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  1. Se CH, Chuah KA, Mishra A, Wickneswari R, Karupaiah T
    Nutrients, 2016 May 20;8(5).
    PMID: 27213446 DOI: 10.3390/nu8050308
    Consumption of white rice predisposes some Asian populations to increased risk of type 2 diabetes. We compared the postprandial glucometabolic responses to three newly-developed crossbred red rice variants (UKMRC9, UKMRC10, UKMRC11) against three selected commercial rice types (Thai red, Basmati white, Jasmine white) using 50-g carbohydrate equivalents provided to 12 normoglycaemic adults in a crossover design. Venous blood was drawn fasted and postprandially for three hours. Glycaemic (GI) and insulin (II) indices, incremental areas-under-the-curves for glucose and insulin (IAUCins), indices of insulin sensitivity and secretion, lactate and peptide hormones (motilin, neuropeptide-Y, orexin-A) were analyzed. The lowest to highest trends for GI and II were similar i.e., UKMRC9 < Basmati < Thai red < UKMRC10 < UKMRC11 < Jasmine. Postprandial insulinaemia and IAUCins of only UKMRC9 were significantly the lowest compared to Jasmine. Crude protein and fiber content correlated negatively with the GI values of the test rice. Although peptide hormones were not associated with GI and II characteristics of test rice, early and late phases of prandial neuropeptide-Y changes were negatively correlated with postprandial insulinaemia. This study indicated that only UKMRC9 among the new rice crossbreeds could serve as an alternative cereal option to improve diet quality of Asians with its lowest glycaemic and insulinaemic burden.
  2. Karupaiah T, Chuah KA, Chinna K, Pressman P, Clemens RA, Hayes AW, et al.
    Sci Rep, 2019 09 20;9(1):13666.
    PMID: 31541144 DOI: 10.1038/s41598-019-49911-6
    We conducted this cross-sectional population study with a healthy multi-ethnic urban population (n = 577) in Malaysia, combining nutritional assessments with cardiometabolic biomarkers defined by lipid, atherogenic lipoproteins, inflammation and insulin resistance. We found diametrically opposing associations of carbohydrate (246·6 ± 57·7 g, 54·3 ± 6·5%-TEI) and fat (total = 64·5 ± 19·8 g, 31·6 ± 5·5%-TEI; saturated fat = 14·1 ± 2·7%-TEI) intakes as regards waist circumference, HDL-C, blood pressure, glucose, insulin and HOMA2-IR as well as the large-LDL and large-HDL lipoprotein particles. Diets were then differentiated into either low fat (LF, <30% TEI or <50 g) or high fat (HF, >35% TEI or >70 g) and low carbohydrate (LC, <210 g) or high carbohydrate (HC, >285 g) which yielded LFLC, LFHC, HFLC and HFHC groupings. Cardiometabolic biomarkers were not significantly different (P > 0.05) between LFLC and HFLC groups. LFLC had significantly higher large-LDL particle concentrations compared to HFHC. HOMA-IR2 was significantly higher with HFHC (1·91 ± 1·85, P 1.7 in the HFHC group was 2.43 (95% CI: 1·03, 5·72) times more compared to LFLC while odds of having large-LDL <450 nmol/L in the HFHC group was 1.91 (95% CI: 1·06, 3·44) more compared to latter group. Our data suggests that a HFHC dietary combination in Malaysian adults is associated with significant impact on lipoprotein particles and insulin resistance.
  3. Karupaiah T, Chuah KA, Chinna K, Matsuoka R, Masuda Y, Sundram K, et al.
    Lipids Health Dis, 2016 Aug 17;15(1):131.
    PMID: 27535127 DOI: 10.1186/s12944-016-0301-9
    BACKGROUND: Mayonnaise is used widely in contemporary human diet with widespread use as a salad dressing or spread on breads. Vegetable oils used in its formulation may be a rich source of ω-6 PUFAs and the higher-PUFA content of mayonnaise may be beneficial in mediating a hypocholesterolemic effect. This study, therefore, evaluated the functionality of mayonnaise on cardiometabolic risk within a regular human consumption scenario.

    METHODS: Subjects underwent a randomized double-blind crossover trial, consuming diets supplemented with 20 g/day of either soybean oil-based mayonnaise (SB-mayo) or palm olein-based mayonnaise (PO-mayo) for 4 weeks each with a 2-week wash-out period. The magnitude of changes for metabolic outcomes between dietary treatments was compared with PO-mayo serving as the control. The data was analyzed by ANCOVA using the GLM model. Analysis was adjusted for weight changes.

    RESULTS: Treatments resulted in significant reductions in TC (diff = -0.25 mmol/L; P = 0.001), LDL-C (diff = -0.17 mmol/L; P = 0.016) and HDL-C (diff = -0.12 mmol/L; P  0.05). Lipoprotein particle change was significant with large LDL particles increasing after PO-mayo (diff = +63.2 nmol/L; P = 0.007) compared to SB-mayo but small LDL particles remained unaffected. Plasma glucose, apolipoproteins and oxidative stress markers remained unchanged.

    CONCLUSIONS: Daily use with 20 g of linoleic acid-rich SB-mayo elicited reductions in TC and LDL-C concentrations without significantly changing LDL-C:HDL-C ratio or small LDL particle distributions compared to the PO-mayo diet.

    TRIAL REGISTRATION: This clinical trial was retrospectively registered with the National Medical Research Register, National Institute of Health, Ministry of Health Malaysia, (NMRR-15-40-24035; registered on 29/01/2015; https://www.nmrr.gov.my/fwbPage.jsp?fwbPageId=ResearchISRForm&fwbAction=Update&fwbStep=10&pk.researchID=24035&fwbVMenu=3&fwbResearchAction=Update ). Ethical approval was obtained from the National University of Malaysia's Medical Ethics Committee (UKM 1.5.3.5/244/SPP/NN-054-2011, approved on 25/05/2011).

  4. Balasubramanian GV, Chuah KA, Khor BH, Sualeheen A, Yeak ZW, Chinna K, et al.
    Nutrients, 2020 Jul 14;12(7).
    PMID: 32674327 DOI: 10.3390/nu12072080
    Cardiometabolic risk is scarcely explored related to dietary patterns (DPs) in Asian populations. Dietary data (n = 562) from the cross-sectional Malaysia Lipid Study were used to derive DPs through principal component analysis. Associations of DPs were examined with metabolic syndrome (MetS), atherogenic, inflammation and insulinemic status. Four DPs with distinctive eating modes were Home meal (HM), Chinese traditional (CT), Plant foods (PF) and Sugar-sweetened beverages (SSB). Within DP tertiles (T3 vs. T1), the significantly lowest risk was associated with CT for hsCRP (AOR = 0.44, 95% CI 0.28, 0.70, p < 0.001) levels. However, SSB was associated with the significantly highest risks for BMI (AOR = 2.01, 95% CI 1.28, 3.17, p = 0.003), waist circumference (AOR = 1.81, 95% CI 1.14, 2.87, p = 0.013), small LDL-C particles (AOR= 1.69, 95% CI 1.02, 2.79, p = 0.043), HOMA2-IR (AOR = 2.63, 95% CI 1.25, 5.57, p = 0.011), hsCRP (AOR = 2.21, 95% CI 1.40, 3.50, p = 0.001), and MetS (AOR = 2.78, 95% CI 1.49, 5.22, p = 0.001). Adherence behaviors to SSBs (T3) included consuming coffee/tea with condensed milk (29%) or plain with sugar (20.7%) and eating out (12 ± 8 times/week, p < 0.001). Overall, the SSB pattern with a highest frequency of eating out was detrimentally associated with cardiometabolic risks.
  5. Sualeheen A, Khor BH, Lim JH, Balasubramanian GV, Chuah KA, Yeak ZW, et al.
    Sci Rep, 2024 Aug 28;14(1):19983.
    PMID: 39198625 DOI: 10.1038/s41598-024-70699-7
    Evaluating dietary guidelines using diet quality (DQ) offers valuable insights into the healthfulness of a population's diet. We conducted a forensic analysis using DQ metrics to compare the Malaysian Dietary Guidelines (MDG-2020) with its former version (MDG-2010) in relation to cardiometabolic risk (CMR) for an adult Malaysian population. A DQ analysis of cross-sectional data from the Malaysia Lipid Study (MLS) cohort (n = 577, age: 20-65yrs) was performed using the healthy eating index-2015 (HEI-2015) framework in conformation with MDG-2020 (MHEI2020) and MDG-2010 (MHEI2010). Of 13 dietary components, recommended servings for whole grain, refined grain, beans and legumes, total protein, and dairy differed between MDGs. DQ score associations with CMR, dietary patterns and sociodemographic factors were examined. Out of 100, total DQ scores of MLS participants were 'poor' for both MHEI2020 (37.1 ± 10.3) and MHEI2010 (39.1 ± 10.4), especially among young adults, males, Malays, and those frequently 'eating out' as well as those with greatest adherence to Sugar-Sweetened Beverages pattern and lowest adherence to Food Plant pattern. Both metrics shared similar correlations with CMR markers, with MHEI2020 exhibiting stronger correlations with WC, BF%, TG, insulin, HOMA2-IR, and smallLDL than MHEI2010, primarily attributed to reduced refined grain serving. Notably, participants with the highest adherence to MHEI2020 scores exhibited significantly reduced odds for elevated TG (AOR 0.44, 95% CI 0.21-0.93, p = 0.030), HOMA2-IR (AOR 0.44, 95% CI 0.21-0.88, p = 0.022), and hsCRP (AOR 0.54, 95% CI 0.31-0.96, p = 0.040, compared to those with the lowest adherence. Each 5-unit increase in MHEI2020 scores reduced odds for elevated BMI (- 14%), WC (- 9%), LDL-C (- 32%), TG (- 15%), HOMA2-IR (- 9%) and hsCRP (- 12%). While MHEI2020 scores demonstrated better calibration with CMR indicators, the overall sub-optimally 'poor' DQ scores of this population call for health promotion activities to target the public to achieve adequate intake of healthful fruits, non-starchy vegetables and whole grain, and moderate intake of refined grain, added sugar and saturated fat.
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