The relationship between altitude and BMI varies across low- and middle-income countries.

OBJECTIVES: Studies suggest that living at high altitude decreases obesity risk, but this research is limited to single-country analyses. We examine the relationship between altitude and body mass index (BMI) among women living in a diverse sample of low- and middle-income countries. MATERIALS AND METHODS: Using Demographic and Health Survey data from 1 583 456 reproductive age women (20-49 years) in 54 countries, we fit regression models predicting BMI and obesity by altitude controlling for a range of demographic factors-age, parity, breastfeeding status, wealth, and education. RESULTS: A mixed-effects model with country-level random intercepts and slopes predicts an overall -0.162 kg/m2 (95% CI -0.220, -0.104) reduction in BMI and lower odds of obesity (OR 0.90, 95% CI 0.87, 0.95) for every 200 m increase in altitude. However, countries vary dramatically in whether they exhibit a negative or positive association between altitude and BMI (34 countries negative, 20 positive). Mixed findings also arise when examining odds of obesity. DISCUSSION: We show that past findings of declining obesity risk with altitude are not universal. Increasing altitude predicts slightly lower BMIs at the global level, but the relationship within individual countries varies in both strength and direction.

One size does not fit all. How universal standards for normal height can hide deprivation and create false paradoxes.

Public health practitioners and social scientists frequently compare height against one-size-fits-all standards of human growth to assess well-being, deprivation, and disease risk. However, underlying differences in height can make some naturally tall populations appear well-off by universal standards, even though they live in severe states of deprivation. In this article, I describe the worldwide extent of these population differences in height and illustrate how using a universal yardstick to compare population height can create puzzling disparities (eg, between South Asia and sub-Saharan Africa) while also underestimating childhood stunting in specific world regions (eg, West Africa and Haiti). I conclude by discussing potential challenges of developing and implementing population-sensitive standards for assessing healthy development.

Learning from failures of protocol in cross-cultural research.

The many tools that social and behavioral scientists use to gather data from their fellow humans have, in most cases, been honed on a rarefied subset of humanity: highly educated participants with unique capacities, experiences, motivations, and social expectations. Through this honing process, researchers have developed protocols that extract information from these participants with great efficiency. However, as researchers reach out to broader populations, it is unclear whether these highly refined protocols are robust to cultural differences in skills, motivations, and expected modes of social interaction. In this paper, we illustrate the kinds of mismatches that can arise when using these highly refined protocols with nontypical populations by describing our experience translating an apparently simple social discounting protocol to work in rural Bangladesh. Multiple rounds of piloting and revision revealed a number of tacit assumptions about how participants should perceive, understand, and respond to key elements of the protocol. These included facility with numbers, letters, abstract number lines, and 2D geometric shapes, and the treatment of decisions as a series of isolated events. Through on-the-ground observation and a collaborative refinement process, we developed a protocol that worked both in Bangladesh and among US college students. More systematic study of the process of adapting common protocols to new contexts will provide valuable information about the range of skills, motivations, and modes of interaction that participants bring to studies as we develop a more diverse and inclusive social and behavioral science.

Disentangling basal and accrued height-for-age for cross-population comparisons.

OBJECTIVES: Current standards for comparing stunting across human populations assume a universal model of child growth. Such comparisons ignore population differences that are independent of deprivation and health outcomes. This article partitions variation in height-for-age that is specifically associated with deprivation and health outcomes to provide a basis for cross-population comparisons. MATERIALS AND METHODS: Using a multilevel model with a sigmoid relationship of resources and growth, we partition variation in height-for-age z-scores (HAZ) from 1.5 million children across 70 countries into two components: (1) "accrued HAZ" shaped by environmental inputs (e.g., undernutrition, infectious disease, inadequate sanitation, poverty) and (2) a country-specific "basal HAZ" independent of such inputs. We validate these components against population-level infant mortality rates and assess how these basal differences may affect cross-population comparisons of stunting. RESULTS: Basal HAZ differs reliably across countries (range of approximately 1.5 SD) and is independent of measures of infant mortality. By contrast, accrued HAZ captures stunting as impaired growth due to deprivation and is more closely associated with infant mortality than observed HAZ. Assessing stunting prevalence by accrued HAZ suggest that populations in West Africa and Haiti suffer much greater levels of stunting than indicated by observed HAZ. DISCUSSION: Current universal standards may dramatically underestimate stunting in populations with taller basal HAZ. Relying on observed HAZ rather than accrued HAZ may also lead to inappropriate cross-population comparisons, such as concluding that Haitian children enjoy better conditions for growth than do Indian or Guatemalan children.

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.

Comparing hemoglobin distributions between population-based surveys matched by country and time.

BACKGROUND: Valid measurement of hemoglobin is important for tracking and targeting interventions. This study compares hemoglobin distributions between surveys matched by country and time from The Demographic and Health Survey (DHS) Program and the Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project. METHODS: Four pairs of nationally representative surveys measuring hemoglobin using HemoCue® with capillary (DHS) or venous (BRINDA) blood were matched by country and time. Data included 17,719 children (6-59 months) and 21,594 non-pregnant women (15-49 y). Across paired surveys, we compared distributional statistics and anemia prevalence. RESULTS: Surveys from three of the four countries showed substantial differences in anemia estimates (9 to 31 percentage point differences) which were consistently lower in BRINDA compared to DHS (2 to 31 points for children, 1 to 16 points for women). CONCLUSION: We identify substantial differences in anemia estimates from surveys of similar populations. Further work is needed to identify the cause of these differences to improve the robustness of anemia estimates for comparing populations and tracking improvements over time.

Worldwide fertility declines do not rely on stopping at ideal parities.

A key demographic hypothesis has been that fertility declines rely on stopping at target parities, but emerging evidence suggests that women frequently reduce fertility without specific numeric targets. To assess the relative importance of these two paths to fertility decline, we develop a novel mixture model to estimate: (1) the proportion of women who stop at a target parity; and (2) mean completed fertility among those who do not. Applied to Demographic and Health Survey data from women aged 45-49 in 84 low- and middle-income countries, and to United States Census cohorts, the model shows considerable variation in the proportion stopping at specific parities (1-84 per cent). The estimates also show that declines in completed fertility are largely attributable to women who do not stop at target parities, suggesting that stopping at ideal parities may be less important than parity-independent decisions for a wide range of fertility transitions.

Testing ecological and universal models of body shape and child health using a global sample of infants and young children.

AIM: To test whether a risk of child illness is best predicted by deviations from a population-specific growth distribution or a universal growth distribution. SUBJECTS AND METHODS: Child weight for height and child illness data from 433 776 children (1-59 months) from 47 different low and lower income countries are used in regression models to estimate for each country the child basal weight for height. This study assesses the extent to which individuals within populations deviate from their basal slenderness. It uses correlation and regression techniques to estimate the relationship between child illness (diarrhoea, fever or cough) and basal weight for height, and residual weight for height. RESULTS: In bivariate tests, basal weight for height z-score did not predict the country level prevalence of child illness (r2 = -0.01, n = 47, p = 0.53), but excess weight for height did (r2 = 0.14, p < 0.01). At the individual level, household wealth is negatively associated with the odds that a child is reported as ill (beta = -0.04, p < 0.001, n = 433 776) and basal weight for height was not (beta = 0.20, p = 0.27). Deviations from country-specific basal weight for height were negatively associated with the likelihood of illness (beta = -0.13, p < 0.01), indicating a 13% reduction in illness risk for every 0.1 standard deviation increase in residual weight-for-height Conclusion: These results are consistent with the idea that populations may differ in their body slenderness, and that deviations from this body form may predict the risk of childhood illness.

Warmth, competence, and closeness may provide more empirically grounded starts for a theory of sentiments.

Gervais & Fessler dissect the folk concept of "contempt" to argue for a functionally integrated model of attitudes and emotions in the context of social relationships. Existing studies of how evaluations of warmth, competence, and closeness shape people's reactions and behaviors towards others may help in operationalizing and testing the proposed model.

Anti-fat discrimination in marriage more clearly explains the poverty-obesity paradox.

The target article proposes the insurance hypothesis as an explanation for higher levels of obesity among food-insecure women living in high-income countries. An alternative hypothesis based on anti-fat discrimination in marriage can also account for such correlations between poverty and obesity and is more consistent with finer-grained analyses by marital status, gender, and age.

Estimating the absolute wealth of households.

OBJECTIVE: To estimate the absolute wealth of households using data from demographic and health surveys. METHODS: We developed a new metric, the absolute wealth estimate, based on the rank of each surveyed household according to its material assets and the assumed shape of the distribution of wealth among surveyed households. Using data from 156 demographic and health surveys in 66 countries, we calculated absolute wealth estimates for households. We validated the method by comparing the proportion of households defined as poor using our estimates with published World Bank poverty headcounts. We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures. FINDINGS: The median absolute wealth estimates of 1,403,186 households were 2056 international dollars per capita (interquartile range: 723-6103). The proportion of poor households based on absolute wealth estimates were strongly correlated with World Bank estimates of populations living on less than 2.00 United States dollars per capita per day (R(2) = 0.84). Absolute wealth estimates were better predictors of anthropometric measures than relative wealth indexes. CONCLUSION: Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality.

The physiological cost of reproduction for rich and poor across 65 countries.

OBJECTIVES: One of the fundamental tradeoffs posited in life history theory is between storing energy for future reproduction versus spending that energy on current reproduction. However, past studies have shown variable and sometimes contradictory effects of reproduction on energy stores among women. METHODS: To examine how varying economic resources can account for these diverse findings, we applied mixed models to Demographic and Health Survey (DHS) data from 187,848 nulliparous and primiparous women of reproductive age (20-34 years) in 65 countries varying widely in economic resources. Using this approach, we tracked average trajectories of body mass through pregnancy and the post-partum period, and assessed how these trajectories varied by household wealth and breastfeeding. RESULTS: In all four wealth categories, sustained breastfeeding posed a substantial tradeoff with energy stores, reducing post-partum BMI by 0.5 to 1.0 kg m(-2) relative to non-breastfeeding women. However, among the wealthiest households (>6,400 USD per capita), this deficit was buffered substantially by greater pre-partum weight gain (+1.1 kg m(-2) compared to women from the poorest households). CONCLUSION: These findings show how the level of economic resources can systematically and profoundly shape a physiological tradeoff in reproduction, and can help account for past contradictory findings. More broadly, these results illustrate how integrating economic and energetic resources in a common framework can help clarify the apparently disparate weight-related outcomes of fertility in different countries.

Population level differences in adult body mass emerge in infancy and early childhood: evidence from a global sample of low and lower-income countries.

Many studies have linked measures of adult body shape and mass in ancient and contemporary populations to ecogeographical variables such as temperature and latitude. These results tend to support Bergmann's rule, which posits that bodies will be relatively less slender for their height in colder climates and more slender in warmer climates. Less well explored is the ontogeny of these population-level differences. Here we use data on infants and children from 46 low and lower income countries to test whether children's weight for height is associated with measures of temperature and latitude. We also test the hypothesis that children living in areas with greater pathogen prevalence will be lighter for their height because of life history trade-offs between investment in immune function and growth. Finally, we test whether population specific adult body mass predicts infant and child body mass, and whether this is independent of ecogeographical variables. Our results show that maximum monthly temperature explains 17% of children's weight for height while adult population-level body mass explains ∼44% (Table ). The measures of pathogen prevalence explain little of the variation in children's body shape (8%; P > 0.05). Our results suggest that population differences are consistent with Bergmann's rule but parental body shape explains more variance. Moreover, these population-level differences arise early in development, suggesting that any possible environmental influences occur in utero and/or result from epigenetic or population genetic differences.

Disentangling basal and accumulated body mass for cross-population comparisons.

Measures of human body mass confound 1) well-established population differences in body form and 2) exposure to obesogenic environments, posing challenges for using body mass index (BMI) in cross-population studies of body form, energy reserves, and obesity-linked disease risk. We propose a method for decomposing population BMI by estimating basal BMI (bBMI) among young adults living in extremely poor, rural households where excess body mass accumulation is uncommon. We test this method with nationally representative, cross-sectional Demographic and Health Surveys (DHS) collected from 69,916 rural women (20-24 years) in 47 low-income countries. Predicting BMI by household wealth, we estimate country-level bBMI as the average BMI of young women (20-24 years) living in rural households with total assets <400 USD per capita. Above 400 USD per capita, BMI increases with both wealth and age. Below this point, BMI hits a baseline floor showing little effect of either age or wealth. Between-country variation in bBMI (range of 4.3 kg m(-2) ) is reliable across decades and age groups (R(2) = 0.83-0.88). Country-level estimates of bBMI show no relation to diabetes prevalence or country-level GDP (R(2) < 0.05), supporting its independence from excess body mass. Residual BMI (average BMI minus bBMI) shows better fit with both country-level GDP (R(2) = 0.55 vs. 0.40) and diabetes prevalence (R(2) = 0.23 vs. 0.17) than does conventional BMI. This method produces reliable estimates of bBMI across a wide range of nationally representative samples, providing a new approach to investigating population variation in body mass.

Assessing the accuracy of two proxy measures for BMI in a semi-rural, low-resource setting in Guatemala.

BACKGROUND: Validation studies of self-reported BMI are limited to populations in high-income countries or urban settings. Here, we assess the accuracy of two proxy measures of measured height, weight and BMI - self-reported values and the Stunkard figure scale - in a semi-rural population in Guatemala. METHODS: Self-reported values and Stunkard figure selection were elicited prior to biometric measurements from a total of 175 non-pregnant women recruited based on a stratified random sample of households, with 92 women providing full data for validation across measures. RESULTS: 86.3% of participants self-reported weight and 62.3% height. Among those responding, self-reported weight is highly accurate though lower relationships for height contribute to error in reported BMI. The Stunkard scale has a higher response rate (97.1%) and while less accurate in predicting BMI values, more accurately predicts BMI categories. CONCLUSIONS: Self-reported measures are more accurate than the Stunkard scale in estimating BMI values, while the latter is more accurate in estimating BMI categories. High non-response rates and lower correlations between reported and measured height caution against using self-reported biometric data other than raw weight in low-resource settings.

Population differences in the relationship between height, weight, and adiposity: an application of Burton's model.

The study of human variation in adiposity and lean mass is important for understanding core processes in human evolution, and is increasingly a public health concern as the "obesity epidemic" expands globally. The dominant measure of population differences in adiposity is Body Mass Index (BMI), which suffers from systematic biases across populations due to variation in the relationship between true body fat, height and weight. Here we develop simplified corrections for such anthropometric-based measures of adiposity that can take into account this population variation. These corrections derive from a recent model proposed by Burton that assumes humans accrue mass in two ways-growth in height that adds bone and muscle, and growth in body fat and the ancillary fat-free mass (FFM) needed to support this additional body fat. We analyze two ethnically diverse datasets with dual X-ray absorptiometry-measured (DXA) fat mass, assessing the fit of Burton's model and deriving novel corrections based on estimated musculoskeletal slenderness. The resulting model provides excellent fit to fat mass within populations (average R2 = 0.92 for women and R2 = 0.83 for men). World populations differ dramatically in musculoskeletal slenderness (up to a difference of 4.4 kg/m2), as do men and women (differences of 3.3-4.5 kg/m2), leading to clear population corrections. These findings point to a conceptually straightforward tool for estimating true differences in adiposity across populations, and suggest an alternative to BMI that provides a more accurate and theoretically based estimate of body fat than that traditionally derived from height and weight measures.

Starting from scratch in a patrilocal society: how women build networks after marriage in rural Bangladesh.

Humans rely on both kin and non-kin social ties for a wide range of support. In patrilocal societies that practice village exogamy, women can face the challenge of building new supportive networks when they move to their husband's village and leave many genetic kin behind. In this paper, we track how women from 10 diverse communities in rural Bangladesh build supportive networks after migrating to their husband's village, comparing their trajectories with women who remained in their childhood village (Bengali: n = 317, Santal: n = 36, Hajong: n = 39, Mandi: n = 36). Women who migrated for marriage started with almost no adult close kin (mean 0.1) compared to women who remained in their childhood village (mean 2.4). However, immigrants compensated for the lack of genetic kin by a combination of close affinal kin and close friends. By their late 20s, immigrants reported substantially more non-kin friends than did non-immigrants (mean 1.4 versus 1.1) and a comparable number of supportive partners in several domains. These findings raise questions about the functions and quality of these different social ties and how different composition of supportive networks may provide different opportunities for women in these settings. This article is part of the theme issue 'Cooperation among women: evolutionary and cross-cultural perspectives'.

Political violence and mental health in Nepal: prospective study.

BACKGROUND: Post-conflict mental health studies in low-income countries have lacked pre-conflict data to evaluate changes in psychiatric morbidity resulting from political violence. AIMS: This prospective study compares mental health before and after exposure to direct political violence during the People's War in Nepal. METHOD: An adult cohort completed the Beck Depression Inventory and Beck Anxiety Inventory in 2000 prior to conflict violence in their community and in 2007 after the war. RESULTS: Of the original 316 participants, 298 (94%) participated in the post-conflict assessment. Depression increased from 30.9 to 40.6%. Anxiety increased from 26.2 to 47.7%. Post-conflict post-traumatic stress disorder (PTSD) was 14.1%. Controlling for ageing, the depression increase was not significant. The anxiety increase showed a dose-response association with conflict exposure when controlling for ageing and daily stressors. No demographic group displayed unique vulnerability or resilience to the effects of conflict exposure. CONCLUSIONS: Conflict exposure should be considered in the context of other types of psychiatric risk factors. Conflict exposure predicted increases in anxiety whereas socioeconomic factors and non-conflict stressful life events were the major predictors of depression. Research and interventions in post-conflict settings therefore should consider differential trajectories for depression v. anxiety and the importance of addressing chronic social problems ranging from poverty to gender and ethnic/caste discrimination.

Do economic constraints on food choice make people fat? A critical review of two hypotheses for the poverty-obesity paradox.

In low income countries worldwide, rising standards of living have spurred an unprecedented rise in obesity. However, in numerous wealthy countries the trend frequently reverses with poorer and less educated women more likely to be overweight than their wealthier compatriots. One prominent explanation for this reverse gradient is that economic deprivation leads to food choices which paradoxically increase energy intake. If true, this would challenge current evolutionary accounts for the modern obesity epidemic and have serious implications for how policy makers tackle increasing obesity in the US and worldwide. In this article, we critically review the hypothesis that deprivation leads people to choose cheaper foods which in turn foster overconsumption of energy. Though the hypothesis is consistent with numerous cross-sectional studies, available longitudinal studies from high-, middle-, and low-income countries show the reverse-that when populations experience resource declines, they experience either declines in BMI or decelerations in BMI growth. Most notably, the recent recession in the US coincides with a clear deceleration in women's obesity across income groups. We conclude by briefly reviewing other plausible explanations for the reverse gradient among women in developing countries. Finally, we discuss how theoretical perspectives and comparative, historical approaches from human biology are useful tools for examining the current wealth of hypotheses about obesity in population health.