Skip to main content

Risk factors for COVID-19-related mortality in people with type 1 and type 2 diabetes in England: a population-based cohort study

Our take —

In this population-based cohort study of individuals with Type 1 and Type 2 diabetes in England, several clinical and demographic factors were associated with COVID-19 mortality. In addition to established risk factors such as age, sex, race/ethnicity, and socioecnomic status, this study highlights renal impairment, elevated HbA1c, and BMI as factors associated with COVID-19 mortality among diabetics. Complications of diabetes may impact COVID-19 outcomes, but the degree to which they can be modified in the context of the current pandemic to improve outcomes among diabetes remains unknown.

Study design

Prospective Cohort

Study population and setting

This population-based cohort study in England explored associations between COVID-19 mortality and several risk factors among individuals with Type 1 and Type 2 diabetes. The study included 98% of general practices in England using data linked via UK National Health Service numbers from the National Diabetes Audit, Hospital Episode Statistics, and Office for National Statistics. The National Diabetes Audit data were used to quantify deaths from all causes during the first 19 weeks of each year 2017-2020, and also provided age, socioeconomic deprivation, ethnicity, region, and duration of diabetes. The study population used in this analyses were individuals with Type 1 or Type 2 diabetes from the last full installment (Jan 1, 2018, to March, 31 2019) who were alive on February 16, 2020. Timing and source of data collection for considered risk factors were variable: clinical data on HbA1c, systolic blood pressure, total cholesterol, estimated glomerular filtration rate (eGFR), and prescription history (antihypertensives and statins) were taken from the most recent recorded measurement in 2019; BMI and tobacco use were based on most recent measurement between January 1, 2017 and December 31, 2019, and medical history (previous myocardial infarction, heart failure, stroke) were identified between April 1, 2017 and December 31, 2019.

Summary of Main Findings

From February 16 to May 11, 2020, there were 1604 and 36,291 deaths recorded among people with Type 1 (population: 264,390, mean age: 46.6 years) and Type 2 diabetes (population: 2,874,020, mean age: 67.5 years), respectively. Of these, 464/1604 and 10,525/36,291 had COVID-19 included as either the primary underlying cause or a secondary cause of death on the death certificate. Among individuals with Type 1 and Type 2 diabetes, male sex, older age, non-white ethnicity, socioeconomic deprivation, lower eGFR (renal impairment), previous stroke, and previous heart failure were associated with increased risk for death in adjusted survival models. Higher levels of HbA1c were associated with death among individuals with Type 1 and Type 2 diabetes, but the association was more pronounced for individuals with Type 2 diabetes. BMI seemed to have a U-shaped relationship with COVID-19 mortality; individuals with low and high BMI (relative to BMI 25-29 kg/m^2) had increased risk of death. At the peak of the outbreak in April, 2020, about 3500 additional deaths per week occurred in people with diabetes, the majority of which listed COVID-19 on the death certificate.

Study Strengths

This was a large population-based study in England with detailed data on individuals with diabetes. The study population includes almost all people with Type 1 or Type 2 diabetes in England. Death records from previous years were used to estimate excess mortality to COVID-19 in this population.

Limitations

Medical history, clinical data, and behavioral factors were based on data collected prior to 2020 and in some cases as early as January 2017. Missing data for individual risk factors ranged from 0-30%; it seems data were analyzed with “missing data” as a column but this isn’t clear in the multivariable analysis, and it’s possible persons with missing data were excluded from adjusted analyses. Many continuous risk factors were categorized or dichotomized, which may result in incomplete control of confounding. Additionally, we caution against interpreting the effect estimates as causal, given none of the risk factors were evaluated as the main exposure of interest, there were no pre-specified hypotheses, and co-adjusting for the entire set of other variables of interest does not accurately consider confounding or eliminate the possibility of confounding due to unknown or unmeasured variables. Results should be considered as descriptive rather than causal.

Value added

This was a large population-based study seeking to explore several risk factors for COVID-19 mortality among persons with diabetes, and estimate the excess mortality from COVID-19 compared to mortality rates of previous years.

This review was posted on: 22 August 2020