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
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: A total of 50 obese children (7-11 years old) were randomized to the intervention group (IG, n = 25) or the control group (CG, n = 25). Data were collected at baseline, at follow-up (every month) and at six months after the end of the intervention. IG received stage-based lifestyle modification intervention based on the Nutrition Practice Guideline for the Management of Childhood Obesity, while CG received standard treatment. Changes in body composition, physical activity and dietary intake were examined in both the intervention and control groups.
RESULTS: Both groups had significant increases in weight (IG: 1.5 ± 0.5 kg; CG: 3.9 ± 0.6 kg) (p
METHODS: A cross-sectional survey was conducted among a sample of 416 (53% male and 47% female) undergraduate students, aged 18-26 years old, between January 6 and April 6, 2019, from colleges of Health Sciences at Jazan University in the Kingdom of Saudi Arabia (K.S.A). Students completed a self-administered questionnaire and recorded their measured anthropometric parameters.
RESULTS: The prevalence of overweight (20.4%) and obesity (14.9%) were relatively high among the participants. There were statistically significant associations between Body Mass Index (BMI) and the different settings of food consumption (i.e., dining on a table (or) in the Islamic way: squatting on the ground) (p<0.001)). BMI was also associated with students' dietary habits regarding consuming food, snacks, and drinking carbonated beverages while watching television (p<0.001), as well as consuming the same pattern of food/drink while watching television, playing video games on mobile phones or computers (p<0.001). Nearly most of the students were oblivious to the fact that metabolic syndrome, reproductive disorders, respiratory disorders along with liver and gallbladder diseases are some of the health risks associated with obesity.
CONCLUSION: The prevalence of obesity and overweight were reasonably high in our study sample and were affected by several factors related to students' eating behaviors and practices. This warrants the need for rigorous and frequent health education interventions on healthy eating behaviors, dietary practices, with an emphasis on the importance of adopting an active, healthy lifestyle.
METHODS: Item selection for the FFQ was based on explained variation and contribution to intake of energy and 24 nutrients. For validation, the FFQ was completed by 135 participants (25-70 y of age) of the Nutrition Questionnaires plus study. Per person, on average 2.8 (range 1-5) telephone-based 24-h dietary recalls (24HRs), two 24-h urinary samples, and one blood sample were available. Validity of 54 nutrients and 22 food groups was assessed by ranking agreement, correlation coefficients, attenuation factors, and ultimately deattenuated correlation coefficients (validity coefficients).
RESULTS: Median correlation coefficients for energy and macronutrients, micronutrients, and food groups were 0.45, 0.36, and 0.38, respectively. Median deattenuated correlation coefficients were 0.53 for energy and macronutrients, 0.45 for micronutrients, and 0.64 for food groups, being >0.50 for 18 of 22 macronutrients, 16 of 30 micronutrients and >0.50 for 17 of 22 food groups. The FFQ underestimated protein and potassium intake compared with 24-h urinary nitrogen and potassium excretion by -18% and -2%, respectively. Correlation coefficients ranged from 0.50 and 0.55 for (fatty) fish intake and plasma eicosapentaenoic acid and docosahexaenoic acid, and from 0.26 to 0.42 between fruit and vegetable intake and plasma carotenoids.
CONCLUSION: Overall, the validity of the 253-item Maastricht FFQ was satisfactory. The comprehensiveness of this FFQ make it well suited for use in The Maastricht Study and similar populations.
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.
Objective: To grade the evidence from published meta-analyses of prospective observational studies that assessed the association of dietary patterns, specific foods, food groups, beverages (including alcohol), macronutrients, and micronutrients with the incidence of CRC.
Data Sources: MEDLINE, Embase, and the Cochrane Library were searched from database inception to September 2019.
Evidence Review: Only meta-analyses of prospective observational studies with a cohort study design were eligible. Evidence of association was graded according to established criteria as follows: convincing, highly suggestive, suggestive, weak, or not significant.
Results: From 9954 publications, 222 full-text articles (2.2%) were evaluated for eligibility, and 45 meta-analyses (20.3%) that described 109 associations between dietary factors and CRC incidence were selected. Overall, 35 of the 109 associations (32.1%) were nominally statistically significant using random-effects meta-analysis models; 17 associations (15.6%) demonstrated large heterogeneity between studies (I2 > 50%), whereas small-study effects were found for 11 associations (10.1%). Excess significance bias was not detected for any association between diet and CRC. The primary analysis identified 5 (4.6%) convincing, 2 (1.8%) highly suggestive, 10 (9.2%) suggestive, and 18 (16.5%) weak associations between diet and CRC, while there was no evidence for 74 (67.9%) associations. There was convincing evidence of an association of intake of red meat (high vs low) and alcohol (≥4 drinks/d vs 0 or occasional drinks) with the incidence of CRC and an inverse association of higher vs lower intakes of dietary fiber, calcium, and yogurt with CRC risk. The evidence for convincing associations remained robust following sensitivity analyses.
Conclusions and Relevance: This umbrella review found convincing evidence of an association between lower CRC risk and higher intakes of dietary fiber, dietary calcium, and yogurt and lower intakes of alcohol and red meat. More research is needed on specific foods for which evidence remains suggestive, including other dairy products, whole grains, processed meat, and specific dietary patterns.
METHODS: The e-intervention group (n = 62) received a 6-month web-delivered intensive dietary intervention while the control group (n = 66) continued with their standard hospital care. Outcomes (DKAB and DSOC scores, FBG and HbA1c) were compared at baseline, post-intervention and follow-up.
RESULTS: While both study groups showed improvement in total DKAB score, the margin of improvement in mean DKAB score in e-intervention group was larger than the control group at post-intervention (11.1 ± 0.9 vs. 6.5 ± 9.4,p
OBJECTIVE: Our aim was to evaluate the nutritional status of BC survivors at 1 year after diagnosis.
DESIGN: This was a cross-sectional study of 194 participants from the MyBCC study, recruited within 1 year of their diagnosis. Participants completed a 3-day food diary.
PARTICIPANTS: Malaysian women (aged 18 years and older) who were newly diagnosed with primary BC, managed at the University Malaya Medical Center, and able to converse either in Malay, English, or Mandarin were included.
MAIN OUTCOME MEASURES: Dietary intake and prevalence of overweight or obesity among participants 1 year after diagnosis were measured.
STATISTICAL ANALYSES PERFORMED: Student's t test and analysis of variance or its equivalent nonparametric test were used for association in continuous variables.
RESULTS: About 66% (n=129) of participants were overweight or obese and >45% (n=86) had high body fat percentage 1 year after diagnosis. The participants' diets were low in fiber (median=8.7 g/day; interquartile range=7.2 g/day) and calcium (median=458 mg/day; interquartile range=252 mg/day). Ethnicity and educational attainment contributed to the differences in dietary intake among participants. Higher saturated fat and lower fiber intake were observed among Malay participants compared with other ethnic groups.
CONCLUSIONS: Overweight and obesity were highly prevalent among BC survivors and suboptimal dietary intake was observed. Provision of an individualized medical nutrition therapy by a qualified dietitian is crucial as part of comprehensive BC survivorship care.
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.
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.