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 AND STUDY DESIGN: Collective food data from MyHeARTs 2012 database were used to construct the MyUM Adolescent FFQ. Seventy-eight participants between 13 and 15 years old in 2014 were selected through convenient sampling for test-retest study. They completed the MyUM Adolescent FFQ twice, with an interval period of one week. One hundred and fifty-six MyHeARTs study participants who were 15 years old in 2014 were randomly selected for this comparative valid-ity study. They completed a 7-day diet history (7DDH) and subsequently completed the self-administered MyUM Adolescent FFQ.
RESULTS: Pearson's correlations between the FFQ and 7DDH for all macronutrients were statistically significant. Energy-adjusted correlations for protein, carbohydrate, and fat were 0.54, 0.63 and 0.49 respectively. Most of the micronutrients and minerals, were statistically correlated ranging from 0.31 to 0.49 after energy adjustment. Cross-classification analyses revealed that more than 70 percent of adolescents were classified into either the same or adjacent quartile of nutrient intake when comparing data of 7DDH and FFQ. No serious systematic bias was evident in the Bland-Altman plots.
CONCLUSION: The 200-item FFQ developed for Malaysian adolescents has moderate to good comparative validity for assessment of macronutrient and micronutrient intake.
METHODS: A total of 1598 questionnaires were posted to all female staff, aged 35 years and above. Their knowledge on breast cancer, practice of BSE and detection rate of breast abnormality as confirmed by CBE was determined.
RESULTS: The response rate for this study was 45 percent (714 respondents). The rate of respondents having awareness on breast cancer was 98.7 percent. Eighty four percent (598) of the respondents had performed BSE in their lifetime. However, in only 41% was it regular at the recommended time. Forty seven percent (334) had undergone CBE at least once in a lifetime but only 26% (185) had CBE at least once in the past 3 years, while 23% (165) had had a mammogram. There was a significant relationship between CBE and BSE whereby those who had CBE were twice more likely to do BSE. Nineteen percent (84 respondents) of those who did BSE claimed they had detected a breast lump. Of these, 87% (73) had gone for CBE and all were confirmed as such.
CONCLUSION: BSE is still relevant as a screening tool of breast cancer since those who detect breast lump by BSE will most probably go for further check up. CBE should be done to all women, especially those at highest risk of breast cancer, to encourage and train for BSE.
METHODS: Data were derived from a cross-sectional study of 1082 adolescents in 22 welfare institutions located across Peninsular Malaysia in 2009. Using supervised self-administered questionnaires, adolescents were asked to assess their self-esteem and to complete questions on pubertal onset, substance use, family structure, family connectedness, parental monitoring, and peer pressure. SRB was measured through scoring of five items: sexual initiation, age of sexual debut, number of sexual partners, condom use, and sex with high-risk partners. Multivariate logistic regression analysis was used to examine the various predictors of sexual risk behaviour.
RESULTS: The study showed that 55.1% (95%CI = 52.0-58.2) of the total sample was observed to practice sexual risk behaviours. Smoking was the strongest predictor of SRB among male adolescents (OR = 10.3, 95%CI = 1.25-83.9). Among females, high family connectedness (OR = 3.13, 95%CI = 1.64-5.95) seemed to predict the behaviour.
CONCLUSION: There were clear gender differences in predicting SRB. Thus, a gender-specific sexual and reproductive health intervention for institutionalised adolescents is recommended.