OBJECTIVES: To characterize dietary patterns among pregnant women living in the UAE and examine their associations with gestational weight gain and gestational weight rate.
METHODOLOGY: Data were drawn from the Mother-Infant Study Cohort, a two-year prospective cohort study of pregnant women living in the United Arab Emirates, recruited during their third trimester (n = 242). Weight gain during pregnancy was calculated using data from medical records. The Institute of Medicine's recommendations were used to categorize gestational weight gain and gestational weight gain rate into insufficient, adequate, and excessive. During face-to-face interviews, dietary intake was assessed using an 89-item culture-specific semi-quantitative food frequency questionnaire that referred to usual intake during pregnancy. Dietary patterns were derived by principal component analysis. Multiple logistic regression analyses were used to evaluate the associations of derived dietary patterns with gestational weight gain/gestational weight gain rate.
RESULTS: Two dietary patterns were derived, a "Diverse" and a "Western" pattern. The "Diverse" pattern was characterized by higher intake of fruits, vegetables, mixed dishes while the "Western" pattern consisted of sweets and fast food. The "Western" pattern was associated with excessive gestational weight gain (OR:4.04,95% CI:1.07-15.24) and gestational weight gain rate (OR: 4.38, 95% CI:1.28-15.03) while the "Diverse" pattern decreased the risk of inadequate gestational weight gain (OR:0.24, 95% CI:0.06-0.97) and gestational weight gain rate (OR:0.28, 95% CI:0.09-0.90).
CONCLUSION: The findings of this study showed that adherence to a "Diverse" pattern reduced the risk of insufficient gestational weight gain/gestational weight gain rate, while higher consumption of the "Western" pattern increased the risk of excessive gestational weight gain/gestational weight gain rate. In view of the established consequences of gestational weight gain on the health of the mother and child, there is a critical need for health policies and interventions to promote a healthy lifestyle eating through a life course approach.
METHODS: A total of 392 children participated in the FFQ development and 112 children aged 9-12 years participated in the validation phase; with a subsample of 50 children participating in the reproducibility phase. Three-day diet record (3DR) as the reference method in validation phase. Spearman correlations, mean difference, Bland-Altman plot and cross-classification analyses were used to assess validity. The reproducibility was tested through a repeat administration of the FFQ, with 1 month time interval. Reproducibility analyses involved intra-class correlation coefficient (ICC), Cronbach's alpha and cross-classification analyses.
RESULTS: The FFQ consisted of 156 whole grain food items from six food groups. Mean intake of whole grain in FFQ1 and 3DR were correlated well (r = 0.732), demonstrated good acceptance of the FFQ. Bland Altman plots showed relatively good agreement for both the dietary methods. Cross-classification of whole grain intake between the two methods showed that
METHOD: This is a cross-sectional market survey conducted from February to May 2023 on 3428 products sold in Malaysian supermarkets. Product information including the brand, name, nutrition information panel, food product indicator (front-of-pack nutrition labelling, NHC, other claims), ingredients list and manufacturer or importer were collected. Compliance of products carrying NHC and HCL is evaluated against local guidelines. Credibility as a healthy product is evaluated against the WHO Nutrient Profile Model for the Western Pacific Region on a subsample (products with HCL and/or NHC).
RESULTS: 53% of food products surveyed had food product indicators (n=1809). A total of 32% carried at least one NHC (n=1101), of which 47% had excellent overall compliance (n=522). Only 4% carried Malaysia's HCL (n=138), of which 48% had excellent nutrient compliance (n=66). Only 13% of the products carrying Malaysia's HCL and NHC could be identified as absolute healthy food products as defined by the WHO standard (n=147).
CONCLUSION: Although half of the products surveyed had food product indicators, merely half of them had excellent compliance towards the standards. Only 13% of the subsample qualified as healthy food products. Voluntary application of the local HCL was low among food industries. Ensuring high standards of compliance and credibility of food products in the Malaysian market is crucial for food companies and government authorities.
METHODS: Therefore, using linear programming, this study is aimed to develop a healthy and balanced menu with minimal cost in accordance to individual needs that could in return help to prevent cancer. A cross sectional study involving 100 adults from a local university in Kuala Lumpur was conducted in 3 phases. The first phase is the data collection for the subjects, which includes their socio demographic, anthropometry and diet recall. The second phase was the creation of a balanced diet model at a minimum cost. The third and final phase was the finalization of the cancer prevention menu. Optimal and balanced menus were produced based on respective guidelines of WCRF/AICR (World Cancer Research Fund/ American Institute for Cancer Research) 2007, MDG (Malaysian Dietary Guidelines) 2010 and RNI (Recommended Nutrient Intake) 2017, with minimum cost.
RESULTS: Based on the diet recall, most of subjects did not achieve the recommended micronutrient intake for fiber, calcium, potassium, iron, B12, folate, vitamin A, vitamin E, vitamin K, and beta-carotene. While, the intake of sugar (51 ± 19.8 g), (13% ± 2%) and sodium (2585 ± 544 g) was more than recommended. From the optimization model, three menus, which met the dietary guidelines for cancer prevention by WCRF/AICR 2007, MDG 2010 and RNI 2017, with minimum cost of RM7.8, RM9.2 and RM9.7 per day were created.
CONCLUSION: Linear programming can be used to translate nutritional requirements based on selected Dietary Guidelines to achieve a healthy, well-balanced menu for cancer prevention at minimal cost. Furthermore, the models could help to shape consumer food choice decision to prevent cancer especially for those in low income group where high cost for health food has been the main deterrent for healthy eating.
METHODS: We developed the International Diet-Health Index (IDHI) to measure health impacts of dietary intake across 186 countries in 2010, using age-specific and sex-specific data on country-level dietary intake, effects of dietary factors on cardiometabolic diseases and country-specific cardiometabolic disease profiles. The index encompasses the impact of 11 foods/nutrients on 12 cardiometabolic diseases, the mediation of health effects of specific dietary intakes through blood pressure and body mass index and background disease prevalence in each country-age-sex group. We decomposed the index into IDHIbeneficial for risk-reducing factors, and IDHIadverse for risk-increasing factors. The flexible functional form of the IDHI allows inclusion of additional risk factors and diseases as data become available.
RESULTS: By sex, women experienced smaller detrimental cardiometabolic effects of diet than men: (females IDHIadverse range: -0.480 (5th percentile, 95th percentile: -0.932, -0.300) to -0.314 (-0.543, -0.213); males IDHIadverse range: (-0.617 (-1.054, -0.384) to -0.346 (-0.624, -0.222)). By age, middle-aged adults had highest IDHIbeneficial (females: 0.392 (0.235, 0.763); males: 0.415 (0.243, 0.949)) and younger adults had most extreme IDHIadverse (females: -0.480 (-0.932, -0.300); males: -0.617 (-1.054, -0.384)). Regionally, Central Latin America had the lowest IDHIoverall (-0.466 (-0.892, -0.159)), while Southeast Asia had the highest IDHIoverall (0.272 (-0.224, 0.903)). IDHIoverall was highest in low-income countries and lowest in upper middle-income countries (-0.039 (-0.317, 0.227) and -0.146 (-0.605, 0.303), respectively). Among 186 countries, Honduras had lowest IDHIoverall (-0.721 (-0.916, -0.207)), while Malaysia had highest IDHIoverall (0.904 (0.435, 1.190)).
CONCLUSION: IDHI encompasses dietary intakes, health effects and country disease profiles into a single index, allowing policymakers a useful means of assessing/comparing health impacts of diet quality between populations.