OBJECTIVE: The study aimed to derive dietary patterns empirically and to examine the consistency and generalizability of patterns across sex, ethnicity, and urban status in a working population.
DESIGN: This was a cross-sectional study using data from the Clustering of Lifestyle Risk Factors and Understanding its Association with Stress on Health and Well-Being among School Teachers in Malaysia study collected between August 2014 and November 2015. Dietary intake was assessed using a food frequency questionnaire, and dietary patterns were derived using factor analysis.
PARTICIPANTS/SETTING: Participants were teachers from selected public schools from three states in Peninsular Malaysia (n=4,618).
MAIN OUTCOME MEASURES: Dietary patterns derived using factor analysis.
STATISTICAL ANALYSES PERFORMED: Separate factor analysis was conducted by sex, ethnicity, and urban status to identify dietary patterns. Eigenvalue >2, scree plot, Velicer's minimum average partial analysis, and Horn's parallel analysis were used to determine the number of factors to retain. The interpretability of each dietary pattern was evaluated. The consistency and generalizability of dietary patterns across subgroups were assessed using the Tucker congruence coefficient.
RESULTS: There was no subgroup-specific dietary pattern found. Thus, dietary patterns were derived using the pooled sample in the final model. Two dietary patterns (Western and Prudent) were derived. The Western dietary pattern explained 15.4% of total variance, characterized by high intakes of refined grains, animal-based foods, added fat, and sugar-sweetened beverages as well as fast food. The Prudent dietary pattern explained 11.1% of total variance and was loaded with pulses, legumes, vegetables, and fruits.
CONCLUSIONS: The derived Western and Prudent dietary patterns were consistent and generalizable across subgroups of sex, ethnicity, and urban status. Further research is needed to explore associations between these dietary patterns and chronic diseases.
METHODS: An analysis was conducted among 2237 older adults who participated in a longitudinal study on aging (LRGS TUA). This study involved four states in Malaysia, with 49.4% from urban areas. Respondents were divided into three categories of SES based on percentile, stratified according to urban and rural settings. SES was measured using household income.
RESULTS: The prevalence of low SES was higher among older adults in the rural area (50.6%) as compared to the urban area (49.4%). Factors associated with low SES among older adults in an urban setting were low dietary fibre intake (Adj OR:0.91),longer time for the Timed up and Go Test (Adj OR:1.09), greater disability (Adj OR:1.02), less frequent practice of caloric restriction (Adj OR:1.65), lower cognitive processing speed score (Adj OR:0.94) and lower protein intake (Adj OR:0.94). Whilst, among respondents from rural area, the factors associated with low SES were lack of dietary fibre intake (Adj OR:0.79), lower calf circumference (Adj OR: 0.91), lesser fresh fruits intake (Adj OR:0.91), greater disability (Adj OR:1.02) and having lower score in instrumental activities of daily living (Adj OR: 0.92).
CONCLUSION: Lower SES ismore prevalent in rural areas. Poor dietary intake, lower fitness and disability were common factors associated with low in SES, regardless of settings. Factors associated with low SES identifiedin both the urban and rural areas in our study may be useful inplanning strategies to combat low SES and its related problems among older adults.
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.
DESIGN: DP were derived from the MANS FFQ using principal component analysis. The cross-sectional association of the derived DP with prevalence of overweight was analysed.
SETTING: Malaysia.
PARTICIPANTS: Nationally representative sample of Malaysian adults from MANS (2003, n 6928; 2014, n 3000).
RESULTS: Three major DP were identified for both years. These were 'Traditional' (fish, eggs, local cakes), 'Western' (fast foods, meat, carbonated beverages) and 'Mixed' (ready-to-eat cereals, bread, vegetables). A fourth DP was generated in 2003, 'Flatbread & Beverages' (flatbread, creamer, malted beverages), and 2014, 'Noodles & Meat' (noodles, meat, eggs). These DP accounted for 25·6 and 26·6 % of DP variations in 2003 and 2014, respectively. For both years, Traditional DP was significantly associated with rural households, lower income, men and Malay ethnicity, while Western DP was associated with younger age and higher income. Mixed DP was positively associated with women and higher income. None of the DP showed positive association with overweight risk, except for reduced adjusted odds of overweight with adherence to Traditional DP in 2003.
CONCLUSIONS: Overweight could not be attributed to adherence to a single dietary pattern among Malaysian adults. This may be due to the constantly morphing dietary landscape in Malaysia, especially in urban areas, given the ease of availability and relative affordability of multi-ethnic and international foods. Timely surveys are recommended to monitor implications of these changes.