ArticleAmerican journal of epidemiology2012
Revealing the complexity of health determinants in resource-poor settings.
Article in American journal of epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review.PLoS neglected tropical diseases · 2017Pooled it
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Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An epidemiologic systems analysis of diarrhea in children in Pakistan is presented. Application of additive Bayesian network modeling to 2005-2006 data from the Pakistan Social and Living Standards Measurement Survey reveals the complexity of child diarrhea as a disease system. The key distinction between standard analytical approaches, such as multivariable regression, and Bayesian network analyses is that the latter attempt to not only identify statistically associated variables but also, additionally and empirically, separate these into those directly and indirectly dependent upon the outcome variable. Such discrimination is vastly more ambitious but has the potential to reveal far more about key features of complex disease systems. Additive Bayesian network analyses across 41 variables from the Pakistan Social and Living Standards Measurement Survey identified 182 direct dependencies but with only 3 variables: 1) access to a dry pit latrine (protective; odds ratio = 0.67); 2) access to an atypical water source (protective; odds ratio = 0.49); and 3) no formal garbage collection (unprotective; odds ratio = 1.32), supported as directly dependent with the presence of diarrhea. All but 2 of the remaining variables were also, in turn, directly or indirectly dependent upon these 3 key variables. These results are contrasted with the use of a standard approach (multivariable regression).
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