Repeat breeding: prevalence and potential causes in dairy cows at different milk pocket areas of Bangladesh

The objective of this study was to figure out the prevalence and probable causes of repeat breeding (RB) in dairy cows. Hence, a cross-sectional study was conducted on randomly selected 265 dairy farms in Sirajganj, Bogura, Rangpur, Satkhira, and Munshiganj districts of Bangladesh from December 2018 to February 2019. Data were collected through a direct interview method using a survey questionnaire. The reproductive organs of repeat breeder cows were examined for pathological, infectious, and functional reasons, and genital tract abnormalities. Additionally, the influence of nutrition, season, and age on the frequency of RB was recorded. The prevalence of RB was 28% among the 3824 cows investigated. Among the total repeat breeder cases, 72.54% of RB cases were found in Holstein–Friesian crossbred, 23.90% in Jersey crossbred, 1.50% in Sahiwal crossbred, and 2.06% in indigenous cows. The prevalence of RB was significantly highest (P < 0.01) in Satkhira (44.35%) and lowest in the Munshiganj district (15.87%). Data indicated that a major proportion of cows significantly (P < 0.05) faced RB problems due to functional causes (34.18%), followed by pathological causes (28.01%), genital tract abnormalities (21.32%), and infectious causes (16.49%). Furthermore, the cows were remarkably (P < 0.001) affected in RB during the summer season and nutritional deficient diseases like milk fever (70%). Age (3–7 years) had a significant (P < 0.001) effect on the RB occurrence (90%) in crossbred cows. However, particular focus should be given to systematic breeding, balanced nutrition, artificial inseminator efficiency, and hygienic inseminating tools to reduce RB incidence in high-yielding crossbred cows.


Introduction
Dairying is an efficient farming system that contributes as a potent tool for developing the national economy and sustainable food production systems (Saadullah 2001;Herrero et al. 2013). The profitability of dairy farms mainly depends on the higher milk yield and optimum reproductive efficiency (Khair et al. 2018). Our previous research report (Islam et al. 2019) revealed that repeat breeding negatively affects farm profitability and losses due to repeat breeding were greater in the Sirajganj district compared to other milk pocket districts (Satkhira, Rangpur, Munshiganj, and Bogura) in Bangladesh. Regular breeding of female animals is an economically crucial trait as it affects the calving interval, calf crop, and milk production (Garcia-Ispierto et al. 2007). Dhaliwal (2005) mentioned that the success of dairy farming relies remarkably on the calving regularity of each cow within the normal physiological range. But the repeat breeder cows are the major constraint to the efficient and profitable reproductive management of dairy farms (Khair et al. 2018).
Repeat breeding (RB) is a condition when a cow fails to become pregnant following three or more breeding (natural and artificial insemination) without visible defects (Purohit 2008;Amiridis et al. 2009). The repeat breeder cow appears to be in good health and has a normal estrus cycle (Warriach et al. 2009). RB leads to economic loss by reducing fertility and lifetime production, extending calving intervals, and augmenting culling in dairy cows (Bonneville-Hebert et al. 2011). It also lowers farm profitability through wastage of semen, increasing insemination cost, treatment cost, culling, and replacement costs (Bartlett et al. 1986). The etiology of RB includes hormonal dysfunction (Bage et al. 2002), uterine infection and reproductive system abnormalities (Villarroel et al. 2004), haphazard breeding, semen quality, and insemination methods (Hallap et al. 2006), and inadequate diet and health management (Purohit 2008).
Generally, 9-12% of the cows are expected to be repeat breeders in a herd with average fertility and a 50-55% conception rate. The prevalence of RB in dairy cows is between 3 and 10% worldwide (Bartlett et al. 1986), with India accounting for 37.4% (Singh et al. 1996). In addition, the prevalence rate of RB varies among the genotypes of the cow. Mandefro and Negash (2014) found fewer repeat breeders in the local cows than in the Friesian crossbred cows. From different studies, the prevalence of RB cows was found at 11.3% (Nath et al. 2014), 11.5% (Asaduzzaman et al. 2016), and 22.3% (Hassan 2017) in different areas of Bangladesh.
Dairying in Bangladesh largely depends on smallholder dairy farmers (> 70%) who contribute 70-80% of the country's milk supply, where cows alone provide 95% of the total milk (Uddin et al. 2012). Approximately, 70-75% of dairy farmers use artificial insemination to upgrade their local cows under an extensive dairy production system, but cow distribution is not uniform throughout the country. Few districts in Bangladesh are well known as milk pocket areas because of the faster growth of smallscale dairying, many dairy farms, and more intensified dairying (Islam et al. 2019). Dairy cows in milk pocket areas are mostly crossbred and have superior milk production potential (Uddin et al. 2011). On the contrary, the reproductive efficiency of dairy animals is markdown due to the advancement of exotic inheritance via crossbreeding. Shamsuddoha and Edwards (2000) and Islam et al. (2019) mentioned that farmers of milk pocket areas generally prefer to rear high-yielding crossbred dairy cows but face problems related to breeding, herd fertility, diseases, and milk marketing. Among these, the RB incidence of high-yielding crossbred dairy animals was dominant in milk pocket areas (Islam et al. 2017(Islam et al. , 2019. Many researchers have identified several risk factors related to the occurrence of RB in cows and buffaloes, viz. age, body condition score, season, parity, lactation stage, milk yield, breed, nutritional management, bull factor, failure to fertilization, and early embryonic death (Nath et al. 2014;Singh et al. 2008;Saraswat and Purohit 2016;Washaya et al. 2019). Some reports considered the degree of RB of dairy cows in specific regions and fewer repeat breeder cases in Bangladesh; however, information relating its prevalence and risk factors for RB is very scanty and unorganized (Islam et al. 2017;Asaduzzaman et al. 2016;Matubber et al. 2018). Hence, this study was undertaken to envisage the prevalence and potential risk factors associated with RB in dairy cows in selected milk pocket districts of Bangladesh, viz. Rangpur, Bogura, Sirajganj, Munshiganj, and Satkhira.

Study areas and farm size
This study was carried out in milk pocket districts of Bangladesh, viz. Sirajganj, Bogura, Rangpur, Satkhira, and Munshiganj (Fig. 1). These districts were selected based on the density of high-yielding crossbred dairy cows. A total of 3824 cows from 265 dairy farms were surveyed randomly. It includes 1132 cows (58 farms) from Sirajganj, 245 cows (48 farms) from Bogura, 1689 cows (94 farms) from Rangpur, 487 cows (40 farms) from Satkhira, and 272 cows (25 farms) from the Munshiganj district (Table 1). The size of the dairy farm is defined in this study based on the number of dairy cows in a herd, such as small (1-5 cows), medium (6-15 cows), and large (> 15 cows), as described by Islam et al. 1 3 (2019). The seasonal temperature-humidity index (THI) values for the study areas were calculated over a 4-year period from January 2016 until December 2019. As described by Bouraoui et al. (2002), the THI was calculated using the formula, THI = 1.8 × T − (1 − RH) × (T − 14.3) + 32. Here, T = average ambient temperature in °C, and RH = average relative humidity as a fraction of the unit. The average ambient temperature and relative humidity data were collected from the Climate Information Management System of the Bangladesh Agricultural Research Council (BARC, 2022). However, the BARC does not have stations in Sirajganj and Munshiganj regions; therefore, we used nearby station (viz. Ishurdi and Faridpur, respectively) data regarding T and RH for these regions. The seasonal THI data are presented in Table 2.

Questionnaire development and data collection
Primary data were collected from dairy farm owners using the direct interview method. Before the actual interview, farmers were informed about the nature and purpose of the study. The questions were asked systematically, and explanations were given whenever it was deemed necessary. The information provided by the farmers during face-to-face interview was directly recorded and checked before leaving the farms. We ran a trial survey among 20 farms before adopting the final survey schedule to review the questions for clarity, the correctness of response options, scientific words, and the overall survey flow. The survey schedule had the following information: farm size, age of the animal, case history of RB, methods of artificial insemination (AI), used frozen semen quality, semen thawing temperature and time, cleanliness of AI tools, and timing of AI. In addition, data on the deposition site of semen into the genital organ of cows were recorded. Data were collected on repeat breeder cows focusing on pathological factors, infectious and nutritional deficiency diseases, functional causes of genital organs, and congenital abnormalities of the genital tract. Data regarding the age of cows and seasonal impacts on RB were also recorded.

Rectal palpation and causal agent diagnosis
Rectal palpation was also performed by the experienced person wearing disposable hand gloves on repeat breeder cows to identify respective reproductive disorders or functional abnormalities. The cervix, uterine body, and uterine horns were examined for uterine infection, pyometra, endometriosis, pregnancy, and abnormal contents. The ovaries were palpated carefully to detect the presence and size of the normal follicles, corpus luteum or abnormal structures, or ovarian cysts. Infectious and pathological causes were diagnosed at the respective Upazila Veterinary Hospital of the respective district using standard veterinary clinical protocols and then, the veterinary doctor gave prescriptions with detailed causal agents. Thereafter, farmers recorded that information in their animal health register book and we gather that information from the health register book.

Efficiency of the AI worker
The AI workers in this survey were licensed veterinary technicians and were known as skilled persons by dairy farmers. They observed and comprehended the anatomy and ovulation cycle of dairy cows with great attention. AI workers were quite expert in inseminating cows at the right time and ensuring proper semen deposition into the reproductive tract. Generally, AI workers used specific tools to insert sperm into the reproductive tract of cows that facilitated impregnate breeding. The inseminated semen was packed in labeled straws and submerged in a liquid nitrogen can. Artificial inseminators were very careful in handling and thawing before inseminating the animal for maximum sperm cell recovery. The technicians always ensured that all equipment was properly maintained and cleaned.

Determination of age and body condition score of animals
The animal ages were calculated using birth records. A manual assessment of the thickness of the fat covered and the prominence of bone at the tail head and loin area was used to score body condition. The tail head was scored by feeling the amount of fat around the tail head and the prominence of the pelvic bones. Touching the horizontal and vertical spinal projections and the quantity of fat in between was used to score the loin. A score of 1.0 was considered extremely thin or in poor body condition on a scale of 1.0-5.0 with 0.5 fractions, while a score of 5.0 was considered extremely fat. The average body condition score (BCS) of cows is given in Table 3.

Selection of RB cows
Cows complaining of repeated conception failure were identified on the farms, and the owners were interviewed about the history of RB problems: failed to conceive after three or more services, had a normal estrus cycle, was free and/or having palpable abnormalities, had normal and/or abnormal vaginal discharges, and was delivered to the calf at least once before being treated as a repeat breeder. Semen deposited by artificial insemination into the cow's genital organ in different places (head, 2nd/3rd rings of the cervix, and the body of the uterus) is shown in Table 4.

Statistical analysis
Statistical analysis was performed in SPSS version 20 (SPSS Inc. Chicago, USA) and Excel version 2010 (Microsoft Corp., Redmond, WA). Pearson's chi-square tests were used to examine the prevalence of RB and proportionate cases of RB factors (including pathological, infectious, functional, genital tract abnormality, nutritional disorders, season, and age) among the districts (Bogura, Sirajganj, Rangpur, Satkhira, and Munshiganj). For significant values, a post hoc pair-wise comparison test with Bonferroni corrections was performed for multiple comparisons to investigate differences among the districts further. The threshold for statistical significance was set at P < 0.05.

Distribution pattern of repeat breeder cows
The distribution pattern of repeat breeder cows in the studied areas is presented in Table 5. It shows that the Sirajganj district had the highest number (395) of repeat breeder cows, of which 304 cows were Holstein-Friesian crossbred (HFX). In contrast, the Munshiganj district had the lowest (43) occurrences with a similar trend for HFX. Results also indicated that HFX cows were mostly (73%) affected by the RB problems, followed by Jersey crossbred (JX) (24%) and other genotypes (3%). Repeat breeder indigenous cows were found only in the Rangpur district (22).

Prevalence of repeat breeding
The prevalence of RB was 28% (n = 1067) out of the total 3824 cases investigated in the study areas (Table 5). Nearly all cases (98%) of RB happened in crossbred cows, specifically HFX, JX, and Sahiwal crossbreds (ShX) than the indigenous cows (2%). RB significantly prevailed (P < 0.01) in Satkhira (44%) than that in the other districts, whereas the Munshiganj district was in a better position in terms of RB prevalence (16%) and frequency (43). Cows of both Sirajganj (34.89%) and Bogura (31%) districts experienced almost similar repeat breeding prevalence, although their frequencies (395 vs. 76) were different ( Table 5).

Causes of repeat breeding
Proportionate cases of RB due to pathological, infectious, and functional causes and genital tract abnormalities are presented in Table 6. Results revealed that the highest incidences (P < 0.05) of RB were exhibited due to functional causes (34.18%), followed by pathological causes (28.01%), genital tract abnormalities (21.32%), and infectious causes (16.49%). Around 55-74% of cases of RB due to genital tract abnormalities and functional and infection causes were found in the Sirajganj district. Satkhira (46%) and Sirajganj (55%) had the highest rates of RB incidence attributable to pathological and functional causes, respectively.
The cystic ovary was identified as the key functional reason (in more than half of the cases) for the occurrence of RB, and the majority of these cases were detected in HFX cows (309 cases out of 742). Similarly, abortion was the most dominant pathological reason behind the RB compared to pyometra, uterine prolapse, anestrus, bovine brucellosis, etc. On account of the pathological causes, the incidences were also more dominant in HFX than in the other genotypes. Research findings also indicated that ovarian abnormalities are mostly (50%) responsible for RB in cows than the abnormalities of other parts of the female reproductive tracts. On the other hand, vaginitis creates half of the fertility problem among infectious causes, mostly found in HFX cows. Table 7 shows the influence of nutritional deficiencies and overfeeding on the proportionate cases of RB in cows. Results demonstrated that cows that were affected by milk fever in the previous lactation had a significant impact (70%) on the occurrence of RB incidences than the cows that faced ketosis and overfeeding (P < 0.001). However, overfeeding (17.41%) and ketosis (12.5%) had similar (P > 0.05) effects on RB cases. Overall, proportionate cases to total cases for RB due to nutritional deficiencies and overfeeding varied significantly (P < 0.001) among the studied districts. More than half of the total cases were identified at Sirajganj (53.57%), followed by Rangpur (26.79%), Satkhira (11.61%), Bogura (5.36%), and Munshiganj (2.67%).

Effects of seasons on repeat breeding
The effects of seasons on the proportionate cases of RB in cows are presented in Table 8. Results revealed that the incidence of RB was significantly varied with seasonal variation and the proportional issues of RB were remarkably (P < 0.001) higher in the summer season (36%). But the proportional prevalence of RB remained statistically similar (P > 0.05) among the other seasons. However, the relative number of cases of RB with seasons varied statistically (P < 0.001) among the studied districts in Bangladesh, and the highest share of RB was found in the Satkhira district (49%). Table 9 describes the influence of age on the proportionate cases of RB in dairy cows in different milk pocket districts of Bangladesh. Almost all of the repeat breeders (90%) faced RB problems between 3 and 7 years old, and the remaining 10% experienced RB incidence before 3 years of age (P < 0.001). However, the proportion of cases of RB in terms of age significantly (P < 0.001) varied among the studied districts, and Bogura (40.77%) had the highest RB cases owing to age.

Discussion
The outline of this cross-sectional study on 265 dairy farms provides a benchmark for dairy cows regarding the risk factors of RB in Bangladesh. The average repeat breeder cows  Values with different superscripts within the same column differ significantly (P < 0.05). Total cases for a certain feature of each genotype are calculated by the sum of five district RB case numbers. Again, total cases of a certain district feature are calculated by the sum of all genotypes RB cases in that district. The percent total cases in a particular district are computed by dividing the total case numbers in that district by the sum of all cases in all districts and multiplying by 100. Proportions of RB cases for a certain feature to total RB case percentages were calculated as the total RB case numbers for that feature divided by the sum of all feature case numbers by multiplying 100  Values with different superscripts within the same column differ significantly (P < 0.001). Summer season (mid-April to mid-June), rainy season (mid-June to mid-August), autumn season (mid-August to mid-October), late autumn season (mid-October to mid-December), winter season (mid-December to mid-February), and spring season (mid-February to mid-April). Total cases for a certain feature of each genotype are calculated by summing up five district RB case numbers of that feature. Again, total cases for all characteristics of a district are computed by adding all genotype RB cases from all seasons in that district. % of total cases in a certain district is calculated as the total case numbers of that district divided by the total cases in all districts by multiplying 100. Proportions of RB cases for a certain season to total RB case percentages were calculated as the total RB case numbers for that season divided by the total case numbers of all seasons by multiplying 100  Table 9 Effect of age on the proportionate cases of repeat breeding in cows Values with different superscripts within the same column differ significantly (P < 0.01). Total cases for all district features are calculated by the sum of all genotype RB cases for all seasons in that district. % of total cows in a certain district is calculated as the total cow numbers of that district divided by the total cow numbers in all districts by multiplying 100. Proportions of RB cases for a certain age to total RB case percentages were calculated as the total RB case numbers for that age divided by the total case numbers of all ages by multiplying 100 per farm were 1.58, 6.81, 3.58, 5.4, and 1.65 in Bogura, Sirajganj, Rangpur, Satkhira, and Munshiganj districts, respectively (Table 5). The highest repeat breeder cows were found in the Sirajganj district, which might be for larger farm sizes than other districts (Table 1). Again, cows on small farms received more individual attention from their owners than cows on large farms (Hewett 1968). In addition to this, it is easier to detect heat more successfully on farms with fewer cows than with more cows. Besides, sub-clinical uterine infection is more frequent in large-sized farms (Jaskowski 1971), which might be another cause of the increasing RB rate in districts with more large farms. High-yielding crossbred cows have mostly faced RB problems than the indigenous cows, in which HFX is the most affected genotype throughout the study areas. More RB prevalence was found in HFX than in other genotypes. That may be due to more percentages of exotic inheritance in genotype through indiscriminate breeding, lack of proper housing and nutrition to support their genetic merits, heat stress, poor dry cow and fertility management, etc. On the other hand, the channel island breeds (like Jersey) can withstand harsh conditions compared to other dairy breeds. According to Uddin et al. (2011), about 98% of the cows are crossbred with temperate genotypes, and the remaining 2% are local cows in the milk pocket districts of Bangladesh. Such unplanned crossbreeding practices increased milk yield and negatively affected herd fertility (Dobson et al. 2007).
Similarly, Rearte et al. (2018) stated that an antagonistic relation exists between high milk yield and the reproductive performance of dairy cows. Islam et al. (2019) reported the highest milk yield per cow (10.33 L/day) in Satkhira and Table 5 shows the highest prevalence of repeat breeding in Satkhira. However, they found the second-best milk production in Munshiganj (9.2 L/cow/day) but the present study indicated the lowest RB incidence (16%) in that area. In the same report, milk production in Bogura, Rangpur, and Sirajganj ranged between 7 and 8 L/cow/day but the RB incidence rate is 20-35% (Table 5). In the case of tropical breeds, the current study recorded the lowest number of RB cases for ShX cows. This finding aligns with Islam et al. (2017) and Asaduzzaman et al. (2016), who reported that HFX is more susceptible to RB. However, ShX and indigenous cows are less susceptible to Bangladeshi conditions. The prevalence of RB varied widely (16-44%) among the study areas and was the highest in the Satkhira district. These differences in prevalence among the districts may be due to the variations in cow management, more graded exotic genotypes, environmental stress, diseases, AI tool cleanliness, and inseminator skills. From Table 3, it was found that no one AI technician used sterile AI guns during insemination, which possibly led to infections in the reproductive tract of cows and contributed to the highest prevalence of RB in the Satkhira district. Moreover, Wolfenson and Roth (2019) showed that heat stress disrupts several reproductive processes and reduces the reproductive performance of lactating cows. According to Jeelani et al. (2019), a temperature-humidity index (THI) value of less than 74 induced no or mild heat stress, a THI of 74 to 78 resulted in moderate heat stress, and a THI of over 80 caused severe heat stress in crossbred dairy cows in the subtropical regions. Table 2 shows that the THI was highest in Satkhira among the study areas in most seasons, and the THI threshold exceeded Satkhira in all seasons except winter. This might have contributed to the highest RB prevalence in the Satkhira region.
The prevalence of RB cows was 11.5% (Asaduzzaman et al. 2016) and 22.3% (Hassan 2017) in different areas of Bangladesh, where 11.3% in commercial dairy farms in Chittagong (Nath et al. 2014). But the prevalence of RB was noticeably higher (28%) in the areas of the current study. Such increment of RB may be due to the differences in the study area, the number of observations, and differences in the exotic blood level of the animal covered in a different study. Moreover, the milk productivity of our crossbred dairy cows has increased in the recent few years but negatively affects the fertility of the cows (Asaduzzaman et al. 2016;Rearte et al. 2018). Again, an increase in milk yield proportionately increases the risk of RB incidence (Gustafsson and Emanuelson 2002). Moreover, farmers of milk pocket areas faced fertility problems with their cows as they generally preferred to rear high-yielding crossbred dairy cows (Shamsuddoha and Edwards 2000;Islam et al. 2019).
The maximum proportion of cows in the milk pocket areas that faced RB problems was due to functional causes (34.18%), followed by pathological causes (28.01%), genital tract abnormalities (21.32%), and infectious causes (16.49%). This finding agrees with Rao (1981), who found a higher incidence of functional abnormalities (73.14%) in repeat breeder cows followed by infections (20.85%) in genetic admixture cows in India.
Most of the cases (55-75%) of RB due to functional cases (cystic ovary), infection (vaginitis), and genital tract abnormalities (mostly in ovaries) were found in the Sirajganj district, but this incidence due to pathological (abortion) causes was highest in the Satkhira district (46%). These defects were observed more in HFX (70-80% cases) than in the JX and other genotypes among the milk pocket areas, which may be due to the rapid transformation of other genotypes into HFX and increment of exotic inheritance that causes failure in adaptation to the environment and management systems of milk pocket areas in Bangladesh (Islam et al. 2017(Islam et al. , 2019. This finding aligns with Asaduzzaman et al. (2016), who reported that RB is more prevalent in HFX cows than in other genotypes. With regard to the cystic ovary, information on days from calving is important which was not recorded in the present study.
Milk fever greatly impacted the proportionate cases of RB in cows of milk pocket areas. Milk fever is a calcium deficiency metabolic disease, and calcium has a crucial function in muscle contraction. Hence, deficiency in calcium leads to the alteration of normal uterine muscle tone and thus possibly promotes prolapse of the uterus, retention of the placenta, and infertility (Goff 2008;Oetzel and Miller 2012;Reinhardt et al. 2011). The calcium requirement during advanced pregnancy and after parturition is very high due to the rapid development of the fetus and higher milk production (Patel et al. 2011). Generally, farmers of our country reared high-yielding crossbred cows with imbalanced feeding; thereby, animals cannot fulfill their nutrient requirements (Uddin et al. 2011), which may be another cause of milk fever in dairy cows (Samad 2019). A decline in the ruminal muscle contraction resulting from calcium deficiency provokes less feed intake, and the animal becomes energy-deficient which leads to anestrous and repeat breeding (Verma and Kumar 2018). Our study revealed that RB is more frequent in HFX cows than in JX, ShX, and indigenous cows. This can be explained by the fact that HFX cows produce more milk, and their nutritional management is more crucial than other genotypes. However, dairy farmers are unaware of their dietary requirements, and HFX cows are more susceptible to nutritional deficiency and consequently susceptible to RB.
In this study, the incidence of RB varied with seasonal variation, and most of the cases were in the summer season. These findings are similar to , who found maximum RB incidence of cows in the summer season and minimum in the autumn season. It may be due to the hot weather of the summer season that increases heat stress in lactating cows (Yusuf et al. 2012), and the reduction in fertilization rate (Sartori et al. 2002) results in an increased number of services per conception (Lucy 2001;Dochi et al. 2008;Yusuf et al. 2010) that increases the risk of RB. Prolactin hormone levels in the blood increase during the summer season, whereas luteinizing and progesterone hormone levels decrease. Prolactin has a detrimental impact on cow fertility (Khosa 2020). Likewise, Nabenishi et al. (2011) mentioned that the high ambient temperature was inversely associated with the conception rate.
Compared to Sirajganj and Rangpur districts, the Satkhira district had the highest proportionate RB cases due to its geographical location. The Satkhira district is situated in the Khulna region of Bangladesh, where the average environmental temperature remains consistently higher than in other studied districts. HFX cows occupied the most significant proportion of cows and repeated breeders among different genotypes in the studied areas (Tables 2 and 5). During the summer season, the average temperature remains 30-40℃, and the maximum temperature is recorded at 35.4℃ (BMD 2012). At > 29℃, the breeding rate of Holstein-Friesian cows is very low (Cavestany et al. 1985), and this might be the reason behind the higher proportion of RB during the summer season in the HFX population. Takahashi (2012) reported that the fertility of high-yielding dairy cattle is lower in summer and much lower in fall than in winter.
Results indicated that proportionate cases of RB increased with the advancement of age which is similar to the findings of Hasib et al. (2020) and Nishi et al. (2018). Hodel et al. (1995) stated that age impacts the fertility of cows negatively, and older cows had a greater possibility of RB (Hewett, 1968) which may be owing to the difference in hypothalamic or pituitary hormonal levels or variation in the ovarian response among the different age groups (Bullman and Lamming 1978). Asaduzzaman et al. (2016) also reported that the occurrence of RB in cows was significantly lower in the 3-6 years age group than in the 7-13 years. The current study found that ≈90% of dairy cows were affected with RB at 3-7 years of age. This finding may be due to the early culling of high-yielding repeat breeders, especially HFX, after one and two lactation. In Bangladesh, it is common practice that farmers rear high-yielding crossbred cows (mostly HFX) for 1 or 2 lactations, at best 3 lactations. After that, the cows are culled, mentioning the fertility problems (Islam et al. 2019), and sold for slaughter as dairy beef animals.

Conclusions
Overall, the prevalence of RB in cows is 27.90% in the studied dairy regions of Bangladesh. The Satkhira district has the highest rate of RB, followed by the Sirajganj, Bogura, Rangpur, and Munshiganj districts. The study shows that functional and pathological causes, milk fever, summer season, and cows over 3 years of age significantly impacted RB. In addition, the breed, herd size, body condition score, and farm size might influence RB in cows. The breed effect can be corrected by reducing the unplanned crossbreeding with exotic genotypes, especially for Holstein-Friesian. Particular attention should be paid to balancing feeding with a focus on green grass and mineral supplement to prevent nutritional disorders and maintain good reproductive health. Special considerations should also be given to increase the efficiency of artificial insemination workers and the cleanliness of AI tools to reduce infections like the incidence of RB in cows. Results also necessitate further study to clarify the causes of repeat breeding in cows considering the parity of cows, ranges of milk yield, stress factors, environmental temperature and humidity index, and dairy animal welfare aspects.