A Short Adverse Experiences Measure Among Mothers of Young Children.

OBJECTIVES: Screening for parental adverse childhood experiences (ACEs) in pediatric settings can be burdensome because of the questionnaire's length and sensitive nature. Rapid screening tools may help address these challenges. We evaluated a 2-item short ACE measure developed for adults in a cross-sectional sample of mothers of young children in an urban pediatric emergency department. METHODS: From January 2011 to March 2020, we administered the ACE questionnaire in English or Spanish to 3999 biological mothers of children aged <4 years in a pediatric emergency department in Philadelphia, Pennsylvania. We assessed sensitivity and specificity of a shortened 2-item ACE measure defined as report of childhood emotional abuse and/or household substance use, using 4+ ACEs on the full questionnaire as the standard. We assessed convergent validity by comparing associations of the 2-item and standard measures with maternal, household, and child outcomes using adjusted log-binomial regression. RESULTS: Mothers were racially and ethnically diverse (54% Latina, 35% Black non-Latina); 94% of children were publicly insured. Thirteen percent of mothers reported childhood emotional abuse and 16% childhood household substance use; 23% reported at least 1 of these and 6% both. Compared with 4+ ACEs on the full questionnaire, the 2-item measure had sensitivity 88% and specificity 90%. In adjusted models, high adversity was associated with poor maternal, household, and child outcomes. CONCLUSIONS: A 2-item ACE measure assessing childhood emotional abuse and household substance use may be useful in pediatric settings to identify mothers who may have experienced significant child adversity and inform development, testing, or provision of comprehensive family supports.

Moving Because of Unaffordable Housing and Disrupted Social Safety Net Access Among Children.

OBJECTIVES: To measure associations between residential moves because of unaffordable housing costs and disruptions in access to the Supplemental Nutrition Assistance Program; the Special Supplemental Nutrition Program for Women, Infants, and Children; and Medicaid in a health care-based sample of families with young children. METHODS: We used cross-sectional survey data on social safety net-eligible caregivers and children recruited into the Children's HealthWatch study from emergency departments and primary care clinics in Baltimore and Philadelphia (2011-2019). Children's HealthWatch measured residential moves (cost-driven and noncost-driven) in the past year and disruptions in safety net access. We used logistic regression to estimate associations between each type of move and disrupted access to social safety nets. RESULTS: Across 9344 children, cost-driven residential moves were associated with higher odds of disrupted access to at least 1 safety net program (Supplemental Nutrition Assistance Program; the Special Supplemental Nutrition Program for Women, Infants, and Children; or Medicaid; adjusted odds ratio 1.44; 95% confidence interval 1.16-1.80), as well as higher odds of disruption to each program separately. Noncost-driven moves were also associated with disruptions to at least 1 safety net program, but less strongly so (adjusted odds ratio 1.14; confidence interval 1.01-1.29; P value for comparison with cost-driven = .045). CONCLUSIONS: Residential moves, particularly cost-driven moves, are associated with social safety net benefit disruptions. The association between these events suggests a need for action to ensure consistent safety net access among children facing cost-driven moves and vice versa (ie, access to housing supports for children with disrupted safety net access).

Unintended consequences of disseminating behavioral health evidence to policymakers: Results from a survey-based experiment.

Background: Communication research demonstrates that messages often have unintended consequences, but this work has received limited attention in implementation science. This dissemination experiment sought to determine whether state-tailored policy briefs about the behavioral health consequences of adverse childhood experiences (ACEs), compared to national policy briefs on the topic, increased state legislators'/staffers' perceptions of the policy brief relevance and parental blame for the consequences of ACEs, and whether effects differed between Democrats and Republicans. Method: A preregistered, web-based survey experiment with U.S. state legislators/staffers was conducted in 2021 (n = 133). Respondents were randomized to view a policy brief about the behavioral health consequences of ACEs that included state-tailored data (intervention condition) or national data (control condition) and then answered survey questions. Dependent variables were perceived policy brief relevance and parental blame for the consequences of ACEs. Results: The mean policy brief relevance score was 4.1% higher in the intervention than in the control condition (p = .24), but the mean parental blame score was 16.5% higher (p = .02). When outcomes were dichotomized, 61.2% of respondents in the intervention condition rated parents as "very much to blame" for the consequences of ACEs compared to 37.1% in the control condition (p = .01). When the sample was stratified by political affiliation, the effect of the state-tailored policy brief on parental blame was larger in magnitude among Democrats and not significant among Republicans. The intervention policy brief increased the mean parental blame score by 22.8% among Democrats relative to the control policy brief (p = .007) and doubled the proportion rating parents as "very much to blame" (52.2% vs. 26.1%, p = .03). Conclusions: Despite limited statistical power, state-tailored policy briefs significantly increased state legislators'/staffers' perceptions of parental blame for the behavioral health consequences of ACEs, relative to a policy brief with national data. Unintended messaging effects warrant greater attention in dissemination research and practice.

Prior studies have tested the effects of dissemination strategies on policymakers' engagement with research evidence. However, little research has assessed the potential unintended consequences of disseminating evidence to policymakers. This knowledge gap is important because a large body of communication research has found that messages often have negative and unintended effects. This paper adds to the literature on disseminating evidence about behavioral health issues to policymakers. A web-based survey experiment was conducted in which U.S. state legislators/staffers were randomized to view a policy brief about adverse childhood experiences (ACEs) that was tailored to present data from their state (intervention condition) or a policy brief that presented national data and then completed a survey. Legislators/staffers who viewed the state-tailored policy brief perceived the brief as slightly more relevant, but also rated parents as being significantly more to blame for the behavioral health consequence of ACEs. The effect of the state-tailored policy brief on parental blame is an unintended messaging effect that signals cause for caution when disseminating evidence about ACEs to policymakers and other practice audiences. More broadly, the findings highlight a need to consider unintended messaging effects in dissemination research and practice.

Ethnic Enclaves and Incidence of Cancer Among US Ethnic Minorities in the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Since immigrants and their descendants represent a growing proportion of the US population, there is a strong demographic imperative for scientists to better understand the cancer risk factors at multiple levels that exist for these populations. Understanding the upstream causes of cancer, including neighborhood context, may help prevention efforts. Residence in ethnic enclaves may be one such contextual cause; however, the evidence is mixed, and past research has not utilized prospective designs examining cancer incidence or mortality. METHODS: We examined the association between residency in ethnic enclaves and cancer events among Hispanic (n = 753) and Chinese (n = 451) participants without a history of cancer in the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective cohort study that enrolled participants ages 45-84 in six US cities. Cancer events included deaths and hospitalization for any cancer diagnosis from 2000-2012. Residency in an ethnic enclave was operationalized as their geocoded baseline census tract having a concentration of residents of the same ethnicity greater than the 75th percentile (compared to non-ethnic enclave otherwise). Potential confounders were blocked into three categories: sociodemographic, acculturation, and biomedical/health behavior variables. To examine the association between ethnic enclaves and cancer, we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional hazards models. RESULTS: Among Hispanic participants, residing in ethnic enclaves (vs. not) was associated with a 39% reduction in cancer risk (HR 0.61, 95%CI: 0.31, 1.21) after adjusting for sociodemographic variables. Among Chinese participants, residing in ethnic enclaves was associated with a 2.8-fold increase in cancer risk (HR 2.86, 95%CI; 1.38, 5.94) after adjusting for sociodemographic variables. CONCLUSIONS: Our results suggest that the association between ethnic enclaves and cancer events differs by ethnic group, suggesting that different social and contextual factors may operate in different communities.

Development and Validation of an Abbreviated Child and Adult Food Security Scale for Use in Clinical and Research Settings in the United States.

BACKGROUND: Food insecurity (FI) prevalence was consistently >10% over the past 20 years, indicating chronic economic hardship. Recession periods exacerbate already high prevalence of FI, reflecting acute economic hardship. To monitor FI and respond quickly to changes in prevalence, an abbreviated food security scale measuring presence and severity of household FI in adults and children is needed. OBJECTIVE: Our aim was to develop an abbreviated, sensitive, specific, and valid food security scale to identify severity levels of FI in households with children. DESIGN: Cross-sectional and longitudinal survey data were analyzed for years 1998 to 2022. PARTICIPANTS/SETTING: Participants were racially diverse primary caregivers of 69,040 index children younger than 4 years accessing health care in 5 US cities. STATISTICAL ANALYSES PERFORMED: Sensitivity, specificity, positive and negative predictive values, accuracy, and area under the receiver operator curve were used to test combinations of questions for the most effective abbreviated scale to assess levels of severity of adult and child FI compared with the Household Food Security Survey Module. Adjusted logistic regression models assessed convergent validity between the Abbreviated Child and Adult Food Security Scale (ACAFSS) and health measures. McNemar tests examined the ACAFSS performance in times of acute economic hardship. RESULTS: The ACAFSS exhibited 91.2% sensitivity; 99.6% specificity; 98.3% and 97.6% positive and negative predictive values, respectively; 97.7% accuracy; and a 99.6% area under the receiver operator curve, while showing high convergent validity. CONCLUSIONS: The ACAFSS is highly sensitive, specific, and valid for detecting severity levels of FI among racially diverse households with children. The ACAFSS is recommended as a stand-alone scale or a follow-up scale after households with children screen positive for FI risk. The ACAFSS is also recommended for planning interventions and evaluating their effects not only on the binary categories of food security and FI, but also on changes in levels of severity, especially when rapid decision making is crucial.

Associations of longitudinal BMI percentile classification patterns in early childhood with neighborhood-level social determinants of health.

Background: Understanding social determinants of health (SDOH) that may be risk factors for childhood obesity is important to developing targeted interventions to prevent obesity. Prior studies have examined these risk factors, mostly examining obesity as a static outcome variable. Objectives: This study aimed to identify distinct subpopulations based on BMI percentile classification or changes in BMI percentile classifications over time and explore these longitudinal associations with neighborhood-level SDOH factors in children from 0 to 7 years of age. Methods: Using Latent Class Growth (Mixture) Modelling (LCGMM) we identify distinct BMI% classification groups in children from 0 to 7 years of age. We used multinomial logistic regression to study associations between SDOH factors with each BMI% classification group. Results: From the study cohort of 36,910 children, five distinct BMI% classification groups emerged: always having obesity (n=429; 1.16%), overweight most of the time (n=15,006; 40.65%), increasing BMI% (n=9,060; 24.54%), decreasing BMI% (n=5,058; 13.70%), and always normal weight (n=7,357; 19.89%). Compared to children in the decreasing BMI% and always normal weight groups, children in the other three groups were more likely to live in neighborhoods with higher rates of poverty, unemployment, crowded households, and single-parent households, and lower rates of preschool enrollment. Conclusions: Neighborhood-level SDOH factors have significant associations with children's BMI% classification and changes in classification over time. This highlights the need to develop tailored obesity interventions for different groups to address the barriers faced by communities that can impact the weight and health of the children living within them.

Child Care Feeding Programs Associated With Food Security and Health for Young Children From Families With Low Incomes.

BACKGROUND: The Child and Adult Care Food Program is the primary national program that enables child-care settings to provide healthy meals for children. Associations between Child and Adult Care Food Program participation and child health and development and health care utilization are understudied. OBJECTIVE: To assess associations between children's health, development, health care utilization and food security by meal source (child-care-provided vs parent-provided) among children from low-income families with a child care subsidy attending child-care in settings likely eligible to participate in Child and Adult Care Food Programs. DESIGN: The study used repeat cross-sectional surveys (new sample at successive time points) conducted year-round. PARTICIPANTS AND SETTING: Primary caregivers of 3,084 young children accessing emergency departments or primary care in Baltimore, MD; Boston, MA; Little Rock, AR; Minneapolis, MN; and Philadelphia, PA, were interviewed between 2010 and 2020. The sample was limited to children aged 13 to 48 months, receiving a child care subsidy and attending child-care centers or family child-care homes ≥20 hours per week. MAIN OUTCOME MEASURES: Outcomes included household and child food security; child health, growth, and developmental risk; and admission to the hospital on the day of the emergency department visit. STATISTICAL ANALYSES: Meal source and participant characteristics were analyzed using χ2 tests; associations of outcomes with parent-provided meals were analyzed with adjusted logistic regression. RESULTS: The majority of children had child-care-provided meals (87.2% child-care-provided vs 12.8% parent-provided). Compared with children with parent-provided meals, children with child-care-provided meals had lower adjusted odds of living in a food-insecure household (adjusted odds ratio 0.70, 95% CI 0.55 to 0.88), being in fair or poor health (adjusted odds ratio 0.61, 95% CI 0.46 to 0.81), or hospital admission from the emergency department (adjusted odds ratio 0.59, 95% CI 0.41 to 0.83), with no differences in growth or developmental risk. CONCLUSIONS: Compared with meals provided from home, child-care-provided meals likely supported by the Child and Adult Care Food Program are related to food security, early childhood health, and reduced hospital admissions from an emergency department among low-income families with young children.

The next phases of the Migrante Project: Study protocol to expand an observatory of migrant health on the Mexico-U.S. border.

Background: Mexican migrants traveling across the Mexico-United States (U.S.) border region represent a large, highly mobile, and socially vulnerable subset of Mexican nationals. Population-level health data for this group is hard to obtain given their geographic dispersion, mobility, and largely unauthorized status in the U.S. Over the last 14 years, the Migrante Project has implemented a unique migration framework and novel methodological approach to generate population-level estimates of disease burden and healthcare access for migrants traversing the Mexico-U.S. border. This paper describes the rationale and history of the Migrante Project and the protocol for the next phases of the project. Methods/design: In the next phases, two probability, face-to-face surveys of Mexican migrant flows will be conducted at key crossing points in Tijuana, Ciudad Juarez, and Matamoros (N = 1,200 each). Both survey waves will obtain data on demographics, migration history, health status, health care access, COVID-19 history, and from biometric tests. In addition, the first survey will focus on non-communicable disease (NCD), while the second will dive deeper into mental health and substance use. The project will also pilot test the feasibility of a longitudinal dimension with 90 survey respondents that will be re-interviewed by phone 6 months after completing the face-to-face baseline survey. Discussion: Interview and biometric data from the Migrante project will help to characterize health care access and health status and identify variations in NCD-related outcomes, mental health, and substance use across migration phases. The results will also set the basis for a future longitudinal extension of this migrant health observatory. Analyses of previous Migrante data, paired with data from these upcoming phases, can shed light on the impact of health care and immigration policies on migrants' health and inform policy and programmatic responses to improve migrant health in sending, transit, and receiving communities.

Research and Evaluation in a Child-Focused Place-Based Initiative: West Philly Promise Neighborhood.

Place-based initiatives attempt to reduce persistent health inequities through multisectoral, cross-system collaborations incorporating multiple interventions targeted at varying levels from individuals to systems. Evaluations of these initiatives may be thought of as part of the community change process itself with a focus on real-time learning and accountability. We described the design, implementation, challenges, and initial results of an evaluation of the West Philly Promise Neighborhood, which is a comprehensive, child-focused place-based initiative in Philadelphia, Pennsylvania. Priorities for the evaluation were to build processes for and a culture of ongoing data collection, monitoring, and communication, with a focus on transparency, accountability, and data democratization; establish systems to collect data at multiple levels, with a focus on multiple uses of the data and future sustainability; and adhere to grant requirements on data collection and reporting. Data collection activities included the compilation of neighborhood-level indicators; the implementation of a program-tracking system; administrative data linkage; and neighborhood, school, and organizational surveys. Baseline results pointed to existing strengths in the neighborhood, such as the overwhelming majority of caregivers reporting that they read to their young children (86.9%), while other indicators showed areas of need for additional supports and were programmatic focuses for the initiative (e.g., about one-quarter of young children were not engaged in an early childhood education setting). Results were communicated in multiple formats. Challenges included aligning timelines, the measurement of relationship-building and other process-focused outcomes, data and technology limitations, and administrative and legal barriers. Evaluation approaches and funding models that acknowledge the importance of capacity-building processes and allow the development and measurement of population-level outcomes in a realistic timeframe are critical for measuring the success of place-based approaches.

Association Between Material Hardship in Families With Young Children and Federal Relief Program Participation by Race and Ethnicity and Maternal Nativity.

Importance: Even brief periods of hardship during early childhood may have lifelong consequences. Prior cross-sectional research limited to respondents with English proficiency and internet access during the COVID-19 crisis documented families with young children that struggled to afford basic needs like food and rent. Few studies have examined experiences of families with young children by race and ethnicity and maternal nativity. Objective: To examine the association of COVID-19 relief programs with the mitigation of household food insecurity among families with young children, as well as being behind on rent and disparities in program receipt. Design, Setting, and Participants: This cohort study used data from the ongoing repeat cross-sectional Children's HealthWatch study comprising families surveyed at baseline (January 1, 2018, to March 20, 2020) and during the COVID-19 crisis (September 1, 2020, to June 30, 2021). Baseline questionnaires were administered face to face to caregivers of children aged 48 months or younger in English or Spanish in emergency departments or primary care clinics in 5 US cities. The follow-up questionnaires were administered via telephone. Exposures: Supplemental Nutrition Assistance Program (SNAP) participation or receipt of at least 1 Economic Impact Payment (EIP; ie, stimulus check) during the COVID-19 crisis. Main Outcomes and Measures: The primary outcomes were household food insecurity (assessed via the US Household Food Security Survey Module: Six-Item Short Form) and being behind on rent. Logistic and binomial regression models were used to calculate adjusted odds ratios (aORs) and unadjusted and adjusted prevalence ratios (PRs). Results: Of 1396 caregiver-child dyads (20.3% response rate), race and ethnicity data were available for 1357 caregivers: 514 (37.9%) were Black, non-Latino; 558 (41.1%) were Latino; 230 (16.9%) were White, non-Latino; and 55 (4.1%) were of other non-Latino race or ethnicity. Among 1390 responses with nonmissing data, 417 children (30.0%) had an immigrant mother, and among 1388 responses, 1238 (33.5%) were publicly insured. During the crisis, 467 of 1395 respondents (33.5%) reported household food insecurity, and 567 of 1391 respondents (40.8%) reported being behind on rent. Families with immigrant mothers had lower odds of EIP and SNAP participation than families with US-born mothers (eg, aOR, 0.07 [95% CI, 0.05-0.12] for both EIP and SNAP vs neither), despite being more likely to report household food insecurity (adjusted PR [aPR], 1.48 [95% CI, 1.28-1.71]) and being behind on rent (aPR, 1.14 [95% CI, 1.00-1.30]). Families with Black (unadjusted PR [uPR], 1.40 [95% CI, 1.08-1.82]) or Latino (uPR, 1.54 [95% CI, 1.19-1.98]) caregivers or caregivers of other race and ethnicity (uPR, 1.67 [1.12-2.49]) were also more likely than families with White, non-Latino caregivers to experience household food insecurity or being behind on rent (families with Black caregivers: uPR, 2.02 [95% CI, 1.58-2.58]; families with Latino caregivers: 1.68 [95% CI, 1.30-2.16]; families with caregivers of other race or ethnicity: uPR, 1.94 [95% CI, 1.34-2.80]). Adjustment for covariates and differential participation in relief programs did not entirely account for these disparities. Conclusions and Relevance: The results of this cohort study suggest that the COVID-19 crisis exacerbated preexisting inequities in food insecurity and difficulty paying rent according to race and ethnicity and maternal nativity and that equity-focused policy changes are needed to ensure that all children and their families in the US can afford basic needs for optimal health.

Associations of household unmet basic needs and health outcomes among very low birth weight children.

OBJECTIVE: We examined associations of past year household hardships (housing, energy, food, and healthcare hardships) with postnatal growth, developmental risk, health status, and hospitalization among children 0-36 months born with very low birth weight (VLBW) and the extent that these relationships differed by receipt of child supplemental security income (SSI). STUDY DESIGN: We examined cross-sectional data from 695 families. Growth was measured as weight-for-age z-score change. Developmental risk was defined as ≥1 concerns on the "Parents' Evaluation of Developmental Status" screening tool. Child health status was categorized as excellent/good vs. fair/poor. Hospitalizations excluded birth hospitalizations. RESULTS: Compared to children with no household hardships, odds of developmental risk were greater with 1 hardship (aOR 2.0 [1.26, 3.17]) and ≥2 hardships (aOR) 1.85 [1.18, 2.91], and odds of fair/poor child health (aOR) 1.59 [1.02, 2.49] and hospitalizations (aOR) 1.49 [1.00, 2.20] were greater among children with ≥2 hardships. In stratified analysis, associations of hardships and developmental risk were present for households with no child SSI and absent for households with child SSI. CONCLUSION: Household hardships were associated with developmental risk, fair/poor health status, and hospitalizations among VLBW children. Child SSI may be protective against developmental risk among children living in households with hardships.

Changes in Economic Hardships Arising During the COVID-19 Pandemic: Differences by Nativity and Race.

Hardships in early childhood impact health. Few longitudinal studies have examined pandemic-related hardships among families with young children by race/ethnicity or nativity. We used prospective longitudinal data from 1,165 caregivers of children < 4 years surveyed in English and Spanish face-to-face in 5 urban hospitals 1/2018 to 3/2020 (pre-pandemic) and again by telephone 9/2020 to 3/2021 (during pandemic). Caregivers reported hardships (household food insecurity [HFI], child food insecurity [CFI]), behind on rent [BOR]) and maternal race/ethnicity and nativity. During the pandemic vs pre-pandemic, families with immigrant mothers had greater increases in HFI [aOR = 2.15 (CI 1.49-3.09)] than families with US-born mothers [aOR = 1.44 (CI 1.09-1.90)] and greater increases in BOR [families with immigrant mothers aOR = 4.09 (CI 2.78-6.01) vs. families with US-born mothers aOR = 2.19 (CI 1.68-2.85)]. CFI increases for all groups did not vary by nativity nor race/ethnicity. HFI and BOR increases during COVID were significantly greater in families with Latina mothers and those with immigrant mothers than other groups.

Eviction and Household Health and Hardships in Families With Very Young Children.

BACKGROUND: Families with versus without children are at greater eviction risk. Eviction is a perinatal, pediatric, and adult health concern. Most studies evaluate only formal evictions. METHODS: Using cross-sectional surveys of 26 441 caregiver or young child (<48 months) dyads from 2011 to 2019 in emergency departments (EDs) and primary care clinics, we investigated relationships of 5 year history of formal (court-involved) and informal (not court-involved) evictions with caregiver and child health, history of hospitalizations, hospital admission from the ED on the day of the interview, and housing-related and other material hardships. RESULTS: 3.9% of 26 441 caregivers reported 5 year eviction history (eviction), of which 57.0% were formal evictions. After controlling for covariates, we found associations were minimally different between formal versus informal evictions and were, therefore, combined. Compared to no evictions, evictions were associated with 1.43 (95% CI: 1.17-1.73), 1.55 (95% confidence interval [CI]: 1.32-1.82), and 1.24 (95% CI: 1.01-1.53) times greater odds of child fair or poor health, developmental risk, and hospital admission from the ED, respectively, as well as adverse caregiver and hardship outcomes. Adjusting separately for household income and for housing-related hardships in sensitivity analyses did not significantly alter results, although odds ratios were attenuated. Hospital admission from the ED was no longer significant. CONCLUSIONS: Demonstrated associations between eviction and health and hardships support broad initiatives, such as housing-specific policies, income-focused benefits, and social determinants of health screening and community connections in health care settings. Such multifaceted efforts may decrease formal and informal eviction incidence and mitigate potential harmful associations for very young children and their families.

Migration is the driving force of rapid aging in Puerto Rico: A Research Brief.

The combined effects of declining fertility and increased longevity have accelerated population aging in different parts of the world. Unlike other countries, Puerto Rico is also experiencing unprecedented levels of working-age out-migration. The full impact of high out-migration on Puerto Rican demography is not fully understood. Placing Puerto Rico's aging process in an international context is useful in identifying the role out-migration is having on the accelerated aging of the Puerto Rican society. Using the World Population Prospects 2019 estimates, we compared the pattern of rapid aging found for Puerto Rico with the trajectories of six other countries with the highest population of 65+ in the World, Europe, and the Caribbean from 1960 to 2020. Prior to 2010, the aging process in Puerto Rico was comparable to the other countries. After 2010, the percent of the population over 65 years in Puerto Rico nearly doubled from 11% to 21%. The nearly doubling of the percent of older adults is not observed in any of the comparison countries. We find that the rapid aging of Puerto Rico, changing from a linear trend to an exponential one, is a result of accelerating levels of out-migration, which is concentrated in the working-age population.

State Policies that Impact the Design of Children's Mental Health Services: A Modified Delphi Study.

To identify the state-level policies and policy domains that state policymakers and advocates perceive as most important for positively impacting the use of children's mental health services (CMHS). We used a modified Delphi technique (i.e., two rounds of questionnaires and an interview) during Spring 2021 to elicit perceptions among state mental health agency officials and advocates (n = 28) from twelve states on state policies that impact the use of CMHS. Participants rated a list of pre-specified policies on a 7-point Likert scale (1 = not important, 7 = extremely important) in the following policy domains: insurance coverage and limits, mental health services, school and social. Participants added nine policies to the initial list of 24 policies. The "school" policy domain was perceived as the most important, while the "social" policy domain was perceived as the least important after the first questionnaire and the second most important policy domain after the second questionnaire. The individual policies perceived as most important were school-based mental health services, state mental health parity, and Medicaid reimbursement rates. Key stakeholders in CMHS should leverage this group of policies to understand the current policy landscape in their state and to identify gaps in policy domains and potential policy opportunities to create a more comprehensive system to address children's mental health from a holistic, evidence-based policymaking perspective.

Partisan differences in the effects of economic evidence and local data on legislator engagement with dissemination materials about behavioral health: a dissemination trial.

BACKGROUND: State legislators make policy decisions that influence children's exposure to adverse childhood experiences (ACEs), such as child maltreatment, and their effects on behavioral health. Effective dissemination of scientific research can increase the likelihood that legislators' decisions are aligned with evidence to prevent ACEs and their consequences, and effective dissemination requires legislators to engage with dissemination materials. Informed by the elaboration likelihood model of persuasive communication and Brownson's Model of Dissemination Research, we tested the hypothesis that inclusion of economic evidence and local data would increase legislator engagement with dissemination materials about evidence-supported policies related to ACEs and behavioral health. METHODS: A three-arm randomized dissemination trial was conducted. A university researcher e-mailed dissemination materials which contained evidence about ACEs and behavioral health problems to state legislators (two e-mails sent 2 weeks apart, 12,662 e-mails delivered to 6509 legislators). The e-mail subject lines, text, and policy brief content were manipulated across the study arms. The intervention condition received state-tailored data about rates of ACEs and state-tailored economic evidence about the costs of ACEs for public systems, the enhanced control condition received state-tailored data and not economic evidence, and the control condition received national data and not economic evidence. Outcomes were rates of e-mail views, policy brief link clicks, requests for researcher consultation, and mentions of child maltreatment terms in legislators' social media posts. RESULTS: For the first e-mail, the e-mail view rate was 42.6% higher in the intervention than in the enhanced control condition (22.8% vs. 14.8%) and 20.8% higher than in the control condition (22.8% vs. 18.5%) (both p < .0001). Similar results were observed for the second e-mail. These differences remained significant after adjustment for demographic differences across study conditions in individual-level models, but not multilevel models. There was a significant interaction between the experimental condition and political party (p < .0001) in which the intervention increased e-mail view rates among Democrats but not Republicans. The intervention had no effect on policy brief link clicks or requests for consultation and a mixed effect on social media posts. CONCLUSIONS: Inclusion of state-tailored economic evidence in dissemination materials can increase engagement with research evidence among Democrat, but not Republican, legislators. Dissemination strategies tailored for legislators' political party affiliation may be needed.

Household unmet basic needs in the first 1000 days and preterm birth status.

OBJECTIVE: To examine the relationship of individual and composite number of unmet basic needs (housing, energy, food, and healthcare hardships) in the past year with preterm birth status among children aged 0-24 months. STUDY DESIGN: We examined cross-sectional 2011-18 data of 17,926 families with children aged 0-24 months. We examined children born <31 weeks', 31-33 weeks', and 34-36 weeks' gestation versus term (≥37 weeks) using multivariable multinomial logistic regression. RESULTS: At least 1 unmet basic need occurred among ≥60% of families with preterm children, compared to 56% of families with term children (p = 0.007). Compared to term, children born ≤30 weeks' had increased odds of healthcare hardships (aOR 1.28 [1.04, 1.56]) and children born 34-36 weeks' had increased odds of 1 (aOR 1.19 [1.05, 1.35]) and ≥2 unmet needs (aOR 1.15 [1.01, 1.31]). CONCLUSION: Unmet basic needs were more common among families with preterm, compared to term children.

Prenatal WIC Is Associated with Increased Birth Weight of Infants Born in the United States with Immigrant Mothers.

BACKGROUND: The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) improves health outcomes for participating mothers and children. Recent immigration policy changes increased chilling effects on WIC access and utilization. Associations between WIC participation and neonatal outcomes among infants born to immigrant parents-23% of all births in the United States-are understudied. OBJECTIVE: Our aim was to examine relationships between prenatal participation in WIC and birth weight among infants of income-eligible immigrant mothers. DESIGN: The study design was repeat cross-sectional in-person surveys. PARTICIPANTS/SETTING: Participants were 9,083 immigrant mothers of publicly insured or uninsured US-born children younger than 48 months accessing emergency departments or primary care in Baltimore, MD; Boston, MA; Little Rock, AR; Minneapolis, MN; and Philadelphia, PA interviewed from 2007 through 2017. MAIN OUTCOME MEASURES: Outcomes were mean birth weight (in grams) and low birth weight (<2,500 g). STATISTICAL ANALYSES: Multivariable linear regression assessed associations between prenatal WIC participation and mean birth weight; multivariable logistic regression examined association between prenatal WIC participation and low birth weight. RESULTS: Most of the immigrant mothers (84.6%) reported prenatal WIC participation. Maternal ethnicities were as follows: 67.4% were Latina, 27.0% were Black non-Latina, 2.2% were White non-Latina, and 3.5% were other/multiple races non-Latina. Infants of prenatal WIC-participant immigrant mothers had higher adjusted mean birth weight (3,231.1 g vs 3,149.8 g; P < .001) and lower adjusted odds of low birth weight (adjusted odds ratio 0.79, 95% CI 0.65 to 0.97; P = .02) compared with infants of nonparticipants. Associations were similar among groups when stratified by mother's length of stay in United States. CONCLUSIONS: Prenatal WIC participation for income-eligible immigrant mothers is associated with healthier birth weights among infants born in the United States, including for those who arrived most recently.

Longitudinal associations of neighborhood environment features with pediatric body mass index.

INTRODUCTION: It has been posited that policies to promote child health and prevent obesity should target neighborhood environments but evidence on the impact of neighborhoods on child weight is conflicting and longitudinal studies (which have benefits for causal inference) are scarce. METHODS: We used electronic health records (2007-2016) from an urban, pediatric integrated delivery system and linked children (N = 51,873, ages 6-19 years, 77% African American) to neighborhood-level data to investigate how changes in neighborhood environments relate to changes in body mass index (BMI). Measures of neighborhood environment were resources for healthy foods and physical activity ('resources'), greenness, violent crime rate, perceived safety and social cohesion. Fixed effects models estimated associations between changes in neighborhood environment exposures and changes in BMI z-score and whether effects differed by sex, baseline age, neighborhood socioeconomic status and population density. RESULTS: Approximately 22% of the cohort was obese (BMI z-score ≥ 95th percentile). In adjusted models, increases in neighborhood greenness and perceived safety were associated with decreases in BMI z-score (mean change in BMI z-score for 1-SD increase for both: -0.012; 95% CI= (-0.018, -0.007)). Increases in neighborhood safety had a stronger effect in children ages 6-10 years than in older children. Increases in social cohesion were associated with increases in BMI z-score (mean change: 0.005 95% CI = (0.003, 0.008)) especially in boys. Increases in food and physical activity resources were not associated with changes in BMI. CONCLUSIONS: This study suggests that increasing neighborhood greenness and safety are potential approaches to reduce children's BMI.

Prediction of early childhood obesity with machine learning and electronic health record data.

OBJECTIVE: This study compares seven machine learning models developed to predict childhood obesity from age > 2 to ≤ 7 years using Electronic Healthcare Record (EHR) data up to age 2 years. MATERIALS AND METHODS: EHR data from of 860,510 patients with 11,194,579 healthcare encounters were obtained from the Children's Hospital of Philadelphia. After applying stringent quality control to remove implausible growth values and including only individuals with all recommended wellness visits by age 7 years, 27,203 (50.78 % male) patients remained for model development. Seven machine learning models were developed to predict obesity incidence as defined by the Centers for Disease Control and Prevention (age/sex adjusted BMI>95th percentile). Model performance was evaluated by multiple standard classifier metrics and the differences among seven models were compared using the Cochran's Q test and post-hoc pairwise testing. RESULTS: XGBoost yielded 0.81 (0.001) AUC, which outperformed all other models. It also achieved statistically significant better performance than all other models on standard classifier metrics (sensitivity fixed at 80 %): precision 30.90 % (0.22 %), F1-socre 44.60 % (0.26 %), accuracy 66.14 % (0.41 %), and specificity 63.27 % (0.41 %). DISCUSSION AND CONCLUSION: Early childhood obesity prediction models were developed from the largest cohort reported to date. Relative to prior research, our models generalize to include males and females in a single model and extend the time frame for obesity incidence prediction to 7 years of age. The presented machine learning model development workflow can be adapted to various EHR-based studies and may be valuable for developing other clinical prediction models.