OBJECTIVE: To examine ethnic differences in participation in medical check-ups among the elderly.
DESIGN: A nationally representative data set was employed. Multiple logistic regressions were utilised to examine the relationship between ethnicity and the likelihood of undergoing medical check-ups. The regressions were stratified by age, income, marital status, gender, household location, insurance access and health status. These variables were also controlled for in the regressions (including stratified regressions).
PARTICIPANTS: The respondents were required to be residents of Malaysia and not be institutionalised. Overall, 30,806 individuals were selected to be interviewed, but only 28,650 were actually interviewed, equivalent to a 93% response rate. Of those, only 2248 were used in the analyses, because 26,402 were others or below aged 60.
MAIN MEASURES: The dependent variable was participation in a medical check-up. The main independent variables were the three major ethnic groups in Malaysia (Malay, Chinese, Indian).
KEY RESULTS: Among the elderly aged 70-79 years, Chinese (aOR 1.89; 95% CI 1.28, 2.81) and Indians (aOR 2.39; 95% CI 1.20, 4.74) were more likely to undergo medical check-ups than Malays. Among the elderly with monthly incomes of ≤ RM999, Chinese (aOR 1.44; 95% CI 1.12, 1.85) and Indians (aOR 1.50; 95% CI 0.99, 2.28) were more likely to undergo medical check-ups than Malays. Indian males were more likely to undergo medical check-ups than Malay males (aOR 2.32; 95% CI 1.15, 4.67). Chinese with hypercholesterolaemia (aOR 1.45; 95% CI 1.07, 1.98) and hypertension (aOR 1.32; 95% CI 1.02, 1.72) were more likely to undergo medical check-ups than Malays.
CONCLUSIONS: There were ethnic differences in participation in medical check-ups among the elderly. These ethnic differences varied across age, income, marital status, gender, household location, insurance access and health status.
BACKGROUND: We report the 6-year incidence and progression of age-related cataract and associated risk factors in Malay adults living in Singapore.
DESIGN: Population-based cohort study.
PARTICIPANTS: A total of 3280 Malays aged 40+ years participated in baseline examinations of the Singapore Malay Eye Study (2004-2006). Six years later, 1901 (72.1% of eligible) baseline participants were re-examined.
METHODS: Cataract was assessed using lens photos, taken during eye examinations, following the Wisconsin Cataract Grading System.
MAIN OUTCOMES AND MEASURES: Incidence and progression of cortical, nuclear and posterior subcapsular (PSC) cataract. Poisson regression models and generalized estimating equations models (with Poisson link) were used to assess factors associated with cataract incidence and progression, respectively, adjusting for age, sex and other risk factors.
RESULTS: Age-adjusted 6-year incidence of cortical, nuclear and PSC cataract was 14.1%, 13.6% and 8.7%, respectively, and was strongly age-related (P for trend
OBJECTIVE: This study aimed to determine the parental barrier toward the reduction of excessive child screen time and its predictors among parents of children aged younger than 5 years in the Petaling District, Selangor, Malaysia.
METHODS: A cross-sectional study was conducted from April 2019 to June 2020 among 789 parent-child dyads attending child health clinics in the Petaling District. Validated self-administered questionnaires were used to capture information on sociodemographic, parental, child-related, and environmental factors and parental barriers. Stratified sampling with probability proportionate to size was employed. Data were analyzed using SPSS Statistics version 25 (IBM Corp). Descriptive analysis and bivariable analysis were performed before multiple linear regression was used to identify predictors of parental barriers.
RESULTS: The overall mean score of parental barriers was 3.51 (SD 0.83), indicating that the average numbers of barriers experienced by parents were more than 3. The multivariable analysis showed that the predictors of parental barriers included monthly household income (adjusted β=-.03, 95% CI -0.05 to -0.02), parents who worked in public sectors (adjusted β=.18, 95% CI 0.06 to 0.29), positive parental attitude on screens (adjusted β=.68, 95% CI 0.58 to 0.79), low parent self-efficacy to influence child's physical activity (adjusted β=-.32, 95% CI -0.43 to -0.20), and child screen time (adjusted β=.04, 95% CI 0.02 to 0.06).
CONCLUSIONS: The strongest predictor of parental barriers to reduce excessive child screen time was the positive parental attitude on screen time which could contribute to their abilities to limit child screen time. Thus, future intervention strategies should aim to foster correct parental attitudes toward screen time activities among young children.