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Pre-pregnancy fast food and fruit intake is associated with time to pregnancy

Overview of attention for article published in Human Reproduction, May 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#3 of 6,023)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

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184 news outlets
blogs
9 blogs
twitter
121 tweeters
facebook
10 Facebook pages
googleplus
1 Google+ user

Citations

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24 Dimensions

Readers on

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138 Mendeley
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Title
Pre-pregnancy fast food and fruit intake is associated with time to pregnancy
Published in
Human Reproduction, May 2018
DOI 10.1093/humrep/dey079
Pubmed ID
Authors

Jessica A Grieger, Luke E Grzeskowiak, Tina Bianco-Miotto, Tanja Jankovic-Karasoulos, Lisa J Moran, Rebecca L Wilson, Shalem Y Leemaqz, Lucilla Poston, Lesley McCowan, Louise C Kenny, Jenny Myers, James J Walker, Robert J Norman, Gus A Dekker, Claire T Roberts

Abstract

Is preconception dietary intake associated with reduced fecundity as measured by a longer time to pregnancy (TTP)? Lower intake of fruit and higher intake of fast food in the preconception period were both associated with a longer TTP. Several lifestyle factors, such as smoking and obesity, have consistently been associated with a longer TTP or infertility, but the role of preconception diet in women remains poorly studied. Healthier foods or dietary patterns have been associated with improved fertility, however, these studies focused on women already diagnosed with or receiving treatments for infertility, rather than in the general population. This was a multi-center pregnancy-based cohort study of 5628 nulliparous women with low-risk singleton pregnancies who participated in the Screening for Pregnancy Endpoints (SCOPE) study. A total of 5598 women were included. Data on retrospectively reported TTP and preconception dietary intake were collected during the first antenatal study visit (14-16 weeks' gestation). Dietary information for the 1 month prior to conception was obtained from food frequency questions for fruit, green leafy vegetables, fish and fast foods, by a research midwife. Use of any fertility treatments associated with the current pregnancy was documented (yes, n = 340, no, n = 5258). Accelerated failure time models with log normal distribution were conducted to estimate time ratios (TR) and 95% CIs. The impact of differences in dietary intake on infertility (TTP >12 months) was compared using a generalized linear model (Poisson distribution) with robust variance estimates, with resulting relative risks (RR) and 95% CIs. All analyses were controlled for a range of maternal and paternal confounders. Sensitivity analyses were conducted to explore potential biases common to TTP studies. Lower intakes of fruit and higher intakes of fast food were both associated with modest increases in TTP and infertility. Absolute differences between the lowest and highest categories of intake for fruit and fast food were in the order of 0.6-0.9 months for TTP and 4-8% for infertility. Compared with women who consumed fruit ≥3 times/day, the adjusted effects of consuming fruit ≥1-<3 times/day (TR = 1.06, 95% CI: 0.97-1.15), 1-6 times/week (TR = 1.11, 95% CI: 1.01-1.22) or <1-3 times/month (TR = 1.19, 95% CI: 1.03-1.36), corresponded to 6, 11 and 19% increases in the median TTP (Ptrend = 0.007). Similarly, compared with women who consumed fast food ≥4 times/week, the adjusted effects of consuming fast food ≥2-<4 times/week (TR = 0.89, 95% CI: 0.81-0.98), >0-<2 times/week (TR 0.79, 95% CI 0.69-0.89) or no fast food (TR = 0.76, 95% CI: 0.61-0.95), corresponded to an 11, 21 and 24% reduction in the median TTP (Ptrend <0.001). For infertility, compared with women who consumed fruit ≥3 times/day, the adjusted effects of consuming fruit ≥1-<3 times/day, 1-6 times/week or <1-3 times/month corresponded to a 7, 18 and 29% increase in risk of infertility (Ptrend = 0.043). Similarly, compared with women who consumed fast food ≥4 times/week, the adjusted effects of consuming fast food ≥2-<4 times/week, >0-<2 times/week, or no fast food, corresponded to an 18, 34 and 41% reduced risk of infertility (Ptrend <0.001). Pre-pregnancy intake of green leafy vegetables or fish were not associated with TTP or infertility. Estimates remained stable across a range of sensitivity analyses. Collection of dietary data relied on retrospective recall and evaluated a limited range of foods. Paternal dietary data was not collected and the potential for residual confounding cannot be eliminated. Compared to prospective TTP studies, retrospective TTP studies are prone to a number of potential sources of bias. These findings underscore the importance of considering preconception diet for fecundity outcomes and preconception guidance. Further research is needed assessing a broader range of foods and food groups in the preconception period. The SCOPE database is provided and maintained by MedSciNet AB (http://medscinet.com). The Australian SCOPE study was funded by the Premier's Science and Research Fund, South Australian Government (http://www.dfeest.sa.gov.au/science-research/premiers-research-and-industry-fund). The New Zealand SCOPE study was funded by the New Enterprise Research Fund, Foundation for Research Science and Technology; Health Research Council (04/198); Evelyn Bond Fund, Auckland District Health Board Charitable Trust. The Irish SCOPE study was funded by the Health Research Board of Ireland (CSA/2007/2; http://www.hrb.ie). The UK SCOPE study was funded by National Health Service NEAT Grant (Neat Grant FSD025), Biotechnology and Biological Sciences Research council (www.bbsrc.ac.uk/funding; GT084) and University of Manchester Proof of Concept Funding (University of Manchester); Guy's and St. Thomas' Charity (King's College London) and Tommy's charity (http://www.tommys.org/; King's College London and University of Manchester); and Cerebra UK (www.cerebra.org.uk; University of Leeds). L.E.G. is supported by an Australian National Health and Medical Research Council (NHMRC) Early Career Fellowship (ID 1070421). L.J.M. is supported by a SACVRDP Fellowship; a program collaboratively funded by the National Heart Foundation, the South Australian Department of Health and the South Australian Health and Medical Research Institute. L.C.K. is supported by a Science Foundation Ireland Program Grant for INFANT (12/RC/2272). C.T.R. was supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship (GNT1020749). There are no conflicts of interest to declare. Not applicable.

Twitter Demographics

The data shown below were collected from the profiles of 121 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 138 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 17%
Student > Bachelor 20 14%
Student > Master 20 14%
Researcher 9 7%
Student > Doctoral Student 9 7%
Other 26 19%
Unknown 30 22%
Readers by discipline Count As %
Medicine and Dentistry 31 22%
Nursing and Health Professions 20 14%
Biochemistry, Genetics and Molecular Biology 9 7%
Psychology 8 6%
Social Sciences 7 5%
Other 24 17%
Unknown 39 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 1601. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 September 2021.
All research outputs
#3,990
of 18,912,409 outputs
Outputs from Human Reproduction
#3
of 6,023 outputs
Outputs of similar age
#94
of 289,530 outputs
Outputs of similar age from Human Reproduction
#2
of 61 outputs
Altmetric has tracked 18,912,409 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,023 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.0. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 289,530 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.