PMU69 Modifiable Lifestyle Risk Factors for Arterial Hypertension and Diabetes Mellitus in Beneficiaries of a Health PLAN in Brazil: A Retrospective Cohort

2021 ◽  
Vol 24 ◽  
pp. S157
Author(s):  
Neto JP Reis ◽  
J. Busch
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Arterial Hypertension ◽  
Health Plan ◽  
Retrospective Cohort ◽  
Lifestyle Risk Factors ◽  
Lifestyle Risk

scholarly journals Lifestyle Risk Factors and Cardiovascular Disease in Cubans and Cuban Americans

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Melissa S. Burroughs Peña ◽  
Dhaval Patel ◽  
Delfin Rodríguez Leyva ◽  
Bobby V. Khan ◽  
Laurence Sperling
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Type 2 Diabetes Mellitus ◽  
Cardiovascular Prevention ◽  
Lifestyle Risk Factors ◽  
Lifestyle Risk ◽  
Cuban Americans

Cardiovascular disease is the leading cause of mortality in Cuba. Lifestyle risk factors for coronary heart disease (CHD) in Cubans have not been compared to risk factors in Cuban Americans. Articles spanning the last 20 years were reviewed. The data on Cuban Americans are largely based on the Hispanic Health and Nutrition Examination Survey (HHANES), 1982–1984, while more recent data on epidemiological trends in Cuba are available. The prevalence of obesity and type 2 diabetes mellitus remains greater in Cuban Americans than in Cubans. However, dietary preferences, low physical activity, and tobacco use are contributing to the rising rates of obesity, type 2 diabetes mellitus, and CHD in Cuba, putting Cubans at increased cardiovascular risk. Comprehensive national strategies for cardiovascular prevention that address these modifiable lifestyle risk factors are necessary to address the increasing threat to public health in Cuba.

scholarly journals Lifestyle Risk Factors and New-Onset Diabetes Mellitus in Older Adults

2009 ◽  
Vol 169 (8) ◽  
pp. 798 ◽  
Author(s):  
Dariush Mozaffarian ◽  
Aruna Kamineni ◽  
Mercedes Carnethon ◽  
Luc Djoussé ◽  
Kenneth J. Mukamal ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Older Adults ◽  
Lifestyle Risk Factors ◽  
Onset Diabetes ◽  
Lifestyle Risk ◽  
New Onset Diabetes Mellitus ◽  
New Onset

scholarly journals Lifestyle Risk Factors in the Development of Kidney Cancer: A Russian Experience

2018 ◽  
Vol 19 (1) ◽  
pp. 35-40
Author(s):  
IP Artyukhov ◽  
RA Zukov ◽  
VA Reshetnikov ◽  
VV Kozlov ◽  
SB Bolevich ◽  
...  
Keyword(s):  
Risk Factors ◽  
Renal Cell Carcinoma ◽  
Early Diagnosis ◽  
Arterial Hypertension ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Control Group ◽  
Study Group ◽  
Lifestyle Risk Factors ◽  
Lifestyle Risk

Abstract The objective of our study was the evaluation of major lifestyle risk factors for the development of renal cell carcinoma (RCC) and the assessment of chances of developing this disease among inhabitants in the region, in the presence of and with combinations of the studied risk factors. Risk factors for developing RCC that are associated with lifestyle (smoking, obesity and hypertension) were observed in 500 patients with RCC aged 30-64 years who were investigated at the Krasnoyarsk Oncology Dispensary (study group) and 858 participants in the Krai (control group). The results of our study showed that smoking increases the risk of developing RCC 2.9 times and arterial hypertension 3.3 times in men; in women, obesity and hypertension increased these risks 2.6 and 3.2 times, respectively. All three risk factors were combined in 13.6% of men and in 8.4% of women with RCC. Our data may be useful for the prevention, development of screening programmes and early diagnosis of RCC.

ASSESSMENT OF DEMENTIA IN THE TYPE 2 DIABETES BY MOCA

2017 ◽  
pp. 35-44
Author(s):  
Dinh Toan Nguyen
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
High Sensitivity ◽  
Cross Sectional ◽  
Average Value ◽  
Lifestyle Risk ◽  
Diabetes Mellitus Risk

Background: Studies show that diabetes mellitus is the greatest lifestyle risk factor for dementia. Appropriate management and treatment of type 2 diabetes mellitus could prevent the onset and progression of mild cognitive impairment to dementia. MoCA test is high sensitivity with mild dementia but it have not been used and studied widespread in Vietnam. Aim: 1. Using MoCA and MMSE to diagnose dementia in patients with type 2 diabetes mellitus. 2. Assessment of the relationship between dementia and the risk factors. Methods: cross-sectional description in 102 patients with type 2 diabetes mellitus. The Mini-Mental State Examination(MMSE) and the Montreal Cognitive Assessment (MoCA) were used to assess cognitive function. The diagnosis of dementia was made according to Diagnostic and Statistical Manual of Mental Disorders. Results: The average value for MoCA in the group of patients with dementia (15.35 ± 2.69) compared with non-dementia group (20.72 ± 4.53). The sensitivity and specificity of MoCA were 84.8% and 78.3% in identifying individuals with dementia, and MMSE were 78.5% and 82.6%, respectively. Using DSMIV criteria as gold standard we found MoCA and MMSE were more similar for dementia cases (AUC 0.871 and 0.890). The concordance between MoCA and MMSE was moderate (kappa = 0.485). When considering the risk factors, the education,the age, HbA1c, dyslipidemia, Cholesterol total related with dementia in the type 2 diabetes. Conclusion: MoCA scale is a good screening test of dementia in patients with type 2 diabetes mellitus.When compared with the MMSE scale, MoCA scale is more sensitive in detecting dementia. Key words: MoCA, dementia, type 2 diabetes mellitus, risk factors

Novel Machine-Learned Approach for COVID-19 Resource Allocation: A Tool for Evaluating Community Susceptibility (Preprint)

2020 ◽  
Author(s):  
Neil Kale
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Insurance Coverage ◽  
Premature Mortality ◽  
Health Insurance Coverage ◽  
Heart Attacks ◽  
Lifestyle Risk Factors ◽  
The People ◽  
Potential Risk Factors ◽  
Lifestyle Risk

BACKGROUND Despite worldwide efforts to develop an effective COVID vaccine, it is quite evident that initial supplies will be limited. Therefore, it is important to develop methods that will ensure that the COVID vaccine is allocated to the people who are at major risk until there is a sufficient global supply. OBJECTIVE The purpose of this study was to develop a machine-learning tool that could be applied to assess the risk in Massachusetts towns based on community-wide social, medical, and lifestyle risk factors. METHODS I compiled Massachusetts town data for 29 potential risk factors, such as the prevalence of preexisting comorbid conditions like COPD and social factors such as racial composition, and implemented logistic regression to predict the amount of COVID cases in each town. RESULTS Of the 29 factors, 14 were found to be significant (p < 0.1) indicators: poverty, food insecurity, lack of high school education, lack of health insurance coverage, premature mortality, population, population density, recent population growth, Asian percentage, high-occupancy housing, and preexisting prevalence of cancer, COPD, overweightness, and heart attacks. The machine-learning approach is 80% accurate in the state of Massachusetts and finds the 9 highest risk communities: Lynn, Brockton, Revere, Randolph, Lowell, New Bedford, Everett, Waltham, and Fitchburg. The 5 most at-risk counties are Suffolk, Middlesex, Bristol, Norfolk, and Plymouth. CONCLUSIONS With appropriate data, the tool could evaluate risk in other communities, or even enumerate individual patient susceptibility. A ranking of communities by risk may help policymakers ensure equitable allocation of limited doses of the COVID vaccine.

scholarly journals The Prevalence of Insulin Resistance and the Associated Risk Factors in a Sample of 14–18-Year-Old Slovak Adolescents

2021 ◽  
Vol 18 (3) ◽  
pp. 909
Author(s):  
Jana Jurkovičová ◽  
Katarína Hirošová ◽  
Diana Vondrová ◽  
Martin Samohýl ◽  
Zuzana Štefániková ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Insulin Resistance ◽  
Venous Blood ◽  
Significant Risk ◽  
Lifestyle Changes ◽  
Skewed Distribution ◽  
Model Assessment ◽  
Lifestyle Risk Factors ◽  
Lifestyle Risk

The prevalence of cardiometabolic risk factors has increased in Slovakian adolescents as a result of serious lifestyle changes. This cross-sectional study aimed to assess the prevalence of insulin resistance (IR) and the associations with cardiometabolic and selected lifestyle risk factors in a sample of Slovak adolescents. In total, 2629 adolescents (45.8% males) aged between 14 and 18 years were examined in the study. Anthropometric parameters, blood pressure (BP), and resting heart rate were measured; fasting venous blood samples were analyzed; and homeostasis model assessment (HOMA)-insulin resistance (IR) was calculated. For statistical data processing, the methods of descriptive and analytical statistics for normal and skewed distribution of variables were used. The mean HOMA-IR was 2.45 ± 1.91, without a significant sex differences. IR (cut-off point for HOMA-IR = 3.16) was detected in 18.6% of adolescents (19.8% males, 17.6% females). IR was strongly associated with overweight/obesity (especially central) and with almost all monitored cardiometabolic factors, except for total cholesterol (TC) and systolic BP in females. The multivariate model selected variables such as low level of physical fitness, insufficient physical activity, breakfast skipping, a small number of daily meals, frequent consumption of sweetened beverages, and low educational level of fathers as significant risk factors of IR in adolescents. Recognizing the main lifestyle risk factors and early IR identification is important in terms of the performance of preventive strategies. Weight reduction, regular physical activity, and healthy eating habits can improve insulin sensitivity and decrease the incidence of metabolic syndrome, type 2 diabetes, and cardiovascular disease (CVD).

scholarly journals Smoking, drinking, diet and physical activity—modifiable lifestyle risk factors and their associations with age to first chronic disease

2019 ◽  
Vol 49 (1) ◽  
pp. 113-130 ◽  
Author(s):  
Ryan Ng ◽  
Rinku Sutradhar ◽  
Zhan Yao ◽  
Walter P Wodchis ◽  
Laura C Rosella
Keyword(s):  
Risk Factors ◽  
Chronic Disease ◽  
Chronic Diseases ◽  
Lifestyle Factors ◽  
Competing Risk ◽  
Chronic Obstructive ◽  
Common Disease ◽  
Heavy Smoking ◽  
Lifestyle Risk Factors ◽  
Lifestyle Risk

AbstractBackgroundThis study examined the incidence of a person’s first diagnosis of a selected chronic disease, and the relationships between modifiable lifestyle risk factors and age to first of six chronic diseases.MethodsOntario respondents from 2001 to 2010 of the Canadian Community Health Survey were followed up with administrative data until 2014 for congestive heart failure, chronic obstructive respiratory disease, diabetes, lung cancer, myocardial infarction and stroke. By sex, the cumulative incidence function of age to first chronic disease was calculated for the six chronic diseases individually and compositely. The associations between modifiable lifestyle risk factors (alcohol, body mass index, smoking, diet, physical inactivity) and age to first chronic disease were estimated using cause-specific Cox proportional hazards models and Fine-Gray competing risk models.ResultsDiabetes was the most common disease. By age 70.5 years (2015 world life expectancy), 50.9% of females and 58.1% of males had at least one disease and few had a death free of the selected diseases (3.4% females; 5.4% males). Of the lifestyle factors, heavy smoking had the strongest association with the risk of experiencing at least one chronic disease (cause-specific hazard ratio = 3.86; 95% confidence interval = 3.46, 4.31). The lifestyle factors were modelled for each disease separately, and the associations varied by chronic disease and sex.ConclusionsWe found that most individuals will have at least one of the six chronic diseases before dying. This study provides a novel approach using competing risk methods to examine the incidence of chronic diseases relative to the life course and how their incidences are associated with lifestyle behaviours.

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