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Int J Obes (Lond). Author manuscript; available in PMC 2017 April 30. Published in final edited form as: Int J Obes (Lond). 2017 February ; 41(2): 203–209. doi:10.1038/ijo.2016.194.
Circadian timing and alignment in healthy adults: associations with BMI, body fat, caloric intake and physical activity KG Baron1, KJ Reid2, T Kim2, L Van Horn3, H Attarian2, L Wolfe2, J Siddique3, G Santostasi2, and PC Zee2 1Department
of Behavioral Sciences, Section of Sleep Disorders and Sleep Research, Rush University Medical Center
Author Manuscript
2Center
for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine
3Department
of Preventive Medicine, Northwestern University Feinberg School of Medicine
Abstract
Author Manuscript
Introduction—Disruption of circadian rhythms is one of the proposed mechanisms linking late sleep timing to obesity risk but few studies have evaluated biological markers outside of the laboratory. The goal of this study was to determine the relationship between the timing and alignment of melatonin and sleep onset (phase angle) with BMI, body fat and obesity related behaviors. We hypothesized that circadian alignment (relationship of melatonin to sleep timing) rather than circadian (melatonin) timing would be associated with higher BMI, body fat, dietary intake and lower physical activity. Subjects/Methods—Adults with sleep duration ≥6.5 hours completed 7 days of wrist actigraphy, food diaries and SenseWear arm band monitoring. Circadian timing, measured by dim light melatonin onset (DLMO) was measured in the clinical research unit. Circadian alignment was calculated as the duration between dim light melatonin onset and average sleep onset time in the prior week (phase angle). Body fat was evaluated using dual-energy absorptiometry (DXA). Data were analyzed using bivariate correlations and multivariable regression analyses controlling for age, sex, sleep duration and evening light exposure.
Author Manuscript
Results—Participants included 97 adults (61 F, age 26.8 ± 7.3 years) with average sleep duration 443.7 (SD= 50.4) minutes. Average phase angle was 2.2 hours (SD= 1.5). Circadian alignment was associated with circadian timing (p300 mg per day, smoking, pregnancy or the desire to become pregnant during the study period.
Int J Obes (Lond). Author manuscript; available in PMC 2017 April 30.
Baron et al.
Page 4
Procedure
Author Manuscript
Screening procedures—Prospective participants first completed an initial web or telephone screening to screen for self-reported short sleep duration, comorbid conditions and health behaviors (smoking, alcohol and substance use). Next, potential participants attended an in-person screening visit. During this visit, they completed questionnaires and then one night of home sleep apnea screening and 7 days of actigraphy to determine if they met study criteria. After screening actigraphy and apnea screening data were reviewed, eligible participants were scheduled for one night in the Clinical Research Unit for melatonin assessment and DXA.
Author Manuscript
Pre-laboratory procedures—Participants completed 7 days of actigraphy, sleep and food diaries prior to the laboratory session. Participants were asked to keep their habitual bedtimes and wake times at screening stable, within ± 1 hour of their average at screening times.
Author Manuscript
Laboratory session—Participants arrived at approximately 1:00 PM. After admission, participants underwent a history and physical exam by a sleep medicine physician and female participants underwent a urine pregnancy screening. Then, participants completed a Dual-energy X-ray Absorptiometry (DXA) tissue measurement to assess body fat. Bedtime, wake time and blood sampling times were determined based on habitual bedtime. Circadian time 0 (CT 0) was determined by average sleep onset time plus 8 hours because participants were not required to spend 8 hours in bed in the week prior to the CRU visit. The lights were dimmed to 5 on the Apnea Link recording were excluded from the study.
Author Manuscript
Subjective Sleep quality—Subjective sleep quality was measured by the the Pittsburgh Sleep Quality Questionnaire (PSQI).34 This measure assesses self-reported sleep quality and disturbances over a one-month time interval. A higher PSQI global score indicates greater sleep disturbance. Scores ≥5 are associated with clinically significant sleep disturbance.34 Subscores of the PSQI include sleep duration, sleep disturbance, sleep latency, daytime dysfunction, habitual sleep efficiency, sleep quality and medication use. Sleep—Sleep/wake patterns were estimated using 7 days of wrist actigraphy at screening and before the laboratory session using the Actiwatch Spectrum (Philips/Respironics, Inc, Bend, OR). Actiwatches were worn on the non-dominant wrist and set with 30 second epoch length and medium sensitivity. Actigraphic sleep parameters were calculated using Actiware-Sleep 6.0 software with default settings and included the following variables: sleep onset time, sleep offset time and sleep duration. Sleep diary based measures of bedtime and wake time were manually entered in Actiware and used in scoring. Off wrist time was excluded based on the Spectrum’s off wrist detection. A day was not considered valid if there was any off-wrist time during the sleep period reported on the sleep diary. In order to be included in analyses, participants needed at least 5 days of valid actigraphy data.
Author Manuscript
Evening light exposure—White light exposure was measured using the Actiwatch Spectrum (Philips/Respironics, Inc, Bend, OR). We calculated evening light exposure as the sum of white light exposure (lux) in the 3 hours prior to bedtime on each day of recording and averaged over the valid recording days.
Author Manuscript
Circadian timing (DLMO)—Plasma melatonin levels were assayed using a commercially available radioimmunoassay for the in-vitro diagnostic quantitative determination of melatonin from IBL (IBL International GmbH, Hamburg, Germany). Lower limit of this assay is 3.5 kg/mL and upper limit is 281 pg/mL. After blood draws, samples were centrifuged, aliquoted and stored at −70 F until assayed. All melatonin profiles were first visually inspected. Dim light melatonin onset was determined using 2 SD above the baseline + 15% of the 3 highest values.35 Circadian alignment (also known as phase angle) was calculated as the duration of time between DLMO to average sleep onset time recorded on actigraphy during the prior 7 days. Body Mass index—Body Mass Index (kg/m2) was calculated using measurements from the laboratory session: height measured at admission by nursing and weight taken in light clothing, without eating or drinking after the morning void.
Int J Obes (Lond). Author manuscript; available in PMC 2017 April 30.
Baron et al.
Page 6
Author Manuscript
Body fat and body fat distribution—Body Fat was measured using DXA on a whole body Hologic scanner (Version 13.1). Body fat values were calculated for total body fat mass, trunk fat mass, android and gynoid regions using automated calculations provided by Hologic. Values were calculated for total body fat % and the gynoid/android ratio, a measure of central adiposity.
Author Manuscript
Dietary Intake—Participants completed 7 days of written food diaries during the week before the laboratory assessment. On the food diaries, participants recorded time, location, type of food, amount consumed and a description of each component including brands and restaurant names. Participants were instructed to break down foods into component parts (e.g. turkey sandwich= 2 slices of white bread, 3 oz of deli turkey and 1 Tbs of reduced fat mayo) and to remember to record drinks and condiments. Participants emailed, faxed or called in diaries each day to ensure they were completed on time. At the laboratory session, study staff reviewed the food diaries with the participant and queried for missing foods and components (e.g. cream in coffee, drinks, condiments, cooking with oil or other missed foods). Food diaries were analyzed using the Food Processor software (ESHA, Inc, Salem, OR). For foods that were not in the database, they were looked up on company or restaurant websites. If caloric information was not available, the closest substitute was used. Total daily caloric intake, grams of protein, fat and carbohydrates each day was computed and averaged. Meal frequency was calculated as the number of eating occasions each day, with an eating occasion defined as >50 calories consumed >30 minutes after the previous meal or snack.
Author Manuscript
Physical activity—Physical Activity was assessed using the Sensewear Pro armband monitor (Bodymedia Inc., Pittsburgh, PA). The Sensewear monitor estimates physical activity and energy expenditure using several sensors including a 3 axis accelerometer, heat flux sensor, skin temperature sensor, near body ambient temperature sensor and galvanic skin response sensor). The Sensewear monitor has demonstrated accuracy and reliability for physical activity assessment.36–38 Physical activity values were calculated using Sensewear Professional software (Version 8.1). Sensewear recordings were considered valid if participants had at least 3 days of recording with ≥ 18 hours of wear time each day. Statistical Analyses
Author Manuscript
Data were analyzed using SPSS (Version 22, IBM Inc., Chicago, IL). First, sample characteristics were calculated using means (SD) and frequencies. Next, we calculated Pearson correlations to examine associations between circadian timing and alignment with sleep characteristics, age and evening light exposure. We also used t-tests to evaluate sex differences in circadian timing and alignment. Next we conducted multivariable regression models predicting BMI, body fat, dietary intake and physical activity controlling for potentially confounding variables, age, sex and sleep duration. Models predicting diet variables were also adjusted for BMI. Both circadian timing and alignment were entered into the each model. Due to known sex differences in body fat39, circadian timing and alignment22, we conducted exploratory analyses testing for interactions with sex. There was one outlier for phase angle (phase angle −2.0 hours, which indicates DLMO occurred 2 hours after sleep onset). We examined the actigraphy data from this participant which indicated a sleep pattern consistent with study entry criteria and there was no clear
Int J Obes (Lond). Author manuscript; available in PMC 2017 April 30.
Baron et al.
Page 7
Author Manuscript
behavioral reason why sleep onset was before DLMO (e.g., shift work). We then conducted our regression analyses with and without this participant and results were similar. Therefore data from this participant is included our analyses. Statistical significance was defined as p
Int J Obes (Lond). Author manuscript; available in PMC 2017 April 30. Published in final edited form as: Int J Obes (Lond). 2017 February ; 41(2): 203–209. doi:10.1038/ijo.2016.194.
Circadian timing and alignment in healthy adults: associations with BMI, body fat, caloric intake and physical activity KG Baron1, KJ Reid2, T Kim2, L Van Horn3, H Attarian2, L Wolfe2, J Siddique3, G Santostasi2, and PC Zee2 1Department
of Behavioral Sciences, Section of Sleep Disorders and Sleep Research, Rush University Medical Center
Author Manuscript
2Center
for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine
3Department
of Preventive Medicine, Northwestern University Feinberg School of Medicine
Abstract
Author Manuscript
Introduction—Disruption of circadian rhythms is one of the proposed mechanisms linking late sleep timing to obesity risk but few studies have evaluated biological markers outside of the laboratory. The goal of this study was to determine the relationship between the timing and alignment of melatonin and sleep onset (phase angle) with BMI, body fat and obesity related behaviors. We hypothesized that circadian alignment (relationship of melatonin to sleep timing) rather than circadian (melatonin) timing would be associated with higher BMI, body fat, dietary intake and lower physical activity. Subjects/Methods—Adults with sleep duration ≥6.5 hours completed 7 days of wrist actigraphy, food diaries and SenseWear arm band monitoring. Circadian timing, measured by dim light melatonin onset (DLMO) was measured in the clinical research unit. Circadian alignment was calculated as the duration between dim light melatonin onset and average sleep onset time in the prior week (phase angle). Body fat was evaluated using dual-energy absorptiometry (DXA). Data were analyzed using bivariate correlations and multivariable regression analyses controlling for age, sex, sleep duration and evening light exposure.
Author Manuscript
Results—Participants included 97 adults (61 F, age 26.8 ± 7.3 years) with average sleep duration 443.7 (SD= 50.4) minutes. Average phase angle was 2.2 hours (SD= 1.5). Circadian alignment was associated with circadian timing (p300 mg per day, smoking, pregnancy or the desire to become pregnant during the study period.
Int J Obes (Lond). Author manuscript; available in PMC 2017 April 30.
Baron et al.
Page 4
Procedure
Author Manuscript
Screening procedures—Prospective participants first completed an initial web or telephone screening to screen for self-reported short sleep duration, comorbid conditions and health behaviors (smoking, alcohol and substance use). Next, potential participants attended an in-person screening visit. During this visit, they completed questionnaires and then one night of home sleep apnea screening and 7 days of actigraphy to determine if they met study criteria. After screening actigraphy and apnea screening data were reviewed, eligible participants were scheduled for one night in the Clinical Research Unit for melatonin assessment and DXA.
Author Manuscript
Pre-laboratory procedures—Participants completed 7 days of actigraphy, sleep and food diaries prior to the laboratory session. Participants were asked to keep their habitual bedtimes and wake times at screening stable, within ± 1 hour of their average at screening times.
Author Manuscript
Laboratory session—Participants arrived at approximately 1:00 PM. After admission, participants underwent a history and physical exam by a sleep medicine physician and female participants underwent a urine pregnancy screening. Then, participants completed a Dual-energy X-ray Absorptiometry (DXA) tissue measurement to assess body fat. Bedtime, wake time and blood sampling times were determined based on habitual bedtime. Circadian time 0 (CT 0) was determined by average sleep onset time plus 8 hours because participants were not required to spend 8 hours in bed in the week prior to the CRU visit. The lights were dimmed to 5 on the Apnea Link recording were excluded from the study.
Author Manuscript
Subjective Sleep quality—Subjective sleep quality was measured by the the Pittsburgh Sleep Quality Questionnaire (PSQI).34 This measure assesses self-reported sleep quality and disturbances over a one-month time interval. A higher PSQI global score indicates greater sleep disturbance. Scores ≥5 are associated with clinically significant sleep disturbance.34 Subscores of the PSQI include sleep duration, sleep disturbance, sleep latency, daytime dysfunction, habitual sleep efficiency, sleep quality and medication use. Sleep—Sleep/wake patterns were estimated using 7 days of wrist actigraphy at screening and before the laboratory session using the Actiwatch Spectrum (Philips/Respironics, Inc, Bend, OR). Actiwatches were worn on the non-dominant wrist and set with 30 second epoch length and medium sensitivity. Actigraphic sleep parameters were calculated using Actiware-Sleep 6.0 software with default settings and included the following variables: sleep onset time, sleep offset time and sleep duration. Sleep diary based measures of bedtime and wake time were manually entered in Actiware and used in scoring. Off wrist time was excluded based on the Spectrum’s off wrist detection. A day was not considered valid if there was any off-wrist time during the sleep period reported on the sleep diary. In order to be included in analyses, participants needed at least 5 days of valid actigraphy data.
Author Manuscript
Evening light exposure—White light exposure was measured using the Actiwatch Spectrum (Philips/Respironics, Inc, Bend, OR). We calculated evening light exposure as the sum of white light exposure (lux) in the 3 hours prior to bedtime on each day of recording and averaged over the valid recording days.
Author Manuscript
Circadian timing (DLMO)—Plasma melatonin levels were assayed using a commercially available radioimmunoassay for the in-vitro diagnostic quantitative determination of melatonin from IBL (IBL International GmbH, Hamburg, Germany). Lower limit of this assay is 3.5 kg/mL and upper limit is 281 pg/mL. After blood draws, samples were centrifuged, aliquoted and stored at −70 F until assayed. All melatonin profiles were first visually inspected. Dim light melatonin onset was determined using 2 SD above the baseline + 15% of the 3 highest values.35 Circadian alignment (also known as phase angle) was calculated as the duration of time between DLMO to average sleep onset time recorded on actigraphy during the prior 7 days. Body Mass index—Body Mass Index (kg/m2) was calculated using measurements from the laboratory session: height measured at admission by nursing and weight taken in light clothing, without eating or drinking after the morning void.
Int J Obes (Lond). Author manuscript; available in PMC 2017 April 30.
Baron et al.
Page 6
Author Manuscript
Body fat and body fat distribution—Body Fat was measured using DXA on a whole body Hologic scanner (Version 13.1). Body fat values were calculated for total body fat mass, trunk fat mass, android and gynoid regions using automated calculations provided by Hologic. Values were calculated for total body fat % and the gynoid/android ratio, a measure of central adiposity.
Author Manuscript
Dietary Intake—Participants completed 7 days of written food diaries during the week before the laboratory assessment. On the food diaries, participants recorded time, location, type of food, amount consumed and a description of each component including brands and restaurant names. Participants were instructed to break down foods into component parts (e.g. turkey sandwich= 2 slices of white bread, 3 oz of deli turkey and 1 Tbs of reduced fat mayo) and to remember to record drinks and condiments. Participants emailed, faxed or called in diaries each day to ensure they were completed on time. At the laboratory session, study staff reviewed the food diaries with the participant and queried for missing foods and components (e.g. cream in coffee, drinks, condiments, cooking with oil or other missed foods). Food diaries were analyzed using the Food Processor software (ESHA, Inc, Salem, OR). For foods that were not in the database, they were looked up on company or restaurant websites. If caloric information was not available, the closest substitute was used. Total daily caloric intake, grams of protein, fat and carbohydrates each day was computed and averaged. Meal frequency was calculated as the number of eating occasions each day, with an eating occasion defined as >50 calories consumed >30 minutes after the previous meal or snack.
Author Manuscript
Physical activity—Physical Activity was assessed using the Sensewear Pro armband monitor (Bodymedia Inc., Pittsburgh, PA). The Sensewear monitor estimates physical activity and energy expenditure using several sensors including a 3 axis accelerometer, heat flux sensor, skin temperature sensor, near body ambient temperature sensor and galvanic skin response sensor). The Sensewear monitor has demonstrated accuracy and reliability for physical activity assessment.36–38 Physical activity values were calculated using Sensewear Professional software (Version 8.1). Sensewear recordings were considered valid if participants had at least 3 days of recording with ≥ 18 hours of wear time each day. Statistical Analyses
Author Manuscript
Data were analyzed using SPSS (Version 22, IBM Inc., Chicago, IL). First, sample characteristics were calculated using means (SD) and frequencies. Next, we calculated Pearson correlations to examine associations between circadian timing and alignment with sleep characteristics, age and evening light exposure. We also used t-tests to evaluate sex differences in circadian timing and alignment. Next we conducted multivariable regression models predicting BMI, body fat, dietary intake and physical activity controlling for potentially confounding variables, age, sex and sleep duration. Models predicting diet variables were also adjusted for BMI. Both circadian timing and alignment were entered into the each model. Due to known sex differences in body fat39, circadian timing and alignment22, we conducted exploratory analyses testing for interactions with sex. There was one outlier for phase angle (phase angle −2.0 hours, which indicates DLMO occurred 2 hours after sleep onset). We examined the actigraphy data from this participant which indicated a sleep pattern consistent with study entry criteria and there was no clear
Int J Obes (Lond). Author manuscript; available in PMC 2017 April 30.
Baron et al.
Page 7
Author Manuscript
behavioral reason why sleep onset was before DLMO (e.g., shift work). We then conducted our regression analyses with and without this participant and results were similar. Therefore data from this participant is included our analyses. Statistical significance was defined as p
