Aggregate Risk Factor Control in Persons with Diabetes Mellitus: Current State and Future Directions

In recent years, there has been a deceleration in the rate of decline of cardiovascular disease (CVD) mortality. These trends are paralleled by a steady rise in the prevalence of diabetes mellitus (DM),1 which is associated with a high degree of morbidity and mortality from CVD. Recognizing the high burden of CVD in persons with DM, there is an important need to prevent the onset of disease in this high-risk population.

Observational studies have demonstrated that persons with DM and well-controlled risk factors are at lower risk of incident CVD events.2 This is further supported by randomized controlled studies showing that tight control of glucose, blood pressure (BP), cholesterol, and antiplatelet use is associated with a greater than 50% reduction of atherosclerotic cardiovascular disease (ASCVD) risk compared to conventional therapy.3 However, risk factor control rates from national survey data are sobering with just one in four people with DM achieving targets for glycated hemoglobin (HbA1c), BP, and low-density lipoprotein cholesterol (LDL-C).4 It is therefore important to evaluate how well modifiable risk factors are controlled in people with DM. This enables tracking risk factor burden over time and the timely institution of interventions aimed at improving target attainment. The creation of registries provides unique opportunities to systemically address this issue among patients.

In this context, Wenjun et al used data from the Diabetes Collaborative Registry (DCR), a real-world registry of patients from multiple outpatient centers including primary and specialty care.5 Target risk factors included HbA1c <7%, LDL-C <100 mg/dL, BP <140/90 mmHg, and nonsmoking status. The authors first examined prevalence of risk factor targets among the overall study population and stratifying by gender, race/ethnicity, and history of ASCVD. Multivariable logistic regression models were used to study the determinants of target attainment.

Some salient results are worth discussing. First, only 22% of patients with DM met targets for all four risk factors (even less when more stringent BP criteria were used). Second, there were important differences by gender and race with both men and whites achieving adequate risk factor control compared to their counterparts. Such disparities are well known and have been described in the literature.6,7 The present results underscore the importance of risk factor control in everyone, but particularly among diabetic women and blacks who may be disproportionately affected by burden of CVD. Third, control of risk factors among patients with DM and history of ASCVD is suboptimal; it is not much better among primary prevention populations either. Fourth, depression is inversely related with risk factor control. The directionality of this result is difficult to evaluate in this cross-sectional study. Depressed individuals may be less likely to be engaged in their care and adhere to physician's recommendations. Alternatively, people with DM and poor risk factor control may be more likely to report depression. Psychosocial stress including depression is a recognized risk factor for ASCVD,8 and therefore patients with DM and poor risk factor control may benefit from depression screening.

There are some noteworthy limitations that should be pointed out: First, patients included in the study may not be representative of the US population. The study cohort was comprised of patients who were established within a health care system; such individuals may be different from those enrolled in national surveys where some have no follow up with a health care provider. Moreover, a large majority (~70%) of patients were older adults and had history of CVD, and are therefore at higher risk than the average population. Furthermore, 88% of patients were white which may limit generalizability to other race/ethnic groups. Second, data collection in registries is often not uniformed across different sites and measurements may not be performed according to standardized protocols. Third, missing data in registries may not be at random and as the authors point out, patients who were excluded were significantly different from those included in the study. Fourth, it is difficult to account for potential confounders in observational data, which raises the possibility of residual confounding when performing regression analyses.

The present study began with an important question: how well are risk factors controlled among patients with DM? The answer is not very well. The pressing issue now becomes how to translate these findings into clinical practice. Multisociety guidelines provide clear evidence-based recommendations for risk factor control.9-11 There is clearly a gap between standard of care and delivery of care that this study highlights. Important challenges need to be addressed: access to health care may be limited, which can hinder patients' ability to seek medical attention. Patients may also not be able to purchase medications or even engage in healthy lifestyle options such as diet and exercise due to financial constraints. Furthermore, poor health literacy can make it difficult for patients to adhere to treatment recommendations. There is a need for a multidisciplinary approach to treat persons with DM that requires multiple key stakeholders including partners from medical communities and public health sectors. This is important if we are to reverse the alarming trends of rising DM prevalence and CVD rates.


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  9. Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults. Hypertension 2018;71:1269-1324
  10. Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol. Circulation 2018;139:CIR.0000000000000625.
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Keywords: Risk Factors, Hemoglobin A, Cholesterol, LDL, Cross-Sectional Studies, Outpatients, Health Literacy, Ethnic Groups, Depression, Blood Pressure, Factor V, Factor IX, Glucose, Deceleration, Public Health, Standard of Care, Stress, Psychological, Cohort Studies, Diabetes Mellitus, Cholesterol, Cardiovascular Diseases, Diet, Primary Prevention, Registries, Health Personnel, Health Services Accessibility, Metabolic Syndrome

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