METHODS: A sample of 3895 individuals without known diabetes underwent detailed interview and health examination, including anthropometric and biochemical evaluation, between 2004 and 2007. Pearson's correlation, analysis of variance and multiple linear regression analyses were used to examine the influence of ethnicity on HbA(1c) .
RESULTS: As fasting plasma glucose increased, HbA(1c) increased more in Malays and Indians compared with Chinese after adjustment for age, gender, waist circumference, serum cholesterol, serum triglyceride and homeostasis model assessment of insulin resistance (P-interaction < 0.001). This translates to an HbA(1c) difference of 1.1 mmol/mol (0.1%, Indians vs. Chinese), and 0.9 mmol/mol (0.08%, Malays vs. Chinese) at fasting plasma glucose 5.6 mmol/l (the American Diabetes Association criterion for impaired fasting glycaemia); and 2.1 mmol/mol (0.19%, Indians vs. Chinese) and 2.6 mmol/mol (0.24%, Malays vs. Chinese) at fasting plasma glucose 7.0 mmol/l, the diagnostic criterion for diabetes mellitus.
CONCLUSIONS: Using HbA(1c) in place of fasting plasma glucose will reclassify different proportions of the population in different ethnic groups. This may have implications in interpretation of HbA(1c) results across ethnic groups and the use of HbA(1c) for diagnosing diabetes mellitus.
METHODS: Two separate studies were conducted among adult community-dwelling Singapore residents of Chinese, Malay or Indian ethnicity where participants completed self-administered questionnaires. In the first study, secondary data analysis was conducted using confirmatory factor analysis (CFA) to shorten the PMH instrument. In the second study, the newly developed short PMH instrument and other scales were administered to 201 residents to establish its factor structure, validity and reliability.
RESULTS: A 20-item short PMH instrument fulfilling a higher-order six-factor structure was developed following secondary analysis. The mean age of the participants in the second study was 41 years and about 53% were women. One item with poor factor loading was further removed to generate a 19-item version of the PMH instrument. CFA demonstrated a first-order six-factor model of the short PMH instrument. The PMH-19 instrument and its subscales fulfilled criterion validity hypotheses. Internal consistency and test-retest reliability of the PMH-19 instrument were high (Cronbach's α coefficient = 0.87; intraclass correlation coefficient = 0.93, respectively).
CONCLUSIONS: The 19-item PMH instrument is multidimensional, valid and reliable, and most importantly, with its reduced administration time, the short PMH instrument can be used to measure and evaluate PMH in Asian communities.
METHODS: We conducted a nationally representative survey among 1925 adults aged 18-79 years of Chinese, Malay, Indian or other ethnicity. Participants reported socio-demographic characteristics and completed the PMH-I along with measures of health-related quality of life (HRQoL) and psychological distress. Construct validity of the PMH-I was assessed using confirmatory factor analysis and concurrent validity was tested through correlation with other psychological measures. Normative PMH values and differences in population subgroups were estimated.
RESULTS: The six-factor-higher-order structure of the PMH-I comprising six subscales of general coping, emotional support, spirituality, interpersonal skills, personal growth and autonomy and global affect was confirmed. Concurrent validity was shown through significant positive correlation of the total PMH score and its subscales with HRQoL and an inverse correlation with psychological distress. Weighted age, gender and ethnicity-specific norms were derived for the Singapore population. Total PMH was significantly higher in participants aged over 40 years as compared with 18-29 year olds and in non-Chinese ethnic groups as compared with Chinese. These differences were observed for all PMH-I subscales, with the exception of emotional support and interpersonal skills score differences by age. In contrast, gender, marital status, and education level were significantly associated with some of the subscales, but not with total PMH.
CONCLUSIONS: These results support the psychometric properties of the PMH-I in a multi-ethnic Asian population sample. The generalizable population-based norms support the application of the PMH-I for measuring mental health and assessing its determinants within the Singapore general population.