Materials and Methods: Blood samples were collected from a total of 91 goats selected at random. Blood serum was harvested and used for competitive enzyme-linked immunosorbent assay test to detect antibodies against CAE virus.
Results: The result obtained showed that 8/91 (8.8%) of the goats were seropositive for CAEV. In addition, biosecurity management, source of origin and sex of the animal were observed to be important risk factors associated with the occurrence of CAE in goats.
Conclusion: The findings of this study affirmed that the seroprevalence of CAEV infection among goat population in small ruminant farms in Selangor, Malaysia, is low. However, there is need to institute strict control measures such as testing and culling positive animals or separation of infected animals from those that tested negative to the disease for effective eradication of the disease.
METHODS AND STUDY DESIGN: Using a stratified multi-stage sampling, a total of 816 children (282 boys and 534 girls) aged 10 to 11 years from 12 selected primary schools in the state of Selangor, participated in this study. Data were collected on socio-demographic characteristics, pubertal status and disordered eating behaviors. The Pubertal Development Scale and the Children's Eating Attitudes Test (ChEAT) were used to assess pubertal status and disordered eating, respectively. Logistic regression analysis was conducted to determine the risk factors of disordered eating.
RESULTS: The prevalence of disordered eating was 30.8% (32.8% in boys and 29.7% in girls). However, the sex difference in the prevalence was not statistically significant. Age, ethnicity and pubertal status were significantly associated with disordered eating in univariate logistic regression analysis. Multivariate logistic regression analysis showed that among boys, being either in an advanced or post-pubertal stage (adjusted OR=8.64) and older age group (adjusted OR=2.03) were risk factors of disordered eating. However, among girls, being a Malay (adjusted OR=3.79) or Indian (adjusted OR=5.04) in an advanced or post-pubertal stage (adjusted OR=2.34) and older age group (adjusted OR=1.53) were risk factors of disordered eating.
CONCLUSION: This study found one in three children had disordered eating. Since ethnicity and pubertal status were identified as risk factors, ethnicity-specific intervention programs on the prevention of disordered eating among children should take into consideration their pubertal status.
Methods: A multi-centred matched case control study was conducted in five local hospitals. A total of 140 histologically confirmed CRC cases were matched with 280 cancer free controls. Mean value and prevalence of the components of metabolic syndrome between cases and controls were measured based on the three definitions. A multiple variable analysis using Cox regression was conducted to measure the strength of the association between the definitions of MetS, components of MetS and risk of CRC.
Results: Multiple variable analyses showed that metabolic syndrome significantly and independently increased the risk of CRC, with an odds ratio ranging from 1.79 to 2.61. This study identified that the definition of metabolic syndrome by the International Diabetes Federation is the most sensitive in predicting the risk of CRC, compared to metabolic syndrome as defined by the World Health Organization and National Cholesterol Education Program Adults Treatment Panel III. Abdominal obesity, low HDL-cholesterol, and hypertension were identified as the three core risk factors, which promote inflammatory signals that contribute to metabolic syndrome and an increased risk of CRC.
Conclusions: These data hypothesized that simple measurement of abdominal obesity, abnormal BP and HDL-cholesterol especially using International Diabetes Federation (IDF) definition of MetS for South Asians for to detect individuals at CRC risk may have higher clinical utility than applying other universal complex MetS definitions.
Objective: To investigate medication adherence among patients with and without medication subsidies and to identify factors that may influence patients' adherence to medication. Setting: Government healthcare institutions in Kuala Lumpur, Selangor, and Negeri Sembilan and private healthcare institutions in Selangor and Negeri Sembilan, Malaysia.
Methods: This cross-sectional study sampled patients with and without medication subsidies (self-paying patients). Only one of the patient's medications was re-packed into Medication Event Monitoring Systems (MEMS) bottles, which were returned after four weeks. Adherence was defined as the dose regimen being executed as prescribed on 80% or more of the days. The factors that may influence patients' adherence were modelled using binary logistic regression. Main outcome measure: Percentage of medication adherence.
Results: A total of 97 patients, 50 subsidized and 47 self-paying, were included in the study. Medication adherence was observed in 50% of the subsidized patients and 63.8% of the self-paying patients (χ2=1.887, df=1, p=0.219). None of the evaluated variables had a significant influence on patients' medication adherence, with the exception of attending drug counselling. Patients who attended drug counselling were found to be 3.3 times more likely to adhere to medication than those who did not (adjusted odds ratio of 3.29, 95% CI was 1.42 to 7.62, p = 0.006).
Conclusion: There is no significant difference in terms of medication adherence between subsidized and self-paying patients. Future studies may wish to consider evaluating modifiable risk factors in the examination of non-adherence among subsidized and self-paying patients in Malaysia.
METHODS: Data were obtained from the 2012 Malaysia Global School-based Student Health Survey. Generalized ordered logit regression analysis was conducted on 24 339 adolescents by PA status.
RESULTS: Early- (ages 11-13) and middle-stage (ages 14-16) adolescents were associated with higher overweight and obesity risks than their older peers (ages 17-18). Male adolescents faced higher underweight and obesity likelihoods than females. Hunger due to food shortage at home was associated with higher likelihoods of underweight and normal weight BMI categories. Smokers were more likely to be underweight or normal weight than non-smokers. Segmented-sample analysis by PA status indicated that, while the direction of associations was parallel across PA status, the magnitudes of association between age, hunger and smoking status with BMI status were greater among active than inactive adolescents.
CONCLUSIONS: Male adolescents faced a dual burden of underweight and obesity. Other sociodemographic and dietary-lifestyle factors were associated with adolescent BMI categories. Segmented-sample analysis by PA status uncovered varying associations between factors that would otherwise be masked in pooled sample analysis. Public health authorities should take these factors into consideration when deliberating programs to ensure healthy adolescent body weight.