Evidence map›Paper›PMID 42828141›Full record

ArticleThe Lancet regional health. Western Pacific2026

Projections of diabetes mellitus in Japan through 2040: a bayesian age-period-cohort analysis of the national health and nutrition survey population.

Rajib Mondal, Soshiro Ogata, Eri Kiyoshige, Yuriko Nakaoku, Kiyomasa Nakatsuka, Tomomi Watanabe, Kanako Teramoto, Aya Kadota, Katsuyuki Miura, Chris Kypridemos and 2 more

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Article in The Lancet regional health. Western Pacific, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

12 authors.

Rajib MondalDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan.
Soshiro OgataDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan.
Eri KiyoshigeDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan.
Yuriko NakaokuDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan.
Kiyomasa NakatsukaDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan.
Tomomi WatanabeDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan.
Kanako TeramotoDepartment of Biostatistics, National Cerebral and Cardiovascular Center, Osaka, Japan.
Aya KadotaDepartment of Preventive Medicine, Shiga University of Medical Science, Shiga, Japan.
Katsuyuki MiuraDepartment of Preventive Medicine, Shiga University of Medical Science, Shiga, Japan.
Chris KypridemosDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, United Kingdom.
Yusuke YoshikawaDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan.
Kunihiro NishimuraDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accurate projection of the burden of diabetes mellitus (DM) requires consideration of age, period, and cohort (APC) effects underlying prevalence trends. We estimated projected trends in DM prevalence and case numbers in Japan from 2020 until 2040, by sex, using the Bayesian APC (BAPC) model. Methods: We employed Bayesian age-period-cohort modeling and prediction (BAMP), using observed populations (aged 40 years or older) and DM cases from the National Health and Nutrition Survey from 2003 to 2019, to project national-level DM prevalence and cases from 2020 to 2040 using the national-level projected population until 2040. We further compared BAPC's predictive performance with that of conventional prediction model 1 with a constant prevalence rate and conventional prediction model 2 with a monotonically changing prevalence rate, using root mean square error (RMSE) between observed and projected case numbers for model validation during 2015-2019. Findings: The prevalence (95% credible intervals) of DM in Japan was projected to increase from 16.4% (12.3%-21.6%) in 2020 to 18.1% (6.4%-40.8%) in 2040 in men by BAPC, while it was projected to decline from 9.6% (6.8%-13.3%) to 7.7% (2.3%-22.7%) in women, variations primarily suggested by age effects and cohort effects. DM cases (95% credible intervals) are expected to increase from 6,070,000 (4,530,000-7,980,000) in 2020 to 6,336,000 (2,230,000-14,290,000) in 2040 in men, while they were expected to decline from 3,995,000 (2,840,000-5,540,000) to 3,032,000 (910,000-8,910,000) in women. The BAPC demonstrated the best predictive performance with lower RMSE (men, 40.1; women, 11.5), compared to conventional model 1 (men, 51.3; women, 20.8) and conventional model 2 (men, 42.4; women, 23.1). Interpretation: This study suggests that Japan is expected to experience increases in the prevalence and number of DM cases from 2020 to 2040, particularly among men, given the APC factors. Funding: This research was supported by JSPS KAKENHI Grant.

Indexed as

Bayesian age-period-cohortBayesian age-period-cohort modeling and predictionDiabetes trendsProjection modeling

Identifiers

PMID42828141
PMCPMC13631670

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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.