OBJECTIVE: To examine the relationships between health-related quality of life (HRQoL) scores with the stages of change of adequate physical activity and fruit and vegetables intake.
DESIGN: This was a cross-sectional study conducted among employees of the main campus and Engineering campus of Universiti Sains Malaysia (USM) during October 2009 and March 2010.
MAIN VARIABLES STUDIED: Data on physical activity and fruit and vegetable intake was collected using the WHO STEPS instrument for chronic disease risk factors surveillance. The Short Form-12 health survey (SF-12) was used to gather information on participants' HRQoL. The current stages of change are measured using the measures developed by the Pro-Change Behaviour Systems Incorporation.
STATISTICAL ANALYSIS: One way ANOVA and its non-parametric equivalent Kruskal-Wallis were used to compare the differences between SF-12 scores with the stages of change.
RESULTS: A total of 144 employees were included in this analysis. A large proportion of the participants reported inadequate fruits and vegetable intake (92.3%) and physical activity (84.6%). Mean physical and mental component scores of SF-12 were 50.39 (SD = 7.69) and 49.73 (SD = 8.64) respectively. Overall, there was no statistical significant difference in the SF-12 domains scores with regards to the stages of change for both the risk factors.
CONCLUSIONS: There were some evidence of positive relationship between stages of change of physical activity and fruit and vegetable intake with SF-12 scores. Further studies need to be conducted to confirm this association.
METHODS: Two cross-sectional studies were conducted in urban and rural areas of Yangon Region in 2013 and 2014 respectively, using the WHO STEPwise approach to surveillance of risk factors of NCDs. Through a multi-stage cluster sampling method, 1486 participants were recruited.
RESULTS: Age-standardized prevalence of the behavioral risk factors tended to be higher in the rural than urban areas for all included factors and significantly higher for alcohol drinking (19.9% vs. 13.9%; p = 0.040) and low fruit & vegetable consumption (96.7% vs. 85.1%; p = 0.001). For the metabolic risk factors, the tendency was opposite, with higher age-standardized prevalence estimates in urban than rural areas, significantly for overweight and obesity combined (40.9% vs. 31.2%; p = 0.023), obesity (12.3% vs.7.7%; p = 0.019) and diabetes (17.2% vs. 9.2%; p = 0.024). In sub-group analysis by gender, the prevalence of hypercholesterolemia and hypertriglyceridemia were significantly higher in urban than rural areas among males, 61.8% vs. 40.4%; p = 0.002 and 31.4% vs. 20.7%; p = 0.009, respectively. Mean values of age-standardized metabolic parameters showed higher values in urban than rural areas for both male and female. Based on WHO age-standardized Framingham risk scores, 33.0% (95% CI = 31.7-34.4) of urban dwellers and 27.0% (95% CI = 23.5-30.8) of rural dwellers had a moderate to high risk of developing CHD in the next 10 years.
CONCLUSION: The metabolic risk factors, as well as a moderate or high ten-year risk of CHD were more common among urban residents whereas behavioral risk factors levels were higher in among the rural people of Yangon Region. The high prevalences of NCD risk factors in both urban and rural areas call for preventive measures to reduce the future risk of NCDs in Myanmar.