ArticleBMC public health2025
Determination of the optimal cutoff point for the suboptimal health status questionnaire: a latent profile analysis.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe Suboptimal Health Status Questionnaire (SHSQ-25) is a widely used tool for assessing suboptimal health, however, the determination of an optimal cutoff point remains unclear. This study aimed to determine the optimal cutoff point for the SHSQ-25 using latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses.
methodsA cross-sectional online survey was conducted among adults aged 18 years and above in five regions in China. Participants completed questionnaires assessing demographic characteristics and suboptimal health status using the SHSQ-25. LPA was applied to identify distinct subgroups based on participants' responses to the SHSQ-25 items. ROC analysis was performed to establish the optimal cutoff point for the SHSQ-25. The optimal cutoff point was determined using the maximum Youden index.
resultsA total of 4918 participants (mean age = 30.1 ± 12.6 years) were included in the final analysis. The majority of participants were female (73.6%), college-educated (60.1%), single (55.1%), and living with others (93.5%). The LPA revealed a 3-profile model, including high-risk group (19.0%), middle-risk group (51.4%), and a low-risk group (29.6%). The optimal cutoff point for the SHSQ-25 was determined to be 44, maximizing sensitivity (97.53%) and specificity (97.77%) in identifying individuals with suboptimal health. Furthermore, individuals living with others exhibited a lower likelihood of developing suboptimal health compared to those living alone, even after adjusting for demographic factors (OR = 0.617, p < 0.001).
conclusionsThis study determined an optimal cutoff point of 44 for the SHSQ-25, enhancing its utility in identifying individuals with suboptimal health. These findings have implications for clinical practice, public health interventions, and future research endeavors aimed at improving the identification, understanding, and management of suboptimal health.
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