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Background and objective: The way we think about schizophrenia today is profoundly different from the way this illness was seen in the twentieth century. We now know that the etiology of schizophrenia is multifactorial and reflects an interaction between genetic vulnerability and environmental contributors. Environmental risk factors such as pregnancy and birth complications, childhood trauma, migration, social isolation, urbanicity, and substance abuse, alone and in combination, acting at a number of levels over time, influence the individual’s likelihood to develop the disorder. There are no studies on mental health in Yemen in general and schizophrenia in particular. Thus, the aim of this study was to study the non-genetic risk factors of schizophrenia. The specific objectives were to compare exposure to suspected risk factors for schizophrenia in a cohort of schizophrenia patients with those randomly selected from the community.
Methods: The researchers approached inpatient in Al-Amal Hospital for Psychiatric Diseases with a diagnosis of schizophrenia. Patients from this list were then randomly selected using the card-shuffling technique. Patients were included in the study if a review of their records confirmed a diagnosis of schizophrenia according to DSM IV criteria, they were ≥18 years old, and had attended the clinics between the period January 2021 and December 2021. Controls were from general population by selected randomly from the list of censuses by simple random selection from Sana’a governorate.
Results: Regarding associated risk factors of schizophrenia, there was significant association with low income (OR= 7.1), loss work (OR=57), smoking (OR=5.9) , Khat chewing (OR=12.4), birth complications (OR=7.2) , 1-6 Apgar scores (OR=1.8), older paternal age (OR=3.2), the spring birth (OR=2.2), and winter birth (OR=1.9), childhood trauma (OR=1.9), cannabis (OR=7.4), hypertension(OR=4.7) , and diabetics (OR=6.6).
Conclusion: Future research in Yemen should also explore potential protective factors in groups at risk for psychotic disorders. A new area of research should involve big data and predictive models, by replacing traditional paper notes with electronic patient records.
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