Evidence map›Paper›PMID 32662080›Full record

ArticleHealth economics2021

Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross-sectional data.

Megumi Kasajima, Hideki Hashimoto, Sze-Chuan Suen, Brian Chen, Hawre Jalal, Karen Eggleston, Jay Bhattacharya

Open access · hybridAbstract read
In one paragraph

Article in Health economics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
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  3. Review
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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

7 authors at 6 institutions in 4 countries.

Megumi KasajimaDepartment of Health and Social Behavior, School of Public Health, University of Tokyo, Bunkyo-ku, Japan.ORCID 0000-0003-3804-8328
Hideki HashimotoDepartment of Health and Social Behavior, School of Public Health, University of Tokyo, Bunkyo-ku, Japan.
Sze-Chuan SuenEpstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California.
Brian ChenDepartment of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina.
Hawre JalalDepartment of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Karen EgglestonFSI Shorenstein Asia Pacific Research Center, Stanford University, Stanford, California.
Jay BhattacharyaCenter for Primary Care and Outcomes Research, Stanford School of Medicine, Stanford, California.
Department of Health · IEPacific Research Institute · USStanford Medicine · USUniversity of Pittsburgh · USUniversity of South Carolina · USUniversity of Southern California · US

Funding

USC Resource Center for Minority Aging Research (US-RCMAR)P30AG043073 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI EMMA AGUILA, JENNIFER A AILSHIRE · 2012 to 2026
$10.1M
EXPANDING MHAS RESEARCH INFRASTRUCTURE WITH HISTORICAL CLIMATE AND LIFETIME WORKPLACE ENVIRONMENTAL EXPOSURES INFLUENCING INEQUITIES IN AD/ADRDP30AG066589 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI DANA P GOLDMAN, JULIE M ZISSIMOPOULOS · 2020 to 2026
$6.1M
CORE--PROGRAM DEVELOPMENTP30AG017253 · NIA · STANFORD UNIVERSITY · PI BHATTACHARYA, JAY · 1999 to 2019
$5.8M
NIA NIH HHS P30 AG017253NIA NIH HHS P30 AG043073NIA NIH HHS P30 AG066589
6 · The paper itself

Abstract

Accurate future projections of population health are imperative to plan for the future healthcare needs of a rapidly aging population. Multistate-transition microsimulation models, such as the U.S. Future Elderly Model, address this need but require high-quality panel data for calibration. We develop an alternative method that relaxes this data requirement, using repeated cross-sectional representative surveys to estimate multistate-transition contingency tables applied to Japan's population. We calculate the birth cohort sex-specific prevalence of comorbidities using five waves of the governmental health surveys. Combining estimated comorbidity prevalence with death record information, we determine the transition probabilities of health statuses. We then construct a virtual Japanese population aged 60 and older as of 2013 and perform a microsimulation to project disease distributions to 2046. Our estimates replicate governmental projections of population pyramids and match the actual prevalence trends of comorbidities and the disease incidence rates reported in epidemiological studies in the past decade. Our future projections of cardiovascular diseases indicate lower prevalence than expected from static models, reflecting recent declining trends in disease incidence and fatality.

Indexed as

Birth CohortFunctional StatusAgedCross-Sectional StudiesFemaleForecastingHumansJapanMaleMiddle Ageddemographic trends, economics of the elderlyforecasting modelshealth and economic developmentsimulation methods

Identifiers

PMID32662080
PMCPMC8032851
OpenAlexW3042826391

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.