Evidence map›Paper›PMID 33900203›Full record

Observational studyJournal of medical Internet research2021

Effects of an mHealth App (Kencom) With Integrated Functions for Healthy Lifestyles on Physical Activity Levels and Cardiovascular Risk Biomarkers: Observational Study of 12,602 Users.

Rikuta Hamaya, Hiroshi Fukuda, Masaki Takebayashi, Masaki Mori, Ryuji Matsushima, Ken Nakano, Kuniaki Miyake, Yoshiaki Tani, Hirohide Yokokawa

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
13.1field-weighted citation impact, top 1% of its field
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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Inequalities in Exclusively Mobile Interventions Targeting Weight-Related Behaviors: Systematic Review of Observational Studies.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
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  20. Current situation of telemedicine research for cardiovascular risk in Japan.Hypertension research : official journal of the Japanese Society of Hypertension · 2023
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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

9 authors at 3 institutions in 2 countries.

Rikuta HamayaDivision of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.ORCID 0000-0003-1635-1983
Hiroshi FukudaDepartment of General Medicine, School of Medicine, Juntendo University, Tokyo, Japan.ORCID 0000-0002-1072-3021
Masaki TakebayashiGraduate School of Health Science, Aomori University of Health and Welfare, Aomori, Japan.ORCID 0000-0002-7221-4126
Masaki MoriDeSC Healthcare Inc., Tokyo, Japan.ORCID 0000-0002-1862-2989
Ryuji MatsushimaDeSC Healthcare Inc., Tokyo, Japan.ORCID 0000-0002-6309-3510
Ken NakanoDeSC Healthcare Inc., Tokyo, Japan.ORCID 0000-0003-4071-9733
Kuniaki MiyakeDeSC Healthcare Inc., Tokyo, Japan.ORCID 0000-0002-4493-6965
Yoshiaki TaniDeSC Healthcare Inc., Tokyo, Japan.ORCID 0000-0002-2260-4169
Hirohide YokokawaDepartment of General Medicine, School of Medicine, Juntendo University, Tokyo, Japan.ORCID 0000-0001-9464-9828
Juntendo University · JPAomori University of Health and Welfare · JPBrigham and Women's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health (mHealth) apps are considered to be potentially powerful tools for improving lifestyles and preventing cardiovascular disease (CVD), although only few have undergone large, well-designed epidemiological research. "kencom" is a novel mHealth app with integrated functions for healthy lifestyles such as monitoring daily health/step data, providing tailored health information, or facilitating physical activity through group-based game events. The app is linked to large-scale Japanese insurance claims databases and annual health check-up databases, thus comprising a large longitudinal cohort.

objectiveWe aimed to assess the effects of kencom on physical activity levels and CVD risk factors such as obesity, hypertension, dyslipidemia, and diabetes mellitus in a large population in Japan.

methodsDaily step count, annual health check-up data, and insurance claim data of the kencom users were integrated within the kencom system. Step analysis was conducted by comparing the 1-year average daily step count before and after kencom registration. In the CVD risk analysis, changes in CVD biomarkers following kencom registration were evaluated among the users grouped into the quintile according to their change in step count.

resultsA total of 12,602 kencom users were included for the step analysis and 5473 for the CVD risk analysis. The participants were generally healthy and their mean age was 44.1 (SD 10.2) years. The daily step count significantly increased following kencom registration by a mean of 510 steps/day (P<.001). In particular, participation in "Arukatsu" events held twice a year within the app was associated with a remarkable increase in step counts. In the CVD risk analysis, the users of the highest quintile in daily step change had, compared with those of the lowest quartile, a significant reduction in weight (-0.92 kg, P<.001), low-density lipoprotein cholesterol (-2.78 mg/dL, P=.004), hemoglobin A

conclusionsThe framework of kencom successfully integrated the Japanese health data from multiple data sources to generate a large, longitudinal data set. The use of the kencom app was significantly associated with enhanced physical activity, which might lead to weight loss and improvement in lipid profile.

Indexed as

Cardiovascular DiseasesMobile ApplicationsTelemedicineAdultBiomarkersExerciseHealthy LifestyleHeart Disease Risk FactorsHumansRisk FactorsBiomarkersappcardiovascular diseasemHealthmobile phonephysical activitysmartphone

Identifiers

PMID33900203
PMCPMC8111509
OpenAlexW3138829471

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.