ORIGINAL ARTICLE: OBSERVATIONAL STUDIES
|Year : 2019 | Volume
| Issue : 3 | Page : 224-231
Are dental caries and overweight/obesity interrelated? A cross-sectional study in rural and urban preschool children
Bhavika Sharma1, KR Indushekar1, Bhavna Gupta Saraf1, Divesh Sardana2, Neha Sheoran1, Sunny Mavi3
1 Department of Paediatric Dentistry, Sudha Rustagi Institute of Dental Sciences and Research, Faridabad, Haryana, India
2 Department of Paediatric Dentistry, Sudha Rustagi Institute of Dental Sciences and Research, Faridabad, Haryana, India; Department of Paediatric Dentistry, Faculty of Dentistry, Prince Philip Dental Hospital, The University of Hong Kong, Hong Kong, SAR China
3 Department of Periodontics, Sudha Rustagi Institute of Dental Sciences and Research, Faridabad, Haryana, India
|Date of Web Publication||30-Sep-2019|
Dr. Divesh Sardana
Department of Paediatric Dentistry, Faculty of Dentistry, Prince Philip Dental Hospital, The University of Hong Kong, Hong Kong
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Obesity and dental caries are two distinct diseases which are somewhat preventable through a common risk factor approach, as they have common underlying etiological factor, i.e., high sugar intake. Aim: The aim of the study is to examine the correlation between dental caries and body mass index (BMI) in rural and urban areas of Hisar (Haryana, India) and intercompare their correlations. Settings and Design: This was a cross-sectional study in rural and urban preschool children of Hisar, Haryana. Methods: A total of 500 urban and 500 rural children (age group 3–6 years) were selected from schools of Hisar and the values of their mean BMI and mean decayed, missing, and filled teeth (dmft) (using the World Health Organization criteria, 2005) were compared using independent sample t-test among different groups and subgroups. Pearson correlation coefficients between dmft and BMI were calculated for groups and subgroups and intercompared. Results: Males had significantly higher BMI than females (P < 0.05) and urban preschool children had significantly higher BMI than rural preschool children (P < 0.05). Mean deft was statistically non-significant across the genders and both geographical areas. Non-significant negative correlation was observed between dmft and BMI across different areas and genders. The overall prevalence of obesity/overweight was 20.2% (25.6% urban preschool children; 14.8% rural preschool children). More rural preschool children were underweight (23.8%) than urban preschool children (14.4%) with the overall prevalence of underweight being 19.1%. Conclusions: There was no significant correlation between dental caries and BMI in preschool children of rural and urban areas. Obesity/overweight was more prevalent in urban preschool children, whereas rural preschool children predominantly were underweight.
Keywords: Body mass index, dental caries, malnutrition, obesity, rural population, urban population
|How to cite this article:|
Sharma B, Indushekar K R, Saraf BG, Sardana D, Sheoran N, Mavi S. Are dental caries and overweight/obesity interrelated? A cross-sectional study in rural and urban preschool children. J Indian Soc Pedod Prev Dent 2019;37:224-31
|How to cite this URL:|
Sharma B, Indushekar K R, Saraf BG, Sardana D, Sheoran N, Mavi S. Are dental caries and overweight/obesity interrelated? A cross-sectional study in rural and urban preschool children. J Indian Soc Pedod Prev Dent [serial online] 2019 [cited 2020 Apr 3];37:224-31. Available from: http://www.jisppd.com/text.asp?2019/37/3/224/268175
| Introduction|| |
Urbanization and economic development have resulted in unprecedented changes in diet and lifestyles. This change is shifting the beam-balance of prevalence from one aspect of malnutrition, i.e., nutritional deficiency to the other extreme of malnutrition which is overweight and obesity. The changes mentioned above are even rapid in growing economies like India and China which have resulted in the higher prevalence of obesity in these countries. A study from 1980 to 2015 spanning 195 territories and countries has found that China tops the list of number of obese children (15.3 million) in the country followed by India (14.4 million). The World Health Organization (WHO) data suggest that vast majority of these children live in developing countries where the increase in prevalence has been 30% higher in developing countries than developed countries from 1990 to 2016. To date, studies investigating relationship between obesity and dental caries in have produced equivocal results, while some studies claiming higher prevalence of obesity in rural populations  while others claiming higher prevalence in urban populations , and some of the studies even becoming inconclusive about difference between overweight and obesity in both populations. Sugar intake and other nutrients intake differ among rural and urban populations which might affect the varied results among different populations.,
Dental caries is another multifactorial disease with at least one shared denominator underlying the etiopathogenesis of both dental caries and obesity, i.e., excessive sugar intake. The other common factor among two diseases is that both diseases are gratuitous and preventable with systemic consequences if left untreated. Both obesity and dental caries share a common etiological factor i.e., high sugar intake. It is pertinent to think that obese children may have higher caries due to high sugar intake. In contrast, it is also quite possible that children who have large dental caries might not be able to chew food, thus limiting their diet and hence may suffer from malnourishment. Knowledge of the relationship between body mass index (BMI) and dental caries could lead to preventive health measures designed to decrease the prevalence and incidence of both obesity and dental caries. Surveillance of both dental disease and obesity can identify populations at highest risk for both conditions, as well as strategies for joint prevention efforts and more research should address these important public health problems to facilitate prevention and health promotion. Hence, the present cross-sectional study was carried out with an aim to determine if there is an association between BMI and dental caries in children aged 3–6 years and compare the figures in rural and urban areas of Haryana, India.
| Methods|| |
The present cross-sectional epidemiological study was carried out to assess the correlation between BMI and dental caries and its comparative evaluation in preschool children (aged 3–6 years) in rural and urban areas of Haryana. Sample size calculation was done using G*Power 3.1 software (Heinrich-Heine-Universität, Düsseldorf, Germany) for two independent groups assuming the inequality with the following parameters: α err probability (two-tailed) = 0.05 and power (1-β err probability) = 0.90, proportion 1 = 0.4, and proportion 2 = 0.3 with allocation ratio (N2/N1) of 1:1 in both the groups giving a final sample of 992 (446 in each group). The final sample was rounded-off to 1000 children with 500 participants per group. To cover the complete area, schools located in different areas were randomly selected using a random number sequence generator.
The study protocol was approved by the Institutional Review Board of Sudha Rustagi Dental College, Fardiabad (IRB no. Pedo No 14/248 dated March 29, 2014). Informed consent was confirmed by the IRB. Purpose of the study was informed, explained, and prior consent was obtained from respective school authorities and from parents/guardians through schools before the onset of the study. Children present on the day of examination were included in the study. Those who were not willing to participate or unwell were excluded.
Inclusion criteria of study
- Children with the chronological age between 3 and 6 years
- Children going to rural schools and belonging to rural area
- Children going to urban schools and belonging to urban area
- Children for whom the parental consent is given.
Exclusion criteria of study
- Children with long-standing systemic illness and/or on medications for long duration
- Children with physical or mental disability
- Children for whom parental consent was not given
- Children residing in rural areas and attending the schools in urban area
- Children residing in urban areas and attending the schools in rural area.
The principal investigator was trained and calibrated in the Department of Pediatric and Preventive Dentistry under the guidance of the chief supervisor before proceeding for the study till consistent results were obtained. Each individual/group of individuals in a classroom was explained about the method of examination and the entire procedure using the study models. Assistance from the school teachers was obtained during the measurement of weight and height. Oral examination was carried out by a single examiner with a recording assistant both who were blinded to the weight and height of the child. In all the locations, natural light was used and the patient was placed in such a way that maximum illumination was obtained.
Extraoral and intraoral examinations were carried out. Dental caries was recorded as per index specified by the WHO which grades primary teeth into following categories (A – sound, B – caries, C – filled, with caries, D – filled, no caries, and E – missing due to caries). Tooth was counted as decay when any of the following were met: (a) the lesion was clinically visible and obvious, (b) the explorer tip could penetrate deep into soft yielding material, (c) there were discolorations or loss of translucency typical of undermined or demineralized enamel, (d) the explorer tip in a pit or fissure had a catch or resisted removal after moderate-to-firm pressure on insertion, or (e) when there was softness at the base of the area.
For recording the BMI, weight and height of each child was recorded. Weight of each child barefooted was measured to the nearest 0.1 kg using a digital and a portable glass personal weighing scale placed on a flat floor which was calibrated before use. Each child was instructed to stand still, with mass equally distributed between feet, until the scale reading stabilized. The reading was then recorded. Height was measured to the nearest 0.1 cm using a stature meter attached to the wall provided in each school. Each child was asked to stand barefoot against the stature meter, and the value was recorded. BMI values were calculated for every individual at the end of each day with the formula:
BMI= Weight in kg/(Height in m 2)
BMI percentile was calculated according to Center for Disease Control (CDC)
BMI-for age growth chart. Using age- and gender-specific criteria, participants were categorized as:
- Underweight – <5%
- Normal – <5%–<85%
- Overweight – 85%–<95%
- Obese – ≥95%.
After calculating the BMI value, this value was plotted on the appropriate chart for his/her age and the findings were interpreted.
All the quantitative variables (age, d, e, f, body weight, and height) were entered into Statistical Package for the Social Sciences (IBM SPSS Statistics for Windows, Version 24.0, IBM Corp., Armonk, NY) for comparison of means among different groups and subgroups. Independent sample t-test was used to compare means at significant level of P < 0.05. Pearson correlation coefficient was computed between BMI and deft among different subgroups and statistically analyzed at P < 0.05. Correlation coefficients of the groups and subgroups were statistically compared manually using a calculator. First, Z values corresponding to r of the group and its respectiveP value was computed from the statistical table. Then, Z values were compared using the formula Zobserved= (Z1 – Z2)/(square root of ([1/N1 – 3] + [1/N2 – 3]) where Z1 and Z2 represent Z values of the groups and N1 and N2 represents the sample size of the respective groups. The Zobserved value was again compared to the critical Z = 1.96 corresponding to Z = 2 to assess the significance level among groups.
| Results|| |
The present study was conducted on a sample of 1000 preschool children (577 males and 423 females) with a mean age of 4.496 ± 1.118 years equally divided into two groups of rural and urban areas (n = 500 each). [Table 1] depicts the distribution of age according to genders and geographical areas. The mean age was statistically non-significant across rural and urban locations (P = 0.955) and across genders (P = 0.614). The mean BMI among males and females across both urban and rural locations is presented in [Table 2]. Overall, males had significantly higher BMI than females (P < 0.05) and urban preschool children had significantly higher BMI than rural preschool children (P < 0.05) [Table 2]. Mean deft was statistically non-significant across the genders and both geographical areas [Table 3]. Pearson correlation coefficient (r) was calculated between BMI and deft in urban and rural preschool children according to genders and has been enlisted in [Table 4]. The value of r was −0.038 for the overall population of 1000 children, thus signifying no correlation between dental caries and BMI in preschool children. Although all the values of r were negative suggestive of inverse correlation between dental caries and BMI, none of them reached statistically significant level, thus speculating that deft is not correlated with BMI. The relationship between deft and BMI can be graphically analyzed using scatter plots in [Figure 1] which do not show any significant correlations. [Figure 2] depicts correlation between genders and different locations through the means of scatter plots. [Figure 3] shows distribution of different children into BMI categories as per the CDC classifications. The overall prevalence of obesity and overweight was 20.2% with 25.6% prevalence in urban preschool children and 14.8% prevalence in rural preschool children. More rural preschool children were underweight (23.8%) than urban preschool children (14.4%) with the overall prevalence of underweight being 19.1%. [Figure 4] demonstrates the prevalence of dental caries in the study population as per their BMI category. The prevalence of dental caries was 50.8% overall with maximum prevalence in overweight category (53.6%) and least in the normal BMI category children (51.2%). The difference in the prevalence of dental caries among all the 4 categories in the overall population was statistically not significant (P ~ 0.568).
|Table 3: Mean decayed, missing, and filled teeth distribution of the study population|
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|Table 4: Pearson correlation coefficients between body mass index, dmft, and gender in urban and rural populations|
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|Figure 1: Scatter plots showing correlation between decayed, missing, and filled teeth and body mass index in the study participants|
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|Figure 2: (a) Scatter plots showing correlation between decayed, missing, and filled teeth and body mass index in urban preschool children, (b) Scatter plots showing correlation between decayed, missing, and filled teeth and body mass index in rural preschool children, (c) Scatter plots showing correlation between decayed, missing, and filled teeth and body mass index in preschool males, (d) Scatter plots showing correlation between decayed, missing, and filled teeth and body mass index in preschool females|
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|Figure 3: Distribution of different children into body mass index categories|
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|Figure 4: Percentage distribution of children with dental caries (prevalence) and without dental caries in overall population according to body mass index category|
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| Discussion|| |
Historically, assessing and addressing childhood overweight/obesity has been the purview of the pediatrician or family physician. As the obesity epidemic escalates, it is apparent that screening solely during well-child visits may no longer be an expedient strategy for addressing this emerging issue. Dentists likely will aid in diagnosing a small percentage of children compared to the percentage diagnosed by physicians. These small successes, however, make a significant difference on a population level. Considering that weight status and its dietary correlates are related to dental health, the dental team has a unique opportunity to collaborate with other health providers such as pediatricians, family physicians, and dietitians to address the epidemic.
Urban children had significantly higher BMI than rural children [Table 2] possibly due to one or more of these reasons: low levels of physical activity, consuming junk foods, less emphasis on outdoor games and sports, lack of parental influence, abuse, anxiety, depression and family stress, and genetic and environmental factors. Urban females from developing countries, especially have higher chances of obesity possibly due to changing lifestyles  which can be seen in present study from the significant difference between mean BMI between urban and rural females [Table 2]. In the present study, the prevalence of overweight was 8.4% and obesity was 11.8% (combined figure of 20.2%) which are similar to another study on South Indian children with the reported prevalence of overweight and obesity being 17% and 3%, respectively (combined 20%).
Many studies involving body weight use BMI percentile as the measure of “body fatness,” as it is age and sex adjusted and allows for the ability to accurately compare children of differing ages and gender. Growth charts can be computed for different genders and age groups and compared to CDC norms. However, since growth chart below 2 years is not specified by CDC, the age group selected in the present study was above 2 years (i.e., 3–6 year age group). Various authors have tried to identify the relationship between dental caries and BMI utilizing different methods of recording obesity, different age groups, and impact of obesity on dental caries or vice versa. Inverse relationship between caries activity and BMI and waist circumference has been reported in elemental schoolchildren of Jeddah, Saudi Arabia. Negative relationship between obesity/overweight and dental caries have also been found by many authors., The results of the present study show weak-negative correlation between dental caries and BMI in preschool children which are similar to the results obtained by another study in 744 children aged 8 years in China. Various other studies done on different population groups have also not found a significant correlation between dental caries and BMI or obesity.,, A systematic review and meta-analysis  did not find a significant association between obesity and dental caries in primary dentition which supports our data that dental caries in primary dentition is not correlated significantly to BMI. In contrast, dental caries in permanent dentition of adults was found to be significantly positively correlated with BMI after controlling confounding factors of smoking and brushing. Similarly, studies done in child participants have also found higher BMI Z-scores in children with severe early childhood caries compared to caries-free children. The direct relationship between dental caries and obesity or overweight has also been found in many other studies.,
With the increased migration and expansion of cities, strict boundaries of urban and rural areas are difficult to establish. The authors in the present study used definitions of urban and rural from Census of India for differentiating urban and rural populations and selected the children from these areas. Since the data were cross-sectional, causal relationships cannot be established, and the observed association could be due to other unexplored factors. Both overweight/obesity and caries are conditions with multifactorial causes which can be influenced by several factors (dietary habits, genetic factors, or host factors). Although the investigators tried to eliminate confounding due to migration of rural population to urban areas and vice versa (as specified in the inclusion and exclusion criteria), some amount of confounding due to better transportation facilities and rapid urbanization spreading across the cities might have influenced the results. Therefore, the possibility of residual confounding may always be present and cannot be totally eliminated in similar type of studies. Another limitation of the study was that early carious lesions were not recorded (white spot lesions) due to settings of the examination in school premises rather than dental clinic. Inclusion of noncavitated early carious lesions using ICDAS II criteria was found to change the higher prevalence of caries in obese when WHO decayed, missing, and filled teeth (dmft) criteria was used which showed higher prevalence in nonobese. Furthermore, caries detection was carried out visually without taking radiographs which could have not disclosed proximal caries or occult caries. Thus, the deft estimated in the present study could be slightly underestimated.
Dentists who care for children are in a unique position to help address the childhood obesity epidemic for several reasons. First, dentists may see children by 1 year old, providing an opportunity for longitudinal counseling and monitoring of weight status starting at an early age. Normative BMI percentiles are not available for children younger than 2 years old. For these children, the dental team is encouraged to rely upon anticipatory guidance that includes a discussion of appropriate dietary habits, the importance of avoiding caloric-dense, low nutrition foods, and the consequences of nonideal growth trajectories that lead to development of overweight or obesity. Beginning at 2 years old or as soon as is reasonably achievable, dental teams should measure and record height, weight, and BMI percentiles at regular intervals. This will facilitate the provision of longitudinal data regarding the child's growth and development.
Second, dentists have a higher likelihood than pediatricians of seeing older children on a regular basis for recall visits. The implication is not that dentists should replace pediatricians or family physicians in addressing childhood overweight or obesity, but that dentists can utilize dental visits to add additional screening and counseling that complements a physician's efforts in addressing overweight or obesity. Third, dentists are credible sources for dietary counseling and already counsel about caries prevention. Most dentists who treat children feel that dietary counseling is an important component of oral health. The main thrust of dietary counseling from dentists, however, focuses on the reduction of cariogenic foods and related consumption habits. Dentists could easily expand their dietary counseling efforts to emphasize the implications of poor diet on oral and systemic health that extend well into adulthood. It is encouraging that initial studies exploring dental office-based dietary counseling have proven to be successful, feasible, well-accepted, and effective in changing the dietary habits of parents and children., In addition, these efforts have been well received by caregivers of pediatric patients as found in a study, wherein greater than 94% of parents who participated in a dental office-based healthy weight intervention program felt that it was an appropriate place to address healthy eating and weight issues. Fourth, some dentists currently measure children's weight and height for other purposes. Weight is essential to calculate safe dosages of local anesthesia for young children, and obtaining weight is important for most conscious sedation procedures or dental rehabilitation under general anesthesia. For these practitioners, calculation and longitudinal tracking of BMI percentiles requires only minor changes in routine protocols. Fifth, minimal equipment is needed to collect weight/height measurements, which can be collected with little disruption to patient flow. The equipment needed to institute BMI percentile measurements includes only a scale for measuring weight and a stadiometer for measuring height – both can be obtained for low start-up and maintenance costs.
After a child's BMI percentile and weight category have been determined, the dental team should make recommendations that are consistent with the child's weight and health status. The goals of these clinical recommendations are to: reinforce “universal” recommendations for healthy activity and nutrition, even for those in healthy weight categories; identify and refer individuals with an unhealthy BMI category for further assessment and confirmation of weight status; and inform parents of children in unhealthy weight categories of the serious effects of childhood overweight or obesity with appropriate urgency in a sensitive manner. It is important for the dental professional to also consider parental obesity, family health status, and current diet and physical activity behaviors.
| Conclusions|| |
Males had significantly higher (P < 0.05) BMI than females and urban preschool children had significantly higher BMI than rural preschool children (P < 0.05). Mean deft was statistically non-significant across the genders and both geographical areas. Nonsignificant negative correlation was observed between dmft and BMI in males and females and urban and rural preschool children. The overall prevalence of obesity and overweight was 20.2% with 25.6% in urban preschool children and 14.8% in rural preschool children. More rural preschool children were underweight (23.8%) than urban preschool children (14.4%) with the overall prevalence of underweight being 19.1%.
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Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4]