Evidence map›Paper›PMID 38157236›Full record

ArticleJMIR public health and surveillance2023

Trends and Projection of the Incidence of Active Pulmonary Tuberculosis in Southwestern China: Age-Period-Cohort Analysis.

Jinou Chen, Yubing Qiu, Wei Wu, Rui Yang, Ling Li, Yunbin Yang, Xing Yang, Lin Xu

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

13 citing papers in PubMed, 16 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Jinou ChenDivision of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0000-0001-6074-2178
Yubing QiuDivision of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0009-0005-3401-3621
Wei WuDivision of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0000-0002-3098-9708
Rui YangDivision of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0009-0004-3076-6469
Ling LiDivision of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0009-0001-1548-4162
Yunbin YangDivision of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0009-0005-8784-0727
Xing YangDivision of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0009-0009-1357-1578
Lin XuDivision of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0000-0003-4512-347X
Yunnan Center for Disease Control And Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe control of pulmonary tuberculosis (PTB) is critical for achieving the vision of World Health Organization's End TB goal.

objectiveThis study analyzes the temporal trends in PTB incidence associated with age, period, and birth cohorts from 2006 to 2020 in Yunnan, China; projects the PTB burden till 2030; and explores the drivers of PTB incidence.

methodsThe aggregated PTB incidence rates between 2005 and 2020 were obtained from the National Notifiable Disease Reporting System. We used the age-period-cohort model to evaluate the age, period, and cohort effects on PTB incidence. We applied the Bayesian age-period-cohort model to project future PTB incidence from 2021 to 2030. We applied the decomposition algorithm to attribute the incidence trends to population aging, population growth, and age-specific changes from 2006 to 2030.

resultsFrom 2006 to 2020, the PTB incidence in Yunnan was relatively stable, although the absolute number showed an increase. The net drift was -1.56% (95% CI -2.41% to -0.70%). An M-shaped bimodal local drift and a longitudinal age curve were observed. The overall local drift was below zero for most age groups except for the age groups of 15-19 years (2.37%, 95% CI -0.28% to 5.09%) and 50-54 years (0.41%, 95% CI -1.78% to 2.64%). The highest risk of PTB incidence was observed in the age group of 65-69 years, and another peak was observed in the age group of 20-24 years. Downward trends were observed for both period and cohort effects, but the cohort effect trends were uneven. A higher risk was observed for the birth cohorts of 1961-1970 (rate ratio [RR]

conclusionsAlthough there are several levels and measures for PTB control, the disease burden is likely to increase in the future. To bridge the gap of TB-free vision, our study suggests that public health policies be put in place soon, including large-scale active case-finding, priority prevention policies for high-risk older adult and young adult populations, and reduction of possible grandparent-grandchildren transmission patterns.

Indexed as

TuberculosisTuberculosis, PulmonaryAdolescentAdultAgedBayes TheoremChinaCohort StudiesHumansIncidenceYoung Adultage-period-cohort modelingbayesian age-period-cohort modeldecomposition of disease burdenprojectionpulmonary tuberculosis

Identifiers

PMID38157236
PMCPMC10787335
OpenAlexW4388085621

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.