40 research outputs found
Neighborhood Resources for Physical Activity and Healthy Foods and Their Association with Insulin Resistance
OBJECTIVE:: Little is known about the influence of the built environment, and in particular neighborhood resources, on health. We hypothesized that neighborhood resources for physical activity and healthy foods are associated with insulin resistance. METHODS:: Person-level data (n = 2026) came from 3 sites of The Multi-Ethnic Study of Atherosclerosis, a study of adults aged 45-84 years. Area-level data were derived from a population-based residential survey. The homeostasis model assessment index was used as an insulin resistance measure among persons not treated for diabetes. We used linear regression to estimate associations between area features and insulin resistance. RESULTS:: Greater neighborhood physical activity resources consistently were associated with lower insulin resistance. Adjusted for age, sex, family history of diabetes, race/ethnicity, income and education, insulin resistance was reduced by 17% (95% confidence interval = -31% to -1%) for an increase from the 10th to 90th percentiles of resources. Greater healthy food resources were also inversely related to insulin resistance, although the association was not robust to adjustment for race/ethnicity. Analyses including diet, physical activity, and body mass index suggested that these variables partly mediated observed associations. Results were similar when impaired fasting glucose/diabetes was considered as the outcome variable. CONCLUSION:: Diabetes prevention efforts may need to consider features of residential environment.http://deepblue.lib.umich.edu/bitstream/2027.42/57885/1/Neighborhood Resources for Physical Activity and Healthy Foods and Their Association With Insulin Resistance.pd
Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study
Objective The aim of this work was to estimate agreement of self-reported heart failure (HF) with physician-diagnosed HF and compare the prevalence of HF according to method of ascertainment. Methods and Results ARIC cohort members (60–83 years of age) were asked annually whether a physician indicated that they have HF. For those self-reporting HF, physicians were asked to confirm their patients' HF status. Physician-diagnosed HF included surveillance of hospitalized HF and hospitalized and outpatient HF identified in administrative claims databases. We estimated sensitivity, specificity, positive predicted value, kappa, prevalence and bias–adjusted kappa (PABAK), and prevalence. Compared with physician-diagnosed HF, sensitivity of self-report was low (28%–38%) and specificity was high (96%–97%). Agreement was poor (kappa 0.32–0.39) and increased when adjusted for prevalence and bias (PABAK 0.73–0.83). Prevalence of HF measured by self-report (9.0%), ARIC-classified hospitalizations (11.2%), and administrative hospitalization claims (12.7%) were similar. When outpatient HF claims were included, prevalence of HF increased to 18.6%. Conclusions For accurate estimates HF burden, self-reports of HF are best confirmed by means of appropriate diagnostic tests or medical records. Our results highlight the need for improved awareness and understanding of HF by patients, because accurate patient awareness of the diagnosis may enhance management of this common condition
Racial Differences in Trends and Prognosis of Guideline-Directed Medical Therapy for Heart Failure with Reduced Ejection Fraction: the Atherosclerosis Risk in Communities (ARIC) Surveillance Study
Background: Racial disparities in guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) have not been fully documented in a community setting. Methods: In the ARIC Surveillance Study (2005–2014), we examined racial differences in GDMT at discharge, its temporal trends, and the prognostic impact among individuals with hospitalized HFrEF, using weighted regression models to account for sampling design. Optimal GDMT was defined as beta blockers (BB), mineralocorticoid receptor antagonist (MRA) and ACE inhibitors (ACEI) or angiotensin II receptor blockers (ARB). Acceptable GDMT included either one of BB, MRA, ACEI/ARB or hydralazine plus nitrates (H-N). Results: Of 16,455 (unweighted n = 3,669) HFrEF cases, 47% were Black. Only ~ 10% were discharged with optimal GDMT with higher proportion in Black than White individuals (11.1% vs. 8.6%, p 80% in both racial groups while Black individuals were more likely to receive ACEI/ARB (62.0% vs. 54.6%) and MRA (18.0% vs. 13.8%) than Whites, with a similar pattern for H-N (21.8% vs. 10.1%). There was a trend of decreasing use of optimal GDMT in both groups, with significant decline of ACEI/ARB use in Whites (− 2.8% p < 0.01) but increasing H-N use in both groups (+ 6.5% and + 9.2%, p < 0.01). Only ACEI/ARB and BB were associated with lower 1-year mortality. Conclusions: Optimal GDMT was prescribed in only ~ 10% of HFrEF patients at discharge but was more so in Black than White individuals. ACEI/ARB use declined in Whites while H-N use increased in both races. GDMT utilization, particularly ACEI/ARB, should be improved in Black and Whites individuals with HFrEF
Lung function impairment and risk of incident heart failure: the NHLBI Pooled Cohorts Study
Aims: The aim is to evaluate associations of lung function impairment with risk of incident heart failure (HF). Methods and results: Data were pooled across eight US population-based cohorts that enrolled participants from 1987 to 2004. Participants with self-reported baseline cardiovascular disease were excluded. Spirometry was used to define obstructive [forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) <0.70] or restrictive (FEV1/FVC ≥0.70, FVC <80%) lung physiology. The incident HF was defined as hospitalization or death caused by HF. In a sub-set, HF events were sub-classified as HF with reduced ejection fraction (HFrEF; EF <50%) or preserved EF (HFpEF; EF ≥50%). The Fine-Gray proportional sub-distribution hazards models were adjusted for sociodemographic factors, smoking, and cardiovascular risk factors. In models of incident HF sub-types, HFrEF, HFpEF, and non-HF mortality were treated as competing risks. Among 31 677 adults, there were 3344 incident HF events over a median follow-up of 21.0 years. Of 2066 classifiable HF events, 1030 were classified as HFrEF and 1036 as HFpEF. Obstructive [adjusted hazard ratio (HR) 1.17, 95% confidence interval (CI) 1.07-1.27] and restrictive physiology (adjusted HR 1.43, 95% CI 1.27-1.62) were associated with incident HF. Obstructive and restrictive ventilatory defects were associated with HFpEF but not HFrEF. The magnitude of the association between restrictive physiology and HFpEF was similar to associations with hypertension, diabetes, and smoking. Conclusion: Lung function impairment was associated with increased risk of incident HF, and particularly incident HFpEF, independent of and to a similar extent as major known cardiovascular risk factors
Simulação da expectativa de perdas de solo em microbacia sob diferentes manejos florestais
Efeito da administração de propileno glicol e cobalto associado à vitamina B12 sobre o perfil metabólico e a atividade enzimática de ovelhas da raça Santa Inês no periparto
Composição florÃstica da vegetação arbórea de um trecho de floresta de galeria do Parque Estadual do Rola-Moça na Região Metropolitana de Belo Horizonte, MG, Brasil
Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design
The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories
Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program
The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits