Evidence map›Paper›PMID 21432065›Full record

ArticleEnvironmental health and preventive medicine2007

Age-period-cohort analysis of asthma prevalence among school children.

Etsuji Okamoto, Eiichi Hata, Masako Kobayashi, Kenji Hayashi

Open access · bronzeAbstract read
In one paragraph

Article in Environmental health and preventive medicine, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 78% 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Etsuji OkamotoNational Institute of Public Health, 2-3-6, Minami, 351-0197, Wako-shi, Saitama, Japan, atoz@niph.go.jp.
Eiichi Hata
Masako Kobayashi
Kenji Hayashi
National Institute of Public Health · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prevalence of age-dependent diseases such as asthma is confounded not only by aging effects but also by cohort and period effects. Age-period-cohort (APC) analysis is commonly performed to isolate the effects of these three factors from two-way tables of prevalence by age and birth cohort. However, APC analysis suffers from technical difficulties such as non-identifiability problems. We isolated the effects of these three factors in a step-by-step manner by analyzing Japan's school health data collected from 1984 to 2004 focusing on asthma prevalence among school children aged 6-17 years consisting of 30 birth cohorts (entering classes). We verified the accuracy of our method showing high agreement of the observed age-, period- and cohort-specific data and the data predicted by our method. The aging effects were found to follow cubic equations whose multinomial coefficients were determined by an optimization technique. The obtained aging effect curves of age-specific asthma prevalence showed that boys reach the peak prevalence at 13 and girls at 14, declining markedly afterward. The cohort effects, defined as the arithmetic asthma prevalence means for ages 6-17 years, showed consistent upward trends for the 30 birth cohorts born in 1968-97 for both sexes. The period effects showed a consistent decline since 1984 but abruptly increased in 1999 and then declined again. We were not able to identify the exact cause of the increase in 1999, therefore, this should be examined in the future studies. Because the cohort effects show no sign of leveling off yet, asthma prevalence will likely increase in the foreseeable future.

Indexed as

age-period-cohort analysisasthmacohort effectschool health

Identifiers

PMID21432065
PMCPMC2723228
OpenAlexW2088840695

What OpenQuestion holds

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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.