Johanna Roche1, Dale E Rae2, Kirsten N Redman1, Kristen L Knutson3, Malcolm von Schantz4, F Xavier Gómez-Olivé5, Karine Scheuermaier1. 1. Wits Sleep Laboratory, Brain Function Research Group, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. 2. Division of Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa. 3. Feinberg School of Medicine, Northwestern University, Chicago, Illinois. 4. Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom. 5. MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Abstract
STUDY OBJECTIVES: The association between obstructive sleep apnea (OSA) and increased cardiometabolic risk (CMR) has been well documented in higher-income countries. However, OSA and its association with CMR have not yet been investigated, based on objective measures, in southern Africa. We measured polysomnography-derived sleep characteristics, OSA prevalence, and its association with cardiometabolic diseases in a rural, low-income, African-ancestry sample of older adult participants in South Africa. METHODS: Seventy-five participants completed the study. Body mass index, hypertension, diabetes, dyslipidemia, and HIV status were determined. A continuous CMR score was calculated using waist circumference, random glucose, high-density-lipoprotein cholesterol, triglycerides, and mean arterial blood pressure. Sleep architecture, arousal index, and apnea-hypopnea index for detection of the OSA (apnea-hypopnea index ≥ 15 events/h) were assessed by home-based polysomnography. Associations between CMR score and age, sex, socioeconomic status, apnea-hypopnea index, and total sleep time were investigated by multivariable analysis. RESULTS: In our sample (53 women, age 66.1 ± 10.7 years, 12 HIV+), 60.7% of participants were overweight/obese, 61.3% were hypertensive, and 29.3% had undiagnosed OSA. Being older (P = .02) and having a higher body mass index (P = .02) and higher waist circumference (P < .01) were associated with OSA. Apnea-hypopnea index severity (β = 0.011; P = .01) and being a woman (β = 0.369; P = .01) were independently associated with a higher CMR score in socioeconomic status- and age-adjusted analyses. CONCLUSIONS: In this South African community with older adults with obesity and hypertension, OSA prevalence is alarming and associated with CMR. We show the feasibility of detecting OSA in a rural setting using polysomnography. Our results highlight the necessity for actively promoting health education and systematic screening and treatment of OSA in this population to prevent future cardiovascular morbidity, especially among women.
STUDY OBJECTIVES: The association between obstructive sleep apnea (OSA) and increased cardiometabolic risk (CMR) has been well documented in higher-income countries. However, OSA and its association with CMR have not yet been investigated, based on objective measures, in southern Africa. We measured polysomnography-derived sleep characteristics, OSA prevalence, and its association with cardiometabolic diseases in a rural, low-income, African-ancestry sample of older adult participants in South Africa. METHODS: Seventy-five participants completed the study. Body mass index, hypertension, diabetes, dyslipidemia, and HIV status were determined. A continuous CMR score was calculated using waist circumference, random glucose, high-density-lipoprotein cholesterol, triglycerides, and mean arterial blood pressure. Sleep architecture, arousal index, and apnea-hypopnea index for detection of the OSA (apnea-hypopnea index ≥ 15 events/h) were assessed by home-based polysomnography. Associations between CMR score and age, sex, socioeconomic status, apnea-hypopnea index, and total sleep time were investigated by multivariable analysis. RESULTS: In our sample (53 women, age 66.1 ± 10.7 years, 12 HIV+), 60.7% of participants were overweight/obese, 61.3% were hypertensive, and 29.3% had undiagnosed OSA. Being older (P = .02) and having a higher body mass index (P = .02) and higher waist circumference (P < .01) were associated with OSA. Apnea-hypopnea index severity (β = 0.011; P = .01) and being a woman (β = 0.369; P = .01) were independently associated with a higher CMR score in socioeconomic status- and age-adjusted analyses. CONCLUSIONS: In this South African community with older adults with obesity and hypertension, OSA prevalence is alarming and associated with CMR. We show the feasibility of detecting OSA in a rural setting using polysomnography. Our results highlight the necessity for actively promoting health education and systematic screening and treatment of OSA in this population to prevent future cardiovascular morbidity, especially among women.
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