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Progress in pediatric asthma surveillance II: geospatial patterns of asthma in Alameda County, California.

Roberts EM, English PB, Wong M, Wolff C, Valdez S, Van den Eeden SK, Ray GT - Prev Chronic Dis (2006)

Bottom Line: Health care use was categorized by type and analyzed by census tract demographic information.Geospatial analysis enabled visualization of this phenomenon; it further detected areas with elevated emergency department visit rates and potentially related environmental hazards in and around communities of concern.Proceedings of group evaluations suggested that the material aided in the translation of data describing spatial variations in health event risk to address specific community experiences and concerns.

View Article: PubMed Central - PubMed

Affiliation: California Department of Health Services, Environmental Health Investigations Branch, Richmond, CA 94804, USA.

ABSTRACT

Introduction: As with many diseases, the epidemic of asthma among children over the past few decades has been shaped by a social and environmental context that is becoming progressively more evident. Commonly used methods for asthma surveillance, however, are based on national rather than local data. The purpose of this study was to develop high-resolution asthma surveillance techniques responsive to the needs of health care professionals and local child health and social justice advocates.

Methods: We assembled a working data set of health care use records from 2001 from public and private sources covering 1.7 million person-months among children younger than 18 years in Alameda County, California. Health care use was categorized by type and analyzed by census tract demographic information. Images of the geographic distribution of health service events were created using density estimation mapping with overlapping 0.5-mile (805-m) radius spatial buffers, and statistical significance (two-tailed P & .05) was estimated using a Monte Carlo simulation algorithm.

Results: High-poverty communities had higher rates of emergency department visits due to asthma than low-poverty communities but had lower rates for indicators of quality primary asthma care. Geospatial analysis enabled visualization of this phenomenon; it further detected areas with elevated emergency department visit rates and potentially related environmental hazards in and around communities of concern. Areas of the county not previously considered to be deeply burdened by asthma were identified as having high emergency department visit rates.

Conclusion: The assembly and high-resolution geospatial analysis of health care use data contributed to a more detailed depiction of pediatric asthma disparities than was previously available to community members, public health professionals, and clinicians. Information generated using these techniques facilitated discussion among stakeholders of the environmental and social contexts of asthma and health disparities in general. Proceedings of group evaluations suggested that the material aided in the translation of data describing spatial variations in health event risk to address specific community experiences and concerns.

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Related in: MedlinePlus

Raster surface for rates of asthma-related emergency department visits among Kaiser Permanente and Medi-Cal fee-for-service enrollees younger than 18 years in 2001, Alameda County, California. Subsets of the total areas having statistically significantly elevated rates are indicated with arrows. (A, neighborhood of North Oakland; B, neighborhood of West Oakland; C, neighborhood of San Antonio; D, neighborhood of East Oakland; E, western portion of city of Castro Valley; F, neighborhood of South Hayward; G, southwestern portion of city of Pleasanton; H, southeastern portion of city of Livermore; I, southwestern portion of city of Fremont.)
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Figure 3: Raster surface for rates of asthma-related emergency department visits among Kaiser Permanente and Medi-Cal fee-for-service enrollees younger than 18 years in 2001, Alameda County, California. Subsets of the total areas having statistically significantly elevated rates are indicated with arrows. (A, neighborhood of North Oakland; B, neighborhood of West Oakland; C, neighborhood of San Antonio; D, neighborhood of East Oakland; E, western portion of city of Castro Valley; F, neighborhood of South Hayward; G, southwestern portion of city of Pleasanton; H, southeastern portion of city of Livermore; I, southwestern portion of city of Fremont.)

Mentions: Raster surfaces and the geographic distribution of statistically significant elevations for each health care use rate are shown in Figures 3 and 4. The distribution of emergency department visits due to asthma (Figure 3) is very similar to that of hospitalizations depicted using Office of Statewide Healthcare Planning and Development data (Figure 1); the difference was that density estimation produced a higher resolution map. Within ZIP codes known to have elevated asthma hospitalization rates, areas of concern became visible. Also, additional discrete areas with elevated health care use rates became apparent in several ZIP codes in the far southern and eastern regions of the county.


Progress in pediatric asthma surveillance II: geospatial patterns of asthma in Alameda County, California.

Roberts EM, English PB, Wong M, Wolff C, Valdez S, Van den Eeden SK, Ray GT - Prev Chronic Dis (2006)

Raster surface for rates of asthma-related emergency department visits among Kaiser Permanente and Medi-Cal fee-for-service enrollees younger than 18 years in 2001, Alameda County, California. Subsets of the total areas having statistically significantly elevated rates are indicated with arrows. (A, neighborhood of North Oakland; B, neighborhood of West Oakland; C, neighborhood of San Antonio; D, neighborhood of East Oakland; E, western portion of city of Castro Valley; F, neighborhood of South Hayward; G, southwestern portion of city of Pleasanton; H, southeastern portion of city of Livermore; I, southwestern portion of city of Fremont.)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC1637800&req=5

Figure 3: Raster surface for rates of asthma-related emergency department visits among Kaiser Permanente and Medi-Cal fee-for-service enrollees younger than 18 years in 2001, Alameda County, California. Subsets of the total areas having statistically significantly elevated rates are indicated with arrows. (A, neighborhood of North Oakland; B, neighborhood of West Oakland; C, neighborhood of San Antonio; D, neighborhood of East Oakland; E, western portion of city of Castro Valley; F, neighborhood of South Hayward; G, southwestern portion of city of Pleasanton; H, southeastern portion of city of Livermore; I, southwestern portion of city of Fremont.)
Mentions: Raster surfaces and the geographic distribution of statistically significant elevations for each health care use rate are shown in Figures 3 and 4. The distribution of emergency department visits due to asthma (Figure 3) is very similar to that of hospitalizations depicted using Office of Statewide Healthcare Planning and Development data (Figure 1); the difference was that density estimation produced a higher resolution map. Within ZIP codes known to have elevated asthma hospitalization rates, areas of concern became visible. Also, additional discrete areas with elevated health care use rates became apparent in several ZIP codes in the far southern and eastern regions of the county.

Bottom Line: Health care use was categorized by type and analyzed by census tract demographic information.Geospatial analysis enabled visualization of this phenomenon; it further detected areas with elevated emergency department visit rates and potentially related environmental hazards in and around communities of concern.Proceedings of group evaluations suggested that the material aided in the translation of data describing spatial variations in health event risk to address specific community experiences and concerns.

View Article: PubMed Central - PubMed

Affiliation: California Department of Health Services, Environmental Health Investigations Branch, Richmond, CA 94804, USA.

ABSTRACT

Introduction: As with many diseases, the epidemic of asthma among children over the past few decades has been shaped by a social and environmental context that is becoming progressively more evident. Commonly used methods for asthma surveillance, however, are based on national rather than local data. The purpose of this study was to develop high-resolution asthma surveillance techniques responsive to the needs of health care professionals and local child health and social justice advocates.

Methods: We assembled a working data set of health care use records from 2001 from public and private sources covering 1.7 million person-months among children younger than 18 years in Alameda County, California. Health care use was categorized by type and analyzed by census tract demographic information. Images of the geographic distribution of health service events were created using density estimation mapping with overlapping 0.5-mile (805-m) radius spatial buffers, and statistical significance (two-tailed P & .05) was estimated using a Monte Carlo simulation algorithm.

Results: High-poverty communities had higher rates of emergency department visits due to asthma than low-poverty communities but had lower rates for indicators of quality primary asthma care. Geospatial analysis enabled visualization of this phenomenon; it further detected areas with elevated emergency department visit rates and potentially related environmental hazards in and around communities of concern. Areas of the county not previously considered to be deeply burdened by asthma were identified as having high emergency department visit rates.

Conclusion: The assembly and high-resolution geospatial analysis of health care use data contributed to a more detailed depiction of pediatric asthma disparities than was previously available to community members, public health professionals, and clinicians. Information generated using these techniques facilitated discussion among stakeholders of the environmental and social contexts of asthma and health disparities in general. Proceedings of group evaluations suggested that the material aided in the translation of data describing spatial variations in health event risk to address specific community experiences and concerns.

Show MeSH
Related in: MedlinePlus