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Social Epidemiology and Global Mental Health: Expanding the Evidence from High-Income to Low- and Middle-Income Countries

Social Epidemiology and Global Mental Health: Expanding the Evidence from High-Income to Low- and... Curr Epidemiol Rep (2017) 4:166–173 DOI 10.1007/s40471-017-0107-y SOCIAL EPIDEMIOLOGY (A AIELLO, SECTION EDITOR) Social Epidemiology and Global Mental Health: Expanding the Evidence from High-Income to Low- and Middle-Income Countries Joanna Maselko Published online: 18 April 2017 The Author(s) 2017. This article is an open access publication Abstract and distribution of a given social variable may differ signifi- Purpose of the Review The vast majority of research on the cantly from what is commonly observed in HICs. These social determinants of mental health has been generated from points of departure point to opportunities for social epidemi- high-income country (HIC) populations, even as the greatest ology to make a contribution to the field of global mental health disparities, and greatest disease burden, is observed in health. lower- and middle-income countries (LMICs). The goal of . . this review is to examine the evidence base on how key social Keywords Global mental health Social epidemiology . . epidemiology constructs relate to mental health in LMIC con- Healthdisparities Low-andmiddle-incomecountry(LMIC) texts. A special focus is on points of departure from the HIC Common mental disorders Socioeconomic status knowledge base, gaps in overall understanding, and opportu- nities for social epidemiology to make a significant contribution. Introduction Recent Findings A growing body of literature suggests that there is significant heterogeneity, both in the direction and Over the last decade, health researchers and funders have be- magnitude, of association between factors such as socioeco- come increasingly concerned with the 10/90 gap: the phenom- nomic status, income inequality, gender, and social networks/ enon that only 10% of health-related research addresses prob- supports and mental health in LMIC. For example, higher lems of 90% of the world’s population [1, 2]. This inequality is levels of education and being married can be risk factors for of special concern to social epidemiology given the implica- worse mental health among women in certain contexts. tion that the vast majority of research applies to the wealthiest However, many studies have methodological limitations that and healthiest countries, with the vast health disparities occur- make causal inference difficult. Poverty alleviation interven- ring in the remaining 90% of the global population. The topic tions offer a unique opportunity to examine the impact of of health disparities in low- and middle-income countries improving economic resources and mental health. (LMICs) has emerged as an active area of research and pro- Summary Much remains unknown about the impact of key vides an opportunity for social epidemiology to meaningfully social factors on mental health in LMIC. Findings from contribute to research on key social determinants of health HICs may not apply to LMIC populations, since the meaning beyond high-income country (HIC) contexts [3� , 4–6]. The shift from social determinants as they manifest in the This article is part of the Topical Collection on Social Epidemiology USA, UK, and other European countries to their manifestation in LMIC contexts is not, however, completely straightfor- * Joanna Maselko ward. In many LMICs, the meaning and distribution of a so- jmaselko@unc.edu cial factor, such as income inequality or education, may depart drastically from what is commonly observed in HICs. For Department of Epidemiology, Gillings School of Global Public example, in South Africa, the income inequality measure, Health, University of North Carolina at Chapel Hill, 2105e the GINI index, is 63 (in 2011) and a very small middle class, McGavran-Greenberg Hall, Campus Box 7435, Chapel Hill, NC 27599-7435, USA while in the USA, the GINI index is 41 (in 2013) with a much Curr Epidemiol Rep (2017) 4:166–173 167 larger middle class, making the USA a much more equitable precipitated by factors such as poverty or gender inequality country [7]. In the South African context, the independent [4, 21, 22]. Although the anthropological approach has some- effect of income inequality on health is more difficult to dis- times been in tension with the more medical or public health entangle from the effects of poverty with which it is entangled. approach to mental health, the importance of social determi- Focusing on education, in Bhutan, 68% of the population nants has rarely been questioned [23]. 25 years and older has received no schooling, and this number However, the fact that social determinants are acknowl- represents a 20% gender difference (57.8% of men and 77.8% edged, or even accepted, does not mean they are well under- of women have had no schooling). The comparable statistic in stood. There is significant heterogeneity in the findings the USA is 0.4%, with no detectible gender difference [8]. So, linking key social factors to mental health [24] and tensions while in HIC such as the USA, much of the discourse is about have risen about which factors are ‘really’ important for men- disparities in high school graduation rates and the value of a tal health vs. just being markers for something else [25]. This college education, the health benefits of the first few years of lack of clarity has led to calls for more, higher quality, research primary education are not nearly as well characterized. And into the social determinants of mental health in LMICs [3� , 5]. yet, this is the margin at which education affects the health of a Specifically, much more knowledge is needed in low-resource much larger portion of the world’s population. Such differ- settings to (1) better understand the causal relationships be- ences between HIC and LMIC emerge with most social tween social factors and diverse mental health problems, and determinants. (2) elucidate the mechanisms through which social factors The field of global mental health (GMH) is explicitly con- impact mental health. Such questions are also of central inter- cerned with reducing disparities in mental ill-health and hence est to social epidemiology. is very concerned with social determinants, making it a natural complement to social epidemiology. A key goal of GMH has Socioeconomic Status and Poverty been to reduce disparities between and within countries through increasing access to culturally appropriate evidence- Of all the social determinants of mental health, socioeconomic based interventions as well as addressing social determinants status (SES) has received the most attention [3� , 24, 26]. of mental ill-health [9–11]. Mental ill-health is broadly de- Although a full review is beyond the scope of this paper, a fined, and the vast majority of research focuses on depression majority of studies show an inverse association between lower and anxiety, often referred to as the common mental disorder SES and numerous mental health outcomes [24, 26]. (CMD), in addition to a growing body of research on schizo- However, there is significant heterogeneity in findings, and phrenia, dementias, autism, substance use disorders, and self- this might be due in part to lack of clarity of both conceptual harm [12–15]. Together, the broader category of mental dis- and methodological issues [27� ]. Two key areas of debate are orders account for up to 13% of disability adjusted life years measurement of SES and directionality of effects. (DALYs), making them the second leading cause of the global burden of disease after cardiovascular diseases [16]. Measurement Drawing on both social epidemiology and global mental health, the goal of this article is to examine how key social The majority of studies examining SES and mental health fail determinants, such as socioeconomic status, income inequal- to clearly define the choice of SES measure, or explain its ity, or gender, relate to mental health in LMIC contexts. A theoretical rationale [27� ]. Commonly used indicators include main focus is on points of departure from the HIC knowledge consumption/expenditure amounts, income, occupation, edu- base, gaps in overall understanding, and opportunities for so- cation, or assets, leading to seemingly conflicting findings. cial epidemiology to make a significant contribution. Because each of these measures captures a different aspect of SES, with potentially a different pathway linking it to men- Social Determinants Within Global Mental Health tal health, homogenous findings should not be expected, with- in or between countries. It has been challenging to synthesize The social context has always been important in global mental the diverse findings of multiple SES indicators in a coherent health, both in shaping the risk of a neuropsychiatric disorder way. as well as its likelihood of recovery [9, 10, 14, 17, 18]. The Many studies of SES use the terms SES and poverty inter- importance of social determinants within global mental health changeably without explicitly acknowledging how the choice can be traced to the fields’ anthropological roots and the cross- of term influences analyses or interpretation of results [3� , cultural psychiatrists who first described the experiences of 27� ]. Dichotomous proxies for poverty are frequent, such as mental illness outside of Western, HICs [19, 20]. living on less than $2/day, being in debt, living in overcrowd- Approaching mental health with an inherently social, anthro- ed conditions, or experiencing food insecurity. While a dichot- pological lens, an understanding of mental ill-health emerged omous poverty indicator is arguably easier to measure, fits that is embedded in one’s social environment and often well with the poverty alleviation agenda, and can be useful 168 Curr Epidemiol Rep (2017) 4:166–173 for policy makers, it oversimplifies the SES-mental health problems, which in turn further reinforce SES vulnerabilities relationship. Importantly, this reliance on poverty, with com- is an empirical question that social epidemiology is well parisons of those with the highest levels of adversity with poised to address. everyone else, obscures the gradient nature of the SES- Unlike in HIC where experimental data on social determi- mental health relationship. There is little reason to expect the nants and mental health is fairly scarce, in LMIC, some of the gradient to be any less strong in LMIC contexts than in HIC most informative empirical contributions are from poverty ones. The focus on high-risk poverty can also lead to an un- alleviation interventions that assess mental health outcomes, intended consequence of weakening the case for improving as well as mental health interventions that assess socioeco- access to prevention and treatment options because of a belief nomic outcomes [17, 26]. These interventions provide evi- that mental health problems are ‘inevitable’ at such high levels dence on how a change in economic circumstances can impact of adversity. Such oversimplifications can be prevented with a mental health, and whether improvements in mental health more fine-grained measure of SES which, in turn, facilitates a can lead to improved economic outcomes. Additionally, they better understanding of the nature of the association between provide information on the extent to which mental health socioeconomic status and mental health at all levels of adver- problems may get in the way of people taking full advantage sity. To guide future work on SES and mental health, re- of available socioeconomic opportunities. In other words, they searchers have recently proposed a set of guidelines for choos- help point to how the cycle of poverty-mental health problems ing an SES measure, including (a) choosing a measure based may bebroken[5, 17]. Here, I will focus on the social causa- on a theoretical basis with conceptual and contextual rele- tion part of the cycle with economic interventions and their vance, (b) determining and stating the unit of measurement impacts on mental health. and time period, and (c) being clear about how categories and Loan and micro-enterprise interventions provide access to groupings were created and why [27� ]. To guide an improved credit. The goal of these interventions is usually to provide theoretical basis for measurement, researchers would benefit enough capital (either through a loan or grant) so that the greatly from the extremely rich body of scholarship that ex- participant can invest those funds in a small business enter- amines the theoretical underpinnings and lived experience of prise or other income generating activity (e.g., purchase a plot poverty and social class (e.g., [28–31]). of land that can be farmed or raw materials to make textiles to be sold). The findings from these interventions are mixed for Directionality mental health outcomes, even as financial indicators show some improvement. For example, a trial in the Democratic The idea of reciprocal and cyclical relationship between pov- Republic of Congo helped with saving and small loans found erty and mental health is mostly accepted within global mental improvements in per capita food spending but not any mental health [17]. The term ‘social drift’ is used more often than health symptoms [34]. The authors hypothesized that the in- ‘social selection’ since this portion of the cycle, where a per- creased savings may not have been sufficient to improve men- son with mental illness becomes poor as a result of their ill- tal health in this traumatized population; a combination of ness, is also understood to be shaped by social factors related mental health and economic support may have been needed. to family and community support and integration. It has been Another microenterprise intervention in Uganda reported sim- hypothesized that social drift may be a stronger contributor to ilar results: monthly cash earnings increased 16 months after the SES gradient observed with disorders such as schizophre- start of the program, but there was no impact on depression nia, while social causation is more likely to explain the de- symptoms [35]. These, and other similar interventions, are pression SES gradient [5]. The relative magnitude of effect in complex, with multiple components aimed to help participants both parts of the cycle has direct implications for allocation of lift themselves out of poverty. One might argue that in order to resources whose goal is reducing disease burden. Is an anti- succeed, they require a level of functioning from the partici- poverty measure or an increase in access to mental health care pants that might be too high. However, findings with simpler a ‘better’ use of resources? In areas where poverty is over- interventions also vary. For example, a program in South whelming, efforts at treating mental illness without addressing Africa was based solely on improving access to loans with adversity can seem naïve at best, and an encroachment of existing banks, reported overall increased levels of stress 6– Western biomedicine and pharmaceutical industries at worst 12 months post intervention, while depression symptoms re- [32]. On the other hand, changing more upstream determi- duced among men, but not among women in the study [36]. nants is extremely difficult, and usually outside of the exper- The mixed findings may result from several factors. It is pos- tise of those working in global mental health. This dichoto- sible that mental health impacts take longer to emerge, once mized view of social vs. biomedical approaches has the risk of not only the immediate economic circumstances improve but becoming polarized even as it is ultimately overly simplistic a more long-term security is achieved. Alternatively, the mag- and unproductive [18, 23, 33]. The degree to which social nitude of the economic boost resulting from the intervention determinants such as SES impact risk of mental health may not be sufficient given the very low starting SES of the Curr Epidemiol Rep (2017) 4:166–173 169 participants. Finally, the mechanism of supporting entrepre- simultaneously have high poverty and inequality rates, mak- neurial activities may only benefit a portion of participants— ing it more difficult to isolate the impact of inequality per se. those who have the skills and aptitude for a small business As might be expected, findings have been mixed. Several pursuit. This would lead to heterogeneous impacts on both studies from South Africa and Mexico found no association economic and mental health outcomes. [41, 42], while a study from Sao Paulo Brazil found income Another group of poverty alleviation programs that address inequality to be positively associated with depression [43]. these questions are cash transfer interventions, whether con- Several reasons may explain these findings. One is methodo- ditional on activities such as sending children to school and logical: studies utilizing larger geographical measures of in- getting immunized, or unconditional, no-strings attached, cash equality, such as district or state levels, seem more likely have transfer programs. Mexico’s well-documented Oportunidades null results (South Africa, Mexico), while more micro level program was an intervention where women received a signif- measures are more likely to find an association (Brazil). Other icant stipend, conditional on several health-related behaviors potential explanations include the fact that, in high inequality including prenatal care, immunizations, and educational LMICs, there may not be enough variation in inequality, es- workshops [37]. The stipend was roughly 25% of household pecially if a ceiling effect has been reached; the GINI coeffi- income and, at the time of the evaluation, women had been in cient may not be the appropriate indicator; or the common the program between 3.5 and 5 years. Depression symptoms focus on depression may miss other mental health problems were significantly lower in the intervention group and this susceptible to the effects of inequality, such as substance use effect was partially mediated through both a reduction in stress [41–44]. In addition to these challenges, Adjaye-Gbewonyo and increase in perceived control [38� ]. It is noteworthy that hypothesized potential contextual reasons for why an associ- the positive impact was greater among women who were rel- ation might not be observed in a country such as South Africa: atively better-off at the start of the study; there is some debate people in South Africa may be more tolerant of high-income about whether interventions that promote health overall may inequality. This could be either because they consider income increase inequalities because those who are at the very bottom inequality as temporary on the way to improved post- are not able to fully take advantage of a program’sbenefits apartheid economic development. Alternatively, in other con- [39]. The long-term evaluation, at 5 years, is also notable texts, people’s expectations for equality may be lower, and when compared to the previously described interventions that communities so segregated that people are less aware of in- were evaluated within a year or two of the program rollout. It equality while being more impacted by their own SES level. It might take time for mental health effects to become apparent. has also been suggested that income inequality is only impor- While the Oportunidades program is one of the best docu- tant for health in places of low poverty levels such as in HIC, mented, other similar cash infusion programs at a smaller while in places with high poverty levels, health is driven by scale, such as significant wage increases at factories, similarly absolute poverty [45]. Much remains unknown about how report lower depressive symptoms among program beneficia- income inequality interacts with other social, cultural, and ries [40]. economic factors to influence mental health [3� ]. In summary, poverty alleviation interventions provide im- portant insights into the SES-mental health relationship: We have learned that purely economic interventions among poor Gender participants may not have enough impact when other signifi- cant sources of distress remain. Individuals may also need a After SES and poverty, gender is one of the most well- broader safety net than one provided by cash and/or the described social determinant of mental health in LMIC. amount of money needed may be much more significant than Gender differences in CMD prevalence are regularly reported previously assumed [34, 35]. The evaluation of poverty reduc- and gender is routinely included in analyses predicting mental tion programs from the perspective of mental health is thus a health outcomes. As in HIC, in LMIC women are at higher very powerful approach toward disentangling the mechanisms risk of CMD and almost all studies acknowledge women’s through which SES impacts population mental health [26]. vulnerability resulting from their lower status in society as a key driver of higher CMD rates [14, 46, 47]. It is not clear to Income Inequality what extent the excess risk associated with female gender for CMD differs in magnitude between LMIC and HIC. The gen- Discussions of poverty often dovetail with those about income der difference in alcohol use disorders does appear to be larger inequality [3� ] and a few studies have attempted to quantify in magnitude in some LMICs, with men’srisk up to 20 times the impact of income inequality on mental health in LMIC. As greater than what is observed among women [14]. This dif- mentioned above, levels of income inequality are generally ference is potentially driven by lower prevalence of women significantly higher in LMIC than in HIC and LMICs tend consuming any alcohol in many LMICs in combination with a to have a much smaller middle class. These countries much greater proportion of men who consume any alcohol, 170 Curr Epidemiol Rep (2017) 4:166–173 consuming it at hazardous levels. Moderate alcohol consump- ‘confinement’ or ‘chilla’ of a new mother during the first 30– tion appears to be more normative in HIC. 40 days after birth. The specifics of this period vary cross- Given that gender interacts with social institutions such as culturally but in almost all circumstances, it is a period for rest marriage or the labor market, we may expect different epide- and bonding between the mother and her new infant. The miological patterns of mental health problems among women mother is relieved from household chores and generally stays than those observed in HIC, Western countries [48]. For ex- protected indoors. This practice has been found to be protec- ample, in India, higher education has been associated with a tive against maternal depression [11, 58] and is understood to twofold greater risk of suicide among women [49]. Several indicate a strong social support, family-based, network. hypotheses have emerged about why a higher educational Indeed, it is only possible with a commitment from multiple attainment might be a risk factor. In certain communities, ef- people to provide significant support. forts to encourage girls’ education have resulted in young However, other research has revealed some of the com- women being, on average, more educated than young men plexities around activating one’s social support network. [50]. These years of education sometimes come with signifi- One’s social network can be a source of shame or stigma, as cant personal sacrifice and anthropological work has shed was the case in one study where food-insecure mothers feared light on the difficulties and stressors faced by some women asking for help due to the shame they felt for not being able as they try to achieve their education goals; stressors that, in provide food to their family [59]. This fear of revealing a turn, may lead to mental health problems [51]. However, even perceived weakness may apply both to close members of once education is complete, a higher level of education may one’s networks, such as other family members, or those who not translate into economic empowerment, as women often are less close, such as neighbors. The worry about stigma cannot successfully compete with men for scarce jobs. As coming from one’s network can also hinder participation in women become married, they may revert to traditional gender other poverty alleviation type interventions as well [60]. It is roles and a lower status, which can be all the more distressing plausible that the impact of both positive and negative aspects after having been ‘temporarily empowered’ through their ed- of social networks, e.g., support vs. shame, might be stronger ucation. The lower status of newly married women might also in cultures that are more community vs. individual focused, help explain why widowed or divorced women can be at although this hypothesis remains to be tested. lesser risk for suicide and CMD compared to those who are Much remains unknown about other aspects of social net- married [14, 49]. With a strong emphasis on childbearing, works, such as men’s networks, more extended non-kin-based there is evidence that adverse life events related to reproduc- networks, or how technology facilitates social network con- tion may be partially responsible for the high burden of mental tacts. For example, cellular phone usage has been found to be health problems among women in places like India [46]. associated with higher stress in HIC, but a recent study in Interpersonal violence may be another potential mechanism Uganda found that cell phone ownership and usage was asso- linking negative reproductive outcomes with CMD [52]. ciated with better mental health, especially among those whose families did not live nearby [61]. In locations with high Social Networks and Supports migrant, or displaced, populations, the improved social con- nectivity from internet or cellular technology may be especial- Although access to social support networks, especially during ly protective. Such differences in the structure of social net- times of adversity, is consistently shown to have a protective works, how they are activated, and the supports they provide effect on mental health [53–55], there are several notable dif- are likely to continue to emerge with continued study. ferences between the HIC and LMIC bodies of research. One key difference is the greater importance given to Conclusions and Going Forward family-based networks. This is, in part, a result of a higher prevalence of extended, multi-generational, family house- This targeted review reveals that much remains unknown holds in LMICs; an arrangement that encourages a higher about how social determinants shape the risk of mental ill- level of caregiving expectations and support between family health in LMIC. The examples of SES, income inequality, members. Consistent with a focus on childbearing mentioned gender, and social networks/supports suggest that, while some above, the majority of the research in this area has focused on knowledge from HIC does translate to LMIC, a considerable maternal mental health, especially the perinatal period. For body of evidence does not. Importantly, it is not always clear example, studies in South Asia have found that the presence a priori which lessons transfer well and which ones need of the grandmother in the household has generally been cor- significant revisions. These same challenges apply to social related with better mental health outcomes among mothers factors such as race/ethnicity, neighborhood effects, or so- and children, with the most likely pathway being through cial capital that were not discussed in this review but are also provided social support [56, 57]. One commonly described areas of active research (e.g., [62–64]). The intersection of example of this family-based social support is the practice of global mental health and social epidemiology offers an Curr Epidemiol Rep (2017) 4:166–173 171 Open Access This article is distributed under the terms of the Creative exciting opportunity to address these challenges and ad- Commons Attribution 4.0 International License (http:// vance the knowledge base of social determinants of mental creativecommons.org/licenses/by/4.0/), which permits unrestricted use, health in LMIC. distribution, and reproduction in any medium, provided you give appro- Cross-disciplinary collaborations are key in this effort and priate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. the fields of economics and anthropology will continue to play a significant role in GMH. For example, development econo- mists are increasingly aware of the importance of mental References health in poverty alleviation efforts: mental health problems, such as depression or anxiety symptoms, impact decision making and risk taking, which may in turn, affect how indi- Papers of particular interest, published recently, have been viduals respond to economic changes [65, 66]. A recent call highlighted as: for the use of Amartya Sen’s Capabilities Approach to help � Of importance inform how the global mental health agenda links with the 1. CMAJ. Western medical journals and the 10/90 problem. CMAJ. economic development agenda is very promising [28, 67, Canadian Medical Association journal = journal de l'Association 68]. The Capabilities Approach emphasis on upstream, struc- medicale canadienne. 2004;170(1):5. 7 tural factors that may limit individuals’ ability to function and 2. Saxena S, Paraje G, Sharan P, Karam G, Sadana R. 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Social Epidemiology and Global Mental Health: Expanding the Evidence from High-Income to Low- and Middle-Income Countries

Current Epidemiology Reports , Volume 4 (2) – Apr 18, 2017

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Abstract

Curr Epidemiol Rep (2017) 4:166–173 DOI 10.1007/s40471-017-0107-y SOCIAL EPIDEMIOLOGY (A AIELLO, SECTION EDITOR) Social Epidemiology and Global Mental Health: Expanding the Evidence from High-Income to Low- and Middle-Income Countries Joanna Maselko Published online: 18 April 2017 The Author(s) 2017. This article is an open access publication Abstract and distribution of a given social variable may differ signifi- Purpose of the Review The vast majority of research on the cantly from what is commonly observed in HICs. These social determinants of mental health has been generated from points of departure point to opportunities for social epidemi- high-income country (HIC) populations, even as the greatest ology to make a contribution to the field of global mental health disparities, and greatest disease burden, is observed in health. lower- and middle-income countries (LMICs). The goal of . . this review is to examine the evidence base on how key social Keywords Global mental health Social epidemiology . . epidemiology constructs relate to mental health in LMIC con- Healthdisparities Low-andmiddle-incomecountry(LMIC) texts. A special focus is on points of departure from the HIC Common mental disorders Socioeconomic status knowledge base, gaps in overall understanding, and opportu- nities for social epidemiology to make a significant contribution. Introduction Recent Findings A growing body of literature suggests that there is significant heterogeneity, both in the direction and Over the last decade, health researchers and funders have be- magnitude, of association between factors such as socioeco- come increasingly concerned with the 10/90 gap: the phenom- nomic status, income inequality, gender, and social networks/ enon that only 10% of health-related research addresses prob- supports and mental health in LMIC. For example, higher lems of 90% of the world’s population [1, 2]. This inequality is levels of education and being married can be risk factors for of special concern to social epidemiology given the implica- worse mental health among women in certain contexts. tion that the vast majority of research applies to the wealthiest However, many studies have methodological limitations that and healthiest countries, with the vast health disparities occur- make causal inference difficult. Poverty alleviation interven- ring in the remaining 90% of the global population. The topic tions offer a unique opportunity to examine the impact of of health disparities in low- and middle-income countries improving economic resources and mental health. (LMICs) has emerged as an active area of research and pro- Summary Much remains unknown about the impact of key vides an opportunity for social epidemiology to meaningfully social factors on mental health in LMIC. Findings from contribute to research on key social determinants of health HICs may not apply to LMIC populations, since the meaning beyond high-income country (HIC) contexts [3� , 4–6]. The shift from social determinants as they manifest in the This article is part of the Topical Collection on Social Epidemiology USA, UK, and other European countries to their manifestation in LMIC contexts is not, however, completely straightfor- * Joanna Maselko ward. In many LMICs, the meaning and distribution of a so- jmaselko@unc.edu cial factor, such as income inequality or education, may depart drastically from what is commonly observed in HICs. For Department of Epidemiology, Gillings School of Global Public example, in South Africa, the income inequality measure, Health, University of North Carolina at Chapel Hill, 2105e the GINI index, is 63 (in 2011) and a very small middle class, McGavran-Greenberg Hall, Campus Box 7435, Chapel Hill, NC 27599-7435, USA while in the USA, the GINI index is 41 (in 2013) with a much Curr Epidemiol Rep (2017) 4:166–173 167 larger middle class, making the USA a much more equitable precipitated by factors such as poverty or gender inequality country [7]. In the South African context, the independent [4, 21, 22]. Although the anthropological approach has some- effect of income inequality on health is more difficult to dis- times been in tension with the more medical or public health entangle from the effects of poverty with which it is entangled. approach to mental health, the importance of social determi- Focusing on education, in Bhutan, 68% of the population nants has rarely been questioned [23]. 25 years and older has received no schooling, and this number However, the fact that social determinants are acknowl- represents a 20% gender difference (57.8% of men and 77.8% edged, or even accepted, does not mean they are well under- of women have had no schooling). The comparable statistic in stood. There is significant heterogeneity in the findings the USA is 0.4%, with no detectible gender difference [8]. So, linking key social factors to mental health [24] and tensions while in HIC such as the USA, much of the discourse is about have risen about which factors are ‘really’ important for men- disparities in high school graduation rates and the value of a tal health vs. just being markers for something else [25]. This college education, the health benefits of the first few years of lack of clarity has led to calls for more, higher quality, research primary education are not nearly as well characterized. And into the social determinants of mental health in LMICs [3� , 5]. yet, this is the margin at which education affects the health of a Specifically, much more knowledge is needed in low-resource much larger portion of the world’s population. Such differ- settings to (1) better understand the causal relationships be- ences between HIC and LMIC emerge with most social tween social factors and diverse mental health problems, and determinants. (2) elucidate the mechanisms through which social factors The field of global mental health (GMH) is explicitly con- impact mental health. Such questions are also of central inter- cerned with reducing disparities in mental ill-health and hence est to social epidemiology. is very concerned with social determinants, making it a natural complement to social epidemiology. A key goal of GMH has Socioeconomic Status and Poverty been to reduce disparities between and within countries through increasing access to culturally appropriate evidence- Of all the social determinants of mental health, socioeconomic based interventions as well as addressing social determinants status (SES) has received the most attention [3� , 24, 26]. of mental ill-health [9–11]. Mental ill-health is broadly de- Although a full review is beyond the scope of this paper, a fined, and the vast majority of research focuses on depression majority of studies show an inverse association between lower and anxiety, often referred to as the common mental disorder SES and numerous mental health outcomes [24, 26]. (CMD), in addition to a growing body of research on schizo- However, there is significant heterogeneity in findings, and phrenia, dementias, autism, substance use disorders, and self- this might be due in part to lack of clarity of both conceptual harm [12–15]. Together, the broader category of mental dis- and methodological issues [27� ]. Two key areas of debate are orders account for up to 13% of disability adjusted life years measurement of SES and directionality of effects. (DALYs), making them the second leading cause of the global burden of disease after cardiovascular diseases [16]. Measurement Drawing on both social epidemiology and global mental health, the goal of this article is to examine how key social The majority of studies examining SES and mental health fail determinants, such as socioeconomic status, income inequal- to clearly define the choice of SES measure, or explain its ity, or gender, relate to mental health in LMIC contexts. A theoretical rationale [27� ]. Commonly used indicators include main focus is on points of departure from the HIC knowledge consumption/expenditure amounts, income, occupation, edu- base, gaps in overall understanding, and opportunities for so- cation, or assets, leading to seemingly conflicting findings. cial epidemiology to make a significant contribution. Because each of these measures captures a different aspect of SES, with potentially a different pathway linking it to men- Social Determinants Within Global Mental Health tal health, homogenous findings should not be expected, with- in or between countries. It has been challenging to synthesize The social context has always been important in global mental the diverse findings of multiple SES indicators in a coherent health, both in shaping the risk of a neuropsychiatric disorder way. as well as its likelihood of recovery [9, 10, 14, 17, 18]. The Many studies of SES use the terms SES and poverty inter- importance of social determinants within global mental health changeably without explicitly acknowledging how the choice can be traced to the fields’ anthropological roots and the cross- of term influences analyses or interpretation of results [3� , cultural psychiatrists who first described the experiences of 27� ]. Dichotomous proxies for poverty are frequent, such as mental illness outside of Western, HICs [19, 20]. living on less than $2/day, being in debt, living in overcrowd- Approaching mental health with an inherently social, anthro- ed conditions, or experiencing food insecurity. While a dichot- pological lens, an understanding of mental ill-health emerged omous poverty indicator is arguably easier to measure, fits that is embedded in one’s social environment and often well with the poverty alleviation agenda, and can be useful 168 Curr Epidemiol Rep (2017) 4:166–173 for policy makers, it oversimplifies the SES-mental health problems, which in turn further reinforce SES vulnerabilities relationship. Importantly, this reliance on poverty, with com- is an empirical question that social epidemiology is well parisons of those with the highest levels of adversity with poised to address. everyone else, obscures the gradient nature of the SES- Unlike in HIC where experimental data on social determi- mental health relationship. There is little reason to expect the nants and mental health is fairly scarce, in LMIC, some of the gradient to be any less strong in LMIC contexts than in HIC most informative empirical contributions are from poverty ones. The focus on high-risk poverty can also lead to an un- alleviation interventions that assess mental health outcomes, intended consequence of weakening the case for improving as well as mental health interventions that assess socioeco- access to prevention and treatment options because of a belief nomic outcomes [17, 26]. These interventions provide evi- that mental health problems are ‘inevitable’ at such high levels dence on how a change in economic circumstances can impact of adversity. Such oversimplifications can be prevented with a mental health, and whether improvements in mental health more fine-grained measure of SES which, in turn, facilitates a can lead to improved economic outcomes. Additionally, they better understanding of the nature of the association between provide information on the extent to which mental health socioeconomic status and mental health at all levels of adver- problems may get in the way of people taking full advantage sity. To guide future work on SES and mental health, re- of available socioeconomic opportunities. In other words, they searchers have recently proposed a set of guidelines for choos- help point to how the cycle of poverty-mental health problems ing an SES measure, including (a) choosing a measure based may bebroken[5, 17]. Here, I will focus on the social causa- on a theoretical basis with conceptual and contextual rele- tion part of the cycle with economic interventions and their vance, (b) determining and stating the unit of measurement impacts on mental health. and time period, and (c) being clear about how categories and Loan and micro-enterprise interventions provide access to groupings were created and why [27� ]. To guide an improved credit. The goal of these interventions is usually to provide theoretical basis for measurement, researchers would benefit enough capital (either through a loan or grant) so that the greatly from the extremely rich body of scholarship that ex- participant can invest those funds in a small business enter- amines the theoretical underpinnings and lived experience of prise or other income generating activity (e.g., purchase a plot poverty and social class (e.g., [28–31]). of land that can be farmed or raw materials to make textiles to be sold). The findings from these interventions are mixed for Directionality mental health outcomes, even as financial indicators show some improvement. For example, a trial in the Democratic The idea of reciprocal and cyclical relationship between pov- Republic of Congo helped with saving and small loans found erty and mental health is mostly accepted within global mental improvements in per capita food spending but not any mental health [17]. The term ‘social drift’ is used more often than health symptoms [34]. The authors hypothesized that the in- ‘social selection’ since this portion of the cycle, where a per- creased savings may not have been sufficient to improve men- son with mental illness becomes poor as a result of their ill- tal health in this traumatized population; a combination of ness, is also understood to be shaped by social factors related mental health and economic support may have been needed. to family and community support and integration. It has been Another microenterprise intervention in Uganda reported sim- hypothesized that social drift may be a stronger contributor to ilar results: monthly cash earnings increased 16 months after the SES gradient observed with disorders such as schizophre- start of the program, but there was no impact on depression nia, while social causation is more likely to explain the de- symptoms [35]. These, and other similar interventions, are pression SES gradient [5]. The relative magnitude of effect in complex, with multiple components aimed to help participants both parts of the cycle has direct implications for allocation of lift themselves out of poverty. One might argue that in order to resources whose goal is reducing disease burden. Is an anti- succeed, they require a level of functioning from the partici- poverty measure or an increase in access to mental health care pants that might be too high. However, findings with simpler a ‘better’ use of resources? In areas where poverty is over- interventions also vary. For example, a program in South whelming, efforts at treating mental illness without addressing Africa was based solely on improving access to loans with adversity can seem naïve at best, and an encroachment of existing banks, reported overall increased levels of stress 6– Western biomedicine and pharmaceutical industries at worst 12 months post intervention, while depression symptoms re- [32]. On the other hand, changing more upstream determi- duced among men, but not among women in the study [36]. nants is extremely difficult, and usually outside of the exper- The mixed findings may result from several factors. It is pos- tise of those working in global mental health. This dichoto- sible that mental health impacts take longer to emerge, once mized view of social vs. biomedical approaches has the risk of not only the immediate economic circumstances improve but becoming polarized even as it is ultimately overly simplistic a more long-term security is achieved. Alternatively, the mag- and unproductive [18, 23, 33]. The degree to which social nitude of the economic boost resulting from the intervention determinants such as SES impact risk of mental health may not be sufficient given the very low starting SES of the Curr Epidemiol Rep (2017) 4:166–173 169 participants. Finally, the mechanism of supporting entrepre- simultaneously have high poverty and inequality rates, mak- neurial activities may only benefit a portion of participants— ing it more difficult to isolate the impact of inequality per se. those who have the skills and aptitude for a small business As might be expected, findings have been mixed. Several pursuit. This would lead to heterogeneous impacts on both studies from South Africa and Mexico found no association economic and mental health outcomes. [41, 42], while a study from Sao Paulo Brazil found income Another group of poverty alleviation programs that address inequality to be positively associated with depression [43]. these questions are cash transfer interventions, whether con- Several reasons may explain these findings. One is methodo- ditional on activities such as sending children to school and logical: studies utilizing larger geographical measures of in- getting immunized, or unconditional, no-strings attached, cash equality, such as district or state levels, seem more likely have transfer programs. Mexico’s well-documented Oportunidades null results (South Africa, Mexico), while more micro level program was an intervention where women received a signif- measures are more likely to find an association (Brazil). Other icant stipend, conditional on several health-related behaviors potential explanations include the fact that, in high inequality including prenatal care, immunizations, and educational LMICs, there may not be enough variation in inequality, es- workshops [37]. The stipend was roughly 25% of household pecially if a ceiling effect has been reached; the GINI coeffi- income and, at the time of the evaluation, women had been in cient may not be the appropriate indicator; or the common the program between 3.5 and 5 years. Depression symptoms focus on depression may miss other mental health problems were significantly lower in the intervention group and this susceptible to the effects of inequality, such as substance use effect was partially mediated through both a reduction in stress [41–44]. In addition to these challenges, Adjaye-Gbewonyo and increase in perceived control [38� ]. It is noteworthy that hypothesized potential contextual reasons for why an associ- the positive impact was greater among women who were rel- ation might not be observed in a country such as South Africa: atively better-off at the start of the study; there is some debate people in South Africa may be more tolerant of high-income about whether interventions that promote health overall may inequality. This could be either because they consider income increase inequalities because those who are at the very bottom inequality as temporary on the way to improved post- are not able to fully take advantage of a program’sbenefits apartheid economic development. Alternatively, in other con- [39]. The long-term evaluation, at 5 years, is also notable texts, people’s expectations for equality may be lower, and when compared to the previously described interventions that communities so segregated that people are less aware of in- were evaluated within a year or two of the program rollout. It equality while being more impacted by their own SES level. It might take time for mental health effects to become apparent. has also been suggested that income inequality is only impor- While the Oportunidades program is one of the best docu- tant for health in places of low poverty levels such as in HIC, mented, other similar cash infusion programs at a smaller while in places with high poverty levels, health is driven by scale, such as significant wage increases at factories, similarly absolute poverty [45]. Much remains unknown about how report lower depressive symptoms among program beneficia- income inequality interacts with other social, cultural, and ries [40]. economic factors to influence mental health [3� ]. In summary, poverty alleviation interventions provide im- portant insights into the SES-mental health relationship: We have learned that purely economic interventions among poor Gender participants may not have enough impact when other signifi- cant sources of distress remain. Individuals may also need a After SES and poverty, gender is one of the most well- broader safety net than one provided by cash and/or the described social determinant of mental health in LMIC. amount of money needed may be much more significant than Gender differences in CMD prevalence are regularly reported previously assumed [34, 35]. The evaluation of poverty reduc- and gender is routinely included in analyses predicting mental tion programs from the perspective of mental health is thus a health outcomes. As in HIC, in LMIC women are at higher very powerful approach toward disentangling the mechanisms risk of CMD and almost all studies acknowledge women’s through which SES impacts population mental health [26]. vulnerability resulting from their lower status in society as a key driver of higher CMD rates [14, 46, 47]. It is not clear to Income Inequality what extent the excess risk associated with female gender for CMD differs in magnitude between LMIC and HIC. The gen- Discussions of poverty often dovetail with those about income der difference in alcohol use disorders does appear to be larger inequality [3� ] and a few studies have attempted to quantify in magnitude in some LMICs, with men’srisk up to 20 times the impact of income inequality on mental health in LMIC. As greater than what is observed among women [14]. This dif- mentioned above, levels of income inequality are generally ference is potentially driven by lower prevalence of women significantly higher in LMIC than in HIC and LMICs tend consuming any alcohol in many LMICs in combination with a to have a much smaller middle class. These countries much greater proportion of men who consume any alcohol, 170 Curr Epidemiol Rep (2017) 4:166–173 consuming it at hazardous levels. Moderate alcohol consump- ‘confinement’ or ‘chilla’ of a new mother during the first 30– tion appears to be more normative in HIC. 40 days after birth. The specifics of this period vary cross- Given that gender interacts with social institutions such as culturally but in almost all circumstances, it is a period for rest marriage or the labor market, we may expect different epide- and bonding between the mother and her new infant. The miological patterns of mental health problems among women mother is relieved from household chores and generally stays than those observed in HIC, Western countries [48]. For ex- protected indoors. This practice has been found to be protec- ample, in India, higher education has been associated with a tive against maternal depression [11, 58] and is understood to twofold greater risk of suicide among women [49]. Several indicate a strong social support, family-based, network. hypotheses have emerged about why a higher educational Indeed, it is only possible with a commitment from multiple attainment might be a risk factor. In certain communities, ef- people to provide significant support. forts to encourage girls’ education have resulted in young However, other research has revealed some of the com- women being, on average, more educated than young men plexities around activating one’s social support network. [50]. These years of education sometimes come with signifi- One’s social network can be a source of shame or stigma, as cant personal sacrifice and anthropological work has shed was the case in one study where food-insecure mothers feared light on the difficulties and stressors faced by some women asking for help due to the shame they felt for not being able as they try to achieve their education goals; stressors that, in provide food to their family [59]. This fear of revealing a turn, may lead to mental health problems [51]. However, even perceived weakness may apply both to close members of once education is complete, a higher level of education may one’s networks, such as other family members, or those who not translate into economic empowerment, as women often are less close, such as neighbors. The worry about stigma cannot successfully compete with men for scarce jobs. As coming from one’s network can also hinder participation in women become married, they may revert to traditional gender other poverty alleviation type interventions as well [60]. It is roles and a lower status, which can be all the more distressing plausible that the impact of both positive and negative aspects after having been ‘temporarily empowered’ through their ed- of social networks, e.g., support vs. shame, might be stronger ucation. The lower status of newly married women might also in cultures that are more community vs. individual focused, help explain why widowed or divorced women can be at although this hypothesis remains to be tested. lesser risk for suicide and CMD compared to those who are Much remains unknown about other aspects of social net- married [14, 49]. With a strong emphasis on childbearing, works, such as men’s networks, more extended non-kin-based there is evidence that adverse life events related to reproduc- networks, or how technology facilitates social network con- tion may be partially responsible for the high burden of mental tacts. For example, cellular phone usage has been found to be health problems among women in places like India [46]. associated with higher stress in HIC, but a recent study in Interpersonal violence may be another potential mechanism Uganda found that cell phone ownership and usage was asso- linking negative reproductive outcomes with CMD [52]. ciated with better mental health, especially among those whose families did not live nearby [61]. In locations with high Social Networks and Supports migrant, or displaced, populations, the improved social con- nectivity from internet or cellular technology may be especial- Although access to social support networks, especially during ly protective. Such differences in the structure of social net- times of adversity, is consistently shown to have a protective works, how they are activated, and the supports they provide effect on mental health [53–55], there are several notable dif- are likely to continue to emerge with continued study. ferences between the HIC and LMIC bodies of research. One key difference is the greater importance given to Conclusions and Going Forward family-based networks. This is, in part, a result of a higher prevalence of extended, multi-generational, family house- This targeted review reveals that much remains unknown holds in LMICs; an arrangement that encourages a higher about how social determinants shape the risk of mental ill- level of caregiving expectations and support between family health in LMIC. The examples of SES, income inequality, members. Consistent with a focus on childbearing mentioned gender, and social networks/supports suggest that, while some above, the majority of the research in this area has focused on knowledge from HIC does translate to LMIC, a considerable maternal mental health, especially the perinatal period. For body of evidence does not. Importantly, it is not always clear example, studies in South Asia have found that the presence a priori which lessons transfer well and which ones need of the grandmother in the household has generally been cor- significant revisions. These same challenges apply to social related with better mental health outcomes among mothers factors such as race/ethnicity, neighborhood effects, or so- and children, with the most likely pathway being through cial capital that were not discussed in this review but are also provided social support [56, 57]. One commonly described areas of active research (e.g., [62–64]). The intersection of example of this family-based social support is the practice of global mental health and social epidemiology offers an Curr Epidemiol Rep (2017) 4:166–173 171 Open Access This article is distributed under the terms of the Creative exciting opportunity to address these challenges and ad- Commons Attribution 4.0 International License (http:// vance the knowledge base of social determinants of mental creativecommons.org/licenses/by/4.0/), which permits unrestricted use, health in LMIC. distribution, and reproduction in any medium, provided you give appro- Cross-disciplinary collaborations are key in this effort and priate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. the fields of economics and anthropology will continue to play a significant role in GMH. 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