Epidemiology and Health

Original Articles

Predicting over-the-counter antibiotic use in rural Pune, India, using machine learning methods: Pravin Arun Sawant, Sakshi Shantanu Hiralkar, Yogita Purushottam Hulsurkar, Mugdha Sharad Phutane, Uma Satish Mahajan, Abhay Machindra Kudale; Epidemiol Health. 2024;46:e2024044. Published online April 13, 2024; DOI: https://doi.org/10.4178/epih.e2024044

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Abstract PDF Supplementary Material: Abstract
OBJECTIVES
Over-the-counter (OTC) antibiotic use can cause antibiotic resistance, threatening global public health gains. To counter OTC use, this study used machine learning (ML) methods to identify predictors of OTC antibiotic use in rural Pune, India.
METHODS
The features of OTC antibiotic use were selected using stepwise logistic, lasso, random forest, XGBoost, and Boruta algorithms. Regression and tree-based models with all confirmed and tentatively important features were built to predict the use of OTC antibiotics. Five-fold cross-validation was used to tune the models’ hyperparameters. The final model was selected based on the highest area under the curve (AUROC) with a 95% confidence interval (CI) and the lowest log-loss.
RESULTS
In rural Pune, the prevalence of OTC antibiotic use was 35.9% (95% CI, 31.6 to 40.5). The perception that buying medicines directly from a medicine shop/pharmacy is useful, using antibiotics for eye-related complaints, more household members consuming antibiotics, and longer duration and higher doses of antibiotic consumption in rural blocks and other social groups were confirmed as important features by the Boruta algorithm. The final model was the XGBoost+Boruta model with 7 predictors (AUROC, 0.934; 95% CI, 0.891 to 0.978; log-loss, 0.279) log-loss.
CONCLUSIONS
XGBoost+Boruta, with 7 predictors, was the most accurate model for predicting OTC antibiotic use in rural Pune. Using OTC antibiotics for eye-related complaints, higher consumption of antibiotics and the perception that buying antibiotics directly from a medicine shop/pharmacy is useful were identified as key factors for planning interventions to improve awareness about proper antibiotic use.; Summary

Effects of antibiotic consumption on children 2-8 years of age developing asthma: Hamid Reza Khalkhali, Sima Oshnouei, Shaker Salarilak, Mohammadhossein Rahimi Rad, Mohammad Karamyar, Javad Khashabi; Epidemiol Health. 2014;36:e2014006. Published online July 4, 2014; DOI: https://doi.org/10.4178/epih/e2014006

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Abstract

OBJECTIVES
Antibiotic exposure in children is a possible contributor to the increasing asthma prevalence in several countries. The present study aimed to investigate the association between antibiotic exposure and the risk of developing childhood asthma at 2-8 years of age.

METHODS

A case-control study was undertaken among children aged 2-8 years old between March and September 2010 in the Urmia district in the northwest of Iran. The cases were doctor-diagnosed asthmatic children based on Global Initiative for Asthma criteria (n=207), and the controls were children without respiratory symptoms (n=400) selected by frequency matching by age and gender. Clinical data including antibiotic exposure was collected by a validated and reliable questionnaire, which was completed by interviewing parents/guardians.

RESULTS

Antibiotic consumption during the first year of life increased the odds ratio [OR] of asthma symptoms at 2-8 years of age (crude OR, 2.26; 95% confidence interval [CI], 1.53-3.35; p<0.01), and the strength of association was similar after adjusting for a family history of asthma or atopic disorder, preterm delivery, birth order, and delivery method (adjusted OR, 1.91; 95% CI, 1.27-2.88; p=0.03).

CONCLUSIONS

Our study suggests that antibiotic consumption in children was associated with an increased risk of childhood asthma, and an additional confirmative study is needed.

Summary

Citations

Citations to this article as recorded by

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Antibiotic exposure and adverse long-term health outcomes in children: A systematic review and meta-analysis
Quynh A Duong, Laure F Pittet, Nigel Curtis, Petra Zimmermann
Journal of Infection.2022; 85(3): 213. CrossRef
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Hoon Jang, Mustafa Ozkaynak, Claudia R. Amura, Turgay Ayer, Marion R. Sills
Journal of Asthma.2021; 58(2): 180. CrossRef
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Marion R. Sills, Mustafa Ozkaynak, Hoon Jang
International Journal of Medical Informatics.2021; 151: 104468. CrossRef
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Yang Yie Sio, Fook Tim Chew
Journal of Physiological Anthropology.2021;[Epub] CrossRef
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Zeyi Zhang, Jingjing Wang, Haixia Wang, Yizhang Li, Yuanmin Jia, Mo Yi, Ou Chen
World Allergy Organization Journal.2021; 14(11): 100607. CrossRef
Early-Life Exposure to Oral Antibiotics and Lung Function Into Early Adulthood
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Ruth Baron, Meron Taye, Isolde Besseling-van der Vaart, Joanne Ujčič-Voortman, Hania Szajewska, Jacob C. Seidell, Arnoud Verhoeff
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Evaluation of Allergic Symptoms Prevalence and Its Relationship with Acetaminophen/Antibiotic Use and Hospitalization Among School-Aged Children in Tehran, Iran
Mohammad Reza Fazlollahi, Javid Morad Abbasi, Vahid Ghobadi Dana, Alireza Yousefzade, Nastaran Sabetkish, Shahpar Haghighat
Iranian Red Crescent Medical Journal.2017;[Epub] CrossRef
Airway Microbiota and the Implications of Dysbiosis in Asthma
Juliana Durack, Homer A. Boushey, Susan V. Lynch
Current Allergy and Asthma Reports.2016;[Epub] CrossRef
Early-life antibiotic use is associated with wheezing among children with high atopic risk: a prospective European study
Wenjie Sun, Erik R. Svendsen, Wilfried J. J. Karmaus, Joachim Kuehr, Johannes Forster
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Characteristics of Shigella sonnei Isolated in Kyungsangbuk-do in 1998: Biochemical Characteristics, Biotyping, Antibiotic Resistance Pattern, and Plasmid Profile.: Chang Kyu Sohn, Wan Huh, Doo Young Lee, Si Kyu Lim, Je Wook Lee, Byung Chun Kim, Wan Park; Korean J Epidemiol. 1999;21(2):227-233.

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Abstract PDF: Abstract
Thirty nine strains and 109 strains of Shigella sonnei were isolated from the outbreaks of Youngchun and Kyungju, respectively, while 15 strains were isolated from sporadic cases of eight regions in Kyungbuk province from September to November in 1998. We investigated the relationship among the S. sonnei strains by using biochemical characteristics, biotyping, antibiotic resistance pattern, and plasmid profile. Among the isolates, seven strains of S. sonnei isolated in Youngchun showed gelatin hydrolyase positive but the others showed gelatin hydrolyase negative. One hundred and fifty two strains were a type, while eleven among thirty nine strains isolated in Youngchun were g type. Antibiotics resistance patterns of S. sonnei strains isolated in Youngchun and Kyungju were significantly different. Thirty nine strains of S. sonnei isolated in Youngchun were resistant to SM, TE, and TMP/SMX, while eighty six of S. sonnei among one hundred and nine strains isolated in Kyungju were resistant to AM, CB, K, SM, TE, and TMP/SMX. Antibiotics resistance patterns of residual twenty three isolates were similar to those of eighty six strains. The Plasmid profiles of strains of S. sonnei isolated from the Kyungju were different from those of S. sonnei strains isolated in Youngchun. The Plasmid profiles of S. sonnei strains isolated from Youngchun were identical to those of a S. sonnei strains randomly selected from the outbreak in Daegu in 1998. The Plasmid profiles of S. sonnei strains isolated from Kyungju were identical to those of two strains of S. sonnei randomly selected from the outbreaks of Kanglung and Wonju in 1998. From the above results, it is considered that the strains of S. sonnei isolated from Kyungju and Youngchun region are not identical clone.; Summary

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