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OBJECTIVE: Continuous glucose monitoring (CGM) can detect early dysglycemia in older children and adults with presymptomatic type 1 diabetes (T1D) and predict risk of progression to clinical onset. However, CGM data for very young children at greatest risk of disease progression are lacking. This study aimed to investigate the use of CGM data measured in children being longitudinally observed in the Australian Environmental Determinants of Islet Autoimmunity (ENDIA) study from birth to age 10 years. RESEARCH DESIGN AND METHODS: Between January 2021 and June 2023, 31 ENDIA children with persistent multiple islet autoimmunity (PM Ab+) and 24 age-matched control children underwent CGM assessment alongside standard clinical monitoring. The CGM metrics of glucose SD (SDSGL), coefficient of variation (CEV), mean sensor glucose (SGL), and percentage of time >7.8 mmol/L (>140 mg/dL) were determined and examined for between-group differences. RESULTS: The mean (SD) ages of PM Ab+ and Ab− children were 4.4 (1.8) and 4.7 (1.9) years, respectively. Eighty-six percent of eligible PM Ab+ children consented to CGM wear, achieving a median (quartile 1 [Q1], Q3) sensor wear period of 12.5 (9.0, 15.0) days. PM Ab+ children had higher median (Q1, Q3) SDSGL (1.1 [0.9, 1.3] vs. 0.9 [0.8, 1.0] mmol/L; P < 0.001) and CEV (17.3% [16.0, 20.9] vs. 14.7% [12.9, 16.6]; P < 0.001). Percentage of time >7.8 mmol/L was greater in PM Ab+ children (median [Q1, Q3] 8.0% [4.4, 13.0] compared with 3.3% [1.4, 5.3] in Ab− children; P = 0.005). Mean SGL did not differ significantly between groups (P = 0.10). CONCLUSIONS: CGM is feasible and well tolerated in very young children at risk of T1D. Very young PM Ab+ children have increased SDSGL, CEV, and percentage of time >7.8 mmol/L, consistent with prior studies involving older participants. [ABSTRACT FROM AUTHOR]

Advanced hybrid closed-loop (AHCL) therapy with the Medtronic MiniMed™ 780G system improves glycemia; however, the clinical outcomes in younger children remain less established. This pilot study aimed to explore the continuous glucose monitoring (CGM) metrics in very young children on AHCL. Children between 2 and 7 years of age and on insulin pump therapy were recruited. A 2-week phase in manual mode was followed by a 6-week AHCL phase. CGM metrics were analyzed to review glycemic outcomes. Out of 11 participants enrolled [mean (standard deviation [SD]) age 5.3 (0.8) years], 10 completed the study. Time in closed loop was 96.7 (3.9)%. In AHCL, participants had a mean (SD) time in range of 72.6 (7.4)% and spent 3.0 (1.74)% and 0.63 (0.46)% in time <70 and <54 mg/dL, respectively. AHCL is a feasible option for management of young children with type 1 diabetes. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Technology use in type 1 diabetes (T1D) is impacted by socioeconomic status (SES). This analysis explored relationships between SES, glycemic outcomes, and technology use. RESEARCH DESIGN AND METHODS: A cross-sectional analysis of HbA1c data from 2,822 Australian youth with T1D was undertaken. Residential postcodes were used to assign SES based on the Index of Relative Socio-Economic Disadvantage (IRSD). Linear regression models were used to evaluate associations among IRSD quintile, HbA1c, and management regimen. RESULTS: Insulin pump therapy, continuous glucose monitoring, and their concurrent use were associated with lower mean HbA1c across all IRSD quintiles (P < 0.001). There was no interaction between technology use and IRSD quintile on HbA1c (P = 0.624), reflecting a similar association of lower HbA1c with technology use across all IRSD quintiles. CONCLUSIONS: Technology use was associated with lower HbA1c across all socioeconomic backgrounds. Socioeconomic disadvantage does not preclude glycemic benefits of diabetes technologies, highlighting the need to remove barriers to technology access. [ABSTRACT FROM AUTHOR]

Continuous glucose monitoring (CGM) systems are used in therapeutic decisions for diabetes management, however, the impact of body composition on CGM accuracy is not known. Body composition variables (body mass index [BMI], midarm circumference, percentage fat, and impedance) were collected in an observational study designed to determine the accuracy of an investigational Medtronic Guardian™ sensor 3. Seven days of sensor glucose data were analyzed from 112 participants >7 years of age with mean BMI Z score 0.48 (<18 years) and BMI 26.7 kg/m2 (≥18 years). The outcome was the absolute relative difference between the sensor and blood glucose readings. Data were analyzed using generalized estimating equations to account for correlation between repeated measures. No statistically significant associations between measures of body composition and device accuracy were found. Body composition does not have a meaningful impact on the accuracy of CGM systems. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between dietary patterns and ADHD in a population-based cohort of adolescents. Method: The Raine Study is a prospective study following 2,868 live births. At the 14-year follow-up, the authors collected detailed adolescent dietary data, allowing for the determination of major dietary patterns using factor analysis. ADHD diagnoses were recorded according to International Classification of Diseases, 9th Revision coding conventions. Logistic regression was used to assess the relationship between scores for major dietary pattern and ADHD diagnoses. Results: Data were available for 1,799 adolescents, and a total of 115 adolescents had an ADHD diagnosis. Two major dietary patterns were identified: "Western" and "Healthy." A higher score for the Western dietary pattern was associated with ADHD diagnosis (odds ratio = 2.21, 95% confidence interval = 1.18, 4.13) after adjusting for known confounding factors from pregnancy to 14 years. ADHD diagnosis was not associated with the "Healthy" dietary pattern. Conclusion: A Western-style diet may be associated with ADHD. (Contains 3 tables.)

Objective: To explore the impact of missing data on the accuracy of continuous glucose monitoring (CGM) metrics collected for a 2-week period in a clinical trial. Research Design and Methods: Simulations were conducted to examine the effect of various patterns of missingness on the accuracy of CGM metrics as compared with a "complete" data set. The proportion of missing data, the "block size" in which the data were missing, and the missing mechanism were modified for each "scenario." The degree of agreement between simulated and "true" glycemic measures under each scenario was presented as R2. Results: Under all missing patterns, R2 declined as the proportion of missing data increased, however, as the "block size" of missing data increased, the percentage of missing data had a more pronounced effect on the agreement between measures. For a 14-day CGM data set to be considered representative for percentage time in range (%TIR), at least 70% of CGM data should be available over at least 10 days (R2 > 0.9). Skewed outcome measures, such as percentage time below range and coefficient of variation, were more affected by missing data than the less skewed measures (%TIR, percentage time above range, mean glucose). Conclusions: Both the degree and pattern of missing data impact upon the accuracy of recommended CGM-derived glycemic measures. In planning research, an understanding of patterns of missing data in the study population is required to gauge the likely effects of missing data on outcome accuracy. Trial registration number: Australian New Zealand Clinic Trials Registry ACTRN12616000753459. [ABSTRACT FROM AUTHOR]

Aim: To examine the within‐person variability in plasma glucose responses to moderate‐intensity morning exercise in young individuals with type 1 diabetes after overnight fasting and under basal insulin conditions. Methods: In this pilot study, eight participants completed 40 min of moderate‐intensity exercise at 60% V̇O2 peak on three separate days. The within‐person standard deviation (SDw) in plasma glucose response was analysed both during and 1 h after exercise using the two visits per participant most closely matched by pre‐exercise plasma glucose level. Results: When the two closest matched visits per individual were included for analysis, mean (±SD) change in plasma glucose level was −1.8 ± 1.1 mmoL/L during exercise and −0.6 ± 1.0 mmoL/L during recovery, with the SDw of these changes being 0.5 mmol (95% CI 0.2, 0.8) during exercise and 0.8 mmoL/L (95% CI 0.4, 1.3) during recovery. The median intra‐individual difference in plasma glucose level change was 0.3 mmoL/L [IQR 0.1, 0.7] during exercise and 0.8 mmoL/L [IQR 0.4, 1.0] during recovery. Conclusion: Within‐person plasma glucose responses to moderate‐intensity exercise may be reproducible under fasting and basal insulin conditions and similar pre‐exercise plasma glucose levels. This finding may assist the design of future studies investigating both the reproducibility of glycaemic responses to exercise and blood glucose management for individuals with type 1 diabetes. [ABSTRACT FROM AUTHOR]

Objective: To determine if the relationship between meal carbohydrate quantity and the insulin to carbohydrate ratio (ICR) required to maintain glycaemia is linear in people with type 1 diabetes. Methods: We used an open labelled randomized four‐arm cross‐over study design. Participants (N = 31) aged 12–27 years, HbA1c ≤ 64 mmol/mol (8.0%) received insulin doses based on the individual's ICR and the study breakfast carbohydrate quantity and then consumed four breakfasts containing 20, 50, 100 and 150 g of carbohydrate over four consecutive days in randomized order. The breakfast fat and protein percentages were standardized. Postprandial glycaemia was assessed by 5 h continuous glucose monitoring. The primary outcome was percent time in range (TIR) and secondary outcomes included hypoglycaemia, glucose excursion and incremental area under the curve. Statistical analysis included linear mixed modelling and Wilcoxon signed rank tests. Results: The 20 g carbohydrate breakfast had the largest proportion of TIR (0.74 ± 0.29 p < 0.04). Hypoglycaemia was more frequent in the 50 g (n = 13, 42%) and 100 g (n = 15, 50%) breakfasts compared to the 20 g (n = 6, 20%) and 150 g (n = 7, 26%) breakfasts (p < 0.029). The 150 g breakfast glucose excursion pattern was different from the smaller breakfasts with the lowest glucose excursion 0–2 h and the highest excursion from 3.5 to 5 h. Conclusions: A non‐linear relationship between insulin requirement and breakfast carbohydrate content was observed, suggesting that strengthened ICRs are needed for meals with ≤20 and ≥150 g of carbohydrate. Meals with ≥150 g of carbohydrate may benefit from dual wave bolusing. [ABSTRACT FROM AUTHOR]

It is recommended that people with type 1 diabetes should generally aim to achieve glycated hemoglobin (HbA1c) <53 mmol/mol.[1],[2] Likewise, as defined by continuous glucose monitoring (CGM) metrics, the proposed general aims are to spend >70% time-in-range (TIR, 70-180 mg/dL), <4% below 70 mg/dL, <1% below 54 mg/dL, <25% above 180 mg/dL, and <5% above 250 mg/dL.[3] However, the proportion of individuals achieving the goals of CGM metrics among cohorts meeting target HbA1c is not much known. Percentage TIR was higher in participants who met target HbA1c, with less time in hyperglycemia but more time in hypoglycemia than individuals not meeting target HbA1c (Table 1). [Extracted from the article]

Background: The Predictive Low-Glucose Management (PLGM) system suspends basal insulin when hypoglycemia is predicted and reduces hypoglycemia. The aim of this analysis was to explore the characteristics of automated insulin suspension and sensor glucose (SG) responses following PLGM-initiated pump suspension.Research Design and Methods: Children and adolescents with type 1 diabetes used the Medtronic MiniMed™ 640G pump as part of a randomized controlled trial. Data collected on a subgroup of participants on PLGM (suspend before low enabled) from CareLink® Therapy Management Software were analyzed to explore the time and duration of PLGM-initiated pump suspension. Day and nighttime were defined as 06:00 am to 10:00 pm and 10:00 pm to 6:00 am, respectively.Results: There were 20,183 suspend before low events in 8523 days (2.37 events/day). The mean suspend duration was 55.0 ± 32.7 min (day 50.0 ± 30.1, night 71.7 ± 35.1; P < 0.001). Although a 2-h pump suspension was more frequent at night (day 5%, night 18%), a patient-initiated resumption occurred more during day (day 34%, night 12%). SG values did not reach <3.5 and <3 mmol/L in 79% and 91% of the events, respectively. The 2-h SG following pump resumption was higher following autoresumption during the day (day vs. night 9.3 mmol/L vs. 8.4 mmol/L; P < 0.001).Conclusions: Longer suspends and fewer glycemic excursions occur at night compared with day. The higher glycemic daytime excursions could be due to carbohydrate consumption to increase glucose levels and highlights the need for health care professionals to educate patients about carbohydrate intake around pump suspension. [ABSTRACT FROM AUTHOR]

Objective: Short-term studies with automated systems that suspend basal insulin when hypoglycemia is predicted have shown a reduction in hypoglycemia; however, efficacy and safety have not been established in long-term trials.Research Design and Methods: We conducted a 6-month, multicenter, randomized controlled trial in children and adolescents with type 1 diabetes using the Medtronic MiniMed 640G pump with Suspend before low (predictive low-glucose management [PLGM]) compared with sensor-augmented pump therapy (SAPT) alone. The primary outcome was percentage time in hypoglycemia with sensor glucose (SG) <3.5 mmol/L (63 mg/dL).Results: In an intent-to-treat analysis of 154 subjects, 74 subjects were randomized to SAPT and 80 subjects to PLGM. At baseline, the time with SG <3.5 mmol/L was 3.0% and 2.8% in the SAPT and PLGM groups, respectively. During the study, PLGM was associated with a reduction in hypoglycemia compared with SAPT (% time SG <3.5 mmol/L: SAPT vs. PLGM, 2.6 vs. 1.5, P < 0.0001). A similar effect was also noted in time with SG <3 mmol/L (P < 0.0001). This reduction was seen both during day and night (P < 0.0001). Hypoglycemic events (SG <3.5 mmol/L for >20 min) also declined with PLGM (SAPT vs. PLGM: events/patient-year 227 vs. 139, P < 0.001). There was no difference in glycated hemoglobin (HbA1c) at 6 months (SAPT 7.6 ± 1.0% vs. PLGM 7.8 ± 0.8%, P = 0.35). No change in quality of life measures was reported by participants/parents in either group. There were no PLGM-related serious adverse events.Conclusions: In children and adolescents with type 1 diabetes, PLGM reduced hypoglycemia without deterioration in glycemic control. [ABSTRACT FROM AUTHOR]

Background: There has been a change in the management of type 1 diabetes (T1D) with the availability of continuous glucose monitoring (CGM) systems. In Australia, subsidized CGM is available to patients below the age of 21. A randomized controlled trial (RCT) evaluating hybrid closed loop therapy is currently underway and the baseline data provided an opportunity to analyze the glycemic patterns in patients on contemporary management. Methods: Adolescents and young adults with T1D and HbA1c <10.5% were eligible. All participants wore masked CGM (Enlite® Sensor 3, Medtronic) for 3 weeks during the run-in period. Glucose data from masked CGM were evaluated for glycemic patterns including sensor glucose (SG), glucose variability, percentage time in range, time in hypoglycemia and hyperglycemia. Results: Data were analyzed from 100 participants (47M, 53F; pump 80, MDI 20) with (mean±SD) age 14.9±2.7 years, diabetes duration 7.6±0.9 years, HbA1c 7.9±0.9% of which 55% participants were on real-time CGM. The (mean±SD) SG was 9.6±1.6mmol/l with fasting SG of 8.8±1.9mmol/l. The SG coefficient of variation was 41.3±6.04%. The median [IQR] %time in range (3.9 to 10mmol/l) was 55.9 [44.1,62.3]. The %time in hypoglycemia (<3.0 and < 3.9mmol/l) were 1.1[0.3,2.2] and 4.4[2.2,8.6] respectively. The %time in hyperglycemia (>10 and >13.9mmol/l) were 35.5[24.7,45.7] and 14.1[8.1,18.8] respectively. Conclusion: Majority of adolescents in the trial were on insulin pump therapy with half of them on CGM. The baseline CGM data of these participants provide a snapshot of the glycemic management in patients with T1D on current therapy; especially highlighting the reduced time in hypoglycemia compared to earlier trials. The data can further inform the conduct of future trials. Disclosure: M.B. Abraham: None. G.J. Smith: None. M. de Bock: None. B.R. King: None. J. Fairchild: None. G. Ambler: None. F. Cameron: None. E.A. Davis: None. D.N. ONeal: None. T. Jones: Research Support; Self; Dexcom, Inc., Medtronic MiniMed, Inc. Speaker's Bureau; Self; Eli Lilly and Company, Roche Diabetes Care. [ABSTRACT FROM AUTHOR]

Racism is a fundamental determinant of health inequities among racial and ethnic groups and is understudied among adolescents. In 2023, the national Youth Risk Behavior Survey questionnaire included an item assessing experiences of racism in the school setting among students in grades 9-12 in the United States. This report estimates the prevalence of students who reported ever having experienced racism in school and compares prevalence by racial and ethnic groups. For each racial and ethnic group, prevalence differences and prevalence ratios were estimated comparing the prevalence of indicators of poor mental health, suicide risk, and substance use among students who reported that they have ever versus never experienced racism in school. In 2023, approximately one in three high school students (31.5%) said that they had ever experienced racism in school. Reported experiences of racism were most prevalent among Asian (56.9%), multiracial (48.8%), and Black or African American (Black) (45.9%) students and least prevalent among White students (17.3%). Black and Hispanic or Latino (Hispanic) students who reported experiencing racism had a higher prevalence of all health risk behaviors and experiences investigated, including indicators of poor mental health, suicide risk, and substance use compared with students of their racial and ethnic group who reported never experiencing racism. Many of these associations were also found among multiracial and White students. Student reports of racism were associated with indicators of mental health and suicide risk among American Indian or Alaska Native (AI/AN) and Asian students. Among students of color, including AI/AN, Asian, Black, Hispanic, and multiracial students, the prevalence of seriously considering and attempting suicide was more than two times higher among students who ever compared with never experienced racism. These findings demonstrate that racism in the school setting is experienced by high school students attending public and private schools and continues to disproportionately affect students of color. Students who reported experiencing racism had a higher prevalence of indicators of poor mental health, suicide risk, and substance use. Schools can incorporate policies and practices to prevent unfair treatment on the basis of race and ethnicity and offer resources to help students cope with these experiences., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Jonetta Mpofu reported being a board member of the American School Health Association. No other potential conflicts of interest were disclosed.

The Youth Risk Behavior Surveillance System (YRBSS) is a set of surveys that tracks a broad range of behaviors, experiences, and conditions that can lead to poor health among high school students. The system includes a nationally representative Youth Risk Behavior Survey (YRBS) and separate school-based YRBSs conducted by states, tribes, territories, and local school districts. For the 2023 national YRBS, CDC made changes to the sampling method, survey administration mode, and questionnaire. Specifically, the sampling design added an American Indian or Alaska Native (AI/AN) supplemental sample so that separate, precise estimates could be made for AI/AN high school students, in addition to the usual sample designed to provide nationally representative data for the population of students in grades 9-12. To decrease the time needed to collect and process data, CDC changed the survey administration mode from paper-and-pencil scannable booklets to a tablet-based electronic survey. To provide national data on topics of emerging interest, CDC added new questions to the questionnaire. These new questions assessed social media use, experiences of racism at school, adverse childhood experiences, transgender identity, consent for sexual contact, and unfair discipline at school. Public health practitioners and researchers can use YRBSS data to examine the prevalence of youth health behaviors, experiences, and conditions; monitor trends; and guide interventions. This overview report describes 2023 YRBSS survey methodology, including sampling, data collection, data processing, weighting, and data analyses. The 2023 YRBS participation map, survey response rates, and a detailed examination of student demographic characteristics are included in this report. During 2023, in addition to the national YRBS, 68 site-level surveys were administered to high school students in 39 states, three tribal governments, five territories, and 21 local school districts. These site-level surveys use site-specific questionnaires that are similar to the national YRBS questionnaire but are modified to meet sites' needs. This overview and methods report is one of 11 featured in this MMWR supplement, which reports results from the 2023 national YRBS but does not include data from the 68 site-level surveys. Each report is based on data collected using methods presented in this overview report. A full description of YRBSS results and downloadable data are available (https://www.cdc.gov/yrbs/index.html)., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Jonetta Mpofu reported being a board member of the American School Health Association. Lindsay Trujillo reported receiving a grant from Social & Scientific Systems, Inc. No other potential conflicts of interest were disclosed.

Objective: To determine the efficacy of advanced hybrid closed loop (AHCL) therapy in a high-risk cohort of youth on continuous subcutaneous insulin infusion (CSII) ± continuous glucose monitoring (CGM) with suboptimal glycemia., Research Design and Methods: In a 6-month multicenter clinical trial, youth with type 1 diabetes with mean and most recent HbA1c > 8.5% (65 mmol/mol) were randomly assigned 1:1 to AHCL or treatment as usual (CSII ± CGM). The primary outcome was the 24-week between-group difference in HbA1c. Secondary outcomes included CGM metrics from masked CGM and psychological measures (youth-reported problem areas in diabetes [PAID], quality of life, anxiety, depression, and hypoglycemia fear) assessed using validated questionnaires., Results: A total of 42 participants were randomized (mean [SD] age 16.2 [2.5] years, HbA1c 9.8 [1.1]% or 84 [12] mmol/mol, PAID score 50.3 [19.8]). At study end, the mean (SD) HbA1c was 8.8 (1.1)% or 73 (12) mmol/mol with AHCL and 9.9 (1.2)% or 85 (13.1) mmol/mol with CSII ± CGM, with mean adjusted group difference of -0.77% (95% CI -1.45 to -0.09) or -8.4 mmol/mol (-15.8 to -1.0); P = 0.027. AHCL increased time in range 70-180 mg/dL (difference 19.1%; 95% CI 11.1 to 27.1), reduced time >180 mg/dL (difference -17.7%; 95% CI -26.6 to -8.8), with no increase in time spent <70 mg/dL (difference -0.8%; 95% CI -2.7 to 0.6). There was no evidence for difference in psychosocial outcomes between the two groups at study end., Conclusions: AHCL should be encouraged in youth with suboptimal glycemia, as AHCL improves glycemia. However, psychological support remains vital, as technology alone may not be able to reduce the burden of diabetes care in this subgroup., (© 2024 by the American Diabetes Association.)

Advanced hybrid closed-loop (AHCL) therapy with the Medtronic MiniMed™ 780G system improves glycemia; however, the clinical outcomes in younger children remain less established. This pilot study aimed to explore the continuous glucose monitoring (CGM) metrics in very young children on AHCL. Children between 2 and 7 years of age and on insulin pump therapy were recruited. A 2-week phase in manual mode was followed by a 6-week AHCL phase. CGM metrics were analyzed to review glycemic outcomes. Out of 11 participants enrolled [mean (standard deviation [SD]) age 5.3 (0.8) years], 10 completed the study. Time in closed loop was 96.7 (3.9)%. In AHCL, participants had a mean (SD) time in range of 72.6 (7.4)% and spent 3.0 (1.74)% and 0.63 (0.46)% in time <70 and <54 mg/dL, respectively. AHCL is a feasible option for management of young children with type 1 diabetes.

The Youth Risk Behavior Surveillance System (YRBSS) is the largest public health surveillance system in the United States, monitoring a broad range of health-related behaviors among high school students. The system includes a nationally representative Youth Risk Behavior Survey (YRBS) and separate school-based YRBSs conducted by states, tribes, territories, and local school districts. In 2021, these surveys were conducted during the COVID-19 pandemic. The pandemic underscored the importance of data in understanding changes in youth risk behaviors and addressing the multifaceted public health needs of youths. This overview report describes 2021 YRBSS survey methodology, including sampling, data collection procedures, response rates, data processing, weighting, and analyses. The 2021 YRBS participation map, survey response rates, and a detailed examination of student demographic characteristics are included in this report. During 2021, in addition to the national YRBS, a total of 78 surveys were administered to high school students across the United States, representing the national population, 45 states, two tribal governments, three territories, and 28 local school districts. YRBSS data from 2021 provided the first opportunity since the onset of the COVID-19 pandemic to compare youth health behaviors using long-term public health surveillance. Approximately half of all student respondents represented racial and ethnic minority groups, and approximately one in four identified as lesbian, gay, bisexual, questioning, or other (a sexual identity other than heterosexual) (LGBQ+). These findings reflect shifts in youth demographics, with increased percentages of racial and ethnic minority and LGBQ+ youths compared with previous YRBSS cycles. Educators, parents, local decision makers, and other partners use YRBSS data to monitor health behavior trends, guide school health programs, and develop local and state policy. These and future data can be used in developing health equity strategies to address long-term disparities so that all youths can thrive in safe and supportive environments. This overview and methods report is one of 11 featured in this MMWR supplement. Each report is based on data collected using methods presented in this overview. A full description of YRBSS results and downloadable data are available (https://www.cdc.gov/healthyyouth/data/yrbs/index.htm)., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Youths experiencing unstable housing face higher risks for poor physical, mental, and sexual health outcomes and increased risk for suicide compared with their peers experiencing stable housing. In addition, youths of color and sexual minority youths are disproportionately more likely to experience homelessness. For the first time, in 2021, the nationally representative Youth Risk Behavior Survey included an item assessing housing stability, or nighttime residence among students in grades 9-12 in the United States. During 2021, 2.7% of U.S. high school students experienced unstable housing. Among racial and ethnic subgroups, Native Hawaiian or other Pacific Islander youths were most likely to experience unstable housing, followed by American Indian or Alaska Native and Black youths. Sexual minority (lesbian, gay, bisexual, and questioning or other) youths were more likely to experience unstable housing compared with their heterosexual peers. Compared with students who were stably housed, students who were unstably housed were more likely to engage in risky sexual behaviors, substance use, and suicide ideation and attempts, and to experience violence. These findings highlight which adverse health risks and behaviors are elevated among youths experiencing housing insecurity. Focused public health interventions are required to address the disproportionate burden of health risks prevalent among youths who are unstably housed., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Introduction: Access to effective contraception prevents unintended pregnancies among sexually active female youth. Potentially impacted by the Affordable Care Act's Medicaid-related policies, contraception use increased among sexually active high-school students from 2013 to 2019., Methods: Analyses conducted in 2021 assessed state-level Youth Risk Behavior Survey data among female students in grades 9-12 who reported being sexually active. States that expanded Medicaid were compared with other states in 2013 (baseline) and 2019 (after expansion). Measured outcomes included self-reported use of moderately effective or highly effective, long-acting reversible contraception at last sex. Long-acting reversible contraception included intrauterine devices and implants. Moderately effective contraception included birth control pills, injectables, patches, or rings. Results were weighted and adjusted for age and race/ethnicity., Results: Students in Medicaid expansion states (n=27,564) did not differ significantly from those in nonexpansion states (n=6,048) at baseline or after expansion with respect to age, age at first sex, or the number of sexual partners in the past 3 months; however, race/ethnicity population characteristics changed over time. Postexpansion increased use of intrauterine devices/implants was greater in Medicaid expansion states than in nonexpansion states (238.1% increase vs 120.0% increase, adjusted p=0.047). For those aged 16-17 years, Medicaid expansion states had a 283.3% increase in intrauterine device/implant use compared with an increase of 69.7% in nonexpansion states (adjusted p=0.004)., Conclusions: Medicaid expansion was associated with a greater population-level increase in intrauterine device/implant use among sexually active female high-school students aged 16-17 years. These findings point to the possibility that the Affordable Care Act's Medicaid-related policies played a role in young women's use of intrauterine devices/implants., (Published by Elsevier Inc.)