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Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

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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:  
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The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
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Testing Club Convergence in Female Smoking Prevalence.

Fabrizio Ferretti1, Michele Mariani1, Elena Sarti1

  • 1Department of Communication and Economics, School of Social Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy.

Frontiers in Global Women'S Health
|July 28, 2022
PubMed
Summary
This summary is machine-generated.

Global smoking rates among women did not converge. However, analysis identified distinct country clubs with similar smoking trends, showing lower cigarette affordability correlates with lower female smoking prevalence.

Keywords:
affordabilityclubsconvergencefemale smoking prevalenceordered logit model

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Area of Science:

  • Public Health
  • Econometrics
  • Sociology

Background:

  • Smoking prevalence among women varies globally.
  • Understanding trends in female smoking is crucial for public health interventions.
  • Previous research has not fully explored convergence patterns in female smoking rates.

Purpose of the Study:

  • To investigate the convergence of female smoking prevalence across 191 countries from 1990 to 2019.
  • To identify country clusters exhibiting similar smoking prevalence trajectories.
  • To assess the influence of cigarette affordability on club membership.

Main Methods:

  • Applied a non-linear time-varying factor model (Phillips and Sul) to identify convergence clubs.
  • Utilized an ordered logit regression to analyze the impact of cigarette affordability.
  • Analyzed data from 191 countries over a 30-year period (1990-2019).

Main Results:

  • The hypothesis of global convergence in female smoking rates was rejected.
  • Five clubs of increasing smoking prevalence and nine clubs of decreasing prevalence were identified.
  • Increased cigarette affordability (higher income-price ratio) was associated with a higher probability of belonging to a low-prevalence smoking club.

Conclusions:

  • Female smoking prevalence does not exhibit global convergence.
  • Country-specific clustering reveals distinct patterns in smoking trends.
  • Economic factors, specifically cigarette affordability, play a significant role in shaping female smoking prevalence.