北部战区总医院700例3～6岁儿童乳牙患龋影响因素分析及与龋活跃性检测的相关性分析

Influencing factors of deciduous caries in 700 children aged 3-6 years at the General Hospital of Northern Theater Command of Chinese People's Liberation Army and their correlation with caries activity

摘要:

目的 探讨北部战区总医院3～6岁儿童乳牙患龋的影响因素，并分析龋活跃性检测（Cariostat值）与患龋风险的关联性，为儿童龋病防控提供科学依据。方法 回顾性分析2024年8月—2025年5月北部战区总医院就诊的700例3～6岁疑似乳牙患龋患儿。根据是否患龋将患儿分为患龋组（323例）与未患龋组（377例）。统计患儿患龋情况。收集患儿一般资料，通过对家长问卷调查患儿饮食偏好、患儿及家长卫生生活习惯、行为习惯、饮食习惯等情况。收集患儿在医院收治时龋活性检测结果龋态值。采用多因素逐步Logistic回归模型分析北部战区总医院儿童乳牙患龋影响因素。采用Spearman法分析影响因素与患儿龋态值的相关性。结果 患龋组高年龄分级比例低于未患龋组，父母月收入<6 000元、母亲未接受过高等教育率、睡前或刷牙后喝奶、吃零食率、过去1年检查过牙齿率、监护人营养KAP得分<18分率、甜饮料摄入频率≥3次/周率、父母未早晚刷牙率、父母未定期检查牙齿率和高龋活性龋态值均高于未患龋组（P <0.05）。多因素逐步Logistic回归分析结果显示，年龄（5岁）［O^R=0.444（95% CI：0.222，0.888）］、年龄（6岁）［O^R=0.158（95% CI：0.056，0.444）］、中低龋活性［O^R=0.127（95% CI：0.033，0.493）］为儿童患龋独立保护因素（P <0.05）。过去1年未检查过牙齿［O^R=5.716（95% CI：2.614，12.498）］、监护人营养KAP得分<18分［O^R=2.110（95% CI：1.065，4.180）］、甜饮料摄入频率≥3次/周［O^R=120.430（95% CI：64.171，226.012）］为儿童患龋独立危险因素（P <0.05）。睡前或刷牙后喝奶、吃零食，甜饮料摄入频率与患儿高龋活性呈正相关（r_s =0.184、0.271，均P <0.05），母亲接受过高等教育与患儿高龋活性呈负相关（r_s =-0.089，P <0.05）。结论 乳牙龋病的发生是多因素交互作用的结果，年龄、家庭社会经济地位及龋活跃性检测值是核心预测指标。

Abstract:

Objective To investigate the influencing factors of deciduous caries in 700 children aged 3-6 years at the General Hospital of Northern Theater Command of Chinese People's Liberation Army and to analyze the association between caries activity (Cariostat value) and caries risk, so as to provide a scientific basis for the prevention and control of dental caries in children.Methods A retrospective analysis was conducted on 700 children aged 3-6 years with suspected deciduous caries who visited our hospital from August 2024 to May 2025. The children were divided into a caries group (n = 323) and a non-caries group (n = 377) according to the presence of caries. General information was collected, and questionnaires completed by parents were used to obtain data on children's dietary preferences, hygiene practices, lifestyle, behavioral habits, and dietary habits. Cariostat values were collected at admission. A multivariable stepwise logistic regression model was used to analyze the influencing factors of deciduous caries. Spearman correlation analysis was performed to assess the relationships between influencing factors and Cariostat values.Results The proportion of children in higher age groups was lower in the caries group than in the non-caries group. The proportions of children with parental monthly income < 6 000 RMB, mothers without higher education, drinking milk before bedtime or after brushing, snacking, dental examination within the past year, caregiver nutrition KAP score < 18, frequent intake of sweet beverages (≥ 3 times/week), parents not brushing teeth morning and evening, parents not undergoing regular dental check-ups, and high caries activity were all higher in the caries group than in the non-caries group (P < 0.05). Multivariable stepwise logistic regression analysis (P = 0.05 for including variables and P = 0.10 for excluding variables) showed that age (5 years) [O^R = 0.444 (95% CI: 0.222, 0.888) ], age (6 years) [O^R = 0.158 (95% CI: 0.056, 0.444) ], and moderate-to-low caries activity [O^R = 0.127 (95% CI: 0.033, 0.493) ] were independent protective factors for deciduous caries (P < 0.05). No dental examination in the past year [O^R = 5.716 (95% CI: 2.614, 12.498) ], caregiver nutrition KAP score < 18 [O^R = 2.110 (95% CI: 1.065, 4.180) ], and frequent intake of sweet beverages (≥ 3 times/week) [O^R = 120.430 (95% CI: 64.171, 226.012) ] were independent risk factors for deciduous caries (P < 0.05). Drinking milk before bedtime or after brushing, snacking, and frequent intake of sweet beverages were positively correlated with high caries activity (r_s = 0.184 and 0.271, both P < 0.05), while maternal higher education level was negatively correlated with high caries activity (r_s = -0.089, P < 0.05).Conclusion Early childhood caries results from multifactorial interactions, with age, family socioeconomic status, and caries activity test values serving as core predictive indicators.