The role of socio-demographic factors and physical functioning in the intra- and interpersonal variability of older adults’ sedentary time: an observational two-country study
Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location i...
Saved in:
| Published in | BMC geriatrics Vol. 22; no. 1; pp. 495 - 14 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
BioMed Central Ltd
09.06.2022
BioMed Central BMC |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability.
Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability.
Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time.
The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults' sedentary time. |
|---|---|
| AbstractList | Background Insight into the variability of older adults’ sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability. Methods Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability. Results Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time. Conclusions The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults’ sedentary time. Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability. Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability. Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time. The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults' sedentary time. Abstract Background Insight into the variability of older adults’ sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability. Methods Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability. Results Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time. Conclusions The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults’ sedentary time. Background Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability. Methods Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability. Results Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time. Conclusions The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults' sedentary time. Keywords: Sitting time, elderly, diurnal patterns, epidemiology Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability.BACKGROUNDInsight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability.Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability.METHODSCross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability.Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time.RESULTSMost of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time.The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults' sedentary time.CONCLUSIONSThe oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults' sedentary time. Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and interpersonal variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location in this variability. Cross-sectional data from 818 community-dwelling older adults (mean age: 74.8 years; 61.1%women) of the Active Lifestyle and the Environment in Chinese Seniors and Belgian Environmental Physical Activity Study in Seniors were used. An interview questionnaire was administered to collect socio-demographic information. The Short Physical Performance Battery was performed to evaluate physical functioning, and Actigraph GT3X( +) accelerometers were used to estimate sedentary time. Linear mixed models with random intercepts at the neighborhood, person and day levels examined the variability in sedentary time, and the moderating role of socio-demographics, physical functioning and geographical location within this variability. Most of the variance in accelerometry-assessed sedentary time was due to intrapersonal variability across periods of the day (72.4%) followed by interpersonal variability within neighborhoods (25.6%). Those who were older, men, lived in Hong Kong, and experienced a lower level of physical functioning were more sedentary than their counterparts. Sedentary time increased throughout the day, with highest levels of sedentary time observed between 6:00 and 9:00 pm. The patterns of sedentary time across times of the day differed by gender, educational attainment, age, physical functioning and/or geographical location. No significant differences were detected between week and weekend day sedentary time. The oldest old, men, and those with functional limitations are important target groups for sedentary behavior interventions. As sedentary time was the highest in the evening future sedentary behavior intervention should pay particular attention to the evening hours. The variations in diurnal patterns of sedentary time between population subgroups suggest that personalized just-in-time adaptive interventions might be a promising strategy to reduce older adults' sedentary time. |
| ArticleNumber | 495 |
| Audience | Academic |
| Author | Barnett, Anthony Van Cauwenberg, Jelle Compernolle, Sofie Zhang, Casper J. P. Van Dyck, Delfien Cerin, Ester |
| Author_xml | – sequence: 1 givenname: Sofie surname: Compernolle fullname: Compernolle, Sofie – sequence: 2 givenname: Ester surname: Cerin fullname: Cerin, Ester – sequence: 3 givenname: Anthony surname: Barnett fullname: Barnett, Anthony – sequence: 4 givenname: Casper J. P. surname: Zhang fullname: Zhang, Casper J. P. – sequence: 5 givenname: Jelle surname: Van Cauwenberg fullname: Van Cauwenberg, Jelle – sequence: 6 givenname: Delfien surname: Van Dyck fullname: Van Dyck, Delfien |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35681115$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9kstu1DAUhiNURC_wAiyQJTZsUnycxElYIFUVl0qV2JS15dgnM64y9mA7RbPjNXgLnokn4cxMKS1CKIvYJ9_5zyX_cXHgg8eieA78FKCTrxOIrm1LLkTJKwqU8Kg4grqFUtD14N75sDhO6ZpzaDshnxSHVSM7AGiOih9XS2QxTMjCyFIwLpQWV2ER9XrpDBu1ySEmpr1l6-UmOaMnNs7eZBe88wvmPMuk4HyOutxhdMS4xpiCJ_ZGR6cHN7m82VYIk8XItJ2nnH5--84SWvRZxw3LboVvSICFIWG80dsClJ-_htKEmeQ3LOXZbp4Wj0c9JXx2-z4pPr9_d3X-sbz89OHi_OyyNI2sclmJ1vQtWFP3oh_BjKixqySvDLccht5KBNMNIFrO22EwvdQauBiwBkHLlNVJcbHXtUFfq3V0K-pSBe3ULhDiQumYnZlQWT3oWnQNVraua5JtEMYORwMt4lAPpPV2r7WehxVag9ttTQ9EH37xbqkW4Ub19MOaetvMq1uBGL7MmLJauWRwmrTHMCclZNtILpu6JvTlX-h1mCOtckd10NPE_R9qoWkA58dAdc1WVJ21XEqAumqJOv0HRQ9ZxBky4-go_iDhxf1B7yb87TcCxB4wMaQUcbxDgKutqdXe1IpMrXamVkBJ3V9JxuWdQagdN_0v9Rd3k_-O |
| CitedBy_id | crossref_primary_10_1016_j_tjnut_2023_02_034 crossref_primary_10_61186_unmf_21_1_66 crossref_primary_10_3390_jcm12175453 crossref_primary_10_3390_jcm12155005 |
| Cites_doi | 10.1186/s12966-017-0525-8 10.1016/j.maturitas.2018.08.002 10.1093/tbm/ibz189 10.1186/1471-2458-13-213 10.1186/s12966-015-0292-3 10.1037/hea0000306 10.1016/j.healthplace.2016.08.009 10.1136/bmjopen-2015-010384 10.1515/9783110208856.233 10.11622/smedj.2020022 10.2196/26387 10.1186/s12966-020-00979-8 10.1093/geront/gnv203.03 10.1037/hea0000304 10.1186/s12877-018-0987-9 10.1080/17461391.2017.1327983 10.1016/S1073-4449(99)70028-2 10.3390/jcm11061568 10.1007/s12160-016-9830-8 10.1186/s12877-020-01521-y 10.1186/1471-2458-14-333 10.1186/s12966-018-0669-1 10.1186/s13054-017-1827-6 10.1016/j.mad.2021.111524 10.1093/geronj/49.2.M85 10.1093/geroni/igz038.602 10.1249/MSS.0000000000000924 10.1093/ptj/pzy158 10.1093/ije/dyx123 10.1093/geront/gnz127 10.1136/bmjopen-2014-007557 10.1186/s12877-021-02163-4 10.2139/ssrn.3044368 10.1093/jamia/ocy160 10.1111/j.1365-2869.2008.00718.x 10.1007/s40675-020-00183-x 10.1155/2020/8432934 10.1123/japa.17.1.17 10.2522/ptj.20080213 10.1016/j.jsams.2013.07.002 10.1093/geront/gnu163 10.1371/journal.pone.0183911 10.1123/japa.16.4.416 10.1371/journal.pone.0136161 10.3934/medsci.2020002 10.1007/s40520-019-01457-3 10.1371/journal.pone.0133175 10.1186/s12966-014-0110-3 10.1017/S0144686X05004228 10.1186/s12889-015-1976-y 10.1159/000134296 10.3390/ijerph10126645 10.1136/bmj.e2451 |
| ContentType | Journal Article |
| Copyright | 2022. The Author(s). COPYRIGHT 2022 BioMed Central Ltd. 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. The Author(s) 2022 |
| Copyright_xml | – notice: 2022. The Author(s). – notice: COPYRIGHT 2022 BioMed Central Ltd. – notice: 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: The Author(s) 2022 |
| DBID | AAYXX CITATION NPM 3V. 7QP 7TK 7X7 7XB 88E 8FI 8FJ 8FK ABUWG AFKRA AZQEC BENPR CCPQU COVID DWQXO FYUFA GHDGH K9. M0S M1P PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQQKQ PQUKI PRINS 7X8 5PM DOA |
| DOI | 10.1186/s12877-022-03186-1 |
| DatabaseName | CrossRef PubMed ProQuest Central (Corporate) Calcium & Calcified Tissue Abstracts Neurosciences Abstracts ProQuest Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central ProQuest One Coronavirus Research Database ProQuest Central Proquest Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Health & Medical Complete (Alumni) ProQuest Health & Medical Collection Medical Database ProQuest Central Premium ProQuest One Academic (New) ProQuest Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef PubMed Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Central China ProQuest Central ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Health & Medical Research Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest One Academic Eastern Edition Coronavirus Research Database ProQuest Hospital Collection Health Research Premium Collection (Alumni) Neurosciences Abstracts ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic Calcium & Calcified Tissue Abstracts ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | Publicly Available Content Database MEDLINE - Academic PubMed |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1471-2318 |
| EndPage | 14 |
| ExternalDocumentID | oai_doaj_org_article_daba4285e3d4441c85e1f8efc17eeb4b PMC9178546 A706611437 35681115 10_1186_s12877_022_03186_1 |
| Genre | Journal Article |
| GeographicLocations | Belgium China Hong Kong China |
| GeographicLocations_xml | – name: China – name: Belgium – name: Hong Kong China |
| GroupedDBID | --- 0R~ 23N 2WC 53G 5GY 5VS 6J9 6PF 7X7 88E 8FI 8FJ AAFWJ AAJSJ AASML AAWTL AAYXX ABUWG ACGFO ACGFS ACHQT ACIHN ACPRK ADBBV ADRAZ ADUKV AEAQA AENEX AFKRA AFPKN AHBYD AHMBA AHYZX ALIPV ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS BAPOH BAWUL BCNDV BENPR BFQNJ BMC BPHCQ BVXVI C6C CCPQU CITATION CS3 DIK DU5 E3Z EBD EBLON EBS EMB EMOBN F5P FYUFA GROUPED_DOAJ GX1 HMCUK HYE IAO IHR INH INR ITC KQ8 M1P M48 M~E O5R O5S OK1 OVT P2P PGMZT PHGZM PHGZT PIMPY PQQKQ PROAC PSQYO RBZ RNS ROL RPM RSV SMD SOJ SV3 TR2 UKHRP W2D WOQ WOW XSB -A0 3V. ACRMQ ADINQ C24 NPM PMFND 7QP 7TK 7XB 8FK AZQEC COVID DWQXO K9. PJZUB PKEHL PPXIY PQEST PQUKI PRINS 7X8 5PM PUEGO |
| ID | FETCH-LOGICAL-c563t-327c971dc4929f1cfeae83603c0d01b9d6e1c8b127007bbc96aa102be41203163 |
| IEDL.DBID | M48 |
| ISSN | 1471-2318 |
| IngestDate | Wed Aug 27 01:31:25 EDT 2025 Thu Aug 21 18:19:13 EDT 2025 Fri Jul 11 13:58:16 EDT 2025 Fri Jul 25 20:56:31 EDT 2025 Tue Jun 17 21:44:02 EDT 2025 Tue Jun 10 20:41:07 EDT 2025 Wed Feb 19 02:27:01 EST 2025 Tue Jul 01 04:31:11 EDT 2025 Thu Apr 24 23:09:11 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | epidemiology Sitting time diurnal patterns elderly |
| Language | English |
| License | 2022. The Author(s). Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c563t-327c971dc4929f1cfeae83603c0d01b9d6e1c8b127007bbc96aa102be41203163 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 ObjectType-Undefined-3 |
| OpenAccessLink | https://www.proquest.com/docview/2678192709?pq-origsite=%requestingapplication% |
| PMID | 35681115 |
| PQID | 2678192709 |
| PQPubID | 44817 |
| PageCount | 14 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_daba4285e3d4441c85e1f8efc17eeb4b pubmedcentral_primary_oai_pubmedcentral_nih_gov_9178546 proquest_miscellaneous_2675606544 proquest_journals_2678192709 gale_infotracmisc_A706611437 gale_infotracacademiconefile_A706611437 pubmed_primary_35681115 crossref_primary_10_1186_s12877_022_03186_1 crossref_citationtrail_10_1186_s12877_022_03186_1 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2022-06-09 |
| PublicationDateYYYYMMDD | 2022-06-09 |
| PublicationDate_xml | – month: 06 year: 2022 text: 2022-06-09 day: 09 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: London |
| PublicationTitle | BMC geriatrics |
| PublicationTitleAlternate | BMC Geriatr |
| PublicationYear | 2022 |
| Publisher | BioMed Central Ltd BioMed Central BMC |
| Publisher_xml | – name: BioMed Central Ltd – name: BioMed Central – name: BMC |
| References | 3186_CR39 LA Pruitt (3186_CR31) 2008; 16 JA Harvey (3186_CR46) 2013; 10 S-H Chang (3186_CR49) 2018; 18 J Van Cauwenberg (3186_CR16) 2015; 10 3186_CR34 A Koster (3186_CR55) 2016; 48 3186_CR35 H Kikuchi (3186_CR38) 2013; 13 JM Guralnik (3186_CR29) 1994; 49 LFM de Rezende (3186_CR4) 2014; 14 WC Taylor (3186_CR5) 2020; 7 JG Thomas (3186_CR12) 2015; 34 E Cerin (3186_CR28) 2016; 42 S Compernolle (3186_CR54) 2021; 9 N Aguilar-Farías (3186_CR33) 2014; 17 V Van Holle (3186_CR26) 2014; 11 VJ Palmer (3186_CR37) 2019; 59 3186_CR44 A Mañas (3186_CR7) 2017; 17 3186_CR47 NM Gell (3186_CR43) 2019; 3 LP Ng (3186_CR48) 2020; 61 I Nahum-Shani (3186_CR36) 2015; 34 I Nahum-Shani (3186_CR14) 2018; 52 S Compernolle (3186_CR23) 2020; 60 3186_CR40 O Olanrewaju (3186_CR8) 2020; 32 L Choi (3186_CR32) 2009; 2012 MS Tremblay (3186_CR1) 2017; 14 S Gonul (3186_CR13) 2019; 26 JA Aunger (3186_CR10) 2018; 116 B del Pozo-Cruz (3186_CR3) 2017; 12 F González-Seguel (3186_CR21) 2019; 99 KM Tomey (3186_CR20) 2009; 89 E Cerin (3186_CR52) 2020; 17 J Bellettiere (3186_CR41) 2015; 10 3186_CR50 C Sartini (3186_CR18) 2015; 15 RL Walker (3186_CR24) 2021; 21 MA Greenwood-Hickman (3186_CR53) 2016; 56 P Painter (3186_CR19) 1999; 6 D Yerrakalva (3186_CR17) 2017; 46 3186_CR2 3186_CR6 CE Milner (3186_CR42) 2009; 18 3186_CR9 J-AD Chase (3186_CR11) 2020; 10 JL Copeland (3186_CR30) 2009; 17 A Barnett (3186_CR45) 2015; 5 SF Chastin (3186_CR15) 2015; 12 Z-j Wu (3186_CR51) 2020; 20 EC Lefferts (3186_CR56) 2022; 11 3186_CR27 SM Parry (3186_CR22) 2017; 21 E Cerin (3186_CR25) 2016; 6 |
| References_xml | – volume: 14 start-page: 1 year: 2017 ident: 3186_CR1 publication-title: Int J Behav Nutr Phys Act doi: 10.1186/s12966-017-0525-8 – volume: 116 start-page: 89 year: 2018 ident: 3186_CR10 publication-title: Maturitas doi: 10.1016/j.maturitas.2018.08.002 – volume: 10 start-page: 1078 year: 2020 ident: 3186_CR11 publication-title: Transl Behav Med doi: 10.1093/tbm/ibz189 – volume: 13 start-page: 1 year: 2013 ident: 3186_CR38 publication-title: BMC Public Health doi: 10.1186/1471-2458-13-213 – volume: 12 start-page: 1 year: 2015 ident: 3186_CR15 publication-title: Int J Behav Nutr Phys Act doi: 10.1186/s12966-015-0292-3 – volume: 34 start-page: 1209 year: 2015 ident: 3186_CR36 publication-title: Health Psychol doi: 10.1037/hea0000306 – volume: 42 start-page: 1 year: 2016 ident: 3186_CR28 publication-title: Health Place doi: 10.1016/j.healthplace.2016.08.009 – volume: 6 year: 2016 ident: 3186_CR25 publication-title: BMJ Open doi: 10.1136/bmjopen-2015-010384 – ident: 3186_CR27 doi: 10.1515/9783110208856.233 – volume: 61 start-page: 266 year: 2020 ident: 3186_CR48 publication-title: Singapore Med J doi: 10.11622/smedj.2020022 – volume: 9 year: 2021 ident: 3186_CR54 publication-title: JMIR Mhealth Uhealth doi: 10.2196/26387 – volume: 17 start-page: 1 year: 2020 ident: 3186_CR52 publication-title: Int J Behav Nutr Phys Act doi: 10.1186/s12966-020-00979-8 – ident: 3186_CR9 doi: 10.1093/geront/gnv203.03 – volume: 34 start-page: 1261 year: 2015 ident: 3186_CR12 publication-title: Health Psychol doi: 10.1037/hea0000304 – volume: 18 start-page: 1 year: 2018 ident: 3186_CR49 publication-title: BMC Geriatr doi: 10.1186/s12877-018-0987-9 – volume: 17 start-page: 940 year: 2017 ident: 3186_CR7 publication-title: Eur J Sport Sci doi: 10.1080/17461391.2017.1327983 – volume: 6 start-page: 110 year: 1999 ident: 3186_CR19 publication-title: Adv Ren Replace Ther doi: 10.1016/S1073-4449(99)70028-2 – volume: 11 start-page: 1568 year: 2022 ident: 3186_CR56 publication-title: J Clin Med doi: 10.3390/jcm11061568 – volume: 52 start-page: 446 year: 2018 ident: 3186_CR14 publication-title: Ann Behav Med doi: 10.1007/s12160-016-9830-8 – volume: 2012 start-page: 44 year: 2009 ident: 3186_CR32 publication-title: Med Sci Sports Exerc – volume: 20 start-page: 1 year: 2020 ident: 3186_CR51 publication-title: BMC Geriatr doi: 10.1186/s12877-020-01521-y – volume: 14 start-page: 1 year: 2014 ident: 3186_CR4 publication-title: BMC Public Health doi: 10.1186/1471-2458-14-333 – ident: 3186_CR50 doi: 10.1186/s12966-018-0669-1 – volume: 21 start-page: 1 year: 2017 ident: 3186_CR22 publication-title: Crit Care doi: 10.1186/s13054-017-1827-6 – ident: 3186_CR6 doi: 10.1016/j.mad.2021.111524 – volume: 49 start-page: M85 year: 1994 ident: 3186_CR29 publication-title: J Gerontol doi: 10.1093/geronj/49.2.M85 – volume: 59 start-page: 686 year: 2019 ident: 3186_CR37 publication-title: Gerontologist – volume: 3 start-page: S169 year: 2019 ident: 3186_CR43 publication-title: Innov Aging doi: 10.1093/geroni/igz038.602 – volume: 48 start-page: 1514 year: 2016 ident: 3186_CR55 publication-title: Med Sci Sports Exerc doi: 10.1249/MSS.0000000000000924 – volume: 99 start-page: 627 year: 2019 ident: 3186_CR21 publication-title: Phys Ther doi: 10.1093/ptj/pzy158 – volume: 46 start-page: 1871 year: 2017 ident: 3186_CR17 publication-title: Int J Epidemiol doi: 10.1093/ije/dyx123 – volume: 60 start-page: 572 year: 2020 ident: 3186_CR23 publication-title: Gerontologist doi: 10.1093/geront/gnz127 – volume: 5 year: 2015 ident: 3186_CR45 publication-title: BMJ Open doi: 10.1136/bmjopen-2014-007557 – volume: 21 start-page: 1 year: 2021 ident: 3186_CR24 publication-title: BMC Geriatr doi: 10.1186/s12877-021-02163-4 – ident: 3186_CR35 doi: 10.2139/ssrn.3044368 – volume: 26 start-page: 198 year: 2019 ident: 3186_CR13 publication-title: J Am Med Inform Assoc doi: 10.1093/jamia/ocy160 – volume: 18 start-page: 272 year: 2009 ident: 3186_CR42 publication-title: J Sleep Res doi: 10.1111/j.1365-2869.2008.00718.x – ident: 3186_CR44 doi: 10.1007/s40675-020-00183-x – ident: 3186_CR47 doi: 10.1155/2020/8432934 – ident: 3186_CR34 – volume: 17 start-page: 17 year: 2009 ident: 3186_CR30 publication-title: J Aging Phys Act doi: 10.1123/japa.17.1.17 – volume: 89 start-page: 705 year: 2009 ident: 3186_CR20 publication-title: Phys Ther doi: 10.2522/ptj.20080213 – volume: 17 start-page: 293 year: 2014 ident: 3186_CR33 publication-title: J Sci Med Sport doi: 10.1016/j.jsams.2013.07.002 – volume: 56 start-page: 660 year: 2016 ident: 3186_CR53 publication-title: Gerontologist doi: 10.1093/geront/gnu163 – volume: 12 year: 2017 ident: 3186_CR3 publication-title: PLoS ONE doi: 10.1371/journal.pone.0183911 – volume: 16 start-page: 416 year: 2008 ident: 3186_CR31 publication-title: J Aging Phys Act doi: 10.1123/japa.16.4.416 – volume: 10 year: 2015 ident: 3186_CR41 publication-title: PLoS ONE doi: 10.1371/journal.pone.0136161 – volume: 7 start-page: 10 year: 2020 ident: 3186_CR5 publication-title: AIMS Medical Science doi: 10.3934/medsci.2020002 – volume: 32 start-page: 969 year: 2020 ident: 3186_CR8 publication-title: Aging Clin Exp Res doi: 10.1007/s40520-019-01457-3 – volume: 10 year: 2015 ident: 3186_CR16 publication-title: PLoS ONE doi: 10.1371/journal.pone.0133175 – volume: 11 start-page: 1 year: 2014 ident: 3186_CR26 publication-title: Int J Behav Nutr Phys Act doi: 10.1186/s12966-014-0110-3 – ident: 3186_CR39 doi: 10.1017/S0144686X05004228 – volume: 15 start-page: 1 year: 2015 ident: 3186_CR18 publication-title: BMC Public Health doi: 10.1186/s12889-015-1976-y – ident: 3186_CR40 doi: 10.1159/000134296 – volume: 10 start-page: 6645 year: 2013 ident: 3186_CR46 publication-title: Int J Environ Res Public Health doi: 10.3390/ijerph10126645 – ident: 3186_CR2 doi: 10.1136/bmj.e2451 |
| SSID | ssj0017826 |
| Score | 2.3069687 |
| Snippet | Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the intra- and... Background Insight into the variability of older adults' sedentary time is needed to inform future interventions. The aim of this study was to examine the... Background Insight into the variability of older adults’ sedentary time is needed to inform future interventions. The aim of this study was to examine the... Abstract Background Insight into the variability of older adults’ sedentary time is needed to inform future interventions. The aim of this study was to examine... |
| SourceID | doaj pubmedcentral proquest gale pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | 495 |
| SubjectTerms | Accelerometers Aged Behavior Data collection Demographic aspects Demography diurnal patterns elderly epidemiology Exercise Geographical distribution Geriatrics Health aspects Health behavior Neighborhoods Older people Physical activity Retirement Sedentary behavior Sitting time Sociodemographics Surveys Variability |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3NbtQwEB6hHhAXRPkNFGQkJA7Iapw4dsytIKoKCU5U6s2yHUesBEnV3YJ662vwFjwTT8KM4402QoILp12t7U3sGXu-scffALyotAit14KLTjguq7LnxtAmjihdr01F9EMUbfFRnZzK92fN2U6qL4oJm-iBp4E77Jx3CJGbWHcSTXfAb6JvYx-EjtFLT6sv2rytM5XPD9Duqe0VmVYdrnEV1ppT5DopseJiYYYSW_-fa_KOUVoGTO5YoOM7cDtDR3Y0vfI-3IjDXbj5IR-O34OfKHJG0YJs7BkN-si7-HWipF4FljPrMDd07DxLh5FZy1uybDUwRIP4gQ_nqdoqRSRmuM6-oVs9sXpf0RNGyu_NEn_H-tf1D7aOdOfXXVwxylf_Gv-AjX7e88X2m-8jT6kpsEpitb0Pp8fvPr094TkhAw-Nqje8rnQwWnRBIqjqReiji3QJpA5lVwpvOhVJ8ukwW3sfjHIOAYyPUlQ47qp-AHvDOMRHwFxlWulD4xEvSXShXIyqFdp3oXSN8K4AsZWPDZmtnJJmfLHJa2mVnWRqUaY2ydSKAl7Nbc4nro6_1n5DYp9rEs92-gG1z2bts__SvgJektJYWg3w9YLLlxqwk8SrZY80Qjp0OWtdwMGiJs7isCzeqp3Nq8jaVogkEIHr0hTwfC6mlhQZN8TxMtVB0KoaKQt4OGnp3KWa2OUQ8hegF_q76POyZFh9Thzj6MW3jVSP_8cgPYFbVZp6ipfmAPY2F5fxKUK5jX-WZu1vWttK5Q priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Health & Medical Collection dbid: 7X7 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3NbtQwELagSIgL4p9AQUZC4oCsxoljJ72ggqgqJDhRaW-W_wIrlWTZbEG98Rp9iz5Tn4QZxxsaIfW0q_VkE2fG42_s8TeEvC4Ud7VVnHHPDRNF3rKmwUUcnptWNQXSD2G2xRd5dCw-LapFWnAbUlrl1idGR-17h2vkewV4VUAjKm_erX4yrBqFu6uphMZNcgupy9Cq1WIKuDjMfnJ7UKaWewP4YqUY5q-jKUvGZ5NR5Oz_3zNfmZrmaZNX5qHDe-RuApD0YNT4fXIjdA_I7c9pi_whuQDFU8wZpH1L8dX3zIcfIzH10tFUX4eaztNV0hHFyS0tzNJlRwETwgfcnEWxZcxLTKCd_oLgeuT2PsM79Fjlm0YWj-HyzzkdAp78NeszilXr9-EPaG-nlV-4fvO7Z7FABYhEbttH5Pjw49cPRyyVZWCukuWGlYVyjeLeCYBWLXdtMAGPgpQu9zm3jZcB9R-3tJW1rpHGAIyxQfAC3rssH5Odru_CU0JN0dTCusoCahIQSJkQZM2V9S43FbcmI3yrH-0SZzmWzjjRMXappR51qkGnOupU84y8na5ZjYwd10q_R7VPksi2HX_o1990GrzaG2sgTKtC6QXARwffeFuH1nEVghU2I2_QaDT6BHg8Z9LRBugksmvpAwXADgLPUmVkdyYJY9nNm7dmp5MvGfQ_y8_Iq6kZr8T8uC70p1EGoKushMjIk9FKpy6VyDEHwD8jama_sz7PW7rl98g0DrF8XQn57PrHek7uFHFQSZY3u2Rnsz4NLwCqbezLOB7_AvwiQOc priority: 102 providerName: ProQuest |
| Title | The role of socio-demographic factors and physical functioning in the intra- and interpersonal variability of older adults’ sedentary time: an observational two-country study |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/35681115 https://www.proquest.com/docview/2678192709 https://www.proquest.com/docview/2675606544 https://pubmed.ncbi.nlm.nih.gov/PMC9178546 https://doaj.org/article/daba4285e3d4441c85e1f8efc17eeb4b |
| Volume | 22 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3fb9MwELbGJiFeEL8JjMpISHtAhjhx7AQJoRVtmpA2oYlKFS-W7Tij0khG2wH9p_gbuXPcsogJ8dJWjZ3Eubvcd_b5O0JeZIq70irOeM0NE1nasKrCSRyemkZVGdIPYbbFiTyaiA_TYrpF1uWO4gNcXBvaYT2pyfz81c9vq3dg8G-DwZfy9QLesUoxzEtHFZUMoqEd8EwKKxociz-rCuAN-91GcG-Aa8r1JpprzzFwVIHP_--39hW3NUypvOKjDu-Q2xFc0v1eG-6SLd_eIzeP4_L5ffILlIJiPiHtGopi6Vjtv_ak1TNHY-0datqaXkT5UXR8cdKWzloKeBG-4OIsNJuFnMUI6Ol3CLx73u8VXqHDCuA0MHws9ujC455gM19RrGf_BrrTzm7mhKH38kfHQukKaBJYbx-QyeHBp_dHLBZsYK6Q-ZLlmXKV4rUTALoa7hpvPG4SyV1ap9xWtfSoGWGxW1nrKmkMABzrBc_gqcv8Idluu9Y_JtRkVSmsKyzgKQEhlvFellzZ2qWm4NYkhK-lo11kM8eiGuc6RDWl1L1ENUhUB4lqnpCXmz4XPZfHP1uPUeiblsjDHf7o5mc6mrWujTUQwBU-rwUASwe_eFP6xnHlvRU2IXuoMhr1F27PmbjpAQaJvFt6XwHkg5A0VwnZHbQEK3fDw2ul02sj0RkgDUDoKq0S8nxzGHti5lzru8vQBkCtLIRIyKNeRzdDypF9DkKChKiB9g7GPDzSzr4EDnKI8stCyCf_Pb6n5FYWrEuytNol28v5pX8GeG5pR-SGmqoR2RkfnHw8HYVZkVEwXPg8HX_-Da_GTKE |
| linkProvider | Scholars Portal |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtR3JbtQw1CpFAi6InUABI4E4IKtxFjtBQqgs1ZQup1aam7EdByLRZJiZUs2N3-AnEN_El_Ces9AIqbeeJho_J7bebr-FkGeR5DYzkjNecM2SKCxZnuMhDg91KfMIyw9htMWBmBwlH6fpdI386nNhMKyyl4leUBeNxTPyzQikKlgjMszfzL4x7BqFt6t9C42WLHbd6hRctsXrnfeA3-dRtP3h8N2EdV0FmE1FvGRxJG0ueWETsAxKbkunHWYyxDYsQm7yQjhcvr-RlcbYXGgNWti4hEfAASKG914il0Hxhujsyeng4HHQtqJPzMnE5gJkv5QM4-WRdQTjI-XnewT8rwnOqMJxmOYZvbd9g1zvDFa61VLYTbLm6lvkyn53JX-b_AZCoxijSJuSIqobVrjjthB2ZWnXz4fquqCzjiYoKtPuIJhWNQUbFH7g48yDVT4OsnMS6Hdw5tta4iv8QoNdxamvGrL48-MnXTjMNNbzFV1Wx-4VvIA2ZjhphvnL04b5hhgA4mvp3iFHF4Kwu2S9bmp3n1Ad5VlibGrASkvAcdPOiYxLU9hQp9zogPAeP8p2NdKxVcdX5X2lTKgWpwpwqjxOFQ_Iy2HOrK0Qci70W0T7AInVvf0fzfyz6oSFKrTR4BamLi4SMFctPPEyc6Xl0jmTmIC8QKJRKINgeVZ3qRSwSazmpbYkGJLg6MYyIBsjSJAddjzck53qZNdC_eO0gDwdhnEmxuPVrjnxMGAqizRJAnKvpdJhSzHWtANHIyByRL-jPY9H6uqLr2yeAwuliXhw_rKekKuTw_09tbdzsPuQXIs8gwkW5htkfTk_cY_ATFyax543Kfl00cLgL8alfOQ |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=The+role+of+socio-demographic+factors+and+physical+functioning+in+the+intra-+and+interpersonal+variability+of+older+adults%27+sedentary+time%3A+an+observational+two-country+study&rft.jtitle=BMC+geriatrics&rft.au=Compernolle%2C+Sofie&rft.au=Cerin%2C+Ester&rft.au=Barnett%2C+Anthony&rft.au=Zhang%2C+Casper+J.+P&rft.date=2022-06-09&rft.pub=BioMed+Central+Ltd&rft.issn=1471-2318&rft.eissn=1471-2318&rft.volume=22&rft.issue=1&rft_id=info:doi/10.1186%2Fs12877-022-03186-1&rft.externalDocID=A706611437 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1471-2318&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1471-2318&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1471-2318&client=summon |