On subgroup analyses, investigators found significant effects of study location on PSQIgen (P <.001), PSQIc1 (P = .004), PSQIc2 (P <.001), PSQIc5 (P = .004), PSQIc7 (P <.001), and ISI (P <.001) scores. Then, subgroup effects of type of population were significant on PSQIc1 (P = .02), PSQIc2 (P = .01), PSQIc3 (P <.001), PSQIc7 (P <.001) scores. Lastly, subgroup effects of risk of bias were statistically significant on PSQIgen (P = .003) and PSQIc7 (P = .01) scores. Overall, most of the subcategories with respect to geographic distribution, gender, population, and risk of bias, reported poor sleep quality (ie, PSQIgen > 5) and subthreshold insomnia (ie, ISI >7).
Combination of PTSD and Insomnia Elevates Risk for Major Cardiovascular Events
Even after adjusting for multiple confounding variables including recognized factors associated with cardiovascular diseases, PTSD plus insomnia remained an independent factor of major adverse cardiovascular events.
Government stringency index (GSI), a measure calculated by the Oxford Coronavirus Government Response Tracker, is compounded from several metrics, and included school closures; workplace closures; cancellation of public events; restrictions on public gatherings; closures of public transport; stay-at-home requirements; public information campaigns; restrictions on internal movements; and international travel controls. A series of meta-regression analyses was conducted to verify whether the meta-analytic outcomes were predicted by continuous variables such as female percentage, days, GSI, cases, and deaths.
The findings showed that PSQIgen was significantly predicted by days with a negative slope (coefficient, –0.002; P <.001), by a female percentage with a positive slope (coefficient, 1.57; P <.001), and by GSI with a negative slope (coefficient, 0.94; P = .048). Although both genders reported clinically significant scores in PSQIgen, subgroup analyses showed a mean global PSQI score of 6.83 (95% CI, 6.56-7.10) among females and 5.57 (95% CI, 5.22-5.92) among males, which was in line with previous studies.
"The inverse association between PSQIgen and less stringent measures might have several possible explanations,” Christian et al wrote. "First, during a period of more severe restrictions, people might have had the possibility to adapt their sleep-wake schedule to their chronotype rather than to social or working requirements." Additionally, they noted that the easing of restrictions allowed people to go out and start over a relatively ordinary routine after prolonged confinement and forced individuals to face the unpleasant emotions related to the risk of infection, possibly causing sleep impairment in turn.
REFERENCE
1. Scarpelli S, Zagaria A, Ratti PL, et al. Subjective sleep alterations in health subjects worldwide during COVID-19 pandemic: a systematic review, meta-analysis, and meta-regression. Sleep Med. 2022;100:89-100. doi:10.1016/j.sleep.2022.07.012