Identity, Preparation, Dosages and Conservation Knowledge of the Antidiabetic Herbs Used by The Tugen Living in Baringo County-Kenya

The primary goal of managing Diabetes Mellitus (DM) is to regulate blood sugar levels within the physiologic limits (3Mmol/l to7Mmmol/l-fasting blood sugars). This can be either done pharmacologically (conventional or non-conventional) or non- pharmacologically (exercises etc.). Available reports show that, more than 80% of the African population use non-conventional pharmacological approaches- especially herbal remedies in the management of their ailments including DM. Objectives: The study sought to identify the antidiabetic herbs used by the Tugen community living in Baringo county-Kenya. Establish the plant parts in use, preparation methods and the dosage of each specific herb. Equally assess the knowledge of both the diabetics and the antidiabetic herbalists on possible antidiabetic herbal medicine conservation. Materials and Methodolog: A descriptive cross-sectional survey study design was adopted. Information about the local names of commonly used herbs and the plant parts, their preparation, their doses and the knowledge of antidiabetic herbal conservation was obtained from 39 medically ascertained diabetics between 27 to 70 years old and 12 herbalists, using a researcher administered questionnaire and an interview guiderespectively. They were identified through snow balling and purposive sampling method. Samples of the identified plants’/ herbs’ parts were collected and taken for taxonomic identification and Assigning of botanical names based on their morphological characteristics was done at the department of Botany, University of Eldoret, Kenya. Data entry, cleaning, and coding was done using Excel Office 13. Analysising with SPSS version 21 software. The summarized data were presented in tables of frequencies and graphs where applicable. Results : The commonly used herbal medications in the management of diabetes, in Baringo as reported by the herbalist were Urtica dioica (stinging nettle (UD)) (75%) and Carissa edulis (CE) (58%). Most (85%) of the herbs according to the diabetics were dried, crushed to powder then added to boiling water before drinking. Dosage, unanimously, the herbs were taken twice a day 2-3 teaspoonfuls in either 250mls or 500mls of boiled and/or cooled water. Diabetics (77%) took these herbs because they believed herbal medicine improve their health. Herbalists (67%), believed their diabetic herbal medications stabilize blood sugars and cured their patients. Diabetic patients and herbalists had some knowledge about bio conservation, 44% of the diabetics understood conservation as planting more medicinal herbal plants/herbs. Herbalists 75% of them described conservations as a surity of constant supply annually. According to the herbalists “those herbs which can be dried and stored, could be harvested in plenty during the rainy season to last till the next rainy season”. Conclusions: Among the Tugen living in baringo, Carissa edulis (CE) and Urtica dioica (UD) were the most frequently used antidiabetics followed by Hypoestes forskaolii (HF) to regulate sugar levels. There was no standard method of preparation and dosaging of these herbs due variations from patients/herbalists. Recommendations: Policymakers need to create awareness on the importance of standardization and bio conservation for enhancement of sustainability and careful use of these very important scarce environmental resources and not loose the diabetic herb/plant biodiversity. Taking care of biodiversity and its services in the community, creates one of the reasons why we should enhance and promote conservation and sustainable use of medicinal plants Keywords: Anti-diabetic herbal medicinal plants/herbs, Diabetics, Antidiabetic plant/herb herbalists, Preparation, Dosaging, Tugen community, Baringo County

Risk Assessment of Aflatoxin and Fumonisin in Fish Feeds, Kenya: A Review

Fish is a protein source and constitutes other significant nutrients that have been crucial to human health. Aquaculture in Kenya has grown faster than any other food production sector, with fish feeds being prepared from different cereal products commonly contaminated by Mycotoxins. But controlling the growth of fungi that cause mycotoxin has been a challenge due to conditions that enable their development. With fish contamination primarily ignored, there is still high consumption of fish being propagated by improved and increased aquacultural activities. There have been various qualitative and quantitative assessments on Aflatoxin and Fumonisin in animal feed and food with little focus on fish feed which might be the most significant risk factor for cancer development. Kenya's high occurrence warranted the current review, which describes sources of fish feeds, conditions for mould growth, exposure of fish too contaminated feeds, decontamination of fish feed and feed ingredients, effects of Fumonisin and Aflatoxin on fish and human, risk characterization and management strategies. This review provides a platform and insights to novice researchers to pave the way for future research in the area. Keywords: Mycotoxins; Aflatoxins; Fumonisin; Uasin Gishu; Kisumu. DOI: 10.7176/JBAH/11-10-05 Publication date:May 31st 202

Aberration of Metals Competing for Iron on Exposure to Lambda Cyhalothrin and Aflatoxins in Dietary Fish from Selected Aquatic Sources in Kenya

Excess or deficiency of minerals may seriously disturb biochemical processes and upset internal homeostasis, leading to various diseases and disorders in fish species due to deficiency or excess of micro and macro elements caused by improper nutrition, avitaminosis or poisoning. The specific objectives of the study were to determine the iron levels and aberration of metals competing on exposure to lambda-cyhalothrin and aflatoxins in dietary fish from selected aquatic sources in Kenya. The concentration of elements cadmium, zinc, and iron in Oreochromis niloticus and Clarias gariepinus bred in Kenya Marine and Fisheries Research Institute at Sagana and obtained from River Nyando was measured using atomic absorption spectrophotometer. Iron availability was lower on treatment with Aflatoxin compared to Lambda-Cyhalothrin with a mean of 3.66 ± 0.84 mg/kg, but on subjection to zinc, competition was 3.82 mg/kg on consideration of zinc competition. The naturally occurring toxins cause micronutrient deprival and therefore relevant stakeholders be keen to prevent contamination from farm to fork

Geochemistry and health data to inform public health outcomes in western Kenya

Environmental geochemistry data can reveal spatial differences in dietary intake with implications for health status. For example, soil and subsequently crop chemistry data is influenced by changes in soil type, pH, geology and geographical features (amongst other factors). Specific soil and food composition data can support estimates of dietary mineral supplies (Watts et al. 2019, 2021a). However, additional metrics can supplement the understanding of links between geochemistry and health in Western Kenya. Here we present a summary of data from a survey of soil and crops, but will focus in particular on the private drinking water and urines as an estimate of nutritional status or exposure to potentially harmful elements collected across 20 Counties in Western Kenya. We discuss the potential for interpreting health metrics, including: food dietary estimates, drinking water and biomonitoring data (urine – Watts et al. 2020; 2021b). Comparisons between these metrics will be discussed, along with the limitations in interpreting these data. These datasets were presented to stakeholders from each of the 20 Counties in June 2022 to provide feedback on data outcomes and to co-design the data delivery to assist in dissemination. Stakeholders included the leaders of agriculture and public health offices in each County government office and from academia. This second point of discussion will raise the importance of information flow back and the challenges in doing so e.g. mis-/over-interpretation of data, opportunities to incorporate into decision making and the stimulation of new research. In particular, the value of undertaking a multi-disciplinary research project to encourage stakeholders to plan intervention strategies with a multi-disciplinary consideration

Public health assessment of Kenyan ASGM communities using multi-element biomonitoring, dietary and environmental evaluation

The Kakamega gold belt's natural geological enrichment and artisanal and small-scale gold mining (ASGM) have resulted in food and environmental pollution, human exposure, and subsequent risks to health. This study aimed to characterise exposure pathways and risks among ASGM communities. Human hair, nails, urine, water, and staple food crops were collected and analysed from 144 ASGM miners and 25 people from the ASGM associated communities. Exposure to PHEs was predominantly via drinking water from mine shafts, springs and shallow-wells (for As>Pb>Cr>Al), with up to 366 µg L−1 arsenic measured in shaft waters consumed by miners. Additional exposure was via consumption of locally grown crops (for As>Ni>Pb>Cr>Cd>Hg>Al) besides inhalation of Hg vapour and dust, and direct dermal contact with Hg. Urinary elemental concentrations for both ASGM workers and wider ASGM communities were in nearly all cases above bioequivalents and reference upper thresholds for As, Cr, Hg, Ni, Pb and Sb, with median concentrations of 12.3, 0.4, 1.6, 5.1, 0.7 and 0.15 µg L−1, respectively. Urinary As concentrations showed a strong positive correlation (0.958) with As in drinking water. This study highlighted the importance of a multidisciplinary approach in integrating environmental, dietary, and public health investigations to better characterise the hazards and risks associated with ASGM and better understand the trade-offs associated with ASGM activities relating to public health and environmental sustainability. Further research is crucial, and study results have been shared with Public Health and Environmental authorities to inform mitigation efforts

Iodine status in western Kenya: a community-based cross-sectional survey of urinary and drinking water iodine concentrations

Spot urinary iodine concentrations (UIC) are presented for 248 individuals from western Kenya with paired drinking water collected between 2016 and 2018. The median UIC was 271 µg L−1, ranging from 9 to 3146 µg L−1, unadjusted for hydration status/dilution. From these data, 12% were potentially iodine deficient ( 300 µg L−1). The application of hydration status/urinary dilution correction methods was evaluated for UICs, using creatinine, osmolality and specific gravity. The use of specific gravity correction for spot urine samples to account for hydration status/urinary dilution presents a practical approach for studies with limited budgets, rather than relying on unadjusted UICs, 24 h sampling, use of significantly large sample size in a cross-sectional study and other reported measures to smooth out the urinary dilution effect. Urinary corrections did influence boundary assessment for deficiency–sufficiency–excess for this group of participants, ranging from 31 to 44% having excess iodine intake, albeit for a study of this size. However, comparison of the correction methods did highlight that 22% of the variation in UICs was due to urinary dilution, highlighting the need for such correction, although creatinine performed poorly, yet specific gravity as a low-cost method was comparable to osmolality corrections as the often stated ‘gold standard’ metric for urinary concentration. Paired drinking water samples contained a median iodine concentration of 3.2 µg L−1 (0.2–304.1 µg L−1). A weak correlation was observed between UIC and water-I concentrations (R = 0.11)

Spatial distribution and loss of micronutrients in soils from two different land use management

Land use – land cover changes affect the ecosystems' status and integrity to support and supply the services. Agricultural activities and attendant soil erosion, leaching or depletion of nutrients may result in increased soil degradation. The study investigated micronutrient spatial distribution and concentration in soils within two different agricultural land use management. The study employed RUSLE equations to determine the erosion rate within the selected plots. Topsoils (5-10cm) from different points within the plots were collected and analyzed for micronutrients using ICPMS(QQQ). The plots are located in high potential soil erosion places with soil erodibility (K) factor OF 0.031-ton ha-1MJ-1mm-1 within the Ombeyi river catchment. The soil erosion was estimated to be > 50t ha-1 year-1 , implying the high loss of nutrients; hence, over 52 elements were analyzed. The two plots compared micronutrients iodine (I), calcium (Ca), copper (Cu), iron (Fe), magnesium (Mg), selenium (Se), zinc (Zn), and molybdenum (Mo). In Plot 1(no terraces), micronutrients were concentrated at the base of the plot, while in plot 2 ( terraces), some elements were evenly distributed. There is a significant difference in the concentration of elements between the plots; I, Se, Cu, Ca and Mg, depicting a p-Value of 0.05. Elements in plot one were mapped with high concentration at the lower part of the plot as related to plot two which most of the elements were evenly distributed hence reduced micronutrients in plot 2. This encourages educating farmers on the importance of good terrain soil management

Predictive geochemical mapping using machine learning in western Kenya

Digital soil mapping techniques represent a cost-effective method for obtaining detailed information regarding the spatial distribution of chemical elements in soils. Machine learning (ML) algorithms using random forest (RF) models have been developed for classification, pattern recognition and regression tasks, they are capable of modelling non-linear relationships using a range of datasets, identifying hierarchical relationships, and determining the importance of predictor variables. In this study, we describe a framework for spatial prediction based on RF modelling where inverse distance weighted (IDW) predictors are used in conjunction with ancillary environmental covariates. The model was applied to predict the total concentration (mg kg−1) and assess the prediction uncertainty of 56 elements, soil pH and organic matter content using 466 soil samples in western Kenya; the results of iodine (I), selenium (Se), zinc (Zn) and soil pH are highlighted in this work. These elements were selected due to contrasting biogeochemical cycles and widespread dietary deficiencies in sub-Saharan Africa, whilst soil pH is an important parameter controlling soil chemical reactions. Algorithm performance was evaluated determining the relative importance of each predictor variable and the model's response using partial dependence profiles. The accuracy and precision of each RF model were assessed by evaluating out-of-bag predicted values. The models R2 values range from 0.31 to 0.64 whilst CCC values range from 0.51 to 0.77. The IDW predictor variables had the greatest impact on assessing the distribution of soil properties in the study area, however, the inclusion of ancillary environmental data improved model performance for all soil properties. The results presented in this paper highlight the benefits of ML algorithms which can incorporate multiple layers of data for spatial prediction, uncertainty assessment and attributing variable importance. Additional research is now required to ensure health practitioners and the agri-community utilise the geochemical maps presented here for assessing the relationship between environmental geochemistry, endemic diseases and preventable micronutrient deficiency

Predictive geochemical mapping using machine learning in western Kenya

Digital soil mapping is a cost-effective method for obtaining detailed information regarding the spatial distribution of chemical elements in soils. Machine learning (ML) algorithms such as random forest (RF) models have been developed for such tasks as they are capable of modelling non-linear relationships using a range of datasets and determining the importance of predictor variables, offering multiple benefits to traditional techniques such as kriging. In this study, we describe a framework for spatial prediction based on RF modelling where inverse distance weighted (IDW) predictors are used in conjunction with auxiliary environmental covariates. The model was applied to predict the total concentration (mg kg-1 ) of 56 elements, soil pH and organic matter content, as well as to assess prediction uncertainty using 466 soil samples in western Kenya (Watts et al 2021). The results of iodine (I), selenium (Se), zinc (Zn) and soil pH are highlighted in this work due to their contrasting biogeochemical cycles and widespread dietary deficiencies in sub-Saharan Africa, whilst soil pH was assessed as an important parameter to define soil chemical reactions. Algorithm performance was evaluated to determine the importance of each predictor variable and the model’s response using partial dependence profiles. The accuracy and precision of each RF model were assessed by evaluating the out-of-bag predicted values. The IDW predictor variables had the greatest impact on assessing the distribution of soil properties in the study area, however, the inclusion of auxiliary values did improve model performance for all soil properties. The results presented in this paper highlight the benefits of ML algorithms which can incorporate multiple layers of data for spatial prediction, uncertainty assessment and attributing variable importance. Additional research is now required to ensure health practitioners and the agricommunity utilise the geochemical maps presented here, and the webtool, for assessing the relationship between environmental geochemistry and endemic diseases and preventable micronutrient deficiency

Review: Artisanal Gold Mining in Africa—Environmental Pollution and Human Health Implications

About nine million Artisanal and Small-scale Gold Mining (ASGM) workers in Africa and people living near ASGM activities are highly exposed to geogenic and anthropogenic potentially toxic elements (PTEs). Despite the hazards and risks posed by ASGM being well characterized, coordinated multidisciplinary environmental characterization with combined public health studies are limited, with often piecemeal and snapshot studies reported, as highlighted by this review. Furthermore, studies are often not connected with efforts to minimize hazards holistically. Given this, we systematically reviewed the scientific literature on human health hazards associated with ASGM in Africa through Google Scholar, Science Direct, and Pubmed databases. One hundred and seventy-three peer-reviewed papers published between 1996 and June 2023 from 30 African countries were identified. Toxicological environmental hazards were reported in 102 peer-reviewed papers, notably As, Cd, CN, Cr, Hg, Pb, respirable SiO2-laden dust, and radionuclides. Exposure to PTEs in human biomonitoring matrices and associated health impacts were documented in 71 papers. Hg was the most reported hazard. Gaps in research robustness, regulation and policy framework, technology, risk detection, surveillance, and management were found. Despite international and in-country mitigation efforts, ASGM-related hazards in Africa are worsening. This review paper highlights the need for coordinated action and multidisciplinary collaborative research to connect dispersed isolated studies to better characterize the associated disease burden associated with ASGM in Africa and sustainably maximize the wider benefits of ASGM whilst protecting public health and the environment