for mental health among people living with HIV.

Childcare and depression during the coronavirus pandemic in South Africa: A gendered analysis.

BACKGROUND: The 2019 coronavirus disease (COVID-19) pandemic resulted in the closure of businesses and schools, the remote provision of services and the disruption of the services of professional childminders. These disruptions resulted in a significant increase in parental responsibility for childcare. Such a substantial increase in time requirements for childcare domestically has potential mental health consequences. We therefore ascertained the relationship between childcare and depression in South Africa during the pandemic. METHODS: Data came from the National Income Dynamics Study-Coronavirus Rapid Mobile Survey, a longitudinal telephonic survey conducted during the COVID-19 pandemic in South Africa. The outcome was a depression index obtained from the two-item Patient Health Questionnaire while the main covariate was the average number of hours spent in taking care of children per weekday. We employed the ordered logit model. FINDINGS: We found a positive relationship between spending more hours on childcare and worse depressive health for caregivers in both periods analyzed. Childcare responsibilities preventing/mitigating the ability of caregivers to work as well as preventing caregivers from searching for jobs moderated the depression-childcare relationship. CONCLUSION: These findings highlight the need to carefully consider policy responses aimed at containing the pandemic. We advocate a multi-stakeholder approach to mitigating the mental health impact of COVID-19 by encouraging more collaboration between government, school authorities, employers and parents/guardians.

Income-related health inequalities associated with the coronavirus pandemic in South Africa: A decomposition analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has resulted in an enormous dislocation of society especially in South Africa. The South African government has imposed a number of measures aimed at controlling the pandemic, chief being a nationwide lockdown. This has resulted in income loss for individuals and firms, with vulnerable populations (low earners, those in informal and precarious employment, etc.) more likely to be adversely affected through job losses and the resulting income loss. Income loss will likely result in reduced ability to access healthcare and a nutritious diet, thus adversely affecting health outcomes. Given the foregoing, we hypothesize that the economic dislocation caused by the coronavirus will disproportionately affect the health of the poor. METHODS: Using the fifth wave of the National Income Dynamics Study (NIDS) dataset conducted in 2017 and the first wave of the NIDS-Coronavirus Rapid Mobile Survey (NIDS-CRAM) dataset conducted in May/June 2020, this paper estimated income-related health inequalities in South Africa before and during the COVID-19 pandemic. Health was a dichotomized self-assessed health measure, with fair and poor health categorized as "poor" health, while excellent, very good and good health were categorized as "better" health. Household per capita income was used as the ranking variable. Concentration curves and indices were used to depict the income-related health inequalities. Furthermore, we decomposed the COVID-19 era income-related health inequality in order to ascertain the significant predictors of such inequality. RESULTS: The results indicate that poor health was pro-poor in the pre-COVID-19 and COVID-19 periods, with the latter six times the value of the former. Being African (relative to white), per capita household income and household experience of hunger significantly predicted income-related health inequalities in the COVID-19 era (contributing 130%, 46% and 9% respectively to the inequalities), while being in paid employment had a nontrivial but statistically insignificant contribution (13%) to health inequality. CONCLUSIONS: Given the significance and magnitude of race, hunger, income and employment in determining socioeconomic inequalities in poor health, addressing racial disparities and hunger, income inequality and unemployment will likely mitigate income-related health inequalities in South Africa during the COVID-19 pandemic.

Explaining changes in wealth inequalities in child health: The case of stunting and wasting in Nigeria.

BACKGROUND: Malnutrition is a major cause of child death, and many children suffer from acute and chronic malnutrition. Nigeria has the second-highest burden of stunting globally and a higher-than-average child wasting prevalence. Moreover, there is substantial spatial variation in the prevalence of stunting and wasting in Nigeria. This paper assessed the socioeconomic inequalities and determinants of the change in socioeconomic inequalities in child stunting and wasting in Nigeria between 2013 and 2018. METHODS: Data came from the 2013 and 2018 Nigeria Demographic and Health Survey. Socioeconomic inequalities in stunting and wasting were measured using the concentration curve and Erreygers' corrected concentration index. A pro-poor concentration index is negative, meaning that the poor bear a disproportionately higher burden of stunting or wasting than the wealthy. A positive or pro-rich index is the opposite. Standard methodologies were applied to decompose the concentration index (C) while the Oaxaca-Blinder approach was used to decompose changes in the concentration indices (ΔC). FINDINGS: The socioeconomic inequalities in child stunting and wasting were pro-poor in 2013 and 2018. The concentration indices for stunting reduced from -0.298 (2013) to -0.330 (2018) (ΔC = -0.032). However, the concentration indices for wasting increased from -0.066 to -0.048 (ΔC = 0.018). The changes in the socioeconomic inequalities in stunting and wasting varied by geopolitical zones. Significant determinants of these changes for both stunting and wasting were changes in inequalities in wealth, maternal education and religion. Under-five dependency, access to improved toilet facilities and geopolitical zone significantly explained changes in only stunting inequality, while access to improved water facilities only significantly determined the change in inequality in wasting. CONCLUSION: Addressing the socio-economic, spatial and demographic determinants of the changes in the socioeconomic inequalities in child stunting and wasting, especially wealth, maternal education and access to sanitation is critical for improving child stunting and wasting in Nigeria.

An Alternative Approach to Decomposing the Redistributive Effect of Health Financing Between and Within Groups Using the Gini Index: The Case of Out-of-Pocket Payments in Nigeria.

Equity in health financing remains significant in the universal health coverage discourse. The way a health system is financed, apart from determining whether people have access to needed health services, also has implications for income inequality in a country. Traditionally, the impact of health financing on income inequality or the redistributive effect of health financing is assessed by looking at whether income inequality reduces because of health financing. This is also decomposed into a vertical component (the extent of progressivity), a horizontal component (the extent to which households with similar incomes are treated equally when financing health services) and a reranking component (whether households change their relative socio-economic ranking after financing health services). Such an approach to decomposition is mainly essential to assess the equal treatment of equals and unequal treatment of unequals in the entire population. This paper argues that in decomposing the redistributive effect of health financing, the impact of health financing on changes in income inequality between and within population groups should be investigated as they are relevant for policy dialogues in many countries. It develops a framework for such analysis and applies this to data from Nigeria. Decomposing the Gini index of income inequality using the Shapley value approach, the results show that changes in inequality associated with out-of-pocket payments for health services within the geopolitical zones in Nigeria dominate the changes in income inequality between the geopolitical zones. Although not all the results in the application in this paper are statistically significant, this framework is still useful for policies in countries that aim to use health financing to reduce, among other things, income disparities between and within defined population groups.

Socioeconomic inequalities in maternal health service utilisation: a case of antenatal care in Nigeria using a decomposition approach.

BACKGROUND: Antenatal care (ANC) services are critical for maternal health but Nigeria performs poorly in ANC utilisation compared to other countries in sub-Saharan Africa. This study aimed to assess socioeconomic inequalities in ANC utilisation and the determinants of these inequalities in Nigeria. METHODS: The 2013 Nigeria Demographic and Health Survey data with 18,559 women was used for analysis. The paper used concentration curves and indices for different measures of ANC utilisation (no ANC visit, 1-3 ANC visits, at least four ANC visits, and the number of ANC visits). A positive (or negative) concentration index means that the measure of ANC utilisation was concentrated on the richer (poorer) population compared to their poorer (richer) counterparts. The concentration indices were also decomposed using standard methodologies to examine the significant determinants of the socioeconomic inequalities in no ANC visit, at least four ANC visits, and the number of ANC visits. RESULTS: No ANC visit was disproportionately concentrated among the poor (concentration index (CI) = - 0.573), whereas at least four ANC visits (CI = 0.582) and a higher number of ANC visits (CI = 0.357) were disproportionately concentrated among the rich. While these results were consistent across all the geopolitical zones and rural and urban areas, the inequalities were more prevalent in the northern zones (which also have the highest incidence of poverty in the country) and the rural areas. The significant contributors to inequalities in ANC utilisation were the zone of residence, wealth, women's education (especially secondary) and employment, urban-rural residence, ethnicity, spousal education, and problems with obtaining permission to seek health care and distance to the clinic. CONCLUSIONS: Addressing wealth inequalities, enhancing literacy, employment and mitigating spatial impediments to health care use will reduce socioeconomic inequalities in ANC utilisation in Nigeria. These factors are the social determinants of health inequalities. Thus, a social determinants of health approach is needed to address socioeconomic inequalities in ANC coverage in Nigeria.

Decomposition of socioeconomic inequalities in cigarette smoking: the case of Namibia.

BACKGROUND: Namibia has one of the highest levels of income inequality in the world. Increased smoking prevalence, especially among the youth, may leave the country facing the spectre of higher smoking-related disease prevalence in the years to come. This study examines socioeconomic inequalities in smoking in Namibia and explores the drivers of this inequality. METHODS: Data are obtained from the Namibia 2013 Demographic and Health Survey, a nationally representative survey. Concentration curves and indices are calculated for cigarette smoking prevalence and intensity to assess the respective inequalities. Smoking intensity is defined as the number of cigarette sticks smoked within the last 24 h before the survey. We use a decomposition technique to identify the contribution of various covariates to socioeconomic inequalities in smoking prevalence and intensity. RESULTS: The concentration indices for socioeconomic inequality in cigarette smoking prevalence and smoking intensity are estimated at 0.021 and 0.135, respectively. This suggests that cigarette smoking is more prevalent among the wealthy and that they smoke more frequently compared to less wealthy Namibians. For smoking intensity, the biggest statistically significant contributors to inequality are marital status, wealth and region dummy variables while for smoking prevalence, education and place of dwelling (urban vs rural) are the main contributors. CONCLUSION: While overall inequality in smoking prevalence and intensity is focused among the wealthy, the contribution of region of residence and education warrant some attention from policy makers. Based on our results, we suggest an assessment of compliance and enforcement of the Tobacco Products Control Act, that initially focuses on regions with reportedly low education statistics followed by an appropriate implementation strategy to address the challenges identified in implementing effective tobacco control interventions.