0514 Risk Factors for Symptoms and Signs of Sleep Apnea Impacting Quality of Life in an Urban Pediatric Community-Based Sample. (25th May 2022)

• Record Type: Journal Article
• Authors: Gueye-Ndiaye, Seyni; Hauptman, Marissa; Yu, Xinting; Rueschman, Michael; Castro-Diehl, Olga Cecilia; Owens, Judith; Gold, Diane; Adamkiewicz, Gary; Phipatanakul, Wanda; Redline, Susan
• Is Part Of: Sleep. Volume 45(2022)Supplement 1
• Page Start: A227
• Page End: A227
• Publication Date: 2022-05-25
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsac079.511
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: Pediatric obstructive sleep apnea (OSA) disproportionately affects children from minority groups and children living in disadvantaged neighborhoods, but the risk factors that drive this risk are not well understood. We investigated the relationship between minority race/ethnicity, household risk factors (smoking, socio-economic status [SES]), and neighborhood disadvantage with OSA-related quality of life (QOL) scores in participants in the Environmental Assessment of Sleep Youth (EASY) observational study. Methods: Families of children 5-12 years old recruited from largely low-income Boston-area neighborhoods participated in an extensive in-home evaluation of OSA risk factors. OSA-related QOL was assessed with parent-reported OSA-18 questionnaire (values >37 indicative of negative impact of symptoms and signs of OSA on QOL). Secondhand smoking (SHS) was defined by parent-report of smoking in the home. Neighborhood disadvantage was characterized using geocoded addresses, calculating the Neighborhood Socioeconomic (NSES) index. We performed logistic regression with OSA-18 >37 as the dependent variable and age, gender, race/ethnicity, BMI, household smoking, household measures of SES and NSES index as independent variables. Results: The sample included 256 children (40%-Hispanic ethnicity, 31%-Black, 20%-White, 9%-Other; 56% were female), with a mean age 9.1±1.9 and BMI percentile 69.9±29.8. 33% and 40% of children were from households with income <$25, 000 and $25, 000-$75, 000, respectively, and 10% had SHS exposure. Mean NSES index was 47.9±15.4 (national average of 50). An elevated OSA-18 was reported for 35% of participants and significantly associated with Hispanic ethnicity and smoking exposure (OR=2.16, CI 1.01-4.62 and OR=2.71, CI 1.2-6.3) after adjusting for age, gender, and BMI percentile. Further adjustment for family income attenuated the association of OSA-18 with Hispanic ethnicity, but a significant association with household smoking persisted. NSES index and BMI percentile were not associated with OSA-18. Conclusion: High symptoms and signs of OSA impacting QOL were associated with Hispanic ethnicity, household smoking and SES in this diverse cohort of children living in urban and predominantly low-income communities. The study points to the need for strategies to reduce household smoking as one strategy for decreasing sleep health disparities, and the further need to understand other factors associated with low SES that increase risk for poor sleep health. Support (If Any): NIH-NHLBI/T32HL007901, R35HL1358181, P30ES000002, K24AI106822, R01Hl137192, K23ES031663