Estimating the prevalence of select non-communicable diseases in Saudi Arabia using a population-based sample: econometric analysis with natural language processing

BACKGROUND:
Non-communicable diseases (NCDs) are a major public health challenge globally, including in Saudi Arabia. However, measuring the true extent of NCD prevalence has been hampered by a paucity of nationally representative epidemiological studies.


OBJECTIVES:
Assess the prevalence of selected NCDs, using population-based electronic health records and applying novel analytical methods to identify cases of NCDs.


DESIGN:
Retrospective


SETTINGS:
A large healthcare network in Saudi Arabia.


PATIENTS AND METHODS:
We included all beneficiaries aged 16 years or older (n=650 835[a]) and used the International Classification of Disease (ICD-10) codes, laboratory results, and associated medications to identify individuals with diabetes, obesity, hypertension, dyslipidemia, mental disorders, and injuries. For diabetes and hypertension, we used natural language processing (NLP) on clinical notes in the electronic health records. The prevalence of multimorbidity across age groups was also tabulated, and logistic regression was used to examine its association with glycemic control.


MAIN OUTCOME MEASURES:
The primary outcomes measured were the prevalence of diabetes, hypertension, and multimorbidity, and their association with glycemic control.


SAMPLE SIZE:
650 835 individuals aged 16 years or older.


RESULTS:
The study population was relatively young, with 41.2% aged between 26 and 45 years, and around two-thirds were married. The prevalence of diabetes and hypertension was 18.5% (95% CI: 18.5-18.7) and 13.0% (95% CI: 12.9-13.1), respectively. Approximately 26.7% (95% CI: 26.7-26.8) of the population had multimorbidity, with levels increasing to 62.9% for those aged 65 or older. Multimorbidity was associated with a four-fold increase in the likelihood of poor glycemic control. NLP analysis suggested that the prevalence of diabetes or hypertension may be underestimated by no more than 1.5%.


CONCLUSIONS:
The study suggests a higher prevalence of NCDs than earlier national estimates. Electronic health records with regular analysis provide an opportunity to estimate changes in the prevalence of NCDs in Saudi Arabia. Health policies and interventions are needed to address the high levels of multimorbidity, which adversely impact glycemic control.


LIMITATIONS:
Retrospective design and reliance on electronic health records, which may not capture all cases of NCDs.