RISK FACTORS IN AUSTRALIANS: NATIONAL HEART FOUNDATION'S RISK FACTOR PREVALENCE STUDY, 1980

1984 ◽  
Vol 14 (4) ◽  
pp. 395-399 ◽  
Author(s):  
R. L. HODGE
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Prevalence Study ◽  
Risk Factor Prevalence ◽  
National Heart

Abstract WP236: The Urban-Rural Divide: Risk Factor Prevalence in Ischemic Stroke Patients Across Two Decades

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Dinesh V Jillella ◽  
Sara Crawford ◽  
Anne S Tang ◽  
Rocio Lopez ◽  
Ken Uchino
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Ischemic Stroke ◽  
Regression Models ◽  
Stroke Risk ◽  
Stroke Patients ◽  
Stroke Risk Factor ◽  
Risk Factor Prevalence ◽  
Urban Rural ◽  
Artery Disease

Introduction: Regional disparities exist in stroke incidence and stroke related mortality in the United States. We aimed to elucidate the stroke risk factor prevalence trends based on urban versus rural location. Methods: From the National Inpatient Sample database the comorbid stroke risk factors were collected among hospitalized ischemic stroke patients during 2000-2016. Crude and age-and sex-standardized prevalence estimates were calculated for each risk factor during the time periods 2000-2008 and 2009-2016. We compared risk factor prevalence over the defined time periods using regression models, and differences in risk factor trends based on patient location categorized as urban (metropolitan with population of ≥ 1 million) and rural (neither micropolitan or metropolitan) using interaction terms in the regression models. Results: Stroke risk factor prevalence significantly increased from 2000-2008 to 2009-2016. When stratified based on patient location, most risk factors increased in both urban and rural groups. In the crude model, the urban to rural trend difference across 2000-08 and 2009-16 was significant in hypertension (p<0.0001), hyperlipidemia (p=0.0008), diabetes mellitus (p<0.0001), coronary artery disease (p<0.0001), smoking (p<0.0001) and alcohol (p=0.02). With age and sex standardization, the urban to rural trend difference was significant in hypertension (p<0.0001), hyperlipidemia (p=0.0007), coronary artery disease (p=0.01) and smoking (p<0.0001). Conclusion: The prevalence of vascular risk factors among ischemic stroke patients has increased over the last two decades. There exists an urban-rural divide, with rural patients showing larger increases in prevalence of several risk factors compared to urban patients.

The National Cooperative Trial on Multifactorial Prevention of First Heart Attacks and Coronary Mortality in Free-Living, High-Risk, Middle-Aged American Men, Also Known as JUMBO: A Short Story

2019 ◽  
Vol 189 (6) ◽  
pp. 491-498 ◽  
Author(s):  
Henry Blackburn
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Multiple Risk Factor ◽  
Intervention Trial ◽  
Heart Attacks ◽  
Heart Institute ◽  
National Heart ◽  
Multiple Risk ◽  
National Cooperative

Abstract The concept of a multiple risk-factor intervention trial (MRFIT) originated in mid-20th century efforts to determine whether modifying the “risk factors” established by cardiovascular disease epidemiology would prevent heart attacks. The term “MRFIT” probably first appeared in the 1968 report to the National Heart Institute from investigators of the National Diet-Heart Feasibility Study. Based on their pilot experience, they recommended a trial of diet alone. Aware, however, that authorities might agree with the rationale but not the implementation of such a massive and risky undertaking, they also proposed an alternative: whether coronary heart disease was preventable at all by simultaneous intervention on several risk factors; that is, a multiple risk-factor intervention trial. After some years agonizing by serial expert committees, the National Heart Institute opted against an explanatory diet trial and for a pragmatic multiple risk-factor intervention, one designed by Institute staff and operated under contract. Meanwhile, an impatient community of investigators met together in the Makarska Conference, outlined a broad cardiovascular disease prevention policy, and submitted their idealized version of a multiple risk-factor trial, called JUMBO. But the National Heart Institute, because of the plan for its own trial, had no funds left for an investigator-initiated proposal. Hence, this background and story of the MRFIT that wasn’t.

scholarly journals Trends of Prevalence of Uncontrolled Risk Factors for Cerebrocardiovascular Disease: Southern Italy from 1988/9 to 2008/9

Cholesterol ◽  
2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Vincenzo Capuano ◽  
Norman Lamaida ◽  
Ernesto Capuano ◽  
Rocco Capuano ◽  
Eduardo Capuano ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Southern Italy ◽  
Cross Sectional ◽  
Targeted Interventions ◽  
Risk Factor Prevalence ◽  
Cross Sectional Studies ◽  
Prevention Of Cardiovascular Disease

The aim of this study was to determine the trends of cardiovascular risk factor prevalence between 1988/9 and 2008/9 in the 25–74-year-old population in an area of Southern Italy. We compared three cross-sectional studies conducted in random population samples, in 1988/9, 1998/9, and 2008/9 in Salerno, Italy. The methodology of data collection (lipid profile, systolic and diastolic blood pressure, glycaemia, and smoking) and conducting tests which the population underwent during the three phases was standardized and comparable. Prevalence of diabetes, hypertension, hypercholesterolemia, and smoking was calculated and standardized for age. A total of 3491 subjects were included. From 1988/9 to 2008/9, in males, the prevalence of all four risk factors was reduced. In women, there was a clear reduction of hypertension, a similar prevalence of hypercholesterolemia, and an increase of smoking and diabetes. In the area of Salerno, our data confirm that the global prevalence of the major risk factors is decreasing in men, but their absolute values are still far from optimization. In women, diabetes and smoking showed a negative trend, therefore requiring targeted interventions. These data are now used as a base for executive targeted programs to improve prevention of cardiovascular disease in our community.

scholarly journals A Causally Naïve and Rigid Population Model of Disease Occurrence Given Two Non-Independent Risk Factors

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
Olaf Dammann ◽  
Kenneth Chui ◽  
Anselm Blumer
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Retinopathy Of Prematurity ◽  
Population Model ◽  
Outcome Variable ◽  
Risk Factor Prevalence ◽  
Disease Occurrence ◽  
Independent Risk Factors ◽  
Simulation Results ◽  
Changes In Risk

We describe a computational population model with two risk factors and one outcome variable in which the prevalence (%) of all three variables, the association between each risk factor and the disease, as well as the association between the two risk factors is the input. We briefly describe three examples: retinopathy of prematurity, diabetes in Panama, and  smoking and obesity as risk factors for diabetes. We describe and discuss the simulation results in these three scenarios including how the published information is used as input and how changes in risk factor prevalence changes outcome prevalence.

scholarly journals Graphical comparisons of relative disease burden across multiple risk factors

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
John Ferguson ◽  
Neil O’Leary ◽  
Fabrizio Maturo ◽  
Salim Yusuf ◽  
Martin O’Donnell
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Relative Risk ◽  
Disease Burden ◽  
Health Interventions ◽  
Continuous Exposure ◽  
Odds Ratios ◽  
Risk Factor Prevalence ◽  
Attributable Fractions ◽  
Log Odds

Abstract Background Population attributable fractions (PAF) measure the proportion of disease prevalence that would be avoided in a hypothetical population, similar to the population of interest, but where a particular risk factor is eliminated. They are extensively used in epidemiology to quantify and compare disease burden due to various risk factors, and directly influence public policy regarding possible health interventions. In contrast to individual specific metrics such as relative risks and odds ratios, attributable fractions depend jointly on both risk factor prevalence and relative risk. The relative contributions of these two components is important, and usually needs to be presented in summary tables that are presented together with the attributable fraction calculation. However, representing PAF in an accessible graphical format, that captures both prevalence and relative risk, may assist interpretation. Methods Taylor-series approximations to PAF in terms of risk factor prevalence and log-odds ratio are derived that facilitate simultaneous representation of PAF, risk factor prevalence and risk-factor/disease log-odds ratios on a single co-ordinate axis. Methods are developed for binary, multi-category and continuous exposure variables. Results The methods are demonstrated using INTERSTROKE, a large international case control dataset focused on risk factors for stroke. Conclusions The described methods could be used as a complement to tables summarizing prevalence, odds ratios and PAF, and may convey the same information in a more intuitive and visually appealing manner. The suggested nomogram can also be used to visually estimate the effects of health interventions which only partially reduce risk factor prevalence. Finally, in the binary risk factor case, the approximations can also be used to quickly convert logistic regression coefficients for a risk factor into approximate PAFs.

Abstract P267: Geographic Patterns of Cardiovascular Disease Risk Factor Prevalence in the Continental US

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Matthew S Loop ◽  
George Howard ◽  
Gustavo de los Campos ◽  
Mohammad Z Al-Hamdan ◽  
Monika M Safford ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Geographic Variation ◽  
Smoking Prevalence ◽  
Local Population ◽  
Community Dwelling ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Risk Factor Prevalence

Objectives: Our understanding of geographic variation in cardiovascular disease (CVD) risk factors is based upon self-reported variables or geographically limited coverage. Our objective was to explore geographic variation in measured hypertension, measured diabetes, measured dyslipidemia, and self-reported current smoking prevalence. Methods: We used baseline data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, whose community-dwelling participants were recruited nationally between 2003 and 2007. Participants underwent a telephone interview and in-home examination. Hypertension, diabetes, and dyslipidemia were based on physiologic measures or reported medication use. Current cigarette smoking was self-reported. Using participants’ residential latitude and longitude, we tested for clustering of each risk factor using the difference in Ripley’s K functions test and, when we found evidence of clustering, used thin plate regression splines (TPRS) in a logistic regression framework to create age- race-, and sex-adjusted maps of risk factor prevalence. Results: Risk factor status and location data were available for 27,787 of the 30,239 participants (92%). Mean (±SD) age of these participants was 65(±9) years, 41% were black, 55% were women, 59% had hypertension, 22% had diabetes, 54% had dyslipidemia, and 15% were current smokers. We found statistically significant geographic clustering of hypertension, diabetes, and smoking prevalence, but not dyslipidemia. The regions with the highest prevalence varied across risk factors (Figure 1). Conclusions: Louisiana and Mississippi might require the most intense management of CVD risk factors. These maps show variation across and within administrative units, providing an accurate representation of geographic variation in risk factor prevalence. High resolution maps could be put to use by healthcare organizations to justify requests for higher reimbursement rates based upon local population health.

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