Background. Over a fifth (21.9%) of children under 5
years of age in Haiti suffer from chronic malnutrition,
11.4% are underweight, and 5.1% suffer from acute
malnutrition. Léogâne Commune has one of the highest
under-five mortality rates in the country. Ordinary least
squares regression conducted using data from household
surveys to assess the impact of causal factors on child
undernutrition may mask important local variations.
Objective. To characterize the nutrition and health situation
of children 6 to 35 months of age in Léogâne Commune,
Haiti, using geographically weighted regression.
Methods. In July 2008, the Children’s Nutrition Program
of Haiti conducted a representative cross-sectional
household survey (N = 150) using a modified 33 × 6
alternative sampling design. Household questionnaires
were administered to caregivers of children 6 to 35
months of age and anthropometric measurements
were collected. Geographically weighted regression was
employed to evaluate how undernutrition (weight-forage)
and its household determinants vary across the
region. Geographically weighted regression and ordinary
least squares regression models were compared.
Results. The residuals of the ordinary least squares
regression model were spatially autocorrelated (Moran’s
I = 0.08, z = 1.90, p = .058), indicating that undernutrition
occurs in pockets rather than being evenly
distributed throughout the population. There was no
improvement in performance from the ordinary least
squares regression model to the geographically weighted
regression model.