Geographic Patterns in Overall and Specific Cardiovascular Disease Incidence in Apparently Healthy Men in the United States

Rich, David Q.; Gaziano, J. Michael; Kurth, Tobias

doi:10.1161/strokeaha.107.483719

Cited by 44 publications

(27 citation statements)

References 19 publications

(17 reference statements)

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“…The observed geographic patterns of stroke hospitalization rates among Medicare beneficiaries are consistent with previously observed patterns of stroke incidence, 9,19 prevalence, 20 and death. [1][2][3][4][5][6] The consistency of these geographic patterns supports the hypothesis that place-based characteristics play an important role in the occurrence of stroke and its risk factors.…”

Section: Discussionsupporting

confidence: 89%

“…[1][2][3][4][5][6] Furthermore, the pattern is evident regardless of the geographic unit that is used (eg, county, state economic area, state) and is observed for both stroke death and hospitalization rates. [7][8][9] Several studies monitored changes in the geographic pattern of stroke death over time ranging from 1939 to 1996. 2,4,5 The results show persistence in regional patterns with important changes in subregional patterns (eg, within the Southeast, the concentration of high-rate counties shifted away from the coastal regions to the Mississippi Delta).…”

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confidence: 99%

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Tracking Stroke Hospitalization Clusters Over Time and Associations With County-Level Socioeconomic and Healthcare Characteristics

Schieb

Mobley

George

et al. 2013

Stroke

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Our study included hospital claims data for fee-for-service Medicare beneficiaries aged ≥65 for 1995, 1996, 2005, and 2006 from the Centers for Medicare and Medicaid Services' Medicare Provider Analysis and Review file, Part A. We defined a stroke hospitalization Background and Purpose-This study evaluated clustering of stroke hospitalization rates, patterns of the clustering over time, and associations with community-level characteristics. Methods-We used Medicare hospital claims data from 1995-1996 to 2005-2006 with a principal discharge diagnosis of stroke to calculate county-level stroke hospitalization rates. We identified statistically significant clusters of highand low-rate counties by using local indicators of spatial association, tracked cluster status over time, and assessed associations between cluster status and county-level socioeconomic and healthcare profiles. Results-Clearly defined clusters of counties with high-and low-stroke hospitalization rates were identified in each time.Approximately 75% of counties maintained their cluster status from 1995-1996 to 2005-2006. In addition, 243 counties transitioned into high-rate clusters, and 148 transitioned out of high-rate clusters. Persistently high-rate clusters were located primarily in the Southeast, whereas persistently low-rate clusters occurred mostly in New England and in the West. In general, persistently low-rate counties had the most favorable socioeconomic and healthcare profiles, followed by counties that transitioned out of or into high-rate clusters. Persistently high-rate counties experienced the least favorable socioeconomic and healthcare profiles. Conclusions-The persistence of clusters of high-and low-stroke hospitalization rates during a 10-year period suggests that the underlying causes of stroke in these areas have also persisted. In this study, we refer to cerebrovascular disease as stroke. Beneficiaries were determined from the Medicare Denominator Files and were excluded if they were members of a health maintenance organization, died before July 1, or were <65 years on July 1 for each of the study years. All stroke hospitalizations and Medicare beneficiaries were assigned to the county of the patient's residence in the Medicare claims files. The study years were combined to create 2 periods: 1995-1996 and 2005-2006. Two-year stroke hospitalization rates were calculated for each period and age-adjusted by using the 2000 US standard population weights.10 Data for independent cities in Virginia were merged with their surrounding counties. Only counties located in the 48 contiguous United States that had at least 1 neighboring county were included (n=3074). Stroke hospitalization rates were calculated by using SAS software (version 9.1.3).11 Maps were created by using ArcMap software (version 10.0). 12 Spatial Clustering AnalysesWe undertook a 2-step process to assess positive spatial autocorrelation, or clustering. All spatial clustering analyses were conducted by using GeoDa software (version 0.9.5-i), 13 and the Empirical-B...

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Section: Discussionsupporting

confidence: 89%

mentioning

confidence: 99%

Tracking Stroke Hospitalization Clusters Over Time and Associations With County-Level Socioeconomic and Healthcare Characteristics

Schieb

Mobley

George

et al. 2013

Stroke

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“…This is counter to the general population, where incidence of CHD equals or exceeds that of all other CV events together (36,37). This may be related to the higher incidence of stroke noted in the southeastern United States compared with in the rest of the country (38,39). The higher rates of stroke observed in blacks versus whites may also contribute to this finding (40).…”

Section: Discussionmentioning

confidence: 92%

Diabetes, Kidney Disease, and Cardiovascular Outcomes in the Jackson Heart Study

Afkarian

Katz

Bansal

et al. 2016

CJASN

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Background and objectives Blacks have high rates of cardiovascular disease and mortality. Diabetes and CKD, risk factors for cardiovascular mortality in the general population, are common among blacks. We sought to assess their contribution to cardiovascular disease and mortality in blacks.Design, setting, participants, & measurements This observational cohort study was of 3211 participants in the Jackson Heart Study (enrolled 2000-2004). Rates of incident stroke, incident coronary heart disease, and cardiovascular mortality were quantified in participants with diabetes, CKD (eGFR,60 ml/min per 1.73 m 2 , urine albumin-to-creatinine ratio $30 mg/g, or both), or both through 2012, with a median follow-up of 6.99 years.Results Four hundred fifty-six (14.2%) participants had only diabetes, 257 (8.0%) had only CKD, 201 (6.3%) had both, and 2297 (71.5%) had neither. Diabetes without CKD was associated with excess risks of incident stroke, incident coronary heart disease, and cardiovascular mortality after adjustment for demographic and clinical covariates, including prevalent cardiovascular disease (excess incidence rates, 2.6; 95% confidence interval, 0.5 to 4.7; 2.6; 95% confidence interval, 0.3 to 4.8; and 2.4; 95% confidence interval, 0.4 to 4.3 per 1000 person-years, respectively). CKD without diabetes was associated with comparable nonsignificant excess risks for incident stroke and coronary heart disease (2.5; 95% confidence interval, 20.1 to 5.2 and 2.4; 95% confidence interval, 20.8 to 5.5 per 1000 person-years, respectively) but a larger excess risk for cardiovascular mortality (7.3; 95% confidence interval, 3.0 to 11.5 per 1000 person-years). Diabetes and CKD together were associated with greater excess risks for incident stroke (13.8; 95% confidence interval, 5.3 to 22.3 per 1000 person-years), coronary heart disease (12.8; 95% confidence interval, 4.9 to 20.8 per 1000 person-years), and cardiovascular mortality (14.8; 95% confidence interval, 7.2 to 22.3 per 1000 person-years). The excess risks associated with the combination of diabetes and CKD were larger than those associated with established risk factors, including prevalent cardiovascular disease.Conclusions The combination of diabetes and kidney disease is associated with substantial excess risks of cardiovascular events and mortality among blacks.

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“…The Stroke Belt region (SB) in the southeastern United States has higher stroke mortality than the rest of the United States, 1,2 and national data suggest that similar regional differences exist in stroke incidence. [3][4][5][6] There are several hypothesized reasons for this but data for testing the underlying factors are limited. 2 Research to date has shown that only a portion of the higher stroke mortality can be explained by traditional risk factors.…”

mentioning

confidence: 99%

Effect of duration and age at exposure to the Stroke Belt on incident stroke in adulthood

Howard¹,

McClure²,

Glymour³

et al. 2013

Neurology

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Objective: To assess whether there are differences in the strength of association with incident stroke for specific periods of life in the Stroke Belt (SB).Methods: The risk of stroke was studied in 24,544 black and white stroke-free participants, aged 451, in the Reasons for Geographic and Racial Differences in Stroke study, a national populationbased cohort enrolled [2003][2004][2005][2006][2007]. Incident stroke was defined as first occurrence of stroke over an average 5.8 years of follow-up. Residential histories (city/state) were obtained by questionnaire. SB exposure was quantified by combinations of SB birthplace and current residence and proportion of years in SB during discrete age categories (0-12, 13-18, 19-30, 31-45, last 20 years) and entire life. Proportional hazards models were used to establish association of incident stroke with indices of exposure to SB, adjusted for demographic, socioeconomic (SES), and stroke risk factors.Results: In the demographic and SES models, risk of stroke was significantly associated with proportion of life in the SB and with all other exposure periods except birth, ages 31-45, and current residence. The strongest association was for the proportion of the entire life in SB. After adjustment for risk factors, the risk of stroke remained significantly associated only with proportion of residence in SB in adolescence (hazard ratio 1.17, 95% confidence interval 1.00-1.37).Conclusions: Childhood emerged as the most important period of vulnerability to SB residence as a predictor of future stroke. Improvement in childhood health circumstances should be considered as part of long-term health improvement strategies in the SB. The Stroke Belt region (SB) in the southeastern United States has higher stroke mortality than the rest of the United States, 1,2 and national data suggest that similar regional differences exist in stroke incidence. [3][4][5][6] There are several hypothesized reasons for this but data for testing the underlying factors are limited. 2 Research to date has shown that only a portion of the higher stroke mortality can be explained by traditional risk factors.7-10 SB has been defined using state of residence at time of death. Population migration may contribute to differences in regional mortality rates but few US studies have considered the impact of population redistribution on geographic disparities in stroke incidence and mortality.11-14 Some, 12-14 but not all, 11 studies have shown that birthplace is associated with cardiovascular mortality, with individuals born in the Southeast having higher rates than those born in other regions of the United States. With respect to stroke incidence, one national study showed increased incidence of self-reported stroke associated with living in the SB during childhood. 6 It is not known whether there is a "sensitive period" for residence in the SB, i.e., a developmental period during which SB exposure has the greatest consequences for later stroke risk, or whether stroke risk accumulates with each additiona...

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Geographic Patterns in Overall and Specific Cardiovascular Disease Incidence in Apparently Healthy Men in the United States

Cited by 44 publications

References 19 publications

Tracking Stroke Hospitalization Clusters Over Time and Associations With County-Level Socioeconomic and Healthcare Characteristics

Tracking Stroke Hospitalization Clusters Over Time and Associations With County-Level Socioeconomic and Healthcare Characteristics

Diabetes, Kidney Disease, and Cardiovascular Outcomes in the Jackson Heart Study

Effect of duration and age at exposure to the Stroke Belt on incident stroke in adulthood

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