Next Article in Journal
Effect of Personal and Contextual Factors of Regulation on Academic Achievement during Adolescence: The Role of Gender and Age
Previous Article in Journal
Cesium in Biology, Pancreatic Cancer, and Controversy in High and Low Radiation Exposure Damage—Scientific, Environmental, Geopolitical, and Economic Aspects
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 18
Issue 17
10.3390/ijerph18178943
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Study Protocol

Parental Preconception Exposures to Outdoor Neighbourhood Environments and Adverse Birth Outcomes: A Protocol for a Scoping Review and Evidence Map

by
Suzanne Mavoa
1,2,3,*,
Daniel Keevers
4,
Stefan C. Kane
5,6,
Melissa Wake
2,7,8,
Rachel Tham
3,
Kate Lycett
2,7,9,
Yen Ting Wong
10 and
Katherine Chong
11
1
Melbourne School of Population & Global Health, University of Melbourne, Parkville, VIC 3010, Australia
2
Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia
3
Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia
4
Melbourne Medical School, University of Melbourne, Parkville, VIC 3010, Australia
5
Department of Obstetrics and Gynaecology, University of Melbourne, Parkville, VIC 3010, Australia
6
Department of Maternal Fetal Medicine, Royal Women’s Hospital, Parkville, VIC 3052, Australia
7
Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia
8
Liggins Institute, University of Auckland, Grafton, Auckland 1023, New Zealand
9
School of Psychology, Faculty of Health, Deakin University, Burwood, VIC 3125, Australia
10
IMPACT Institute, School of Medicine, Deakin University, Waurn Ponds, VIC 3216, Australia
11
Ingram School of Nursing, McGill University, Montreal, QC H3A 2M7, Canada
 
add Show full affiliation list
 
remove Hide full affiliation list
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(17), 8943; https://doi.org/10.3390/ijerph18178943
Submission received: 29 July 2021 / Revised: 22 August 2021 / Accepted: 23 August 2021 / Published: 25 August 2021
(This article belongs to the Section Reproductive Health)
Versions Notes

Abstract

:
Parental preconception exposures to built and natural outdoor environments could influence pregnancy and birth outcomes either directly, or via a range of health-related behaviours and conditions. However, there is no existing review summarising the evidence linking natural and built characteristics, such as air and noise pollution, walkability, greenness with pregnancy and birth outcomes. Therefore, the planned scoping review aims to collate and map the published literature on parental preconception exposures to built and natural outdoor environments and adverse pregnancy and birth outcomes. We will search electronic databases (MEDLINE, EMBASE, Scopus) to identify studies for inclusion. Studies will be included if they empirically assess the relationship between maternal and paternal preconception exposures to physical natural and built environment features that occur outdoors in the residential neighbourhood and adverse pregnancy and birth outcomes. Two reviewers will independently screen titles and abstracts, and then the full text. Data extraction and assessment of study quality will be performed by one researcher and checked by a second researcher. Results will be summarised in a narrative synthesis, with additional summaries presented as tables and figures. The scoping review will be disseminated via a peer-reviewed publication, at academic conferences, and published on a website.

1. Introduction

1.1. Rationale

Adverse pregnancy and birth outcomes are an ongoing health challenge globally. They also have lifelong consequences, with small and preterm infants having an increased risk of hypertension [1], type 2 diabetes [1], cardiovascular disease [1,2], asthma [3], and poorer mental health [4] in later life. Similarly, congenital anomalies cause infant mortality and contribute to preterm birth, but also childhood morbidity [5]. For mothers, transient non-communicable diseases experienced during pregnancy, such as gestational diabetes and preeclampsia, present an emergent risk for later-life maternal non-communicable diseases [6,7,8]. Additionally, poor perinatal maternal mental health, while being an adverse outcome for the mother, also influences later child outcomes [9,10].
Built and natural outdoor environments are important, yet underappreciated, avenues to intervene to improve pregnancy and birth outcomes at the population level. Considerable evidence shows that environmental characteristics near the home (i.e., pollutants, natural environments, built environments including access to a range of facilities and services) are associated with health-related outcomes in both children and adults [11,12,13,14]. There is also accumulating evidence highlighting the importance of exposure to different types of outdoor environments during pregnancy. For instance, air pollution [15,16,17], environmental noise [18,19] and green space [20,21,22] have all been linked to adverse pregnancy and/or birth outcomes. However, far less attention has been directed at the role that these same environments play prior to conception.
Preconception is a critical window of susceptibility [23,24,25]. Experimental animal studies and limited human studies show that conditions parents experience prior to conception can affect maternal and child health [25,26,27,28]. This is likely to occur through epigenetic mechanisms [29,30], which, given a single DNA sequence, result in different gene activity states [31]. Of interest here is the potential for epigenetic changes to occur as a result of environmental exposures, and through transgenerational inheritance [31]. While there is no agreed upon definition of preconception [32], previous research has considered preconception periods that range from months to years including prenatal or pubertal development [26,27,33]. While certain time windows are considered ‘critical’ or ‘sensitive’ it is important to note that preconception exposures may also have cumulative effects [26].
Outdoor built and natural environments therefore, could well play a role in preconception health. There is a small but growing body of evidence demonstrating that maternal preconception exposure to environmental toxins–including air pollutants that commonly occur in residential neighbourhoods (e.g., particulate matter, sulphur dioxide)-adversely affects pregnancy and birth outcomes [34,35]. There is even less evidence for fathers, despite animal studies demonstrating that paternal environmental exposures may affect offspring health via epigenetic modifications transmitted through sperm [36,37,38,39,40,41]. Few studies have explored non-occupational paternal exposures and offspring health in the general population [27,42], and it is unclear whether paternal preconception exposures are linked with adverse birth outcomes [24,42,43,44].
Beyond air pollutants, other aspects of the built and natural environment could also play an important role in preconception health. We know these outdoor environments are associated with health-related behaviours and conditions, such as physical activity, sedentary behaviour, diet, obesity, mental health, stress, smoking, and alcohol consumption. For instance, neighbourhoods with highly connected streets, high population density and a variety of destinations are associated with higher levels of physical activity and less sedentary behaviour [45] and obesity [45,46]. Tobacco and alcohol outlet density are associated with smoking and alcohol consumption behaviours [47,48], and there is mixed evidence that access to healthy/unhealthy food retail locations is linked to diet and obesity [49,50,51]. Greener neighbourhoods with more parks and vegetation are also linked to higher levels of physical activity [52,53] mental health and wellbeing [52,54], and lower levels of stress [52] and obesity [53]. There is also emerging evidence that other natural features of the environment, such as water and biodiversity may be linked to health [13,54,55,56,57]. Finally, there is some evidence that the psychosocial factors may also be linked to natural and built environments [58,59,60].
These same behaviours and conditions, which are in part determined by built and natural outdoor environments, also contribute to preconception health and to pregnancy and birth outcomes. For instance, the preconception diet for mothers predicts risk of gestational diabetes [61], preeclampsia [62] and preterm birth [63], with mixed evidence on the role of maternal diet on the child’s birth weight [63,64]. Psychosocial factors, such as personality traits, substance abuse, support, stressful life events are also known to be risk factors for maternal perinatal mental health [65]. Similarly, maternal preconception physical activity, mental health, obesity, smoking and alcohol consumption have all been linked to pregnancy and birth outcomes [28,61,66,67].
We know less about the impact of paternal preconception behaviours and health on birth outcomes [68]. Most evidence is based on animal models, and a few recent studies suggested that the paternal preconception environment, such as diet and early-life stress or trauma plays a role in foetal development and offspring health outcomes [69,70,71,72,73]. A handful of human studies have shown links between paternal alcohol consumption, smoking and mental health in the preconception period with birth outcomes [66,74,75], although in some cases the evidence is mixed [74]. Several studies have demonstrated that paternal health status is linked with preterm birth and low birth weight in the child, as well as gestational diabetes and preeclampsia in the mother [76,77]. However, there is likely substantial confounding factors since both parents often live at the same address and undertake activities together, resulting in similar environmental exposures. Thus, it is likely to be challenging to disentangle the impact of paternal and maternal preconceptional natural and built environment exposures, especially when considering shorter preconception periods.
In summary, parental preconception exposures to built and natural outdoor environments could influence pregnancy and birth outcomes either directly, or via a range of health-related behaviours and conditions. A clear understanding of these relationships would enable us to identify modifiable environmental and behavioural risk factors that could improve the lifelong health of mothers, fathers, and infants. Yet the existing evidence is sparse and scattered, with a necessary first step being a coherent and systematic appraisal of what evidence exists and key evidence gaps. This is a task that is best suited to a systematic scoping review [78], which aims to provide an overview of the available evidence rather than a systematic evidence review, which focuses on a specific question and usually aims to determine causality, efficacy/effectiveness and/or effect size. Therefore, we have planned a scoping review to collate and map the published literature on parental preconception exposures to built and natural outdoor environments and adverse pregnancy and birth outcomes.

1.2. Objectives

Since there are no existing scoping or systematic reviews on parental preconception exposures to outdoor natural and built environments, we will conduct a scoping review that aims to:
(1)
Identify and characterise the existing scientific evidence on relationships between maternal and paternal outdoor residential neighbourhood environments in the preconception period and adverse pregnancy and birth outcomes.
(2)
Identify evidence gaps and publish a narrative summary of the review and evidence map.
Previous versions of the protocol are registered in Zenodo. Version 1 was the initial protocol. We modified this prior to submission of this manuscript (Version 2). This manuscript represents the current version of the protocol. Any future modifications to this protocol will be similarly documented (including date and description of change), registered in Zenodo and reported in the final review paper.

2. Methods and Analysis

2.1. Information Sources and Search Strategy

We will identify relevant peer-reviewed published literature by searching the following databases: PubMed, Embase, CINAHL and Scopus. The search terms will cover three topics: (1) the outdoor neighbourhood environment, (2) the preconception period, and (3) adverse pregnancy and birth outcomes. The specific search strings for each database and the initial number of hits are provided in Table S1. The search will be restricted to literature published in the English language. The publication date will not be restricted.

2.2. Eligibility Criteria

Eligibility for inclusion is based on the Populations, Exposures, Comparators, and Outcomes PECO statement (Table 1). To be included in this systematic evidence map, studies must contain primary research investigating the relations between one or more of the specified outdoor environment exposures and one or more adverse birth outcomes.
Preconception exposures: Given the variation in definition of the preconception period [26,33], we will include all studies that explicitly state that they are investigating the preconception period regardless of how they define or measure this. We will also include studies that (a) explicitly assess environments during preconception (e.g., knowing the address at one month prior to conception, and sourcing pollution data for that month), and/or (b) make assumptions about location or environmental conditions during the preconception period (e.g., using the address at birth as a proxy for the preconception address and sourcing average pollution data for the year of birth).
Objectively assessed physical outdoor environment features: We will restrict exposures to the physical characteristics of the outdoor environment. These will include environmental pollutants most commonly associated with residential neighbourhoods (e.g., traffic related air pollution, woodfire smoke, noise), weather/climate, and built and natural environmental features. We will focus only on the residential neighbourhood. We will include multiple definitions of residential neighbourhoods (administrative units, radial buffers, road network buffers) at any scale.
Additional inclusion criteria are:
  • Objective and quantitative measurement of the environment.
  • Peer reviewed, full text publications in the English language (acknowledging that this may result in English language bias).

2.3. Data Management and Selection Process

Search results will be imported into Covidence where the screening/selection process will be managed [79]. Duplicate records will be automatically removed during the import. First, two screeners will independently assess each title and abstract for relevance, with included literature moving to the next stage. Next, two screeners will assess the full text to determine whether the manuscript meets the inclusion criteria. Disagreements will be resolved by consensus, and if necessary, a third screener.
The number of studies evaluated at each step will be recorded. Any modifications to the search or protocol will be included as amendments to the registered protocol.

2.4. Data Extraction and Coding Strategy

Data shown in Table 2 will be extracted into a standardised Microsoft Excel form. Data will be collected at either the study or exposure-outcome level depending on the variable. The form allows for collection of the variables listed in Table 2. Two researchers (RT, KC) have already independently piloted the form for three studies. Any amendments to the form will be recorded in the registered protocol.
Two researchers will independently extract the data from the included full text studies into the form. Inconsistencies will be discussed and if no agreement is reached, a third reviewer will decide.

2.5. Quality Assessment

During data extraction, study quality will be assessed for each included study using the relevant Joanna Briggs Institute critical appraisal checklist [80,81].

2.6. Synthesis and Visualisation of Results

As is appropriate for a scoping review, we will systematically map the existing evidence on parental preconception exposures to the natural and built environment, and we will visualise the evidence using charts, tables and maps. We will also provide a narrative summary of the results. Gaps and trends in the evidence will be discussed with reference to study quality. The synthesis will be grouped by exposures, outcomes, and study regions.

3. Conclusions

This will be the first synthesis of evidence on parental preconception exposures to the broad range of natural and built environment features that we are exposed to in the course of our everyday lives. The findings from this review will be an important step towards helping to identify modifiable environmental and behavioural risk factors that could improve pregnancy and birth outcomes, as well as the lifelong health of mothers, fathers and infants. It will aid researchers by identifying key evidence gaps and important targets for future research and be of interest to stakeholders involved in urban environmental planning and design. The results will also be of practical use to primary care practitioners, who may use the findings to enhance evidence-based preconception patient education. Furthermore, these results will be applicable to clinicians’ assessments of women during the preconception period, as they may be better equipped to conduct an evidence-informed patient assessment related to environmental determinants of health. The review will be submitted for publication in a peer-reviewed journal and result summaries (e.g., the evidence map) will be published online. The scoping review does not require ethics approval since it consists of collecting and review publicly available documents.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/ijerph18178943/s1, Table S1: Search strings and number of hits for each database (searches conducted on 22 August 2021).

Author Contributions

Conceptualization, S.M.; Methodology, S.M., D.K., S.C.K., M.W., R.T., K.L., Y.T.W. and K.C.; Writing—Original Draft Preparation, S.M. and D.K.; Writing—Review & Editing, S.M., D.K., S.C.K., M.W., R.T., K.L., Y.T.W. and K.C.; Supervision, S.M. All authors have read and agreed to the published version of the manuscript.

Funding

S.M., K.L. and M.W.: were supported by Australian National Health and Medical Research Council fellowships (#1121035, #1091124, #1160906). S.M. was additionally supported by a University of Melbourne Faculty of Medicine, Dentistry and Health Sciences Research Fellowship (grant number not applicable).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Knop, M.R.; Geng, T.; Gorny, A.W.; Ding, R.; Li, C.; Ley, S.H.; Huang, T. Birth Weight and Risk of Type 2 Diabetes Mellitus, Cardiovascular Disease, and Hypertension in Adults: A Meta-Analysis of 7 646 267 Participants from 135 Studies. J. Am. Heart Assoc. 2018, 7, e008870. [Google Scholar] [CrossRef] [Green Version]
  2. Markopoulou, P.; Papanikolaou, E.; Analytis, A.; Zoumakis, E.; Siahanidou, T. Preterm Birth as a Risk Factor for Metabolic Syndrome and Cardiovascular Disease in Adult Life: A Systematic Review and Meta-Analysis. J. Pediatr. 2019, 210, 69–80.e5. [Google Scholar] [CrossRef] [PubMed]
  3. Matheson, M.C.; D’Olhaberriague, A.L.-P.; Burgess, J.A.; Giles, G.G.; Hopper, J.L.; Johns, D.P.; Abramson, M.J.; Walters, E.H.; Dharmage, S.C. Preterm birth and low birth weight continue to increase the risk of asthma from age 7 to 43. J. Asthma 2017, 54, 616–623. [Google Scholar] [CrossRef] [PubMed]
  4. Mathewson, K.J.; Chow, C.H.T.; Dobson, K.G.; Pope, E.I.; Schmidt, L.A.; Van Lieshout, R.J. Mental health of extremely low birth weight survivors: A systematic review and meta-analysis. Psychol. Bull. 2017, 143, 347–383. [Google Scholar] [CrossRef]
  5. Stothard, K.J.; Tennant, P.W.G.; Bell, R.; Rankin, J. Maternal overweight and obesity and the risk of congenital anomalies: A systematic review and meta-analysis. JAMA 2009, 301, 636–650. [Google Scholar] [CrossRef]
  6. Mosca, L.; Benjamin, E.J.; Berra, K.; Bezanson, J.L.; Dolor, R.J.; Lloyd-Jones, D.M.; Newby, L.K.; Pina, I.L.; Roger, V.L.; Shaw, L.J.; et al. Effectiveness-based guidelines for the prevention of cardiovascular disease in women—2011 update: A guideline from the American Heart Association. J. Am. Coll. Cardiol. 2011, 57, 1404–1423. [Google Scholar] [CrossRef] [Green Version]
  7. Shah, B.R.; Retnakaran, R.; Booth, G.L. Increased Risk of Cardiovascular Disease in Young Women Following Gestational Diabetes Mellitus. Diabetes Care 2008, 31, 1668–1669. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Bohrer, J.; Ehrenthal, D.B. Other adverse pregnancy outcomes and future chronic disease. Semin. Perinatol. 2015, 39, 259–263. [Google Scholar] [CrossRef] [PubMed]
  9. Meaney, M.J. Perinatal Maternal Depressive Symptoms as an Issue for Population Health. Am. J. Psychiatry 2018, 175, 1084–1093. [Google Scholar] [CrossRef] [Green Version]
  10. Borschmann, R.; Molyneaux, E.; Spry, E.; Moran, P.; Howard, L.; Macdonald, J.; Brown, S.J.; Moreno-Betancur, M.; Olsson, C.A.; Patton, G.C. Pre-conception self-harm, maternal mental health and mother–infant bonding problems: A 20-year prospective cohort study. Psychol. Med. 2019, 49, 2727–2735. [Google Scholar] [CrossRef] [Green Version]
  11. Flies, E.J.; Mavoa, S.; Zosky, G.R.; Mantzioris, E.; Williams, C.; Eri, R.; Brook, B.W.; Buettel, J.C. Urban-associated diseases: Candidate diseases, environmental risk factors, and a path forward. Environ. Int. 2019, 133, 105187. [Google Scholar] [CrossRef] [PubMed]
  12. Tham, R.; Erbas, B.; Akram, M.; Dennekamp, M.; Abramson, M.J. The impact of smoke on respiratory hospital outcomes during the 2002–2003 bushfire season, Victoria, Australia. Respirology 2009, 14, 69–75. [Google Scholar] [CrossRef] [PubMed]
  13. Mavoa, S.; Lucassen, M.; Denny, S.; Utter, J.; Clark, T.; Smith, M. Natural neighbourhood environments and the emotional health of urban New Zealand adolescents. Landsc. Urban Plan. 2019, 191, 103638. [Google Scholar] [CrossRef]
  14. Pinter-Wollman, N.; Jelić, A.; Wells, N.M. The impact of the built environment on health behaviours and disease transmission in social systems. Philos. Trans. R. Soc. B Biol. Sci. 2018, 373, 20170245. [Google Scholar] [CrossRef]
  15. Bai, W.; Li, Y.; Niu, Y.; Ding, Y.; Yu, X.; Zhu, B.; Duan, R.; Duan, H.; Kou, C.; Li, Y.; et al. Association between ambient air pollution and pregnancy complications: A systematic review and meta-analysis of cohort studies. Environ. Res. 2020, 185, 109471. [Google Scholar] [CrossRef]
  16. Li, X.; Huang, S.; Jiao, A.; Yang, X.; Yun, J.; Wang, Y.; Xue, X.; Chu, Y.; Liu, F.; Liu, Y.; et al. Association between ambient fine particulate matter and preterm birth or term low birth weight: An updated systematic review and meta-analysis. Environ. Pollut. 2017, 227, 596–605. [Google Scholar] [CrossRef]
  17. Ravindra, K.; Chanana, N.; Mor, S. Exposure to air pollutants and risk of congenital anomalies: A systematic review and metaanalysis. Sci. Total Environ. 2020, 765, 142772. [Google Scholar] [CrossRef]
  18. Nieuwenhuijsen, M.J.; Ristovska, G.; Dadvand, P. WHO Environmental Noise Guidelines for the European Region: A Systematic Review on Environmental Noise and Adverse Birth Outcomes. Int. J. Environ. Res. Public Health 2017, 14, 1252. [Google Scholar] [CrossRef] [Green Version]
  19. Auger, N.; Duplaix, M.; Bilodeau-Bertrand, M.; Lo, E.; Smargiassi, A. Environmental noise pollution and risk of preeclampsia. Environ. Pollut. 2018, 239, 599–606. [Google Scholar] [CrossRef]
  20. Zhan, Y.; Liu, J.; Lu, Z.; Yue, H.; Zhang, J.; Jiang, Y. Influence of residential greenness on adverse pregnancy outcomes: A systematic review and dose-response meta-analysis. Sci. Total Environ. 2020, 718, 137420. [Google Scholar] [CrossRef]
  21. Twohig-Bennett, C.; Jones, A. The health benefits of the great outdoors: A systematic review and meta-analysis of greenspace exposure and health outcomes. Environ. Res. 2018, 166, 628–637. [Google Scholar] [CrossRef]
  22. Banay, R.F.; Bezold, C.P.; James, P.; E Hart, J.; Laden, F. Residential greenness: Current perspectives on its impact on maternal health and pregnancy outcomes. Int. J. Women Health 2017, 9, 133–144. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Marcho, C.; Oluwayiose, O.A.; Pilsner, J.R. The preconception environment and sperm epigenetics. Andrology 2020, 8, 924–942. [Google Scholar] [CrossRef]
  24. Mustieles, V.; Zhang, Y.; Yland, J.; Braun, J.M.; Williams, P.L.; Wylie, B.J.; Attaman, J.A.; Ford, J.B.; Azevedo, A.; Calafat, A.M.; et al. Maternal and paternal preconception exposure to phenols and preterm birth. Environ. Int. 2020, 137, 105523. [Google Scholar] [CrossRef] [PubMed]
  25. Messerlian, C.; Williams, P.L.; Ford, J.B.; Chavarro, J.; Mínguez-Alarcón, L.; Dadd, R.; Braun, J.M.; Gaskins, A.J.; Meeker, J.D.; James-Todd, T.; et al. The Environment and Reproductive Health (EARTH) Study: A prospective preconception cohort. Hum. Reprod. Open 2018, 2018, hoy001. [Google Scholar] [CrossRef] [PubMed]
  26. Stephenson, J.; Heslehurst, N.; Hall, J.; Schoenaker, D.A.J.M.; Hutchinson, J.; Cade, J.E.; Poston, L.; Barrett, G.; Crozier, S.R.; Barker, M.; et al. Before the beginning: Nutrition and lifestyle in the preconception period and its importance for future health. Lancet 2018, 391, 1830–1841. [Google Scholar] [CrossRef]
  27. Braun, J.M.; Messerlian, C.; Hauser, R. Fathers Matter: Why It’s Time to Consider the Impact of Paternal Environmental Exposures on Children’s Health. Curr. Epidemiol. Rep. 2017, 4, 46–55. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Segal, T.R.; Giudice, L.C. Before the beginning: Environmental exposures and reproductive and obstetrical outcomes. Fertil. Steril. 2019, 112, 613–621. [Google Scholar] [CrossRef] [PubMed]
  29. Noble, D.; Jablonka, E.; Joyner, M.J.; Müller, G.B.; Omholt, S.W. Evolution evolves: Physiology returns to centre stage. J. Physiol. 2014, 592, 2237–2244. [Google Scholar] [CrossRef]
  30. Toivonen, K.I.; Oinonen, K.A.; Duchene, K.M. Preconception health behaviours: A scoping review. Prev. Med. 2017, 96, 1–15. [Google Scholar] [CrossRef] [PubMed]
  31. Cavalli, G.; Heard, E. Advances in epigenetics link genetics to the environment and disease. Nature 2019, 571, 489–499. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Hill, B.; Hall, J.; Skouteris, H.; Currie, S. Defining preconception: Exploring the concept of a preconception population. BMC Pregnancy Childbirth 2020, 20, 1–11. [Google Scholar] [CrossRef] [PubMed]
  33. Jacob, C.M.; Newell, M.; Hanson, M. Narrative review of reviews of preconception interventions to prevent an increased risk of obesity and non-communicable diseases in children. Obes. Rev. 2019, 20, 5–17. [Google Scholar] [CrossRef]
  34. Robledo, C.A.; Mendola, P.; Yeung, E.; Männistö, T.; Sundaram, R.; Liu, D.; Ying, Q.; Sherman, S.; Grantz, K. Preconception and early pregnancy air pollution exposures and risk of gestational diabetes mellitus. Environ. Res. 2015, 137, 316–322. [Google Scholar] [CrossRef]
  35. Zhang, M.; Wang, X.; Yang, X.; Dong, T.; Hu, W.; Guan, Q.; Tun, H.M.; Chen, Y.; Chen, R.; Sun, Z.; et al. Increased risk of gestational diabetes mellitus in women with higher prepregnancy ambient PM2.5 exposure. Sci. Total Environ. 2020, 730, 138982. [Google Scholar] [CrossRef]
  36. Daxinger, L.; Whitelaw, E. Understanding transgenerational epigenetic inheritance via the gametes in mammals. Nat. Rev. Genet. 2012, 13, 153–162. [Google Scholar] [CrossRef]
  37. Fernandez-Twinn, D.S.; Constância, M.; Ozanne, S.E. Intergenerational Epigenetic Inheritance in Models of Developmental Programming of Adult Disease. In Seminars in Cell & Developmental Biology; Elsevier: Amsterdam, The Netherlands, 2015. [Google Scholar]
  38. Krawetz, S.A. Paternal contribution: New insights and future challenges. Nat. Rev. Genet. 2005, 6, 633–642. [Google Scholar] [CrossRef]
  39. Puri, D.; Dhawan, J.; Mishra, R.K. The paternal hidden agenda: Epigenetic inheritance through sperm chromatin. Epigenetics 2010, 5, 386–391. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Rando, O.J. Daddy Issues: Paternal Effects on Phenotype. Cell 2012, 151, 702–708. [Google Scholar] [CrossRef] [Green Version]
  41. Szyf, M. Nongenetic inheritance and transgenerational epigenetics. Trends Mol. Med. 2015, 21, 134–144. [Google Scholar] [CrossRef] [PubMed]
  42. Zhang, Y.; Mustieles, V.; Yland, J.; Braun, J.M.; Williams, P.L.; Attaman, J.A.; Ford, J.B.; Calafat, A.M.; Hauser, R.; Messerlian, C. Association of Parental Preconception Exposure to Phthalates and Phthalate Substitutes With Preterm Birth. JAMA Netw. Open 2020, 3, e202159. [Google Scholar] [CrossRef]
  43. Mustieles, V.; Williams, P.L.; Fernandez, M.F.; Mínguez-Alarcón, L.; Ford, J.B.; Calafat, A.M.; Hauser, R.; Messerlian, C. Environment and Reproductive Health (EARTH) Study Team Maternal and paternal preconception exposure to bisphenols and size at birth. Hum. Reprod. 2018, 33, 1528–1537. [Google Scholar] [CrossRef] [Green Version]
  44. Smarr, M.M.; Grantz, K.L.; Sundaram, R.; Maisog, J.M.; Kannan, K.; Louis, G.M.B. Parental urinary biomarkers of preconception exposure to bisphenol A and phthalates in relation to birth outcomes. Environ. Health 2015, 14, 1–11. [Google Scholar] [CrossRef] [Green Version]
  45. Sallis, J.F.; Cerin, E.; De Bourdeaudhuij, I.; Owen, N.; Kerr, J.; Adams, M.A.; Sugiyama, T.; Christiansen, L.B.; Schipperijn, J.; Davey, R.; et al. Built Environment, Physical Activity, and Obesity: Findings from the International Physical Activity and Environment Network (IPEN) Adult Study. Annu. Rev. Public Health 2020, 41, 119–139. [Google Scholar] [CrossRef] [Green Version]
  46. Oliver, M.; Witten, K.; Sweetsur, P.; Kearns, R.; Blakely, T.; Parker, K.; Badland, H.; Schofield, G.; Ivory, V.; Pearce, J.; et al. Neighbourhood built environment associations with body size in adults: Mediating effects of activity and sedentariness in a cross-sectional study of New Zealand adults. BMC Public Health 2015, 15, 1–11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Finan, L.; Lipperman-Kreda, S.; Abadi, M.; Grube, J.; Kaner, E.; Balassone, A.; Gaidus, A. Tobacco outlet density and adolescents’ cigarette smoking: A meta-analysis. Tob. Control 2018, 28, 27–33. [Google Scholar] [CrossRef]
  48. Popova, S.; Giesbrecht, N.; Bekmuradov, D.; Patra, J. Hours and Days of Sale and Density of Alcohol Outlets: Impacts on Alcohol Consumption and Damage: A Systematic Review. Alcohol Alcohol. 2009, 44, 500–516. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Stevenson, A.C.; Brazeau, A.-S.; Dasgupta, K.; Ross, N.A. Evidence synthesis-Neighbourhood retail food outlet access, diet and body mass index in Canada: A systematic review. Health Promot. Chronic Dis. Prev. Can. 2019, 39, 261–280. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Pitt, E.; Gallegos, D.; Comans, T.; Cameron, C.; Thornton, L. Exploring the influence of local food environments on food behaviours: A systematic review of qualitative literature. Public Health Nutr. 2017, 20, 2393–2405. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  51. Caspi, C.E.; Sorensen, G.; Subramanian, S.; Kawachi, I. The local food environment and diet: A systematic review. Health Place 2012, 18, 1172–1187. [Google Scholar] [CrossRef] [Green Version]
  52. Fong, K.C.; Hart, J.E.; James, P. A Review of Epidemiologic Studies on Greenness and Health: Updated Literature through 2017. Curr. Environ. Health Rep. 2018, 5, 77–87. [Google Scholar] [CrossRef] [Green Version]
  53. Villeneuve, P.J.; Jerrett, M.; Su, J.G.; Weichenthal, S.; Sandler, D.P. Association of residential greenness with obesity and physical activity in a US cohort of women. Environ. Res. 2018, 160, 372–384. [Google Scholar] [CrossRef]
  54. Mavoa, S.; Davern, M.; Breed, M.; Hahs, A. Higher levels of greenness and biodiversity associate with greater subjective wellbeing in adults living in Melbourne, Australia. Health Place 2019, 57, 321–329. [Google Scholar] [CrossRef]
  55. Lai, H.; Flies, E.J.; Weinstein, P.; Woodward, A. The impact of green space and biodiversity on health. Front. Ecol. Environ. 2019, 17, 383–390. [Google Scholar] [CrossRef]
  56. White, M.P.; Elliott, L.R.; Gascon, M.; Roberts, B.; Fleming, L.E. Blue space, health and well-being: A narrative overview and synthesis of potential benefits. Environ. Res. 2020, 191, 110169. [Google Scholar] [CrossRef]
  57. Aerts, R.; Honnay, O.; Van Nieuwenhuyse, A. Biodiversity and human health: Mechanisms and evidence of the positive health effects of diversity in nature and green spaces. Br. Med. Bull. 2018, 127, 5–22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Berry, M.S.; Rung, J.M.; Crawford, M.C.; Yurasek, A.M.; Ferreiro, A.V.; Almog, S. Using greenspace and nature exposure as an adjunctive treatment for opioid and substance use disorders: Preliminary evidence and potential mechanisms. Behav. Process. 2021, 186, 104344. [Google Scholar] [CrossRef] [PubMed]
  59. Cabrera, J.F.; Najarian, J.C. How the Built Environment Shapes Spatial Bridging Ties and Social Capital. Environ. Behav. 2015, 47, 239–267. [Google Scholar] [CrossRef]
  60. Van den Berg, A.E.; Maas, J.; Verheij, R.A.; Groenewegen, P.P. Green space as a buffer between stressful life events and health. Soc. Sci. Med. 2010, 70, 1203–1210. [Google Scholar] [CrossRef] [Green Version]
  61. Schoenaker, D.A.; Vergouwe, Y.; Soedamah-Muthu, S.S.; Callaway, L.K.; Mishra, G.D. Preconception risk of gestational diabetes: Development of a prediction model in nulliparous Australian women. Diabetes Res. Clin. Pract. 2018, 146, 48–57. [Google Scholar] [CrossRef] [PubMed]
  62. Grieger, J.A. Preconception diet, fertility, and later health in pregnancy. Curr. Opin. Obstet. Gynecol. 2020, 32, 227–232. [Google Scholar] [CrossRef]
  63. Gete, D.G.; Waller, M.; Mishra, G.D. Prepregnancy dietary patterns and risk of preterm birth and low birth weight: Findings from the Australian Longitudinal Study on Women’s Health. Am. J. Clin. Nutr. 2020, 111, 1048–1058. [Google Scholar] [CrossRef]
  64. Salavati, N.; Bakker, M.K.; Lewis, F.; Vinke, P.C.; Mubarik, F.; Erwich, J.H.M.; Van Der Beek, E.M. Associations between preconception macronutrient intake and birth weight across strata of maternal BMI. PLoS ONE 2020, 15, e0243200. [Google Scholar] [CrossRef]
  65. Reilly, N.; Loxton, D.; Black, E.; Austin, M.-P. The Antenatal Risk Questionnaire-Revised: Development, use and test-retest reliability in a community sample of pregnant women in Australia. J. Affect. Disord. 2021, 293, 43–50. [Google Scholar] [CrossRef]
  66. Philips, E.M.; Santos, S.; Trasande, L.; Aurrekoetxea, J.J.; Barros, H.; Von Berg, A.; Bergström, A.; Bird, P.K.; Brescianini, S.; Chaoimh, C.N.; et al. Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: An individual participant data meta-analysis of 229,000 singleton births. PLoS Med. 2020, 17, e1003182. [Google Scholar] [CrossRef] [PubMed]
  67. Witt, W.P.; Wisk, L.E.; Cheng, E.R.; Hampton, J.M.; Hagen, E.W. Preconception Mental Health Predicts Pregnancy Complications and Adverse Birth Outcomes: A National Population-Based Study. Matern. Child Health J. 2012, 16, 1525–1541. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Kothari, A.; Thayalan, K.; Dulhunty, J.; Callaway, L. The forgotten father in obstetric medicine. Obstet. Med. 2019, 12, 57–65. [Google Scholar] [CrossRef]
  69. Hannan, A.J. Paternal bloodlines sculpting seminal concepts: Circulating factors as mediators of transgenerational ‘epigenopathy’ and ‘epigenetic resilience’. EMBO J. 2020, 39, e107014. [Google Scholar] [CrossRef] [PubMed]
  70. Day, J.; Savani, S.; Krempley, B.D.; Nguyen, M.; Kitlinska, J.B. Influence of paternal preconception exposures on their offspring: Through epigenetics to phenotype. Am. J. Stem Cells 2016, 5, 11–18. [Google Scholar] [PubMed]
  71. McPherson, N.O.; Owens, J.; Fullston, T.; Lane, M. Preconception diet or exercise intervention in obese fathers normalizes sperm microRNA profile and metabolic syndrome in female offspring. Am. J. Physiol. Metab. 2015, 308, E805–E821. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Messerlian, C.; Bellinger, D.; Mínguez-Alarcón, L.; Romano, M.; Ford, J.B.; Williams, P.L.; Calafat, A.M.; Hauser, R.; Braun, J.M. Paternal and maternal preconception urinary phthalate metabolite concentrations and child behavior. Environ. Res. 2017, 158, 720–728. [Google Scholar] [CrossRef]
  73. Donkin, I.; Barrès, R. Sperm epigenetics and influence of environmental factors. Mol. Metab. 2018, 14, 1–11. [Google Scholar] [CrossRef]
  74. McBride, N.; Johnson, S. Fathers’ Role in Alcohol-Exposed Pregnancies: Systematic Review of Human Studies. Am. J. Prev. Med. 2016, 51, 240–248. [Google Scholar] [CrossRef] [PubMed]
  75. A Spry, E.; A Wilson, C.; Middleton, M.; Moreno-Betancur, M.; Doyle, L.W.; Howard, L.M.; Hannan, A.J.; E Wlodek, M.; Cheong, J.L.; A Hines, L.; et al. Parental mental health before and during pregnancy and offspring birth outcomes: A 20-year preconception cohort of maternal and paternal exposure. EClinicalMedicine 2020, 27, 100564. [Google Scholar] [CrossRef] [PubMed]
  76. Kasman, A.M.; Zhang, C.A.; Li, S.; Stevenson, D.K.; Shaw, G.M.; Eisenberg, M.L. Association of preconception paternal health on perinatal outcomes: Analysis of U.S. claims data. Fertil. Steril. 2020, 113, 947–954. [Google Scholar] [CrossRef]
  77. Moss, J.L.; Harris, K.M. Impact of maternal and paternal preconception health on birth outcomes using prospective couples’ data in Add Health. Arch. Gynecol. Obstet. 2014, 291, 287–298. [Google Scholar] [CrossRef] [Green Version]
  78. Peters, M.D.J.; Godfrey, C.M.; Khalil, H.; McInerney, P.; Parker, D.; Soares, C.B. Guidance for conducting systematic scoping reviews. Int. J. Evid. Based Health 2015, 13, 141–146. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  79. Veritas Health Innovation. Covidence Systematic Review Software; Veritas Health Innovation: Melbourne, Australia, 2021.
  80. Ma, L.-L.; Wang, X.; Yang, Z.-H.; Huang, D.; Weng, H.; Zeng, X.-T. Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: What are they and which is better? Mil. Med. Res. 2020, 7, 1–11. [Google Scholar] [CrossRef] [Green Version]
  81. Moola, S.; Munn, Z.; Tufanaru, C.; Aromataris, E.; Sears, K.; Sfetcu, R.; Currie, M.; Lisy, K.; Qureshi, R.; Mattis, P.; et al. Chapter 7: Systematic reviews of etiology and risk. In JBI Manual for Evidence Synthesis; Aromataris, E., Munn, Z., Eds.; JBI: Adelaide, Australia, 2020. [Google Scholar] [CrossRef]
Table
Table 1. Populations, Exposures, Comparators, and Outcomes (PECO) Statement.
Table 1. Populations, Exposures, Comparators, and Outcomes (PECO) Statement.
PopulationPregnant and/or Postpartum Human Women of any Reproductive Age and Neonates.
ExposuresAt least one feature of the physical outdoor residential neighbourhood environment that has been objectively assessed for the preconceptual period for one or both parents. Environmental features include pollutants (e.g., sulphur dioxide, nitrogen oxides, particulate matter), weather (e.g., temperature, humidity), built environment (e.g., dwelling density, walkability), and the natural environment (e.g., vegetation, coastline). The exposures may be individual exposures or aggregate indices. The preconceptual period includes the period prior to conception and during pregnancy (all-trimesters).
Comparators(1) Mothers and (2) Fathers exposed to higher versus lower levels of the exposures.
OutcomesAt least one adverse pregnancy or birth outcome including:
Maternal (during all trimesters of pregnancy and at/immediately following birth): gestational diabetes mellitus, gestational hyperglycaemia, pre-eclampsia, eclampsia, gestational hypertension, pregnancy complications, mental health, Neonate (assessed at/immediately following birth): low or large birth weight, gestational age, preterm birth, premature rupture of membranes, congenital anomalies, birth complications, stillbirths.
Table
Table 2. Data extraction and coding variables. Import (I) indicates variable data will be imported from Covidence. Export (E) indicates the researcher will extract the data from the paper. Derive (D) indicates that the researcher will calculate the variable based on extracted data.
Table 2. Data extraction and coding variables. Import (I) indicates variable data will be imported from Covidence. Export (E) indicates the researcher will extract the data from the paper. Derive (D) indicates that the researcher will calculate the variable based on extracted data.
VariableImport/Extract/DeriveCategories
Bibliographic information
-
authors
Ifree text
-
publication year
Ifree text
-
title
Ifree text
-
journal
Ifree text
-
citation
Ifree text
Study information
-
study type
Eobservational, natural experiment, intervention
-
year/s conducted
Efree text
-
number of mothers
Efree text (integer)
-
number of fathers
Efree text (integer)
Study location
-
city/area/region
Efree text
-
country
Efree text
-
region
DAfrica, North America, Central/South America, Central Asia, East Asia, South East Asia, West Asia, Europe, Australasia, Other Oceania
-
country income group
DWorld Bank income group at first year of study: low, lower-middle, upper-middle, high
-
urban/rural
E/Durban, rural, both, unknown
Exposure information
-
paternal/maternal
Ematernal, paternal
-
preconception definition
Efree text
-
location used to represent residence
Emother’s home, birth hospital, other
-
residential location resolution
Eaddress, street, area unit, other
-
timing of location details
Epreconception, pregnancy, birth, other
-
neighbourhood definition
Eadministrative unit, radial buffer, network buffer, other
-
neighbourhood scale
Efree text (either a distance or the name of the administrative unit)
-
outdoor environment feature
Efree text
-
outdoor environment feature data source
Efree text
-
time period of data source
Efree text
-
exposure measurement
Efree text
Outcome information
-
timing of outcome assessment
Efree text
-
preeclampsia
Eyes/no
-
gestational diabetes
Eyes/no
-
preterm birth
Eyes/no
-
low birth weight
Eyes/no
-
other outcome
Efree text
-
preeclampsia measurement method
Efree text
-
gestational diabetes measurement method
Efree text
-
preterm birth measurement method
Efree text
-
low birth weight measurement method
Efree text
-
other outcome measurement method
Efree text
Covariate information
-
covariates/confounders
Efree text
Results
-
summary of results
Efree text
Critical appraisal checklist
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Mavoa, S.; Keevers, D.; Kane, S.C.; Wake, M.; Tham, R.; Lycett, K.; Wong, Y.T.; Chong, K. Parental Preconception Exposures to Outdoor Neighbourhood Environments and Adverse Birth Outcomes: A Protocol for a Scoping Review and Evidence Map. Int. J. Environ. Res. Public Health 2021, 18, 8943. https://doi.org/10.3390/ijerph18178943

AMA Style

Mavoa S, Keevers D, Kane SC, Wake M, Tham R, Lycett K, Wong YT, Chong K. Parental Preconception Exposures to Outdoor Neighbourhood Environments and Adverse Birth Outcomes: A Protocol for a Scoping Review and Evidence Map. International Journal of Environmental Research and Public Health. 2021; 18(17):8943. https://doi.org/10.3390/ijerph18178943

Chicago/Turabian Style

Mavoa, Suzanne, Daniel Keevers, Stefan C. Kane, Melissa Wake, Rachel Tham, Kate Lycett, Yen Ting Wong, and Katherine Chong. 2021. "Parental Preconception Exposures to Outdoor Neighbourhood Environments and Adverse Birth Outcomes: A Protocol for a Scoping Review and Evidence Map" International Journal of Environmental Research and Public Health 18, no. 17: 8943. https://doi.org/10.3390/ijerph18178943

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop