The Clustering of Lifestyle Behaviours in New Zealand and their Relationship with Optimal Wellbeing
Purpose The purpose of this research was to determine (1) associations between multiple lifestyle behaviours and optimal wellbeing and (2) the extent to which five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—cluster in...
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Veröffentlicht in: | International journal of behavioral medicine 2016-10, Vol.23 (5), p.571-579 |
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description | Purpose
The purpose of this research was to determine (1) associations between multiple lifestyle behaviours and optimal wellbeing and (2) the extent to which five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—cluster in a national sample.
Method
A national sample of New Zealand adults participated in a web-based wellbeing survey. Five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—were dichotomised into healthy (meets recommendations) and unhealthy (does not meet recommendations) categories. Optimal wellbeing was calculated using a multi-dimensional flourishing scale, and binary logistic regression analysis was used to calculate the relationship between multiple healthy behaviours and optimal wellbeing. Clustering was examined by comparing the observed and expected prevalence rates (O/E) of healthy and unhealthy two-, three-, four-, and five-behaviour combinations.
Results
Data from 9425 participants show those engaging in four to five healthy behaviours (23 %) were 4.7 (95 % confidence interval (CI) 3.8–5.7) times more likely to achieve optimal wellbeing compared to those engaging in zero to one healthy behaviour (21 %). Clustering was observed for healthy (5 %, O/E 2.0, 95 % CI 1.8–2.2) and unhealthy (5 %, O/E 2.1, 95 % CI 1.9–2.3) five-behaviour combinations and for four- and three-behaviour combinations. At the two-behaviour level, healthy fruit and vegetable intake clustered with all behaviours, except sleep which did not cluster with any behaviour.
Conclusion
Multiple lifestyle behaviours were positively associated with optimal wellbeing. The results show lifestyle behaviours cluster, providing support for multiple behaviour lifestyle-based interventions for optimising wellbeing. |
doi_str_mv | 10.1007/s12529-016-9552-0 |
format | Article |
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The purpose of this research was to determine (1) associations between multiple lifestyle behaviours and optimal wellbeing and (2) the extent to which five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—cluster in a national sample.
Method
A national sample of New Zealand adults participated in a web-based wellbeing survey. Five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—were dichotomised into healthy (meets recommendations) and unhealthy (does not meet recommendations) categories. Optimal wellbeing was calculated using a multi-dimensional flourishing scale, and binary logistic regression analysis was used to calculate the relationship between multiple healthy behaviours and optimal wellbeing. Clustering was examined by comparing the observed and expected prevalence rates (O/E) of healthy and unhealthy two-, three-, four-, and five-behaviour combinations.
Results
Data from 9425 participants show those engaging in four to five healthy behaviours (23 %) were 4.7 (95 % confidence interval (CI) 3.8–5.7) times more likely to achieve optimal wellbeing compared to those engaging in zero to one healthy behaviour (21 %). Clustering was observed for healthy (5 %, O/E 2.0, 95 % CI 1.8–2.2) and unhealthy (5 %, O/E 2.1, 95 % CI 1.9–2.3) five-behaviour combinations and for four- and three-behaviour combinations. At the two-behaviour level, healthy fruit and vegetable intake clustered with all behaviours, except sleep which did not cluster with any behaviour.
Conclusion
Multiple lifestyle behaviours were positively associated with optimal wellbeing. The results show lifestyle behaviours cluster, providing support for multiple behaviour lifestyle-based interventions for optimising wellbeing.</description><identifier>ISSN: 1070-5503</identifier><identifier>EISSN: 1532-7558</identifier><identifier>DOI: 10.1007/s12529-016-9552-0</identifier><identifier>PMID: 26944753</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Adult ; Behavior ; Cluster Analysis ; Exercise ; Family Medicine ; Female ; Fruit ; General Practice ; Health ; Health Behavior ; Health Psychology ; Humans ; Life Style ; Lifestyles ; Male ; Medicine ; Medicine & Public Health ; Middle Aged ; New Zealand ; Prevalence ; Sleep</subject><ispartof>International journal of behavioral medicine, 2016-10, Vol.23 (5), p.571-579</ispartof><rights>International Society of Behavioral Medicine 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c415t-61b13682d410bf699aa27fcda6717ca6d941409bf45aa3a1a9dace2b2034832e3</citedby><cites>FETCH-LOGICAL-c415t-61b13682d410bf699aa27fcda6717ca6d941409bf45aa3a1a9dace2b2034832e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12529-016-9552-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12529-016-9552-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26944753$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Prendergast, Kate B.</creatorcontrib><creatorcontrib>Mackay, Lisa M.</creatorcontrib><creatorcontrib>Schofield, Grant M.</creatorcontrib><title>The Clustering of Lifestyle Behaviours in New Zealand and their Relationship with Optimal Wellbeing</title><title>International journal of behavioral medicine</title><addtitle>Int.J. Behav. Med</addtitle><addtitle>Int J Behav Med</addtitle><description>Purpose
The purpose of this research was to determine (1) associations between multiple lifestyle behaviours and optimal wellbeing and (2) the extent to which five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—cluster in a national sample.
Method
A national sample of New Zealand adults participated in a web-based wellbeing survey. Five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—were dichotomised into healthy (meets recommendations) and unhealthy (does not meet recommendations) categories. Optimal wellbeing was calculated using a multi-dimensional flourishing scale, and binary logistic regression analysis was used to calculate the relationship between multiple healthy behaviours and optimal wellbeing. Clustering was examined by comparing the observed and expected prevalence rates (O/E) of healthy and unhealthy two-, three-, four-, and five-behaviour combinations.
Results
Data from 9425 participants show those engaging in four to five healthy behaviours (23 %) were 4.7 (95 % confidence interval (CI) 3.8–5.7) times more likely to achieve optimal wellbeing compared to those engaging in zero to one healthy behaviour (21 %). Clustering was observed for healthy (5 %, O/E 2.0, 95 % CI 1.8–2.2) and unhealthy (5 %, O/E 2.1, 95 % CI 1.9–2.3) five-behaviour combinations and for four- and three-behaviour combinations. At the two-behaviour level, healthy fruit and vegetable intake clustered with all behaviours, except sleep which did not cluster with any behaviour.
Conclusion
Multiple lifestyle behaviours were positively associated with optimal wellbeing. The results show lifestyle behaviours cluster, providing support for multiple behaviour lifestyle-based interventions for optimising wellbeing.</description><subject>Adult</subject><subject>Behavior</subject><subject>Cluster Analysis</subject><subject>Exercise</subject><subject>Family Medicine</subject><subject>Female</subject><subject>Fruit</subject><subject>General Practice</subject><subject>Health</subject><subject>Health Behavior</subject><subject>Health Psychology</subject><subject>Humans</subject><subject>Life Style</subject><subject>Lifestyles</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>New Zealand</subject><subject>Prevalence</subject><subject>Sleep</subject><issn>1070-5503</issn><issn>1532-7558</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kc1q3DAUhUVoSCaTPEA2RdBNN26u_ix72Q5NWhgSCAmBbIRsX9caPLYr2R3m7SMzaQmFLIS0-O7RPecQcsngCwPQV4FxxfMEWJrkSvEEjsiCKcETrVT2Ib5BQ6IUiFNyFsIGAJTWcEJOeZpLqZVYkPKhQbpqpzCid90v2td07WoM475F-g0b-8f1kw_UdfQWd_QZbWu7is5nbNB5eo-tHV3fhcYNdOfGht4No9valj5h2xYYRc_JcW3bgBev95I8Xn9_WP1I1nc3P1df10kpmRqTlBVMpBmvJIOiTvPcWq7rsrKpZrq0aZVLJiEvaqmsFZbZvLIl8oKDkJngKJbk80F38P3vKXowWxfKuIXtsJ-CYRkXIJSKES3Jp__QTbTZxe1mioPOMgmRYgeq9H0IHmsz-GjN7w0DMzdgDg2Y2ICZGzDzzMdX5anYYvVv4m_kEeAHIAxz4ujffP2u6guVm5Bv</recordid><startdate>20161001</startdate><enddate>20161001</enddate><creator>Prendergast, Kate B.</creator><creator>Mackay, Lisa M.</creator><creator>Schofield, Grant M.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M2O</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20161001</creationdate><title>The Clustering of Lifestyle Behaviours in New Zealand and their Relationship with Optimal Wellbeing</title><author>Prendergast, Kate B. ; Mackay, Lisa M. ; Schofield, Grant M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c415t-61b13682d410bf699aa27fcda6717ca6d941409bf45aa3a1a9dace2b2034832e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adult</topic><topic>Behavior</topic><topic>Cluster Analysis</topic><topic>Exercise</topic><topic>Family Medicine</topic><topic>Female</topic><topic>Fruit</topic><topic>General Practice</topic><topic>Health</topic><topic>Health Behavior</topic><topic>Health Psychology</topic><topic>Humans</topic><topic>Life Style</topic><topic>Lifestyles</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>New Zealand</topic><topic>Prevalence</topic><topic>Sleep</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Prendergast, Kate B.</creatorcontrib><creatorcontrib>Mackay, Lisa M.</creatorcontrib><creatorcontrib>Schofield, Grant M.</creatorcontrib><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>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</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 Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>International journal of behavioral medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Prendergast, Kate B.</au><au>Mackay, Lisa M.</au><au>Schofield, Grant M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Clustering of Lifestyle Behaviours in New Zealand and their Relationship with Optimal Wellbeing</atitle><jtitle>International journal of behavioral medicine</jtitle><stitle>Int.J. Behav. Med</stitle><addtitle>Int J Behav Med</addtitle><date>2016-10-01</date><risdate>2016</risdate><volume>23</volume><issue>5</issue><spage>571</spage><epage>579</epage><pages>571-579</pages><issn>1070-5503</issn><eissn>1532-7558</eissn><abstract>Purpose
The purpose of this research was to determine (1) associations between multiple lifestyle behaviours and optimal wellbeing and (2) the extent to which five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—cluster in a national sample.
Method
A national sample of New Zealand adults participated in a web-based wellbeing survey. Five lifestyle behaviours—sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake—were dichotomised into healthy (meets recommendations) and unhealthy (does not meet recommendations) categories. Optimal wellbeing was calculated using a multi-dimensional flourishing scale, and binary logistic regression analysis was used to calculate the relationship between multiple healthy behaviours and optimal wellbeing. Clustering was examined by comparing the observed and expected prevalence rates (O/E) of healthy and unhealthy two-, three-, four-, and five-behaviour combinations.
Results
Data from 9425 participants show those engaging in four to five healthy behaviours (23 %) were 4.7 (95 % confidence interval (CI) 3.8–5.7) times more likely to achieve optimal wellbeing compared to those engaging in zero to one healthy behaviour (21 %). Clustering was observed for healthy (5 %, O/E 2.0, 95 % CI 1.8–2.2) and unhealthy (5 %, O/E 2.1, 95 % CI 1.9–2.3) five-behaviour combinations and for four- and three-behaviour combinations. At the two-behaviour level, healthy fruit and vegetable intake clustered with all behaviours, except sleep which did not cluster with any behaviour.
Conclusion
Multiple lifestyle behaviours were positively associated with optimal wellbeing. The results show lifestyle behaviours cluster, providing support for multiple behaviour lifestyle-based interventions for optimising wellbeing.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>26944753</pmid><doi>10.1007/s12529-016-9552-0</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; SpringerLink Journals - AutoHoldings |
subjects | Adult Behavior Cluster Analysis Exercise Family Medicine Female Fruit General Practice Health Health Behavior Health Psychology Humans Life Style Lifestyles Male Medicine Medicine & Public Health Middle Aged New Zealand Prevalence Sleep |
title | The Clustering of Lifestyle Behaviours in New Zealand and their Relationship with Optimal Wellbeing |
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