OBJECTIVE: The goal of the present study was to examine the influence of community environment on the nutritional status (weight-for-age and height-for-age) of children (aged 0-59 months) in Bangladesh. In addition, we tested the association between specific characteristics of community environments and child nutritional status. DESIGN: Cross-sectional survey. SETTING: The data are from the nationally representative 2004 Bangladesh Demographic and Health Survey. SUBJECTS: Respondents were ever-married women (aged 15-49 years) and their children (n 5731), residing in 361 communities. Child nutritional outcomes are physical measurements of weight-for-age and height-for-age in sd units. We considered the following attributes of community environments potentially related to child nutrition: (i) community water and sanitation infrastructure; (ii) availability of community health and education services; (iii) community employment and social participation; and (iv) education level of the community. RESULTS: Multilevel regression analysis showed that the spatial distribution of maternal and child covariates did not entirely explain the between-community variation in child nutritional status. The education level of the community emerged as the strongest community-level predictor of child height-for-age (highest v. lowest tertile, β = 0.18 (SE 0.07)) and weight-for-age (highest v. lowest tertile, β = 0.21 (SE 0.06)). In the height-for-age model, community employment and social participation also emerged as being statistically significant (highest v. lowest tertile, β = 0.13 (SE = 0.06)). CONCLUSIONS: The community environment influences child nutrition in Bangladesh, and maternal- and child-level covariates may fail to capture the entire influence of communities. Interventions to reduce child undernutrition in developing countries should take into consideration the wider community context.
OBJECTIVE: The goal of the present study was to examine the influence of community environment on the nutritional status (weight-for-age and height-for-age) of children (aged 0-59 months) in Bangladesh. In addition, we tested the association between specific characteristics of community environments and child nutritional status. DESIGN: Cross-sectional survey. SETTING: The data are from the nationally representative 2004 Bangladesh Demographic and Health Survey. SUBJECTS: Respondents were ever-married women (aged 15-49 years) and their children (n 5731), residing in 361 communities. Child nutritional outcomes are physical measurements of weight-for-age and height-for-age in sd units. We considered the following attributes of community environments potentially related to child nutrition: (i) community water and sanitation infrastructure; (ii) availability of community health and education services; (iii) community employment and social participation; and (iv) education level of the community. RESULTS: Multilevel regression analysis showed that the spatial distribution of maternal and child covariates did not entirely explain the between-community variation in child nutritional status. The education level of the community emerged as the strongest community-level predictor of child height-for-age (highest v. lowest tertile, β = 0.18 (SE 0.07)) and weight-for-age (highest v. lowest tertile, β = 0.21 (SE 0.06)). In the height-for-age model, community employment and social participation also emerged as being statistically significant (highest v. lowest tertile, β = 0.13 (SE = 0.06)). CONCLUSIONS: The community environment influences child nutrition in Bangladesh, and maternal- and child-level covariates may fail to capture the entire influence of communities. Interventions to reduce child undernutrition in developing countries should take into consideration the wider community context.
Authors: James A Fuller; Eduardo Villamor; William Cevallos; James Trostle; Joseph Ns Eisenberg Journal: Int J Epidemiol Date: 2016-03-02 Impact factor: 7.196
Authors: Ana María Osorio; Gustavo Alfonso Romero; Harold Bonilla; Luis Fernando Aguado Journal: Rev Saude Publica Date: 2018-07-26 Impact factor: 2.106