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INTRODUCTION: A cross-sectional study is used to evaluate the lifestyle factors associated with cardiovascular disease (CVD) risk among healthcare workers in tertiary hospitals in Sarawak, Malaysia. METHODS: A questionnaire-based survey using the Simple Lifestyle Indicator Questionnaire (SLIQ) was administered to, and anthropometric measurements were collected from, 494 healthcare workers. RESULTS: The mean age of the subjects was 32.4±8.4, with a range of 19 to 59 years. The subjects were from the allied health (45.5%), management and professional (25.1%) and executive (29.4%) fields. Overall, 47.4% of the subjects were of normal weight, 30.2% were overweight, 17.2% were obese and 5.2% were underweight. The mean number of working hours per week for the subjects was 47.6±14.0 with the highest working hours found among the management and professional group, followed by the executive and allied health groups. Overall, 39.7% of the healthcare workers worked office hours, 36.6% worked within the shift system, 20.9% worked office hours and were on-call and the remaining 2.8% worked a mixture of office hours and shifts. Based on the SLIQ score, 58.1% were classified as at intermediate risk for CVD, 38.5% were in the healthy category and 3.4% were in the unhealthy category. Factors associated with a healthier lifestyle were being female (Odds Ratio [OR]= 12.1; CI=3.2-46.4), professional (mean score= 6.70), in the allied health group (mean score=7.33) and in the normal BMI group (OR= 9.3, CI= 1.8-47.0). CONCLUSION: In our study, healthcare workers had an intermediate risk of developing CVD in the future. Thus, there is a need to intervene in the lifestyle factors contributing to CVD.
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INTRODUCTION: Clinical parameters especially co-morbidities among end stage renal disease (ESRD) patients are associated with mortality. This study aims to determine the risk factors that are associated with mortality within three years among prevalent patients with ESRD. METHODS: This is a cohort study where prevalent ESRD patients' details were recorded between May 2012 and October 2012. Their records were matched with national death record at the end of year 2015 to identify the deceased patients within three years. Four models were formulated with two models were based on logistic regression models but with different number of predictors and two models were developed based on risk scoring technique. The preferred models were validated by using sensitivity and specificity analysis. RESULTS: A total of 1332 patients were included in the study. Majority succumbed due to cardiovascular disease (48.3%) and sepsis (41.3%). The identified risk factors were mode of dialysis (P < 0.001), diabetes mellitus (P < 0.001), chronic heart disease (P < 0.001) and leg amputation (P = 0.016). The accuracy of four models was almost similar with AUC between 0.680 and 0.711. The predictive models from logistic regression model and risk scoring model were selected as the preferred models based on both accuracy and simplicity. Besides the mode of dialysis, diabetes mellitus and its complications are the important predictors for early mortality among prevalent ESRD patients. CONCLUSIONS: The models either based on logistic regression or risk scoring model can be used to screen high risk prevalent ESRD patients.