Modelling within-individual variation in repeated continuous exposures

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Measurements of biological and emotional states are often made repeatedly for the same person. These are used to monitor people with different health problems, or to alert people to health risks. Examples include the measurement of prostate specific antigen (PSA) every 3 months in monitoring of low-risk prostate cancer, and measurement of blood pressure at antenatal appointments to identify risk of pre-eclampsia in pregnant women. Measures are collected at varying intervals, but typically in months (PSA) or weeks (blood pressure during pregnancy) rather than days. Intensively-collected measures are made increasingly possible by new technology, including 'apps' on smartphones such as those which ask about mood at intervals throughout the day. Other examples include blood glucose monitoring in pregnant mothers for detecting and reducing the risk of delivery of a high-birthweight baby, and 24-hour blood pressure monitoring in routine clinical practice.With these repeated measurements, doctors are often interested in the level of the measure (e.g. does a pregnant woman have high blood pressure), or in how fast the measure is rising (e.g. a rising PSA might indicate a worsening of prostate cancer). However, there is growing interest in whether the variability, or fluctuation, of an individual's measures might also be related to health. For example, how much a person's mood goes up and down, and the timing of these fluctuations, may tell us more about their mental health than just whether they tend to have high or low mood on average. Similarly, someone with blood pressure which varies a lot may be at higher risk of future heart attack or stroke than someone with more stable blood pressure. There are many separate features of the way a measure varies for an individual which may predict future disease. One could be called the 'amplitude', and is a measure of how many very high and very low values a person experiences (for example, the difference between the very highest and very lowest blood pressures a person experiences during one day). Another is 'variation', and is a measure of how much the person's measure changes for their overall average. Disentangling these features of variation may be important in some situations. For example, it could be that it is the variation in blood pressure which predicts future heart attacks, but the amplitude of blood pressure during pregnancy which predicts problems for mother and child. There have been many statistical methods developed to relate the level or change in a person's measures to a future disease, but far fewer to look at variation in a person's measurements. In this project, we aim to develop these much-needed statistical methods for modelling fluctuation in measures within an individual, and relating that fluctuation to risk factors and later disease. The developments we will make in this project will allow clinicians to make the best possible use of measures taken repeatedly within people in predicting their future health. We will make sure our new methods are freely available to all scientists in a user-friendly format.We will apply these methods to two studies that have previously been published. The first is blood pressure readings during pregnancy from mothers whose children were part of ALSPAC, and relating these to the health of the child at birth. The second is a study that monitored blood pressure at 15-minute intervals over one day, and relating variation in this to later cardiovascular health.