evidence-based blog of Filippo Dibari

Posts Tagged ‘nutrition survey’

Association between economic growth and early childhood undernutrition: evidence from 121 Demographic and Health Surveys from 36 low-income and middle-income countries

In Under-nutrition on April 2, 2014 at 5:06 pm

by  Sebastian Vollmer, Kenneth Harttgen, Malavika A Subramanyam, Jocelyn Finlay, Stephan Klasen, S V Subramanian

The Lancet Global Health. Volume 2, Issue 4, April 2014, Pages e225–e234

(download)

Abstract

Background

Economic growth is widely regarded as a necessary, and often sufficient, condition for the improvement of population health. We aimed to assess whether macroeconomic growth was associated with reductions in early childhood undernutrition in low-income and middle-income countries.

Methods

We analysed data from 121 Demographic and Health Surveys from 36 countries done between Jan 1, 1990, and Dec 31, 2011. The sample consisted of nationally representative cross-sectional surveys of children aged 0–35 months, and the outcome variables were stunting, underweight, and wasting. The main independent variable was per-head gross domestic product (GDP) in constant prices and adjusted for purchasing power parity. We used logistic regression models to estimate the association between changes in per-head GDP and changes in child undernutrition outcomes. Models were adjusted for country fixed effects, survey-year fixed effects, clustering, and demographic and socioeconomic covariates for the child, mother, and household.

Findings

Sample sizes were 462 854 for stunting, 485 152 for underweight, and 459 538 for wasting. Overall, 35·6% (95% CI 35·4–35·9) of young children were stunted (ranging from 8·7% [7·6–9·7] in Jordan to 51·1% [49·1–53·1] in Niger), 22·7% (22·5–22·9) were underweight (ranging from 1·8% [1·3–2·3] in Jordan to 41·7% [41·1–42·3] in India), and 12·8% (12·6–12·9) were wasted (ranging from 1·2% [0·6–1·8] in Peru to 28·8% [27·5–30·0] in Burkina Faso). At the country level, no association was seen between average changes in the prevalence of child undernutrition outcomes and average growth of per-head GDP. In models adjusted only for country and survey-year fixed effects, a 5% increase in per-head GDP was associated with an odds ratio (OR) of 0·993 (95% CI 0·989–0·995) for stunting, 0·986 (0·982–0·990) for underweight, and 0·984 (0·981–0·986) for wasting. ORs after adjustment for the full set of covariates were 0·996 (0·993–1·000) for stunting, 0·989 (0·985–0·992) for underweight, and 0·983 (0·979–0·986) for wasting. These findings were consistent across various subsamples and for alternative variable specifications. Notably, no association was seen between per-head GDP and undernutrition in young children from the poorest household wealth quintile. ORs for the poorest wealth quintile were 0·997 (0·990–1·004) for stunting, 0·999 (0·991–1·008) for underweight, and 0·991 (0·978–1·004) for wasting.

Interpretation

A quantitatively very small to null association was seen between increases in per-head GDP and reductions in early childhood undernutrition, emphasising the need for direct health investments to improve the nutritional status of children in low-income and middle-income countries.

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Shorter, Cheaper, Quicker, Better Linking Measures of Household Food Security to Nutritional Outcomes in Bangladesh, Nepal, Pakistan, Uganda, and Tanzania

In Under-nutrition on February 23, 2014 at 9:01 pm

by Sailesh Tiwari, Emmanuel Skoufias, Maya Sherpa

Policy Research Working Paper 6584

World Bank – August 2013

(download the entire doc)

world bank

Abstract

Using nationally representative household survey data from five countries—three from South Asia (Bangladesh, Pakistan, and Nepal) and two from Sub-Saharan Africa (Tanzania and Uganda)—this paper conducts a systematic assessment of the correlation between various measures of household food security and nutritional outcomes of children.The analysis, following the universally accepted and applied definition of food security, is based on some of the most commonly used indicators of food security.

The results show that the various measures of household food security do appear to carry significant signals about the nutritional status of children that reside within the household. This result holds even after the analysis controls for a wide array of other socio-economic characteristics of the households that are generally also thought to be associated with the quality of child nutrition. If using these food security indicators as proxy measures for the underlying nutritional status of children is of some interest, then the results show that simple, cost-effective, and easy-to-collect measures, such as the food consumption score or the dietary diversity score, may carry at least as much information as other measures, such as per capita expenditure or the starchy staple ratio, which require longer and costlier surveys with detailed food consumption modules.

Across five different countries in South Asia and Africa, the results suggest that the food consumption score, in particular, performs extremely well in comparison with all other measures from the perspective of nutritional targeting as well as for monitoring nutritional outcomes.

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Semi-Quantitative Evaluation of Access and Coverage (SQUEAC)/ Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC) Technical Reference (2012)

In Under-nutrition on May 26, 2013 at 9:07 am

from FANTA web site.

FANTA, in collaboration with Valid International, Action Against Hunger, Concern Worldwide, Tufts University, and Brixton Health, has developed a technical reference guide for two new low-resource coverage assessment methods for evaluating access and coverage of Community-Based Management of Acute Malnutrition (CMAM) and other selective feeding programs.

The first method—Semi-Quantitative Evaluation of Access and Coverage (SQUEAC)—combines routine program monitoring data, an array of qualitative information, and small-sample quantitative surveys. This combination is used to identify key issues affecting timely presentation at a clinic program uptake and provides an estimate of the level of program coverage achieved. SQUEAC can be used in real time, allowing the collected data to be of immediate practical use to adjust program design and implementation.

The second method—Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC)—is a small-sample quantitative method. The keys features of SLEAC are simplicity, low cost, and versatility. SLEAC can be used to map and estimate coverage over large areas.

The report is available for download in whole or parts. If you have difficulty downloading the PDFs, please send an email to fantamail@fhi360.org with your mailing address and we can send you the files via CD-rom.

PDF icon Download the report [7.09 mb]

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