Individual risk factors that modify the short-term effects of air pollution on mortality : a population-based study of Chinese population

2008 ◽  
Author(s):  
Chunquan Ou
Keyword(s):  
Risk Factors ◽  
Air Pollution ◽  
Chinese Population ◽  
Population Based ◽  
Individual Risk ◽  
Short Term ◽  
Population Based Study ◽  
Individual Risk Factors ◽  
Short Term Effects

Dietary habits and the short-term effects of air pollution on mortality in the Chinese population in Hong Kong

2010 ◽  
Vol 66 (3) ◽  
pp. 254-258 ◽  
Author(s):  
Chun-Quan Ou ◽  
Chit-Ming Wong ◽  
Sai-Yin Ho ◽  
Mary Schooling ◽  
Lin Yang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Hong Kong ◽  
Chinese Population ◽  
Dietary Habits ◽  
Short Term ◽  
Short Term Effects

scholarly journals Risk factors of short-term survival in the aged in elective colon cancer surgery: a population-based study

2019 ◽  
Vol 35 (2) ◽  
pp. 307-315 ◽  
Author(s):  
Susanna Niemeläinen ◽  
Heini Huhtala ◽  
Anu Ehrlich ◽  
Jyrki Kössi ◽  
Esa Jämsen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Colon Cancer ◽  
Postoperative Complications ◽  
Population Based ◽  
Cancer Surgery ◽  
Mortality Data ◽  
Short Term ◽  
Population Based Study ◽  
Colon Cancer Surgery ◽  
Elective Colon

Abstract Purpose Patients aged > 80 years represent an increasing proportion of colon cancer diagnoses. Selecting patients for elective surgery is challenging because of possibly compromised health status and functional decline. The aim of this retrospective, population-based study was to identify risk factors and health measures that predict short-term mortality after elective colon cancer surgery in the aged. Methods All patients > 80 years operated electively for stages I–III colon cancer from 2005 to 2016 in four Finnish hospitals were included. The prospectively collected data included comorbidities, functional status, postoperative surgical and medical outcomes as well as mortality data. Results A total of 386 patients (mean 84.0 years, range 80–96, 56% female) were included. Male gender (46% vs 35%, p = 0.03), higher BMI (51% vs 37%, p = 0.02), diabetes mellitus (51% vs 37%, p = 0.02), coronary artery disease (52% vs 36%, p = 0.003) and rheumatic diseases (67% vs 39%, p = 0.03) were related to higher risk of complications. The severe complications were more common in patients with increased preoperative hospitalizations (31% vs 15%, p = 0.05) and who lived in nursing homes (30% vs 17%, p = 0.05). The 30-day and 1-year mortality rates were 6.0% and 15% for all the patients compared with 30% and 45% in patients with severe postoperative complications (p < 0.001). Severe postoperative complications were the only significant patient-related variable affecting 1-year mortality (OR 9.60, 95% CI 2.33–39.55, p = 0.002). Conclusions The ability to identify preoperatively patients at high risk of decreased survival and thus prevent severe postoperative complications could improve overall outcome of aged colon cancer patients.

scholarly journals Clustering of risk factors and the risk of incident cardiovascular disease in Asian and Caucasian populations: results from the Asia Pacific Cohort Studies Collaboration

BMJ Open ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. e019335 ◽  
Author(s):  
Sanne A E Peters ◽  
Xin Wang ◽  
Tai-Hing Lam ◽  
Hyeon Chang Kim ◽  
Suzanne Ho ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Cohort Studies ◽  
Cox Regression ◽  
Population Based ◽  
Asia Pacific ◽  
Individual Risk ◽  
Cvd Risk ◽  
Individual Risk Factors

ObjectiveTo assess the relationship between risk factor clusters and cardiovascular disease (CVD) incidence in Asian and Caucasian populations and to estimate the burden of CVD attributable to each cluster.SettingAsia Pacific Cohort Studies Collaboration.ParticipantsIndividual participant data from 34 population-based cohorts, involving 314 024 participants without a history of CVD at baseline.Outcome measuresClusters were 11 possible combinations of four individual risk factors (current smoking, overweight, blood pressure (BP) and total cholesterol). Cox regression models were used to obtain adjusted HRs and 95% CIs for CVD associated with individual risk factors and risk factor clusters. Population-attributable fractions (PAFs) were calculated.ResultsDuring a mean follow-up of 7 years, 6203 CVD events were recorded. The ranking of HRs and PAFs was similar for Australia and New Zealand (ANZ) and Asia; clusters including BP consistently showed the highest HRs and PAFs. The BP–smoking cluster had the highest HR for people with two risk factors: 4.13 (3.56 to 4.80) for Asia and 3.07 (2.23 to 4.23) for ANZ. Corresponding PAFs were 24% and 11%, respectively. For individuals with three risk factors, the BP–smoking–cholesterol cluster had the highest HR (4.67 (3.92 to 5.57) for Asia and 3.49 (2.69 to 4.53) for ANZ). Corresponding PAFs were 13% and 10%.ConclusionsRisk factor clusters act similarly on CVD risk in Asian and Caucasian populations. Clusters including elevated BP were associated with the highest excess risk of CVD.

scholarly journals The Association of Neighbourhood Built and Social Environment and Cancer: Evidence From Australia

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 135s-135s
Author(s):  
Y. Feng ◽  
A. Elshaug
Keyword(s):  
Risk Factors ◽  
Social Environment ◽  
Cancer Incidence ◽  
National Level ◽  
Population Based ◽  
Individual Risk ◽  
Cancer Outcomes ◽  
Geographic Variations ◽  
Local Neighborhood ◽  
Individual Risk Factors

Background and context: Australia is among the worst countries in terms of cancer incidence and displays substantial variations in cancer outcomes across multiple geographic scales. Aim: This research project aims to examine how neighborhood social and environmental attributes interact with individual risk factors, affect cancer outcomes and contribute to the geographic variations in cancer outcomes. Specifically, it will answer the following research questions: What neighborhood built and social environment attributes are associated with individual health outcomes? How do neighborhood features influence cancer outcomes, at multiple geographic scales? At what geographical scales the variations in cancer outcomes are the most pronounced and how much is contributed by neighborhood attributes? What initiatives and guidelines should be developed and at what level: local neighborhood, regional, state, national level? Strategy/Tactics: Innovative geospatial techniques will be developed to analyze cancer risk factors and variations at multiple spatial levels utilizing population-based hospital inpatient data in NSW, Australia Program/Policy process: The study is the first population-based study evaluating how neighborhood influences cancer outcomes from multiple scales in the Australian context. The project has tangible potentials to be translated into initiatives and practices. This includes various levels such as local neighborhood, state and national level for the prevention and control of cancer and ultimately improve cancer outcomes in Australia. Outcomes: A large proportion of geographic variations in cancer outcomes are contributed by differences in the neighborhood built and social environment characteristics, which interact with individual risk factors and have synergistic effects on cancer outcomes. What was learned: Neighborhood physical and social environment has a strong effect on cancer outcomes. Through modification of neighborhood attributes, we can reduce the exposure to neighborhood risk factors and promote healthy lifestyle choices, which, in turn, reduce cancer incidence and improve survival rates. Effective initiatives and guidelines for cancer control should be developed and at all government levels including the local neighborhood, regional, state, national level.

Distribution of short and lifetime risks for cardiovascular disease in Italians

2011 ◽  
Vol 19 (4) ◽  
pp. 723-730 ◽  
Author(s):  
Augusto Di Castelnuovo ◽  
Simona Costanzo ◽  
Mariarosaria Persichillo ◽  
Marco Olivieri ◽  
Amalia de Curtis ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Primary Prevention ◽  
Population Based ◽  
Lifetime Risk ◽  
Individual Risk ◽  
Cvd Risk ◽  
Cross Sectional ◽  
Individual Risk Factors ◽  
Short Time

Background: Guidelines for primary prevention recommend calculation of lifetime risk for cardiovascular disease (CVD) in addition to short-time risk. We aimed at evaluating the distribution of CVD lifetime risk and the percentage of Italians having low short-term, but high lifetime, risk. Design: Cross-sectional general population-based cohort study. Methods: We included 8,403 (46% men) cardiovascular disease-free individuals aged 35–50 years, among those randomly recruited in the framework of the MOLI-SANI cohort. Participants were stratified into three groups: low short-time (10-year) (≤3% and non diabetic)/low lifetime, low short-time/high lifetime, and high short-time risk. Short-time risk was evaluated by the equation provided by the Italian CUORE project. Lifetime risk was evaluated using the algorithm derived from the Framingham cohort. Results: High short-time risk was prevalent in 16% population (32% of men and 2% of women). Among individuals with low short-time risk, 80% had high lifetime risk (82% men and 78% women). The proportion of individuals with very low lifetime risk due to all optimal risk factors was 4.1% only (1.5% men and 6.3% women). Conclusions: A large proportion of Italian adults not qualified for CVD primary prevention because of their very low short-time predicted CVD risk, are in fact at high risk to develop a CVD event in their lifetime; therefore population-based approaches should be sought to modify the overall distribution of individual risk factors. These findings offer helpful information for policy makers involved in contrasting the burden of CVD, especially in women and young men.

Probability in Diagnostic Thinking

2019 ◽  
pp. 83-100
Author(s):  
Cym Anthony Ryle
Keyword(s):  
Risk Factors ◽  
Population Based ◽  
Diagnostic Reasoning ◽  
Individual Risk ◽  
Diagnostic Process ◽  
Test Results ◽  
Medically Unexplained ◽  
Individual Risk Factors ◽  
Diagnostic Thinking ◽  
Early Phases

This chapter observes that diagnostic reasoning involves both informal and mathematical estimates of probability. It argues that intuitive estimates of the likelihood of disease are necessary in the early phases of the diagnostic process but notoriously inaccurate. It notes that formal calculations are not possible when the question is, What might be wrong with this person? but are much more accurate than intuition in estimating the probability that a specific disease is present. The chapter suggests that population-based calculations of the likelihood of disease may lead clinicians to play Russian roulette by proxy because individual variation and individual risk factors may alter that risk in a given patient. It refers to evidence that many clinicians are inexpert in statistical methods. The chapter describes some basic statistical processes and their place in the clinical application of test results. It discusses the necessity and challenges of managing patients whose symptoms are medically unexplained.

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