DESIGN AND SETTINGS: This is a retrospective study of all patients who had undergone coronary angioplasty from 2007 to 2009 in 11 hospitals across Malaysia.
METHODS: Data were obtained from the NCVD-PCI Registry, 2007 to 2009. Patients were categorized into 2 groups-young and old, where young was defined as less than 45 years for men and less than 55 years for women and old was defined as more than or equals to 45 years for men and more than or equals to 55 years for women. Patients' baseline characteristics, risk factor profile, extent of coronary disease and outcome on dis.charge, and 30-day and 1-year follow-up were compared between the 2 groups.
RESULTS: We analyzed 10268 patients, and the prevalence of young CAD was 16% (1595 patients). There was a significantly low prevalence of Chinese patients compared to other major ethnic groups. Active smoking (30.2% vs 17.7%) and obesity (20.9% vs 17.3%) were the 2 risk factors more associated with young CAD. There is a preponderance toward single vessel disease in the young CAD group, and they had a favorable clinical outcome in terms of all-cause mortality at discharge (RR 0.49 [CI 0.26-0.94]) and 1-year follow-up (RR 0.47 [CI 0.19-1.15]).
CONCLUSION: We observed distinctive features of young CAD that would serve as a framework in the primary and secondary prevention of the early onset CAD.
DESIGN: This is a cross-sectional study among Form 1 (year 7) students from 15 schools selected using a stratified random sampling design. Information regarding sociodemographic characteristics, clinical data and environmental factors was collected and blood samples were taken for total vitamin D. Descriptive and multivariable logistic regression was performed on the data.
SETTING: National secondary schools in Peninsular Malaysia.
PARTICIPANTS: 1361 students (mean age 12.9±0.3 years) (61.4% girls) completed the consent forms and participated in this study. Students with a chronic health condition and/or who could not understand the questionnaires due to lack of literacy were excluded.
MAIN OUTCOME MEASURES: Vitamin D status was determined through measurement of sera 25-hydroxyvitamin D (25(OH)D). Body mass index (BMI) was classified according to International Obesity Task Force (IOTF) criteria. Self-reported physical activity levels were assessed using the validated Malay version of the Physical Activity Questionnaire for Older Children (PAQ-C).
RESULTS: Deficiency in vitamin D was seen in 78.9% of the participants. The deficiency was significantly higher in girls (92.6%, p<0.001), Indian adolescents (88.6%, p<0.001) and urban-living adolescents (88.8%, p<0.001). Females (OR=8.98; 95% CI 6.48 to 12.45), adolescents with wider waist circumference (OR=2.64; 95% CI 1.65 to 4.25) and in urban areas had higher risks (OR=3.57; 95% CI 2.54 to 5.02) of being vitamin D deficient.
CONCLUSIONS: The study shows a high prevalence of vitamin D deficiency among young adolescents. Main risk factors are gender, ethnicity, place of residence and obesity.
METHODS: Two cross-sectional studies were conducted in urban and rural areas of Yangon Region in 2013 and 2014 respectively, using the WHO STEPwise approach to surveillance of risk factors of NCDs. Through a multi-stage cluster sampling method, 1486 participants were recruited.
RESULTS: Age-standardized prevalence of the behavioral risk factors tended to be higher in the rural than urban areas for all included factors and significantly higher for alcohol drinking (19.9% vs. 13.9%; p = 0.040) and low fruit & vegetable consumption (96.7% vs. 85.1%; p = 0.001). For the metabolic risk factors, the tendency was opposite, with higher age-standardized prevalence estimates in urban than rural areas, significantly for overweight and obesity combined (40.9% vs. 31.2%; p = 0.023), obesity (12.3% vs.7.7%; p = 0.019) and diabetes (17.2% vs. 9.2%; p = 0.024). In sub-group analysis by gender, the prevalence of hypercholesterolemia and hypertriglyceridemia were significantly higher in urban than rural areas among males, 61.8% vs. 40.4%; p = 0.002 and 31.4% vs. 20.7%; p = 0.009, respectively. Mean values of age-standardized metabolic parameters showed higher values in urban than rural areas for both male and female. Based on WHO age-standardized Framingham risk scores, 33.0% (95% CI = 31.7-34.4) of urban dwellers and 27.0% (95% CI = 23.5-30.8) of rural dwellers had a moderate to high risk of developing CHD in the next 10 years.
CONCLUSION: The metabolic risk factors, as well as a moderate or high ten-year risk of CHD were more common among urban residents whereas behavioral risk factors levels were higher in among the rural people of Yangon Region. The high prevalences of NCD risk factors in both urban and rural areas call for preventive measures to reduce the future risk of NCDs in Myanmar.
Objective: To assess whether sleep timing and napping behavior are associated with increased obesity, independent of nocturnal sleep length.
Design, Setting, and Participants: This large, multinational, population-based cross-sectional study used data of participants from 60 study centers in 26 countries with varying income levels as part of the Prospective Urban Rural Epidemiology study. Participants were aged 35 to 70 years and were mainly recruited during 2005 and 2009. Data analysis occurred from October 2020 through March 2021.
Exposures: Sleep timing (ie, bedtime and wake-up time), nocturnal sleep duration, daytime napping.
Main Outcomes and Measures: The primary outcomes were prevalence of obesity, specified as general obesity, defined as body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 30 or greater, and abdominal obesity, defined as waist circumference greater than 102 cm for men or greater than 88 cm for women. Multilevel logistic regression models with random effects for study centers were performed to calculate adjusted odds ratios (AORs) and 95% CIs.
Results: Overall, 136 652 participants (81 652 [59.8%] women; mean [SD] age, 51.0 [9.8] years) were included in analysis. A total of 27 195 participants (19.9%) had general obesity, and 37 024 participants (27.1%) had abdominal obesity. The mean (SD) nocturnal sleep duration was 7.8 (1.4) hours, and the median (interquartile range) midsleep time was 2:15 am (1:30 am-3:00 am). A total of 19 660 participants (14.4%) had late bedtime behavior (ie, midnight or later). Compared with bedtime between 8 pm and 10 pm, late bedtime was associated with general obesity (AOR, 1.20; 95% CI, 1.12-1.29) and abdominal obesity (AOR, 1.20; 95% CI, 1.12-1.28), particularly among participants who went to bed between 2 am and 6 am (general obesity: AOR, 1.35; 95% CI, 1.18-1.54; abdominal obesity: AOR, 1.38; 95% CI, 1.21-1.58). Short nocturnal sleep of less than 6 hours was associated with general obesity (eg, <5 hours: AOR, 1.27; 95% CI, 1.13-1.43), but longer napping was associated with higher abdominal obesity prevalence (eg, ≥1 hours: AOR, 1.39; 95% CI, 1.31-1.47). Neither going to bed during the day (ie, before 8pm) nor wake-up time was associated with obesity.
Conclusions and Relevance: This cross-sectional study found that late nocturnal bedtime and short nocturnal sleep were associated with increased risk of obesity prevalence, while longer daytime napping did not reduce the risk but was associated with higher risk of abdominal obesity. Strategic weight control programs should also encourage earlier bedtime and avoid short nocturnal sleep to mitigate obesity epidemic.
METHODS: This was a cross sectional study carried out in two primary care clinics in a semi-urban locality of Ampangan, Negeri Sembilan, Malaysia. Data was collected through self-administered questionnaires assessing the demographic characteristics, medical history, lifestyle and physical activity. The Short Form 36-items health survey was used to measure HRQOL among the pre-diabetics. Data entry and analysis were performed using the SPSS version 19.
RESULTS: A total of 268 eligible pre-diabetics participated in this study. The prevalence of normal weight, overweight and obesity were 7.1%, 21.6% and 71.3% respectively. Their mean (SD) age was 52.5 (8.3) years and 64.2% were females. Among the obese pre-diabetics, 42.2% had both IFG and IGT, 47.0% had isolated IFG and 10.8% had isolated IGT, 36.2% had combination of hypertension, dyslipidemia and musculoskeletal diseases. More than 53.4% of the obese pre-diabetics had family history of diabetes, 15.7% were smokers and 60.8% were physically inactive with mean PA of <600 MET-minutes/week. After adjusted for co-variants, Physical Component Summary (PCS) was significantly associated with BMI categories [F (2,262)=11.73, p<0.001] where pre-diabetics with normal weight and overweight had significantly higher PCS than those obese; normal vs obese [Mdiff=9.84, p=0.006, 95% CIdiff=2.28, 17.40] and between overweight vs obese [Mdiff=8.14, p<0.001, 95% CIdiff=3.46, 12.80].
CONCLUSION: Pre-diabetics who were of normal weight reported higher HRQOL compared to those overweight and obese. These results suggest a potentially greater risk of poor HRQOL among pre-diabetics who were overweight and obese especially with regard to the physical health component. Promoting recommended amount of physical activity and weight control are particularly important interventions for pre-diabetics at the primary care level.
METHODS: In this study, a systematic search was conducted across electronic databases, including PubMed, Scopus, Web of Science, Embase, ScienceDirect, and Google Scholar. The search aimed to identify studies published between December 2000 and August 2022 that reported metabolic syndrome's impact on female sexual dysfunction.
RESULTS: The review included nine studies with a sample size of 1508 obese women. The I2 heterogeneity index indicated high heterogeneity (I2: 97.5). As a result, the random effects method was used to analyze the data. Based on this meta-analysis, the prevalence of sexual dysfunction in women with obesity was reported as 49.7% (95%CI: 35.8-63.5). Furthermore, the review comprised five studies involving 1411 overweight women. The I2 heterogeneity test demonstrated high heterogeneity (I2: 96.6). Consequently, the random effects model was used to analyze the results. According to the meta-analysis, the prevalence of sexual dysfunction in overweight women was 26.9% (95% CI: 13.5-46.5).
CONCLUSION: Based on the results of this study, it has been reported that being overweight and particularly obese is an important factor affecting women's sexual dysfunction. Therefore, health policymakers must acknowledge the significance of this issue in order to raise awareness in society about its detrimental effect on the female population.