Analysis of Race and Ethnicity, Socioeconomic Factors, and Tooth Decay Among US Children.
Analysis of Race and Ethnicity, Socioeconomic Factors, and Tooth Decay Among US Children.
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DOI：
10.1001/jamanetworkopen.2023.18425
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发表时间：
2023-06-01
影响因子：
13.8
通讯作者：
Normand, Sharon-Lise
中科院分区：
文献类型：
--
作者：
Choi, Sung Eun;White, Joel;Mertz, Elizabeth;Normand, Sharon-Lise
哪些因素与美国儿童患蛀牙风险的种族和民族差异有关？这项针对61083名儿童和青少年的队列研究发现，与白色儿童相比，0至5岁的所有其他种族和族裔群体、6至10岁的西班牙裔和黑人儿童以及11至18岁的黑人青少年患蛀牙的风险更高。中介分析显示，个人和社区层面的因素，包括保险和牙科手术类型，解释了蛀牙风险的大多数种族和民族差异。这些发现表明，减少蛀牙的种族和民族差异的努力应该针对不同的个人和社区因素，这取决于年龄，种族和民族群体。这项队列研究评估了种族和民族在蛀牙风险方面的差异，并评估了介导美国儿童中观察到的差异的因素的相对贡献。虽然儿童的种族和民族之间仍然存在巨大的口腔健康差异，但种族，民族和中介因素与口腔健康结果的关联性很差。找出解释这些差异的途径对于制定有效减少这些差异的政策至关重要。测量美国儿童中发生蛀牙风险的种族和民族差异，并量化介导观察到的差异的因素的相对贡献。这项回顾性队列研究使用2014年至2020年美国儿童的电子健康记录来衡量蛀牙风险的种族和民族差异。弹性网络正则化被用来选择变量包括在模型中的医疗条件，牙科手术类型，以及个人和社区层面的社会经济因素。数据分析时间为2023年1月9日至4月28日。儿童的种族和民族。主要结果是诊断乳牙或恒牙中的蛀牙，定义为至少1颗龋齿导致的蛀牙、填充牙或缺失牙。估计了Anderson-Gill模型，一种具有时变协变量的复发性蛀牙事件的时间-事件模型，按年龄组（0-5岁、6-10岁和11-18岁）分层。一个非线性多元加性回归树为基础的中介分析量化的相对贡献的因素所观察到的种族和民族的差异。在61083例基线时年龄为0 - 18岁的儿童和青少年中（平均[SD]年龄，9.9 [4.6]岁; 30 773 [50.4%]女性），2 654名黑人（4.3%），11 213名西班牙裔人（18.4%），42 815名白色人（70.1%），4401人被确定为另一个种族（例如，美洲印第安人，亚洲人，夏威夷人和太平洋岛民）（7.2%）。与其他年龄组相比，在0至5岁的儿童中观察到更大的种族和民族差异（西班牙裔儿童：调整后的风险比[aHR]，1.47; 95% CI，1.40-1.54;黑人儿童：aHR，1.30; 95% CI，1.19-1.42;其他种族儿童：aHR，1.39; 95% CI，1.29-1.49），与白色儿童相比。对于6至10岁的儿童，与白色儿童相比，观察到黑人儿童（aHR，1.09; 95% CI，1.01-1.19）和西班牙裔儿童（aHR，1.12; 95% CI，1.07-1.18）的龋齿风险更高。对于11至18岁的青少年，仅在黑人青少年中观察到更高的蛀牙风险（aHR，1.17; 95% CI，1.06-1.30）。一项中介分析显示，种族和民族与第一次蛀牙时间的关联变得可以忽略不计，除了西班牙裔和其他种族的0至5岁的儿童，这表明中介解释了大部分观察到的差异。保险类型解释了最大比例的差异，范围从23.4%（95%CI，19.8%-30.2%）到78.9%（95%CI，59.0%-114.1%），其次是牙科手术（接受局部氟化物和修复手术）和社区层面的因素（教育程度和地区贫困指数）。在这项回顾性队列研究中，儿童和青少年的保险类型和牙科手术类型解释了与种族和种族相关的首次蛀牙时间差异的大部分。这些发现可用于制定有针对性的策略，以减少口腔健康差异。
What factors are associated with racial and ethnic differences in the risk of developing tooth decay among US children? This cohort study of 61 083 children and adolescents found that compared with White children, all other racial and ethnic groups among those aged 0 to 5 years, Hispanic and Black children among those aged 6 to 10 years, and Black adolescents among those aged 11 to 18 years were at a higher risk of tooth decay. Mediation analysis revealed that individual- and community-level factors, including insurance and dental procedure types, explained most racial and ethnic disparities in the risk of tooth decay. These findings suggest that efforts to reduce racial and ethnic disparities in tooth decay should target different individual- and community-level factors, depending on age and racial and ethnic group. This cohort study assesses racial and ethnic disparities in the risk of developing tooth decay and evaluates relative contributions of factors mediating the observed disparities among US children. While large oral health disparities remain by race and ethnicity among children, the associations of race, ethnicity, and mediating factors with oral health outcomes are poorly characterized. Identifying the pathways that explain these disparities would be critical to inform policies to effectively reduce them. To measure racial and ethnic disparities in the risk of developing tooth decay and quantify relative contributions of factors mediating the observed disparities among US children. This retrospective cohort study used electronic health records of US children from 2014 to 2020 to measure racial and ethnic disparities in the risk of tooth decay. Elastic net regularization was used to select variables to be included in the model among medical conditions, dental procedure types, and individual- and community-level socioeconomic factors. Data were analyzed from January 9 to April 28, 2023. Race and ethnicity of children. The main outcome was diagnosis of tooth decay in either deciduous or permanent teeth, defined as at least 1 decayed, filled, or missing tooth due to caries. An Anderson-Gill model, a time-to-event model for recurrent tooth decay events with time-varying covariates, stratified by age groups (0-5, 6-10, and 11-18 years) was estimated. A nonlinear multiple additive regression tree–based mediation analysis quantified the relative contributions of factors underlying the observed racial and ethnic disparities. Among 61 083 children and adolescents aged 0 to 18 years at baseline (mean [SD] age, 9.9 [4.6] years; 30 773 [50.4%] female), 2654 Black individuals (4.3%), 11 213 Hispanic individuals (18.4%), 42 815 White individuals (70.1%), and 4401 individuals who identified as another race (eg, American Indian, Asian, and Hawaiian and Pacific Islander) (7.2%) were identified. Larger racial and ethnic disparities were observed among children aged 0 to 5 years compared with other age groups (Hispanic children: adjusted hazard ratio [aHR], 1.47; 95% CI, 1.40-1.54; Black children: aHR, 1.30; 95% CI, 1.19-1.42; other race children: aHR, 1.39; 95% CI, 1.29-1.49), compared with White children. For children aged 6 to 10 years, higher risk of tooth decay was observed for Black children (aHR, 1.09; 95% CI, 1.01-1.19) and Hispanic children (aHR, 1.12; 95% CI, 1.07-1.18) compared with White children. For adolescents aged 11 to 18 years, a higher risk of tooth decay was observed only in Black adolescents (aHR, 1.17; 95% CI, 1.06-1.30). A mediation analysis revealed that the association of race and ethnicity with time to first tooth decay became negligible, except for Hispanic and children of other race aged 0 to 5 years, suggesting that mediators explained most of the observed disparities. Insurance type explained the largest proportion of the disparity, ranging from 23.4% (95% CI, 19.8%-30.2%) to 78.9% (95% CI, 59.0%-114.1%), followed by dental procedures (receipt of topical fluoride and restorative procedures) and community-level factors (education attainment and Area Deprivation Index). In this retrospective cohort study, large proportions of disparities in time to first tooth decay associated with race and ethnicity were explained by insurance type and dental procedure types among children and adolescents. These findings can be applied to develop targeted strategies to reduce oral health disparities.
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影响因子：
13.8
作者：
Eberly LA;Garg L;Yang L;Markman TM;Nathan AS;Eneanya ND;Dixit S;Marchlinski FE;Groeneveld PW;Frankel DS
通讯作者：
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影响因子：
5.1
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
158.5
作者：
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通讯作者：
EPSTEIN, AM
影响因子：
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作者：
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通讯作者：
Nelson, AR