The reliability of self-reporting chronic diseases: how reliable is the result of population-based cohort studies

F Najafi1, M Moradinazar1, B Hamzeh1

  • 1Research Center for Environmental Determinants of Health (RCEDH), Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.

Insights

Self-reporting chronic diseases in the Ravansar Non-Communicable Diseases (RaNCD) cohort study showed good reliability for many conditions. This suggests self-reported data can be valuable for certain chronic disease research.

Area of Science:

  • Public Health
  • Epidemiology
  • Chronic Disease Research

Background:

  • Reliable data collection is crucial for epidemiological studies.
  • Self-reporting is a common method for gathering health information in cohort studies.
  • The accuracy of self-reported chronic diseases needs validation.

Purpose of the Study:

  • To assess the reliability of self-reported chronic diseases.
  • To evaluate baseline data from the Ravansar Non-Communicable Diseases (RaNCD) cohort study.
  • To determine the validity of self-reported conditions in a western Iranian population.

Main Methods:

  • A random sample of 202 participants from the RaNCD cohort study was re-assessed.
  • Participants were queried about chronic conditions 30-35 days post-recruitment.
  • Kappa statistics were used to measure agreement for self-reported diseases.

Main Results:

  • Kappa agreement ranged from 39.52% to 100%.
  • Lower reliability was observed for hypertension and hepatitis.
  • Higher reliability was found for cancer, cardiac ischemia, and diabetes.

Conclusions:

  • Self-reporting of chronic diseases demonstrated relative reliability in the RaNCD cohort.
  • Self-reported data can be utilized for specific chronic conditions when validity is acceptable.
  • Findings support the use of self-reported data in certain public health research contexts.
Abstract

Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
13.0K
Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies01:27

Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies

Assessing and diagnosing Chronic Obstructive Pulmonary Disease (COPD) involves a detailed approach that includes a comprehensive review of medical history, physical examination, and a variety of diagnostic tests. This thorough evaluation is essential to ensure an accurate diagnosis and guide effective management strategies.
Medical History
3.0K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.2K
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
421
Observational Studies01:11

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
10.6K
Introduction to Epidemiology01:26

Introduction to Epidemiology

Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
1.5K