Evidence map›Paper›PMID 20566665›Full record

ArticleDiabetes2010

Age-period-cohort analysis of 1990-2003 incidence time trends of childhood diabetes in Italy: the RIDI study.

Graziella Bruno, Milena Maule, Franco Merletti, Giulia Novelli, Alberto Falorni, Antonio Iannilli, Lorenzo Iughetti, Emma Altobelli, Giuseppe d'Annunzio, Silvano Piffer and 8 more

Abstract read
In one paragraph

Article in Diabetes, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Endocrine Disrupting Chemicals and Type 1 Diabetes.International journal of molecular sciences · 2020
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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

18 authors.

Graziella BrunoDepartment of Internal Medicine, University of Turin, Turin, Italy. graziella.bruno@unito.it
Milena Maule
Franco Merletti
Giulia Novelli
Alberto Falorni
Antonio Iannilli
Lorenzo Iughetti
Emma Altobelli
Giuseppe d'Annunzio
Silvano Piffer
Paolo Pozzilli
Dario Iafusco
Marco Songini
Federico Roncarolo
Sonia Toni
Flavia Carle
Valentino Cherubini
RIDI Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate age-period-cohort effects on the temporal trend of type 1 diabetes in children age 0-14 years in Italian registries. RESEARCH DESIGN AND

methodsThis report is based on 5,180 incident cases in the period 1990-2003 from the Registry for Type 1 Diabetes Mellitus in Italy (RIDI). Multilevel (random intercept) Poisson regression models were used to model the effects of sex, age, calendar time, and birth cohorts on temporal trends, taking into account the registry-level variance component.

resultsThe incidence rate was 12.26 per 100,000 person-years and significantly higher in boys (13.13 [95% CI 12.66-13.62]) than in girls (11.35 [10.90-11.82]). Large geographical variations in incidence within Italy were evident; incidence was highest in Sardinia, intermediate in Central-Southern Italy, and high in Northern Italy, particularly in the Trento Province, where the incidence rate was 18.67 per 100,000 person-years. An increasing temporal trend was evident (2.94% per year [95% CI 2.22-3.67]). With respect to the calendar period 1990-1992, the incidence rates increased linearly by 15, 27, 35, and 40% in the following time periods (P for trend < 0.001). With respect to the 1987-1993 birth cohort, the incidence rate ratio increased approximately linearly from 0.63 (95% CI 0.54-0.73) in the 1975-1981 cohort to 1.38 (1.06-1.80) in the 1999-2003 cohort. The best model, however, included sex, age, and a linear time trend (drift).

conclusionsLarge geographical variations and an increasing temporal trend in diabetes incidence are evident among type 1 diabetic children in Italy. Age-period-cohort analysis shows that the variation over time has a linear component that cannot be ascribed to either the calendar period or the birth cohort.

Indexed as

AdolescentChildChild, PreschoolCohort StudiesDiabetes Mellitus, Type 1FemaleGeographyHumansIncidenceInfantItalyLikelihood FunctionsMalePoisson DistributionRegistries

Identifiers

PMID20566665
PMCPMC2927951

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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.