DOI: 10.1177/20552076261416726 ISSN: 2055-2076

Association between BMI and dyslipidemia in patients with severe mental disorders: An electronic health record study

Kangjun Wu, Yujian Lu, Yan Zhang, Anping Liu, Yuefang Wang, Xiandong Shen, Lei Shi
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Background

It's well known that obesity is a significant risk factor for dyslipidemia in the general population, but research related to individuals with mental disorders remains scarce. This study aimed to investigate the association between body mass index (BMI) and dyslipidemia among adult patients with severe mental disorders (SMD).

Methods

We implemented a cross-sectional study based on electronic health records. A total of 1145 adult SMD patients who underwent health examinations in 2022 were selected as study subjects. The multivariate logistic regression was used to explore association between BMI and dyslipidemia (including specific lipid abnormalities), and the exposure-response curves were plotted for whole population and subgroups.

Results

Among the study subjects, 574 SMD patients had dyslipidemia. Compared with patients of normal weight, underweight was negatively associated with dyslipidemia ( OR = 0.47, 95% CI : 0.24–0.94), while overweight ( OR = 1.75, 95% CI : 1.33–2.30) and obesity ( OR = 2.26, 95% CI : 1.59–3.21) were positively associated with dyslipidemia. The OR per 1.0 kg/m 2 increases in BMI was 1.11 (95% CI : 1.08–1.15). The exposure-response curves indicated that associations between BMI and dyslipidemia generally followed an S-shaped curves. Across different subgroups, the association exhibited variations, with greater strength observed among females, individuals aged ≥60 years, and those with hypertension, diabetes, and mental retardation accompanied by mental disorders. Associations between BMI and specific blood lipid abnormalities varied across populations. However, there were no significant interactions between all subgroup factors and BMI.

Conclusions

In the management of SMD patients, it is crucial to strengthen weight control and implement targeted interventions based on individual characteristics and specific types of dyslipidemia.

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