Evidence map›Paper›PMID 23353079›Full record

ArticleInjury prevention : journal of the International Society for Child and Adolescent Injury Prevention2013

Population-based characteristics of fatal and hospital admissions for poisoning in Fiji: TRIP Project-11.

Roshini Peiris-John, Berlin Kafoa, Iris Wainiqolo, Ravi Krishnan Reddy, Eddie McCaig, Shanthi N Ameratunga

Open access · hybridAbstract read
In one paragraph

Article in Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 20% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Poisoning deaths in China, 2006-2016.Bulletin of the World Health Organization · 2018
    Article
  4. 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

6 authors at 2 institutions in 2 countries.

Roshini Peiris-JohnSection of Epidemiology & Biostatistics, School of Population Health, The University of Auckland, , Auckland, New Zealand.
Berlin Kafoa
Iris Wainiqolo
Ravi Krishnan Reddy
Eddie McCaig
Shanthi N Ameratunga
Fiji National University · FJUniversity of Auckland · NZ

Funding

Wellcome TrustWellcome Trust GR071671MA
6 · The paper itself

Abstract

This study investigated the incidence and characteristics of poisoning fatalities and hospital admissions among indigenous Fijians and Indians in Viti Levu, Fiji. Individuals with a mechanism of injury classified as poisoning were identified using the Fiji injury surveillance in hospitals system, a population-based registry established for 12 months in Viti Levu, and analysed using population-based denominators. The mean annual rates of fatalities and hospitalisations were 2.3 and 26.0 per 100 000, respectively. Over two-thirds of poisonings occurred among people of Indian ethnicity. Most intentional poisoning admissions occurred among women (58.3%) and in 15-29-year-old individuals (73.8%). Unintentional poisoning admission rates were highest among Indian boys aged 0-14 years. While over 75% of events occurred at home, the substances involved were not systematically identified. The findings indicate the need for a strategy that addresses the differing contexts across age group, gender and ethnicity, and a lead agency responsible for implementing and monitoring its effectiveness.

Indexed as

AdolescentAdultAge DistributionChildChild, PreschoolFemaleFijiHospitalizationHumansIncidenceInfantMaleMiddle AgedPoisoningRegistriesRisk Factors

Identifiers

PMID23353079
PMCPMC3786648
OpenAlexW2127023213

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.