Main causes of pregnancy losses in beef cattle: Systematic review and meta-analysis

Abstract

Embryonic losses in beef cattle are a significant problem in reproduction, as they directly impact the efficiency of the production system and the fertility rates of the herd. The objective of this study was to identify and quantify the main causes of pregnancy losses in beef cattle through a systematic review and meta-analysis. Forty-five relevant studies were included, with a total of 53,876 female cattle, with gestational diagnoses performed between days 28 and 100 of gestation. The main causes identified were hormonal, sanitary, nutritional and management-related, with significant differences in loss rates during pregnancy depending on the phase and cause involved. Early embryonic losses (EEL), predominantly caused by nutritional deficiencies (35%) and hormonal failures (29%), showed the highest rates. In the late embryonic/early fetal (LFL) period, losses related to hormonal (9%), sanitary (10%), nutritional (7%) and management (5%) causes demonstrated an impact on gestational viability. The high heterogeneity between studies, especially in hormonal and Sanitary factors (98%), highlights the complexity and multifactorial nature of pregnancy losses. This study reinforces the need for adequate reproductive, hormonal, nutritional and sanitary management practices to mitigate losses (EEL) and (LFL) by improving reproductive efficiency in breeding systems.

Keywords:
risk factors; early embryonic mortality; fetal loss; reproductive efficiency; systematic review

Introduction

Reproductive efficiency significantly influences the productivity of beef and dairy production systems. Early embryonic loss during the first month of gestation ranges from 48% to 57% (Inskeep and Dailey, 2005; Reese et al., 2020), occurring from the moment of fertilization until approximately day 24–28, before maternal recognition of pregnancy and embryo implantation (Diskin and Morris, 2008; Bazer et al., 2015). Late embryonic loss (days 28–42) coincides with the onset of placental attachment and organogenesis (Perry et al., 2005; Wiltbank et al., 2016), while fetal losses (after day 42) occur less frequently, specifically between 2% and 7% (Santos et al., 2004; Perry et al., 2005; Franco et al., 2020). These gestational losses are multifactorial and involve various factors such as nutritional, hormonal, environmental, genetic, Sanitary, and management (Zobel et al., 2011; Diskin et al., 2011; Lucy et al., 2016). A negative postpartum energy balance compromises embryonic or fetal viability (Diskin et al., 2016), while inadequate progesterone or maternal-embryonic signaling leads to premature corpus luteum lysis and pregnancy loss (Parr et al., 2012). Heat and handling stress, along with infectious diseases such as leptospirosis, brucellosis, bovine viral diarrhea, and infectious bovine rhinotracheitis, are factors that further increase embryonic or fetal losses (Azevedo et al., 2017).

Previous meta-analyses, particularly Reese et al. (2020), have provided important insights into pregnancy loss in beef cattle. However, these studies primarily focused on overall loss rates, without a detailed quantification of specific causal categories and their interaction with gestational stages. Therefore, the present study aimed to expand this approach by systematically classifying pregnancy losses according to their main causes and evaluating their relative contribution during different gestational periods.

Materials and methods

Meta-analysis

This study was based on a meta-analysis of published research investigating the main causes of pregnancy losses in beef cattle. Meta-analysis enables the integration of data from multiple studies, thereby improving the precision of overall estimates and identifying consistent patterns across diverse populations and experimental conditions. However, the reliability of a meta-analysis depends heavily on the rigorous selection of studies, which requires meticulous definition of inclusion criteria, search strategies, and keyword filters to ensure that the studies included are relevant, comparable, and of adequate methodological quality.

In this meta-analysis, pregnancy loss was classified into early embryonic (EEL) and late embryonic/early fetal loss, based on gestational diagnoses generally performed at 30, 60, and 90 days on farms and not strict diagnoses of physiological development of a pregnancy (Pohler et al., 2016; Reese et al., 2020). Although the physiological transition from embryonic to fetal development in cattle occurs around days 42 to 45 of gestation (Bertolini et al., 2007). Thus, for analytical purposes: EEL was defined as conception up to 32 days, covering maternal recognition and initial embryonic differentiation, and LFL as 32–100 days. Most secondary diagnoses are made by ultrasound or PAG testing. This classification reflects the management practices of a commercial herd and ensures methodological consistency across studies.

Search methods to identify studies.

The bibliographic search strategy was defined based on the main concepts in the PICO model: Population, Intervention, Control and outcome, aiming to identify the most relevant studies for the research (Table 1).

Table 1
Population, intervention and outcome search terms used in the systematic review on the main causes of pregnancy losses in beef cattle.

Acronym	Search string
Population	"beef cattle" OR "cattle“ OR "beef cow" OR "cow“ OR "beef heifer“ OR “heifer” OR “bos indicus” OR "bos tauros” OR " primiparous " OR " multiparous "
Intervention	"main causes" OR "progesterone" OR "hormone factors" OR "hormone" OR "nutrient restriction" OR "hemoparasites" OR "vaccination" OR "dietary energy" OR "venereal disease" OR "immune response" OR "immune" OR "heat stress" OR "stress factors" OR "pregnancy associated glycoprotein" OR "mineral supplementation" OR "vitamin supplementation" OR " genetic factors" OR "genetic" OR "management factors" OR "infection" OR "infection factors" OR "nutrition factors" OR "nutrition"
Outcome	"fetal loss" OR "fetal mortality" OR "pregnancy loss" OR "embryo mortality" OR "embryonic loss “OR “abortion“ OR “embryo survival“ OR “fertilization Failure" OR “fertilization“

The study population consisted of pregnant beef cows and heifers. The interventions of interest were the main causes of pregnancy losses in this population and the outcomes of interest were the percentages of the main causes of these losses.

To be considered relevant, studies had to include at least one of the outcomes of interest. Studies that used reproductive biotechnologies such as embryo transfer, twin pregnancies, diagnosis of the first pregnancy after 32 days of gestation or involving dairy animals, and trials with treatments that could blind the success of the study were excluded from the meta-analysis. Additionally, any articles reporting detrimental losses due to treatment (such as induced disease states, severe nutrient restriction, etc.), were excluded from the mean analysis. No language or publication year restrictions were applied; however, only studies that included early pregnancy diagnosis between days 28 and 32 of gestation were considered eligible. A search protocol was developed, and each detection tool was adapted from forms applied in previous studies (Mederos et al., 2012; Canozzi et al., 2017). The protocol was tested before being implemented.

Search methods to identify studies

The search was conducted in January 2024 and updated in July 2024 using three electronic databases: Scopus (Elsevier), Web of Science (Clarivate Analytics) and PubMed (Medline). The search strategy was based on the PICO framework and included combinations of keywords related to population, intervention, and outcomes. Additionally, was validated by manually reviewing the reference lists of two literature reviews on pregnancy loss in beef cattle (Pohler et al., 2016; Franco et al., 2020). All references were exported to Mendeley software Copyright^© 2024 Elsevier Ltd, for organization and removal of duplicates.

Criteria for selecting studies and assessing their relevance

At this stage, potentially relevant studies were screened. Two reviewers independently with expertise in bovine reproduction and systematic reviews evaluated the titles, abstracts, and keywords of all retrieved references. No restrictions regarding language or publication year were applied. If all reviewers answered “no” to one or more evaluation questions, the reference was removed. Any conflicts among reviewers were resolved by agreement; if no agreement was reached, a third reviewer was consulted. Both randomized and non-randomized studies were included in the analysis. Microsoft Excel® was used during all relevant selection steps.

Methodological evaluation and data extraction process

The data extraction form was developed based on previous templates. Manuscripts reporting more than one study were duplicated and data were extracted as separate studies to obtain as much detail as possible. The information extracted from each study was divided into general information (study population, intervention, parameters assessed and outcome data)

Considerations on data collection and processing

For each of the outcomes analyzed, a database was constructed that included different variables important for this meta-analysis: mean, standard error (or other measure of dispersion), p-value, and sample size per experimental group. This pooling of data allowed for accurate estimation and comparison between studies. Only original research determining pregnancy rates in beef cattle was included. Studies that applied treatments to reduce pregnancy losses were excluded to avoid bias in the assessment of natural influencing factors. The mandatory inclusion criteria were: (i) beef cows or heifers; (ii) early pregnancy diagnosis by ultrasound between days 28 and 32, ensuring the pregnancy status of each female cattle; and (iii) detailed information on the timing of pregnancy diagnosis, the subspecies, and the animal category. Given the expected variability among studies, a random effects model was applied, assuming that the differences that occurred were due to both sampling error and variability inherent in management, environment, and herd genetics.

The nonparametric variance was calculated using the following equation:

$V=\frac{\text{P}\times (\text{P}-1)}{n}\times {\text{m}}^{05}$ (1)

Where, V is estimated variance, P, point estimate (for example, the observed pregnancy rate), n, sample size (number of animals evaluated in the specific period), m, number of studies extracted from the same article. Some articles report results from several studies conducted on a single herd. In these cases, the correction represented by the m factor was applied to reduce the weight that could be given to studies from the same herd, thus minimizing bias and avoiding overvaluation of redundant data.

This methodological approach guarantees greater robustness to the analyses and ensures that the results more reliably show the real variations in pregnancy losses in beef cattle.

Quality assessment

Assessment of the quality of the studies included in this meta-analysis was performed using the Cochrane Collaboration's risk of bias tool (Higgins and Green, 2011). This tool is widely used to identify potential biases that may compromise the validity and reliability of the results of individual studies. Regarding detection bias, which assesses the possibility of distortion in the results due to the evaluators' knowledge about the interventions applied, it was found that the risk was low in all included studies. This approach strengthens the robustness of the meta-analysis results, ensuring that the estimates generated accurately reflect the real effects of the variables analyzed.

Meta-analysis

This meta-analysis aimed to identify the main causes of pregnancy loss in beef cattle at different reproductive stages and determine their corresponding incidence rates. These selected studies provided a large amount of quantitative data to estimate pooled proportions of pregnancy loss with corresponding 95% confidence intervals (CI), using a random-effects model. As pregnancy loss was analyzed as a single-group outcome, this approach allowed estimation of its magnitude without the need for control groups. Given the wide diversity in experimental designs, heterogeneity was considered and quantified using the DerSimonian and Laird random-effects model (DerSimonian and Laird, 1986), which accounts for both sampling error and true inter-study variability. Statistical analyses were performed in Stata v14.0 (StataCorp., Texas, USA). For each outcome, pooled proportion estimates and 95% CI were generated and presented in forest plots to visualize individual and overall effects. Heterogeneity was assessed using Cochran's Q test and the I² statistic, interpreted as low (25%), moderate (50%), or high (75%) according to Higgins et al. (2003). In addition, hormonal, Sanitary, nutritional, and management factors were analyzed, where available, assessing their influence on pregnancy losses. This methodological design ensured analytical robustness and facilitated the identification of key causal factors and critical periods affecting reproductive efficiency in non-breeding beef cattle.

Publication bias

Publication bias was assessed graphically (funnel plot) and statistically (Begg correlation and Egger linear regression tests) for each outcome of interest. If there was any tendency for publication bias (P < 0.10), the “trim and fill” method was applied to estimate the degree of bias (Duval and Tweedie, 2000). This method indicates the number of studies that should be included in the analysis to obtain symmetry in the weight distribution graph.

Meta-regression

To explore the sources of heterogeneity observed in the meta-analysis data, a univariate meta-regression was performed using the method of moments approach, as described by Borenstein et al. (2009). Meta-regression allows investigating the influence of moderating variables on the results of the meta-analysis, identifying potential factors that explain the variation among the included studies. The following independent (moderating) variables were explored in the analysis; randomization, Cluster control, confounding factors identified and controlled, year of publication, continent, genetic groups (Bos indicus, Bos taurus), evaluation period (days), sample size, parity of females, causes of losses, (hormonal, nutritional, Sanitary and management), by gestation period, classified into two stages to identify when gestational losses were most significant: early embryonic (from the day of conception to approximately 28 days), late embryonic/early fetal (28 to 100 days of gestation).

Cumulative MA and sensitivity analysis

Cumulative analyses were conducted to evaluate the stability of pregnancy loss estimates as studies were sequentially included over time. Sensitivity analyses were performed to assess whether individual studies influenced the pooled proportion estimates by removing one study at a time and evaluating changes in the overall results.

Results

Study selection

The search identified 696 citations, of which 380 full texts were assessed for eligibility for full-text reading and 350 were excluded after methodological validation and data extraction (Figure 1). Among the remaining manuscripts, five did not report sufficient data for quantitative analysis and. Finally, 45 manuscripts on the causes of embryonic and fetal loss were included in this SR-MA. The descriptive characteristics of the included studies are presented in Table 2, whereas the pooled estimates for each gestational stage and causal category are summarized in Table 3.

Figure 1
Flow diagram indicating the number of abstracts and publications included and excluded in each level of the systematic review on the main causes of pregnancy losses in beef cattle, adapted from Moher et al. (2009). All search results are included in the diagram to allow better understanding of the total number of records found.

Table 2
Descriptive summary of each of the 45 relevant worldwide scientific studies included in the MA and meta-regression to evaluate main causes of pregnancy losses in beef cattle.

Reference	Country	Cause	Loss Period	Parity		Subspecies	No. of Animals
Carter et al. (2008)	Ireland	H	E		N	T	125
Diskin and Sreenan (1980)	Ireland	H	E		N	T	246
Colazo et al. (2004)	Canada	H	E		N, M	T	363
Lopes et al. (2009)	Brazil	H	E		P, M	I	2,667
Maurer and Chenault (1983)	USA	H	E		M	T	314
Meneghetti et al. (2009)	Brazil	H	E		P, M	I	3,260
Northrop et al. (2019)	USA	H	E		N, M	T	984
Sá et al. (2009)	Brazil	H	E		M	I	2,259
Sá et al. (2010)	Brazil	H	E		P	I	1,028
Vieira et al. (2021)	Brazil	H	E		N	T	677
Radigonda et al. (2017)	Brazil	H	E		M	T	150
Larson et al. (2006)	USA	H	E		P, M	T	2,598
Alvarez et al. (2018)	Brazil	H	E, F		M	I	261
Burns et al. (2008)	USA	H	E, F		M	T	676
Couto et al. (2022)	Brazil	H	E, F		M	I	939
Dobbins et al. (2009)	USA	H	E, F		M	T	605
Franco et al. (2018)	Brazil	H	E, F		M	I	1,228
Franco et al. (2020)	Brazil	H	E, F		N, M	T	658
King et al. (1994)	Canadá	H	E, F		N	T	104
Lima et al. (2022)	Brazil	H	E, F		N, M	I	18,462
Magopa et al. (2022)	South Africa	H	E, F		M	T	96
Martinez et al. (2002)	Canada	H	E, F		N	T	503
Oliveira et al. (2020)	USA	H	E, F		M	I	804
Perry et al. (2003)	USA	H	E, F		M	T	273
Perry et al. (2007)	USA	H	E, F		N	T	208
Pessoa et al. (2012)	Brazil	H	E, F		N, M	I	658
Pohler et al. (2013)	USA	H	E, F		N, M	T	38
Pohler et al. (2016)	Brazil	H	E, F		M	I	2,869
Prado et al. (2024)	Brazil	H	E, F		N, M	I	4,926
Sá et al. (2014)	Brazil	H	E, F		N, M	I	664
Ferreira et al. (2016)	Brazil	S	E, F		N	I	604
Ferreira et al. (2018)	Brazil	S	E, F		M	I	692
Andreotti et al. (2010)	Brazil	S	E, F		P	I	1,098
Aono et al. (2013)	Brazil	S	E, F		P, M	I	12,724
Rodriguez et al. (2020)	Argentina	S	E, F		N, M	T	500
Sanhueza et al. (2013)	New Zealand	S	E, F		M	T	814
Willett et al. (1955)	USA	S	E, F		P, M	T	13,490
Ayres et al. (2014)	Brazil	N	E, F		M	I	266
Burke et al. (2001)	USA	N	E, F		M	T	50
Cordeiro et al. (2015)	Brazil	N	E		N, M	I	133
Maturana et al. (2024)	Brazil	N	E, F		M	I	1,722
Beal et al. (1992)	USA	M	E, F		M	T	205
Cooke et al. (2017)	Brazil	M	E, F		M	I	953
Dunne et al. (2000)	USA	M	E		N	T	158
Richardson et al. (2010)	USA	M	E, F		N	T	2,190
45 studies	7 countries						84,242

• H = hormonal, E = Early Embryonic, F = Late Embryonic / Early Fetal, S = Sanitary, N = Nutritional, M = Management, T = Bos taurus, I = Bos indicus, N = Nulliparous, P = Primiparous, M = Multiparous

Table 3
Overall values of the main causes of pregnancy losses in beef cattle.

Pregnancy Loss Stage	Variable / Cause	Number of Studies	Number of Animals	Loss (%)	95%-CI	Heterogeneity (%)
Early Embryonic	Hormonal	13	10.196	29%	0.17 - 0.45	98%
	Nutritional	1	66	35%	0.24 - 0.48
Total / Mean		14	10.262	29%	0.28 - 0.30	98%
Late Embryonic / Early Fetal	Hormonal	17	17.308	9%	0.06 - 0.14	98%
	Sanitary	7	21.367	10%	0.06 - 0.17	98%
	Management	4	3.792	5%	0.01 - 0.17	95%
	Nutritional	3	1.147	7%	0.03 -0.14	17%
Total / Mean		31	43.614	9%	0.89 - 0.91	99.3%
OVERALL TOTAL		45	53.876	13%	0.10-0.18	99%

• H = Hormonal, E = Early Embryonic, F = Late Embryonic / Early Fetal, S = Sanitary, N = Nutritional, M = Management

A total of 84,242 beef females across seven countries. However, a notable limitation lies in the high variability of sample sizes, which ranged from 38 to 18,462 animals per study. Data were analyzed using a random-effects model, in which each study was weighted by the inverse of its variance.

A further consideration is the geographical imbalance in data sources, with approximately 70% of the total sample size derived from Brazilian studies. Additionally, the temporal variation among studies may reflect genetic progress, as well as improvements in reproductive management and nutritional strategies over time, which could influence pregnancy outcomes and contribute to variability in the pooled estimates.

Main causes of pregnancy loss

The meta-analysis results present the main causes of embryonic and fetal losses, along with their respective 95% confidence intervals.

Pregnancy losses due to nutritional causes during the early embryonic stage (n=1) Showed the highest percentage (35%) with a wide confidence interval. Losses associated with to hormonal causes in the early embryonic stage (n=13) showed a pregnancy loss rate of 30% with a high heterogeneity (I² = 98%).

In the late embryonic/early fetal stage, losses attributed to hormonal (n=17), infectious (n=7), nutritional (n=3), and management (n=4) factors showed loss rates of 9%, 10%, 7%, and 5%, respectively. The pooled pregnancy loss estimates and heterogeneity observed across the different causal categories and gestational stages are summarized in Figure 2.

Figure 2
Forest plot summarizing pooled pregnancy loss estimates and heterogeneity across different causal categories and gestational stages in beef cattle.

Early embryonic loss (EEL)

Pregnancy losses in cattle can occur at various stages of gestation, with the early embryonic period being particularly vulnerable. This stage is typically defined as occurring from conception (Day 0) through Day 28–30 of gestation, prior to definitive embryo implantation. Early embryonic loss was evaluated in studies reporting hormonal and nutritional causes. Hormonal causes (n=13; 10,196 animals) showed a pregnancy loss rate of 29% with high heterogeneity (I² = 98%). Nutritional causes were evaluated in one study (n=66 animals), with a reported loss rate of 35% (Figure 2).

Late embryonic losses and early fetal losses (LFL)

Between days 32 and 100, pregnancy diagnoses were made and classified as late embryonic loss/early fetal loss (LFL). Although the embryonic-fetal transition occurs between days 42 and 45, most secondary pregnancy diagnoses are made between days 60 and 100 using ultrasound. Hormonal factors (n=17; 17,308 animals) showed a loss rate of 9% with high heterogeneity (I² = 98%). Infectious causes (n=7; 21,367 animals) showed a loss rate of 10%, also with high heterogeneity (I² = 98%). Management-related factors (n=4; 3,792 animals) showed a loss rate of 5% (I² = 95%). Nutritional causes (n=3; 1,147 animals) showed a loss rate of 7% with low heterogeneity (I² = 17%).

Publication bias

No evidence of publication bias was detected in studies evaluating hormonal, infectious, nutritional, and management-related pregnancy losses. Funnel plot analysis showed symmetrical distribution, and Egger and Begg tests were not significant (p > 0.05) (Figure 3).

Figure 3
Funnel plot assessing potential publication bias in studies evaluating main causes of pregnancy losses in beef cattle.

Discussion

Reese et al. (2020) reported overall pregnancy loss rates based on a large dataset comprising 159 studies. In contrast, the present study provides a more detailed evaluation by categorizing pregnancy losses according to their primary causes and gestational stages, allowing a broader understanding of the mechanisms underlying these losses. While both studies identified early embryonic loss as the most critical period for gestational failure, our findings further emphasize the predominance of hormonal and nutritional factors during this stage. This approach contributes to a more integrative interpretation of reproductive failure in beef cattle systems. Collectively, recent evidence supports the multifactorial nature of pregnancy loss in beef cattle, involving interactions among endocrine, nutritional, environmental, and management-related factors that ultimately affect gestational maintenance (Albertini et al., 2026).

Main causes of early embryonic stage (EEL) losses

Accounting for 29% of the loss cases in this meta-analysis, compared to 9% in late embryonic/early fetal losses. This highlights the importance of endocrine balance for the establishment and maintenance of pregnancy. Previous studies (Perry et al., 2005; Pohler et al., 2016) emphasize the critical role of maternal recognition of pregnancy between days 15-17, when conceptus-derived interferon tau (IFN-τ) specifically from trophoblasts prevents luteolysis and maintains corpus luteum function (Diskin et al., 2011). Therefore, the first 28-30 days represent an important period due to high vulnerability, where embryo viability depends on uterine and luteal hormonal synchrony.

Progesterone (P4), which is initially produced by the corpus luteum and subsequently by the fetoplacental unit, is one of the main hormones that promotes preimplantation and uterine receptivity (Klein, 2015; Bazer et al., 2015; Brooks et al., 2014). In cattle, implantation occurs around days 19–21 of gestation, highlighting the importance of maintaining adequate luteal P4 levels during early gestation. In addition to progesterone, interferon tau (IFN-τ) play a central role in early embryonic survival. The bovine blastocyst begins to produce IFN-τ around day 7, with significant secretion by days 15–16 (Bazer et al., 1997; Spencer et al., 2007). IFN-τ acts on the uterine endometrium to inhibit oxytocin receptors, preventing PGF₂α-induced luteolysis and maintaining corpus luteum function (Meyer et al., 1995; Shirasuna et al., 2015). Failures in IFN-τ signaling may result from low interferon production, delayed conceptus elongation, or reduced uterine receptivity. These alterations impair maternal recognition of pregnancy, leading to luteolysis, decreased progesterone production, and early embryonic loss between days 17 and 24 of gestation (Inskeep and Dailey, 2005; Diskin and Morris, 2008). These findings are consistent with previous reports indicating that early embryonic survival is highly dependent on adequate progesterone concentrations and effective maternal recognition of pregnancy (Diskin and Morris, 2008; Pohler et al., 2016). Furthermore, cows exhibiting lower concentrations of pregnancy-associated glycoproteins (PAGs) on day 28 of gestation have been shown to experience higher rates of late embryonic and early fetal mortality between days 28 and 72, compared to cows with higher PAG levels (Pohler et al., 2013). Recent evidence from beef cattle managed under tropical extensive systems demonstrated that approximately 50% of pregnancy losses occurred before 90 days of gestation, reinforcing the concept that early gestation represents the most vulnerable period for pregnancy maintenance (Albertini et al., 2026).

Another important factor contributing to early embryonic loss was nutritional imbalance, accounting for 35% of cases (95% CI: 24–48%; n=66). Periconceptional alterations critically affect embryo viability. Negative energy balance in high-producing cows decreases fertility and increases early loss due to decreased dry matter intake and postpartum energy deficits (Parr et al., 2015). Also, accelerated hepatic metabolism in these cows increases progesterone clearance, which affects corpus luteum function and uterine receptivity (Smith et al., 2022). Furthermore, abrupt changes in diet or feed quality can alter the uterine environment, so adequate nutrition is recommended, avoiding sudden changes or alterations in diet, and minimizing hormonal fluctuations (Diskin et al., 2016).

Nutritional interventions, such as sunflower seed supplementation, have been shown to increase cholesterol availability and enhance progesterone synthesis. Progesterone plays a pivotal role in pregnancy maintenance by inhibiting uterine contractions, modulating cervical tone, stimulating uterine gland secretions (Reece, 2006), and promoting endometrial changes that support embryonic development (Noakes, 1991). Overall, the evidence suggests that achieving balanced nutrition, avoiding both deficiencies and excesses, is essential for optimizing early embryonic survival. Nutritional programs tailored to the physiological status of the animal and adapted to specific production systems can significantly contribute to reducing reproductive losses. Similarly, previous studies have demonstrated that nutritional status during the periconceptional period plays a critical role in embryo development and uterine environment, directly influencing pregnancy success rates.

Major causes of late embryonic/early fetal (LFL) stage Losses

Hormonal imbalances play a very important role in fetal viability, as progesterone is essential for establishing and maintaining pregnancy (Lonergan et al., 2016). During this stage, it is crucial because implantation is completed and fetal development and growth begin, so hormonal production is crucial. Stress in bovine females can increase cortisol concentrations, altering endocrine balance and compromising fetal viability (Dobson et al., 2001). In this meta-analysis, hormonal causes explained an average of 9% of fetal losses, highlighting its clinical and productive importance. Progesterone remains essential and vital for placental function and uterine homeostasis; alterations in its synthesis, metabolism, or receptor sensitivity can alter or affect vascularization and histotroph production, increasing fetal mortality (Pohler et al., 2016; Wiltbank et al., 2016). Similarly, imbalances in estrogen or prostaglandin can induce premature secretion of PGF₂α and lysis of the corpus luteum, leading to pregnancy termination. These changes often present with subclinical uterine inflammation, metabolic stress, or impaired maternal-fetal immune signaling (Smith et al., 2022).

Sanitary causes also contribute significantly to reproductive loss. Pathogens such as Neospora caninum, Leptospira spp., and bovine viral diarrhea virus (BVDV) can directly damage fetal or placental tissues or trigger immune rejection (Bondurant, 2005). In these studies, we found that regional variation was quite evident: tropical herds, particularly Bos indicus in Brazil, showed higher exposure to infectious agents (Ferreira et al., 2016; Rodríguez et al., 2020). Heifers and primiparous cows were particularly more susceptible, demonstrating incomplete immune maturity. In Brazil, between 37% and 50% of pregnancy losses have been associated with infectious agents, mainly infectious bovine rhinotracheitis (IBR), bovine viral diarrhea virus (BVDV), and leptospirosis (Aono et al., 2013; Ferreira et al., 2018; Andreotti et al., 2010). On the other hand, vaccinated herds had significantly lower pregnancy loss rates (1.6%) compared to unvaccinated female cattle (4.3%), demonstrating the importance of complete immunization before TAI programs. These results are in agreement with previous studies that identify infectious diseases as major contributors to pregnancy loss during later stages of gestation, particularly in tropical production systems. Nutritional factors were responsible for 7% of LFL losses. During late gestation, low energy or trace mineral intake (selenium, zinc, copper) compromises placental function and fetal immune development (Wu et al., 2006; Noya et al., 2019). A negative energy balance similarly affects fetal growth and development and the maintenance of pregnancy (Bazer et al., 2015; LeMaster et al., 2017). Management-related factors contributed to approximately 5% of LFL losses. The pregnancy diagnosis technique is very important: rectal palpation, primarily performed by inexperienced technicians, increased fetal loss compared to ultrasound palpation (Beal et al., 1992; Richardson et al., 2010). It is important to note that the temperament of female cattle also plays a role: excitable or nervous cows showed higher cortisol levels and higher pregnancy loss rates (9.9% vs. 5.9%; Cooke et al., 2017).

Finally, paternal factors can affect fetal survival. Franco et al. (2018) reported that embryos from certain bulls had higher pregnancy loss rates despite normal semen quality. Cows with pregnancy loss were also found to have low PAG concentrations (Franco et al., 2020), suggesting a correlation between bull genetics, placental function and development, and embryo viability. Taken together, these results highlight the multifactorial nature of LFL, where hormonal, infectious, nutritional, management, and genetic components interact to determine gestational viability.

A limitation of this study is the lack of consistent reporting of reproductive management programs (e.g., artificial insemination, estrus synchronization protocols) across the included studies, which may influence pregnancy outcomes and limit the ability to fully interpret the observed variability in pregnancy loss rates.

Conclusions

This systematic review and meta-analysis demonstrated that pregnancy losses in beef cattle constitute a multifactorial phenomenon, predominantly influenced by hormonal, nutritional, sanitary, and management factors. Losses occurring during the early embryonic stage were particularly significant, with hormonal deficiencies and nutritional imbalances identified as the main contributing causes. In the late embryonic/early fetal stage, hormonal and sanitary factors predominated as major contributors to pregnancy loss. The high degree of heterogeneity observed among the studies analyzed reflects methodological and contextual variations that should be carefully considered when interpreting these findings. These results reinforce the critical importance of implementing effective reproductive management strategies, well-structured nutritional programs, and comprehensive preventive health measures to reduce pregnancy losses and enhance the productivity of beef cattle herds. Moreover, this meta-analysis underscores the necessity for deeper exploration of specific causal subcategories within each main group (e.g., progesterone deficiency under hormonal, leptospirosis or BVD under sanitary causes, or energy/protein imbalance under nutritional factors). Understanding these individual mechanisms will facilitate the development of targeted, evidence-based interventions. In addition, it is worth considering that these causal categories may vary in terms of difficulty of correction or prevention. Management-related and nutritional factors, for instance, may be more easily modifiable through on-farm practices, while hormonal imbalances or infectious diseases may require more complex interventions or long-term strategies. Therefore, presenting causes in a gradient of ease of correction, from management to hormonal or sanitary, could be a valuable tool for practitioners and producers when prioritizing actions to reduce gestational losses. Ultimately, beyond identifying causes, the goal must be to support practical decision-making that promotes reproductive efficiency in beef cattle systems.

Data availability statement

Research data is available in the body of the article.

Financial support:

GHS received funding for this research from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

How to cite:

Holguin-Sanabria G, Díaz Sánchez DJ, Zago D, Barcellos JOJ. Main causes of pregnancy losses in beef cattle: systematic review and meta-analysis. Anim Reprod. 2026;23(4):e20250143. https://doi.org/10.1590/1984-3143-AR2025-0143

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*

Corresponding author: [e-mail]

Conflicts of interest:

The authors have no conflict of interest to declare.

Editor-in-Chief:

Carlos Eduardo Ambrósio

Publication Dates

• Publication in this collection
  26 Oct 2026
• Date of issue
  2026

History

• Received
  05 Oct 2025
• Accepted
  13 July 2026