Mortality and associated risk factors in diabetics

1985 ◽  
Vol 110 (4_Suppl) ◽  
pp. S21-S26 ◽  
Author(s):  
R. J. Jarrett ◽  
M. J. Shipley
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Mortality Risk ◽  
Mortality Rates ◽  
Potential Risk Factors ◽  
Diabetic Population ◽  
Associated Risk Factors ◽  
The Relationship

Summary. In 168 male diabetics aged 40-64 years participating in the Whitehall Study, ten-year age adjusted mortality rates were significantly higher than in non-diabetics for all causes, coronary heart disease, all cardiovascular disease and, in addition, causes other than cardiovascular. Mortality rates were not significantly related to known duration of the diabetes. The predictive effects of several major mortality risk factors were similar in diabetics and non-diabetics. Excess mortality rates in the diabetics could not be attributed to differences in levels of blood pressure or any other of the major risk factors measured. Key words: diabetics; mortality rates; risk factors; coronary heart disease. There are many studies documenting higher mortality rates - particularly from cardiovascular disease -in diabetics compared with age and sex matched diabetics from the same population (see Jarrett et al. (1982) for review). However, there is sparse information relating potential risk factors to subsequent mortality within a diabetic population, information which might help to explain the increased mortality risk and also suggest preventive therapeutic approaches. In the Whitehall Study, a number of established diabetics participated in the screening programme and data on mortality rates up to ten years after screening are available. We present here a comparison of diabetics and non-diabetics in terms of relative mortality rates and the influence of conventional risk factors as well as an analysis of the relationship between duration of diabetes and mortality risk.

Abstract P115: How Many Coronary Heart Disease Deaths In Poland In 2020 Might Be Prevented By Further Reductions In Population Risk Factor Levels?

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Piotr Bandosz ◽  
Maria Guzman-Castillo ◽  
Simon Capewell ◽  
Tomasz Zdrojewski ◽  
Julia Critchley ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Risk Factor ◽  
Heart Disease ◽  
Smoking Prevalence ◽  
Mortality Rates ◽  
Mortality Reduction ◽  
Scenario Reduction ◽  
Saturated Fats ◽  
Changes In Risk

Background: Poland has experienced one of the most dramatic declines in coronary heart disease (CHD) mortality rates in recent decades. This decline reflects the use of evidence based treatments and, crucially, population wide changes in diet. Our aim is to explore the potential for further gains in Poland by achieving population wide reductions in smoking, dietary salt and saturated fat intake and physical inactivity levels. Methods: A validated and updated policy model was used to forecast potential decreases in CHD deaths by 2020 as consequence of lifestyle and dietary changes in the population. Data from the most recent Polish risk factor survey was used for the baseline (2011). We modeled two different policy scenarios regarding possible future changes in risk factors: A) conservative scenario: reduction of smoking prevalence and physically inactivity rates by 5% between 2011 and 2020, and reduction of dietary consumption of energy from saturated fats by 1% and of salt by 10%. B) ideal scenario: reduction of smoking and physically inactivity prevalence by 15%, and dietary reduction of energy from saturated fats by 3% and of salt by 30%. We also conducted extensive sensitivity analysis using different counterfactual scenarios of future mortality trends. Results: Baseline scenarios. By assuming continuing declines in mortality and no future improvements in risk factors the predicted number of CHD deaths in 2020 would be approximately 13,600 (9,838-18,184) while if mortality rates remain stable, the predicted number of deaths would approximate 22,200 (17,792-26,688). Conservative scenario. Assuming continuing declines in mortality, small changes in risk factors could result in approximately 1,500 (688-2,940) fewer deaths. This corresponds to a 11% mortality reduction. Under the ideal scenario, our model predicted some 4,600 (2,048-8,701) fewer deaths (a 34% mortality reduction). Reduction in smoking prevalence by 5% (conservative scenario) or 15% (ideal scenario) could result in mortality reductions of 4.5% and 13.8% respectively. Decreases in salt intake by 10% or 30% might reduce CHD deaths by 3.0% and 8.6% respectively. Replacing 1% or 3% of dietary saturated fats by poly-unsaturates could reduce CHD deaths by 2.6% or 7.7% Lowering the prevalence of physically inactive people by 5%-15% could decrease CHD deaths by 1.2%-3.7%. Conclusion: Small and eminently feasible population reductions in lifestyle related risk factors could substantially decrease future number of CHD deaths in Poland, thus consolidating the earlier gains.

Heart Disease Diagnosis Using Fuzzy Supervised Learning Based on Dynamic Reduced Features

2014 ◽  
Vol 5 (3) ◽  
pp. 78-101 ◽  
Author(s):  
Walid Moudani ◽  
Mohamad Hussein ◽  
Mariam abdelRazzak ◽  
Félix Mora-Camino
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Potential Risk ◽  
Heart Attack ◽  
Rough Set Theory ◽  
Disease Diagnosis ◽  
Fuzzy Classification ◽  
Classification Problems ◽  
Potential Risk Factors

The health industry collects huge amounts of health data which, unfortunately, are not mined to discover hidden information. However, there is a lack of effective analytical tools to discover hidden relationships and trends in data. Information technologies can provide alternative approaches to the diagnosis of the heart attach disease. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to develop an innovative fuzzy classification solution approach based on dynamic reduced sets of potential risk factors using the promising Rough Set theory which is a new mathematical approach to data analysis based on classification of objects. Therefore, we propose to validate the classification using Multi-classifier decision tree to identify the risky heart disease cases. This work is based on a dataset collected from several clinical institutions based on the medical profile of patient. Moreover, the experts' knowledge in this field has been taken into consideration in order to define the disease, its risk factors, to follow up the issue results, and to establish significant knowledge relationships between medical factors related to Coronary Heart Disease. To identify cases of heart attack, experiments of several classification techniques have been performed leading to rank the suitable techniques. The reduction of potential risk factors contributes to enumerate dynamically one or more optimal subsets of the potential risk factors of high interest which implicitly leads to reduce the complexity of the classification problems while maintaining the prediction classification quality. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

scholarly journals Sex Differences in the Age of Diagnosis for Cardiovascular Disease and Its Risk Factors Among US Adults: Trends From 2008 to 2017, the Medical Expenditure Panel Survey

2020 ◽  
Vol 9 (24) ◽  
Author(s):  
Victor Okunrintemi ◽  
Martin Tibuakuu ◽  
Salim S. Virani ◽  
Laurence S. Sperling ◽  
Annabelle Santos Volgman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Medical Expenditure Panel Survey ◽  
Medical Expenditure ◽  
Age At Diagnosis ◽  
Panel Survey ◽  
Cvd Risk Factors ◽  
Cvd Risk

Background Sex differences in the trends for control of cardiovascular disease (CVD) risk factors have been described, but temporal trends in the age at which CVD and its risk factors are diagnosed and sex‐specific differences in these trends are unknown. Methods and Results We used the Medical Expenditure Panel Survey 2008 to 2017, a nationally representative sample of the US population. Individuals ≥18 years, with a diagnosis of hypercholesterolemia, hypertension, coronary heart disease, or stroke, and who reported the age when these conditions were diagnosed, were included. We included 100 709 participants (50.2% women), representing 91.9 million US adults with above conditions. For coronary heart disease and hypercholesterolemia, mean age at diagnosis was 1.06 and 0.92 years older for women, compared with men, respectively (both P <0.001). For stroke, mean age at diagnosis for women was 1.20 years younger than men ( P <0.001). The mean age at diagnosis of CVD risk factors became younger over time, with steeper declines among women (annual decrease, hypercholesterolemia [women, 0.31 years; men 0.24 years] and hypertension [women, 0.23 years; men, 0.20 years]; P <0.001). Coronary heart disease was not statistically significant. For stroke, while age at diagnosis decreased by 0.19 years annually for women ( P =0.03), it increased by 0.22 years for men ( P =0.02). Conclusions The trend in decreasing age at diagnosis for CVD and its risk factors in the United States appears to be more pronounced among women. While earlier identification of CVD risk factors may provide opportunity to initiate preventive treatment, younger age at diagnosis of CVD highlights the need for the prevention of CVD earlier in life, and sex‐specific interventions may be needed.

scholarly journals Coronary heart disease and associated risk factors in sub-Saharan Africans

2007 ◽  
Vol 21 (5) ◽  
pp. 411-414 ◽  
Author(s):  
E Marijon ◽  
L Trinquart ◽  
D Jani ◽  
H Jourdier ◽  
E Garbarz ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Sub Saharan ◽  
Associated Risk Factors
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