智利aysen地区capitan Prat省Tortel公社15 - 64岁人口龋病史与龋病变量的关系:多变量分析

Natalie Ehremberg Godoy, Diego Morales Montecinos, Marie-Claire Hempel Leyton, Cristian Salgado González, Simone Faleiros Chioca, Gonzalo Rodríguez Martínez, Rodrigo Cabello Ibacache
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引用次数: 1

摘要

龋齿是智利城市和农村地区的一个公共卫生问题。一种简单的评估龋齿风险的方法是龋齿图。它由一个计算机程序组成,该程序测量龋齿疾病的病因,并以图形显示患者的潜在龋齿风险,为实施预防和治疗策略提供信息。目的研究智利Tortel公社15 ~ 64岁人群的龋史与龋谱变量之间的关系。材料和方法对173个个体样本进行观察分析的横断面研究。通过对临床记录和胸片的分析,获得相关信息。采用Stata 11.0统计程序对变量进行多元线性回归(MLR)和逻辑回归(LR)分析。结果smlr分析显示,在模型1中(模型1只包括来自龋齿图计划的变量,不包括氟化物的使用),龋齿图变量与龋齿史、相关疾病(P = 0.032)、龋齿经历(P = 0)和饮食含量(P = 0.031)之间存在显著关系。在模型3中(加入变量“年龄”),龋齿史与龋齿经历(P = 0)、性别(P = 0.007)、年龄(P = 0)之间存在显著相关,其中LR与龋齿史与gt之间存在显著相关;在模型1中,10与龋龄有关(P = 0.002),与龋龄有关(P = 0)。结论患龋经历、性别、年龄与患龋史有显著相关性;10. 根据这些结果,个体年龄越大,累积的损伤就越多。当模型中不包括年龄变量时,龋病经历、相关疾病和饮食内容与龋病史之间也存在这种关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asociación entre las variables del Cariograma e historia de caries en la población de 15 a 64 años de la comuna de Tortel, provincia del Capitán Prat de la xi Región de Aysén, Chile: análisis multivariable

Introduction

Dental caries represent a public health problem in both urban and rural areas of our Chile.

A simple method to evaluate cariogenic risk is the Cariogram. This consists of a computer program that measures etiological factors of dental caries disease, and shows graphically the potential cariogenic risk of a patient, providing information that allows prevention and treatment strategies to be implemented.

Objectives

This study aims to establish the association between Cariogram variables and history of dental caries in the population aged 15 to 64 years from Tortel Commune, XI region, Chile.

Materials and methods

Observational-analytical, cross-sectional study of a sample of 173 individuals.

The information was obtained by analysis of clinical records and Cariogram. The variables were analyzed by multiple linear regression (MLR) and logistic regression (LR) using Stata 11.0 statistical program.

Results

MLR analysis shows a significant relationship in model 1 (which only includes variables from the Cariogram Program, except for the use of fluoride) between Cariogram variables and history of dental caries, related diseases (P = .032), experience of caries (P = 0) and diet content (P = .031). In model 3 (the variable “age” is added), there is a significant relationship between history of caries and experience of caries (P = 0), gender (P = .007), and age (P = 0).

The LR showed a statistically significant relationship between history of caries > 10 and experience of caries (P = .002) in Model 1, and with age (P = 0) in model 3.

Conclusions

There is significant relationship between experience of caries, gender and age with history of caries > 10. Based on these results, the older the individual, the more accumulated damage can be found. This relationship was also found between experience of caries, related diseases and diet content with history of dental caries, when the age variable is not included in the model.

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