Prevalence and correlates of mitral valve prolapse in a population-based sample of American Indians: the strong heart study

2001 ◽  
Vol 111 (9) ◽  
pp. 679-685 ◽  
Author(s):  
Richard B Devereux ◽  
Erica C Jones ◽  
Mary J Roman ◽  
Barbara V Howard ◽  
Richard R Fabsitz ◽  
...  
2007 ◽  
Vol 86 (2) ◽  
pp. 480-487 ◽  
Author(s):  
Jiaqiong Xu ◽  
Sigal Eilat-Adar ◽  
Catherine M Loria ◽  
Barbara V Howard ◽  
Richard R Fabsitz ◽  
...  

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Ozan Unlu ◽  
Zaid Almarzooq ◽  
Amanda M Fretts ◽  
Ying Zhang ◽  
Julie Stoner ◽  
...  

Background: Prior work has shown that fibrinogen, a well-known inflammatory marker, is associated with cardiovascular (CV) events. While it is known that physical activity (PA) imparts CV health benefits, there remains a knowledge gap on the interactions of PA with systemic inflammation on risk of CV death among American Indians. Hypothesis: To investigate the relationship between PA, inflammation, and CV death, we tested the hypotheses that: (i) PA is associated with lower risk of CV death, and (ii) the CV benefit of PA is mediated via an inflammatory pathway. Methods: We examined the association between PA (leisure-time plus occupational as METs[Metabolic Equivalent of Task]-hours per week via a validated questionnaire) and CV death among 3,135 adults (mean age 56 ± 8) without baseline CV disease in Strong Heart Study (1989-1991), a longitudinal study among American Indians. Preacher and Hayes bootstrap method was used for the model assessing mediation by fibrinogen. Results: During 26 years (mean 17.3 ± 8 years) of follow-up, there were 378 CV deaths. Compared to participants with minimal activity, subjects with higher levels of PA had a lower risk of CV death. Odds ratios were 0.91 (95% confidence interval [CI]: 0.65-1.21), 0.69 (95% CI: 0.51-0.92), and 0.56 (95% CI: 0.39-0.71) (p-trend=0.003), for increasing quartile of activity compared to the lowest, after adjustment for age, sex, study site, education, smoking, diabetes, hypertension, BMI, LDL cholesterol, and urine albumin-creatinine ratio. Mediation analysis showed the effect of PA on CV death was fully mediated via fibrinogen level (correlation coefficient: 0.998, 95% CI 0.995-0.999; Sobel test z= -3.11, p=0.03) (Figure). Conclusion: In a population-based study of American Indians, PA compared to inactivity, was associated with lower risk of CV death. This study highlights that PA is associated with improved CV outcomes and this effect is largely driven by inflammation.


2021 ◽  
Vol 74 ◽  
pp. 101978
Author(s):  
Dorothy A. Rhoades ◽  
John Farley ◽  
Stephen M. Schwartz ◽  
Kimberly M. Malloy ◽  
Wenyu Wang ◽  
...  

Diabetes Care ◽  
2002 ◽  
Vol 25 (1) ◽  
pp. 49-54 ◽  
Author(s):  
E. T. Lee ◽  
T. K. Welty ◽  
L. D. Cowan ◽  
W. Wang ◽  
D. A. Rhoades ◽  
...  

2008 ◽  
Vol 108 (5) ◽  
pp. 794-802 ◽  
Author(s):  
Sigal Eilat-Adar ◽  
Jiaqiong Xu ◽  
Uri Goldbourt ◽  
Ellie Zephier ◽  
Barbara V. Howard ◽  
...  

2009 ◽  
Vol 170 (5) ◽  
pp. 632-639 ◽  
Author(s):  
A. M. Fretts ◽  
B. V. Howard ◽  
A. M. Kriska ◽  
N. L. Smith ◽  
T. Lumley ◽  
...  

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Ying Zhang ◽  
Wenyu Wang ◽  
Elisa T Lee ◽  
Thomas K Welty ◽  
Jorge R Kizer ◽  
...  

Background— Stroke prediction models are valuable to physicians in evaluating the risk of their patients so that preventive interventions can be promoted. The Framingham Risk Profile is a widely used stroke prediction equation. However, the contributions of some common risk factors for stroke vary across populations and some risk factors are specific to certain populations. For example, albuminuria is an important risk factor in American Indians (AIs), which is not included in the Framingham equation. The objective of the current study is to develop stroke prediction equations using routinely collected variables in AIs, a population with high rates of diabetes and stroke. Methods— The data used in the analysis are from 4507 stroke free participants at enrollment in the Strong Heart Study (SHS), the largest population-based longitudinal study of cardiovascular disease (CVD) and its risk factors in AIs in Arizona, Oklahoma, and South/North Dakota. As of December 2008, 379/4507 (8.4%) participants suffered a first stroke during an average follow-up of 17 years. Baseline potential risk factors were included in the Cox proportional-hazard models to develop gender-specific prediction equations. Backward selection was used to choose the predictors. Model performance was assessed using Harrell’s C statistics based on bootstrapping methods. Results— Baseline age, untreated systolic blood pressure, treated diastolic blood pressure, HDL-C, current smoking, diabetes, macro-albuminuria, and history of CVD are significant predictors for incident stroke among women. Most of these predictors except HDL-C were also in the prediction equation for men. The equations provided good discrimination ability, as indicated by a C statistic of 0.72 for men and 0.73 for women. Conclusions— Predicted risk of stroke in 10 years can be provided for physicians and their patients. Then appropriate intervention can be implemented. The stroke prediction equations from SHS can be applied to other AIs as well as other ethnic groups with high rates of diabetes and albuminuria.


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