Comparison of surveillance-based metrics for the assessment and monitoring of disease detection: simulation study about type 2 diabetes

Analysing detection of chronic diseases with prolonged sub-clinical periods: modelling and application to hypertension in the U.S

Background

We recently introduced a system of partial differential equations (PDEs) to model the prevalence of chronic diseases with a possibly prolonged state of asymptomatic, undiagnosed disease preceding a diagnosis. Common examples for such diseases include coronary heart disease, type 2 diabetes or cancer. Widespread application of the new method depends upon mathematical treatment of the system of PDEs.

Methods

In this article, we study the existence and the uniqueness of the solution of the system of PDEs. To demonstrate the usefulness and importance of the system, we model the age-specific prevalence of hypertension in the US 1999–2010.

Results

The examinations of mathematical properties provide a way to solve the systems of PDEs by the method of characteristics. In the application to hypertension, we obtain a good agreement between modeled and surveyed age-specific prevalences.

Conclusions

The described system of PDEs provides a practical way to examine the epidemiology of chronic diseases with a state of undiagnosed disease preceding a diagnosis.

Considerations in Epidemiologic Definitions of Undiagnosed Diabetes

Accurately quantifying undiagnosed type 2 diabetes is an important challenge for conducting diabetes surveillance and identifying the potential missed opportunities for preventing complications. However, there has been little focused attention on how undiagnosed diabetes is defined in epidemiologic surveys and how limitations in methods used to ascertain undiagnosed diabetes may impact our understanding of the magnitude of this important public health problem. This Perspective highlights weaknesses in how undiagnosed diabetes is quantified in epidemiologic research and the biases and caveats that should be considered when using estimates of undiagnosed diabetes to influence public health policy.

Trends in type 2 diabetes detection among adults in the USA, 1999-2014

OBJECTIVE

To examine recent trends in type 2 diabetes detection among adults in the USA.

RESEARCH DESIGN AND METHODS

We used data from the 1999-2014 National Health and Nutrition Examination Surveys on non-pregnant adults (aged ≥18 years) not reporting a diagnosis of diabetes (n=16 644 participants, averaging about 2000 for each 2-year cycle). We defined undiagnosed diabetes as a fasting plasma glucose ≥126 mg/dL or a hemoglobin A1c ≥6.5% (48 mmol/mol). We measured case detection as the probability of finding undiagnosed type 2 diabetes among the population without diagnosed diabetes. Linear regression models were used to examine trends overall and by sociodemographic characteristics (ie, age, gender, race/ethnicity, education, poverty-income ratio (PIR)).

RESULTS

Age-standardized probability of finding undiagnosed type 2 diabetes was 3.0% (95% CI 2.1% to 4.2%) during 1999-2000 and 2.8% (2.2%-3.6%) during 2013-2014 (P for trend=0.52). Probability increased among Mexican-Americans (P for trend=0.01) but decreased among adults aged 65 years or older (P for trend=0.04), non-Hispanic (NH) white (P for trend=0.02), and adults in the highest PIR tertile (P for trend=0.047). For all other sociodemographic groups, no significant trends were detected.

CONCLUSIONS

We found little evidence of increased detection of undiagnosed type 2 diabetes among adults in the USA during the past 15 years. Although improvements were seen among NH white, older, and wealthy adults, these improvements were not large. As the scope of primary prevention efforts increases, case detection may improve.