Introduction: More than half of diabetes mellitus (DM) and pre-diabetes (pre-DM) cases remain undiagnosed, while existing risk assessment models are limited by focusing on diabetes mellitus only (omitting pre-DM) and often lack lifestyle factors such as sleep. This study aimed to develop a non-laboratory risk assessment model to detect undiagnosed diabetes mellitus and pre-diabetes mellitus in Chinese adults. Methods: Based on a population-representative dataset, 1,857 participants aged 18-84 years without self-reported diabetes mellitus, pre-diabetes mellitus, and other major chronic diseases were included. The outcome was defined as a newly detected diabetes mellitus or pre-diabetes by a blood test. The risk models were developed using logistic regression (LR) and interpretable machine learning (ML) methods. Models were validated using area under the receiver-operating characteristic curve (AUC-ROC), precision-recall curve (AUC-PR), and calibration plots. Two existing diabetes mellitus risk models were included for comparison. Results: The prevalence of newly diagnosed diabetes mellitus and pre-diabetes mellitus was 15.08%. In addition to known risk factors (age, BMI, WHR, SBP, waist circumference, and smoking status), we found that sleep duration, and vigorous recreational activity time were also significant risk factors of diabetes mellitus and pre-diabetes mellitus. Both LR (AUC-ROC = 0.812, AUC-PR = 0.448) and ML models (AUC-ROC = 0.822, AUC-PR = 0.496) performed well in the validation sample with the ML model showing better discrimination and calibration. The performance of the models was better than the two existing models. Conclusions: Sleep duration and vigorous recreational activity time are modifiable risk factors of diabetes mellitus and pre-diabetes in Chinese adults. Non-laboratory-based risk assessment models that incorporate these lifestyle factors can enhance case detection of diabetes mellitus and pre-diabetes. BACKGROUNDDiabetes mellitus (DM) is a major public health burden as it is common and chronic, and its complications including cardiovascular diseases, renal disease, and retinopathy can lead to disabilities and premature mortality 1 . Diabetes mellitus develops slowly and the progression from normal blood glucose to diabetes mellitus may take up to a decade 2 . Prediabetes mellitus (pre-DM) refers to the condition where blood glucose is between normal and diabetic levels. Globally, the prevalence of diabetes mellitus was estimated to be 9.3%

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ObjectivesTo develop an equivalent Chinese translation of the Person-Centered Primary Care Measure (PCPCM) and to establish its cultural adaptability and content validity through cognitive debriefing.DesignThe original English PCPCM was first translated into Chinese by double forward-translation by professional translators. The reconciliated Chinese version was then doubly back-translated into English by two other professional translators blinded to the forward-translation. On affirmation on its linguistic equivalence with the developers of the original English PCPCM, the reconciliated Chinese PCPCM was sent for cognitive debriefing with 20 Chinese-speaking primary care subjects by a trained interviewer using structured probing questions to collect their opinions on the clarity, comprehensibility and relevance of each item and response option in the Measure.SettingSubjects were invited from a primary care clinic in Hong Kong to undergo the cognitive debriefing interviews. The interviews were divided into four groups chronologically to allow revision of the items to be made in between.ParticipantsTen males and 10 females above the age of 18 completed the cognitive interviews. They were all Cantonese-speaking Chinese recruited by convenience sampling. Subjects with cognitive impairment, could not read Chinese, too old or too sick to complete the interviews were excluded from the study.ResultsAn average of 3.3 min (range 3–4 min) was required for the subjects to self-complete the Measure. All items were generally perceived to be easily understood and relevant. Modifications were made to items with the content validity index (CVI) on clarity or understanding <0.8 in each round of the interviews or if a majority of the subjects suggested rewording. Revisions were made to two items in the Chinese PCPCM throughout the whole cognitive debriefing process before the final version was confirmed. The average CVI on clarity of the Chinese PCPCM items ranged from 0.75 to 1. The average CVI on understanding ranged from 0.7 to 1. The average CVI on relevance ranged from 0.55 to 1.ConclusionsThe content validity of the PCPCM was ascertained in terms of its clarity, understandability and relevance to allow further testing of its psychometric properties in a larger Chinese population.