Glucose, blood pressure and cholesterol levels and their relationships to clinical outcomes in type 2 diabetes: a retrospective cohort study

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The problem

Uncertainties exist regarding the relationship between biological parameter levels and outcomes in diabetes patients, and a greater understanding of these relationships is required in real world settings. We aimed to describe the shape of observed relationships between risk factor levels and clinically important outcomes in type 2 diabetes after adjusting for multiple confounders.

The approach

We used retrospective longitudinal data on 246,544 adults with type 2 diabetes from 600 practices in the Clinical Practice Research Datalink, 2006-2012. Proportional hazards regression models quantified the risks of mortality, microvascular or macrovascular events associated with four modifiable biological parameters: glycated haemoglobin (HbA1c), blood pressure (systolic/diastolic) and total cholesterol, while controlling for important patient and practice covariates.


U-shaped relationships were observed between all-cause mortality and levels of the four biometric risk factors. Lowest risks were associated with HbA1c 7.25-7.75% (56-61mmol/mol); total cholesterol 3.5-4.5 mmol/l; systolic blood pressure 135-145 mmHg; and diastolic blood pressure 82.5-87.5 mmHg. Coronary and stroke mortality related to the four risk factors in a positive, curvilinear way, with the exception of systolic blood pressure which related to deaths in a U-shape. Macrovascular events showed a positive and curvilinear relationship with HbA1c but U-shaped for total cholesterol and systolic blood pressure. Microvascular related to the four risk factors in a curvilinear way: positive for HbA1c and systolic blood pressure but negative for cholesterol and diastolic blood pressure.


We identified several relationships which support a call for major changes to clinical practice. Most importantly, our results support trial data indicating that normalisation of glucose and blood pressure can lead to poorer outcomes, which makes a strong case for target ranges for these risk factors rather than target levels.


  • Evangelos Kontopantelis, NIHR School for Primary Care Research, Manchester, UK
  • David Springate, NIHR School for Primary Care Research, Manchester, UK
  • David Reeves, NIHR School for Primary Care Research, Manchester, UK
  • Darren Ashcroft, Institute of Human Development, University of Manchester, Manchester, UK
  • Martin Rutter, Manchester Diabetes Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
  • Iain Buchan, NIHR School for Primary Care Research, Manchester, UK
  • Tim Doran