Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
Office of the Director, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia.
JAMA Pediatr. 2023 Aug 1;177(8):827-836. doi: 10.1001/jamapediatrics.2023.2012.
Nearly 40% of US youth aged 2 to 19 years do not have a body mass index (BMI) in the healthy weight category. However, there are no recent estimates for BMI-associated expenditures using clinical or claims data.
To estimate medical expenditures among US youth across all BMI categories along with sex and age groups.
DESIGN, SETTING, PARTICIPANTS: This cross-sectional study used IQVIA's ambulatory electronic medical records (AEMR) data set linked with IQVIA's PharMetrics Plus Claims database from January 2018 through December 2018. Analysis was performed from March 25, 2022, through June 20, 2022. It included a convenience sample of a geographically diverse patient population from AEMR and PharMetrics Plus. The study sample included privately insured individuals with a BMI measurement in 2018 and excluded patients with pregnancy-related visits.
BMI categories.
Total medical expenditures were estimated using generalized linear model regression with γ distribution and log-link function. For out-of-pocket (OOP) expenditures, a 2-part model was used that included logistic regression to estimate the probability of positive expenditures followed by generalized linear model. Estimates were shown with and without accounting for sex, race and ethnicity, payer type, geographic region, age interacted with sex and BMI categories, and confounding conditions.
The sample included 205 876 individuals aged 2 to 19 years; 104 066 were male (50.5%) and the median age was 12 years. Compared with those with healthy weight, total and OOP expenditures were higher for all other BMI categories. Differences in total expenditures were highest for those with severe obesity ($909; 95% CI, $600-$1218) followed by underweight ($671; 95% CI, $286-$1055) compared with healthy weight. Differences in OOP expenditures were highest for those with severe obesity ($121; 95% CI, $86-$155) followed by underweight ($117; 95% CI, $78-$157) compared with healthy weight. Having underweight was associated with higher total expenditures at ages 2 to 5 years and 6 to 11 years by $679 (95% CI, $228-$1129) and $1166 (95% CI, $632-$1700), respectively; having severe obesity was associated with higher total expenditures at ages 2 to 5 years, 6 to 11 years, and 12 to 17 years by $1035 (95% CI, $208-$1863), $821 (95% CI, $414-$1227), and $1088 (95% CI, $594-$1582), respectively.
The study team found medical expenditures to be higher for all BMI categories when compared with those with healthy weight. These findings may indicate potential economic value of interventions or treatments aimed at reducing BMI-associated health risks.
近 40%的美国 2 至 19 岁的年轻人的体重指数(BMI)不在健康体重范围内。然而,使用临床或索赔数据对与 BMI 相关的支出没有最近的估计。
根据所有 BMI 类别、性别和年龄组,估计美国青年的医疗支出。
设计、地点和参与者:这项横断面研究使用了 IQVIA 的门诊电子病历(AEMR)数据集,并与 IQVIA 的 PharMetrics Plus 索赔数据库相关联,时间范围为 2018 年 1 月至 2018 年 12 月。分析于 2022 年 3 月 25 日至 2022 年 6 月 20 日进行。它包括 AEMR 和 PharMetrics Plus 中具有地理位置多样性的患者人群的便利样本。研究样本包括 2018 年进行 BMI 测量的私人保险个体,排除了与妊娠相关的就诊患者。
BMI 类别。
使用具有γ分布和对数链接函数的广义线性模型回归估计总医疗支出。对于自付支出,使用了两部分模型,包括 logistic 回归来估计阳性支出的概率,然后是广义线性模型。显示了包括和不包括性别、种族和民族、支付类型、地理区域、年龄与性别和 BMI 类别相互作用以及混杂条件的估计值。
样本包括 205876 名 2 至 19 岁的个体;其中 104066 名是男性(50.5%),中位年龄为 12 岁。与健康体重者相比,所有其他 BMI 类别者的总支出和自付支出都更高。与健康体重者相比,严重肥胖者的总支出差异最高(909 美元,95%CI,600-1218 美元),其次是消瘦者(671 美元,95%CI,286-1055 美元)。与健康体重者相比,严重肥胖者的自付支出差异最高(121 美元,95%CI,86-155 美元),其次是消瘦者(117 美元,95%CI,78-157 美元)。消瘦与 2 至 5 岁和 6 至 11 岁的总支出增加相关,分别为 679 美元(95%CI,228-1129 美元)和 1166 美元(95%CI,632-1700 美元);严重肥胖与 2 至 5 岁、6 至 11 岁和 12 至 17 岁的总支出增加相关,分别为 1035 美元(95%CI,208-1863 美元)、821 美元(95%CI,414-1227 美元)和 1088 美元(95%CI,594-1582 美元)。
研究小组发现,与健康体重者相比,所有 BMI 类别者的医疗支出都更高。这些发现可能表明,针对降低 BMI 相关健康风险的干预或治疗具有潜在的经济价值。