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The objectives of this study were to critically review randomized controlled trials, and quantify, using meta-analysis and meta-regression, the effects of supplementation with fats on milk production and components by dairy cows. We reviewed 59 papers, of which 38 (containing 86 comparisons) met eligibility criteria. Five groups of fats were evaluated: tallows, calcium salts of palm fat (Megalac, Church and Dwight Co. Inc., Princeton, NJ), oilseeds, prilled fat, and other calcium salts. Milk production responses to fats were significant, and the estimated mean difference was 1.05 kg/cow per day, but results were heterogeneous. Milk yield increased with increased difference in dry matter intake (DMI) between treatment and control groups, decreased with predicted metabolizable energy (ME) balance between these groups, and decreased with increased difference in soluble protein percentage of the diet between groups. Decreases in DMI were significant for Megalac, oilseeds, and other Ca salts, and approached significance for tallow. Feeding fat for a longer period increased DMI, as did greater differences in the amount of soluble protein percentage of the diet between control and treatment diets. Tallow, oilseeds, and other Ca salts reduced, whereas Megalac increased, milk fat percentage. Milk fat percentage effects were heterogeneous for fat source. Differences between treatment and control groups in duodenal concentrations of C18:2 and C 18:0 fatty acids and Mg percentage reduced the milk fat percentage standardized mean difference. Milk fat yield responses to fat treatments were very variable. The other Ca salts substantially decrease, and the Megalac and oilseeds increased, fat yield. Fat yield increased with increased DMI difference between groups and was lower with an increased estimated ME balance between treatment and control groups, indicating increased partitioning of fat to body tissue reserves. Feeding fats decreased milk protein percentage, but results were heterogeneous. An increased number of milkings increased the milk protein percentage, whereas the difference between the treatment and control groups in duodenal concentrations of 18:2 fatty acids and dietary Mg concentration reduced the milk protein percentage. None of the fat treatments influenced milk protein production. The range of responses to different fats fed approached or exceeded 5 standard deviations from the mean and differed in point direction for all variables studied, indicating the varied and profound biological effects of fats. Responses to fat feeding were highly heterogeneous for all variables studied and heterogeneity was present within responses to individual fat groups. The lower DMI combined with higher milk and milk fat production showed that fats could improve the efficiency of milk production. More studies are required to more completely characterize sources of variation in responses to fats.

Data from 137 published trials involving 2,545 calvings were analyzed using random effects normal logistic regression models to identify risk factors for clinical hypocalcemia in dairy cows. The aim of the study was to examine which form, if any, of the dietary cation anion difference (DCAD) equation provided the best estimate of milk fever risk and to clarify roles of calcium, magnesium, and phosphorus concentrations of prepartum diets in the pathogenesis of milk fever. Two statistically equivalent and biologically plausible models were developed that predict incidence of milk fever. These models were validated using data from 37 trials excluded from the original data used to generate the models; missing variables were replaced with mean values from the analyzed data. The preferred models differed slightly; Model 1 included prepartum DCAD, and Model 2 included prepartum dietary concentrations of potassium and sulfur alone, but not sodium and chloride. Other factors, included in both models were prepartum dietary concentrations of calcium, magnesium, phosphorus; days exposed to the prepartum diet; and breed. Jersey cows were at 2.25 times higher risk of milk fever than Holstein cows in Model 1. The results support the DCAD theory of greater risk of milk fever with higher prepartum dietary DCAD (odds ratio = 1.015). The only DCAD equation supported in statistical analyses was (Na(+) + K(+)) - (Cl(-) + S(2-)). This finding highlights the difference between developing equations to predict DCAD and those to predict milk fever. The results support a hypothesis of a quadratic role for Ca in the pathogenesis of milk fever (model 1, odds ratio = 0.131; Model 2, odds ratio = 0.115). Milk fever risk was highest with a prepartum dietary concentration of 1.35% calcium. Increasing prepartum dietary magnesium concentrations had the largest effect on decreasing incidence of milk fever in both Model 1 (odds ratio = 0.006) and Model 2 (odds ratio = 0.001). Increasing dietary phosphorus concentrations prepartum increased the risk of milk fever (Model 1, odds ratio = 6.376; Model 2, odds ratio = 9.872). The models presented provide the basis for the formulation of diets to reduce the risk of milk fever and strongly support the need to evaluate macro mineral nutrition apart from DCAD of the diet.