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Habitual sleep duration and sleep duration variation are independently associated with body mass index
Background: Sleep plays a vital role in maintaining homeostasis and promoting health. Previous studies show that shorter sleep duration is associated with elevated body mass index (BMI) and other cardiovascular risk factors. The goal of this study was to investigate the effects of habitual sleep dur...
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| Published in: | International Journal of Obesity 2018-04, Vol.42 (4), p.794-800 |
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| Main Authors: | , , , , , |
| Format: | Article |
| Language: | English |
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| cited_by | cdi_FETCH-LOGICAL-c455t-27c352ca5a6480622c2d63d436008db1a5edc656aca811d31f247392f9f57fa83 |
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| cites | cdi_FETCH-LOGICAL-c455t-27c352ca5a6480622c2d63d436008db1a5edc656aca811d31f247392f9f57fa83 |
| container_end_page | 800 |
| container_issue | 4 |
| container_start_page | 794 |
| container_title | International Journal of Obesity |
| container_volume | 42 |
| creator | Xu, X Conomos, M P Manor, O Rohwer, J E Magis, A T Lovejoy, J C |
| description | Background:
Sleep plays a vital role in maintaining homeostasis and promoting health. Previous studies show that shorter sleep duration is associated with elevated body mass index (BMI) and other cardiovascular risk factors. The goal of this study was to investigate the effects of habitual sleep duration and nightly sleep duration variation based on daily device-recorded data on BMI and obesity-related biomarkers.
Methods:
In all, 748 individuals (50.6% females, 85.4% European-Americans, average age: 49.7 years old) participated in a commercial lifestyle coaching program beginning in July 2015. Daily sleep data were recorded by Fitbit Charge HR wristbands. Clinical laboratory blood tests were measured up to three times over a 12-month period. Linear regression models were used for cross-sectional analyses, and generalized estimating equations for longitudinal analyses. All models were adjusted for age, sex, geographic location, season, genetic ancestry inferred from whole genome sequencing data, and BMI (if applicable). Multiple testing issues were corrected by false discovery rate.
Results:
We calculated habitual sleep duration and nightly sleep duration variation. In general, females slept 15-min longer on average than males. A negative correlation was found between habitual sleep duration and BMI (
β
=−1.12, standard error=0.25,
P |
| doi_str_mv | 10.1038/ijo.2017.223 |
| format | article |
| fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_1938187493</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A539615726</galeid><sourcerecordid>A539615726</sourcerecordid><originalsourceid>FETCH-LOGICAL-c455t-27c352ca5a6480622c2d63d436008db1a5edc656aca811d31f247392f9f57fa83</originalsourceid><addsrcrecordid>eNptkd1rFDEUxYModlt981kGBOmDs-Zjksk8lqJWKPRFn0M2uelmySRrMqPuf2_W3VpbSiCBe373cG8OQm8IXhLM5Ee_SUuKSb-klD1DC9L1ouXd0D9HC8xw32Iu-Ak6LWWDMeYc05fohEo5cC75ArkrvfLTrENTAsC2sXPWk0-x0dE-Lv3U2R_FDI2PFrZQrziFXaNLSaaqYJtfflo3q2R3zVirf7nfr9ALp0OB18f3DH3__Onb5VV7ffPl6-XFdWs6zqeW9oZxajTXopNYUGqoFcx2TGAs7YpoDtYILrTRkhDLiKNdzwbqBsd7pyU7Q-cH321OP2Yokxp9MRCCjpDmosjAJJF9N7CKvnuEbtKcY51OUdwRgaXgwz11qwMoH12asjZ7U3XB2SAI76mo1PIJqh4LozcpgvO1_qDh_X8Na9BhWpcU5v3vlofghwNociolg1Pb7Eedd4pgtc9f1fzVPn9V86_42-NS82oE-w--C7wC7QEoVYq3kO-3ftLwD7K2uCA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2041608659</pqid></control><display><type>article</type><title>Habitual sleep duration and sleep duration variation are independently associated with body mass index</title><source>Springer Nature</source><source>Nature</source><source>Alma/SFX Local Collection</source><creator>Xu, X ; Conomos, M P ; Manor, O ; Rohwer, J E ; Magis, A T ; Lovejoy, J C</creator><creatorcontrib>Xu, X ; Conomos, M P ; Manor, O ; Rohwer, J E ; Magis, A T ; Lovejoy, J C</creatorcontrib><description>Background:
Sleep plays a vital role in maintaining homeostasis and promoting health. Previous studies show that shorter sleep duration is associated with elevated body mass index (BMI) and other cardiovascular risk factors. The goal of this study was to investigate the effects of habitual sleep duration and nightly sleep duration variation based on daily device-recorded data on BMI and obesity-related biomarkers.
Methods:
In all, 748 individuals (50.6% females, 85.4% European-Americans, average age: 49.7 years old) participated in a commercial lifestyle coaching program beginning in July 2015. Daily sleep data were recorded by Fitbit Charge HR wristbands. Clinical laboratory blood tests were measured up to three times over a 12-month period. Linear regression models were used for cross-sectional analyses, and generalized estimating equations for longitudinal analyses. All models were adjusted for age, sex, geographic location, season, genetic ancestry inferred from whole genome sequencing data, and BMI (if applicable). Multiple testing issues were corrected by false discovery rate.
Results:
We calculated habitual sleep duration and nightly sleep duration variation. In general, females slept 15-min longer on average than males. A negative correlation was found between habitual sleep duration and BMI (
β
=−1.12, standard error=0.25,
P
<0.001). Moreover, we identified a positive correlation between sleep duration variation and BMI (
β
=2.97, standard error=0.79,
P
<0.001) while controlling for sleep duration, indicating that larger sleep duration variation is significantly and independently associated with increased BMI.
Conclusions:
We explored the impact of habitual sleep duration and sleep duration variation, and identified that shorter habitual sleep duration and larger duration variation were independently associated with increased BMI.</description><identifier>ISSN: 0307-0565</identifier><identifier>EISSN: 1476-5497</identifier><identifier>DOI: 10.1038/ijo.2017.223</identifier><identifier>PMID: 28895585</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>692/499 ; 692/700/478/174 ; Biomarkers ; Body mass index ; Body size ; Cardiovascular diseases ; Epidemiology ; Females ; Gene sequencing ; Genomes ; Health aspects ; Health promotion ; Health Promotion and Disease Prevention ; Health risks ; Homeostasis ; Internal Medicine ; Mathematical analysis ; Mathematical models ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Obesity ; original-article ; Public Health ; Regression analysis ; Regression models ; Risk analysis ; Risk factors ; Sleep ; Sleep deprivation ; Standard error</subject><ispartof>International Journal of Obesity, 2018-04, Vol.42 (4), p.794-800</ispartof><rights>Macmillan Publishers Limited, part of Springer Nature. 2018</rights><rights>COPYRIGHT 2018 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Apr 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c455t-27c352ca5a6480622c2d63d436008db1a5edc656aca811d31f247392f9f57fa83</citedby><cites>FETCH-LOGICAL-c455t-27c352ca5a6480622c2d63d436008db1a5edc656aca811d31f247392f9f57fa83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28895585$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xu, X</creatorcontrib><creatorcontrib>Conomos, M P</creatorcontrib><creatorcontrib>Manor, O</creatorcontrib><creatorcontrib>Rohwer, J E</creatorcontrib><creatorcontrib>Magis, A T</creatorcontrib><creatorcontrib>Lovejoy, J C</creatorcontrib><title>Habitual sleep duration and sleep duration variation are independently associated with body mass index</title><title>International Journal of Obesity</title><addtitle>Int J Obes</addtitle><addtitle>Int J Obes (Lond)</addtitle><description>Background:
Sleep plays a vital role in maintaining homeostasis and promoting health. Previous studies show that shorter sleep duration is associated with elevated body mass index (BMI) and other cardiovascular risk factors. The goal of this study was to investigate the effects of habitual sleep duration and nightly sleep duration variation based on daily device-recorded data on BMI and obesity-related biomarkers.
Methods:
In all, 748 individuals (50.6% females, 85.4% European-Americans, average age: 49.7 years old) participated in a commercial lifestyle coaching program beginning in July 2015. Daily sleep data were recorded by Fitbit Charge HR wristbands. Clinical laboratory blood tests were measured up to three times over a 12-month period. Linear regression models were used for cross-sectional analyses, and generalized estimating equations for longitudinal analyses. All models were adjusted for age, sex, geographic location, season, genetic ancestry inferred from whole genome sequencing data, and BMI (if applicable). Multiple testing issues were corrected by false discovery rate.
Results:
We calculated habitual sleep duration and nightly sleep duration variation. In general, females slept 15-min longer on average than males. A negative correlation was found between habitual sleep duration and BMI (
β
=−1.12, standard error=0.25,
P
<0.001). Moreover, we identified a positive correlation between sleep duration variation and BMI (
β
=2.97, standard error=0.79,
P
<0.001) while controlling for sleep duration, indicating that larger sleep duration variation is significantly and independently associated with increased BMI.
Conclusions:
We explored the impact of habitual sleep duration and sleep duration variation, and identified that shorter habitual sleep duration and larger duration variation were independently associated with increased BMI.</description><subject>692/499</subject><subject>692/700/478/174</subject><subject>Biomarkers</subject><subject>Body mass index</subject><subject>Body size</subject><subject>Cardiovascular diseases</subject><subject>Epidemiology</subject><subject>Females</subject><subject>Gene sequencing</subject><subject>Genomes</subject><subject>Health aspects</subject><subject>Health promotion</subject><subject>Health Promotion and Disease Prevention</subject><subject>Health risks</subject><subject>Homeostasis</subject><subject>Internal Medicine</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolic Diseases</subject><subject>Obesity</subject><subject>original-article</subject><subject>Public Health</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Sleep</subject><subject>Sleep deprivation</subject><subject>Standard error</subject><issn>0307-0565</issn><issn>1476-5497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNptkd1rFDEUxYModlt981kGBOmDs-Zjksk8lqJWKPRFn0M2uelmySRrMqPuf2_W3VpbSiCBe373cG8OQm8IXhLM5Ee_SUuKSb-klD1DC9L1ouXd0D9HC8xw32Iu-Ak6LWWDMeYc05fohEo5cC75ArkrvfLTrENTAsC2sXPWk0-x0dE-Lv3U2R_FDI2PFrZQrziFXaNLSaaqYJtfflo3q2R3zVirf7nfr9ALp0OB18f3DH3__Onb5VV7ffPl6-XFdWs6zqeW9oZxajTXopNYUGqoFcx2TGAs7YpoDtYILrTRkhDLiKNdzwbqBsd7pyU7Q-cH321OP2Yokxp9MRCCjpDmosjAJJF9N7CKvnuEbtKcY51OUdwRgaXgwz11qwMoH12asjZ7U3XB2SAI76mo1PIJqh4LozcpgvO1_qDh_X8Na9BhWpcU5v3vlofghwNociolg1Pb7Eedd4pgtc9f1fzVPn9V86_42-NS82oE-w--C7wC7QEoVYq3kO-3ftLwD7K2uCA</recordid><startdate>20180401</startdate><enddate>20180401</enddate><creator>Xu, X</creator><creator>Conomos, M P</creator><creator>Manor, O</creator><creator>Rohwer, J E</creator><creator>Magis, A T</creator><creator>Lovejoy, J C</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T2</scope><scope>7TK</scope><scope>7TS</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20180401</creationdate><title>Habitual sleep duration and sleep duration variation are independently associated with body mass index</title><author>Xu, X ; Conomos, M P ; Manor, O ; Rohwer, J E ; Magis, A T ; Lovejoy, J C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c455t-27c352ca5a6480622c2d63d436008db1a5edc656aca811d31f247392f9f57fa83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>692/499</topic><topic>692/700/478/174</topic><topic>Biomarkers</topic><topic>Body mass index</topic><topic>Body size</topic><topic>Cardiovascular diseases</topic><topic>Epidemiology</topic><topic>Females</topic><topic>Gene sequencing</topic><topic>Genomes</topic><topic>Health aspects</topic><topic>Health promotion</topic><topic>Health Promotion and Disease Prevention</topic><topic>Health risks</topic><topic>Homeostasis</topic><topic>Internal Medicine</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolic Diseases</topic><topic>Obesity</topic><topic>original-article</topic><topic>Public Health</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Sleep</topic><topic>Sleep deprivation</topic><topic>Standard error</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, X</creatorcontrib><creatorcontrib>Conomos, M P</creatorcontrib><creatorcontrib>Manor, O</creatorcontrib><creatorcontrib>Rohwer, J E</creatorcontrib><creatorcontrib>Magis, A T</creatorcontrib><creatorcontrib>Lovejoy, J C</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Physical Education Index</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection (ProQuest Medical & Health Databases)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>ProQuest Psychology Journals</collection><collection>ProQuest Biological Science Journals</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>International Journal of Obesity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, X</au><au>Conomos, M P</au><au>Manor, O</au><au>Rohwer, J E</au><au>Magis, A T</au><au>Lovejoy, J C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Habitual sleep duration and sleep duration variation are independently associated with body mass index</atitle><jtitle>International Journal of Obesity</jtitle><stitle>Int J Obes</stitle><addtitle>Int J Obes (Lond)</addtitle><date>2018-04-01</date><risdate>2018</risdate><volume>42</volume><issue>4</issue><spage>794</spage><epage>800</epage><pages>794-800</pages><issn>0307-0565</issn><eissn>1476-5497</eissn><abstract>Background:
Sleep plays a vital role in maintaining homeostasis and promoting health. Previous studies show that shorter sleep duration is associated with elevated body mass index (BMI) and other cardiovascular risk factors. The goal of this study was to investigate the effects of habitual sleep duration and nightly sleep duration variation based on daily device-recorded data on BMI and obesity-related biomarkers.
Methods:
In all, 748 individuals (50.6% females, 85.4% European-Americans, average age: 49.7 years old) participated in a commercial lifestyle coaching program beginning in July 2015. Daily sleep data were recorded by Fitbit Charge HR wristbands. Clinical laboratory blood tests were measured up to three times over a 12-month period. Linear regression models were used for cross-sectional analyses, and generalized estimating equations for longitudinal analyses. All models were adjusted for age, sex, geographic location, season, genetic ancestry inferred from whole genome sequencing data, and BMI (if applicable). Multiple testing issues were corrected by false discovery rate.
Results:
We calculated habitual sleep duration and nightly sleep duration variation. In general, females slept 15-min longer on average than males. A negative correlation was found between habitual sleep duration and BMI (
β
=−1.12, standard error=0.25,
P
<0.001). Moreover, we identified a positive correlation between sleep duration variation and BMI (
β
=2.97, standard error=0.79,
P
<0.001) while controlling for sleep duration, indicating that larger sleep duration variation is significantly and independently associated with increased BMI.
Conclusions:
We explored the impact of habitual sleep duration and sleep duration variation, and identified that shorter habitual sleep duration and larger duration variation were independently associated with increased BMI.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>28895585</pmid><doi>10.1038/ijo.2017.223</doi><tpages>7</tpages></addata></record> |
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| identifier | ISSN: 0307-0565 |
| ispartof | International Journal of Obesity, 2018-04, Vol.42 (4), p.794-800 |
| issn | 0307-0565 1476-5497 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1938187493 |
| source | Springer Nature; Nature; Alma/SFX Local Collection |
| subjects | 692/499 692/700/478/174 Biomarkers Body mass index Body size Cardiovascular diseases Epidemiology Females Gene sequencing Genomes Health aspects Health promotion Health Promotion and Disease Prevention Health risks Homeostasis Internal Medicine Mathematical analysis Mathematical models Medicine Medicine & Public Health Metabolic Diseases Obesity original-article Public Health Regression analysis Regression models Risk analysis Risk factors Sleep Sleep deprivation Standard error |
| title | Habitual sleep duration and sleep duration variation are independently associated with body mass index |
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