Paternal preconception modifiable risk factors for adverse pregnancy and offspring outcomes: a review of contemporary evidence from observational studies
BMC Public Health volume 23, Article number: 509 (2023)
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.
Medline, Embase, Maternity and Infant care, CINAHL, PsycINFO, Scopus, and ISI Proceedings were searched on the 5th 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.
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.
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.
Plain English Summary
The time prior to conception, preconception, is widely acknowledged as an integral period whereby a woman’s health, lifestyle, and diet influence the outcomes of future pregnancy and the health of future offspring. Similarly, the influence of a man’s health, lifestyle, and diet during preconception on pregnancy and offspring outcomes must be considered. However, the male reproductive partner’s role during preconception has attracted much less researcher attention when compared to maternal exposures and outcomes and may be undervalued.
Therefore, this review explores the modifiable risk factors of males in the preconception period and how these risks influence adverse pregnancy and/or offspring outcomes. A total of 65 papers are included for review which examined risks associated with factors such as alcohol use, physical activity, stress, and nutrition. Overall, the papers identified some consistent results: paternal smoking increased risk of adverse offspring outcomes, while increased paternal body mass index was associated with higher offspring birthweight. Nevertheless, this review concludes that paternal preconception modifiable risk factors remain largely underexplored. Evidently, more high-quality research must be conducted to better understand the health, lifestyle, and diets of males in the preconception period and how various paternal modifiable risks can influence their partner’s pregnancy and the health and developmental outcomes of their offspring.
Preconception care is defined as the provision of health interventions (behavioural, social, and/or biomedical) to women and couples prior to conception . It addresses the transgenerational opportunity of enabling and optimizing health while limiting risk factors associated with both short- and long-term adverse health outcomes for women, men, and their children. There is global consensus on the key aspects of preconception care , yet a consistent definition and clear attributes of the preconception population remain elusive . Preconception research predominately focuses on maternal modifiable risks or health behaviours associated with offspring outcomes  as demonstrated by a scoping review of preconception health behaviours which found only 11% of all studies included paternal modifiable risks or health behaviours . Nonetheless, the research community recognizes the father or male partner’s contribution to child health and development before birth [6, 7] and the need to balance our gaze on men in preconception care . This is further supported by the increasing number and diversity of publications about paternal preconception health  and formulation of the Paternal Origins of Health and Disease (POHaD) model . As such, the preconception population may include all reproductively aged individuals in a period from their birth to the conception of their (or their partner’s) pregnancy. The care provided during this period must respond to a clear set of identified risk factors and exposures as relevant to each individual.
Indeed, when planning parenthood, males find themselves within a contentious grey zone; concurrently involved while also considered an outsider . A recent survey in the UK found that men are interested in engaging in positive preconception health behaviours . Of the over 500 men surveyed, 19% had visited a primary health provider for preconception health advice, and those who had received advice were more likely to adopt positive health behaviours before their partner’s pregnancy. On the other hand, general practitioners (GPs) report low confidence in their knowledge about paternal preconception health care and modifiable factors affecting male fertility [12, 13]. They describe feeling apprehensive or even sensitive to the subject matter and/or challenged by navigating the stereotypical masculine predispositions toward fertility and preconception care . In general, preconception risks are not raised by GPs with male patients unless subfertility is involved and preconception discussions are often encumbered by numerous impediments including the limited time, financial constraints, and knowledge of GPs, plus in some cases, a lack of GP motivation and perceived need for health care . A systematic review of preconception care guidelines found that six of the 11 guidelines included provided preconception care guidance for men . Only one guideline, a position paper from the American Academy of Family Physicians, contained a dedicated section outlining recommendations on preconception interventions for men . Evidently, there is an unmet need for health professionals, and men, to readily access current relevant information regarding paternal preconception health exposures and outcomes, informing clinical practice and directing health decisions.
Evidence supporting paternal preconception care considers males contribution to child health and development before conception via direct (genetic and epigenetic contributions – health and lifestyle behaviours, exposure to environmental toxins, life stressors, and neuroendocrinology) and indirect pathways (the couple’s relationship, and the influence of men on their partner’s health and health behaviours) . Yet, there is a stark contrast between the magnitude of research investigating maternal preconception health risks—including body composition, lifestyle behaviours, and diet/nutrition – and the relative scarcity of research attention directed towards understanding paternal health exposures and outcomes. In direct response, this systematic review aims to advance paternal preconception research by synthesising the current evidence on associations of modifiable paternal preconception health behaviours and risk factors with pregnancy and/or offspring outcomes.
A search was conducted on January 5th 2023, (See Supplementary File 1 Search strategy), through the following databases: 1) Medline (OVID) 2) Embase (OVID), 3) Maternity and Infant care [MIDIRS] (OVID) 4) CINAHL (EBSCO), 5) PsycINFO (EBSCO), 6) Scopus, & 7) ISI Proceedings. For each database, a date limit of 2012–2023 was set. When available, subject headings identified from the controlled vocabulary of each database were also included in the search. On January 11th 2023, a Google Scholar search was conducted for the search term ‘Paternal preconception’, applying the filter to limit articles published since 2022 and searching through to page seven, identifying any other recently published relevant papers. Google Scholar was also used to identify relevant studies citing each included paper. Reference lists of each included paper were then checked for additional relevant studies.
Papers were included if they were original contemporary observational research (cross-sectional, cohort or case–control study designs) involving males in the preconception period, examining an association or correlation of a modifiable risk factor or health behaviour to pregnancy and/or offspring health and developmental outcomes. The male participants must identify as being the partner of the pregnant women and/or the biological father of the child for which pregnancy and offspring outcomes were reported (Table 1 – PICO).
Observational study designs are generally utilized to identify correlations and establish findings at the population level hence are solely considered in this review.
Papers were excluded if they were: reviews, did not report new empirical findings from original studies (i.e. commentaries, opinion-pieces and editorials), not studying humans, not examining male parent exposures, did not differentiate between maternal and paternal preconception exposures, or if the exposure examined specific illness populations. Papers were also excluded when the exposure was not assessed or retrospectively recalled during the preconception period, the outcome was not related to pregnancy or offspring health or development, or the risk factor or health behaviour was not modifiable. Google Translate was used to decipher any studies located in languages other than English.
Papers were imported into Covidence systematic review software , and duplicates removed by automation. Titles and abstracts were screened by TC, AS and DS. Full-text articles were obtained for relevant studies and reviewed based on inclusion criteria by TC who then extracted data from each included paper. AS or DS randomly reviewed the extracted data of ten included studies for accuracy and completeness. Any conflicts were resolved by consensus.
Data extracted from each paper included: the authors and year, study design and duration, location, the preconception population, total number of participants, the paternal exposures (and exposure measures), paternal outcomes (and outcome measures), any covariates considered and the main results from each association reported.
The quality of each paper was assessed by TC using the Newcastle–Ottawa Scale (NOS). The NOS comprises three domains 1) selection of participants, 2) comparability of study groups, and 3) outcome of interest (cohort studies) or ascertainment of exposure (case–control studies), assigning stars in each domain to a maximum of nine stars . Papers were then categorized as good quality (7–9 stars), fair quality (4–6 stars) or poor quality (0–3 stars) using groupings employed in previous research .
A meta-analysis was considered, but not possible due to exposure and outcome heterogeneity.
A total of 65 papers were included in this review (Fig. 1 – PRISMA Flowchart) , comprising cohort (n = 56) and case control studies (n = 9) (Table 2 – Summary Table) & (Table 3 – Summary Table Findings). The majority of papers were conducted in the USA (n = 18), Europe and the UK (n = 19), and China (n = 17), several papers were from Australia [23,24,25,26,27,28,29] or included an Australian health centre [30,31,32,33,34]. Approximately half of all papers (n = 29) included a sample size between 370 and 2,900, while others included > 20,000 (n = 11) or ≤ 200 participants (n = 13).
Study participants were diverse consisting of couples either intending pregnancy or pregnant (n = 25), sub-fertile and seeking fertility treatment undergoing IVF/ICSI (n = 11), or mothers and fathers of infants (n = 26). Two studies included adolescents followed into parenthood as adults [42, 80], and one study included individual respondents of a national family growth survey, actively attempting pregnancy .
Modifiable preconception risk factors and/or health behaviour exposures examined include 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) (including dietary folate intake and consumption of foods and dietary patterns). Two papers investigated multiple exposures [42, 43].
Outcomes examined include fecundability (n = 6) [38, 61, 72, 77, 78, 85], (time to) pregnancy (n = 4) [48, 54, 59, 68], IVF/ICSI ongoing pregnancy (n = 1)  or live birth (n = 7) [41, 49, 58, 60, 81, 82, 86, 87], offspring birthweight or adiposity (n = 10) [40, 42, 45, 47, 50, 52, 53, 62, 65, 66], including small for gestational age [SGA] , neonatal (n = 1)  and offspring body composition (n = 4) [24, 30, 39, 73]. Other outcomes examined include offspring asthma (n = 4) [25, 31, 33, 69] and lung function (n = 2) [32, 34], childhood leukemia (n = 4) [26, 29, 64, 67], childhood brain tumours (n = 2) [27, 28], and offspring behavioural issues (n = 2) [46, 55].
There was an increasing number of papers identified for inclusion in this review with the least number of papers published in 2012 and the greatest number of papers published in 2022 (see Fig. 2).
Results below are described for papers assessed as good quality with approximately half (n = 30) rated good quality and two receiving a maximum nine-star rating [36, 54] (Table 4—Newcastle Ottawa Scale [NOS] quality assessment (Cohorts)) & (Table 5—Newcastle Ottawa Scale [NOS] quality assessment (Case controls)). Results for the fair and poor-quality papers are not further described.
Twenty-five papers investigated associations between paternal BMI and various offspring outcomes. These papers were derived from studies (n = 21) conducted in the US, Europe, China, Australia, and Turkey and less than half (n = 11) rated as good quality.
Less than half of the papers (n = 10) used anthropometric assessment by the research team to determine BMI [37, 38, 40,41,42, 45, 47,48,49, 54]; heights and weights utilized to formulate BMI were determined in the preconception period, generally from males in couples undergoing IVF/ICSI [41, 49] or males in couples currently attempting pregnancy/pregnant [40, 45, 48, 54]. Of the papers validating the BMI utilizing anthropometric assessments, most were good quality and generally affirmed significant results. The remaining papers utilize retrospective reports of preconception paternal weight and height or collect paternal height and weight from medical records. Maternal reporting (n = 7) occurred at approximately 10 to 18 weeks gestation; or up to four months postpartum [35, 46]. Paternal self-reporting of their own weight and height (n = 8) occurred at approximately week 17 of gestation [39, 43, 50, 52, 53] or up to 6 months postpartum . In two papers, overweight paternal status, when a child of 8 years, was reported years later through a validated drawing of silhouettes [33, 34].
The outcomes and outcome measures varied, however, ten studies assessed the association of paternal BMI with offspring BMI/bodyweight [23, 39, 40, 42, 45, 47, 50, 52, 53], and one paper assesses offspring weight and BMI changes from childhood (5 years) into adulthood (21 years) .
Results of associations between body composition and offspring outcomes were inconsistent. In some studies paternal preconception overweight (25.0—29.9 kg/m2) and obesity (> 30 kg/m2) were not associated with offspring birthweight  and paternal pregravid BMI was not an independent predictor for large for gestational age (LGA) or small for gestational age (SGA) . However, other studies found that offspring birthweight increased by 10.7 g per unit increase in paternal pregravid BMI (95% CI: 0.5, 20.9, P = 0.04) , and each standard deviation (SD) increment of paternal BMI (approximately 3.27 kg/m2) was associated with an additional 29.6 g increase of birth weight (95% CI: 5.7, 53.5, P = 0.02) . Further, compared with normal weight men, paternal pre-pregnancy overweight was associated with a significantly increased risk of preterm birth (aOR 1.34 95% CI: 1.25,1.45) and low birth weight (aOR 1.60 95% CI: 1.46–1.74) in offspring .
Paternal pregravid weight (P = 0.04), not height (P = 0.43), was associated with infant birth weight  and with increased risk of macrosomia (aOR = 1.49, [95% CI: 1.16, 1.92]) , while neonatal birth weight was associated with paternal height only (β = 0.08, P = 0.003) . In another study, paternal pre-pregnancy BMI was only associated with offspring BMI when using absolute BMI values not BMI as a z-score .
Fathers’ overweight before puberty had a negative indirect effect, mediated through sons’ height, on sons’ forced expiratory volume in one second (FEV1) (beta (95% CI): − 144 (− 272, − 23) mL) and forced vital capacity (FVC) (beta (95% CI): − 210 (− 380, − 34) mL), and a negative direct effect on sons’ FVC (beta (95% CI): − 262 (− 501, − 9) mL) .
Male BMI ≥ 25 kg m2 was not associated with time to pregnancy (TTP) , yet underweight (< 18.5 kg/ m2) was associated with a longer TTP (adjusted fecundability odds ratio [aFOR] = 0.95, [95% CI: 0.94, 0.96]) compared to normal BMI (18.5—23.9 kg/m2) .
In couples undergoing IVF/ICSI, paternal periconceptional BMI was negatively associated with fertilization rate (β = − 0.01 [SE = 0.004], P = 0.002]), while paternal BMI was not associated with the total motile sperm count (TMSC), the KIDScore, the embryo usage rate, a positive pregnancy, fetal heartbeat, or live birth .
Offspring methylation was associated with paternal BMI independent of maternal BMI (P = < 0.05) . Methylation decreased by 5% in cord blood with every 1-unit increase in paternal BMI (P = 3.13 × 10 -҆ꝰ), decreases persist at 3 years old (P = 0.002) and 7 years old (P = 0.004) . Paternal BMI was associated with methylation at cg01029450 in the promoter region of the ARFGAP3 gene; methylation at this site was also associated with lower infant birthweight (β = − 0.0003; SD = 0.0001; P = 0.03) .
No association was found between behavioural outcomes at pre-school age and underweight (< 18.5 kg/m2) or obesity (≥ 30 kg/m2) in fathers . Equally, no associations were found between paternal BMI overweight (≥ 25 kg/m2- < 30 kg/m2), obese class I (≥ 30 kg/m2- < 35 kg/m2) and obese class II (≥ 35 kg/m2) and offspring behavioural issues or psychiatric symptoms at 7–8 years .
Six papers examined alcohol as an exposure [26, 42, 43, 55,56,57]; three rated as good quality [42, 55, 56]. Excluding one, each paper used paternal self-reports of alcohol consumption with varying definitions; one article specified units/per week , the others assessed consumption more broadly either as intake ≥ 1/week , ≥ 1/month  or general intake . A single study presented a maternal report of paternal preconception alcohol consumption, 3 months before conception, at 12–16 weeks gestation .
When examining an outcome of offspring anogenital distance (AGD), in the paternal alcohol-exposed group (> 81 g/wk), male offspring had shorter mean AGDs ; for AGD-AP [the centre of the anus to the cephalad insertion of the penis] at birth (β =—1.73, P = 0.04) and 12 months (β = -7.29, P = 0.05), and shorter mean AGD-AS [the centre of the anus to the posterior base of the scrotum] at 6 months (β =—4.91, P = 0.02) . Female offspring had shorter mean AGD-AF [ the centre of the anus to the posterior convergence of the fourchette) (β = -0.72, P = 0.02) at birth yet longer mean AGD AC [the centre of the anus to the clitoris] (β = 2.81, P = 0.04) and AGD-AF (B = 1.91, P = 0.04) at 12 months . Further, the relative risks of anxiety or depression were increased by 33% (RR = 1.33 [95% CI: 1.09, 1.61]) and 37% (RR = 1.37 [95% CI: 1.02,1.84]) among girls in the exposed group at ages 4 and 6, respectively . Paternal alcohol consumption greater than once per month was not associated with offspring birthweight or gestational age .
Paternal cannabis exposure was assessed in five papers [42, 58,59,60,61], two rate as good quality [42, 60]. Each paper has a sample size < 1,200 and each utilized paternal self-reporting of cannabis use broadly assessing general use, rather than specific amounts, over a pre-determined period (i.e., last 2 months or 12 months).
In sub-fertile couples undergoing IVF/ICSI, compared to males who were past or never cannabis users, couples where the male partner used cannabis at enrolment had increased probability of implantation (77.9, [95% CI: 53.5, 91.5], P = < 0.05) and live birth (47.6, [95% CI: 32.4, 63.3], P = < 0.05), independent of women's cannabis use . Clinical pregnancy was not associated with male cannabis use , nor was gestational age or offspring birthweight .
The associations of paternal physical activity with offspring outcomes were assessed in two papers [42, 43], one rated as good quality . This study found no association between paternal preconception bouts of physical activity per week and gestational age or offspring birthweight .
The association of tobacco smoking with offspring outcomes was examined in 20 papers [27, 30,31,32, 42, 62,63,64,65,66,67,68,69,70,71,72,73,74,75, 88]; half (n = 10) were rated as good quality [31, 32, 42, 63, 64, 66,67,68, 73, 74] and nine papers adjusted for maternal smoking and/or paternal passive smoking in their analysis [32, 62, 64,65,66, 71, 73, 74].
Paternal cigarette smoking was associated with a longer TTP compared with never users (aFOR = 0.41, [95% CI: 0.24, 0.68]), while no associations were found for other tobacco products including cigars or snuff and chew tobacco .
Outcomes involving smoking and birth defects report that during the periconceptional period, light paternal smoking [1–9 cigarettes/day] increased the risk of isolated conotruncal heart defects (aOR = 2.23, [95% CI: 1.05, 4.73]) . Medium paternal smoking [10–19 cigarettes/day] increased the risk of septal defects (aOR = 2.04, [95% CI: 1.05, 3.98]) and left ventricular outflow tract obstructions (aOR = 2.48, [95% CI: 1.04, 5.95]) . Heavy paternal smoking (≥ 20 cigarettes/day) increased the risk of isolated conotruncal heart defects (aOR = 8.16, [95% CI: 1.13, 58.84]) and left ventricular outflow tract obstructions (aOR = 13.12, [95% CI: 2.55, 67.39]) . Likewise, an increased risk of birth defects was found for continued-smoking (OR = 1.87, [95% CI: 1.36, 2.56], P < 0.001) and decreased-smoking groups (OR = 1.41, [95% CI: 1.10, 1.82], P = 0.007) compared with those fathers that quit smoking during early pregnancy and those who did not smoke at all during preconception .
Paternal preconception smoking at least one cigarette/day for one month was not associated with gestational age or offspring birthweight . In contrast, a second study found sons whose fathers started smoking < 11 years, the adjusted mean differences in BMI, waist circumference, and fat mass all showed higher values at ages 13, 15, and 17 . Further, the risk of childhood overweight and obesity was increased among children exposed to paternal preconception smoking compared to children without paternal smoking exposure (OR = 1.41 [95% CI: 1.17, 1.85]) .
Paternal preconception smoking 12 months prior to conception was associated with an increased risk of childhood acute myeloid leukemia (AML) (OR = 2.51, 95% CI: 1.21, 5.17)  and paternal smoking just 3 months prior to conception provided significant associations with acute lymphoblastic leukemia (ALL) (OR = 1.2 [95% CI: 1.1,1.5)] and acute myeloblastic leukemia (AML) (OR = 1.5 [95% CI: 1.0–2.3]) .
Paternal preconception smoking also provided significant associations with offspring lung function and asthma; fathers’ smoking initiation in prepuberty (generation G1) had a negative direct effect on their own FEV1/FVC (difference in offspring’s expected score − 0.36, 95% CI: − 0.68, -0.04) compared with fathers’ never smoking. This exposure had a negative direct effect on both offspring’s FEV1 (− 0.36, 95% CI: − 0.63, − 0.10) and FVC (− 0.50, 95% CI: − 0.80, − 0.20) (generation G2) . Fathers’ smoking before age 15 years was associated with higher risk of asthma without nasal allergies in their offspring [relative risk ratio ((RRR) = 1.43 95% CI: 1.01, 2.01] .
Paternal stress exposure was examined in three papers [43, 76, 77]; including one rated as good quality . This study found men's baseline perceived stress scale [PSS] scores were not associated with fecundability .
Papers examining paternal nutrition (n = 13) evaluated the associations of a range of nutritional exposures including paternal preconception folate, vitamins B6 and B12, and general dietary patterns with numerous offspring outcomes. These papers utilized data from several studies (n = 8) originating in the US, Norway, The Netherlands, and Australia. Approximately half of these papers (n = 7) rated as good quality.
Paternal nutritional factors explored included dietary patterns [82, 83] or specific foods groups including dairy , and meat . IVF/ICSI-induced live birth was an outcome examined in three papers [82, 86, 87]. A positive association was found between paternal poultry intake and fertilization rate, with a higher fertilization rate among men in the highest quartile of poultry intake [78%] compared with those in the lowest quartile [65%] . Men's total dairy intake was not associated with fertilization rate, implantation rate, clinical pregnancy rate, or live birth rate . Also, paternal adherence to specific dietary patterns [pattern 1 = greater intake of processed foods/meats/high fat/dairy/sugar; pattern 2 = greater intake of fruit/vegetables/legumes/whole grains/nuts/fish] was not associated with fertilization rate  when undergoing IVF cycles.
One paper investigated dietary exposures during adolescence and subsequent neonatal health . In a sample of adolescents followed into adulthood becoming fathers (n = 2,140), an extra serving of fruit per week was associated with a 2.35 g increase in offspring placenta weight [95% CI: 0.284, 4.42], P = 0.03 . Further, paternal lunching regularly in adolescence was associated with an increase in offspring head circumference (β = 0.160, [95% CI: 0.001, 0.320], P = 0.05) and whole grain bread consumption was associated with a lower ponderal index (β = -0.003, [95% CI: -0.005, -0.001], P = 0.01) . Birthweight was not associated with any paternal dietary exposures .
Generally, paternal preconception dietary patterns were collected through paternal self-reports on standardised food frequency questionnaires (FFQ) at baseline and include fast foods ; males eating fast food more frequently had infants born earlier than men who eat fast food less frequently (-0.16, [95% CI: − 0.32, 0.00], P = 0.04) .
Two papers specifically investigated paternal folate [79, 81]. In males undergoing fertility treatment, a 400 μg/day higher preconception folate intake was associated with a 2.6-day longer gestation [95% CI: 0.8, 4.3], P = 0.004 . In spontaneously conceived pregnancies, a significant negative association was found between paternal red blood cell [RBC] folate status and crown-rump length (CRL) trajectories, in Quartile 2 [875–1,018 nmol/L;] (β = -0.14; [95% CI:—0.28, -0.006], P = 0.04) and Quartile 4 [1,196–4,343 nmol/L] (β =—0.19, [95% CI:—0.33, -0.04], P = 0.012) compared with the reference values in Quartile 3 . A negative association was also found for embryonic volume (EV) trajectories in Quartile 4 (β =—0.12, [95% CI: -0.20, -0.05], P = 0.001) .
This paper reports the first review collating literature assessing modifiable paternal health behaviours and risk factors in the preconception period and highlights clear disparity between the preconception research for women as compared to that for men. While single papers identified in our review do demonstrate adverse pregnancy and offspring outcomes associated with paternal risk factors in the preconception period, current research of paternal health behaviours and risk factors provides an emerging rather than mature evidence-base. Nevertheless, our review did identify a number of important findings.
One consistent finding of this review was the association between paternal preconception smoking and increased risk of adverse infant outcomes, including birth defects and childhood leukemia especially acute myeloid leukemia/acute myeloblastic leukemia (AML). Adverse outcomes such as birth defects are mirrored in maternal preconception smoking literature [89,90,91], yet the impact of maternal smoking on the risk of AML remains contentious [92, 93]. Smoking in the preconception period may be as perilous for males as for females, as smoking can potentially affect semen quality . Many male smokers (and even more so in smoking couples) consider smoking an indispensable characteristic of their domestic, social and working lives  and many report a lack of motivation, willpower, and/or strength to successfully quit , in turn influencing female smoking patterns and family environments . Paternal preconception smoking may well be contributing to the estimated 240,000 newborns dying worldwide annually due to birth defects . The finding of paternal preconception smoking and the increased risk of adverse infant outcomes is altogether disconcerting considering the widespread use of tobacco, and that males are more likely than females to engage in risk-taking behaviours, including smoking ; the estimated global prevalence of male adolescent smokers in 133 countries is 23.29%.
The papers in this review which focus upon body composition with birthweight outcomes generally affirm positive associations between increasing paternal BMI and offspring birthweight. Indeed, this finding aligns with the literature outside this review which acknowledges that mothers and fathers with overweight or obesity are more likely to have children with overweight or obesity [99,100,101,102], compared with those with a normal weight. The positive associations between increasing paternal BMI and offspring bodyweight may, in part, be due to paternal contributions of sperm quality and potential changes to the epigenetic profiles of spermatoza [10, 103] resulting from unhealthy preconception environments and relationships with food. Food-based parenting strategies  and spending too much time sedentary  may also contribute to influencing offspring weight status. One paper in this review did chart offspring weight and BMI changes from childhood into adulthood , however, this reported research did not control for the offspring’s diet and physical exercise.
Nonetheless, an individual’s birthweight can influence both their body weight in childhood  and their body weight as they transition into adulthood ; external literature positively associates both a higher birthweight and childhood obesity with overweight/obesity at 15–20 years of age . Frameworks to maintain healthy bodyweight, in turn promoting healthy birthweights, endure in the Global action plan on physical activity 2018–2030  and in national overweight/obesity guidelines in countries such as Australia  and the Unites States .
It is important to note that most papers included in this review utilize retrospective reports (paternal self-reports or maternal reports) of anthropometric data collected at baseline. Such retrospective self-reporting is also evident in the maternal preconception literature [111, 112] and is often considered unreliable and subject to inaccuracies due to self-reporting bias or recall bias . Inaccuracies and reporting bias may be present in particular in papers that utilize maternal reports of paternal preconception height and body weight at minimum 10 weeks of gestation in some papers up to 4 months postpartum. Consequently, retrospective reports of data at baseline may undermine the validity, accuracy, and therefore the reliability of BMI data used in these papers.
The majority of papers in our review report research undertaken in distinct geographical regions with the USA, Europe and the UK, and China heavily represented. As such, the implications for reduced geographical spread of the available research examining paternal preconception health exposures and outcomes must also be considered. It may be that existing region-specific idiosyncrasies of paternal health behaviours, and associated adverse health outcomes for their children, are yet to be described due to the absence of research conducted in other countries and cultures. These gaps limit the opportunities for tailored preconception care policies and interventions and constrain the broader understanding of the potential importance of paternal preconception care. Notwithstanding, such issues foster opportunities for other countries and cultures to identify, learn from and support paternal health.
While almost all papers in this review adjust for some confounders, less than half (n = 23) adjusted for the same maternal exposure (i.e., paternal BMI studies adjusting for maternal BMI). Many papers in this review did not adjust for maternal exposures and thus may present biased results and conclusions. Further, many maternal studies do not control for paternal exposures which is a limitation in the field that requires urgent research attention and refocus.
The date parameters set during the search may also represent a limitation as it may have resulted in manuscripts published before the 2012 being overlooked. However, up until recently the preconception research field has primarily focused on the effects of maternal exposures and as such it is unlikely that significant research was overlooked by this date restriction.
Further limitations of the review include the potential for missed citations due to issues with article indexing. Our search protocol did not employ search term truncations or singular synonyms in the final search string which may have resulted in some citations being missed. However, the search protocol was informed by an experienced health librarian, and additional methods – such as reference list and citation checking—were used to identify relevant manuscripts not identified through the primary search. Furthermore, previous search strings trialed for this review that used different synonyms, truncations and search term categories did not result in any additional relevant manuscripts being identified beyond those included in the final search. As such, the literature review is the most comprehensive review of the topic conducted to date.
This review is innovative in that it provides the first examination of paternal preconception risk factors and their association with adverse pregnancy and offspring outcomes. The rigour of the review is also bolstered through adhering to established systematic review reporting guidelines (PRISMA and AMSTAR).
Overall, this review shows that paternal preconception modifiable risk factors are largely underexplored; smoking and body composition appear to be important areas for consideration in paternal preconception care. While the current literature identifies an emerging evidence-base around paternal preconception modifiable risk factors, there is a need for further investigation to help better inform paternal preconception care and national and international preconception care guidelines. In particular, further research is necessary to identify and better understand the modifiable risk factors affecting males in the preconception period, and how these risk factors influence offspring outcomes, to inform clinical recommendations and health decisions. The future of paternal preconception care and the integration of such care into frontline health practice and policy rests with informed collaboration between clinicians, researchers and policymakers .
Availability of data and materials
All data extracted for this systematic review are presented as part of the manuscript.
Body mass index
Food frequency questionnaires
Intracytoplasmic sperm injection
Large for gestational age
Newcastle–Ottawa Scale [NOS]
Paternal Origins of Health and Disease
Population, Intervention, Comparison, Outcome
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Small for gestational age
Time to pregnancy
Tasmanian Longitudinal Health Study
National Free Pre-conception Check-up Projects
The Respiratory Health in Northern Europe, Spain and Australia multigeneration study
Childhood acute lymphoblastic leukemia
Forced expiratory volume in one second
Forced vital capacity
Child Behaviour Checklist
Childhood brain tumours
European Community Respiratory Health Survey
Costa Rican Childhood Leukemia Study
Acute Myeloid Leukemia
Fat mass index
Childhood acute leukemia
National Registry of Childhood Hematopoietic Malignancies
Respiratory Heath in Northern Europe
Achieving a Healthy Pregnancy
Relative risk ratio
Preconception Dietary Risk Score
Guangxi Zhaung Birth Cohort
World Health Organization [WHO]. Preconception care: maximising the gains for maternal and child health - Policy brief World Health Organization - All rights reserved; 2013 15 February 2013. Contract No.: WHO REFERENCE NUMBER: WHO-FWC-MCA-13.02.
World Health Organization [WHO], editor Meeting to develop a global consensus on preconception care to reduce maternal and childhood mortality and morbidity Meeting to develop a global consensus on preconception care to reduce maternal and childhood mortality and morbidity 2012; Geneva: World Health Organization [WHO].
Hill B, Hall J, Currie S. Defining preconception: exploring the concept of a preconception population. BMC Pregnancy and Childbirth. 2020.
Caut C, Schoenaker, D., McIntyre, E., Vilcins, D., Gavine, A., Steel, A., . Relationships between women’s and men’s modifiable preconception risks and health behaviors and maternal and offspring health outcomes: an umbrella review. . Seminars in Reproductive Medicine. 2022.
Toivonen KI, Oinonen KA, Duchene KM. Preconception health behaviours: A scoping review. Prev Med. 2017;96:1–15.
Cardenas S, Morris A, Marshall N, Aviv E, García M, Sellery P, et al. Fathers matter from the start: The role of expectant fathers in child development. Child Develop Perspect. 2021.
Shawe J, Patel D, Joy M, Howden B, Barrett G, Stephenson J. Preparation for fatherhood: a survey of men’s preconception health knowledge and behaviour in England. PLoS ONE. 2019;14(3):e0213897.
Steel A, Carter T. Balancing our gaze on preconception health and care to include men. Adv Integrat Med. 2021;8(2):79–80.
Rutkowska J, Lagisz M, Bonduriansky R, Nakagawa S. Mapping the past, present and future research landscape of paternal effects. BMC Biol. 2020;18(1):1–24.
Soubry A. POHaD: why we should study future fathers. Environ Epigenet. 2018;4(2):dvy007-dvy.
Kotelchuck M, Lu M. Father’s role in preconception health. Matern Child Health J. 2017;21(11):2025–39.
Ojukwu O, Patel D, Stephenson J, Howden B, Shawe J. General practitioners’ knowledge, attitudes and views of providing preconception care: a qualitative investigation. Upsala J Med Sci. 2016;121(4):256–63.
Mazza D, Chapman A, Michie S. Barriers to the implementation of preconception care guidelines as perceived by general practitioners: a qualitative study. BMC Health Serv Res. 2013;13:36.
Hogg K, Rizio T, Manocha R, McLachlan RI, Hammarberg K. Men’s preconception health care in Australian general practice: GPs’ knowledge, attitudes and behaviours. Aust J Prim Health. 2019;25(4):353–8.
Dorney E, Boyle JA, Walker R, Hammarberg K, Musgrave L, Schoenaker D, et al. A Systematic Review of Clinical Guidelines for Preconception Care. Semin Reprod Med. 2022.
American Academy of Family Physicians (AAFP). Preconception Care (Position Paper): AAFP; 2015 [Available from: https://www.aafp.org/about/policies/all/preconception-care.html.
Cardenas SI, Morris AR, Marshall N, Aviv EC, Martínez García M, Sellery P, et al. Fathers matter from the start: The role of expectant fathers in child development. Child Develop Perspect. 2022;16(1):54–9.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. PLoS Med. 2021;18(3):e1003583.
Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.
Covidence systematic review software (COVIDENCE). Melbourne, Australia Veritas Health Innovation; [Available from: www.covidence.org.
Luchini C, Stubbs B, Solmi M, Veronese N. Assessing the quality of studies in meta-analyses: Advantages and limitations of the Newcastle Ottawa Scale. World J Meta-Anal. 2017;5:80.
Sharmin S, Kypri K, Khanam M, Wadolowski M, Bruno R, Mattick RP. Parental Supply of Alcohol in Childhood and Risky Drinking in Adolescence: Systematic Review and Meta-Analysis. Int J Environ Res Public Health. 2017;14(3):287.
Pomeroy E, Wells JCK, Cole TJ, O’Callaghan M, Stock JT. Relationships of maternal and paternal anthropometry with neonatal body size, proportions and adiposity in an Australian cohort. Am J Phys Anthropol. 2015;156(4):625–36.
Zalbahar N, Najman J, McIntyre HD, Mamun A. Parental pre-pregnancy obesity and the risk of offspring weight and body mass index change from childhood to adulthood. Clinical Obesity. 2017;7(4):206–15.
Bowatte G, Bui DS, Priyankara S, Lowe AJ, Perret JL, Lodge CJ, et al. Parental preconception BMI trajectories from childhood to adolescence and asthma in the future offspring. J Allergy Clin Immunol. 2022;150(1):67-74.e30.
Milne E, Greenop KR, Scott RJ, de Klerk NH, Bower C, Ashton LJ, et al. Parental alcohol consumption and risk of childhood acute lymphoblastic leukemia and brain tumors. Cancer Causes Control. 2013;24(2):391–402.
Milne E, Greenop KR, Scott RJ, Ashton LJ, Cohn RJ, De Klerk NH, et al. Parental smoking and risk of childhood brain tumors. Int J Cancer. 2013;133(1):253–9.
Greenop KR, Miller M, Bailey HD, Scott RJ, Attia J, Bower C, et al. Paternal dietary folate, B6 and B12 intake, and the risk of childhood brain tumors. Nutr Cancer. 2015;67(2):224–30.
Bailey HD, Miller M, Greenop KR, Bower C, Attia J, Marshall GM, et al. Paternal intake of folate and vitamins B6 and B12 before conception and risk of childhood acute lymphoblastic leukemia. Cancer Cause Contr. 2014;25(12):1615–25.
Knudsen GTM, Dharmage S, Janson C, Abramson MJ, Benediktsdóttir B, Malinovschi A, et al. Parents’ smoking onset before conception as related to body mass index and fat mass in adult offspring: findings from the RHINESSA generation study. PLoS ONE. 2020;15(7):e0235632.
Accordini S, Calciano L, Johannessen A, Portas L, Benediktsdóttir B, Bertelsen RJ, et al. A three-generation study on the association of tobacco smoking with asthma. Int J Epidemiol. 2018;47(4):1106–17.
Accordini S, Calciano L, Johannessen A, Benediktsdóttir B, Bertelsen RJ, Bråbäck L, et al. Prenatal and prepubertal exposures to tobacco smoke in men may cause lower lung function in future offspring: a three-generation study using a causal modelling approach. Eur Respir J. 2021;58(4):2002791.
Johannessen A, Lønnebotn M, Calciano L, Benediktsdóttir B, Bertelsen RJ, Bråbäck L, et al. Being overweight in childhood, puberty, or early adulthood: Changing asthma risk in the next generation? J Allergy Clin Immunol. 2020;145(3):791-9.e4.
Lønnebotn M, Calciano L, Johannessen A, Jarvis DL, Abramson MJ, Benediktsdóttir B, et al. Parental Prepuberty Overweight and Offspring Lung Function. Nutrients. 2022;14(7):1506.
Broadney MM, Chahal N, Michels KA, McLain AC, Ghassabian A, Lawrence DA, et al. Impact of parental obesity on neonatal markers of inflammation and immune response. Int J Obes. 2017;41(1):30–7.
Casas M, Forns J, Martinez D, Guxens M, Fernandez-Somoano A, Ibarluzea J, et al. Maternal pre-pregnancy obesity and neuropsychological development in pre-school children: a prospective cohort study. Pediatr Res. 2017;82(4):596–606.
Chen R, Chen L, Liu Y, Wang F, Wang S, Huang Y, et al. Association of parental prepregnancy BMI with neonatal outcomes and birth defect in fresh embryo transfer cycles: a retrospective cohort study. BMC Pregnancy Childbirth. 2021;21(1):1–11.
Fang Y, Liu J, Mao Y, He Y, Li M, Yang L, et al. Pre-pregnancy body mass index and time to pregnancy among couples pregnant within a year: A China cohort study. PLoS ONE [Electronic Resource]. 2020;15(4):e0231751.
Fleten C, Nystad W, Stigum H, Skjaerven R, Lawlor DA, Davey Smith G, et al. Parent-offspring body mass index associations in the Norwegian Mother and Child Cohort Study: a family-based approach to studying the role of the intrauterine environment in childhood adiposity. Am J Epidemiol. 2012;176(2):83–92.
Guo T, Yang Y, Jia J, Deng Y, Wang Y, Zhang Y, et al. Preconception Paternal/Maternal Body Mass Index and Risk of Small/Large for Gestational Age Infant in over 4·7 Million Chinese Women Aged 20–49 Years: A Population-based Cohort Study in China. Br J Nutr. 2022:1–28.
Hoek J, Schoenmakers S, van Duijn L, Willemsen SP, van Marion ES, Laven JSE, et al. A higher preconceptional paternal body mass index influences fertilization rate and preimplantation embryo development. Andrology. 2022;10(3):486–94.
Moss JL, Harris KM. Impact of maternal and paternal preconception health on birth outcomes using prospective couples’ data in Add Health. Arch Gynecol Obstet. 2015;291(2):287–98.
Mutsaerts MA, Groen H, Buiter-Van der Meer A, Sijtsma A, Sauer PJ, Land JA, et al. Effects of paternal and maternal lifestyle factors on pregnancy complications and perinatal outcome. A population-based birth-cohort study: the GECKO Drenthe cohort. Hum Reprod. 2014;29(4):824–34.
Noor N, Cardenas A, Rifas-Shiman SL, Pan H, Dreyfuss JM, Oken E, et al. Association of Periconception Paternal Body Mass Index With Persistent Changes in DNA Methylation of Offspring in Childhood. JAMA Netw Open. 2019;2(12):e1916777.
Retnakaran R, Wen SW, Tan H, Zhou S, Ye C, Shen M, et al. Paternal weight prior to conception and infant birthweight: a prospective cohort study. Nutr Diabetes. 2021;11(1):28.
Robinson SL, Ghassabian A, Sundaram R, Trinh M-H, Lin T-C, Bell EM, et al. Parental Weight Status and Offspring Behavioral Problems and Psychiatric Symptoms. J Pediatr. 2020;220:227-36.e1.
Sun M, Zhang S, Chen L, Li Y, Diao J, Li J, et al. Association between paternal pre-pregnancy body mass index with preterm birth and low birth weight. Front Pediatr. 2022;10:955544.
Sundaram R, Mumford SL, Buck Louis GM. Couples’ body composition and time-to-pregnancy. Hum Reprod. 2017;32(3):662–8.
Umul M, Köse SA, Bilen E, Altuncu AG, Oksay T, Güney M. Effect of increasing paternal body mass index on pregnancy and live birth rates in couples undergoing intracytoplasmic sperm injection. Andrologia. 2015;47(3):360–4.
Wei J, Wang T, Shu J, Liu Y, Song X, Sun M, et al. Parental pre-pregnancy body mass index and risk of low birth weight in offspring: A prospective cohort study in central China. Front Public Health. 2022;10:1036689.
Wei B, Shao Y, Liang J, Tang P, Mo M, Liu B, et al. Maternal overweight but not paternal overweight before pregnancy is associated with shorter newborn telomere length: evidence from Guangxi Zhuang birth cohort in China. BMC Pregnancy Childbirth. 2021;21(1):283.
Xu R, Zhao W, Tan T, Li H, Wan Y. Paternal body mass index before conception associated with offspring’s birth weight in Chinese population: a prospective study. medRxiv. 2021:2021.06.17.21258438.
Yang S, Zhou A, Xiong C, Yang R, Bassig BA, Hu R, et al. Parental Body Mass Index, Gestational Weight Gain, and Risk of Macrosomia: A Population-Based Case-Control Study in China. Paediatr Perinat Epidemiol. 2015;29(5):462–71.
Zhang Y, Zhang J, Zhao J, Hong X, Zhang H, Dai Q, et al. Couples’ prepregnancy body mass index and time to pregnancy among those attempting to conceive their first pregnancy. Fertil Steril. 2020;114(5):1067–75.
Luan M, Zhang X, Fang G, Liang H, Yang F, Song X, et al. Preconceptional paternal alcohol consumption and the risk of child behavioral problems: a prospective cohort study. Sci Rep. 2022;12(1):1–11.
Xia R, Jin L, Li D, Liang H, Yang F, Chen J, et al. Association Between Paternal Alcohol Consumption Before Conception and Anogenital Distance of Offspring. Alcoholism. Clin Exp Res. 2018;42(4):735–42.
Zuccolo L, DeRoo LA, Wills AK, Davey Smith G, Suren P, Roth C, et al. Pre-conception and prenatal alcohol exposure from mothers and fathers drinking and head circumference: results from the Norwegian Mother-Child Study (MoBa). Sci Rep. 2016;7:39535.
Har-Gil E, Heled A, Dixon M, Ahamed AMS, Bentov Y. The relationship between cannabis use and IVF outcome—a cohort study. J Cannabis Res. 2021;3(1):42.
Kasman AM, Thoma ME, McLain AC, Eisenberg ML. Association between use of marijuana and time to pregnancy in men and women: findings from the National Survey of Family Growth. Fertil Steril. 2018;109(5):866–71.
Nassan FL, Arvizu M, Mínguez-Alarcón L, Gaskins AJ, Williams PL, Petrozza JC, et al. Marijuana smoking and outcomes of infertility treatment with assisted reproductive technologies. Hum Reprod. 2019;34(9):1818–29.
Wise LA, Wesselink AK, Hatch EE, Rothman KJ, Mikkelsen EM, Sørensen HT, et al. Marijuana use and fecundability in a North American preconception cohort study. J Epidemiol Community Health. 2018;72(3):208–15.
Carslake D, Pinger PR, Romundstad P, Davey SG. Early-onset paternal smoking and offspring adiposity: further investigation of a potential intergenerational effect using the HUNT study. PLoS ONE. 2016;11(12):e0166952.
Deng K, Liu Z, Lin Y, Mu D, Chen X, Li J, et al. Periconceptional paternal smoking and the risk of congenital heart defects: A case-control study. Birth Defects Research Part A - Clinical and Molecular Teratology. 2013;97(4):210–6.
Frederiksen LE, Erdmann F, Wesseling C, Winther JF, Mora AM. Parental tobacco smoking and risk of childhood leukemia in Costa Rica: a population-based case-control study. Environ Res. 2020;180:108827.
Ko TJ, Tsai LY, Chu LC, Yeh SJ, Leung C, Chen CY, et al. Parental smoking during pregnancy and its association with low birth weight, small for gestational age, and preterm birth offspring: A birth cohort study. Pediatr Neonatol. 2014;55(1):20–7.
Northstone K, Golding J, Davey Smith G, Miller LL, Pembrey M. Prepubertal start of father’s smoking and increased body fat in his sons: further characterisation of paternal transgenerational responses. Eur J Hum Genet. 2014;22(12):1382–6.
Orsi L, Rudant J, Ajrouche R, Leverger G, Baruchel A, Nelken B, et al. Parental smoking, maternal alcohol, coffee and tea consumption during pregnancy, and childhood acute leukemia: the ESTELLE study. Cancer Causes Control. 2015;26(7):1003–17.
Sapra KJ, Barr DB, Maisog JM, Sundaram R, Buck Louis GM. Time-to-Pregnancy Associated With Couples’ Use of Tobacco Products. Nicotine Tob Res. 2016;18(11):2154–61.
Svanes C, Koplin J, Skulstad SM, Johannessen A, Bertelsen RJ, Benediktsdottir B, et al. Father’s environment before conception and asthma risk in his children: A multi-generation analysis of the Respiratory Health In Northern Europe study. Int J Epidemiol. 2017;46(1):235–45.
Wang L, Deng Y, Yang Y, Liu F, Xu Q, Peng Z, et al. Paternal smoking and preterm birth: a population-based retrospective cohort study among non-smoking women aged 20–49 years in rural China. Reprod Health. 2022;19(1):72.
Wang L, Yang Y, Liu F, Yang A, Xu Q, Wang Q, et al. Paternal smoking and spontaneous abortion: A population-based retrospective cohort study among non-smoking women aged 20–49 years in rural China. J Epidemiol Community Health. 2018;72(9):783–9.
Wesselink AK, Hatch EE, Rothman KJ, Mikkelsen EM, Aschengrau A, Wise LA. Prospective study of cigarette smoking and fecundability. Hum Reprod. 2019;34(3):558–67.
You Y, Liu R, Zhou H, Wu R, Lin R, Li B, et al. Effect of Exposure to Paternal Smoking on Overweight and Obesity in Children: Findings from the Children Lifeway Cohort in Shenzhen. Southern China Obes Facts. 2022;15(4):609–20.
Zhou Q, Zhang S, Wang Q, Shen H, Zhang Y, Tian W, et al. Association between preconception paternal smoking and birth defects in offspring: evidence from the database of the National Free Preconception Health Examination Project in China. BJOG. 2020;127(11):1358–64.
Zwink N, Choinitzki V, Baudisch F, Holscher A, Boemers TM, Turial S, et al. Comparison of environmental risk factors for esophageal atresia, anorectal malformations, and the combined phenotype in 263 German families. Dis Esophagus. 2016;29(8):1032–42.
Bae J, Lynch CD, Kim S, Sundaram R, Sapra KJ, Buck Louis GM. Preconception stress and the secondary sex ratio in a population-based preconception cohort. Fertil Steril. 2017;107(3):714–22.
Wesselink AK, Hatch EE, Rothman KJ, Weuve JL, Aschengrau A, Song RJ, et al. Perceived Stress and Fecundability: A Preconception Cohort Study of North American Couples. Am J Epidemiol. 2018;187(12):2662–71.
Hatch EE, Wesselink AK, Hahn KA, Michiel JJ, Mikkelsen EM, Sorensen HT, et al. Intake of sugar-sweetened beverages and fecundability in a North American preconception cohort. Epidemiology. 2018;29(3):369.
Hoek J, Koster MPH, Schoenmakers S, Willemsen SP, Koning AHJ, Steegers EAP, et al. Does the father matter? the association between the periconceptional paternal folate status and embryonic growth. J Urol. 2019;202(3):446.
Lippevelde W, Vik F, Wills A, Strömmer S, Barker M, Skreden M, et al. The impact of diet during adolescence on the neonatal health of offspring: evidence on the importance of preconception diet. The HUNT study. J Dev Orig Health Dis. 2020;12:1–13.
Martín-Calvo N, Mínguez-Alarcón L, Gaskins AJ, Nassan FL, Williams PL, Souter I, et al. Paternal preconception folate intake in relation to gestational age at delivery and birthweight of newborns conceived through assisted reproduction. Reprod Biomed Online. 2019;39(5):835–43.
Mitsunami M, Salas-Huetos A, Mínguez-Alarcón L, Attaman JA, Ford JB, Kathrins M, et al. Men’s dietary patterns in relation to infertility treatment outcomes among couples undergoing in vitro fertilization. J Assist Reprod Genet. 2021;38(9):2307–18.
Oostingh EC, de Vos I, Ham AC, Brouwer-Brolsma EM, Willemsen SP, Eggink AJ, et al. No independent associations between preconception paternal dietary patterns and embryonic growth; the Predict Study. Clin Nutr. 2019;38(5):2333–41.
Twigt JM, Bolhuis ME, Steegers EA, Hammiche F, van Inzen WG, Laven JS, et al. The preconception diet is associated with the chance of ongoing pregnancy in women undergoing IVF/ICSI treatment. Hum Reprod. 2012;27(8):2526–31.
Wesselink AK, Wise LA, Rothman KJ, Hahn KA, Mikkelsen EM, Mahalingaiah S, et al. Caffeine and caffeinated beverage consumption and fecundability in a preconception cohort. Reprod Toxicol. 2016;62:39–45.
Xia W, Chiu YH, Afeiche MC, Williams PL, Ford JB, Tanrikut C, et al. Impact of men’s dairy intake on assisted reproductive technology outcomes among couples attending a fertility clinic. Andrology. 2016;4(2):277–83.
Xia W, Chiu YH, Williams PL, Gaskins AJ, Toth TL, Tanrikut C, et al. Men’s meat intake and treatment outcomes among couples undergoing assisted reproduction. Fertil Steril. 2015;104(4):972–9.
Mutsaerts MAQ, Groen H, Buiter-Van Der Meer A, Sijtsma A, Sauer PJJ, Land JA, et al. Effects of paternal and maternal lifestyle factors on pregnancy complications and perinatal outcome. A population-based birth-cohort study: The GECKO Drenthe cohort. Human Reprod. 2014;29(4):824–34.
Lassi ZS, Imam AM, Dean SV, Bhutta ZA. Preconception care: Caffeine, smoking, alcohol, drugs and other environmental chemical/radiation exposure. Reproduct Health. 2014;11(Supplement 3).
Perry MF, Mulcahy H, DeFranco EA. Influence of periconception smoking behavior on birth defect risk. Am J Obstet Gynecol. 2019;220(6):588.e1-e7.
Bolin EH, Gokun Y, Romitti PA, Tinker SC, Summers AD, Roberson PK, et al. Maternal Smoking and Congenital Heart Defects, National Birth Defects Prevention Study, 1997–2011. J Pediatr. 2022;240:79-86.e1.
Metayer C, Dahl G, Wiemels J, Miller M. Childhood Leukemia: A Preventable Disease. Pediatrics. 2016;138(Suppl 1):S45-s55.
Chunxia D, Meifang W, Jianhua Z, Ruijuan Z, Xiue L, Zhuanzhen Z, et al. Tobacco smoke exposure and the risk of childhood acute lymphoblastic leukemia and acute myeloid leukemia: A meta-analysis. Medicine (Baltimore). 2019;98(28):e16454.
Sharma R, Harlev A, Agarwal A, Esteves SC. Cigarette Smoking and Semen Quality: A New Meta-analysis Examining the Effect of the 2010 World Health Organization Laboratory Methods for the Examination of Human Semen. Eur Urol. 2016;70(4):635–45.
Flemming K, Graham H, McCaughan D, Angus K, Bauld L. The barriers and facilitators to smoking cessation experienced by women’s partners during pregnancy and the post-partum period: a systematic review of qualitative research. BMC Public Health. 2015;15(1):849.
Morphett K, Partridge B, Gartner C, Carter A, Hall W. Why Don’t Smokers Want Help to Quit? A Qualitative Study of Smokers’ Attitudes towards Assisted vs. Unassisted Quitting. Int J Environ Res Public Health. 2015;12(6):6591–607.
World Health Organization [WHO]. Birth defects 2022 [Available from: https://www.who.int/news-room/fact-sheets/detail/birth-defects.
Higgins ST, Kurti AN, Redner R, White TJ, Gaalema DE, Roberts ME, et al. A literature review on prevalence of gender differences and intersections with other vulnerabilities to tobacco use in the United States, 2004–2014. Prev Med. 2015;80:89–100.
Bahreynian M, Qorbani M, Khaniabadi BM, Motlagh ME, Safari O, Asayesh H, et al. Association between Obesity and Parental Weight Status in Children and Adolescents. J Clin Res Pediatr Endocrinol. 2017;9(2):111–7.
Patel C, Karasouli E, Shuttlewood E, Meyer C. Food Parenting Practices among Parents with Overweight and Obesity: A Systematic Review. Nutrients. 2018;10(12):1966.
Toschke AM, Beyerlein A, von Kries R. Children at high risk for overweight: a classification and regression trees analysis approach. Obes Res. 2005;13(7):1270–4.
Schnurr TM, Morgen CS, Borisevich D, Beaumont RN, Engelbrechtsen L, Ängquist L, et al. The influence of transmitted and non-transmitted parental BMI-associated alleles on the risk of overweight in childhood. Sci Rep. 2020;10(1):4806.
Fleming TP, Watkins AJ, Velazquez MA, Mathers JC, Prentice AM, Stephenson J, et al. Origins of lifetime health around the time of conception: causes and consequences. The Lancet. 2018;391(10132):1842–52.
Hidding LM, Altenburg TM, van Ekris E, Chinapaw MJM. Why Do Children Engage in Sedentary Behavior? Child- and Parent-Perceived Determinants. Int J Environ Res Public Health. 2017;14(7):671.
Qiao Y, Ma J, Wang Y, Li W, Katzmarzyk PT, Chaput JP, et al. Birth weight and childhood obesity: a 12-country study. Int J Obes Suppl. 2015;5(Suppl 2):S74–9.
Zhao Y, Wang S-F, Mu M, Sheng J. Birth weight and overweight/obesity in adults: a meta-analysis. Eur J Pediatr. 2012;171(12):1737–46.
Evensen E, Emaus N, Kokkvoll A, Wilsgaard T, Furberg A-S, Skeie G. The relation between birthweight, childhood body mass index, and overweight and obesity in late adolescence: a longitudinal cohort study from Norway, The Tromsø Study, Fit Futures. BMJ Open. 2017;7(6):e015576.
World Health Organization [WHO]. Global action plan on physical activity 2018–2030: more active people for a healthier world 2018 [Available from: https://www.who.int/publications/i/item/9789241514187.
Australian Government: Department of Health. National Obesity Strategy 2022–2032. Government 2022.
Centers for Disease Control and Prevention [CDC]. Prevention Strategies & Guidelines: CDC; 2018 [Available from: https://www.cdc.gov/obesity/resources/strategies-guidelines.html.
Wahab RJ, Jaddoe VWV, van Klaveren D, Vermeulen MJ, Reiss IKM, Steegers EAP, et al. Preconception and early-pregnancy risk prediction for birth complications: development of prediction models within a population-based prospective cohort. BMC Pregnancy Childbirth. 2022;22(1):165.
Mastroiacovo P, Nilsen RM, Leoncini E, Gastaldi P, Allegri V, Boiani A, et al. Prevalence of maternal preconception risk factors: an Italian multicenter survey. Ital J Pediatr. 2014;40(1):91.
Althubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016;9:211–7.
TC is funded under a Commonwealth Government research training stipend (RTP stipend). DS is supported by the National Institute for Health and Social Care Research (NIHR) Southampton Biomedical Research Centre [IS-BRC-1215–20004]). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.
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Carter, T., Schoenaker, D., Adams, J. et al. Paternal preconception modifiable risk factors for adverse pregnancy and offspring outcomes: a review of contemporary evidence from observational studies. BMC Public Health 23, 509 (2023). https://doi.org/10.1186/s12889-023-15335-1
- Risk factor
- Pregnancy outcomes
- Offspring outcomes