Literature DB >> 26622171

Associated factors vs risk factors in cross-sectional studies.

David Antay-Bedregal1, Evelyn Camargo-Revello1, German F Alvarado2.   

Abstract

Entities:  

Year:  2015        PMID: 26622171      PMCID: PMC4654543          DOI: 10.2147/PPA.S98023

Source DB:  PubMed          Journal:  Patient Prefer Adherence        ISSN: 1177-889X            Impact factor:   2.711


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Dear editor We have read with great interest the study of Karukunchit et al1 published in Patient Preference and Adherence. This study is important because it investigates a health problem that has not been well studied. However, we have some comments: It should be noted that cross-sectional studies are the best choice when the aim of the research is to estimate the prevalence of a characteristic in a specific population, they may also be useful if we wish to evaluate factors associated with a disease or condition.2 On the other hand, when we wish to evaluate risk factors, we need to estimate the incidence; this measure of occurrence can be computed in longitudinal studies (involving follow-up); clear examples of this are cohort studies. That is why cross-sectional studies can only estimate the prevalence and associated factors of a condition or disease, unless we can assure temporality.3 Another comment that we would like to make is about the use of odds ratio vs prevalence ratio. When working with a frequent outcome in the context of a cross-sectional study, the use of the odds ratio overestimates the association.4,5 In the study of Karukunchit et al,1 the outcome is frequent, therefore, the use of prevalence ratio would have been a better measure of association. Dear editor Thank you very much for taking the time to read our paper and for your helpful critique on our method and measures. We note the difference between prevalence and risk factors and agree that a cohort study would have been a more useful approach. However, the disadvantages of using a cohort study design were threefold: (1) participants must be followed over a prolonged period of time for observations; (2) the possible loss of study participants to follow up; and (3) high costs. Moreover, in a retrospective cohort study the investigators must collect historical data on risk factors.1,2 In our study we did not collect historical data on risk factors such as body mass index and occupational characteristics. Thank you for also pointing out the fact that a prevalence ratio would have been a preferred measure and that an odds ratio may have over-estimated the prevalence. Reading the articles you referred to in your comments has furthered our understanding about this preferred measure. However, most of the recent studies we reviewed showed that the odds ratio (OR) remains the most popular measure of the exposure disease relationship in epidemiology.3–6 The OR has an important role in describing the results of cross-sectional studies, mainly due to mathematical convenience and the easy availability of advanced statistical or logistic regression analysis. Therefore, we reported the OR to evaluate risk factor associations.2
  5 in total

1.  Use of the prevalence ratio v the prevalence odds ratio as a measure of risk in cross sectional studies.

Authors:  O Axelson; M Fredriksson; K Ekberg
Journal:  Occup Environ Med       Date:  1994-08       Impact factor: 4.402

2.  Musculoskeletal symptoms and associated risk factors in a large sample of Chinese workers in Henan province of China.

Authors:  Shanfa Yu; Ming-Lun Lu; Guizhen Gu; Wenhui Zhou; Lihua He; Sheng Wang
Journal:  Am J Ind Med       Date:  2011-11-28       Impact factor: 2.214

3.  Prevalence and risk factor analysis of lower extremity abnormal alignment characteristics among rice farmers.

Authors:  Usa Karukunchit; Rungthip Puntumetakul; Manida Swangnetr; Rose Boucaut
Journal:  Patient Prefer Adherence       Date:  2015-06-17       Impact factor: 2.711

4.  Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio.

Authors:  Aluísio J D Barros; Vânia N Hirakata
Journal:  BMC Med Res Methodol       Date:  2003-10-20       Impact factor: 4.615

5.  Human Papillomavirus prevalence and probable first effects of vaccination in 20 to 25 year-old women in Germany: a population-based cross-sectional study via home-based self-sampling.

Authors:  Yvonne Deleré; Cornelius Remschmidt; Josefine Leuschner; Melanie Schuster; Michaela Fesenfeld; Achim Schneider; Ole Wichmann; Andreas M Kaufmann
Journal:  BMC Infect Dis       Date:  2014-02-19       Impact factor: 3.090

  5 in total
  2 in total

1.  Determinants of hypertension among adults in Bangladesh as per the Joint National Committee 7 and 2017 American College of Cardiology/American Hypertension Association hypertension guidelines.

Authors:  Gulam Muhammed Al Kibria; Krystal Swasey; Md Zabir Hasan; Allysha Choudhury; Rajat Das Gupta; Samuel A Abariga; Atia Sharmeen; Vanessa Burrowes
Journal:  J Am Soc Hypertens       Date:  2018-10-22

2.  Factors associated with hypertension among adults in Nepal as per the Joint National Committee 7 and 2017 American College of Cardiology/American Heart Association hypertension guidelines: a cross-sectional analysis of the demographic and health survey 2016.

Authors:  Rajat Das Gupta; Sojib Bin Zaman; Kusum Wagle; Reese Crispen; Mohammad Rashidul Hashan; Gulam Muhammed Al Kibria
Journal:  BMJ Open       Date:  2019-08-10       Impact factor: 2.692

  2 in total

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