What differs former, light and heavy smokers? Evidence from a post-conflict setting
Tatjana Gazibara1, Marija Milic2, Milan Parlic2
1Institute of Epidemiology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia.
African Health Sciences
|August 16, 2021
Summary
Smoking is prevalent in conflict-affected regions. This study found that environmental second-hand smoke exposure and depression are linked to increased smoking among students in Kosovo, highlighting the need for community-wide prevention programs.
Area of Science:
- Public Health
- Epidemiology
- Social Science
Background:
- Armed conflict zones are associated with higher smoking rates.
- Understanding smoking behaviors in post-conflict settings is crucial for public health interventions.
Purpose of the Study:
- To investigate factors associated with smoking status among university students in northern Kosovo.
- To identify predictors for different levels of smoking (non-smoker, former, light, heavy).
Main Methods:
- A cross-sectional study of 514 university students in Kosovska Mitrovica, Kosovo.
- Data collected via socio-demographic, behavioral questionnaires, and the Beck Depression Inventory (BDI).
- Students categorized into non-smokers, former smokers, light smokers (1-13/day), and heavy smokers (>13/day).
Main Results:
- 22.6% of students were smokers.
- Factors associated with smoking included higher father's education, alcohol consumption, living with smokers, and depression.
- Exposure to second-hand smoke was linked to former, light, and heavy smoking.
Conclusions:
- Smoking prevention and cessation programs should involve the wider community due to second-hand smoke exposure.
- Prioritizing depression screening for student smokers is essential for post-conflict public health rebuilding.
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
635
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
635
Observational Studies
10.2K
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...
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...
10.2K
Stress Prevention and Stress Management Techniques IV
86
Stress often leads to unhealthy habits like smoking, excessive drinking, and overeating, which offer short-term relief but ultimately increase long-term health risks. These behaviors create a cycle that temporarily lowers stress levels but can result in severe long-term health consequences. Breaking these habits is essential to reduce the risk of chronic diseases and improve overall well-being. Three primary changes that support better health include quitting smoking, reducing alcohol intake,...
86
Longitudinal Research
12.8K
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...
12.8K
Criteria for Causality: Bradford Hill Criteria - II
805
The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
805
Bias in Epidemiological Studies
842
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:
842


