Fluoride levels of Irish Potatoes (Solanum tuberosum L.), Beans (Phaseolus vulgaris L.) and Green Peas (Possum sativa) from Nakuru County, Kenya, and the risk of fluoride overexposure

doi:10.21203/rs.3.rs-2370661/v1

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Research Article

Fluoride levels of Irish Potatoes (Solanum tuberosum L.), Beans (Phaseolus vulgaris L.) and Green Peas (Possum sativa) from Nakuru County, Kenya, and the risk of fluoride overexposure

https://doi.org/10.21203/rs.3.rs-2370661/v1

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Background

Considerable research has been dedicated to investigating fluoride (F) contaminations of water along the Eastern Africa Rift Valley System (EARS) but critical F data on the food systems is still needed for assessing the risk of human F overexposure and for informing the development of plausible strategies for ameliorating its deleterious effects among the communities. The current study investigated F levels of potatoes (Solanum tuberosum L.), beans (Phaseolus vulgaris L.) and garden peas (Possum sativa) from Nakuru County, Kenya, and then assessed the risk of human F overexposure through contaminated foodstuffs.

Results

High F levels exceeding WHO’s recommended dietary allowance of 4 mg/kg has been reported in the three foodstuffs. Fluoride levels in the beans and in the potatoes were high and varied from with regions but F levels in peas were lower and nearly constant across the regions. Risks of F overexposure through F-contaminated foodstuffs increased with increasing body weight and physical activity levels, especially in young children and among male populations.

Conclusions

High F in the foodstuffs have adverse public health implications on the resident communities and the development of plausible remediation and preventive strategies for ameliorating its deleterious effects among the communities is of essence.

Beans

Body Weight

Diets

East Africa Rift Valley System

Fluoride overexposure

Garden Peas

Irish potatoes

Nutrition

Physical Activity Levels

Prolonged F ingestion through foods and water leads adverse health effects to human body, which range from dental fluorosis to skeletal fluorosis and other non-skeletal adverse symptoms. The Eastern African Rift Valley System (EARS) is one of the regions of the world where highest F concentrations have been reported in the environmental samples (Gizaw, 1996). as a result, high F levels exceeding World Health Organization (WHO) permissible standards of 1.5 mg/L for drinking water (WHO, 1984) and the United States Environmental Protection Agency (USEPA) reference dose (RfD) of 0.06 mg/kg/day for non-liquid foodstuffs (U.S. Department of Health and Human Services, 2003) has been reported in majority of the natural water sources (Wambu and Muthakia, 2011) and in certain foodstuffs (Asembo et al., 2021; Maina et al., 2020) within the EARS regions. This has heightened food safety concerns in these areas and prompted investigations focusing on evaluating the F content of key foodstuffs from these areas (Gevera et al., 2022). Nonetheless, there is still paucity in crucial accurate scientific data on the F levels of basic staple foodstuffs, which is necessary for in-depth understanding of the fluoride problem and for informing the strategies for dealing with fluoride overexposure and amelioration of its deleterious effects among the communities.

The current study was therefore designed to investigate the F content of Irish potatoes (Solanum tuberosum L.), beans and peas (Possum sativa) obtained from parts of Nakuru County of Kenya and assess the risk of F overexposure of different categories of people in the affected communities. It was anticipated the results would improve knowledge of the local F problem and to contribute to the ongoing global efforts to develop credible working solutions to the harmful effects of F overexposure among the communities living in high F regions of the world.

The results of the analyses of F levels of the foodstuffs by the sub-counties are presented in Table 1.

Table 1

Spatial distribution of [F] mg/kg by the sub-counties
Sub-County	F concentrations, [F], of the foodstuffs (mg/kg)
Sub-County	[F]_potatoes	[F]_beans	[F]_peas
Rongai	4.88 ± 0.39	13.90 ± 1.13	4.78 ± 0.63
Molo	15.03 ± 3.26	6.55 ± 0.64	5.12 ± 0.40
Njoro	7.19 ± 1.11	4.90 ± 0.31	4.79 ± 0.28
Nakuru North	10.12 ± 1.40	14.38 ± 1.41	5.28 ± 0.46
Nakuru East	7.29 ± 0.60	8.09 ± 0.90	5.55 ± 0.30
Nakuru West	8.81 ± 0.93	12.80 ± 2.22	5.33 ± 0.80
Gilgil	5.35 ± 0.56	4.45 ± 0.88	4.19 ± 0.24
Naivasha	4.47 ± 0.56	4.21 ± 0.37	3.79 ± 1.05
Overall	8.16 ± 0.63	8.66 ± 1.55	4.92 ± 0.18

The F content of the foodstuffs was found to be in the order:

$${\left[F\right]}_{peas}\ll {\left[F\right]}_{beans}\approx {\left[F\right\}}_{potatoes}$$

where, [F]_peas, [F]_beans, and [F]_potatoes are the F concentrations (mg/kg) in the respective foodstuffs. The highest (5.55 ± 0.30 mg/kg) and the lowest (3.79 ± 1.05 mg/kg) mean F levels in peas was recorded in the samples from Nakuru East and Naivasha sub-counties, respectively but the highest mean F content of the beans (17.33 mg/kg) and of the potato samples (15.03 mg/kg) were recorded among the samples collected from Nakuru North and Molo sub-counties, respectively. On the whole, however, the combined lowest F levels in the foodstuffs were in the foodstuffs obtained from Naivasha, Gilgil and Njoro whereas the highest values occurred in the foodstuff samples from Nakuru North, Nakuru West, Molo, Rongai and Nakuru East sub-counties, respectively. F variations between sampling site were analyzed statistically using ANOVA and t-test.

The ANOVA showed there was no significant difference in the F content of peas samples between the 8 sub-counties (p = .436) of Nakuru county according to the results of the analyses of the variance (ANOVA). Nonetheless, it was observed that the F levels of both the beans and potatoes samples were significantly different between the 8 sub-counties studied (p = .000).

Using paired t-test, the mean fluoride level recorded was (p ˂ .05) significantly different between peas and beans (P = .033, T=-2.657) and between peas and potatoes (P = 0.030, T= -2.712). However, paired t-test, the mean fluoride level recorded was not significantly different between beans and potatoes (P = 0.067, T = 0.415).

Paired t-test showed that there was no significant difference in fluorides levels in peas found in Njoro and Naivasha region (t=-3.151, df = 3, P = 0.051). Paired t-test was also used to compare fluorides levels of peas from in Nakuru and Gilgil region; the results showed strong significant in fluorides levels in peas in both regions (t=-23.33, d f = 4, P = 0.00). Then, using paired t-test, the beans mean fluoride level recorded was (p ˂ 0.05) significantly different between Njoro and Naivasha region and between Nakuru and Gilgil (p = 0.000, t=-1.367) and (p = 0.020, t= -2.361), respectively. Also, the potatoes mean fluoride level recorded was (p ˂ 0.05) significantly different between Njoro and Naivasha (t=-1.167, P = 0.001).

In order to assess the potential of F overexposure through the foodstuffs, the household dietary patterns of local communities based on food diversification data and the food production for the area was analyzed in order to estimate the food energy contribution (FEC), and hence, the importance of the foodstuffs in contributing to the daily household food menu and the results presented in Table 2.

Table 2

The main foodstuffs contributing to household dietary energy requirement and nourishments in Nakuru County, Kenya
Foodstuffs	E (kcal/kg)	[F] (mg/kg)	FEC (%)	Literature source for [F] values
Maize (Zea mays)	1110	13.6	21.3	Unpublished data
Irish Potatoes (Solanum tuberosum L.),	1050	8.2	20.1	Current Study
Garden Peas (Possum sativa)	1200	4.9	10.4	Current Study
Others (e.g., tea beverage etc.)			9.0	-
Carrots (Daucus carota)	320		8.7	-
Cabbage (Brassica oleracea capitata)	1000		6.5	-
Onions (Allium cepa)	420		6.5	-
Sukuma (Brassica oleracea)	540	13.3	6.5	(Maina et al., 2020)
Tomatoes (Lycopersicum esculentum)	280	12.9	6.5	(Maina et al., 2020)
Beans (Phaseolus vulgaris L.)	1090	8.7	4.6	Current Study

It was found that the main foodstuffs contributing to meeting the daily energy requirements of the average household in Nakuru County included maize (Zea mays), Irish potatoes, garden peas (Possum sativa), carrots (Daucus carota), cabbage (Brassica oleracea capitata), and local varieties of kales known as Sukuma wiki (Brassica oleracea). Also, the average households consumed large quantities of tomatoes (Lycopersicum esculentum), onions (Allium cepa) used in preparing the main dishes in every meal. These data were used in computing estimated average daily F dosage, EADD (mg/kg/day) for the residents of Nakuru County by age groups, gender, body weight (BW) and physical activities level (PAL).

The computation of the estimated average daily F dosage, EADD (mg/kg/day) for the residents of Nakuru county was based on the 50th percentile weight-for-age data (National Center for Health Statistics, 2000) and on the corresponding Food and Agriculture Organization’s food consumption patterns (FAO/WHO/UNU Expert Consultation, 2001) and the results presented in FIGURE 1 and 2.

The results for dietary F exposure through food for boys and girls aged 1–18 years is depicted in FIGURE 1. It was found that F exposure was higher in boys than in the girls and that the EADD increased with increasing age of the children from age of one year and leveled off at 16 and 18 years for the girls and the boys, respectively. The EADD for boys was about 1.10 times that for the girls in the age bracket of 1–12 years and about 1.36 times greater for boys than for girls in the adolescent age bracket of 12–18 years.

The levels of EADD computed for different categories of BW and PAL by gender and age groups are depicted in FIGURES 2 (a)–(c).

The results showed that the risk of F overexposure through the foodstuffs increased with increasing BW and increasing PAL. It was clear that the risk of F overexposure was greater the young adults (18–29 years) than among the older categories of people. It could be observed that at low BW of 50 kg, therefore, the F exposure for the young adults (18–29 years) were similar to those for males of 30–59 years of age but differed markedly from those for elder men above 60 years age. The value of EADD was notably different for the 18–29, 30–59 and 60 and above age categories for higher BW of 70 and above as depicted in Figs. 4 (b) and (c), respectively.

The results in the current study showed that peas, beans and Irish potatoes from Nakuru county contained high levels of F above the WHO’s recommended dietary allowance (RDA) levels but the F levels in garden peas were somewhat lower compared to that of the beans and the potatoes. Also, the ANOVA showed that the F levels in the beans and Irish potatoes varied with ecological/climactic conditions of the regions within Nakuru County but the F content in the peas was not statistically different between the regions despite their heterogeneous attributes.

Differences in the mean F levels in foodstuffs produced under similar conditions can be caused, in part, by variations in soil and soil-water F conditions and to dissimilarities in ecological conditions including the rainfall patterns and the temperature across the region. Other than ecological conditions affecting the F accumulation of the foodstuffs, the type and extent of vegetation cover, prevailing land use forms and practices, other human activities s (Li et al., 2021) can influence the soil-water F content to varying degrees. Also, minor variations in the local geology including disparities in the volcanic terrains and presence of widespread active geothermal activities, which are widespread in the present study area can contribute to the net spatial differences in the soil-water F status. Thus, the high F content in the foodstuffs obtained from Molo and Njoro regions, as well from Nakuru North and Rongai could, therefore, be attributed to the presence of high-F volcanic terrains and to the F enriched soils from ascent of hydrothermal fluids of active geothermal activities in parts of these latter areas (Ghiglieri et al., 2017).

On the other hand, the diverse phenotypic traits of the crop species may control how and the extents to which the different plants absorb nutrients including F from the soils (Maina et al., 2020). The low F concentrations in the peas samples across the regions of Nakuru County compared to the F levels of the beans and the potatoes samples indicated that the F uptake by the peas plants was probably not controlled by variations in the ecological, climatological and geological F conditions of the regions. It showed that the pea’s plant could more resistant to F uptake from the environment than both the beans and the Irish potatoes.

It was revealed that males at all ages could absorb higher F levels compared to the corresponding female populations. It was expected that, under the similar conditions of external exposure, the populations of people would be affected more strongly and more extensively by F than the corresponding female populations. Indeed, in a previous survey of 3771 adult males and 4495 adult females on the F risks of bone fractures among rural communities in China, authors indicated that prevalence of the F-instigated bone fractures was higher among the male populations by a factor of 1.35 compared to those among the female populations (Li et al., 2001). A comparison of the different effects of F overexposures between male and female human populations reported in the literature around the world is depicted in Table 3.

Table 3

Differential impact of fluoride on the male and female gender reported in the literature all over the world
Fluoride adverse health effect	Place of study	Sample size (n)	Female Index (I_f)	Male index (I_m)	Units	I_m/I_f	Literature source	Age bracket (years)	Age category
Dental fluorosis prevalence (< 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with < 1.5 mg/L F water	244	4.58	6.67	%	1.46	(Kotecha et al., 2012)	0–4	Children
Dental fluorosis prevalence (> 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with > 1.5 mg/L F water	315	7.04	7.55	%	1.07	(Kotecha et al., 2012)	0–4	Children
Dental fluorosis prevalence	Ledhupur & Rustampur, Varanasi	218	4.49	4.58	%	1.02	(Ray et al., 1983)	1–5	Children
Dental fluorosis prevalence	Nawa tehsil, Nagaur district, Rajasthan (India)	60	90	91.67	%	1.02	(Gautam et al., 2011)	4–16	Children
Blood serum/plasma F	Balavenkatapuram, Kalyandurg Mandal, Anantapur, Andhra Pradesh, India	10	0.18	0.51	ppm	2.83	(Bhagavan and Raghu, 2006)	5–11	Children
Urine F	Ayyagarlapalli, Setturu Mandal, Anantapur District, Andhra Pradesh, India	10	2.14	3.08	ppm	1.44	(Bhagavan and Raghu, 2006)	5–11	Children
Urine F	Kanukuru, Setturu Mandal, Anantapur District, Andhra Pradesh, India	10	5.12	7.26	ppm	1.42	(Bhagavan and Raghu, 2006)	5–11	Children
Urine F	Balavenkatapuram, Kalyandurg Mandal, Anantapur, Andhra Pradesh, India	10	4.12	5.4	ppm	1.31	(Bhagavan and Raghu, 2006)	5–11	Children
Blood serum/plasma F	Ayyagarlapalli, Setturu Mandal, Anantapur District, Andhra Pradesh, India	10	0.36	0.46	ppm	1.28	(Bhagavan and Raghu, 2006)	5–11	Children
Dental fluorosis prevalence (< 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with < 1.5 mg/L F water	663	36.76	38.01	%	1.03	(Kotecha et al., 2012)	5–11	Children
Blood serum/plasma F	Kanukuru, Setturu Mandal, Anantapur District, Andhra Pradesh, India	10	0.64	0.64	ppm	1.00	(Bhagavan and Raghu, 2006)	5–11	Children
Dental fluorosis prevalence (> 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with > 1.5 mg/L F water	533	63.94	56.67	%	0.89	(Kotecha et al., 2012)	5–11	Children
Dental fluorosis prevalence (DMFT scores)	Thailand	271	0.2	0.1	DMFT score	0.50	(Leatherwood et al., 1965)	5–9	Children
Dental fluorosis prevalence	Libyan Population	6244	62.28	64.27	%	1.03	(Sunil-Tejaswi et al., 2013)	6–60	All
Dental fluorosis prevalence	Rural Area, Tianjin, China	709	46.26	53.74	%	1.16	(Wang et al., 2021)	6–13	Children
Dental fluorosis prevalence	Ledhupur & Rustampur, Varanasi	256	37.19	37.1	%	1.00	(Ray et al., 1983)	6–10	Children
Dental fluorosis prevalence	Israel-administered Gaza Strip	152	52.6	47.4	%	0.90	(Mann et al., 1990)	6–8	Children
Dental fluorosis prevalence	Han, China	182	9.33	10.28	%	1.10	(Cao et al., 1996)	8–15	Adolescents
Dental fluorosis prevalence	Tibetan, China	375	52.47	50.23	%	0.96	(Cao et al., 1996)	8–15	Adolescents
Dental fluorosis prevalence	Alappuzha district, Kerala, India	1124	39.2	31.3	%	0.80	(Gopalakrishnan et al., 1999)	10–17	Adolescents
Dental fluorosis prevalence	Thailand	299	0.8	0.4	DMFT scores	0.50	(Leatherwood et al., 1965)	10–14	Adolescents
Dental fluorosis prevalence	Ledhupur & Rustampur, Varanasi	158	53.94	58.86	%	1.09	(Ray et al., 1983)	11–15	Adolescents
Dental fluorosis prevalence	Fluorotic rural area, Turkey	293	4.75	8.13	%DMFT scores	1.71	(Keçeci et al., 2014)	12–80	All
Dental fluorosis prevalence (< 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with < 1.5 mg/L F water	744	40.2	48.87	%	1.22	(Kotecha et al., 2012)	12–24	Adolescents
Dental fluorosis prevalence (> 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with > 1.5 mg/L F water	599	71.83	83.74	%	1.17	(Kotecha et al., 2012)	12–24	Adolescents
Blood serum/plasma F	Kanukuru, Setturu Mandal, Anantapur District, Andhra Pradesh, India	8	0.35	0.39	ppm	1.11	(Bhagavan and Raghu, 2006)	12–18	Adolescents
Blood serum/plasma F	Ayyagarlapalli, Setturu Mandal, Anantapur District, Andhra Pradesh, India	10	0.17	0.18	ppm	1.06	(Bhagavan and Raghu, 2006)	12–18	Adolescents
Urine F	Kanukuru, Setturu Mandal, Anantapur District, Andhra Pradesh, India	8	6.87	7.18	ppm	1.05	(Bhagavan and Raghu, 2006)	12–18	Adolescents
Urine F	Ayyagarlapalli, Setturu Mandal, Anantapur District, Andhra Pradesh, India	10	3.58	2.67	ppm	0.75	(Bhagavan and Raghu, 2006)	12–18	Adolescents
Dental fluorosis prevalence	Schools in Southern India	1025	63.6	65.2	%	1.03	(Verma et al., 2017)	12–17	Adolescents
Dental fluorosis prevalence	Nalgonda district, Andhra Pradesh, India	775	77	78	%	1.01	(Sukhabogi et al., 2013)	12	Adolescents
Dental fluorosis prevalence	Nalgonda district, Andhra Pradesh, India	778	76.9	78.8	%	1.02	(Sukhabogi et al., 2013)	15	Adolescents
Dental fluorosis prevalence	Ledhupur & Rustampur, Varanasi	95	27.41	54.73	%	2.00	(Ray et al., 1983)	16–20	Adults
Dental fluorosis prevalence	Nawa tehsil, Nagaur district, Rajasthan (India)	28	81.82	95.93	%	1.17	(Gautam et al., 2011)	17–28	Adults
Urine F	Ayyagarlapalli, Setturu Mandal, Anantapur District, Andhra Pradesh, India	9	2.13	2.55	ppm	1.20	(Bhagavan and Raghu, 2006)	19–35	Adults
Blood serum/plasma F	Ayyagarlapalli, Setturu Mandal, Anantapur District, Andhra Pradesh, India	9	0.22	0.24	ppm	1.09	(Bhagavan and Raghu, 2006)	19–35	Adults
Dental fluorosis prevalence (DMFT scores)	Thailand	116	1.2	0.8	DMFT scores	0.67	(Leatherwood et al., 1965)	20–24	Adults
Dental fluorosis prevalence	Ledhupur & Rustampur, Varanasi	91	22.41	42.83	%	1.91	(Ray et al., 1983)	21–25	Adults
Dental fluorosis prevalence (DMFT scores)	Thailand	261	0.9	0.6	DMFT scores	0.67	(Leatherwood et al., 1965)	24–34	Adults
Dental fluorosis prevalence (> 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with > 1.5 mg/L F water	302	60.27	67.3	%	1.12	(Kotecha et al., 2012)	25–44	Adults
Dental fluorosis prevalence (< 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with < 1.5 mg/L F water	442	40.62	46.77	%	1.15	(Kotecha et al., 2012)	25–44	Adults
Dental fluorosis prevalence (> 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with > 1.5 mg/L F water	480	64.45	72.32	%	1.12	(Kotecha et al., 2012)	25–34	Adults
Dental fluorosis prevalence (< 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with < 1.5 mg/L F water	516	42.33	45.37	%	1.07	(Kotecha et al., 2012)	25–34	Adults
Dental fluorosis prevalence	Ledhupur & Rustampur, Varanasi	80	16.66	31.25	%	1.88	(Ray et al., 1983)	26–30	Adults
Dental fluorosis prevalence	Nawa tehsil, Nagaur district, Rajasthan (India)	49	95	96.43	%	1.02	(Gautam et al., 2011)	29–40	Adults
Dental fluorosis prevalence	Ledhupur & Rustampur, Varanasi	299	5.12	16.72	%	3.27	(Ray et al., 1983)	31	Adults
Dental fluorosis prevalence	Thailand	202	1.5	1.5	DMFT scores	1.00	(Leatherwood et al., 1965)	35–44	Adults
Blood serum/plasma F	Xinhuai, Sihong County, Jiangsu Province, China	36	0.073	0.077	mg/L	1.05	(Xiang et al., 2005)	36–78	Adults
Skeletal fluorosis prevalence	Wamiao, Sihong County, Jiangsu Province, China	132	36.21	27.03	%	0.75	(Xiang et al., 2005)	36–78	Adults
Dental fluorosis prevalence	Nawa tehsil, Nagaur district, Rajasthan (India)	20	94.44	100		1.06	(Gautam et al., 2011)	40 <	Adults
Dental fluorosis prevalence	Thailand	297	8.1	9.2	DMFT scores	1.14	(Leatherwood et al., 1965)	45<	Adults
Dental fluorosis prevalence (> 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with > 1.5 mg/L F water	430	56.22	69.01	%	1.23	(Kotecha et al., 2012)	45–64	Adults
Dental fluorosis prevalence (> 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with < 1.5 mg/L F water	156	27.17	37.5	%	1.38	(Kotecha et al., 2012)	65<	Adults
Dental fluorosis prevalence (> 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with > 1.5 mg/L F water	183	45.74	52.8	%	1.15	(Kotecha et al., 2012)	65<	Adults
Dental fluorosis prevalence	Thailand	125	1.1	0.8	DMFT scores	0.73	(Leatherwood et al., 1965)	,	Adolescents
Dental fluorosis prevalence (< 1.5 mg/L water F)	Villages in Vadodara district, Gujarat, India, with < 1.5 mg/L F water	487	44.15	45.49	%	1.03	(Kotecha et al., 2012)		Adults
Health risk	Vattamalaikarai River basin, South India	118	73	64	%	0.88	(Arya et al., 2021)		Adults

Table 3

It can be observed that about 69% of the literature records indicated that, under the similar conditions, the male children under the age of 11 years were about 1.21 times more likely to be more strongly and more widely suffer the adverse impacts of F than their female counterparts. Similarly, 67% of literature sources indicated likelihood of higher prevalence and/or severity of F impacts in the adolescent boys than in the girls and among the adult populations, at least 79% literature records sampled from around the world showed that, under similar conditions of exposure, men are 1.25 times more likely suffer more adverse impact and prevalence of F impacts than women. This is because the degree of F exposure through consumption of F-contaminated foodstuffs is linked to the quantities of food consumption, which in turn is controlled by the body weight (BW) and the physical activity levels (PAL). High quantities of food consumption and heightened risk of F overexposure among the high fluoride area correlate to increased BW and high PAL of the individuals. Thus, the high risk of F overexposure and manifestation of greater adverse impacts among the male populations from around the world compared the female populations is therefore linked to greater average body weight (BW), and higher average physical activity levels (PAL) in the males. It has been demonstrated that young adults of both sexes with greater BW were at greatest risk of F overexposure of up to 30 mg/kg/day EADD. Nonetheless the risk of F overexposure appear to correlated strongly with young ages, high BW and high PAL showing that younger children with highest BW are at the greatest susceptibility levels.

According to the findings of the current work, the following conclusions could be drawn:

The study revealed high levels F exceeding WHO RDA level of 4 mg/kg in potatoes (Solanum tuberosum L.), beans (Phaseolus vulgaris L.) and peas sampled from Nakuru County.
The F levels in both the beans and potatoes varied from region to region showing that they were controlled by conditions that control F availability in the environment but the F levels of peas (Possum sativa) samples were not controlled by regional variations in the environmental F content showing. So, F levels in the pea samples were lower and somewhat uniform across the regions.
The risk of F overexposure through the contaminated foodstuffs was greater in younger children, in male populations than in the female populations, and in individuals with high BW and PAL.
Elevated levels of fluorides in peas, beans and potatoes have adverse public health implications of the risk of fluoride overexpose through food to the resident communities. Therefore, it’s recommended that public awareness be done to farmers and consumers on the health implications and to develop and disseminate fluoride impact prevention and amelioration strategies.

Figure 1 shows the map of the current study area in relation to the map of Kenya and the map Africa. The area, which comprises parts of Nakuru County of Kenya is about 7,500 km² across latitudes 0º13′ S and 1º10′ S and longitudes 35º28′ E and 35º36′ E. It is divide into 9 administrative sub-counties including Gilgil, Naivasha, Nakuru East, Nakuru West, Nakuru North, Njoro, Molo, and Rongai sub-counties, which were the main focus for this study.

The landscape is composed of a volcanic geologic terrain (The County Executive Committee Member -Departement of Finance and Economic Planning, 2018) characterized by bimodal annual rainfall comprising short rains in the months of October–December and long rains during the period of March–June (Wakachala et al., 2015). The amount of annual rainfall decreases from above 1500 mm in Molo and Njoro highlands linked to the Mau escarpment to below 500 mm in Rongai and Naivasha sub-counties at the rift valley floor. The temperatures (12–30 ^oC) are lowest in the months of June–July and hottest in December–March, respectively. This conditions makes this area one of the agricultural hubs in the country.

The estimated human population is of the area is 2.5 million people with about 36% consisting urban population, which is the primary market for the agricultural products from the county. Children under 13 years, who are at highest risk of adverse F effects, make up to 38.2% of the overall total population of the area (The County Executive Committee Member -Departement of Finance and Economic Planning, 2018).

A total of 165 samples consisting 75 Irish potatoes samples, 54 beans samples and 43 peas samples were collected randomly from sample points selected to cover the entire study area according to the criterion depicted in Table 4. The samples were collected from the farms where they were produced directly into dry clean polythene zip lock bags and transported to the laboratory for processing.

Table 4

Distribution of sample collection points by the target sub-counties
Sub-counties	Foodstuffs
Sub-counties	Potatoes (n)	Beans (n)	Peas (n)	Total (N)
Molo	10	5	8	23
Njoro	10	7	9	26
Rongai	9	6	6	21
Nakuru N.	11	5	6	22
Nakuru W.	10	4	4	18
Nakuru E.	10	4	3	17
Gilgil	7	8	3	18
Naivasha	8	8	4	20
OVERALL	75	47	43	165

At the laboratory, the samples were washed with excess doubly-deionized water (DDW) to remove soils and other impurities. The potatoes were sliced into cubes of about 1.5 cm dimensions and dried on a ULM-400 constant-temperature oven (Memmert, Germany) at 110 ^oC for 24 h. the peas and beans samples were dried in the same way without prior treatment. The dry samples were pulverized to fine powder using an SBG-301 Blender/Grinder (ASL Ltd, Kenya) and preserved in air-tight sample bottles for subsequent tests.

A portion of 1.25 g of each of the powdered samples was digested in 10 mL of 6 M NaOH until the samples dissolved in the base. The solution was allowed to cool to room temperature and neutralized by careful addition of 3 M H₂SO₄ to a pH of 7.1 ± 0.1. It was transferred to a 50-mL volumetric flask and made up to the 50-mL mark with DDW. Exactly 10.0 mL of each of the solutions was mixed with an equal volume of TISAB II solution and the F concentration measured using a Thermo Fisher Scientific K.K. 9609BNWP pH/Ion Meter (STAR) with a Thermo Fisher Fluoride ion selective electrode (Thermo Fischer Scientific, UK). All the experiments were conducted in triplicate.

The results were analyzed using descriptive statistics by determining the mean and standard deviations. Analysis of variance (ANOVA) was used to determine whether there were any significant differences at p ≤ 0.05 between the concentrations of fluoride peas, beans and potatoes from different regions in Nakuru County. Paired t-test was used to determine significant difference at p ≤ 0.05 confidence level in fluoride level between peas, beans and potatoes. It was also used to compare means from different regions. The results were used to calculate the exposure daily F intake, DFI, (mg/kg/day) for individual foodstuffs and to compute the estimated average daily F dosage, EADD (mg/kg/day) for the households.

The main household foodstuffs and the percentage daily energy contribution (FEC) of each of the studied foodstuff were estimated from the Ministry of Health dietary diversification data (Action Against Hunger (ACF-USA) and Ministry of Health (KEN), 2008) and from the food production data of the study area. The exposure daily F intake, DFI, (mg/kg/day) for the foodstuffs was calculated by considering the weight-for-age data (National Center for Health Statistics, 2000) and the corresponding food consumption patterns (FAO/WHO/UNU Expert Consultation, 2001) according to Eq. (2) as follows:

$$DFI=\frac{\left[F\right]\times DEI\times FEC\times AF}{E}$$

where, [F] is the F content of the foodstuff (mg/kg), DEI is the daily energy requirements (kcal/kg/day) for different categories of individuals according to their ages, body weight and physical activity levels (FAO/WHO/UNU Expert Consultation, 2001), FEC is the percentage daily energy contribution, AF is the F absorption factor estimated as 60% for most foodstuffs (Prystupa, 2011), and E is the dietary calorific value (kcal/kg) of the foodstuffs. The estimated average daily F dosage, EADD (Gevera et al., 2022)was then computed from individual DFI according to Eq. (3) as:

$$EADD=\sum _{i}^{n}{DFI}_{i}$$

where i is the i^th foodstuff and DFI_i is the DFI corresponding to the i^th foodstuff.

[F] Fluoride concentration (mg/kg or mg/L)

AF Absorption factor for foodstuffs

ANOVA Analysis of variance

BMR Basal metabolic rate

DDW Doubly-deionized water

DEI Daily energy intake through food (kcal/kg/day)

E Dietary calorific value (kcal/kg) of food

EADD Estimated average daily F dosage

EARS Eastern African Rift Valley System

F Fluoride

FEC percentage daily energy contribution of food

RDA Recommended dietary allowance

TEE Total energy expenditure in 24 hours

TISAB Total ionic strength adjustment buffer

Ethics approval and Consent to participate

Not applicable

Consent for publication

Not applicable

Availability of data and materials

Competing interests

Authors declare that there are no competing interests.

Funding

This work was part of the FLOWERED Research project which was supported the EU’s Horizon 2020 research and innovation programme under grant agreement No 690378.

Authors' contributions

D.N. contacted the field and laboratory data collection and analysis and wrote the main manuscript text, E.W.W. designed the initial field and laboratory experiments, and reviewed the field and laboratory results as well as the manuscript, and J.L.K. participated in the initial design of the experiments and in the field data collection.

Acknowledgements

Authors acknowledge the contribution and support of the late Prof. Giorgio Ghiglieri of the University of Cagliari, Sardinia, Italy, who was the coordinator of the EU’s H2020 FLOWERED Project.

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Fluoride levels of Irish Potatoes (Solanum tuberosum L.), Beans (Phaseolus vulgaris L.) and Green Peas (Possum sativa) from Nakuru County, Kenya, and the risk of fluoride overexposure

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