Evidence map›Paper›PMID 35889812›Full record

SynthesisNutrients2022

Early-Life Exposure to the Chinese Famine of 1959-1961 and Type 2 Diabetes in Adulthood: A Systematic Review and Meta-Analysis.

Chihua Li, L H Lumey

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
17.1field-weighted citation impact, top 1% 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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 45 citations in OpenAlex.

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  17. Accelerated biological aging six decades after prenatal famine exposure.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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

2 authors at 2 institutions in 2 countries.

Chihua LiDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.ORCID 0000-0002-0933-8425
L H LumeyDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
Columbia University · USZhengzhou Central Hospital · CN

Funding

Genetic analysis of the Dutch Hunger Winter Families Study to Boost Rigor and Robustness for Testing In-Utero Famine Effects on Aging-Related Health Conditions and Biological AgingR01AG066887 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BELSKY, DANIEL WALKER, LUMEY, L H · 2020 to 2024
$3.5M
NIA NIH HHS R01 AG066887
6 · The paper itself

Abstract

backgroundThe fast-growing literature suggests that the Chinese famine of 1959-1961 drives current and future type 2 diabetes (T2D) epidemics in China. This conclusion may be premature, as many Chinese famine studies have major methodological problems. We examine these problems, demonstrate how they bias the study results, and formulate recommendations to improve the quality of future studies.

methodsWe searched English and Chinese databases for studies that examined the relationship between prenatal exposure to the Chinese famine and adult T2D from inception to 8 February 2022. We extracted information on T2D cases and study populations of individuals born during the famine (famine births), before the famine (prefamine births), and after the famine (postfamine births). We used random-effects models to compare the odds of T2D in famine births to several control groups, including postfamine births, combined pre- and postfamine births, and prefamine births. We used meta-regressions to examine the impacts of age differences between comparison groups on famine effect estimates and the role of other characteristics, including participant sex, age, and T2D assessments; famine intensity; residence; and publication language. Potential sources of heterogeneity and study quality were also evaluated.

resultsTwenty-three studies met our inclusion criteria. The sample sizes ranged from less than 300 to more than 360,000 participants. All studies defined the famine exposure based on the participants' dates of birth, and 18 studies compared famine births and postfamine births to estimate famine effects on T2D. The famine and postfamine births had an age difference of three years or more in all studies. The estimates of the famine effect varied by the selection of controls. Using postfamine births as controls, the OR for T2D among famine births was 1.50 (95% CI 1.34-1.68); using combined pre- and postfamine births as controls, the OR was 1.12 (95% CI 1.02-1.24); using prefamine births as controls, the OR was 0.89 (95% CI 0.79-1.00). The meta-regressions further showed that the famine effect estimates increased by over 1.05 times with each one-year increase in ignored age differences between famine births and controls. Other newly identified methodological problems included the poorly assessed famine intensity, unsuitable study settings for famine research, and poor confounding adjustment.

interpretationThe current estimates of a positive relationship between prenatal exposure to the Chinese famine and adult T2D are mainly driven by uncontrolled age differences between famine births and postfamine births. Studies with more rigorous methods, including age-balanced controls and robust famine intensity measures, are needed to quantify to what extent the famine exposure is related to current T2D patterns in China.

Indexed as

Diabetes Mellitus, Type 2Prenatal Exposure Delayed EffectsStarvationAdultChild, PreschoolChinaFamineFemaleHumansLanguagePregnancyage differenceconfounding adjustmentfaminefamine intensitymethodological problemsstudy settingtype 2 diabetes

Identifiers

PMID35889812
PMCPMC9317968
OpenAlexW4285093667

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.