The Relationship of Neonatal Calf Diarrhea and Yield Losses with Managerial Factors in Dairy Cattle Farms

The Relationship of Neonatal Calf Diarrhea and Yield Losses with Managerial Factors in Dairy Cattle Farms | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Relationship of Neonatal Calf Diarrhea and Yield Losses with Managerial Factors in Dairy Cattle Farms Yasin PARLATIR, Seyfettin TUNCEL, Pınar Ayvazoğlu Demir This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7462598/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract This study, which examined the epidemiological characteristics and associated risk factors of neonatal calf diarrhea in dairy cattle farms in Türkiye, was based on survey data covering 115 farms from seven geographical regions. The study determined the prevalence of diarrhea in calves as 26.81% and the mortality rate due to diarrhea as 15.58%. In addition, diarrhea was found to cause a decrease in weight gain by 11–30%. According to logistic regression analysis, the presence of birth and calf compartments, timely colostrum transfer and hygienic practices (teat and bottle cleaning) statistically significantly reduce the risk of diarrhea. The probability of diarrhea was found to be 81% lower in holdings with a maternity compartment and 71% lower in holdings with a calf compartment. Vaccination and producer experience also stand out as critical factors; the risk of diarrhea was found to be 5.5 times higher in inexperienced producers. Seasonal effects were also observed in the study. Accordingly, it was found that the risk of diarrhea was lower in spring months compared to winter and summer months, and the risk decreased by 64.5% in temperate climates compared to continental climates. As a result of the study, it was determined that neonatal diarrhea causes not only mortality, but also growth retardation and economic losses. Calf Diarrhea Economic loss Economic effects Peripheral factors Introduction Reducing mortality and morbidity rates in the neonatal calf period is of strategic importance for the sustainability of milk and red meat production in Türkiye. The healthy survival of newborn calves is a critical parameter not only in terms of animal welfare, but also in terms of the economic efficiency of livestock enterprises and the protection of animal production potential at national level. It was reported that 15% of approximately 6 million calves born in Türkiye in 2022 died during calving period (Turk and Emlik 2022 ). When the calf mortality rates in Türkiye compared with the worldwide, the studies reported that Denmark has 6.7% mortality ratio in calves, in Norway 4.4%, in Sub-Saharan Africa region 12% and Ethiopia has the 22% ratio rates (Østerås et al. 2007 , Wudu et al. 2008 ). These results shows that Türkiye is among the high-risk countries in terms of neonatal calf losses. The majority of these losses in the neonatal period occur in the first 28 days of life when the immune system is not yet developed and calves are dependent on passive immunity. This period is a critical time period in which approximately 75% of total calf losses occur (Bartels et al. 2010 , Fanda 2023 ). The main health problems seen during this period include diarrhea, pneumonia and sepsis, and diarrhea is usually the disease with the most significant share in calf mortality (Cho and Yoon 2014 , Aydoğdu et al. 2019 ). In Türkiye, diarrheal morbidity rates in neonatal calves were reported as 25.7% by Arslan et al. ( 2001 ) and 22.9% by Tokgöz et al. ( 2013 ) (Arslan et al. 2001 , Tokgöz et al. 2013 ). These ratios corresponds to the upper limit of the levels reported in European countries, ranging from 5 to 23 per cent (Waltner-Toews et al. 1986 , Windeyer et al. 2014 , Murray et al. 2016 , Wilson et al. 2023 ). In this context, it is considered that morbidity rates in Türkiye are quite high and this situation poses a serious threat to both animal health and economic productivity. Calf mortality during the neonatal period is known to affect not only animal welfare but also total factor productivity in animal production and national income. Indeed, in 2006, the economic losses attributed to neonatal calf losses in countries such as Norway, Finland, Sweden and Denmark were reported as €9.5 million, €48 million, €7.4 million and €40 million, respectively (Østerås et al. 2007 ). In Türkiye, this loss was reported to be around € 525 million (Şahal et al. 2018 ). These differences are directly related to animal population size, morbidity rates and the effectiveness of biosecurity measures between countries. In the etiopathogenesis of neonatal diarrhea, the frequency of bacterial (especially ETEC K99+), viral (BRV, BCoV) and protozoal ( Cryptosporidium spp., Giardia spp.) agents as mixed infections is high and this increases the severity of the clinical picture (Blanchard 2012 , Dall Agnol et al. 2021 , Güreli and Kara 2023 ). However, environmental (temperature, humidity, disinfection, ventilation) and management (colostrum quality, umbilical hygiene, vaccination programme, herd structure) factors also have a significant impact on the incidence of the disease (Frank and Kaneene 1993 , Keleş et al. 2022 , Yanar 2022 ) This study aims to determine the prevalence of calf losses caused by neonatal diarrhea cases, to reveal the morbidity and mortality rates related to these losses and also to identify the predisposing factors affecting this situation and to analyse their risk levels based on surveys and field observations conducted throughout Türkiye. Indeed, the fact that epidemiological prevalence data on the prevalence of neonatal calf diarrhea in Türkiye are supported by a limited number of studies reveals the need for up-to-date and comprehensive data at national level. In this context, the findings of this study are expected to contribute to the improvement of animal husbandry policies and the development of sustainable animal production strategies. Material Methods Data Collection and Sample Size Within the scope of this study, dairy cattle farms operating in different geographical regions of Türkiye were interviewed in order to estimate the economic losses caused by diarrhea during the neonatal calf period. The sample size of the study was determined by taking into account the population size of dairy cattle farms operating in Türkiye. In the sample size calculation with 95% confidence level and ± 10% margin of error, the minimum required sample size was calculated as 96 enterprises. However, in order to increase the representativeness of the study, face-to-face interviews were conducted with a total of 115 enterprises selected by simple random sampling method to cover seven geographical regions of Türkiye and who agreed to answer the questionnaire. The data were collected in 2025. Survey Data The data were evaluated about the capacity of enterprises and producing abilities according to the information received from the breeders and the experience of the breeders. For this purpose, numbers of breeding cows, born calf, diarrheic calf, dead calf and ill thrift calf were taken part in the survey. The enterprises were classified as small, middle and large scale with the numbers of cattle. According to classification, all groups were evaluated with each other. The yield loss were evaluated associated with diarrhea according to taken data. The ratios of diarrhea, dead causing from diarrhea, ill thrift calves, loss of weight and the percentage of milk yield loss were recorded in the survey. These data were analyzed with descriptive statistics parameters and logistic regression models. At the same time, the vaccination status of cows and calves was recorded. The types of enterprises, production types, the presence of calving pens and calf units were evaluated. In addition to these data, calf feeding methods and postnatal application of colostrum were included in the questionnaire study. The climatic characteristics of the enterprises were recorded. Also the months of the diarrhea was noted. Bottle cleaning, bottle cleaning method, umbilical cord disinfection and umbilical cord tying status were included in the disinfection procedures related to calf diarrhoea. All data were expressed as percentages and analysed by logistic regression methods. Statistical Analyses The aim of this study was to investigate the prevalence and mortality of neonatal calf diarrhea and the management factors affecting them in cattle farms in Türkiye. For this purpose, logistic regression model was used in the study. Logistic ordinal regression is one of the commonly used analysis methods when the dependent variable is ordinal (1, 2, 3), and it is preferred because it does not require normality assumption and its results are easy to interpret. The logistic ordinal regression model is based on the odds ratio and the maximum likelihood method is used to estimate the model parameters. With this method, the probabilities of the dependent variable against the determined independent variables and the effect sizes of each variable can be calculated reliably. The results of the analyses are presented with odds ratios and 95% confidence intervals. In addition, the ANOVA test for independent samples was used to analyse the differences between variables and the Chi-square (χ²) test was used to determine the relationships between various discrete (categorical) variables. Statistical significance level was accepted as p < 0.05 in all tests. All analyses were performed using SPSS 26.0 and Excel package programmes. Ethical principles were observed in the study and verbal and written informed consent was obtained from the participants. It was reported by the Ethics Committee of Kırıkkale University that this study did not require ethics committee approval. Results Within the scope of the study, as of 2025, the average number of cows per enterprise was 82.38 ± 125.09 and the average number of calves born was 57.83 ± 108.53, and it was determined that there were 10,720 breeding cows and 7,724 calves in total (Table 1 ). In the study, the average number of calves with diarrhea per farm was 11.26 ± 23.13, 1.296 calves had diarrhea in total and the rate of calves with diarrhea was 26.81 ± 18.78%. The distribution of the number of sick, dead and illthrift calves according to the scale of the enterprise is given in Table 1 . Table 1 The number of sick, dead, illthrift, born calves and breeding cows. Parametre Small-Scale Enterprise Middle-Scale Enterprise Large-Scale Enterprise Mean F / p Breeding Cow 7,47 ± 2,34 27,21 ± 11,45 214,68 ± 150,50 82,38 ± 125,09 65,560 / <0,01 Born Calf 5,17 ± 2,15 18,88 ± 9,90 151,05 ± 154,60 57,83 ± 108,53 30,910 / <0,01 Diarrhea 1,30 ± 1,02 4,60 ± 3,55 28,00 ± 35,32 11,26 ± 23,13 19,018 / <0,01 Dead Calf 0,27 ± 0,58 0,85 ± 1,30 4,65 ± 5,62 1,92 ± 3,79 18,785 / <0,01 İllthrift Calf 0,30 ± 0,65 1,02 ± 1,37 5,86 ± 16,77 2,39 ± 9,77 3,654 / 0,029 In the survey results, it was reported that the mortality rate due to diarrhea was below 10% in 52.2% of the holdings, the average number of calves die per holding was 1.92 ± 3.79, 221 calves in total died due to diarrhea and the average mortality rate due to diarrhea in the holdings was 15.58 ± 20.49%. In the study, the number of calves with developmental retardation was determined as 2.39 ± 9.78 per farm and 275 in total, and the average rate of calves with developmental retardation due to diarrhea was calculated as 18.29 ± 27.77%. In the study, the health and productivity losses due to neonatal calf diarrhea and their rates are shown in Table 2 . Table 2 Health and productivity loss rates due to calf diarrhea Parameters Option N % The ratio of diarrhea Under the %10 28 24,3 %11–30 37 32,2 %31 and higher 50 43,5 Mean 115 26,8 The ratio of death according to diarrhea Under the %10 60 52,2 %11–20 34 29,6 %21–30 21 18,3 Mean 115 15,6 The ratio of illthrift according to diarrhea Under the %10 66 57,4 %11–30 49 42,6 Mean 115 18,3 The loss of weight gain Under the %10 37 32,2 %11–20 36 31,3 %21–30 42 36,5 Infertility rate in calves with diarrhea in the future Under the %10 24 20,9 %11–20 15 13,0 %21–30 14 12,2 Not affected 54 53,9 Loss of milk yield in calves with a history of diarrhea Under the %10 31 27,0 %11–20 30 26,1 %21–30 25 21,7 Not affected 29 25,2 In the study, it was determined that neonatal calf diarrhea caused a decrease in the live weight of calves in the majority of the holdings. When the rate of live weight loss due to diarrhea is examined in Table 2 , it is seen that 67.8% of the participants reported a decrease between 11–30%. Similarly, 20.9% of the enterprises reported that the rate of infertility in calves in the following periods was 10% or less, and 53.9% of the enterprises reported that they did not encounter infertility problems in the following periods. On the other hand, 25.2% of the participants reported that this rate was between 11–30%. According to the producers' reports, the rate of decrease in milk yield in the following period in calves with diarrhea was below 10% in 27.0% of the respondents and between 11–30% in 47.8% of the respondents. 25.2% of the participants stated that diarrhea did not affect the milk yield of calves in the following period. Logistic regression analysis was used to determine the factors affecting the incidence of diarrhea in livestock farms. Firstly, descriptive statistics of the variables included in the model are presented in Table 3 . In this table, the intensity of diarrhea cases (low, medium and high) as the dependent variable and parameters such as producer age, husbandry experience, annual income, type of enterprise, septicaemia vaccination, umbilical cord cleaning, teat and bottle cleaning as independent variables are included. Table 3 Statistics of the variables used in the logistic regression model Parametre Frekans Yüzde (n) Severe of Diarrhea Low (1) 28 24,3% Middle (2) 37 32,2% High (3) 50 43,5% Enterprise Type Dairy (1) 44 38,3% Combine (2) 71 61,7% Working Experience Time 0–10 year (1) 39 33,9% 11–20 year (2) 51 44,3% 21–50 year (3) 25 21,7% Stable type Semi-open barns (1) 67 58,3% Closed barns (2) 48 41,7% Birth stalls Available (1) 73 63,5% Non available (0) 42 36,5% Calf stalls Available (1) 73 63,5% Non available (0) 42 36,5% Giving colostrum within the first 4 hours Every time (1) 103 89,6% Sometimes (2) 12 10,4% Feeding calf Without feeder (1) 34 29,6% With feeder (2) 81 70,4% Vaccination the calf Every time (1) 73 63,5% Rarely (2) 42 36,5% Vaccination the cow Every time (1) 53 46,1% Rarely (2) 62 53,9% Cleaning the teat Every time (1) 65 56,5% Rarely (2) 50 43,5% Cleaning the feeder Yes (1) 83 72,2% No 32 27,8% Cleaning way to feeder Boiling(1) 31 27,0% With disinfectant (2) 52 45,2% Only water (3) 32 27,8% Cleaning the umbilical cord Yes (1) 78 67,8% Rarely (2) 37 32,2% Clamping the umbilical cord Every time (1) 51 44,3% Sometimes (2) 14 12,2% No (3) 50 43,5% The months of diarrhea Winter (1) 49 42,6% Spring (2) 41 35,7% Summer (3) 25 21,7% Climate Moderate, Hot (Egean, Marmara, Meditarrenean, Black sea) (1) 53 46,1% Continental Climate (East, Southern East, Cantral Anatolia) (2) 62 53,9% In the study, the significance and fit of the ordinal logistic regression model established to determine the factors affecting the intensity of diarrhea in livestock farms were evaluated. It was determined that the model was generally significant and well fitted to the data. The results regarding the fit and explanatory power of the model are presented in Table 4 . Table 4 Fit and explanatory test results for ordinal logistic regression model Model Fitting Information Model -2 Log Likelihood Chi-Square df Sig. Intercept Only 246,321 Final 143,875 102,446 23 ,000 Goodness-of-Fit Chi-Square df Sig. Pearson 194,780 205 0,684 Deviance 143,875 207 0,999 Pseudo R-Square Cox and Snell 0,590 Nagelkerke 0,668 McFadden 0,416 When Table 5 is analysed, in the Model Fitting Information section, which shows that the model is generally significant, when the model with only constant term and the final model with the addition of independent variables are compared, it is seen that the − 2 Log Likelihood value of the final model decreased significantly (143.875) and the difference is statistically significant (χ² = 102.446; df = 23; p < 0.001). In the Goodness-of-Fit tests evaluating the fit of the model to the data, the p-values of both Pearson (p = 0.684) and Deviance (p = 0.999) tests being greater than 0.05 indicate that the model fits the data well. Pseudo R-Square values showing the level of the model explaining the variance of the dependent variable were found as Cox & Snell R² = 0.590, Nagelkerke R² = 0.668 and McFadden R² = 0.416, respectively. Especially Nagelkerke R² value (65.2%) shows that the independent variables of the model explain a significant portion of the variance in the dependent variable. It can be said that the ordinal logistic regression model created in line with these data is a statistically significant model that fits the data well and has a strong explanatory power. The results of the logistic regression analysis applied to determine the factors affecting the intensity of diarrhea in livestock farms are given in Table 5 . Table 5 The results of logistic regression analysis of the survey parameters Estimate Std. Error Wald Odds Ratio OR Sig. 95% Confidence Interval Lower Bound Upper Bound Monthly income ( $ ) -5,425 3,381 2,575 0,004 0,109 0,000 1,201 Age -0,032 0,030 1,174 0,969 0,279 -0,091 0,026 Enterprise Type 0,221 0,623 ,126 1,247 0,723 -1,000 1,441 Working Experience Time 1,702 0,832 4,179 5,485 0,041* 0,070 3,333 Stable Type -1,060 0,596 3,171 0,346 0,075* -2,228 0,107 Birth Stalls -1,642 0,663 6,126 0,194 0,013** -2,942 -0,342 Calf Stalls -1,239 0,644 3,702 0,290 0,054* -2,502 0,023 Giving Colostrum -3,539 1,336 7,021 0,029 0,008** -6,157 -0,921 Feeding Calf -2,859 0,959 8,890 0,057 0,003** -4,739 -0,980 Vaccination the Calf -3,102 0,708 19,184 0,045 0,000*** -4,490 -1,714 Vaccination the Cow -2,806 0,659 18,150 0,060 0,000*** 0,017 0,220 Cleaning the teat -1,632 0,600 7,392 0,196 0,007** -2,808 -0,455 Cleaning the feeder -2,559 0,843 9,215 0,077 0,002** -4,211 -0,907 Type of cleaning feeder -1,419 0,717 3,920 0,242 0,048* -2,825 -0,014 Cleaning the umbilical cord 0,298 0,709 ,176 1,347 0,674 -1,092 1,688 Clamping the umbilical cord -0,243 0,517 ,220 0,784 0,639 -1,257 0,771 Month of diarrhea -1,634 0,737 4,915 0,195 0,027* -3,078 -0,189 Climate -1,035 0,584 3,141 0,355 0,076* -2,180 0,110 *,**,***Statistically signifance In the study, it was determined that the average age of the participants was 36.64 ± 10.45 years and the average duration of animal husbandry experience was 16.01 ± 8.78 years. In the study, it was determined that the livestock enterprises earned an average annual income of 50.991 $ . Table 5 shows that hygiene and care practices significantly reduced the risk of diarrhea. In the study, it was determined that the risk of diarrhea was significantly lower in calves that received colostrum within the first 4 hours compared to those that did not receive colostrum (OR = 0.029; p = 0.008). Similarly, it was found that the risk of diarrhea was significantly lower in calves fed with breast milk (OR = 0.06; p = 0.003), calves and mothers were vaccinated against septicaemia (OR = 0.045; p < 0.001; OR = 0.06; p < 0.001), calves cleaned teat before suckling (OR = 0.20; p = 0.007) and bottle cleaned (OR = 0.08; p = 0.002). In addition, washing the bottle with detergent and/or disinfectant was found to reduce the risk of diarrhea by approximately 76% compared to bottles rinsed with water only (OR = 0.24; p = 0.048). In the analysis, it was determined that housing structure was associated with diarrhea cases in the holdings. It was found that the risk of diarrhea decreased in holdings with birth stalls (OR = 0.19; p = 0.013) and calf stalls (OR = 0.29; p = 0.054) and semi-open barns (OR = 0.35; p = 0.075). In the study, it was also found that the risk of diarrhea was significantly lower in spring compared to winter and summer (OR = 0.19; p = 0.027). Similarly, it was determined that the risk of diarrhea was approximately 64.5% lower in regions with temperate and Mediterranean climate than in regions with continental climate (OR = 0.355; p = 0.076), but this relationship was statistically significant (p < 0.10). In the study, it was also determined that the risk of diarrhea was approximately 5.5 times higher in producers with low work experience (OR = 5.49; p = 0.041). On the other hand, there was no statistically significant relationship between age, type of enterprise, application of baticon to the umbilical region after birth, umbilical cord clamping and the risk of diarrhea (p > 0.10). Discussion The neonatal period in calves is used to define the first 28 days after birth (Sayber and Kabu 2021 ). Successful management of this period is among the basic policies of both Türkiye and the global livestock sector worldwide. Accordingly, diarrhea is among the most common and most important factors that result in calf loss in the neonatal period (Aydoğdu et al. 2019 ). Global prevalence rates of neonatal calf diarrhea in the literature range from 5–25%, depending on regional differences, management conditions and the effectiveness of animal health services (Wilson et al. 2023 ). In this study, the prevalence of neonatal calf diarrhea was determined as 26.81% as a result of field surveys conducted in different geographical regions of Türkiye. While this prevalence value is close to the 23% rate reported in Canada, it is lower than the rates reported in the USA (38.5%), South Korea (53%) and Iran (58%) (Windeyer et al. 2014 , Gomez and Weese 2017 , Urie et al. 2018 ). When evaluated in terms of epidemiological data specific to Türkiye, in a systematic review conducted by Kozat ( 2024 ), it was reported that the prevalence of neonatal diarrhea was above 50% in field studies based on etiological agents in different regions and enterprises throughout the country (Kozat 2024 ). However, this review may have some limitations in terms of representing the general prevalence, since it was formed by bringing together studies focusing on specific agents. Accordingly, the prevalence value of 26.81% obtained in the present study suggests that neonatal diarrhea cases in Türkiye are common but within the limits of diarrhea rates reported worldwide. Neonatal period is defined as the most risky period in terms of morbidity and mortality in all farm animals (Mee 2023 ). 66% of the morbidity rates of calves in the first 6 months and all of the mortality rates in the first year are associated with diseases encountered in the first 6 months of life (Todd et al. 2018 , Barry et al. 2020 ). In this study, the average mortality rate due to neonatal calf diarrhea in livestock farms in Türkiye was calculated as 15.58 ± 20.49%. This rate shows a significant consistency when compared with the global data reported in the literature. As a matter of fact, in a study conducted in cow-calf farms in the USA, it was reported that digestive system-related calf mortality rates ranged between 14% and 23% (Maier et al. 2022 ). Similarly, Urie et al. ( 2018 ) reported that digestive system diseases had a 32% share in calf mortality (Urie et al. 2018 ). In a field study conducted by Ider et al. ( 2023 ) in Türkiye, 56.4% of calf deaths were reported to be associated with neonatal diarrhea (Ider et al. 2023 ). These data clearly demonstrate that diarrhea in the neonatal period causes not only high morbidity but also serious mortality. As a matter of fact, this situation causes serious damages to national economies (Häsler et al. 2012 ). One of the long-term effects of neonatal diarrhea is that it reduces the calf's growth potential, causing significant reductions in weaning weight and daily weight gain (Abuelo et al. 2021 , Wilson et al. 2023 ). In this study, a decrease in live weight gain ranging between 11–30% was found in calves with diarrhea in the neonatal period. This finding is largely in agreement with the results reported in the literature. Wittum et al. ( 1994 ) reported that calves with diarrhea in the neonatal period had an average 10.7 kg lower weaning weight (Wittum et al. 1994 ). Similarly, Donovan et al. ( 1998 ) reported that calves treated for diarrhea showed approximately 9.1 kg less weight gain at 180 days of age (Donovan et al. 1998 ). Sutherland et al. ( 2018 ) and Gaharshahi et al. (2021) reported that neonatal diarrhea prolongs the length of stay in calves and this process leads to a decrease in milk consumption and hampers growth (Sutherland et al. 2018 , Goharshahi et al. 2021 ). It has been reported that health problems encountered in the neonatal period cause height development and decreases in carcass yield in calves (Van Der Fels-Klerx et al. 2002 , Aghakeshmiri et al. 2017 ). It has also been reported that calves with lower weights in the peripubertal period grow more slowly and reach adulthood at a later age (Mioč et al. 2011 ). This situation reveals that neonatal calf diarrhea is an important risk factor not only for short term but also for future growth performance. Although there is no professional recording system in the farms, it is seen that the results of the breeders' observations are consistent with the literature. In this study, it was determined that 71% of the participants thought that neonatal calf diarrhea negatively affected milk yield. This finding was found to be consistent with the results reported by Wilson-Abuelo et al. ( 2021 ) and Aghakeshmiri et al. ( 2017 ) (Aghakeshmiri et al. 2017 , Abuelo et al. 2021 ). There are many studies showing that female calves with diarrhea in the neonatal period show lower milk yield in the first lactation period (Svensson et al. 2006 , Aghakeshmiri et al. 2017 ). However, some studies have also reported that neonatal diarrhea has no significant effect on first lactation milk yield (Warnick et al. 1995 , Rossini 2004 ). Variability in field conditions such as the timing of veterinary intervention, experience of the specialist personnel, early diagnosis of the disease, treatment protocol, climatic conditions and the season in which the study was carried out may lead to differences in interpretation in such epidemiological observations (Aghakeshmiri et al. 2017 ). It has been reported in the literature that diarrhea in calves during the neonatal period has negative effects not only on growth and milk yield, but also on reproductive performance (Aghakeshmiri et al. 2017 , Urie et al. 2018 ). In this study, approximately 25% of the participants stated that they observed 11–30% infertility or fertility problems in the adult period in calves with diarrhea in the neonatal period. It is reported that in heifers with diarrhea in the neonatal period, the age at first calving is delayed and therefore prolongation of both the reproductive cycle and birth interval occurs (Aghakeshmiri et al. 2017 ). This prolongation is not only limited to a decrease in the number of births, but also causes the calves born to be born with a lower live weight and thus the negative effect is carried to the next generation. In this framework, it can be said that calves with neonatal diarrhea cause a significant economic loss by disrupting not only development but also reproductive performance. As a matter of fact, in this study, the rate of calves with developmental retardation due to diarrhea cases was found to be approximately 18% and the mortality rate was 16%, which directly decreases the presence of calves and indirectly reduces the future milk, meat and reproductive potential of the enterprise. Indeed, in the economic modelling study conducted by Riley et al. ( 2019 ), it was shown that mortality in the neonatal period is not only limited to direct losses per calf, but also has significant negative effects on milk yield, fertility and culling rates in the herd in the long term. In this context, it was stated that diarrhea-related losses in the neonatal period have a significant share in the total production cost and have suppressive effects on the profitability of the enterprise in the long term. In the logistic analysis, the first five variables (Monthly Income, Age of Owner, Type of Enterprise, Work Experience, Type of Barn) did not have a statistically significant effect on calf diarrhea. However, although the variable ‘type of barn’ did not reach statistical significance level (p = 0.075), the Odds Ratio (OR = 0.346) obtained indicates that the semi-open barn system may have a potential protective effect on calf diarrhea. Niilo ( 1970 )reported that in Alberta, Canada, coccidiosis cases in unsheltered calves in winter were affected by outdoor conditions compared to sheltered calves. Thakur ( 2015 ) reported that based on the differences between shelter types, shelter density (low area) causes higher parasitic load. Accordingly, it is necessary to look at environmental conditions as a whole. In parallel with our study finding. Lorenz et al. ( 2011 ) emphasised that appropriate environmental conditions (air flow, humidity control, prevention of ammonia accumulation) play a decisive role on the immune functions of calves and increase resistance against infectious agents. In this context, it can be said that semi-open barn structures have the potential to reduce the pathogen load through natural ventilation compared to closed structures. In the study, it was determined that the variables of ‘birth barn and calf barn’ had a statistically significant effect on calf diarrhea. Accordingly, it was determined that the probability of diarrhea was 81% lower in holdings with a birth pen than in those without a birth barn, while the probability of diarrhea was 71% lower in holdings with a calf barn than in those without a birth barn. In parallel with the finding of this study, Klein-Jöbstl et al ( 2014 ) reported that the rate of calf diarrhea was 32.2% in holdings with a birth barn and 57.9% in holdings without a birth barn. As a matter of fact, the presence of a birth barn allows the calf to gain its first immunity in a separate and hygienic environment after birth, while reducing its contact with infectious agents and reducing the general stress level (Lorenz et al. 2011 , Cho and Yoon 2014 ). Likewise, keeping calves in separate barns reduces the risk of cross-infection, provides individual monitoring and allows better control of hygiene conditions. For this reason, before calves are taken into the calving barn and before they are placed in the calving barn, the cleanliness and hygiene criteria of these areas must be ensured. In the analysis, it was determined that the variable of giving colostrum to calves within 4 hours after birth had a statistically highly significant and strong protective effect on calf diarrhea. In parallel with the finding of this study, Yüceer ( 2008 ) reported that 25% of the calves with insufficient serum antibody levels had the disease in the neonatal period, while only 5% of the calves with sufficient antibody levels had the disease. Smith et al. ( 2014 ) reported that 93 (71.5%) of a total of 130 calves receiving inadequate colostrum became ill at least once and 23 (17.7%) of them died. Therefore, it was seen that adequate and high quality colostrum intake in the first hours after birth is critical to provide protection against calf diseases and mortality (Kara and Ceylan 2021 ). In the study, it was determined that hygiene practices play a critical role in the prevention of neonatal calf diarrhea as well as timely and adequate transfer of passive immunity. In particular, the variables of ‘calf suckling’ and ‘teat cleaning’ were found to have highly statistically significant and strong protective effects on calf diarrhea. It was determined that timely and adequate transfer of passive immunity and hygiene practices play a synergistic role in the prevention of neonatal calf diarrhea. Passive immunity provides a humoral defence shield against pathogens by transferring maternal immunoglobulins to the calf through colostrum, while hygienic practices prevent direct transmission of pathogens to the calf. In this context, it was found that calf suckling and teat cleaning variables had highly statistically significant protective effects. While the calf's natural sucking behaviour ensures that colostrum is rapidly taken up from the neonatal intestines before the absorption window closes, teat hygiene minimises the risk of infection by preventing the entry of pathogens into the calf's digestive system with colostrum during this process. The coordinated management of these two factors is critical in reducing the incidence of calf diarrhea. Lorenz et al. ( 2011 ) emphasised that intake of colostrum in sufficient quantity and quality within the first two hours after birth is decisive for the success of passive immune transfer, rather than the way in which colostrum is given. In particular, bottle colostrum feeding provides advantages in terms of measurability, ease of application and providing an alternative in calves with weak sucking reflex. Keleş et al. ( 2022 ) reported that bottle-administered colostrum, especially when given under hygienic conditions, reduces the risk of transmission of pathogens such as E. coli and coronavirus and contributes positively to the development of immune response in calves. As a matter of fact, in the study, it was determined that the washing method of the bottle as well as bottle cleaning had a statistically significant and strong protective effect on calf diarrhea. In particular, cleaning with detergent, hot water or disinfectant reduces the pathogen load that may accumulate on the bottle and reduces the possibility of calf infection. This finding suggests that feeding bottles are an effective tool in the prevention of neonatal infections when appropriate cleaning and disinfection protocols are applied. Walker et al. ( 1998 ) demonstrated that disinfection of feed and water containers significantly reduced the severity of neonatal diarrhea in a controlled experimental model. Cho and Yoon ( 2014 ) emphasised that environmental contamination and inadequate hygiene are among the main predisposing factors in the multifactorial nature of neonatal diarrhea. The findings of the study revealed that septicaemia vaccine administered to both calves and mothers during pregnancy provided a statistically highly significant and strong protective effect against neonatal calf diarrhea. In parallel with the finding of this study, Keleş et al. ( 2022 ) reported that the probability of developing major enteric pathogen-induced diarrhea in calves born to cows vaccinated with E. coli K99+, bovine rotavirus (BRV) and bovine coronavirus (BCoV) antigens in the last period of pregnancy was 3.5 times less compared to calves born to unvaccinated mothers. In the same study, it was also reported that the likelihood of diarrhea caused by Cryptosporidium spp. increased 1.9 times in calves whose mothers were not vaccinated (Keleş et al. 2022 ). However, the prevalence of vaccination practices in Türkiye is still not at the desired level. In a study conducted by Özdemir et al. ( 2023 ) in Erzurum province, it was determined that 79.8% of the breeders did not vaccinate their pregnant cows against septicaemia. This rate reveals both the lack of awareness and the inadequacy of preventive medicine practices at the field level. It can be stated that maternal vaccination, especially before birth, both supports herd immunity and significantly reduces the risk of infection in the first weeks by increasing the level of passive immunity in newborn calves (Lorenz et al. 2011 , Cho and Yoon 2014 ). The possible reasons for the decreased risk of diarrhea in spring in our study may be that the air temperature and humidity conditions are not as favourable as winter and summer for the proliferation of pathogens during this period and at the same time calves are under less environmental stress. This may be interpreted as the fact that environmental temperature and humidity conditions are more stable in spring months, which reduces stress levels in calves and allows the immune system to work more effectively. Walker et al. ( 1998 ) and Cho & Yoon ( 2014 ) reported that extreme heat and cold temperatures may increase susceptibility to infections by suppressing the immune system, so moderate seasons may carry a relatively lower risk. In support of this seasonal finding, it was also found that the risk of diarrhea was approximately 64.5% lower in temperate and Mediterranean climate zones than in continental climate zones (OR = 0.355; p = 0.076). Although this latter finding is at the borderline statistically significant level, it shows a protective trend in direction and points to the effect of climatic environment on the environmental spread of pathogens and the immune capacity of the calf. Keleş et al. ( 2022 ) reported that the risk of diarrhea caused by E. coli K99 + was significantly higher in calves born in autumn compared to those born in other seasons and this risk increased 3.6 times compared to those born in spring. Similarly, Gulliksen et al. ( 2009 ) reported that the incidence of diarrhea was significantly increased in calves born in winter, especially in calves born in February, with the highest diarrhea rate of 37.9%. This finding is in parallel with Frank and Kaneene ( 1993 ) who reported that cold weather conditions increase susceptibility to pathogens in relation to immunosuppression and stress. In addition, Hur et al. ( 2013 ) reported that most of the calf deaths occurred in winter (48.6%) and autumn (21.2%). Also in another study, it was reported that heat stress effected the colostrum quality. In this study it has been stated that cows should be protected heat stress during and after the postpartum period. Heat stress reduce the colostrum quality and these situation predisposes calves to the diseases (Kara and Güven 2024 ). However, some studies have obtained different results on seasonal effects. For example, the effect of seasonal variation could not be clearly confirmed in the studies conducted by Svensson et al. ( 2006 ) in Sweden. This shows that environmental factors should be considered not only in terms of climate but also in interaction with other variables such as management practices, shelter structure, hygiene conditions and herd density. The findings of the study indicate that producer experience is an important determinant of the occurrence of neonatal calf diarrhea. In particular, it was found that the risk of diarrhea was approximately 5.5 times higher in producers with low level of work experience (OR = 5.49; p = 0.041). This finding points to the weak effect of lack of knowledge and poor practice in herd management on the prevention of infectious diseases in the neonatal period. Considering that the level of experience reflects not only individual knowledge but also compliance with hygiene protocols, early symptom recognition and appropriate intervention skills, the clinical and economic implications of this difference become more evident. In contrast, some other managerial variables assessed in the study did not show a statistically significant effect. Age, management type, application of baticon to the umbilical region after birth and umbilical cord tying did not stand out as a significant determinant of calf diarrhea (p > 0.10). In particular, there was no statistically significant relationship between the variables ‘application of baticon to the umbilical region’ and ‘tying the umbilical cord’ and neonatal calf diarrhea (p > 0.10). This result suggests that the protective effect of these practices on the development of diarrhea may be limited or indirect. However, this finding does not mean that these practices are insignificant, but rather that these practices alone are not effective in a disease with a multifactorial etiology such as diarrhea. Age, management type, application of baticon to the umbilical region after birth and umbilical cord clamping were not found to be significant determinants of calf diarrhea (p > 0.10). In particular, there was no statistically significant relationship between the variables ‘application of baticon to the umbilical region’ and ‘tying the umbilical cord’ and neonatal calf diarrhea (p > 0.10). This result suggests that the protective effect of these practices on the development of diarrhea may be limited or indirect. However, this finding does not indicate that these practices are insignificant, but rather that they are not determinant alone in a disease with multifactorial etiology such as diarrhea. However, the lack of a clear effect of umbilical applications directly on the incidence of diarrhea suggests that these applications are more effective in preventing septicaemia, omphalophlebitis and local umbilical infections. In a study by Bendali et al. ( 1999 ), the rate of diarrhea was reported to be 9.6% in calves with navel disinfection and 8.4% in those without disinfection and this difference was found to be statistically significant (p = 0.05). This suggests that umbilical disinfection alone may have a limited effect in reducing the risk of diarrhea, but may become more significant when evaluated in combination with multiple protective practices. Conclusion In this study, it was determined that neonatal calf diarrhea is not only limited to short-term morbidity and mortality rates, but also has long-term effects on growth performance, milk yield and reproductive capacity. In this respect, neonatal diarrhea should be considered as a multifaceted production risk that has critical importance not only in the field of veterinary health but also at the level of business economics and herd management. Increasing migration from rural to urban areas and lack of qualified labour force in Türkiye, difficulties in providing trained personnel in livestock enterprises, especially in small and medium-sized enterprises, and the fact that individual breeders mostly adhere to traditional knowledge and practices indicate that the high morbidity and mortality rates observed in diarrhea cases may be associated with unsuitable environmental conditions and inadequate management practices. The findings of the study indicate that factors such as feeding method and practice, hygiene protocols, equipment cleaning, postnatal care and environmental management should be addressed in an integrated manner in the prevention of neonatal calf diarrhea. In particular, the administration of colostrum in adequate amounts and under hygienic conditions in the first hours after birth plays a decisive role in reducing both diarrhea incidence and mortality rates. Accordingly, the preventive health protocols to be developed should be based not only on clinical practices but also on sustainable management strategies that can be implemented at the enterprise level. In conclusion, the dissemination of practices for the prevention of neonatal calf diarrhea in the field is of great importance not only for improving animal welfare but also for maintaining herd regeneration capacity and sustainability of enterprise profitability. In this context, it is necessary to focus on the feasibility of implementing site-specific intervention strategies by supporting education-based extension activities and training . Declarations Competing Interest The authors have no relevant financial or non-financial interests to disclose. Ethics Approval This is an observational study. The Animal Research Ethics Committee of Kırıkkale University has confirmed that no ethical approval is required. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection performed by Yasin PARLATIR, Seyfettin TUNCEL and analysis were made by Pınar AYVAZOĞLU DEMİR, Seyfettin TUNCEL. The manuscript was written by Yasin PARLATIR, Seyfettin TUNCEL, Pınar AYVAZOĞLU DEMİR. All authors read and approved the final manuscript. Data Availability The data supporting this study's findings are available from the corresponding author upon reasonable request. References Abuelo A, Cullens F, Brester JL (2021) Effect of preweaning disease on the reproductive performance and first-lactation milk production of heifers in a large dairy herd. 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13:27:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":887877,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7462598/v1/7af71f8d-c48a-43e9-833d-14afbe10378c.pdf"},{"id":93142115,"identity":"50185733-2e28-4664-b73e-5ef082feafc4","added_by":"auto","created_at":"2025-10-09 13:11:04","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":795797,"visible":true,"origin":"","legend":"","description":"","filename":"renamed0d7d2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7462598/v1/2e4a6a78ff08af7b65d72f1a.pdf"}],"financialInterests":"","formattedTitle":"The Relationship of Neonatal Calf Diarrhea and Yield Losses with Managerial Factors in Dairy Cattle Farms","fulltext":[{"header":"Introduction","content":"\u003cp\u003eReducing mortality and morbidity rates in the neonatal calf period is of strategic importance for the sustainability of milk and red meat production in T\u0026uuml;rkiye. The healthy survival of newborn calves is a critical parameter not only in terms of animal welfare, but also in terms of the economic efficiency of livestock enterprises and the protection of animal production potential at national level. It was reported that 15% of approximately 6\u0026nbsp;million calves born in T\u0026uuml;rkiye in 2022 died during calving period (Turk and Emlik \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). When the calf mortality rates in T\u0026uuml;rkiye compared with the worldwide, the studies reported that Denmark has 6.7% mortality ratio in calves, in Norway 4.4%, in Sub-Saharan Africa region 12% and Ethiopia has the 22% ratio rates (\u0026Oslash;ster\u0026aring;s et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, Wudu et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). These results shows that T\u0026uuml;rkiye is among the high-risk countries in terms of neonatal calf losses.\u003c/p\u003e\u003cp\u003eThe majority of these losses in the neonatal period occur in the first 28 days of life when the immune system is not yet developed and calves are dependent on passive immunity. This period is a critical time period in which approximately 75% of total calf losses occur (Bartels et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Fanda \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The main health problems seen during this period include diarrhea, pneumonia and sepsis, and diarrhea is usually the disease with the most significant share in calf mortality (Cho and Yoon \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Aydoğdu et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn T\u0026uuml;rkiye, diarrheal morbidity rates in neonatal calves were reported as 25.7% by Arslan et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) and 22.9% by Tokg\u0026ouml;z et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) (Arslan et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2001\u003c/span\u003e, Tokg\u0026ouml;z et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These ratios corresponds to the upper limit of the levels reported in European countries, ranging from 5 to 23 per cent (Waltner-Toews et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1986\u003c/span\u003e, Windeyer et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Murray et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Wilson et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this context, it is considered that morbidity rates in T\u0026uuml;rkiye are quite high and this situation poses a serious threat to both animal health and economic productivity.\u003c/p\u003e\u003cp\u003eCalf mortality during the neonatal period is known to affect not only animal welfare but also total factor productivity in animal production and national income. Indeed, in 2006, the economic losses attributed to neonatal calf losses in countries such as Norway, Finland, Sweden and Denmark were reported as \u0026euro;9.5\u0026nbsp;million, \u0026euro;48\u0026nbsp;million, \u0026euro;7.4\u0026nbsp;million and \u0026euro;40\u0026nbsp;million, respectively (\u0026Oslash;ster\u0026aring;s et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In T\u0026uuml;rkiye, this loss was reported to be around \u0026euro; 525\u0026nbsp;million (Şahal et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These differences are directly related to animal population size, morbidity rates and the effectiveness of biosecurity measures between countries.\u003c/p\u003e\u003cp\u003eIn the etiopathogenesis of neonatal diarrhea, the frequency of bacterial (especially ETEC K99+), viral (BRV, BCoV) and protozoal (\u003cem\u003eCryptosporidium\u003c/em\u003e spp., \u003cem\u003eGiardia\u003c/em\u003e spp.) agents as mixed infections is high and this increases the severity of the clinical picture (Blanchard \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Dall Agnol et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, G\u0026uuml;reli and Kara \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, environmental (temperature, humidity, disinfection, ventilation) and management (colostrum quality, umbilical hygiene, vaccination programme, herd structure) factors also have a significant impact on the incidence of the disease (Frank and Kaneene \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1993\u003c/span\u003e, Keleş et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Yanar \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThis study aims to determine the prevalence of calf losses caused by neonatal diarrhea cases, to reveal the morbidity and mortality rates related to these losses and also to identify the predisposing factors affecting this situation and to analyse their risk levels based on surveys and field observations conducted throughout T\u0026uuml;rkiye. Indeed, the fact that epidemiological prevalence data on the prevalence of neonatal calf diarrhea in T\u0026uuml;rkiye are supported by a limited number of studies reveals the need for up-to-date and comprehensive data at national level. In this context, the findings of this study are expected to contribute to the improvement of animal husbandry policies and the development of sustainable animal production strategies.\u003c/p\u003e"},{"header":"Material Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Collection and Sample Size\u003c/h2\u003e\u003cp\u003eWithin the scope of this study, dairy cattle farms operating in different geographical regions of T\u0026uuml;rkiye were interviewed in order to estimate the economic losses caused by diarrhea during the neonatal calf period. The sample size of the study was determined by taking into account the population size of dairy cattle farms operating in T\u0026uuml;rkiye. In the sample size calculation with 95% confidence level and \u0026plusmn;\u0026thinsp;10% margin of error, the minimum required sample size was calculated as 96 enterprises. However, in order to increase the representativeness of the study, face-to-face interviews were conducted with a total of 115 enterprises selected by simple random sampling method to cover seven geographical regions of T\u0026uuml;rkiye and who agreed to answer the questionnaire. The data were collected in 2025.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSurvey Data\u003c/h3\u003e\n\u003cp\u003e The data were evaluated about the capacity of enterprises and producing abilities according to the information received from the breeders and the experience of the breeders. For this purpose, numbers of breeding cows, born calf, diarrheic calf, dead calf and ill thrift calf were taken part in the survey. The enterprises were classified as small, middle and large scale with the numbers of cattle. According to classification, all groups were evaluated with each other.\u003c/p\u003e\u003cp\u003eThe yield loss were evaluated associated with diarrhea according to taken data. The ratios of diarrhea, dead causing from diarrhea, ill thrift calves, loss of weight and the percentage of milk yield loss were recorded in the survey. These data were analyzed with descriptive statistics parameters and logistic regression models. At the same time, the vaccination status of cows and calves was recorded. The types of enterprises, production types, the presence of calving pens and calf units were evaluated. In addition to these data, calf feeding methods and postnatal application of colostrum were included in the questionnaire study. The climatic characteristics of the enterprises were recorded. Also the months of the diarrhea was noted. Bottle cleaning, bottle cleaning method, umbilical cord disinfection and umbilical cord tying status were included in the disinfection procedures related to calf diarrhoea. All data were expressed as percentages and analysed by logistic regression methods.\u003c/p\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eThe aim of this study was to investigate the prevalence and mortality of neonatal calf diarrhea and the management factors affecting them in cattle farms in T\u0026uuml;rkiye. For this purpose, logistic regression model was used in the study. Logistic ordinal regression is one of the commonly used analysis methods when the dependent variable is ordinal (1, 2, 3), and it is preferred because it does not require normality assumption and its results are easy to interpret.\u003c/p\u003e\u003cp\u003eThe logistic ordinal regression model is based on the odds ratio and the maximum likelihood method is used to estimate the model parameters. With this method, the probabilities of the dependent variable against the determined independent variables and the effect sizes of each variable can be calculated reliably. The results of the analyses are presented with odds ratios and 95% confidence intervals. In addition, the ANOVA test for independent samples was used to analyse the differences between variables and the Chi-square (χ\u0026sup2;) test was used to determine the relationships between various discrete (categorical) variables. Statistical significance level was accepted as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in all tests.\u003c/p\u003e\u003cp\u003eAll analyses were performed using SPSS 26.0 and Excel package programmes. Ethical principles were observed in the study and verbal and written informed consent was obtained from the participants. It was reported by the Ethics Committee of Kırıkkale University that this study did not require ethics committee approval.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWithin the scope of the study, as of 2025, the average number of cows per enterprise was 82.38\u0026thinsp;\u0026plusmn;\u0026thinsp;125.09 and the average number of calves born was 57.83\u0026thinsp;\u0026plusmn;\u0026thinsp;108.53, and it was determined that there were 10,720 breeding cows and 7,724 calves in total (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the study, the average number of calves with diarrhea per farm was 11.26\u0026thinsp;\u0026plusmn;\u0026thinsp;23.13, 1.296 calves had diarrhea in total and the rate of calves with diarrhea was 26.81\u0026thinsp;\u0026plusmn;\u0026thinsp;18.78%. The distribution of the number of sick, dead and illthrift calves according to the scale of the enterprise is given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe number of sick, dead, illthrift, born calves and breeding cows.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParametre\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmall-Scale Enterprise\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMiddle-Scale Enterprise\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLarge-Scale Enterprise\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF / p\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBreeding Cow\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e7,47\u0026thinsp;\u0026plusmn;\u0026thinsp;2,34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e27,21\u0026thinsp;\u0026plusmn;\u0026thinsp;11,45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e214,68\u0026thinsp;\u0026plusmn;\u0026thinsp;150,50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e82,38\u0026thinsp;\u0026plusmn;\u0026thinsp;125,09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e65,560 / \u0026lt;0,01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBorn Calf\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5,17\u0026thinsp;\u0026plusmn;\u0026thinsp;2,15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e18,88\u0026thinsp;\u0026plusmn;\u0026thinsp;9,90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e151,05\u0026thinsp;\u0026plusmn;\u0026thinsp;154,60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e57,83\u0026thinsp;\u0026plusmn;\u0026thinsp;108,53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30,910 / \u0026lt;0,01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiarrhea\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1,30\u0026thinsp;\u0026plusmn;\u0026thinsp;1,02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4,60\u0026thinsp;\u0026plusmn;\u0026thinsp;3,55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e28,00\u0026thinsp;\u0026plusmn;\u0026thinsp;35,32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e11,26\u0026thinsp;\u0026plusmn;\u0026thinsp;23,13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19,018 / \u0026lt;0,01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDead Calf\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0,27\u0026thinsp;\u0026plusmn;\u0026thinsp;0,58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0,85\u0026thinsp;\u0026plusmn;\u0026thinsp;1,30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e4,65\u0026thinsp;\u0026plusmn;\u0026thinsp;5,62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e1,92\u0026thinsp;\u0026plusmn;\u0026thinsp;3,79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18,785 / \u0026lt;0,01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eİllthrift Calf\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0,30\u0026thinsp;\u0026plusmn;\u0026thinsp;0,65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1,02\u0026thinsp;\u0026plusmn;\u0026thinsp;1,37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5,86\u0026thinsp;\u0026plusmn;\u0026thinsp;16,77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e2,39\u0026thinsp;\u0026plusmn;\u0026thinsp;9,77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3,654 / 0,029\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the survey results, it was reported that the mortality rate due to diarrhea was below 10% in 52.2% of the holdings, the average number of calves die per holding was 1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;3.79, 221 calves in total died due to diarrhea and the average mortality rate due to diarrhea in the holdings was 15.58\u0026thinsp;\u0026plusmn;\u0026thinsp;20.49%. In the study, the number of calves with developmental retardation was determined as 2.39\u0026thinsp;\u0026plusmn;\u0026thinsp;9.78 per farm and 275 in total, and the average rate of calves with developmental retardation due to diarrhea was calculated as 18.29\u0026thinsp;\u0026plusmn;\u0026thinsp;27.77%.\u003c/p\u003e\u003cp\u003eIn the study, the health and productivity losses due to neonatal calf diarrhea and their rates are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHealth and productivity loss rates due to calf diarrhea\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOption\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eThe ratio of diarrhea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder the %10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24,3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%11\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%31 and higher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e43,5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26,8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eThe ratio of death according to diarrhea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder the %10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e52,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%11\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%21\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18,3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eThe ratio of illthrift according to diarrhea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder the %10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57,4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%11\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e42,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18,3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eThe loss of weight gain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder the %10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%11\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31,3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%21\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36,5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eInfertility rate in calves with diarrhea in the future\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder the %10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20,9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%11\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%21\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot affected\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e53,9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eLoss of milk yield in calves with a history of diarrhea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder the %10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%11\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26,1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e%21\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot affected\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the study, it was determined that neonatal calf diarrhea caused a decrease in the live weight of calves in the majority of the holdings. When the rate of live weight loss due to diarrhea is examined in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, it is seen that 67.8% of the participants reported a decrease between 11\u0026ndash;30%. Similarly, 20.9% of the enterprises reported that the rate of infertility in calves in the following periods was 10% or less, and 53.9% of the enterprises reported that they did not encounter infertility problems in the following periods. On the other hand, 25.2% of the participants reported that this rate was between 11\u0026ndash;30%. According to the producers' reports, the rate of decrease in milk yield in the following period in calves with diarrhea was below 10% in 27.0% of the respondents and between 11\u0026ndash;30% in 47.8% of the respondents. 25.2% of the participants stated that diarrhea did not affect the milk yield of calves in the following period.\u003c/p\u003e\u003cp\u003eLogistic regression analysis was used to determine the factors affecting the incidence of diarrhea in livestock farms. Firstly, descriptive statistics of the variables included in the model are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In this table, the intensity of diarrhea cases (low, medium and high) as the dependent variable and parameters such as producer age, husbandry experience, annual income, type of enterprise, septicaemia vaccination, umbilical cord cleaning, teat and bottle cleaning as independent variables are included.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStatistics of the variables used in the logistic regression model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParametre\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrekans\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eY\u0026uuml;zde (n)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eSevere of Diarrhea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24,3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32,2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eEnterprise Type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDairy (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38,3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCombine (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61,7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eWorking Experience Time\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;10 year (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33,9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u0026ndash;20 year (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44,3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u0026ndash;50 year (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21,7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eStable type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSemi-open barns (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58,3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eClosed barns (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41,7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eBirth stalls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAvailable (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon available (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCalf stalls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAvailable (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon available (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGiving colostrum within the first 4 hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvery time (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e89,6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSometimes (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10,4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFeeding calf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWithout feeder (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29,6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWith feeder (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70,4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVaccination the calf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvery time (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRarely (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVaccination the cow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvery time (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46,1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRarely (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53,9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCleaning the teat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvery time (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRarely (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCleaning the feeder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72,2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eCleaning way to feeder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoiling(1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWith disinfectant (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45,2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOnly water (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCleaning the umbilical cord\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67,8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRarely (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32,2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eClamping the umbilical cord\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvery time (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44,3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSometimes (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12,2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eThe months of diarrhea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWinter (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42,6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpring (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35,7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSummer (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21,7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eClimate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate, Hot (Egean, Marmara, Meditarrenean, Black sea) (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46,1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eContinental Climate (East, Southern East, Cantral Anatolia) (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53,9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the study, the significance and fit of the ordinal logistic regression model established to determine the factors affecting the intensity of diarrhea in livestock farms were evaluated. It was determined that the model was generally significant and well fitted to the data. The results regarding the fit and explanatory power of the model are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFit and explanatory test results for ordinal logistic regression model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eModel Fitting Information\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2 Log Likelihood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChi-Square\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept Only\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e246,321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFinal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e143,875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e102,446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e,000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGoodness-of-Fit\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChi-Square\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePearson\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e194,780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,684\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeviance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e143,875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePseudo R-Square\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCox and Snell\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,590\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNagelkerke\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,668\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMcFadden\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,416\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e is analysed, in the Model Fitting Information section, which shows that the model is generally significant, when the model with only constant term and the final model with the addition of independent variables are compared, it is seen that the \u0026minus;\u0026thinsp;2 Log Likelihood value of the final model decreased significantly (143.875) and the difference is statistically significant (χ\u0026sup2; = 102.446; df\u0026thinsp;=\u0026thinsp;23; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eIn the Goodness-of-Fit tests evaluating the fit of the model to the data, the p-values of both Pearson (p\u0026thinsp;=\u0026thinsp;0.684) and Deviance (p\u0026thinsp;=\u0026thinsp;0.999) tests being greater than 0.05 indicate that the model fits the data well. Pseudo R-Square values showing the level of the model explaining the variance of the dependent variable were found as Cox \u0026amp; Snell R\u0026sup2; = 0.590, Nagelkerke R\u0026sup2; = 0.668 and McFadden R\u0026sup2; = 0.416, respectively. Especially Nagelkerke R\u0026sup2; value (65.2%) shows that the independent variables of the model explain a significant portion of the variance in the dependent variable. It can be said that the ordinal logistic regression model created in line with these data is a statistically significant model that fits the data well and has a strong explanatory power.\u003c/p\u003e\u003cp\u003eThe results of the logistic regression analysis applied to determine the factors affecting the intensity of diarrhea in livestock farms are given in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe results of logistic regression analysis of the survey parameters\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eWald\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eOdds Ratio OR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e95% Confidence Interval\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLower Bound\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eUpper Bound\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonthly income (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-5,425\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,381\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,575\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,201\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0,032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,969\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-0,091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,026\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnterprise Type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,623\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e,126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1,247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,723\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-1,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,441\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorking Experience Time\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,179\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5,485\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,041*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3,333\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStable Type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1,060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3,171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,075*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-2,228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBirth Stalls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1,642\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,663\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6,126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,013**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-2,942\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0,342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalf Stalls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1,239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,644\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3,702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,290\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,054*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-2,502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,023\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGiving Colostrum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-3,539\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,336\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7,021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,008**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-6,157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0,921\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeeding Calf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2,859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8,890\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,003**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-4,739\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0,980\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVaccination the Calf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-3,102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,708\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19,184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,000***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-4,490\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-1,714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVaccination the Cow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2,806\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18,150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,000***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,220\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCleaning the teat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1,632\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7,392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,007**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-2,808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0,455\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCleaning the feeder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2,559\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9,215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,002**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-4,211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0,907\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of cleaning feeder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1,419\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,717\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3,920\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,048*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-2,825\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0,014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCleaning the umbilical cord\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,709\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e,176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1,347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,674\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-1,092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1,688\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClamping the umbilical cord\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0,243\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e,220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,784\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,639\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-1,257\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,771\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonth of diarrhea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1,634\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,737\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4,915\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,027*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-3,078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0,189\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClimate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1,035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3,141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,355\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,076*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-2,180\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e*,**,***Statistically signifance\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the study, it was determined that the average age of the participants was 36.64\u0026thinsp;\u0026plusmn;\u0026thinsp;10.45 years and the average duration of animal husbandry experience was 16.01\u0026thinsp;\u0026plusmn;\u0026thinsp;8.78 years. In the study, it was determined that the livestock enterprises earned an average annual income of 50.991\u003cspan\u003e$\u003c/span\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows that hygiene and care practices significantly reduced the risk of diarrhea. In the study, it was determined that the risk of diarrhea was significantly lower in calves that received colostrum within the first 4 hours compared to those that did not receive colostrum (OR\u0026thinsp;=\u0026thinsp;0.029; p\u0026thinsp;=\u0026thinsp;0.008). Similarly, it was found that the risk of diarrhea was significantly lower in calves fed with breast milk (OR\u0026thinsp;=\u0026thinsp;0.06; p\u0026thinsp;=\u0026thinsp;0.003), calves and mothers were vaccinated against septicaemia (OR\u0026thinsp;=\u0026thinsp;0.045; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; OR\u0026thinsp;=\u0026thinsp;0.06; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), calves cleaned teat before suckling (OR\u0026thinsp;=\u0026thinsp;0.20; p\u0026thinsp;=\u0026thinsp;0.007) and bottle cleaned (OR\u0026thinsp;=\u0026thinsp;0.08; p\u0026thinsp;=\u0026thinsp;0.002). In addition, washing the bottle with detergent and/or disinfectant was found to reduce the risk of diarrhea by approximately 76% compared to bottles rinsed with water only (OR\u0026thinsp;=\u0026thinsp;0.24; p\u0026thinsp;=\u0026thinsp;0.048).\u003c/p\u003e\u003cp\u003eIn the analysis, it was determined that housing structure was associated with diarrhea cases in the holdings. It was found that the risk of diarrhea decreased in holdings with birth stalls (OR\u0026thinsp;=\u0026thinsp;0.19; p\u0026thinsp;=\u0026thinsp;0.013) and calf stalls (OR\u0026thinsp;=\u0026thinsp;0.29; p\u0026thinsp;=\u0026thinsp;0.054) and semi-open barns (OR\u0026thinsp;=\u0026thinsp;0.35; p\u0026thinsp;=\u0026thinsp;0.075). In the study, it was also found that the risk of diarrhea was significantly lower in spring compared to winter and summer (OR\u0026thinsp;=\u0026thinsp;0.19; p\u0026thinsp;=\u0026thinsp;0.027). Similarly, it was determined that the risk of diarrhea was approximately 64.5% lower in regions with temperate and Mediterranean climate than in regions with continental climate (OR\u0026thinsp;=\u0026thinsp;0.355; p\u0026thinsp;=\u0026thinsp;0.076), but this relationship was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.10).\u003c/p\u003e\u003cp\u003eIn the study, it was also determined that the risk of diarrhea was approximately 5.5 times higher in producers with low work experience (OR\u0026thinsp;=\u0026thinsp;5.49; p\u0026thinsp;=\u0026thinsp;0.041). On the other hand, there was no statistically significant relationship between age, type of enterprise, application of baticon to the umbilical region after birth, umbilical cord clamping and the risk of diarrhea (p\u0026thinsp;\u0026gt;\u0026thinsp;0.10).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe neonatal period in calves is used to define the first 28 days after birth (Sayber and Kabu \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Successful management of this period is among the basic policies of both T\u0026uuml;rkiye and the global livestock sector worldwide. Accordingly, diarrhea is among the most common and most important factors that result in calf loss in the neonatal period (Aydoğdu et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Global prevalence rates of neonatal calf diarrhea in the literature range from 5\u0026ndash;25%, depending on regional differences, management conditions and the effectiveness of animal health services (Wilson et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this study, the prevalence of neonatal calf diarrhea was determined as 26.81% as a result of field surveys conducted in different geographical regions of T\u0026uuml;rkiye. While this prevalence value is close to the 23% rate reported in Canada, it is lower than the rates reported in the USA (38.5%), South Korea (53%) and Iran (58%) (Windeyer et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Gomez and Weese \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Urie et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). When evaluated in terms of epidemiological data specific to T\u0026uuml;rkiye, in a systematic review conducted by Kozat (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), it was reported that the prevalence of neonatal diarrhea was above 50% in field studies based on etiological agents in different regions and enterprises throughout the country (Kozat \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, this review may have some limitations in terms of representing the general prevalence, since it was formed by bringing together studies focusing on specific agents. Accordingly, the prevalence value of 26.81% obtained in the present study suggests that neonatal diarrhea cases in T\u0026uuml;rkiye are common but within the limits of diarrhea rates reported worldwide.\u003c/p\u003e\u003cp\u003eNeonatal period is defined as the most risky period in terms of morbidity and mortality in all farm animals (Mee \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). 66% of the morbidity rates of calves in the first 6 months and all of the mortality rates in the first year are associated with diseases encountered in the first 6 months of life (Todd et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Barry et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In this study, the average mortality rate due to neonatal calf diarrhea in livestock farms in T\u0026uuml;rkiye was calculated as 15.58\u0026thinsp;\u0026plusmn;\u0026thinsp;20.49%. This rate shows a significant consistency when compared with the global data reported in the literature. As a matter of fact, in a study conducted in cow-calf farms in the USA, it was reported that digestive system-related calf mortality rates ranged between 14% and 23% (Maier et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similarly, Urie et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported that digestive system diseases had a 32% share in calf mortality (Urie et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In a field study conducted by Ider et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) in T\u0026uuml;rkiye, 56.4% of calf deaths were reported to be associated with neonatal diarrhea (Ider et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These data clearly demonstrate that diarrhea in the neonatal period causes not only high morbidity but also serious mortality. As a matter of fact, this situation causes serious damages to national economies (H\u0026auml;sler et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOne of the long-term effects of neonatal diarrhea is that it reduces the calf's growth potential, causing significant reductions in weaning weight and daily weight gain (Abuelo et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Wilson et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this study, a decrease in live weight gain ranging between 11\u0026ndash;30% was found in calves with diarrhea in the neonatal period. This finding is largely in agreement with the results reported in the literature. Wittum et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) reported that calves with diarrhea in the neonatal period had an average 10.7 kg lower weaning weight (Wittum et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Similarly, Donovan et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) reported that calves treated for diarrhea showed approximately 9.1 kg less weight gain at 180 days of age (Donovan et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Sutherland et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Gaharshahi et al. (2021) reported that neonatal diarrhea prolongs the length of stay in calves and this process leads to a decrease in milk consumption and hampers growth (Sutherland et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Goharshahi et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIt has been reported that health problems encountered in the neonatal period cause height development and decreases in carcass yield in calves (Van Der Fels-Klerx et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, Aghakeshmiri et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It has also been reported that calves with lower weights in the peripubertal period grow more slowly and reach adulthood at a later age (Mioč et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This situation reveals that neonatal calf diarrhea is an important risk factor not only for short term but also for future growth performance. Although there is no professional recording system in the farms, it is seen that the results of the breeders' observations are consistent with the literature.\u003c/p\u003e\u003cp\u003eIn this study, it was determined that 71% of the participants thought that neonatal calf diarrhea negatively affected milk yield. This finding was found to be consistent with the results reported by Wilson-Abuelo et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Aghakeshmiri et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) (Aghakeshmiri et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Abuelo et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). There are many studies showing that female calves with diarrhea in the neonatal period show lower milk yield in the first lactation period (Svensson et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, Aghakeshmiri et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, some studies have also reported that neonatal diarrhea has no significant effect on first lactation milk yield (Warnick et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1995\u003c/span\u003e, Rossini \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Variability in field conditions such as the timing of veterinary intervention, experience of the specialist personnel, early diagnosis of the disease, treatment protocol, climatic conditions and the season in which the study was carried out may lead to differences in interpretation in such epidemiological observations (Aghakeshmiri et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIt has been reported in the literature that diarrhea in calves during the neonatal period has negative effects not only on growth and milk yield, but also on reproductive performance (Aghakeshmiri et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Urie et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this study, approximately 25% of the participants stated that they observed 11\u0026ndash;30% infertility or fertility problems in the adult period in calves with diarrhea in the neonatal period. It is reported that in heifers with diarrhea in the neonatal period, the age at first calving is delayed and therefore prolongation of both the reproductive cycle and birth interval occurs (Aghakeshmiri et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This prolongation is not only limited to a decrease in the number of births, but also causes the calves born to be born with a lower live weight and thus the negative effect is carried to the next generation. In this framework, it can be said that calves with neonatal diarrhea cause a significant economic loss by disrupting not only development but also reproductive performance. As a matter of fact, in this study, the rate of calves with developmental retardation due to diarrhea cases was found to be approximately 18% and the mortality rate was 16%, which directly decreases the presence of calves and indirectly reduces the future milk, meat and reproductive potential of the enterprise. Indeed, in the economic modelling study conducted by Riley et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), it was shown that mortality in the neonatal period is not only limited to direct losses per calf, but also has significant negative effects on milk yield, fertility and culling rates in the herd in the long term. In this context, it was stated that diarrhea-related losses in the neonatal period have a significant share in the total production cost and have suppressive effects on the profitability of the enterprise in the long term.\u003c/p\u003e\u003cp\u003eIn the logistic analysis, the first five variables (Monthly Income, Age of Owner, Type of Enterprise, Work Experience, Type of Barn) did not have a statistically significant effect on calf diarrhea. However, although the variable \u0026lsquo;type of barn\u0026rsquo; did not reach statistical significance level (p\u0026thinsp;=\u0026thinsp;0.075), the Odds Ratio (OR\u0026thinsp;=\u0026thinsp;0.346) obtained indicates that the semi-open barn system may have a potential protective effect on calf diarrhea. Niilo (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1970\u003c/span\u003e)reported that in Alberta, Canada, coccidiosis cases in unsheltered calves in winter were affected by outdoor conditions compared to sheltered calves. Thakur (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) reported that based on the differences between shelter types, shelter density (low area) causes higher parasitic load. Accordingly, it is necessary to look at environmental conditions as a whole. In parallel with our study finding. Lorenz et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) emphasised that appropriate environmental conditions (air flow, humidity control, prevention of ammonia accumulation) play a decisive role on the immune functions of calves and increase resistance against infectious agents. In this context, it can be said that semi-open barn structures have the potential to reduce the pathogen load through natural ventilation compared to closed structures.\u003c/p\u003e\u003cp\u003eIn the study, it was determined that the variables of \u0026lsquo;birth barn and calf barn\u0026rsquo; had a statistically significant effect on calf diarrhea. Accordingly, it was determined that the probability of diarrhea was 81% lower in holdings with a birth pen than in those without a birth barn, while the probability of diarrhea was 71% lower in holdings with a calf barn than in those without a birth barn. In parallel with the finding of this study, Klein-J\u0026ouml;bstl et al (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) reported that the rate of calf diarrhea was 32.2% in holdings with a birth barn and 57.9% in holdings without a birth barn. As a matter of fact, the presence of a birth barn allows the calf to gain its first immunity in a separate and hygienic environment after birth, while reducing its contact with infectious agents and reducing the general stress level (Lorenz et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, Cho and Yoon \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Likewise, keeping calves in separate barns reduces the risk of cross-infection, provides individual monitoring and allows better control of hygiene conditions. For this reason, before calves are taken into the calving barn and before they are placed in the calving barn, the cleanliness and hygiene criteria of these areas must be ensured.\u003c/p\u003e\u003cp\u003eIn the analysis, it was determined that the variable of giving colostrum to calves within 4 hours after birth had a statistically highly significant and strong protective effect on calf diarrhea. In parallel with the finding of this study, Y\u0026uuml;ceer (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) reported that 25% of the calves with insufficient serum antibody levels had the disease in the neonatal period, while only 5% of the calves with sufficient antibody levels had the disease. Smith et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) reported that 93 (71.5%) of a total of 130 calves receiving inadequate colostrum became ill at least once and 23 (17.7%) of them died. Therefore, it was seen that adequate and high quality colostrum intake in the first hours after birth is critical to provide protection against calf diseases and mortality (Kara and Ceylan \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the study, it was determined that hygiene practices play a critical role in the prevention of neonatal calf diarrhea as well as timely and adequate transfer of passive immunity. In particular, the variables of \u0026lsquo;calf suckling\u0026rsquo; and \u0026lsquo;teat cleaning\u0026rsquo; were found to have highly statistically significant and strong protective effects on calf diarrhea. It was determined that timely and adequate transfer of passive immunity and hygiene practices play a synergistic role in the prevention of neonatal calf diarrhea. Passive immunity provides a humoral defence shield against pathogens by transferring maternal immunoglobulins to the calf through colostrum, while hygienic practices prevent direct transmission of pathogens to the calf. In this context, it was found that calf suckling and teat cleaning variables had highly statistically significant protective effects. While the calf's natural sucking behaviour ensures that colostrum is rapidly taken up from the neonatal intestines before the absorption window closes, teat hygiene minimises the risk of infection by preventing the entry of pathogens into the calf's digestive system with colostrum during this process. The coordinated management of these two factors is critical in reducing the incidence of calf diarrhea. Lorenz et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) emphasised that intake of colostrum in sufficient quantity and quality within the first two hours after birth is decisive for the success of passive immune transfer, rather than the way in which colostrum is given. In particular, bottle colostrum feeding provides advantages in terms of measurability, ease of application and providing an alternative in calves with weak sucking reflex. Keleş et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported that bottle-administered colostrum, especially when given under hygienic conditions, reduces the risk of transmission of pathogens such as E. coli and coronavirus and contributes positively to the development of immune response in calves. As a matter of fact, in the study, it was determined that the washing method of the bottle as well as bottle cleaning had a statistically significant and strong protective effect on calf diarrhea. In particular, cleaning with detergent, hot water or disinfectant reduces the pathogen load that may accumulate on the bottle and reduces the possibility of calf infection. This finding suggests that feeding bottles are an effective tool in the prevention of neonatal infections when appropriate cleaning and disinfection protocols are applied. Walker et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) demonstrated that disinfection of feed and water containers significantly reduced the severity of neonatal diarrhea in a controlled experimental model. Cho and Yoon (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) emphasised that environmental contamination and inadequate hygiene are among the main predisposing factors in the multifactorial nature of neonatal diarrhea.\u003c/p\u003e\u003cp\u003eThe findings of the study revealed that septicaemia vaccine administered to both calves and mothers during pregnancy provided a statistically highly significant and strong protective effect against neonatal calf diarrhea. In parallel with the finding of this study, Keleş et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported that the probability of developing major enteric pathogen-induced diarrhea in calves born to cows vaccinated with E. coli K99+, bovine rotavirus (BRV) and bovine coronavirus (BCoV) antigens in the last period of pregnancy was 3.5 times less compared to calves born to unvaccinated mothers. In the same study, it was also reported that the likelihood of diarrhea caused by Cryptosporidium spp. increased 1.9 times in calves whose mothers were not vaccinated (Keleş et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the prevalence of vaccination practices in T\u0026uuml;rkiye is still not at the desired level. In a study conducted by \u0026Ouml;zdemir et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) in Erzurum province, it was determined that 79.8% of the breeders did not vaccinate their pregnant cows against septicaemia. This rate reveals both the lack of awareness and the inadequacy of preventive medicine practices at the field level. It can be stated that maternal vaccination, especially before birth, both supports herd immunity and significantly reduces the risk of infection in the first weeks by increasing the level of passive immunity in newborn calves (Lorenz et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, Cho and Yoon \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe possible reasons for the decreased risk of diarrhea in spring in our study may be that the air temperature and humidity conditions are not as favourable as winter and summer for the proliferation of pathogens during this period and at the same time calves are under less environmental stress. This may be interpreted as the fact that environmental temperature and humidity conditions are more stable in spring months, which reduces stress levels in calves and allows the immune system to work more effectively. Walker et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) and Cho \u0026amp; Yoon (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) reported that extreme heat and cold temperatures may increase susceptibility to infections by suppressing the immune system, so moderate seasons may carry a relatively lower risk.\u003c/p\u003e\u003cp\u003eIn support of this seasonal finding, it was also found that the risk of diarrhea was approximately 64.5% lower in temperate and Mediterranean climate zones than in continental climate zones (OR\u0026thinsp;=\u0026thinsp;0.355; p\u0026thinsp;=\u0026thinsp;0.076). Although this latter finding is at the borderline statistically significant level, it shows a protective trend in direction and points to the effect of climatic environment on the environmental spread of pathogens and the immune capacity of the calf. Keleş et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported that the risk of diarrhea caused by E. coli K99\u0026thinsp;+\u0026thinsp;was significantly higher in calves born in autumn compared to those born in other seasons and this risk increased 3.6 times compared to those born in spring. Similarly, Gulliksen et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) reported that the incidence of diarrhea was significantly increased in calves born in winter, especially in calves born in February, with the highest diarrhea rate of 37.9%. This finding is in parallel with Frank and Kaneene (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) who reported that cold weather conditions increase susceptibility to pathogens in relation to immunosuppression and stress. In addition, Hur et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) reported that most of the calf deaths occurred in winter (48.6%) and autumn (21.2%). Also in another study, it was reported that heat stress effected the colostrum quality. In this study it has been stated that cows should be protected heat stress during and after the postpartum period. Heat stress reduce the colostrum quality and these situation predisposes calves to the diseases (Kara and G\u0026uuml;ven \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, some studies have obtained different results on seasonal effects. For example, the effect of seasonal variation could not be clearly confirmed in the studies conducted by Svensson et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) in Sweden. This shows that environmental factors should be considered not only in terms of climate but also in interaction with other variables such as management practices, shelter structure, hygiene conditions and herd density.\u003c/p\u003e\u003cp\u003eThe findings of the study indicate that producer experience is an important determinant of the occurrence of neonatal calf diarrhea. In particular, it was found that the risk of diarrhea was approximately 5.5 times higher in producers with low level of work experience (OR\u0026thinsp;=\u0026thinsp;5.49; p\u0026thinsp;=\u0026thinsp;0.041). This finding points to the weak effect of lack of knowledge and poor practice in herd management on the prevention of infectious diseases in the neonatal period. Considering that the level of experience reflects not only individual knowledge but also compliance with hygiene protocols, early symptom recognition and appropriate intervention skills, the clinical and economic implications of this difference become more evident. In contrast, some other managerial variables assessed in the study did not show a statistically significant effect. Age, management type, application of baticon to the umbilical region after birth and umbilical cord tying did not stand out as a significant determinant of calf diarrhea (p\u0026thinsp;\u0026gt;\u0026thinsp;0.10). In particular, there was no statistically significant relationship between the variables \u0026lsquo;application of baticon to the umbilical region\u0026rsquo; and \u0026lsquo;tying the umbilical cord\u0026rsquo; and neonatal calf diarrhea (p\u0026thinsp;\u0026gt;\u0026thinsp;0.10). This result suggests that the protective effect of these practices on the development of diarrhea may be limited or indirect. However, this finding does not mean that these practices are insignificant, but rather that these practices alone are not effective in a disease with a multifactorial etiology such as diarrhea. Age, management type, application of baticon to the umbilical region after birth and umbilical cord clamping were not found to be significant determinants of calf diarrhea (p\u0026thinsp;\u0026gt;\u0026thinsp;0.10). In particular, there was no statistically significant relationship between the variables \u0026lsquo;application of baticon to the umbilical region\u0026rsquo; and \u0026lsquo;tying the umbilical cord\u0026rsquo; and neonatal calf diarrhea (p\u0026thinsp;\u0026gt;\u0026thinsp;0.10). This result suggests that the protective effect of these practices on the development of diarrhea may be limited or indirect. However, this finding does not indicate that these practices are insignificant, but rather that they are not determinant alone in a disease with multifactorial etiology such as diarrhea. However, the lack of a clear effect of umbilical applications directly on the incidence of diarrhea suggests that these applications are more effective in preventing septicaemia, omphalophlebitis and local umbilical infections. In a study by Bendali et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), the rate of diarrhea was reported to be 9.6% in calves with navel disinfection and 8.4% in those without disinfection and this difference was found to be statistically significant (p\u0026thinsp;=\u0026thinsp;0.05). This suggests that umbilical disinfection alone may have a limited effect in reducing the risk of diarrhea, but may become more significant when evaluated in combination with multiple protective practices.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, it was determined that neonatal calf diarrhea is not only limited to short-term morbidity and mortality rates, but also has long-term effects on growth performance, milk yield and reproductive capacity. In this respect, neonatal diarrhea should be considered as a multifaceted production risk that has critical importance not only in the field of veterinary health but also at the level of business economics and herd management. Increasing migration from rural to urban areas and lack of qualified labour force in T\u0026uuml;rkiye, difficulties in providing trained personnel in livestock enterprises, especially in small and medium-sized enterprises, and the fact that individual breeders mostly adhere to traditional knowledge and practices indicate that the high morbidity and mortality rates observed in diarrhea cases may be associated with unsuitable environmental conditions and inadequate management practices. The findings of the study indicate that factors such as feeding method and practice, hygiene protocols, equipment cleaning, postnatal care and environmental management should be addressed in an integrated manner in the prevention of neonatal calf diarrhea. In particular, the administration of colostrum in adequate amounts and under hygienic conditions in the first hours after birth plays a decisive role in reducing both diarrhea incidence and mortality rates. Accordingly, the preventive health protocols to be developed should be based not only on clinical practices but also on sustainable management strategies that can be implemented at the enterprise level.\u003c/p\u003e\u003cp\u003eIn conclusion, the dissemination of practices for the prevention of neonatal calf diarrhea in the field is of great importance not only for improving animal welfare but also for maintaining herd regeneration capacity and sustainability of enterprise profitability. In this context, it is necessary to focus on the feasibility of implementing site-specific intervention strategies by supporting education-based extension activities and training .\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting Interest\u003c/h2\u003e\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eEthics Approval\u003c/h2\u003e\u003cp\u003eThis is an observational study. The Animal Research Ethics Committee of Kırıkkale University has confirmed that no ethical approval is required.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection performed by Yasin PARLATIR, Seyfettin TUNCEL and analysis were made by Pınar AYVAZOĞLU DEMİR, Seyfettin TUNCEL. The manuscript was written by Yasin PARLATIR, Seyfettin TUNCEL, Pınar AYVAZOĞLU DEMİR. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting this study's findings are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbuelo A, Cullens F, Brester JL (2021) Effect of preweaning disease on the reproductive performance and first-lactation milk production of heifers in a large dairy herd. J Dairy Sci 104: 7008\u0026ndash;7017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3168/jds.2020-19791\u003c/span\u003e\u003cspan address=\"10.3168/jds.2020-19791\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAghakeshmiri F, Azizzadeh M, Farzaneh N, Gorjidooz M (2017) Effects of neonatal diarrhea and other conditions on subsequent productive and reproductive performance of heifer calves. 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Dissertation, University of Ankara.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Calf, Diarrhea, Economic loss, Economic effects, Peripheral factors","lastPublishedDoi":"10.21203/rs.3.rs-7462598/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7462598/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study, which examined the epidemiological characteristics and associated risk factors of neonatal calf diarrhea in dairy cattle farms in T\u0026uuml;rkiye, was based on survey data covering 115 farms from seven geographical regions. The study determined the prevalence of diarrhea in calves as 26.81% and the mortality rate due to diarrhea as 15.58%. In addition, diarrhea was found to cause a decrease in weight gain by 11\u0026ndash;30%. According to logistic regression analysis, the presence of birth and calf compartments, timely colostrum transfer and hygienic practices (teat and bottle cleaning) statistically significantly reduce the risk of diarrhea. The probability of diarrhea was found to be 81% lower in holdings with a maternity compartment and 71% lower in holdings with a calf compartment. Vaccination and producer experience also stand out as critical factors; the risk of diarrhea was found to be 5.5 times higher in inexperienced producers. Seasonal effects were also observed in the study. Accordingly, it was found that the risk of diarrhea was lower in spring months compared to winter and summer months, and the risk decreased by 64.5% in temperate climates compared to continental climates. As a result of the study, it was determined that neonatal diarrhea causes not only mortality, but also growth retardation and economic losses.\u003c/p\u003e","manuscriptTitle":"The Relationship of Neonatal Calf Diarrhea and Yield Losses with Managerial Factors in Dairy Cattle Farms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-09 13:11:00","doi":"10.21203/rs.3.rs-7462598/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-10-24T07:25:42+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-27T21:01:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-29T13:35:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Animal Health and Production","date":"2025-08-28T03:15:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"50bf775d-8158-472a-9afc-9407e9055f51","owner":[],"postedDate":"October 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-29T19:41:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-09 13:11:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7462598","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7462598","identity":"rs-7462598","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}