Evidence map›Paper›PMID 36749588›Full record

ArticleJAMA network open2023

Modifiable Risk Factor Score and Fecundability in a Preconception Cohort in Singapore.

See Ling Loy, Chee Wai Ku, Michelle Mei Ying Tiong, Carissa Shi Tong Ng, Yin Bun Cheung, Keith M Godfrey, Shan Xuan Lim, Marjorelee T Colega, Jun Shi Lai, Yap-Seng Chong and 6 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.5field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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  4. Observational
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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

16 authors at 7 institutions in 3 countries.

See Ling LoyDepartment of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore.
Chee Wai KuDepartment of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore.
Michelle Mei Ying TiongKK Women's and Children's Hospital, Singapore, Singapore.
Carissa Shi Tong NgYong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore.
Yin Bun CheungProgram in Health Services and Systems Research and Center for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
Keith M GodfreyMedical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom.
Shan Xuan LimSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, Singapore.
Marjorelee T ColegaSingapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore.
Jun Shi LaiSingapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore.
Yap-Seng ChongYong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore.
Lynette Pei-Chi ShekSingapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore.
Kok Hian TanDuke-NUS Medical School, Singapore, Singapore.
Shiao-Yng ChanSingapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore.
Mary Foong-Fong ChongSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, Singapore.
Fabian YapDuke-NUS Medical School, Singapore, Singapore.
Jerry Kok Yen ChanDepartment of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore.
Duke-NUS Medical School · SGKK Women's and Children's Hospital · SGNational University of Singapore · SGSingapore Institute for Clinical Sciences · SGAgency for Science, Technology and Research · SGMRC Lifecourse Epidemiology Unit · GBNational University Health System · SG

Funding

British Heart Foundation RG/15/17/3174British Heart Foundation SP/F/21/150013Department of Health IS-BRC-1215-20004Department of Health NF-SI-0515-10042Medical Research Council MC_UU_12011/4
6 · The paper itself

Abstract

Importance: Although multiple modifiable risk factors have been identified for reduced fecundability (defined as lower probability of conception within a menstrual cycle), no scoring system has been established to systematically evaluate fecundability among females who are attempting to conceive. Objective: To examine the association of a risk score based on 6 modifiable factors with fecundability, and to estimate the percentage reduction in incidence of nonconception if all study participants achieved a minimal risk score level. Design, Setting, and Participants: This population-based cohort study obtained data from the S-PRESTO (Singapore Preconception Study of Long-Term Maternal and Child Outcomes) prospective cohort study. Females of reproductive age who were trying to conceive were enrolled from February 2015 to October 2017 and followed for 1 year, ending in November 2018. Data were analyzed from March to May 2022. Exposures: A reduced fecundability risk score was derived by giving participants 1 point for each of the following factors: unhealthy body mass index, unhealthy diet, smoking, alcohol intake, folic acid supplement nonuser, and older maternal age. Total scores ranged from 0 to 6 and were classified into 5 levels: level 1 (score of 0 or 1), level 2 (score of 2), level 3 (score of 3), level 4 (score of 4), and level 5 (score of 5 or 6). Main Outcomes and Measures: Fecundability, measured by time to conception in cycles, was analyzed using discrete-time proportional hazards models with confounder adjustment. Results: A total of 937 females (mean [SD] age, 30.8 [3.8] years) were included, among whom 401 (42.8%) spontaneously conceived within 1 year of attempting conception; the median (IQR) number of cycles before conception was 4 (2-7). Compared with participants with a level 1 risk score, those with level 2, 3, 4, and 5 risk scores had reductions in fecundability of 31% (adjusted fecundability ratio [FR], 0.69; 95% CI, 0.54-0.88), 41% (FR, 0.59; 95% CI, 0.45-0.78), 54% (FR, 0.46; 95% CI, 0.31-0.69) and 77% (FR, 0.23; 95% CI, 0.07-0.73), respectively. Assessment of the population attributable fraction showed that all participants achieving a minimal (level 1) risk level would be associated with a reduction of 34% (95% CI, 30%-39%) in nonconception within a year. Conclusions and Relevance: Results of this study revealed the co-occurrence of multiple modifiable risk factors for lowered fecundability and a substantially higher conception rate among participants with no or minimal risk factors. The risk assessment scoring system proposed is a simple and potentially useful public health tool for mitigating risks and guiding those who are trying to conceive.

Indexed as

FertilityAdultChildCohort StudiesFemaleHumansProspective StudiesRisk FactorsSingapore

Identifiers

PMID36749588
PMCPMC10408273
OpenAlexW4319333580

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.