Heterogenous subtypes of health literacy among individuals with Metabolic syndrome: a latent class analysis

Abstract

Objective To explore the heterogenous subtypes and the associated factors of health literacy among patients with metabolic syndrome.

Methods A cross-sectional study was conducted, and 337 patients with metabolic syndrome were recruited from Sir Run Run Shaw Hospital in Zhejiang Province from December 2021 to February 2022. The Social Support Questionnaire, Short version of the Health Literacy Scale European Questionnaire (HLS-EU-Q16), and MacArthur Scale of Subjective Social Status were used for investigation. Latent class analysis (LCA) was performed to explore the heterogenous subtypes of health literacy among Metabolic syndrome patients. Univariate analysis and logistic regression were used to identify the predictors of the latent classes.

Results The findings of LCA suggested that three heterogeneous subtypes of health literacy among individuals with metabolic syndrome were identified: high levels of health literacy, moderate levels of health literacy, and low levels of health literacy. The multinomial logistic regression results indicated that compared with low levels of health literacy class, the high levels of health literacy class were predicted by age (OR 0.932, 95%CI[0.900-0.966]), socio-economic status (OR 1.185, 95%CI[1.058–1.328]), and social support (OR 1.065, 95%CI[1.012–1.120]). Compared with low levels of health literacy class, the moderate levels of health literacy class were predicted by age (OR 0.964, 95%CI[0.934–0.995]), socio-economic status (OR 1.118, 95%CI[1.006–1.242]), male (OR 0.229, 95%CI[0.092–0.576]).

Conclusion The levels of health literacy among patients with metabolic syndrome can be divided into three heterogenous subtypes. The results can inform policy-makers and care professionals to design targeted interventions for different subgroups among patients with metabolic syndrome who are male, at older age, have less social support, and with disadvantaged socio-economic status to improve health literacy.

Keywords:

• MetS
• health literacy
• latent class analysis
• predictors

Acknowledgements

The authors would like to thank research participants.

Authors’ contributions

HZ and XYW designed this present study, HZ, XYW and DDC collected data, analyzed the data, and drafted the manuscript. HZ, XYW, DDC, JS, JJW, NQC, DJL, LWT, ZHY, EXX and PZ interpreted the data and revised the manuscript. All authors read and approved the final manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data is available upon a reasonable request from the corresponding author.

Additional information

Funding

This work was supported by Guizhou Provincial People’s hospital Yuan Ren cai Xiang Mu [2022]-18, shanghai sailing Program 21YF1422400, and Zhejiang Provincial Natural Science Foundation LY23G030.