Determinants and patterns of antibiotic consumption for children under five in Nepal: analysis and modelling of Demographic Health Survey data from 2006 to 2016

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Abstract

Objectives: Our aims were to examine AMR-specific and AMR-sensitive factors associated with antibiotic consumption in Nepal between 2006 and 2016, to explore health care-seeking patterns and the source of antibiotics. Methods: Cross-sectional data from children under five in households in Nepal were extracted from the 2006, 2011 and 2016 Demographic Health Surveys (DHS). Bivariable and multivariable analyses were carried out to assess the association of disease prevalence and antibiotic use with age, sex, ecological location, urban/rural location, wealth index, household size, maternal smoking, use of clean fuel, sanitation, nutritional status, access to health care and vaccinations. Results: Prevalence of fever, acute respiratory infection (ARI) and diarrhoea decreased between 2006 and 2016, whilst the proportion of children under five receiving antibiotics increased. Measles vaccination, basic vaccinations, nutritional status, sanitation and access to health care were associated with antibiotic use. Those in the highest wealth index use less antibiotics and antibiotic consumption in rural areas surpassed urban regions over time. Health seeking from the private sector has overtaken government facilities since 2006 with antibiotics mainly originating from pharmacies and private hospitals. Adherence to WHO-recommended antibiotics has fallen over time. Conclusions: With rising wealth, there has been a decline in disease prevalence but an increase in antibiotic use and more access to unregulated sources. Understanding factors associated with antibiotic use will help to inform interventions to reduce inappropriate antibiotic use whilst ensuring access to those who need them.

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APA

Zheng, C., Karkey, A., Wang, T., Makuka, G., van Doorn, H. R., & Lewycka, S. (2021). Determinants and patterns of antibiotic consumption for children under five in Nepal: analysis and modelling of Demographic Health Survey data from 2006 to 2016. Tropical Medicine and International Health, 26(4), 397–409. https://doi.org/10.1111/tmi.13540

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