Conectar
by Chalachew Genet, Wendemagegn Enbiale, Anna Rommerskirchen, Rajiha Abubeker, Wudu Tafere, Tsehaynesh Gebre-Eyesus, Michael Getie, Alem Tsega, Muluken Acham, Addisu Melese, Tewachew Awoke, Wondemagegn Mulu, Degu Ashagrie, Tadele Amsalu, Achenef Motbainor, Endalew Gebeyehu, Mulugeta Kibret, Bayeh Abera, Endalkachew Nibret, Abaineh Munshea
IntroductionExtended spectrum β-lactamase (ESBL) and carbapenemase-producing Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae) emanating from raw cow milk are among the leading contributors to the spread of antimicrobial resistance (AMR). Due to the misuse and overuse of antibiotics in dairy farms, cow’s milk has become a reservoir of ESBL- and carbapenemase-producing E. coli and K. pneumoniae posing a growing public health threat, especially in areas where the consumption of raw milk is common. However, compared to the clinical sector, the prevalence of ESBL- and carbapenemase-producing E. coli and K. pneumoniae in the food sector is under-studied.
ObjectiveThis study aimed to determine the prevalence of ESBL and carbapenemase-producing E. coli and K. pneumoniae in raw bulk cow milk from Dairy Cooperatives in Northwest Amhara, Ethiopia.
MethodsA cross-sectional study was conducted from January to April, 2025 among 257 dairy cooperative member farms. Sociodemographic and related data were collected using a structured questionnaire. Five milliliters of raw bulk cow milk were collected aseptically from each farm in four Dairy Cooperatives (DCs) (DC-A to D). 10 microliters of milk sample were directly inoculated into MacConkey agar. Escherichia coli and K. pneumoniae were identified using standard microbiological techniques. Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method. ESBL and carbapenemase production were confirmed phenotypically via combination disk tests and modified carbapenem inactivation methods, respectively.
ResultsThe prevalence of E. coli and/or K. pneumoniae in raw cow milk was 21% (95% CI, 16.5–26.4%), with respective individual prevalence of 8.2% and 14.8%. ESBL-producing E. coli and K. pneumoniae accounted for 23.8% and 15.8% of isolates, respectively, while 2.6% of isolates (only K. pneumoniae) were carbapenemase producers. Resistance to ampicillin and amoxicillin-clavulanic acid exceeded 70%. All E. coli and 94.7% of K. pneumoniae isolates remained susceptible to carbapenems. Nearly half of all isolates (45.8%) were multidrug resistant (MDR), and 51.9% of MDR isolates were co-resistant to at least six antibiotics. Having additional non-farming occupations (AOR: 4.17, 95% CI: 1.49–11.67), large herd size (AOR: 3.21, 95% CI: 1.26–8.18), having pet animals (AOR: 6.53, 95% CI: 1.39–30.7), and use of calabash milk pail (AOR: 7.37, 95% CI: 1.45–37.49) were significantly associated with milk culture positive result for E. coli and/or K. pneumoniae.
ConclusionRaw milk in Northwest Amhara harbors ESBL and carbapenemase-producing E. coli and K. pneumoniae posing a substantial public health risk coupled with MDR and resistance to critically important antimicrobials. Strengthened AMR surveillance, improved farm hygiene, restricted antibiotic use, and public education on milk safety are urgently needed.
This study employs structural equation modelling to explore the inter-relationships among optimal antenatal care (ANC), health facility delivery and early postnatal care (EPNC) in Ethiopia. By identifying both direct and indirect influencing factors, the study offers valuable insights to support integrated maternal health strategies and guide informed decision-making by policymakers and women alike.
The secondary analysis of the Ethiopian Demographic and Health Survey 2016 was performed to investigate inter-relationships between optimal ANC, health facility delivery and postnatal care (PNC) among women in Ethiopia. Data were analysed with R software V.4.3.2. The study used binary logistic regression to examine differences in optimal ANC, health facility delivery and EPNC, focusing on variables with a p value of 0.1 or less. Selected variables were incorporated into a generalised structural equation model (GSEM) using the LAVAAN package to explore both direct and indirect effects. The GSEM method assessed the impact of exogenous variables on endogenous variables, all binary, using a logistic link and binomial family. Missing data were handled with the multiple imputation by chained equations package, and sampling weights were applied to ensure national and regional representativeness.
The source population comprised all women of reproductive age (15–49 years) who gave birth in the 5 years preceding the survey. From 16 650 interviewed households (98% response rate), we identified 7590 eligible women with recent births. Finally, we included 2415 women who had attended four or more ANC visits.
Media exposure significantly boosts the likelihood of using ANC (OR=1.8, 95% CI (1.04 to 3.23), p=0.04), health facility delivery (OR=1.7, 95% CI (1.23 to 2.45), p=0.05) and PNC (OR=2.0, 95% CI (1.6 to 4.01), p=0.01). Urban residence and secondary education also enhance ANC (OR=1.2, 95% CI (1.01 to 2.88), p=0.022; OR=1.3, 95% CI (1.20 to 3.01), p=0.018), health facility delivery (OR=1.1, 95% CI (1.01 to 3.24), p=0.035; OR=1.5, 95% CI (1.22 to 3.45), p=0.03) and PNC (OR=1.6, 95% CI (1.01 to 4.32), p=0.03). ANC directly affects health facility delivery (OR=1.4, 95% CI (1.28 to 3.09), p=0.01) and PNC (OR=1.6, 95% CI (1.01 to 3.80), p=0.03). Additionally, women aged 20–34 years and those from male-headed households positively impact health facility delivery (OR=1.5, 95% CI (1.20 to 4.80), p=0.01; OR=1.3, 95% CI (1.07 to 3.45), p=0.014) and PNC (OR=1.4, 95% CI (1.10 to 2.90), p=0.01; OR=1.2, 95% CI (1.07 to 3.08), p=0.025).
Optimal ANC is vital for encouraging health facility delivery and EPNC. To enhance maternal and neonatal health, policies should integrate these services. Key predictors include being aged 20–34, having secondary and higher education, media exposure, male-headed households and living in urban areas. Improving education and media exposure can boost maternal healthcare service use.
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