Open access

Original research

Masahiro Nishi ‍ ‍,1,2 Reo Nagamitsu,3,2 Satoaki Matoba1

To cite: Nishi M, Nagamitsu R,
Matoba S. Association between
daily step counts and healthy
life years: a national cross-­
sectional study in Japan.
BMJ Health Care Inform
2024;31:e101051. doi:10.1136/
bmjhci-2024-101051► Additional supplemental
material is published online only.
To view, please visit the journal
online (https://​doi.​org/​10.​1136/​
bmjhci-​2024-​101051).

Received 12 February 2024
Accepted 16 April 2024

© Author(s) (or theiremployer(s)) 2024. Re-­use
permitted under CC BY-­NC. No
commercial re-­use. See rights
and permissions. Published by
BMJ.

ABSTRACT
Background Despite accumulating evidence concerning
the association between daily step counts and mortality or
disease risks, it is unclear whether daily step counts areassociated with healthy life years.
Methods We used the combined dataset of theComprehensive Survey of Living Conditions and the
National Health and Nutrition Survey conducted fora randomly sampled general population in Japan,
2019. Daily step counts were measured for 4957 adultparticipants. The associations of daily step counts withactivity limitations in daily living and self-­assessed healthwere evaluated using a multivariable logistic regression
model. The bootstrap method was employed to mitigate
uncertainties in estimating the threshold of daily step
counts.
Results The median age was 60 (44–71) years, and 2592
(52.3%) were female. The median daily step counts were5650 (3332–8452). The adjusted OR of activity limitations
in daily living for the adjacent daily step counts was 0.27
(95% CI 0.26 to 0.27) for all ages and 0.25 (95% CI 0.25 to0.26) for older adults at the lowest, with the thresholds ofsignificant association at 9000 step counts. The OR of self-­
assessed unhealthy status was 0.45 (95% CI 0.44 to 0.46)
for all ages and 0.42 (95% CI 0.41 to 0.43) for older adults
at the lowest, with the thresholds at 11 000 step counts.
Conclusion Daily step counts were significantly
associated with activity limitations in daily living and self-­
assessed health as determinants of healthy life years,
up to 9000 and 11 000 step counts, respectively. These
results suggest a target of daily step counts to prolong
healthy life years within health initiatives.

1

Department of Cardiovascular
Medicine, Graduate Schoolof Medical Science, Kyoto
Prefectural University of
Medicine, Kyoto, Japan2
Department of Health andWelfare, Kyoto Prefectural
Government, Kyoto, Japan3
Department of Epidemiology
for Community Health andMedicine, Graduate Schoolof Medical Science, Kyoto
Prefectural University of
Medicine, Kyoto, Japan
Correspondence to
Dr Masahiro Nishi;​nishim@​koto.​kpu-​m.​ac.​jp

INTRODUCTION
Healthy life years, also known as healthy
life expectancy, are holistic health indicator
encompassing life, health, disease, disability,
activity limitation and overall well-­being.
Estimations of healthy life years are derived
from national health surveys that incorporate questionnaires to assess the presenceof activity limitations in daily living and self-­
assessed health in the USA and the UK as
well as Japan.1–3 In addition to conventionalrisk factors of lifestyle-­
related diseases,4 5
several non-­fatal conditions, such as mental
health diseases, orthopaedic problems and

WHAT IS ALREADY KNOWN ON THIS TOPIC⇒ Healthy life years, also known as healthy life ex-pectancy, have come to be focused on as a holistic
health indicator in an ageing society. Estimations ofhealthy life years are derived from national healthsurveys to assess the presence of activity limitations
in daily living and self-­assessed health in the USA
and the UK as well as Japan. Despite accumulating
evidence concerning the association between daily
step counts and mortality or disease risks, there islittle knowledge regarding the association between
daily step counts and healthy life years.

WHAT THIS STUDY ADDS
⇒ Daily step counts were significantly associated withactivity limitations in daily living and self-­assessed
health as key determinants of healthy life years, up
to 9000 and 11 000 step counts, respectively.

HOW THIS STUDY MIGHT AFFECT RESEARCH,
PRACTICE OR POLICY⇒ The findings suggest the optimal target of daily step

counts to prolong healthy life years within healthinitiatives aimed at increasing physical activity
and raising health awareness of people. An effective health promotion, such as an increase in daily
step counts in the general population, will prolong
healthy life years and narrow the existing healthdisparities.

neurological disorders, substantially influence healthy life years.6–8 Effective healthpolicies for the disease prevention and healthpromotion are necessary to prolong healthy
life years and narrow the differences between
life expectancy and healthy life years.
Physical activities and exercises are
expected to be beneficial for healthy life
years.9–11 Walking is a cost-­effective aerobic
physical activity in daily life, and its metric,
step count, is readily measured by simple
devices. While the WHO has issued guidelines
recommending regular physical activity topromote a healthy life, it has refrained from
specifying the optimal target of daily step
counts.12 Notably, an increase in daily step
counts ameliorates cardiovascular disease

Nishi M, et al. BMJ Health Care Inform 2024;31:e101051. doi:10.1136/bmjhci-2024-101051

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Association between daily step counts
and healthy life years: a national cross-­
sectional study in Japan

Open access

METHODS
Study design and setting
The Comprehensive Survey of Living Conditions (CSLC),a cross-­
sectional national survey, has been conducted
every 3 years by Japanese Ministry of Health, Labour andWelfare (MHLW) to investigate the fundamental dimensions of the nation’s livelihood, such as health, medicalcare, welfare, pension and income.3 In health questionnaire of the CSLC, subjective symptoms, health problems
in daily life, disease or injury under treatment, subjective health assessment, worries and stress, mental state,
and receiving rate of health check-­ups are surveyed. The
response rate for CSLC in 2019 was recorded at 72.5%.
The National Health and Nutrition Survey (NHNS),
another cross-­
sectional national survey, has been
conducted with a random sample of participants drawn
from the CSLC by the MHLW to comprehensively investigate the nation’s physical status, nutrition intakes and lifestyle.17 The response rate for NHNS in 2019 was recorded
at 63.5%. In the NHNS, daily step counts in a single day
were measured with a pedometer which was distributed
to the participants, accompanied by detailed instruction
on the measurement procedure. These surveys wereconducted for a randomly sampled general population
through face-­to-­face interviews. An online survey format
was used together for questionnaires regarding physicalstatus and lifestyle in NHNS.
The data of CSLC and NHNS were integrated using
common identifier for prefecture, region, unit, household
and household member. Among the combined dataset of
NHNS and CSLC in 2019, data from 22 respondents withmissing values of activity limitations in daily living or self-­
assessed health were excluded. Consequently, data from4957 adult responders aged ≥18 years were prepared forthe analysis (online supplemental figure 1). The data
were analysed from 30 September 2023 to 20 November
2023.
Outcomes
In the CSLC, activity limitations in daily living of
responders were investigated using responses to thequestions, ‘Do you have any health problem which limits
your daily activity?’ Respondents who answered ‘yes’ were2

categorised into the ‘activity limitations’ group, and those
who answered ‘no’ were categorised into the ‘no activity
limitation’ group. In the NHNS, self-­assessed health wasinvestigated using responses to the questions, ‘How would
you rate your current health status?‘. Respondents who
answered ‘excellent’, ‘good’, or ‘fair’ were categorised
into the ‘self-­assessed healthy status’ group, and those
who answered ‘poor’ or ‘bad’ were categorised into the‘self-­assessed unhealthy status’ group. The associationsof daily step counts with activity limitations in daily living
and self-­assessed health were evaluated for all age group≥18 years and older adults group ≥65 years. In addition,
the health condition without activity limitation (HCAL),
a machine-­learning-­
based integrated health index
reflecting on healthy life years,6 was examined.
Statistical analysis
General statistics were performed in R V.4.2.0.18 Categorical values are represented as numbers (along withpercentages), and numerical values are represented as
medians with IQRs. A p<0.05 was considered statisticallysignificant. The HCAL was computed based on predictive probabilities for activity limitations in daily living
employing a machine-­learning model deployed in Python
V.3.10.6. according to our preceding report.6 Spline curveand its slope curve were plotted with a 95% CI.
The bootstrap method followed by bootstrap aggregating, referred to as bagging, was employed to mitigate
uncertainties in estimating the threshold of daily step
counts by reducing the prediction error.19 A large sample
group was generated by repeatedly drawing samples withreplacement from the original sample. Age, sex andseveral kinds of diseases or injuries under treatment are
known to be important predictors for healthy life years.6
After 1000 rounds of bootstrapping, multivariable logistic
regression model was fitted for each sample, incorporating variables such as age, sex, increments of 1000 daily
step counts and the presence of diseases or injuries under
treatment as predictive factors. Subsequently, mean
adjusted ORs were calculated from the set of predictedvalues of each model, and regression curve fitting was
performed. The OR for adjacent daily step counts wascalculated to define the threshold at which the upper
limit of the 95% CI reached 1.0.
Patient and public involvement
Neither patients nor members of the public were directly
involved in the design, conduct or reporting of thisresearch.

RESULTS
Participants characteristics
Among the combined dataset of the CSLC (n=481 255)
and the NHNS (n=6820) in 2019, the data of adult respondents were extracted (online supplemental figure 1). The
baseline characteristics of participants were described forall-­age group ≥18 years (n=4957) and older adults group

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(CVD) and mortality risk.13–15 In this context, target step
counts of 7200 and 8800 per day have been suggested
for mitigating the risk of CVD and all-­cause mortality,
respectively.16
Despite accumulating evidence concerning the association between daily step counts and mortality or diseaserisks, there is limited knowledge regarding the association between daily step counts and healthy life years. The
purpose of this study is to elucidate the associations ofdaily step counts with activity limitations in daily living
and self-­assessed health, as key determinants of healthy
life years, and provide the optimal target of daily step
counts to prolong healthy life years.

Open access
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Table 1 Baseline characteristics of study participants
Characteristics

All aged ≥18 years (n=4957)

Older adults aged ≥65 years(n=2024)Age, years
Sex (female)

60 (44–71)
2592 (52.3)

72 (69–78)
1046 (51.7)

BMI

22.7 (20.5–25.2)

23.0 (20.9–25.3)

Daily step counts

5650 (3332–8452)

4351 (2314–7023) <2000

478 (12.3)

342 (21.1) 2000–3999

757 (19.4)

400 (24.7) 4000–5999

842 (21.6)

339 (20.9) 6000–7999

714 (18.3)

241 (14.9) 8000–9999

468 (12.0)

147 (9.0) 10 000–11 999

284 (7.2)

73 (4.5) 12 000–13 999

156 (4.0)

34 (2.1) 14 000–15 999

93 (2.3)

24 (1.4) 16 000+107 (2.7)

22 (1.3)

Activity limitations in daily living

686 (13.8)

452 (22.3)

Self-­assessed health status (unhealthy)

681 (13.7)

405 (20.1)

HCAL

93.2 (79.6–96.1)

83.4 (62.6–91.3)

Obesity34 (0.68)

24 (1.1)

Hypertension

913 (18.4)

675 (33.3)

Diabetes

364 (7.3)

276 (13.6)

Dyslipidaemia

399 (8.0)

278 (13.7)

Gout

94 (1.9)52 (2.5)

Depression or other mental diseases

103 (2.0)

24 (1.1)

Dementia

34 (0.68)

31 (1.5)

Parkinson disease

15 (0.30)

13 (0.64)

Other neurological disorders, pain or paralysis

46 (0.92)

27 (1.3)

Stroke, cerebral haemorrhage or infarction

72 (1.4)

58 (2.8)

Angina, myocardial infarction

114 (2.3)

94 (4.6)

Other cardiovascular disease

116 (2.3)

89 (4.4)

Malignant neoplasm or cancer

68 (1.3)

47 (2.3)

Anaemia or blood disease

31 (0.62)

14 (0.69)

Thyroid disease89 (1.8)47 (2.3)

Allergic rhinitis

123 (2.4)

60 (2.9)

Acute nasopharyngitis, common cold

19 (0.38)

11 (0.54)

Chronic obstructive pulmonary disease

16 (0.32)

14 (0.69)

Asthma68 (1.3)

34 (1.6)

Other respiratory disease78 (1.5)

54 (2.6)

Stomach or duodenum disease

101 (2.0)

77 (3.8)

Liver or gallbladder disease

68 (1.3)

40 (1.9)

Other digestive disease

65 (1.3)

40 (1.9)

Rheumatoid arthritis

39 (0.78)

28 (1.3)

Arthritis

160 (3.2)

105 (5.1)

Stiff shoulder

149 (3.0)

93 (4.5)

Back pain
Bone fracture

316 (6.3)
39 (0.78)

220 (10.9)
32 (1.5)
Continued

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Characteristics

All aged ≥18 years (n=4957)

Older adults aged ≥65 years(n=2024)

Osteoporosis

116 (2.3)

101 (4.9)

Other injury or burns

37 (0.74)

21 (1.0)

Kidney disease

65 (1.3)

46 (2.2)

Eye disease389 (7.8)

319 (15.8)

Ear disease67 (1.3)

55 (2.7)

Prostatic hypertrophy

108 (2.1)

99 (4.8)

Dental disease

319 (6.4)

194 (9.5)

Atopic dermatitis

45 (0.90)

6 (0.29)

Other skin disease
Menopausal or postmenopausal disorder

112 (2.2)
11 (0.22)

49 (2.4)
1 (0.049)

Categorical values represented as numbers (%) and numerical values as median (IQR).
BMI, body mass index; HCAL, health condition without activity limitations.

≥65 years (n=2024) (table 1). The median age was 60
years vs 72 years, and female sex comprised 2592 (52.3%)
vs 1046 (51.7%) in the all-­age and older adults group,
respectively. The median daily step counts were 5652 step
counts in the all-­age group, compared with 4358 step
counts in the older adults group. The prevalence rate ofactivity limitations in daily living was 686 (13.8%) vs 452(22.3%), and the rate of self-­assessed unhealthy status was
681 (13.7%) vs 405 (20.1%) in the all-­age and older adultgroups, respectively. The median value of HCAL was 93.2
vs 83.4. The older adults group exhibited higher prevalence rate of various kinds of diseases or injuries under
treatments compared with the all-­age group, except for
depression or other mental diseases, atopic dermatitis
and menopausal or postmenopausal disorder.
Association between daily step counts and activity limitations
in daily living
To ascertain the association between daily step counts
and healthy life years, spline curve and its slope curve
were depicted for daily step counts and HCAL (figure 1).
In the all-­age group, as daily step counts increased, HCAL
increased with a marked rise at fewer daily step counts
although the increase was gradually diminished in higher
daily step counts. The lower limit of the 95% CI of slope
descended below 0 at approximately 12 000 step counts
per day. Similar to the all-­age group, in the older adults
group, as daily step counts increased, HCAL showed asimilar trend, and the lower limit of the 95% CI of slope
descended below 0 within the range of 10 000–11 999 step
counts per day. The sex difference was not detected in theassociation between daily step counts and HCAL in boththe all-­age and older adult groups (online supplemental
figure 2).
The associations between daily step counts and activity
limitations in daily living were assessed (figure 2 andonline supplemental figure 3). In the all-­age group, as
daily step counts increased, the unadjusted rate of activity
4

limitations in daily living declined, and the adjusted odds
of activity limitations in daily living steadily decreased. The
adjusted OR for the adjacent daily step counts was 0.27
(95% CI 0.26 to 0.27) at the lowest, and the upper limitof the 95% CI reached 1.0 at 9000 step counts (OR 0.95
(95% CI 0.91 to 1.00)). Similarly, the older adults groupexhibited a parallel trend in the association between daily
step counts and activity limitations in daily living. The
OR was 0.25 (95% CI 0.25 to 0.26) at the lowest, and theupper limit of the 95% CI reached 1.0 at 9000 step counts(OR 0.92 (95% CI 0.85 to 1.00)). The impact of sex was
not significant in both the all-­age and older adult groups(online supplemental figure 4 and 5). Collectively, daily
step counts were significantly associated with activity
limitations in daily living, with the threshold at 9000 step
counts in both the all-­age and older adult groups.
Association between daily step counts and self-assessed
healthThe associations between daily step counts and self-­
assessed health were also assessed (figure 3 and online
supplemental figure 6). In all-­age group, as daily step
counts increased, the unadjusted rate of self-­
assessedunhealthy status declined, and the adjusted odds of self-­
assessed unhealthy status steadily decreased. The OR for
the adjacent daily step counts was 0.45 (95% CI 0.44 to0.46) at the lowest, and the upper limit of the 95% CI
reached 1.0 at 11 000 step counts (OR 0.95 (95% CI 0.89
to 1.00)). The older adults group exhibited similar trendsof the association between daily step counts and self-­
assessed unhealthy status. The OR was 0.42 (95% CI 0.41
to 0.43) at the lowest, and the upper limit of the 95% CI
reached 1.0 at 11 000 step counts (OR 0.91 (95% CI 0.80
to 1.03)). The impact of sex was not significant in boththe all-­age and older adult groups (online supplemental
figures 7 and 8). Thus, daily step counts were significantly
associated with self-­assessed health, with the threshold

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Table 1 Continued

Open accessat 11 000 step counts in both the all-­age and older adultgroups.
DISCUSSION
This study using the combined national health survey
data has provided the insights into the associations ofdaily step counts with activity limitations in daily living
and self-­assessed health, as key determinants of healthy
life years. An increase in daily step counts was significantly
associated with the improvement of activity limitations indaily living and self-­assessed health, with thresholds ofsignificant association at 9000 and 11 000 step counts,
respectively, regardless of age.

This study suggests the optimal target of daily step
counts to prolong healthy life: 9000 step counts for activity
limitations in daily living and 11 000 step counts for self-­
assessed health. Increase in daily step counts reduces CVD
and mortality risks, whereas the effect of step intensity
is controversial.13–15 20 21 A meta-­analysis has introduced
7200 and 8800 step counts per day as potential targets for
reducing CVD and all-­cause mortality risks, respectively.16
Given that healthy life years are shorter than life expectancy, it is conceivable that the optimal targets of daily
step counts, for prolonging healthy life years, may necessitate more step counts than what are required for the
reduction of mortality and CVD risk.

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Figure 1 Association between daily step counts and integrated health index reflecting on healthy life years. Spline curve andslope curve were depicted by plotting daily step counts and health condition without activity limitations (HCAL) for all-­age andolder adult groups. Shaded areas represent 95% CI.

Open access

We evaluated activity limitations in daily living andself-­assessed health status—metrics that do not include
mortality, as alternatives to healthy life years. Indeed,
healthy life years are estimated based on a healthsurvey regarding activity limitations in daily living andself-­assessed health in the USA and the UK as well asJapan.1–3 The prevalence rates of activity limitations indaily living or self-­assessed unhealthy status in each age
groups are incorporated into a life table to estimate
healthy life years.22 Self-­assessed health has been shown
to be a predictor for mortality and morbidity.23 24 In addition, racial and ethnic disparities of self-­assessed healthstatus have been reported.25 While life expectancy has
6been increasing, healthy life years have not kept pace inthe world.26 27 An improvement of activity limitations indaily living and self-­assessed health by an effective healthpromotion, such as an increase in daily step counts in thegeneral population, will prolong healthy life years, andnarrow the existing health disparities.
The data used in this study are derived from nationalcross-­sectional surveys, and no causal inferences can be
deduced. Population-­based cohort will be needed tofurther investigate the prospective effect of daily step
counts on healthy life years. Step intensity was not evaluated because the investigation did not include it. Potential confounding factors, such as income, that could affectNishi M, et al. BMJ Health Care Inform 2024;31:e101051. doi:10.1136/bmjhci-2024-101051

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Figure 2 Association between daily step counts and activity limitations in daily living. Adjusted ORs and ORs of activity
limitation in daily living were evaluated for daily step counts. Once the daily step counts reached 9000, an increase in 1000 step
counts per day was no longer significantly associated with reduced odds of activity limitations in daily living for all-­age andolder adult groups. Error bars and shaded areas represent 95% CI.

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Figure 3 Association between daily step counts and self-­assessed health. Adjusted ORs and ORs of self-­assessed unhealthy
status were evaluated for daily step counts. Once the daily step counts reached 11 000, an increase in 1000 step counts per
day was no longer significantly associated with reduced odds of self-­assessed unhealthy status for all-­age and older adultgroups. Error bars and shaded areas represent 95% CI.

the association between daily step counts and healthy life
years were not considered.
CONCLUSION
Daily step counts were significantly associated withactivity limitations in daily living and self-­a ssessed
health as determinants of healthy life years, up to
9000 and 11 000 step counts, respectively. These findings suggest the optimal target of daily step counts
to prolong healthy life years within health initiatives aimed at increasing physical activity and raising
health awareness of people.

Acknowledgements We are grateful to Tomoyuki Yamamoto, Mika Yamashita,
Satoko Kumagai and Kumiko Katsuyama from the Department of Health andWelfare, Kyoto Prefectural Government.
Contributors MN was responsible for conception of the study and overall content
as guarantor. MN and RN had full access to all of the data in the study and took
responsibility for the integrity of the data and the accuracy of the data analysis. All
authors participated in manuscript writing and approved the final manuscript. SM
provided overall supervision. All the authors were responsible for the decision tosubmit the manuscript for publication.
Funding This study was supported by Foundation for Total Health Promotion.
Competing interests None declared.
Patient consent for publication Not applicable.

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Provenance and peer review Not commissioned; externally peer reviewed.

10

Data availability statement Data may be obtained from a third party and are
not publicly available. We are prohibited from publicly opening the data. Data canbe accessed through the Household Statistics Office of the Japanese Ministry of
Health, Labour and Welfare (https://www.mhlw.go.jp/toukei/itiran/eiyaku.html).

11

Supplemental material This content has been supplied by the author(s). It has
not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been
peer-­reviewed. Any opinions or recommendations discussed are solely thoseof the author(s) and are not endorsed by BMJ. BMJ disclaims all liability andresponsibility arising from any reliance placed on the content. Where the content
includes any translated material, BMJ does not warrant the accuracy and reliabilityof the translations (including but not limited to local regulations, clinical guidelines,
terminology, drug names and drug dosages), and is not responsible for any error
and/or omissions arising from translation and adaptation or otherwise.

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Open access This is an open access article distributed in accordance with theCreative Commons Attribution Non Commercial (CC BY-­NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non-­commercially,and license their derivative works on different terms, provided the original work is
properly cited, appropriate credit is given, any changes made indicated, and the use
is non-­commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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ORCID iD
Masahiro Nishi http://orcid.org/0000-0001-8593-3835

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Nishi M, et al. BMJ Health Care Inform 2024;31:e101051. doi:10.1136/bmjhci-2024-101051

BMJ Health & Care Informatics: first published as 10.1136/bmjhci-2024-101051 on 30 April 2024. Downloaded from https://informatics.bmj.com on 8 October 2024 by guest. Protected bycopyright.

Ethics approval The study received ethical approval from the ethics committeeof Kyoto Prefectural University of Medicine with the approval number ERB-­C-­2878.
This study conformed to the principles outlined in the Declaration of Helsinki. Given
that this study uses pre-­existing national survey data, informed consent from study
participants was exempted.