Journal
AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY
Volume 150, Issue 1, Pages 58-67Publisher
WILEY
DOI: 10.1002/ajpa.22128
Keywords
longitudinal growth data; growth curve; mixed effects modeling
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Funding
- National Institute of Health, USA
- Indian Council of Medical Research, India (Infant Feeding Study, Indo-USA joint initiative on Maternal Child Health Development Research) [5 R01 HD042219-S1]
- UNICEF, New York
- EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH &HUMAN DEVELOPMENT [R01HD042219] Funding Source: NIH RePORTER
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This article demonstrates the use of mixed effects models for characterizing individual and sample average growth curves based on serial anthropometric data. These models are advancement over conventional general linear regression because they effectively handle the hierarchical nature of serial growth data. Using body weight data on 70 infants in the Born in Bradford study, we demonstrate how a mixed effects model provides a better fit than a conventional regression model. Further, we demonstrate how mixed effects models can be used to explore the influence of environmental factors on the sample average growth curve. Analyzing data from 183 infant boys (aged 3-15 months) from rural South India, we show how maternal education shapes infant growth patterns as early as within the first 6 months of life. The presented analyses highlight the utility of mixed effects models for analyzing serial growth data because they allow researchers to simultaneously predict individual curves, estimate sample average curves, and investigate the effects of environmental exposure variables. Am J Phys Anthropol 150:58-67, 2013. (C)2012 Wiley Periodicals, Inc.
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