Is Malnutrition Associated with Crowding in Permanent Dentition? (2023)

Is Malnutrition Associated with Crowding in Permanent Dentition? (1)

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Int J Environ Res Public Health. 2010 Sep; 7(9): 3531–3544.

Published online 2010 Sep 27. doi:10.3390/ijerph7093531

PMCID: PMC2954562

PMID: 20948941

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Abstract

Evidence suggests that energy-protein malnutrition is associated with impaired growth and development of facial bones. The objective of this study was to investigate the association between nutritional status and reduced space for dental eruption (crowding) in permanent dentition. A cross-sectional study with probabilistic sampling design was used. We evaluated 2,060 students aged 12 to 15 years enrolled in schools in the northeast of Brazil. Crowding was defined according to World Health Organization (WHO) as misalignment of teeth due to lack of space for them to erupt in the correct position. Nutritional status was evaluated by means of body mass index and height-for-age, using the WHO’s reference curves. Parents and adolescents responded to a questionnaire about demographic, socioeconomic, biological and behavioral characteristics. The associations were estimated by odds ratio (OR) in multivariate logistic regression analysis (alpha = 0.05). Confounding and effect-modification were taken into account. An association between low height-for-age (z-score < −1SD) and crowding was only observed in adolescents with a prolonged history of mouth breathing (OR = 3.1). No association was observed between underweight and crowding. Malnutrition is related to crowding in permanent dentition among mouth-breathing adolescents. Policy actions aimed at reducing low height-for-age and unhealthy oral habits are strongly recommended. However, further studies are needed to increase the consistency of these findings and improve understanding of the subject.

Keywords: malocclusion, epidemiology, nutrition, protein-energy malnutrition

1. Introduction

The relationship between nutritional status and oral health has recently become a subject of study [14]. Poor oral habits have traditionally been considered the main environmental factor responsible for poor dental occlusion [5]. However, some studies suggest that nutritional status may also be associated with malocclusion [4,6,7].

Malnutrition is a multifactorial disease that can have an early onset during intrauterine life or childhood or can occur during an individual’s lifetime as a result of poor nutrition and/or repeated episodes of infectious or chronic diseases [8]. The highest rates of energy-protein malnutrition (EPM) are recorded in developing countries [9] and represent a major nutritional problem, both because of their magnitude and the health disorders they give rise to [8,10]. EPM is associated with economic deprivation [11] and is an important indicator of a population’s quality of life [12].

Evidence suggests that energy-protein malnutrition acts by either exacerbating an existing morbidity or contributing to the emergence of associated comorbidities. In the field of oral health, the association between malnutrition and impaired growth and the development of facial bones has been reported by a number of researchers [6,13,14] and has been linked to a reduction in the length of the skull base and jaw height [15]. There have also been reports of variations in maxillomandibular width, lower facial height [13] and dental and skeletal ages [6,14,16,17] as a result of malnutrition.

It is believed therefore that malnutrition may also be associated with malocclusion, particularly dental crowding, which is defined as misalignment of the teeth due to insufficient space for them to erupt in the correct place [18]. Altered bone growth in the craniofacial complex caused by poor nutrition could be reflected in reduced space for dental eruption. There is evidence in animal models that support this hypothesis [19,20]. The authors evaluated the effects of dietary deficiencies of protein and calorie on the growth of jaws and teeth in pigs and observed that both the size and shape of the mandible were substantially affected. Moreover, the amount of space available for the teeth was reduced in the protein and calorie deficient animals (experimental groups) and crowding was substantially increased in the experimental animals [19,20]. Another study, in rats, also found reduction in the size of the jaw in animals with protein and calorie malnutrition [21]. These findings suggest that malnutrition produces relative and absolute changes in the spatial arrangements of the teeth in the jaws. To our knowledge, there is only one study in humans that investigated the relationship between underweight or low height-for-age and dental crowding in the literature; however, the study only included low-income children with deciduous teeth [4]. The authors, who studied children aged 3 to 5 years, found that low weight for age was associated with a high risk of dental crowding but failed to find an association between the latter and low height for age. The aim of the present study was therefore to investigate, for the first time, the relationship between anthropometric failure and dental crowding in a large sample of adolescents in permanent dentition.

2. Materials and Methods

2.1. Study Type and Sample Design

The study was a cross-sectional population-based study involving 12 to 15-year-old adolescents in the city of Salvador, BA, Brazil. It was estimated that a sample of 1,580 individuals would have a 80% chance of detecting a 10% difference in the prevalence of dental crowding—estimated at around 35% [22]—between exposed and unexposed groups, with α = 0.05, considering a design effect of two. However, to compensate for possible losses and missing data and to detect possible interactions, the study sample was increased by 30%, to 2,060.

Probabilistic two-stage cluster sampling was used. The schools were the primary sampling units and the adolescents, the secondary units. The sample was further stratified into two groups according to whether the school was a private or public one. There were 398 primary schools in the city and 196,532 students enrolled (83.4% in public schools and 16.6% in private ones) [23]. The same population proportions were maintained in the sample. Forty schools (33 public and seven private), representing 10% of the total, were chosen at random; one additional private school was added later to make up the minimum number of students per school because one of the private schools chosen did not have enough eligible students. To ensure that all the age groups of interest were represented in the study sample, 13 adolescents were selected in each age group, yielding a total of 52 adolescents from each school.

If the student selected was not found in the school at the time of the assessment, the team returned to the school on two additional occasions, after which the information relating to that adolescent was considered a loss.

2.2. Inclusion and Exclusion Criteria

Students aged 12 to 15 years enrolled in the 6th to 9th grades of public or private secondary schools in the municipality of Salvador who had permanent teeth were included in the study. The following individuals were excluded: those who refused to submit to the evaluations (n = 2); those whose parents or guardians did not sign the written voluntary informed-consent form (n = 187); pregnant women (n = 1); adolescents with a physical handicap or who were unable to move because of physical trauma, as anthropometric measurements could not have been taken (n = 3); and those who reported prior or current use of an orthodontic or orthopedic appliance (n = 4).

2.3. Definition of the Variables and Data Collection

Dental crowding was defined according to the World Health Organization (WHO) [18] as a misalignment in the teeth position (in millimeters), using the WHO periodontal probe. It was the dependent variable and, to these analyses, it was classified as present (in one or both arcades) or absent (in neither arcade).

There were two main independent variables assessing the nutritional status of adolescents: nutritional status according to the BMI and height-for-age indexes. The authors acknowledge that assessment of the nutritional status of adolescents is made difficult by variations in growth, by the extent to which the adolescents had grown in previous periods of life and by the intricate relationship between sexual maturation and hormonal factors during this period of life [24]. Nevertheless, the WHO recommends the body mass index (BMI) and height-for-age index as suitable indicators for evaluating the nutritional status of adolescents, and these were used in this study.

For both indicators, the reference curves and cut-off points recently advocated by the WHO for adolescents and children above the age of five years were adopted [25,26]. The following classification was used: severe thinness (BMI z-score of less than −3SD); thinness (−3SD ≤ BMI z-score < −2SD); risk of thinness (−2SD ≤ BMI z-score < −1SD); normal BMI-for-age (−1SD ≤ BMI z-score ≤ +1SD); and overweight (+1SD < BMI z-score ≤ +2SD). Obesity is classified as +2SD < BMI ≤ +3SD, and severe obesity as BMI z-score > +3DP [26]. In the present study, the following categories were defined for BMI: normal BMI-for-age/risk of thinness (−2SD ≤ BMI z-score ≤ +1SD), thinness/severe thinness (BMI z-score < −2SD); and overweight/obesity (BMI z-score > +1SD) [25,26].

A height-for-age deficit was considered moderate/severe when the z-score was more than 2SD below the median for the reference population and mild when −2SD ≤ z-score < −1SD. A z-score ≥ −1SD was considered to indicate normal/high/very high height-for-age [25,26]. Because of the low prevalence of stunting in the sample (4.58%, n = 88), it was decided to group all types of malnutrition [as measured by the height-for-age index] together in a single category, and the adolescents were classified as having normal height-for-age (z-score ≥ −1SD) or some degree of low height-for-age (mild/moderate/severe: z-score < −1SD).

The co-variables in the study, measured by using a questionnaire answered by the students and their mothers/guardians, were: (a) demographic—age in years (‘12–13’ or ‘14–15’), sex (‘male’ or ‘female’), color (‘white’, ‘brown’ or ‘black’); (b) behavioral—duration of nutritious sucking habits (natural and artificial breast-feeding, categorized as ‘never breast-fed/breast-fed up to 12 months’ or ‘breast-fed for more than 12 months’) and non-nutritious sucking (sucking a digit or pacifier), as well as poor oral habits such as nail-biting, bruxism (grinding/clenching teeth) and mouth breathing, both classified as ‘never had the habit/had the habit but stopped at 6 years of age’ or ‘had the habit until after the age of six years’; (c) biological—the absence of posterior teeth (‘yes’ or ‘no’); and (d) socioeconomic—the level of schooling of the head of the family (‘high’—higher-level education not completed to postgraduate qualification, ‘average’—primary and secondary education completed, or ‘low’—illiterate and primary education not completed), family income (‘high’—more than 5 minimum monthly wages, ‘average’—from 2 to 5 minimum monthly wages, or ‘low’—less than 2 minimum monthly wages) and the type of school in which the adolescent was studying (public or private). Color was defined according to the criteria of the Brazilian Geographic and Statistical Institute (IBGE) [27], and because of the small number of individuals with yellow skin coloration (Orientals) or indigenous natives in the study population, these were excluded from the study (n = 19).

Only those interviewers/examiners with concordances equal to or greater than 0.85 were selected for the team. Occlusion was evaluated according to the WHO recommendations [18], and the anthropometric measurements followed Lohman et al. [28]. Duplicate measurements were taken in a double-blind test, and an intra-measurer variability of 100 g for weight and 0.1 cm for height were considered acceptable. The mean of two measurements was used as the final measurement.

2.4. Data Analysis

The data were entered into the database in duplicate. The AnthroPlus® package [26] was used for the anthropometric analysis, and Stata/SE® version 9.0 was used for the remaining statistical analysis.

Descriptive analysis and logistic regression were carried out. Odds ratio (OR) and respective 95% confidence intervals (95% CI) were estimated to investigate the associations of interest. The co-variables included in multivariate (adjusted) models were chosen based on statistical significance (alpha < 0.2) of the univariate (unadjusted) associations between dental crowding and the co-variables, as well as by means of theoretical criteria based on the currently available literature.

In the multivariate analysis, the likelihood ratio test (lrtest) was used to identify potential effect-modifying variables by comparing the unrestricted (model without product terms) and restricted models (model with first order product terms) (alpha = 0.05). For the analysis of confounding variables, the stepwise backward strategy was used to remove variables from the model, keeping those variables (considered confounding variables) that, when removed, produced a difference in individual measurements of the association between nutritional state and malocclusion equal to or greater than 10% [29]. Two different multivariate analyses were performed: one for BMI and another for the height-for-age index.

Estimates took into account the complex selection of the study sample. Standard errors were corrected, design effect (DEFF) was estimated, and the stratification variable and the variable representing the primary sample units were incorporated in the analysis so that the intra-cluster correlation was taken into account [30]. In addition, as the selection probability was not the same for adolescents of different ages and also depended on the school in which they were enrolled—students in smaller schools had a greater probability of being selected—the estimates were weighted by the inverse of the selection probability for each adolescent [30]. The variables age and school were used for the weighting.

3. Results

Three private-sector schools (7.5%) refused to take part in the study and were replaced by other schools selected at random. The return rate for questionnaires sent to adolescents was 100%, and for those sent to parents/guardians, 78.12%. Questionnaires that were not filled out completely represented another source of missing information.

There was a greater prevalence of dental crowding among adolescents with high BMI than among adolescents with normal BMI-for-age (OR = 0.66; 95%CI: 0.45–0.96). No variation in the distribution of dental crowding with nutritional status as measured by height-for-age was observed (OR = 1.13; 95%CI: 0.89–1.42). In addition, bottle feeding for more than one year acted as a statistically significant potential risk factor for dental crowding (OR = 1.42). The following, however, were considered potential protection factors: coming from a low-income family (OR = 0.33), studying at a public school (OR = 0.27) and having a history of breast-feeding for more than 12 months (OR = 0.66) (Table 1).

Table 1.

Frequency distribution and univariate (unadjusted) analysis of the association between dental crowding and demographic, social, economic and behavioral characteristics among adolescents. Brazil, 2004.

VariablesDental crowding
NoYesp-valueDEFFOR***95%CI
n%n%
BMI0.03*1.21
Normal BMI-for-age78077.571179.90.66**0.660.45–0.96
Overweight/Obesity15514.911010.01.00--
Underweight737.68610.11.280.84–1.95
No information177--68--
Height-for-age0.30*1.21
Tall/normal77476.067473.81.00--
Malnourished24024.023326.21.130.89–1.42
No information171--68--
Age0.29*1.24
12–13 years57853.149250.51.00--
14–15 years50746.948349.51.110.91–1.35
Sex0.68*1.64
Male46143.643144.71.00--
Female62456.454455.30.950.76–1.20
Color0.13*2.24
White423.7624.9<0.001**1.00--
Brown74165.570270.20.820.43–1.54
Black29330.820524.90.620.34–1.13
No information19--6--
Family income20.07*1.20
+ 5 m. monthly wages322.1664.5<0.001**1.00--
2–5 m. monthly wages20326.020725.30.450.21–0.99
<2 m. monthly wages51971.945170.20.450.23–0.91
No information1331--251--
Level of Education30.53*1.56
High302.3533.40.02**1.00--
Average38448.236647.00.660.30–1.42
Low37949.533049.60.330.30–1.52
No information1297--226--
Breast-feeding0.53*2.56
Never-up to 12 months61372.558474.71.00--
More than 12 months21827.518725.30.660.47–0.93
No information1254--204--
Bottle feeding0.02*0.99
Never-up to 12 months17417.910113.31.00--
More than 12 months68582.166986.71.421.06–1.92
No information1253--205--
Posterior teeth lost0.61*1.13
No94085,484986.31.00--
Yes14514,612613.70.930.71–1.23
Mouth breathing0.41*1.24
Never- up to 6 years51063,845661.51.00--
More than 6 years29836,229038.51.100.87–1.40
No information1277--229--
Digit sucking0.80*1.71
Never- up to 6 months72887,566286.91.00--
>6 years10412,511013.11.050.71–1.56
No information1253--203--
Pacifier sucking0.19*2.63
Never- up to 6 months77993.971091.51.00--
More than 6 years516.1568.51,430.81–2.51
No information1255--209--
Bruxism0.27*1.76
Never- up to 6 months61473.958577.21.00--
More than 6 years20326.117722.80.840.61–1.16
No information 1268--213--

Weighted estimates for the design effect (DEFF) and for the inverse of the selection probability for the subjects. The prevalence of dental crowding was 47.7% (n=975; 95% CI: 42.0–53.0).

BMI = Body Mass Index; OR = odds ratio; 95% CI = 95% confidence interval.

1Incomplete or blank responses were not taken into consideration in the statistical analysis.

2Minimum monthly wage was R$ 260.00 (U$ 90.1) during the period August to October 2004.

3Level of education: high (higher-level education not completed/postgraduate qualification), average (primary education completed/secondary education completed), low (illiterate/primary education not completed).

*Pearson chi-square test.

**Chi-square test for trend.

***Unadjusted Odds Ratio.

Multivariate analysis of the association between nutritional status, as measured by BMI, and the presence of dental crowding failed to reveal an association after an adjustment had been made for confounding variables (Table 2). Breast-feeding and digit sucking were kept in the multivariate models even without showing statistical significance in the multivariate model due to theoretical reasons.

Table 2.

Odds ratio and the respective 95% confidence intervals for the association between dental crowding and nutritional status (according to Body Mass Index) and family income. Brazil, 2004.

OR95%CIp-value
BMI
Overweight/Obesity0.85**0.44–1.670.64
Normal BMI-for-age1.00----
Underweight1.36**0.59–3.150.45
Family income*
+ 5 minimum monthly wages1.00----
2–5 minimum monthly wages0.42***0.16–1.140.08
<2 minimum monthly wages0.35***0.14–0.940.03

BMI = Body Mass Index; OR = odds ratio; 95%CI = 95% confidence interval.

*Minimum monthly wage was R$ 260.00 (U$ 90.1) during the period August to October 2004.

**Adjusted for family income, color, duration of breast-feeding and bottle feeding, digit sucking and pacifier sucking.

***Adjusted for BMI, color, duration of breast-feeding and bottle feeding, digit sucking and pacifier sucking.

There was an interaction between mouth breathing and malnutrition, as measured by the anthropometric height-for-age index. So the effect of malnutrition on dental crowding was modified by mouth breathing (p-value in the lrtest = 0.04–data not shown). After adjustment for confounding variables, a statistically significant association between low height-for-age and dental crowding (OR = 3.1; 95%CI: 1.56–6.17) was only observed among adolescents with a history of mouth breathing for a longer time (until the age of 6 or longer) (Table 3).

Table 3.

Odds ratio for dental crowding and the respective 95% confidence intervals for combined nutritional status (according to height-for-age) and history of mouth breathing. Brazil, 2004.

OR*95%CIp-value
No history of mouth breathing or a history of mouth breathing up to 6 years of age.1.280.78–2.090.32
A history of mouth breathing until after 6 years of age.3.101.56–6.09<0.001

OR = odds ratio; 95% CI = 95% confidence interval.

*Adjusted for color, family income, duration of breast-feeding and bottle feeding, history of digit sucking and pacifier sucking.

4. Discussion

We failed to find an association between underweight and crowding in permanent dentition. However, we did observe an association between low height-for-age and this orthodontic problem. This association was only observed among those that had breathed through the mouth for a long period, even after adjustment for family income, skin color, duration of breast-feeding, duration of bottle-feeding and a history of digit sucking.

There is some evidence in animal models that support the hypothesis of association between malnutrition and malocclusion using pigs [19,20] and rats [21]. The authors observed that dietary deficiencies of protein and calorie have effects on the reduction of the growth of jaws and of the space available for the teeth in these animals, resulting on increase of crowding in the experimental animals [19,20]. It may indicate that malnutrition changes the growth pattern of the bones of the skeleton, including those of the face and oral cavity.

To our knowledge no studies investigating this relationship in adolescents or adults have been published to date in humans. Only one study has been carried out, and this found an association between underweight and an increased chance of dental crowding in children aged 3 to 5 years with deciduous teeth but failed to find a relationship with low height-for-age [4]. We believe that the divergence between these findings can be explained primarily by the fact that the study subjects belonged to different age groups and were therefore exposed to nutritional deprivation for different lengths of time at different periods during craniofacial growth and development. Thus, children up to 5 years of age may not have been exposed to nutritional deprivation long enough for this to be reflected in maxillomandibular growth, as peak growth in these bone structures occurs at around 6 to 14 years of age in girls and 12 to 18 years in boys [31]. Consequently, the effects of mandibular or maxillary growth deficiency on dental crowding cannot be satisfactorily evaluated before the age of five.

Another plausible explanation is that the sample in the previous study was limited to children in public schools, who are worst off socioeconomically, making it impossible to provide a suitable contrast for this variable, which is considered important in predicting oral health [32]. Accordingly, when the estimates for the variables related to socioeconomic factors were adjusted in the present study, confounding was observed, and the association between underweight and crowding disappeared and the association between low height-for-age and dental crowding was revealed instead. This result agrees with the study hypothesis, as BMI alone is unsuitable for evaluating the chronic consequences of malnutrition in oral health [33], whereas the indicator height-for-age reflects the individual’s prior health and any diseases they have contracted and is thus a better marker for poor living standards, repeated infections during childhood and chronic food deprivation over longer periods of time

Irrespective of these divergences, the results of the present study show the association between low height-for-age and dental crowding and confirm the deleterious effects of mouth breathing on teeth occlusion, as also reported by other researchers [5,34]. Nutritional status has been associated with various oral health problems [13,10,35,36]. To our knowledge, however, this is the first study to find an association between linear deficit and dental crowding.

The mechanisms that might explain this relationship have yet to be fully clarified. One line of reasoning is based on the restricted growth and development of bones in general (and of the bones of the face in particular) in the presence of malnutrition accompanied by stunting. While this relationship has been suggested by a number of investigators, their conclusions are based on studies using small samples, for which the details of the methodology used were not described in full, preventing a more detailed analysis of the results. These studies suggest that stunting could be reflected in, for example, the height of the mandible [15], the height of the lower face and dental and skeletal ages [6,14,16,17, 37].

It is thus reasonable to hypothesize that low height-for-age can be associated with the restricted growth/development of the bones of the face and can change the amount of space available for permanent teeth to erupt in, rendering the association observed in this study more biologically plausible, as shown in animal studies [1921].

This association also highlights the fact that oral habits modify the effect of malnutrition on dental crowding. The interaction found is plausible since both mouth breathing and malnutrition theoretically have the potential to affect the pattern of bone growth. Perhaps the chronic malnutrition renders the skeleton more susceptible to the action of other environmental factors. Mouth breathing is one of the local factors that have a more adverse effect on dental occlusion [5], insofar as the absence of the flow of air through the nasal cavity and the muscular imbalance brought about by breathing through the mouth can result in insufficient vertical growth of the maxilla and mandible [34,38] as well as inadequate transverse growth in these bones [39], which is reflected in a lack of space for teeth to erupt in.

It is also possible that crowding may be indirectly related to nutritional status by means of impaired odontogenesis, leading to delayed dental eruption [6,14,16,40] and an increased incidence of caries [36,37], with a consequent loss of teeth. Such events could compromise the shape of the dental arch [41] and be reflected in maxillomandibular growth in the form of insufficient masticatory stimulus. Individuals who lose their deciduous teeth early because of caries could be more susceptible to tooth migration and occlusion problems, such as dental crowding [42]. The loss of permanent teeth, in contrast, could have the opposite effect, increasing the length of alveolar ridge available for teeth to occupy, thereby reducing crowding [43]. As premature loss of these dental elements usually occurs among populations with a low income and poor level of education [44], dental crowding can be expected to have a greater prevalence in adolescents whose families are financially better off, as observed in this study.

This reasoning is in line with the functional matrix hypothesis [45], according to which the face grows in response to functional needs throughout an individual’s life. The shape of the dental arch would thus be strongly influenced by oral functions, by vertical growth of the alveolar processes in response to the stimulus of dental eruption [41] and by the muscular pressure exerted on these tissues, whereas the loss of teeth would adversely affect this process, highlighting the importance of environmental factors in the arrangement of teeth and the relationship between the bones in the maxillomandibular complex.

The study has a number of strengths: its pioneering nature; the biological plausibility of the association observed; the use of diagnostic criteria for malocclusion validated and recommended by international bodies; the use of anthropometric indicators reflecting both current body composition and events since the very early period of an individual’s life that limited physical growth; the carefully performed statistical analysis; and the accuracy of the estimates. However, some drawbacks make caution necessary when analyzing our results.

Despite being suitable for investigating associations between variables, the cross-sectional design used here is unsuitable for inferring causality and is prone to recall bias when individuals are attempting to remember prior exposures. However, this may have not been an important study limitation since both explanatory and response variables were measured objectively. However, recall bias may have affected some confounding variables. Nevertheless, by using the height-for-age indicator the supposition that there has been prior exposure holds, even in a cross-sectional study. In addition, the use of relatively broad cut-off points for some of the main co-variables helps to reduce the margin of error during classification as a result of memory bias. Furthermore, in an attempt to quantify this error, information was collected from two different sources: the student and the mother/guardian. The concordance (kappa) between the information from these two sources was considered good and varied from 90.72% (nail-biting) to 99.37% (level of education of the head of the family).

Despite the use of self-completed questionnaires in an attempt to reduce embarrassment and minimize errors due to incorrect answers or unanswered questions, especially in relation to oral habits and socioeconomic conditions, our efforts may not have been completely successful, as these variables had the highest rates of unanswered questions, particularly among adolescents in private schools, and may have led to biased estimates.

The variable mouth breathing (presence and duration) was defined based on reports from parents/guardians and not by experts (the gold standard criterion). So, it was subject to classification bias. However, some recent studies have validated and recommended the use of self-reported morbidity as an important diagnostic tool in epidemiological studies [4648]. Analysis of the validity of this information, when compared to other methods, has shown high specificity and satisfactory sensitivity and kappa [48]. Moveover, even using a subjective criterion, it was possible to record the deleterious effects of mouth breathing in the occurrence of malocclusion (crowding), which is consistent with other studies that point out the deleterious effects of mouth breathing in the growth and development of facial structures [5,34,38,48].

Lastly, the theoretical model used in this study proved to have little explanatory value, suggesting that other variables, such as genetic inheritance, need to be included in future multivariate analyses. So, considering that the dental crowding is one of the most important malocclusions that predicts the orthodontic treatment need, especially due to its impact on the facial aesthetic, the study of the factors associated with the high prevalence of dental crowding have contribution to health public.

5. Conclusions

It is reasonable to suggest that poor health and nutrition are related to crowding in permanent dentition among mouth-breathing adolescents. Therefore, policy actions aimed at reducing low height-for-age and unhealthy oral habits are strongly recommended in order to reduce malocclusion. However, due to the limitations of this study, further studies are needed to increase the consistency of these findings and improve understanding of the subject.

Acknowledgments

The authors would like to thank the National Council for Scientific and Technological Development (CNPq) for providing a doctoral fellowship (No. 140779/2003–5); the State of Bahia Research Foundation (FAPESB) for financing the study (grant No. 056/04); the State of Maranhão Research Foundation (FAPEMA) for the Maranhão Talent award (No. 01013/08); the undergraduate students on the nutrition and dentistry courses at the Federal University of Bahia; the statistician Sandra Pinheiro; and the UFBA Institute of Collective Health.

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FAQs

How does malnutrition affect the teeth? ›

Your teeth will absorb the good nutrients as a source of protection against acid and bacteria. When you are malnourished, these acids and bacteria in your mouth can take over all your teeth and cause tooth decay and many other oral health issues.

What are oral manifestations of malnutrition? ›

Nutritional deficiencies and unhealthy habits can cause or contribute to oral pathoses such as scurvy, cleft palate, enamel hypoplasia, poor mineralization, caries, squamous cell carcinoma, and others.

What is the association between malnutrition and oral health status? ›

Poor oral health can cause oral pain, chewing problems, periodontal disease, and tooth loss, which have a negative impact on nutritional intake, leading to poor nutritional status and risk of malnutrition.

Can malnutrition lead to dental caries? ›

Malnutrition is prevalent in the U.S. and can cause oral complications like tooth loss and decay.

Which deficiency causes dental problems? ›

Vitamin D plays a key role in bone and tooth mineralization, and when levels are unregulated it can lead to the “rachitic tooth”, which is a defective and hypomineralized organ highly susceptible to fracture and decay [35,36].

What specific nutritional deficiencies cause the most damage to the oral cavity? ›

Folate and B complex vitamins

A deficiency in one is likely to be accompanied by deficiencies in others. Although they may be accompanied by disparate systemic signs, deficiencies in B2, B3, B6, and B12 will typically manifest in the oral cavity as stomatitis, glossitis, and oral ulcers.

What are the three most common signs of malnutrition? ›

Signs and symptoms of malnutrition

a low body weight – people with a body mass index (BMI) under 18.5 are at risk of being malnourished (use the BMI calculator to work out your BMI) a lack of interest in eating and drinking. feeling tired all the time. feeling weak.

What are 4 signs of malnutrition? ›

Other symptoms of malnutrition include:
  • reduced appetite.
  • lack of interest in food and drink.
  • feeling tired all the time.
  • feeling weaker.
  • getting ill often and taking a long time to recover.
  • wounds taking a long time to heal.
  • poor concentration.
  • feeling cold most of the time.

What are the 6 clinical characteristics of malnutrition? ›

3.2. Criteria selected for malnutrition diagnosis
  • Weight loss.
  • Low body mass index (BMI)
  • Reduced muscle mass.
  • Reduced food intake or assimilation.
  • Disease burden/inflammation.
Mar 28, 2019

What two key groups are at risk of malnutrition? ›

Women, infants, children and adolescents are at the highest risk of malnutrition. Optimizing nutrition early in life – including the 1000 days from conception to a child's second birthday – ensures the best possible start in life, with long-term benefits.

What are the two groups of conditions caused by malnutrition? ›

undernutrition, which includes wasting (low weight-for-height), stunting (low height-for-age) and underweight (low weight-for-age); micronutrient-related malnutrition, which includes micronutrient deficiencies (a lack of important vitamins and minerals) or micronutrient excess; and.

What is the relationship between dentistry and nutrition? ›

A bidirectional relationship exists between oral health and diet and nutrition. Diet and nutrition affect the health of the tissues in the mouth; and the health of the mouth affects nutrients consumed. The consumption of sugars has been associated with an increased risk of developing dental caries.

Can mouth problems be caused by vitamin deficiency? ›

Mouth ulcers or cracks in the corners of the mouth

Lesions in and around the mouth may partly be linked to an insufficient intake of certain vitamins or minerals. For instance, mouth ulcers, also commonly referred to as canker sores, are often the result of deficiencies in iron or B vitamins.

Why do so many modern humans suffer from tooth crowding and malocclusion? ›

The causes of dental crowding are not fully understood, but it may result from an evolutionary trend towards reduced facial volume, without a proportional reduction in tooth sizes. Most previous studies conducted among modern humans have revealed a very low or non-existent correlation between tooth size and jaw size.

What are the symptoms of vitamin deficiency in teeth? ›

A calcium deficiency, also called hypocalcemia, can also increase your risk of tooth decay and general tooth brittleness. The average adult should consume a large percentage of calcium a day to ward off calcium deficiency.

What are the three major dental problems? ›

Gum disease. Root infection. A cracked or broken tooth.

Can B12 deficiency cause teeth problems? ›

Vitamin B12 deficiency may cause an increase in prevalence of dental caries and gingival diseases in children.

What are the most common vitamin and mineral deficiencies among the malnourished? ›

Iron deficiency is the most common form of micronutrient malnutrition globally, according to the World Health Organization (WHO). In the United States, one in six women is iron deficient during pregnancy; deficiency is higher among non-Hispanic blacks and Hispanics. Iron deficiency is a leading cause of anemia.

What are three serious conditions that can result from malnutrition? ›

It can lead to serious health issues, including stunted growth, eye problems, diabetes and heart disease. Malnutrition affects billions of people worldwide.

What is the best indicator of malnutrition? ›

The indicators stunting, wasting, overweight and underweight are used to measure nutritional imbalance; such imbalance results in either undernutrition (assessed from stunting, wasting and underweight) or overweight.

Where do signs of malnutrition most commonly appear on the body? ›

Skin and hair becomes dry. Skin may appear dry, and flaky and hair may turn dry, lifeless, dull and appear like straw. Nails may appear brittle and break easily. Some patients suffer from persistent diarrhea or long term constipation.

What are red flags of malnutrition? ›

Malnutrition Warning Signs

Lack of muscle mass. Swollen stomach (called Kwashiorkor) Fatigue and low energy levels. Lack of growth and low body weight (in children)

What is the fastest way to correct malnutrition? ›

Treating malnutrition
  1. Eat 'little and often' – 3 small meals a day with 2-3 snacks in-between meals.
  2. Include protein at each meal such as meat, fish, chicken, eggs, beans or lentils.
  3. Avoid low fat, sugar-free, diet foods and drinks for example skimmed milk.
May 17, 2021

What is the first stage of malnutrition? ›

During the first stage of starvation, blood glucose levels are maintained through the production of glucose from proteins, glycogen and fats.

What lab tests show malnutrition? ›

The most helpful laboratory studies in assessing malnutrition in a child are hematological studies and laboratory studies evaluating protein status: Hematological studies should include a CBC count with RBC indices and a peripheral smear.

What lab values show malnutrition? ›

Historically, serum proteins — albumin, prealbumin (PAB), transferrin, and retinol-binding protein (RBP) — were used to measure malnutrition. C-reactive protein (CRP), total lymphocyte count (TLC), and serum total cholesterol are not serum proteins but sometimes are used as indicators of malnutrition.

What are 5 effects of malnutrition? ›

Consequences of malnutrition
  • Muscle function. Weight loss due to depletion of fat and muscle mass, including organ mass, is often the most obvious sign of malnutrition. ...
  • Cardio-respiratory function. ...
  • Gastrointestinal function. ...
  • Immunity and wound healing. ...
  • Psychosocial effects.

What is the root cause of malnutrition? ›

Malnutrition (undernutrition) is caused by a lack of nutrients, either as a result of a poor diet or problems absorbing nutrients from food.

How does malnutrition affect the brain? ›

BRAIN: Nutrient deficiencies may speed up the rate at which your brain loses neurons, which can impair your speech, coordination, and memory.

How long can you live malnourished? ›

With no food and no water, the maximum time the body can survive is thought to be about one week . With water only, but no food, survival time may extend up to 2 to 3 months. Over time, a severely restricted food intake can reduce the lifespan.

What are the two immediate causes for malnutrition? ›

The causes of malnutrition are at different levels. The immediate causes are inadequate dietary intake and disease. Inadequate dietary intake and diseases are caused by food insecurity, inadequate care for women and children, insufficient health services, and unsanitary environments.

What is the most important cause of malnutrition? ›

Poverty is the number one cause of malnutrition in developing countries. Often times, families living in poverty lack access to fresh fruits and vegetables.

How are teeth affected by diet and nutrition? ›

Unhealthy diet and poor nutrition affect the teeth and growth of the jaws during development and later during the life-course. The most significant effect of diet is in the mouth, particularly in the development of dental caries (Fig. 1 and 2) and enamel erosion.

Which nutrient are most likely to cause dental caries? ›

Frequent consumption of simple carbohydrates, primarily in the form of dietary sugars is significantly associated with increased dental caries risk.

What is the link between nutrition and a child's dental health? ›

Too many carbohydrates, sugars (for example, from cake, cookies, candies, milk, fruit juice, and other sugary foods and beverages), and savory foods and starches (for example, pretzels and potato chips) can cause tooth decay. How long carbohydrates remain on the teeth is the main culprit that leads to tooth decay.

What diseases can poor oral health cause? ›

Significant associations between oral health status and a number of systemic diseases have been established, including, but not limited to, cardiovascular diseases, Alzheimer's disease and dementia, obesity, diabetes and metabolic disorders, rheumatoid arthritis, and several cancers.

What vitamin is deficient in mouth cracked corners? ›

1: Cracks at the corners of your mouth. The Deficiency: Iron, zinc, and B vitamins like niacin (B3), riboflavin (B2), and B12. "It's common if you're a vegetarian to not get enough iron, zinc, and B12," Blum says.

What vitamin is lacking in a person who has weak bones and teeth? ›

Vitamin D is one of many vitamins your body needs to stay healthy. It plays a crucial role in maintaining the balance of calcium in your blood and bones and in building and maintaining bones. More specifically, you need vitamin D so your body can use calcium and phosphorus to build bones and support healthy tissues.

What happens if you don't fix teeth crowding? ›

Crowding makes proper oral hygiene harder, so over time, this can lead to bacteria growth and excessive plaque build-up, which has serious consequences for your health. It's important to address dental crowding as soon as you can, to straighten the teeth and achieve a healthy smile.

Does teeth crowding get worse as you age? ›

Yes! As we get older, the crowding of our teeth (especially the lower front teeth) does usually worsen. This is due to normal tooth up-righting over time. With or without orthodontic treatment, teeth continue to move when we are adults.

What can overcrowding of teeth lead to? ›

In the most severe cases of crowding where dental hygiene is difficult, the patient may end up suffering from inflammation of the gums and other periodontal diseases. The enamel and teeth wear out and deteriorate more quickly. The overlap can also lead to more serious occlusion problems.

What are the oral manifestations of protein deficiency? ›

Protein deficiency results in an increased susceptibility to dental caries, suggesting that oral host-defense properties are compromised. An important component of oral host defense is salivary gland function, which is affected by both protein deficiency and diet consistency.

What are oral manifestations of vitamin D deficiency? ›

Lack of vitamin D can lead to dental caries, and weak or brittle teeth that easily break, chip, and crack. A controlled study made up of 2,827 children found a reduction of 47% in cavities of the children who received vitamin D supplements.

What are oral manifestations of disease? ›

Oral manifestations of systematic disease are signs and symptoms of disease occurring elsewhere in the body detected in the oral cavity and oral secretions. High blood sugar can be detected by sampling saliva.

What is the primary manifestation of malnutrition? ›

Undernutrition manifests in four broad forms: wasting, stunting, underweight, and micronutrient deficiencies. Wasting is defined as low weight-for-height. It often indicates recent and severe weight loss, although it can also persist for a long time.

What are the three signs of protein deficiency? ›

Signs and symptoms of protein deficiency
  • Skin, hair and nail problems. Protein deficiency may leave its mark on the skin, hair and nails, all of which are largely made of protein. ...
  • Loss of muscle mass. ...
  • Increased risk of bone fractures. ...
  • Bigger appetite and increased calorie intake.
Nov 30, 2018

What are two common diseases that result from protein deficiencies? ›

There are two main syndromes associated with protein deficiencies: Kwashiorkor and Marasmus. Kwashiorkor affects millions of children worldwide.

What are 3 main issues that protein deficiencies can lead to? ›

And over time, a lack of protein can make you lose muscle mass, which in turn cuts your strength, makes it harder to keep your balance, and slows your metabolism. It can also lead to anemia, when your cells don't get enough oxygen, which makes you tired.

Does lack of calcium affect teeth? ›

Low calcium can also lead to tooth decay and cavities forming on teeth, particularly for children. When teeth decay, this can lead to enamel breaking down, creating damage to the surface of the teeth and causing acid reflux. When this happens, you may eventually experience tooth loss.

Can vitamin deficiency cause mouth issues? ›

Vitamin B deficiency can cause stomatitis (inflammation and pain of the mouth) or glossitis (inflammation and pain of the tongue) or get oral ulcers. These issues are more common in the elderly, those dealing with alcoholism, and individuals with vegetarian/vegan diets.

What are the two 2 most common disease of the mouth? ›

Some of the most common diseases that impact our oral health include cavities (tooth decay), gum (periodontal) disease, and oral cancer.

Which systemic disease has oral manifestation? ›

The most significant diseases indicated as having an oral systemic connection are cardiovascular disease, pulmonary disease, diabetes, orthopedic implant failure and kidney disease. Problems encountered in fetal development have also been associated with oral manifestations.

What are 5 diseases caused by malnutrition? ›

The following is a list of diseases caused by malnutrition:
  • Kwashiorkor. This is one of the most acute malnutrition of proteins in the world. ...
  • Marasmus. This disease is caused by the very severe lack of protein and calories. ...
  • Anemia. The most common illness which is caused by malnutrition. ...
  • Mumps. ...
  • Vitamin Deficiency.
Jan 2, 2017

What are two signs that are used to classify severe malnutrition? ›

The main diagnostic features are:
  • weight-for-length/height < -3SD (wasted) or.
  • mid-upper arm circumference < 115 mm or.
  • oedema of both feet (kwashiorkor with or without severe wasting).

References

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