Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
9
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Paternal preconception modifiable risk factors for adverse pregnancy and offspring outcomes: a review of contemporary evidence from observational studies

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The preconception period represents transgenerational opportunities to optimize modifiable risk factors associated with both short and long-term adverse health outcomes for women, men, and children. As such, preconception care is recommended to couples during this time to enable them to optimise their health in preparation for pregnancy. Historically, preconception research predominately focuses on maternal modifiable risks and health behaviours associated with pregnancy and offspring outcomes; limited attention has been given to inform paternal preconception health risks and outcomes. This systematic review aims to advance paternal preconception research by synthesising the current evidence on modifiable paternal preconception health behaviours and risk factors to identify associations with pregnancy and/or offspring outcomes.

          Methods

          Medline, Embase, Maternity and Infant care, CINAHL, PsycINFO, Scopus, and ISI Proceedings were searched on the 5 th of January 2023, a date limit was set [2012–2023] in each database. A Google Scholar search was also conducted identifying all other relevant papers. Studies were included if they were observational, reporting associations of modifiable risk factors in the preconception period among males (e.g., identified as reproductive partners of pregnant women and/or fathers of offspring for which outcomes were reported) with adverse pregnancy and offspring outcomes. Study quality was assessed using the Newcastle–Ottawa Scale. Exposure and outcome heterogeneity precluded meta-analysis, and results were summarised in tables.

          Results

          This review identified 56 cohort and nine case control studies. Studies reported on a range of risk factors and/or health behaviours including paternal body composition ( n = 25), alcohol intake ( n = 6), cannabis use ( n = 5), physical activity ( n = 2), smoking ( n = 20), stress ( n = 3) and nutrition ( n = 13). Outcomes included fecundability, IVF/ISCI live birth, offspring weight, body composition/BMI, asthma, lung function, leukemia, preterm birth, and behavioural issues. Despite the limited number of studies and substantial heterogeneity in reporting, results of studies assessed as good quality showed that paternal smoking may increase the risk of birth defects and higher paternal BMI was associated with higher offspring birthweight.

          Conclusion

          The current evidence demonstrates a role of paternal preconception health in influencing outcomes related to pregnancy success and offspring health. The evidence is however limited and heterogenous, and further high-quality research is needed to inform clinical preconception care guidelines to support men and couples to prepare for a health pregnancy and child.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12889-023-15335-1.

          Related collections

          Most cited references96

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both

          The number of published systematic reviews of studies of healthcare interventions has increased rapidly and these are used extensively for clinical and policy decisions. Systematic reviews are subject to a range of biases and increasingly include non-randomised studies of interventions. It is important that users can distinguish high quality reviews. Many instruments have been designed to evaluate different aspects of reviews, but there are few comprehensive critical appraisal instruments. AMSTAR was developed to evaluate systematic reviews of randomised trials. In this paper, we report on the updating of AMSTAR and its adaptation to enable more detailed assessment of systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. With moves to base more decisions on real world observational evidence we believe that AMSTAR 2 will assist decision makers in the identification of high quality systematic reviews, including those based on non-randomised studies of healthcare interventions.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The PRISMA 2020 statement: An updated guideline for reporting systematic reviews

            Matthew Page and co-authors describe PRISMA 2020, an updated reporting guideline for systematic reviews and meta-analyses.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Information bias in health research: definition, pitfalls, and adjustment methods

              As with other fields, medical sciences are subject to different sources of bias. While understanding sources of bias is a key element for drawing valid conclusions, bias in health research continues to be a very sensitive issue that can affect the focus and outcome of investigations. Information bias, otherwise known as misclassification, is one of the most common sources of bias that affects the validity of health research. It originates from the approach that is utilized to obtain or confirm study measurements. This paper seeks to raise awareness of information bias in observational and experimental research study designs as well as to enrich discussions concerning bias problems. Specifying the types of bias can be essential to limit its effects and, the use of adjustment methods might serve to improve clinical evaluation and health care practice.
                Bookmark

                Author and article information

                Contributors
                Tristan.c.carter@student.uts.edu.au
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                16 March 2023
                16 March 2023
                2023
                : 23
                : 509
                Affiliations
                [1 ]GRID grid.117476.2, ISNI 0000 0004 1936 7611, School of Public Health, Faculty of Health, , University of Technology Sydney, ; Sydney, 2006 Australia
                [2 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, School of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, , University of Southampton, ; Southampton, UK
                [3 ]GRID grid.430506.4, ISNI 0000 0004 0465 4079, NIHR Southampton Biomedical Research Centre, , University of Southampton and University Hospital Southampton NHS Foundation Trust, ; Southampton, UK
                Article
                15335
                10.1186/s12889-023-15335-1
                10022288
                36927694
                70cec160-d467-4e20-8ed0-f63fe676ebbd
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 2 November 2022
                : 28 February 2023
                Categories
                Research
                Custom metadata
                © The Author(s) 2023

                Public health
                paternal,preconception,modifiable,risk factor,pregnancy outcomes,offspring outcomes
                Public health
                paternal, preconception, modifiable, risk factor, pregnancy outcomes, offspring outcomes

                Comments

                Comment on this article