Cardiovascular ageing


Aneta Stefanovska, Lancaster University


  • Peter V.E. McClintock, Lancaster University

  • P. Jane Owen-Lynch, Lancaster University

  • Peter Clarkson, Royal Lancaster Infirmary

Partners and collaborators

  • Peter Clarkson, Royal Lancaster Infirmary

  • The Wellcome Trust (grant on congestive heart failure and hypertension)

  • BRACCIA, Observatory of End of Life Care, Lancaster University


Aneta Stefanovska


The cardiovascular system, including the capillary system, is known to change during aging. These changes are separate from the pathological effects of disease processes.

Despite advances in the understanding of the cellular and molecular mechanisms of vascular aging, functional studies of changes in blood flow over time, where multiple regulatory mechanisms act in combination, have been lacking.

Functional studies in humans have previously not been possible due to the lack of available methodology for the analysis of the complex interactions involved in blood flow in the capillary bed, which is more complicated than flow in the much larger arteries.

This type of functional study, in the aging population, is important if we are to reach an understanding of the normal changes in microvascular function and the links between these changes and clinical pathology.

Advances in sensor technology have opened up new approaches for non-invasive monitoring of the blood flow. Recordings of, eg the electrocardiogram (ECG), respiration, blood pressure, and blood flow signals can be acquired and stored for later analysis by the application of a variety of sophisticated algorithms which we have generated.

One important outcome has been an appreciation of the oscillatory nature of the blood flow through the capillaries and a detailed understanding of the components that contribute to this dynamic process.

Aims and objectives

The overall aim of this project was to use our non-invasive methods for the detailed study of blood flow to assess the effective age of an individual’s vascular system. This will aid the diagnosis of age-related disease, and allow for assessment of the efficacy of any intervention strategies or clinical treatments.

In order to do this we needed to generate a database of measurements from the young to the healthy old to define the normal age-related changes in these measurements.

The following are the sections of work that needed to be undertaken:

  • Measure the age-related changes in the oscillatory processes that make up the total oscillations in blood flow, particularly two components which are related to the cells lining the capillaries.

  • Establish how these different processes interact and how these interactions change with age.

  • Examine age-related changes in temperature control and oxygen transport in the blood.


Research methods


The measurements prior to the project included healthy adults of all ages (16-82). At the start of the project, we had a dataset of 120 individuals but during the project, we increased this to at least 200 subjects to improve our statistics particularly in the very old range. The subject lies on bed and, once he/she is relaxed and comfortable, several different CVS signals are recorded simultaneously over a period of 30 minutes.

Measuring the cardiovascular signals

The measurements we made included ECG, respiration, blood flow using Laser-Doppler Flowmetry system with iontophoresis, arterial blood pressure, skin temperature and levels of oxygen in the blood. All of these measurements were taken 400 times a second over the whole of the 30-minute measurement period.

Analysis tools

The measurements taken reveal the variable nature of the functioning blood flow processes. Earlier, simpler analysis techniques commonly worked by ignoring any variability, an approach that inadvertently loses potentially valuable information.

One of our major contributions to the field has been the development and application of new analysis methods, based around a branch of physics known as non-linear dynamics to take account of this variability.

These methods were applied to the analysis of the cardiovascular time series in each individual to provide an in-depth profile of the cardiovascular function in that individual. We built all of these profiles into an analysis of how the profile changes through the healthy aging process.

Cultural and environmental impacts

Within the UK dataset we assessed the influence of potential moderating variables such as gender, smoking history, and economic and social support levels. To assess possible national (cultural and/or environmental) variations in the parameters, we will compare our data-set with a large data-set already gathered in Slovenia.


The outcomes were as follows:

  1. Identification of the cardiovascular parameters which are particularly associated with the ageing process.

  2. Provide a background data set against which to compare an individual's “cardiovascular age".

  3. Use the database.

  4. Provide a background data set against which to interrogate any changes in these profiles that relate to changes in healthcare practice or to cultural differences.

  5. Inform future research by providing evidence as to which of the parameters are the most influential in the age-related changes.

  6. Publications in the standard scientific journals, including physics, biological, specialised and general interest science journals.

Policy implications

Key policy implications of the research

Policy and practice implications are based around the potential future uses of the data that will be generated including the following:

  • Potential for the development of clinically useful devices and algorithms that are reliable and simple enough for use by general practitioners and other clinical staff.

  • Healthcare benefits could involve an early diagnosis of any departure from the expected age-profile of cardiovascular oscillations.

  • Ability to evaluate the effects of subsequent treatment as measurements can be easily repeated after the commencement of treatment to see whether, and to what extent, the oscillatory pattern has been moved back towards that of the age/gender-matched healthy population.

  • Highlighting the importance of integrative physiology, treating the patient as a whole, when considering the effects of ageing on the body, an aspect that is often missed in modern clinical practice.

Product development opportunities include:

  • Further development of algorithms to extract temporal and spatio-temporal information about the oscillations and their interactions.

  • Development of a database of all dynamical properties extracted from patient signals to establish a database for reference and clinical profiling.

  • Develop concept of simple, non-invasive, clinical diagnostic system based on the use of oscillatory signals and their dynamical properties.

Key non-academic user groups that were targeted

  • Older people, their relatives and friends.

  • Charities and other organisations representing older people.

  • Clinicians with an interest in the processes of ageing or in the dynamics of the cardiovascular system. These include gerontologists, diabetologists, cardiologists, anæsthetists, vascular physiologists, general practitioners.

  • Health care professionals - Primary Care Trusts, nurses, health and social care staff.

  • Educators and trainers of clinical, health and social care professionals.

  • Manufacturers of LDF equipment.

Assistance needed from the NDA programme in this targeting

  • A high corporate and political profile for the overall NDA programme would facilitate maximisation of the recruitment of subjects and dissemination of the findings.

  • Targeted press releases and promotion of findings to a wide range of non-user groups.

  • Facilitation of contacts with non-academic user groups.