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

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.

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Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-30
DOI
https://doi.org/10.5281/zenodo.17235701
Primary Topic
Wireless Sensor Networks for Data Analysis
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article
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Wireless Sensor Networks for Data Analysis
article

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

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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.

Zenodo (CERN European Organization for Nuclear Research)
University of Nairobi (KE)
Sustainable cities and communities
Openalex Percentile: Top 44%
Wireless Sensor Networks for Data Analysis
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