The DOI matches its Crossref record; 50 of the 55 references it cites were found in a registry or an index; none of the 55 sources its claims cite is checked for support yet.
Using accelerometers to measure physical activity in large-scale epidemiological studies: issues and challenges
Open accessAbstract
Background: The current guidelines for aerobic activity require that adults carry out ≥150 min/week of moderate-intensity physical activity, with a large body of epidemiological evidence showing this level of activity to decrease the incidence of many chronic diseases. Less is known about whether light-intensity activities also have such benefits, and whether sedentary behaviour is an independent predictor of increased risks of these chronic diseases, as imprecise assessments of these behaviours and cross-sectional study designs have limited knowledge to date. Methods: Recent technological advances in assessment methods have made the use of movement sensors, such as the accelerometer, feasible for use in longitudinal, large-scale epidemiological studies. Several such studies are collecting sensor-assessed, objective measures of physical activity with the aim of relating these to the development of clinical endpoints. This is a relatively new area of research; thus, in this article, we use the Women's Health Study (WHS) as a case study to illustrate the challenges related to data collection, data processing and analyses of the vast amount of data collected. Results: The WHS plans to collect 7 days of accelerometer-assessed physical activity and sedentary behaviour in ∼18 000 women aged ≥62 years. Several logistical challenges exist in collecting data; nonetheless, as of 31 August 2013, 11 590 women have already provided some data. In addition, the WHS experience on data reduction and data analyses can help inform other similar large-scale epidemiological studies. Conclusions: Important data on the health effects of light-intensity activity and sedentary behaviour will emerge from large-scale epidemiological studies collecting objective assessments of these behaviours.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This methods/commentary paper argues that accelerometers can objectively assess light-intensity physical activity and sedentary behavior in large longitudinal epidemiologic studies, addressing gaps left by self-report. It uses the Women’s Health Study (WHS) accelerometer ancillary study as a case study to illustrate logistical, data-reduction, and analytic challenges.
Key findings
- Current aerobic guidelines recommend ≥150 minutes/week of moderate-intensity activity, but they lack recommendations for light-intensity activity because few data are available, not because existing data show no benefit.
- In the WHS accelerometer study, as of 31 August 2013, 23,266 women were invited; 19,432 (84%) responded; 15,314 (79% of respondents) agreed to participate; and 11,590 had worn and returned devices. The study projects participation by ~18,000 (~63%) of the remaining 28,680 eligible women.
- An interim WHS dataset of 8,373 women (mean age 71 years; 20% obese; 4% current smokers) found 95% wore the device for ≥10 hours/day on ≥4 days. The low-frequency extension filter substantially overestimated steps: median ~5,000 steps/day with the normal filter vs ~13,000 steps/day with the LFE filter.
- Self-reported TV viewing and accelerometer-assessed sedentary time had a correlation of only 0.22, and the paper notes that some self-reported sedentary associations have not been replicated with accelerometry; longitudinal objective studies are needed.
Methods
- Design: A methods/commentary paper using the Women’s Health Study (WHS) as a case study to discuss issues and challenges in accelerometer use for large-scale epidemiologic research.
- Data/sample: The WHS was a completed randomized trial (1992–2004) of 39,876 healthy women ≥45 years; 33,681 (89% of those alive) consented to continue observational follow-up. The accelerometer ancillary study began in 2011, asked women to wear an ActiGraph GT3X+ on the hip during all waking hours for 7 days, and aimed to collect data in ~18,000 women aged ≥62 years.
- Main analysis: Descriptive reporting of WHS recruitment, compliance, data-reduction decisions, and preliminary accelerometer data, including comparison with a comparably aged US national sample; no formal disease-endpoint analysis is presented.
Limitations
- Stated in the paper: Hip-worn accelerometers primarily measure locomotor activity, miss upper-body movement, cannot account for carried weight, and do not measure posture, so they cannot distinguish sitting from standing still.
- Stated in the paper: There is no consensus on wear-time algorithms, cutpoints, or best practices for accelerometer data reduction and analysis; cutpoints are often laboratory-derived, may not apply to older populations, and energy-expenditure predictions can under- or overestimate.
- Evident from the text: The WHS preliminary data are interim and descriptive, with no hard clinical endpoints yet; findings come from a single cohort of older women, limiting generalizability, and the paper is not a systematic review or original prospective outcome study.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
37 Not checked yet · 15 Own interpretation · 6 Own result · 6 No basis given · 1 Own method
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“as of 31 August 2013, 11,590 women have already provided some data.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Abstract > Results
plainn = 11,590- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“They complied well with instructions: 95% wore their device for ≥10 hours each day on ≥4 days (conventionally regarded as “valid” data[49]).”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Some preliminary data
What the sources say
- Not checked yetcites [49] Tudor-Locke, 2012, A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003-2006, Prev Chronic Dis
plainn = 8,373- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Participants do lose or fail to return their accelerometers; the rate of loss in the WHS is 2.1%.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Logistical challenges
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Based on preliminary data, we have found that using logs only to record whether the device was “worn” or “not worn” for the day, but not to indicate times (minimizing participant burden and likelihood of missing data), and then applying the Choi algorithm best reflected actual wear-time as assessed by participant detailed logs.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Challenges related to data reduction
What the sources say
- Not checked yetcites [39] source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Preliminary data in the WHS indicates that the LFE filter substantially overestimates steps taken per day (median of ~5,000 steps per day using the normal filter; ~13,000 steps per day using the LFE filter); thus, we do not recommend this option for assessing steps.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Challenges related to data reduction
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, observational epidemiologic studies that rely on self-reports have tended to limit their assessments to activities of moderate- and vigorous-intensity only.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Current Physical Activity Guidelines – Why No Prescription for Light-Intensity Activity?
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“It is unclear how well self-reported TV/screen time reflects total sedentary time.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Sedentary Behaviour – An Independent Risk Factor?
What the sources say
- Not checked yetcites [22] Clark, 2011, Relationship of television time with accelerometer-derived sedentary time: NHANES, Med Sci Sports Exerc source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Indeed, the US guidelines acknowledge that “we don’t understand enough about whether doing more baseline activity results in health benefits”.[8]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Current Physical Activity Guidelines – Why No Prescription for Light-Intensity Activity?
What the sources say
- Not checked yetcites [8] U.S. Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans. Secondary 2008 Physical Activity Guidelines for Americans. http://www.health.gov/paguidelines/
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“There do exist data from several studies that used accelerometers to objectively measure sedentary behavior, showing unfavourable associations with risk factors (e.g., the Australian AusDiab study,[24] the Proactiv UK trial,[25] the US National Health and Nutrition Examination Survey[26]).”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Sedentary Behaviour – An Independent Risk Factor?
What the sources say
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“For example, in a recent study of almost one-quarter million US older adults (50-71 years) free from cardiovascular disease and cancer, more time spent on TV viewing was associated with higher all-cause mortality rates, regardless of physical activity level.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Sedentary Behaviour – An Independent Risk Factor?
What the sources say
- Not checked yetcites [18] source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 13
- It may state two separate claims as one. 27
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Several logistical challenges exist in collecting data; nonetheless as of 31 August 2013, 11,590 women have already provided some data.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Abstract > Results
plainn = 11,590- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Packets have been mailed to 14,073 women, of whom 11,590 have worn and returned their devices, 725 have requested participation at a later date (we assume some of these will eventually decline), and 1,087 have changed their mind about participation (the remaining 671 women were not due as of 31/8/13 to return their device).”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Logistical challenges
plainn = 14,073- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: Some of the 725 WHS women who requested later participation will eventually decline.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As of 31 August 2013, 23,266 women have been invited; 19,432 (84%) have responded, of whom 15,314 (79% of respondents) have agreed to participate (16% declined and 5% were not eligible because they cannot walk outside without assistance).”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Logistical challenges
plainn = 23,266- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Typically, in the main study, we obtain ~80% response to the first mailing of study questionnaires, another ~10% to the second, and a further ~5% to the third, for a total response of ~95%.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Logistical challenges
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Of those alive, 89% or 33,681 women consented, reporting on their health habits and medical history annually on questionnaires.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > The Women’s Health Study (WHS)
plainn = 33,681- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“While this seems negligible, 2.1% of the ~20,000 whom we anticipate sending accelerometers translates to 420 units, at substantial cost.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Logistical challenges
plaindirectn = 20,000- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Women were of mean age 71 years, 20% were obese, and 4% were current smokers.[30]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Some preliminary data
What the sources say
- Not checked yetcites [30] Shiroma EJ Freedson PS Trost SG . Patterns of accelerometer-assessed sedentary behavior in older women. JAMA; in press [published Online First].
plainn = 8,373- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Self-reports of physical activity are more reliable and valid for activities of moderate-to-vigorous intensity than light-intensity activities, which tend to be poorly reported.[9 10]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Current Physical Activity Guidelines – Why No Prescription for Light-Intensity Activity?
What the sources say
- Not checked yetcites [9 10]
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“A large body of epidemiologic literature, accumulated over more than 60 years, shows that individuals who are physically active have a better cardio-metabolic risk profile, lower rates of major non-communicable diseases, better physical and mental function, and live longer, compared with those inactive.[1-3]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Introduction
What the sources say
- Not checked yetcites [1] U.S. Department of Health & Human Services. 2008 Physical Activity Guidelines Advisory Committee report. Secondary 2008 Physical Activity Guidelines Advisory Committee report. http://www.health.gov/paguidelines/
- Not checked yetcites [2] source
- Not checked yetcites [3] World Health Organization. Global recommendations on physical activity for health. Geneva, Switzerland: WHO Press, 2010.
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Indeed, this high prevalence of insufficient activity has been estimated to cause as many deaths worldwide each year as smoking:[5]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Introduction
What the sources say
- Not checked yetcites [5] source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“With regard to aerobic activities, the guidelines require that adults carry out at least 150 minutes per week of moderate-intensity physical activity (e.g., brisk walking, whether for leisure or commuting), or 75 minutes per week of vigorous-intensity activity (e.g., jogging), or some combination of activities from both intensities that expend an equivalent amount of energy.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Current Physical Activity Guidelines – Why No Prescription for Light-Intensity Activity?
What the sources say
- Not checked yetcites [8] U.S. Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans. Secondary 2008 Physical Activity Guidelines for Americans. http://www.health.gov/paguidelines/
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“It is therefore unfortunate that approximately one-third of the world’s population does not get sufficient physical activity to meet current recommendations.[4]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Introduction
What the sources say
- Not checked yetcites [4] source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“As a consequence, current recommendations have no provision for light-intensity physical activity because few data are available, and not because existing data indicate no benefit.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Current Physical Activity Guidelines – Why No Prescription for Light-Intensity Activity?
What the sources say
- Not checked yetcites [8] U.S. Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans. Secondary 2008 Physical Activity Guidelines for Americans. http://www.health.gov/paguidelines/
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Accelerometers do not inform on body posture; thus, they cannot distinguish between sitting and standing still.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Using Accelerometers in Large-Scale Epidemiologic Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The expert panel did consider data from studies of physical activity in relation to cardio-metabolic risk factors (e.g., blood pressure, lipid parameters, measures of glucose and insulin processing); however, these data were considered supporting information.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Current Physical Activity Guidelines – Why No Prescription for Light-Intensity Activity?
What the sources say
- Not checked yetcites [1] U.S. Department of Health & Human Services. 2008 Physical Activity Guidelines Advisory Committee report. Secondary 2008 Physical Activity Guidelines Advisory Committee report. http://www.health.gov/paguidelines/
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“in a nationally representative sample of adults from the Health Survey for England, cross-sectional analyses showed consistent deleterious associations of self-reported sitting time with a panel of cardio-metabolic risk factors; however, when accelerometer measures of sedentary behaviour were analysed, little relation was observed.[23]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Sedentary Behaviour – An Independent Risk Factor?
What the sources say
- Not checked yetcites [23] source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The WHS is a completed randomized trial (1992-2004) testing aspirin and vitamin E for preventing cardiovascular disease and cancer among 39,876 healthy women, ≥45 years, living throughout the US.[32-34]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > The Women’s Health Study (WHS)
What the sources say
plainn = 39,876- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, these studies are predominantly cross-sectional in design; thus, one cannot ascertain the direction of association (i.e., does being sedentary result in poor health? Or, does being in poor health predispose one towards being sedentary?).”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Sedentary Behaviour – An Independent Risk Factor?
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Important data on the health effects of light-intensity activity and sedentary behaviour will emerge from large-scale epidemiologic studies collecting objective assessments of these behaviours.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Abstract > Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“In recently published results, the intensive intervention clearly improved cardio-metabolic risk factors; however, there was no difference in rates of cardiovascular events between groups after a median follow-up of 9.6 years, when the trial was stopped for futility.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Sedentary Behaviour – An Independent Risk Factor?
What the sources say
- Not checked yetcites [27] source
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“One movement sensor capable of measuring light-intensity physical activity and sedentary behaviour objectively is the accelerometer.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Using Accelerometers in Large-Scale Epidemiologic Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Recent technological advances in assessment methods have made the use of movement sensors, such as the accelerometer, feasible for use in longitudinal, large-scale epidemiologic studies.”
- Also stated in: § Using Accelerometers in Large-Scale Epidemiologic Studies · plain
“Thus, the accelerometer has now become feasible for use in large-scale studies, such as the examples shown in Table 1.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Abstract > Methods
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Using Accelerometers in Large-Scale Epidemiologic Studies · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“They primarily measure locomotor activity when worn over the hip (typical placement position), and so miss upper body movement.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Using Accelerometers in Large-Scale Epidemiologic Studies
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This has occurred because such studies typically require thousands, and even hundreds of thousands, of subjects to possess sufficient statistical power for investigating associations of physical activity with the incidence of hard clinical endpoints (e.g., major non-communicable diseases), and self-report is a cost-effective method of assessment.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Current Physical Activity Guidelines – Why No Prescription for Light-Intensity Activity?
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“This panel emphasized data from studies that examined the relation between physical activity and the risks of developing hard clinical endpoints, such as all-cause mortality, cardiovascular disease, type 2 diabetes, and cancer, reviewing the data from individual studies in detail.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Current Physical Activity Guidelines – Why No Prescription for Light-Intensity Activity?
What the sources say
- Not checked yetcites [1] U.S. Department of Health & Human Services. 2008 Physical Activity Guidelines Advisory Committee report. Secondary 2008 Physical Activity Guidelines Advisory Committee report. http://www.health.gov/paguidelines/
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Additionally, the WHS experience on data reduction and data analyses can help inform other similar large-scale epidemiologic studies.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Abstract > Results
plainn = 11,590- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: The Women’s Health Study is sufficiently similar to other large-scale epidemiologic studies that its data-reduction and analysis experience can inform them.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of the ~30,000 total women, we expect 1320 (4.4%) to be non-eligible, and project participation by ~18,000 (~63%) of the remaining 28,680.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Logistical challenges
hedgedn = 23,266- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, recent technological advances have made the use of movement sensors, such as the accelerometer, feasible for use in longitudinal, large-scale epidemiologic studies.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, we decided a priori to create an interim, closed dataset that comprised all women who returned their accelerometer by 31 March 2013 (n = 8,373; approximately half the total anticipated sample of ~18,000).”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Some preliminary data
plainn = 8,373- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“However, there is no consensus on what the “correct” cutpoints might be, with several proposed in the literature based on calibration studies primarily carried out under laboratory settings and not in free-living conditions.[40 41]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Challenges related to data analyses
What the sources say
- Not checked yetcites [40 41]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Efforts are ongoing to better take advantage of the rich data, such as pattern recognition or machine learning data analytic approaches to identify specific activities carried out.[47 48]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Challenges related to data analyses
What the sources say
- Not checked yetcites [47 48]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Recent work indicates a strong correlation between counts from the vertical axis and counts combined from all three axes using vector magnitude; thus, the vector magnitude data may not provide much additional information beyond vertical axis counts.[46]”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Challenges related to data analyses
What the sources say
- Not checked yetcites [46] source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Further, while best practices and standards have been proposed,[35-37] no consensus has been reached.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Challenges related to data reduction
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Automated algorithms are available (e.g., the commonly used Troiano[38] and Choi[39] algorithms) for wear-time determination; however, these were developed for protocols where participants received the device directly from investigators (thus, “mail noise” is not applicable).”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Challenges related to data reduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Imprecise assessments of these behaviours and cross-sectional study designs have limited our knowledge.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
The Women’s Health Study is sufficiently similar to other large-scale epidemiologic studies that its data-reduction and analysis experience can inform them.
“Additionally, the WHS experience on data reduction and data analyses can help inform other similar large-scale epidemiologic studies.”
The paper relies on this without support.
In the WHS older women, walking is the most common physical activity.
“for example, in the WHS below that includes older women, walking is the most common physical activity.”
The authors state this as an assumption.
Some of the 725 WHS women who requested later participation will eventually decline.
“725 have requested participation at a later date (we assume some of these will eventually decline)”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Although there is no clear consensus about how to define light-intensity activities by accelerometry [37, 38]”
From Proportion of children meeting recommendations for 24-hour movement guidelines and associations with adiposity in a 12-country study (2016) · cites this paper as [38]
In the citing paper
“The subjective measures likely underestimate the total amount of PA, 13 which may be attributed to the lack of consideration of light-intensity PA with an unstructured nature and dispersion during the day.14”
In the citing paper
“The relationship between light-intensity physical activity and health outcomes is largely unknown, partly due to the difficulty of its quantification as many methods to measure physical activity are not precise enough to capture such activities [38].”
From Proportion of children meeting recommendations for 24-hour movement guidelines and associations with adiposity in a 12-country study (2016) · cites this paper as [38]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
“48% (10,863/22,195) of invited participants returned a device with some data.”
§ Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges > A Case Study: Issues and Challenges > Logistical challenges
Reported 48 · recomputed 48.943456
Citations
Cites
The Physical Activity Guidelines for Americans
Piercy, K. L., Troiano, R. P., Ballard, R. M., Carlson, S. A., Fulton, J. E., Galuska, D. A., George, S. M., & Olson, R. D. (2018) · JAMA · doi:10.1001/jama.2018.14854 · Cited by 9,755
Lee, I.-M., Shiroma, E. J., Lobelo, F., Puska, P., Blair, S. N., & Katzmarzyk, P. T. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61031-9 · Cited by 8,215
Self-citationPhysical Activity in the United States Measured by Accelerometer
TROIANO, R. P., BERRIGAN, D., DODD, K. W., MÂSSE, L. C., TILERT, T., & MCDOWELL, M. (2008) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31815a51b3 · Cited by 7,638 · cited 1×
“Figure 1 shows their physical activity levels compared with a comparably aged US national sample (data are presented using commonly used cut-points for de fi ning different intensities of physical activity 18 38 ).”
MethodGlobal physical activity levels: surveillance progress, pitfalls, and prospects
Hallal, P. C., Andersen, L. B., Bull, F. C., Guthold, R., Haskell, W., & Ekelund, U. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60646-1 · Cited by 5,711 · cited 1×
“4 Indeed, this high prevalence of insuf fi cient activity has been estimated to cause as many deaths worldwide each year as smoking 5 : although smoking increases the risk of dying for the individual more than does inactivity, the prevalence of smoking worldwide (about one-quarter) is less than that…”
BackgroundCardiovascular effects of intensive lifestyle intervention in type 2 diabetes
The Look AHEAD Research Group (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1212914 · Cited by 2,908
Conducting accelerometer-based activity assessments in field-based research
TROST, S. G., MCIVER, K. L., & PATE, R. R. (2005) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000185657.86065.98 · Cited by 2,033
A Randomized Trial of Low-Dose Aspirin in the Primary Prevention of Cardiovascular Disease in Women
Ridker, P. M., Cook, N. R., Lee, I.-M., Gordon, D., Gaziano, J. M., Manson, J. E., Hennekens, C. H., & Buring, J. E. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa050613 · Cited by 1,945
Self-citationHu, F. B., Li, T. Y., Colditz, G. A., Willett, W. C., & Manson, J. E. (2003) · JAMA · doi:10.1001/jama.289.14.1785 · Cited by 1,892
Validation of Accelerometer Wear and Nonwear Time Classification Algorithm
CHOI, L., LIU, Z., MATTHEWS, C. E., & BUCHOWSKI, M. S. (2011) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3181ed61a3 · Cited by 1,804
Wilmot, E. G., Edwardson, C. L., Achana, F. A., Davies, M. J., Gorely, T., Gray, L. J., Khunti, K., Yates, T., & Biddle, S. J. H. (2012) · Diabetologia · doi:10.1007/s00125-012-2677-z · Cited by 1,789 · cited 1×
“…of epidemiological literature over the past 5 – 10 years has described the associations between sedentary behaviour and increased risks of all-cause mortality and cardio-metabolic diseases, 11 with plausible biological mechanisms (eg, lipoprotein lipase regulation) proposed from animal studies.”
Background
Research works printed but not linked: 1
- World Health Organization. Global recommendations on physical activity for health. Geneva, Switzerland: WHO Press, 2010.
Cited by
Sorted by citations
Items 101–200 of 414
Hubbard, G., O’Carroll, R. E., Munro, J., Mutrie, N., Haw, S. J., Mason, H., & Treweek, S. P. (2016) · Pilot and Feasibility Studies · doi:10.1186/s40814-016-0090-y · Cited by 35
Orientações para utilização de acelerômetros no Brasil
Sasaki, J. E., Coutinho, A. P. P., Santos, C., Bertuol, C., Minatto, G., Berria, J., Tonosaki, L. M. D., de Lima, L. R. A., Marchesan, M., da Silveira, P. M., et al. (2017) · Revista Brasileira de Atividade Física & Saúde · doi:10.12820/rbafs.v.22n2p110-126 · Cited by 35
Reliable assessment of physical activity in disease
Westerterp, K. R. (2014) · Current Opinion in Clinical Nutrition & Metabolic Care · doi:10.1097/mco.0000000000000080 · Cited by 34
Validity of proximity sensor-based wear-time detection using the ActiGraph GT9X
ARGUELLO, D. J., Andersen, K., Morton, A. L., et al. (2017) · Journal of Sports Sciences · doi:10.1080/02640414.2017.1398891 · Cited by 34
Wyszyńska, J., Matłosz, P., Podgórska‐Bednarz, J., Herbert, J., Przednówek, K., Baran, J., Dereń, K., & Mazur, A. (2019) · BMJ Open · doi:10.1136/bmjopen-2019-030567 · Cited by 38
Obtaining Accelerometer Data in a National Cohort of Black and White Adults
Howard, V. J., Rhodes, J. D., Mosher, A., Hutto, B., Stewart, M., Colabianchi, N., Vena, J. E., Blair, S. N., & Hooker, S. P. (2014) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000000549 · Cited by 34
Biswas, A., Oh, P. I., Faulkner, G. E., & Alter, D. A. (2018) · Annals of Physical and Rehabilitation Medicine · doi:10.1016/j.rehab.2017.06.003 · Cited by 33
“Self-reported questionnaires were used to minimize participant burden [16].”
MethodYj, R., Su, M., Qm, L., et al. (2017) · PubMed · doi:10.3967/bes2017.035 · Cited by 33
Mackey, D. C., Perkins, A., Tai, K. H., Sims‐Gould, J., & McKay, H. A. (2018) · Journal of Aging and Physical Activity · doi:10.1123/japa.2018-0137 · Cited by 32
“Although less is known about the benefits of light-intensity physical activity than MVPA, the traditional focus on MVPA may limit our understanding of the health benefits of the full range of physical activity intensities (Lee & Shiroma, 2014).”
BackgroundObjective and Self-reported Assessment of Physical Activity of Women over 60 Years Old
Ogonowska-Słodownik, A., Morgulec‐Adamowicz, N., Geigle, P. R., Kalbarczyk, M., & Kosmol, A. (2021) · Ageing International · doi:10.1007/s12126-021-09423-z · Cited by 34
“Even so, among these monitors, accelerometers provide the most accurate and reliable PA data among older adults (Copeland & Esliger, 2009; Lee & Shiroma, 2014).”
BackgroundCooper, R., Stamatakis, E., & Hamer, M. (2020) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.13793 · Cited by 37
Gabriel, K. P., Sternfeld, B., Shiroma, E. J., Pérez, A., Cheung, J., & Lee, I.-M. M. (2016) · Sleep Health · doi:10.1016/j.sleh.2016.10.001 · Cited by 35
Self-citationGeidl, W., Semrau, J., Streber, R., Lehbert, N., Wingart, S., Tallner, A., Wittmann, M., Wagner, R., Schultz, K., & Pfeifer, K. (2017) · Trials · doi:10.1186/s13063-017-2124-z · Cited by 31
“While the use of the LFE filter to calculate steps is not recommended, it may be applicable during data analysis of cutoff points for older adults [33, 34].”
MethodYerrakalva, D., Cooper, A., Westgate, K. L., Khaw, K., Wareham, N. J., Brage, S., Griffin, S. J., & Wijndaele, K. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx123 · Cited by 32
24-h Movement and Nonmovement Behaviors in Older Adults. The IMPACT65+ Study
Cabanas‐Sánchez, V., Higueras‐Fresnillo, S., la Cámara, M. Á. D., Esteban‐Cornejo, I., & Martínez‐Gómez, D. (2018) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000001838 · Cited by 29
Byrne, R., Bell, L., Taylor, R. W., Mauch, C. E., Mihrshahi, S., Zarnowiecki, D. M., Hesketh, K. D., Wen, L. M., Trost, S. G., & Golley, R. K. (2018) · Obesity Reviews · doi:10.1111/obr.12801 · Cited by 29
Balci, A., ARSLANOĞLU, E., Yılmaz, A. E., Devrim-Lanpir, A., Akınoğlu, B., Kocahan, T., Hasanoğlu, A., Hill, L., Rosemann, T. J., & Knechtle, B. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.625370 · Cited by 30
Wellman, R. J., Sylvestre, M., Nader, P. A., Chioléro, A., Mésidor, M., Dugas, E. N., Tougri, G., & O’Loughlin, J. L. (2020) · Journal of Clinical Hypertension · doi:10.1111/jch.13806 · Cited by 33
Xu, S. Y., Nelson, S. H., Kerr, J., Godbole, S. V., Patterson, R. E., Merchant, G., ABRAMSON, I. S., STAUDENMAYER, J. W., & Natarajan, L. (2016) · Statistical Methods in Medical Research · doi:10.1177/0962280216657119 · Cited by 30
Walker, R. L., Greenwood-Hickman, M. A., Bellettiere, J., LaCroix, A. Z., Wing, D., Higgins, M., Richmire, K., Larson, E. B., Crane, P. K., & Rosenberg, D. E. (2021) · BMC Geriatrics · doi:10.1186/s12877-021-02163-4 · Cited by 28
Hassani, M., Mika Kivimaki, B., Elbaz, A., Shipley, M. J., Singh‐Manoux, A., & Sabia, S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110816 · Cited by 28
“[11,12,20] Accelerometry is a measure of one part of the body with inferences that apply to the whole body.”
BackgroundMethodLaMonte, M. J., Lee, I.-M. M., Rillamas‐Sun, E., Bellettiere, J., Evenson, K. R., Büchner, D. M., Di, C., Lewis, C. E., Rosenberg, D. E., Stefanick, M. L., et al. (2019) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2018-0057 · Cited by 28
“While accelerometers are now considered to be a more objective devicebased measurement option (Lee & Shiroma, 2014), the fact is that a true gold standard field measure of free-living PA does not exist (LaMonte et al., 2006).”
BackgroundMethodInfluentialSelf-citationMyers, N. D., McMahon, A., Prilleltensky, I., Lee, S., Dietz, S., Prilleltensky, O., Pfeiffer, K. A., Bateman, A. G., & Brincks, A. M. (2020) · JMIR Formative Research · doi:10.2196/15919 · Cited by 27
“Field-based studies that collect physical activity data from objective instrumentation [54-58] in adults with obesity are encouraged [35,52] and are underway in the FFW context [53].”
Macêna, M. D. L., Paula, D. T. D. C., Júnior, A. E. D. S., Praxedes, D. R. S., Pureza, I. R. D. O. M., de Melo, I. S. V., & Bueno, N. B. (2022) · Nutrition Reviews · doi:10.1093/nutrit/nuac031 · Cited by 27
Baere, S. D., Philippaerts, R. M., Martelaer, K. D., & Lefevre, J. (2016) · Journal of Physical Activity and Health · doi:10.1123/jpah.2015-0596 · Cited by 26
Bayraktar, D., Karsli, T. Y., Kaya, D. Ö., Saraç, D. C., Gücenmez, S., Gerçik, Ö., Kabadayi, G., Aysin, İ. K., Solmaz, D., & Akar, S. (2021) · Musculoskeletal Science and Practice · doi:10.1016/j.msksp.2021.102418 · Cited by 26
Examining the Dose–Response Relationship between Physical Activity and Health Outcomes
Wasfy, M. M., & Lee, I.-M. M. (2022) · NEJM Evidence · doi:10.1056/evidra2200190 · Cited by 29
Self-citationMeisinger, C., Linseisen, J., Leitzmann, M. F., Baurecht, H., & Baumeister, S. E. (2020) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2020-001896 · Cited by 26
Suri, A., VanSwearingen, J. M., Dunlap, P. M., Redfern, M. S., Rosso, A. L., & Sejdić, E. (2022) · Aging Clinical and Experimental Research · doi:10.1007/s40520-022-02096-x · Cited by 25
“The current technical challenges to using accelerometry and GPS for assessment of enacted mobility have been detailed in recent reviews [12, 13, 75].”
BackgroundPatterns of Leisure-Time Physical Activity Participation in a British Birth Cohort at Early Old Age
Martin, K. R., Cooper, R., Harris, T. B., Brage, S., Hardy, R., Kuh, D. J., & on behalf of the NSHD scientific and data collection team (2014) · PLoS ONE · doi:10.1371/journal.pone.0098901 · Cited by 27
“Further, we purposefully chose to focus on sport and exercise activities that are of higher intensity (moderate-to-vigorous) partly because they are reported with greater reliability and validity than lower intensity (light) activities [46,47].”
Backgroundda Silva, R. B. P., Marques, A. C., & Reichert, F. F. (2017) · Disability and Rehabilitation · doi:10.1080/09638288.2017.1327984 · Cited by 25
“Questionnaires usually address specific contexts where PA occurs—leisure or occupational, for example [32] and are susceptible to misunderstanding, memory bias and thus results can be either under or overestimated [31].”
BackgroundAlligier, M., Barrès, R., Blaak, E. E., Boirie, Y., Bouwman, J., Brunault, P., Campbell, K., Clément, K., Farooqi, I. S., Farpour‐Lambert, N. J., et al. (2020) · Obesity Facts · doi:10.1159/000505342 · Cited by 30
Yano, S., Koohsari, M. J., Shibata, A., Ishii, K., Frehlich, L., McCormack, G. R., & Oka, K. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16091597 · Cited by 25
“Over the past decade, several accelerometers have been employed to measure physical activity and SB [8,13].”
BackgroundCourtney, J. B., Nuss, K. J., Lyden, K. A., Harrall, K. K., Glueck, D. H., Villalobos, A., Hamman, R. F., Hébert, J. R., Hurley, T. G., Leiferman, J. A., et al. (2020) · Measurement in Physical Education and Exercise Science · doi:10.1080/1091367x.2020.1867146 · Cited by 24
“Researchers regularly use accelerometers to measure physical activity and sedentary behavior in the lab and in free-living settings (Bassett, 2012; Lee & Shiroma, 2014; Quante et al., 2015).”
BackgroundA meta-analysis of Fitbit devices: same company, different models, different validity evidence
Leung, W. C. W., Case, L., Sung, M., & Jung, J. (2021) · Journal of Medical Engineering & Technology · doi:10.1080/03091902.2021.2006350 · Cited by 23
“8 ± 8 Indirect calorimetry Correlation Charge HR Wristband Wrist 2015 Ambulatory No F: 12 Lee and Shiroma [32] 60 26.”
BackgroundSandborg, J., Migueles, J. H., Söderström, E., Blomberg, M. I., Henriksson, P., & Löf, M. (2022) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000002996 · Cited by 28
Flora, S., Marques, A. S. P. D. D., Hipólito, N., Morais, N., Silva, C. G., Januário, F., Rodrigues, F., Carreira, B. P., & Cruz, J. (2022) · Respiratory Medicine · doi:10.1016/j.rmed.2022.107087 · Cited by 31
Liu, M., Gan, X., Ye, Z., Zhang, Y., He, P., Zhou, C., Yang, S., Zhang, Y., & Qin, X. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00969-7 · Cited by 25
“Moreover, due to the inability of self-reported questionnaires to accurately measure light intensity PA (LPA) 13,14 , there is limited evidence for the association between LPA and PD risk, despite LPA being the predominant form of activity in daily life and a more feasible behavioral goal for…”
BackgroundO’Brien, W. J., Shultz, S. P., Firestone, R. T., George, L., Breier, B. H., & Kruger, R. (2017) · European Journal of Sport Science · doi:10.1080/17461391.2017.1323952 · Cited by 25
“Well-structured postal returns are recommended as an effective alternative to face-to-face collection (Trost et al., 2005) and is the method employed in many large-scale studies (Hagströmer et al., 2007; Lee & Shiroma, 2014; Troiano et al., 2008).”
MethodSchneider, S., Popp, W., Brogioli, M., Albisser, U., Demkó, L., Debecker, I., Velstra, I., Gassert, R., & Curt, A. E. P. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.01039 · Cited by 23
“Acute 3 (A III) Total 17 20 6 (35) 7 (35) 10 (59) 11 (55) 49.”
BackgroundCorrelates of sedentary time in young children: A systematic review
Pereira, J. R., Zhang, Z., Sousa‐Sá, E., Santos, R., & Cliff, D. P. (2020) · European Journal of Sport Science · doi:10.1080/17461391.2020.1741689 · Cited by 22
Kwon, S., Kim, Y., Bai, Y., Burns, R. D., Brusseau, T. A., & Byun, W. (2021) · Sensors · doi:10.3390/s21196413 · Cited by 22
“children’s MVPA level [5], accelerometry-based activity monitoring is a reasonable method to objectively assess MVPA time for school-aged children who have a limited ability to recall their habitual activities [35].”
BackgroundMethodRillamas‐Sun, E., Büchner, D. M., Di, C., Evenson, K. R., & LaCroix, A. Z. (2015) · BMC Research Notes · doi:10.1186/s13104-015-1229-2 · Cited by 22
“Logistical and data-related challenges arise when scaling such accelerometer protocols to studies with thousands of participants [5].”
BackgroundBuja, A., Bue, R. L., Mariotti, F., Miatton, A., Zampieri, C., & Leone, G. (2024) · INQUIRY The Journal of Health Care Organization Provision and Financing · doi:10.1177/00469580241248131 · Cited by 31
Weaver, R. G., Tassitano, R. M., Tenório, M. C. M., Brazendale, K., & Beets, M. W. (2021) · Journal of Physical Activity and Health · doi:10.1123/jpah.2021-0254 · Cited by 22
Zink, J., Belcher, B. R., Dzubur, E., Ke, W., O’Connor, S. G., Huh, J., Lopez, N. V., Maher, J. P., & Dunton, G. F. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9592 · Cited by 20
“Depending on their placement, accelerometers do not accurately capture upper body movements [9].”
BackgroundHaegele, J. A., Zhu, X., & Kirk, T. N. (2018) · Journal of Visual Impairment & Blindness · doi:10.1177/0145482x1811200404 · Cited by 21
Baere, S. D., Seghers, J., Philippaerts, R. M., Martelaer, K. D., & Lefevre, J. (2015) · Journal of Physical Activity and Health · doi:10.1123/jpah.2014-0416 · Cited by 19
Fore, R., Hart, J. E., Choirat, C., Thompson, J., Lynch, K. A., Laden, F., Chavarro, J. E., & James, P. (2020) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-19-1386 · Cited by 21
“Wearable devices are often designed to communicate with a smartphone and securely upload data in near realtime, alleviating the need to mail devices back to researchers, which is costly and burdensome (52).”
BackgroundObjectively Assessed Physical Activity of Preschool-Aged Children from Urban Areas
Herbert, J., Matłosz, P., Lenik, J., Szybisty, A., Baran, J., Przednówek, K. H., & Wyszyńska, J. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17041375 · Cited by 19
“This study used the ActiGraph WGT3X‐BT (Pensacola, USA) triaxial accelerometer [27].”
MethodEffect of Reducing Sedentary Behavior on Blood Pressure (RESET BP): Rationale, design, and methods
Gibbs, B. B., Conroy, M. B., Huber, K., Muldoon, M. F., Perera, S., & Jakicic, J. M. (2021) · Contemporary Clinical Trials · doi:10.1016/j.cct.2021.106428 · Cited by 21
Bai, Y., Copeland, W., Burns, R. D., Nardone, H. Y., Devadanam, V., Rettew, J., & Hudziak, J. J. (2021) · JMIR Public Health and Surveillance · doi:10.2196/25375 · Cited by 19
“Being able to monitor individuals’ PA plays an important role on PA promotion initiatives [10].”
BackgroundFarrahi, V., Muhammad, U., Rostami, M., & Oussalah, M. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105004 · Cited by 22
A Priori and a Posteriori Dietary Patterns in Women of Childbearing Age in the UK
Khaled, K., Hundley, V. A., Almilaji, O., Koeppen, M., & Tsofliou, F. (2020) · Nutrients · doi:10.3390/nu12102921 · Cited by 22
“A larger sample size and more credible methods for measuring physical activity (such as Accelerometers) are needed in epidemiological studies to produce robust results [64].”
BackgroundBellettiere, J., Tuz‐Zahra, F., Carlson, J., Ridgers, N. D., Liles, S., Greenwood-Hickman, M. A., Walker, R. L., LaCroix, A. Z., Jankowska, M. M., Rosenberg, D. E., et al. (2021) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2020-0036 · Cited by 20
Solenhill, M., Grotta, A., Pasquali, E., Bakkman, L., Bellocco, R., & Lagerros, Y. T. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.4005 · Cited by 19
“For instance, accelerometers can be used for large surveys at acceptable costs and to provide rather reliable measures [42].”
Mahmood, S., Nguyen, N. H., Bassett, J. K., MacInnis, R. J., Karahalios, A., Owen, N. G., Bruinsma, F., Milne, R. L., Giles, G. G., English, D. R., et al. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz209 · Cited by 18
Aljahdali, A., Baylín, A., Ruiz-Narváez, E., Kim, H. M., Cantoral, A., Téllez‐Rojo, M. M., Banker, M. M., & Peterson, K. E. (2022) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-022-01375-0 · Cited by 18
Cha, S., Park, J. J., Kim, S. Y., Ahn, H. Y., Han, K., Lee, Y., Kim, W., & Paik, N. (2018) · Circulation Journal · doi:10.1253/circj.cj-17-1405 · Cited by 18
Ricardo, L. I. C., Crochemore‐Silva, I., Leão, O. A. D. A., Domingues, M. R., & Wehrmeister, F. C. (2019) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-019-0895-1 · Cited by 17
Yao, J., Brügger, V., Edney, S. M., Tai, E. S., Sim, X., Müller‐Riemenschneider, F., & van Dam, R. M. (2024) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-024-01693-5 · Cited by 20
Accuracy of activPAL Self-Attachment Methods
Kringen, N. L., Healy, G. N., WINKLER, E. A. H., & Clark, B. (2016) · Measurement in Physical Education and Exercise Science · doi:10.1080/1091367x.2016.1189916 · Cited by 17
Bernhardsen, G. P., Stensrud, T., Hansen, B. H., Steene-Johannesen, J., Kolle, E., Nystad, W., Anderssen, S. A., Hallal, P. C., Janz, K. F., Kriemler, S., et al. (2020) · International Journal of Obesity · doi:10.1038/s41366-020-0612-9 · Cited by 17
Bottaz-Bosson, G., Hamon, A., Pépin, J., Bailly, S., & Samson, A. L. (2021) · Statistics in Medicine · doi:10.1002/sim.9130 · Cited by 17
Research Strategies for Nutritional and Physical Activity Epidemiology and Cancer Prevention
Mahabir, S., Willett, W. C., Friedenreich, C. M., Lai, G. Y., Boushey, C. J., Matthews, C. E., Sinha, R. R., Colditz, G. A., Rothwell, J. A., Reedy, J., et al. (2017) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-17-0509 · Cited by 17
Day length is associated with physical activity and sedentary behavior among older women
Schepps, M. A., Shiroma, E. J., Kamada, M., Harris, T. B., & Lee, I.-M. M. (2018) · Scientific Reports · doi:10.1038/s41598-018-25145-w · Cited by 19
Self-citationPuhakka, S., Lankila, T., Pyky, R., Kärmeniemi, M., Niemelä, M., Kangas, K., Rusanen, J., Kangas, M., Näyhä, S., & Korpelainen, R. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17249202 · Cited by 17
“The techniques for measuring objective LPA have taken a step forward [4], and there is growing epidemiological evidence that frequent bouts of LPA can have several positive health outcomes.”
MethodMigueles, J. H., Lee, I.-M. M., Cadenas‐Sánchez, C., Ortega, F. B., Buring, J. E., & Shiroma, E. J. (2021) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-021-01173-0 · Cited by 17
“In 2011, an ancillary study examining accelerometer-assessed physical activity was launched [14, 15].”
BackgroundSelf-citationTong, C., Sims‐Gould, J., & McKay, H. A. (2017) · Journal of Aging and Physical Activity · doi:10.1123/japa.2017-0105 · Cited by 19
“Consistent with Lee & Shiroma (2014), our results support a shift away from focusing solely on MVPA.”
BackgroundResultChen, D., Wu, H., Wang, X., Huang, T., & Jia, J. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.836023 · Cited by 17
Conte, D., Lukonaitienė, I., Matulaitis, K., Sniečkus, A., Kniubaitė, A., Kreivytė, R., & Kamandulis, S. (2023) · Biology of Sport · doi:10.5114/biolsport.2023.122478 · Cited by 17
“Indeed, the ad - opted accelerometer, although considered one of the main tools to assess physical activity intensities in adults, [42] records accelerations while placed on participants’ hip and might not have been able to fully detect the physical demand of the activities performed during the…”
BackgroundValidation of a pouch-mounted activPAL3 accelerometer
Stanton, R., Guertler, D., Duncan, M. J., & Vandelanotte, C. (2014) · Gait & Posture · doi:10.1016/j.gaitpost.2014.07.024 · Cited by 16
la Cámara, M. Á. D., Higueras‐Fresnillo, S., Martínez‐Gómez, D., & Veiga, Ó. L. (2018) · Journal of Aging and Physical Activity · doi:10.1123/japa.2017-0365 · Cited by 16
Verhoog, S., Gubelmann, C., Guessous, I., Bano, A., Franco, O. H., & Marques-Vidal, P. M. (2019) · Maturitas · doi:10.1016/j.maturitas.2019.08.004 · Cited by 17
Chen, G., Qi, Q., Hua, S., Moon, J., Spartano, N. L., Vasan, R. S., Sotres‐Alvarez, D., Castañeda, S. F., Evenson, K. R., Perreira, K. M., et al. (2020) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqaa232 · Cited by 17
“Despite assessing physical activity objectively, accelerometer measurement has limitations in terms of determining certain physical activity types that are more common among younger individuals (39).”
BackgroundSyed, S., Morseth, B., Hopstock, L. A., & Horsch, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-87757-z · Cited by 20
Sedentary Behaviour and Stroke: Foundational Knowledge is Crucial
Verschuren, O. W., Mead, G. E., & Visser‐Meily, A. (2014) · Translational Stroke Research · doi:10.1007/s12975-014-0370-x · Cited by 16
“Objectively, accelerometers have become the standard method of measurement to collect information regarding the intensity of movement [15].”
BackgroundMethodZhao, Q., Chen, C., Zhang, J., Ye, Y., & Fan, X. (2021) · Heart Failure Reviews · doi:10.1007/s10741-021-10132-7 · Cited by 16
“Although there is not a single measure that is considered the best to evaluate sedentary behavior [56], an objective measure is considered to be more reliable [57].”
BackgroundPhysical Activity and Public Health: Four Decades of Progress
Keadle, S. K., Bustamante, E. E., & Buman, M. P. (2021) · Kinesiology Review · doi:10.1123/kr.2021-0028 · Cited by 17
Orme, M. W., Lloyd-Evans, P. H. I., Jayamaha, A. R., Katagira, W., Kirenga, B., Pina, I., Kingsnorth, A. P., Maylor, B. D., Singh, S., & Rowlands, A. V. (2023) · Journal of Physical Activity and Health · doi:10.1123/jpah.2022-0590 · Cited by 14
Brown, N. I., Pekmezi, D., Oster, R. A., Courneya, K. S., McAuley, E., Ehlers, D. K., Phillips, S. M., Anton, P. M., & Rogers, L. Q. (2023) · Nutrients · doi:10.3390/nu15051286 · Cited by 15
“For example, it is unclear whether the device (waist-worn) accurately distinguishes the difference between sitting and standing idle, and upper body movement [49,50].”
BackgroundDutch, D. C., Bell, L., Zarnowiecki, D. M., Johnson, B. J., Denney‐Wilson, E., Byrne, R., Cheng, H., Rossiter, C., Manson, A., House, E. T., et al. (2024) · Obesity Reviews · doi:10.1111/obr.13694 · Cited by 15
“‘ Gold standard ’ methods of measuring health behaviours such as accelerometry and diet histories can be time consuming and are therefore not feasible in time-poor settings such as PHC. 23,24 Brief screening tools can be a time-efficient and cost-effective method of assessing health behaviours, allowing for identifica…”
MethodInfluentialLife's Essential 8 Cardiovascular Health Score and Cardiorespiratory Fitness in the Community
Ravichandran, S., Gajjar, P., Walker, M. E., Prescott, B. R., Tsao, C. W., Jha, M., Rao, P., Miller, P., Larson, M. G., Vasan, R. S., et al. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.123.032944 · Cited by 17
Agarwal, V., Smuck, M. W., Tomkins‐Lane, C., & Shah, N. H. (2018) · JMIR mhealth and uhealth · doi:10.2196/11315 · Cited by 19
Detecting prolonged sitting bouts with the ActiGraph GT3X
Kuster, R. P., Grooten, W. J. A., Baumgartner, D., Blom, V., Hagströmer, M., & Ekblom, Ö. B. (2019) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.13601 · Cited by 16
Habitual physical activity patterns in a nationally representative sample of U.S. adults
Malone, S. K., Patterson, F., Grunin, L., Melkus, G. D., Riegel, B. J., Punjabi, N. M., Yu, G., Urbanek, J. K., Crainiceanu, C., & Pack, A. I. (2020) · Translational Behavioral Medicine · doi:10.1093/tbm/ibaa002 · Cited by 14
“Second, self-reported physical activity may overreport activity [44].”
BackgroundCooper, R., Huang, L., Hardy, R., Crainiceanu, A., Harris, T. B., Schrack, J. A., Crainiceanu, C. M., & Kuh, D. J. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glw331 · Cited by 15
Macêna, M. D. L., Pureza, I. R. D. O. M., de Melo, I. S. V., Clemente, A. P. G., Ferreira, H. S., Florêncio, T. M. D. M. T., Pfrimer, K., Ferriolli, E., Sawaya, A. L., & Bueno, N. B. (2019) · British Journal Of Nutrition · doi:10.1017/s0007114519002460 · Cited by 15
“Given that the use of accurate methods, such as triaxial accelerometers, is also expensive, the use of questionnaires, which are usually imprecise, is common(14).”
MethodAu-Yeung, W.-T. M., Kaye, J. A., & Beattie, Z. (2020) · Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/embc44109.2020.9176511 · Cited by 15
“The wGT3X-BT (referred to throughout the rest of the paper as the Actigraph) and other similar devices from ActiGraph have also been used in several large-scale epidemiological studies[10, 11].”
MethodVisual Inspection for Determining Days When Accelerometer Is Worn
Shiroma, E. J., Kamada, M., Smith, C., Harris, T. B., & Lee, I.-M. M. (2015) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000000725 · Cited by 14
“For example, theWomen_s Health Study (an ancillary investigation that used a direct mail design) collected 7 d of accelerometerassessed physical activity in approximately 18,000 women.”
BackgroundInfluentialSelf-citationMyers, N. D., Lee, S., Bateman, A. G., Prilleltensky, I., Clevenger, K. A., Pfeiffer, K. A., Dietz, S., Prilleltensky, O., McMahon, A., & Brincks, A. M. (2019) · Pilot and Feasibility Studies · doi:10.1186/s40814-019-0455-0 · Cited by 14
Ehrlich, S. F., Casteel, A. J., Crouter, S. E., Hibbing, P. R., Hedderson, M. M., Brown, S. D., Galarce, M., Coe, D. P., Bassett, D. R., & Ferrara, A. M. (2020) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2019-0049 · Cited by 14
“At the visit, research staff explained the PA assessment protocol and provided a device and wrist strap, a diary log (Lee & Shiroma, 2014) (i.e., small paper booklet) to record their daily on and off times, and a postage paid envelope to return the device and diary log at the end of the assessment…”
MethodTynkkynen, N. P., Törmäkangas, T., Palviainen, T., Hyvärinen, M., Klevjer, M., Joensuu, L., Kujala, U. M., Kaprio, J. A., Bye, A., & Sillanpää, E. (2023) · European Journal of Epidemiology · doi:10.1007/s10654-023-01029-w · Cited by 13
Harada, S., Hamai, S., Shiomoto, K., Kawahara, S., Hara, D., Harada, T., & Nakashima, Y. (2023) · International Orthopaedics · doi:10.1007/s00264-023-06022-2 · Cited by 14
“Recent technological advances have enabled the use of the accelerometers in longitudinal studies that aim to investigate the associations of objectively measured physical activity with PROs [37].”
Design and Evaluation of a Computer-Based 24-Hour Physical Activity Recall (cpar24) Instrument
Kohler, S., Behrens, G., Olden, M., Baumeister, S. E., Horsch, A., Fischer, B., & Leitzmann, M. F. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7620 · Cited by 16
“In addition, thanks to recent technologic advances, accelerometers can now be employed to measure short-term physical activity (24 h to 7 days) in large studies [24].”
BackgroundSutherland, S., Penfold, R., Doherty, A., Milne, Z., Dawes, H., Pugh, C. W., Boulton, M. G., & Newton, J. L. (2019) · Disability and Rehabilitation · doi:10.1080/09638288.2019.1672214 · Cited by 15
Parada, H., McDonald, E., Bellettiere, J., Evenson, K. R., LaMonte, M. J., & LaCroix, A. Z. (2020) · British Journal of Cancer · doi:10.1038/s41416-020-0753-6 · Cited by 14
Crane, T. E., Skiba, M. B., Miller, A., Garcia, D. O., & Thomson, C. A. (2020) · JMIR mhealth and uhealth · doi:10.2196/18491 · Cited by 14
“The accelerometer protocol was developed using manufacturer instructions, a review of published literature [28-32], and prior experience of study investigators.”
MethodChen, M., Yerramalla, M. S., van Hees, V. T., Bloomberg, M., Landré, B., Fayossé, A., Benadjaoud, M. A., & Sabia, S. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.6379 · Cited by 14
Kühnhausen, J., Dirk, J., & Schmiedek, F. (2016) · Behavior Research Methods · doi:10.3758/s13428-016-0724-2 · Cited by 15
Metadata
- Authors
- Lee, I.-M., & Shiroma, E. J.
- Affiliations
- Brigham and Women's Hospital (US)
- Corresponding author
- Lee, I-Min
- Venue
- British Journal of Sports Medicine
- Publisher
- BMJ
- Published
- 2013-12-02
- Volume
- 48
- Issue
- 3
- Pages
- 197-201
- ISSN
- 0306-3674 (ISSN-L)
- 1473-0480
- PMC
- PMC3947179
- OpenAlex
- W2136019090
- Semantic Scholar
- 4f904384be8d865260d8f27dfd7a14dccefcee46
- Cited by
- 415
- References
- 55
- Citations by year
- 2026: 10 · 2025: 23 · 2024: 29 · 2023: 27 · 2022: 31 · 2021: 62 · 2020: 41 · 2019: 32 · 2018: 39 · 2017: 46 · 2016: 33 · 2015: 26 · 2014: 16
- FWCI
- 17.41
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- British Journal of Sports Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institutes of Health (5r01hl043851-10)
- National Heart, Lung, and Blood Institute (R01HL080467, R01‐HL043851)
- National Cancer Institute (CA154647, R01CA154647, R01CA047988)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Keywords
- accelerometer, physical activity measurement, sedentary behavior, light physical activity, Women's Health Study, data collection challenges, data processing and analysis, chronic disease risk, older women
- MeSH terms
- Data Collection, Female, Humans, Risk Factors, Exercise, Epidemiologic Studies, Women's Health, Practice Guidelines as Topic, Sedentary Behavior, Accelerometry
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