Evidence map›Paper›PMID 21595911›Full record

ArticleBMC public health2011

Childhood meat eating and inflammatory markers: the Guangzhou Biobank Cohort Study.

C M Schooling, C Q Jiang, T H Lam, W S Zhang, K K Cheng, G M Leung

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2011. 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
1.9field-weighted citation impact, top 15% 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, 7 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

6 authors at 3 institutions in 4 countries.

C M SchoolingSchool of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China. hrmrlth@hkucc.hku.hk.
C Q Jiang
T H Lam
W S Zhang
K K Cheng
G M Leung
University of Hong Kong · HKTwelfth Guangzhou City People's Hospital · CNUniversity of Birmingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe hypothesized that socio-economic development could, via nutritionally driven levels of pubertal sex-steroids, promote a pro-inflammatory state among men but not women in developing countries. We tested this hypothesis, using recalled childhood meat eating as a proxy for childhood nutrition, in southern China.

methodsWe used multivariable linear regression in the Guangzhou Biobank Cohort Study phase 3 (2006-8) to examine the adjusted associations of recalled childhood meat eating, <1/week (n = 5,023), about once per week (n = 3,592) and almost daily (n = 1,252), with white blood cell count and its differentials among older (≥ 50 years) men (n = 2,498) and women (n = 7,369).

resultsAdjusted for age, childhood socio-economic position, education and smoking, childhood meat eating had sex-specific associations with white blood cell count and lymphocyte count, but not granulocyte count. Men with childhood meat eating almost daily compared to <1/week had higher white blood cell count (0.33 109/L, 95% confidence interval (CI) 0.10 to 0.56) and higher lymphocyte count (0.16 109/L, 95% CI 0.07 to 0.25). Adjustment for obesity slightly attenuated these associations.

conclusionIf confirmed, this hypothesis implies that economic development and the associated improvements in nutrition at puberty may be less beneficial among men than women; consistent with the widening sex differentials in life expectancy with economic development.

Indexed as

DietAgedAged, 80 and overBiomarkersChildChinaCohort StudiesEconomic DevelopmentFemaleHumansInflammationLinear ModelsMaleMeatMiddle AgedSex FactorsBiomarkers

Identifiers

PMID21595911
PMCPMC3121633
OpenAlexW1991749233

What OpenQuestion holds

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LicenceCC BY
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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.