Understanding the factors that influence dairy farmers’ awareness of infertility and reproductive performance is critical for improving productivity. This cross-sectional survey sampled farmers across six Tanzanian regions (Njombe, Mbeya, Tanga, Kilimanjaro, Arusha, and Morogoro) and used multivariable analyses to examine associations between 13 predictors and four outcomes: recognition of infertility signs, recognition that failing to produce a calf annually indicates infertility, pregnancy status, and calving interval. Key findings showed that smaller herd sizes were associated with poorer recognition of infertility signs and lower pregnancy rates, while less experienced farmers surprisingly demonstrated better recognition of infertility signs and higher pregnancy rates. Farmers who regarded repeat breeding as a major or moderate constraint had shorter calving intervals than those who considered it a negligible constraint. Farmers relying exclusively on artificial insemination (AI) were more likely to identify failure to produce a calf annually as an indicator of infertility than those using both AI and natural service. Aside from region, other predictors showed no clear or consistent associations in either the univariable or multivariable models. This lack of detectable association does not imply the absence of an effect but rather indicates that the data could not distinguish between positive, negative, or null associations. Region emerged as the most consistent and influential predictor, showing significant associations with at least one category of each outcome variable. Overall, the results highlight the need for context-specific, regionally tailored interventions to improve reproductive performance in Tanzania's smallholder dairy systems.
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