Evening Chronotype Is Associated with Changes in Eating Behavior, More Sleep Apnea, and Increased Stress Hormones in Short Sleeping Obese Individuals
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{"title"=>"Evening Chronotype Is Associated with Changes in Eating Behavior, More Sleep Apnea, and Increased Stress Hormones in Short Sleeping Obese Individuals", "type"=>"journal", "authors"=>[{"first_name"=>"Eliane A.", "last_name"=>"Lucassen", "scopus_author_id"=>"55189621500"}, {"first_name"=>"Xiongce", "last_name"=>"Zhao", "scopus_author_id"=>"13404944800"}, {"first_name"=>"Kristina I.", "last_name"=>"Rother", "scopus_author_id"=>"35278565200"}, {"first_name"=>"Megan S.", "last_name"=>"Mattingly", "scopus_author_id"=>"54954075200"}, {"first_name"=>"Amber B.", "last_name"=>"Courville", "scopus_author_id"=>"24823838500"}, {"first_name"=>"Lilian", "last_name"=>"de Jonge", "scopus_author_id"=>"7004183637"}, {"first_name"=>"Gyorgy", "last_name"=>"Csako", "scopus_author_id"=>"7005827089"}, {"first_name"=>"Giovanni", "last_name"=>"Cizza", "scopus_author_id"=>"7004614295"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84874633642", "sgr"=>"84874633642", "pui"=>"368465846", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"23483886", "doi"=>"10.1371/journal.pone.0056519"}, "id"=>"b0c4b9b4-71a2-3da7-9e07-1493c23a304e", "abstract"=>"BACKGROUND Short sleep duration and decreased sleep quality are emerging risk factors for obesity and its associated morbidities. Chronotype, an attribute that reflects individual preferences in the timing of sleep and other behaviors, is a continuum from morningness to eveningness. The importance of chronotype in relation to obesity is mostly unknown. Evening types tend to have unhealthy eating habits and suffer from psychological problems more frequently than Morning types, thus we hypothesized that eveningness may affect health parameters in a cohort of obese individuals reporting sleeping less than 6.5 hours per night. METHODOLOGY AND PRINCIPAL FINDINGS BASELINE DATA FROM OBESE (BMI: 38.5±6.4 kg/m(2)) and short sleeping (5.8±0.8 h/night by actigraphy) participants (n = 119) of the Sleep Extension Study were analyzed (www.ClinicalTrials.gov, identifier NCT00261898). Assessments included the Horne and Ostberg Morningness-Eveningness questionnaire, a three-day dietary intake diary, a 14-day sleep diary, 14 days of actigraphy, and measurements of sleep apnea. Twenty-four hour urinary free cortisol, 24 h urinary norepinephrine and epinephrine levels, morning plasma ACTH and serum cortisol, fasting glucose and insulin, and lipid parameters were determined. Eveningness was associated with eating later in the day on both working and non-working days. Progression towards eveningness was associated with an increase in BMI, resting heart rate, food portion size, and a decrease in the number of eating occasions and HDL-cholesterol. Evening types had overtly higher 24 h urinary epinephrine and morning plasma ACTH levels, and higher morning resting heart rate than Morning types. In addition, Evening types more often had sleep apnea, independent of BMI or neck circumference. CONCLUSIONS Eveningness was associated with eating later and a tendency towards fewer and larger meals and lower HDL-cholesterol levels. In addition, Evening types had more sleep apnea and higher stress hormones. Thus, eveningness in obese, chronically sleep-deprived individuals compounds the cardiovascular risk associated with obesity.", "link"=>"http://www.mendeley.com/research/evening-chronotype-associated-changes-eating-behavior-more-sleep-apnea-increased-stress-hormones-sho", "reader_count"=>126, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>25, "Student > Doctoral Student"=>9, "Student > Ph. D. Student"=>23, "Student > Postgraduate"=>9, "Student > Master"=>19, "Other"=>6, "Student > Bachelor"=>20, "Lecturer"=>2, "Professor"=>5}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>25, "Student > Doctoral Student"=>9, "Student > Ph. D. Student"=>23, "Student > Postgraduate"=>9, "Student > Master"=>19, "Other"=>6, "Student > Bachelor"=>20, "Lecturer"=>2, "Professor"=>5}, "reader_count_by_subject_area"=>{"Unspecified"=>9, "Agricultural and Biological Sciences"=>33, "Business, Management and Accounting"=>1, "Computer Science"=>1, "Energy"=>1, "Engineering"=>1, "Environmental Science"=>4, "Biochemistry, Genetics and Molecular Biology"=>6, "Nursing and Health Professions"=>7, "Medicine and Dentistry"=>36, "Neuroscience"=>8, "Sports and Recreations"=>2, "Psychology"=>12, "Social Sciences"=>4, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>36}, "Social Sciences"=>{"Social Sciences"=>4}, "Sports and Recreations"=>{"Sports and Recreations"=>2}, "Psychology"=>{"Psychology"=>12}, "Unspecified"=>{"Unspecified"=>9}, "Environmental Science"=>{"Environmental Science"=>4}, "Engineering"=>{"Engineering"=>1}, "Neuroscience"=>{"Neuroscience"=>8}, "Energy"=>{"Energy"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>33}, "Computer Science"=>{"Computer Science"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>7}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>6}}, "reader_count_by_country"=>{"Netherlands"=>1, "United States"=>2, "Brazil"=>1, "Croatia"=>1, "Spain"=>2, "Russia"=>1}, "group_count"=>7}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/978865"], "description"=>"<p>Horizontal bars represent sleep time as measured by actigraphy. Bedtime (mean±SD) and risetime (mean±SD) on all days combined and separately on non-working days and on work days in Morning (grey bars) and Evening types (black bars). The mid-sleep times (MSTs) (mean±SD) are depicted by open diamonds and compared between chronotypes by <i>t</i>-tests.</p>", "links"=>[], "tags"=>["diabetes and endocrinology", "public health and epidemiology", "physiology", "epidemiology"], "article_id"=>645733, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sleep_characteristics_per_chronotype_/645733", "title"=>"Sleep characteristics per chronotype.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-07 09:33:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/978867"], "description"=>"<p>Plot of chronotype scores versus the number of eating occasions (A), the portion size (B), and the amount of caloric intake after 20∶00 (C) with a trend line, respectively. N = 113 for all. R<sup>2</sup>, slope, and <i>p</i>-value for the prediction of chronotype score on food intake variables in each plot are calculated from gender-corrected models. Closed circles represent women, open diamonds represent men.</p>", "links"=>[], "tags"=>["intake", "chronotype"], "article_id"=>645734, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pattern_and_timing_of_food_intake_vs_chronotype_score_/645734", "title"=>"Pattern and timing of food intake <i>vs.</i> chronotype score.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-07 09:33:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/978871"], "description"=>"<p>Plot of Chronotype scores versus BMI (A), neck circumference (B), and HDL-C (C) with a trend line, respectively. N = 119 for all. R<sup>2</sup> slope, and <i>p</i>-value for the prediction of chronotype score on variables in each plot are calculated from gender-corrected models. Closed circles represent women, open diamonds represent men.</p>", "links"=>[], "tags"=>["hdl-c", "chronotype"], "article_id"=>645738, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Anthropometrics_and_HDL_C_vs_chronotype_score_/645738", "title"=>"Anthropometrics and HDL-C <i>vs.</i> chronotype score.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-07 09:34:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/978875"], "description"=>"<p>Chronotype scores on the horizontal axis are regressed against plasma ACTH (<i>n</i> = 118; A), 24 h urinary epinephrine (<i>n</i> = 110; B) and norepinephrine (<i>n</i> = 114; C), and resting heart rate (<i>n</i> = 113; D). R<sup>2</sup> for the gender-corrected model is reported, and slope and <i>p</i>-value for the prediction of chronotype score on variables in the model are given. Closed circles represent women, open diamonds represent men.</p>", "links"=>[], "tags"=>["hormones", "chronotype"], "article_id"=>645742, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Stress_hormones_and_heart_rate_vs_chronotype_score_/645742", "title"=>"Stress hormones and heart rate <i>vs.</i> chronotype score.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-07 09:35:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/1011738"], "description"=>"<p>Values are means ± SD,</p>#<p>median and interquartile range for skewed variables, or %. Skewed variables were log-transformed prior to analysis. <i>P</i>-values for <i>t</i>-tests or *Fisher exact test are depicted and significant <i>p</i>-values (<0.05) are bolded.</p>*<p>Fisher exact test including all races;</p>**<p>Fisher exact test excluding “Other races”.</p>", "links"=>[], "tags"=>["anthropometric"], "article_id"=>672148, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_and_anthropometric_characteristics_of_study_participants_/672148", "title"=>"Demographic and anthropometric characteristics of study participants.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-06 00:35:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1011764"], "description"=>"<p>Values are means ± SD,</p>#<p>median and interquartile range for skewed variables, or %. Skewed variables were log-transformed prior to analysis. <i>P</i>-values for <i>t</i>-tests or *Fisher exact test are depicted and significant <i>p</i>-values (<0.05) are bolded.</p>*<p>Fisher exact test including all races;</p>**<p>Fisher exact test excluding “Other races”.</p>1<p>Sleep duration differed on working <i>vs.</i> non-working days in Morning (diary and actigraphy: <i>p</i><0.001) and in Evening chronotypes (diary: <i>p</i> = 0.053; actigraphy: <i>p</i> = 0.005).</p>", "links"=>[], "tags"=>["diabetes and endocrinology", "public health and epidemiology", "physiology", "epidemiology"], "article_id"=>672168, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sleep_characteristics_of_study_participants_/672168", "title"=>"Sleep characteristics of study participants.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-06 00:36:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/1011786"], "description"=>"<p>Values are means ± SD. Intake parameters of chronotypes were compared with <i>t</i>-tests on working and non-working days separately. Significant <i>p</i>-values (<0.05) are bolded.</p>", "links"=>[], "tags"=>["intake", "divided", "chronotype", "non-working"], "article_id"=>672194, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.t003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Food_intake_parameters_of_study_participants_divided_by_chronotype_on_working_vs_non_working_days_/672194", "title"=>"Food intake parameters of study participants divided by chronotype on working <i>vs.</i> non-working days.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-06 00:36:34"}
  • {"files"=>["https://ndownloader.figshare.com/files/1011806"], "description"=>"<p>Values are means ± SD or <sup>#</sup>median and interquartile range for skewed variables.</p>$<p>Measured in fasting morning plasma samples. <i>P</i>-values for <i>t</i>-tests are depicted.</p>", "links"=>[], "tags"=>["metabolic"], "article_id"=>672218, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.t004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Endocrine_and_metabolic_parameters_of_study_participants_/672218", "title"=>"Endocrine and metabolic parameters of study participants.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-06 00:36:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/1011829"], "description"=>"<p>This model depicts a gender- and age-corrected model, generated by multivariate forward stepwise analysis. R<sup>2</sup> and <i>p</i>-value for the models are given, and <i>p</i>-values and regression β coefficients for separate variables predicting chronotype score are shown. Significant <i>p</i>-values (<0.05) are bolded.</p>", "links"=>[], "tags"=>["diabetes and endocrinology", "public health and epidemiology", "physiology", "epidemiology"], "article_id"=>672233, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Eliane A. Lucassen", "Xiongce Zhao", "Kristina I. Rother", "Megan S. Mattingly", "Amber B. Courville", "Lilian de Jonge", "Gyorgy Csako", "Giovanni Cizza"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056519.t005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multivariate_model_/672233", "title"=>"Multivariate model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-06 00:37:13"}

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Relative Metric

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