How Could Different Obesity Scenarios Alter the Burden of Type 2 Diabetes and Liver Disease in Saudi Arabia?

Abstract

Introduction: Obesity is a major risk factor for type 2 diabetes (T2DM) and liver disease, and obesity-attributable liver disease is a common indication for liver transplant. Obesity prevalence in Saudi Arabia (SA) has increased in recent decades. SA has committed to the WHO "halt obesity" target to shift prevalence to 2010 levels by 2025. We estimated the future benefits of reducing obesity in SA on incidence and costs of T2DM and liver disease under two policy scenarios: (1) SA meets the "halt obesity" target; (2) population body mass index (BMI) is reduced by 1% annually from 2020 to 2040.

Methods: We developed a dynamic microsimulation of working-age people (20-59 years) in SA between 2010 and 2040. Model inputs included population demographic, disease and healthcare cost data, and relative risks of diseases associated with obesity. In our two policy scenarios, we manipulated population BMI and compared predicted disease incidence and associated healthcare costs to a baseline "no change" scenario.

Results: Adults <35 years are expected to meet the "halt obesity" target, but those ≥35 years are not. Obesity is set to decline for females, but to increase amongst males 35-59 years. If SA's working-age population achieved either scenario, >1.15 million combined cases of T2DM, liver disease, and liver cancer could be avoided by 2040. Healthcare cost savings for the "halt obesity" and 1% reduction scenarios are 46.7 and 32.8 billion USD, respectively.

Conclusion: SA's younger working-age population is set to meet the "halt obesity" target, but those aged 35-59 are off track. Even a modest annual 1% BMI reduction could result in substantial future health and economic benefits. Our findings strongly support universal initiatives to reduce population-level obesity, with targeted initiatives for working-age people ≥35 years of age.

Keywords: Dynamic microsimulation modelling; Liver cancer; Liver disease; Non-communicable diseases; Obesity; Type 2 diabetes.

Fig. 1.

Cumulative incidence avoided for type 2 diabetes, liver disease, and liver cancer, for each obesity policy scenario compared to baseline, amongst people 20–59 years, 2010–2040.

Fig. 2.

Cumulative direct healthcare costs avoided (USD) for type 2 diabetes, liver disease, and liver cancer, for each obesity policy scenario compared to baseline amongst people 20–59 years, 2010–2040.