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| Year : 2014 | Volume
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| Issue : 6 | Page : 722-728 |
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| Co-relation of body mass index, dental caries and periodontal status with fluorosis in different high fluoridated areas of Haryana state, India |
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Manisha Vijayran, Naveen Manuja, Seema Chaudhary, Ashish Sinha, TR Chaitra
Department of Pedodontics and Preventive Dentistry, Kothiwal Dental College and Research Centre, Moradabad, Uttar Pradesh, India
Click here for correspondence address and email
| Date of Submission | 11-Jan-2014 |
| Date of Decision | 29-Jan-2014 |
| Date of Acceptance | 14-Jan-2015 |
| Date of Web Publication | 02-Mar-2015 |
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 Abstract | | |
Background and Aim: The aim of the present study is to compare the effect of corticotomy versus prostaglandin E1 injection in human subjects on rate of tooth movement, anchorage loss and their effect on crest bone height and root length.
Settings and Design: Clinical interventional study. Split mouth design was used.
Materials and Methods: Study was done on 32 regular orthodontic patients. A volume of 100 mcg of prostaglandin E1 was injected on the right side once in 2 weeks and on the left side corticotomy was performed, and canine retraction was started on both sides simultaneously. The rate of space closure and anchorage loss was assessed with casts. The root length and crestal bone height changes were assed with IOPAs. The comparison of rate of tooth movement, anchorage loss, crestal bone height and root length changes between the sides were statistically analyzed using paired t-test.
Results: The average rate of space closure on right side was 0.36 mm/week with a standard deviation of 0.05 mm/week and on the left side average rate of space closure was 0.40 mm/week with a standard deviation of 0.04 mm/week. The difference between the rate of closure between the right side and left where found to be statistically significant (P = 0.003). The anchorage loss, the crestal bone height changes and root length changes were not statistically significant.
Conclusion: The rate of tooth movement was significantly more with corticotomies when compared with given dose of prostaglandin injection. Keywords: Canine retraction, corticotomies, prostaglandin E1
How to cite this article:
Vijayran M, Manuja N, Chaudhary S, Sinha A, Chaitra T R. Co-relation of body mass index, dental caries and periodontal status with fluorosis in different high fluoridated areas of Haryana state, India. Indian J Dent Res 2014;25:722-8 |
How to cite this URL:
Vijayran M, Manuja N, Chaudhary S, Sinha A, Chaitra T R. Co-relation of body mass index, dental caries and periodontal status with fluorosis in different high fluoridated areas of Haryana state, India. Indian J Dent Res [serial online] 2014 [cited 2023 Mar 31];25:722-8. Available from: https://www.ijdr.in/text.asp?2014/25/6/722/152174 |
Oral diseases form an important health problem in the community. During the last decade, there has been an increasing prevalence of dental health problems in India. India lies within the geographical belt that extends from Turkey to China. Nearly 12 million of the 85 million tons of fluoride deposits on the Earth's crust are found in India. It is, therefore, not surprising that dental fluorosis is endemic in 15 states in India. The highest rate of endemicity has been reported from Andhra Pradesh, Haryana, Karnataka, Punjab, and Tamil Nadu. [1]
Fluorosis continues to remain a challenging dental and skeletal health problem in India. A dose-dependent relation, not confined to increased caries resistance only, occurs between the effect of fluoride and dentition. Dental fluorosis is the most sensitive sign of prolonged high fluoride exposure while endemic skeletal fluorosis is a chronic metabolic bone and joint disease caused by ingesting large amount of fluoride either through water or rarely from foods of endemic areas. It has been recognized that mottled enamel (dental fluorosis) was associated with the presence of fluoride in drinking water long before the relationship with lower caries prevalence was noted. [2]
India, a developing country, faces many challenges in rendering oral health needs. The two most common oral diseases are dental caries and periodontal disease. Dental caries is the most prevalent dental affliction of childhood, and it is reported that 85% of children suffer from periodontal disease at the same point in time. Despite credible scientific advances and the fact that caries is preventable, the disease continues to be a major public health problem. In India, dental caries has been consistently increasing both in prevalence and severity for last five decades. About 80% of children and 60% of adults suffer from dental caries. [3]
Alongside caries, periodontal diseases are also a burden on global oral health. Periodontitis constitutes a major cause of tooth loss in adults worldwide, and most children and adolescents exhibit signs of gingivitis. [4] Although the effect of fluoride in reduction of dental caries is well established in the history of public health, its effect on periodontal tissues is still obscure. There is inconsistent epidemiological data concerning the prevalence of periodontal disease in subjects living in high-fluoride areas. Many studies, however, have found no difference in periodontal conditions between fluorosis and nonfluorosis areas. Moreover, a higher level of gingival inflammation has been observed in fluoride areas than in nonfluoride areas. [5]
Obesity affects the general health as well as the oral health of an individual. It has become an increasing problem of childhood causing various systemic illnesses, accelerates dental development and decreases masticatory performance. However, many studies have reported no difference between body mass index (BMI) and fluorosis. [6]
Hence, the present study was conducted to explore the relation between BMI, dental caries and periodontal status with fluorosis in different fluoridated areas of Haryana state, India.
| Materials and methods | |  |
The present cross-sectional study was conducted between 5 and 12 years old school going children living in high fluoridated areas: Mewat (A1) and Palwal (A2) districts of Haryana. Permission to conduct the survey in the respected schools was obtained from the respective school authorities and was scheduled over a period of 6 months from January 2013 to May 2013. Before that, the study was reviewed and cleared by the ethical committee of the institution. The inclusion criteria for the study were the presence of subjects during the days of survey whereas, the exclusion criteria includes: Pupils who were physically challenged, subjects with systemic illness and uncooperative subjects.
In order to collect the representative sample, a multi stage sampling procedure was executed. From each district, the area having the highest ppm level of fluoride in drinking water was taken. The data regarding the fluoride level was taken from the Central Ground Water Board, Chandigarh, Haryana (2007). Consecutively, one area was selected from each district. The water level reported in area A1 and A2, was 3.9 ppm and 5.6 ppm, respectively. According to the US Environmental Protection Agency (EPA), one area was found to be higher than the maximum contamination level goals (MCLGs) 4.0 ppm. As noted, EPA set the fluoride MCLG and MCL to protect against the adverse health effect of crippling skeletal fluorosis (Stage III skeletal fluorosis), the symptoms of which include sporadic pain, joint stiffness, and abnormal thickening (osteosclerosis) of the pelvis and spine. Public as well as private schools was randomly chosen, and 5-12 years old children were selected from the data obtained from the school records. A total sample of 2047 children was taken for the study. Public as well as private schools however were taken as covariate for multivariate analysis.
The study includes only caries data among 5 years old children and the clinical data encompassing dental caries, fluorosis and periodontal status were obtained from 12 years old. The survey was carried out using modified World Health Organization (WHO) Oral Health Assessment Form (1997). Apart from this, the height and weight of each child was recorded in a separate sheet and BMI was calculated. For the calculation of BMI, the following formula was used;
The value obtained was then plotted on age and gender - specific percentiles given by the Centers for Disease Control and Prevention, and children were categorized into four groups based on their BMI percentiles as follows:
- Underweight group children with BMI-for age <5 th percentile
- Normal group children with BMI-for-age ≥5 th percentile and <85 th percentile
- Overweight group children with BMI-for-age ≥85 th percentile and <95 th percentile
- Obese group children with BMI ≥95 th percentile.
However, the last group was not included in our study as none of the children fell in this group.
Multivariate analysis of dental caries, fluorosis and periodontal status was also performed with various variables like area, type of school, age and BMI-categories.
The clinical examination of all subjects constituting the sample was entirely done by a single investigator who was trained and calibrated for recording the WHO Oral Health Performa (WHO, 1997) for oral diseases under adequate illumination using plain mouth mirror, No. 23 explorer (caries) and Community Periodontal Index (CPI) probe (periodontal disease). A recording clerk was trained to assist in the recording procedure throughout the study nearby the examiner. Sterilization was carried out using autoclave once during the day. Spot sterilization was done during the survey using chemical sterilizing solution. Surface disinfectants were taken to clean the surface near the examination area or wherever possible.
The data obtained was compiled systematically, transformed from a precoded proforma to a computer, and a master table was prepared. The statistical analysis was done using Statistical Package for Social sciences Version 15.0 (SPSS inc., Chicago IL)statistical analysis software. Spearman's rho test was used for calculating the linear relationship between BMI and fluorosis. However, one-way analysis of variance (ANOVA) and Kruskal-Wallis tests were used for co-relating dental caries and periodontal status with fluorosis, respectively. The values were represented in numbers and percentages (%) and mean ± standard deviation.
| RESULTs | | |
A total sample of 2047 children, 1000 from area A1 and 1047 from area A2 was enrolled in the study. Out of 1000 children enrolled from area A1, 500 (50%) were 5 years and 12 years, respectively, while in area A2, out of 1047 children enrolled, 587 (56.1%) were 5 years and remaining 460 (43.9%) were 12 years old. On comparing the data statistically, there was a significant difference in two groups (P = 0.006) [Table 1].
Under nutrition was quite prevalent overall as well as in the two age groups independently; however, the proportion of normal weight children was significantly lower in area A2 as compared to area A1 for both overall as well as the two age groups (P < 0.05) [Table 2]. | Table 2: BMI wise distribution of 5‑ and 12‑year‑old children from two study areas
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A significant difference in proportion of children with dental caries was observed between 5 years and 12 years age groups with a higher proportion in 12 years (68.5%) as compared to that in 5 years group (44.5%) (P < 0.001) [Table 3]. Similar significant trends were observed for both the areas (P < 0.001) and BMI 15.0-18.49 and 18.5-23.0 kg/m 2 categories (P < 0.001 and P = 0.005) respectively. However, on multivariate analysis, no variable other than the area of living (A1) showed a significant association with the outcome that is, prevalence of caries [Table 4]. | Table 3: Occurrence of dental caries in 5- and 12‑year‑old school children
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 | Table 4: Multiple logistic regression for association of caries with different demographic variables
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As compared to area A1, the proportion of subjects with max CPI score 1 and 2 was significantly higher in area A2 (P < 0.001). With increasing BMI, a significant increase in proportion of patients with maximum CPI score 1 and 2 was observed (P = 0.005) [Table 5]. On multivariate logistic regression with CPI maximum score 2 as a dependent variable with different demographic variables as the independent variables, the association was found to be statistically significant for area A1 and public schools [Table 6]. | Table 6: Multiple logistic regression for association of CPI maximum with different demographic variables
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It was observed that prevalence of dental fluorosis was higher in area A1 (94%) as compared to A2 (84.1%) and higher BMI (96.7%) as compared to lower BMI (88.8%). With respect to mean fluorosis scores, a significant difference in mean fluorosis scores at different areas was noticed [Table 7]. Moreover, area A1 and public schools showed a significant association with the prevalence of fluorosis when compared in multiple logistic regression analysis taking fluorosis as a dependent variable [Table 8]. | Table 8: Multiple logistic regression for association of fluorosis with different demographic variables
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A virtually nonexisting and negative correlation was observed between BMI category and fluorosis scores (ρ = −0.027), which was also not significant statistically (Spearman's ratio test) [Table 9].
Mean decayed missing and filled teeth (dmft) scores of subjects not having fluorosis were found to be significantly lower as compared to those having fluorosis with maximum dmft for fluorosis score 1 and minimum for those having fluorosis score 0 (F = 4.824; P < 0.001) (one-way ANOVA and Kruskal-Wallis tests) [Table 10]. On evaluating this for linear correlation, the correlation was almost nonexistent (ρ = 0.018), which was not significant statistically too (P = 0.570).
As compared to those having fluorosis score 0, those having fluorosis scores 1 and above, a significant increase in number of subjects with maximum CPI score 1 and 2 was observed (P < 0.001) [Table 11].
On evaluating this relationship for linearity, the correlation was found to be weakly positive but statistically significant (ρ =0.224; P < 0.001).
| Discussion | | |
In India, many epidemiological studies on fluorosis and dental caries among school going children have been carried out. Nevertheless, as there is very limited literature available regarding the confounding relation between these variables in high fluoridated areas in the past, there was a need to analyze the relative relationship between BMI, dental caries and periodontal status with fluorosis.
A high prevalence of caries was noticed in 12 years old age group (68.5%) as compared to 5 years old school children (44.5%). Similar findings were seen in other studies. [7],[8] The possible reason could be attributed to the fact that permanent teeth are exposed to cariogenic food for more time as compared to the primary teeth that is, from the time of eruption till the teeth are in situ. [8]
Prevalence of caries was higher in subjects with higher BMI (91.3%) for BMI (18.5-23.0 kg/m 2 ) as compared to those with lower BMI (46.9% and 58.5% respectively for <15 and 15.0-18.49 kg/m 2 ) (P < 0.001). It has been seen that childhood obesity and dental caries are coincidental in many populations, probably due to the common confounding risk factors such as intake frequency, cariogenic food, and poor oral health. In the present study, caries scores gradually increased in both primary and permanent dentition as BMI increased, which shows positive association between caries and BMI. Similar findings were reported by Hilgers et al. [9] and also by others. [10],[11],[12] However, contradictory results were seen in other studies. [13],[14],[15],[16],[17]
A virtually nonexisting and negative correlation was observed between BMI and fluorosis scores for both the areas that was nonsignificant statistically too. Similar results were seen in other studies. [18],[19] However, Rugg-Gunn et al. [20] and Rango et al. [21] reported a high prevalence of dental fluorosis in children suffering from malnutrition.
As compared to those having fluorosis score 0, 1 and above, a significant increase in a number of subjects with maximum CPI score 1 and 2 was observed (P < 0.001).
On evaluating this relationship for linearity by Kruskal-Wallis test, the correlation was found to be weakly positive but statistically significant (ρ = 0.224; P < 0.001). Similar observations were seen earlier also. [5] Reddy et al. [22] in his study found very little evidence of periodontal destruction in high fluoridated areas. Similarly, Grembowski et al. [23] found that fluoridation has small beneficial effects on periodontal health among adults aged between 20 and 34 years relative to adults with no exposure. Further studies are required to confirm the present data as there is very limited text available regarding the periodontal status of children in fluoridated areas.
In the medical literature, it has been hypothesized that cemental necrosis, osteosclerosis and calcification of ligament in human periodontal region can be a consequence of the life time exposure to high fluoride water levels. However, the exact toxic effects of fluorides on human periodontal tissues remain to be researched to confirm the data.
Fluoride, being effective in preventing dental caries, does not remove the cause of the disease permanently. On the contrary, it may lead to the brittleness and mottled teeth, which may be associated with elevated caries levels. This may be the possible reason for high caries experience in the very high fluoride area. Similar results were seen in studies by Grobleri et al., [24] and others. [25],[26],[27]
Studies done by Ermis et al. [28] and Akpata et al. [29] found that increased water fluoride levels had no influence on caries experience in children. There is a lot of controversy around the relationship between dental caries and water fluoride levels. A study conducted at the National Committee on Oral Health of China by Wang et al. [30] showed that the relationship between the average number of dmft of urban residents and fluoride concentration in drinking water to be negatively correlated but not forming a good linear relationship.
There are various other risk factors like fluoride supplements, fluoridated toothpaste and infant formulae, irrespective of fluoridated water, which have a high propensity for the prevalence of dental fluorosis. Many studies, [31],[32],[33] however, found an inappropriate association between the fluoride supplements and fluorosis as the risks of using fluoride supplements in young children might outweigh its benefits. Moreover, these chosen areas in this study come under the still developing region, so lack of motivation and awareness was also a confounding factor for the progression of fluorosis. People may or may not be using fluoride supplements and infant formulae, taking as a strong limitation of our study and no measurements were done regarding these variables. As the areas come under the fluoride belt, we have just tried to found the co-relation of BMI on dental caries, periodontal conditions, and fluorosis.
| Conclusion | | |
It can be concluded from our study that there exists no statistically significant association between BMI and dental caries with fluorosis. However, a positive association was found between periodontal status and fluorosis.
However, this study has some limitations. The direct information of the source of supply of water was not retrieved in this study as the children could not provide this information. Also, the study is school-based not community-based. Moreover, no data were obtained on the duration of consumption of water and therefore the duration of exposure to fluoride was not accurately measured.
| Future direction | | |
All the factors known to be associated with fluorosis were not studied. And, further studies are required in this field as no attempt was made to conduct this study in nonfluoridated areas for comparison evaluation.
Hence, it is recommended to reduce the fluoride content of drinking water in the high fluoride area by making either alternative source available or providing water with reduced fluoride content.
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Correspondence Address:
Naveen Manuja
Department of Pedodontics and Preventive Dentistry, Kothiwal Dental College and Research Centre, Moradabad, Uttar Pradesh
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/0970-9290.152174
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9], [Table 10], [Table 11] |
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