Table 1.
Characteristics of included studies.
| Author and year | Study design | Study location | N | Mean length of diagnosis | Sleep measure | QoL measure | Findings | Quality |
|---|---|---|---|---|---|---|---|---|
| Azharuddin et al. (2020) | Cross sectional | India | 300 | 7.40 ± 6.75 | PSQI | EQ 5D | Poor sleepers had lower HRQoL. Patient FPG and PP were higher among poor sleep quality groups compared to good sleep quality groups. | 20 |
| Bani-issa et al. (2018) | Cross sectional | UAE | 268 | N/A | PSQI | WHOQOL-BREF | Global PSQI score was a strong independent predictor of global HRQoL. Hba1c was not significantly related to HRQoL. | 21 |
| Bironneau et al. (2017) | Cross sectional | France | 126 | 9.0 ± 7.7 | Polysom-nography | SF-36 (French Version) | OSA severity was associated with lower scores across three domains of HRQoL and higher systolic blood pressure. | 19 |
| Chasens et al. (2014) | Secondary analysis | USA | 116 | N/A | PSQI | SF-36v2 | Impaired sleep quality was significantly associated with lower scores on the physical component summary (PCS) and mental component summary (MCS) (p = 0.001) | 20 |
| Daniele et al. (2013) | Observational | Brazil | 200 | 11.7 ± 7.5 | PSQI | SF-36 | There was a significant difference between RLS group and control in five SF-36 domains and hypertension. | 19 |
| Dong et al. (2020) | Cross sectional | China | 944 | 5.6 ± 5.1 | PSQI | DSQL | There was a significant interaction between poor sleep quality and anxiety symptoms; this combined effect significantly reduced QoL | 22 |
| Gabric et al. (2018) | Cross sectional | Croatia | 466 | 13.2 ± 9.4 | ESS, STOP | SF-36 | High-risk OSA group had significantly lower SF-36 scores. The presence of arterial hypertension and asthma was higher in high risk group. | 17 |
| Hashimoto et al. (2020) | Cross sectional | Japan | 342 | 13.54 ± 10.59 | DSM Sleep Disorders | SF- 36v2, EQ-5D | The PCS, MCS, EQ-5D of T2D patients with sleep disorders were lower than those without | 16 |
| Jain et al. (2017) | Cross sectional | India | 50 | 5.6 ± 2.35 | ISI | WHOQOL- BREF | Patients with insomnia scored lower than those without insomnia in all four domains of QOL. These findings were statistically significant for all domains (p < 0.01) | 18 |
| Johnson et al. (2017) | Secondary analysis | Canada | 168 | 13 ± 9 | Actigraphy | EQ-5D-5L, SF- 12. | Lower sleep efficiency was significantly associated with lower scores on both PCS and MCS scores of the SF-12 and longer total sleep time was associated with lower PCS scores | 20 |
| Li et al. (2019) | Secondary analysis | China | 302 | 5.6 ± 5.1 | PSQI | DQoL | Trait anxiety at baseline had a significantly negative prediction of patients’ QOL. Impaired sleep quality negatively influenced patients’ QOL only at baseline | 20 |
| Lou et al. (2015) | Cross sectional | China | 944 | 5.6 ± 5.1 | PSQI | DSQL | Poor sleepers had significantly poorer DSQL. Depressive and anxiety symptoms had a positive relationship with DSQL. | 11 |
| Luyster and Dunbar-Jacob (2011) | Secondary analysis | USA | 300 | 9.4 ± 7.3 | PSQI | SF-36, DQoL | Poor sleepers had poorer QoL scores and more depressive symptoms and comorbidities than good sleepers. | 21 |
| Merlino et al. (2010) | Secondary analysis | Italy | 124 | 12.3 ± 9.86 | IRLS Rating Scale | SF-36 (Italian Version) | RLS+ patients had significantly lower scores across SF-36 domains. The IRLS score showed a significant inverse correlation with vitality (p = 0.02), mental health (p = 0.04), and MCS (p < 0.001) | 20 |
| Modarresnia et al. (2018) | Cross sectional | Iran | 210 | 7.8 ± 4.89 | PSQI | EQ-5D | Those with RLS had a significantly lower QoL score compared to patients without RLS (p = 0.009) | 19 |
| Naranjo et al. (2020) | Cross sectional | Spain | 130 | 11.9 ± 3.14 | (MOS) Sleep Scale | SF-12-v2 | A decrease in mental and physical QoL was associated with sleep disorders. | 20 |
| Narisawa et al. (2017) | Cross sectional | Japan | 622 | N/A | PSQI | SF-8 | Poor sleepers with T2D had lower mental and physical component summary scores (MCS and PCS) than general population. | 21 |
| Seligowski et al. (2013) | Cross sectional | USA | 86 | N/A | PSQI | DQoL | PSQI was significantly related to DQOL. The PSQI had an indirect effect on relationship of anxiety and DQOL and depression and DQOL | 22 |
| Vieira et al. (2008) | Cross sectional | Brazil | 105 | 9.9 ± 7.7 | PSQI | WHOQOL-BREF | Poor sleepers had significantly lower QoL scores than good sleepers. A negative correlation was found between HbA1c and FPG and sleep duration and efficiency. | 16 |
| Yücel et al. (2015) | Descriptive | Turkey | 81 | N/A | PSQI | SF-36 (Turkish Version) | A moderate negative correlation was found between the Global PSQI score and sub-dimensions of SF 36. A highly significant positive correlation was found between PSQI global score and BDI and BAI (p < 0.05) | 11 |
| Zeng et al. (2018) | Cross sectional | China | 798 | N/A | sleep duration and rated sleep quality | DSQL (Chinese version) | The odds ratios of better QoL increased as sleep quality improved. | 15 |
| Zhang et al. (2016) | Secondary analysis | China | 944 | 5.6 ± 5.1 | PSQI | DSQL | Longer sleep duration and good sleep quality were significantly associated with an improvement in QOL. The combined effect of poor sleep quality and depressive symptoms produced reductions in DSQL | 21 |
| Zhao et al. (2016) | Cross sectional | China | 944 | 5.6 ± 5.1 | PSQI | DSQL | Each domain and total DSQL scores of poor sleep quality group were higher than the good sleep quality group. Each domain and total DSQL scores of poor sleep quality and depression group were higher than the normal group (p < 0.01) | 14 |