Evidence map›Paper›PMID 24285630›Full record

ArticleBMJ open2013

Joint effects of serum ferritin and body mass index on the risk of coronary artery disease: a case-control study.

Yunping Zhou, Tongtao Liu, Chongqi Jia

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 6 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

3 authors at 2 institutions in 1 country.

Yunping ZhouDepartment of Epidemiology and Health Statistics, Shandong University, Jinan, Shandong, People's Republic of China.
Tongtao Liu
Chongqi Jia
Shandong University · CNQilu Hospital of Shandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSerum ferritin and body mass index (BMI) have been reportedly associated with coronary artery disease (CAD) risk. The aim of the present study was to explore the interaction between serum ferritin and BMI on CAD risk.

designHospital-based case-control study.

settingPatients with CAD and the controls were recruited from Qilu Hospital, Shandong University.

participants258 CAD cases and 282 healthy controls.

methodsMultiplicative interaction was assessed through a cross-product interaction term in a multivariate logistic regression model. The effect of serum ferritin and BMI were evaluated per 50 µg/L and per 2 kg/m(2), respectively. The presence of additive interaction between serum ferritin and BMI was evaluated by calculation of the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP) and synergy index (S).

resultsThe ORs and 95% CI of the serum ferritin-BMI product term on a multiplicative scale in the univariate and multivariate models were 0.943 (0.904 to 0.984) and 1.004 (0.951 to 1.059), respectively. There was also evidence for interaction on an additive scale; the RERI (95% CI), AP (95% CI) and S (95% CI) in the univariate model were 0.314 (0.026 to 1.506), 0.107 (0.017 to 0.241) and 1.194 (1.053 to 1.406), respectively. After adjusting for the potential confounders, the estimates and 95% CIs for the aforementioned three measures were 0.004 (-0.016 to 0.311), 0.004 (-0.016 to 0.191) and 1.039 (0.774 to 1.285), respectively.

conclusionsSerum ferritin and BMI had an additive interaction on the risk of CAD in Chinese population. Further investigations with big sample size are necessary for confirming this additive interaction.

Indexed as

Nutrition & DieteticsPublic Health

Identifiers

PMID24285630
PMCPMC3845034
OpenAlexW2152784743

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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.