Regional patterns of birthweights in Papua New Guinea in relation to diet, environment and socio-economic factors

Ann Hum Biol. 2002 Jan-Feb;29(1):74-88. doi: 10.1080/03014460110061003.

Abstract

Regional differences in mean birthweight in rural Papua New Guinea (PNG) and the importance of differences in family diet and maternal education and socio-economic status on such patterns were explored using birthweight data collected by the 1982/83 PNG National Nutrition Survey. A total of 6137 birthweight measurements from 85 PNG districts were available, representing 22% of all children included in the survey. The nature of possible selection biases are assessed and their implications discussed. Hierarchical Bayesian spatial models based on conditional autoregressive (CAR) priors were used to model spatial patterns in birthweights and their relation to different sets of covariates. Birthweights were found to exhibit striking geographical differences. Children from the central PNG highlands and from affluent lowland areas had the highest birthweights, while they were lowest in the (largely lowland) Sepik, Western, Madang and Milne Bay Provinces and in remote highland fringe areas. Maternal education, socio-economic status and diet were all important predictors, but only differences in family diet were correlated with the observed spatial patterns. The results of the present study highlight the importance of nutrition and socio-economic status in explaining differences in birthweights in PNG. Besides improving maternal health, interventions for improving birthweights in PNG should therefore aim at strengthening the economic base of rural populations and promote the cultivation and consumption of high quality foods.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Birth Weight*
  • Body Weight*
  • Diet / statistics & numerical data*
  • Environment*
  • Female
  • Food Supply / statistics & numerical data
  • Humans
  • Infant, Newborn
  • Male
  • Papua New Guinea
  • Pregnancy
  • Rural Population
  • Socioeconomic Factors
  • Topography, Medical
  • Weight Gain