Influence of Obesity on Heart Rate Variability in Nurses with Age and Shift Type as Moderators
Obesity is a risk factor of cardiovascular disease-related mortality and may be associated with changes in the autonomic nerve activity. Nurses working shifts and caring for patients are under great mental and physical pressure, and research has proven that these can negatively affect the body. The...
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| description | Obesity is a risk factor of cardiovascular disease-related mortality and may be associated with changes in the autonomic nerve activity. Nurses working shifts and caring for patients are under great mental and physical pressure, and research has proven that these can negatively affect the body. The objective of this study was to examine the influence of obesity in nurses on their heart rate variability (HRV) and determine whether age or shift type moderates this influence. A questionnaire survey and HRV measurements were conducted on nurses at a hospital in Taiwan during a routine employee health checkup. HRV analysis was conducted using a noninvasive HRV monitor for five minutes. A total of 242 nurses with a mean age of 28.98±6.56 years were enrolled in this study. An overly large waist circumference (WC) had a negative impact on high frequency (HF), low frequency (LF), and standard deviation of normal-to-normal interval (SDNN), while an overly high body mass index (BMI) had a negative impact on very low frequency (VLF) and SDNN. The interaction term “overly large WC × age” had a negative impact on HF (β=−0.21, p=0.010) and LF (β=−0.18, p=0.030), whereas the interaction term “overly high BMI×age” had a negative impact on HF (β=−0.27, p=0.001), LF (β=−0.19, p=0.023), and VLF (β=−0.17, p=0.045). The interaction terms “overly large WC × shift type” and “overly high BMI × shift type” did not influence any HRV parameters. As age increased, so did the degree to which the HF and LF of nurses with an overly large WC were lower than normal, and so did the degree to which the HF, LF, and VLF of nurses with an overly high BMI were lower than normal. |
| doi_str_mv | 10.1155/2021/8119929 |
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Nurses working shifts and caring for patients are under great mental and physical pressure, and research has proven that these can negatively affect the body. The objective of this study was to examine the influence of obesity in nurses on their heart rate variability (HRV) and determine whether age or shift type moderates this influence. A questionnaire survey and HRV measurements were conducted on nurses at a hospital in Taiwan during a routine employee health checkup. HRV analysis was conducted using a noninvasive HRV monitor for five minutes. A total of 242 nurses with a mean age of 28.98±6.56 years were enrolled in this study. An overly large waist circumference (WC) had a negative impact on high frequency (HF), low frequency (LF), and standard deviation of normal-to-normal interval (SDNN), while an overly high body mass index (BMI) had a negative impact on very low frequency (VLF) and SDNN. The interaction term “overly large WC × age” had a negative impact on HF (β=−0.21, p=0.010) and LF (β=−0.18, p=0.030), whereas the interaction term “overly high BMI×age” had a negative impact on HF (β=−0.27, p=0.001), LF (β=−0.19, p=0.023), and VLF (β=−0.17, p=0.045). The interaction terms “overly large WC × shift type” and “overly high BMI × shift type” did not influence any HRV parameters. As age increased, so did the degree to which the HF and LF of nurses with an overly large WC were lower than normal, and so did the degree to which the HF, LF, and VLF of nurses with an overly high BMI were lower than normal.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2021/8119929</identifier><identifier>PMID: 34840981</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Adult ; Age ; Age Factors ; Analysis of Variance ; Autonomic Nervous System - physiopathology ; Biomedical research ; Blood ; Body fat ; Body mass ; Body Mass Index ; Body size ; Cardiovascular diseases ; Cardiovascular Diseases - etiology ; Catecholamines ; Diabetes ; Female ; Health risks ; Heart Disease Risk Factors ; Heart rate ; Heart Rate - physiology ; Humans ; Hypotheses ; Influence ; Light ; Male ; Metabolism ; Moderators ; Mortality ; Motility ; Nervous system ; Nurses ; Nursing care ; Obesity ; Obesity - complications ; Obesity - pathology ; Obesity - physiopathology ; Occupational health ; Questionnaires ; Risk analysis ; Risk factors ; Shift Work Schedule - adverse effects ; Standard deviation ; Taiwan ; Variability ; Very Low Frequencies ; Waist Circumference ; Young Adult</subject><ispartof>BioMed research international, 2021, Vol.2021 (1), p.8119929-8119929</ispartof><rights>Copyright © 2021 Wen-Pei Chang et al.</rights><rights>Copyright © 2021 Wen-Pei Chang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2021 Wen-Pei Chang et al. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c448t-52a4b34821373641fe6d62896b4008b953ff783c936ff554a3d72c82376979a3</citedby><cites>FETCH-LOGICAL-c448t-52a4b34821373641fe6d62896b4008b953ff783c936ff554a3d72c82376979a3</cites><orcidid>0000-0002-4906-2136 ; 0000-0002-7027-9508 ; 0000-0002-8181-5097</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8612804/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8612804/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,4010,27900,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34840981$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Carbone, Federico</contributor><creatorcontrib>Chang, Wen-Pei</creatorcontrib><creatorcontrib>Wang, Chia-Hui</creatorcontrib><creatorcontrib>Lin, Yen-Kuang</creatorcontrib><title>Influence of Obesity on Heart Rate Variability in Nurses with Age and Shift Type as Moderators</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Obesity is a risk factor of cardiovascular disease-related mortality and may be associated with changes in the autonomic nerve activity. Nurses working shifts and caring for patients are under great mental and physical pressure, and research has proven that these can negatively affect the body. The objective of this study was to examine the influence of obesity in nurses on their heart rate variability (HRV) and determine whether age or shift type moderates this influence. A questionnaire survey and HRV measurements were conducted on nurses at a hospital in Taiwan during a routine employee health checkup. HRV analysis was conducted using a noninvasive HRV monitor for five minutes. A total of 242 nurses with a mean age of 28.98±6.56 years were enrolled in this study. An overly large waist circumference (WC) had a negative impact on high frequency (HF), low frequency (LF), and standard deviation of normal-to-normal interval (SDNN), while an overly high body mass index (BMI) had a negative impact on very low frequency (VLF) and SDNN. The interaction term “overly large WC × age” had a negative impact on HF (β=−0.21, p=0.010) and LF (β=−0.18, p=0.030), whereas the interaction term “overly high BMI×age” had a negative impact on HF (β=−0.27, p=0.001), LF (β=−0.19, p=0.023), and VLF (β=−0.17, p=0.045). The interaction terms “overly large WC × shift type” and “overly high BMI × shift type” did not influence any HRV parameters. As age increased, so did the degree to which the HF and LF of nurses with an overly large WC were lower than normal, and so did the degree to which the HF, LF, and VLF of nurses with an overly high BMI were lower than normal.</description><subject>Adult</subject><subject>Age</subject><subject>Age Factors</subject><subject>Analysis of Variance</subject><subject>Autonomic Nervous System - physiopathology</subject><subject>Biomedical research</subject><subject>Blood</subject><subject>Body fat</subject><subject>Body mass</subject><subject>Body Mass Index</subject><subject>Body size</subject><subject>Cardiovascular diseases</subject><subject>Cardiovascular Diseases - etiology</subject><subject>Catecholamines</subject><subject>Diabetes</subject><subject>Female</subject><subject>Health risks</subject><subject>Heart Disease Risk Factors</subject><subject>Heart rate</subject><subject>Heart Rate - physiology</subject><subject>Humans</subject><subject>Hypotheses</subject><subject>Influence</subject><subject>Light</subject><subject>Male</subject><subject>Metabolism</subject><subject>Moderators</subject><subject>Mortality</subject><subject>Motility</subject><subject>Nervous system</subject><subject>Nurses</subject><subject>Nursing care</subject><subject>Obesity</subject><subject>Obesity - 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physiopathology</topic><topic>Biomedical research</topic><topic>Blood</topic><topic>Body fat</topic><topic>Body mass</topic><topic>Body Mass Index</topic><topic>Body size</topic><topic>Cardiovascular diseases</topic><topic>Cardiovascular Diseases - etiology</topic><topic>Catecholamines</topic><topic>Diabetes</topic><topic>Female</topic><topic>Health risks</topic><topic>Heart Disease Risk Factors</topic><topic>Heart rate</topic><topic>Heart Rate - physiology</topic><topic>Humans</topic><topic>Hypotheses</topic><topic>Influence</topic><topic>Light</topic><topic>Male</topic><topic>Metabolism</topic><topic>Moderators</topic><topic>Mortality</topic><topic>Motility</topic><topic>Nervous system</topic><topic>Nurses</topic><topic>Nursing care</topic><topic>Obesity</topic><topic>Obesity - complications</topic><topic>Obesity - pathology</topic><topic>Obesity - physiopathology</topic><topic>Occupational health</topic><topic>Questionnaires</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Shift Work Schedule - adverse effects</topic><topic>Standard deviation</topic><topic>Taiwan</topic><topic>Variability</topic><topic>Very Low Frequencies</topic><topic>Waist Circumference</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chang, Wen-Pei</creatorcontrib><creatorcontrib>Wang, Chia-Hui</creatorcontrib><creatorcontrib>Lin, Yen-Kuang</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology 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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>Natural Science Collection (ProQuest)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BioMed research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chang, Wen-Pei</au><au>Wang, Chia-Hui</au><au>Lin, Yen-Kuang</au><au>Carbone, Federico</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Influence of Obesity on Heart Rate Variability in Nurses with Age and Shift Type as Moderators</atitle><jtitle>BioMed research international</jtitle><addtitle>Biomed Res Int</addtitle><date>2021</date><risdate>2021</risdate><volume>2021</volume><issue>1</issue><spage>8119929</spage><epage>8119929</epage><pages>8119929-8119929</pages><issn>2314-6133</issn><eissn>2314-6141</eissn><abstract>Obesity is a risk factor of cardiovascular disease-related mortality and may be associated with changes in the autonomic nerve activity. Nurses working shifts and caring for patients are under great mental and physical pressure, and research has proven that these can negatively affect the body. The objective of this study was to examine the influence of obesity in nurses on their heart rate variability (HRV) and determine whether age or shift type moderates this influence. A questionnaire survey and HRV measurements were conducted on nurses at a hospital in Taiwan during a routine employee health checkup. HRV analysis was conducted using a noninvasive HRV monitor for five minutes. A total of 242 nurses with a mean age of 28.98±6.56 years were enrolled in this study. An overly large waist circumference (WC) had a negative impact on high frequency (HF), low frequency (LF), and standard deviation of normal-to-normal interval (SDNN), while an overly high body mass index (BMI) had a negative impact on very low frequency (VLF) and SDNN. The interaction term “overly large WC × age” had a negative impact on HF (β=−0.21, p=0.010) and LF (β=−0.18, p=0.030), whereas the interaction term “overly high BMI×age” had a negative impact on HF (β=−0.27, p=0.001), LF (β=−0.19, p=0.023), and VLF (β=−0.17, p=0.045). The interaction terms “overly large WC × shift type” and “overly high BMI × shift type” did not influence any HRV parameters. As age increased, so did the degree to which the HF and LF of nurses with an overly large WC were lower than normal, and so did the degree to which the HF, LF, and VLF of nurses with an overly high BMI were lower than normal.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>34840981</pmid><doi>10.1155/2021/8119929</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-4906-2136</orcidid><orcidid>https://orcid.org/0000-0002-7027-9508</orcidid><orcidid>https://orcid.org/0000-0002-8181-5097</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adult Age Age Factors Analysis of Variance Autonomic Nervous System - physiopathology Biomedical research Blood Body fat Body mass Body Mass Index Body size Cardiovascular diseases Cardiovascular Diseases - etiology Catecholamines Diabetes Female Health risks Heart Disease Risk Factors Heart rate Heart Rate - physiology Humans Hypotheses Influence Light Male Metabolism Moderators Mortality Motility Nervous system Nurses Nursing care Obesity Obesity - complications Obesity - pathology Obesity - physiopathology Occupational health Questionnaires Risk analysis Risk factors Shift Work Schedule - adverse effects Standard deviation Taiwan Variability Very Low Frequencies Waist Circumference Young Adult |
| title | Influence of Obesity on Heart Rate Variability in Nurses with Age and Shift Type as Moderators |
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