The Reasons for Geographic and Racial Differences in Stroke Study: Objectives and Design
ABSTRACT The REasons for Geographic And Racial Differences in Stroke (REGARDS) Study is a national, population-based, longitudinal study of 30,000 African-American and white adults aged > or =45 years. The objective is to determine the causes for the excess stroke mortality in the Southeastern US and among African-Americans. Participants are randomly sampled with recruitment by mail then telephone, where data on stroke risk factors, sociodemographic, lifestyle, and psychosocial characteristics are collected. Written informed consent, physical and physiological measures, and fasting samples are collected during a subsequent in-home visit. Participants are followed via telephone at 6-month intervals for identification of stroke events. The novel aspects of the REGARDS study allow for the creation of a national cohort to address geographic and ethnic differences in stroke.
- SourceAvailable from: Stacey A Fedewa
[Show abstract] [Hide abstract]
- "Baseline systolic and diastolic blood pressure was measured twice in the left arm with a standard aneroid sphygmomanometer after participants were seated in a chair for three minutes with both feet on the floor. The two blood pressure measurements were averaged . Baseline serum albuminuria (g/dL) was considered as a continuous variable. "
ABSTRACT: Background Socioeconomic status (SES) is independently associated with chronic kidney disease (CKD) progression; however, its association with other CKD outcomes is unclear. In particular, the potential differential effect of SES on mortality among blacks and whites is understudied in CKD. We aimed to examine survival among individuals with prevalent CKD by income and race in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. Methods We examined 2,761 participants with prevalent CKD stage 3 or 4 between 2003 and 2007 in the REGARDS cohort. Participants were followed through March 2013. Mortality from any cause was assessed by income and race (black or white). Low income was defined as an annual household income < $20,000, and was compared to higher incomes (≥$20,000). Cox proportional hazards models adjusted for age, gender, education, insurance, CKD stage, comorbidity and county-level poverty were used to estimate hazard ratios (HR) and 95% confidence intervals (CI). Results A total of 750 deaths (27.5%) occurred during the follow-up period. Average follow-up time was 6.6 years among those alive and 3.7 years among those who died. Low income participants had an elevated adjusted hazard of mortality (HR = 1.58, 95% CI 1.24-2.00) compared to higher income participants. Low income was associated with all-cause mortality regardless of race (HR 1.53; 95% CI 1.18-1.99 among blacks and HR 1.38; 95% CI 1.10-1.74 among whites), with no significant statistical interaction between household income and race (p-value = 0.634). However, black participants had a higher adjusted hazard of mortality (HR = 1.30, 95% CI 1.02-1.65) compared to whites, which was independent of income. Conclusion Income was associated with increased mortality for both blacks and whites with CKD. Blacks with CKD had higher mortality than whites even after adjusting for important socio-demographic and clinical factors.BMC Nephrology 08/2014; 15(1):136. DOI:10.1186/1471-2369-15-136 · 1.69 Impact Factor
[Show abstract] [Hide abstract]
- "REGARDS is a longitudinal study of United States (US) participants aged 45 years and older . The REGARDS study was designed to investigate reasons underlying the higher rate of stroke mortality among blacks, compared with non-Hispanic whites, and among residents in the Southeastern United States, compared with other US regions. "
ABSTRACT: Background Previous research has suggested that vitamin D and sunlight are related to cardiovascular outcomes, but associations between sunlight and risk factors have not been investigated. We examined whether increased sunlight exposure was related to improved cardiovascular risk factor status. Methods Residential histories merged with satellite, ground monitor, and model reanalysis data were used to determine previous-year sunlight radiation exposure for 17,773 black and white participants aged 45+ from the US. Exploratory and confirmatory analyses were performed by randomly dividing the sample into halves. Logistic regression models were used to examine relationships with cardiovascular risk factors. Results The lowest, compared to the highest quartile of insolation exposure was associated with lower high-density lipoprotein levels in adjusted exploratory (−2.7 mg/dL [95% confidence interval: −4.2, −1.2]) and confirmatory (−1.5 mg/dL [95% confidence interval: −3.0, −0.1]) models. The lowest, compared to the highest quartile of insolation exposure was associated with higher systolic blood pressure levels in unadjusted exploratory and confirmatory, as well as the adjusted exploratory model (2.3 mmHg [95% confidence interval: 0.8, 3.8]), but not the adjusted confirmatory model (1.6 mg/dL [95% confidence interval: −0.5, 3.7]). Conclusions The results of this study suggest that lower long-term sunlight exposure has an association with lower high-density lipoprotein levels. However, all associations were weak, thus it is not known if insolation may affect cardiovascular outcomes through these risk factors.BMC Neurology 06/2014; 14(1):133. DOI:10.1186/1471-2377-14-133 · 2.04 Impact Factor
[Show abstract] [Hide abstract]
- "We conducted a cross-sectional analysis of baseline data from REasons for Geographic And Racial Differences in Stroke (REGARDS) study participants linked to Medicare data. REGARDS is a population-based cohort of 30,239 adults ≥45 years of age enrolled in 2003–2007 in the continental United States . Linkage of REGARDS data with Medicare enrollment data was based on social security number, which is a unique identifier that was required to match exactly on all digits; sex, which was required to match; and birth date, which was required to match on year and month, year and day, or month and day allowing a difference of one year. "
ABSTRACT: Databases of medical claims can be valuable resources for cardiovascular research, such as comparative effectiveness and pharmacovigilance studies of cardiovascular medications. However, claims data do not include all of the factors used for risk stratification in clinical care. We sought to develop claims-based algorithms to identify individuals at high estimated risk for coronary heart disease (CHD) events, and to identify uncontrolled low-density lipoprotein (LDL) cholesterol among statin users at high risk for CHD events. We conducted a cross-sectional analysis of 6,615 participants >=66 years old using data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study baseline visit in 2003-2007 linked to Medicare claims data. Using REGARDS data we defined high risk for CHD events as having a history of CHD, at least 1 risk equivalent, or Framingham CHD risk score >20%. Among statin users at high risk for CHD events we defined uncontrolled LDL cholesterol as LDL cholesterol >=100 mg/dL. Using Medicare claims-based variables for diagnoses, procedures, and healthcare utilization, we developed algorithms for high CHD event risk and uncontrolled LDL cholesterol. REGARDS data indicated that 49% of participants were at high risk for CHD events. A claims-based algorithm identified high risk for CHD events with a positive predictive value of 87% (95% CI: 85%, 88%), sensitivity of 69% (95% CI: 67%, 70%), and specificity of 90% (95% CI: 89%, 91%). Among statin users at high risk for CHD events, 30% had LDL cholesterol >=100 mg/dL. A claims-based algorithm identified LDL cholesterol >=100 mg/dL with a positive predictive value of 43% (95% CI: 38%, 49%), sensitivity of 19% (95% CI: 15%, 22%), and specificity of 89% (95% CI: 86%, 90%). Although the sensitivity was low, the high positive predictive value of our algorithm for high risk for CHD events supports the use of claims to identify Medicare beneficiaries at high risk for CHD events.BMC Health Services Research 04/2014; 14(1):195. DOI:10.1186/1472-6963-14-195 · 1.71 Impact Factor