Rameen Shahid Faiza, Iftikhar Momina, Sherazi Sajid Hussain, Zia Memona, Saeed Muhammad Rawal
Internal Medicine, Bacha Khan Medical College, Mardan Medical Complex, Mardan, PAK.
Neonatal Intensive Care, Queen Alexandra Hospital, Portsmouth, GBR.
Cureus. 2025 Jul 7;17(7):e87469. doi: 10.7759/cureus.87469. eCollection 2025 Jul.
This study investigates the interplay between breastfeeding patterns, chemical pathology, and antibiotic resistance in lactating mothers. A cross-sectional analysis was conducted on 1,200 lactating mothers aged 18 to 45, examining breastfeeding practices, biochemical markers, milk composition, and antibiotic resistance status. The findings reveal significant metabolic variations, with mean glucose and cholesterol levels at 135.23 mg/dL and 224.58 mg/dL, respectively, suggesting potential cardiovascular risks. Exclusive breastfeeding improved milk quality by having higher average fat content (3.48%) and lactose (6.96%), and the reported antibiotic resistance was lower (18.2%), compared with non-exclusive groups (28.6%). Geographically weighted regression (GWR) revealed spatial variability in exclusivity effects, highlighting regional nutritional disparities. Machine learning models, random forest, support vector machine (SVM), and gradient boosting machine (GBM), were used to predict resistance and nutritional status, with cholesterol and BMI emerging as the top predictors. Although model performance was modest (AUC ≈ 0.65), random forest achieved moderate discriminative power (AUC ~0.65), with cholesterol and BMI ranked highest in feature importance. Receiver operating characteristic (ROC) analysis for GBM and SVM also indicated moderate predictive capacity. Spatial mapping of antibiotic resistance revealed clustered patterns, emphasizing the need for region-specific interventions. Furthermore, systolic blood pressure showed a weak correlation with cholesterol levels, indicating independent metabolic risks. This study underscores the critical need for integrated nutritional and antimicrobial stewardship in lactating mothers, particularly in regions with identified spatial vulnerabilities. Policy implications suggest targeted nutritional support and regional antibiotic surveillance to mitigate health risks in this population.
本研究调查了哺乳期母亲的母乳喂养模式、化学病理学和抗生素耐药性之间的相互作用。对1200名年龄在18至45岁的哺乳期母亲进行了横断面分析,检查了母乳喂养习惯、生化指标、乳汁成分和抗生素耐药性状况。研究结果显示出显著的代谢差异,平均葡萄糖和胆固醇水平分别为135.23毫克/分升和224.58毫克/分升,表明存在潜在的心血管风险。与非纯母乳喂养组(28.6%)相比,纯母乳喂养通过具有更高的平均脂肪含量(3.48%)和乳糖含量(6.96%)提高了乳汁质量,且报告的抗生素耐药率较低(18.2%)。地理加权回归(GWR)揭示了纯母乳喂养效果的空间变异性,突出了区域营养差异。使用机器学习模型、随机森林、支持向量机(SVM)和梯度提升机(GBM)来预测耐药性和营养状况,胆固醇和体重指数成为最重要的预测指标。尽管模型性能一般(AUC约为0.65),但随机森林具有中等判别能力(AUC约为0.65),胆固醇和体重指数在特征重要性方面排名最高。GBM和SVM的受试者工作特征(ROC)分析也表明具有中等预测能力。抗生素耐药性的空间映射显示出聚集模式,强调了针对特定区域进行干预的必要性。此外,收缩压与胆固醇水平呈弱相关性,表明存在独立的代谢风险。本研究强调了对哺乳期母亲进行综合营养和抗菌管理的迫切需求,特别是在已确定存在空间脆弱性的地区。政策影响表明,需要有针对性的营养支持和区域抗生素监测,以降低该人群的健康风险。