Evidence map›Paper›PMID 29712719›Full record

ArticleJournal of epidemiology and community health2018

Dietary intake and age at natural menopause: results from the UK Women's Cohort Study.

Yashvee Dunneram, Darren Charles Greenwood, Victoria J Burley, Janet E Cade

Abstract read
In one paragraph

Article in Journal of epidemiology and community health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

23 citing papers in PubMed.

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  20. Toenail metal concentrations and age at menopause: A prospective study.Environmental epidemiology (Philadelphia, Pa.) · 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

4 authors.

Yashvee DunneramNutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, UK.ORCID 0000-0002-1012-7350
Darren Charles GreenwoodDivision of Epidemiology and Biostatistics, University of Leeds, Leeds, UK.
Victoria J BurleyNutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, UK.
Janet E CadeNutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, UK.

Funding

Medical Research Council MR/L02019X/1
6 · The paper itself

Abstract

backgroundAge at natural menopause is a matter of concern for women of reproductive age as both an early or late menopause may have implications for health outcomes.

methodsStudy participants were women aged 40-65 years who had experienced a natural menopause from the UK Women's Cohort Study between baseline and first follow-up. Natural menopause was defined as the permanent cessation of menstrual periods for at least 12 consecutive months. A food frequency questionnaire was used to estimate diet at baseline. Reproductive history of participants was also recorded. Regression modelling, adjusting for confounders, was used to assess associations between diet and age at natural menopause.

resultsDuring the 4-year follow-up period, 914 women experienced a natural menopause. A high intake of oily fish and fresh legumes were associated with delayed onset of natural menopause by 3.3 years per portion/day (99% CI 0.8 to 5.8) and 0.9 years per portion/day (99% CI 0.0 to 1.8), respectively. Refined pasta and rice was associated with earlier menopause (per portion/day: -1.5 years, 99% CI -2.8 to -0.2). A higher intake of vitamin B6 (per mg/day: 0.6 years, 99% CI 0.1 to 1.2) and zinc (per mg/day: 0.3 years, 99% CI -0.0 to 0.6) was also associated with later age at menopause. Stratification by age at baseline led to attenuated results.

conclusionOur results suggest that some food groups (oily fish, fresh legumes, refined pasta and rice) and specific nutrients are individually predictive of age at natural menopause.

Indexed as

Feeding BehaviorMenopauseAdultAgedCohort StudiesFemaleHealth SurveysHumansMiddle AgedUnited Kingdomdietfood groupsnatural menopausenutrientsUKWCS

Identifiers

PMID29712719
PMCPMC6204950

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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.