Skip header and navigation

4 records – page 1 of 1.

Accelerometer-determined physical activity and self-reported health in a population of older adults (65-85 years): a cross-sectional study.

https://arctichealth.org/en/permalink/ahliterature264724
Source
BMC Public Health. 2014;14:284
Publication Type
Article
Date
2014
Author
Hilde Lohne-Seiler
Bjorge H Hansen
Elin Kolle
Sigmund A Anderssen
Source
BMC Public Health. 2014;14:284
Date
2014
Language
English
Publication Type
Article
Keywords
Accelerometry - statistics & numerical data
Activities of Daily Living - classification
Age Factors
Aged
Aged, 80 and over
Cross-Sectional Studies
Exercise
Female
Guideline Adherence - statistics & numerical data
Health status
Humans
Life Style
Male
Middle Aged
Norway
Personal Satisfaction
Quality of Life
Questionnaires
Registries
Regression Analysis
Sedentary lifestyle
Self Report
Abstract
The link between physical activity (PA) and prevention of disease, maintenance of independence, and improved quality of life in older adults is supported by strong evidence. However, there is a lack of data on population levels in this regard, where PA level has been measured objectively. The main aims were therefore to assess the level of accelerometer-determined PA and to examine its associations with self-reported health in a population of Norwegian older adults (65-85 years).
This was a part of a national multicenter study. Participants for the initial study were randomly selected from the national population registry, and the current study included those of the initial sample aged 65-85 years. The ActiGraph GT1M accelerometer was used to measure PA for seven consecutive days. A questionnaire was used to register self-reported health. Univariate analysis of variance with Bonferroni adjustments were used for comparisons between multiple groups.
A total of 560 participants had valid activity registrations. Mean age (SD) was 71.8 (5.6) years for women (n=282) and 71.7 (5.2) years for men (n=278). Overall PA level (cpm) differed considerably between the age groups where the oldest (80-85 y) displayed a 50% lower activity level compared to the youngest (65-70 y). No sex differences were observed in overall PA within each age group. Significantly more men spent time being sedentary (65-69 and 70-74 years) and achieved more minutes of moderate to vigorous PA (MVPA) (75-79 years) compared to women. Significantly more women (except for the oldest), spent more minutes of low-intensity PA compared to men. PA differed across levels of self-reported health and a 51% higher overall PA level was registered in those, with "very good health" compared to those with "poor/very poor health".
Norwegian older adults PA levels differed by age. Overall, the elderly spent 66% of their time being sedentary and only 3% in MVPA. Twenty one percent of the participants fulfilled the current Norwegian PA recommendations. Overall PA levels were associated with self-reported health.
Notes
Cites: Scand J Soc Med. 1996 Sep;24(3):218-248878376
Cites: Age Ageing. 2013 Mar;42(2):222-923117467
Cites: Am J Prev Med. 1998 Nov;15(4):316-339838975
Cites: Eur J Cardiovasc Prev Rehabil. 2005 Apr;12(2):102-1415785295
Cites: Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S512-2216294114
Cites: Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S531-4316294116
Cites: Qual Life Res. 2006 Mar;15(2):191-20116468076
Cites: Diabetes Care. 2007 Jun;30(6):1384-917473059
Cites: Med Sci Sports Exerc. 2007 Sep;39(9):1502-817805081
Cites: Med Sci Sports Exerc. 2008 Jan;40(1):181-818091006
Cites: Med Sci Sports Exerc. 2008 Jan;40(1):59-6418091020
Cites: Am J Epidemiol. 2008 Apr 1;167(7):875-8118303006
Cites: Scand J Med Sci Sports. 2008 Jun;18(3):309-1717645730
Cites: Br J Sports Med. 2009 Jun;43(6):442-5018487253
Cites: Med Sci Sports Exerc. 2009 May;41(5):998-100519346988
Cites: Clin Geriatr Med. 2009 Nov;25(4):661-75, viii19944266
Cites: Am J Epidemiol. 2010 May 15;171(10):1055-6420406758
Cites: Am J Epidemiol. 2010 May 15;171(10):1065-820406761
Cites: Scand J Med Sci Sports. 2010 Feb;20(1):e41-719422647
Cites: Med Sci Sports Exerc. 2011 Apr;43(4):647-5420689449
Cites: Health Rep. 2011 Mar;22(1):7-1421510585
Cites: Prev Chronic Dis. 2012;9:E2622172193
Cites: Med Sci Sports Exerc. 2012 Feb;44(2):266-7221796052
Cites: Res Q Exerc Sport. 2000 Jun;71(2 Suppl):S1-1410925819
Cites: WHO Reg Publ Eur Ser. 1996;58:i-xiii, 1-1618857196
Cites: Med Sci Sports Exerc. 2000 Jul;32(7):1327-3810912901
Cites: Arterioscler Thromb Vasc Biol. 2012 Feb;32(2):500-522075247
Cites: Med Sci Sports Exerc. 2001 Jun;33(6 Suppl):S598-608; discussion S609-1011427784
Cites: Med Sci Sports Exerc. 2001 Jul;33(7):1233-4011445774
Cites: J Gerontol A Biol Sci Med Sci. 2001 Oct;56 Spec No 2:36-4611730236
Cites: Physiol Meas. 2004 Apr;25(2):R1-2015132305
Cites: J Sports Sci. 2004 Aug;22(8):703-2515370483
Cites: J Gerontol. 1993 Jan;48(1):M10-48418139
Cites: Glob Health Action. 2012;5. doi: 10.3402/gha.v5i0.848822833712
Cites: Health Care Women Int. 1997 Mar-Apr;18(2):165-749119792
PubMed ID
24673834 View in PubMed
Less detail

Accelerometer measured level of physical activity indoors and outdoors during preschool time in Sweden and the United States.

https://arctichealth.org/en/permalink/ahliterature130954
Source
J Phys Act Health. 2012 Aug;9(6):801-8
Publication Type
Article
Date
Aug-2012
Author
Anders Raustorp
Peter Pagels
Cecilia Boldemann
Nilda Cosco
Margareta Söderström
Fredrika Mårtensson
Author Affiliation
School of Sport Sciences, Linnaeus University, Kalmar, Sweden.
Source
J Phys Act Health. 2012 Aug;9(6):801-8
Date
Aug-2012
Language
English
Publication Type
Article
Keywords
Accelerometry - statistics & numerical data
Body mass index
Body Weights and Measures
Child, Preschool
Cross-Cultural Comparison
Exercise
Female
Humans
Male
North Carolina - epidemiology
Sex Factors
Sweden - epidemiology
Time Factors
United States - epidemiology
Abstract
It is important to understand the correlates of physical activity (PA) to influence policy and create environments that promote PA among preschool children. We compared preschoolers' PA in Swedish and in US settings and objectively examined differences boys' and girls' indoor and outdoor PA regarding different intensity levels and sedentary behavior.
Accelerometer determined PA in 50 children with mean age 52 months, (range 40-67) was recorded during preschool time for 5 consecutive weekdays at 4 sites. The children wore an Actigraph GTIM Monitor.
Raleigh preschool children, opposite to Malmö preschoolers spent significantly more time indoors than outdoors (P
PubMed ID
21952100 View in PubMed
Less detail

The association between accelerometer-measured patterns of sedentary time and health risk in children and youth: results from the Canadian Health Measures Survey.

https://arctichealth.org/en/permalink/ahliterature115533
Source
BMC Public Health. 2013;13:200
Publication Type
Article
Date
2013
Author
Rachel C Colley
Didier Garriguet
Ian Janssen
Suzy L Wong
Travis J Saunders
Valerie Carson
Mark S Tremblay
Author Affiliation
Health Analysis Division, Statistics Canada, Ottawa, ON, Canada. rcolley@cheo.on.ca
Source
BMC Public Health. 2013;13:200
Date
2013
Language
English
Publication Type
Article
Keywords
Accelerometry - statistics & numerical data
Adolescent
Blood pressure
Body mass index
Canada
Child
Cholesterol - blood
Female
Health status
Health Surveys
Humans
Male
Regression Analysis
Risk factors
Sedentary lifestyle
Time Factors
Waist Circumference
Young Adult
Abstract
Self-reported screen time is associated with elevated health risk in children and youth; however, research examining the relationship between accelerometer-measured sedentary time and health risk has reported mixed findings. The purpose of this study was to examine the association between accelerometer-measured patterns of sedentary time and health risk in children and youth.
The results are based on 1,608 children and youth aged 6 to 19 years from the Canadian Health Measures Survey (2007-2009). Sedentary time was measured using the Actical accelerometer. Breaks in sedentary time and prolonged bouts of sedentary time lasting 20 to 120 minutes were derived for all days, weekend days and during the after-school period (i.e., after 3 pm on weekdays). Regression analyses were used to examine the association between patterns of sedentary time and body mass index (BMI), waist circumference, blood pressure and non-HDL cholesterol.
Boys accumulated more sedentary time on weekdays after 3 pm and had a higher number of breaks in sedentary time compared to girls. Overweight/obese boys (aged 6-19 years) accumulated more sedentary time after 3 pm on weekdays (282 vs. 259 min, p
Notes
Cites: J Phys Act Health. 2011 Jul;8(5):693-821734315
Cites: Int J Pediatr Obes. 2009;4(1):2-2718720173
Cites: PLoS One. 2011;6(11):e2664322069461
Cites: Int J Behav Nutr Phys Act. 2011;8:12022035260
Cites: J Pediatr. 2012 Jan;160(1):104-10.e221839464
Cites: JAMA. 2012 Feb 15;307(7):704-1222337681
Cites: Health Promot Pract. 2012 May;13(3):320-3022447666
Cites: Appl Physiol Nutr Metab. 2012 Jun;37(3):540-222540258
Cites: Pediatr Obes. 2012 Jun;7(3):251-822461356
Cites: PLoS One. 2012;7(5):e3665722586487
Cites: Appl Physiol Nutr Metab. 2009 Apr;34(2):136-4219370043
Cites: Arch Pediatr Adolesc Med. 2009 Aug;163(8):724-3019652104
Cites: Am J Clin Nutr. 2009 Nov;90(5):1185-9219776141
Cites: Int J Pediatr Obes. 2009;4(4):353-919922052
Cites: Rev Esp Cardiol. 2010 Mar;63(3):277-8520196988
Cites: Health Rep. 2010 Mar;21(1):63-920426228
Cites: Health Rep. 2010 Mar;21(1):71-820426229
Cites: Appl Physiol Nutr Metab. 2010 Dec;35(6):725-4021164543
Cites: Health Rep. 2011 Mar;22(1):15-2321510586
Cites: J Phys Act Health. 2011 May;8(4):587-9121597132
Cites: BMC Public Health. 2011;11:27421542910
Cites: J Phys Act Health. 2011 Jul;8(5):613-2521734306
Cites: PLoS One. 2012;7(5):e3634522590532
Cites: BMC Public Health. 2012;12:40622672654
Cites: BMJ. 2000 May 6;320(7244):1240-310797032
Cites: Am J Cardiol. 2000 Aug 1;86(3):299-30410922437
Cites: Am J Hypertens. 2003 Jun;16(6):494-712799100
Cites: Eur J Clin Nutr. 2004 Jul;58(7):1011-515220942
Cites: Med Sci Sports Exerc. 2004 Sep;36(9):1625-3115354047
Cites: Stat Methods Med Res. 1996 Sep;5(3):283-3108931197
Cites: J Adolesc. 2006 Jun;29(3):333-4916246411
Cites: Prev Med. 2007 May;44(5):421-517320158
Cites: Health Rep. 2007;18 Suppl:7-2018210866
Cites: Health Rep. 2007;18 Suppl:37-5118210869
Cites: Diabetes Care. 2008 Mar;31(3):569-7518070991
Cites: Diabetes Care. 2008 Apr;31(4):661-618252901
Cites: J Public Health (Oxf). 2008 Jun;30(2):153-6018375469
Cites: Pediatr Exerc Sci. 2008 Nov;20(4):446-5619168921
Cites: Int J Behav Nutr Phys Act. 2011;8:9821936895
PubMed ID
23497190 View in PubMed
Less detail

A comparison of standard and compositional data analysis in studies addressing group differences in sedentary behavior and physical activity.

https://arctichealth.org/en/permalink/ahliterature296867
Source
Int J Behav Nutr Phys Act. 2018 06 15; 15(1):53
Publication Type
Comparative Study
Journal Article
Research Support, Non-U.S. Gov't
Date
06-15-2018
Author
Nidhi Gupta
Svend Erik Mathiassen
Glòria Mateu-Figueras
Marina Heiden
David M Hallman
Marie Birk Jørgensen
Andreas Holtermann
Author Affiliation
National Research Centre for the Working Environment, Lersø Parkallé 105, 2100, Copenhagen, Denmark. ngu@nrcwe.dk.
Source
Int J Behav Nutr Phys Act. 2018 06 15; 15(1):53
Date
06-15-2018
Language
English
Publication Type
Comparative Study
Journal Article
Research Support, Non-U.S. Gov't
Keywords
Accelerometry - statistics & numerical data
Adult
Age Factors
Cross-Sectional Studies
Denmark
Exercise
Female
Humans
Male
Middle Aged
Sedentary Behavior
Sex Factors
Sleep
Surveys and Questionnaires
Abstract
Data on time spent in physical activity, sedentary behavior and sleep during a day is compositional in nature, i.e. they add up to a constant value. Compositional data have fundamentally different properties from unconstrained data in real space, and require other analytical procedures, referred to as compositional data analysis (CoDA). Most physical activity and sedentary behavior studies, however, still apply analytical procedures adapted to data in real space, which can lead to misleading results. The present study describes a comparison of time spent sedentary and in physical activity between age groups and sexes, and investigates the extent to which results obtained by CoDA differ from those obtained using standard analytical procedures.
Time spent sedentary, standing, and in physical activity (walking/running/stair climbing/cycling) during work and leisure was determined for 1-4 days among 677 blue-collar workers using accelerometry. Differences between sexes and age groups were tested using MANOVA, using both a standard and a CoDA approach based on isometric log-ratio transformed data.
When determining differences between sexes for different activities time at work, the effect size using standard analysis (?2?=?0.045, p?
PubMed ID
29903009 View in PubMed
Less detail