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ZENODO
Article . 2025
License: CC BY NC
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY NC
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY NC
Data sources: Datacite
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TRADITIONAL MEDICINAL PLANTS USED IN GITHUNGURI AREA, KIAMBU COUNTY, KENYA; THE PART OF THE PLANT USED, THEIR PREPARATIONS, AILMENT USED TO TREAT AND A REVIEW ON THEIR PHYTOCHEMICAL COMPOSITION

Authors: Joseph M. Ndegwa*; James M. Mbaria;

TRADITIONAL MEDICINAL PLANTS USED IN GITHUNGURI AREA, KIAMBU COUNTY, KENYA; THE PART OF THE PLANT USED, THEIR PREPARATIONS, AILMENT USED TO TREAT AND A REVIEW ON THEIR PHYTOCHEMICAL COMPOSITION

Abstract

Collection and preservation of ethno-medical information has been given little attention in the modern world due to rapid industrialisation and loss of ethnic culture. Some information on this will definitely get lost. There is, therefore, an immediate need in collection and documentation of information concerning traditional medicine. Hence, a survey on the use of traditional medicine was carried out in Githunguri area, Kiambu County, Kenya followed by a review of their phytochemical composition. A cross-sectional study was used in this study. Study sites were selected using cluster sampling method where villages were used as clusters. 59 respondents were interviewed in all the villages. All the relevant data was collected using a questionnaire which had been developed prior to the study. The data was then analysed using descriptive methods which included the various plants used as traditional medicine, the parts used, how they are prepared and the diseases they are used to treat. The data was then presented in tables, charts and figures. A review of phytochemical composition of these plants was also done. Most people who use traditional medicine in this area are mostly elderly aged above 50 years old (45.76%). The study also revealed that the majority of traditional medicine users are male (55.93%) as compared to their female counterparts (44.07%). Information on traditional medicine has been acquired from parents according to most respondents (44.07%). 61 species of traditional medicinal plants from 37 families were identified. Most of the species came from Asteraceae family (13.11%), followed by solanaceae family (8.19%). The most widely used plant species is Prunus Africana (Hook. f.) Kalkman (69.49%), followed by Croton megalocarpus Hutch. and Melia azadirachta L. both of them used at a rate of 52.54%. Aloe kedongensis Reynolds is next at a rate of 49.15%. The diseases mostly treated using traditional medicine are malaria (76.27%), gastrointestinal (74.58%) and respiratory diseases (47.46%). The most widely used parts of these plants are leaves (68.85%) and roots (32.79%). Most plant preparations were mostly decoctions (91.80%). There is wide usage of traditional medicine in this area. Information concerning the use of these medicines was documented. However, deforestation is a major challenge affecting their usage. Challenges facing the use of traditional medicine should be addressed by the relevant stakeholders. It was also recommended for more study in order to document more plants that are of medicinal value and to determine the safety and efficacy of these medicines.

Related Organizations
Keywords

Traditional medicinal plants, Decoctions, Phytochemical, Ethno-medical

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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