Background: Psychiatric patients are at increased risk of exposure to infection, which may be linked to their living facilities and behaviors. Limited knowledge on the prevalence of infection and its associated risk factors in psychiatric patients are available to the international medical communities. Thus, the aim of the current study was to assess seroprevalence of and its associated risk factors in psychiatric inpatients in Fars Province, southern Iran.
Methods: This cross-sectional study was carried out on psychiatric patients hospitalized in Ibn Sina Hospital affiliated to Shiraz University of Medical Sciences, Fars Province, southern Iran, March to July 2021. Blood samples were collected from 318 psychiatric patients and assessed for the detection of IgG against using enzyme-linked immunosorbent assay (ELISA). Moreover, structured questionnaires were completed for the participants at the time of sampling. Logistic regression analysis was used to assess possible associations between the latent toxoplasmosis and the variables.
Results: The overall seroprevalence of anti- IgG in psychiatric inpatients was 22.3% (71/318; 95% CI = 17.9-27.3). Multivariate analyses revealed that age > 30 years [adjusted odds ratio (AOR) = 2.24, 95% CI = 1.10-4.60, = 0.03], contact with cats (AOR = 2.52, 95% CI = 1.14-5.58, = 0.03), raw vegetable consumption (AOR = 3.65, 95% CI = 1.74-7.65, = 0.001), raw/undercooked meat consumption (AOR = 4.30, 95% CI = 1.47-12.63, = 0.008), suicide attempt (AOR = 3.77, 95% CI = 1.58-8.97, = 0.003) and cigarette smoking history (AOR = 0.38, 95% CI = 0.17-0.83, = 0.02) were independent risk factors for infection.
Conclusion: The current results demonstrated that contact with cats, raw vegetable consumption and raw/undercooked meat consumption were independent risk factors for seropositivity. Moreover, the current study showed significant associations between seropositivity of and suicide attempts as well as negative associations between seropositivity of and cigarette smoking in psychiatric inpatients using multivariate logistic regression.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237562 | PMC |
http://dx.doi.org/10.3389/fpsyt.2022.891603 | DOI Listing |
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