Silent Diabetes: Key Risk Factors Among the Low-Income Population of Langkawi Island, Kedah, Malaysia (2022-2023).

BACKGROUND

Diabetes mellitus (DM) poses a growing global health challenge, contributing to significant morbidity, mortality, and economic burden. In Malaysia, the prevalence of diabetes is increasing, especially among low-income populations with limited access to healthcare. Many cases remain undiagnosed, increasing the risk of severe complications and further straining healthcare resources. Island populations, such as those in Langkawi, are particularly vulnerable due to geographical isolation, socioeconomic constraints, and inadequate healthcare services.

OBJECTIVES

To determine the prevalence of undiagnosed DM and identify the associated risk factors among the low-income population on Langkawi Island, Kedah, Malaysia.

METHODS

We conducted a cross-sectional study from January 2022 to December 2023, involving 1,070 participants aged 40 years and above, all eligible under the low-income scheme. Data on sociodemographic characteristics, body mass index (BMI), lifestyle, and medical history were collected through a structured proforma from four local health clinics. Logistic regression analysis was used to identify significant predictors of undiagnosed DM. The model's predictive accuracy was assessed using the area under the receiver operating characteristic (ROC) curve.

RESULTS

The prevalence of undiagnosed DM among the low-income population on Langkawi Island was 6.7%. Multiple logistic regression found three important predictors: having a higher BMI (overweight: adjusted odds ratio (AOR): 2.72; 95% confidence interval (CI): 1.40-5.30; p = 0.003; obese: AOR: 2.43; 95% CI: 1.19-5.00; p = 0.015); living on a smaller island (AOR: 1.71; 95% CI: 1.03-2.85; p = 0.039); and having a medical history (AOR: 0.21; 95% CI: 0.12-0.36; p < 0.001). The model demonstrated good predictive accuracy with an area under the ROC curve of 0.758 and correctly classified 93.3% of cases.

CONCLUSION

This study reveals a significant burden of undiagnosed DM within Langkawi's low-income population, especially among individuals with higher BMI and those residing in geographically isolated areas. The findings highlight the urgent need for enhanced, context-specific screening programs and early detection efforts tailored to this vulnerable population. Effective public health strategies should prioritize regular health check-ups, obesity management, and improved access to healthcare services in isolated communities to reduce the prevalence and complications associated with undiagnosed diabetes.