Weight Loss as Therapeutic Option to Restore Fertility in Obese Men: A Meta-Analytic Study

Abstract

Purpose

Weight loss has been shown to significantly elevate testosterone serum levels, though the impact on semen analysis parameters and fertility remains incompletely understood. The objective of this study was to examine the influence of body weight loss on semen parameters in obese men.

Materials and Methods

A meta-analysis was performed that included clinical trials in which a semen analysis before and after weight loss was evaluated. All strategies potentially available for weight loss were considered eligible. The primary outcome was the comparison of conventional semen analysis parameters before and after weight loss.

Results

Twelve studies were considered including 345 subjects (mean age 37.6±7.9 years; mean baseline body mass index 45.4±6.0 kg/m²). Weight loss resulted in a significant increase of sperm concentration (effect size 0.495, standard error 0.251 [0.003, 0.986], p=0.049) and progressive motility (effect size 0.567, standard error 0.372 [0.370, 0.764], p<0.001). Moreover, a significant decrease of sperm DNA fragmentation index after weight loss (effect size −0.689, standard error 0.278 [−1.123, −0.255], p=0.002) was observed.

Conclusions

This meta-analytic analysis confirmed that body weight loss may improve qualitative and quantitative sperm characteristics providing evidence for suggesting weight loss to male partners with obesity and semen analysis alteration in couples attempting conception.

INTRODUCTION

The unfavorable effect of overweight and obesity on female fertility is well documented either when spontaneous [1,2,3] or when assisted reproductive-derived pregnancies have been considered [4,5]. Accordingly, obesity has been reported as the most important factor related to anovulatory infertility [6]. In line with this evidence, guidelines from the European Society of Human Reproduction and Embryology strongly recommend a healthy diet and regular exercise, supported by behavioral therapy in overweight and obese women with unexpected infertility [7]. Despite this evidence a clear body mass index (BMI) threshold to suggest in favor or against assisted reproduction still does not exist, although several programs and/or national health systems regulations suggest losing weight before starting these procedures [8].

Obesity plays a well-documented negative impact on male sexual function due to its association with vascular disease and age-related testosterone (T) declined [9,10,11]. Despite this evidence, the role of obesity on male reproduction has not been completely clarified. Available meta-analyses produced conflicting results [12,13]. One of the main limitations of these studies deals with the high heterogeneity derived from the use of different criteria for semen analysis [14]. In order to overcome these pitfalls and obtain a more homogenous population, we recently performed a new systematic review of the literature, including only those papers using WHO 2010 criteria for semen analysis [14]. Our data indeed show, for the first time, a negative impact of body weight excess on male fertility in terms of semen analysis [14]. In addition, in this analysis, we highlighted, for the first time, that just a slight excess of body weight is associated with worse semen parameters, at least when total sperm count and progressive sperm motility were considered.

Regardless of the aforementioned evidence, the real impact of weight loss on male fertility and semen analysis parameters is not completely clarified so far. The aim of this study was to perform a systematic review and meta-analysis of available trials on the effect of body weight loss on semen parameters in obese men, considering all potential available therapeutic approaches.

A large body of evidence has clarified that the negative consequences of obesity on male fertility seem to be potentially reversible since weight loss could restore physiological testicular function. Accordingly, several studies have documented that weight loss significantly improves sexual function [15,16,17], and T circulating levels [18] in men. Available guidelines on age-related T deficiency (also called late onset hypogonadism) strongly recommend weight management strategies based on lifestyle modifications including both regular physical exercise and well-balanced diet. In this context, a lifestyle change in individuals with obesity must reverse the chronic uncoupling of energy intake and energy expenditure that leads to excess weight [19]. Alongside nutritional treatment, additional options include medications that improve underlying mediators of obesity-related complications, such as treatment with glucagon-like peptide-1 receptor (GLP1R) agonists. These drugs are more recently introduced in clinical practice, with interesting evidence about their efficacy on weight loss [20].

This study was designed to evaluate the influence of body weight loss on semen parameters in obese men.

MATERIALS AND METHODS

This meta-analysis was performed in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and a priori registered in the International prospective register of systematic reviews (PROSPERO) database (CRD42023434703).

1. Search strategy

The literature search was performed using the following search ((“weight loss”[All Fields] OR “diet”[All Fields] OR “bariatric surgery”[All Fields] OR “metabolic surgery”[All Fields]) AND “semen analysis”[All Fields]) OR “male fertility”[All Fields]. Three datasets were queried, i.e. Medline, Embase, and Cochrane library.

The literature search was performed until July 31st, 2023. Only English-language articles including human participants were considered.

The identification of relevant studies was performed independently by two authors (D.S., C.G.), and conflicts were resolved a third investigator (G.C.). The Endnote software (Version X9.2; Clarivate Analytics (US) LLC) was used for literature management and duplication filtration and removal.

2. Study selection

The following inclusion criteria were considered: (1) prospective and retrospective design, (2) in which men (3) underwent any strategy available for weight loss, and (4) performed a semen analysis before and after weight loss. Case reports were excluded.

All strategies potentially available for weight loss were considered eligible, such as diet, bariatric-metabolic surgery, and drugs assumption.

3. Outcome and quality assessment

The primary outcome was the comparison of semen parameters, obtained by conventional semen analysis before and after weight loss. Secondary outcomes included effect of weight loss on sperm DNA fragmentation, when available. The therapeutic strategies used to obtain the weight loss were considered as covariates to adjust analysis. Basal BMI and T serum levels, patients’ age, months of follow-up and the change of BMI during follow up were considered as covariates for secondary analyses.

Semen analysis is a complex parameter, and its accurate performance is essential for a thorough understanding of male fertility potential [21]. However, due to the constraints of our study design, we were unable to comprehensively assess the quality of semen analysis conducted in each original work. Therefore, we evaluated whether the semen analysis reported in each study adhered to the WHO manual, noting the manual edition number when available, as an indicator of compliance. Moreover, given that a thorough basic semen examination is fundamental for assessing potential male fertility, the evaluation of semen analysis quality was supplemented by considering the availability of other pertinent andrological sources of information. These may include history collection, physical examination, endocrine assessment, and any additional tests deemed necessary [22].

The quality of trials included was assessed using the Cochrane criteria [23].

4. Statistical analysis

Each study included was considered according to the follow-up duration. If a study considered different follow up after weight loss (i.e., 3, 6, and 12 months), each of them were considered as separated trial.

Heterogeneity in semen parameters was assessed using I² statistics. When low heterogeneity was detected (i.e. I² <60%), the fixed-effect model was applied. Otherwise, the random effect model was applied, because the validity of heterogeneity tests can be limited with a small number of component studies. In addition, in order to avoid possible limitations related to the use of different criteria for semen parameter analysis, standardized means were considered [24].

We used funnel plots and the Begg adjusted rank correlation test to estimate possible publication or disclosure bias [23]. However, undetected biases may still be present because these tests have low statistical power when the number of trials is small.

Continuous data were compared considering the examination before and after weight loss. All semen analysis parameters extracted were analyzed separately.

Meta-regression analyses were performed to test the effect of different covariates on the differences between pre- and post-weight loss. The meta-regression analysis result was synthesized reporting both slope (S) and intercept (I) with appropriate lower and upper limits.

All data were calculated using Comprehensive Meta-analysis Version 2, Biostat.

RESULTS

Out of 8,176 articles only 12 studies were eventually included in the analysis [25,26,27,28,29,30,31,32,33,34,35,36]. Among the 12 studies included, each therapeutic approach to obtain weight loss was analyzed separately. Likewise, if semen analysis was assessed at various follow-up durations, each time-frame interval was treated as a distinct consideration. Consequently, several studies reported different groups, that have been analyzed separately, resulting in a total of 18 trials (Supplement Fig. 1).

The selected studies included 345 subjects with a mean age 37.6±7.9 years. The mean baseline BMI was 45.4±6.0 kg/m², showing a significant decrease during the study (average BMI reduction −6.4±0.1 kg/m², lower limit −6.8, upper limit −6.0, p<0.001). Studies characteristics are reported in Table 1.

Table 1. Characteristics of studies included in the meta-analysis.

First author	Year	Study type	Intervention	Patients number	Age (y)	Inclusion criteria	Control group	Length of follow up (mo)	WHO edition for semen analysis	BMI change after treatment (kg/m2)
Reis [25]	2012	Interventional	Bariatric-metabolic	20	39.3±11.3	NA	Yes, 10 subjects not undergoing surgery	24	WHO 2010	-12.1±5.0
Faure [26]	2014	Observational	Diet	6	31.8±6.3	Abdominal fat >4 as measured by bioimpedance	No	4.6	WHO 2010	-1.2±6.5
Legro [27]	2015	Observational	Bariatric-metabolic	6	35.6±9.5	BMI ≥35.0 kg/m2 and presence of comorbidities or BMI ≥40.0 kg/m2 and aged 20–50 years	No	3, 6, and 12	NR	-5.0±7.0
El Bardisi [28]	2016	Observational	Bariatric-metabolic	46	37.0±6.0	National Institute of Health (NIH) criteria indicating weight loss surgery	No	12	WHO 2010	-22.89 (median)
Samavat [29]	2017	Observational	Bariatric-metabolic	23	45.8±7.4	BMI >40 kg/m2	Yes, 8 subjects not undergoing surgery	6	WHO 2010	-11.1±5.1
Calderón [30]	2019	Observational	Bariatric-metabolic	15	40.0±8.0	BMI >35 kg/m2	No	24	WHO 2010	-18.0±8.5
Carette [31]	2019	Interventional	Bariatric-metabolic	46	38.9±7.9	BMI ≥40 kg/m2 or 35 kg/m2 and, at least one obesity comorbidity	No	12	WHO 2010	12.7 (min, -11.6; max, -13.8)
Wood [32]	2020	Interventional	Bariatric-metabolic	18	39.0±12.9	BMI ≥35.0 kg/m2 and presence of comorbidities or BMI ≥40.0 kg/m2, and aged 20–50 years	Yes, 14 subjects not undergoing surgery	6	WHO 2010	11.6 (median)
Fariello [33]	2021	Interventional	Bariatric-metabolic	15	NR	BMI ≥35.0 kg/m2 and presence of comorbidities or BMI ≥40.0 kg/m2, and aged 20–50 years	No	3, 6, 9, and 12	WHO 2010	-7.6±1.4
Velotti [34]	2021	Observational	Bariatric-metabolic	35	36.4±5.2	Obesity and idiopathic infertility	No	6	WHO 2010	-17.7±6.0
Andersen [36]	2022	Interventional	Diet and GLP1RA	37	41.1±9.7	BMI 32–43 kg/m2	No	2	WHO 2010	-5.0±2.8
La Vignera [35]	2023	Interventional	GLP1RA	35	26.0±6.0	BMI >30 kg/m2	Yes, 40 subjects treated with testosterone	2	WHO 2010	-6.0±2.5

Values are presented as mean±standard deviation.

NA: not applicable, NR: not reported, BMI: body mass index.

Eleven studies reported the WHO manual edition used to perform semen analysis (Table 1), describing the methodology applied and the adherence to the guidelines. On the contrary, one study did not reported the WHO manual edition used to perform semen analysis (Table 1). However, in this study [27], the semen analysis evaluation was completed by a wide andrological work-up [21], useful to improve the accuracy of the analysis performed.

1. Sperm concentration

Fifteen trials reported data on sperm concentration before and after weight loss. Thirteen trials considered weight loss after bariatric surgery, one after diet and one after GLP1R agonist liraglutide administration. The I² was 87.8, p<0.001 suggesting high heterogeneity among the included studies. The funnel plot and Begg adjusted rank correlation test (Kendall’s τ: 0.028; p=0.441) suggested no publication bias. Weight loss led to a substantial increase in sperm concentration, reflecting an overall improvement of approximately 7.6 million/mL (Fig. 1, Supplement Fig. 2A).

Fig. 1. Comprehensive standardized mean difference in each parameter evaluated after weight loss. CI: confidence interval, LL: lower limit, UL: upper limit.

The subgroup analysis performed considering the treatment used confirmed the significant sperm concentration increase, when only bariatric-metabolic surgery was considered (I²=47.6, p=0.028, effect size 0.310, standard error 0.294 [0.124, 0.496], p=0.001) (Supplement Fig. 2B).

Meta-regression analysis performed in the whole sample showed a trend towards a sperm concentration increase as a function of BMI reduction after weight loss (Table 2, Supplement Fig. 3). In order to avoid potential sources of bias, the meta-regression analysis was repeated considering only studies in which the bariatric-metabolic surgery was applied to obtain weight reduction, confirming the direct significant correlation between sperm concentration increase and BMI reduction obtained (Table 2, Supplement Fig. 3).

Table 2. Meta-regression analyses results.

		All studies	Studies applying bariatric-metabolic surgery
Sperm concentration
	BMI at enrollment	S=-0.015 [-0.032, 0.002] p=0.077, I=1.073 [0.207, 1.939], p=0.015	S=-0.015 [-0.032, 0.002] p=0.077, I=1.073 [0.207, 1.939], p=0.015
	BMI reduction	S=0.026 [-0.001, 0.023] p=0.063, I=0.648 [0.231, 1.065], p=0.002	S=0.055 [0.019, 0.092] p=0.002, I=1.180 [0.308, 0.576], p<0.001
	Testosterone serum levels at baseline	S=-0.023 [-0.736, 0.039] p=0.462, I=0.491 [-0.294, 1.276], p=0.220	S=-0.023 [-0.736, 0.039] p=0.462, I=0.491 [-0.294, 1.276], p=0.220
	Follow-up length	S=-0.004 [-0.033, 0.026] p=0.794, I=0.272 [-0.111, 0.655], p=0.163	S=-0.004 [-0.033, 0.026] p=0.794, I=0.272 [-0.111, 0.655], p=0.163
	Patients’ age	S=0.063 [-0.010, 0.135] p=0.092, I=-2.051 [-4.877, 0.776], p=0.155	S=0.063 [-0.010, 0.135] p=0.092, I=-2.051 [-4.877, 0.776], p=0.155
Progressive sperm motility
	BMI at enrollment	S=0.023 [-0.131, 0.177] p=0.770, I=-0.685 [-7.781, 6.410], p=0.850	S=-0.018 [-0.035, 0.001] p=0.245, I=1.336 [0.427, 2.244], p=0.074
	BMI reduction	S=0.038 [-0.027, 0.043] p=0.641, I=0.596 [1.164, 2.054], p=0.039	S=0.038 [0.001, 0.077] p=0.033, I=0.887 [0.253, 1.521], p<0.001
	Testosterone serum levels at baseline	S=-0.049 [-0.124, 0.025] p=0.193, I=0.868 [-0.012, 1.749], p=0.053	S=-0.049 [-0.124, 0.025] p=0.193, I=0.868 [-0.012, 1.749], p=0.053
	Follow-up length	S=-0.023 [-0.070, 0.022] p=0.318, I=0.721 [0.169, 1.273], p=0.010	S=-0.023 [-0.070, 0.022] p=0.318, I=0.721 [0.169, 1.273], p=0.010
	Patients’ age	S=-0.045 [-0.117, 0.028] p=0.227, I=2.054 [-0.782, 4.891], p=0.156	S=-0.045 [-0.117, 0.028] p=0.227, I=2.054 [-0.782, 4.891], p=0.156

Values are presented as standard error.

BMI: body mass index, S: slope, I: intercept.

Other meta-regression analyses showed that the sperm concentration increase after weight reduction was independent to BMI at enrollment, basal total T levels, follow up, and patients’ age (Table 2). The same results were confirmed when only studies on bariatric-metabolic surgery were considered (data not shown).

2. Total sperm number

Nine trials reported the mean total sperm count before and after weight loss, with high heterogeneity (I²=68.6, p=0.001). The funnel plot and Begg adjusted rank correlation test (Kendall’s τ: 0.278; p=0.149) suggested no publication bias. No significant differences between pre- and post-weight loss were observed (Fig. 1, Supplement Fig. 4).

Similarly, the total sperm count did not change after weight loss, when only trials including bariatric surgery were considered (effect size 0.251, standard error 0.232 [−0.110, 0.613], p=0.172).

3. Progressive sperm motility

Eleven trials evaluated progressive sperm motility before and after weight loss. The I² was elevated (92.2; p<0.001). The funnel plot and Begg adjusted rank correlation test (Kendall’s τ: 0.038; p=0.051) suggested no publication bias. A significant sperm progressive motility increase after weight loss was documented when the whole population was considered (Fig. 1, Supplement Fig. 5A).

Similarly to what observed for sperm concentration, sperm progressive motility increase after weight loss was confirmed when only studies related to bariatric-metabolic surgery were analyzed (Supplement Fig. 5B). In line with these data meta-regression analysis considering only trials evaluating bariatric-metabolic surgery, showed a direct relationship between progressive motility increase and BMI reduction (Supplement Fig. 6).

Conversely, the sperm progressive motility increase after weight reduction was not related to basal BMI, total T basal levels, follow up duration, and patients’ age (Table 2). The same results were confirmed when only studies on bariatric-metabolic surgery were considered (data not shown).

4. Total motility

Eleven trials reported the percentage of total motility before and after weight loss, with a reduced heterogeneity (I²=0, p=0.773). The funnel plot and Begg adjusted rank correlation test (Kendall’s τ: 0.236; p=0.156) suggested no publication bias. No significant difference in total sperm motility after weight loss was detected (Fig. 1, Supplement Fig. 7).

Similar results were observed by subgroup analysis, considering only trials applying bariatric-metabolic surgery (effect size −0.073, standard error 0.093 [−0.256, 0.109], p=0.431).

5. Normal sperm morphology

Fifteen trials reported sperm morphology, with a high heterogeneity (I²=81.8, p<0.001). The funnel plot and Begg adjusted rank correlation test (Kendall’s τ: 0.305; p=0.056) suggested no publication bias. No significant changes in sperm morphology after weight loss were seen (effect size 0.411, standard error 0.215 [−0.010, 0.831], p=0.056) (Fig. 1, Supplement Fig. 8).

Similarly, the lack of sperm normal morphology improvement after weight loss was confirmed by subgroup analysis, considering only trials applying bariatric-metabolic surgery (effect size 0.391, standard error 0.223 [−0.046, 0.828], p=0.079).

6. Sperm DNA fragmentation index

Three trials evaluated sperm DNA fragmentation index before and after weight loss with low heterogeneity (I²=29.1, p=0.244). The funnel plot and Begg adjusted rank correlation test (Kendall’s τ: −0.333; p=0.301) suggested no publication bias. Available data showed a significant decrease of DNA fragmentation after weight loss (Fig. 1, Supplement Fig. 9).

DISCUSSION

Here, we report the first comprehensive evidence supporting a putative role of weight loss among therapeutic strategies for male infertility management. Indeed, whether the impaired spermatogenesis is a common finding among obese men, weight reduction improves some of the most relevant semen parameters, such as sperm concentration, progressive motility and sperm DNA fragmentation. Thus, the weight loss improves semen characteristics, both quantitatively and qualitatively, and it should be considered as the first step in the clinical management of obese male patients with infertility.

Studies evaluating the relationship between weight loss and semen analysis mainly consider bariatric-metabolic surgery. Indeed, among 12 studies included in this meta-analysis, only three studies (25.0%) applied a different approach, such as diet (2 studies) or GLP1R agonist (1 study) administration. However, irrespective of the therapeutic approach applied, we report an overall sperm concentration improvement of about 7.6 million/mL. This effect was not statistically significant when only studies applying diet were evaluated, but it is confirmed when either bariatric-metabolic surgery or GLP1R agonists were used. Moreover, this improvement is related to the extent of BMI reduction obtained, while no relationships are detected considering the baseline BMI or the duration of follow up. This result suggests that the greater the weight loss achieved is, the greater is the increase in sperm concentration. On the other side, our results suggest that the beneficial effect of weight loss on semen analysis does not depend to initial impairment of spermatogenesis, as we do not find any correlations with either baseline BMI or pre-treatment T levels which can reflect baseline hypothalamic-pituitary-gonadal axis impairment. Thus, we could speculate that the correlation between weight loss and semen analysis improvement depends mainly on the reduction of body weight. This effect should be carefully considered, as the patients included in the analysis exhibited a variable degree of obesity. Undoubtedly, the excess body weight at baseline could potentially influence the final results observed after intervention. However, which the pathophysiological mechanisms underlie this association is still not completely clarified. A large body of evidence documented that weight loss is associated with an improvement of circulating T levels with both central and peripheral mechanisms [37]. In particular, data derived from animal models have shown that decreasing visceral adiposity through physical exercise can ameliorate meta-inflammation at hypothalamus and testis level resulting in T production increase [38,39,40]. A quantitatively and qualitatively normal spermatogenesis requires high T concentration within the testis [41]. Thus, we could speculate that the sperm concentration improvement after weight loss could be related to the increased hormonal stimulation on spermatogenesis. To better understand this mechanism, we should consider the potential reasons behind the obesity-infertility connection. Indeed, the first mechanism is the expansion of adipose tissue, which could disrupt the hormonal balance, impairing normal testicular function. Second, an increased estrogen serum levels in men with obesity has been suggested, leading to a decrease in T production [42]. In an animal model, increased visceral adiposity was associated with a greater expression of estrogen receptors in the median hypothalamus [39,40]. Although this effect is still debated [43], the negative consequence on testicular function seems to be mediated by negative feedback, inhibiting the pulsatile gonadotropin-releasing hormone release [44]. Accordingly, limited evidence supports the role of SERM in improving T levels and sperm parameters in obese subjects [45,46,47]. Third, insulin resistance and hyperinsulinemia typical of obesity could lead to a reduction in sex-hormone-binding globulin (SHBG) serum levels which are needed for T transportation. In the presence of low SHBG levels, the increase of T bioavailable for aromatization in adipose tissue could occur [48]. Fourth, increased leptin secretion in obesity may also inhibit T production by the Leydig cells [49]. Fifth, adipose tissue produces inflammatory cytokines, which could disrupt normal testicular function, impairing both T production and sperm production and maturation [37,50]. Thus, while weight loss is known to restore normal T production, we cannot rule out other mechanisms behind the increase sperm quantity and quality here comprehensively detected. In particular, weight loss could be related to a reduction in both leptin and pro-inflammatory cytokines, which are known to be abundant in obese men. Evidence available so far are not sufficient to clearly discriminate among potential mechanisms relating weight loss and sperm quantity improvement.

Alongside sperm concentration, we highlight a significant improvement in sperm progressive motility following weight loss. The observed increase in progressive motility exhibits similar characteristics to those detected for sperm concentration. Consequently, we can speculate that weight loss directly influences both sperm quantity and quality. This is further supported by the significant decrease in the sperm DNA fragmentation index after weight loss. However, both total sperm count and total motility remain unaffected by weight loss, suggesting that these parameters may not be accurate variables for measuring the impact of weight loss on male fertility. The degree of improvement in sperm quality appears to be somewhat weaker than that observed in sperm concentration, at least from a statistical standpoint. This discrepancy could be attributed to the relatively low number of studies reporting on these parameters. Given these considerations, future studies should thoroughly investigate the actual extent of sperm quality improvement after weight loss, particularly considering the wealth of evidence suggesting that these parameters significantly impact pregnancy outcomes, especially in the context of assisted reproduction [51,52].

The strict bi-directional correlation between excess body weight and hypogonadism is widely demonstrated [53,54,55], and in this context the weight loss is expected to be efficient in T serum levels raise [56,57]. However, whether the same effect should be expected on the spermatogenetic compartment is largely unclear. Indeed, the literature is still scanty on the topic for several reasons. First, weight loss could be obtained by different approaches, from diet to bariatric-metabolic surgery or GLP1R agonists. These approaches could influence sperm production either directly or indirectly through weight loss. Considering diet, several studies evaluated the positive impact of healthy dietary patterns on the sperm quality, using different healthy eating indexes [58]. A recent systematic review of the literature highlighted that diet modifications may be useful in modulating male fertility [58]. Many hypotheses have been made to explain the association between diet and male fertility, such as the prevention of chronic diseases [59,60], the reduction of inflammatory factors and endothelial dysfunction [61]. Thus, the diet itself could be linked to sperm function and fertility, although the mechanisms are still largely unknown.

It is not possible to determine which is the main effector on semen analysis parameters, e.g. the therapeutic approach itself or the weight loss. Trials evaluating semen analysis parameters after weight loss considered different follow-up duration. Andersen et al [62] demonstrated that the semen parameters improvement after an 8-week-diet was preserved after 52 weeks, suggesting that the beneficial effect of weight loss on male fertility could remain until the weight reduction was maintained. The causes of male infertility are largely unknown, and about 30% of infertile men are still included in the large category of male idiopathic infertility. Thus, whether the sperm alteration in obese men is really related to body weight excess or to still unknown causes could be not defined. With this in mind, obese men with infertility are heterogeneous and the effect of weight loss could lead to different results, depending on the underlying causes of sperm alteration. Besides these limitations several other problems should be taken in account. No information on other parameters which could negatively impact spermatogenesis, such as the loss of mitochondrial membrane potential and high concentrations of reactive oxygen species within the testes was available. Similarly, the impact of weight loss in primary and secondary infertility as well as on pregnancy or live birth rate was not possible due to the lack of information. The vast majority of the data were derived from studies based on bariatric surgery whereas the impact of dieting or use of GLP1 analogs was limited [62].

Several limitations should be recognized. First, no sufficient information related to pregnancy rate or live birth rate was available. Second, the methodologies employed for weight loss and the specific procedures used for semen analysis differed among studies. Indeed, the variability of semen analysis per se should be carefully considered, in particular since these parameters were not controlled in the original study for influential factors, such as age and abstinence time [21]. Moreover, the obesity condition is clearly different among studies included in the meta-analysis, potentially influencing the effect of weight loss on semen analysis. In particular, outcomes related to overweight subjects cannot be evaluated. The observed effects could be driven by the small number of studies detected and included, impeding to analyze whether the semen analysis improvement could be related to other factors other than weight loss, such as alterations in hormones (i.e. like GLP1 or leptin) when drugs were used. Third, the majority of our data derived from bariatric surgery in severely obese patients, and this might not be translatable to non-surgical weight loss in moderately obese men. Thus, our study suggests the necessity for additional investigation on the effects of diet and pharmacological interventions on semen analysis, especially considering that bariatric-metabolic surgery is not a universally accessible, quick, cost-effective, or recommended solution for every obese and infertile man. Finally, the quality of semen analysis conducted in each included study could be deemed a confounding factor. Our meta-analytic approach lacks the ability to assess the impact of semen analysis quality on the final outcome. Nonetheless, all studies included in the analysis have reported the methodology employed for semen analysis, thereby mitigating its potential confounding influence.

CONCLUSIONS

In conclusion, despite all potential challenges in the evaluation of weight loss-related semen analysis improvement, our findings suggest that body weight loss may improve qualitatively and quantitatively semen parameters. Thus, weight loss should be suggested in all male partners suffering by obesity with semen analysis impairment who are attempting conception. Moreover, further studies are also needed to understand specific mechanisms and the effect on fertility outcome induced by weight treatment.

Supplementary Material

Supplementary materials can be found via https://doi.org/10.5534/wjmh.240091.

Supplement Fig. 1

Literature search flow chart.

Supplement Fig. 2

Forest plot showing standardized mean difference in sperm concentration before and after weight loss. (A) All studies and (B) performing subgroup analysis and maintaining studies evaluating bariatric surgery. CI: confidence interval.

Supplement Fig. 3

Meta-regression analysis combining sperm concentration increase after weight loss and body mass index (BMI) reduction, considering all studies. S: slope, I: intercept.

Supplement Fig. 4

Forest plot showing standardized mean difference in total sperm count before and after weight loss. CI: confidence interval.

Supplement Fig. 5

Forest plot showing standardized mean difference in progressive motility before and after weight loss, considering all studies (A) and performing subgroup analysis according to the therapeutic procedure applied to obtain weight loss (B). CI: confidence interval.

Supplement Fig. 6

Meta-regression analysis combining progressive motility increase after weight loss and body mass index (BMI) reduction, considering only trials in which the weight loss was obtained by bariatric-metabolic surgery. S: slope, I: intercept.

Supplement Fig. 7

Forest plot showing standardized mean difference in total motility before and after weight loss. CI: confidence interval.

Supplement Fig. 8

Forest plot showing standardized mean difference in normal morphology before and after weight loss. CI: confidence interval.

Supplement Fig. 9

Forest plot showing standardized mean difference in sperm DNA fragmentation before and after weight loss. CI: confidence interval.