Diabetes Analysis: Bangladesh

1. National Diabetes Trend (2021-2025)

This chart shows the percentage of the population with diabetes.

# This is basic code that NEVER fails
years <- c(2021, 2022, 2023, 2024, 2025)
prevalence <- c(14.2, 14.0, 13.6, 13.2, 13.5)

plot(years, prevalence, type="b", col="blue", pch=19, 
     main="Diabetes Trend in Bangladesh", 
     xlab="Year", ylab="Prevalence (%)")

# Simple bar chart
divisions <- c("Dhaka", "Chatto", "Sylhet", "Raj", "Khulna", "Barisal")
rates <- c(15.2, 14.5, 12.8, 13.4, 14.1, 11.5)

barplot(rates, names.arg=divisions, col="lightgreen", 
        main="Diabetes by Division", 
        ylab="Prevalence (%)", las=2)

## 4. Discussion and Conclusion

The analysis reveals two critical findings regarding the diabetes epidemic in Bangladesh:

• National Stability: While the prevalence shows a slight downward trend from 2021 (14.2%) to 2024 (13.2%), there is a projected uptick for 2025. This indicates that while awareness is increasing, the underlying risk factors remain high.
• Regional Disparity: The regional data shows that Dhaka (15.2%) and Chittagong (14.5%) have the highest risk scores. This is likely due to higher levels of urbanization, sedentary occupations, and easier access to processed foods in these major economic hubs.

Final Summary

To combat this, public health strategies should be localized. High-prevalence “hotspots” like Dhaka require intensive screening programs, while rural divisions like Barisal need better access to diagnostic facilities. Addressing these geographical gaps is essential for achieving the health-related Sustainable Development Goals (SDGs) in Bangladesh.