2011•Ankara Üniversitesi Veteriner Fakültesi DergisiOpen access

Quantification of risk factors of coccidiosis in broilers by using logistic regression analysis

AKÇAY Aytaç ERTUĞRUL

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Abstract

The aim of this research was to determine the most efficient risk factors on broiler coccidiosis in Turkey. The study was performed in 1110 broiler chickens housed in 817 farms located in six geographical region of Turkey between September 2006 and September 2007. Survey questionnaires were held and faecal samples were collected from broiler flocks. Survey results were combined with laboratory findings. A logistic regression analysis was used to assess variables that influenced the occurrence of Coccidiosis. Firstly, simple logistic regression was performed for each variable by using presence or absence criteria of coccidiosis. Then, variables that were associated with coccidiosis-positive flocks at P value of ≤ 0.25 were included in multivariable logistic regression. In the present study, clinical or subclinical coccidiosis ratio was determined to be 56.2% in the analysis of the faeces samples. The multivariate logistic regression model for coccidiosis was completed in 10th step by using the backward elimination procedure. Overall classification ratio of final model was determined to be 87.3%. The results showed an enhanced risk of coccidiosis due to environmental and management factors such as season, number of chick house, age of chick, type of ventilation system, roof isolation, litter materials, having a type of farmyard which is easy to clean, time between production periods, leaving litter material to a safe distance after production period, presence of vermin, climate regulation and other diseases which might facilitate introduction of the parasite

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The aim of this research was to determine the most efficient risk factors on broiler coccidiosis in Turkey. The study was performed in 1110 broiler chickens housed in 817 farms located in six geographical region of Turkey between September 2006 and September 2007. Survey questionnaires were held and faecal samples were collected from broiler flocks. Survey results were combined with laboratory findings. A logistic regression analysis was used to assess variables that influenced the occurrence of Coccidiosis. Firstly, simple logistic regression was performed for each variable by using presence or absence criteria of coccidiosis. Then, variables that were associated with coccidiosis-positive flocks at P value of ≤ 0.25 were included in multivariable logistic regression. In the present study, clinical or subclinical coccidiosis ratio was determined to be 56.2% in the analysis of the faeces samples. The multivariate logistic regression model for coccidiosis was completed in 10th step by using the backward elimination procedure. Overall classification ratio of final model was determined to be 87.3%. The results showed an enhanced risk of coccidiosis due to environmental and management factors such as season, number of chick house, age of chick, type of ventilation system, roof isolation, litter materials, having a type of farmyard which is easy to clean, time between production periods, leaving litter material to a safe distance after production period, presence of vermin, climate regulation and other diseases which might facilitate introduction of the parasite

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Available abstract

The aim of this research was to determine the most efficient risk factors on broiler coccidiosis in Turkey. The study was performed in 1110 broiler chickens housed in 817 farms located in six geographical region of Turkey between September 2006 and September 2007. Survey questionnaires were held and faecal samples were collected from broiler flocks. Survey results were combined with laboratory findings. A logistic regression analysis was used to assess variables that influenced the occurrence of Coccidiosis. Firstly, simple logistic regression was performed for each variable by using presence or absence criteria of coccidiosis. Then, variables that were associated with coccidiosis-positive flocks at P value of ≤ 0.25 were included in multivariable logistic regression. In the present study, clinical or subclinical coccidiosis ratio was determined to be 56.2% in the analysis of the faeces samples. The multivariate logistic regression model for coccidiosis was completed in 10th step by using the backward elimination procedure. Overall classification ratio of final model was determined to be 87.3%. The results showed an enhanced risk of coccidiosis due to environmental and management factors such as season, number of chick house, age of chick, type of ventilation system, roof isolation, litter materials, having a type of farmyard which is easy to clean, time between production periods, leaving litter material to a safe distance after production period, presence of vermin, climate regulation and other diseases which might facilitate introduction of the parasite

Key concepts: Coccidiosis, Flock, Logistic regression, Veterinary medicine, Broiler, Litter, Biology, Animal science

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