DESIGN: GWG trajectories were identified using the latent class growth model. Binary logistic regression was performed to examine the associations between adverse pregnancy outcomes and these trajectories.
SETTING: Negeri Sembilan, Malaysia.
PARTICIPANTS: Two thousand one hundred ninety-three pregnant women.
RESULTS: Three GWG trajectories were identified: 'Group 1 - slow initial GWG but followed by drastic GWG', 'Group 2 - maintaining rate of GWG at 0·58 kg/week' and 'Group 3 - maintaining rate of GWG at 0·38 kg/week'. Group 1 had higher risk of postpartum weight retention (PWR) (adjusted OR (AOR) 1·02, 95 % CI 1·01, 1·04), caesarean delivery (AOR 1·03, 95 % CI 1·01, 1·04) and having low birth weight (AOR 1·04, 95 % CI 1·02, 1·05) compared with group 3. Group 2 was at higher risk of PWR (AOR 1·18, 95 % CI 1·16, 1·21), preterm delivery (AOR 1·03, 95 % CI 1·01, 1·05) and caesarean delivery (AOR 1·02, 95 % CI 1·01, 1·03), but at lower risk of having small-for-gestational-age infants (AOR 0·97, 95 % CI 0·96, 0·99) compared with group 3. The significant associations between group 1 and PWR were observed among non-overweight/obese women; between group 1 and caesarean delivery among overweight/obese women; group 2 with preterm delivery and caesarean delivery were only found among overweight/obese women.
CONCLUSIONS: Higher GWG as well as increasing GWG trajectories was associated with higher risk of adverse pregnancy outcomes. Promoting GWG within the recommended range should be emphasised in antenatal care to prevent the risk of adverse pregnancy outcomes.
METHODS: Out of the 7247 students in the ten selected schools studied, a total of 6248 students (2928 males, 3320 females) took part. A validated self-administered questionnaire was used. Data was analysed using SPSS version 22. Multivariable logistic regression was used to determine the adjusted odd ratio.
RESULTS: The prevalence of overweight and obesity was 16.0% and 11.5% respectively. Obesity/overweight was significantly (p<0.05) associated with gender, age, ethnicity, education level of father, education level of mother, physical activity, disordered eating, smoking status, body size perception and body part satisfaction. The multivariable analysis results showed that the odds of being overweight/obesity were higher in males compared to females (OR 1.56, 95%CI: 1.37, 1.77). The results also showed that the odds of being overweight/obesity were highest among those in age group 12 and 13 years and among Malay ethnicity. The odds of overweight/obesity were higher in those who was dissatisfied with their body parts, (OR 1.96, 95%CI: 1.71, 2.25), dissatisfied with their body size (OR: 4.25, 95%CI: 3.60, 5.02), low physical activity (OR 1.23, 95%CI: 1.06, 1.44), current smokers (OR 1.38, 95%CI: 1.07, 1.78) and at risk of having eating disorder (OR: 1.39, 95%CI 1.22, 1.59).
CONCLUSION: The overall prevalence of overweight and obesity is high. The findings from this study can be used by policy makers to plan an integrated intervention program in schools.
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 is a cross-sectional comparison study whereby 225 overweight/obese children matched for age, sex, and ethnicity with 225 normal weight children participated in this study. Body image dissatisfaction, disordered eating, and depressive symptoms were assessed through a self-administered questionnaire. Blood pressure was measured, whereas blood was drawn to determine insulin, high-sensitivity C-reactive protein (hs-CRP), glucose, and lipid profiles. Homeostasis model assessment-estimated insulin resistance (HOMA-IR) was calculated using glucose and insulin levels. Wechsler's Intelligence Scale for Children-Fourth Edition (WISC-IV) was used to assess cognitive function in children. Ordinary least square regression analysis was conducted to determine the direct and indirect relationships between weight status and cognitive function.
RESULTS: A negative relationship was found between overweight/obesity with cognitive function. Overweight/obese children were on average 4.075 units lower in cognitive function scores compared to normal weight children. Such difference was found through mediators, such as body image dissatisfaction, disordered eating, depression, systolic blood pressure, triglycerides, HOMA-IR, and hs-CRP, contributing 22.2% of the variances in cognitive function in children.
CONCLUSION: Results highlight the important mediators of the relationship between overweight/obesity and cognitive function. Consequently, future interventions should target to improve psychological well-being and reduce cardiovascular disease risk for the prevention of poorer cognitive performance in overweight/obese children.
AIM: To study factors associated with nonalcoholic steatohepatitis (NASH) and advanced fibrosis, and medical treatment of biopsy-proven nonalcoholic fatty liver disease (NAFLD) patients.
METHODS: Retrospective study of biopsy-proven NAFLD patients from centres in the GO ASIA Workgroup. Independent factors associated with NASH and with advanced fibrosis on binary logistic regression analyses in a training cohort were used for the development of their corresponding risk score, which were validated in a validation cohort.
RESULTS: We included 1008 patients from nine centres across eight countries (NASH 62.9%, advanced fibrosis 17.2%). Independent predictors of NASH were body mass index ≥30 kg/m2 , diabetes mellitus, dyslipidaemia, alanine aminotransferase ≥88 U/L and aspartate aminotransferase ≥38 U/L, constituting the Asia Pacific NASH risk score. A high score has a positive predictive value of 80%-83% for NASH. Independent predictors of advanced fibrosis were age ≥55 years, diabetes mellitus and platelet count <150 × 109 /L, constituting the Asia-Pacific NAFLD advanced fibrosis risk score. A low score has a negative predictive value of 95%-96% for advanced fibrosis. Only 1.7% of patients were referred for structured lifestyle program, 4.2% were on vitamin E, and 2.4% were on pioglitazone.
CONCLUSIONS: More severe liver disease can be suspected or ruled out based on factors identified in this study. Utilisation of structured lifestyle program, vitamin E and pioglitazone was limited despite this being a cohort of biopsy-proven NAFLD patients with majority of patients having NASH.