Development and validation of a short-form suboptimal health status questionnaire
School of Medical and Health Sciences / Centre for Precision Health
Natural Science Foundation of Shandong Province / Scientific Research Foundation of Education Department of Yunnan Province
Background: Suboptimal health status (SHS) is a reversible, borderline state between optimal health and disease. Although this condition’s definition is widely understood, related questionnaires must be developed to identify individuals with SHS in various populations relative to predictive, preventive, and personalized medicine (PPPM/3PM). This study presents a short-form suboptimal health status questionnaire (SHSQ-SF) that appears to possess sufficient reliability and validity to assess SHS in large-scale populations. Methods: A total of 6183 participants enrolled from Southern China constituted a training set, while 4113 participants from Northern China constituted an external validation set. The SHSQ-SF includes nine key items from the Suboptimal Health Status Questionnaire-25 (SHSQ-25), an instrument that has been applied to Africans, Asians, and Caucasians. Item analysis and reliability and validity tests were carried out to validate the SHSQ-SF. The receiver operating characteristic (ROC) curve was used to identify an optimal cutoff value for SHS diagnosis, by which the area under the curve (AUC) and 95% confidence interval (CI) were determined. Results: Cronbach’s coefficient for the training dataset was 0.902; the split-half reliability was 0.863. The Kaiser–Meyer–Olkin (KMO) value was 0.880, and Bartlett’s test of sphericity was significant ( 2 = 32,929.680, p < 0.05). Both Kaiser’s criteria (eigenvalues > 1) and the scree plot revealed one factor explaining 57.008% of the total variance. Standardized factor loadings for the confirmatory factor analysis (CFA) indices ranged between 0.58 and 0.74, with 2/dƒ = 4.972, GFI = 0.996, CFI = 0.996, RFI = 0.989, and RMSEA = 0.031. The AUC was equal to 0.985 (95% CI: 0.983–0.988) for the training dataset. A cutoff value ( ≥ 11) was then identified for SHS diagnosis. The SHSQ-SF showed good discriminatory power for the external validation dataset (AUC = 0.975, 95% CI: 0.971–0.979) with a sensitivity of 96.2% and a specificity of 87.4%. Conclusions: We developed a short form of the SHS questionnaire that demonstrated sound reliability and validity when assessing SHS in Chinese residents. From a PPPM/3PM perspective, the SHSQ-SF is recommended for the rapid screening of individuals with SHS in large-scale populations. © 2023, The Author(s), under exclusive licence to European Association for Predictive, Preventive and Personalised Medicine (EPMA).