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An umbrella review of systematic reviews and meta-analyses of observational investigations of obstructive sleep apnea and health outcomes

Abstract

Purpose

The previous analysis of systematic reviews and meta-analyses have illustrated that obstructive sleep apnea (OSA) is correlated with multiple health outcomes. In the present research, our main aim was to execute an umbrella review to assess the available evidence for the associations between OSA and health outcomes.

Methods

Herein, a meta-analysis of previous observational investigations that have reported associations between OSA and health outcomes in all human populations and settings was performed. We used these studies to execute an umbrella review of available meta-analyses and systematic reviews.

Results

Sixty-six articles comprising 136 unique outcomes were enrolled in this analysis. Of the 136 unique outcomes, 111 unique outcomes had significant associations (p < 0.05). Only 7 outcomes (coronary revascularization after PCI, postoperative respiratory failure, steatosis, alaninetrans aminase (ALT) elevation, metabolic syndrome (MS), psoriasis, and Parkinson’s disease) had a high quality of evidence. Twenty-four outcomes had a moderate quality of evidence, and the remaining 80 outcomes had a weak quality of evidence. Sixty-nine outcomes exhibited significant heterogeneity. Twenty-five outcomes exhibited publication bias. Sixty-three (95%) studies showed critically low methodological quality.

Conclusion

Among the 66 meta-analyses exploring 136 unique outcomes, only 7 statistically significant outcomes were rated as high quality of evidence. OSA may correlate with an increased risk of coronary revascularization after PCI, postoperative respiratory failure, steatosis, ALT elevation, MS, psoriasis, and Parkinson’s disease.

Introduction

Obstructive sleep apnea (OSA) is a prevalent but treatable chronic sleep disorder that is determined through episodes of sleep apnea and hypopnea during sleep and results in recurrent episodes of hypercapnia and hypoxemia [1,2,3]. OSA has a prevalence of between 5 and 20% depending on the population surveyed and the definition utilized [4, 5]. The prevalence is also increasing due to an increase in body mass index which is one of its major predisposing factors. Apart from causing uncomfortable symptoms such as headache [6] and attention deficit [7], earlier studies indicated that OSA also contributed to the advancement of several diseases including hypertension [8], cardiovascular disease [9, 10], and diabetes [11]. Recent studies have drawn consistent conclusions [12,13,14]. Recently, a great number of researches have explored the correlation between OSA and other diseases. Multiple investigations and meta-analyses have illustrated that OSA poses a threat to human health because it increases the risk of various diseases, including cancers [15,16,17], depression [18], laryngopharyngeal reflux disease [19], metabolic disease [20], Parkinson’s disease [21], and chronickidney disease (CKD) [22].

These studies suggest a possible causal relationship between OSA and different health outcomes, indicating that OSA has a bad influence on human health. However, several factors are known to decrease the validity and strength of reported evidence including publication bias, protocol design flaws, or inconsistencies of studies. Currently, there have been no systematic reviews that have accurately summarized and critically appraised existing studies. In the current study, an umbrella review was executed to comprehensively evaluate published systematic reviews and meta-analyses of observational researches that reported associations between OSA and health information. This work can provide important guidance in the diagnosis and treatment of OSA.

Materials and methods

The protocol of the research was registered with PROSPERO (registration number: CRD42020220015) before the umbrella review began. A systematic exploration of the literature search was accomplished in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols [23].

Literature search

From initiation until November 23, 2020, literature searches were performed using online databases such as Embase, PubMed, the Cochrane Database of Systematic Reviews, and the Web of Science. Literature searches were independently conducted by two researchers (CZ and LG). The search terms applied were (“obstructive sleep apnea” OR “obstructive sleep apnea–hypopnea” OR “OSA” OR “OSAH”) AND (Meta-Analysis[ptyp] OR metaanaly*[tiab] OR meta-analy*[tiab] OR Systematic review [ptyp] OR “systematic review”[tiab]). The references were manually screened to identify eligible articles to be included in the study. The article titles, abstracts, and the complete manuscripts of the identified paper were then further assessed. A discussion was used to resolve potential discrepancies; ST acted as an arbiter to deal with discrepancies that could not be resolved by discussion among the investigators.

Eligibility criteria and exclusion criteria

The eligibility of articles was based on a systematic search by the authors to identify the most pertinent studies. Only systematic reviews or meta-analyses on the basis of the epidemiological studies performed in humans were considered in the analysis. Diagnostic trials and meta-analyses of interventional trials were not performed as part of the current study. Furthermore, the abstracts of the conference on review questions were not included in the final analysis. The final systematic reviews and meta-analyses that were analyzed had to include the data of pooled summary effects(i.e., relative risks (RRs); odds ratios (ORs); hazard ratios (HRs); mean difference (MD); weighted mean difference (WMD); standard mean difference (SMD); and their 95% confidence intervals (CIs)), number of included researches, number of participants and cases, heterogeneity, and publication bias. Whenever more than one meta-analysis was executed using on the basis of the same outcome, the agreement with the main conclusions reported in the study were verified. When the reported conclusions were conflicting, the meta-analysis with the greatest number of investigations was considered.

Data extraction

For investigations to be eligible for inclusion in the meta-analysis, two researchers (WC and YL) independently extracted data from the articles. This included the first author, the number of included investigations, the year of publication, the study design, the whole numbers of cases, and participants. The reported relative summary risk evaluates (ORs, RRs, HRs, SMD, WMD, or MD) and the corresponding 95% CIs were extracted, for each eligible systematic review and meta-analysis. The values of p for the total pooled effects, Cochran Q measurement, Egger’s measurement, and I2 were extracted. Discrepancies in the analyses were resolved by discussion among the investigators.

Assessment of methodological quality

Two investigators (WC and YL) independently assessed the quality of the methods reported in the studies. This was performed using a 16-criteria checklist included in AMSTAR 2 [24]. AMSTAR 2 is a fundamental revision of the original instrument of AMSTAR which was devised to evaluate systematic reviews that included randomized controlled experiments. The AMSTAR 2 score is categorized as high in studies that have no or one noncritical weakness, moderate in surveys with more than one noncritical weakness, low when the study has only one serious flaw without or with noncritical weaknesses, and seriously low when a study has more than one serious flaw without or with nonserious weaknesses. Discrepancies between the AMSTARS 2 scores for the articles were resolved by discussion between the investigators.

Assessment of the evidence quality

Two investigators (WC and YL) independently evaluated the quality of the evidence conforming to the parameters that have previously been applied in various fields [25,26,27,28]. Discrepancies were resolved by discussion. First, p value for the estimate < 0.001 [29, 30] and more than 1000 cases of the disease, which indicated fewer false-positive results. Second, I2 < 50% and p value for Cochran Q test > 0.10, which indicated consistency of results. Third, p value for Egger’s test > 0.10, which exhibited no evidence of small-study impacts. When all of the above criteria were satisfied, the strength of the epidemiologic evidence was rated as high. When 1 of the criterion was not satisfied and the p value for the estimate was < 0.001, the strength of the epidemiologic evidence was rated as moderate. Then, the rest was defined as weak (p < 0.05). The value of p for the evaluation can be assessed from the 95% confidence interval of the pooled impact estimate utilizing an established method [31] if it was not directly reported in the article.

Data analysis

From each of the published studies, the outcome data of the available meta-analyses was extracted along with the estimated summary effect at the corresponding 95% CI. The total impacts of the pooled meta-analysis were considered significant when the p-value was < 0.05. Heterogeneity was appraised by the I2 test and Q test, publication bias was estimated by utilizing Egger’s test, and both were considered significant at p < 0.1. Studies that did not have the heterogeneity or publication bias results were reanalyzed if raw data were available.

Results

Characteristics of the meta-analyses

The outcomes of the systematic investigation and the selection of eligible investigations are summarized in Fig. 1. Overall, 1972 articles were searched from which 66 meta-analyses of observational investigations were identified that had 136 unique outcomes [21, 22, 32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95]. The 66 eligible non-overlapping meta-analyses had publication dates ranging from 2009 to 2020 and are summarized in Table 1. The median number of primary investigations per evidence synthesis was 7 (range 2–64). Furthermore, 1 meta-analysis [54] lacked the data of both participants and cases, and 2 meta-analyses [52, 95] lacked the data of cases. Among the meta-analyses identified in this study, the median number of cases was 900 (88–3,117,496) and the median number of participants was 2962 (170–56,746,100). An extensive range of data were reported such as cardiovascular disorders (n = 31), cerebral and cerebrovascular disease (n = 7), mortality (n = 5), postoperative complications (n = 20), pregnancy-related disorders (n = 13), ophthalmic disorders (n = 8), digestive disorders (n = 13), endocrine and metabolic system disorders(n = 17), urological disorders (n = 7), and other data (n = 15) (Fig. 2).

Fig. 1
figure 1

Flowchart of the selection procedure

Table 1 Associations between OSA and multiple heath outcomes
Fig. 2
figure 2

Map of achievements related to OSA

Summary effect size

A brief explanation of the effects of the included meta-analysis is given in Table 1. Overall, 111 (82%) of the 136 data reported significant summary outcomes (p < 0.05). These associations relate to the outcomes of the following different systems: 29 meta-analyses in cardiovascular disorders, 5 in cerebral and cerebrovascular disease, 4 in mortality, 14 in postoperative complications, 8 in pregnancy-related disorders, 7 in ophthalmic disorders, 11 in digestive disorders, 14 in endocrine and metabolic system, 7 in urological disorders, and 12 in other outcomes. Therefore, it can be concluded that OSA can enhance the risk of disease and have adverse effects on human health.

Heterogeneity and publication bias

For heterogeneity, 5 results in 5 articles were reanalyzed owing to that they did not exhibit the outcomes of heterogeneity [22, 36, 46, 59, 64]. Among the 136 outcomes including the reanalyzed articles, 47 outcomes showed no heterogeneity between researches (p ≥ 0.1 of Q test), whereas 69 indicated significant heterogeneity (p < 0.1 of Q test). However, there were still 20 results in 2 articles that could not be reanalyzed due to the lack of raw data [52, 95], so we could not evaluate their heterogeneity. For publication bias, 76 outcomes demonstrated no statistical evidence on publication bias (p ≥ 0.1 of Egger’s test), whereas 25 outcomes presented publication bias (p < 0.1 of Egger’s test). There were still 35 results in 9 articles that could not be reanalyzed due to the lack of raw data [45, 52, 54, 55, 87, 92,93,94,95], so we could not evaluate their publication bias.

AMSTAR 2 and summary of evidence

The results for the evaluation of the methodological qualities of the 66 included articles are shown in Table 2. Only 3 (5%) studies were determined to be low; the remaining 63 (95%) studies were determined to be critically low (Fig. 3). Based on the AMSTAR 2 criteria, none of the investigations were graded as moderate or high quality.

Table 2 Assessments of AMSTAR 2 scores
Fig. 3
figure 3

Map of results of AMSTAR 2

The outcomes of the evidence measurement are shown in Table 3. When a study did not present the result of heterogeneity and publication bias, the corresponding criteria were considered to be not satisfied. Among the 111 statistically significant outcomes, 7 (6%) showed high epidemiologic evidence, 24 (22%) showed moderate epidemiologic evidence, and the remaining 80 (72%) were rated as weak (Fig. 4).

Table 3 Detail of results for evidence quality assessing
Fig. 4
figure 4

Map of results of evidence assessment

Discussion

In the current umbrella review, we identified 66 meta-analyses of observational studies and evaluated the current evidence supporting an association between OSA and various health outcomes. Also, we provide an extensive overview of the available evidence and critically evaluate the methodological quality of the meta-analyses and the quality of evidence for all the reported associations. OSA increased the risk of 111 health outcomes, including cardiovascular disorders, cerebral and cerebrovascular disease, mortality, postoperative complications, pregnancy-related disorders, ophthalmic disorders, digestive disorders, endocrine and metabolic system disorders, urological disorders, and other outcomes. The evidence quality was graded as high only for coronary revascularization after PCI, postoperative respiratory failure, steatosis, ALT elevation, MS, psoriasis, and Parkinson’s disease. The evidence quality was either moderate or low for the other associations. Furthermore, this umbrella review showed there were no considerable associations between OSA and 25 health outcomes.

Among the 111 outcomes, 54 outcomes had serious heterogeneity between studies. These possible confounding parameters (e.g., sex, body mass index, age, method of assessing OSA, OSA severity, smoking, alcohol drinking, the region of study, and follow-up period) may be the cause of heterogeneity. Substantial heterogeneity led to unreliable results. Of the 111 health outcomes, 23 outcomes possessed a remarkable publication bias, demonstrating that some negative achievements were not presented. Several reasons were leading to publication bias. First, when people start a study, they tend to assume that a positive result may ensure their work complies with the hypothesis during publication. Second, positive results have a higher probability of being published compared to negative results. Third, the study population is only a small fraction of the actual population with the disease. According to AMSTAR 2 criteria, 95% of the studies included in this umbrella analysis had “critically low” methodological quality. The critical flaws considered the absence of a registered protocol, the absence of the risk of bias in the considered investigations, and the absence of consideration of the risk of bias in the included investigations when interpreting or discussing the achieved outcomes of each study. Moreover, none of the meta-analyses in this study explained details of the funding source that had supported the work. The majority of the evaluated meta-analyses had considerable heterogeneity and small-study impacts; these were the main reasons for the evidence rating downgrade.

An umbrella review is a more beneficial method compared to a normal systematic review or meta-analysis due to it representing an overall illustration of achievements for phenomena or special questions [96]. To our knowledge, we are the first to use this method to present a comprehensive critical literature appraisal on published associations between OSA and diverse health information. Also, our two authors systematically searched four scientific databases using a strong search strategy with clearly defined eligibility criteria and data extraction parameters. The quality of included systematic reviews was also evaluated through AMSTAR 2. This is a benchmark methodological quality measurement that is utilized to assessing the quality of the methods utilized for meta-analyses. Furthermore, we graded the epidemiologic evidence conforming to established, prespecified criteria. Its criteria included an assessment of heterogeneity, publication bias, and precision of the estimate, which is more objective than the GRADE system criteria.

There are some limitations in our umbrella review. First, in this analysis, we explained associations evaluated through the meta-analyses of observational investigations. In doing so, we may have missed other health outcomes that have not yet been investigated by meta-analyses. Second, this umbrella analysis included systematic reviews and meta-analyses that were only published in English. The potential missing information in other languages could influence the assessment outcomes. Third, the majority of the meta-analyses had heterogeneity; observational researches are susceptible to uncertainty and confounding bias.

Conclusions

The associations between OSA and an extensive range of health information have been broadly reported in many meta-analyses. Based on our umbrella review, 66 meta-analyses explored 136 unique outcomes, only 7 outcomes showed a high level of epidemiologic evidence with statistical significance. OSA could be associated with the enhanced risk of coronary revascularization after PCI, postoperative respiratory failure, steatosis, ALT elevation, MS, psoriasis, and Parkinson’s disease. Overall, OSA is harmful to human health but will need further exploration on this topic with high-quality prospective studies.

Data availability

The data used to support the findings of this study are included within the article. The primary data used to support the findings of this study are available from the corresponding author upon request.

References

  1. 1.

    Abboud F, Kumar R (2014) Obstructive sleep apnea and insight into mechanisms of sympathetic overactivity. J Clin Investig 124(4):1454–1457

    CAS  PubMed  Article  Google Scholar 

  2. 2.

    Semelka M, Wilson J, Floyd R (2016) Diagnosis and treatment of obstructive sleep apnea in adults. Am Fam Physician 94(5):355–360

    PubMed  Google Scholar 

  3. 3.

    Jordan AS, McSharry DG, Malhotra A (2014) Adult obstructive sleep apnoea. Lancet (London, England) 383(9918):736–747

    Article  Google Scholar 

  4. 4.

    Punjabi NM (2008) The epidemiology of adult obstructive sleep apnea. Proc Am Thorac Soc 5(2):136–143

    PubMed  PubMed Central  Article  Google Scholar 

  5. 5.

    Durán J, Esnaola S, Rubio R, Iztueta A (2001) Obstructive sleep apnea-hypopnea and related clinical features in a population-based sample of subjects aged 30 to 70 yr. Am J Respir Crit Care Med 163(3 Pt 1):685–689

    PubMed  Article  Google Scholar 

  6. 6.

    Russell MB, Kristiansen HA, Kværner KJ (2014) Headache in sleep apnea syndrome: epidemiology and pathophysiology. Cephalalgia 34(10):752–755

    PubMed  Article  Google Scholar 

  7. 7.

    Youssef NA, Ege M, Angly SS, Strauss JL, Marx CE (2011) Is obstructive sleep apnea associated with ADHD? Ann Clin Psychiatry 23(3):213–224

    PubMed  Google Scholar 

  8. 8.

    Young T, Peppard P, Palta M, Hla KM, Finn L, Morgan B, Skatrud J (1997) Population-based study of sleep-disordered breathing as a risk factor for hypertension. Arch Intern Med 157(15):1746–1752

    CAS  PubMed  Article  Google Scholar 

  9. 9.

    Yaggi HK, Concato J, Kernan WN, Lichtman JH, Brass LM, Mohsenin V (2005) Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med 353(19):2034–2041

    CAS  PubMed  Article  Google Scholar 

  10. 10.

    Bradley TD, Floras JS (2009) Obstructive sleep apnoea and its cardiovascular consequences. Lancet (London, England) 373(9657):82–93

    Article  Google Scholar 

  11. 11.

    Marshall NS, Wong KK, Phillips CL, Liu PY, Knuiman MW, Grunstein RR (2009) Is sleep apnea an independent risk factor for prevalent and incident diabetes in the Busselton Health Study? J Clin Sleep Med 5(1):15–20

    PubMed  PubMed Central  Article  Google Scholar 

  12. 12.

    Dredla BK, Castillo PR (2019) Cardiovascular consequences of obstructive sleep apnea. Curr Cardiol Rep 21(11):137

    PubMed  Article  Google Scholar 

  13. 13.

    Muraki I, Wada H, Tanigawa T (2018) Sleep apnea and type 2 diabetes. J Diabetes Investig 9(5):991–997

    PubMed  PubMed Central  Article  Google Scholar 

  14. 14.

    Strausz S, Havulinna AS, Tuomi T, Bachour A, Groop L, Mäkitie A, Koskinen S, Salomaa V, Palotie A, Ripatti S et al (2018) Obstructive sleep apnoea and the risk for coronary heart disease and type 2 diabetes: a longitudinal population-based study in Finland. BMJ Open 8(10):e022752

    PubMed  PubMed Central  Article  Google Scholar 

  15. 15.

    Choi JH, Lee JY, Han KD, Lim YC, Cho JH (2019) Association between obstructive sleep apnoea and breast cancer: the Korean National Health Insurance Service Data 2007–2014. Sci Rep 9(1):19044

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  16. 16.

    Seijo LM, Pérez-Warnisher MT, Giraldo-Cadavid LF, Oliveros H, Cabezas E, Troncoso MF, Gómez T, Melchor R, Pinillos EJ, El Hachem A et al (2019) Obstructive sleep apnea and nocturnal hypoxemia are associated with an increased risk of lung cancer. Sleep Med 63:41–45

    PubMed  Article  Google Scholar 

  17. 17.

    Brenner R, Kivity S, Peker M, Reinhorn D, Keinan-Boker L, Silverman B, Liphsitz I, Kolitz T, Levy C, Shlomi D et al (2019) Increased risk for cancer in young patients with severe obstructive sleep apnea. Respiration 97(1):15–23

  18. 18.

    Hobzova M, Prasko J, Vanek J, Ociskova M, Genzor S, Holubova M, Grambal A, Latalova K (2017) Depression and obstructive sleep apnea. Neuro Endocrinol Lett 38(5):343–352

    CAS  PubMed  Google Scholar 

  19. 19

    Gouveia CJ, Yalamanchili A, Ghadersohi S, Price CPE, Bove M, Attarian HP, Tan BK (2019) Are chronic cough and laryngopharyngeal reflux more common in obstructive sleep apnea patients? Laryngoscope 129(5):1244–1249

    PubMed  Article  Google Scholar 

  20. 20.

    Li M, Li X, Lu Y (2018) Obstructive sleep apnea syndrome and metabolic diseases. Endocrinology 159(7):2670–2675

    CAS  PubMed  Article  Google Scholar 

  21. 21.

    Sun AP, Liu N, Zhang YS, Zhao HY, Liu XL (2020) The relationship between obstructive sleep apnea and Parkinson’s disease: a systematic review and meta-analysis. Neurol Sci 41(5):1153–1162

  22. 22.

    Hwu DW, Lin KD, Lin KC, Lee YJ, Chang YH (2017) The association of obstructive sleep apnea and renal outcomes-a systematic review and meta-analysis. BMC Nephrol 18(1):313

    PubMed  PubMed Central  Article  Google Scholar 

  23. 23.

    Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA (2015) Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systems Control Found Appl 4(1):1

    Google Scholar 

  24. 24.

    Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, Moher D, Tugwell P, Welch V, Kristjansson E et al (2017) AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ (Clinical research ed) 358:j4008

    Article  Google Scholar 

  25. 25.

    Theodoratou E, Tzoulaki I, Zgaga L, Ioannidis JP (2014) Vitamin D and multiple health outcomes: umbrella review of systematic reviews and meta-analyses of observational studies and randomised trials. BMJ (Clinical research ed) 348:g2035

    Google Scholar 

  26. 26.

    Tsilidis KK, Kasimis JC, Lopez DS, Ntzani EE, Ioannidis JP (2015) Type 2 diabetes and cancer: umbrella review of meta-analyses of observational studies. BMJ (Clinical research ed) 350:g7607

    Google Scholar 

  27. 27.

    Belbasis L, Bellou V, Evangelou E, Ioannidis JP, Tzoulaki I (2015) Environmental risk factors and multiple sclerosis: an umbrella review of systematic reviews and meta-analyses. Lancet Neurol 14(3):263–273

    PubMed  Article  Google Scholar 

  28. 28.

    Piovani D, Danese S, Peyrin-Biroulet L, Nikolopoulos GK, Lytras T, Bonovas S (2019) Environmental risk factors for inflammatory bowel diseases: an umbrella review of meta-analyses. Gastroenterology 157(3):647-659.e644

    PubMed  Article  Google Scholar 

  29. 29.

    Johnson VE (2013) Revised standards for statistical evidence. Proc Natl Acad Sci USA 110(48):19313–19317

    CAS  PubMed  Article  Google Scholar 

  30. 30.

    Ioannidis JP, Tarone R, McLaughlin JK (2011) The false-positive to false-negative ratio in epidemiologic studies. Epidemiology 22(4):450–456

    PubMed  Article  Google Scholar 

  31. 31.

    Altman DG, Bland JM (2011) How to obtain the confidence interval from a P value. BMJ (Clinical research ed) 343:d2090

    Article  Google Scholar 

  32. 32.

    Zhou X, Liu F, Zhang W, Wang G, Guo D, Fu W, Wang L (2018) Obstructive sleep apnea and risk of aortic dissection: a meta-analysis of observational studies. Vascular 26(5):515–523

    PubMed  Article  PubMed Central  Google Scholar 

  33. 33.

    Wang X, Ouyang Y, Wang Z, Zhao G, Liu L, Bi Y (2013) Obstructive sleep apnea and risk of cardiovascular disease and all-cause mortality: a meta-analysis of prospective cohort studies. Int J Cardiol 169(3):207–214

    PubMed  Article  PubMed Central  Google Scholar 

  34. 34.

    Li M, Hou WS, Zhang XW, Tang ZY (2014) Obstructive sleep apnea and risk of stroke: a meta-analysis of prospective studies. Int J Cardiol 172(2):466–469

    PubMed  Article  PubMed Central  Google Scholar 

  35. 35.

    Xie W, Zheng F, Song X (2014) Obstructive sleep apnea and serious adverse outcomes in patients with cardiovascular or cerebrovascular disease: a PRISMA-compliant systematic review and meta-analysis. Medicine 93(29):e336

    PubMed  PubMed Central  Article  Google Scholar 

  36. 36.

    Xie C, Zhu R, Tian Y, Wang K (2017) Association of obstructive sleep apnoea with the risk of vascular outcomes and all-cause mortality: a meta-analysis. BMJ Open 7(12):e013983

    PubMed  PubMed Central  Article  Google Scholar 

  37. 37.

    Youssef I, Kamran H, Yacoub M, Patel N, Goulbourne C, Kumar S, Kane J, Hoffner H, Salifu M, McFarlane SI (2018) Obstructive sleep apnea as a risk factor for atrial fibrillation: a meta-analysis. Journal of Sleep Disorders & Therapy 7(1):282

    Article  Google Scholar 

  38. 38.

    Hou H, Zhao Y, Yu W, Dong H, Xue X, Ding J, Xing W, Wang W (2018) Association of obstructive sleep apnea with hypertension: a systematic review and meta-analysis. J Glob Health 8(1):010405

    PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    Ng CY, Liu T, Shehata M, Stevens S, Chugh SS, Wang X (2011) Meta-analysis of obstructive sleep apnea as predictor of atrial fibrillation recurrence after catheter ablation. Am J Cardiol 108(1):47–51

    PubMed  Article  Google Scholar 

  40. 40.

    Wang X, Fan JY, Zhang Y, Nie SP, Wei YX (2018) Association of obstructive sleep apnea with cardiovascular outcomes after percutaneous coronary intervention: a systematic review and meta-analysis. Medicine 97(17):e0621

    PubMed  PubMed Central  Article  Google Scholar 

  41. 41.

    Qu H, Guo M, Zhang Y, Shi DZ (2018) Obstructive sleep apnea increases the risk of cardiac events after percutaneous coronary intervention: a meta-analysis of prospective cohort studies. Sleep Breath 22(1):33–40

    PubMed  Article  Google Scholar 

  42. 42.

    Cuspidi C, Tadic M, Sala C, Gherbesi E, Grassi G, Mancia G (2020) Obstructive sleep apnoea syndrome and left ventricular hypertrophy: a meta-analysis of echocardiographic studies. J Hypertens 38(9):1640–1649

    CAS  PubMed  Article  Google Scholar 

  43. 43.

    Ho BL, Tseng PT, Lai CL, Wu MN, Tsai MJ, Hsieh CF, Chen TY, Hsu CY (2018) Obstructive sleep apnea and cerebral white matter change: a systematic review and meta-analysis. J Neurol 265(7):1643–1653

    PubMed  Article  Google Scholar 

  44. 44.

    Wu Z, Chen F, Yu F, Wang Y, Guo Z (2018) A meta-analysis of obstructive sleep apnea in patients with cerebrovascular disease. Sleep Breath 22(3):729–742

    PubMed  Article  Google Scholar 

  45. 45.

    Huang Y, Yang C, Yuan R, Liu M, Hao Z (2020) Association of obstructive sleep apnea and cerebral small vessel disease: a systematic review and meta-analysis. Sleep 43(4):zsz264

    PubMed  Article  Google Scholar 

  46. 46.

    Chokesuwattanaskul A, Lertjitbanjong P, Thongprayoon C, Bathini T, Sharma K, Mao MA, Cheungpasitporn W, Chokesuwattanaskul R (2020) Impact of obstructive sleep apnea on silent cerebral small vessel disease: a systematic review and meta-analysis. Sleep Med 68:80–88

    PubMed  Article  Google Scholar 

  47. 47.

    Pan L, Xie X, Liu D, Ren D, Guo Y (2016) Obstructive sleep apnoea and risks of all-cause mortality: preliminary evidence from prospective cohort studies. Sleep Breath 20(1):345–353

    PubMed  Article  Google Scholar 

  48. 48.

    Ge X, Han F, Huang Y, Zhang Y, Yang T, Bai C, Guo X (2013) Is obstructive sleep apnea associated with cardiovascular and all-cause mortality? PLoS One 8(7):e69432

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. 49.

    Zhang XB, Peng LH, Lyu Z, Jiang XT, Du YP (2017) Obstructive sleep apnoea and the incidence and mortality of cancer: a meta-analysis. Eur J Cancer Care 26(2)

  50. 50.

    Hai F, Porhomayon J, Vermont L, Frydrych L, Jaoude P, El-Solh AA (2014) Postoperative complications in patients with obstructive sleep apnea: a meta-analysis. J Clin Anesth 26(8):591–600

    PubMed  Article  Google Scholar 

  51. 51.

    Kaw R, Chung F, Pasupuleti V, Mehta J, Gay PC, Hernandez AV (2012) Meta-analysis of the association between obstructive sleep apnoea and postoperative outcome. Br J Anaesth 109(6):897–906

    CAS  PubMed  Article  Google Scholar 

  52. 52.

    Liu T, Zhan Y, Wang Y, Li Q, Mao H (2021) Obstructive sleep apnea syndrome and risk of renal impairment: a systematic review and meta-analysis with trial sequential analysis. Sleep Breath 25(1):17–27

  53. 53.

    Zhang X, Zhang R, Cheng L, Wang Y, Ding X, Fu J, Dang J, Moore J, Li R (2020) The effect of sleep impairment on gestational diabetes mellitus: a systematic review and meta-analysis of cohort studies. Sleep Med 74:267–277

    PubMed  Article  Google Scholar 

  54. 54

    Liu L, Su G, Wang S, Zhu B (2019) The prevalence of obstructive sleep apnea and its association with pregnancy-related health outcomes: a systematic review and meta-analysis. Sleep Breath 23(2):399–412

    PubMed  Article  Google Scholar 

  55. 55.

    Li L, Zhao K, Hua J, Li S (2018) Association between sleep-disordered breathing during pregnancy and maternal and fetal outcomes: an updated systematic review and meta-analysis. Front Neurol 9:91

    PubMed  PubMed Central  Article  Google Scholar 

  56. 56.

    Xu T, Feng Y, Peng H, Guo D, Li T (2014) Obstructive sleep apnea and the risk of perinatal outcomes: a meta-analysis of cohort studies. Sci Rep 4:6982

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  57. 57.

    Pellegrini M, Bernabei F, Friehmann A, Giannaccare G (2020) Obstructive sleep apnea and keratoconus: a systematic review and meta-analysis. Optom Vis Sci 97(1):9–14

  58. 58.

    Wu X, Liu H (2015) Obstructive sleep apnea/hypopnea syndrome increases glaucoma risk: evidence from a meta-analysis. Int J Clin Exp Med 8(1):297–303

    PubMed  PubMed Central  Google Scholar 

  59. 59

    Huon LK, Liu SY, Camacho M, Guilleminault C (2016) The association between ophthalmologic diseases and obstructive sleep apnea: a systematic review and meta-analysis. Sleep Breath 20(4):1145–1154

    PubMed  Article  Google Scholar 

  60. 60.

    Wu Y, Zhou LM, Lou H, Cheng JW, Wei RL (2016) The association between obstructive sleep apnea and nonarteritic anterior ischemic optic neuropathy: a systematic review and meta-analysis. Curr Eye Res 41(7):987–992

    PubMed  Article  Google Scholar 

  61. 61.

    Wu CY, Riangwiwat T, Rattanawong P, Nesmith BLW, Deobhakta A (2018) Association of obstructive sleep apnea with central serous chorioretinopathy and choroidal thickness: a systematic review and meta-analysis. Retina (Philadelphia, Pa) 38(9):1642–1651

    Article  Google Scholar 

  62. 62.

    Qie R, Zhang D, Liu L, Ren Y, Zhao Y, Liu D, Liu F, Chen X, Cheng C, Guo C et al (2020) Obstructive sleep apnea and risk of type 2 diabetes mellitus: a systematic review and dose-response meta-analysis of cohort studies. J Diabetes 12(6):455–464

    PubMed  Article  Google Scholar 

  63. 63.

    Gu X, Luo X, Wang X, Tang J, Yang W, Cai Z (2018) The correlation between obstructive sleep apnea and diabetic neuropathy: a meta-analysis. Prim Care Diabetes 12(5):460–466

    PubMed  Article  Google Scholar 

  64. 64.

    Leong WB, Jadhakhan F, Taheri S, Thomas GN, Adab P (2016) The association between obstructive sleep apnea on diabetic kidney disease: a systematic review and meta-analysis. Sleep 39(2):301–308

    PubMed  PubMed Central  Article  Google Scholar 

  65. 65.

    Zhu Z, Zhang F, Liu Y, Yang S, Li C, Niu Q, Niu J (2017) Relationship of obstructive sleep apnoea with diabetic retinopathy: a meta-analysis. Biomed Res Int 2017:4737064

    PubMed  PubMed Central  Google Scholar 

  66. 66

    Wu ZH, Yang XP, Niu X, Xiao XY, Chen X (2019) The relationship between obstructive sleep apnea hypopnea syndrome and gastroesophageal reflux disease: a meta-analysis. Sleep Breath 23(2):389–397

    PubMed  Article  Google Scholar 

  67. 67

    Jin S, Jiang S, Hu A (2018) Association between obstructive sleep apnea and non-alcoholic fatty liver disease: a systematic review and meta-analysis. Sleep Breath 22(3):841–851

    PubMed  Article  Google Scholar 

  68. 68

    Musso G, Cassader M, Olivetti C, Rosina F, Carbone G, Gambino R (2013) Association of obstructive sleep apnoea with the presence and severity of non-alcoholic fatty liver disease. A systematic review and meta-analysis. Obes Rev  14(5):417–431

  69. 69.

    Ger TY, Fu Y, Chi CC (2020) Bidirectional association between psoriasis and obstructive sleep apnea: a systematic review and meta-analysis. Sci Rep 10(1):5931

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  70. 70

    Zhou J, Xia S, Li T, Liu R (2020) Association between obstructive sleep apnea syndrome and nocturia: a meta-analysis. Sleep Breath 24:1293–1298

    PubMed  Article  Google Scholar 

  71. 71.

    Cao Y, Wu S, Zhang L, Yang Y, Cao S, Li Q (2018) Association of allergic rhinitis with obstructive sleep apnea: a meta-analysis. Medicine 97(51):e13783

    PubMed  PubMed Central  Article  Google Scholar 

  72. 72.

    Liu L, Kang R, Zhao S, Zhang T, Zhu W, Li E, Li F, Wan S, Zhao Z (2015) Sexual dysfunction in patients with obstructive sleep apnea: a systematic review and meta-analysis. J Sex Med 12(10):1992–2003

    PubMed  Article  Google Scholar 

  73. 73.

    Upala S, Sanguankeo A, Congrete S (2016) Association between obstructive sleep apnea and osteoporosis: a systematic review and meta-analysis. International journal of endocrinology and metabolism 14(3):e36317

    PubMed  PubMed Central  Article  Google Scholar 

  74. 74.

    Shi T, Min M, Sun C, Cheng C, Zhang Y, Liang M, Rizeq FK, Sun Y (2019) A meta-analysis of the association between gout, serum uric acid level, and obstructive sleep apnea. Sleep Breath 23(4):1047–1057

    PubMed  Article  Google Scholar 

  75. 75.

    Liu T, Zhan Y, Wang Y, Li Q, Mao H (2021) Obstructive sleep apnea syndrome and risk of renal impairment: a systematic review and meta-analysis with trial sequential analysis. Sleep Breath 25(1):17–27

  76. 76

    Palamaner Subash Shantha G, Kumar AA, Cheskin LJ, Pancholy SB (2015) Association between sleep-disordered breathing, obstructive sleep apnea, and cancer incidence: a systematic review and meta-analysis. Sleep Med 16(10):1289–1294

    PubMed  Article  Google Scholar 

  77. 77.

    Xu S, Wan Y, Xu M, Ming J, Xing Y, An F, Ji Q (2015) The association between obstructive sleep apnea and metabolic syndrome: a systematic review and meta-analysis. BMC Pulm Med 15:105

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  78. 78.

    Edwards C, Almeida OP, Ford AH (2020) Obstructive sleep apnea and depression: a systematic review and meta-analysis. Maturitas 142:45–54

    PubMed  Article  PubMed Central  Google Scholar 

  79. 79.

    Tregear S, Reston J, Schoelles K, Phillips B (2009) Obstructive sleep apnea and risk of motor vehicle crash: systematic review and meta-analysis. Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine 5(6):573–581

    Google Scholar 

  80. 80.

    Garbarino S, Guglielmi O, Sanna A, Mancardi GL, Magnavita N (2016) Risk of occupational accidents in workers with obstructive sleep apnea: systematic review and meta-analysis. Sleep 39(6):1211–1218

    PubMed  PubMed Central  Article  Google Scholar 

  81. 81.

    Sun CL, Zhou LX, Dang Y, Huo YP, Shi L, Chang YJ (2016) Decreased retinal nerve fiber layer thickness in patients with obstructive sleep apnea syndrome: a meta-analysis. Medicine 95(32):e4499

    PubMed  PubMed Central  Article  Google Scholar 

  82. 82.

    Zhou M, Guo B, Wang Y, Yan D, Lin C, Shi Z (2017) The association between obstructive sleep apnea and carotid intima-media thickness: a systematic review and meta-analysis. Angiology 68(7):575–583

    PubMed  Article  Google Scholar 

  83. 83.

    Song G, Sun F, Wu D, Bi W (2020) Association of epicardial adipose tissues with obstructive sleep apnea and its severity: a meta-analysis study. Nutr Metab Cardiovasc Dis 30(7):1115–1120

    PubMed  Article  Google Scholar 

  84. 84.

    Yu L, Li H, Liu X, Fan J, Zhu Q, Li J, Jiang J, Wang J (2020) Left ventricular remodeling and dysfunction in obstructive sleep apnea : Systematic review and meta-analysis. Herz 45(8):726–738

  85. 85.

    Maripov A, Mamazhakypov A, Sartmyrzaeva M, Akunov A, Muratali Uulu K, Duishobaev M, Cholponbaeva M, Sydykov A, Sarybaev A (2017) Right ventricular remodeling and dysfunction in obstructive sleep apnea: a systematic review of the literature and meta-analysis. Can Respir J 2017:1587865

    PubMed  PubMed Central  Article  Google Scholar 

  86. 86.

    Zhang RH, Zhao W, Shu LP, Wang N, Cai YH, Yang JK, Zhou JB, Qi L (2020) Obstructive sleep apnea is associated with coronary microvascular dysfunction: a systematic review from a clinical perspective. J Sleep Res 29:e13046

    PubMed  PubMed Central  Article  Google Scholar 

  87. 87.

    Kong DL, Qin Z, Wang W, Pan Y, Kang J, Pang J (2016) Association between obstructive sleep apnea and metabolic syndrome: a meta-analysis. Clin Invest Med 39(5):E161-e172

    CAS  PubMed  Article  Google Scholar 

  88. 88.

    Lu M, Fang F, Wang Z, Wei P, Hu C, Wei Y (2019) Association between serum/plasma levels of adiponectin and obstructive sleep apnea hypopnea syndrome: a meta-analysis. Lipids Health Dis 18(1):30

    PubMed  PubMed Central  Article  Google Scholar 

  89. 89.

    Fadaei R, Safari-Faramani R, Rezaei M, Ahmadi R, Rostampour M, Moradi N, Khazaie H (2020) Circulating levels of oxidized low-density lipoprotein in patients with obstructive sleep apnea: a systematic review and meta-analysis. Sleep Breath 24(3):809–815

    PubMed  Article  Google Scholar 

  90. 90.

    Lu F, Jiang T, Wang W, Hu S, Shi Y, Lin Y (2020) Circulating fibrinogen levels are elevated in patients with obstructive sleep apnea: a systemic review and meta-analysis. Sleep Med 68:115–123

    PubMed  Article  Google Scholar 

  91. 91.

    Li K, Zhang J, Qin Y, Wei YX (2017) Association between serum homocysteine level and obstructive sleep apnea: a meta-analysis. Biomed Res Int 2017:7234528

    PubMed  PubMed Central  Google Scholar 

  92. 92.

    Wu X, She W, Niu X, Chen X (2018) Association between serum level of advanced glycation end products and obstructive sleep apnea-hypopnea syndrome: a meta-analysis. J Int Med Res 46(11):4377–4385

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  93. 93.

    Jin ZN, Wei YX (2016) Meta-analysis of effects of obstructive sleep apnea on the renin-angiotensin-aldosterone system. Journal of Geriatric Cardiology : JGC 13(4):333–343

    CAS  PubMed  Google Scholar 

  94. 94.

    Li X, He J, Yun J (2020) The association between serum vitamin D and obstructive sleep apnea: an updated meta-analysis. Respir Res 21(1):294

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  95. 95.

    Nadeem R, Singh M, Nida M, Waheed I, Khan A, Ahmed S, Naseem J, Champeau D (2014) Effect of obstructive sleep apnea hypopnea syndrome on lipid profile: a meta-regression analysis. Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine 10(5):475–489

    Google Scholar 

  96. 96.

    Aromataris E, Fernandez R, Godfrey CM, Holly C, Khalil H, Tungpunkom P (2015) Summarizing systematic reviews: methodological development, conduct and reporting of an umbrella review approach. Int J Evid Based Healthc 13(3):132–140

    PubMed  Article  Google Scholar 

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Acknowledgements

We would like to thank the researchers and study participants for their contributions.

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Idea and design: TSH, CWW. Literature search: ZCX, GLLZ. Data extraction and analysis:CWW, LYT. Manuscript writing: CWW. Manuscript revision: TSH, CWW. All authors read and approved the version of the manuscript to be published. All authors take responsibility for appropriate content.

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Correspondence to Shaohui Tang.

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Weiwei Chen and Yuting Li contributed equally to this work and should be considered co-first authors

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Chen, W., Li, Y., Guo, L. et al. An umbrella review of systematic reviews and meta-analyses of observational investigations of obstructive sleep apnea and health outcomes. Sleep Breath (2021). https://doi.org/10.1007/s11325-021-02384-2

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Keywords

  • Obstructive sleep apnea
  • Health
  • Umbrella review
  • Meta-analysis