ArticlePloS one2025
Multilevel analysis of determinants of cattle deaths in Ethiopia.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In Ethiopia, agriculture is a fundamental element of both the economy and the social fabric of the community. The sector employs 80-85 percent of the population and contributes 47% to the total GDP. Livestock contributes to people's livelihoods through numerous channels: income, food, employment, transport, draft-over, manure, savings and insurance, social status, etc. Ethiopia is believed to have the largest livestock population in Africa. Despite this productive and reproductive performance is accompanied by poor health care, high disease incidence, poor management conditions, and unpredictable climactic conditions causing a significant cause of cattle death. The dependent variable is the count "number of occurrences of cattle death" that occurs randomly over time. A multilevel analysis was carried out with the anticipation that there would be variations in the number of cattle deaths per household throughout the region. Before analyzing the data with a multilevel method, check the variability using intra-class correlation (ICC), revealing that 14.6% of the variance in cattle deaths is attributable to the grouping level (Region) indicating the heterogeneity of cattle deaths between Regions. The multilevel ZINB regression model was identified as the best fit for analyzing cattle deaths per household. Factors such as types of agriculture, feeding areas, treatment methods, vaccination status, household land size, age of the household head, household size, and education level were found to significantly impact cattle mortality in the positive count portion of the random-intercept ZINB regression model. The Ministry of Agriculture should effectively raise awareness among agricultural producers regarding cattle vaccination and enhance the veterinary services available in the country. It is also advisable to promote a mixed farming approach rather than solely focusing on livestock farming to reduce cattle deaths. Farmers should consider reducing their household size and place greater emphasis on the welfare of their cattle.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.