LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Kandala, Ngianga-Bakwin; Fahrmeir, L.; Klasen, Stephan; Priebe, Jan (2009)
Publisher: John Wiley & Sons Ltd.
Languages: English
Types: Article
Subjects: RJ101

Classified by OpenAIRE into

mesheuropmc: parasitic diseases
Identifiers:doi:10.1002/psp.524
We investigate the geographical and socioeconomic determinants of childhood undernutrition in Malawi, Tanzania and Zambia, three neighbouring countries in southern Africa, using the 1992 Demographic and Health Surveys. In particular, we estimate models of undernutrition jointly for the three countries to explore regional patterns of undernutrition that transcend boundaries, while allowing for country-specific interactions. We use geo-additive regression models to flexibly model the effects of selected socioeconomic covariates and spatial effects. Inference is fully Bayesian based on recent Markov chain Monte Carlo techniques.\ud While the socioeconomic determinants generally confirm findings from the literature, we find distinct residual spatial patterns that are not explained by the socioeconomic determinants. In particular, there appears to be a belt transcending boundaries and running from southern Tanzania to northeastern Zambia which exhibits much worse undernutrition. These findings have important implications for planning, as well as in the search for left-out variables that might account for these residual spatial patterns.

Share - Bookmark

Cite this article