MATERIALS AND METHODS: Data were used from the Well-being of the Singapore Elderly (WiSE) study, a nationally representative, cross-sectional survey among Singapore residents aged 60 years and above. Caregiver dependence was ascertained by asking the informant (the person who knows the older person best) a series of open-ended questions about the older person's care needs.
RESULTS: The older adult sample comprised 57.1% females and the majority were aged 60 to 74 years (74.8%), while 19.5% were 75 to 84 years, and 5.7% were 85 years and above. The prevalence of caregiver dependence was 17.2% among older adults. Significant sociodemographic risk factors of caregiver dependence included older age (75 to 84 years, and 85 years and above, P <0.001), Malay and Indian ethnicity (P <0.001), those who have never been married (P = 0.048) or have no education (P = 0.035), as well as being homemakers or retired (P <0.001). After adjusting for sociodemographic variables and all health conditions in multiple logistic regression analyses, dementia (P <0.001), depression (P = 0.011), stroke (P = 0.002), eyesight problems (P = 0.003), persistent cough (P = 0.016), paralysis (P <0.001), asthma (P = 0.016) and cancer (P = 0.026) were significantly associated with caregiver dependence.
CONCLUSION: Various sociodemographic and health-related conditions were significantly associated with caregiver dependence. Dependent older adults will put greater demands on health and social services, resulting in greater healthcare expenditures. Hence, effective planning, services and support are crucial to meet the needs of dependent older adults and their caregivers.
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: Standardised anthropometric measurements were compared against the self-reported values from 5,132 adult residents in a cross-sectional, epidemiological survey. Discrepancies in self-reports from measurements were examined by comparing overall mean differences. Intraclass correlations, Cohen's kappa and Bland-Altman plots with limits of agreement, and sub-analysis by sex and ethnicity were also explored.
RESULTS: Data were obtained from 5,132 respondents. The mean age of respondents was 43.9 years. Overall, the height was overestimated (0.2cm), while there was an underestimation of weight (0.8kg) and derived BMI (0.4kg/m2). Women had a larger discrepancy in height (0.35cm, 95% confidence interval [CI] 0.22 to 0.49), weight (-0.95kg, 95% CI -1.11 to -0.79) and BMI (-0.49kg/m2, 95% CI -0.57 to -0.41) compared with men. Height reporting bias was highest among Indians (0.28cm, 95% CI 0.12 to 0.44) compared with Chinese and Malays, while weight (-1.32kg, 95% CI -1.53 to -1.11) and derived BMI (-0.57kg/m2, 95% CI -0.67 to -0.47) showed higher degrees of underreporting among Malays compared with Chinese and Indians. Substantially high self-reported versus measured values were obtained for intraclass correlations (0.96-0.99, P<0.001) and kappa (0.74). For BMI categories, good to excellent kappa agreement was observed (0.68-0.81, P<0.0001).
CONCLUSION: Self-reported anthropometric estimates can be used, particularly in large epidemiological studies. However, sufficient care is needed when evaluating data from Indians, Malays and women as there is likely an underestimation of obesity prevalence.
MATERIALS AND METHODS: The Well-being of the Singapore Elderly (WiSE) study was a comprehensive single phase, cross-sectional survey. Stage 1 Geriatric Mental State-Automated Geriatric Examination for Computer Assisted Taxonomy (GMS-AGECAT) depression syndrome was used for this analysis. Association of depression and subsyndromal depression with sociodemographic characteristics, social support as well as comorbidity with chronic physical illnesses and quality of life was assessed.
RESULTS: The prevalence of GMS-AGECAT depression and subsyndromal depression was 3.7% and 13.4%, respectively. The odds of depression were significantly higher among those aged 75 to 84 (2.1) as compared to those aged 60 to 74 years and in those who had a history of depression diagnosis by a doctor (4.1). The odds of depression were higher among those of Indian and Malay ethnicities (5.2 and 3.2 times, respectively) as compared to those of Chinese ethnicity. Those with depression and subsyndromal depression were associated with more disability, poorer life satisfaction, and medical comorbidities.
CONCLUSION: Our study suggests that the prevalence of depression seems to have decreased as compared to a decade ago wherein the prevalence of depression was estimated to be 5.5%. This positive trend can be ascribed to concerted efforts across various disciplines and sectors, which need to be continually strengthened, monitored and evaluated.