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  1. Cheong SM, Mohamad Nor NS, Ahmad MH, Manickam M, Ambak R, Shahrir SN, et al.
    BMC Womens Health, 2018 07 19;18(Suppl 1):99.
    PMID: 30066659 DOI: 10.1186/s12905-018-0596-y
    BACKGROUND: Health literacy (HL) consists of different components and associates with several health outcomes, including obesity. It is linked to an individual's knowledge, motivation, competencies, behavior, and application to everyday life. The present study aimed to determine the change of HL scores and to investigate the difference of intervention outcomes at the weight loss (WL) intervention and WL maintenance phase between the HL groups.

    METHODS: A total of 322 participants from the MyBFF@home study completed the Newest Vital Sign (NVS) test at baseline. However, only data from 209 participants who completed the NVS test from baseline to WL intervention were used to determine the HL groups. Change of the NVS scores from baseline to WL intervention phase was categorized into two groups: those with HL improvement (increased 0.1 score and above) and those without HL improvement (no change or decreased 0.1 score and more). Independent variables in this study were change of energy intake, nutrient intake, physical activity, anthropometry measurements, and body composition measurements between baseline and WL intervention as well as between WL intervention and WL maintenance. An Independent sample t-test was used in the statistical analysis.

    RESULTS: In general, both intervention and control participants have low HL. The study revealed that the intervention group increased the NVS mean score from baseline (1.19 scores) to the end of the WL maintenance phase (1.51 scores) compared to the control group. There was no significant difference in sociodemographic characteristics between the group with HL improvement and the group without HL improvement at baseline. Most of the dietary intake measurements at WL intervention were significantly different between the two HL groups among intervention participants. Physical activity and body composition did not differ significantly between the two HL groups among both intervention and control groups.

    CONCLUSION: There was an improvement of HL during the WL intervention and WL maintenance phase in intervention participants compared to control participants. HL shows positive impacts on dietary intake behavior among intervention participants. New research is suggested to explore the relationship between HL and weight loss behaviors in future obesity intervention studies.

  2. Mutalip MH, Kamarudin RB, Manickam M, Abd Hamid HA, Saari RB
    Alcohol Alcohol, 2014 Sep-Oct;49(5):593-9.
    PMID: 25015981 DOI: 10.1093/alcalc/agu042
    AIMS: To identify the characteristics of current drinker and risky alcohol-drinking pattern by profiles in Malaysia.
    METHODS: We analyzed data from the National Health and Morbidity Survey 2011. It was a cross-sectional population-based with two stages stratified random sampling design. A validated Alcohol Use Disorder Identification Test Malay questionnaire was used to assess the alcohol consumption and its alcohol related harms. Analysis of complex survey data using Stata Version 12 was done for descriptive analysis on alcohol use and risky drinking by socio-demography profiles. Logistic regression analysis was used to measure the association of risky drinking status with the socio-demography characteristics.
    RESULTS: The prevalence of current alcohol use was 11.6% [95% confidence interval (CI): 10.5, 12.7], among them 23.6% (95% CI: 21.0, 26.4) practiced risky drinking. The onset for alcohol drinking was 21 years old (standard deviation 7.44) and majority preferred Beer. Males significantly consumed more alcohol and practiced risky drinking. Current alcohol use was more prevalent among urbanites, Chinese, those with high household income, and high education. Conversely, risky drinking was more prevalent among rural drinkers, Bumiputera Sabah and Sarawak, low education and low household income. The estimated odds of risky drinking increased by a factor of 3.5 among Males while a factor of 2.7 among Bumiputera Sabah and Sarawak. Education status and household income was not a significant predictor to risky drinking.
    CONCLUSION: There was an inverse drinking pattern between current drinker and risky drinking by the socio-demography profiles. Initiating early screening and focused intervention might avert further alcohol related harms and dependence among the risky drinkers.
    Study name: National Health and Morbidity Survey (NHMS-2011)
  3. Ghazali SM, Seman Z, Cheong KC, Hock LK, Manickam M, Kuay LK, et al.
    BMC Public Health, 2015;15:68.
    PMID: 25636327 DOI: 10.1186/s12889-015-1432-z
    BACKGROUND: To determine the prevalence and sociodemographic correlates of multiple risk factors for cardiovascular disease (CVD) among Malaysian adults.
    METHODS: We analysed data on 1044 men and 1528 women, aged 24-64 years, participants in the Non Communicable Disease Surveillance 2005/2006, a nationally representative, population-based, cross-sectional study. Prevalence of obesity, high blood pressure, dyslipidaemia, hyperglycemia, physical inactivity, smoking, risky drinking, low vegetable and fruit intake were determined and multivariable logistic regression was used to identify sociodemographic factors associated with having ≥3 of these cardiovascular disease risk factors.
    RESULTS: The response rate was 84.6% (2572/3040). Overall, 68.4% (95% CI: 63.2, 73.1) had at least three risk factors. Among men, older age and Indian ethnicity were independently associated with having ≥3 CVD risk factors; while among women, older age, low education, and housewives were more likely to have ≥3 CVD risk factors.
    CONCLUSION: The prevalence of cardiovascular risk factors clustering among Malaysian adults is high, raising concerns that cardiovascular disease incidence will rise steeply in the near future if no immediate preventive measures are taken. The current national health education and promotion programmes pertaining to modifiable risk factors can be further improved by taking into account the sociodemographic variation in CVD risk factors clustering.
    Study name: Malaysia Non-Communicable Disease Surveillance-1 (MyNCDS-1) survey.
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