Literature DB >> 8744995

Determinants of variability among nations in child growth.

E A Frongillo1, K M Hanson.   

Abstract

This cross-national study aimed at understanding variability in growth among nations and its determinants. It examined the variability of growth among nations, the factors most important for explaining this variability, how these factors jointly determine growth, and the consistency of the patterns and relationships. A conceptual model was adapted from U. Jonsson. National data on height and weight of children, sex, ethnicity, and 15 social, economic, health, education, and political factors were combined from three secondary sources. A sequence of multiple linear regression models was used with three age groups: 1-2, 3-5, and 6-10 years. Substantial variability in growth among nations was seen in comparison to that within nations. Regression models with sex, ethnicity, food security, maternal and child care, and health services and environment explained a large percentage of this variability. Institutions, politics/ideology, economic structure, and potential resources contributed little additionally to the models. Ethnic differences among nations were observed and persisted even when models controlled for other factors, but should not necessarily be interpreted as genetic differences. Determinants for height, weight, and weight adjusted for height were somewhat different. Adjustment for only previous growth and sex explained about 90% of variability in growth, supporting the assumption that growth patterns are generally established early in life. As policy decisions and programmes addressing mild-to-moderate malnutrition are increasingly considered, the implications of cross-national variability in growth may assume greater importance. Future work should examine simultaneously the effects of national, community, family, and individual characteristics on growth using data from individuals in a number of nations.

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Year:  1995        PMID: 8744995     DOI: 10.1080/03014469500004082

Source DB:  PubMed          Journal:  Ann Hum Biol        ISSN: 0301-4460            Impact factor:   1.533


  13 in total

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2.  Secular changes in the height of Polish schoolboys from 1955 to 1988.

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3.  Growth pattern of primary schoolchildren in Benghazi, Libya.

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4.  Examining the socioeconomic effects on third molar maturation in a Portuguese sample of children, adolescents and young adults.

Authors:  J L Carneiro; I M Caldas; A Afonso; H F V Cardoso
Journal:  Int J Legal Med       Date:  2016-10-19       Impact factor: 2.686

5.  Left atrial size and function in a South Asian population and their potential influence on the risk of atrial fibrillation.

Authors:  James O'Neill; Peter P Swoboda; Sven Plein; Muzahir H Tayebjee
Journal:  Clin Cardiol       Date:  2018-10-21       Impact factor: 2.882

6.  The weight and height percentiles in 6-18 year old children in Kayseri and comparison with Istanbul data.

Authors:  Nihal Hatipoğlu; Selim Kurtoğlu; Ahmet Oztürk; Mümtaz Mustafa Mazıcıoğlu
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7.  Prevalence of short stature in Saudi children and adolescents.

Authors:  Mohammad I El Mouzan; Abdullah S Al Herbish; Abdullah A Al Salloum; Peter J Foster; Ahmad A Al Omer; Mansour M Qurachi
Journal:  Ann Saudi Med       Date:  2011 Sep-Oct       Impact factor: 1.526

8.  Regional prevalence of short stature in Saudi school-age children and adolescents.

Authors:  Mohammad I El Mouzan; Abdullah S Al Herbish; Abdullah A Al Salloum; Ahmad A Al Omer; Mansour M Qurachi
Journal:  ScientificWorldJournal       Date:  2012-03-12

9.  Malnutrition and Its Associated Factors among Rural School Children in Fayoum Governorate, Egypt.

Authors:  Wafaa Y Abdel Wahed; Safaa K Hassan; Randa Eldessouki
Journal:  J Environ Public Health       Date:  2017-10-23

10.  Determinants of persistent underweight among children, aged 6-35 months, after huge economic development and improvements in health services in Oman.

Authors:  Deena Alasfoor; Pierre Traissac; Agnès Gartner; Francis Delpeuch
Journal:  J Health Popul Nutr       Date:  2007-09       Impact factor: 2.000

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