Methods: 21 day old male Sprague Dawley rats were assigned as Experiment-1 & 2 - PND rats were divided into 4 groups with interventions for 7 months (n = 8/group). NC- Normal control fed normal chow diet; OB- Obese group, fed high fat diet; OB + CHO + DHA- fed high fat diet and oral supplementation of choline, DHA. OB + EE- fed high fat diet along with exposure to enriched environment .Experiment-2 had similar groups and interventions as experiment 1 but for next 5 months were fed normal chow diet without any interventions. Body mass index was assessed and blood was analyzed for serum lipid profile. Common Carotid Artery (CCA) was processed for Haematoxylin and eosin, Verhoff Vangeison stains. Images of tissue sections were analyzed and quantified using image J and tissue quant software.
Results: In experiment.1, mean body mass index (p
METHOD: This cross-sectional study involved eighty-three (n=83) adults attending a health screening program at Universiti Putra Malaysia (UPM). Demographic data, anthropometric measurements and blood samples for fasting blood glucose (FBG), fasting lipid profile (FSL), glycated haemoglobin (HbA1c) and hsCRP were taken. Respondents were grouped according to FRS and the Joint Interim Statement into 10-year CVD risk categories (low, intermediate and high) and MetS, respectively.
RESULTS: hsCRP was significantly increased in patients with high body mass index (BMI) (p=0.001), at-risk waist circumference (WC) (p=0.001) and MetS (p=0.009). Spearman's correlation coefficient showed a significant positive correlation between hsCRP level and total FRS score (r=0.26, p<0.05) and HDL-C score (r=0.22, p<0.05).
CONCLUSION: The significant difference of hsCRP levels across obesity levels and MetS with its modest correlation with FRS scores supported the adjunctive role of hsCRP in CVD risk prediction, most likely capturing the inflammatory pathological aspect and thus partly accounting for the residual CVD risk.
METHODS: The study used data from the National Health and Morbidity Survey in 2018. It was a cross-sectional study with two-staged stratified cluster sampling design. In total, 3977 adults aged ≥60 years were selected for this study. Respondents were interviewed face to face using a structured questionnaire. Self-reported diabetes, hypertension or hypercholesterolemia was defined as having ever been told they have these diseases by a medical doctor or paramedic. Data were analyzed using SPSS version 25. The multiple logistic regression model was used to examine the factors associated with the prevalence of self-reporting.
RESULTS: The prevalence of self-reported diabetes, hypertension and hypercholesterolemia among older persons in Malaysia were 27.7%, 51.1% and 41.8% respectively. Presence of other comorbidities and being obese showed higher odds for all three diseases. Indians, unemployed, inactive had higher odds for diabetes. Other Bumiputras, unemployed, non-smoker, obese and inactive had higher odds for hypertension. Non-smoker had higher odds for hypercholesterolemia.
CONCLUSIONS: Health promotion, vigilance, attention and services targeting on the associated factors should be strengthened for older persons in Malaysia to ensure healthy aging. Geriatr Gerontol Int 2020; 20: 79-84.
METHODS: Data were derived from the Global School-Based Student Health Survey (GSHS). Data from 71176 adolescents aged 12-15 years residing in 23 countries were analyzed. The Centers for Disease Control and Prevention (CDC) 2000 growth charts were used to identify underweight, normal weight, and overweight/ obesity. Weighted age- and gender-adjusted prevalence of weight categories and tobacco use was calculated. Multivariate logistic regression analysis was performed to estimate the association between weight categories and tobacco use for each country, controlling for covariates. Pooled odds ratios and confidence intervals were computed using random- or fixed-effects meta-analyses.
RESULTS: A significant association between weight categories and tobacco use was evident in only a few countries. Adolescents reporting tobacco use in French Polynesia, Suriname, and Indonesia, had 72% (95% CI: 0.15-0.56), 55% (95% CI: 0.24-0.84), and 24% (95% CI: 0.61-0.94) lower odds of being underweight, respectively. Adolescents reporting tobacco use in Uganda, Algeria, and Namibia, had 2.30 (95% CI: 1.04-5.09), 1.71 (95% CI: 1.25-2.34), and 1.45 (95% CI: 1.00-2.12) times greater odds of being overweight/obese, but those in Indonesia and Malaysia had 33% (95% CI: 0.50-0.91) and 16% (95% CI: 0.73-0.98) lower odds of being overweight/obese.
CONCLUSIONS: The association between tobacco use and BMI categories is likely to be different among adolescents versus adults. Associating tobacco use with being thin may be more myth than fact and should be emphasized in tobacco prevention programs targeting adolescents.