Evidence map›Paper›PMID 31159771›Full record

ArticleBMC public health2019

Daily metabolic expenditures: estimates from US, UK and polish time-use data.

Teresa Harms, David Berrigan, Jonathan Gershuny

Abstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Revisiting the calculation of PAL from physical activity data.BMJ open sport & exercise medicine · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Physical Activity, Step Counts, and Grip Strength in the Chinese Children and Families Cohort Study.International journal of environmental research and public health · 2020
    Article
  6. Trends and correlates of meeting 24-hour movement guidelines: a 15-year study among 167,577 Thai adults.The international journal of behavioral nutrition and physical activity · 2020
    Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Teresa HarmsDepartment of Social Science, Centre for Time Use Research, University College London, 55-59 Gordon Square, London, WCH 0NU, UK. t.harms@ucl.ac.uk.
David BerriganNational Cancer Institute, Division of Cancer Control and Population Sciences, Bethesda, MD, USA.
Jonathan GershunyDepartment of Social Science, Centre for Time Use Research, University College London, 55-59 Gordon Square, London, WCH 0NU, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBehaviour has diverse economic, social and health consequences. Linking time spent in different daily activities to energy expenditure (EE) is one way of investigating the health and physiological consequences of behaviour and identifying targets to improve population health and well-being.

methodsWe estimated behaviour-related EE for respondents to time use surveys (TUS) from three countries: UK 2001, Poland 2012 and US 2003-13. The Harmonised Multinational Time Use Survey (MTUS) activity categories were matched to MET estimates from the 2011 Compendium of Physical Activities. We attach METs values to each successive activity in the TUS, together with both the original UK, Polish and US activity classifications and the 68-category MTUS activity classification. We used TUS estimates of activity durations across 24-h to estimate the Physical Activity Level (PAL) for respondents from the three countries and the average time spent and MET values for different activity categories.

resultsPAL values ranged from 1.59 in the US to 1.74 in Poland. The main sources of daily EE from PA were paid and unpaid work activities. Discretionary PA accounted for only a very small part (~ 3%) of adult daily energy expenditures. Using the harmonised MTUS 68-activity classification reduced the variability of the aggregate PAEE measure by ~ 20%, but the patterns of association between key demographics (age, sex, educational attainment) were unaffected. TUS data were further used to (1) identify sources of daily PA, and (2) assess adherence to physical activity guidelines (PAG) on a single-day basis. Estimated adherence levels were similar to those reported from other TUS as well as frequency based estimates.

conclusionsComparative studies of energy expenditure based on harmonised time use activity categories could provide insight into the relative importance of different activities for energy expenditure across different countries and demographic groups. However, new observational studies combining TUS data with accelerometer, direct observation and other measures of activity intensity are required for more accurate MET assignments to activity categories in TUS.

Indexed as

Energy MetabolismExerciseTime FactorsActivities of Daily LivingAdultFemaleHealth SurveysHuman ActivitiesHumansMaleMiddle AgedPolandUnited KingdomUnited StatesAinsworth compendiaMetabolic equivalent of taskMETs linkagePhysical activityPhysical activity energy expenditureTime use diaryTime use survey

Identifiers

PMID31159771
PMCPMC6546617

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.