Household and community socioeconomic and environmental determinants of child nutritional status in Cameroon
1 Harvard School of Public Health, Boston, MA, USA
2 Population Studies and Training Center, Brown University, Providence, RI, USA
BMC Public Health 2006, 6:98 doi:10.1186/1471-2458-6-98Published: 17 April 2006
Undernutrition is a leading cause of child mortality in developing countries, especially in sub-Saharan Africa. We examine the household and community level socioeconomic and environmental factors associated with child nutritional status in Cameroon, and changes in the effects of these factors during the 1990s economic crisis. We further consider age-specific effects of household economic status on child nutrition.
Child nutritional status was measured by weight-for-age (WAZ) and height-for-age (HAZ) z-scores. Data were from Demographic and Health Surveys conducted in 1991 and 1998. We used analysis of variance to assess the bivariate association between the explanatory factors and nutritional status. Multivariate, multilevel analyses were undertaken to estimate the net effects of both household and community factors.
Average WAZ and HAZ declined respectively from -0.70 standard deviations (SD), i.e. 0.70 SD below the reference median, to -0.83 SD (p = 0.006) and from -1.03 SD to -1.14 SD (p = 0.026) between 1991 and 1998. These declines occurred mostly among boys, children over 12 months of age, and those of low socioeconomic status. Maternal education and maternal health seeking behavior were associated with better child nutrition. Household economic status had an overall positive effect that increased during the crisis, but it had little effect in children under 6 months of age. Improved household (water, sanitation and cooking fuel) and community environment had positive effects. Children living in the driest regions of the country were consistently worst off, and those in the largest cities were best off.
Both household and community factors have significant impact on child health in Cameroon. Understanding these relationships can facilitate design of age- and community-specific intervention programs.