Department of Epidemiology and Public Health, University College London, London, UK.
Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia.
J Dent Res. 2024 May;103(5):477-483. doi: 10.1177/00220345241228834. Epub 2024 Mar 19.
Existing studies on multimorbidity have largely excluded oral diseases in multimorbidity prevalence estimates. The reason behind this is somewhat unclear, as chronic oral conditions are highly prevalent, affecting over half the global population. To address this gap, we examined the relationship between social disadvantage and multimorbidity, stratifying by the inclusion and exclusion of oral conditions. For participants aged 30 y and over ( = 3,693), cross-sectional analysis was carried out using the US National Health and Nutrition Survey (2013-2014). Multimorbidity was defined as having 2 or more chronic conditions. Five medical conditions were examined: diabetes, asthma, arthritis, cardiovascular disease, and depression, as well as 4 oral health conditions: caries, periodontal disease, number of teeth, and edentulousness. Education and income poverty ratio were selected as measures of social disadvantage. Multimorbidity prevalence estimates according to social disadvantage were analyzed on an absolute and relative scale using inverse probability treatment weighting (IPTW), adjusting for age, sex, and ethnicity. The inclusion of oral health conditions in the assessment of multimorbidity increased the overall prevalence of multimorbidity from 20.8% to 53.4%. Findings from IPTW analysis demonstrated clear social gradients for multimorbidity estimates stratified by the exclusion of oral conditions. Upon inclusion of oral conditions, the prevalence of multimorbidity was higher across all social groups for both education and income. Stratifying by the inclusion of oral conditions, the mean probability of multimorbidity was 27% (95% confidence interval [CI], 23%-30%) higher in the low-education group compared to the high-education group. Similarly, the mean probability of multimorbidity was 44% (95% CI, 40%-48%) higher in the low-income group. On a relative scale, low education was associated with a 1.52 times (95% CI, 1.44-1.61) higher prevalence of multimorbidity compared to high education. Low income was associated with a 2.18 (95% CI, 1.99-2.39) higher prevalence of multimorbidity. This novel study strongly supports the impact of chronic oral conditions on multimorbidity prevalence estimates.
现有的关于多种疾病的研究在多种疾病的患病率估计中很大程度上排除了口腔疾病。造成这种情况的原因尚不清楚，因为慢性口腔疾病的患病率很高，影响了全球一半以上的人口。为了解决这一差距，我们研究了社会劣势与多种疾病之间的关系，并对包括和不包括口腔疾病的情况进行了分层。对于年龄在 30 岁及以上的参与者（n=3693），我们使用美国国家健康和营养调查（2013-2014 年）进行了横断面分析。多种疾病的定义是同时患有两种或两种以上的慢性疾病。我们检查了五种医学疾病：糖尿病、哮喘、关节炎、心血管疾病和抑郁症，以及四种口腔健康状况：龋齿、牙周病、牙齿数量和无牙。选择教育和收入贫困率作为社会劣势的衡量标准。我们使用逆概率治疗加权（Inverse Probability Treatment Weighting，IPTW）在绝对和相对规模上分析了根据社会劣势的多种疾病患病率估计值，调整了年龄、性别和种族因素。在评估多种疾病时纳入口腔健康状况，将多种疾病的总体患病率从 20.8%增加到 53.4%。通过 IPTW 分析得出的结果表明，在排除口腔状况的情况下，根据社会劣势分层的多种疾病估计值存在明显的社会梯度。在纳入口腔状况后，对于所有社会群体，教育和收入水平越低，多种疾病的患病率越高。在纳入口腔状况的情况下进行分层，与高教育水平相比，低教育水平组的多种疾病的平均概率高 27%（95%置信区间[CI]，23%-30%）。同样，低收入组的多种疾病的平均概率高 44%（95% CI，40%-48%）。在相对规模上，与高教育水平相比，低教育水平与多种疾病的患病率高 1.52 倍（95% CI，1.44-1.61）相关。与高收入相比，低收入与多种疾病的患病率高 2.18 倍（95% CI，1.99-2.39）相关。这项新的研究有力地支持了慢性口腔疾病对多种疾病患病率估计值的影响。
