Participants Attrition in a Longitudinal Study: The Malaysian Cohort Study Experience.

The attrition rate of longitudinal study participation remains a challenge. To date, the Malaysian Cohort (TMC) study follow-up rate was only 42.7%. This study objective is to identify the cause of attrition among TMC participants and the measures to curb it. A total of 19,343 TMC participants from Kuala Lumpur and Selangor that was due for follow-up were studied. The two most common attrition reasons are undergoing medical treatment at another government or private health center (7.0%) and loss of interest in participating in the TMC project (5.1%). Those who were inclined to drop out were mostly Chinese, aged 50 years and above, unemployed, and had comorbidities during the baseline recruitment. We have also contacted 2183 participants for the home recruitment follow-up, and about 10.9% agreed to join. Home recruitment slightly improved the overall follow-up rate from 42.7% to 43.5% during the three-month study period.

Differing Contributions of Classical Risk Factors to Type 2 Diabetes in Multi-Ethnic Malaysian Populations.

The prevalence of type 2 diabetes is escalating rapidly in Asian countries, with the rapid increase likely attributable to a combination of genetic and lifestyle factors. Recent research suggests that common genetic risk variants contribute minimally to the rapidly rising prevalence. Rather, recent changes in dietary patterns and physical activity may be more important. This nested case-control study assessed the association and predictive utility of type 2 diabetes lifestyle risk factors in participants from Malaysia, an understudied Asian population with comparatively high disease prevalence. The study sample comprised 4077 participants from The Malaysian Cohort project and included sub-samples from the three major ancestral groups: Malay (n = 1323), Chinese (n = 1344) and Indian (n = 1410). Association of lifestyle factors with type 2 diabetes was assessed within and across ancestral groups using logistic regression. Predictive utility was quantified and compared between groups using the Area Under the Receiver-Operating Characteristic Curve (AUC). In predictive models including age, gender, waist-to-hip ratio, physical activity, location, family history of diabetes and average sleep duration, the AUC ranged from 0.76 to 0.85 across groups and was significantly higher in Chinese than Malays or Indians, likely reflecting anthropometric differences. This study suggests that obesity, advancing age, a family history of diabetes and living in a rural area are important drivers of the escalating prevalence of type 2 diabetes in Malaysia.

Association of job sectors with type 2 diabetes mellitus, hypercholesterolemia and obesity: a cross-sectional study from the Malaysian Cohort (TMC) project.

Background: The investigation of risk factors of cardiovascular disease (e.g., major endocrine, nutritional and metabolic diseases) across job sectors is useful for targeted public health intervention. This study examined the occurrence of type 2 diabetes mellitus (T2DM), hypercholesterolemia and obesity in 21 job sectors in the general population. Methods: A baseline cross-sectional analysis of the Malaysian Cohort was conducted, which included 105 391 adults. Multiple logistic regression analyses were conducted for these three diseases across 20 job sectors compared with the unemployed/homemaker sector. Results: The prevalence of T2DM, hypercholesterolemia and obesity was 16.7%, 38.8% and 33.3%, respectively. The Accommodation & Food Service Activities and Transportation & Storage sectors had significantly higher odds for T2DM (adjusted [adj.] prevalence odds ratio [POR] 1.18, p=0.007 and adj. POR 1.15, p=0.008, respectively). No job sector had significantly higher odds for hypercholesterolemia compared with the unemployed/homemaker sector. Only the Accommodation & Food Service Activities sector had significantly higher odds for obesity (adj. POR 1.17, p≤0.001). Conclusions: Many job sectors were significantly associated with lower odds of having these three diseases when compared with the unemployed/homemaker sector. These differing associations between diverse job sectors and these diseases are important for public health intervention initiatives and prioritization.