Associations Between Mean HbA1c, HbA1c Variability, and Both Mortality and Macrovascular Complications in Patients with Diabetes Mellitus: A Registry-Based Cohort Study

Abstract

Background

We investigate the association between mean HbA1c, HbA1c variability, and all-cause mortality and diabetes-related macrovascular complications in patients with diabetes.

Methods

We performed a retrospective cohort study using patients present in the Singapore Health Services diabetes registry (SDR) during 2013 to 2014. We assessed mean HbA1c using three models: a baseline mean HbA1c for 2013–14, the mean across the whole follow-up period, and a time-varying yearly updated mean. We assessed HbA1c variability at baseline using the patient’s HbA1c variability score (HVS) for 2013–14. The association between mean HbA1c, HVS, and 6 outcomes were assessed using Cox proportional hazard models.

Results

We included 43,837–53,934 individuals in the analysis; 99.3% had type 2 diabetes mellitus. The data showed a J-shaped distribution in adjusted hazard ratios (HRs) for all-cause mortality, ischemic heart disease, acute myocardial infarction, peripheral arterial disease, and ischemic stroke, with an increased risk of developing these outcomes at HbA1c <6% (42 mmol/mol) and ≥8% (64 mmol/mol). With the addition of HVS, the J-shaped distribution was maintained for the above outcomes, but HRs were greater at HbA1c <6.0% (42 mmol/mol) and reduced at HbA1c ≥8.0% (64 mmol/mol) when compared to models without HVS. The risk for all outcomes increased substantially with increasing glycaemic variability.

Conclusion

Both low (<6.0% [42 mmol/mol]) and high (≥8.0% [64 mmol/mol]) levels of glycaemic control are associated with increased all-cause mortality and diabetes-related macrovascular complications. Glycaemic variability is independently associated with increased risk for these outcomes. Therefore, patients with stable glycaemic level of 6–8% (42–64mmol/mol) are at lowest risk of all-cause mortality and diabetes-related macrovascular complications.

Keywords:

• diabetes mellitus
• diabetes mellitus complications
• glycated haemoglobin
• glycated haemoglobin analysis
• cardiovascular diseases

Abbreviations

DM, diabetes mellitus; SD, standard deviation; CV, coefficient of variation; HVS, HbA1c variability score; SDR, Singhealth Diabetes Registry; EMR, electronic medical records; ICD-9, international classification of disease nine; ICD-10, international classification of disease 10; BMI, body mass index; LDL, low-density lipoprotein; PH, public housing; IHD, ischemic heart disease; PAD, peripheral arterial disease; AMI, acute myocardial infarction; HRs, hazard ratios; DPP4, dipeptidyl-peptidase-4; SGLT-2, sodium-glucose cotransporter-2; GLP-1, glucagon-like peptide-1.

Data Sharing Statement

The datasets generated during and/or analysed during the current study are not publicly available as the data belongs to the SingHealth Regional Health System and was collected as part of its routine activities, and not specifically for research purposes. Our institution has declined to allow this dataset to be placed in a public repository on the basis that there is sufficient information available for re-identification of individuals. Should there be interest in accessing the data to check our analyses, the data can be made available from the corresponding author on reasonable request.

Ethics Approval and Informed Consent

Ethics approval was obtained from the SingHealth Centralised Institutional Review Board prior to initiating this study (SingHealth CIRB reference number: 2022/2133). As all participant data was de-identified, a waiver for participant consent was also obtained.

Author Contributions

All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing interests.

Additional information

Funding

This research is supported by A*STAR, Singapore under its Industry Alignment Pre-Positioning Fund (Grant No. H19/01/a0/023 – Diabetes Clinic of the Future). The funder supported the maintenance of the SingHealth Diabetes Registry for financial year 2022. The funder was not involved in the design of the study; the collection, analysis, and interpretation of data; writing the report; and did not impose any restrictions regarding the publication of the report.