Convergent Validity Between the Motor Domain of PediaTracTM and Ages and Stages in Term and Preterm Infants at 2, 4, 6, and 9 Months of Age.

The primary aim of this study was to evaluate the convergent validity of the Motor domain (MOT) of PediaTracTM v3.0, an online developmental tracking instrument based on caregiver reports, with fine and gross motor domains (ASQ-FM and ASQ-GM) of the Ages and Stages Questionnaire (ASQ-3) in infants between 2- and 9 months of age. Participants were caregivers of 571 infants born term or preterm (gestational age <37 weeks) enrolled in a multi-site psychometric study of PediaTracTM. Findings revealed significant correlations between MOT and ASQ-3 scores at 2, 4, 6, and 9 months across time periods, term-preterm status, and biological sex. A significantly higher percentage of infants born preterm, compared with those born at term, was identified as a moderate or high risk on both the ASQ-3 and PediaTrac. Future investigations are warranted to further examine the psychometric properties of the MOT domain, including sensitivity, specificity, and positive and negative predictive value.

Measuring Early Relational Health Using PediaTrac TM in a Diverse Sample of Infant-Caregiver Dyads.

OBJECTIVE: Early relational health (ERH) is a key developmental predictor and outcome in infancy and early childhood that reflects social-emotional well-being and promotes resilience throughout childhood. Currently, there is no gold-standard developmental screening tool for ERH in pediatric care settings. This study examined the psychometric properties of items assessing ERH that are part of a web-based, caregiver-report screening tool called PediaTrac TM . It was hypothesized that ERH could be reliably estimated and that second-order factors would be revealed within the latent construct ERH. METHOD: Participants included 571 caregivers of term (n = 331; ≥37 weeks) and preterm (n = 240; <37 weeks) infants recruited shortly after birth from several academic medical centers and a community health clinic. Caregivers completed PediaTrac modules at birth and 2, 4, 6, 9, 12, 15, and 18 months; data for this study are from the newborn through 12-month periods. RESULTS: Results from Item Response Theory Graded Response Modeling revealed excellent reliability for the PediaTrac ERH domain at all time points, ranging from 0.96 to 0.98. Exploratory factor analyses revealed 4 to 5 second-order factors, representing Parent-Child Relationship, Parent Distress, Parenting Stress, Parenting Efficacy, Sensitivity, and Perceptions of Child, depending on period. CONCLUSION: The caregiver-report developmental screening tool, PediaTrac, reliably measures ERH during the first year of life. The measure has promising clinical utility in pediatric clinic settings for tracking ERH over time to ensure early social-emotional well-being and to identify concerns as early as possible.

Longitudinal caregiver-reported motor development in infants born at term and preterm.

AIM: To examine the extent to which estimates of a latent trait or underlying construct of motor ability differ in infants born at term and preterm, based on caregiver ratings of the motor domain of PediaTrac v3.0. METHOD: The sample consisted of 571 caregiver-infant dyads (331 born at term, 240 born preterm), 48% female, with 51.7% of caregivers identifying as an ethnic minority. Latent trait of motor ability was estimated based on item response theory modeling. Gestational group differences (term and preterm birth) were examined at the newborn/term-equivalent, 2-, 4-, 6-, 9-, and 12-month time points. RESULTS: Caregiver ratings of latent trait of motor ability were reliably modeled across the range of abilities at each time point. While the group born preterm exhibited significantly more advanced motor abilities at the term-equivalent time point, by 6 months the group born at term was more advanced. Biological sex difference main and interaction effects were not significant. INTERPRETATION: Caregivers provided reliable, longitudinal estimates of motor ability in infancy, reflecting important differences in the motor development of infants born at term and preterm. The findings suggest that significant motor development occurs in infants born preterm from birth to the term-equivalent time point and provide a foundation to examine motor growth trajectories as potential predictors in the early identification of neurodevelopmental conditions and needs.

Caregiver-reported development in term and preterm infants from birth to nine months of age: Psychometrics of the PediaTracTM social/communication/cognition domain.

Term and preterm neonates were assessed at the newborn (NB) period (term, term equivalent) and at 2, 4, 6, and 9 months in a study of the psychometric properties of the Social/Communication/Cognition (SCG) domain of PediaTrac™ v3.0, a novel caregiver-based developmental monitoring instrument. Item response theory (IRT) was used to model item parameters and estimate theta, an index of the latent trait, social/communication/cognition. Exploratory factor analysis (EFA) was conducted to further clarify the dimensionality of the domain. In a cohort of 571 caregiver-infant dyads (331 term, 240 preterm), mean theta values could be reliably estimated at all time periods, with term infants demonstrating significantly more advanced social/communication/cognition abilities at 9 months of age. Item discrimination and item difficulty of the 15, 15, 35, 47, and 57 items at the NB, 2-, 4-, 6-, and 9-month periods, respectively, could be reliably modeled across the range of ability. Total Information for the SCG domain was high and the reliability ranged from 0.97 to 0.99 (NB = .98, 2 month = .97, 4 month = .98, 6 month = .99 and 9 month = .99). EFA revealed second-order factors at each time period, with two factors at the NB period (affect/emotional expression, social responsiveness) accounting for 43% of variance; three factors at 2, 4, and 6 months (affect/emotional expression, social responsiveness imitation/emerging communication), accounting for 43%, 34%, and 34% of the variance, respectively; and four factors at 9 months (imitation/communication, nonverbal/gestural communication, affect expression, and social responsiveness), accounting for 34% of the variance. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Multiple Imputation with Massive Data: An Application to the Panel Study of Income Dynamics.

Multiple imputation (MI) is a popular and well-established method for handling missing data in multivariate data sets, but its practicality for use in massive and complex data sets has been questioned. One such data set is the Panel Study of Income Dynamics (PSID), a longstanding and extensive survey of household income and wealth in the United States. Missing data for this survey are currently handled using traditional hot deck methods because of the simple implementation; however, the univariate hot deck results in large random wealth fluctuations. MI is effective but faced with operational challenges. We use a sequential regression/chained-equation approach, using the software IVEware, to multiply impute cross-sectional wealth data in the 2013 PSID, and compare analyses of the resulting imputed data with those from the current hot deck approach. Practical difficulties, such as non-normally distributed variables, skip patterns, categorical variables with many levels, and multicollinearity, are described together with our approaches to overcoming them. We evaluate the imputation quality and validity with internal diagnostics and external benchmarking data. MI produces improvements over the existing hot deck approach by helping preserve correlation structures, such as the associations between PSID wealth components and the relationships between the household net worth and sociodemographic factors, and facilitates completed data analyses with general purposes. MI incorporates highly predictive covariates into imputation models and increases efficiency. We recommend the practical implementation of MI and expect greater gains when the fraction of missing information is large.

Family functioning within the context of families with adolescent children in urban India.

Research on family functioning within given cultural contexts is needed. This study aims to describe salient dimensions of family functioning in two urban contexts in India and to examine differences in family functioning by sociodemographic groups. We measured differences in family functioning using cross-sectional survey questionnaire data collected from 13 to 15-year-old adolescents and one of their parents/primary caregivers in Mumbai (n = 843) and Kolkata (n = 913) during 2019-2020. We drew a multi-stage sample representative of neighborhoods and households in both cities. We assessed a multi-dimensional family functioning latent factor that included parent-reported measures (parent-adolescent communication, family cohesion, and parent monitoring of peers) and adolescent-reported measures (parent support, family cohesion, and parent supervision). Our results support an overall measure of family functioning manifested by multiple dimensions for parent- and adolescent-reported data. Families with male adolescents had worse adolescent-reported family functioning in Mumbai and parent-reported family functioning in Kolkata. Higher socioeconomic status was associated with better parent-reported family functioning in both cities and better adolescent-reported family functioning in Kolkata. Muslim religious identification in Kolkata and the Hindi native language in both cities were associated with better adolescent-reported family functioning. Our findings indicate heterogeneity in family functioning across demographic and social-cultural groups within the two urban contexts of India. This study may inform the development of culturally congruent prevention interventions for families with adolescents in India.

Caregiver-reported newborn term and preterm motor abilities: psychometrics of the PediaTracTM Motor domain.

BACKGROUND: Approximately 5-10% of children exhibit developmental deviations in motor skills or other domains; however, physicians detect less than one-third of these abnormalities. Systematic tracking and early identification of motor deviations are fundamental for timely intervention. METHODS: Term and preterm neonates were prospectively assessed at the newborn (NB) period in a study of the psychometric properties of the Motor (MOT) domain of PediaTracTM v3.0, a novel caregiver-based development tracking instrument. Item response theory graded response modeling was used to model item parameters and estimate theta, an index of the latent trait, motor ability. Exploratory factor analysis (EFA) was conducted to examine the dimensionality and factor structure. RESULTS: In a cohort of 571 caregiver/infant dyads (331 term, 240 preterm), NB MOT domain reliability was high (rho = 0.94). Item discrimination and item difficulty of each of the 15 items could be reliably modeled across the range of motor ability. EFA confirmed that the items constituted a single dimension with second-order factors, accounting for 43.20% of variance. CONCLUSIONS: The latent trait, motor ability, could be reliably estimated at the NB period. IMPACT: The caregiver-reported Motor domain of PediaTrac provides a reliable estimate of the latent trait of motor ability during the newborn period. This is the first known caregiver-reported instrument that can assess motor ability in the newborn period with high reliability in term and preterm infants. Item response theory methods were employed that will allow for future characterization of developmental subgroups and motor trajectories. The PediaTrac Motor domain can support early identification of at-risk infants. Including caregivers in digital reporting and child-centered monitoring of motor functioning may improve access to care.

Estimating vaccination coverage for routinely recommended vaccines among children aged 24 months and adolescents aged 13 through 17 years using data from immunization information systems in the United States.

OBJECTIVE: To use a model-based approach to estimate vaccination coverage of routinely recommended childhood and adolescent vaccines for the United States. METHODS: We used a hierarchical model with retrospective cohort data from eleven IIS jurisdictions, which contains vaccination records submitted by providers. Numerators included data from 2014 to 2019 at the county level for 2.4 million children at age 24 months and 14.4 million adolescents aged 13-17. Age-appropriate Census populations were used as denominators. Covariates associated with childhood and adolescent vaccinations were included in the model. Model-based estimates for each county were generated and aggregated to the national level to produce national vaccination coverage estimates and compared to National Immunization Survey (NIS) estimates of vaccination coverage. Trends of estimated vaccination coverage were compared between the model-based approach and NIS. RESULTS: From 2014 to 18, model-based national vaccination coverage estimates were within ten percentage points of NIS-Child vaccination coverage estimates for most vaccines among children at age 24 months. One notable difference was higher model-based vaccination coverage estimates for hepatitis B birth dose compared to NIS-Child coverage estimates. From 2014 to 19, model-based national vaccination coverage estimates were within ten percentage points of NIS-Teen vaccination coverage estimates for most vaccines among adolescents aged 13-17 years. Model-based vaccination coverage estimates were notably lower for varicella, MMR, and Hepatitis B compared to NIS-Teen coverage estimates among adolescents. Trends in estimates of national vaccination coverage were similar between model-based estimates for children and adolescents as compared to NIS-Child and NIS-Teen, respectively. CONCLUSIONS: A hierarchical model applied to data from IIS may be used to estimate coverage for routinely recommended vaccines among children and adolescents and allows for timely analyses of childhood and adolescent vaccines to quickly assess trends in vaccination coverage across the United States. Monitoring real-time vaccination coverage can help promote immunizations to protect children and adolescents against vaccine-preventable diseases.

A Satellite Account for Health in the United States.

This paper develops a satellite account for the US health sector and measures productivity growth in health care for the elderly population between 1999 and 2012. We measure the change in medical spending and health outcomes for a comprehensive set of 80 conditions. Medical care has positive productivity growth over the time period, with aggregate productivity growth of 1.5% per year. However, there is significant heterogeneity in productivity growth. Care for cardiovascular disease has had very high productivity growth. In contrast, care for people with musculoskeletal conditions has been costly but has not led to improved outcomes.

Neighbourhood tobacco retail access and tobacco use susceptibility in young adolescents in urban India.

BACKGROUND: Neighbourhood tobacco retail access may influence adolescent tobacco use. In India, we examined the association between neighbourhood tobacco retail access and cognitive risks for tobacco use during early adolescence. METHODS: In 2019-2020, a population-based sample (n=1759) of adolescents aged 13-15 years was surveyed from 52 neighbourhoods in Mumbai and Kolkata. Neighbourhood tobacco retail access was measured as the frequency of visits to tobacco retailers, mapped tobacco retailer density and perceived tobacco retailer density. We estimated associations between neighbourhood tobacco retail access and cognitive risks for tobacco use (perceived ease of access to tobacco, perceived peer tobacco use and intention to use tobacco). RESULTS: There was high neighbourhood tobacco retail access. Tobacco retailer density was higher in lower income neighbourhoods (p<0.001). Adolescent frequency of tobacco retailer visits was positively associated with cognitive tobacco use risks. Mapped tobacco retailer density was associated with perceived ease of access in Kolkata but not in Mumbai, and it was not associated with perceived peer tobacco use nor intention. Perceived tobacco retailer density was associated with perceived ease of access and perceived peer use, but not with intention. In Kolkata, higher perceived retailer density and frequency of tobacco retailer visits were negatively associated with perceived ease of access. CONCLUSIONS: Efforts to reduce neighbourhood tobacco retail access in India may reduce cognitive tobacco use risk factors in young adolescents. The frequency of tobacco retailer visits and perceived tobacco retailer density increased cognitive risks, though there were some exceptions in Kolkata that further research may explain.

The influence of sociodemographic factors and response style on caregiver report of infant developmental status.

Caregiver report is the most feasible way to assess early childhood development but is susceptible to the influences of response style and sociodemographic factors. In a sample of 571 caregiver-infant dyads (47.8% female; 48% White), we compared caregiver reports on the Ages and Stages Questionnaire-Third Edition (ASQ-3) with reports on a novel, web-based assessment, PediaTrac™. Ratings on PediaTrac correlated with ratings on the ASQ-3 at all time points (2, 4, 6, and 9 months). Caregiver age, response style, and sociodemographic factors accounted for significant variance on both measures. Developmental reporting of early childhood skills is influenced by caregiver response style and sociodemographic factors. These influences must be considered in order to ensure the accurate identification of infant developmental status.

A SEMIPARAMETRIC MULTIPLE IMPUTATION APPROACH TO FULLY SYNTHETIC DATA FOR COMPLEX SURVEYS.

Data synthesis is an effective statistical approach for reducing data disclosure risk. Generating fully synthetic data might minimize such risk, but its modeling and application can be difficult for data from large, complex surveys. This article extended the two-stage imputation to simultaneously impute item missing values and generate fully synthetic data. A new combining rule for making inferences using data generated in this manner was developed. Two semiparametric missing data imputation models were adapted to generate fully synthetic data for skewed continuous variable and sparse binary variable, respectively. The proposed approach was evaluated using simulated data and real longitudinal data from the Health and Retirement Study. The proposed approach was also compared with two existing synthesis approaches: (1) parametric regressions models as implemented in IVEware; and (2) nonparametric Classification and Regression Trees as implemented in synthpop package for R using real data. The results show that high data utility is maintained for a wide variety of descriptive and model-based statistics using the proposed strategy. The proposed strategy also performs better than existing methods for sophisticated analyses such as factor analysis.

PediaTrac V.3.0 protocol: a prospective, longitudinal study of the development and validation of a web-based tool to measure and track infant and toddler development from birth through 18 months.

INTRODUCTION: The need for an efficient, low-cost, comprehensive measure to track infant/toddler development and treatment outcomes is critical, given the importance of early detection and monitoring. This manuscript describes the protocol for the development and testing of a novel measure, PediaTrac, that collects longitudinal, prospective, multidomain data from parents/caregivers to characterise infant/toddler developmental trajectories in term and preterm infants. PediaTrac, a web-based measure, has the potential to become the standard method for monitoring development and detecting risk in infancy and toddlerhood. METHODS AND ANALYSES: Using a multisite, prospective design, primarcaregivers will complete PediaTrac V.3.0, a survey tool that queries core domains of early development, including feeding/eating/elimination, sleep, sensorimotor, social/sensory information processing, social/communication/cognition and early relational health. Information also will be obtained about demographic, medical and environmental factors and embedded response bias indices are being developed as part of the measure. Using an approach that systematically measures infant/toddler developmental domains during a schedule that corresponds to well-child visits (newborn, 2, 4, 6, 9, 12, 15, 18 months), we will assess 360 caregiver/term infant dyads and 240 caregiver/preterm infant dyads (gestational age <37 weeks). Parameter estimates of our items and latent traits (eg, sensorimotor) will be estimated by theta using item response theory-graded response modelling. Participants also will complete legacy (ie, established) measures of development and caregiver health and functioning, used to provide evidence for construct (discriminant) validity. Predictive validity will be evaluated by examining relationships between the PediaTrac domains and the legacy measures in the total sample and in a subsample of 100 participants who will undergo a neurodevelopmental assessment at 24 months of age. ETHICS AND DISSEMINATION: This investigation has single Institutional Review Board (IRB) multisite approval from the University of Michigan (IRB HUM00151584). The results will be presented at prominent conferences and published in peer-reviewed scientific journals.

Validation of Tools for Predicting Incident Adenocarcinoma of the Esophagus or Esophagogastric Junction.

INTRODUCTION: Guidelines suggest screening of individuals who are at increased risk of esophageal adenocarcinoma (EAC). Tools for identifying patients at risk of Barrett's esophagus have been validated. Here, we aimed to compare and validate the tools for the primary outcomes of interest: EAC and esophagogastric junction adenocarcinoma (EGJAC). METHODS: Retrospective longitudinal analysis of the Kaiser Permanente Northern California Multiphasic Health Checkup Cohort, a community-based cohort including 206,974 patients enrolled between 1964 and 1973 followed through 2016. Baseline questionnaires and anthropometrics classified predictor variables for each tool and were linked to cancer registry outcomes. Analyses used logistic regression, Cox proportional hazards regression, and Kaplan-Meier survival curves. RESULTS: We identified 168 incident EAC cases and 151 EGJAC cases at a mean of 32 years after enrollment (mean follow-up among controls 26 years). Gastroesophageal reflux disease (GERD) symptoms predicted incident EAC (hazard ratio 2.66; 95% confidence interval 1.01, 7.00), but not EGJAC. The Nord-Trøndelag Health Study tool, Kunzmann tool, and Michigan Barrett's Esophagus pREdiction Tool were more accurate than GERD for predicting EAC, with individuals in the fourth quartile of Kunzmann having 17-fold the risk of those in the 1st quartile (hazard ratio = 16.7, 95% confidence interval = 4.72, 58.8). Each tool also predicted incident EGJAC with smaller magnitudes of effect. DISCUSSION: The study independently validated 4 tools for predicting incident EAC and EGJAC in a large community-based population. The Kunzmann tool appears best calibrated; all appear preferable to using GERD alone for risk stratification. Future studies should determine how best to implement such tools into clinical practice.

Incomplete Response of Gastroesophageal Reflux Symptoms Poorly Predicts Erosive Esophagitis or Barrett's Esophagus.

BACKGROUND & AIMS: Many patients with symptoms of gastroesophageal reflux disease (GERD) not responding to a proton pump inhibitor (PPI) undergo an upper endoscopy. We hypothesized that an incomplete response to a PPI is not associated with findings of esophageal pathology on endoscopy, and that psychological distress is associated inversely with pathology. METHODS: We enrolled consecutive individuals aged 40 to 79 years with prior heartburn or regurgitation. Logistic regression was used to estimate the effects of incomplete response of GERD symptoms and psychological distress on the odds of finding erosive esophagitis or Barrett's esophagus. RESULTS: A total of 625 patients completed the study. A total of 254 (66.8% of those taking PPI) had GERD symptoms incompletely responsive to a PPI and 352 (56.3%) had severe somatization. An incomplete response to a PPI was associated with psychological distress (P < .001). Erosive esophagitis was found in 148 subjects (23.7%) and Barrett's esophagus in 58 (9.3%). Overall, an incomplete response to a PPI was not found to be associated with these pathologies (odds ratio, 1.17; 95% CI, 0.720-1.91). In contrast, greater psychological distress was associated inversely with erosive esophagitis or Barrett's esophagus (in particular, highest vs lowest tertile somatization: odds ratio, 0.590; 95% CI, 0.365-0.952). CONCLUSIONS: Patients undergoing upper endoscopy frequently have GERD symptoms incompletely responding to a PPI and a high burden of somatization. However, an incomplete response of GERD symptoms is a poor predictor for endoscopic pathology, and should not be relied upon for selecting patients for screening for Barrett's esophagus. Patients with high psychological distress are less likely to have esophageal pathology.

Attributing medical spending to conditions: A comparison of methods.

To understand the cost burden of medical care it is essential to partition medical spending into conditions. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition that physicians list as its cause. The second decomposes total spending for a person over a year to their cumulative set of health conditions. Traditionally, this has been done through regression analysis. This paper has two contributions. First, we develop a new cost attribution method to attribute spending to conditions using a more flexible attribution approach, based on propensity score analysis. Second, we compare the propensity score approach to the claims-based approach and the regression approach in a common set of beneficiaries age 65 and older in the 2009 Medicare Current Beneficiary Survey. Our estimates show that the three methods have important differences in spending allocation and that the propensity score model likely offers the best theoretical and empirical combination.

Validation and Comparison of Tools for Selecting Individuals to Screen for Barrett's Esophagus and Early Neoplasia.

BACKGROUND & AIMS: Guidelines suggest endoscopic screening of individuals who are at increased risk for Barrett's esophagus (BE) and esophageal adenocarcinoma. Tools based on clinical factors are available for identifying patients at risk, but only some have been validated. We aimed to compare and validate available tools. METHODS: We performed a prospective study of 1241 patients, ages 40 to 79 years, presenting either for their first esophagogastroduodenoscopy (EGD) or their first endoscopic therapy of early neoplastic BE, from April 2015 through June 2018. We calculated risk scores for 6 previously published tools (the Gerson, Locke, Thrift, Michigan BE pREdiction Tool [M-BERET], Nord-Trøndelag Health Study [HUNT], and Kunzmann tools). We also investigated the accuracy of frequency and duration of gastroesophageal reflux disease (GERD), using data from a randomly selected 50% of patients undergoing their first EGD. We compared the ability of all these tools to discriminate patients with BE and early neoplasia from patients without BE, using findings from endoscopy as the reference standard. RESULTS: BE was detected in 81 of 1152 patients during their first EGD (7.0%). GERD symptoms alone identified patients with BE with an area under the receiver operating characteristic curve (AuROC) of 0.579. All of the tools were more accurate in identifying patients with BE than the frequency and duration of GERD (AuROC for GERD, 0.579 vs range for other tools, 0.660-0.695), and predicted risk correlated well with observed risk (calibration). The AUROCs of the HUNT tool (0.796), the M-BERET (0.773), and the Kunzmann tool (0.763) were comparable in discriminating between patients with early neoplasia (n = 94) vs no BE. Each tool was more accurate in discriminating BE with early neoplasia than GERD frequency and duration alone (AuROC, 0.667; P < .01). CONCLUSIONS: The HUNT, M-BERET, and Kunzmann tools identify patients with BE with AuROC values ranging from 0.665 to 0.695, and discriminate patients with early neoplasia from patients without BE with AuROC values ranging from 0.763 to 0.796. These tools are more accurate than frequency and duration of GERD in identifying individuals at risk for neoplastic BE.

COMBINING INFORMATION FROM MULTIPLE DATA SOURCES TO ASSESS POPULATION HEALTH.

Information about an extensive set of health conditions on a well-defined sample of subjects is essential for assessing population health, gauging the impact of various policies, modeling costs, and studying health disparities. Unfortunately, there is no single data source that provides accurate information about health conditions. We combine information from several administrative and survey data sets to obtain model-based dummy variables for 107 health conditions (diseases, preventive measures, and screening for diseases) for elderly (age 65 and older) subjects in the Medicare Current Beneficiary Survey (MCBS) over the fourteen-year period, 1999-2012. The MCBS has prevalence of diseases assessed based on Medicare claims and provides detailed information on all health conditions but is prone to underestimation bias. The National Health and Nutrition Examination Survey (NHANES), on the other hand, collects self-reports and physical/laboratory measures only for a subset of the 107 health conditions. Neither source provides complete information, but we use them together to derive model-based corrected dummy variables in MCBS for the full range of existing health conditions using a missing data and measurement error model framework. We create multiply imputed dummy variables and use them to construct the prevalence rate and trend estimates. The broader goal, however, is to use these corrected or modeled dummy variables for a multitude of policy analysis, cost modeling, and analysis of other relationships either using them as predictors or as outcome variables.

Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys.

BACKGROUND: National health surveys, such as the National Health Interview Survey (NHIS) and the Behavioral Risk Factor Surveillance System (BRFSS), collect data on cancer screening and smoking-related measures in the US noninstitutionalized population. These surveys are designed to produce reliable estimates at the national and state levels. However, county-level data are often needed for cancer surveillance and related research. METHODS: To use the large sample sizes of BRFSS and the high response rates and better coverage of NHIS, we applied multilevel models that combined information from both surveys. We also used relevant sources such as census and administrative records. By using these methods, we generated estimates for several cancer risk factors and screening behaviors that are more precise than design-based estimates. RESULTS: We produced reliable, modeled estimates for 11 outcomes related to smoking and to screening for female breast cancer, cervical cancer, and colorectal cancer. The estimates were produced for 3,112 counties in the United States for the data period from 2008 through 2010. CONCLUSION: The modeled estimates corrected for potential noncoverage bias and nonresponse bias in the BRFSS and reduced the variability in NHIS estimates that is attributable to small sample size. The small area estimates produced in this study can serve as a useful resource to the cancer surveillance community.

Measurement error correction and sensitivity analysis in longitudinal dietary intervention studies using an external validation study.

In lifestyle intervention trials, where the goal is to change a participant's weight or modify their eating behavior, self-reported diet is a longitudinal outcome variable that is subject to measurement error. We propose a statistical framework for correcting for measurement error in longitudinal self-reported dietary data by combining intervention data with auxiliary data from an external biomarker validation study where both self-reported and recovery biomarkers of dietary intake are available. In this setting, dietary intake measured without error in the intervention trial is missing data and multiple imputation is used to fill in the missing measurements. Since most validation studies are cross-sectional, they do not contain information on whether the nature of the measurement error changes over time or differs between treatment and control groups. We use sensitivity analyses to address the influence of these unverifiable assumptions involving the measurement error process and how they affect inferences regarding the effect of treatment. We apply our methods to self-reported sodium intake from the PREMIER study, a multi-component lifestyle intervention trial.