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  1. Andoy-Galvan JA, Sriram S, Kiat TJ, Xin LZ, Shin WJ, Chinna K
    F1000Res, 2023;12:550.
    PMID: 37868299 DOI: 10.12688/f1000research.125203.1
    Background: Doctors with a normal BMI and healthy living habits have shown to be more confident and effective in providing realistic guidance and obesity management to their patients. This study investigated obesogenic tendencies of medical students as they progress in their medical studies. Methods: A cohort of forty-nine medical students enrolled in a five-year cohort study and was followed up after one year. At the initiation of the cohort, socio-demography and information on anthropometry, accommodation, eating behavior, stress and sleeping habits of the students had been recorded. Follow-up data was collected using a standardized self-administered questionnaire. Results: Thirty-seven percent of the students in the cohort are either obese or overweight in the one-year period.. A year of follow-up suggests that there is an increase in BMI among the male students (P=0.008) and the changes are associated with changes in accommodation (P=0.016), stress levels (P=0.021), and sleeping habits (P=0.011). Conclusion: Medical education system should seriously consider evaluating this aspect in the curriculum development to help our future medical practitioners practice a healthy lifestyle and be the initiator of change in the worsening prevalence of obesity worldwide.
  2. Andoy Galvan JA, Ramalingam PN, Patil SS, Bin Shobri MAS, Chinna K, Sahrir MS, et al.
    Heliyon, 2020 Oct;6(10):e05068.
    PMID: 33083595 DOI: 10.1016/j.heliyon.2020.e05068
    Rising prevalence of autism spectrum disorders (ASD) in the last decades has led research to focus on the diagnosis and identification of factors associated with ASD. This paper sought for possible factors that put children at risk for ASD. In this study, we investigated the association between ASD and parental ages, parental age gaps, birth order and birth delivery method in Malaysian population. In this school-based case control study, 465 children with ASD 464 controls participated. Questionnaires were distributed to the parents of the selected children through the respective principals. Among the tested variables, Caesarean section (OR = 1.63, 95% CI 1.20, 2.20), earlier order of birth in the family (OR = 0.68, 95% CI 0.59, 0.77) and increasing gap in parental ages (OR = 1.04, 95% CI 1.001, 1.07) were significantly associated with ASD. This study concludes that Caesarean section, earlier order of birth in the family and increasing gap in parental age are independent risk factors for developing autism among Malaysian children.
  3. Lugova H, Andoy-Galvan JA, Patil SS, Wong YH, Baloch GM, Suleiman A, et al.
    Community Ment Health J, 2021 11;57(8):1489-1498.
    PMID: 33417170 DOI: 10.1007/s10597-020-00765-7
    Growing prevalence of mental illnesses and the role they play in the global disease burden is an emerging public health issue. The prevalence of depression and anxiety is on the rise in Malaysia. Low-income urban communities are among the key affected populations with regards to mental health problems. This cross-sectional study was aimed to determine the prevalence and severity of depression, anxiety and stress, and their associated factors among adults in the low-income community of Kuala Lumpur, Malaysia. A total of 248 participants aged 18-60 years old were recruited. Data were collected via face-to-face interviews using the Depression, Anxiety and Stress Scale-21 Items (DASS-21). Chi-squared test was used to examine the association between the variables. Multiple ordinal regression model was introduced to identify the predictors of depression, anxiety and stress. The proportions of participants with depression, anxiety and stress were 24.2% (95% CI: 19.6-30.4), 36.3% (95% CI: 29.9-43.0), and 20.6% (95% CI: 15.4-26.5), respectively. There was a statistically significant association of ethnicity (p = 0.002) and age (p = 0.014) with the severity of depression, ethnicity (p = 0.001) and age (p = 0.024) with the severity of anxiety, and ethnicity (p 
  4. Andoy-Galvan JA, Lugova H, Patil SS, Wong YH, Baloch GM, Suleiman A, et al.
    F1000Res, 2020;9:160.
    PMID: 32399203 DOI: 10.12688/f1000research.22236.1
    Background: Recent studies have shown that higher income is associated with a higher risk for subsequent obesity in low- and middle-income countries, while in high-income countries there is a reversal of the association - higher-income individuals have a lower risk of obesity. The concept of being able to afford to overeat is no longer a predictor of obesity in developed countries. In Malaysia, a trend has been observed that the prevalence of obesity increases with an increase in income among the low-income (B40) group. This trend, however, was not further investigated. Therefore, this study was performed to investigate the association of income and other sociodemographic factors with obesity among residents within the B40 income group in an urban community.  Methods: This cross-sectional study used a systematic sampling technique to recruit participants residing in a Program Perumahan Rakyat (PPR), Kuala Lumpur, Malaysia. The sociodemographic characteristics were investigated through face-to-face interviews. Weight and height were measured, and body mass index (BMI) was calculated and coded as underweight, normal, overweight and obese according to the cut-off points for the Asian population. A chi-squared test was used to compare the prevalence of obesity in this study with the national prevalence. A generalized linear model was introduced to identify BMI predictors. Results: Among the 341 participants, 25 (7.3%) were underweight, 94 (27.6%) had normal weight, 87 (25.5%) were overweight, and 135 (39.6%) were obese. The proportion of obese adults (45.8%) was significantly higher than the national prevalence of 30.6% (p<0.001). Among all the tested variables, only income was significantly associated with BMI (p=0.046). Conclusion: The proportion of obesity in this urban poor community was higher compared with the national average. BMI increased as the average monthly household income decreased.
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