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.

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.

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.

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.

Delayed onset of lactation and risk of ending full breast-feeding early in rural Guatemala.

Mothers of infants (n = 328) born between 1996 and 1999 in four Guatemalan communities were interviewed every 2 wk until 6 mo postpartum (pp) to collect prospective breast-feeding data and assess the association between delayed (>3 d pp) onset of lactation (OL) and the risk of ending full breast-feeding. Cox proportional hazards regression was used to examine the association between delayed OL and the hazard of ending full breast-feeding in the first 6 mo, adjusted for potential confounders and effect modifiers. A significant interaction with community was found (community-specific hazard ratios: HR(A) = 2.87, 95% CI = 1.25, 6.60; HR(B) = 3.43, 95% CI = 1.55, 7.59; HR(C) = 0.26, 95% CI = 0.06, 1.14; HR(D) = 1.11, 95% CI = 0.44, 2.77). Supplementation before OL (preonset supplementation) was associated with delayed OL [odds ratio (OR) = 4.87, 95% CI = 2.29, 10.36] and an increased risk of ending full breast-feeding (HR = 1.49, 95% CI = 1.05, 2.11). In the two communities in which mothers who experienced delayed OL had a significantly greater risk of ending full breast-feeding than did mothers experiencing normal OL, the association between delayed OL and full breast-feeding was mediated in part by preonset supplementation. Further analyses suggest that this was due to delayed OL leading to nonbreast milk feeds, rather than to introduction of supplements delaying OL. We conclude that some mothers who experience delayed OL are less likely to continue full breast-feeding in the first 6 mo and that further research should examine the contextual factors that modify this relationship.