Juan A Esquivel-Mendoza, Brooke G Rogers, Steven A Safren
{"title":"Sleep actigraphy results and HIV health outcomes in an urban HIV clinic sample.","authors":"Juan A Esquivel-Mendoza, Brooke G Rogers, Steven A Safren","doi":"10.1080/13548506.2024.2407444","DOIUrl":null,"url":null,"abstract":"<p><p>Sleep disorders are prevalent and interfering conditions that affect people living with HIV (PLWH) at higher rates than the general population. Lower quality sleep has been associated with poorer health-related quality of life and immune function in PWH, though sleep is typically assessed subjectively. The current study aimed to examine the association between objective sleep/wake patterns measured via actigraphy with HIV outcomes. Participants (<i>N</i> = 87) were recruited from a public, urban HIV clinic located in the Southeastern United States. Participants were instructed to wear actigraphy monitors for one week (Range: 5-8 days). Log viral load and absolute CD4 were obtained via medical chart review. Linear regression analyses predicting HIV RNA Viral Load (log transformed) and CD4 Count were employed with three actigraphy sleep variables: sleep efficiency, wake after sleep onset (WASO), and sleep quantity. Backward entry regression with both significant actigraphy predictors, sleep efficiency and WASO, included as predictors resulted in sleep efficiency remaining in the model and WASO being removed. Separate models revealed that each one-unit increase in sleep efficiency was associated with a b = 0.032-point decrease in the log-transformed HIV RNA viral load (<i>p</i> = 0.03) and for each one-unit increase in wake after sleep onset (WASO) was associated with a b = 0.35-point increase in the log-transformed HIV RNA viral load (<i>p</i> = 0.04). Sleep quantity, however, was not, and none were associated with absolute CD4 count. The findings add to the evidence for an association of objectively measured poorer sleep efficiency being associated with higher HIV RNA viral load. Implications for clinical practice include assessing and addressing sleep efficiency as part of comprehensive clinical HIV care.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/13548506.2024.2407444","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Sleep disorders are prevalent and interfering conditions that affect people living with HIV (PLWH) at higher rates than the general population. Lower quality sleep has been associated with poorer health-related quality of life and immune function in PWH, though sleep is typically assessed subjectively. The current study aimed to examine the association between objective sleep/wake patterns measured via actigraphy with HIV outcomes. Participants (N = 87) were recruited from a public, urban HIV clinic located in the Southeastern United States. Participants were instructed to wear actigraphy monitors for one week (Range: 5-8 days). Log viral load and absolute CD4 were obtained via medical chart review. Linear regression analyses predicting HIV RNA Viral Load (log transformed) and CD4 Count were employed with three actigraphy sleep variables: sleep efficiency, wake after sleep onset (WASO), and sleep quantity. Backward entry regression with both significant actigraphy predictors, sleep efficiency and WASO, included as predictors resulted in sleep efficiency remaining in the model and WASO being removed. Separate models revealed that each one-unit increase in sleep efficiency was associated with a b = 0.032-point decrease in the log-transformed HIV RNA viral load (p = 0.03) and for each one-unit increase in wake after sleep onset (WASO) was associated with a b = 0.35-point increase in the log-transformed HIV RNA viral load (p = 0.04). Sleep quantity, however, was not, and none were associated with absolute CD4 count. The findings add to the evidence for an association of objectively measured poorer sleep efficiency being associated with higher HIV RNA viral load. Implications for clinical practice include assessing and addressing sleep efficiency as part of comprehensive clinical HIV care.