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. 2018 Dec 17;13(12):e0208632.
doi: 10.1371/journal.pone.0208632. eCollection 2018.

Who self-medicates? Results from structural equation modeling in the Greater Paris area, France

Affiliations

Who self-medicates? Results from structural equation modeling in the Greater Paris area, France

A Vanhaesebrouck et al. PLoS One. .

Abstract

Objectives: Our study aimed to describe the prevalence of self-medication among the Paris adult population and to identify the factors associated with self-medication.

Materials and methods: This cross-sectional study was based on data collected from the SIRS cohort (a French acronym for "Health, inequalities and social ruptures") in 2005 in the Paris metropolitan area using a face-to-face administration questionnaire among a representative sample of 3,023 French-speaking adults. Structural equation models were used to investigate the factors associated with self-medication in the overall population and according to income.

Results: The prevalence of self-medication in the past four weeks was 53.5% in the Paris metropolitan area. Seven factors were directly associated with self-medication in the structural equation model. Self-medication was found more common among women, young people, in active employment or student, with a high income, but also among people with a health information seeking behavior, with a high daily mobility, and/or with a history of unmet healthcare needs due to economic reasons. When looking at these coefficients according to income, the association between self-medication and daily mobility appeared stronger in the bottom quartile of income whereas it was no longer significant in the rest of the survey population.

Conclusion: Self-medication is a frequent practice in the Paris metropolitan area. This study confirms the role of some factors found to be associated with self-medication in the literature such as age or gender and draws attention to other factors rarely explored such as daily mobility, especially among people with a low income, or health information seeking behavior.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Hypothesized path diagram of self-medication, n = 2872.
Ellipses: latent variables; boxes: observed variables. Arrows starting from the same explanatory variable are in the same color. For the sake of clarity, indicators of latent variables are not shown. Indicators of self-perceived health are general health, physical health and psychological health. Indicators of chronic disease are regular treatment or follow-up, chronic health condition and “at least one condition among those listed over the last 12 months” (see note in Table 1). Indicators of daily mobility are “where they usually meet friends”, “where they usually go for a walk” and “where they usually go to the restaurant, to the café”. Indicators of health seeking information are researching information or advice on an illness or a symptom, researching information on healthcare news and researching information or advice on a medicine or a treatment. Indicators of self-perceived susceptibility to disease are “You generally catch everything that lays around”, “You become ill more easily than others” and “Your body do not seem to resist very well to disease”.
Fig 2
Fig 2. Path diagram of self-medication, n = 2893.
Ellipses: latent variables; boxes: observed variables. Arrows starting from the same explanatory variable are in the same color. All coefficients are standardized. Robust CFI = 0.915. Robust RMSEA = 0.039 [0.036–0.042] *: <0.05 **: <0.001.

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