Use of Spatial Epidemiology and Hot Spot Analysis to Target Women Eligible for Prenatal Women, Infants, and Children Services

Stopka, Thomas J.; Krawczyk, Christopher; Gradziel, Pat; Geraghty, Estella M.

doi:10.2105/ajph.2013.301769

Cited by 48 publications

(29 citation statements)

References 17 publications

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“…Los SIG pueden ser aplicados en el análisis de la distribución geoespacial de la anemia gestacional, y ser una herramienta de ayuda para la implementación de acciones preventivo-promocionales, así como en el diseño y seguimiento de programas y políticas en salud orientadas a mejorar la salud materna. Una metodología aplicada dentro de este tipo de análisis es el índice de Moran, el cual, mediante la evaluación de la correlación espacial, permite determinar la presencia de conglomerados poblacionales donde la necesidad de abordar los problemas de salud sea prioritaria (15) . Sin embargo, en el Perú, la utilización de estos sistemas es muy limitada y aún no han sido lo suficientemente usados para el estudio del problema de la anemia gestacional.…”

Section: Introductionunclassified

Análisis espacial de la anemia gestacional en el Perú, 2015.

Hernández-Vasquéz

Azañedo

Antiporta

et al. 2017

Rev Peru Med Exp Salud Publica

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Objetivos. Establecer las prevalencias regionales e identificar conglomerados distritales con altas prevalencias de anemia en gestantes atendidas en los establecimientos de salud públicos del Perú en el 2015. Materiales y métodos. Se realizó un estudio ecológico de datos de gestantes con anemia, registrados en el Sistema de Información del Estado Nutricional (SIEN), que fueron atendidas en 7703 establecimientos públicos de salud durante el 2015. Se calcularon prevalencias de anemia gestacional regionales y distritales. Mediante el índice de Moran se identificaron conglomerados distritales con alta prevalencia de anemia gestacional. Resultados. Se recolectó información de 311 521 gestantes, distribuidas en 1638 distritos del Perú. La prevalencia nacional de anemia fue de 24,2% (IC 95%: 24,0-24,3) y 30,5% en el área rural vs. 22,0% en el área urbana. Las regiones de Huancavelica (45,5%; IC 95%: 44,2-46,7), Puno (42,8%; IC 95%: 41,9-43,7), Pasco (38,5%; IC 95%: 36,9-40,0), Cusco (36,0%; IC 95%: 35,8) y Apurímac (32,0%; IC 95%: 30,8-33,1) tuvieron las mayores prevalencias de anemia. El índice local de Moran identificó 202 distritos (12,3%) (44 urbanos y 158 rurales) de alta prioridad (alto-alto o hot spots) situados en Ancash, Apurímac, Arequipa, Ayacucho, Cajamarca, Cusco, Huancavelica, Huánuco, Junín, La Libertad, Lima, Pasco y Puno, que muestran conglomerados distritales con altas prevalencias. Conclusiones. La anemia gestacional en Perú concentra sus mayores prevalencias en las áreas rural y sur de la sierra. Los conglomerados distritales con altas prevalencias de anemia gestacional coinciden con las zonas de alta prevalencia regional. Palabras clave: Sistemas de Información Geográfica; Anemia; Mujeres Embarazadas; Embarazo; Perú (fuente: DeCS BIREME). SPATIAL ANALYSIS OF GESTATIONAL ANEMIA IN PERU, 2015 ABSTRACTObjectives. To establish regional prevalences of anemia in pregnant women receiving care at public clinics in Peru in 2015 and identify high-prevalence district conglomerates. Materials and Methods. An ecological study was carried out on data from pregnant women with anemia registered on the Nutritional Status Information System (SIEN) who received care in 7703 public clinics in 2015. Regional and district prevalences of gestational anemia were calculated. District conglomerates with a high prevalence of gestational anemia were identified using the Moran Index. Results. Information was gathered from 311,521 pregnant women distributed in 1638 districts in Peru. The national prevalence of anemia was 24.2% (95% confidence interval [95% CI]: 24.0-24.3%), the rural prevalence was 30.5%, and the urban prevalence was 22.0%. The regions of Huancavelica (45.5%; 95% CI: 44.2-46.7%), Puno (42.8%; 95% CI: 41.9-43.7%), Pasco (38.5%; 95% CI: 36.9-40.0%), Cusco (36.0%; 95% CI: 35.3-36.8%), and Apurímac (32.0%; 95% CI: 30.8-33.1%) had the highest prevalences of anemia. The local Moran Index identified 202 high-priority districts (hot spots) (12.3% of total; 44 urban and 158 rural) located in Ancash, Apurímac, Arequipa, ...

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Section: Introductionunclassified

Análisis espacial de la anemia gestacional en el Perú, 2015.

Hernández-Vasquéz

Azañedo

Antiporta

et al. 2017

Rev Peru Med Exp Salud Publica

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“…Similar geospatial analyses have been used in NC to map the distribution of dental Medicaid providers available to provide pediatric oral health services (Kranz, Lee, Divaris, Baker, & Vann, 2014) and in California to determine hot spots of WIC-eligible nonparticipants to improve outreach efforts (Stopka, Krawczyk, Gradziel, & Geraghty, 2014). Visual representations of data to highlight the association between the availability of providers and health outcomes or to identify regional disparities in access provide easily interpretable evidence to policymakers seeking to reduce differential access to health care services.…”

Section: Discussionmentioning

confidence: 99%

Improving Access to Medical Lactation Support and Counseling: Building the Case for Medicaid Reimbursement

Wouk

Chetwynd

Vitaglione

et al. 2016

Matern Child Health J

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Objectives While the Affordable Care Act improves access to lactation services for many women across the US, low-income mothers in states without Medicaid expansion lack coverage for lactation support. As these states consider individual Medicaid reimbursement policies, the availability, effectiveness, and cost-benefit of lactation services must be evaluated. We conducted such an analysis for low-income mothers in North Carolina (NC), providing a model for other states. Methods First, we analyzed the distribution of NC International Board Certified Lactation Consultants (IBCLCs) and county-level breastfeeding rates among low-income infants. Logistic regression was used to examine the association between IBCLC density and six-week breastfeeding duration. Finally, state advocates collaborated on a cost-benefit analysis of Medicaid coverage of IBCLCs. Results Maps of the NC breastfeeding support landscape indicate that IBCLCs are available to provide services to low-income women across the state. Compared to counties with no IBCLCs, those with high IBCLC density were found to have a six-week breastfeeding prevalence ratio of 1.20 (95% CI: 1.12, 1.28). Medicaid reimbursement of IBCLCs showed an estimated annual cost savings of $2.33 million. Conclusions In one state without Medicaid expansion, we found that breastfeeding support resources are available across the state, high density IBCLC support is associated with increased breastfeeding by low-income mothers, and services are cost-effective. Our model for Medicaid reimbursement in NC provides a framework for states to improve equity in access to optimal lactation support.

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“…However, the Getis-Ord Gi* module demands that optimal threshold distances (i.e., distances at which spatial processes that promote clustering are most obvious) be supplied before it can analyze spatial data. Therefore, we used the incremental spatial autocorrelation module to determine the optimal distance threshold for aggregated areas [33]. Measures of spatial autocorrelation for a range of distances and optimal distances establish a line graph for those distances and their corresponding z-scores.…”

Section: Spatial Statistical Analysismentioning

confidence: 99%

Individual and Interactive Influences of Anthropogenic and Ecological Factors on Forest PM2.5 Concentrations at an Urban Scale

et al. 2018

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Abstract:Integration of Landsat images and multisource data using spatial statistical analysis and geographical detector models can reveal the individual and interactive influences of anthropogenic activities and ecological factors on concentrations of atmospheric particulate matter less than 2.5 microns in diameter (PM 2.5 ). This approach has been used in many studies to estimate biomass and forest disturbance patterns and to monitor carbon sinks. However, the approach has rarely been used to comprehensively analyze the individual and interactive influences of anthropogenic factors (e.g., population density, impervious surface percentage) and ecological factors (e.g., canopy density, stand age, and elevation) on PM 2.5 concentrations. To do this, we used Landsat-8 images and meteorological data to retrieve quantitative data on the concentrations of particulates (PM 2.5 ), then integrated a forest management planning inventory (FMPI), population density distribution data, meteorological data, and topographic data in a Geographic Information System database, and applied a spatial statistical analysis model to identify aggregated areas (hot spots and cold spots) of particulates in the urban area of Jinjiang city, China. A geographical detector model was used to analyze the individual and interactive influences of anthropogenic and ecological factors on PM 2.5 concentrations. We found that particulate concentration hot spots are mainly distributed in urban centers and suburbs, while cold spots are mainly distributed in the suburbs and exurban region. Elevation was the dominant individual factor affecting PM 2.5 concentrations, followed by dominant tree species and meteorological factors. A combination of human activities (e.g., population density, impervious surface percentage) and multiple ecological factors caused the dominant interactive effects, resulting in increased PM 2.5 concentrations. Our study suggests that human activities and multiple ecological factors effect PM 2.5 concentrations both individually and interactively. We conclude that in order to reveal the direct and indirect effects of human activities and multiple factors on PM 2.5 concentrations in urban forests, quantification of fusion satellite data and spatial statistical methods should be conducted in urban areas.

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Use of Spatial Epidemiology and Hot Spot Analysis to Target Women Eligible for Prenatal Women, Infants, and Children Services

Cited by 48 publications

References 17 publications

Análisis espacial de la anemia gestacional en el Perú, 2015.

Análisis espacial de la anemia gestacional en el Perú, 2015.

Improving Access to Medical Lactation Support and Counseling: Building the Case for Medicaid Reimbursement

Individual and Interactive Influences of Anthropogenic and Ecological Factors on Forest PM2.5 Concentrations at an Urban Scale

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