Fluorine often occurs in combined form in minerals like fluoride. Fluoride is a naturally occurring chemical substance present in minor quantities in air, water, soil, plants, animals and humans ( Haruna et al., 2014 ). It is the most electronegative of all chemical elements and is therefore never encountered in nature in the elemental form; however it is highly reactive and represents about 0.06% to 0.09% of the earth crust ( WHO, 2004 ). The main source of fluorine in groundwater is basically from mafic minerals which are concentrated in rocks. Fluoride rich minerals which are present in rocks and soils, when in contact with water of high alkalinity are released into groundwater by hydrolysis. However, fluoride is present universally in all waters but higher concentrations are found in groundwater, minerals and rocks. The optimal value of fluoride in drinking water is considered to be around 0.5 - 1.5 mg/l ( WHO, 2004 ) and too low (<0.5 mg/l) or too much (>1.5 mg/l) which can affect bone and teeth structure. Higher concentration of fluoride also causes respiratory failure, drop in blood pressure and paralysis. Continuous intake of nonfatal dose of fluorides causes permanent inhibition of growth. Lar and Tejan (2008) highlighted the human health effect related to the consumption of fluoride in groundwater particularly in Nigeria. Dibal, et al. (2008) reported the high incidence of dental fluorosis to consumption of high fluoride in groundwater of Langtang area. Dibal and Schoeneich (2009) reported the occurrence of high fluoride in groundwater in several rural communities in some parts of northern Nigeria. The most common symptoms of fluoride effects are dental fluorosis, a condition involving interaction of fluoride with tooth enamel, which involves blackening or staining, weakening and possible eventual loss of teeth. With high exposure to fluoride, skeletal fluorosis can result. This manifests in the earliest stages of osteoclerosis which involves hardening and calcifying of bones and causing stiffness, pain, and irregular bone growth. At its persisting, the condition can result in severe bone deformation. Degree of weathering and the leachable F in a hard rock terrain is more important in deciding F content in the water rather than the mere presence of F⁻-bearing minerals in the bulk rocks/soils ( Ramesam & Rajagopalan, 1985 ). However, Fluoride-bearing minerals (fluorite, apatite, biotite, hornblende, etc.) present in hard rock terrains (basalts, granites, gneisses, schists, charnockites, khondalites, etc.) and anthropogenic sources (chemical fertilizers, sewage, sludge, etc.) in India are mainly responsible for higher content of F in groundwater with a combination of higher rate of evaporation and longer interaction of water with aquifer materials under alkaline environment ( Shaji et al., 2007 ; Srinivasamoorthy et al., 2008, 2012 ; Ramachandran et al., 2012 ; Reddy et al., 2010 ; Deepu & Shaji, 2011 ; Chidambaram et al., 2013 ; Manikandan et al., 2014 ). Also Handa (1975) reported positive correlation between fluoride and silica as well as between fluoride and sodium in groundwater, which indicate a silica-mineral source of fluoride. According to ( Abu Rukah & Alsokhny, 2004 ; Jacks et al., 2004 ), the concentration of fluoride in groundwater depends on the geological, chemical and physical characteristics of aquifers (e.g., porosity and acidity of soils, rocks, temperature and depth).

Dental fluorosis is a common manifestation in the inhabitants of the study area. This has inspired this study in order to determine the occurrence of fluoride in the groundwater of Kaltungo area and environs.

Kaltungo area and environs is the study area located in the north eastern part of Nigeria and is defined by Latitudes 9˚45'00"N and 9˚51'00"N and Longitudes, 11˚15'00"E and 11˚21'00"E and covers an area of about 121 km². The study area is characterized by tropical continental (Sudan) climate. It is also characterized by two seasons; a rainy season, which starts in April and ends in October and the dry season, which normally spans between November and April. The vegetation of the area is of Sudan Savannah type which covers more than half of northern Nigeria. It is characterized by short grasses with sporadic thorny bushes and scattered trees. The topography of the area is generally hilly with some parts having elevations more than the other surroundings. The elevation ranges from about 450 m to 850 m (Figure 1). The outcrops generally consist of rocks which are made up of Coarse Porphyritic granite, Biotite granite, Bima sandstones and Tertiary Basalt. Surface drainage systems in the study area comprise numerous streams formed in the direction of the river basin towards the southeast.

The study area is underlain by Pre Cambrian Basement Complex rocks and Cretaceous sediments. The basement Complex rocks are represented by Coarse Porphyritic Granite and Biotite Granites, the Cretaceous sediment is represented by Bima Formations and the Tertiary Volcanic Rock is represented by Basalt (Figure 2). Studies indicate that the rocks in the area were subjected to a wide range of tectonic disturbances involving Faulting. The orientation of the fault is mainly trending NE-SW. The continental Bima formation is the basal part of the sedimentary successions in the study area. It lies unconformably on the Precambrian Basement Complex. It ranges in age from Upper Aptian to Lower Albian ( Allix et al., 1981 ). The sediments consist of poorly sorted, angular, highly arkosic pebbly sandstones, granulestones and pebble conglomerates ( Zarboski et al., 1997 ). However, over 50% of the area is underlain by coarse porphyritic granite intruded by small portion of fine grained biotite granites on the extreme south western part of the map (Figure 2), volcanic rocks are also common. The southern, northern and eastern portion of the study area is underlain by Bima Sandstone with intrusions of basalt to the southern part, which belongs to the Tertiary Volcanic Basalt that intruded into the Benue Trough.

A total of 30 groundwater samples from hand dug wells and boreholes were collected (Figure 1) in a container that was rinsed two to three times using the representative groundwater samples according to Barcelona et al. (1985) . Water samples were filtered with UNICEF standard filter to free them from suspended particles. Samples were kept in a field cooler throughout the period of the sampling

exercise. The coordinates of each boreholes and hand-dug wells were determined using GPS (Model Garmine Trex HC Series), and later transferred to the base map of the study area. Immediately after sampling, field parameters such as: pH and Temperature were measured using Pen PH and Temperature meter (Model CT6021A), Turbidity was measured using Hand held turbidity meter (Model HAUX 2100Q), Conductivity was measured using Pen Conductivity meter (Model CT 3030), and Total Dissolved Solids (TDS) was measured using Pen TDS Meters (Model 21000). Carbonate and bicarbonate were determined in the field using titrimetric method by HACH Digital Titrator (Model 16900). All other parameters such as Potassium (K⁺), Calcium (Ca²⁺), Copper (Cu²⁺), Sodium (Na⁺), Magnesium (Mg²⁺), Iron (Fe²⁺), Manganese (Mn⁻), Chloride (Cl⁻), Nitrate (NO³⁻), Fluoride (F, Zinc (Zn), Sulphate ( ), Lead (Pb⁻) and Chromium (Cr⁶⁺) were determined in the laboratory by spectrophotometry using HACH digital Spectrophotometer (Model DR2400, USA).

The variables were subjected to Pearson correlation to observe the strength and direction of association that exist between fluoride and other parameters. The Karl Pearson correlation coefficient is used as a measure to establish the relationship between two variables X and Y. The correlation studies are useful to find a predictable relationship which can be exploited in practice. It is used for the measurement of the strength and statistical significance of the relation between two or more water quality parameters. Direct correlation exists when increase or decrease in the value of one parameter is associated with a corresponding increase or decrease in the value of other parameter V.T Patil and P.R Patil (2011) . To find the relationship between two parameters x and y, the Karl Pearson’s correlation coefficient, r is used and it is determined as follows ( Antony et al., 2008 ).

Here, n = number of data points; x = values of x–variable; y = values of y-variable. SPSS version 20 was used for the statistical analysis.

Characterisation of the water in the study area was done using Piper Trilinear Diagram. In the diagram, an ion can be considered as type facies when its concentration is within 50% to 100% domain. AqQa Software Version 1.5.0 was used to develop the piper diagram.