METHODS: Diabetes data were derived from the Malaysian National Health and Morbidity Surveys conducted in 2006, 2011 and 2015. The air pollution data (NOx, NO2, SO2, O3 and PM10) were obtained from the Department of Environment Malaysia. Using multiple logistic and linear regression models, the association between long-term exposure to these pollutants and prevalence of diabetes among Malaysian adults was evaluated.
RESULTS: The PM10 concentration decreased from 2006 to 2014, followed by an increase in 2015. Levels of NOx decreased while O3 increased annually. The air pollutant levels based on individual modelled air pollution exposure as measured by the nearest monitoring station were higher than the annual averages of the five pollutants present in the ambient air. The prevalence of overall diabetes increased from 11.4% in 2006 to 21.2% in 2015. The prevalence of known diabetes, underdiagnosed diabetes, overweight and obesity also increased over these years. There were significant positive effect estimates of known diabetes at 1.125 (95% CI, 1.042, 1.213) for PM10, 1.553 (95% CI, 1.328, 1.816) for O3, 1.271 (95% CI, 1.088, 1.486) for SO2, 1.124 (95% CI, 1.048, 1.207) for NO2, and 1.087 (95% CI, 1.024, 1.153) for NOx for NHMS 2006. The adjusted annual average levels of PM10 [1.187 (95% CI, 1.088, 1.294)], O3 [1.701 (95% CI, 1.387, 2.086)], NO2 [1.120 (95% CI, 1.026, 1.222)] and NOx [1.110 (95% CI, 1.028, 1.199)] increased significantly from NHMS 2006 to NHMS 2011 for overall diabetes. This was followed by a significant decreasing trend from NHMS 2011 to 2015 [0.911 for NO2, and 0.910 for NOx].
CONCLUSION: The findings of this study suggest that long-term exposure to O3 is an important associated factor of underdiagnosed DM risk in Malaysia. PM10, NO2 and NOx may have mixed effect estimates towards the risk of DM, and their roles should be further investigated with other interaction models. Policy and intervention measures should be taken to reduce air pollution in Malaysia.
Methods: Thirteen focus group discussions involving 129 participants from a weight-loss intervention program were conducted within the first 1 month of recruitment. These discussions were moderated by two trained researchers in the Malay language and assisted by an interview guide. They were audio-recorded and transcribed verbatim. A thematic analysis was performed, and codes and themes from each discussion were constructed.
Results: The participants understood dieting with various meanings, including skipping meals and removing rice from daily diets. They applied numerous methods to lose weight and achieved various outcomes. Health and appearance, social support, and compliance with current trends were the factors motivating these participants to lose weight. Their determination to lose weight was limited by lack of self-control and motivation, experiences of unpleasant effects, influence on weight, and environmental and health factors.
Conclusion: Real-life weight loss experiences and perceptions provided relevant insights into current weight loss management strategies. Some of these issues and misunderstandings should be emphasized in weight loss strategies during health promotion.
METHODS: To grade the evidence from published meta-analyses of RCTs that assessed the association of KD, ketogenic low-carbohydrate high-fat diet (K-LCHF), and very low-calorie KD (VLCKD) with health outcomes, PubMed, EMBASE, Epistemonikos, and Cochrane database of systematic reviews were searched up to February 15, 2023. Meta-analyses of RCTs of KD were included. Meta-analyses were re-performed using a random-effects model. The quality of evidence per association provided in meta-analyses was rated by the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) criteria as high, moderate, low, and very low.
RESULTS: We included 17 meta-analyses comprising 68 RCTs (median [interquartile range, IQR] sample size of 42 [20-104] participants and follow-up period of 13 [8-36] weeks) and 115 unique associations. There were 51 statistically significant associations (44%) of which four associations were supported by high-quality evidence (reduced triglyceride (n = 2), seizure frequency (n = 1) and increased low-density lipoprotein cholesterol (LDL-C) (n = 1)) and four associations supported by moderate-quality evidence (decrease in body weight, respiratory exchange ratio (RER), hemoglobin A1c, and increased total cholesterol). The remaining associations were supported by very low (26 associations) to low (17 associations) quality evidence. In overweight or obese adults, VLCKD was significantly associated with improvement in anthropometric and cardiometabolic outcomes without worsening muscle mass, LDL-C, and total cholesterol. K-LCHF was associated with reduced body weight and body fat percentage, but also reduced muscle mass in healthy participants.
CONCLUSIONS: This umbrella review found beneficial associations of KD supported by moderate to high-quality evidence on seizure and several cardiometabolic parameters. However, KD was associated with a clinically meaningful increase in LDL-C. Clinical trials with long-term follow-up are warranted to investigate whether the short-term effects of KD will translate to beneficial effects on clinical outcomes such as cardiovascular events and mortality.
METHODS: This study was a cross-sectional study using multi-stage stratified sampling method. Data collection was carried out via face-to-face interview at the respondent's home from October 2017 until March 2018. A total of 1047 respondents aged 18 years and above completed the questionnaires and blood pressure measurement. A person who reported diagnosis of hypertension by a physician and had systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg on three readings was categorised as hypertensive. Risk factors of hypertension were analysed using multiple logistic regression.
RESULTS: The prevalence of hypertension in the present study was 49.39% (95% CI 44.27-54.51). There was no statistically significant difference in gender. Age, household income, BMI, and diabetes were significantly associated with hypertension. Hypertension found had inverse association with the level of education. Age was the strongest predictor of hypertension (35-44 years old; OR=2.39, 95% CI=1.39-4.09, 45-54 years old; OR=5.50, 95% CI=3.23-9.38, 55-64 years old OR=13.56, 95% CI=7.77-23.64 and 65 years old and above; OR=25.28, 95% CI=13.33-48.66). Those who had higher BMI more likely to be hypertensive as compared to respondents with normal weight (overweight, OR=1.84; 95% CI=1.18-2.86; obese, OR=4.29% CI=2.56-7.29).
CONCLUSION: The findings showed that hypertension is prevalent among adults in Malaysia. Those with older age, higher BMI, and diabetes are more likely to have hypertension. Efforts regarding lifestyle modification and education could be important in hypertension management and prevention.
AIM: To investigate the effects of food order on postprandial glucose (PPG) excursion, in Indian adults with normal (NL) and overweight/obese (OW) Body Mass Index.
METHODS: This randomised crossover study was conducted at a Malaysian university among Indian adults without diabetes. The participants consumed isocaloric test meals at three study visits based on randomised food orders: carbohydrate first/protein last (CF); protein first/carbohydrate last (CL); and a composite meal containing carbohydrate and protein (CM). Capillary blood glucose was measured at baseline, 30, 60, 90 and 120 minutes after starting the meal.
RESULTS: The CL food order had a blunting effect on PPG excursion at 30 and 60 minutes (p < 0.01). The CL food order resulted in lower glucose peak when compared with the CF and CM food order (p < 0.001). The CL food order resulted in lower incremental glucose peak (mmol/L) (NL: CF 3.9 ± 0.3, CM 3.0 ± 0.3, CL 2.0 ± 0.2; OW: CF 2.9 ± 0.3, CM 2.5 ± 0.3, CL 1.8 ± 0.2) and iAUC 0-120 min (mmol/Lxmin) (NL: CF 272.4 ± 26.7, CM 206.2 ± 30.3, CL 122.0 ± 14.8; OW: CF 193.2 ± 23.1, CM 160.1 ± 21.7, CL 113.6 ± 15.3) when compared with the CF food order (p < 0.001). The effect of food order on postprandial excursion did not differ between the NL (n = 14) and the OW (n = 17) groups.
CONCLUSION: In participants with normal and overweight/obese BMI, consuming food in the protein first/carbohydrate last order had the biggest effect in reducing PPG excursion.