scholarly journals Characterizing Tweet Volume and Content About Common Health Conditions Across Pennsylvania: Retrospective Analysis (Preprint)

2018 ◽  
Author(s):  
Christopher Tufts ◽  
Daniel Polsky ◽  
Kevin G Volpp ◽  
Peter W Groeneveld ◽  
Lyle Ungar ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Heart Disease ◽  
Disease Surveillance ◽  
Health Conditions ◽  
Chronic Obstructive ◽  
Common Disease ◽  
Web Based ◽  
Medical Diagnoses ◽  
Disease Term

BACKGROUND Tweets can provide broad, real-time perspectives about health and medical diagnoses that can inform disease surveillance in geographic regions. Less is known, however, about how much individuals post about common health conditions or what they post about. OBJECTIVE We sought to collect and analyze tweets from 1 state about high prevalence health conditions and characterize the tweet volume and content. METHODS We collected 408,296,620 tweets originating in Pennsylvania from 2012-2015 and compared the prevalence of 14 common diseases to the frequency of disease mentions on Twitter. We identified and corrected bias induced due to variance in disease term specificity and used the machine learning approach of differential language analysis to determine the content (words and themes) most highly correlated with each disease. RESULTS Common disease terms were included in 226,802 tweets (174,381 tweets after disease term correction). Posts about breast cancer (39,156/174,381 messages, 22.45%; 306,127/12,702,379 prevalence, 2.41%) and diabetes (40,217/174,381 messages, 23.06%; 2,189,890/12,702,379 prevalence, 17.24%) were overrepresented on Twitter relative to disease prevalence, whereas hypertension (17,245/174,381 messages, 9.89%; 4,614,776/12,702,379 prevalence, 36.33%), chronic obstructive pulmonary disease (1648/174,381 messages, 0.95%; 1,083,627/12,702,379 prevalence, 8.53%), and heart disease (13,669/174,381 messages, 7.84%; 2,461,721/12,702,379 prevalence, 19.38%) were underrepresented. The content of messages also varied by disease. Personal experience messages accounted for 12.88% (578/4487) of prostate cancer tweets and 24.17% (4046/16,742) of asthma tweets. Awareness-themed tweets were more often about breast cancer (9139/39,156 messages, 23.34%) than asthma (1040/16,742 messages, 6.21%). Tweets about risk factors were more often about heart disease (1375/13,669 messages, 10.06%) than lymphoma (105/4927 messages, 2.13%). CONCLUSIONS Twitter provides a window into the Web-based visibility of diseases and how the volume of Web-based content about diseases varies by condition. Further, the potential value in tweets is in the rich content they provide about individuals’ perspectives about diseases (eg, personal experiences, awareness, and risk factors) that are not otherwise easily captured through traditional surveys or administrative data.

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.

scholarly journals Prediction of Heart Disease Using Machine Learning Algorithms

2018 ◽  
Vol 7 (2.32) ◽  
pp. 363 ◽  
Author(s):  
N Rajesh ◽  
Maneesha T ◽  
Shaik Hafeez ◽  
Hari Krishna
Keyword(s):  
Risk Factors ◽  
Heart Disease ◽  
Decision Trees ◽  
Naive Bayes ◽  
Heart Diseases ◽  
Naïve Bayes ◽  
Machine Learning Algorithms ◽  
Common Disease ◽  
Bayes Algorithm ◽  
The One

Heart disease is the one of the most common disease. This disease is quite common now a days we used different attributes which can relate to this heart diseases well to find the better method to predict and we also used algorithms for prediction. Naive Bayes, algorithm is analyzed on dataset based on risk factors. We also used decision trees and combination of algorithms for the prediction of heart disease based on the above attributes. The results shown that when the dataset is small naive Bayes algorithm gives the accurate results and when the dataset is large decision trees gives the accurate results.  

Aromatase inhibitors and cardiac outcomes in women undergoing cardiac angiography after early breast cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 558-558 ◽  
Author(s):  
Bostjan Seruga ◽  
Vesna Zadnik ◽  
Cvetka Grasic Kuhar ◽  
Tanja Marinko ◽  
Darko Zorman ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Early Breast Cancer ◽  
Conditional Logistic Regression ◽  
Left Breast ◽  
Left Ventricular ◽  
Ischemic Heart ◽  
Cardiac Angiography

558 Background: Data show that in post-menopausal women with early breast cancer, longer use of aromatase inhibitor (AI) is associated with increased odds of ischemic heart disease. Here we explore the association between adjuvant AI use and cardiac disease in women undergoing cardiac angiography after a diagnosis of early breast cancer. Methods: We linked a database of 7,681 women who underwent cardiac angiography at the University Clinical Center of Ljubljana between December 2004 and November 2010 with the Cancer Registry for Slovenia. Women with early breast cancer that subsequently underwent cardiac angiography were identified. Information on cardiovascular risk factors was retrieved from the patients’ charts and from discharge letters after cardiac angiography. The endpoint of interest was a diagnosis of ischemic heart disease or left ventricular dysfunction (IHD-LVD) without evidence of valvular heart disease at the time of angiography. Conditional, logistic regression was used to test for associations between variables. Results: Among 117 eligible women 75% (n=88) were postmenopausal and 62% (n=73) had hormonal receptor positive (HR+) disease. Of these 42% (n=31) were treated with AI. Overall, 48% (n=56) of women were found to have IHD-LVD. In patients with HR+ breast cancer, use of AIs was significantly associated with IHD-LVD as compared to tamoxifen alone (HR 2.50, 95% CI 1.01-6.29, p=0.046). For each year of AI therapy, there was a trend for higher odds of IHD-LVD (OR: 1.25, 95% CI 0.95-1.67, p=0.116). This effect appeared independent of age, body mass index, baseline hypertension, hypercholesterolemia, diabetes and heart disease or prior anthracyclines exposure. Among all patients, use of anthracyclines and left-sided irradiation was associated with non-significant increases in IHD-LVD (HR 2.37, 95% CI 0.89-6.09, p=0.45 and HR 1.28, 95% CI 0.69-2.40, p=0.44 respectively). Conclusions: Compared to tamoxifen, AIs are associated with a time dependent increase in IHD-LVD. This risk appears independent of other risk factors for heart disease. Anthracycline exposure and left breast or chest wall radiation showed non-significant associations with IHD-LVD in this small cohort.

scholarly journals The COVID-19 mortality effects of underlying health conditions in India: a modelling study

2020 ◽  
Author(s):  
Paul Novosad ◽  
Radhika Jain ◽  
Alison Campion ◽  
Sam Asher
Keyword(s):  
Risk Factors ◽  
Heart Disease ◽  
Kidney Disease ◽  
Mortality Risk ◽  
Age Distribution ◽  
Chronic Respiratory Disease ◽  
Health Conditions ◽  
Middle Income ◽  
Middle Income Countries ◽  
Chronic Heart Disease

ABSTRACTObjectiveTo model how known COVID-19 comorbidities will affect mortality rates and the age distribution of mortality in a large lower middle income country (India), as compared with a high income country (England), and to identify which health conditions drive any differences.DesignModelling study.SettingEngland and India.Participants1,375,548 respondents aged 18 to 99 to the District Level Household Survey-4 and Annual Health Survey in India. Additional information on health condition prevalence on individuals aged 18 to 99 was obtained from the Health Survey for England and the Global Burden of Diseases, Risk Factors, and Injuries Studies (GBD).Main outcome measuresThe primary outcome was the proportional increase in age-specific mortality in each country due to the prevalence of each COVID-19 mortality risk factor (diabetes, hypertension, obesity, chronic heart disease, respiratory illness, kidney disease, liver disease, and cancer, among others). The combined change in overall mortality and the share of deaths under 60 from the combination of risk factors was estimated in each country.ResultsRelative to England, Indians have higher rates of diabetes (10.6% vs. 8.5%), chronic respiratory disease (4.8% vs. 2.5%), and kidney disease (9.7% vs. 5.6%), and lower rates of obesity (4.4% vs. 27.9%), chronic heart disease (4.4% vs. 5.9%), and cancer (0.3% vs. 2.8%). Population COVID-19 mortality in India relative to England is most increased by diabetes (+5.4%) and chronic respiratory disease (+2.3%), and most reduced by obesity (−9.7%), cancer (−3.2%), and chronic heart disease (−1.9%). Overall, comorbidities lower mortality in India relative to England by 9.7%. Accounting for demographics and population health explains a third of the difference in share of deaths under age 60 between the two countries.ConclusionsKnown COVID-19 health risk factors are not expected to have a large effect on aggregate mortality or its age distribution in India relative to England. The high share of COVID-19 deaths from people under 60 in low- and middle-income countries (LMICs) remains unexplained. Understanding mortality risk associated with health conditions prevalent in LMICs, such as malnutrition and HIV/AIDS, is essential for understanding differential mortality.SUMMARY BOXWhat is already known on this topicCOVID-19 infections in low- and middle-income countries (LMICs) are rising rapidly, with the burden of mortality concentrated at much younger ages than in rich countries.A range of pre-existing health conditions can increase the severity of COVID-19 infections.It is feared that poor population health may worsen the severity of the pandemic in LMICs.What this study addsThe COVID-19 comorbidities that have been studied to date may have only a very small effect on aggregate mortality in India relative to England and do not shift the mortality burden toward lower ages at all.India’s younger demographics can explain only a third of the substantial difference in the share of deaths under age 60 between India and England.However, mortality risk associated with health conditions prevalent in LMICs, such as malnutrition and HIV/AIDS, is unknown and research on this topic is urgently needed.

Abstract 14833: The Association Between Cardiovascular Disease Knowledge and Risk Factors Among African American Breast Cancer Survivors in the Deep South

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Michelle S Williams ◽  
Chizoba Anyimukwu
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
African American ◽  
Heart Disease ◽  
Cancer Survivors ◽  
Breast Cancer Survivors ◽  
Deep South ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Disease Knowledge

Introduction: African American breast cancer survivors in the Deep South have a disproportionately high burden of cardiovascular disease (CVD) mortality. This is due, in large part, to multiple potentially modifiable CVD risk factors that are disproportionately high in this group, such as high blood pressure, obesity, and poor dietary habits. The purpose of this study was to assess the association between CVD risk factors and heart disease knowledge among African American breast cancer survivors in the Deep South. Hypothesis: We hypothesize that the key CVD risk factors (smoking, BMI, physical activity, healthy diet, total cholesterol, blood pressure, and blood sugar) will be positively associated with heart disease knowledge score. Methods: The Heart Disease Knowledge Questionnaire was used to assess the participants’ knowledge of heart disease and heart disease risk factors. Questions from My Life Check were used to assess the participants CVD risk factors. Multivariate regression analyses were performed to determine which CVD risk factors and demographic characteristics can predict the participants’ heart disease knowledge score. Results: Seventy African American breast cancer survivors living in the Deep South enrolled in the study. A research team member administered the questionnaires over the phone. The mean age of the participants was 56.76 years (± 10.36) and 42.9% had a college degree or higher level of education. Results of a multivariate regression analysis showed that the number of healthy diet score components was the only cardiovascular health metric that was statistically significantly associated with heart disease knowledge score (p = .01). Education level was the only demographic characteristic that was statistically significantly associated with heart disease knowledge score (p = .004). Conclusions: Our results indicate that women with more knowledge of heart disease and higher levels of education are more likely to have better cardiovascular health metrics. Our findings underscore the need to disseminate and implement health education interventions aimed at increasing knowledge of modifiable CVD risk factors that are targeted towards African American breast cancer survivors in the Deep South.

scholarly journals Investigation on Risk Factors of Ventilator-Associated Pneumonia in Acute Cerebral Hemorrhage Patients in Intensive Care Unit

2017 ◽  
Vol 2017 ◽  
pp. 1-4 ◽  
Author(s):  
Li Chang ◽  
Yun Dong ◽  
Ping Zhou
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Coronary Heart Disease ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Heart Disease ◽  
Hospital Stay ◽  
Cerebral Hemorrhage ◽  
Chronic Obstructive ◽  
Ventilator Associated Pneumonia

Ventilator-associated pneumonia (VAP) is a predominant factor of pulmonary infection. We analyzed the risk factors of VAP with acute cerebral hemorrhage in intensive care unit (ICU) by univariate and multivariate logistic regression analyses. After comparison of 197 cases of the VAP and non-VAP patients, we found that age > 65 years (P=0.003), smoke (P=0.003), coronary heart disease (P=0.005), diabetes (P=0.001), chronic obstructive pulmonary disease (COPD) (P=0.002), ICU and hospital stay (P=0.01), and days on mechanical ventilation (P=0.01) were significantly different, indicating that they are risk factors of VAP. All the age > 65 years (OR = 3.350, 95% CI = 1.936–5.796, P≤0.001), smoke (OR = 3.206, 95% CI = 1.909–5.385, P≤0.001), coronary heart disease (OR = 3.179, 95% CI = 1.015–4.130, P=0.017), diabetes (OR = 5.042, 95% CI = 3.518–7.342, P≤0.001), COPD (OR = 1.942, 95% CI = 1.258–2.843, P=0.012), ICU and hospital stay (OR = 2.34, 95% CI = 1.145–3.892, P=0.038), and days on mechanical ventilation (OR = 1.992, 95% CI = 1.107–3.287, P=0.007) are independent risk factors of VAP. After observation of patients with 6 months of follow-up, the BI score was significantly lower in VAP than that in non-VAP, and the rebleeding rate and mortality rate were significantly higher in VAP than those in non-VAP. Thus, the prognosis of the patients with acute cerebral hemorrhage and VAP in ICU is poor.

scholarly journals Tomato Role on Seven Deadliest Non-Communicable Disease

2021 ◽  
Vol 2 (8) ◽  
pp. 1295-1308
Author(s):  
Lathifah Dzakiyyah Zulfa ◽  
Dessyani Salim ◽  
Abigail Tirza Melia Silalahi ◽  
Sharon Levita Hutapea ◽  
Margaretha Maria Odilia Natasha
Keyword(s):  
Risk Factors ◽  
Lung Cancer ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Communicable Disease ◽  
Communicable Diseases ◽  
Chronic Obstructive ◽  
Non Communicable Diseases ◽  
Non Communicable Disease ◽  
Inflammatory Effect

Non-communicable diseases such as ischemic heart disease, stroke, chronic obstructive pulmonary disease, lung cancer, Alzheimer, diabetes melitus, and kidney disease are leading causes of death in the world. There are many risk factors which can contribute to non-communicable diseases such as dietary. Vegetable consumption such as tomato may lower risk factors to non-communicable diseases because of its active ingredient, lycopene, retinol, alpha tomatine, and tomatidine. In this study, authors aim to explain the mechanism of tomato’s active compound in lowering risk factors of non-communicable disease based on biomarker found on each disease collected from recent epidemiological, in silico, in vitro, and in vivo researches. Lycopene and retinol have proven in reducing ischemic heart disease and stroke because of its anti-atherogenic properties and anti-inflammatory effect. Anti-oxidative and anti-inflammatory effect of lycopene also proven in lowering risk factors of chronic obstructive pulmonary diseases by modulate reverse cholesterol transport, so cholesterol homeostasis is created. In lung cancer, lycopene and other bioactive compound such as α-tomatine and tomatidine also have an anti-proliferative effect by interacting with Epidermal growth factor receptor (EGFR). Its ability to reduce the final product of lipid peroxidation level makes lycopene lower Alzheimer risk factor. There is much more function of tomato’s active coumpound although pure tomato has contradictive effect on some disease.

scholarly journals Research Progress on the Relationship between Lipoprotein Associated Phospholipase A2 and Coronary Atherosclerotic Heart Disease

2021 ◽  
Vol 6 (1) ◽  
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Phospholipase A2 ◽  
Age Of Onset ◽  
Detection Methods ◽  
Research Progress ◽  
Inflammatory Factors ◽  
Common Disease ◽  
Coronary Syndrome

Coronary atherosclerotic heart disease is a common disease which seriously endangers human health. The incidence rate is increasing year by year and the age of onset is becoming younger. As a kind of Inflammatory factors of vascular, Lipoprotein associated Phospholipase A2 (Lp-PLA2) can promote the progress of inflammation and coronary atherosclerosis, and its serum level can reflect the stability of atherosclerotic plaque. Among the risk factors of coronary heart disease, Lp-PLA2, as a supplement to the traditional risk factors, has a significant reference value for the prediction of coronary heart disease. More and more studies have found that Lp-PLA2 has a significant potential value in evaluating the prognosis of coronary heart disease, especially in acute coronary syndrome patients. This review summarizes the research progress of Lp-PLA2 on the pathogenesis, detection methods, independent risk factors of predicting coronary heart disease and the treatment and prognosis evaluation of coronary heart disease.

Sign in / Sign up

Export Citation Format

Share Document