{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T19:57:30Z","timestamp":1790884650439,"version":"4.1.0"},"reference-count":26,"publisher":"Cambridge University Press (CUP)","issue":"7","license":[{"start":{"date-parts":[[2007,1,2]],"date-time":"2007-01-02T00:00:00Z","timestamp":1167696000000},"content-version":"unspecified","delay-in-days":823,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Public Health Nutr."],"published-print":{"date-parts":[[2004,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec id=\"S136898000400103X_sec01\"><jats:title>Objective:<\/jats:title><jats:p>The effectiveness of geographic targeting in nutrition programmes depends largely on the degree to which malnutrition clusters within particular areas. This study investigates the extent to which the childhood nutrition indicators, stunting (height-for-age <jats:italic>Z<\/jats:italic>-score &lt;\u22122) and wasting (weight-for-height <jats:italic>Z<\/jats:italic>-score &lt;\u22122), are spatially clustered; this information is used to determine the implications of spatial clustering for the effectiveness of geographic targeting.<\/jats:p><\/jats:sec><jats:sec id=\"S136898000400103X_sec02\"><jats:title>Design:<\/jats:title><jats:p>Analysis of data from Demographic and Health Survey (DHS) results. Clustering is assessed by calculating intra-cluster correlation coefficients (ICCs). Estimating the proportion of malnourished children covered by a programme successfully targeting 10% of clusters with the highest malnutrition prevalences allows an assessment of the effectiveness of geographic targeting.<\/jats:p><\/jats:sec><jats:sec id=\"S136898000400103X_sec03\"><jats:title>Setting:<\/jats:title><jats:p>Fifty-eight DHS III (1992\u20131997) and DHS IV (1998\u20132001) reports from 46 developing countries.<\/jats:p><\/jats:sec><jats:sec id=\"S136898000400103X_sec04\"><jats:title>Subjects:<\/jats:title><jats:p>Pre-school children of mothers interviewed by DHS.<\/jats:p><jats:p>Main results: The extent of clustering of nutritional status was surprisingly low (median ICC for national samples: stunting=0.054, wasting=0.032) and most countries were characterised by having an ICC &lt;0.1 \u2013 i.e. low clustering \u2013 for childhood undernutrition (91% of countries for wasting and 78% for stunting). Our assessment of the effectiveness of geographic targeting showed that coverage was better for wasting than for stunting; for wasting, 23% of countries would achieve less than 20% coverage, compared with 76% of countries achieving less than 20% coverage for stunting. Coverage is dependent on the overall prevalence of malnutrition and the ICC.<\/jats:p><\/jats:sec><jats:sec id=\"S136898000400103X_sec05\"><jats:title>Conclusions:<\/jats:title><jats:p>Childhood nutritional status is determined at the household, or even individual, level; nutrition programmes that are geographically targeted may result in high levels of under-coverage and leakage, thereby compromising their cost-effectiveness; the lack of clustering questions the appropriateness of current nutrition interventions.<\/jats:p><\/jats:sec>","DOI":"10.1079\/phn2004632","type":"journal-article","created":{"date-parts":[[2004,10,13]],"date-time":"2004-10-13T22:28:46Z","timestamp":1097706526000},"page":"829-834","source":"Crossref","is-referenced-by-count":25,"title":["Do childhood growth indicators in developing countries cluster? Implications for intervention strategies"],"prefix":"10.1017","volume":"7","author":[{"given":"Bridget","family":"Fenn","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saul S","family":"Morris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chris","family":"Frost","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2007,1,2]]},"reference":[{"key":"S136898000400103X_ref015","first-page":"98","article-title":"A simplified general method for cluster-sample surveys of health in developing countries","volume":"44","author":"Bennett","year":"1991","journal-title":"World Health Statistics Quarterly"},{"key":"S136898000400103X_ref021","doi-asserted-by":"publisher","DOI":"10.1016\/0167-5877(94)90087-6"},{"key":"S136898000400103X_ref017","volume-title":"Survey Sampling","author":"Kish","year":"1965"},{"key":"S136898000400103X_ref001","unstructured":"1 Millennium Development Goals. Millennium Declaration 2000 [online]. Available at www.developmentgoals.org. Accessed 1 July 2002."},{"key":"S136898000400103X_ref012","volume-title":"Statistical Methods","author":"Snedecor","year":"1989"},{"key":"S136898000400103X_ref026","volume-title":"Patterns of Human Growth","author":"Bogin","year":"1999"},{"key":"S136898000400103X_ref009","volume-title":"Recommended Sample Design for 1999 Enquete Permanenet Aupres des M\u00e9nages","author":"Megill","year":"1999"},{"key":"S136898000400103X_ref008","volume-title":"Physical Status: The Use and Interpretation of Anthropometry","year":"1995"},{"key":"S136898000400103X_ref002","doi-asserted-by":"publisher","DOI":"10.1016\/0305-750X(94)90143-0"},{"key":"S136898000400103X_ref003","unstructured":"3 Hoddinott J . Targeting: Principles and Practice. Technical Report No. 9. Washington, DC: International Food Policy Research Institute, 1999."},{"key":"S136898000400103X_ref013","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780060408"},{"key":"S136898000400103X_ref007","volume-title":"NCHS Growth Curves for Children Birth\u201318 years","author":"Hamil","year":"1977"},{"key":"S136898000400103X_ref004","doi-asserted-by":"publisher","DOI":"10.1016\/S0306-9192(00)00029-4"},{"key":"S136898000400103X_ref005","doi-asserted-by":"crossref","DOI":"10.1016\/S0305-750X(99)00098-4","volume-title":"Does Geographic Targeting of Nutrition Interventions Make Sense in Cities? Evidence from Abidjan and Accra","author":"Morris","year":"1999"},{"key":"S136898000400103X_ref025","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.aje.a009904"},{"key":"S136898000400103X_ref022","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-5877(98)00076-2"},{"key":"S136898000400103X_ref010","unstructured":"10 Yansaneh IS , Eltinge JL , Empirical Studies of Design Effect Components in the Demographic and Health Surveys 2003 [online]. Available at http:\/\/unstats.un.org\/unsd\/hhsurveys\/final.htm. Accessed April 2003."},{"key":"S136898000400103X_ref014","unstructured":"14 Edwards TC , Moisen GG , Cutler DR . Assessing Map Accuracy in Remotely-Sensed, Ecoregion-Scale Cover Map [online], 1998. Available at http:\/\/ella.nr.usu.edu\/~utcoop\/tce\/publications\/rse98.pdf. Accessed 9 July 2002."},{"key":"S136898000400103X_ref006","first-page":"21","article-title":"The EPI cluster sampling method. A critical appraisal","volume":"55","author":"Bennett","year":"1993","journal-title":"Bulletin of the International Statistical Institute"},{"key":"S136898000400103X_ref016","unstructured":"16 Shackman G . Sample size and design effect. Presented at Albany Chapter of American Statistical Association March 2001 [online]. Available at http:\/\/faculty.smu.edu\/slstokes\/stat6380\/deff%20doc.pdf. 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