IMPORTANCE: Universal screening to identify unfavorable lipid levels is recommended for US children aged 9 to 11 years and adolescents aged 17 to 21 years (hereafter, young adults); however, screening benefits in these individuals have been questioned. Current use of lipid screening and prevalence of elevated lipid measurements among US youths is not well understood. OBJECTIVE: To investigate the prevalence of ambulatory pediatric lipid screening and elevated or abnormal lipid measurements among US screened youths by patient characteristic and test type. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the IQVIA Ambulatory Electronic Medical Record database and included youths aged 9 to 21 years with 1 or more valid measurement of height and weight during the observation period (2018-2021). Body mass index (BMI) was calculated and categorized using standard pediatric BMI percentiles (9-19 years) and adult BMI categories (≥20 years). The data were analyzed from October 6, 2022, to January 18, 2023. MAIN OUTCOMES AND MEASURES: Lipid measurements were defined as abnormal if 1 or more of the following test results was identified: total cholesterol (≥200 mg/dL), low-density lipoprotein cholesterol (≥130 mg/dL), very low-density lipoprotein cholesterol (≥31 mg/dL), non-high-density lipoprotein cholesterol (≥145 mg/dL), and triglycerides (≥100 mg/dL for children aged 9 years or ≥130 mg/dL for patients aged 10-21 years). After adjustment for age group, sex, race and ethnicity, and BMI category, adjusted prevalence ratios (aPRs) and 95% CIs were calculated. RESULTS: Among 3 226 002 youths (23.9% aged 9-11 years, 34.8% aged 12-16 years, and 41.3% aged 17-21 years; 1 723 292 females [53.4%]; 60.0% White patients, 9.5% Black patients, and 2.4% Asian patients), 11.3% had 1 or more documented lipid screening tests. The frequency of lipid screening increased by age group (9-11 years, 9.0%; 12-16 years, 11.1%; 17-21 years, 12.9%) and BMI category (range, 9.2% [healthy weight] to 21.9% [severe obesity]). Among those screened, 30.2% had abnormal lipid levels. Compared with youths with a healthy weight, prevalence of an abnormal result was higher among those with overweight (aPR, 1.58; 95% CI, 1.56-1.61), moderate obesity (aPR, 2.16; 95% CI, 2.14-2.19), and severe obesity (aPR, 2.53; 95% CI, 2.50-2.57). CONCLUSIONS AND RELEVANCE: In this cross-sectional study of prevalence of lipid screening among US youths aged 9 to 21 years, approximately 1 in 10 were screened. Among them, abnormal lipid levels were identified in 1 in 3 youths overall and 1 in 2 youths with severe obesity. Health care professionals should consider implementing lipid screening among children aged 9 to 11 years, young adults aged 17 to 21 years, and all youths at high cardiovascular risk.

INTRODUCTION: Improving hypertension control is a national priority. Electronic health record data have the potential to augment traditional surveillance systems. This study aimed to assess hypertension prevalence and control at the state level using a previously established electronic health record-based phenotype for hypertension. METHODS: Adult patients (N=11,031,368) were included from the IQVIA ambulatory electronic medical record-U.S. 2019 data set. IQVIA ambulatory electronic medical record comprises electronic health records from >100,000 providers and includes patients from every U.S. state and Washington DC. Authors compared hypertension prevalence and control estimates against those from the Behavioral Risk Factor Surveillance System 2019. Results were age-standardized and stratified by state and sociodemographic characteristics. Statistical analyses were conducted in 2022-2023. RESULTS: IQVIA ambulatory electronic medical record-U.S. patients had a median age of 55 years, and 56.7% were women. Overall age-standardized hypertension prevalence was higher in IQVIA ambulatory electronic medical record-U.S. (35.0%) than in the Behavioral Risk Factor Surveillance System (29.7%), however, state-level geographic patterns were similar, with the highest burden in the South and Appalachia. Similar patterns were also observed by sociodemographic characteristics in both data sets: hypertension prevalence was higher in older age groups (than younger), men (than women), and Black patients (than other races). Hypertension control varied widely across states: among states with >1% data coverage, control rates were lowest in Nevada (51.1%), Washington DC (52.0%), and Mississippi (55.2%); highest in Kansas (73.4%), New Jersey (72.3%), and Iowa (71.9%). CONCLUSIONS: This study provided the first-ever estimates of hypertension control for all states and Washington DC. Electronic health record-based surveillance could support hypertension prevention and control efforts at the state level.

BACKGROUND: Hypertension is an important risk factor for cardiovascular diseases. Electronic health records (EHRs) may augment chronic disease surveillance. We aimed to develop an electronic phenotype (e-phenotype) for hypertension surveillance. METHODS: We included 11,031,368 eligible adults from the 2019 IQVIA Ambulatory Electronic Medical Records-US (AEMR-US) dataset. We identified hypertension using three criteria, alone or in combination: diagnosis codes, blood pressure (BP) measurements, and antihypertensive medications. We compared AEMR-US estimates of hypertension prevalence and control against those from the National Health and Nutrition Examination Survey (NHANES) 2017-18, which defined hypertension as BP ≥ 130/80mmHg or ≥ 1 antihypertensive medication. RESULTS: The study population had a mean (SD) age of 52.3 (6.7) years, and 56.7% were women. The selected three-criteria e-phenotype (≥1 diagnosis code, ≥2 BP measurements of ≥130/80mmHg, or ≥1 antihypertensive medication) yielded similar trends in hypertension prevalence as NHANES: 42.2% (AEMR-US) vs. 44.9% (NHANES) overall, 39.0% vs. 38.7% among women, and 46.5% vs. 50.9% among men. The pattern of age-related increase in hypertension prevalence was similar between AEMR-US and NHANES. The prevalence of hypertension control in AEMR-US was 31.5% using the three-criteria e-phenotype, which was higher than NHANES (14.5%). CONCLUSIONS: Using an EHR dataset of 11 million adults, we constructed a hypertension e-phenotype using three criteria, which can be used for surveillance of hypertension prevalence and control.

INTRODUCTION: Policies and practices at the local level can help reduce chronic disease risk by providing environments that facilitate healthy decision-making about diet. METHODS: We used data from the 2014 and 2021 National Survey of Community-Based Policy and Environmental Supports for Healthy Eating and Active Living to examine prevalence among US municipalities of policies to support access to healthier food in supermarkets, convenience stores, and farmers markets, as well as policies to support breastfeeding among government employees. Chi-square tests were conducted to compare prevalence estimates from 2021 to 2014 overall and according to municipal characteristics. RESULTS: In 2021, 29% of municipalities had at least 1 policy to encourage full-service grocery stores to open stores, which was not significantly different from 31% in 2014. Prevalence of having at least 1 policy to help corner stores sell healthier foods declined significantly from 13% in 2014 to 9% in 2021. Prevalence of policies providing all local government employees who were breastfeeding breaktime and space to pump breast milk increased significantly from 25% in 2014 to 52% in 2021. The percentage of municipalities that provided 8 or more weeks of paid maternity leave for employees increased significantly from 16% in 2014 to 19% in 2021. CONCLUSION: Prevalence of supports for supermarkets, convenience stores, and farmers markets generally did not increase among US municipalities from 2014 to 2021, while some supports for breastfeeding among municipal employees increased during this time. Opportunities exist to improve municipal-level policies that support healthy eating and breastfeeding among community residents and employees.

IMPORTANCE: Information on the probability of weight loss among US adults with overweight or obesity is limited. OBJECTIVE: To assess the probability of 5% or greater weight loss, 10% or greater weight loss, body mass index (BMI) reduction to a lower BMI category, and BMI reduction to the healthy weight category among US adults with initial overweight or obesity overall and by sex and race. DESIGN, SETTING, AND PARTICIPANTS: This cohort study obtained data from the IQVIA ambulatory electronic medical records database. The sample consists of US ambulatory patients 17 years or older with at least 3 years of BMI information from January 1, 2009, to February 28, 2022. Minimum age was set at 17 years to allow for the change in BMI or weight starting at 18 years. Maximum age was censored at 70 years. EXPOSURES: Initial BMI (calculated as weight in kilograms divided by height in meters squared) category was the independent variable of interest, and the categories were as follows: lower than 18.5 (underweight), 18.5 to 24.9 (healthy weight), 25.0 to 29.9 (overweight), 30.0 to 34.9 (class 1 obesity), 35.0 to 39.9 (class 2 obesity), and 40.0 to 44.9 and 45.0 or higher (class 3 or severe obesity). MAIN OUTCOMES AND MEASURES: The 2 main outcomes were 5% or greater weight loss (ie, a ≥5% reduction in initial weight) and BMI reduction to the healthy weight category (ie, BMI of 18.5-24.9). RESULTS: The 18 461 623 individuals in the sample had a median (IQR) age of 54 (40-66) years and included 10 464 598 females (56.7%) as well as 7.7% Black and 72.3% White patients. Overall, 72.5% of patients had overweight or obesity at the initial visit. Among adults with overweight and obesity, the annual probability of 5% or greater weight loss was low (1 in 10) but increased with higher initial BMI (from 1 in 12 individuals with initial overweight to 1 in 6 individuals with initial BMI of 45 or higher). Annual probability of BMI reduction to the healthy weight category ranged from 1 in 19 individuals with initial overweight to 1 in 1667 individuals with initial BMI of 45 or higher. Both outcomes were generally more likely among females than males and were highest among White females. Over the 3 to 14 years of follow-up, 33.4% of persons with overweight and 41.8% of persons with obesity lost 5% or greater of their initial weight. At the same time, 23.2% of persons with overweight and 2.0% of persons with obesity reduced BMI to the healthy weight category. CONCLUSIONS AND RELEVANCE: Results of this cohort study indicate that the annual probability of 5% or greater weight loss was low (1 in 10) despite the known benefits of clinically meaningful weight loss, but 5% or greater weight loss was more likely than BMI reduction to the healthy weight category, especially for patients with the highest initial BMIs. Clinicians and public health efforts can focus on messaging and referrals to interventions that are aimed at clinically meaningful weight loss (ie, ≥5%) for adults at any level of excess weight.

IMPORTANCE: 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. OBJECTIVE: 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. EXPOSURE: BMI categories. MAIN OUTCOMES AND MEASURES: 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. RESULTS: The sample included 20 876 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. CONCLUSIONS AND RELEVANCE: 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.

Background: Youth with excess weight are at risk of developing type 2 diabetes (T2DM). Guidelines recommend screening for prediabetes and/or T2DM after 10 years of age or after puberty in youth with excess weight who have ≥1 risk factor(s) for T2DM. Electronic health records (EHRs) offer an opportunity to study the use of tests to detect diabetes in youth. Methods: We examined the frequency of (1) diabetes testing and (2) elevated test results among youth aged 10-19 years with at least one BMI measurement in an EHR from 2019 to 2021. We examined the presence of hemoglobin A1C (A1C), fasting plasma glucose (FPG), or oral glucose tolerance test (2-hour plasma glucose [2-hrPG]) results and, among those tested, the frequency of elevated values (A1C ≥6.5%, FPG ≥126 mg/dL, or 2-hrPG ≥200 mg/dL). Patients with pre-existing diabetes (n = 6793) were excluded. Results: Among 1,024,743 patients, 17% had overweight, 21% had obesity, including 8% with severe obesity. Among patients with excess weight, 10% had ≥1 glucose test result. Among those tested, elevated values were more common in patients with severe obesity (27%) and obesity (22%) than in those with healthy weight (8%), and among Black youth (30%) than White youth (13%). Among patients with excess weight, >80% of elevated values fell in the prediabetes range. Conclusions: In youth with excess weight, the use of laboratory tests for prediabetes and T2DM was infrequent. Among youth with test results, elevated FPG, 2hrPG, or A1C levels were most common in those with severe obesity and Black youth.

Background: Data sources for assessing pediatric chronic diseases and associated screening practices are rare. One example is non-alcoholic fatty liver disease (NAFLD), a common chronic liver disease prevalent among children with overweight and obesity. If undetected, NAFLD can cause liver damage. Guidelines recommend screening for NAFLD using alanine aminotransferase (ALT) tests in children ≥9 years with obesity or those with overweight and cardiometabolic risk factors. This study explores how real-world data from electronic health records (EHRs) can be used to study NAFLD screening and ALT elevation. Research Design: Using IQVIA's Ambulatory Electronic Medical Record database, we studied patients 2-19 years of age with body mass index ≥85th percentile. Using a 3-year observation period (January 1, 2019 to December 31, 2021), ALT results were extracted and assessed for elevation (≥1 ALT result ≥22.1 U/L for females and ≥25.8 U/L for males). Patients with liver disease (including NAFLD) or receiving hepatotoxic medications during 2017-2018 were excluded. Results: Among 919,203 patients 9-19 years of age, only 13% had ≥1 ALT result, including 14% of patients with obesity and 17% of patients with severe obesity. ALT results were identified for 5% of patients 2-8 years of age. Of patients with ALT results, 34% of patients 2-8 years of age and 38% of patients 9-19 years of age had ALT elevation. Males 9-19 years of age had a higher prevalence of ALT elevation than females (49% vs. 29%). Conclusions: EHR data offered novel insights into NAFLD screening: despite screening recommendations, ALT results among children with excess weight were infrequent. Among those with ALT results, ALT elevation was common, underscoring the importance of screening for early disease detection.

OBJECTIVE: Many U.S. youth experienced accelerated weight gain during the early COVID-19 pandemic. Using an ambulatory electronic health record dataset, we compared children's rates of BMI change in three periods: prepandemic (January 2018-February 2020), early pandemic (March-December 2020), and later pandemic (January-November 2021). METHODS: We used mixed-effects models to examine differences in rates of change in BMI, weight, and obesity prevalence among the three periods. Covariates included time as a continuous variable; a variable indicating in which period each BMI was taken; sex; age; and initial BMI category. RESULTS: In a longitudinal cohort of 241,600 children aged 2-19years with 4 BMIs, the monthly rates of BMI change (kg/m(2) ) were 0.056 (95%CI: 0.056, 0.057) prepandemic, 0.104 (95%CI: 0.102, 0.106) in the early pandemic, and 0.035 (95%CI: 0.033, 0.036) in the later pandemic. The estimated prevalence of obesity in this cohort was 22.5% by November 2021. CONCLUSIONS: In this large geographically-diverse cohort of U.S. youth, accelerated rates of BMI change observed during 2020 were largely attenuated in 2021. Positive rates indicate continued weight gain rather than loss, albeit at a slower rate. Childhood obesity prevalence remained high, which raises concern about long-term consequences of excess weight and underscores the importance of healthy lifestyle interventions. This article is protected by copyright. All rights reserved.