Visitas de personajes ilustres .1 Conde de Pallares

As discussed in Chapter 1 (Section 1.11, page 44), this Doctoral thesis addresses four separate objectives. To achieve each of these objectives, the following studies were performed:

2.1.1 Systematic review and meta-analysis

A systematic review and meta-analysis was undertaken to provide a comprehensive overview of the current extent of knowledge on the subject matter in hand. Within the so-called ‘hierarchy of evidence’, systematic reviews and related meta-analyses are generally considered the highest ‘level’ of evidence attainable (albeit, particularly so when generated from multiple primary experimental studies), and it is for this reason that this was the first analytical chapter to be undertaken for inclusion in the present thesis, providing (as this should) a critical evaluation of the current evidence regarding the possible association between sleep and pregnancy outcomes. This required a systematic search of the published scientific literature to optimise the identification of relevant primary studies (initially, at least), regardless of their study design (be this experimental or observational). Similarly, a careful process of critical appraisal and data extraction was required to evaluate possible reporting gaps and likely limitations or flaws in the data and analytical techniques these primary studies used – limitations and flaws that might then be addressed or mitigated in the design and conduct of the de novo studies conducted for inclusion in the present thesis.

2.1.2 Empirical de novo primary studies

These de novo studies comprised three separate observational analytical studies, each study with its own specific objective (as described in Chapter 1), which together contributed towards addressing the principal aim of the thesis (Figure 2-2).

Each of these studies is briefly described below:

2.1.2.1 UKHLS (UK Household Longitudinal Study) latent class analysis This study was performed to carefully examine the complex nature of sleep and any unmeasured (‘latent’) sleep patterns evident therein, using the seven self-reported sleep characteristics collected during the first and fourth Waves of the UK Household Longitudinal Study (UKHLS). As discussed in the introductory chapter, there is still much to learn and understand about sleep and the biology of sleep, though there is substantial consensus on a number of sleep features or

‘characteristics’ that can be reasonably reliably evaluated using both subjective and objective tools. However, these characteristics seem likely to interact with one another in a complex way to shape an individual’s sleep pattern, yet very little is known about their inter-item associations (be these, for example: cumulative, permissive or multiplicative).Studying each sleep characteristic at a time (as many primary studies do) might therefore introduce a number of biases (not least if some characteristics act as confounders or mediators for others) and cause the loss of substantial valuable information. Instead, treating ‘sleep’ (as a ‘whole’) as a latent structure (i.e. one that cannot not be directly measured but is nonetheless present) might warrant further attention, not least if it were then possible to limit the necessity of estimating and evaluating complicated inter-characteristic associations by combining and considering all available characteristics simultaneously using a single latent variable. This would then result in allocating individuals to latent ‘sleep pattern’ clusters on the basis of their measured sleep characteristics (see Figure 2-1).

Figure 2-1 Sleep as perceived when treating it as a latent structure (to which each component contributes, though in a potentially complex, interactive fashion)

2.1.2.2 Sleep and pregnancy outcomes amongst UKHLS participants The second of the de novo primary observational analytical studies was performed to examine the association between sleep and pregnancy outcomes in pregnant women from the UK population using both the 7 separate sleep characteristics available within the UKHLS and any latent ‘sleep patterns’ identified in the preceding chapter. The source of the data used (i.e. the UKHLS) was chosen to enhance the external validity of these analyses, albeit at the cost of not having access to comprehensive clinical information on UKHLS participants who were pregnant to permit the adjustment of all potential, salient confounding variables considered plausible for such analyses. Nonetheless, despite the relatively modest proportion of UKHLS participants who were pregnant at the time the seven sleep characteristics were measured (i.e. during Wave 1 and Wave 4), because the UKHLS was a large-scale study, there were still several hundred participants available for inclusion in these analyses (as described in more detail, below).

2.1.2.3 Sleep and pregnancy outcomes amongst women at risk of GDM in the Scott/Ciantar study

The final de novo primary observational analytical study was performed to examine the association between sleep and pregnancy outcomes in pregnant women likely to have an enhanced risk of both less favourable sleep and poor pregnancy outcomes; again, using both 7 separate sleep characteristics available within the UKHLS and any ‘latent’ sleep patterns identified in Chapter 4 (see Section 2.1.2.1 page 47). The rationale for using data from the Scott/Ciantar study (which had already commenced the recruitment of participants and the collection of sleep data by the time the present Doctoral thesis began), was the ready availability of clinical data within participants’ medical records – data that might help to address a potential weakness in the analyses undertaken in the preceding chapter (which used a population-based sample, with limited clinical information, drawn from the UKHLS). The Scott/Ciantar study dataset thereby offered: the possibility of developing better analytical models, that had been more comprehensively adjusted using a minimally sufficient adjustment set of (clinical and non-clinical) covariates identified once more using a directed acyclic graph (or ‘DAG’ – as described later in the present Chapter); the better understanding required (from this prospective study) on the temporal sequences of the events and characteristics measured by each of the available variables to permit the confident specification of the DAG (again, see Chapter 2, Section 2.4, page 60 for further details); and a larger number and greater variety of pregnancy outcomes to examine. Meanwhile, the larger

prevalence of poor pregnancy outcomes expected in this dataset (given it comprised women at increased risk of GDM, and therefore at increased risk of poor pregnancy outcomes) was also expected to be somewhat higher that that observed in the population sample drawn from the UKHLS; and this was also viewed as helpful for improving the analytical power of analyses examining the association between sleep and pregnancy outcomes.

Figure 2-2 Graphical illustration of the way in which each of the thesis’ de novo primary observational analytical studies built upon one another to address each of the objectives these set, and thereby achieve the overall aim of the thesis.