Spatial variations in physico-chemical parameters of Makurdi groundwater
The characteristics of raw groundwater for all 21 locations are presented in Tables S5 and S6 in supplementary material. The descriptive statistics is presented in Table 1. From Table 1, it was observed that majority of the samples were slightly acidic as the pH was noticed to range from 6.2–6.8 across the 21 sampling points as can be seen in Fig. 2, with a mean value of 6.52. Generally, almost 52.4% of the samples had pH levels that fell below the permissible limits for drinking water as stipulated by WHO (WHO, 2017) while the remaining 47.6% complied with the WHO standard. The slightly acidic nature of the water was which was attributed to the extensive use of fertilizers and pesticides by famers in the water shed of the study locations may impact body metabolism in humans (Chabukdhara et al., 2017).
Table 1
Descriptive Statistics for Physico-Chemical Quality of Water Samples
S/No | Parameter | Minimum | Maximum | Mean | SD | WHO Limit | % Violation |
1 | pH | 6.20 | 6.83 | 6.52 | 0.19 | 6.50–8.50 | 52.38 |
2 | TDS | 89.80 | 1471.50 | 708.02 | 405.09 | 1000 | 28.57 |
3 | EC | 158.40 | 2487.40 | 1233.46 | 701.60 | 1500 | 38.10 |
4 | Chloride | 38.10 | 532.60 | 165.10 | 110.03 | 200 | 28.57 |
5 | Carbonate | 0.00 | 196.00 | 18.70 | 25.52 | - | - |
6 | Bicarbonate | 95.00 | 601.00 | 331.56 | 131.85 | 500 | 9.52 |
7 | Sulphate | 39.60 | 492.10 | 283.88 | 122.07 | 250 | 71.43 |
8 | Nitrate | 0.58 | 16.39 | 5.88 | 3.37 | 50 | 0.00 |
9 | Fluoride | 0.32 | 2.06 | 1.26 | 0.41 | 1.5 | 33.33 |
10 | Sodium | 34.30 | 403.1 | 211.94 | 98.63 | 200 | 57.14 |
11 | Potassium | 1.47 | 11.49 | 5.00 | 2.32 | 50 | 0.00 |
12 | Calcium | 45.80 | 221.00 | 102.78 | 44.75 | 75 | 47.62 |
13 | Magnesium | 28.60 | 237.70 | 90.02 | 48.52 | 150 | 14.29 |
Note: N = 63, All units are in mg/L with exception of EC (µs/cm) and pH (no unit). SD is Standard Deviation. |
Total Dissolved Solids (TDS) and Electrical Conductivity (EC) ranged from 89.80–1471.50 mg/L and 158.40–2487.40 µs/cm (Fig. 2) with mean values of 708.02 mg/L and 1233.46 µs/cm respectively. It was found that 28.57 and 38.10% of the samples violated the WHO limits of 1000 mg/L and 1500 µs/cm for TDS and EC respectively. Although high concentrations of TDS and EC in drinking water may not be of any severe health implications, such elevated levels can affect the acceptability of such water for drinking purposes as a result of the high scaling effects of such water in household utilities and pipes (WHO 2017).
Additionally, high TDS levels in water can cause gastrointestinal disorders in persons with kidney or renal problems (Chebet et al., 2020). The high levels of TDS and EC in the sampled water can be attributed to the extensive use of fertilizers and pesticides, deep infiltration of rainwater, dissolved sediments and ion exchange (Emenike et al., 2018a; Egbueri and Mgbenu, 2020). It can also be specifically linked with the dissolution of bicarbonate, sulphate, sodium, calcium and magnesium in the water from natural and anthropogenic processes (Chebet et al., 2020).
Similarly, chloride was found to range from 38.10–532.20 mg/L with average of 165.10 mg/L. Furthermore, about 28.57% of chloride concentration in the water samples exceeded the WHO limit of 200 mg/L. It should be noted that elevated chloride concentrations in water can induce a salty taste in the water, depending on the associated cation; the salty taste of the chloride anion could be triggered if the concentration falls between 200–300 mg/L for sodium, calcium and potassium chloride (WHO 2017). The elevated concentrations of chloride in water could be connected with the release of industrial, commercial, and agricultural effluents and runoff (containing de-icing salts) into the environment as well as with the natural solubility of chloride bearing minerals (salts) in water. Similar observations were also reported in the study of Emenike et al., (2018)b and that of Asuma et al., (2020).
Carbonate and bicarbonate varied from 0.00–196.00 mg/L and 95.00–601.60 mg/L with average values of 18.70mg/L and 331.56 mg/L respectively. Although there are no strict regulations for carbonate content of drinking water, it was found that about 9.52 % of the samples exceeded the WHO stipulated limit of 500 mg/L for bicarbonate in water.
Figure 2 Spatial Variation of Physico-chemical Parameters (a): pH, (b): TDS and EC, (c): Anions and (d): Cations
Activities relating to geological mineralization, irrigation, runoff, and seepage which mix up with groundwater during recharge may be responsible for the heightened levels of bicarbonate in the samples. Similar findings have been reported in previous studies (Akoteyon, 2013; Rasool et al., 2016).
Sulphate concentrations in the samples fell between 39.60–492.10 mg/L with an average of 283.88 mg/L which was higher than the WHO acceptable limit (250 mg/L) for drinking water. In overview, about 71.4% violations were noticed from the 21 samples with respect to the WHO stipulated limits (250 mg/L) for sulphate ions in drinking water. Excessive levels of sulphate in water can lead to laxative effects in humans, while moderate levels could induce salty taste in drinking water depending on the associated anions. The foregoing may be responsible for the salty taste of water from deep aquifers within the study area. Furthermore excessively high values of sulphate in drinking water may induce respiratory ailments in humans (Emenike et al., 2018b). The elevated sulphate concentration is also associated with the excessive use of agro-chemical and dissolution of basement rocks.
Nitrate concentrations in the water sampled was observed to range from 0.58–16.39 mg/L with a mean concentration of 5.88 mg/L. Nitrate is a strictly regulated compound in drinking water due to its health implications. It causes the blue baby syndrome (methamoglobinemia) in infants and children when present in drinking water at levels higher than 50 mg/L (Sellami et al., 2019). Despite the excessive use of agro-chemicals and fertilizers by farmers in the study area it was observed in this study that none of the samples exceeded the threshold value. Thus, the moderate/low nitrate levels in the groundwater may be linked to the removal of dissolved nitrate by filtration and adsorption activities of the soil profile during seepage and deep percolation (Emenike et al., 2018b).
Fluoride concentration varied from 0.23–2.03 mg/L with an average concentration of 1.26 mg/L. Most of the water samples complied with the minimum (0.5 mg/L) and maximum (1.5 mg/L) threshold values for fluoride in drinking water (WHO 2017). Succinctly, about one-third (33.33 %) of samples were found to exceed the maximum permissible limits, while only one of the samples had fluoride concentrations lower than the minimum acceptable limit (0.5 mg/L). High fluoride levels in water samples can be linked to the fluoride bearing rocks found in the geological formations, and myriad of anthropogenic activities in the study area. Fluoride concentration in water above 1.5 mg/L is reported to be responsible for dental fluorosis in humans (especially children), while excessive concentrations are reported to cause skeletal fluorosis in children and adults (WHO, 2004). It is usually referred to as the double edge sword as low intakes of fluoride in humans can also cause dental caries (Yousefi et al., 2018). Based on the reports from recent studies, it is presumed that excessive intake of fluoride can be carcinogenic in humans (WHO, 2004). Thus, fluoride removal from drinking water supplies is highly essential in the provision of potable drinking water. Sodium concentrations in the samples ranged from 34.30–403.1 mg/L (with mean value of 211.94 ± 98.63 mg/L). There was an evident high variability in the sodium content of the water with about 57. 14% of the samples surpassing the WHO limits of 200 mg/L. The high sodium level in the water was attributed to aquifer chemistry and the mixing of wastewater effluent (generated through human activities) with the groundwater in the study locations (Tirkey et al., 2017).
Potassium, calcium and magnesium concentrations in the water samples were found to range from 1.47–11.49 mg/L, 45.80–221.00 mg/L and 28.60–237.70 mg/L respectively. Potassium concentrations in the samples were found to fully comply (100%) with the WHO limits. Since Mg+ and Ca+ are major pointers to water hardness. In the current study, Ca+ values were within the WHO permissible limit (200 mg/L) for all 21 samples, while about 47.6% of the samples surpassed the WHO most desirable limits of 75 mg/L for Ca+ drinking water, while 14.3% of the samples had Mg+ concentrations above the WHO permissible limit (150 mg/L) and over 90% of the samples had values higher than the most desirable limits of 50 mg/L. It was inferred therefore, those groundwater in the study locations were generally hard and tasty. High levels of these cations in the water samples were traced to mineral dissolution in the basement and ion exchange activities (Magesh et al., 2017).
Water quality assessment
The quality of water samples was assessed through the Water Quality Index (WQI) and water type (hydrogeochemical facies) using piper diagram consisting of composite-double triangles and a diamond shape. Each of the triangles represents either the cation or anion composition of the water samples, while the diamond shape is a composite plot for both the cations and anions.
For the WQI, weights and relative weights were assigned to the water quality parameters as depicted in the supplementary material (Table S1). The data in Table S3 is the computations of the WQI and remarks for all the studied locations and the results are presented in Fig. 3. It was observed that about 95% of the samples fell into class II (good water), see Table S2, while one sample (P14) had quality that fell into class I of the WQI classification, which suggest that the water is clean and safe. Furthermore, it was noticed that the major contributors to the overall WQI in the study locations were in the order of sulphate > EC > Chloride > Calcium > Fluoride > TDS > pH > Sodium. Magnesium and bicarbonate were observed to have moderate contributions to the water quality, while nitrate and potassium had the least contributions. The findings of this study are in tandem with that of Adimalla et al., (2018).
Figure 3 Water Quality Index (WQI) for the Studied Locations
Although most of the samples were found to be good for drinking, the threshold values obtained for most locations (P1, P2, P4, P6, P8, P13) were observed to be very close to been ranked as class III water type (“poor water”). Thus, it is suggested that simple technologies such as filtration and adsorption could be deployed as treatment techniques for water in the affected locations to eliminate the major contributing pollutants such as sulphate, chloride, fluoride, calcium sodium, among others). In light of this, the affected water may be safer for human consumption.
Furthermore, the piper diagram (Figure S1) shows that the Na+, Ca2+ and Mg2+ are the major cations with Ca2+ and Na+ dominating, while K+ was found to have a moderate contribution to the general description as indicated the in WQI computations. In the anions sections, SO42− and Cl− were observed to dominate the facies, while contributions from HCO3was found to be moderate. The dominance of Ca2+ and Na+ in the water composition is an indicator of the possibility of ion exchange through rock weathering in the aquifer. The dominance of SO42− and Cl− on the other hand reveal ion contributions as a result of silica weathering (Achary et al., 2016).
Additionally, Aghazadeh, et al., (2016) posited that when the ratio of calcium/magnesium ions in water is between 0.6 and a value higher than 2, it is a pointer to the possible dissolution of dolomite and silicate rock constituents in the aquifer. In the current study, more than 80% of the samples had calcium/magnesium ratios that fell between 0.6 and 3.4 confirming the interaction of silicate and dolomite materials in the aquifer. The overall characterization of the hydrogeochemical facies revealed the dominance of Na-SO4 (42.8 %), Na- Cl (14.30 %), Mg-HCO3 (14.30 %), Mg-SO4 (9.5 %), Ca-HCO3 (4.8 %), Mg-Cl (4.8 %), Ca-Cl (4.5 %) and mixed water types (5 %) in the studied locations (Fig. 4).The foregoing is indicative of the predominant salty taste of bore-hole water in the study area. Additional information on the hydro-chemical characterization of the water samples in form of the Durov and Schoeller diagrams can also be found in supplementary material (Figures S2 and S3).
Multivariate statistical analysis and pollution source apportionment
In the current study, Pearson’s correlation, principal component, and hierarchical cluster analyses were adopted to further corroborate the relationship and likely sources of contaminants in groundwater of the study area. These techniques have been utilized in several studies on the water quality assessment (Emenike et al., 2018b; Ali and Ali, 2018; Ravikumar and Somashekar, 2017; Rassol et al., 2016; Salifu et al., 2012). For correlation analysis (CA) when r values less than 0.3 the association was taken as weak correlation, when it varied between 0.3–0.7, the relationship is regarded as being moderate and when r was greater than 0.7 the relationship is considered as strong (Emenike et al., 2018b: Salifu et al., 2012).
Correlation analysis
The results of correlation analysis (CA) are presented in Table 2. With regards to the relationship between fluoride and other ions in the water samples, it was found that fluoride was moderately and positively correlated with TDS, EC, Cl− and NO3−. This suggests that these parameters have similar sources with fluoride, which occurs from rock weathering and geological interactions. For instance, Bempah, (2014) reported similar relationship between fluoride, TDS and EC in his study on arsenic contamination of groundwater in Ghana.
Table 2
Correlation Analysis for Water Quality Parameters
| pH | TDS | EC | Cl− | CO32− | HCO3− | SO42− | NO3− | F− | Na+ | K+ | Ca2+ | Mg2+ |
pH | 1 | | | | | | | | | | | | |
TDS | 0.229 | 1 | | | | | | | | | | | |
EC | 0.235 | 0.980** | 1 | | | | | | | | | | |
Cl− | -0.133 | 0.162 | 0.159 | 1 | | | | | | | | | |
CO32− | -0.130 | 0.326** | 0.324** | 0.378** | 1 | | | | | | | | |
HCO3− | -0.196 | 0.290* | 0.338** | 0.012 | 0.205 | 1 | | | | | | | |
SO42− | 0.197 | 0.113 | 0.158 | 0.094 | -0.023 | 0.142 | 1 | | | | | | |
NO3− | 0.131 | -0.134 | -0.076 | 0.147 | -0.241 | -0.322** | 0.117 | 1 | | | | | |
F− | 0.004 | 0.472** | 0.484** | 0.457** | 0.142 | -0.085 | 0.087 | 0.279* | 1 | | | | |
Na+ | 0.105 | 0.184 | 0.223 | -0.017 | -0.108 | 0.176 | 0.869** | 0.176 | 0.068 | 1 | | | |
K+ | 0.011 | 0.341** | 0.361** | 0.067 | -0.004 | 0.177 | 0.756** | 0.122 | 0.239 | 0.805** | 1 | | |
Ca2+ | 0.148 | -0.074 | -0.071 | -0.099 | -0.218 | -0.179 | 0.499** | 0.156 | -0.117 | 0.512** | 0.540** | 1 | |
Mg2+ | 0.039 | 0.200 | 0.252* | 0.352** | 0.129 | 0.295* | 0.374** | -0.040 | 0.018 | 0.259* | 0.285* | 0.070 | 1 |
** Significant at P = 0.01 (2-tailed). * Significant at P = 0.05 (2-tailed) |
Similarly, F− was observed to be positively and weakly correlated with SO42−, CO3− pH and all the cations except Ca2+. This indicates that the sources of these contaminants in the water are probably from geological interactions. It was however observed that F− had a negative and weak correlation with HCO3− and Ca2+, signifying that the trio are likely from different sources (HCO3−, and Ca2+ from anthropogenic and F− from natural sources). Similar observations were reported by Emenike et al., (2018b) in addition to that of Adimilla and Venkatayogi, (2017).
Also, strong positive correlations were observed for EC - TDS, Na+ - SO42−, K+ - SO42− and Na+ - K+, while moderate positive correlations were noticed for CO3− - TDS, K+ - TDS, CO3− - EC, HCO3− - EC, K+ - EC, CO3− - Cl−, Mg2+ - Cl−, NO3− - HCO3−, Ca2+ - SO42−, Mg2+ - SO42−, Ca2+ - Na+ and Ca2+ - K+ (Table 2), thus indicating source similarities of the parameters. No negatively strong or moderate correlations were observed, however, most of the parameter (pH – Cl−, pH – CO3−, pH - HCO3−, NO3− - Mg2+ among others) exhibited a weak negative relationship suggesting that these input into the water samples from different routes (Table 2).
Comparatively, fluoride concentrations in the current study were observed to be higher than the mean values reported from other studies (Emenike et al., 2018b: Salifu et al., 2012: Schen and Schafer, 2015: Ravikumar and Somashekar, 2017). It is important to note that fluoride content in groundwater tends to increase as the TDS and EC values increases (Rafique et al., 2009). This trend was also observed in the current study. Although fluoride was found to be weakly correlated with pH in this study, the findings support the assertion that fluoride solubility is pH dependent (fluoride solubility in water is favoured when the pH ranges from 6–9).
The pH of the samples were found to range between 6.2–6.83 in the current study with an average of 6.52 which is likely responsible for the high fluoride values recorded (Saxena and Ahmed, 2001). Furthermore, the presence of fluoride in the water samples could be linked to the dissolutions from quartzite and shale (which are the major geological sediments of the study locations) into the underlying aquifer (Eneji et al., 2011).
Principal component analysis (PCA)
In this study, PCA revealed four principal components (PC) with a cumulative variance of 71.53% (rotation sum of squared loadings) as illustrated in Table 3 and the scree plot (Figure S4). It was observed from Figure S4 that about 13 factors were extracted in total but only four of them were seen to have Eigen values greater than 1 and they were considered as the principal components (PC). PC1 had strong and positive factor loadings for sulphate, sodium, calcium, potassium, and magnesium with an explicated variance of 24.7% (Table 3). This also indicates the contribution of rock weathering and ion exchange activities in the hydro-geo-chemistry of the studied aquifers, which also implies that the cations originate from similar geogenic sources (dolomite and gypsum).
Table 3
Varimax Rotated Principal Component Analysis for the Water Samples
Parameter | Rotated Component Matrix |
PC1 | PC2 | PC3 | PC4 |
pH | 0.109 | 0.428 | -0.509 | 0.251 |
Total Dissolved Solids | 0.097 | 0.945 | 0.085 | -0.176 |
Electrical Conductivity | 0.140 | 0.943 | 0.107 | -0.174 |
Chloride | 0.005 | 0.135 | 0.847 | 0.242 |
Carbonate | -0.154 | 0.293 | 0.533 | -0.309 |
Bicarbonate | 0.157 | 0.179 | 0.206 | -0.744 |
Sulphate | 0.913* | 0.067 | 0.068 | -0.001 |
Nitrate | 0.182 | -0.025 | 0.076 | 0.773 |
Fluoride | 0.010 | 0.585 | 0.428 | 0.466 |
Sodium | 0.921 | 0.108 | -0.054 | -0.021 |
Potassium | 0.869 | 0.244 | 0.095 | -0.006 |
Calcium | 0.696 | -0.148 | -0.236 | 0.197 |
Magnesium | 0.407 | 0.092 | 0.451 | -0.253 |
% of Variance | 24.69 | 19.62 | 13.74 | 13.47 |
Cummulative % | 24.69 | 44.32 | 58.06 | 71.53 |
*Bolded indices show heightened positive loadings |
PC2 was observed to have strong positive loadings for pH, TDS, EC, and fluoride with a total explainable variance of 19.6%. This indicate that the occurrence of these contaminants in water owing to similar natural and/or anthropogenic activities, probably from the solubilization of halite and high evapotranspiration rates. It also implies the role of pH in the dissolution and mobility of anions (especially fluoride) and cations in water, as the solubility of fluoride in water is favoured in the pH range of 6–9 as earlier stated (Saxena and Ahmed, 2001), since both TDS and EC values are major indicators of ion concentrations in water.
PC2 also confirms the positive correlation of TDS and EC with fluoride in water and further substantiate the assertion that fluoride concentrations in water tends to increase with upsurge in TDS and EC (Rafique et al., 2009). The component plot in rotated space illustrates the factor loadings for the principal components as shown in Figure S5. PC3 and PC4 were found to have negligible contributions to the water chemistry as they had strong positive factor loadings for chloride, carbonate, nitrate, fluoride, and magnesium with explainable variance of 13.74 and 13.47 % respectively.
The dominance of carbonate in PC3 indicates its contribution in the dissolution and distribution of fluoride and nitrate in groundwater. It was also observed that fluoride and magnesium exhibited a quasi-independent behaviour in PC1, PC2, PC3 and PC 4, which implies that they are introduced into the water from majorly from natural (geogenic) and on a minor note through anthropogenic sources (Hosseini et al., 2019).
Hierarchical cluster analysis (HCA)
The HCA were performed in this study using the Ward’s method by selecting the squared Euclidean distance as the interval and the hydro-chemical results of all samples were statistically analyzed. The data used was normalized before the analysis. The HCA was performed in the Variable and Case-modes, such that the Variable-mode provided the relationships between water quality parameters, while the Case-mode revealed the relationships between the sample locations (Sharaf and Subyani, 2011: Bempah, 2014).
The HCA was performed for the set of water samples from 21 locations with three replications each (giving rise to 63 cases) and 13 water quality parameters (variables). The result of HCA in form of a dendrogram for the Variable-mode is shown in Figure S6, while that for the Case-mode is depicted in Figure S7. It was observed that the variables were grouped into two clusters. The parameters were observed to be grouped on account of their concentrations in the water samples. The pH, K+, NO3−, F−, CO3−, Ca2+, Mg2+, Cl−, SO42−, Na+ and HCO3− were grouped in the same cluster (cluster 1), while TDS and EC formed the second cluster. Despite TDS and EC having relatively higher linkage as compared to the other variable, they were found to be closely related owing to their strong positive correlations with most of the studied parameters (Bempah, 2014).
Furthermore, Na+, SO42, HCO3− were observed to be closely connected which indicate the impact of rock weathering and ion exchange activities on the water chemistry as earlier shown in the correlation and PCA together with the dominance of Na-SO4 and Na-HCO3 water types in the hydrogeochemical facies of the studied locations. The pH, Cl−, CO3−, NO3−, F−, K+, Ca2+, Mg2+ were also found to be closely clustered suggesting source similarities and the involvement of pH in the mobility and speciation of the ions in groundwater.
On the other hand, it was observed that the sample locations were grouped into four clusters on the basis of the similarities in the water chemistry of the locations. Locations P1, P2, P3, P4, P5, P6, P8, P10, P12 and P18 were grouped into clusters 1 and 2, while locations P7, P9, P11, P13, P14, P15, P16, P17, P19, P20 and P21 were grouped into clusters 3 and 4. The implications of the groupings may be linked to the close proximity of the sample locations as earlier stated in the coordinate locations. In general, there was no significant distinctions in the water quality of the studied locations as the samples were observed to have similar characteristics in terms of its quality.
Human health risk analysis for fluoride contamination of groundwater
Despite the seemingly good quality of the groundwater for drinking purposes as demonstrated in the results of the WQI analysis, it is essential to evaluate the potential health risk of the exposed populations to fluoride contamination. This is apparent as some fractions of the samples were observed to contain fluoride concentrations that exceeded the allowable limits for drinking water in order to prevent fluorosis in humans.
The results of the estimated daily fluoride intake for each location is presented in Figure S8, while that for the hazard quotient per location for every human category is shown in Fig. 4. Figure S8 represents the exposure levels of the populations (infants, children, teenagers and adults) to fluoride risk, while Fig. 4 depicts the hazard quotient (an indicator of actual risk) for risk of fluorosis in the vulnerable population. Details of the computations for the risk assessment are available as supplementary material (Table S7).
From Figure S8, it was observed that the EDI Values were considerably high in most of the locations especially in infants and children. A moderate level of EDI was observed in most locations for teenagers, while adults in all locations except one (P13) were found to have EDI levels for fluoride that were lower than the RfD value of 0.06 mg/kg/d. Generally, EDI values ranged from 0.023–0.100, 0.025–0.110, 0.020–0.088 and 0.016–0.071 mg/kg/d for infants, children, teenagers and adults respectively. Among the studied cases locations, P14 and P13 had the lowest and highest EDI values respectively, which follow after the mean fluoride concentrations of these locations.
From the computations of the hazard quotient (HQ) (Fig. 4), it was noticed that for infants, about 66.7 % of the sample locations had HQ values in excess of the set limit (1). This implies that this population is vulnerable to high risk of fluoride related disorders due to ingestion of fluoride laden groundwater. Similarly, with respect to children, teenagers and adults, it was observed that about 71.4, 52.4 and 9.5% of the sample locations were at elevated risk of developing fluoride related diseases from the consumption of high-fluoride content water.
Figure 4 Hazard Quotient for Fluoride Risk in the studied Populations
It is evident that children had the highest potential risks for developing fluorosis even higher than that for infants, since the ratio of the daily water intake rates and body weight for the children is considerably higher than that for the infants. Moreover, this is expected as the children undergo more metabolic activities as a result of mobility and play which demands for more water consumption as compared to the infants. As for the teenagers and adults, the risk as earlier stated could be moderate and low respectively. This could be attributable to the ratio of the daily water intake rates and body weight, coupled with the associated metabolisms. As expected, teenagers are more prone to high metabolic rates and thus higher water intake rates irrespective of their moderate body weight.
Despite the moderate and low risk levels for teenagers and adults respectively when considering the entire study location, it is pertinent to note that locations P13 and P19 had very high risk levels for all age categories and therefore, this study recommend that groundwater from these locations should be subjected to affordable defluoridation systems prior to consumption. Several studies have reported analogous risk levels for fluoride in drinking water in many parts of the world (Emenike et al., 2018b; Radfard et al., 2018; Yousefi et al., 2018; Karunanidhi et al., 2019; Nakazawa et al., 2020).