METHODS: This was an analytical cross sectional study. Ethics approval was obtained and informed consent was given by all participants. Anthropometric measurements, blood pressure, fasting blood glucose and lipid profile were taken following standard protocols.
RESULTS: Metabolic Syndrome was diagnosed in 41.4% and 38.2% participants using the modified NCEP and IDF criteria respectively. Among those diagnosed with Metabolic Syndrome by modified NCEP, 7.6% were missed by the IDF criteria. Participants diagnosed by the modified NCEP criteria had lower BMI and waist circumference but had higher cardiometabolic risks than those diagnosed with both criteria. Their blood pressure, glucose, total cholesterol and triglyceride were more adverse than the IDF group. This demonstrated that central obesity may not be a prerequisite for the development of increased cardiometabolic risks within this Malay cohort.
CONCLUSION: Metabolic syndrome is common in this Malay cohort regardless of the criterion used. The modified NCEP ATP III criteria may be more suitable in diagnosis of metabolic syndrome for this Malay cohort.
METHODS: We conducted a cross-sectional study involving teachers recruited via multi-stage sampling from the state of Melaka, Malaysia. MONO was defined as individuals with BMI 18.5-29.9 kg/m(2) and metabolic syndrome. Metabolic syndrome was diagnosed based on the Harmonization criteria. Participants completed self-reported questionnaires that assessed alcohol intake, sleep duration, smoking, physical activity, and fruit and vegetable consumption.
RESULTS: A total of 1168 teachers were included in the analysis. The prevalence of MONO was 17.7% (95% confidence interval [CI], 15.3-20.4). Prevalence of metabolic syndrome among the normal weight and overweight participants was 8.3% (95% CI, 5.8-11.8) and 29.9% (95% CI, 26.3-33.7), respectively. MONO prevalence was higher among males, Indians, and older participants and inversely associated with sleep duration. Metabolic syndrome was also more prevalent among those with central obesity, regardless of whether they were normal or overweight. The odds of metabolic syndrome increased exponentially from 1.9 (for those with BMI 23.0-24.9 kg/m(2)) to 11.5 (for those with BMI 27.5-29.9 kg/m(2)) compared to those with BMI 18.5-22.9 kg/m(2) after adjustment for confounders.
CONCLUSIONS: The prevalence of MONO was high, and participants with BMI ≥23.0 kg/m(2) had significantly higher odds of metabolic syndrome. Healthcare professionals and physicians should start to screen non-obese individuals for metabolic risk factors to facilitate early targeted intervention.
MATERIALS AND METHODS: We conducted a cross-sectional study among 481 Malaysians of ages 18 years and above living in the state of Johor, Malaysia. Information on demographics, lifestyle and diet habits were collected using a structured questionnaire. Harmonized criteria were used to assess the status of MetS. Multiple logistic regression was employed to determine any associations between sociodemographic and lifestyle factors and dietary behaviours with MetS.
RESULTS: MetS was found among 32.2% of the respondents and was more prevalent among the Indians (51.9%), followed by the Malays (36.7%) and the Chinese (20.2%). Overall, increasing age (AOR = 2.44[95%CI = 1.27-4.70] at 40-49 years vs. AOR = 4.14[95%CI = 1.97-8.69] at 60 years and above) and Indian ethnicity (AOR = 1.95[95%CI = 1.12-3.38)] increased the odds of MetS, while higher education (AOR = 0.44[95%CI = 0.20-0.94] decreased the odds of MetS in this population. Quick finishing of meals (AOR = 2.17[95%CI = 1.02-4.60]) and low physical activity (AOR = 4.76[95%CI = 1.49-15.26]) were associated with increased odds of MetS among the Malays and the Chinese, respectively.
CONCLUSION: The population of Johor depicts a diverse lifestyle and diet behaviour, and some of these factors are associated with MetS in certain ethnic groups. In the light of such differences, ethnic specific measures would be needed to reduce the prevalence of MetS among those in this population.