Results of generating the sleep clusters

4.4.2.1 Choosing the best-fit model

In the temporal stability study, the best fitting model included six clusters in data from both Wave 1 and Wave 4. Both of these models were the simplest models, with the lowest BIC, AIC and estimation error as well as the highest R² (after accounting for the number of parameters examined). Similarly, the models with six clusters were chosen as the simplest models with the lowest BIC, AIC and estimation error as well as the highest R² (again, when considering the number of parameters used) in the subsequent ‘correlates of sleep classes’ sub-study (see Appendix, Section 8.3.2, page 316).

It is important to note, however, that when binary coding was used for the seven sleep indicators to generate the clusters (instead of the original categorisation), the temporal stability of the sleep clusters over time was lost. This loss of stability was evident in number of the differences in the patterns of sleep clusters that emerged between data from Wave 1 and 4, despite the fact that the number of clusters remained the same (see Appendix, Section 8.3.4, page 317).

4.4.2.2 Description of sleep patterns and clusters

In the temporal stability study, the best fitting models in both Waves (1 and 4) were models containing six clusters, with a number of similarities in patterns therein. Three clusters displayed essentially identical patterns (clusters 1, 3 and 6), whilst the remaining three clusters differed in the severity of restriction of sleep duration and/or the frequency of sleep latency. Inconsistencies in the contribution that sleep duration made was observed in clusters 2 and 4. In cluster 2, the relevant sleep duration changed from normal to short, while in cluster 4, the duration changed from short to restricted (i.e. one-hour difference). Likewise, in cluster 2, the frequency of sleep latency changed from non-habitual to habitual, while in cluster 5 this changed from non-habitual to no event (i.e. a change of just one adjacent category; Table 4-7 and Table 4-8).

Regardless of the stability of the six clusters between data generated in Wave 1 and Wave 4, there was also some evidence that participants ‘moved’ between sleep clusters from Wave 1 to Wave and 4 (i.e. their membership of sleep cluster changed over time; Table 4-9). Most such movements involved participants who moved from cluster 2 in Wave 1 to cluster 1 in Wave 4 (n=2,244, 58.4%), whilst the least number of participants moved from cluster 3 in Wave 1 to cluster 2 in Wave 4 (n=61, 2%). The most stable cluster was cluster 1, since 61% of participants who were members of this cluster remained in that cluster in both Wave 1 and Wave 2. At the other extreme,

cluster 2 had the least stability, since only 296 (7.7%) of the participants in that cluster remained therein.

In the correlates of sleep classes study, the best fitting model was the model that had six clusters, as it was the simplest model with the lowest BIC (taking account of the number of parameters examined (Table 4-10). These clusters were named on the basis of the patterns observed there in, paying particular attention to the following sleep items: sleep duration, subjective assessment of sleep quality and the most dominant sleep-related event. In this way the six clusters were referred to as short bad sleeper, long moderate sleeper, long good sleeper, disturbed bad sleeper, struggle-to-sleep sleeper and snoring good sleeper. The majority of participants were in cluster 1 (n=19464, 43.1%), and the minority were in cluster 6 (n=1,591, 3.5%). Cluster 1 had the highest prevalence of unfavourable sleep events, whilst cluster 3 had a complete absence of unfavourable sleep events. Clusters 4 and 5 shared similar patterns of unfavourable sleep events, except that cluster 5 had a poor level of sleep quality.

Cluster 6 included participants with habitual (i.e. frequently occurring) snoring and habitual disturbances but with normal quality and duration. Cluster 2 contained participants exhibiting non-habitual sleep disturbances in the absence of other sleep-related events.

Table 4-7 Patterns of sleep clusters based on the latent class analysis for participants from Wave 1 who also participated in Wave 4 (n=19,442). The patterns described are based on the probabilities of the mean event within each cluster.

Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6

Habitual No event Habitual Habitual Non-habitual

Table 4-8 Patterns of sleep clusters based on the latent class analysis for participants from Wave 4 who had previously participated in Wave 1 (n=19,442). The patterns described are based on the probabilities of the mean event within each cluster.

Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6 Duration Normal Short Normal Restricted Short Short

0.723 0.397 0.769 0.411 0.370 0.394

Latency No event Habitual No event Habitual No event Non-habitual

0.473 0.923 0.988 0.942 0.719 0.553

Snoring No event No event No event No event No event No event

0.809 0.673 0.946 0.653 0.721 0.748

Disturbance Non-habitual

Habitual No event Habitual Habitual Non-habitual

0.524 0.992 0.999 0.959 0.997 0.524

Sleepiness No event No event No event No event No event No event

0.919 0.907 0.966 0.755 0.823 0.803

Medication No event No event No event No event No event No event

0.951 0.858 1.000 0.723 0.882 0.887

Quality Good Good Good Bad Bad Bad

1.000 0.600 0.991 0.998 0.604 0.575

Table 4-9 The distribution of participants amongst clusters in Waves 1 and 4 presented as percentages and frequencies.¹

Wave 4

Wave 1

Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6 Total

Cluster 1 (n) 5,137 275 1,805 285 352 309 8,163

(%) 62.93 3.37 22.11 3.49 4.31 3.79 100.00

Cluster 2 (n) 2,244 296 509 305 329 157 3,840

(%) 58.44 7.71 13.26 7.94 8.57 4.09 100.00

Cluster 3 (n) 1,431 61 1,351 64 82 95 3,084

(%) 46.40 1.98 43.81 2.08 2.66 3.08 100.00

Cluster 4 (n) 528 228 111 801 209 177 2,054

(%) 25.71 11.10 5.40 39.00 10.18 8.62 100.00

Cluster 5 (n) 539 78 112 215 320 107 1,371

(%) 39.31 5.69 8.17 15.68 23.34 7.80 100.00

Cluster 6 (n) 416 45 119 115 76 159 930

(%) 44.73 4.84 12.80 12.37 8.17 17.10 100.00

Total (n) 10,295 983 4,007 1,785 1,368 1,004 19,442

(%) 52.95 5.06 20.61 9.18 7.04 5.16 100.00

1 Bold text indicates the percentages of participants who remained within their clusters between Wave 1 and 4.

Table 4-10 Patterns of sleep clusters based on the latent class analysis for participants from Wave 1and/or Wave 4 (n=45, 141). The patterns described are based on the probabilities of the mean event within each cluster.

Cluster1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6 Cluster name Short Bad

sleeper

restricted Normal Normal Short Restricted Normal

0.9998 0.778 0.820 0.349 0.301 0.587

Non-habitual No event Habitual Habitual Habitual

1.000 0.503 0.999 0.530 0.981 0.709