Stability of Physical Activity across the Lifespan

Frıedman, Howard S.; Martin, Leslie R.; Tucker, Joan S.; Criqui, Michael H.; Kern, Margaret L.; Reynolds, Chandra A.

doi:10.1177/1359105308095963

Cited by 103 publications

(79 citation statements)

References 37 publications

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“…In females these ranged between -0.04 [27] (non-significant over 7 years) and 0.37 [29][30][31][32] (p<0.001 over 6 years). These between gender differences appeared to reduce with increasing age at baseline (Figure 2), and to mediate the strength of the associations found in those studies which combined their data, correlation coefficients ranging from 0.06 [26] (non-significant over 50 years) to 0.20 [25] (p<0.05 over 24 years).…”

Section: Associations Between Physical Activity Levels At Baseline Anmentioning

confidence: 85%

“…Outcomes were reported inconsistently, the majority referring to all leisure activity, but some only reporting sports participation [17,18]. Frequently, outcomes were reported as a product of frequency, intensity and duration (in terms of total time spent in moderate to vigorous physical activity, daily energy expenditure or as a physical activity score), although some reported only frequency of activity [24,25] or intensity [26] at either or both time-points.…”

Section: Study Characteristics For Physical Activity Tracking Datamentioning

confidence: 99%

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Tracking of obesity-related behaviours from childhood to adulthood: A systematic review

et al. 2011

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(2011) 'Tracking of obesity-related behaviours from childhood to adulthood : a systematic review. ', Maturitas., 70 (3). pp. 266-284. Further information on publisher's website:http://dx.doi.org/10.1016/j.maturitas. 2011.08.005 Publisher's copyright statement: NOTICE: this is the author's version of a work that was accepted for publication in Maturitas. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reected in this document. Changes may have been made to this work since it was submitted for publication. A denitive version was subsequently published in Maturitas, 70/3, 2011Maturitas, 70/3, , 10.1016Maturitas, 70/3, /j.maturitas.2011 Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Key words: tracking; diet; physical activity; childhood obesity; adult obesity. ABSTRACTObesity in childhood carries a wide range of physical, psychological and social disbenefits and also increases the risk of adult obesity with its well-recognised, enhanced risk of several common complex diseases as well as adverse socioeconomic and psychosocial sequelae. Understanding the tracking of the two key modifiable behaviours, food consumption and physical activity, between childhood and adulthood may illuminate the childhood determinants of adult obesity and contribute to the development of effective interventions.We performed a systematic review of the available literature on tracking of both physical activity and of dietary intake between childhood and adulthood by searching MEDLINE, EMBASE, CINAHL, PSYCInfo, Google and Google Scholar. For inclusion, studies had to report baseline measurements when the children were less than, or equal to, 18 years and to report follow-up for at least 5 years to any age over 18 years.After removal of duplicates, 9625 search hits were screened by title and/or abstract and 79 potentially relevant papers were identified and full papers obtained. In total 39 papers were included in this analysis. Of these, 11 papers (from 5 studies) reported data on tracking of diet from childhood to adulthood and 28 papers (from 16 studies) reported data on tracking of physical activity or inactivity.Despite the diversity of study design and measurement methodology, we found evidence of tracking of both physical activity and of diet between childhood and adulthood with estimates of strength of tracking of a similar order for both behaviours. Because of the inherent methodological difficulties...

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Section: Associations Between Physical Activity Levels At Baseline Anmentioning

confidence: 85%

Section: Study Characteristics For Physical Activity Tracking Datamentioning

confidence: 99%

Tracking of obesity-related behaviours from childhood to adulthood: A systematic review

et al. 2011

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“…Thus, the inherent imprecision in a single measurement of both lifestyle factors and telomere length may non-differentially influence the observed estimates of association. However, good short-term reliability in measurement of telomere length over a period of months has been demonstrated (64), and longitudinal panel studies have also demonstrated some degree of stability in lifestyle factors measured in adult populations (65)(66)(67)(68)(69)(70)(71).…”

Section: Cancer Epidemiol Biomarkers Prev; 25(2) February 2016mentioning

confidence: 99%

The Influence of Alcohol Consumption, Cigarette Smoking, and Physical Activity on Leukocyte Telomere Length

Latifovic

Peacock

Massey

et al. 2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background: Telomeres protect from DNA degradation and maintain chromosomal stability. Short telomeres have been associated with an increased risk of cancer at several sites. However, there is limited knowledge about the lifestyle determinants of telomere length. We aimed to determine the effect of three factors, known to be important in cancer etiology, on relative leukocyte telomere length (rLTL): alcohol consumption, smoking, and physical activity.Methods: This cross-sectional study included 477 healthy volunteers ages 20 to 50 years who completed a questionnaire and provided a fasting blood sample. Multiplex quantitative realtime PCR (qPCR) was used to measure rLTL. Regression coefficients were calculated using multiple linear regression while controlling for important covariates.Results: There was no association between alcohol consumption and rLTL. Daily smokers and those in the middle and lower

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“…Some of these associations have limited magnitude; however, previous studies have shown that cardiovascular risk factors and associated lifestyle developed in childhood persist and amplify in adulthood. [36][37][38] Thus, it…”

Section: Strengths and Limitationsmentioning

confidence: 99%