Strategies to analyze milk losses caused by diseases with potential incidence throughout the lactation: a lameness example.

The objective of this study was to test the hypothesis that lameness incidence in lactating dairy cows decreases milk production compared with controls and to determine the best method of the 5 combinations of 2 study designs (retrospective cohort and retrospective matched cohort) and 3 repeated measures statistical methods: ANOVA (with binary classification of lameness); ANOVA with a lameness index (LAMIX) as the variable of interest; and analysis of covariance (ANCOVA, controlling for mean milk production for the first 3 wk of lactation and with a binary classification of lameness). Data were from 1 dairy farm located near Ithaca, NY, and from cows that calved between January 1, 2004 and January 1, 2007. The LAMIX was defined as -1, -2, -3, -4, and -5 = 1, 2, 3, 4, and > or =5 mo before lameness was detected, respectively; 1, 2, 3, 4, and 5 = 1, 2, 3, 4, and 5 mo after diagnosis, respectively; and 0 = cows that were never lame. With the binary lameness classification analyzed by repeated measures ANOVA, there was no effect of lameness on milk yield. The model was biased because lame cows had higher milk yields before lameness compared with nonlame cows. When the LAMIX was used, milk production before lameness was greater than after lameness (3.1 +/- 0.28 kg/d). Yet, point estimates generated for LAMIX were inaccurate because of the multicollinearity detected between LAMIX and week of lactation and because of the inability of adjusting the least squares means for the interaction of LAMIX and week of lactation. Therefore, the most appropriate models were the ANCOVA models (both for the matched and nonmatched retrospective-cohort designs). The estimated losses associated with lameness were 314 and 424 kg/cow per 305-d lactation, respectively, for the matched and nonmatched designs. Furthermore, high milk yield in the beginning of the lactation was a risk factor for lameness.