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Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks

OBJECTIVE: This paper introduces a novel method to evaluate the local impact of behavioral scenarios on disease prevalence and burden with representative individual level data while ensuring that the model is in agreement with the qualitative patterns of global relative risk (RR) estimates. The meth...

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Autores principales: Ali, Ozden Gur, Ghanem, Angi Nazih, Ustun, Bedirhan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219750/
https://www.ncbi.nlm.nih.gov/pubmed/32401782
http://dx.doi.org/10.1371/journal.pone.0232951
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author Ali, Ozden Gur
Ghanem, Angi Nazih
Ustun, Bedirhan
author_facet Ali, Ozden Gur
Ghanem, Angi Nazih
Ustun, Bedirhan
author_sort Ali, Ozden Gur
collection PubMed
description OBJECTIVE: This paper introduces a novel method to evaluate the local impact of behavioral scenarios on disease prevalence and burden with representative individual level data while ensuring that the model is in agreement with the qualitative patterns of global relative risk (RR) estimates. The method is used to estimate the impact of behavioral scenarios on the burden of disease due to ischemic heart disease (IHD) and diabetes in the Turkish adult population. METHODS: Disease specific Hierarchical Bayes (HB) models estimate the individual disease probability as a function of behaviors, demographics, socio-economics and other controls, where constraints are specified based on the global RR estimates. The simulator combines the counterfactual disease probability estimates with disability adjusted life year (DALY)-per-prevalent-case estimates and rolls up to the targeted population level, thus reflecting the local joint distribution of exposures. The Global Burden of Disease (GBD) 2016 study meta-analysis results guide the analysis of the Turkish National Health Surveys (2008 to 2016) that contain more than 90 thousand observations. FINDINGS: The proposed Qualitative Informative HB models do not sacrifice predictive accuracy versus benchmarks (logistic regression and HB models with non-informative and numerical informative priors) while agreeing with the global patterns. In the Turkish adult population, Increasing Physical Activity reduces the DALYs substantially for both IHD by 8.6% (6.4% 11.2%), and Diabetes by 8.1% (5.8% 10.6%), (90% uncertainty intervals). Eliminating Smoking and Second-hand Smoke predominantly decreases the IHD burden 13.1% (10.4% 15.8%) versus Diabetes 2.8% (1.1% 4.6%). Increasing Fruit and Vegetable Consumption, on the other hand, reduces IHD DALYs by 4.1% (2.8% 5.4%) while not improving the Diabetes burden 0.1% (0% 0.1%). CONCLUSION: While the national RR estimates are in qualitative agreement with the global patterns, the scenario impact estimates are markedly different than the attributable risk estimates from the GBD analysis and allow evaluation of practical scenarios with multiple behaviors.
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spelling pubmed-72197502020-05-29 Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks Ali, Ozden Gur Ghanem, Angi Nazih Ustun, Bedirhan PLoS One Research Article OBJECTIVE: This paper introduces a novel method to evaluate the local impact of behavioral scenarios on disease prevalence and burden with representative individual level data while ensuring that the model is in agreement with the qualitative patterns of global relative risk (RR) estimates. The method is used to estimate the impact of behavioral scenarios on the burden of disease due to ischemic heart disease (IHD) and diabetes in the Turkish adult population. METHODS: Disease specific Hierarchical Bayes (HB) models estimate the individual disease probability as a function of behaviors, demographics, socio-economics and other controls, where constraints are specified based on the global RR estimates. The simulator combines the counterfactual disease probability estimates with disability adjusted life year (DALY)-per-prevalent-case estimates and rolls up to the targeted population level, thus reflecting the local joint distribution of exposures. The Global Burden of Disease (GBD) 2016 study meta-analysis results guide the analysis of the Turkish National Health Surveys (2008 to 2016) that contain more than 90 thousand observations. FINDINGS: The proposed Qualitative Informative HB models do not sacrifice predictive accuracy versus benchmarks (logistic regression and HB models with non-informative and numerical informative priors) while agreeing with the global patterns. In the Turkish adult population, Increasing Physical Activity reduces the DALYs substantially for both IHD by 8.6% (6.4% 11.2%), and Diabetes by 8.1% (5.8% 10.6%), (90% uncertainty intervals). Eliminating Smoking and Second-hand Smoke predominantly decreases the IHD burden 13.1% (10.4% 15.8%) versus Diabetes 2.8% (1.1% 4.6%). Increasing Fruit and Vegetable Consumption, on the other hand, reduces IHD DALYs by 4.1% (2.8% 5.4%) while not improving the Diabetes burden 0.1% (0% 0.1%). CONCLUSION: While the national RR estimates are in qualitative agreement with the global patterns, the scenario impact estimates are markedly different than the attributable risk estimates from the GBD analysis and allow evaluation of practical scenarios with multiple behaviors. Public Library of Science 2020-05-13 /pmc/articles/PMC7219750/ /pubmed/32401782 http://dx.doi.org/10.1371/journal.pone.0232951 Text en © 2020 Ali et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ali, Ozden Gur
Ghanem, Angi Nazih
Ustun, Bedirhan
Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks
title Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks
title_full Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks
title_fullStr Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks
title_full_unstemmed Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks
title_short Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks
title_sort estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219750/
https://www.ncbi.nlm.nih.gov/pubmed/32401782
http://dx.doi.org/10.1371/journal.pone.0232951
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