Supplementary Materials- A prospective cohort study examining the association of claw anatomy and sole temperature with the development of claw horn disruption lesions in dairy cattle

Supplementary Table S1. Case definitions and descriptions of the grading system for sole haemorrhage, sole ulcers and white line lesions.

Supplementary Table S2. Descriptive Statistics of explanatory variables at each time point. Continuous variables are presented alongside the mean, standard deviation (SD), range and number of missing values (%). Categorical variables are presented alongside the frequency within each level (%). T1-Precalving, n = 1982, T2- Calving, n = 2082. Farm and Parity variables are presented at the T1-Precalving timepoint .

Supplementary Table S3. Results from univariable analysis with logistic regression of T1-Precalving and T2-Calving explanatory variables with white line lesion at T3-Early as an outcome. Odds ratios are calculated, either for a single unit increase or compared to the reference level.

Supplementary Table S4. Results from univariable analysis with logistic regression of T1-Precalving and T2-Calving explanatory variables with sole lesion at T3-Early as an outcome. Odds ratios are calculated, either for a single unit increase or compared to the reference level.

Supplementary Table S5. Pairwise Pearson’s Correlation Coefficients (r) between explanatory variables are presented.

Supplementary Table S6. The model-adjusted probabilities of sole and white line lesions at each timepoint from four multivariable fixed-effect logistic regression models (1a, 1b, 2a and 2b). The arithmetic mean of the variable (sole horn thickness or foot angle) was calculated after grouping by industry recommended levels.

Supplementary Figure S1. Schematic showing the study design and variables recorded at each timepoint. Timepoints are described as days relative to the expected calving date.

Supplementary Figure S2. Data handling workflow to create the final datasets used in the analysis.

补充表S1：单纯性蹄底出血、单纯性蹄底溃疡及白线病变的分级系统定义与说明。

补充表S2：各时间点解释变量的描述性统计结果。连续变量以均值、标准差（SD）、取值范围及缺失值数量（百分比）呈现；分类变量以各水平的频数（百分比）呈现。时间点T1为围产期前期（T1-Precalving），样本量n=1982；时间点T2为产犊期（T2-Calving），样本量n=2082。农场与胎次变量均统计于T1围产期前期时间点。

补充表S3：以T3早期（T3-Early）白线病变为结局变量，对T1围产期前期及T2产犊期解释变量开展单变量逻辑回归分析的结果。比值比（OR）按单单位增量或与参照组对比的方式计算得出。

补充表S4：以T3早期蹄底病变为结局变量，对T1围产期前期及T2产犊期解释变量开展单变量逻辑回归分析的结果。比值比（OR）按单单位增量或与参照组对比的方式计算得出。

补充表S5：解释变量间的皮尔逊（Pearson）两两相关系数（r）。

补充表S6：基于4个多变量固定效应逻辑回归模型（模型1a、1b、2a及2b）计算得到的各时间点蹄底病变与白线病变的模型校正概率。按行业推荐水平分组后，计算对应变量（蹄底角质厚度或蹄角度）的算术均值。

补充图S1：研究设计及各时间点记录变量的示意图。时间点以相对于预期产犊日期的天数标注。

补充图S2：构建分析所用最终数据集的数据处理工作流程。