Estimating Prevalence of Overweight or Obese Children and Adolescents in Small Geographic Areas Using Publicly Available Data

Davila-Payan, Carlo; DeGuzman, Michael A.; Johnson, Karen M.; Serban, Nicoleta; Swann, Julie

doi:10.5888/pcd12.140229

Cited by 15 publications

(16 citation statements)

References 18 publications

(18 reference statements)

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“…Priority areas that cover 80% of the overweight or obese children in Georgia, as estimated using approaches described in Davila Payan et al [34]. Georgia, as estimated in the approach described in Davila Payan et al [34]. The method was validated by comparing it to school examination data in Arkansas, and we found that it generally performed well.…”

Section: Chronic Diseasesmentioning

confidence: 79%

“…A different aspect of obesity has been considered by Davila Payan et al [34]. Public health practitioners were interested in intervening to reduce overweight or obesity prevalence among children and youths.…”

Section: Chronic Diseasesmentioning

confidence: 99%

“…See Figure 3 for the priority areas in Figure 3. Priority areas that cover 80% of the overweight or obese children in Georgia, as estimated using approaches described in Davila Payan et al [34]. Georgia, as estimated in the approach described in Davila Payan et al [34].…”

Section: Chronic Diseasesmentioning

confidence: 99%

See 2 more Smart Citations

Research in Public Health for Efficient, Effective, and Equitable Outcomes

Ayer¹,

Keskinocak²,

Swann³

2014

Bridging Data and Decisions

Self Cite

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Public health focuses on preventing disease, prolonging life, and promoting health in a population, and there are many ways in which operations research and management science (OR/MS) researchers can contribute to improved decision making in this area. In this tutorial, we discuss examples of work in several areas of public health, including access and equity, disease screening, chronic diseases, and infectious diseases. In each of these areas, we give a brief overview of challenging issues and related literature, give a specific example of a research topic, and point to potential future directions for research. We describe several trends that could impact future public health research including population ageing and an increased use of electronic records. The tutorial is intended to introduce OR/MS researchers to the many opportunities for having a positive impact on specific populations and society overall, through OR/MS research related to public health.

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Section: Chronic Diseasesmentioning

confidence: 79%

Section: Chronic Diseasesmentioning

confidence: 99%

See 1 more Smart Citation

Research in Public Health for Efficient, Effective, and Equitable Outcomes

Ayer¹,

Keskinocak²,

Swann³

2014

Bridging Data and Decisions

Self Cite

View full text Add to dashboard Cite

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“…Our geographically detailed maps provide actionable evidence of where to geographically target interventions by identifying which neighborhoods experience the worst health outcomes. [13] These findings can also spur investigations of what specific health challenges these geographic areas face, which can help shape the interventions for minority communities that face the highest health disparities. [14] …”

Section: Discussionmentioning

confidence: 99%

Using Geospatial Analysis and Emergency Claims Data to Improve Minority Health Surveillance

Lee

Athens

et al. 2017

J. Racial and Ethnic Health Disparities

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Traditional methods of health surveillance often under-represent racial and ethnic minorities. Our objective was to use geospatial analysis and emergency claims data to estimate local chronic disease prevalence separately for specific racial and ethnic groups. We also performed a regression analysis to identify associations between median household income and local disease prevalence among Black, Hispanic, Asian, and White adults in New York City. The study population included individuals who visited an emergency department at least once from 2009 to 2013. Our main outcomes were geospatial estimates of diabetes, hypertension, and asthma prevalence by Census tract as stratified by race and ethnicity. Using emergency claims data, we identified 4.9 million unique New York City adults with 28.5% of identifying as Black, 25.2% Hispanic, and 6.1% Asian. Age-adjusted disease prevalence was highest among Black and Hispanic adults for diabetes (13.4 and 13.1%), hypertension (28.7 and 24.1%), and asthma (9.9 and 10.1%). Correlation between disease prevalence maps demonstrated moderate overlap between Black and Hispanic adults for diabetes (0.49), hypertension (0.57), and asthma (0.58). In our regression analysis, we found that the association between low income and high disease prevalence was strongest for Hispanic adults, whereas increases in income had more modest reductions in disease prevalence for Black adults, especially for diabetes. Our geographically detailed maps of disease prevalence generate actionable evidence that can help direct health interventions to those communities with the highest health disparities. Using these novel geographic approaches, we reveal the underlying epidemiology of chronic disease for a racially and culturally diverse population.

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“…Based on the previous statements and the literature you can find in many studies working the obesity influence factors, they have implemented several data mining techniques as you can find in (Davila-Payan et al, 2015;Manna and Jewkes, 2014;Adnan and Husain, 2012;Adnan et al, 2010;Dugan et al, 2015;Zhang et al, 2009;Suguna, 2016;Abdullah et al, 2016). Data mining is a discipline that studies massive data sources, with the objective of obtaining new information from it, to support decision making.…”

Section: Introductionmentioning

confidence: 99%