Jewel Gausman1, Jessica M Perkins2, Hwa-Young Lee3, Ivan Mejia-Guevara4, You-Seon Nam5, Jong-Koo Lee6, Juhwan Oh7, S V Subramanian8. 1. Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA. 2. Department of Human and Organizational Development, Peabody College, Vanderbilt University, Nashville, Tennessee, USA; Vanderbilt Institute of Global Health, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 3. Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; JW Lee Center for Global Medicine, Seoul National University, College of Medicine, Seoul, Republic of Korea. 4. Center for Population Health Sciences, Stanford University, Stanford, California, USA; Department of Biology, Stanford University, Stanford, California, USA; Department of Demography, University of California at Berkeley, Berkeley, California, USA. 5. JW Lee Center for Global Medicine, Seoul National University, College of Medicine, Seoul, Republic of Korea. 6. JW Lee Center for Global Medicine, Seoul National University, College of Medicine, Seoul, Republic of Korea; Department of Family Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea. 7. JW Lee Center for Global Medicine, Seoul National University, College of Medicine, Seoul, Republic of Korea. Electronic address: oh328@snu.ac.kr. 8. Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Harvard Center for Population and Development Studies, Harvard University, Cambridge, Massachusetts, USA.
Abstract
OBJECTIVE: Dietary diversity (DD) measures dietary variation in children. Factors at the child, community, and state levels may be associated with poor child nutritional outcomes. However, few studies have examined the role of macro-level factors on child DD. This study seeks to 1) describe the distribution of child DD in India, 2) examine the variation in DD attributable to the child, community and state levels, and 3) explore the relationship between community socioeconomic context and child DD. RESEARCH METHODS AND PROCEDURES: Using nationally representative data from children aged 6-23 months in India, multilevel models were used to determine the associations between child DD and individual- and community-level factors. RESULTS: There was substantial variation in child DD score across demographic and socioeconomic characteristics. In an age and sex-only adjusted regression model, the largest portion of variation in child DD was attributable to the child level (75%) while the portions of variance attributable to the community-level and state level were similar to each other (15% and 11%). Including individual-level socioeconomic factors explained 35.6 percent of the total variation attributed to child DD at the community level and 24.8 percent of the total variation attributed to child DD at the state level. Finally, measures of community disadvantage were associated with child DD in when added to the fully adjusted model. CONCLUSIONS: This study suggests that both individual and contextual factors are associated with child DD. These results suggest that a population-based approach combined with a targeted intervention for at-risk children may be needed to improve child DD in India.
OBJECTIVE: Dietary diversity (DD) measures dietary variation in children. Factors at the child, community, and state levels may be associated with poor child nutritional outcomes. However, few studies have examined the role of macro-level factors on child DD. This study seeks to 1) describe the distribution of child DD in India, 2) examine the variation in DD attributable to the child, community and state levels, and 3) explore the relationship between community socioeconomic context and child DD. RESEARCH METHODS AND PROCEDURES: Using nationally representative data from children aged 6-23 months in India, multilevel models were used to determine the associations between child DD and individual- and community-level factors. RESULTS: There was substantial variation in child DD score across demographic and socioeconomic characteristics. In an age and sex-only adjusted regression model, the largest portion of variation in child DD was attributable to the child level (75%) while the portions of variance attributable to the community-level and state level were similar to each other (15% and 11%). Including individual-level socioeconomic factors explained 35.6 percent of the total variation attributed to child DD at the community level and 24.8 percent of the total variation attributed to child DD at the state level. Finally, measures of community disadvantage were associated with child DD in when added to the fully adjusted model. CONCLUSIONS: This study suggests that both individual and contextual factors are associated with child DD. These results suggest that a population-based approach combined with a targeted intervention for at-risk children may be needed to improve child DD in India.
Authors: Jacob P Beckerman-Hsu; Pritha Chatterjee; Rockli Kim; Smriti Sharma; S V Subramanian Journal: J Glob Health Date: 2020-12 Impact factor: 4.413