Measuring material wealth in low-income settings: A conceptual and how-to guide

The relationship between mental well-being and wealth varies by wealth type, place and sex/gender: Evidence from Namibia

This paper explores the impact of livelihood strategies and place on mental well-being. Identifying different socioeconomic factors that impact mental well-being across contexts is pressing given the global rise in mental health disorders. Numerous studies in the population and social sciences have emphasized the protective role of material wealth on human health and well-being; however, scholars frequently assess wealth as a one-dimensional variable, which may fail to capture diverse forms of wealth. Acknowledging different forms of wealth may be particularly important in settings where agricultural economies coexist with cash economies. Using data from the 2013 Namibia Demographic Health Survey (n = 13 377), we use a newly developed measure of success in agricultural activities, an agricultural wealth index, or AWI, generated by Hackman et al., (2021). To examine the role of different forms of wealth on mental health symptoms. We find mental well-being, assessed through three survey questions, is lower among urban dwellers and females and shows varied associations with wealth type and sex/gender. In general, success in agricultural activities is associated with better mental well-being, while the association with market success is null or and conditional upon sex/gender and place. This study adds to recent work on the value of using multidimensional measures of wealth and raises important questions about why wealth type and sex/gender differentially impact mental well-being.

Global rural health disparities in Alzheimer's disease and related dementias: State of the science

INTRODUCTION

Individuals living in rural communities are at heightened risk for Alzheimer's disease and related dementias (ADRD), which parallels other persistent place-based health disparities. Identifying multiple potentially modifiable risk factors specific to rural areas that contribute to ADRD is an essential first step in understanding the complex interplay between various barriers and facilitators.

METHODS

An interdisciplinary, international group of ADRD researchers convened to address the overarching question of: "What can be done to begin minimizing the rural health disparities that contribute uniquely to ADRD?" In this state of the science appraisal, we explore what is known about the biological, behavioral, sociocultural, and environmental influences on ADRD disparities in rural settings.

RESULTS

A range of individual, interpersonal, and community factors were identified, including strengths of rural residents in facilitating healthy aging lifestyle interventions.

DISCUSSION

A location dynamics model and ADRD-focused future directions are offered for guiding rural practitioners, researchers, and policymakers in mitigating rural disparities.

HIGHLIGHTS

Rural residents face heightened Alzheimer's disease and related dementia (ADRD) risks and burdens due to health disparities. Defining the unique rural barriers and facilitators to cognitive health yields insight. The strengths and resilience of rural residents can mitigate ADRD-related challenges. A novel "location dynamics" model guides assessment of rural-specific ADRD issues.

How reliable is the asset score in measuring socioeconomic status? Comparing asset ownership reported by male and female heads of households

Asset scores are widely used as the preferred method of measuring socioeconomic wellbeing of households in developing countries. We examine the degree of discrepancies in reporting asset ownership by male and female heads of the same household. Household asset scores were estimated separately for male and female responses, using Principal Component Analysis, the method widely used in the literature, and households were categorized into wealth quintiles. The results indicate that only half of the households belonged to the same quintile groups for both male and female response-based asset scores. In addition, the two estimates of asset scores within the same quintile deviate by more than 20% for 71% of households in the top three quintiles and for 18% in the poorest two quintiles. Inter-individual (male/female) variability in reporting the asset ownership was high enough to raise concerns about the validity and reliability of asset scores as a metric of household socioeconomic status. Although the study did not try to ascertain underlying reasons for differential reporting, possible explanations could be a lack of awareness among household members on asset ownership or differential propensity to demonstrate relatively better social status of the household by male and female respondents. To improve reliability of asset scores, methodology for collecting asset ownership information should define who in the household may or may not be used as a respondent. Visual verification of reported ownership of assets will reduce male-female discrepancies but the verification process is time-consuming and intrusive, thus negating the advantages of collecting asset data. Alternatives to asset-based scoring need to be considered and one approach could be to solicit subjective opinions from male and female heads on the location of households in the social hierarchy.

Strengths and limitations of relative wealth indices derived from big data in Indonesia

Accurate relative wealth estimates in Low and Middle-Income Countries (LMICS) are crucial to help policymakers address socio-demographic inequalities under the guidance of the Sustainable Development Goals set by the United Nations. Survey-based approaches have traditionally been employed to collect highly granular data about income, consumption, or household material goods to create index-based poverty estimates. However, these methods are only capture persons in households (i.e., in the household sample framework) and they do not include migrant populations or unhoused citizens. Novel approaches combining frontier data, computer vision, and machine learning have been proposed to complement these existing approaches. However, the strengths and limitations of these big-data-derived indices have yet to be sufficiently studied. In this paper, we focus on the case of Indonesia and examine one frontier-data derived Relative Wealth Index (RWI), created by the Facebook Data for Good initiative, that utilizes connectivity data from the Facebook Platform and satellite imagery data to produce a high-resolution estimate of relative wealth for 135 countries. We examine it concerning asset-based relative wealth indices estimated from existing high-quality national-level traditional survey instruments, the USAID-developed Demographic Health Survey (DHS), and the Indonesian National Socio-economic survey (SUSENAS). In this work, we aim to understand how the frontier-data derived index can be used to inform anti-poverty programs in Indonesia and the Asia Pacific region. First, we unveil key features that affect the comparison between the traditional and non-traditional sources, such as the publishing time and authority and the granularity of the spatial aggregation of the data. Second, to provide operational input, we hypothesize how a re-distribution of resources based on the RWI map would impact a current social program, the Social Protection Card (KPS) of Indonesia and assess impact. In this hypothetical scenario, we estimate the percentage of Indonesians eligible for the program, which would have been incorrectly excluded from a social protection payment had the RWI been used in place of the survey-based wealth index. The exclusion error in that case would be 32.82%. Within the context of the KPS program targeting, we noted significant differences between the RWI map's predictions and the SUSENAS ground truth index estimates.

Socioeconomic inequalities in the 90-90-90 target, among people living with HIV in 12 sub-Saharan African countries - Implications for achieving the 95-95-95 target - Analysis of population-based surveys

Background

Inequalities undermine efforts to end AIDS by 2030. We examined socioeconomic inequalities in the 90-90-90 target among people living with HIV (PLHIV) -men (MLHIV), women (WLHIV) and adolescents (ALHIV).

Methods

We analysed the available Population HIV Impact Assessment (PHIA) survey data for each of the 12 sub-Saharan African countries, collected between 2015 and 2018 to estimate the attainment of each step of the 90-90-90 target by wealth quintiles. We constructed concentration curves, computed concentration indices (CIX) -a negative (positive) CIX indicated pro-poor (pro-rich) inequalities- and identified factors associated with, and contributing to inequality.

Findings

Socioeconomic inequalities in achieving the 90-90-90 target components among PLHIV were noted in 11 of the 12 countries surveyed: not in Rwanda. Awareness of HIV positive status was pro-rich in 5/12 countries (Côte d'Ivoire, Tanzania, Uganda, Malawi, and Zambia) ranging from CIX=0·085 (p< 0·05) in Tanzania for PLHIV, to CIX = 0·378 (p<0·1) in Côte d'Ivoire for ALHIV. It was pro-poor in 5/12 countries (Côte d'Ivoire, Ethiopia, Malawi, Namibia and Eswatini), ranging from CIX = -0·076 (p<0·05) for PLHIV in Eswatini, and CIX = -0·192 (p<0·05) for WLHIV in Ethiopia. Inequalities in accessing ART were pro-rich in 5/12 countries (Cameroun, Tanzania, Uganda, Malawi and Zambia) ranging from CIX=0·101 (p<0·05) among PLHIV in Zambia to CIX=0·774 (p<0·1) among ALHIV in Cameroun and pro-poor in 4/12 countries (Tanzania, Zimbabwe, Lesotho and Eswatini), ranging from CIX = -0·072 (p<0·1) among PLHIV in Zimbabwe to CIX = -0·203 (p<0·05) among WLHIV in Tanzania. Inequalities in HIV viral load suppression were pro-rich in 3/12 countries (Ethiopia, Uganda, and Lesotho), ranging from CIX = 0·089 (p< 0·1) among PLHIV in Uganda to CIX = 0·275 (p<0·01) among WLHIV in Ethiopia. Three countries (Tanzania CIX = 0·069 (p< 0·5), Uganda CIX = 0·077 (p< 0·1), and Zambia CIX = 0·116 (p< 0·1)) reported pro-rich and three countries (Côte d'Ivoire CIX = -0·125 (p< 0·1), Namibia CIX = -0·076 (p< 0·05), and Eswatini CIX = -0·050 (p< 0·05) pro-poor inequalities for the cumulative CIX for HIV viral load suppression. The decomposition analysis showed that age, rural-urban residence, education, and wealth were associated with and contributed the most to inequalities observed in achieving the 90-90-90 target.

Interpretation

Some PLHIV in 11 of 12 countries were not receiving life-saving HIV testing, treatment, or achieving HIV viral load suppression due to socioeconomic inequalities. Socioeconomic factors were associated with and explained the inequalities observed in the 90-90-90 target among PLHIV. Governments should scale up equitable 95-95-95 target interventions, prioritizing the reduction of age, rural-urban, education and wealth-related inequalities. Research is needed to understand interventions to reduce socioeconomic inequities in achieving the 95-95-95 target.

Funding

This study was supported by the Swiss National Science Foundation (grant 202660).

Women 'holding it' in urban India: Toilet avoidance as an under-recognized health outcome of sanitation insecurity

Emerging research on sanitation challenges in the Global South increasingly uncovers health and social impacts by gender, particularly lack of sanitation safety. Women may employ strategies to avoid urination or defecation ('holding it') in the absence of safe sanitation, but the practice is not well understood. We quantitatively analyze survey data on women from urban slums across three cities in Maharashtra, India whose households constructed a toilet through an intervention programme. We assess relationships between household versus shared sanitation, perceptions of safety, and women's toilet avoidance behaviours, including diet restriction. At baseline, women have more than three times the odds of reporting avoidance behaviours if they perceive a community toilet to be unsafe, even after controlling for other factors. Household water insecurity is also instrumental in the relationship between avoidance and lack of safety. Finally, avoidance exhibits a significant and major drop upon provision of a household toilet. This study provides substantial support for the prevalence of habitual toilet avoidance among vulnerable urban women without access to safe sanitation. We conclude with recommendations for policy approaches and call for more attention to the health repercussions of habitual toilet avoidance among women as a consequence of sanitation insecurity.

Assessing comparative asset-based measures of material wealth as predictors of physical growth and mortality

Social scientists and policymakers have increasingly relied on asset-based indices of household wealth to assess social disparities and to identify economically vulnerable populations in low- and middle-income countries. In the last decade, researchers have proposed a number of asset-based measures that permit global comparisons of household wealth across populations in different countries and over time. Each of these measures relies on different assumptions and indicators, and little is known about the relative performance of these measures in assessing disparities. In this study, we assess four comparative, asset-based measures of wealth-the Absolute Wealth Estimate (AWE), the International Wealth Index (IWI), the Comparative Wealth Index (CWI), and the "Standard of Living" portion of the Multi-Dimensional Poverty Index (MPI), along with a variable measuring television ownership-and compare how well each predicts health related variables such as women's BMI, children's height-for-age Z scores, and infant mortality at the household and survey level. Analyzing data from over 300 Demographic and Health surveys in 84 countries (n = 2,304,928 households), we found that AWE, IWI, CWI, MPI are all highly correlated (r = 0.7 to 0.9). However, IWI which is based on a common set of universally weighted indicators, typically best accounts for variation in all three health measures. We discuss the implications of these findings for choosing and interpreting these measures of wealth for different purposes.

Kin Ties and Market Integration in a Yucatec Mayan Village

The importance of kin relationships varies with socioecological demands. Among subsistence agriculturalists, people commonly manage fluctuations in food availability by relying on family members to share resources and pool labor. However, the process of market integration may disrupt these support networks, which may begin to carry costs or liabilities in novel market environments. The current study aims to address (1) how kin are distributed in household support networks (2) how kin support varies as households become more engaged in market activities, and (3) how variation in kin support is associated with income disparities within a Yucatec Maya community undergoing rapid market integration. Using long-term census data combined with social networks and detailed household economic data, we find that household support networks are primarily composed of related households. Second, households engaged predominantly in wage labor rely less on kin support than agricultural or mixed economy households. Finally, kin support is associated with lower household net income and income per capita. Understanding how kin support systems shift over the course of market integration and in the face of new opportunities for social and economic production provides a unique window into the social and economic drivers of human family formation.

Unpacking the "black box" of global food insecurity and mental health

Food insecurity is a global concern. While it was once characterized mainly as a problem of undernutrition, it is now recognized that a person may be food insecure without experiencing hunger. Numerous studies have demonstrated that food insecurity is strongly related to poor mental health around the world, but the mechanisms that underpin that relationship remain poorly understood. One body of research from nutritional sciences posits that nutrient deficiency impacts brain function, producing symptoms of depression and anxiety. Another body of research from the social sciences posits that the social consequences of having to eat non-preferred foods or obtain food in socially unacceptable ways may compromise mental health through stress. This study was designed to clarify the mechanisms linking food insecurity and mental health using case studies in rural Brazil and urban Ethiopia. Working with samples consisting of about 200 adult household decision-makers (mostly female) recruited between 2015 and 2019 at each site, we tested for nutritional and social mediation of the food insecurity-mental health relationship using multivariable linear regression and mediation analysis. Our analyses found no evidence of mediation in either setting. Moreover, there was no association between nutritional status variables and food insecurity. These findings suggest that food insecurity likely impacts mental health directly through forms of basic needs deprivation, such as worrying about where one's next meal will come from, rather than by acting as a social signal or even by impacting nutritional status. These results underscore the power of basic-needs deprivation for impacting mental health.

Less Expectation, Less Pain: Low Wealth Alleviates Sense of Unfairness

Objective wealth plays an important role in social interaction and economic decision making. Previous studies indicate that objective wealth of others may influence the way we participate in resources allocation. However, the effect of objective wealth on responses to fairness-related resource distribution is far from clear, as are the underlying neural processes. To address this issue, we dynamically manipulated proposers' objective wealth and analyzed participants' behavior as responders in a modified Ultimatum Game, during which event-related potentials were recorded. Behavioral results showed that participants were prone to reject unfair proposals although that rejection would reduce their own benefit. Importantly, participants were more likely to accept unfair offers from proposers with low objective wealth than from proposers with high objective wealth, with a drastic increase in acceptance rates of unfair offers from 32.79 to 50.59%. Further electrophysiological results showed that there was significantly enhanced feedback-related negativity amplitude toward proposers with high (relative to low) objective wealth for unfair offers. Furthermore, the late frontal negativity amplitude was larger for all the conditions which are not high-fair, which might be the only option that did not elicit any ambiguity. These findings suggest a strong role of proposers' objective wealth in modulating responders' behavioral and neural responses to fairness.

Socioeconomic status effects on health vary between rural and urban Turkana

Background and objectives

Understanding the social determinants of health is a major goal in evolutionary biology and human health research. Low socioeconomic status (often operationalized as absolute material wealth) is consistently associated with chronic stress, poor health and premature death in high-income countries. However, the degree to which wealth gradients in health are universal—or are instead made even steeper under contemporary, post-industrial conditions—remains poorly understood.

Methodology

We quantified absolute material wealth and several health outcomes among a population of traditional pastoralists, the Turkana of northwest Kenya, who are currently transitioning toward a more urban, market-integrated lifestyle. We assessed whether wealth associations with health differed in subsistence-level versus urban contexts. We also explored the causes and consequences of wealth-health associations by measuring serum cortisol, potential sociobehavioral mediators in early life and adulthood, and adult reproductive success (number of surviving offspring).

Results

Higher socioeconomic status and greater material wealth predicts better self-reported health and more offspring in traditional pastoralist Turkana, but worse cardiometabolic health and fewer offspring in urban Turkana. We do not find robust evidence for either direct biological mediators (cortisol) or indirect sociobehavioral mediators (e.g. adult diet or health behaviors, early life experiences) of wealth–health relationships in either context.

Conclusions and implications

While social gradients in health are well-established in humans and animals across a variety of socioecological contexts, we show that the relationship between wealth and health can vary within a single population. Our findings emphasize that changes in economic and societal circumstances may directly alter how, why and under what conditions socioeconomic status predicts health.

Lay Summary

High socioeconomic status predicts better health and more offspring in traditional Turkana pastoralists, but worse health and fewer offspring in individuals of the same group living in urban areas. Together, our study shows that under different economic and societal circumstances, wealth effects on health may manifest in very different ways.

Malnutrition, illness, poverty, and infant growth: A test of a syndemic hypothesis in Nuñoa, Peru

The concept of syndemics provides an important framework for understanding the complex interactions of biological and social conditions. Its use in public health and epidemiological research has increased substantially in the past ten years. Many syndemic analyses rely on the use of a sum score and subsequently fail to demonstrate biological interaction, leading some scholars to question the utility of the syndemic approach. Here, we utilize data from 86 mother/infant pairs from the rural district of Nuñoa, Peru to test a potential syndemic relationship among infection, malnutrition and infant growth. Between 2014 and 2015, surveys were conducted to assess household wealth, sanitation, dietary diversity, and reported illness, while anthropometric measures of mothers and infants were conducted to assess nutritional status via height-for-age and weight-for-height z-scores. Ethnographic insight was used in the selection of key economic variables including the development of an agricultural wealth index. We then assessed whether this constellation of health outcomes met the criteria for a syndemic by performing a quantitative analysis in which we tested for (1) an association between economic marginalization and high-risk environments; (2) the concentration of malnutrition, poor growth, and infection; and (3) biological interaction among these health outcomes. We found that economic measures were associated with pathogenic and nutritional risk, and that these in turn were associated with infectious disease, nutritional status, and growth. However, we did not find evidence that the proposed syndemic met criteria (2) or (3). We conclude that, despite being both socially and biologically plausible, a syndemic of malnutrition, poor growth, and infection did not exist in this context. This analysis moves syndemic research forward by demonstrating that such hypotheses are falsifiable, thus presenting a process by which they may be tested and lending support to the use of syndemic theory as an effective analytic framework.

Syndemics theory must take local context seriously: An example of measures for poverty, mental health, and food insecurity

Syndemics theory has provided insight into the ways that disease states and social adversity interact in marginalized populations to further disempower these groups. Yet, until recently, scholars have not identified how we might actually recognize and measure a syndemic, as opposed to a situation where there are multiple but non-interacting diseases present in a population. As researchers like those included in this special issue develop new methods for assessing syndemic interactions in diverse global populations, this short communication argues for the value of locally relevant measures. Poverty, mental health, food insecurity, and type 2 diabetes are used to illustrate the assessment of a potential syndemic from a locally grounded perspective. The discussion emphasizes the insights locally adapted measures can add and what information would be lost without their use.

Agricultural wealth better predicts mental wellbeing than market wealth among highly vulnerable households in Haiti: Evidence for the benefits of a multidimensional approach to poverty

OBJECTIVES

Lack of wealth (poverty) impacts almost every aspect of human biology. Accordingly, many studies include its assessment. In almost all cases, approaches to assessing poverty are based on lack of success within cash economies (eg, lack of income, employment). However, this operationalization deflects attention from alternative forms of poverty that may have the most substantial influence on human wellbeing. We test how a multidimensional measure of poverty that considers agricultural assets expands the explanatory power of the construct of household poverty by associating it with one key aspect of wellbeing: symptoms of mental health.

METHODS

We used the case of three highly vulnerable but distinctive communities in Haiti-urban, town with a rural hinterland, and rural. Based on survey responses from adults in 4055 geographically sampled households, linear regression models were used to predict depression and anxiety symptom levels controlling for a wide range of covariates related to detailed measures of material poverty, including cash-economy and agricultural assets, income, financial stress, and food insecurity.

RESULTS

Household assets related to the cash economy were significantly associated with lower (ie, better) depression scores (-0.7, [95% CI: -1.2 to, -0.1]) but unrelated to anxiety scores (-0.3 [95% CI: -0.8 to 0.3]). Agricultural wealth was significantly-and more strongly-associated with both reductions in depression symptoms (-1.4 [95% CI: -2.2 to -0.7]) and anxiety symptoms (-1.8 [95% CI: -2.6 to -1.0]). These associations were consistent across the three sites, except in the fully urban site in Port-au-Prince where level of depression symptoms was not significantly associated with household agricultural wealth.

CONCLUSIONS

Standard measures of poverty based on success in the cash economy can mask important associations between poverty and wellbeing, in this case related to household-level subsistence capacity and crucial food-producing household assets.

Household water insecurity may influence common mental disorders directly and indirectly through multiple pathways: Evidence from Haiti

Living in poverty significantly elevates risk of common mental disorders, but the underlying mechanisms are poorly specified. The stress of coping with household food insecurity is posed as one fundamental driver. While much less tested, the stress of failing to meet household water needs may also matter. We test (a) a hypothesized direct influence of household water insecurity (as household access to water sources and quality/quantity of water available in the household) on anxiety and depression symptoms. We also test (b) if there are indirect (mediated) effects of these aspects of water insecurity on common mental disorder symptom levels via household food insecurity, and (c) via their association with sanitation insecurity (lack of toilet). Data were collected in Haiti in June-July 2016 from 4,055 geographically-sampled households representing three distinct low-resource communities, purposefully differentiated as urban, town, and rural. We confirm that household water insecurity exerts a direct, strong independent effect on anxiety and depression levels, even once food insecurity and household assets are taken into account. Additionally, household water insecurity appears to have an indirect effect on anxiety and depression levels through its influence on household food insecurity. In the rural community sample, there is also support for the proposition of additional influence of household water on anxiety through its association with lack of sanitation. This Haitian case supports theories posing a central, influential role for household water insecurity as a potential driver of common mental illness in low-resource households via direct and indirect (food insecurity, sanitation) pathways.

Identifying the limits to socioeconomic influences on human growth

Contemporary humans occupy the widest range of socioeconomic environments in their evolutionary history, and this has revealed unprecedented environmentally-induced plasticity in physical growth. This plasticity also has limits, and identifying those limits can help researchers: (1) parse when population differences arise from environmental inputs or not and (2) determine when it is possible to infer socioeconomic disparities from disparities in body form. To illustrate potential limits to environmental plasticity, we analyze body mass index (BMI) and height data from 1,768,962 women and 207,341 men (20-49 y) living in households exhibiting 1000-fold variation in household wealth (51 countries, 1985-2017, 164 surveys) across four world regions-sub-Saharan Africa, South Asia, Latin America, and North Africa and the Middle East. We find that relationships of environmental inputs with both mean height and BMI bottom out at roughly 100-700 USD per capita household wealth (2011 international units, PPP), but at different basal BMIs and basal heights for different regions. The relationship with resources tops out for BMI at around 20 K-35 K USD for women, with growth potential due to environmental inputs in the range of 6.2-8.4 kg/m². By contrast, mean BMI for men and mean height for both sexes remains sensitive to environmental inputs even at levels far above the low- and middle-income samples studied here. This suggest that further work integrating comparable data from low- and high-income samples should provide a better picture of the full range of environmental inputs on human height and BMI. We conclude by discussing how neglecting such population-specific limits to human growth can lead to erroneous inferences about population differences.

Secondary data analysis to answer questions in human biology

Despite a growing number of publicly available datasets, the use of these datasets for secondary analyses in human biology is less common compared with other fields. Secondary analysis of existing data offers an opportunity for human biologists to ask unique questions through an evolutionary and biocultural lens, allowing for an analysis of cultural and structural nuances that affect health. Leveraging publicly available datasets for human biology research is a way for students and established researchers to complement their data collection, use existing data for master's and doctoral theses, pilot test questions, and use existing data to answer interesting new questions or explore questions at the population level. Here we describe where publicly available data are stored, highlighting some data repositories and how to access them. We then discuss how to decide which dataset is right, depending on the research question. Next, we describe steps to construct datasets, analytical considerations and methodological challenges, best practices, and limitations depending on the structure of the study. We close by highlighting a number of publicly available datasets that have been used by human biologists and other datasets that may be of interest to the community, including research that has been conducted on some example datasets.

Exploring unobserved household living conditions in multilevel choice modeling: An application to contraceptive adoption by Indian women

This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index-Household Living Conditions (HLC)-is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available.

Material wealth in 3D: Mapping multiple paths to prosperity in low- and middle- income countries

Material wealth is a key factor shaping human development and well-being. Every year, hundreds of studies in social science and policy fields assess material wealth in low- and middle-income countries assuming that there is a single dimension by which households can move from poverty to prosperity. However, a one-dimensional model may miss important kinds of prosperity, particularly in countries where traditional subsistence-based livelihoods coexist with modern cash economies. Using multiple correspondence analysis to analyze representative household data from six countries-Nepal, Bangladesh, Ethiopia, Kenya, Tanzania and Guatemala-across three world regions, we identify a number of independent dimension of wealth, each with a clear link to locally relevant pathways to success in cash and agricultural economies. In all cases, the first dimension identified by this approach replicates standard one-dimensional estimates and captures success in cash economies. The novel dimensions we identify reflect success in different agricultural sectors and are independently associated with key benchmarks of food security and human growth, such as adult body mass index and child height. The multidimensional models of wealth we describe here provide new opportunities for examining the causes and consequences of wealth inequality that go beyond success in cash economies, for tracing the emergence of hybrid pathways to prosperity, and for assessing how these different pathways to economic success carry different health risks and social opportunities.