Department of Animal Sciences, University of Florida, Gainesville 32611.
Department of Large Animal Clinical Sciences, University of Florida, Gainesville 32610.
J Dairy Sci. 2021 Aug;104(8):8885-8900. doi: 10.3168/jds.2021-20119. Epub 2021 May 28.
The association between dry period length (DPL) and time to culling and pregnancy in the subsequent lactation may be important for the economically optimal length of the dry period. Therefore, this study aimed to (1) quantify the association between DPL and hazard of culling and pregnancy in the subsequent lactation; (2) develop continuous functions of DPL for the hazard ratios of culling and pregnancy; and (3) investigate the effect of a cause-specific hazards model and a subdistribution model to analyze competing events. The data used in this observational cohort study were from dairy herd improvement milk test lactation records from 40 states in the United States. After edits, there remained 1,108,515 records from 6,730 herds with the last days dry in 2014 or 2015. The records from 2 adjacent lactations (current, subsequent) were concatenated with the DPL of interest, 21 to 100 d, in between both lactations. We defined 8 DPL categories of 10 d each. Kaplan-Meier survival curves were used to show associations between DPL and time to culling or pregnancy for 3 lactation groups: lactation 1 and 2, lactation 2 and 3, and lactation 3 and greater. To control for confounding factors in Cox proportional models, we included 6 current lactation covariates and 3 time-dependent variables in the survival models. Hazard ratios of culling were estimated for 4 days in milk (DIM) categories from 1 to 450 DIM. Hazard ratios of pregnancy were estimated for 3 DIM categories from 61 to 300 DIM. Competing risk analysis of 8 disposal codes (i.e., farmer reported reasons) for culling and the culling event for pregnancy were conducted by a cause-specific hazards model and a subdistribution model. Hazard ratios were also estimated as quadratic polynomials of DPL. Compared with the reference DPL category of 51 to 60 d, hazard ratios of culling and pregnancy of the other 7 DPL categories ranged between 0.70 and 1.49, and 0.93 and 1.15, respectively. Short DPL were associated with lower risk of culling in the early lactation but not over the entire lactation. Short DPL were associated with greater hazard of pregnancy. Trends in hazard ratios over the ranges of the 8 DPL categories were not always consistent. Competing risk analysis with both models provided little differences in hazard ratios of culling and pregnancy. In conclusion, variations in DPL were associated with meaningful differences in the hazard ratios for culling and pregnancy and minor differences in the relative frequency of disposal codes. Subdistribution hazards models produced hazard ratios similar to cause-specific hazard models. The quadratic polynomials may be useful for decision support on customization of DPL for individual cows.
干奶期长度(DPL)与随后泌乳期淘汰和妊娠之间的关系可能对干奶期的经济最佳长度很重要。因此,本研究旨在:(1)量化 DPL 与随后泌乳期淘汰和妊娠风险之间的关系;(2)为淘汰和妊娠风险比开发 DPL 的连续函数;(3)研究原因特定风险模型和亚分布模型分析竞争事件的效果。本观察队列研究使用的数据来自美国 40 个州的奶牛群改良牛奶测试泌乳记录。经过编辑,仍有来自 6730 个牛群的 1108515 条记录,最后一次干奶时间为 2014 年或 2015 年。将当前和随后的 2 个泌乳期(当前、随后)的记录与 DPL 相关联,DPL 为 21 至 100 天。我们定义了 8 个 DPL 类别,每个类别 10 天。Kaplan-Meier 生存曲线用于显示 DPL 与 3 个泌乳组淘汰或妊娠时间之间的关系:泌乳 1 和 2、泌乳 2 和 3、泌乳 3 和更多。为了在 Cox 比例模型中控制混杂因素,我们在生存模型中包含了 6 个当前泌乳期协变量和 3 个时间依赖变量。对 1 至 450 DIM 的 4 天泌乳(DIM)类别进行了淘汰风险比的估计。对 61 至 300 DIM 的 3 个 DIM 类别进行了妊娠风险比的估计。对 8 个处置代码(即农民报告的原因)的竞争风险分析以及妊娠事件的淘汰,通过特定原因的风险模型和亚分布模型进行了分析。还将风险比估计为 DPL 的二次多项式。与 51 至 60 d 的参考 DPL 类别相比,其他 7 个 DPL 类别的淘汰和妊娠风险比的范围在 0.70 至 1.49 和 0.93 至 1.15 之间。短 DPL 与早期泌乳淘汰的风险较低相关,但与整个泌乳期无关。短 DPL 与更高的妊娠风险相关。8 个 DPL 类别范围内风险比的趋势并不总是一致。使用两种模型的竞争风险分析在淘汰和妊娠的风险比方面差异不大。总之,DPL 的变化与淘汰和妊娠风险比的显著差异以及处置代码相对频率的微小差异有关。亚分布风险模型产生的风险比与特定原因的风险模型相似。二次多项式可能有助于为个别奶牛定制 DPL 提供决策支持。