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Original Contribution  |   October 2019
Association Between Sleep and Obesity in African Americans in the Jackson Heart Study
Author Notes
  • From the Jackson Heart Study Graduate Training and Education Center at the School of Public Health (Ms Jefferson and Drs Addison and Jenkins); the Department of Behavioral and Environmental Health (Dr Sharma); and the Institute of Epidemiology and Health Services Research and Center of Excellence in Minority Health (Dr Payton) at Jackson State University in Mississippi. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the US Department of Health and Human Services. 
  • Financial Disclosures: None reported. 
  • Support: The Jackson Heart Study Graduate Training and Education Center is supported by contract HHSN268201300049C. The Jackson Heart Study is supported and conducted in collaboration with Jackson State University (HHSN268201300049C and HHSN268201300050C), Tougaloo College (HHSN268201300048C), and the University of Mississippi Medical Center (HHSN268201300046C and HHSN268201300047C), contracts from the National Heart, Lung, and Blood Institute and the National Institute for Minority Health and Health Disparities. 
  •  *Address correspondence to Trimella Jefferson, MPH, CHES, CPH, Jackson Heart Study Graduate Training and Education Center, 350 W Woodrow Wilson Ave, Suite 2900B, Jackson, MS 39213-7674. Email: trimella.m.jefferson@students.jsums.edu
     
Article Information
Cardiovascular Disorders / Sleep Medicine
Original Contribution   |   October 2019
Association Between Sleep and Obesity in African Americans in the Jackson Heart Study
The Journal of the American Osteopathic Association, October 2019, Vol. 119, 656-666. doi:10.7556/jaoa.2019.113
The Journal of the American Osteopathic Association, October 2019, Vol. 119, 656-666. doi:10.7556/jaoa.2019.113
Abstract

Background: In the United States, data from the National Health and Nutrition Examination Survey suggest that 68% of adults are overweight and obese. Obesity has been shown in previous cross-sectional and longitudinal studies to be influenced by short sleep duration, which can lead to unregulated appetite, excessive eating during awake time, and decreased energy expenditure.

Objective: To examine the associations among sleep duration, sleep quality, body mass index (BMI), and waist circumference (WC) in African Americans.

Methods: The sample included participants in the Jackson Heart Study. During a clinic visit, the sleep habits of participants were recorded via a sleep history questionnaire, and BMI and WC measurements were also recorded. Multivariate analysis was used to examine the associations among sleep duration, sleep quality, general obesity (measured by BMI), and abdominal obesity (measured by WC).

Results: The authors studied participants who provided data for the variables of interest (N=3778; 1363 men and 2415 women). Of all participants, 3317 (87.8%) were overweight, and 2149 (56.9%) were obese. The mean (SD) BMI was 32.1 (7.2) kg/m 2 , and the mean (SD) WC was 103.3 (16.0) cm. Mean sleep duration was 6.3 (1.4) hours for men and 6.4 (1.5) hours for women. Among the men, a significant negative relationship was found between sleep duration and body composition: longer sleep was associated with lower BMI levels but negatively associated with WC in men (β=−1.06; P<.01)]. Sleep quality was positively associated with WC in men (β=1.20; P<.01) and women (β=0.61; P<.05).

Conclusions: This study's findings highlight the high rate of overweight and obesity among participants in the Jackson Heart Study. About one-fourth of the participants described themselves as enjoying ideal health. In men, longer sleep duration was associated with lower BMI levels and lower WC; in both men and women, good sleep quality was associated with lower WC. However, more research is needed to examine sleep and body composition as risk factors for disease development in African Americans.

The chronic, deleterious nature and increasing prevalence of obesity has become a threat to public health and, therefore, is of major concern. According to the World Health Organization, the prevalence of obesity has more than doubled between 1980 and 2014, with more than 1.9 billion adults aged 18 years and older being overweight, of whom more than 600 million were obese in 2014.1 
The prevalence of obesity was approximately 36% among adults and 17% among youth between 2011 and 2014 in the United States.1 Some minority groups are more susceptible to becoming overweight and obese than others. Non-Hispanic blacks have the highest age-adjusted rates of obesity (48.1%) followed by Hispanics (42.5%), non-Hispanic whites (34.5%), and non-Hispanic Asians (11.7%).1 Being overweight and obese has far-ranging negative effects on health and is a leading risk factor for many chronic diseases.1,2 
It has been proposed that shorter sleep may also be a contributor to the obesity epidemic.2-5 Sleep curtailment may affect energy balance and result in weight gain via 3 distinct pathways: unregulated appetite, more time for excessive eating, or a decrease in energy expenditure.3 The National Sleep Foundation recommends 7 to 9 hours of sleep for adults aged 18 to 64 years and 7 to 8 hours of sleep for adults aged 65 years and older.6 According to the 2014 Sleep Health Index, the quality of sleep reported mirrored the health of people in the United States. The higher rates of subjective and objective short (≤5 hours) and long (≥9 hours) sleep duration reported among African Americans is thought to mediate higher rates of cardiovascular disease, diabetes, and obesity among African Americans.2,4 Socioeconomic, social, and environmental factors have been found to contribute to the duration and quality of sleep in African Americans.7 
Patel and Hu8 found a mixed response when validating the association of short sleep duration with a high body mass index (BMI) and waist circumference (WC) in adolescents and young adults. A population-based study of women from the Collaborative Breast Cancer Study found increased odds of overweight (BMI, 25-29.9 kg/m2) and obesity (BMI, 30-39.9 kg/m2) among women who reported short sleep duration and extreme obesity (BMI, ≥40 kg/m2) among women reporting short and long durations of sleep in the recent past.9 A U-shaped association was found between women who were extremely obese who reported both short and long durations of sleep in the recent past (P<.001).9 Short sleep duration contributes to obesity by increasing ghrelin, decreasing leptin, and conceding insulin sensitivity according to findings from the Wisconsin Sleep Cohort Study.5 In a large US sample, significant differences in sleep duration and obesity were found between participants aged 32 to 49 years at baseline; participants differed when stratified by gender.5 However, none of these studies was conducted with an African American population. There is a definitive need to test this hypothesis with an African American population by examining the impact of sleep quality on body mass index (BMI) and WC. The purpose of this study was to examine the association among duration and quality of sleep, BMI, and WC. We hypothesized that after adjusting for covariates, short sleep duration would be associated with a higher BMI and WC in African Americans, with expected variations by gender. 
Methods
The study used data collected from a subset of the 5301 participants in the Jackson Heart Study (JHS), a large-scale prospective, observational, longitudinal study that examines risk factors for cardiovascular disease.10,11 The JHS data, methods, surveys, manuals, and procedures have been reported previously.10-12 Demographic and sociodemographic data were collected from the participants using questionnaires. The JHS cohort is made up of African American men and women aged 21 to 84 years who reside in the Jackson, Mississippi metropolitan area.10,11 A community-based recruitment model used community representatives to facilitate recruitment. The sample included random and volunteer sampling and included participants continuing from the Atherosclerosis Risk in Communities study and family members of selected participants. Details of the recruitment are presented in other studies. Our sample included those participants who provided data for the variables of interest. 
The cross-sectional study analyzed data from JHS Exam 1 and Exam 3 to assess how the duration and quality of sleep related to BMI and WC in African Americans after adjusting for demographic factors (gender, age), socioeconomic factors (educational achievement, household income), behavioral factors (alcohol consumption and physical activity), and psychosocial factors (depressive symptoms). Exam 1 was the baseline induction examination conducted from September 26, 2000, through March 31, 2004. Exam 3, a follow-up examination that added several additional surveys, such as sleep history, was conducted from February 26, 2009, to January 31, 2013. 
Sleep Measures
All sleep measures were derived from the Sleep History Form, a questionnaire completed in Exam 3 during the participant's clinical visit. Sleep duration was assessed through the responses of the participants to the survey item “How much sleep do you usually get at night (or your main sleep period) on weekdays or workdays?” The values were self-recorded in hours and classified into 5 categories (≤5, 6, 7, 8, and ≥9 hours). Sleep quality was assessed through the responses of the participants to the survey item “During the past month, how would you rate your sleep quality overall?” Responses were recorded as follows: excellent (1), very good (2), good (3), fair (4), poor (5), don't know (7), refused (8), missing (9). 
Body Composition Measures
Body mass index was computed using objectively measured height and weight during the participants’ visit to the JHS examination center. Participants with a BMI less than 25 kg/m2 were considered normal weight, those with a BMI between 25 and 29.9 kg/m2 were considered overweight, and those with a BMI of 30 to 39.9 kg/m2 were considered obese. Waist circumference was measured in centimeters; WC greater than 102 cm for men and 88 cm for women determined abdominal obesity, respectively. 
Covariates
The following covariates that are known to affect sleep behaviors as well as health outcomes were also analyzed: demographic, socioeconomic, behavioral, and psychosocial factors. Age was assessed as a continuous variable. Educational level was categorized into 4 groups: college graduate, some college or completion of vocational school, high school/general education diploma, and less than high school. Income was categorized as affluent, upper middle, lower middle, or low. Physical activity was categorized as ideal, intermediate, and poor. Depression was included as a dichotomized variable with categories that included those who felt depressed and those who did not. 
Statistical Analysis
SPSS software (version 25.0, SPSS Inc, IBM) was used for all analyses, and statistical significance was determined at P=.05. Descriptive statistics for continuous variables are presented using mean (SD) and No. (%) for categorical variables. Univariate analyses were computed for all variables stratified by gender using the independent t test or χ2 test as appropriate. Linear regression analyses were computed to examine differences in BMI and WC with sleep duration and sleep quality. Multivariate analysis was used to examine how the potential confounding variables of age, educational achievement, household income, alcohol consumption, physical activity, and depressive symptoms, were associated with BMI and WC in men and women. These analyses were performed in 3 stages: model 1 was unadjusted; model 2 was adjusted for age, income, and physical activity; and model 3 was adjusted for alcohol consumption and depression. 
Results
The sample included 1363 men (36.1%) and 2415 women (63.9%) with a mean (SD) age of 61.9 (11.9) years for men and 63.1 (12.1) years for women. Table 1 summarizes the sample characteristics stratified by gender. Of the study sample, 1450 participants (38.4%) were college graduates, 612 (16.2%) had less than a high school education, 1110 (29.4%) were in the upper middle income category, and 589 participants (15.6%) were in the low income category. A total of 1666 participants (44.1%) consumed alcohol and 2111 (55.9%) did not. Of all participants, 1715 (45.4%) were reported to have the American Heart Association physical activity categorization of low activity, and 933 participants (24.7%) were considered to have ideal activity. The mean sleep duration was 6.3 (1.4) hours for men and 6.4 (1.5) hours for women. Men and women reported their average overall sleep quality as good. Two hundred seventy-five participants (7.3%), with the majority being women (n=208), reported being consistently depressed or down. A substantial number of participants were overweight, and about two-thirds of the women (n=1476) and more than half of the men (n=605) were obese. The overall mean (SD) BMI was 32.1 (7.2) kg/m2 (men, 30.4 [6.3] kg/m2; women, 33.1 [7.5] kg/m2). The overall mean (SD) WC was 103.3 (16.0) cm (men, mean [SD], 104.1 [15.7] cm; women, 102.8 [16.1] cm). 
Table 1.
Characteristics of Jackson Heart Study Variables Stratified by Gender
Characteristics Men (n=1363) FemaleWoman (n=2415) Total (N=3778) P Value
Age, mean (SD), y 61.9 (11.9) 63.1 (12.1) 62.5 (12.1) <.001
Education, No. (%) .030
 College Graduate 518 (38.3) 925 (38.5) 1443 (38.4)
 Some college/completed vocational school 405 (29.9) 690 (28.8) 1095 (29.2)
 High school/GED 204 (15.1) 402 (16.8) 606 (16.1)
 <High school 226 (16.7) 383 (16.0) 609 (16.2)
Income for Family of 4, No. (%)
 Affluent (>$100,000) 418 (35.4) 523 (21.7) 941 (28.5)
 Upper-middle ($50,000-$99,999) 361 (30.6) 612 (28.8) 973 (29.4)
 Lower-middle ($20,000-$34,999) 240 (20.3) 635 (29.9) 875 (26.5)
 Low (<$15, 999) 161 (13.6) 356 (16.7) 517 (15.6) <.001
Alcohol Consumption, No. (%) <.001
 Yes 763 (56.0) 903 (37.4) 1666 (44.1)
 No 599 (44.0) 1512 (62.6) 2111 (55.9)
Physical Activity, No. (%) <.001
 Ideal 406 (29.9) 524 (21.7) 930 (24.7)
 Intermediate 356 (26.2) 771 (32.0) 1127 (29.9)
 Poor 597 (43.9) 1115 (46.3) 1712 (45.4)
Sleep Duration, mean (SD), h 6.3 (1.4) 6.4 (1.5) 6.4 (1.5) .013
Sleep Quality Good, No. (%)= 1281 (94.0) 2220 (91.9) 3501 (97.9) .007
Depressive Symptoms, No. (%)       <.001
 Consistently depressed or down, most of the day, nearly every day, for the past 2 weeks
  Yes 56 (4.3) 208 (9.3) 7.3
  No 1257 (95.7) 2036 (90.7) 92.6
Body Composition Measures        
 BMI, No. (%)       <.001
  <18.5 (underweight) 220 (16.4) 266 (11.3) 11.6  
  18.5-24.9 (healthy) 515 (38.4) 617 (26.2) 30.9
  25-29.9 (overweight) 605 (45.1) 1476 (62.6) 56.9
  ≥30 (obese) 30.4 (6.3) 33.1 (7.5) 32.1 (7.2)
 BMI, mean (SD), kg/m2 104.1 (15.7) 102.8 (16.1) 103.3 (16.0) <.001
 WC, mean (SD), cm 518 (38.3) 925 (38.5) 1443 (38.4) .016

Abbreviations BMI, body mass index; GED, general education development; WC, waist circumference.

Table 1.
Characteristics of Jackson Heart Study Variables Stratified by Gender
Characteristics Men (n=1363) FemaleWoman (n=2415) Total (N=3778) P Value
Age, mean (SD), y 61.9 (11.9) 63.1 (12.1) 62.5 (12.1) <.001
Education, No. (%) .030
 College Graduate 518 (38.3) 925 (38.5) 1443 (38.4)
 Some college/completed vocational school 405 (29.9) 690 (28.8) 1095 (29.2)
 High school/GED 204 (15.1) 402 (16.8) 606 (16.1)
 <High school 226 (16.7) 383 (16.0) 609 (16.2)
Income for Family of 4, No. (%)
 Affluent (>$100,000) 418 (35.4) 523 (21.7) 941 (28.5)
 Upper-middle ($50,000-$99,999) 361 (30.6) 612 (28.8) 973 (29.4)
 Lower-middle ($20,000-$34,999) 240 (20.3) 635 (29.9) 875 (26.5)
 Low (<$15, 999) 161 (13.6) 356 (16.7) 517 (15.6) <.001
Alcohol Consumption, No. (%) <.001
 Yes 763 (56.0) 903 (37.4) 1666 (44.1)
 No 599 (44.0) 1512 (62.6) 2111 (55.9)
Physical Activity, No. (%) <.001
 Ideal 406 (29.9) 524 (21.7) 930 (24.7)
 Intermediate 356 (26.2) 771 (32.0) 1127 (29.9)
 Poor 597 (43.9) 1115 (46.3) 1712 (45.4)
Sleep Duration, mean (SD), h 6.3 (1.4) 6.4 (1.5) 6.4 (1.5) .013
Sleep Quality Good, No. (%)= 1281 (94.0) 2220 (91.9) 3501 (97.9) .007
Depressive Symptoms, No. (%)       <.001
 Consistently depressed or down, most of the day, nearly every day, for the past 2 weeks
  Yes 56 (4.3) 208 (9.3) 7.3
  No 1257 (95.7) 2036 (90.7) 92.6
Body Composition Measures        
 BMI, No. (%)       <.001
  <18.5 (underweight) 220 (16.4) 266 (11.3) 11.6  
  18.5-24.9 (healthy) 515 (38.4) 617 (26.2) 30.9
  25-29.9 (overweight) 605 (45.1) 1476 (62.6) 56.9
  ≥30 (obese) 30.4 (6.3) 33.1 (7.5) 32.1 (7.2)
 BMI, mean (SD), kg/m2 104.1 (15.7) 102.8 (16.1) 103.3 (16.0) <.001
 WC, mean (SD), cm 518 (38.3) 925 (38.5) 1443 (38.4) .016

Abbreviations BMI, body mass index; GED, general education development; WC, waist circumference.

×
A linear regression was calculated to predict BMI based on sleep duration for men and women. Table 2 displays the relationship between sleep duration and BMI, with univariate and multivariate analyses stratified by gender. There was a significant negative relationship between sleep duration and BMI in men (regression coefficient [β]=−0.12; 95% CI, −0.79 to −0.29), but the relationship was not significant in women (β=−0.02; 95% CI, −0.30–0.11). Increased sleep duration was shown to be associated with decreased BMI. After adjusting for demographic and socioeconomic factors (β=−0.09; 95% CI, −0.682 to −0.145) and psychosocial and behavioral factors (β=−0.09; 95% CI, −0.680 to −0.123), sleep duration was negatively associated with BMI in men (P<.05). Sleep duration in the adjusted models was not found to be associated with BMI in women (P>.05). The Figure displays general and abdominal obesity prevalence by sleep duration for men and women. The prevalence of general and abdominal obesity was higher for women, represented in rows, in all sleep duration categories. 
Figure
General and abdominal obesity prevalence by sleep duration for men and women. The prevalence of general and abdominal obesity was higher for women in all sleep duration categories (≤5, 6, 7, 8, and ≥9 hours).
Figure
General and abdominal obesity prevalence by sleep duration for men and women. The prevalence of general and abdominal obesity was higher for women in all sleep duration categories (≤5, 6, 7, 8, and ≥9 hours).
Table 2.
Linear Regression—Relationship between Sleep Duration and Body Mass Index Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep −0.539 0.126 −0.116 −4.291 <.001 −0.095 0.103 −0.019 −0.918 .359
Model 2c
 Sleep −0.414 0.137 −0.088 −3.020 .003 −0.014 0.116 −0.003 −0.119 .906
 Age −0.112 0.016 −0.210 6.991 <.001 −0.153 0.015 −0.235 −10.13 <.001
 Education −0.073 0.069 −0.034 1.059 .290 −0.184 0.068 −0.072 −2.720 .007
 Income 0.098 0.072 0.043 1.356 .175 −0.145 0.069 −0.055 −2.084 .037
Model 3d
 Sleep −0.402 0.142 −0.085 .005 −0.023 0.119 −0.004 −0.195 .845
 Age −0.128 0.017 −0.242 −7.695 <.001 −0.167 0.016 −0.259 −10.37 <.001
 Education −0.042 0.073 −0.020 −0.578 .563 −0.074 0.071 −0.029 −1.046 .296
 Income −0.096 0.076 0.042 1.265 .206 −0.131 0.072 −0.050 −1.807 .071
 Alcohol −1.089 0.381 −0.086 −2.854 .004 −1.310 0.371 −0.085 −3.529 <.001
 Physical Activity −0.426 0.227 −0.058 −1.878 .061 −1.399 0.225 −0.147 −6.224 <.001
 Depression −1.380 0.916 −0.045 −1.507 .132 0.768 0.527 0.033 1.457 .145

a β values reflect difference in BMI for each increased hour of sleep.

b Unadjusted for sleep duration.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

Table 2.
Linear Regression—Relationship between Sleep Duration and Body Mass Index Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep −0.539 0.126 −0.116 −4.291 <.001 −0.095 0.103 −0.019 −0.918 .359
Model 2c
 Sleep −0.414 0.137 −0.088 −3.020 .003 −0.014 0.116 −0.003 −0.119 .906
 Age −0.112 0.016 −0.210 6.991 <.001 −0.153 0.015 −0.235 −10.13 <.001
 Education −0.073 0.069 −0.034 1.059 .290 −0.184 0.068 −0.072 −2.720 .007
 Income 0.098 0.072 0.043 1.356 .175 −0.145 0.069 −0.055 −2.084 .037
Model 3d
 Sleep −0.402 0.142 −0.085 .005 −0.023 0.119 −0.004 −0.195 .845
 Age −0.128 0.017 −0.242 −7.695 <.001 −0.167 0.016 −0.259 −10.37 <.001
 Education −0.042 0.073 −0.020 −0.578 .563 −0.074 0.071 −0.029 −1.046 .296
 Income −0.096 0.076 0.042 1.265 .206 −0.131 0.072 −0.050 −1.807 .071
 Alcohol −1.089 0.381 −0.086 −2.854 .004 −1.310 0.371 −0.085 −3.529 <.001
 Physical Activity −0.426 0.227 −0.058 −1.878 .061 −1.399 0.225 −0.147 −6.224 <.001
 Depression −1.380 0.916 −0.045 −1.507 .132 0.768 0.527 0.033 1.457 .145

a β values reflect difference in BMI for each increased hour of sleep.

b Unadjusted for sleep duration.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

×
A linear regression was calculated to predict WC based on sleep duration for men and women. Sleep duration was negatively associated with WC among men (β=−0.09; 95% CI, −1.68 to −0.44) but not among women (Table 3). In a linear multivariate regression adjusted for demographic and socioeconomic factors (β=−0.09; 95% CI, −1.76 to −0.38) and behavioral and psychosocial factors (β=−0.09; 95% CI, −1.76 to −0.33), sleep duration was negatively associated with WC in men (P<.05). 
Table 3.
Linear Regression—Relationship between Sleep Duration and Waist Circumference Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 1.060 0.314 0.092 3.372 .001 0.104 0.219 0.010 0.476 .634
Model 2
 Sleep −1.071 0.352 −0.091 −3.046 .002 0.092 0.248 0.008 0.369 .712
 Age −0.094 0.041 −0.070 −2.283 .023 −0.144 0.032 −0.105 −4.468 <.001
 Education −0.158 0.177 −0.029 −0.898 .370 −0.561 0.146 −0.103 −3.835 <.001
 Income 0.239 0.186 0.042 1.286 .199 −0.471 0.150 −0.085 −3.140 .002
Model 3d
 Sleep −1.045 0.365 −0.089 −2.860 .004 0.022 0.255 0.002 0.087 .931
 Age −0.133 0.043 −0.100 −3.085 .002 −0.174 0.034 −0.128 5.051 <.001
 Education −0.057 0.187 −0.011 −0.308 .758 −0.290 0.153 −0.054 1.899 .058
 Income 0.241 0.196 0.042 1.228 .220 −0.473 0.156 −0.085 3.023 .003
 Alcohol −2.011 0.983 −0.063 −2.045 .041 −2.684 0.807 −0.081 3.328 .001
 Physical Activity −1.621 0.585 −0.088 −2.769 .006 −2.858 0.488 −0.140 5.861 <.001
 Depression −3.139 2.333 −0.041 −1.345 .179 1.193 1.140 0.024 1.047 .295

a β values reflect difference in WC for each increased hour of sleep.

b Unadjusted for sleep duration.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

Table 3.
Linear Regression—Relationship between Sleep Duration and Waist Circumference Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 1.060 0.314 0.092 3.372 .001 0.104 0.219 0.010 0.476 .634
Model 2
 Sleep −1.071 0.352 −0.091 −3.046 .002 0.092 0.248 0.008 0.369 .712
 Age −0.094 0.041 −0.070 −2.283 .023 −0.144 0.032 −0.105 −4.468 <.001
 Education −0.158 0.177 −0.029 −0.898 .370 −0.561 0.146 −0.103 −3.835 <.001
 Income 0.239 0.186 0.042 1.286 .199 −0.471 0.150 −0.085 −3.140 .002
Model 3d
 Sleep −1.045 0.365 −0.089 −2.860 .004 0.022 0.255 0.002 0.087 .931
 Age −0.133 0.043 −0.100 −3.085 .002 −0.174 0.034 −0.128 5.051 <.001
 Education −0.057 0.187 −0.011 −0.308 .758 −0.290 0.153 −0.054 1.899 .058
 Income 0.241 0.196 0.042 1.228 .220 −0.473 0.156 −0.085 3.023 .003
 Alcohol −2.011 0.983 −0.063 −2.045 .041 −2.684 0.807 −0.081 3.328 .001
 Physical Activity −1.621 0.585 −0.088 −2.769 .006 −2.858 0.488 −0.140 5.861 <.001
 Depression −3.139 2.333 −0.041 −1.345 .179 1.193 1.140 0.024 1.047 .295

a β values reflect difference in WC for each increased hour of sleep.

b Unadjusted for sleep duration.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

×
A linear regression was calculated to predict WC based on sleep quality for men and women (Table 4). Table 5 presents the linear univariate and multivariate regression analysis between sleep quality and WC stratified by gender. In a linear univariate regression, sleep quality was positively associated with WC among men (β=0.08; 95% CI, 0.41-1.99) and women (β=0.04; 95% CI, 0.00-1.22). After adjusting for demographic and socioeconomic factors, sleep quality was positively associated with WC among men (β=0.06; 95% CI, 0.01-1.77). 
Table 4.
Linear Regression—Relationship between Sleep Quality and Body Mass Index Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 0.455 0.160 0.077 2.836 .005 0.269 0.145 0.038 1.849 .065
Model 2c
 Sleep 0.264 0.174 0.044 1.518 .129 0.142 0.158 0.020 0.899 .369
 Age 0.119 0.016 0.223 7.522 <.001 0.152 0.015 0.233 10.057 <.001
 Education 0.071 0.069 0.033 1.034 .301 0.182 0.068 0.071 −2.685 .007
 Income 0.105 0.073 0.046 1.450 .147 0.140 0.070 0.053 −2.003 .045
Model 3d
 Sleep 0.243 0.180 0.041 1.346 .179 0.118 0.165 0.016 0.718 .473
 Age 0.136 0.016 −0.256 −8.242 <.001 −0.167 0.016 −0.258 −10.364 <.001
 Education 0.039 0.073 −0.018 −0.540 .589 −0.072 0.071 −0.028 −1.016 .310
 Income 0.106 0.076 0.046 1.396 .163 −0.128 0.073 −0.049 −1.762 .078
 Alcohol 0.454 0.228 −0.062 −1.995 .046 −1.392 0.225 −0.146 −6.190 <.001
 Physical Activity −1.115 0.383 −0.088 −2.912 .004 −1.321 0.372 −0.086 −3.555 <.001
 Depression −1.427 0.925 −0.046 −1.543 .123 0.805 0.530 0.035 1.520 .129

a β values reflect difference in body mass index for each increased hour of sleep.

b Unadjusted for sleep quality.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

Table 4.
Linear Regression—Relationship between Sleep Quality and Body Mass Index Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 0.455 0.160 0.077 2.836 .005 0.269 0.145 0.038 1.849 .065
Model 2c
 Sleep 0.264 0.174 0.044 1.518 .129 0.142 0.158 0.020 0.899 .369
 Age 0.119 0.016 0.223 7.522 <.001 0.152 0.015 0.233 10.057 <.001
 Education 0.071 0.069 0.033 1.034 .301 0.182 0.068 0.071 −2.685 .007
 Income 0.105 0.073 0.046 1.450 .147 0.140 0.070 0.053 −2.003 .045
Model 3d
 Sleep 0.243 0.180 0.041 1.346 .179 0.118 0.165 0.016 0.718 .473
 Age 0.136 0.016 −0.256 −8.242 <.001 −0.167 0.016 −0.258 −10.364 <.001
 Education 0.039 0.073 −0.018 −0.540 .589 −0.072 0.071 −0.028 −1.016 .310
 Income 0.106 0.076 0.046 1.396 .163 −0.128 0.073 −0.049 −1.762 .078
 Alcohol 0.454 0.228 −0.062 −1.995 .046 −1.392 0.225 −0.146 −6.190 <.001
 Physical Activity −1.115 0.383 −0.088 −2.912 .004 −1.321 0.372 −0.086 −3.555 <.001
 Depression −1.427 0.925 −0.046 −1.543 .123 0.805 0.530 0.035 1.520 .129

a β values reflect difference in body mass index for each increased hour of sleep.

b Unadjusted for sleep quality.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

×
Table 5.
Linear Regression—Relationship between Sleep Quality and Waist Circumference Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 1.204 0.403 0.081 2.990 .003 0.612 0.312 0.040 1.965 .049
Model 2c
 Sleep 0.891 0.448 0.059 1.989 .047 0.334 0.341 0.022 0.979 .328
 Age −0.110 0.041 −0.083 −2.714 .007 −0.139 0.032 −0.102 −4.331 <.001
 Education −0.150 0.177 −0.028 −0.848 .397 −0.555 0.146 −0.102 −3.793 <.001
 Income 0.261 0.187 0.046 1.399 .162 −0.455 0.150 −0.082 −3.025 .003
Model 3d
 Sleep 0.863 0.465 0.057 1.854 .064 0.345 0.356 0.022 0.968 .333
 Age −0.150 0.042 −0.113 −3.529 <.001 −0.171 0.034 −0.126 −4.983 <.001
 Education −0.047 0.187 −0.009 −0.252 .801 −0.283 0.153 −0.052 −1.855 .064
 Income 0.269 0.197 0.047 1.369 .171 −0.462 0.157 −0.083 −2.950 .003
 Alcohol −1.672 0.586 −0.091 −2.851 .004 −2.836 0.488 −0.139 −5.813 <.001
 Physical Activity −2.115 0.986 −0.067 −2.146 .032 −2.705 0.807 −0.082 −3.354 .001
 Depression −3.074 2.355 −0.040 −1.305 .192 1.327 1.145 0.027 1.159 .247

a β values reflect difference in waist circumference for each increased hour of sleep.

b Unadjusted for sleep quality.

Table 5.
Linear Regression—Relationship between Sleep Quality and Waist Circumference Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 1.204 0.403 0.081 2.990 .003 0.612 0.312 0.040 1.965 .049
Model 2c
 Sleep 0.891 0.448 0.059 1.989 .047 0.334 0.341 0.022 0.979 .328
 Age −0.110 0.041 −0.083 −2.714 .007 −0.139 0.032 −0.102 −4.331 <.001
 Education −0.150 0.177 −0.028 −0.848 .397 −0.555 0.146 −0.102 −3.793 <.001
 Income 0.261 0.187 0.046 1.399 .162 −0.455 0.150 −0.082 −3.025 .003
Model 3d
 Sleep 0.863 0.465 0.057 1.854 .064 0.345 0.356 0.022 0.968 .333
 Age −0.150 0.042 −0.113 −3.529 <.001 −0.171 0.034 −0.126 −4.983 <.001
 Education −0.047 0.187 −0.009 −0.252 .801 −0.283 0.153 −0.052 −1.855 .064
 Income 0.269 0.197 0.047 1.369 .171 −0.462 0.157 −0.083 −2.950 .003
 Alcohol −1.672 0.586 −0.091 −2.851 .004 −2.836 0.488 −0.139 −5.813 <.001
 Physical Activity −2.115 0.986 −0.067 −2.146 .032 −2.705 0.807 −0.082 −3.354 .001
 Depression −3.074 2.355 −0.040 −1.305 .192 1.327 1.145 0.027 1.159 .247

a β values reflect difference in waist circumference for each increased hour of sleep.

b Unadjusted for sleep quality.

×
Discussion
This study examined the relationship between sleep duration, sleep quality, and general obesity, measured by BMI, and abdominal obesity, measured by WC, in African Americans in the JHS. Sleep quality was positively associated with WC among men and women. Since the literature has recorded BMI as strongly correlated to metabolic and disease outcomes, and the mean BMI puts the JHS cohort in the obesity range, increased community intervention strategies are warranted. According to the literature, WC is also associated with increased health risks, particularly, heart disease, diabetes, and high blood pressure; the men and women in the JHS have WC measurements that exceed the normal range. This finding highlights the need for immediate intervention, such as community groups who operate with a focus on reducing health disparities and with the intention of reducing cardiovascular disease. The fact that sleep behaviors affect obesity, which is detrimental to health, supports the osteopathic tenet: structure and function are reciprocally interrelated.13 
The average sleep duration of men and women in the JHS is less than the recommended amount. The findings from this study depict a significant negative relationship between sleep duration and body composition (BMI and WC) in men, which is in contrast to findings from the Cardia Study,14 which examined gender differences in sleep duration and body composition in whites and African Americans and concluded that sleep duration may have a greater influence on women's body composition than men's. In addition, the Sleep and Health in Women study15 assessed the sleep duration, sleep stages, and central obesity in women and found significant negative associations between sleep duration and central obesity after adjusting for BMI. The current study did not find any relationship between sleep duration and body composition in women. The Nurses’ Health Study,16 a cohort of married, middle-aged women in the nursing profession, found that over a 16-year period, women who slept 5 hours or less gained 1.14 kg. They also found that women who slept 6 hours gained 0.71 kg more than women who slept 7 hours. Meyer et al17 found the prevalence of overweight (BMI, ≥25) and obesity (BMI, ≥30) among men to be inversely associated with sleep duration and a positive, statistically significant association in women between mean BMI and trouble falling or staying asleep. Park et al18 also found the inverse log relationship in men between sleep and general obesity. A population-based study that examined the relationship between recent and lifetime sleep in women via a telephone interview determined that women who were obese (BMI, 30-39.9 kg/m2) and severely obese (BMI, ≥40 kg/m2) were more likely to report shorter sleep durations in the recent past and over their lifetime.9 In a Chinese population, persons who were overweight and obese as defined by the Ministry of Health and Welfare in Taiwan had an increased risk of 40% to 60%, respectively, of being poor sleepers.19 Reportedly, African Americans have more short and long sleep durations.4,20 Furthermore, sleep duration has been shown to mitigate the risk of symptoms of cardiovascular disease, type 2 diabetes mellitus, and high blood pressure in African Americans.4,21,22 
The results of the current study did not reveal any relationship between sleep quality and BMI. The conclusions regarding the mechanisms between sleep and both general and abdominal obesity still have not been completely elucidated. A combination of factors are thought to contribute to the amount of sleep a person receives, including environmental, physiologic, and biological processes. Duration of sleep may further influence lifestyle habits. Certain neuroendocrine functions have been implicated in the varying effects sleep duration has on obesity across age groups.23 Short sleep may cause a person to feel sleepy during the day and unconsciously begin a cycle of physical inactivity and weight gain.16,24 As indicated in Healthy People 2020,25 adequate sleep is needed to support metabolism, fight off infection, and perform efficiently; sleep loss and untreated sleep disorders negatively affect interpersonal relationships and family health. Differences in women can be explained by hormonal levels,18 biological processes, and physical changes in puberty, menstruation, pregnancy/lactation, and menopause26,27 and dietary intake,17 which are often accompanied by sleep disturbances and sleep disorders. Krishnan and Collop26 found women to have more sleep-related complaints than men, although they had better sleep quality with longer sleep times, shorter sleep onset latency, and higher sleep efficiency. 
The large, robust dataset of African Americans in the JHS was a major strength to the analyses conducted in this study. Unfortunately, sleep data were collected in only one exam; therefore, it is a limitation of the study because temporal relationships cannot be established. There are other limitations of the work to be considered. For instance, all measures of sleep were based on the sleep history questionnaire and is, therefore, subject to recall basis. Cardiometabolic risk factors that may have influence on weight gain were not considered. Also, the sample was composed of more women than men. 
Conclusion
A large percentage of the Jackson Heart Study participants in the current study were obese and overweight. About one-fourth of the participants described themselves as enjoying ideal health. In men, longer duration of sleep was associated with lower BMI levels but higher WC. Sleep quality was not associated with BMI in either men or women. Sleep quality was positively associated with WC in men and women. However, more research is needed to examine sleep as a risk factor for disease development and the effect of sleeping habits on health in the African American population. The study points to the need for designing more interventions for improving both sleep quality and quantity in all populations. 
Acknowledgments
We thank the staff and participants of the Jackson Heart Study. 
References
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Figure
General and abdominal obesity prevalence by sleep duration for men and women. The prevalence of general and abdominal obesity was higher for women in all sleep duration categories (≤5, 6, 7, 8, and ≥9 hours).
Figure
General and abdominal obesity prevalence by sleep duration for men and women. The prevalence of general and abdominal obesity was higher for women in all sleep duration categories (≤5, 6, 7, 8, and ≥9 hours).
Table 1.
Characteristics of Jackson Heart Study Variables Stratified by Gender
Characteristics Men (n=1363) FemaleWoman (n=2415) Total (N=3778) P Value
Age, mean (SD), y 61.9 (11.9) 63.1 (12.1) 62.5 (12.1) <.001
Education, No. (%) .030
 College Graduate 518 (38.3) 925 (38.5) 1443 (38.4)
 Some college/completed vocational school 405 (29.9) 690 (28.8) 1095 (29.2)
 High school/GED 204 (15.1) 402 (16.8) 606 (16.1)
 <High school 226 (16.7) 383 (16.0) 609 (16.2)
Income for Family of 4, No. (%)
 Affluent (>$100,000) 418 (35.4) 523 (21.7) 941 (28.5)
 Upper-middle ($50,000-$99,999) 361 (30.6) 612 (28.8) 973 (29.4)
 Lower-middle ($20,000-$34,999) 240 (20.3) 635 (29.9) 875 (26.5)
 Low (<$15, 999) 161 (13.6) 356 (16.7) 517 (15.6) <.001
Alcohol Consumption, No. (%) <.001
 Yes 763 (56.0) 903 (37.4) 1666 (44.1)
 No 599 (44.0) 1512 (62.6) 2111 (55.9)
Physical Activity, No. (%) <.001
 Ideal 406 (29.9) 524 (21.7) 930 (24.7)
 Intermediate 356 (26.2) 771 (32.0) 1127 (29.9)
 Poor 597 (43.9) 1115 (46.3) 1712 (45.4)
Sleep Duration, mean (SD), h 6.3 (1.4) 6.4 (1.5) 6.4 (1.5) .013
Sleep Quality Good, No. (%)= 1281 (94.0) 2220 (91.9) 3501 (97.9) .007
Depressive Symptoms, No. (%)       <.001
 Consistently depressed or down, most of the day, nearly every day, for the past 2 weeks
  Yes 56 (4.3) 208 (9.3) 7.3
  No 1257 (95.7) 2036 (90.7) 92.6
Body Composition Measures        
 BMI, No. (%)       <.001
  <18.5 (underweight) 220 (16.4) 266 (11.3) 11.6  
  18.5-24.9 (healthy) 515 (38.4) 617 (26.2) 30.9
  25-29.9 (overweight) 605 (45.1) 1476 (62.6) 56.9
  ≥30 (obese) 30.4 (6.3) 33.1 (7.5) 32.1 (7.2)
 BMI, mean (SD), kg/m2 104.1 (15.7) 102.8 (16.1) 103.3 (16.0) <.001
 WC, mean (SD), cm 518 (38.3) 925 (38.5) 1443 (38.4) .016

Abbreviations BMI, body mass index; GED, general education development; WC, waist circumference.

Table 1.
Characteristics of Jackson Heart Study Variables Stratified by Gender
Characteristics Men (n=1363) FemaleWoman (n=2415) Total (N=3778) P Value
Age, mean (SD), y 61.9 (11.9) 63.1 (12.1) 62.5 (12.1) <.001
Education, No. (%) .030
 College Graduate 518 (38.3) 925 (38.5) 1443 (38.4)
 Some college/completed vocational school 405 (29.9) 690 (28.8) 1095 (29.2)
 High school/GED 204 (15.1) 402 (16.8) 606 (16.1)
 <High school 226 (16.7) 383 (16.0) 609 (16.2)
Income for Family of 4, No. (%)
 Affluent (>$100,000) 418 (35.4) 523 (21.7) 941 (28.5)
 Upper-middle ($50,000-$99,999) 361 (30.6) 612 (28.8) 973 (29.4)
 Lower-middle ($20,000-$34,999) 240 (20.3) 635 (29.9) 875 (26.5)
 Low (<$15, 999) 161 (13.6) 356 (16.7) 517 (15.6) <.001
Alcohol Consumption, No. (%) <.001
 Yes 763 (56.0) 903 (37.4) 1666 (44.1)
 No 599 (44.0) 1512 (62.6) 2111 (55.9)
Physical Activity, No. (%) <.001
 Ideal 406 (29.9) 524 (21.7) 930 (24.7)
 Intermediate 356 (26.2) 771 (32.0) 1127 (29.9)
 Poor 597 (43.9) 1115 (46.3) 1712 (45.4)
Sleep Duration, mean (SD), h 6.3 (1.4) 6.4 (1.5) 6.4 (1.5) .013
Sleep Quality Good, No. (%)= 1281 (94.0) 2220 (91.9) 3501 (97.9) .007
Depressive Symptoms, No. (%)       <.001
 Consistently depressed or down, most of the day, nearly every day, for the past 2 weeks
  Yes 56 (4.3) 208 (9.3) 7.3
  No 1257 (95.7) 2036 (90.7) 92.6
Body Composition Measures        
 BMI, No. (%)       <.001
  <18.5 (underweight) 220 (16.4) 266 (11.3) 11.6  
  18.5-24.9 (healthy) 515 (38.4) 617 (26.2) 30.9
  25-29.9 (overweight) 605 (45.1) 1476 (62.6) 56.9
  ≥30 (obese) 30.4 (6.3) 33.1 (7.5) 32.1 (7.2)
 BMI, mean (SD), kg/m2 104.1 (15.7) 102.8 (16.1) 103.3 (16.0) <.001
 WC, mean (SD), cm 518 (38.3) 925 (38.5) 1443 (38.4) .016

Abbreviations BMI, body mass index; GED, general education development; WC, waist circumference.

×
Table 2.
Linear Regression—Relationship between Sleep Duration and Body Mass Index Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep −0.539 0.126 −0.116 −4.291 <.001 −0.095 0.103 −0.019 −0.918 .359
Model 2c
 Sleep −0.414 0.137 −0.088 −3.020 .003 −0.014 0.116 −0.003 −0.119 .906
 Age −0.112 0.016 −0.210 6.991 <.001 −0.153 0.015 −0.235 −10.13 <.001
 Education −0.073 0.069 −0.034 1.059 .290 −0.184 0.068 −0.072 −2.720 .007
 Income 0.098 0.072 0.043 1.356 .175 −0.145 0.069 −0.055 −2.084 .037
Model 3d
 Sleep −0.402 0.142 −0.085 .005 −0.023 0.119 −0.004 −0.195 .845
 Age −0.128 0.017 −0.242 −7.695 <.001 −0.167 0.016 −0.259 −10.37 <.001
 Education −0.042 0.073 −0.020 −0.578 .563 −0.074 0.071 −0.029 −1.046 .296
 Income −0.096 0.076 0.042 1.265 .206 −0.131 0.072 −0.050 −1.807 .071
 Alcohol −1.089 0.381 −0.086 −2.854 .004 −1.310 0.371 −0.085 −3.529 <.001
 Physical Activity −0.426 0.227 −0.058 −1.878 .061 −1.399 0.225 −0.147 −6.224 <.001
 Depression −1.380 0.916 −0.045 −1.507 .132 0.768 0.527 0.033 1.457 .145

a β values reflect difference in BMI for each increased hour of sleep.

b Unadjusted for sleep duration.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

Table 2.
Linear Regression—Relationship between Sleep Duration and Body Mass Index Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep −0.539 0.126 −0.116 −4.291 <.001 −0.095 0.103 −0.019 −0.918 .359
Model 2c
 Sleep −0.414 0.137 −0.088 −3.020 .003 −0.014 0.116 −0.003 −0.119 .906
 Age −0.112 0.016 −0.210 6.991 <.001 −0.153 0.015 −0.235 −10.13 <.001
 Education −0.073 0.069 −0.034 1.059 .290 −0.184 0.068 −0.072 −2.720 .007
 Income 0.098 0.072 0.043 1.356 .175 −0.145 0.069 −0.055 −2.084 .037
Model 3d
 Sleep −0.402 0.142 −0.085 .005 −0.023 0.119 −0.004 −0.195 .845
 Age −0.128 0.017 −0.242 −7.695 <.001 −0.167 0.016 −0.259 −10.37 <.001
 Education −0.042 0.073 −0.020 −0.578 .563 −0.074 0.071 −0.029 −1.046 .296
 Income −0.096 0.076 0.042 1.265 .206 −0.131 0.072 −0.050 −1.807 .071
 Alcohol −1.089 0.381 −0.086 −2.854 .004 −1.310 0.371 −0.085 −3.529 <.001
 Physical Activity −0.426 0.227 −0.058 −1.878 .061 −1.399 0.225 −0.147 −6.224 <.001
 Depression −1.380 0.916 −0.045 −1.507 .132 0.768 0.527 0.033 1.457 .145

a β values reflect difference in BMI for each increased hour of sleep.

b Unadjusted for sleep duration.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

×
Table 3.
Linear Regression—Relationship between Sleep Duration and Waist Circumference Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 1.060 0.314 0.092 3.372 .001 0.104 0.219 0.010 0.476 .634
Model 2
 Sleep −1.071 0.352 −0.091 −3.046 .002 0.092 0.248 0.008 0.369 .712
 Age −0.094 0.041 −0.070 −2.283 .023 −0.144 0.032 −0.105 −4.468 <.001
 Education −0.158 0.177 −0.029 −0.898 .370 −0.561 0.146 −0.103 −3.835 <.001
 Income 0.239 0.186 0.042 1.286 .199 −0.471 0.150 −0.085 −3.140 .002
Model 3d
 Sleep −1.045 0.365 −0.089 −2.860 .004 0.022 0.255 0.002 0.087 .931
 Age −0.133 0.043 −0.100 −3.085 .002 −0.174 0.034 −0.128 5.051 <.001
 Education −0.057 0.187 −0.011 −0.308 .758 −0.290 0.153 −0.054 1.899 .058
 Income 0.241 0.196 0.042 1.228 .220 −0.473 0.156 −0.085 3.023 .003
 Alcohol −2.011 0.983 −0.063 −2.045 .041 −2.684 0.807 −0.081 3.328 .001
 Physical Activity −1.621 0.585 −0.088 −2.769 .006 −2.858 0.488 −0.140 5.861 <.001
 Depression −3.139 2.333 −0.041 −1.345 .179 1.193 1.140 0.024 1.047 .295

a β values reflect difference in WC for each increased hour of sleep.

b Unadjusted for sleep duration.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

Table 3.
Linear Regression—Relationship between Sleep Duration and Waist Circumference Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 1.060 0.314 0.092 3.372 .001 0.104 0.219 0.010 0.476 .634
Model 2
 Sleep −1.071 0.352 −0.091 −3.046 .002 0.092 0.248 0.008 0.369 .712
 Age −0.094 0.041 −0.070 −2.283 .023 −0.144 0.032 −0.105 −4.468 <.001
 Education −0.158 0.177 −0.029 −0.898 .370 −0.561 0.146 −0.103 −3.835 <.001
 Income 0.239 0.186 0.042 1.286 .199 −0.471 0.150 −0.085 −3.140 .002
Model 3d
 Sleep −1.045 0.365 −0.089 −2.860 .004 0.022 0.255 0.002 0.087 .931
 Age −0.133 0.043 −0.100 −3.085 .002 −0.174 0.034 −0.128 5.051 <.001
 Education −0.057 0.187 −0.011 −0.308 .758 −0.290 0.153 −0.054 1.899 .058
 Income 0.241 0.196 0.042 1.228 .220 −0.473 0.156 −0.085 3.023 .003
 Alcohol −2.011 0.983 −0.063 −2.045 .041 −2.684 0.807 −0.081 3.328 .001
 Physical Activity −1.621 0.585 −0.088 −2.769 .006 −2.858 0.488 −0.140 5.861 <.001
 Depression −3.139 2.333 −0.041 −1.345 .179 1.193 1.140 0.024 1.047 .295

a β values reflect difference in WC for each increased hour of sleep.

b Unadjusted for sleep duration.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

×
Table 4.
Linear Regression—Relationship between Sleep Quality and Body Mass Index Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 0.455 0.160 0.077 2.836 .005 0.269 0.145 0.038 1.849 .065
Model 2c
 Sleep 0.264 0.174 0.044 1.518 .129 0.142 0.158 0.020 0.899 .369
 Age 0.119 0.016 0.223 7.522 <.001 0.152 0.015 0.233 10.057 <.001
 Education 0.071 0.069 0.033 1.034 .301 0.182 0.068 0.071 −2.685 .007
 Income 0.105 0.073 0.046 1.450 .147 0.140 0.070 0.053 −2.003 .045
Model 3d
 Sleep 0.243 0.180 0.041 1.346 .179 0.118 0.165 0.016 0.718 .473
 Age 0.136 0.016 −0.256 −8.242 <.001 −0.167 0.016 −0.258 −10.364 <.001
 Education 0.039 0.073 −0.018 −0.540 .589 −0.072 0.071 −0.028 −1.016 .310
 Income 0.106 0.076 0.046 1.396 .163 −0.128 0.073 −0.049 −1.762 .078
 Alcohol 0.454 0.228 −0.062 −1.995 .046 −1.392 0.225 −0.146 −6.190 <.001
 Physical Activity −1.115 0.383 −0.088 −2.912 .004 −1.321 0.372 −0.086 −3.555 <.001
 Depression −1.427 0.925 −0.046 −1.543 .123 0.805 0.530 0.035 1.520 .129

a β values reflect difference in body mass index for each increased hour of sleep.

b Unadjusted for sleep quality.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

Table 4.
Linear Regression—Relationship between Sleep Quality and Body Mass Index Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 0.455 0.160 0.077 2.836 .005 0.269 0.145 0.038 1.849 .065
Model 2c
 Sleep 0.264 0.174 0.044 1.518 .129 0.142 0.158 0.020 0.899 .369
 Age 0.119 0.016 0.223 7.522 <.001 0.152 0.015 0.233 10.057 <.001
 Education 0.071 0.069 0.033 1.034 .301 0.182 0.068 0.071 −2.685 .007
 Income 0.105 0.073 0.046 1.450 .147 0.140 0.070 0.053 −2.003 .045
Model 3d
 Sleep 0.243 0.180 0.041 1.346 .179 0.118 0.165 0.016 0.718 .473
 Age 0.136 0.016 −0.256 −8.242 <.001 −0.167 0.016 −0.258 −10.364 <.001
 Education 0.039 0.073 −0.018 −0.540 .589 −0.072 0.071 −0.028 −1.016 .310
 Income 0.106 0.076 0.046 1.396 .163 −0.128 0.073 −0.049 −1.762 .078
 Alcohol 0.454 0.228 −0.062 −1.995 .046 −1.392 0.225 −0.146 −6.190 <.001
 Physical Activity −1.115 0.383 −0.088 −2.912 .004 −1.321 0.372 −0.086 −3.555 <.001
 Depression −1.427 0.925 −0.046 −1.543 .123 0.805 0.530 0.035 1.520 .129

a β values reflect difference in body mass index for each increased hour of sleep.

b Unadjusted for sleep quality.

c Adjusted analyses include age, educational achievement, and household income.

d Adjusted for age, educational achievement, household income, depressive symptoms, physical activity score, and alcohol consumption.

×
Table 5.
Linear Regression—Relationship between Sleep Quality and Waist Circumference Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 1.204 0.403 0.081 2.990 .003 0.612 0.312 0.040 1.965 .049
Model 2c
 Sleep 0.891 0.448 0.059 1.989 .047 0.334 0.341 0.022 0.979 .328
 Age −0.110 0.041 −0.083 −2.714 .007 −0.139 0.032 −0.102 −4.331 <.001
 Education −0.150 0.177 −0.028 −0.848 .397 −0.555 0.146 −0.102 −3.793 <.001
 Income 0.261 0.187 0.046 1.399 .162 −0.455 0.150 −0.082 −3.025 .003
Model 3d
 Sleep 0.863 0.465 0.057 1.854 .064 0.345 0.356 0.022 0.968 .333
 Age −0.150 0.042 −0.113 −3.529 <.001 −0.171 0.034 −0.126 −4.983 <.001
 Education −0.047 0.187 −0.009 −0.252 .801 −0.283 0.153 −0.052 −1.855 .064
 Income 0.269 0.197 0.047 1.369 .171 −0.462 0.157 −0.083 −2.950 .003
 Alcohol −1.672 0.586 −0.091 −2.851 .004 −2.836 0.488 −0.139 −5.813 <.001
 Physical Activity −2.115 0.986 −0.067 −2.146 .032 −2.705 0.807 −0.082 −3.354 .001
 Depression −3.074 2.355 −0.040 −1.305 .192 1.327 1.145 0.027 1.159 .247

a β values reflect difference in waist circumference for each increased hour of sleep.

b Unadjusted for sleep quality.

Table 5.
Linear Regression—Relationship between Sleep Quality and Waist Circumference Stratified by Gender
Variable Men Women
B SE B βa t P Value B SE B βa t P Value
Model 1b
 Sleep 1.204 0.403 0.081 2.990 .003 0.612 0.312 0.040 1.965 .049
Model 2c
 Sleep 0.891 0.448 0.059 1.989 .047 0.334 0.341 0.022 0.979 .328
 Age −0.110 0.041 −0.083 −2.714 .007 −0.139 0.032 −0.102 −4.331 <.001
 Education −0.150 0.177 −0.028 −0.848 .397 −0.555 0.146 −0.102 −3.793 <.001
 Income 0.261 0.187 0.046 1.399 .162 −0.455 0.150 −0.082 −3.025 .003
Model 3d
 Sleep 0.863 0.465 0.057 1.854 .064 0.345 0.356 0.022 0.968 .333
 Age −0.150 0.042 −0.113 −3.529 <.001 −0.171 0.034 −0.126 −4.983 <.001
 Education −0.047 0.187 −0.009 −0.252 .801 −0.283 0.153 −0.052 −1.855 .064
 Income 0.269 0.197 0.047 1.369 .171 −0.462 0.157 −0.083 −2.950 .003
 Alcohol −1.672 0.586 −0.091 −2.851 .004 −2.836 0.488 −0.139 −5.813 <.001
 Physical Activity −2.115 0.986 −0.067 −2.146 .032 −2.705 0.807 −0.082 −3.354 .001
 Depression −3.074 2.355 −0.040 −1.305 .192 1.327 1.145 0.027 1.159 .247

a β values reflect difference in waist circumference for each increased hour of sleep.

b Unadjusted for sleep quality.

×