An Evaluation of Messages to Promote Parental Intent to Vaccinate Children Aged <12 Years Against COVID-19.

OBJECTIVES: Effective health communication can increase intent to vaccinate. We compared 8 messages that may influence parents' intent to vaccinate their children against COVID-19. METHODS: In a cross-sectional survey of adults in the United States administered online in August 2021, 1837 parents and legal guardians were exposed to 8 messages (individual choice, gain/practical benefits, nonexpert, health care provider recommendation, altruism/community good, safety/effectiveness, safety, and effectiveness) to determine message reception and influence on intent to vaccinate their children. Parents responded to 10 questions using a Likert scale. We computed odds ratios (ORs) for each message, with an OR >1.0 indicating greater observed odds of participant agreement with the follow-up statement as compared with a reference message. We compared outcomes individually across messages with ordinal logistic regression fit using generalized estimating equations. RESULTS: The individual choice message had the highest odds of agreement for understanding intent (OR = 2.10; 95% CI, 1.94-2.27), followed by the health care provider recommendation message (OR = 1.58; 95% CI, 1.46-1.71). The individual choice message had the highest odds of memorability, relatability, and trustworthiness. The altruism/community good message was at or near second best. The altruism/community good message had the highest or near-highest odds of increasing parents' intent to vaccinate their children, asking friends and family for their thoughts, and searching for additional information. The message that most motivated parents to vaccinate their children depended on parental intent to vaccinate prior to being exposed to the tested messages. CONCLUSIONS: Messages with themes of individual choice, health care provider recommendation, and altruism/community good may be used in future message campaigns. Further research is needed to refine message concepts related to altruism/community good.

Comparison of the NHANES dietary screener questionnaire to the Automated Self-Administered 24-Hour Recall for Children in the Healthy Communities Study.

BACKGROUND: A dietary screener questionnaire (DSQ) was used to assess dietary outcomes among children in the Healthy Communities Study (HCS), a study of the relationships between programs and policies to prevent child obesity and child diet, physical activity and weight outcomes. METHODS: To compare dietary intake estimates derived from the DSQ against those from the Automated Self-Administered 24-Hour Recalls for Children (ASA24-Kids) among children, a measurement error model, using structural equation modelling, was utilized to estimate slopes, deattenuated correlation coefficients, and attenuation factors by age and sex, ethnicity, and BMI status. PARTICIPANTS/SETTING: A randomly selected sub-sample of HCS participants aged 4-15 years in 130 communities throughout the U.S. who completed the DSQ and up to two ASA24-Kids recalls (n = 656;13% of HCS participants). RESULTS: For most nutrient/foods examined, the DSQ yielded larger mean intake estimates than the ASA24-Kids, and agreement between the two measures varied by food/nutrient, age and sex, ethnicity, and BMI category. Deattenuated correlation coefficients of 0.4 or greater were observed for added sugars from SSBs (0.54), fruits and vegetables (0.40), and dairy foods (0.50). Lower deattenuated correlation coefficients were seen for total added sugars (0.37), whole grains (0.34), and fiber (0.34). Attenuation factors were most severe for total added sugars intake among overweight children, and for several other dietary outcomes among children aged 9-11 years. CONCLUSIONS: The DSQ was found to be a tool with acceptable agreement with the ASA24-Kids for measuring multiple dietary outcomes of interest in the HCS, although there may be potential due to measurement error to underestimate results (bias towards the null). In future studies, measurement error modelling and regression calibration may be possible solutions to correct for bias due to measurement error in most food/nutrient intake estimates from the DSQ when used among children.

Community Policies and Programs to Prevent Obesity and Child Adiposity.

INTRODUCTION: Evidence regarding impact of community policies and programs (CPPs) to prevent child obesity is limited, and which combinations of strategies and components are most important is not understood. The Healthy Communities Study was an observational study to assess relationships of characteristics and intensity of CPPs with adiposity, diet, and physical activity in children, taking advantage of variation across the U.S. in community actions to prevent child obesity. The study examined the association of CPPs to prevent child obesity with measured BMI and waist circumference, hypothesizing that communities with more-comprehensive CPPs would have children with lower adiposity. METHODS: The study included 130 communities selected by probability-based sampling or because of known CPPs targeting child obesity. Data were collected at home visits on 5,138 children during 2013-2015. CPPs were scored for multiple attributes to create a CPP intensity score. A CPP target behavior score reflected the number of distinct target behaviors addressed. Scores were standardized with the smallest observed score across communities being 0 and the largest 1. Multilevel regression analysis in 2016 adjusted for community, household, and individual characteristics. RESULTS: Higher CPP target behavior score was significantly associated with lower BMI and waist circumference in a dose-response relationship, with magnitude for the past 3 years of CPPs of 0.843 (p=0.013) for BMI and 1.783 cm (p=0.020) for waist circumference. CONCLUSIONS: This study provides plausible evidence that comprehensive CPPs targeting a greater number of distinct physical activity and nutrition behaviors were associated with lower child adiposity.

The Healthy Communities Study: Its Rationale, Aims, and Approach.

Communities across the U.S. are implementing programs and policies designed to address the epidemic of childhood obesity. These programs vary widely in their approaches, including the intensity level, duration, funding, target population, and implementation techniques. However, no previous studies have examined these variations and determined how such aspects of community programs and policies are related to childhood obesity outcomes. The Healthy Communities Study is an observational study that is assessing the associations between characteristics of community programs and policies and BMI, nutrition, and physical activity in children. The Healthy Communities Study was funded in 2010, field data collection and medical record abstraction will be completed in 2015, and data cleaning and analyses will be completed by mid-year 2016. One-hundred and thirty communities (defined as a high school catchment area) and approximately 5,000 children in kindergarten through eighth grade and their parents have been recruited from public elementary and middle schools across the country. The study is examining quantitative and qualitative information obtained from community-based initiatives; measures of community characteristics (e.g., school environment); and child and parent measures, including children's physical activity levels and dietary practices and children's and parents' BMI. The Healthy Communities Study employs a complex study design that includes a diverse sample of communities across the country and combines current/cross-sectional and retrospective data (abstracted from children's medical records). This paper describes the rationale for the Healthy Communities Study, the study aims and logic model, and a brief overview of the study design.

Statistical Design Features of the Healthy Communities Study.

The Healthy Communities Study is designed to assess relationships between characteristics of community programs and policies targeting childhood obesity and children's BMI, diet, and physical activity. The study involved a complex data collection protocol implemented over a 2-year period (2013-2015) across a diverse sample of 130 communities, defined as public high school catchment areas. The protocol involved baseline assessment within each community that included in-person or telephone interviews regarding community programs and policies and in-home collection of BMI, nutritional, and physical activity outcomes from a sample of up to 81 children enrolled in kindergarten through eighth grade in public schools. The protocol also involved medical record reviews to establish a longitudinal trajectory of BMI for an estimated 70% of participating children. Staged sampling was used to collect less detailed measures of physical activity and nutrition across the entire sample of children, with a subset assessed using more costly, burdensome, and detailed measures. Data from the Healthy Community Study will be analyzed using both cross-sectional and longitudinal models that account for the complex design and correct for measurement error and bias using a likelihood-based Markov-chain Monte Carlo methodology. This methods paper provides insights into the complex design features of the Healthy Communities Study and may serve as an example for future large-scale studies that assess the relationship between community-based programs and policies and health outcomes of community residents.

Operational Implementation of the Healthy Communities Study: How Communities Shape Children's Health.

The Healthy Communities Study (HCS) is examining how characteristics of community programs and policies targeting childhood obesity are related to childhood diet, physical activity, and obesity outcomes. The study involves selected districts and public schools in 130 communities; families recruited through schools; and data collected at the community, school, household, and child levels. Data collection took place in two waves-Wave 1 in Spring 2012 and Wave 2 from 2013 to 2015-with analysis to be completed by August 2016. This paper describes operational elements of the HCS, including recruitment activities, field operations, training of data collectors, human subjects protection, and quality assurance and quality control procedures. Experienced trainers oversaw and conducted all training, including training of (1) district and school recruitment staff; (2) telephone interviewers for household screening and recruitment; (3) field data collectors for conducting household data collection; and (4) community liaisons for conducting key informant interviews, document abstraction, and community observations. The study team developed quality assurance and quality control procedures that were implemented for all aspects of the study. Planning and operationalizing a study of this complexity and magnitude, with multiple functional teams, required frequent communication and strong collaboration among all study partners to ensure timely and effective decision making.

Improving cost-effectiveness of epidemiological studies via designed missingness strategies.

Modern epidemiological studies face opportunities and challenges posed by an ever-expanding capacity to measure a wide range of environmental exposures, along with sophisticated biomarkers of exposure and response at the individual level. The challenge of deciding what to measure is further complicated for longitudinal studies, where logistical and cost constraints preclude the collection of all possible measurements on all participants at every follow-up time. This is true for the National Children's Study (NCS), a large-scale longitudinal study that will enroll women both prior to conception and during pregnancy and collect information on their environment, their pregnancies, and their children's development through early adulthood-with a goal of assessing key exposure/outcome relationships among a cohort of approximately 100 000 children. The success of the NCS will significantly depend on the accurate, yet cost-effective, characterization of environmental exposures thought to be related to the health outcomes of interest. The purpose of this paper is to explore the use of cost saving, yet valid and adequately powered statistical approaches for gathering exposure information within epidemiological cohort studies. The proposed approach involves the collection of detailed exposure assessment information on a specially selected subset of the study population, and collection of less-costly, and presumably less-detailed and less-burdensome, surrogate measures across the entire cohort. We show that large-scale efficiency in costs and burden may be achieved without making substantive sacrifices on the ability to draw reliable inferences concerning the relationship between exposure and health outcome. Several detailed scenarios are provided that document how the targeted sub-sampling design strategy can benefit large cohort studies like the NCS, as well as other more focused environmental epidemiologic studies.

Exposures of preschool children to chlorpyrifos, diazinon, pentachlorophenol, and 2,4-dichlorophenoxyacetic acid over 3 years from 2003 to 2005: A longitudinal model.

The impact of the US EPA-required phase-outs starting in 2000-2001 of residential uses of the organophosphate (OP) pesticides chlorpyrifos (CPF) and diazinon (DZN) on preschool children's pesticide exposures was investigated over 2003-2005, in the Raleigh-Durham-Chapel Hill area of North Carolina. Data were collected from 50 homes, each with a child initially of age 3 years (OCh) and a younger child (YCh). Environmental samples (indoor and outdoor air, dust, soil) and child-specific samples (hand surface residue, urine, diet) were collected annually over 24-h periods at each home. Child time-activity diaries and household pesticide use information were also collected. Analytes included CPF and DZN; pentachlorophenol (PCP); 2,4-dichlorophenoxyacetic acid (2,4-D); the CPF metabolite 3,5,6-trichloro-2-pyridinol (TCP); and the DZN metabolite 2-isopropyl-6-methyl-4-pyrimidinol (IMP). Exposures (ng/day) through the inhalation, dietary ingestion, and indirect ingestion were calculated. Aggregate potential doses in ng/kg body weight per day (ng/kg/day) were obtained by summing the potential doses through the three routes of exposure. Geometric mean aggregate potential doses decreased from 2003 to 2005 for both OCh and YCh, with the exception of 2,4-D. Child-specific longitudinal modeling indicated significant declines across time of the potential doses of CPF, DZN, and PCP for both children; declines of IMP for both children, significant only for OCh; a decline of TCP for OCh but an increase of TCP for YCh; and no significant change of 2,4-D for either child. Age-adjusted modeling indicated significant effects of the child's age for all except CPF, and of time for all except PCP and 2,4-D. Within-home variability was small compared with that between homes; variability was smallest for 2,4-D, both within and between homes. The aggregate potential doses of CPF and DZN were well below published reference dose values. These findings show the success of the US EPA restrictions in reducing young children's pesticide exposures.

Exposure of U.S. children to residential dust lead, 1999-2004: I. Housing and demographic factors.

BACKGROUND: Lead-contaminated house dust is a major source of lead exposure for children in the United States. In 1999-2004, the National Health and Nutrition Examination Survey (NHANES) collected dust lead (PbD) loading samples from the homes of children 12-60 months of age. OBJECTIVES: In this study we aimed to compare national PbD levels with existing health-based standards and to identify housing and demographic factors associated with floor and windowsill PbD. METHODS: We used NHANES PbD data (n=2,065 from floors and n=1,618 from windowsills) and covariates to construct linear and logistic regression models. RESULTS: The population-weighted geometric mean floor and windowsill PbD were 0.5 microg/ft2 [geometric standard error (GSE)=1.0] and 7.6 microg/ft2 (GSE=1.0), respectively. Only 0.16% of the floors and 4.0% of the sills had PbD at or above current federal standards of 40 and 250 microg/ft2, respectively. Income, race/ethnicity, floor surface/condition, windowsill PbD, year of construction, recent renovation, smoking, and survey year were significant predictors of floor PbD [the proportion of variability in the dependent variable accounted for by the model (R2)=35%]. A similar set of predictors plus the presence of large areas of exterior deteriorated paint in pre-1950 homes and the presence of interior deteriorated paint explained 20% of the variability in sill PbD. A companion article [Dixon et al. Environ Health Perspect 117:468-474 (2009)] describes the relationship between children's blood lead and PbD. CONCLUSION: Most houses with children have PbD levels that comply with federal standards but may put children at risk. Factors associated with PbD in our population-based models are primarily the same as factors identified in smaller at-risk cohorts. PbD on floors and windowsills should be kept as low as possible to protect children.

Exposure of U.S. children to residential dust lead, 1999-2004: II. The contribution of lead-contaminated dust to children's blood lead levels.

BACKGROUND: The U.S. Centers for Disease Control and Prevention collected health, housing, and environmental data in a single integrated national survey for the first time in the United States in 1999-2004. OBJECTIVES: We aimed to determine how floor dust lead (PbD) loadings and other housing factors influence childhood blood lead (PbB) levels and lead poisoning. METHODS: We analyzed data from the 1999-2004 National Health and Nutrition Examination Survey (NHANES), including 2,155 children 12-60 months of age with PbB and PbD measurements. We used linear and logistic regression models to predict log-transformed PbB and the odds that PbB was >or=5 and >or=10 microg/dL at a range of floor PbD. RESULTS: The population-weighted geometric mean (GM) PbB was 2.0 microg/dL (geometric standard error=1.0). Age of child, race/ethnicity, serum cotinine concentration, poverty-to-income ratio, country of birth, year of building construction, floor PbD by floor surface and condition, windowsill PbD, presence of deteriorated paint, home-apartment type, smoking in the home, and recent renovation were significant predictors in either the linear model [the proportion of variability in the dependent variable accounted for by the model (R2)=40%] or logistic model for 10 microg/dL (R2=5%). At floor PbD=12 microg/ft2, the models predict that 4.6% of children living in homes constructed before 1978 have PbB>or=10 microg/dL, 27% have PbB>or=5 microg/dL, and the GM PbB is 3.9 microg/dL. CONCLUSIONS: Lowering the floor PbD standard below the current standard of 40 microg/ft2 would protect more children from elevated PbB.

Optimal design for epidemiological studies subject to designed missingness.

In large epidemiological studies, budgetary or logistical constraints will typically preclude study investigators from measuring all exposures, covariates and outcomes of interest on all study subjects. We develop a flexible theoretical framework that incorporates a number of familiar designs such as case control and cohort studies, as well as multistage sampling designs. Our framework also allows for designed missingness and includes the option for outcome dependent designs. Our formulation is based on maximum likelihood and generalizes well known results for inference with missing data to the multistage setting. A variety of techniques are applied to streamline the computation of the Hessian matrix for these designs, facilitating the development of an efficient software tool to implement a wide variety of designs.

Community guide recommendations and state level tobacco control programmes: 1999-2004.

OBJECTIVE: To identify the level of effort state tobacco control programmes and partners have expended on interventions recommended by the community guide and how those efforts have changed over time between 1999 and 2004. DESIGN: Longitudinal study. SETTING: United States. PARTICIPANTS: State tobacco control partners, including the state health department, voluntary agencies and tobacco control coalitions. MAIN OUTCOME MEASURE: We used the Strength of Tobacco Control survey responses in 1999, 2002 and 2004 to calculate the mean proportion of state tobacco control partners working on recommended interventions and subsequently analysed changes in effort over time. RESULTS: The proportion of state tobacco control partners working to promote clean indoor air legislation remained at more than 70% in all three years. The proportion working to increase taxes on tobacco rose significantly between 1999 and 2002 (from 54% to 70%), and those working to reduce patient costs for tobacco cessation treatments never exceeded 31% in any year. Use of mass media targeting youths decreased significantly in all years (from 40% to 32% to 26%), and the proportion of state tobacco control partners participating in a quitline has increased steadily and significantly in all years (from 24% to 36% to 41%). The level of effort in each area varied widely between states and over time. CONCLUSIONS: State tobacco control partners are implementing evidence based interventions, but more focus is needed on the tobacco cessation and mass media campaign components of comprehensive tobacco control programmes.

Evaluation of HUD-funded lead hazard control treatments at 6 years post-intervention.

The Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program (Evaluation) was a HUD-funded study of the effectiveness of lead hazard control (LHC) treatments conducted by 14 grantees in communities across the country. A stratified random sampling scheme was used to select treated units at four grantee sites for continued environmental assessment at 6 years post-intervention. The study compared the relative effectiveness after 6 years of the different classes of interventions used by the grantees, after controlling for such factors as housing conditions and characteristics and resident and neighborhood characteristics. Geometric mean dust-lead levels on floors and window sills were 11% and 23% lower, respectively, at 6 years post-intervention than at any preceding point following the intervention. Although geometric mean window trough dust-lead levels were slightly higher at 6 years post-intervention than at other post-intervention time periods, they were still over 75% lower than before intervention. Treatment at more-intensive levels was associated with lower window sill and window trough dust-lead levels; however, statistical modeling found no significant difference in floor dust-lead loadings over time between the levels of treatment; however, significant differences in window sill and window trough dust-lead levels between treatment levels were evident. Findings from the 6-Year Extension study indicate that across all grantees and treatment strategies the treatments applied were effective at significantly reducing environmental lead levels on floors, window sills, and window troughs at least 6 years following the intervention.

Evaluation of lead hazard control treatments in four Massachusetts communities through analysis of blood-lead surveillance data.

This study utilized existing blood-lead surveillance data and records of housing properties treated for lead hazard control (LHC) in order to investigate the effectiveness of LHC treatments performed in four Massachusetts communities (Boston, Cambridge, Malden, and Springfield). This research is part of the US Department of Housing and Urban Development's (HUD) overall program evaluation strategy for assessing the effectiveness of their LHC Grant Program. Childhood blood-lead levels (BLLs) in housing units that were treated through HUD's LHC Grant Program were compared to BLLs in untreated matched control housing units. Data from multiple sources-local housing departments, local tax assessor departments, and the Massachusetts Department of Public Health-were linked to identify similar sets of treated and untreated dwellings. Geometric mean BLLs from before and after treatment were compared for the two sets of housing. Ten years of blood-lead surveillance data for children living in the selected dwellings were analyzed using log-linear mixed models and logistic regression models. Results indicate a 50% decline in BLLs in treated homes, a significantly larger decline than in untreated homes after adjusting for the general downward trend in BLLs observed in the general population for the last several years. Data show that homes that received HUD LHC treatments had children with blood-lead levels that declined twice as fast as in similar untreated homes. These findings show that LHC efforts are successful in reducing children's blood-lead levels.

A Bayesian hierarchical approach for relating PM(2.5) exposure to cardiovascular mortality in North Carolina.

Considerable attention has been given to the relationship between levels of fine particulate matter (particulate matter < or = 2.5 microm in aerodynamic diameter; PM(2.5) in the atmosphere and health effects in human populations. Since the U.S. Environmental Protection Agency began widespread monitoring of PM(2.5) levels in 1999, the epidemiologic community has performed numerous observational studies modeling mortality and morbidity responses to PM(2.5) levels using Poisson generalized additive models (GAMs). Although these models are useful for relating ambient PM(2.5) levels to mortality, they cannot directly measure the strength of the effect of exposure to PM(2.5) on mortality. In order to assess this effect, we propose a three-stage Bayesian hierarchical model as an alternative to the classical Poisson GAM. Fitting our model to data collected in seven North Carolina counties from 1999 through 2001, we found that an increase in PM(2.5) exposure is linked to increased risk of cardiovascular mortality in the same day and next 2 days. Specifically, a 10- microg/m3 increase in average PM(2.5) exposure is associated with a 2.5% increase in the relative risk of current-day cardiovascular mortality, a 4.0% increase in the relative risk of cardiovascular mortality the next day, and an 11.4% increase in the relative risk of cardiovascular mortality 2 days later. Because of the small sample size of our study, only the third effect was found to have > 95% posterior probability of being > 0. In addition, we compared the results obtained from our model to those obtained by applying frequentist (or classical, repeated sampling-based) and Bayesian versions of the classical Poisson GAM to our study population.