Rebecca Hardy

A likelihood approach to meta-analysis with random effects

In a meta-analysis of a set of clinical trials, a crucial but problematic component is providing an estimate and confidence interval for the overall treatment effect theta. Since in the presence of heterogeneity a fixed effect approach yields an artificially narrow confidence interval for theta, the random effects method of DerSimonian and Laird, which incorporates a moment estimator of the between-trial components of variance sigma B2, has been advocated. With the additional distributional assumptions of normality, a confidence interval for theta may be obtained. However, this method does not provide a confidence interval for sigma B2, nor a confidence interval for theta which takes account of the fact that sigma B2 has to be estimated from the data. We show how a likelihood based method can be used to overcome these problems, and use profile likelihoods to construct likelihood based confidence intervals. This approach yields an appropriately widened confidence interval compared with the standard random effects method. Examples of application to a published meta-analysis and a multicentre clinical trial are discussed. It is concluded that likelihood based methods are preferred to the standard method in undertaking random effects meta-analysis when the value of sigma B2 has an important effect on the overall estimated treatment effect.

Diurnal cortisol patterns are associated with physical performance in the Caerphilly Prospective Study

Background Cross-sectional studies have suggested that elevated cortisol is associated with worse physical performance, a surrogate of ageing. We examined the relationship between repeat cortisol measures over 20 years and physical performance in later life. Methods Middle-aged men (45–59 years) were recruited between 1979 and 1983 (Phase 1) from the Caerphilly Prospective Study (CaPS) and re-examined 20 years later at 65–83 years of age (Phase 5). Participants included 750 and 898 subjects with either Phase 1 and/or Phase 5 data on exposure and outcomes. Outcome measures were walking speed and balance time and exposures included morning fasting serum cortisol (Phase 1) and four salivary samples on 2 consecutive days (Phase 5). Results Faster walking speed was associated with higher morning cortisol at Phase 1 [coefficient per standard deviation (SD) increase 0.68, 95% confidence interval (95% CI) 0.09–1.27; Pu2009=u20090.02] though this was attenuated after adjustment for covariates (coefficient per SD increase 0.45; 95% CI –0.16 to 1.07; Pu2009=u20090.15). Higher night-time cortisol at Phase 5 was associated with slower speed (coefficient per SD increase –1.06; 95% CI –1.60 to –0.52; Pu2009<u20090.001) and poorer balance (odds ratio of top tertile vs bottom 2.49; 95% CI 1.63–3.81; Pu2009<u20090.001). Worst performance was seen for men with a poor morning response (Phase 1) and less nocturnal decline (Phase 5). Conclusions Dysregulation of the hypothalamic pituitary adrenal (HPA) axis is associated with worse physical performance in later life. This may reflect a causal effect of the HPA axis on ageing or that ageing itself is associated with reduced HPA reactivity.

A Life Course Perspective on Body Size and Cardio-metabolic Health

The growth of a child and the amount of weight gained across the life course is associated with risk for many chronic degenerative diseases. The life course approach to this area of epidemiological research has burgeoned over the last 25 years, since the initial observation of an inverse relationship between birth weight and coronary heart disease. We review the substantial amount of published research to demonstrate which age-related body size trajectories are indicative of increased risk of cardio-metabolic diseases such as coronary heart disease, stroke, and type two diabetes. Association does not mean causation. The chapter thus also provides an overview of the key sociocultural and other factors responsible for deleterious trajectories, and the biological pathways through which they act, to show how the trajectories are driven by biology but modifiable by the environment. Attention is paid to critical periods and transitions, both biological (e.g., puberty) and behavioural (e.g., marriage), and the influences that these might have on an individual’s trajectory. We highlight the importance of life course trajectories of body size and their associations with trajectories of markers of cardio-metabolic health such as blood pressure and lipids, and the need to integrate biological and social research to move towards a more complete understanding of cardio-metabolic disease processes and, ultimately, how to delay the onset of disease.