Heterogeneous gender gaps in mental wellbeing: Do women with low economic status face the biggest gender gaps?

Gender differences in depression are globally documented across a wide range of studies that analyse self-reports of depressive symptoms or clinical diagnoses. Extensive research fails to identify any single reason for this finding but given systematic variation in depressive symptomatology across social groups, gender differences must derive at least partly from environmental or social factors. Among the social factors that are considered most important are those relating to gender differences in socio-economic status and the underlying gender division of labor. In this study, we add to existing research by interrogating heterogeneity in gender differences in mental health. Studies that investigate environmental factors typically consider these only in relation to the average gender gap in depression. We use a novel sorting and classification method (Chernozhukov et al., 2018) that makes it possible to map the full distribution of gender differences in depressive symptomatology among comparable women and men. Although we cannot attribute causality, the method allows us to isolate those social factors that are distinctive to women who experience the largest gender gap in depressive symptoms compared to those who exhibit the smallest. The study analyses detailed nationally representative micro-data from South Africa, a country with high rates of poverty, which are higher still among women. As is common elsewhere, women report significantly more depressive symptoms than men, and low socio-economic status is correlated with poor mental health. However, women with low socio-economic status are not relatively more concentrated among women who face the largest gender gap in depressive symptomatology. These findings would not be consistent with the hypothesis that women have a greater tendency than men to ruminate over economic hardship and could rather point to resilience and a "steeling effect" among poor women.

Mental distress, COVID19 vaccine distrust and vaccine hesitancy in South Africa: A causal mediation regression analysis.

AIM: Within the context of increasing mental distress noted since the beginning of the COVID19 pandemic, the study aims at analysing the relationship between mental health, vaccine distrust and vaccine hesitancy in South Africa. SUBJECT AND METHODS: The study uses nationally representative panel data of 3241 individuals interviewed prior to and during the COVID19 pandemic. The study uses a range of regression techniques including logit, mediation and gradient-boosted causal mediation models to identify the causal relationship while accounting for selection bias. RESULTS: The results of multivariate logit regression reveal that vaccine distrust is the most important predictor of vaccine hesitancy [Coeff: 3.420, CI 3.122, 3.717]. Mental distress is not found to be a significant driver in a fully specified logit model, pointing to the need to analyse the pathways through which mental distress impacts vaccine hesitancy. The mediation regression undertaken for this purpose finds that the mental distress has a positive and significant association with vaccine distrust [Coeff: 0.027, CI: 0.0029, 0.052]. The increased vaccine distrust in turn results in increased vaccine hesitancy [Coeff: 0.661, CI: 0.611, 0.711]. The results of mediation regression therefore indicate strong and significant mediation effects, whereby mental health effects vaccine hesitancy through the mediating variable of vaccine distrust. These results are robust to the gradient boosted causal mediation model which establishes strong and significant indirect effects [Coeff: 0.015, CI: 0.01, 0.019], whereby mental health effects vaccine hesitancy through the mediating variable of vaccine distrust. CONCLUSION: The study concludes that mental health impacts on vaccine intention through the mediating role of vaccine distrust. The findings indicate that individuals at high risk of depression are more concerned regarding the safety of vaccines, which in turn feeds into vaccine hesitancy. Therefore, depressive symptoms impact on vaccine hesitancy through the mediating factor of vaccine distrust.

Does noncompliance with COVID-19 regulations impact the depressive symptoms of others?

Before vaccines became commonly available, compliance with nonpharmaceutical only preventive measures offered protection against COVID-19 infection. Compliance is therefore expected to have physical health implications for the individual and others. Moreover, in the context of the highly contagious coronavirus, perceived noncompliance can increase the subjective risk assessment of contracting the virus and, as a result, increase psychological distress. However, the implications of (public) noncompliance on the psychological health of others have not been sufficiently explored in the literature. Examining this is of utmost importance in light of the pandemic's elevated prevalence of depressive symptoms across countries. Using nationally representative data from South Africa, we explore the relationship between depressive symptoms and perceived noncompliance. We examine this relationship using a double machine learning approach while controlling for observable selection. Our result shows that the perception that neighbors are noncompliant is correlated with self-reported depressive symptoms. Therefore, in the context of a highly infectious virus, noncompliance has detrimental effects on the wellbeing of others.

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.

COVID-19 risk perceptions and depressive symptoms in South Africa: Causal evidence in a longitudinal and nationally representative sample.

BACKGROUND: Studies worldwide have highlighted the acute and long-term depressive impacts of psychosocial stressors due to the 2019 coronavirus disease (COVID-19) pandemic, particularly in low- and middle-income countries. Among the wide range of risk factors for depression that transpired during pandemic, greater perceptions of individual vulnerability to the COVID-19 have emerged as a major predictor of increased depressive risk and severity in adults. METHODS: We estimated the extent to which COVID-19 risk perceptions affected adult depressive symptoms in a longitudinal, nationally representative sample in South Africa. We used covariate balanced propensity scores to minimize the bias from treatment assignment to estimate average causal effects of COVID-19 risk perceptions. RESULTS: The point prevalence of perceived COVID-19 infection risk increased between the third and fifth months of the pandemic, which corresponded with elevations in national COVID-19 infection rates. Approximately 33% of adults met or surpassed the PHQ-2 cut-off score of 2. An increase in perceived risk of COVID-19 infection predicted worse depressive symptoms in adults four months later. CONCLUSIONS: Our findings highlight the widespread mental health burdens of the COVID-19 pandemic and emphasize the importance of greater psychological resources and structural changes to promote equitable access to COVID-19 risk mitigation policies.

Does Socioeconomic status mediate the relationship between income loss and depression scores? Evidence from South Africa.

This paper examines the role of socioeconomic status (SES) in mediating the effect of job and household income loss on mental health during the COVID-19 pandemic. We note that even though job loss will invariably reduce household income, the relationship between these factors and mental health may be mediated by SES. Specifically, in the context of COVID-19 induced shock, job loss may not be a threat to survival for an individual with relatively high SES, while this is not the case for individuals with low SES. Our empirical analysis uses threshold regression under the assumption that the relationship between depressive symptoms and pandemic induced job/ income loss has a threshold effect. We find that job loss (but not the decline in household income) is a stronger predictor of poor mental health for individuals that live in households above a certain SES threshold. This suggests that the psychological trauma of job loss due to loss of identity and purpose outweighs the financial loss for individuals with higher SES. On the other hand, a decrease in household income (as against the loss of individual income) is a stronger predictor of poor mental health for individuals with lower SES. We argue that these findings are related to high-income inequality in South Africa. The results highlight the different implications of job loss and income loss for depressive symptoms in the context of high socioeconomic inequality.

COVID19 vaccine intentions in South Africa: health communication strategy to address vaccine hesitancy.

BACKGROUND: Vaccine hesitancy is emerging as a significant challenge in many parts of the world in the fight against the COVID19 pandemic. The continued infection amongst the unvaccinated can lead to a heightened risk of further virus mutation, exposing even those vaccinated to new virus strains. Therefore, there are social benefits in minimising vaccine hesitancy. The objective of this study is to assess the level of COVID19 vaccine hesitancy in South Africa, identify the socio-economic patterns in vaccine hesitancy and highlight insights from the national survey that can inform the development of a COVID-19 vaccination acceptance communication campaign. METHODS: The study uses the nationally representative National Income Dynamics Study - Coronavirus Rapid Mobile Survey (NIDS-CRAM) survey. The analysis combines univariate and bivariate statistics, as well as multivariate regression models like binomial/ordinal and multinomial logit. RESULTS: The study finds that vaccine acceptance is lower than that of non-pharmaceutical intervention like face-mask use. Only 55% fully accept the vaccine, while a further 16% are moderately accepting of vaccines. Together, vaccine acceptance is estimated at 70.8%, and vaccine hesitancy against COVID19 is estimated at 29.2% amongst the adult South African population. The study has identified the perceived risk of infection with the mediating role of efficacy as a key predictor of vaccine intention. Higher awareness of COVID19 related information and higher household income are correlated with lower vaccine hesitancy. The non-black African population group has significantly high vaccine hesitancy compared to black Africans. CONCLUSIONS: There are other significant differences across socio-economic and demographic variables in vaccine hesitancy. From a communication perspective, it is imperative to continue risk messaging, hand in hand with clearer information on the efficacy of the vaccines.

Behavioural response to the Covid-19 pandemic in South Africa.

BACKGROUND: Given the economic and social divide that exists in South Africa, it is critical to manage the health response of its residents to the Covid-19 pandemic within the different socio-economic contexts that define the lived realities of individuals. OBJECTIVE: The objective of this study is to analyse the Covid-19 preventive behaviour and the socio-economic drivers behind the health-response behaviour. DATA: The study employs data from waves 1 and 2 of South Africa's nationally representative National Income Dynamics Study (NIDS)-Coronavirus Rapid Mobile Survey (CRAM). The nationally representative panel data has a sample of 7073 individuals in Wave 1 and 5676 individuals in Wave 2. METHODS: The study uses bivariate statistics, concentration indices and multivariate estimation techniques, ranging from a probit, control-function approach, special-regressor method and seemingly unrelated regression to account for endogeneity while identifying the drivers of the response behaviour. FINDINGS: The findings indicate enhanced behavioural responsiveness to Covid-19. Preventive behaviour is evolving over time; the use of face mask has overtaken handwashing as the most utilised preventive measure. Other measures, like social distancing, avoiding close contact, avoiding big groups and staying at home, have declined between the two periods of the study. There is increased risk perception with significant concentration among the higher income groups, the educated and older respondents. Our findings validate the health-belief model, with perceived risk, self-efficacy, perceived awareness and barriers to preventive strategy adoption identified as significant drivers of health-response behaviour. Measures such as social distancing, avoiding close contact, and the use of sanitisers are practised more by the rich and educated, but not by the low-income respondents. CONCLUSION: The respondents from lower socio-economic backgrounds are associated with optimism bias and face barriers to the adoption of preventive strategies. This requires targeted policy attention in order to make response behaviour effective.

Job loss and mental health during the COVID-19 lockdown: Evidence from South Africa.

OBJECTIVES: Existing literature on how employment loss affects depression has struggled to address potential endogeneity bias caused by reverse causality. The COVID-19 pandemic offers a unique natural experiment because the source of unemployment is very likely to be exogenous to the individual. This study assessed the effect of job loss and job furlough on the mental health of individuals in South Africa during the COVID-19 pandemic. DATA AND METHODS: The data for the study came from the first and second waves of the national survey, the National Income Dynamics-Coronavirus Rapid Mobile Survey (NIDS-CRAM), conducted during May-June and July-August 2020, respectively. The sample for NIDS-CRAM was drawn from an earlier national survey, conducted in 2017, which had collected data on mental health. Questions on depressive symptoms during the lockdown were asked in Wave 2 of NIDS-CRAM, using a 2-question version of the Patient Health Questionnaire (PHQ-2). The PHQ-2 responses (0-6 on the discrete scale) were regrouped into four categories making the ordered logit regression model the most suited for assessing the impact of employment status on depressive symptoms. RESULTS: The study revealed that adults who retained paid employment during the COVID-19 lockdown had significantly lower depression scores than adults who lost employment. The benefits of employment also accumulated over time, underscoring the effect of unemployment duration on mental health. The analysis revealed no mental health benefits to being furloughed (on unpaid leave), but paid leave had a strong and significant positive effect on the mental health of adults. CONCLUSIONS: The economic fallout of the COVID-19 pandemic resulted in unprecedented job losses, which impaired mental wellbeing significantly. Health policy responses to the crisis therefore need to focus on both physical and mental health interventions.

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.