METHODS: We randomized 108 overweight and obese patients with T2D (46 M/62F; age 60 ± 10 years; HbA1c 8.07 ± 1.05%; weight 101.4 ± 21.1 kg and BMI 35.2 ± 7.7 kg/m2) into three groups. Group A met with RDN to develop an individualized eating plan. Group B met with RDN and followed a structured meal plan. Group C did similar to group B and received weekly phone support by RDN.
RESULTS: After 16 weeks, all three groups had a significant reduction of their energy intake compared to baseline. HbA1c did not change from baseline in group A, but decreased significantly in groups B (- 0.66%, 95% CI -1.03 to - 0.30) and C (- 0.61%, 95% CI -1.0 to - 0.23) (p value for difference among groups over time
METHODS: A comprehensive search of PubMed, Web of Science, Scopus, Cochrane Library, and Google Scholar databases were performed. Only randomized placebo-controlled human studies that examined the effects of carnitine supplementation on liver function, lipid profile, body mass index, body weight, and homeostasis model assessment of insulin resistance up to September 2019 were included. Fixed effects or random-effects models were applied to compute the pooled effect size. Heterogeneity assessments were performed using Cochran's Q test and I-squared statistics. The quality of the studies was assessed using the Jaded scale.
RESULTS: A total of 5 articles were selected, including 334 individuals (167 in control and 167 in intervention groups). The results demonstrated that carnitine supplementation significantly reduced homeostasis model assessment of insulin resistance (HOMA-IR) (WMD: -0.91; 95 % CI: -1.11, -0.72; p
METHODS: This a randomized controlled trial (RCT) randomized 208 patients with T2DM [mean age = 48.8 ± 11.8 years, Glycated Hemoglobin (HbA1c) = 9.5 ± 2.4%, and Body Mass Index = 28.0 ± 5.6 kg/m2] to intervention group (n = 104) or control group (n = 104). Participants in the intervention group received a weekly diabetes nutrition module based on the health belief model for 12 weeks in addition to the usual care whereas the control participants were given the usual care. We evaluated HbA1c and diabetes-related outcomes (metabolic parameters, dietary intake, and physical activity level) at baseline, 12 weeks, and 22 weeks. Health beliefs, diabetes knowledge, and health literacy were also evaluated.
RESULTS: After 22 weeks, HbA1c improved significantly in the intervention group (-1.7%) from the baseline value, compared to the control group (+0.01%) (p
METHODS: We performed a systematic search using PubMed, Scopus, Cochrane Library, Web of Science for randomised controlled trials (RCTs), published until March 17, 2021. The quality assessment was carried out using the Cochrane Collaboration risk of bias tool. The Q-test and I 2 tests were used for the determination of heterogeneity of the included studies. Data were pooled using a random-effects model, and weighted mean difference (WMD) was used for the overall effect size.
RESULTS: Pooled findings of the five RCTs demonstrated that ginger supplementations had significantly reduced hs-CRP (WMD -0.42 mg/L; 95% CI, -0.78, -0.05, P = 0.03), TNF-α (-2.13 pg/mL; 95% CI: -3.41, -0.86, P = 0.001), and IL-6 (WMD: -0.61 pg/mL; 95% CI: -0.92, -0.30, P = 0.001) levels in patients with T2DM. The quality assessment of the studies showed that all of the included studies were at high risk of bias.
CONCLUSIONS: The meta-analysis shows that ginger supplementations reduced inflammatory parameters in patients with T2DM. Nonetheless, the reduction is relatively small, and its meaningful clinical effects are unknown. Future high-quality RCTs are needed to confirm the beneficial effects of ginger supplementation in patients with T2DM.
MATERIALS AND METHODS: This cross-sectional study was conducted on 124 breast cancer outpatients within the first year of diagnosis and yet to commence oncological treatment. Body composition parameters [body weight, body mass index (BMI), body fat percentage, fat mass over fat-free mass ratio (FM/FFM), muscle mass, and visceral fat] were obtained using a bioelectrical impedance analyzer. Body fat percentage was categorized into two groups which were normal (<35%) and high (≥35%). The E-DII was calculated from the validated 165-items Food Frequency Questionnaire (FFQ) and categorized into three groups or tertiles. Multiple logistic regression analysis was used to determine the association between the E-DII and body fat percentage.
RESULTS: Mean body weight, body fat percentage, FM/FFM, and visceral fat increased as E-DII increased from the lowest tertile (T1) to the most pro-inflammatory tertile (T3) (p for trend <0.05). E-DII was positively associated with body fat percentage (OR 2.952; 95% CI 1.154-7.556; p = 0.024) and remained significant after adjustment for cancer stage, age, physical activity, ethnicity, smoking history, and presence of comorbidities. Compared to T1, participants in T3 had a significantly lower consumption of fiber, vitamin A, beta-carotene, vitamin C, iron, thiamine, riboflavin, niacin, vitamin B6, folic acid, zinc, magnesium, and selenium, but a higher intake of total fat, saturated fat, and monounsaturated fatty acids.
CONCLUSIONS: A higher E-DII was associated with increased body fat percentage, suggesting the potential of advocating anti-inflammatory diet to combat obesity among newly diagnosed breast cancer patients.
METHODS: A total of 288 university students aged 18 to 29 years participated in this comparative cross-sectional study. We assessed dietary intake, level of physical activity, knowledge of diabetes and T2DM risk.
RESULTS: Respondents with a family history of diabetes had significantly higher weight (P = 0.003), body mass index (P < 0.001), waist circumference (P < 0.001), diabetes knowledge level (P < 0.005) and T2DM risk (P < 0.001). Ethnicity, fibre intake, T2DM risk score and knowledge about diabetes were significant contributors toward family history of diabetes (P = 0.025, 0.034, < 0.001 and 0.004, respectively).
CONCLUSION: Young adults with a family history of diabetes had suboptimal nutritional status. Despite being more knowledgeable about diabetes, they did not practice a healthy lifestyle. Family history status can be used to screen young adults at the risk of developing T2DM for primary disease prevention.
METHODS: We searched MEDLINE (via PubMed) and Science Direct databases for articles that included the component of nutrition for adult patients with type 2 diabetes (T2D), published in English between 2010 and 2020.
RESULTS: Fourteen studies met the criteria. Eight of 14 studies had an intervention with a control arm. In comparison to the control group, all studies (n = 8) showed a reduction in hypoglycemic events. However, only half of these studies (n = 4) had shown at least one positive clinical outcome. Features of nutrition therapy that appeared to have favorable clinical outcomes include individualized caloric prescription; distributing carbohydrates equally between Suhoor, Iftar and snacks; providing meal plans; adjusting food intake to suit Ramadan; and incorporating diabetes-specific formula as part of Suhoor or snack.
CONCLUSIONS: The review provides evidence for the effectiveness of Ramadan-focused nutrition therapy among people with T2D and identifies key features of nutrition therapy that may provide favourable clinical outcomes. Additional data on dietary quality and adequacy during Ramadan fasting warrants further studies.
METHODS: This was a prospective cohort study of 452 pregnant women recruited from 3 health clinics in a southern state of Peninsular Malaysia. PA levels at the first, second, and third trimester were assessed using the Pregnancy Physical Activity Questionnaire. GDM was diagnosed at 24-28 weeks of gestation following the Ministry of Health Malaysia criteria. Group-based trajectory modeling was used to identify PA trajectories. Three multivariate logistic models were used to estimate the odds of trajectory group membership and GDM.
RESULTS: Two distinct PA trajectories were identified: low PA levels in all intensity of PA and sedentary behavior (Group 1: 61.1%, n = 276) and high PA levels in all intensity of PA as well as sedentary behavior (Group 2: 38.9%, n = 176). Moderate and high intensity PA decreased over the course of pregnancy in both groups. Women in group 2 had significantly higher risk of GDM in two of the estimated logistic models. In all models, significant associations between PA trajectories and GDM were only observed among women with excessive gestational weight gain in the second trimester.
CONCLUSIONS: Women with high sedentary behavior were significantly at higher risk of GDM despite high PA levels by intensity and this association was significant only among women with excessive GWG in the second trimester. Participation in high sedentary behavior may outweigh the benefit of engaging in high PA to mitigate the risk of GDM.