OBJECTIVE: This study aims to assess physical activity levels among Malaysian adolescents and investigate the association between physical activity levels and body composition such as body mass index (BMI), waist circumference (WC) and percentage of body fat.
SUBJECTS AND METHODS: 1361 school-going 13 year old multi-ethnic adolescents from population representative samples in Malaysia were involved in our study. Self-reported physical activity levels were assessed using the validated Malay version of the Physical Activity Questionnaire for Older Children (PAQ-C). Height, weight, body fat composition and waist circumference (WC) were measured. Data collection period was from March to May 2012.
RESULTS: 10.8% of the males and 7.4% of the females were obese according to the International Obesity Task Force standards. A majority of the adolescents (63.9%) were physically inactive. There is a weak but significant correlation between physical activity scores and the indicators of obesity. The adjusted coefficient for body fatness was relatively more closely correlated to physical activity scores followed by waist circumference and lastly BMI.
CONCLUSION: This study demonstrates that high physical activity scores were associated with the decreased precursor risk factors of obesity.
METHODS: Behavioural Risk Factors Surveillance System data were used to estimate the weight the US population needed to lose to achieve a BMI
OBJECTIVE: To localize and quantify geometric morphometric differences in facial soft tissue morphology in adults with and without OSA.
MATERIALS AND METHODS: Eighty adult Malays, consisting of 40 patients with OSA and 40 non-OSA controls, were studied. Both groups were evaluated by the attending physician and through ambulatory sleep studies. 3-D stereophotogrammetry was used to capture facial soft tissues of both groups. The 3-D mean OSA and control facial configurations were computed and subjected to principal components analysis (PCA) and finite-element morphometry (FEM).
RESULTS: The body mass index was significantly greater for the OSA group (32.3 kg/m(2) compared to 24.8 kg/m(2), p < 0.001). The neck circumference was greater for the OSA group (42.7 cm compared to 37.1 cm, p < 0.001). Using PCA, significant differences were found in facial shape between the two groups using the first two principal components, which accounted for 50% of the total shape change (p < 0.05). Using FEM, these differences were localized in the bucco-submandibular regions of the face predominantly, indicating an increase in volume of 7-22% (p < 0.05) for the OSA group.
CONCLUSION: Craniofacial obesity in the bucco-submandibular regions is associated with OSA and may provide valuable screening information for the identification of patients with undiagnosed OSA.
METHODS: Data from World Health Survey conducted in 2002-2004 in low-middle- and high-income countries were used. Participants aged 18 years and over were selected using multistage, stratified cluster sampling. BMI was used as an outcome variable. Culture of the countries was measured using Hofstede's cultural dimensions: Uncertainty avoidance, individualism, Power Distance and masculinity. The potential determinants of individual-level BMI were participants' sex, age, marital status, education, occupation as well as household-wealth and location (rural/urban) at the individual-level. The country-level factors used were average national income (GNI-PPP), income inequality (Gini-index) and Hofstede's cultural dimensions. A two-level random-intercepts and fixed-slopes model structure with individuals nested within countries were fitted, treating BMI as a continuous outcome variable.
RESULTS: A sample of 156,192 people from 53 countries was included in this analysis. The design-based (weighted) mean BMI (SE) in these 53 countries was 23.95(0.08). Uncertainty avoidance (UAI) and individualism (IDV) were significantly associated with BMI, showing that people in more individualistic or high uncertainty avoidance countries had higher BMI than collectivist or low uncertainty avoidance ones. This model explained that one unit increase in UAI or IDV was associated with 0.03 unit increase in BMI. Power distance and masculinity were not associated with BMI of the people. National level Income was also significantly associated with individual-level BMI.
CONCLUSION: National culture has a substantial association with BMI of the individuals in the country. This association is important for understanding the pattern of obesity or overweight across different cultures and countries. It is also important to recognise the importance of the association of culture and BMI in developing public health interventions to reduce obesity or overweight.