OBJECTIVE: This study assessed the diet quality of households by their type of engagement in homestead aquaculture and/or horticulture. Socio-demographic determinants of diet quality were also studied.
METHOD: Diet quality was assessed using a nutrient adequacy ratio (NAR), based on the preceding 7 days' dietary recall at the household level. Adult male equivalent units (AMEs) were used for age- and sex-specific intra-household distribution of household intakes. Mean adequacy ratios (MAR) were computed as an overall measure of diet quality, using NAR.
RESULTS: Better diet quality (mean ± SD) was associated with households engaged in both homestead aquaculture and horticulture (0.43 ± 0.23; p < 0.001) compared to only one type of agriculture (0.38 ± 0.20) or none (0.36 ± 0.20). Tukey's post-hoc test confirmed significant differences in diet quality between both and either engagement (0.05 ± 0.01, p < 0.001), both and no engagement (0.07 ± 0.01, p < 0.001), and either and no engagement households (0.02 ± 0.01, p < 0.001). Beyond farm production of nutrient-rich foods, generalized estimating equations showed that diet quality was influenced by the higher educational level and occupation of adult household members, higher daily per capita food expenditure, sex, family size and region.
CONCLUSIONS: Projects that promote and support household engagement in both homestead aquaculture and horticulture have the potential to improve the diet quality of households.
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: A total of 590 preschoolers, comprising 317 boys and 273 girls were included. Pre-pilot parental questionnaires were used to assess diet, physical activity (PA) and sedentary behaviour practices and anthropometry was assessed in preschoolers and their parents.
RESULTS: Multiple logistic regression analyses showed that preschoolers with more frequent weekly intake of snacks [OR 2.7; 95% CI, 1.6-4.4; p diet, physical activity and sedentary behaviour factors were significantly associated with SSB intake among Malaysian preschoolers. Continued effort is required to encourage healthier beverage choices, as well as healthy diet and active lifestyle practices among children during the critical early years of growth and development.
Methods: We used information of the EPIC-NL cohort, a prospective cohort of 39 393 men and women, aged 20-70 years at recruitment. A lifestyle questionnaire and a validated food frequency questionnaire were administered at recruitment (1993-97). Low adherence to a Mediterranean-style diet was used to determine an unhealthy dietary pattern. Lifestyle-related factors included body mass index, waist circumference, smoking status, physical activity level, dietary supplement use and daily breakfast consumption. Multivariate logistic regression analyses were performed for the total population and by strata of educational level.
Results: In total 30% of the study population had an unhealthy dietary pattern: 39% in the lowest educated group and 20% in the highest educated group. Physical inactivity, a large waist circumference, no dietary supplement use and skipping breakfast were associated with an unhealthy dietary pattern in both low and high educated participants. Among low educated participants, current smokers had a greater odds of an unhealthy diet compared with never smokers: OR 1.42 (95% CI: 1.25; 1.61). This association was not observed in the high educated group.
Conclusions: Most associations between lifestyle-related factors and unhealthy diet were consistent across educational levels, except for smoking. Only among low educated participants, current smokers reported an unhealthier dietary pattern in comparison to never smokers. These results can be used in the development of targeted health promotion strategies.
METHOD: This cross-sectional study assessed the level of general nutrition knowledge in a convenience sample of Australian carers (C) of people with ID and compared this to the general Australian community (CM). Nutrition knowledge was evaluated using the validated General Nutrition Knowledge Questionnaire. Total knowledge score as well as performance on instrument sub-sections (dietary guidelines, nutrient sources, healthy food choices and diet disease relationships) were assessed (expressed as %). Knowledge scores were adjusted for known confounders (age, sex, education level, BMI, living arrangement and English spoken at home) using generalised linear modelling.
RESULTS: A total of 589 participants were recruited (C: n = 40; CM: n = 549). Age (C: 40.8 ± 12.1 year; CM: 37.8 ± 13.3 years; P = 0.145), sex distribution (C: 62.5%; CM: 67.2% female; P = 0.602) and English spoken at home (C: 82.5%; CM: 89.6%; P = 0.183) were similar between groups, but BMI (C: 28.5 ± 5.7 kgm-2 ; CM: 25.3 kgm-2 ; P = 0.002) was significantly lower and tertiary education (C: 52.5%; CM: 85.1%; P diet for people with ID in group homes.
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.
METHODS: Using 3 d of dietary records, FA intakes of 333 recruited patients were calculated using a food database built from laboratory analyses of commonly consumed Malaysian foods. Plasma triacylglycerol (TG) and erythrocyte FAs were determined by gas chromatography.
RESULTS: High dietary saturated fatty acid (SFA) and monounsaturated fatty acid (MUFA) consumption trends were observed. Patients on HD also reported low dietary ω-3 and ω-6 polyunsaturated fatty acid (PUFA) consumptions and low levels of TG and erythrocyte FAs. TG and dietary FAs were significantly associated respective to total PUFA, total ω-6 PUFA, 18:2 ω-6, total ω-3 PUFA, 18:3 ω-3, 22:6 ω-3, and trans 18:2 isomers (P < 0.05). Contrarily, only dietary total ω-3 PUFA and 22:6 ω-3 were significantly associated with erythrocyte FAs (P < 0.01). The highest tertile of fish and shellfish consumption reflected a significantly higher proportion of TG 22:6 ω-3. Dietary SFAs were directly associated with TG and erythrocyte MUFA, whereas dietary PUFAs were not.
CONCLUSION: TG and erythrocyte FAs serve as biomarkers of dietary PUFA intake in patients on HD. Elevation of circulating MUFA may be attributed to inadequate intake of PUFAs.
METHODS: This cross-sectional study was conducted among 392 schoolchildren aged 9-11 years, cluster sampled from five randomly selected schools in Kuala Lumpur. Whole-grain and fatty acids intakes were assessed by 3-day, 24-h diet recalls. All whole-grain foods were considered irrespective of the amount of whole grain they contained.
RESULTS: In total, 55.6% (n = 218) were whole-grain consumers. Mean (SD) daily intake of whole grain in the total sample was 5.13 (9.75) g day-1 . In the whole-grain consumer's only sample, mean (SD) intakes reached 9.23 (11.55) g day-1 . Significant inverse associations were found between whole-grain intake and saturated fatty acid (SAFA) intake (r = -0.357; P