Estimation of seasonal variations in risk factor profiles and mortality from coronary heart disease

Hanno Ulmer1, Cecily Kelleher, Günter Diem

  • 1Department of Biostatistics and Documentation, Innsbruck Medical University, Innsbruck, Austria. Hanno.Ulmer@uibk.ac.at

Insights

Seasonal variations in coronary heart disease (CHD) risk factors contribute to mortality. Winter increases risk factors like cholesterol and blood pressure, particularly for chronic CHD, affecting both men and women.

Area of Science:

  • Cardiovascular epidemiology
  • Public health research
  • Biostatistics

Background:

  • Seasonal variations in coronary heart disease (CHD) and risk factors are documented.
  • Previous studies lacked quantification of seasonal risk factor impact on CHD mortality in large, diverse populations.

Purpose of the Study:

  • To quantify the contribution of seasonal risk factor variations to coronary heart disease (CHD) mortality.
  • To analyze these effects across different demographic groups, including men and women.

Main Methods:

  • Utilized a large database (149,650 individuals, >450,000 measurements) from the Western Austrian Vorarlberg Health Monitoring and Promotion Programme (1985-1999).
  • Analyzed seasonal patterns in CHD mortality (ICD-9 410-414) and risk factors (cholesterol, blood pressure, BMI).

Main Results:

  • Higher coronary heart disease (CHD) mortality observed in winter (27.9%) vs. summer (21.7%).
  • Chronic CHD (ICD-9 414) significantly more frequent in winter (p < 0.001).
  • Risk factors (cholesterol, blood pressure, BMI) were higher in winter, increasing estimated risk by 6.8% (men) and 3.6% (women).

Conclusions:

  • Quantified seasonal risk factor variation's contribution to coronary heart disease (CHD) mortality for the first time.
  • Observed consistent effects across demographics, suggesting a physiological basis.
  • Recommended incorporating seasonal fluctuations into the interpretation of CHD risk scores.
Abstract

Related Concept Videos

Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Assessment of the Cardiovascular System I: Subjective Data01:23

Assessment of the Cardiovascular System I: Subjective Data

A thorough health history and physical assessment are essential for identifying cardiovascular disease (CVD) symptoms and distinguishing them from other health issues.
Initial Enquiry
Ask the patient about their primary concern and thoroughly explore all reported symptoms.
Medical History
Investigate past illnesses affecting the cardiovascular system, such as angina, anemia, rheumatic fever, congenital heart disease, stroke, thrombophlebitis, dysrhythmias, varicosities
Inquire about symptoms...
Coronary Artery Disease IV: Preventive Measures01:26

Coronary Artery Disease IV: Preventive Measures

Effective preventive measures for coronary artery disease (CAD) focus on controlling modifiable risk factors, including cholesterol abnormalities and lifestyle changes.Cholesterol ManagementFirst, the Mediterranean diet and the American Heart Association advocate for maintaining low-density lipoprotein (LDL) cholesterol levels below 100 mg/dL, with a more stringent recommendation of below 70 mg/dL for individuals at high risk. LDL cholesterol, often termed "bad cholesterol," can lead to the...
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
Hazard Rate01:11

Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
Factors Influencing Heart Rate01:30

Factors Influencing Heart Rate

The heart rate, or pulse rate, is a vital indicator of cardiovascular health. It reflects the number of times the heart beats per minute. Various physiological and environmental factors influence heart rate, increasing or decreasing cardiac output. Understanding these factors is crucial for assessing heart function and identifying potential health issues.
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...