Biostatistics applied to ODF
Introduction :
Statistics has become an essential discipline in the medical field for clinical and basic research.
It is often encountered during the consultation of bibliographic references, hence the need to understand and possibly criticize the value of the proposed works.
If the orthodontist himself has to undertake a study in which statistics are involved, he must be able to be sure that he understands what the statistician is providing him and to check that the latter has understood it correctly.
- 1. Definition:
Biostatistics is a discipline that uses statistical methods to solve problems in biology and medicine.
It plays an important role in the collection, analysis and interpretation of health data to improve the understanding of diseases and the development of new treatments.
Biostatistics applied to ODF
- 2. Basic concepts:
- Population : This is the set of all individuals for which we seek to determine one or more characteristics, each individual is distinct from the others, very often the population is large.
- The individual : Also called a statistical element or unit, it is the basic elementary entity observed by the statistician. This can be a person, a biological or anatomical unit (patient, dental arch, ear, etc.) .
- Sample : It is a finite-sized subset of a population, a fraction of the population studied of deliberately reduced size. In order for the results to be generalized to the statistical population, the sample must be representative of the latter.
- Representative sample : This is a sample whose composition is consistent with that of the population; it must faithfully reflect its composition and complexity. The simplest way to constitute a representative sample is to draw the subjects of the sample at random from the population.
- The variable (characteristic) : Unlike a constant, a characteristic having the same value for all individuals, a variable necessarily includes more than one modality. It can be: quantitative (SNA Angle, Overbite, etc.) or qualitative (atypical swallowing).
- Modalities : are the different categories that a variable can present.: Sex is a variable with two modalities, male and female, “dichotomous variables” because they are of the “one or the other” type. While variables with more than two modalities, such as “blood group” are called multichotomous.
- 3. Descriptive statistics:
- Definition :
It is a set of tools for describing and analyzing phenomena that can be counted and classified. Its aim is to describe and not to explain. .
It allows data to be collected and put into tables or graphs , the information collected to be synthesized, processed and interpreted in order to facilitate knowledge.
- The variables:
3.2.1 Qualitative variables:
Qualitative variables are non-measurable variables , they have no numerical value, their values are qualities, they are expressed in words.
We distinguish:
- Nominal qualitative variables : (Blood type, sex, eye color.).
- Ordinal qualitative variables : which can be classified in ascending or descending order (level of education: bac+3, bac+4, bac+5, etc.).
3.2.2 Quantitative variables:
Quantitative variables are measurable , they are characterized by numerical values. We distinguish:
- Continuous quantitative variable : it has an infinite number of possible values, between two distinct values, there is always a possible intermediate value. This is the case for all variables that measure physical quantities: height, weight, age, etc.
- Discrete (discontinuous) quantitative variable : it has a finite or countable number of possible values, these values are distinct and separate, no intermediate value is possible. Exp: number of teeth on the arch, heart rate.
- Representation of a statistical series:
3.3.1 Tabular representation:
A table is used to present a set of data in an aggregated, synthetic form. It must be simple , it must contain all the information necessary for its understanding, it is sufficient in itself. .
We distinguish:
- The single-entry statistical table : this is the simplest, it will include two or three columns, the first column will concern the values of the character studied, the second column will include the numbers and the third column for the relative frequencies or percentages.
Biostatistics applied to ODF
- The double-entry statistical table : On the same unit we can observe two or more characteristics.
Distribution of male children in the pediatric department
3.3.2 Graphical representation:
Graphical representation allows data to be presented in a clear and precise visual form and allows for rapid interpretation. of the data.
It gives an overall picture of the results, and provides information on the general appearance shape of the distribution, thus facilitating the interpretation of the data collected.
The chart should be simple, clear and understandable by itself .
Graphical representations depend on the characteristics of the data studied, their type and size:
- Graphic representation in organ pipes : It is made up of disjointed vertical bars or organ pipes (a constant space is kept between two bars).
Biostatistics applied to ODF
Frequency of germs causing surgical site infections
- Representation in the form of a circular diagram “Camembert” : We draw a circle divided into sectors, each sector represents a modality of the variable.
Distribution of patients by sex.
Distribution according to stage of the disease
- Graphical representation in “Bar chart” : It shows the values on the abscissa and the frequencies or numbers on the ordinate.
- Graphical representation “Histogram” : It is made up of contiguous, side-by-side vertical bars ; the numbers are represented on the ordinate and the classes of the variable are represented on the abscissa.
Biostatistics applied to ODF
Distribution of drug addicts by age
- Characterization of ordinal data:
3.4.1 Absolute frequency
Absolute frequency is the number of individuals corresponding to a given modality of a variable. Example: We counted on a set of 180 subjects, the individuals who belonged to the different skeletal classes.
| Class I | Class II | Class III |
| 98 | 52 | 30 |
Description of the orthodontic sample
3.4.2 Relative frequency:
We can define the relative frequencies which are for each class , the ratio of its size to the total number of individuals in the series of measurements. The sum of the relative frequencies is equal to 1. Sometimes, the results are expressed as a percentage.
Class size
Relative frequency = ————————————– x 100
Total workforce
| Class I | Class II | Class III |
| 45% | 29% | 17% |
Relative frequencies expressed as a percentage
3.4.3 Cumulative frequencies:
They are used for ordinal data that exhibit classes . They are calculated for both numbers and relative frequencies.
They allow us to say how many individuals have a value greater or less than a given value.
Example: the distribution of 80 patients received for ODF consultation this month according to age.
Biostatistics applied to ODF
| Age (years) | Absolute frequency | Relative Frequency % | Cumulative frequency % |
| 08 – 10 | 10 | 12.5% | 12.5% |
| 10 – 12 | 50 | 62.5% | 75% |
| 12 – 14 | 20 | 25% | 100% |
Distribution of patients in ODF consultation according to age.
- Position indices:
3.5.1 The average:
The “average” value is equal to the quotient of the sum of all the values in the series by the total number.
Two other position indices are used:
3.5.2 The median
This is the number that divides the statistical series into two parts of the same size.
3.5.3 The mode
The most frequent value of a statistical series is the value(s) of the characteristic whose number is the largest.
- Dispersion parameters:
3.6.1 Variance:
It indicates how the statistical series or random variable is dispersed around its mean or its expectation.
3.6.2 Standard deviation
This is the most used dispersion characteristic because it is the most satisfactory,
- Epidemiological studies:
- Types of studies in epidemiology:
There are 3 types of studies that answer 3 different questions:
- Descriptive studies that seek to describe the health status of the population
- Analytical studies that seek to understand the link between a risk factor and the occurrence of a disease
- Evaluative studies that seek to determine the most effective intervention or treatment among several strategies.
- Pyramid of the level of scientific evidence
Biostatistics applied to ODF
- The statistical test:
- Definition :
It is a test that allows us to compare different parameters (variance, mean); in order to validate or refute a statistical hypothesis , based on a sample taken from a population.
From calculations based on the data from this sample, we will be able to conclude on the initial hypothesis, is it acceptable or refutable .
The statistical test also allows us to know whether the difference between our observed data and the population data is simply due to sampling fluctuation or whether there is a real difference.
- The main tests used:
- X² test (KHI-2) • Ficher test
- Student’s T-test
- ANOVA test
- MacNemar Test
- Kolmogorov-Smirnov test
- Mann-Whitney test
- Frequencies of certain anomalies in ODF:
- Skeletal Class III : Its frequency is low, 2 to 8% of the orthodontic population (DEMOGE).
- Class II/1 : Very common; ¾ of the orthodontic population.
- Class II/2 : Relatively rare, affects 2 to 3% of the general population and does not exceed 10% of the orthodontic population.
- DDM : Affects 50% of the orthodontic population (BOUVET).
- Agenesis : its prevalence varies according to studies from 2.6% to 11.3%,
- Supernumerary tooth : its prevalence varies between 0.15% and 3.9%.
- Cleft lip and alveolar cleft : They are frequent, incidence = 1/1000.
- Conclusion :
Statistics are essential in the medical field, they are used to:
Master reading and understanding biomedical scientific literature, which makes extensive use of statistics.
Allow a critical reading of the articles
Improve the health sector by enabling doctors to follow the guidelines and recommendations resulting from this research for adequate care.