Patterns of low birth weight in greater Mexico City: A Bayesian spatio-temporal analysis. (September 2021)

• Record Type: Journal Article
• Authors: Lome-Hurtado, Alejandro; Li, Guangquan; Touza-Montero, Julia; White, Piran C.L.
• Is Part Of: Applied geography. Volume 134(2021)
• Publication Date: 2021-09
• Subjects: Child health -- Term low birth weight -- Bayesian spatio-temporal modelling -- Space-time variation -- Spatial random effects; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2021.102521
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: There is strong evidence that low birth weight (LBW) has a negative impact on infants' health. Children with LBW are more vulnerable to having disabilities. There are many studies on LBW, but only a small proportion has examined local geographical patterns in LBW and its determinants. LBW is a particular health concern in Mexico. The study aims to: (i) model the change in the LBW risk at the municipality level in Greater Mexico City, identifying municipalities with highest and lowest LBW risk; and (ii) explore the role of some socioeconomic and demographic risk factors in explaining LBW variations. We propose a Bayesian spatio-temporal analysis to control for space-time patterning of the data and for maternal age and prenatal care, both found to be important LBW determinants. Most of the high-risk municipalities are in the south-west and west of Greater Mexico City; and although for many of these municipalities the trend is stable, some present an increasing LBW risk over time. The results also identify those with medium-risk and with an increasing trend. These findings can support decision-makers in geographical targeting efforts to address spatial health inequalities, they may also facilitate a more proactive and cost-efficient approach to reduce LBW risk. Highlights: Spatial-temporal analysis was executed to assess municipalities with different level of risk. High-risk municipalities of LWB were identified. Some high-risk municipalities presented an increasing trend. Decision-makers need to focus in such high-risk areas.