Abstract
Background
Congenital urogenital anomalies affect 4–60 per 10,000 births. Maternal obesity, along with other risk factors, is well documented as a contributing factor. However, the impact of paternal obesity on risk is unclear. Obesity is prevalent among men of reproductive age, highlighting the need for further research into the potential association between paternal obesity and offspring congenital urogenital anomalies.
Objectives
This study aims to determine the association between paternal obesity and the risk of congenital urogenital malformations in offspring.
Methods
Case–control study conducted on 179 newborns (91 cases, 88 controls) selected from the Notre Dame des Secours—university hospital database. Cases were identified as newborns presenting at least one congenital urogenital abnormality, defined as developmental anomalies that can result in a variety of malformations affecting the kidneys, ureters, bladder, and urethra. Controls were identified as newborns without any congenital abnormalities. The exclusion criteria were maternal obesity, infections during pregnancy, chronic diseases, prematurity, growth retardation, assisted reproductive technologies for conception, substance abuse, down syndrome, and other malformations. Data were collected through phone interviews, medical records, and questionnaires. In this study, the exposure was the preconceptional paternal body mass index (BMI), which was calculated based on self‐reported height and weight. According to guidelines from the US Centers for Disease Control and Prevention (CDC), individuals are considered to be in the healthy weight range if their BMI (kg/m2) is between 18.5 and < 25. They are classified as overweight if their BMI is ≥ 25, obese class I if their BMI is between 30 and < 35, obese class II if their BMI is between 35 and < 40, and obese class III if their BMI is 40 or higher. Logistic regression analysis was employed to quantify the association between paternal obesity and urogenital conditions in offspring.
Results
Significant differences in median (minimum–maximum) paternal BMI values were noted between the cases and controls at the time of conception (cases: 27.7 (43–20.1), controls: 24.8 (40.7–19.6); p < 0.0001). Logistic regression analysis confirmed that at the time of conception, compared to normal‐weight fathers, overweight fathers displayed a heightened risk of offspring congenital malformations, with an odds ratio (OR) of 4.44 (95% CI = 2.1–9.1). Similarly, fathers categorized as obese Class I at conception had approximately eight times higher odds (OR = 8.62, 95% CI = 2.91–25.52) of having offspring with urogenital conditions compared to normal‐weight fathers. Additionally, fathers classified as obese Class II at conception exhibited 5.75 times higher odds (OR = 5.75, 95% CI = 0.96–34.44) of having offspring with urogenital conditions in comparison to normal‐weight fathers.
Discussion and conclusion
We found that the risk of urogenital malformations increased with paternal BMI during the preconceptional period. The findings suggest the importance of addressing paternal obesity in efforts to reduce the risk of urogenital congenital malformations in offspring.
Keywords: congenital abnormalities, obesity, paternal exposure, urogenital system
1. INTRODUCTION
Congenital urogenital abnormalities are embryonic anomalies that can manifest as various malformations in the kidneys, ureters, bladder, and urethra. According to epidemiological studies, the estimated prevalence of these anomalies worldwide ranges from 4 to 60 per 10,000 births. 1 This highlights the substantial burden of this group of diseases on the global population, as they are linked to significant morbidity and premature mortality. 1
Previous research has identified several maternal risk factors 2 , 3 , 4 , 5 associated with congenital urogenital anomalies, including factors such as maternal age, obesity, diabetes mellitus, environmental exposure, smoking, drug use, substance abuse, alcohol, and use of assisted reproductive technologies. 3 , 6 , 7 , 8 While maternal risk factors have been thoroughly studied in the literature and found to be associated with an increased risk of congenital anomalies and birth defects, 3 , 6 , 7 , 8 the potential impact of paternal exposure on the risk of these malformations remains largely unexplored. 9 , 10
Emerging research suggests that paternal exposure to environmental factors may play a critical role in the origin of health and disease. 11 , 12 , 13 Recent studies have shed light on the importance of the sperm epigenome in transmitting environmental cues to future generations. 11 , 12 , 13 Of particular interest, obesity has emerged as a major healthcare concern worldwide, with its prevalence increasing significantly over the past decade. 14 Men are twice as likely to be obese as women, 15 making it a particular area of interest. Research has linked paternal obesity to various adverse health outcomes in offspring, including an increased risk of birth defects in children born through assisted reproductive technology. 16 , 17 Additionally, paternal obesity may lead to alterations in the sperm epigenome, involving chemical modifications of the DNA, chromatin composition, and the activity of the noncoding RNA activity. 12 , 13 , 18 , 19 These epigenetic modifications, in turn, may contribute to an increased risk of malformations in the offspring. 9
Although studies have shown that acquired obesity in rats can lead to an increased risk of kidney damage in offspring, 20 the impact of paternal obesity on the development of congenital urogenital anomalies in humans remains uncertain. This presents a significant gap in the current literature and highlights the need for further investigation. Therefore, the aim of our study is to explore the potential association between paternal obesity and urogenital congenital malformations in offspring.
2. METHODS
2.1. Study design
This study was a case–control study designed to investigate the association between paternal obesity and the risk of congenital urogenital abnormalities. This study is reported according to the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) guidelines. 21
2.2. Ethical considerations
Ethical approval was obtained from the ethics committee of Notre Dame des Secours—University Hospital. Informed consent was obtained from all participants, and their privacy and confidentiality were protected.
2.3. Setting
The study was conducted at Notre Dame des Secours—University Hospital (CHUNDS), Jbeil, Lebanon in December 2022, where cases and controls were selected from the hospital's database. Phone interviews were then conducted with the parents who agreed to participate.
2.4. Participants
Two hundred eighty files were screened, and after applying inclusion and exclusion criteria, as well as removing files where parents were unable or unwilling to provide data, the remaining number of files was 179. Thus, the study sample consisted of 179 neonates, including 91 cases with congenital urogenital abnormalities and 88 controls without these abnormalities. All neonates were born at term, and their mothers were under 30 years of age at the time of conception (Figure 1A,B).
FIGURE 1.
The study design and flow diagram for the present case–control study. (A) A case–control study was conducted to investigate the association between paternal body mass index (BMI) and the risk of adverse birth outcomes. The study included 179 newborns, with cases (n = 91) and controls (n = 88) selected from the Notre Dame des Secours–University hospital database. Exclusion criteria were applied to ensure that the study population was free of maternal obesity, infections during pregnancy, chronic diseases, prematurity, growth retardation, assisted reproductive technologies for conception, substance abuse, down syndrome, and other malformations. Data were collected through phone interviews, medical records, and questionnaires. Paternal BMI was calculated and used as the exposure variable in the analysis. The study design was approved by the relevant institutional review board, and all participants provided informed consent. (B) Flow diagram illustrating the screening process and participant selection for the study. Out of the initial 280 files screened, 131 cases and 149 controls were identified. Following the application of inclusion and exclusion criteria, as well as removal of files with missing parental data or refusal to participate (40 cases and 61 controls), the final sample comprised 179 files. This sample consisted of 91 neonates with congenital urogenital abnormalities and 88 neonates without these abnormalities.
2.4.1. Case definition
Congenital anomalies included in this sample were inguinal hernia, hypospadias, bilateral or right/left orchidopexia, testicular torsion, ureteral reimplantation, cryptorchidism, renal agenesis, ectopic kidney, bilateral inguinal hernia with orchidopexia, and hydronephrosis. Cases were defined as newborns with at least one of these abnormalities.
2.4.2. Control selection
Controls were randomly selected from the CHUNDS hospital database through a randomized software program. Controls were selected based on the absence of congenital urogenital abnormalities and the same inclusion and exclusion criteria used for cases.
2.4.3. Exclusion criteria
This study excluded records of neonates with maternal obesity (defined as a body mass index (BMI) > 30 kg/m2), maternal infections during pregnancy, chronic maternal diseases, prematurity, growth retardation, usage of assisted reproductive technologies for conception, substance abuse during pregnancy, children with down syndrome, and the presence of other malformations. 2 , 5 , 22 A visual representation of the study design can be seen in Figure 1.
2.5. Data collection
The investigators collected data through structured phone interviews using a questionnaire composed of three sections tailored to assess the studied risk factors, inclusion and exclusion criteria for the study. The sections included information about the child, mother, and father, and the questionnaire covered a range of factors such as age, BMI, smoking status, alcohol consumption, drug use, and exposure to environmental toxins. These factors were assessed both 5 years prior to conception and at the time of conception. To confirm the diagnosis of congenital urogenital abnormalities and exclude newborns with other malformations or maternal conditions that could affect the risk of these abnormalities, medical records were also utilized.
2.6. Variables
2.6.1. BMI
The main exposure of interest in this study was paternal obesity, which was measured by BMI. We calculated BMI using retrospective self‐reported weight 5 years before conception and at the time of conception, along with self‐reported height, using the following formula: BMI = body weight (kg)/ height2 (m2). According to the US Centers for Disease Control and Prevention (CDC), a BMI below 18.5 indicates underweight, while a BMI between 18.5 and <25 is considered within the healthy weight range. Individuals with a BMI between 25.0 and <30 are classified as overweight, and those with a BMI of 30.0 or higher are categorized as obese. Obesity is further divided into classes: Class I includes individuals with a BMI between 30 and <35, Class II comprises those with a BMI between 35 and <40, and Class III includes individuals with a BMI of 40 or higher. 23
2.6.2. Lifestyle factors
Participants were asked to recall parental age, smoking status, alcohol consumption, substance abuse, and exposure to environmental toxins around the time of conception. Smoking was measured by estimating the number of cigarettes consumed per day and the duration of the smoking habit in years, which were multiplied to create an estimate in pack‐years. We grouped the estimates as follows: light (1–20 cig/day or box/day), moderate (21–40 cig/day or 2 box/day), and heavy (> 41 cig/day or > 3 box/day). 24 Research has shown that this method of self‐reported measure of smoking is valid and accurate. 25 In parallel, alcohol consumption was assessed using quantity‐frequency measures, which aimed to evaluate the frequency per week and volume of alcohol consumed. 26 This approach is suggested to yield the most dependable and authentic evaluation of the alcohol consumption in population surveys. 26 Furthermore, substance abuse was reported by the participant up to 3 months before conception, while exposure to environmental toxins was assessed by asking about exposure to paint, pesticides, or other toxins in the workspace.
2.7. Sample size calculation
The main predictor variable is the BMI of father at the time of conception. Hence, a logistic regression model was performed. The G‐Power 3.1.9.7 program was used to compute required sample size with the given and power as 80%.
Assuming that the father's BMI at the time of conception was one standard deviation above the mean, the probability of the child having a urogenital condition was estimated to be 20%. The expected R‐squared, which measures the amount of variability in the father's BMI at conception accounted for by covariates, was assumed to be low at 0.094. It was also assumed that the distribution of the father's BMI at conception followed a normal distribution. The odds ratio (OR) was calculated as the odds of the child having a urogenital condition in the exposed group (when the father's BMI at conception was greater than normal weight) divided by the odds in the non‐exposed group (when the father's BMI at conception was in the normal weight category). The OR was estimated to be 1.6. Based on this information, a sample size of 179 was estimated for a one‐tailed test in the logistic regression analysis.
2.8. Statistical analysis
SPSS version 25 was used for statistical analysis. The application of the Kolmogorov–Smirnov test showed that the continuous variables in the dataset did not follow a normal distribution. Therefore, continuous variables were reported as median (minimum–maximum), and categorical variables were reported as number (%). Continuous variables were compared using the Mann–Whitney U‐test, and the Chi‐square test was utilized to compare categorical variables between the case group and the control. Univariate analysis served as a foundational step in assessing the relationship of each predictor variable with the outcome variable. Hence, each paternal and maternal factor was analyzed separately in the univariate analysis, and OR and their corresponding 95% confidence intervals (CI) were reported. Subsequently, for binary logistic regression analysis, only those factors that showed statistical significance in the univariate analysis were included. In the binary logistic regression conducted, the relationship between the selected parental factors and the presence of a urogenital condition was investigated, with the latter serving as the dependent variable. The parental factors were examined as independent variables to discern any associations with the occurrence of the urogenital condition. Statistical significance was considered when p < 0.05.
3. RESULTS
3.1. Prevalence of congenital urogenital diseases in the study population
A total of 179 patients were included in the analysis, with 88 patients (49%) classified as controls, and 91 patients (51%) classified as cases (Table 1): inguinal hernia (52%), hypospadias (27%), bilateral or left/right orchidopexy (7%), testicular torsion (1%), ureteral reimplantation (4%), cryptorchidism (3%), right or left renal agenesis (2%), ectopic kidney (1%), bilateral orchidopexy with hernia (1%), and hydronephrosis (1%).
TABLE 1.
Proportion of urogenital diseases in study population.
| N (%) | |
|---|---|
| Control | 88/179 (49.2) |
| Case | 91/179 (50.8) |
| Inguinal Hernia | 47/91 (51.6) |
| Hypospadias | 25/91 (27.5) |
| Bilateral orchidopexy, right, left | 6/91 (6.6) |
| Testicular torsion | 1/91 (1.1) |
| Left ureteral reimplantation, pyeloplasty, according to duplay | 4/91 (4.4) |
| Crytochidism | 3/91 (3.3) |
| Right renal agenesis, left renal agenesis | 2/91 (2.2) |
| Ectopic kidney | 1/91 (1.1) |
| Bilateral orchidopexy + hernia | 1/91 (1.1) |
| Hydronephrosis | 1/91 (1.1) |
Note: Results are expressed as ratio (percentage).
3.2. Characteristics of the study population
There were statistically significant higher paternal BMI among cases as compared to controls 5 years prior to conception (case: median: 27.5 (minimum–maximum: 20.1–41), control: 24.5 (19.6–35.1); (p < 0.0001)) and at the time of conception (case: 27.7 (20.1–43), control: 24.8 (19.6–40.74); (p < 0.0001)). Comparison of other factors at the time of conception, including parental age at conception, substance abuse, smoking, alcohol consumption, and exposure to pesticides for both the father and mother, revealed no significant disparity between the case and control groups (p > 0.05). Additionally, there was no significant difference found between the groups in paternal urogenital history, history of infections, or maternal diet during pregnancy, folic acid consumption, and multivitamin use during pregnancy (p > 0.05) (Table 2). Therefore, these variables were not included in the subsequent adjusted logistic regression.
TABLE 2.
Characteristics of cases and controls and a comparison between two groups.
| Case | Control | p‐value | ||
|---|---|---|---|---|
| Paternal characteristics | Age of the father (years) | 35 (27–52) | 35 (25–50) | 0.288 |
| BMI of the father 5 years before conception (kg/m2) | 27.50 (20.1–41) | 24.55 (19.6–35.1) | <0.0001 | |
| Underweight | 0/91 (0) | 0/88 (0) | <0.0001 | |
| Normal weight | 23/91 (25.3) | 50/88 (56.8) | ||
| Overweight | 48/91 (52.7) | 31/88 (35.2) | ||
| Obesity Class I | 14/91 (15.4) | 6/88 (6.8) | ||
| Obesity Class II | 5/91 (5.5) | 1/88 (1.1) | ||
| Obesity Class III | 1/91 (1.1) | 0/88 (0) | ||
| BMI of the father at the time of the conception (kg/m2) | 27.68 (20.1–43) | 24.85 (19.60–40.7) | <0.0001 | |
| Underweight | 0/91 (0) | 0/88 (0) | <0.0001 | |
| Normal weight | 16/91 (17.6) | 46/88 (52.3) | ||
| Overweight | 51/91 (56) | 33/88 (37.5) | ||
| Obesity Class I | 18/91 (19.8) | 6/88 (6.8) | ||
| Obesity Class II | 4/91 (4.4) | 2/88 (2.3) | ||
| Obesity Class III | 2/91 (2.2) | 1/88 (1.1) | ||
| Father underwent chronic treatment (Yes, %) | 20/91 (22) | 19/88 (21.6) | 1 | |
| Urogenital history of the father (No, %) | 79/91 (86.8) | 83/88 (94.3) | 0.125 | |
| Father suffering from infection (No, %) | 87/91 (95.6) | 87/88 (98.9) | 0.368 | |
| Smoking father (Yes, %) | 54/91 (59.3) | 43/88 (48.9) | 0.179 | |
| Alcohol consumption of the father (Yes, %) | 48/91 (52.7) | 35/88 (39.8) | 0.099 | |
| Substance abuse of the father (Yes, %) | 1/91 (1.1) | 0/88 (0) | 1 | |
| Father working with products like painting (Yes, %) | 8/91 (8.8) | 2/88 (2.3) | 0.1 | |
| Father working with products like pesticides (Yes, %) | 9/91 (9.9) | 3/88 (3.4) | 0.133 | |
| Maternal characteristics | Age of mothers (years) | 30 (36–22) | 30 (34–21) | 0.362 |
| BMI of mothers at the time of the conception (kg/m2) | 23.40 (29.41–16.40) | 22.73 (28.72–17.70) | 0.072 | |
| Underweight | 5/91 (5.5) | 4/88 (4.5) | 0.255 | |
| Normal weight | 53/91 (58.2) | 62/88 (70.5) | ||
| Overweight | 33/91 (36.3) | 22/88 (25) | ||
| Obesity Class I | 0/91 (0) | 0/88 (0) | ||
| Obesity Class II | 0/91 (0) | 0/88 (0) | ||
| Obesity Class III | 0/91 (0) | 0/88 (0) | ||
| Smoker mothers (Yes, %) | 27/91 (29.7) | 24/88 (27.3) | 0.743 | |
| Alcohol consumption of mothers (Yes, %) | 30/91 (33) | 19/88 (21.6) | 0.096 | |
| Substance abuse of mothers (Yes, %) | 0/91 (0) | 1/88 (1.1) | 0.492 | |
| Mothers working with products like painting (Yes, %) | 0/91 (0) | 0/88 (0) | – | |
| Mothers working with products like pesticides (Yes, %) | 1/91 (1.1) | 1/88 (1.1) | 1 | |
| Mother underwent a diet during pregnancy (Yes, %) | 86/91 (94.5) | 88/88 (100) | 0.059 | |
| Folic acid consumption during pregnancy by the mother (Yes, %) | 78/91 (85.7) | 72/88 (81.8) | 0.545 | |
| Multivitamin consumption during pregnancy by the mother (Yes, %) | 87/91 (95.6) | 87/88 (98.9) | 0.368 | |
Notes: Results are expressed as median (minimum–maximum) for non‐normally distributed continuous variables and as ratio (percentage) for categorical variables. Statistical significance is considered when p < 0.05.
Abbreviation: BMI, Body mass index.
3.3. Dose–response analysis of paternal body mass index on offspring urogenital conditions 5 years before conception and at conception
3.3.1. 5 Years prior to conception
The analysis revealed a possible dose–response pattern between paternal BMI and the risk of offspring urogenital conditions. Overweight fathers exhibited a more than threefold increased risk of offspring congenital malformations (OR = 3.36, 95% CI = 1.72–6.57) compared to normal‐weight fathers. Moreover, obese Class I fathers demonstrated a significantly elevated risk, with odds approximately 5.07 times higher (OR = 5.07, 95% CI = 1.72–14.88) compared to normal‐weight fathers. The risk further escalated for obese Class II fathers, showing a substantial tenfold increase in the odds of offspring urogenital conditions (OR = 10.87, 95% CI = 1.20–98.40) compared to normal‐weight fathers. Although not statistically significant, obese Class III fathers also displayed an elevated risk, with an OR of e21.979 (95% CI = 0.0001–…) compared to normal‐weight fathers (Table 3).
TABLE 3.
Logistic regression on the effect of paternal BMI on congenital urogenital anomalies.
| OR | 95% CI | p‐value | ||
|---|---|---|---|---|
| Paternal BMI at 5 years before conception (Model 1) | ||||
| Normal weight | Reference | |||
| Overweight | 3.36 | 1.72–6.57 | <0.001 | |
| Obese class I | 5.07 | 1.72–14.88 | 0.003 | |
| Obese class II | 10.87 | 1.20–98.40 | 0.034 | |
| Obese class III |
|
0.0001–… | 1.000 | |
| Paternal BMI at conception (Model 2) | ||||
| Normal weight | Reference | |||
| Overweight | 4.44 | 2.16–9.10 | <0.001 | |
| Obese class I | 8.62 | 2.91–25.52 | <0.001 | |
| Obese class II | 5.75 | 0.96–34.44 | 0.055 | |
| Obese class III | 5.75 | 0.48–67.77 | 0.165 | |
Abbreviations: BMI, Body mass index; CI, confidence interval; OR, odds ratios.
3.3.2. At the time of conception
At the time of conception, a possible dose–response relationship persisted between paternal BMI and the risk of offspring urogenital conditions. Overweight fathers displayed a heightened risk of offspring congenital malformations, with an OR of 4.44 (95% CI = 2.1–9.1) compared to normal‐weight fathers. Similarly, obese Class I fathers exhibited a significant increase in risk, with odds approximately eight times higher (OR = 8.62, 95% CI = 2.91–25.52) compared to normal‐weight fathers. Moreover, obese Class II fathers showed a substantial 5.75 times higher odds (OR = 5.75, 95% CI = 0.96–34.44) of having offspring with urogenital conditions compared to normal‐weight fathers. Although the association for obese Class III fathers did not reach statistical significance, there was a trend indicating elevated risk, with an OR of 5.75 (95% CI = 0.48–67.77) compared to normal‐weight fathers (Table 3).
3.4. Comparison of father's body mass index before and during conception in urogenital conditions
The BMI of fathers was compared 5 years before conception and at the time of conception among different types of urogenital conditions. The results are presented in Table 4. We found no significant difference in the BMI values of fathers 5 years before conception (p = 0.76) and at the time of conception (p = 0.98) among the different groups of urogenital conditions.
TABLE 4.
Factors associated with specific types of congenital urogenital diseases in the study population.
| BMI of father 5 years before conception (kg/m2) | BMI of father at the time of conception (kg/m2) | |
|---|---|---|
| Inguinal hernia (n = 47) | 26.49 (20.10–41) | 27.20 (20.10–41) |
| Hypospadias (n = 25) | 26.90 (21.10–39.10) | 27.76 (21.10–43) |
| Bilateral orchidopexy, right, left (n = 6) | 28.10 (27.70–35.10) | 27.80 (26.20–35.10) |
| Testicular torsion (n = 1) | 24.8 | 24.8 |
| Left ureteral reimplantation, pyeloplasty, according to duplay (n = 4) | 29.80 (24.50–31.30) | 29.80 (24.50–31.90) |
| Crytochidism (n = 3) | 29.40 (22.90–31.30) | 31.30 (26.10–32) |
| Right renal agenesis, left renal agenesis (n = 2) | 24.30 (24.20–24.40) | 26.55 (26–27.10) |
| Ectopic kidney (n = 1) | 26.79 | 26 |
| Bilateral orchidopexy + hernia (n = 1) | 28.4 | 28.4 |
| Hydronephrosis (n = 1) | 24.45 | 25.27 |
| p‐Value | 0.692 | 0.982 |
Notes: Results are expressed as median (minimum–maximum) for non‐normally distributed continuous variables. Statistical significance is considered when p < 0.05.
Abbreviation: BMI, Body mass index.
4. DISCUSSION
Results of this case–control study suggest that paternal overweight and obesity, whether 5 years prior to conception or at the time of conception, were associated with increased risk of offspring urogenital conditions, in general and for each specific type of urogenital condition, compared to those in the normal BMI range. Of particular interest, the results at 5 years prior to conception and at the time of conception showed a potential dose–response relationship between paternal BMI and the risk of offspring urogenital conditions. For example, in the analysis conducted 5 years before conception, there was a gradual increase in the risk of offspring urogenital conditions with higher paternal BMI, as evidenced by the elevated OR observed for overweight, obese Class I, and obese Class II fathers in comparison to normal‐weight fathers. Additionally, although not statistically significant, obese Class III fathers also exhibited an increased risk, hinting at a potential dose–response trend. Similarly, at the time of conception, a consistent pattern emerged, with overweight and obese Class I and II fathers demonstrating notably heightened risks of offspring urogenital conditions compared to normal‐weight fathers, thus suggesting a dose–response relationship. These findings highlight the potential role of paternal BMI in assessing offspring urogenital condition risks, guiding targeted interventional studies. As global obesity rates increase, 15 they stress the importance of preventive public health measures for reproductive‐age individuals. Prioritizing preconception health can potentially reduce offspring urogenital condition risks for couples planning pregnancy. Moreover, the results prompt further research into mechanistic pathways, providing opportunities for innovative studies.
When interpreting the results, it is crucial to take into account the various limitations of this study. First, the retrospective nature of the study limits its validity. 27 Second, the reliance on self‐reported data may have introduced recall bias or social desirability bias, potentially affecting the accuracy of the results. 28 , 29 , 30 Thus, it is important to note that recalled weight may vary significantly at the individual level, even if it is similar to the assessed population mean. Therefore, caution must be exercised when using recalled weight. 30 As well as substance abuse and environmental exposure to chemicals that may often be underreported. 28 , 29 To mitigate potential recall bias, future research should consider validating recalled weights with more objective measures, such as medical records or contemporaneous measurements, where feasible. For example, recall bias may have led to an overestimation of the observed associations, particularly if individuals with offspring urogenital conditions were more likely to accurately recall their weight status prior to conception. 31 This could result in inflated OR. Furthermore, residual confounding remains a concern. For instance, incomplete or inaccurate reporting of paternal physical activity levels at the time of conception could lead to residual confounding, influencing the observed associations. 32 Therefore, it is essential for future studies to address these potential biases to enhance the validity and reliability of the findings.
Our study results are consistent with earlier studies suggesting the implication of paternal risk factors in the development of birth defects including urogenital anomalies, anorectal malformations, cardiac malformations, and neural tube defects. 9 , 33 , 34 For instance, a previous meta‐analysis grouping 5,217 cases claimed that paternal age was associated with the development of urogenital congenital anomalies. 34 Another meta‐analysis using 552 studies revealed a link between paternal exposure to pesticides and hypospadias. 35 However, this study is the first to specifically assess the role of paternal obesity in the development of urogenital congenital anomalies. Nevertheless, other lifestyle risk factors showed no significant association with urogenital congenital anomalies in this study.
One potential explanation for the findings could be the role of epigenetics in transmitting paternal risk factors to offspring. 36 , 37 The concept of non‐genetic inheritance of acquired phenotypes suggests that environmental cues can affect the molecular information carried by spermatozoa. 11 In this context, various studies suggest that paternal obesity may alter the sperm epigenome, which could have negative effects on the health of future generations. 13 , 19 Epigenetic modifications, including chemical modifications of DNA and histones, as well as noncoding RNA activity in spermatozoa, are susceptible to obesity. 13 Studies on human sperm have shown that obesity affects the global DNA methylation/hydroxymethylation status, 12 sperm DNA methylation at specific genomic regions, 38 and the expression of several ncRNAs in spermatozoa. 18 Epididymal microRNAs regulate gene networks involved in epididymis and gamete maturation, and alterations in their expression have been observed in spermatozoa from obese men. 39 , 40 , 41 , 42 In this context, a study in male mice has shown that a Western diet for several generations enhances fat mass and metabolic diseases, and sperm RNAs are sufficient to establish the epigenetic inheritance of paternal acquired obesity. 11
Thus, our findings hold relevant clinical implications for the management and prevention of urogenital congenital anomalies. Specifically, the results suggest that screening and management of paternal obesity may be a relevant factor in minimizing the risk of urogenital congenital anomalies. Future longitudinal research on larger samples is necessary to validate these findings and further examine the potential role of epigenetics in the transmission of paternal risk factors to offspring.
5. CONCLUSION
In conclusion, this study provides support for an association between paternal overweight and obesity and the risk of urogenital congenital anomalies in offspring. The results suggest that paternal factors could play a role in the genesis of these anomalies and highlight the importance of managing paternal obesity in order to optimize offspring health. Nevertheless, further research is necessary to confirm these findings and explore the potential mechanisms underlying the association between paternal obesity and urogenital congenital anomalies.
AUTHOR CONTRIBUTIONS
Substantial contributions to conception and design: Mariella El Achkar, Marie‐Claude Fadous Khalife, Georges Raad. Data acquisition: Mariella El Achkar, Carole Ghadban, Elie Ghadban, Toufic Awad. Data interpretation: Mariella El Achkar, Zalihe Yarkiner, Valerie Grandjean, Marie‐Claude Fadous Khalife, Georges Raad. Drafting the manuscript: Mariella El Achkar, Carole Ghadban, Zalihe Yarkiner, Valerie Grandjean, Marie‐Claude Fadous Khalife, Georges Raad. Revising manuscript critically for important intellectual content: All authors. Final approval of the manuscript: All authors.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
FUNDING INFORMATION
This study did not receive any external funding.
Achkar ME, Atieh O, Ghadban C, et al. Preconceptional paternal obesity may increase the risk of congenital urogenital anomalies in offspring: A case–control study. Andrology. 2025;13:45–54. 10.1111/andr.13673
Georges Raad and Marie‐Claude Fadous Khalife are co‐last authors and contributed equally to this work.
DATA AVAILABILITY STATEMENT
Data are available from the authors upon request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data are available from the authors upon request.