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08.07.2023 | Sleep Breathing Physiology and Disorders • Review

Anthropometric measures and obstructive sleep apnea in children and adolescents: a systematic review of the literature and meta-analysis

verfasst von: Luiza Lassi de Araújo Lopes, Fábio Wildson Gurgel Costa, Lúcia Helena Soares Cevidanes, Paulo Goberlânio de Barros Silva, Marcela Lima Gurgel, Francisco Samuel Rodrigues Carvalho, Cauby Maia Chaves Júnior, Thyciana Rodrigues Ribeiro

Erschienen in: Sleep and Breathing | Ausgabe 1/2024

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Abstract

Background

Anthropometric measurements can be used to identify children at risk of developing obstructive sleep apnea (OSA). The study aimed to assess which anthropometric measurements (AMs) are most associated with an increased predisposition to develop OSA in healthy children and adolescents.

Methods

We performed a systematic review (PROSPERO #CRD42022310572) that searched eight databases and gray literature.

Results

In eight studies with low-to-high risk of bias, investigators reported the following AMs: body mass index (BMI), neck circumference, hip circumference, waist-to-hip ratio, neck-to-waist ratio, waist circumference, waist-to-height ratio, and facial AMs. The meta-analysis showed that the OSA group had an average of 1.00 cm greater for the neck circumference (p < 0.001; Cohen’s d = 2.26 [0.72, 5.23]), 3.07 cm greater for the waist circumference (p = 0.030; Cohen’s d = 0.28 [0.02, 0.53]), 3.96 cm greater for the hip circumference (p = 0.040; Cohen’s d = 0.28 [0.02, 0.55]), 5.21° greater for the cervicomental angle (p = 0.020; Cohen’s d = 0.31 [0.03, 0.59]), and 1.23° greater for maxillary-mandibular relationship angle (p < 0.001; Cohen’s d = 0.47 [0.22, 0.72]) than the control group. The mandibular depth angle had a reduction of 1.86° (p = 0.001; Cohen’s d = −0.36° [−0.65, −0.08]) in control than in patients with OSA. The BMI (p = 0.180), waist-to-hip ratio (p = 0.280), neck-to-waist ratio (p = 0.070), maxillary depth angle (p = 0.250), and upper/lower face height ratio (p = 0.070) showed no significant differences between groups.

Conclusions

Compared to the control group, the OSA group exhibited a greater mean difference in neck circumference, the only anthropometric measurement with high certainty of evidence.

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Abazi Y, Cenko F, Cardella M et al (2020) Sleep disordered breathing: an epidemiological study among Albanian children and adolescents. Int J Environ Res Public Health 17:1–11. https://doi.org/10.3390/ijerph17228586CrossRef

Marcus CL, Brooks LJ, Ward SD et al (2012) Diagnosis and management of childhood obstructive sleep apnea syndrome. Pediatrics 130:e714–e755. https://doi.org/10.1542/peds.2012-1672CrossRefPubMed

Muzumdar H, Arens R (2013) Physiological effects of obstructive sleep apnea syndrome in childhood. Respir Physiol Neurobiol 188:370–382CrossRefPubMedPubMedCentral

Sateia MJ (2014) International classification of sleep disorders-third edition highlights and modifications. Chest 146:1387–1394. https://doi.org/10.1378/chest.14-0970CrossRefPubMed

Bixler EO, Vgontzas AN, Lin HM et al (2009) Sleep disordered breathing in children in a general population sample: prevalence and risk factors. Sleep 32:731–736. https://doi.org/10.1093/sleep/32.6.731CrossRefPubMedPubMedCentral

Li AM, So HK, Au CT et al (2010) Epidemiology of obstructive sleep apnoea syndrome in Chinese children: a two-phase community study. Thorax 65:991–997. https://doi.org/10.1136/thx.2010.134858CrossRefPubMed

Tan HL, Gozal D, Kheirandish-Gozal L (2013) Obstructive sleep apnea in children: a critical update. Nat Sci Sleep 5:109–123. https://doi.org/10.2147/NSS.S51907CrossRefPubMedPubMedCentral

Sánchez-Armengol A, Fuentes-Pradera MA, Capote-Gil F et al (2001) Sleep-related breathing disorders in adolescents aged 12 to 16 years: clinical and polygraphic findings. Chest 119:1393–1400. https://doi.org/10.1378/chest.119.5.1393CrossRefPubMed

Lumeng JC, Chervin RD (2008) Epidemiology of pediatric obstructive sleep apnea. Proc Am Thorac Soc 5:242–252. https://doi.org/10.1513/pats.200708-135MGCrossRefPubMedPubMedCentral

10.

Brouillette RT, Horwood L, Constantin E et al (2011) Childhood sleep apnea and neighborhood disadvantage. J Pediatr 158:789–795.e1. https://doi.org/10.1016/j.jpeds.2010.10.036CrossRefPubMed

11.

Wang Y, Mao L, Zhang X (2022) Waist-hip ratio is an independent predictor of moderate-to-severe OSA in nonobese males: a cross-sectional study. BMC Pulm Med 22:1–9. https://doi.org/10.1186/s12890-022-01886-3CrossRef

12.

Williamson A, Fan J, Distel L et al (2023) Nighttime sleep duration and variability in children with obstructive sleep apnea syndrome: sociodemographic disparities and neurobehavioral outcomes. Sleep Med 102:165–172. https://doi.org/10.1016/j.sleep.2023.01.003CrossRefPubMedPubMedCentral

13.

Campbell AJ, Mather SJ, Elder DE (2021) Obstructive sleep apnea risk factors and symptoms in children with a known parental obstructive sleep apnea diagnosis. Sleep Med 78:149–152. https://doi.org/10.1016/j.sleep.2020.12.030CrossRefPubMed

14.

Gulotta G, Iannella G, Vicini C et al (2019) Risk factors for obstructive sleep apnea syndrome in children: state of the art. Int J Environ Res Public Health 16. https://doi.org/10.3390/ijerph16183235

15.

Bitners A, Arens R (2020) Evaluation and management of adults with obstructive sleep apnea syndrome. Lung 198:257–270. https://doi.org/10.1007/s00408-021-00426-wCrossRefPubMedPubMedCentral

16.

Savini S, Ciorba A, Bianchini C et al (2019) Assessment of obstructive sleep apnoea (OSA) in children: an update. Acta Otorhinolaryngol Ital 39:289–297. https://doi.org/10.14639/0392-100X-N0262CrossRefPubMedPubMedCentral

17.

De Luca CG, Singh V, Major MP et al (2014) Diagnostic capability of questionnaires and clinical examinations to assess sleep-disordered breathing in children: a systematic review and meta-analysis. J Am Dent Assoc 145:165–178. https://doi.org/10.14219/jada.2013.26CrossRef

18.

Balaei AT, Sutherland K, Cistulli PA, De Chazal P (2017) Automatic detection of obstructive sleep apnea using facial images. In: Proc - International Symposium on Biomedical Imaging, pp 215–218. https://doi.org/10.1109/ISBI.2017.7950504CrossRef

19.

Kang J-H, Kim HJ, Song SI (2022) Obstructive sleep apnea and anatomical structures of the nasomaxillary complex in adolescents. PloS One 17:e0272262. https://doi.org/10.1371/journal.pone.0272262CrossRefPubMedPubMedCentral

20.

Te LW, Wu HT, Juang JN et al (2017) Prediction of the severity of obstructive sleep apnea by anthropometric features via support vector machine. PloS One 12:1–11. https://doi.org/10.1371/journal.pone.0176991CrossRef

21.

Kang HH, Kang JY, Ha JH et al (2014) The associations between anthropometric indices and obstructive sleep apnea in a Korean population. PloS One 9:1–12. https://doi.org/10.1371/journal.pone.0114463CrossRef

22.

Katz S, Murto K, Barrowman N et al (2014) Neck circumference percentile: a screening tool for pediatric obstructive sleep apnea. Pediatr Pulmonol 50:196–201. https://doi.org/10.1002/ppul.23003CrossRefPubMed

23.

Smith DF, Dalesio NM, Benke JR et al (2016) Anthropometric and dental measurements in children with obstructive sleep apnea. J Clin Sleep Med 12:1279–1284. https://doi.org/10.5664/jcsm.6132CrossRefPubMedPubMedCentral

24.

Chaves CM Jr, Teles MP, Carvalhedo de Bruin PF et al (2015) Assessment of the craniofacial and cervical parameters using standardized photography in individuals with obstructive sleep apnea. Int Arch Med 8:1–9. https://doi.org/10.3823/1772CrossRef

25.

Kuvat N, Tanriverdi H, Armutcu F (2020) The relationship between obstructive sleep apnea syndrome and obesity: a new perspective on the pathogenesis in terms of organ crosstalk. Clin Respir J 14:595–604. https://doi.org/10.1111/crj.13175CrossRefPubMed

26.

Romero-Corral A, Caples SM, Lopez-Jimenez F, Somers VK (2010) Interactions between obesity and obstructive sleep apnea: implications for treatment. Chest 137:711–719. https://doi.org/10.1378/chest.09-0360CrossRefPubMedPubMedCentral

27.

Bonsignore MR, McNicholas WT, Montserrat JM, Eckel J (2012) Adipose tissue in obesity and obstructive sleep apnoea. Eur Respir J 39:746–767. https://doi.org/10.1183/09031936.00047010CrossRefPubMed

28.

Durgan D, Ganesh B, Cope J et al (2016) Role of the gut microbiome in obstructive sleep apnea-induced hypertension. Hypertension 67:469–474. https://doi.org/10.1161/HYPERTENSIONAHA.115.06672CrossRefPubMed

29.

Page MJ, McKenzie JE, Bossuyt PM et al (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372. https://doi.org/10.1136/bmj.n71

30.

Haddaway NR, Collins AM, Coughlin D, Kirk S (2015) The role of google scholar in evidence reviews and its applicability to grey literature searching. PloS One 10:1–17. https://doi.org/10.1371/journal.pone.0138237CrossRef

31.

Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A (2016) Rayyan—a web and mobile app for systematic reviews. Syst Rev 5:1–10. https://doi.org/10.1186/s13643-016-0384-4CrossRef

32.

Gurgel ML, Junior CC, Cevidanes LHS et al (2022) Methodological parameters for upper airway assessment by cone-beam computed tomography in adults with obstructive sleep apnea: a systematic review of the literature and meta-analysis. Sleep Breath 27(1):1–30. https://doi.org/10.1007/s11325-022-02582-6CrossRefPubMedPubMedCentral

33.

Schünemann H, Brożek J, Guyatt G, Oxman A (2013) GRADE handbook

34.

De Sousa MR, Ribeiro ALP (2009) Systematic review and meta-analysis of diagnostic and prognostic studies: a tutorial. Arq Bras Cardiol 92:235–245. https://doi.org/10.1590/S0066-782X2009000300013CrossRef

35.

Walter LM, Tamanyan K, Nisbet LC et al (2018) Obesity and anthropometric determinants of autonomic control in children with sleep-disordered breathing-which measurements matter? Int J Obes (Lond) 42:1195–1201. https://doi.org/10.1038/s41366-018-0130-1CrossRefPubMed

36.

Banhiran W, Junlapan A, Assanasen P, Chongkolwatana C (2014) Physical predictors for moderate to severe obstructive sleep apnea in snoring patients. Sleep Breath 18:151–158. https://doi.org/10.1007/s11325-013-0863-yCrossRefPubMed

37.

Kim JH, Koo YC, Cho HJ, Kang JW (2018) Relationship between various anthropometric measures and apnea-hypopnea index in Korean men. Auris Nasus Larynx 45:295–300. https://doi.org/10.1016/j.anl.2017.05.005CrossRefPubMed

38.

Subramanian S, Jayaraman G, Majid H et al (2012) Influence of gender and anthropometric measures on severity of obstructive sleep apnea. Sleep Breath 16:1091–1095. https://doi.org/10.1007/s11325-011-0607-9CrossRefPubMed

39.

Bachrach K, Danis DON, Cohen MB, Levi JR (2022) The relationship between obstructive sleep apnea and pediatric obesity: a nationwide analysis. Ann Otol Rhinol Laryngol 131:520–526. https://doi.org/10.1177/00034894211028489CrossRefPubMed

40.

Yuen HM, Chan KC, Chu WCW et al (2022) Craniofacial phenotyping by photogrammetry in Chinese prepubertal children with obstructive sleep apnea. Sleep 1–10. https://doi.org/10.1093/sleep/zsac289

41.

Androutsos O, Grammatikaki E, Moschonis G et al (2012) Neck circumference: a useful screening tool of cardiovascular risk in children. Pediatr Obes 7:187–195. https://doi.org/10.1111/j.2047-6310.2012.00052.xCrossRefPubMed

42.

Cizza G, De Jonge L, Piaggi P et al (2014) Neck circumference is a predictor of metabolic syndrome and obstructive sleep apnea in short-sleeping obese men and women. Metab Syndr Relat Disord 12:231–241. https://doi.org/10.1089/met.2013.0093CrossRefPubMedPubMedCentral

43.

Simpson L, Mukherjee S, Cooper MN et al (2010) Sex differences in the association of regional fat distribution with the severity of obstructive sleep apnea. Sleep 33:467–474. https://doi.org/10.1093/sleep/33.4.467CrossRefPubMedPubMedCentral

44.

Alves Junior CAS, Mocellin MC, Gonçalves ECA et al (2017) Anthropometric indicators as body fat discriminators in children and adolescents: a systematic review and meta-analysis. Adv Nutr 8:718–727. https://doi.org/10.3945/an.117.015446CrossRefPubMedPubMedCentral

45.

Stevens J, Katz E, Huxley R (2010) Associations between gender, age and waist circumference. Eur J Clin Nutr 64:6–15. https://doi.org/10.1038/ejcn.2009.101CrossRefPubMed

46.

Mardali F, Naziri M, Sohouli MH et al (2022) Predictors of central and general obesity in Iranian preschool children: which anthropometric indices can be used as screening tools? BMC Pediatr 22:1–10. https://doi.org/10.1186/s12887-022-03365-4CrossRef

47.

De Sousa Caixêta JA, Saramago AM, de Cácia Pradella-Hallinan ML et al (2014) Waist-to-height ratio distinguish obstructive sleep apnea from primary snoring in obese children. Sleep Breath 19:231–237. https://doi.org/10.1007/s11325-014-1001-1CrossRefPubMed

48.

Sutherland K, Lee RWW, Petocz P et al (2016) Craniofacial phenotyping for prediction of obstructive sleep apnoea in a Chinese population. Respirology 21:1118–1125. https://doi.org/10.1111/resp.12792CrossRefPubMed

49.

Lee RWW, Chan ASL, Grunstein RR, Cistulli PA (2009) Craniofacial phenotyping in obstructive sleep apnea — a novel quantitative photographic approach. Sleep 32:37–45. https://doi.org/10.5665/sleep/32.1.37CrossRefPubMedPubMedCentral

50.

Ikävalko T, Närhi M, Lakka T et al (2015) Lateral facial profile may reveal the risk for sleep disordered breathing in children—the PANIC-study. Acta Odontol Scand 73:550–555. https://doi.org/10.3109/00016357.2014.997795CrossRefPubMed

51.

Flores-Mir C, Korayem M, Heo G et al (2013) Craniofacial morphological characteristics in children with obstructive sleep apnea syndrome. Jada 144:269–277PubMed

52.

Sutherland K, Weichard AJ, Davey MJ et al (2019) Craniofacial photography and association with sleep-disordered breathing severity in children. Sleep Breath 24:1173–1179. https://doi.org/10.1007/s11325-019-01928-xCrossRefPubMed

53.

Hsueh WY, Kang KT, Yao CCJ et al (2022) Measurements of craniofacial morphology using photogrammetry in children with sleep-disordered breathing. Int J Pediatr Otorhinolaryngol 162:111287. https://doi.org/10.1016/j.ijporl.2022.111287CrossRefPubMed

54.

Sutherland K, Schwab RJ, Maislin G et al (2014) Facial phenotyping by quantitative photography reflects craniofacial morphology measured on magnetic resonance imaging in Icelandic sleep apnea patients. Sleep 37:959–968. https://doi.org/10.5665/sleep.3670CrossRefPubMedPubMedCentral

55.

Markkanen S, Niemi P, Rautiainen M et al (2019) Craniofacial and occlusal development in 2.5-year-old children with obstructive sleep apnoea syndrome. Eur J Orthod 41:316–321. https://doi.org/10.1093/ejo/cjz009CrossRefPubMed

56.

Andrade C (2020) Sample size and its importance in research. Indian J Psychol Med 42:102–103. https://doi.org/10.4103/IJPSYM.IJPSYM_504_19CrossRefPubMedPubMedCentral

Titel: Anthropometric measures and obstructive sleep apnea in children and adolescents: a systematic review of the literature and meta-analysis
verfasst von: Luiza Lassi de Araújo Lopes
Fábio Wildson Gurgel Costa
Lúcia Helena Soares Cevidanes
Paulo Goberlânio de Barros Silva
Marcela Lima Gurgel
Francisco Samuel Rodrigues Carvalho
Cauby Maia Chaves Júnior
Thyciana Rodrigues Ribeiro
Publikationsdatum: 08.07.2023
Verlag: Springer International Publishing
Erschienen in: Sleep and Breathing / Ausgabe 1/2024
Print ISSN: 1520-9512
Elektronische ISSN: 1522-1709
DOI: https://doi.org/10.1007/s11325-023-02861-w

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Anthropometric measures and obstructive sleep apnea in children and adolescents: a systematic review of the literature and meta-analysis