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 301–400 of 414
Hyde, E. T., Nguyen, S., LaMonte, M. J., Di, C., Bellettiere, J., Tinker, L. F., Foraker, R. E., Tindle, H. A., Stefanick, M. L., & LaCroix, A. Z. (2024) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2024.102904 · Cited by 2
“Device-based measurements of physical activity, such as those produced by accelerometers, may be able to reduce the exposure misclassification that occurs in self-reported measures (Lee and Shiroma, 2014; Wijndaele et al., 2015).”
BackgroundHamaya, R., Evenson, K. R., Lieberman, D. E., & Lee, I.-M. M. (2025) · British Journal of Sports Medicine · doi:10.1136/bjsports-2025-110311 · Cited by 2
“19 A total of 18 289 women aged ≥62 years were eligible, of whom 17 708 wore and returned their devices.”
Self-citationJames, P., & Redline, S. S. (2019) · Springer eBooks · doi:10.1007/978-3-030-20992-6_3 · Cited by 2
Calorimetry of students’ heart rate during exercises of various intensity
Nagovitsyn, R. S., Chelnokova, E., Vaganova, O. I., Smirnova, Z. V., & Kutepov, M. M. (2020) · BIO Web of Conferences · doi:10.1051/bioconf/20202600033 · Cited by 1
Cardon, G., CHASTIN, S. F. M., Stappen, V. V., Huys, N., Stefanova, T., Chakarova, N. Y., Kivelä, J., Moreno, L. A., Radó, S. I., Androutsos, O., et al. (2022) · Health Promotion International · doi:10.1093/heapro/daac092 · Cited by 2
Step-Based Metrics and Translations of Physical Activity Guidelines among Adults in the HCHS/SOL
Moore, C. C., Cuthbertson, C. C., Sotres‐Alvarez, D., Castañeda, S. F., Cordero, C., Daviglus, M. L., Mossavar‐Rahmani, Y., Perreira, K. M., & Evenson, K. R. (2023) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000003177 · Cited by 2
Quiles, N. N., Uher, D. T., Balachandran, A. T., Ortíz, A., & Garber, C. E. (2024) · Journal of Physical Activity and Health · doi:10.1123/jpah.2023-0697 · Cited by 2
Han, S., Oh, B., Kim, H. J., Hwang, S. E., & Kim, J. S. (2024) · JMIR Human Factors · doi:10.2196/59659 · Cited by 2
Alòs, F., Puig-Ribera, A. M., Bort‐Roig, J., Chirveches-Pérez, E., Berenguera, A., Martín-Cantera, C., & Colomer, M. À. (2025) · Primary care diabetes · doi:10.1016/j.pcd.2025.03.001 · Cited by 2
Gama-Pinto, J., & Mielke, G. I. (2025) · Maturitas · doi:10.1016/j.maturitas.2025.108245 · Cited by 2
Biswas, A., Smith, P. M., & Gignac, M. A. M. (2018) · Journal of Applied Gerontology · doi:10.1177/0733464818755313 · Cited by 2
CTASS: a framework for contextualized travel behavior advice to cardiac patients
Batool, T., Vanrompay, Y., Neven, A., Janssens, D., & Wets, G. (2017) · Procedia Computer Science · doi:10.1016/j.procs.2017.08.330 · Cited by 2
Yerrakalva, D., Wijndaele, K., Hajna, S., Westgate, K. L., Khaw, K., Wareham, N. J., Griffin, S. J., & Brage, S. (2019) · PLoS ONE · doi:10.1371/journal.pone.0224225 · Cited by 2
Kaneya, S., & Hashidate, H. (2020) · Journal of Physical Therapy Science · doi:10.1589/jpts.32.529 · Cited by 2
Gilbert, A. S., Beck, A. M., SERRANO, N. H., & Brownson, R. C. (2022) · Journal of Physical Activity and Health · doi:10.1123/jpah.2021-0677 · Cited by 2
Adolescent sedentary behavior and body composition in early adulthood: results from a cohort study
Hyde, E. T., Gahagan, S., Martinez, S. M., East, P. L., Wing, D., Burrows, R. A., Correa‐Burrows, P., Algarín, C. R., Peirano, P. D., Reyes, S., et al. (2023) · Pediatric Research · doi:10.1038/s41390-023-02616-z · Cited by 3
Brühmann, B. A., Schmidt, M. E., Wientzek, A., Vigl, M., Teucher, B., Katzke, V. A., Boeing, H., Bergmann, M. M., Kaaks, R., & Steindorf, K. (2014) · Cited by 2
Application of force and inertial sensors to monitor gait on legacy walkers
Viegas, V. M. R., Pereira, J. M. D., Postolache, O. A., et al. (2019) · ACTA IMEKO · doi:10.21014/acta_imeko.v7i4.575 · Cited by 2
“In this case, long-term drifts and persistent DC components must be filtered out so as not to affect the time integration of the signals [16].”
BackgroundEffectiveness of M-Health in Improving Physical Activity: An Indian Perspective
Arora, V., Mishra, S. S., Sahoo, J., et al. (2024) · National Journal of Community Medicine · doi:10.55489/njcm.150120243345 · Cited by 1
“12,27 Ac-celerometers cannot distinguish between sitting and standing still as they do not provide information about body posture.”
BackgroundHuang, J., Zhou, S., Li, X., Zhao, Y., Feng, H., & Hu, M. (2024) · Journal of Applied Gerontology · doi:10.1177/07334648241297049 · Cited by 1
“However, the bene fi ts of walking, a light-intensity PA (LPA), to health outcomes have been controversial (Füz´eki et al., 2017).”
InfluentialYounesian, H., Singleton, D., Vereijken, B., García‐Aymerich, J., Rochester, L., Berge, M. A., Engdal, M., Buekers, J., Koch, S., Helbostad, J. L., et al. (2025) · Sensors · doi:10.3390/s25082557 · Cited by 1
“Wearable digital devices, such as miniaturized accelerometers, facilitate the continuous capture of real-world mobility performance (daily PA), particularly in large-scale cohorts, and overcome the above-mentioned limitations [13,14].”
Hyde, E. T., Bandoli, G., Zou, J., Crespo, N. C., Parada, H., Evenson, K. R., Howard, A. G., LaMonte, M. J., Stefanick, M. L., Tinker, L. F., et al. (2025) · The Journals of Gerontology Series A · doi:10.1093/gerona/glaf206 · Cited by 1
Self-citationAderanti, O., Srinivasan, C. S., & Zanello, G. (2025) · Feminist Economics · doi:10.1080/13545701.2025.2548289 · Cited by 1
“Most importantly, as they capture movements, they do not capture the additional effort involved in carrying weight or activities performed while stationary (Lee and Shiroma 2014).”
Arumugam, A., Raghunathan, M. R. K., Safarini, M. F., Narasimhan, S., Ramakrishnan, S., Qadah, R. M., Shalash, R. J., Hegazy, F. A., Shousha, T. M., Nassis, G. P., et al. (2025) · BMC Public Health · doi:10.1186/s12889-025-24779-6 · Cited by 1
“Alternatively, while accelerometers offer objective and reliable measures of movement, they may not capture all dimensions of PA, such as perceived exertion, upper body movements, or load-bearing tasks [29, 45, 46].”
Herold, F., Giurgiu, M., Ebner‐Priemer, U., Brakenridge, C. J., Hallgren, M. Å., Owen, N. G., & Gronwald, T. (2025) · Exercise and Sport Sciences Reviews · doi:10.1249/jes.0000000000000377 · Cited by 2
Löppönen, A., Lindeman, K., Palmberg, L., Roie, E. V., Delecluse, C., Portegijs, E., Rantanen, T., Rantalainen, T., & Karavirta, L. (2025) · European Review of Aging and Physical Activity · doi:10.1186/s11556-025-00385-8 · Cited by 3
“This study aims to address the well-known limitation that accelerometers cannot detect activities like swimming, cycling, carrying a child, walking uphill, or carrying a load [42] by examining the intensity distribution across all 5-second MAD bouts (Fig.”
Duhamahoro, J., Hibbing, P. R., Lamoureux, N. R., Berg, E. J., & Welk, G. J. (2026) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2025-0024 · Cited by 1
Zhou, T., Su, S., Yuan, C., Jiang, D., Qiu, Y., Xiao, J., Lu, X., Gu, D., & Liu, F. (2026) · Medicine Plus · doi:10.1016/j.medp.2026.100137 · Cited by 2
Weng, Z., & Wang, X. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1862227 · Cited by 1
Sitzender Lebensstil und Gesundheit
Engeroff, T., & Füzéki, E. (2016) · Springer eBooks · doi:10.1007/978-3-662-50335-5_5 · Cited by 2
Macêna, M. D. L., Hoffman, D. J., Clemente, A. P. G., Ferriolli, E., Pfrimer, K., Florêncio, T. M. D. M. T., & Bueno, N. B. (2022) · American Journal of Human Biology · doi:10.1002/ajhb.23780 · Cited by 1
Aktivitas Fisik dan Teknologinya pada Pasien dengan Penyakit Kronis
Santoso, B. I. (2019) · Conferences of Medical Sciences Dies Natalis Faculty of Medicine Universitas Sriwijaya · doi:10.32539/confmednatalisunsri.v1i1.14 · Cited by 1
Mielnik, P., Hjelle, A. M., Pollen, B., Tokarz, K., & Fojcik, M. (2023) · Procedia Computer Science · doi:10.1016/j.procs.2023.10.022 · Cited by 1
Vazquez, J. E., Sotres‐Alvarez, D., Carlson, J., Gallo, L. C., Talavera, G. A., Castañeda, S. F., & Evenson, K. R. (2024) · Journal of science and medicine in sport · doi:10.1016/j.jsams.2024.06.005 · Cited by 1
Rodrigues, P. S., de Lima, M. V. C., CARVALHO, C. F. M. D., de Lima, T. J. A., de Oliveira, K. K. D., & Cardoso, G. A. (2024) · Revista Família Ciclos de Vida e Saúde no Contexto Social · doi:10.18554/refacs.v12i1.7529 · Cited by 1
Barber, B. V., Kephart, G. C., Vallis, M., Matthews, S. A., Martin‐Misener, R., & Rainham, D. G. C. (2024) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph21091128 · Cited by 1
“For example, accelerometers have been useful for measuring the level of exertion according to cut points associated with metabolic equivalent scores (METs) for large-scale epidemiologic studies [32].”
BackgroundThe promise of teacher-led physical activity strategies informed by pupil data
Wort, G. K., Wiltshire, G., Sebire, S. J., et al. (2024) · Health Education Journal · doi:10.1177/00178969241288048 · Cited by 1
“A limitation of wearable devices is their inability to measure all bodily movement, such as muscle strengthening or some upper body activities (Lee and Shiroma, 2014).”
Bewegung mit leichter Intensität und Gesundheit
Füzéki, E. (2016) · Springer eBooks · doi:10.1007/978-3-662-50335-5_6 · Cited by 1
A scoping review of physical activity measurement tools in free-living conditions
Nechvátal, P., Eliášová, A., Kiško, A., Derňarová, Ľ., & Kundraciková, Ľ. (2018) · Medicina · doi:10.21860/medflum2018_198229 · Cited by 1
Self-Report and Contemporaneously Recorded Running Agreement in Recreational Athletes
Leech, R. D., Grunseit, A. C., & Edwards, K. (2020) · The Journal of Strength and Conditioning Research · doi:10.1519/jsc.0000000000003759 · Cited by 1
“The logistical and practical challenges of providing large cohorts with, and analyzing data from, wearable technology have been well documented, for example in financial costs and adherence (16,22).”
BackgroundEffects of community-based interventions on physical activity levels: systematic review
Guerra, P. H., Ribeiro, E. H. C., de Lima, T. R., Andrade, D. R., & Loch, M. R. (2020) · Revista Brasileira de Atividade Física & Saúde · doi:10.12820/rbafs.25e0130 · Cited by 1
Realization of step exercises using the independent calorimetry during the period of self-isolation
Nagovitsyn, R. S., Osipov, A. Y., Kudryavtsev, M. D., Doroshenko, S. A., & Vapaeva, A. V. (2020) · Summer Conferences of Sports Science · doi:10.14198/jhse.2020.15.proc4.04 · Cited by 1
“A certain distrust of these products is created in society and requires simple and affordable methods of instant verification of the services offered (Lee & Shiroma, 2014).”
BackgroundMethodReliability of the PhysioPlay™ device for assessing the reaction time of cancer patients
Anciães, J. D. C., Alves, R. D. S., Pereira, P. D. P. S., et al. (2020) · Acta Fisiátrica · doi:10.11606/issn.2317-0190.v27i4a180347 · Cited by 1
Agarwal, V., Smuck, M. W., & Shah, N. H. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1801.08668 · Cited by 1
Novel Methods of Measuring and Visualising Youths’ Physical Activity
Crossley, S. G. M. (2019) · Cronfa (Swansea University) · doi:10.23889/suthesis.50756 · Cited by 1
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Bell, J. A. (2015) · UCL Discovery (University College London)
Li, Y. (2015) · Scholar Commons (University of South Carolina)
Physical functioning among community-dwelling older people
Tikkanen, P. (2015) · UEF eRepo (University of Eastern Finland)
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Exploring outcome measures for adults with myotonic dystrophy type 1
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A Methodological Approach to Retaining Accelerometers and Associated Data in Community-Based Studies
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Motivation in Physical Activity: Smartphone Sport Tracker Applications
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Physical Activity and Its Technology in Patients with Chronic Disease
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“Self-monitoring of daily physical activity levels has been emphasized to promote a physically active lifestyle in children (Lee & Shiroma, 2014; Rowlands & Eston, 2007).”
Physical Activity and Weight Gain During Pregnancy: Is This Association Modified by Sleep?
Flores, T. R., Leão, O. A. D. A., Wendt, A. T., Crochemore‐Silva, I., Mielke, G. I., Domingues, M. R., Hallal, P. C., & da Silveira, M. F. (2024) · Research Quarterly for Exercise and Sport · doi:10.1080/02701367.2024.2424210
“…are well established in the literature, not only because they are able to provide raw estimations from free living conditions, but also because they can be used to provide more practical indicators, like moderate-to-vigorous physical activity per day or week (Lee & Shiroma, 2014; Liu et al., 2022).”
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“Furthermore, these devices cannot discriminate between sitting and standing motionless [48].”
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“In fact, Lee and Shiroma [44] showed that monitor types, monitor setup, fixation methods, calibration methods, and data processing procedures, together with further developments in measurement methodology, represent emerging challenges in this research area, especially for the standardization of…”
Digital Innovation for Individual Approach to Incorrect Spine Posture in Adolescents “NOVA-SPINE”
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Wassenaar, T. M., Wheatley, C. M., Beale, N., Nichols, T., Salvan, P., Meaney, A., Atherton, K., Diaz‐Ordaz, K., Dawes, H., & Johansen-Berg, H. (2021) · Figshare · doi:10.6084/m9.figshare.14355667
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Wassenaar, T. M., Wheatley, C. M., Beale, N., Nichols, T., Salvan, P., Meaney, A., Atherton, K., Diaz‐Ordaz, K., Dawes, H., & Johansen‐Berg, H. (2021) · Figshare · doi:10.6084/m9.figshare.14355664
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Wassenaar, T. M., Wheatley, C. M., Beale, N., Nichols, T., Salvan, P., Meaney, A., Atherton, K., Diaz‐Ordaz, K., Dawes, H., & Johansen-Berg, H. (2021) · Figshare · doi:10.6084/m9.figshare.14355670
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Pulsford, R. M., Brocklebank, L. A., Fenton, S. A. M., Bakker, E., Mielke, G. I., Tsai, L.-T., Atkin, A. J., Harvey, D. L., Blodgett, J. M., Ahmadi, M., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22622464
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Pulsford, R. M., Brocklebank, L. A., Fenton, S. A. M., Bakker, E., Mielke, G. I., Tsai, L.-T., Atkin, A. J., Harvey, D. L., Blodgett, J. M., Ahmadi, M., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22622467
Yerramalla, M. S., McGregor, D. E., van Hees, V. T., Fayossé, A., Dugravot, A., Tabák, Á. G., Chen, M., Chastin, S. F. M., & Sabia, S. (2021) · Figshare · doi:10.6084/m9.figshare.14955980
Wassenaar, T. M., Wheatley, C. M., Beale, N., Nichols, T., Salvan, P., Meaney, A., Atherton, K., Diaz‐Ordaz, K., Dawes, H., & Johansen-Berg, H. (2021) · Figshare · doi:10.6084/m9.figshare.14355646
Pulsford, R. M., Brocklebank, L. A., Fenton, S. A. M., Bakker, E., Mielke, G. I., Tsai, L.-T., Atkin, A. J., Harvey, D. L., Blodgett, J. M., Ahmadi, M., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22622458
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Self-citationYerramalla, M. S., McGregor, D. E., van Hees, V. T., Fayossé, A., Dugravot, A., Tabák, Á. G., Chen, M., Chastin, S. F. M., & Sabia, S. (2021) · Figshare · doi:10.6084/m9.figshare.14955983
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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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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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