Related Experiment Video
Updated: Aug 6, 2026

10:46
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Onset and Risk Period of Functional Sound Tooth Loss: A Hyperbolic Tangent Model
1Department of Chemical and Biological Engineering, Inha Technical College, Incheon, Republic of Korea.
International Dental Journal
|July 18, 2026
Summary
A new hyperbolic tangent model accurately predicts age-related tooth loss. It identifies the onset age and duration of the high-risk period for preventive dental care planning.
Area of Science:
- Gerodontology
- Biostatistics
- Epidemiology
Background:
- Existing analyses of age-related tooth loss lack quantification of accelerated loss onset and duration.
- Understanding tooth loss trajectories is crucial for effective preventive dental strategies.
Purpose of the Study:
- To apply a hyperbolic tangent model to functional sound tooth loss data.
- To derive clinically interpretable transition parameters for tooth loss trajectories.
Main Methods:
- A hyperbolic tangent regression model was fitted to normalized tooth loss data from 27,215 Korean adults (2010-2015).
- Data represented 10th, 25th, 50th, and 75th percentile groups.
- Model fit was compared to linear, polynomial, and logistic models using R-squared and AIC.
Main Results:
- The hyperbolic tangent model demonstrated superior goodness of fit (R² = 0.963–0.996) across all percentile groups.
- Peak tooth loss velocity (onset age) ranged from 57.3 to 85.9 years, with high-risk period durations (2c) from 9.8 to 17.6 years.
- Onset age (b-c) varied from 47.4 to 68.3 years, with narrow 95% confidence intervals.
Conclusions:
- The hyperbolic tangent model offers a concise 2-parameter characterization of tooth loss trajectories.
- Identified onset ages and high-risk durations enable percentile-specific risk stratification for dental care.
- Findings provide population-level estimates for oral health planning.
Related Concept Videos
Types of Functions II
Trigonometric and exponential functions are essential mathematical tools used to model distinct types of real-world behavior, particularly in periodic and growth-related phenomena. These functions extend the capabilities of basic algebraic models by capturing recurring cycles and rapid changes across various scientific and engineering contexts.Trigonometric functions, such as sine and cosine, are particularly effective for representing periodic phenomena. Their cyclic behavior makes them...
Exponential and Sinusoidal Signals
The exponential function is crucial for characterizing waveforms that rise and decay rapidly. This continuous-time exponential function is defined using exponential terms with constants α and A. When both constants are real, the function is represented as,
Parametric Survival Analysis: Weibull and Exponential Methods
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Properties of Laplace Transform-II
Time differentiation, convolution, integration, and periodicity are fundamental concepts in analyzing functions and signals over time. Each concept provides a unique perspective on how functions evolve, interact, and repeat, offering essential tools for various scientific and engineering applications.
Time differentiation involves analyzing the rate of change of a function over time. Mathematically, it is the derivative of a function with respect to time. This concept can be likened to tracking...
Time differentiation involves analyzing the rate of change of a function over time. Mathematically, it is the derivative of a function with respect to time. This concept can be likened to tracking...
Teeth
The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin and...
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin and...
Introduction to Exponential Functions
Exponential functions are fundamental in modeling dynamic processes where the rate of change is proportional to the current value. Defined by f(x) = bx, where b is a positive constant not equal to one, they form the basis for describing processes of growth and decay depending on whether the base b is greater than or less than one.Exponential models describe situations where change occurs at a rate proportional to the current amount. These include phenomena such as bacterial proliferation,...

