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Social and spatial processes associated with childhood diarrheal disease in Matlab, Bangladesh - PubMed

Social and spatial processes associated with childhood diarrheal disease in Matlab, Bangladesh

Carolina Perez-Heydrich et al. Health Place. 2013 Jan.

Abstract

We develop novel methods for conceptualizing geographic space and social networks to evaluate their respective and combined contributions to childhood diarrheal incidence. After defining maternal networks according to direct familial linkages between females, and road networks using satellite imagery of the study area, we use a spatial econometrics model to evaluate the significance of correlation terms relating childhood diarrheal incidence to the incidence observed within respective networks. Disease was significantly clustered within road networks across time, but only inconsistently correlated within maternal networks. These methods could be widely applied to systems in which both social and spatial processes jointly influence health outcomes.

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Figures

Figure 1
Figure 1

Map of (A) road network and (B) diarrheal disease incidence within the study area, Matlab, Bangladesh, located about 55 kilometers southeast of Dhaka. Roads were digitized using satellite imagery provided by Google Earth (Google, 2012). Total bari-level incidence per 1,000 people between 1999 and 2003 are plotted in (B) using graduated symbols, whereby smaller points represent baris with lower disease incidence and larger points represent baris with high disease incidence during the study period. Village boundaries are also overlaid in (B).

Figure 2
Figure 2

Maternal network graph indicating the structure of family linkages within sample baris. The above graph depicts a subset of T, the maternal network adjacency matrix. Colors and sizes of nodes correspond to total number of childhood diarrheal cases observed in a given bari. Nodes are connected by edges that depict which individual baris are linked according to family ties.

Figure 3
Figure 3

Moran's I statistics used to determine the significance of spatial clustering of diarrheal cases road networks between 1999–2003. Points highlighted in black indicate significant clustering effects. The horizontal dashed line represents the expected value of the Moran coefficient under the null hypothesis of no autocorrelation in geographic space. Index values that are greater than that expected by random chance (assuming a significance level of 0.05) are represented by filled dots. Childhood diarrheal disease incidence significantly clustered within road networks across four of five years.

Figure 4
Figure 4

Estimates of the lag simultaneous autoregressive lag coefficient (ρ) and standard errors. Points highlighted in black indicate estimates that were significantly different from zero. Overall, social structure was only significantly associated with childhood diarrheal incidence for two of the five years.

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