Table 1 Variables available in broiler datasets.

From: Longitudinal national-level monitoring of on-farm broiler welfare identifies consistently poorly performing farms

Variable name

Additional Information

Intended use

Abattoir ID

Identifier of abattoir

Grouping variable

Farm CPH number

Identifier of farm

Grouping variable

Farm house ID

Identifier of farm house

Grouping variable

Region

Derived from postcode of farm7

Grouping variable

Datea

Date of inspection at slaughterhousex

Predictor

Number of animals

Number of animals in batch sent to slaughterx

Predictor

Number in houseb

Number of animals in house on the farmx

Predictor

Production systemc

Pre-categorised+: (intensive indoor; extensive indoor, free-range, organic)y

Predictor

Stocking density

Density of animals in kg/m2 (pre-categorised+: < 33 kg/m2, 33–39 kg/m2, > 39 kg/m2)z

Predictor

Breed

Breed of animals (pre-categorised+: Cobb, Hubbard, Hybro, Ross) y

Predictor

Age

Age of birds in daysx

Predictor

Mortality in house

Cumulative daily mortality rate in housex

Predictor

FPD Swedish score

Swedish score of footpad dermatitis8

Outcome

Abnormal colour feveredb

Count and percentage

Outcome

Antemortem rejectsb

Count and percentage

Outcome

Ascites and oedema

Count and percentage

Outcome

Bruising and fracturesb

Count and percentage

Outcome

Cellulitisb

Count and percentage

Outcome

Dermatitis and cellulitisd

Count and percentage

Outcome

Dermititisb

Count and percentage

Outcome

Dead on arrival

Count and percentage

Outcome

Emaciation

Count and percentage

Outcome

Hepatitisb

Count and percentage

Outcome

Joint Lesions

Count and percentage

Outcome

Jaundiceb

Count and percentage

Outcome

Pericarditisb

Count and percentage

Outcome

Perihepatitis and peritonitisb

Count and percentage

Outcome

Respiratory diseased

Count and percentage

Outcome

Salpingitisb

Count and percentage

Outcome

Total rejectionsd

Count and percentage

Outcome

Tumours and nodulesb

Count and percentage

Outcome

  1. aVariable was used to compute the relevant time of year predictors in the statistical models.
  2. bVariable was not available for 2010–2014 data.
  3. cThis variable has no variance for 2010–2014 data, as all recorded batches came from intensive indoor farming.
  4. dVariable was not available for 2016–2018 data.
  5. xContinuous data.
  6. yCategorical data.
  7. zOrdinal data.
  8. +Pre-categorised data was supplied with the categories already determined.