Where do Overweight Women in Ghana Live? Answers from Exploratory Spatial Data Analysis

Spatial Clusters of Diabetes and Physical Inactivity: Do Neighborhood Characteristics in High and Low Clusters Differ?

This study aims to find spatial clusters of diabetes and physical inactivity among a sample population in Kerala, India, and evaluate built environment characteristics within the high and low spatial clusters. Spatial clusters with a higher and lower likelihood of diabetes and physical inactivity were identified using spatial scan statistic at various radii. Built environment characteristics were captured at panchayat level and 1600 m buffer around participant location using Geographical Information Systems. Comparison of sociodemographic and built environment factors was carried out for participants within high and low spatial clusters using t tests. Ten high and 8 low spatial clusters of diabetes and 17 high and 23 low spatial clusters of physical inactivity were identified in urban and rural areas of Kerala. Significant differences in built environment characteristics were consistent for low spatial clusters of diabetes and physical inactivity in the urban scenario. Built environment characteristics were found to be relevant in both urban and rural areas of Kerala. There is an urgent call to explore spatial clustering of non-communicable diseases in Kerala and undo the one-size-fits-all approach for prevention and control of non-communicable diseases.

Maternal Determinants of Birth Weight in Northern Ghana

OBJECTIVES

Weight at birth is usually considered as an indicator of the health status of a given society. As a result this study was designed to investigate the association between birth weight and maternal factors such as gestational weight gain, pre-pregnancy BMI and socio-economic status in Northern Ghana.

METHODS

The study was a facility-based cross-sectional survey conducted in two districts in the Northern region of Ghana. These districts were purposively sampled to represent a mix of urban, peri-urban and rural population. The current study included 419 mother-infant pairs who delivered at term (37-42 weeks). Mother's height, pre-pregnancy weight and weight changes were generated from the antenatal records. Questionnaires were administered to establish socio-economic and demographic information of respondents. Maternal factors associated with birth weight were examined using multiple and univariate regressions.

RESULTS

The mothers were generally well nourished before conception (Underweight 3.82%, Normal 57.76%, Overweight 25.06% and Obesity 13.37%) but approximately half of them could not gain adequate weight according to Institute of Medicine recommendations (Low weight gain 49.64%, Adequate weight gain 42.96% and Excessive weight gain 7.40%). Infants whose mothers had excess weight gain were 431g (95% CI 18-444) heavier compared to those whose mothers gained normal weight, while those whose mothers gained less were 479g (95% CI -682- (-276) lighter. Infants of mothers who were overweight and obese before conception were 246g (95% CI 87-405) and 595g (95% CI 375-815) respectively heavier than those of normal mothers, whereas those whose mothers were underweight were 305g (95% CI -565 -(-44) lighter. The mean birth weight observed was 2.98 ± 0.68 kg.

CONCLUSION

Our findings show that pre-pregnancy body mass index and weight gain during pregnancy influence birth weight. Therefore, emphasis should be placed on counseling and assisting pregnant women to stay within the recommended weight gain ranges.