Displaying publications 21 - 22 of 22 in total

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  1. Wan Puteh SE, Siwar C, Zaidi MAS, Abdul Kadir H
    BMC Public Health, 2019 Jun 13;19(Suppl 4):551.
    PMID: 31196024 DOI: 10.1186/s12889-019-6853-7
    BACKGROUND: The rapid growth of economy and increasing cost of living in Malaysia have given significant impact especially to the lowest household income population. The main objective of this study was to determine risk factors for low quality of life (QOL) and poor health status of this population.

    METHODS: This was a cross sectional study design. A total of 347 respondents from low household income groups, including persons with disability and Orang Asli were recruited from E-kasih. A semi-guided self-administered questionnaire was used. QOL measured by EQ. 5D utility value and health status measured by visual analogue score (VAS). Descriptive statistic, bivariate Chi-square analysis and binary logistic regression were conducted to determine factors influencing low QOL and poor health status.

    RESULTS: Majority of the respondents were Malay, female (61%), 63% were married, 60% were employed and 46% with total household income of less than 1 thousand Ringgit Malaysia. 70% of them were not having any chronic medical problems. Factors that associated with low QOL were male, single, low household income, and present chronic medical illness, while poor health status associated with female, lower education level and present chronic medical illness. Logistic regression analysis has showed that determinants of low QOL was present chronic illness [AOR 4.15 95%CI (2.42, 7.13)], while determinants for poor health status were; female [AOR 1.94 95%CI (1.09,3.44)], lower education [AOR 3.07 95%CI (1.28,7.34)] and present chronic illness [AOR 2.53 95%CI (1.39,4.61)].

    CONCLUSION: Low socioeconomic population defined as low total household income in this study. Low QOL of this population determined by present chronic illness, while poor health status determined by gender, education level and chronic medical illness.

    Matched MeSH terms: Employment/statistics & numerical data
  2. Chua YC, Abdin E, Tang C, Subramaniam M, Verma S
    Schizophr Res, 2019 09;211:63-68.
    PMID: 31327504 DOI: 10.1016/j.schres.2019.07.009
    Most studies on predictors of vocational outcomes are cross-sectional and results are varied. This study aimed to examine the vocational rates of patients with first-episode psychosis (FEP), identify factors predicting a lack of engagement in age-appropriate roles, and evaluate the predictive ability of a model with baseline sociodemographic information and 2-year symptom and functioning trajectories on vocational outcomes. The Singapore Early Psychosis Intervention Program (EPIP) has maintained a standing database on patient clinico-demographic information. The primary outcome, vocational status, was operationalized as "meaningfully employed", that is, being gainfully employed or engaged in an age-appropriate role, and "unemployed". Using logistic regression, the predictive ability of the proposed model was evaluated. Vocational data was available for 1177 patients accepted into EPIP between 2001 and 2012. At the end of two years in the service, 829 (70.4%) patients were meaningfully employed and 348 (29.6%) patients were unemployed. The binary logistic regression model on the prediction of 2-year vocational outcomes yielded an AUC of 0.759 (SE = 0.016, p-value 
    Matched MeSH terms: Employment/statistics & numerical data*; Unemployment/statistics & numerical data*
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