The Linked CENTURY Study: linking three decades of clinical and public health data to examine disparities in childhood obesity

Racial and Ethnic Disparities in Pediatric Counseling on Nutrition, Lifestyle, and Weight: A Secondary Analysis of the BP-CATCH Randomized Clinical Trial

Importance

Pediatric obesity and hypertension are highly correlated. To mitigate both conditions, provision of counseling on nutrition, lifestyle, and weight to children with high blood pressure (BP) measurements is recommended.

Objective

To examine racial and ethnic disparities in receipt of nutrition, lifestyle, and weight counseling among patients with high BP at pediatric primary care visits stratified by patients' weight status.

Design, Setting, and Participants

This was a post hoc secondary analysis of the BP-CATCH study, a matched, stepped-wedge cluster randomized clinical trial investigating the best methods to screen children with high BP measurements and manage their care. Urban, suburban, and rural pediatric primary care practices across the US with a multidisciplinary team of at least 1 physician, 1 nurse and another practice associate, and a hypertension specialist for their practice group submitted baseline data from clinical encounters documented between November 2018 and January 2019. Practices identified the first 17 eligible patients with high BP measurements each month. This analysis was conducted from October 2023 to July 2024.

Exposures

Race and ethnicity (Black, Hispanic, White, and other [Asian, multiracial, other races, and unknown race]) and weight status (with or without obesity).

Main Outcomes and Measures

Primary outcomes were receipt of counseling on nutrition, lifestyle, and weight during primary care visits. Baseline measures extracted from medical records included demographics, anthropometric measures, and systolic and diastolic BP.

Results

Of 2677 participants from 59 practices, 1516 (56.6%) were male; mean (SD) age was 10.8 (5.2) years. A total of 593 (21.1%) were Black; 414 (15.5%), Hispanic; 1111 (41.5%), White; and 559 (20.9%), other race and ethnicity. The overall crude unadjusted rates of receiving counseling were 63.5% (n = 1564 of 2463) for nutrition, 57.6% (n = 1419 of 2462) for lifestyle, 47.5% (n = 571 of 1202) for weight, and 46.4% (n = 1142 of 2461) for all counseling topics. Compared with the other 3 groups, Hispanic participants received significantly higher adjusted rates of nutrition (78.6%; 95% CI, 73.5%-83.8%), lifestyle (69.3%; 95% CI, 63.6%-74.9%), and all 3 (52.1%; 95% CI, 46.1%-58.2%) counseling topics. There were no significant differences in rates of receiving weight counseling between any pairs of groups. These findings were consistent in general among participants without obesity, and no significant pairwise differences were noted among participants with obesity except that nutrition counseling rates were significantly different between White participants and those reporting other race and ethnicity (68.3% [95% CI, 61.1%-75.4%] vs 81.6% [95% CI, 74.2%-89.1%]; Bonferroni-corrected P = .02).

Conclusions and Relevance

This secondary analysis of the BP-CATCH trial found that among children with high BP measurements, racial and ethnic disparities in receiving nutrition, lifestyle, and all 3 counseling topics were significant, although no significant disparities in receipt of weight counseling were noted. Racial disparities in receipt of counseling were not observed in participants with and without obesity.

Trial Registration

ClinicalTrials.gov Identifier: NCT03783650.

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. Methods: We extracted electronic health record data from 2012 to 2019 for a children's health system that includes two hospitals and wide network of outpatient clinics spanning five East Coast states in the United States. Using data-driven and algorithmic clustering, we have identified distinct BMI-percentile classification groups in children from 0 to 7 years of age. We used two separate algorithmic clustering methods to confirm the robustness of the identified clusters. We used multinomial logistic regression to examine the associations between clusters and 27 neighborhood SDOHs and compared positive and negative SDOH characteristics separately. Results: From the cohort of 36,910 children, five BMI-percentile classification groups emerged: always having obesity (n = 429; 1.16%), overweight most of the time (n = 15,006; 40.65%), increasing BMI percentile (n = 9,060; 24.54%), decreasing BMI percentile (n = 5,058; 13.70%), and always normal weight (n = 7,357; 19.89%). Compared to children in the decreasing BMI percentile and always normal weight groups, children in the other three groups were more likely to live in neighborhoods with higher poverty, unemployment, crowded households, single-parent households, and lower preschool enrollment. Conclusions: Neighborhood-level SDOH factors have significant associations with children's BMI-percentile classification and changes in classification. 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 children living within them.

Wearable Activity Tracking Device Use in an Adolescent Weight Management Clinic: A Randomized Controlled Pilot Trial

BACKGROUND

The use of physical activity tracker devices has increased within the general population. However, there is limited medical literature studying the efficacy of such devices in adolescents with obesity. In this study, we explored the feasibility of using wearable activity tracking devices as an adjunct intervention on adolescents with obesity.

METHODS

Randomized controlled pilot trial evaluated the feasibility (attrition ≤50%) of an activity tracking intervention (ATI) and its effects on weight loss in adolescents with obesity enrolled in an adolescent weight management clinic (AWMC). Outcomes included feasibility (attrition rate) and absolute change in BMI. Differences between groups at 6, 12, and 18 weeks were examined.

RESULTS

Forty-eight participants were enrolled in the study. Eighteen subjects were randomly assigned to the ATI group and 30 to control. The average age was 14.5 years. Overall, the majority of participants were Hispanic (56%). Sexes were equally distributed. The average baseline BMI was 37.5 kg/m². At the study conclusion, the overall attrition rate was 52.1%, 44.4% in the ATI group versus 56.6% in the control group, with a differential attrition of 12.2%. The ATI and control groups each showed an absolute decrease in BMI of -0.25 and -2.77, respectively, with no significant differences between the groups.

CONCLUSION

The attrition rate in our study was >50%. Participation in the AWMC by the ATI and control groups resulted in maintenance of BMI and body weight for the study duration. However, the use of an activity tracking device was not associated with greater weight loss. This trial is registered with NCT03004378.

CIDACS-RL: a novel indexing search and scoring-based record linkage system for huge datasets with high accuracy and scalability

Background

Record linkage is the process of identifying and combining records about the same individual from two or more different datasets. While there are many open source and commercial data linkage tools, the volume and complexity of currently available datasets for linkage pose a huge challenge; hence, designing an efficient linkage tool with reasonable accuracy and scalability is required.

Methods

We developed CIDACS-RL (Centre for Data and Knowledge Integration for Health – Record Linkage), a novel iterative deterministic record linkage algorithm based on a combination of indexing search and scoring algorithms (provided by Apache Lucene). We described how the algorithm works and compared its performance with four open source linkage tools (AtyImo, Febrl, FRIL and RecLink) in terms of sensitivity and positive predictive value using gold standard dataset. We also evaluated its accuracy and scalability using a case-study and its scalability and execution time using a simulated cohort in serial (single core) and multi-core (eight core) computation settings.

Results

Overall, CIDACS-RL algorithm had a superior performance: positive predictive value (99.93% versus AtyImo 99.30%, RecLink 99.5%, Febrl 98.86%, and FRIL 96.17%) and sensitivity (99.87% versus AtyImo 98.91%, RecLink 73.75%, Febrl 90.58%, and FRIL 74.66%). In the case study, using a ROC curve to choose the most appropriate cut-off value (0.896), the obtained metrics were: sensitivity = 92.5% (95% CI 92.07–92.99), specificity = 93.5% (95% CI 93.08–93.8) and area under the curve (AUC) = 97% (95% CI 96.97–97.35). The multi-core computation was about four times faster (150 seconds) than the serial setting (550 seconds) when using a dataset of 20 million records.

Conclusion

CIDACS-RL algorithm is an innovative linkage tool for huge datasets, with higher accuracy, improved scalability, and substantially shorter execution time compared to other existing linkage tools. In addition, CIDACS-RL can be deployed on standard computers without the need for high-speed processors and distributed infrastructures.

Identification of temporal condition patterns associated with pediatric obesity incidence using sequence mining and big data

BACKGROUND

Electronic health records (EHRs) are potentially important components in addressing pediatric obesity in clinical settings and at the population level. This work aims to identify temporal condition patterns surrounding obesity incidence in a large pediatric population that may inform clinical care and childhood obesity policy and prevention efforts.

METHODS

EHR data from healthcare visits with an initial record of obesity incidence (index visit) from 2009 through 2016 at the Children's Hospital of Philadelphia, and visits immediately before (pre-index) and after (post-index), were compared with a matched control population of patients with a healthy weight to characterize the prevalence of common diagnoses and condition trajectories. The study population consisted of 49,694 patients with pediatric obesity and their corresponding matched controls. The SPADE algorithm was used to identify common temporal condition patterns in the case population. McNemar's test was used to assess the statistical significance of pattern prevalence differences between the case and control populations.

RESULTS

SPADE identified 163 condition patterns that were present in at least 1% of cases; 80 were significantly more common among cases and 45 were significantly more common among controls (p < 0.05). Asthma and allergic rhinitis were strongly associated with childhood obesity incidence, particularly during the pre-index and index visits. Seven conditions were commonly diagnosed for cases exclusively during pre-index visits, including ear, nose, and throat disorders and gastroenteritis.

CONCLUSIONS

The novel application of SPADE on a large retrospective dataset revealed temporally dependent condition associations with obesity incidence. Allergic rhinitis and asthma had a particularly high prevalence during pre-index visits. These conditions, along with those exclusively observed during pre-index visits, may represent signals of future obesity. While causation cannot be inferred from these associations, the temporal condition patterns identified here represent hypotheses that can be investigated to determine causal relationships in future obesity research.

One Size Does Not Fit All: Sociodemographic Factors Affecting Weight Loss in Adolescents

Successful lifestyle changes for weight reduction are heavily dependent on recognizing the importance of societal and cultural factors. Patients 13-19 years of age with a BMI ≥95th percentile are eligible for our multidisciplinary adolescent weight loss clinic. A behavioral questionnaire was administered at the initial visit. Patients were seen every 4-6 weeks. Bivariate analysis was used to identify sociodemographic factors associated with differences in weight loss. Overall, receiving reduced cost meals was associated with a lower likelihood of losing weight (kg) (p < 0.01). When stratified by race, White adolescents were more likely to lose weight if caretakers reported having enough money to buy healthy food (p < 0.05); in contrast, Black adolescents were less likely to lose weight (p < 0.05). However, Black patients were more likely to lose weight if they reported eating fruits and vegetables (p < 0.05). Female adolescents were more likely to lose weight if they felt unhappy about their appearance (p < 0.05). Interestingly, male adolescents were less likely to lose weight if they felt unhappy about their appearance (p < 0.05). Social and cultural norms influence weight loss in adolescents in unique and differing ways. Culturally competent individualized interventions could increase weight loss in diverse groups of adolescents with obesity.

Application of Big Data analysis in gastrointestinal research

Big Data, which are characterized by certain unique traits like volume, velocity and value, have revolutionized the research of multiple fields including medicine. Big Data in health care are defined as large datasets that are collected routinely or automatically, and stored electronically. With the rapidly expanding volume of health data collection, it is envisioned that the Big Data approach can improve not only individual health, but also the performance of health care systems. The application of Big Data analysis in the field of gastroenterology and hepatology research has also opened new research approaches. While it retains most of the advantages and avoids some of the disadvantages of traditional observational studies (case-control and prospective cohort studies), it allows for phenomapping of disease heterogeneity, enhancement of drug safety, as well as development of precision medicine, prediction models and personalized treatment. Unlike randomized controlled trials, it reflects the real-world situation and studies patients who are often under-represented in randomized controlled trials. However, residual and/or unmeasured confounding remains a major concern, which requires meticulous study design and various statistical adjustment methods. Other potential drawbacks include data validity, missing data, incomplete data capture due to the unavailability of diagnosis codes for certain clinical situations, and individual privacy. With continuous technological advances, some of the current limitations with Big Data may be further minimized. This review will illustrate the use of Big Data research on gastrointestinal and liver diseases using recently published examples.

Examining Associations between Perinatal and Postnatal Risk Factors for Childhood Obesity Using Sibling Comparisons

Background: One of the major criticisms of observational studies examining risk factors for childhood obesity is unmeasured confounding. We examined the associations between breastfeeding initiation, cesarean delivery, prenatal smoking, and gestational diabetes mellitus (GDM) with childhood obesity using both a traditional observational approach and a sibling-pair design with family fixed effects. Methods: We used data from the Linked the Collecting Electronic Nutrition Trajectory Data Using e-Records of Youth (CENTURY) Study, a clinical database created through the linkage of well-child visits with children's birth certificates, with obesity measured at 2 (N = 55,058) and 5 (N = 43,894) years of age. We conducted three sets of regression models: (1) full sample to examine the adjusted association between each risk factor and obesity with clustering by family; (2) rerun only among siblings with clustering by family; and (3) fixed effects analysis among siblings. Results: Across risk factors, 30%-39% of children had siblings. In the full sample, breastfeeding initiation was associated with a lower BMI z-score, while cesarean delivery and smoking during pregnancy were associated with a higher BMI z-score. Effect sizes were consistent in models with siblings only. However, in the fixed effects models, the coefficients attenuated and were no longer significant for each of these risk factors. We found no association between GDM and child BMI z-score in any of the models. Results were consistent for childhood obesity as a dichotomous measure and at 5 years of age. Conclusions: Our findings suggest that unmeasured genetic, environmental, and familial factors are likely confounding associations between breastfeeding, cesarean delivery, prenatal smoking, and GDM with childhood obesity in observational studies.

Adherence With Multiple National Healthy Lifestyle Recommendations in a Large Pediatric Center Electronic Health Record and Reduced Risk of Obesity

OBJECTIVE

To evaluate the utility of a routine assessment of lifestyle behaviors incorporated into the electronic health record (EHR) to quantify lifestyle practices and obesity risk at a pediatric primary care center.

PATIENTS AND METHODS

Participants included 24,255 patients aged 2 to 18 years whose parent/caregiver completed a self-report lifestyle assessment during a well-child examination (January 1, 2013, through June 30, 2016). Cross-sectional analyses of age, race/ethnicity, body mass index, and lifestyle assessment responses were performed. Outcome measures included prevalence of patients meeting consensus recommendations for physical activity; screen time; and dairy, water, and fruit/vegetable consumption and the odds of obesity based on reported lifestyle behaviors.

RESULTS

Prevalence of meeting recommendations for lifestyle behaviors was highest for physical activity (84%), followed by screen time (61%) and consumption of water (51%), dairy (27%), and fruits/vegetables (10%). Insufficient physical activity was the strongest predictor of obesity (odds ratio [OR], 1.65; 95% CI, 1.51-1.79), followed by excess screen time (OR, 1.36; 95% CI, 1.27-1.45). Disparities existed across ages, races/ethnicities, and sexes for multiple lifestyle habits. Youth who met 0 or 1 lifestyle recommendation were 1.45 to 1.71 times more likely to have obesity than those meeting all 5 recommendations.

CONCLUSION

Healthy behaviors vary in prevalence, as does their association with obesity. This variation is partially explained by age, sex, and race/ethnicity. Meeting national recommendations for specific behaviors is negatively associated with obesity in a dose-dependent manner. These findings support the assessment of lifestyle behaviors in primary care as one component of multilevel initiatives to prevent childhood obesity.

A Solutions-Based Approach to Building Data-Sharing Partnerships

INTRODUCTION

Although researchers recognize that sharing disparate data can improve population health, barriers (technical, motivational, economic, political, legal, and ethical) limit progress. In this paper, we aim to enhance the van Panhuis et al. framework of barriers to data sharing; we present a complementary solutions-based data-sharing process in order to encourage both emerging and established researchers, whether or not in academia, to engage in data-sharing partnerships.

BRIEF DESCRIPTION OF MAJOR COMPONENTS

We enhance the van Panhuis et al. framework in three ways. First, we identify the appropriate stakeholder(s) within an organization (e.g., criminal justice agency) with whom to engage in addressing each category of barriers. Second, we provide a representative sample of specific challenges that we have faced in our data-sharing partnerships with criminal justice agencies, local clinical systems, and public health. Third, and most importantly, we suggest solutions we have found successful for each category of barriers. We grouped our solutions into five core areas that cut across the barriers as well as stakeholder groups: Preparation, Clear Communication, Funding/Support, Non-Monetary Benefits, and Regulatory Assurances.Our solutions-based process model is complementary to the enhanced framework. An important feature of the process model is the cyclical, iterative process that undergirds it. Usually, interactions with new data-sharing partner organizations begin with the leadership team and progress to both the data management and legal teams; however, the process is not always linear.

CONCLUSIONS AND NEXT STEPS

Data sharing is a powerful tool in population health research, but significant barriers hinder such partnerships. Nevertheless, by aspiring to community-based participatory research principles, including partnership engagement, development, and maintenance, we have overcome barriers identified in the van Panhuis et al. framework and have achieved success with various data-sharing partnerships.In the future, systematically studying data-sharing partnerships to clarify which elements of a solutions-based approach are essential for successful partnerships may be helpful to academic and non-academic researchers. The organizational climate is certainly a factor worth studying also because it relates both to barriers and to the potential workability of solutions.

Racial differences in crossing major growth percentiles in infancy

BACKGROUND/AIMS

We examined associations of ever crossing upwards ≥2 (vs <2) major weight-for-length (WFL) percentiles in the first 24 months with obesity at 5 years among white and black children.

METHODS

We included 10 979 white and 1245 black children from the Linked CENTURY Study with percentile crossing data in all four 6-month periods in the first 24 months and obesity (age-specific and sex-specific body mass index ≥95th percentile) at 5 years. We used adjusted logistic regression models and stratified by race.

RESULTS

64% of children crossed upwards ≥2 major WFL percentiles in the first 2 years. Among white children, 12% were obese vs 7% for <2 crossings, while among black children the frequencies were 23% vs 9%. Black children (adjusted OR 2.94, 2.04 to 4.23) who had ever crossed upwards ≥2 major WFL percentiles had a higher odds of obesity at age 5 than white children (adjusted OR 1.89, 1.64 to 2.18) (interaction p=0.02).

CONCLUSIONS

Our results suggest that rapid weight gain in infancy is more deleterious among black than white children for later obesity.

Association of Cesarean Delivery With Body Mass Index z Score at Age 5 Years

This study describes a within-family study of more than 16 000 siblings to investigate the potential link between cesarean delivery and childhood obesity.

Health Disparities in Adolescent Bariatric Surgery: Nationwide Outcomes and Utilization

PURPOSE

Bariatric surgery represents an appropriate treatment for adolescent severe obesity, but its utilization remains low in this patient population. We studied the impact of race and sex on preoperative characteristics, outcomes, and utilization of adolescent bariatric surgery.

METHODS

Retrospective analysis (2007-2014) of adolescent bariatric surgery using the Bariatric Outcomes Longitudinal Database, a national database that collects bariatric surgical care data. We assessed the relationships between baseline characteristics and outcomes (weight loss and remission of obesity-related conditions [ORCs]). Using the National Health and Nutrition Examination Survey and U.S. census data, we calculated the ratio of severe obesity and bariatric procedures among races and determined the ratio of ratios to assess for disparities.

RESULTS

About 1,539 adolescents underwent bariatric surgery. Males had higher preoperative body mass index (BMI; 51.8 ± 10.5 vs. 47.1 ± 8.7, p < .001) and higher rates of obstructive sleep apnea and dyslipidemia. Blacks had higher preoperative BMI (52.4 ± 10.6 vs. 47.3 ± 8.3; 48.7 ± 8.8; 48.2 ± 12.1 kg/m2; whites, Hispanics, and others, respectively p < .001) and higher rates of hypertension, obstructive sleep apnea, and asthma. Weight loss and ORCs remission rates did not differ between sexes or races after accounting for the rate of severe obesity in each racial group. White adolescents underwent bariatric surgery at a higher proportion than blacks and Hispanics (2.5 and 2.3 times higher, respectively).

CONCLUSIONS

Preoperative characteristics vary according to race and sex. Race and sex do not impact 12-month weight loss or ORC's remission rates. Minority adolescents undergo bariatric surgery at lower-than-expected rates.

Association of missing paternal demographics on infant birth certificates with perinatal risk factors for childhood obesity

BACKGROUND

The role of fathers in the development of obesity in their offspring remains poorly understood. We evaluated associations of missing paternal demographic information on birth certificates with perinatal risk factors for childhood obesity.

METHODS

Data were from the Linked CENTURY Study, a database linking birth certificate and well-child visit data for 200,258 Massachusetts children from 1980-2008. We categorized participants based on the availability of paternal age, education, or race/ethnicity and maternal marital status on the birth certificate: (1) pregnancies missing paternal data; (2) pregnancies involving unmarried women with paternal data; and (3) pregnancies involving married women with paternal data. Using linear and logistic regression, we compared differences in smoking during pregnancy, gestational diabetes, birthweight, breastfeeding initiation, and ever recording a weight for length (WFL) ≥ the 95th percentile or crossing upwards ≥2 WFL percentiles between 0-24 months among the study groups.

RESULTS

11,989 (6.0 %) birth certificates were missing paternal data; 31,323 (15.6 %) mothers were unmarried. In adjusted analyses, missing paternal data was associated with lower birthweight (β -0.07 kg; 95 % CI: -0.08, -0.05), smoking during pregnancy (AOR 4.40; 95 % CI: 3.97, 4.87), non-initiation of breastfeeding (AOR 0.39; 95 % CI: 0.36, 0.42), and with ever having a WFL ≥ 95th percentile (AOR 1.10; 95 % CI: 1.01, 1.20). Similar associations were noted for pregnancies involving unmarried women with paternal data, but differences were less pronounced.

CONCLUSIONS

Missing paternal data on the birth certificate is associated with perinatal risk factors for childhood obesity. Efforts to understand and reduce obesity risk factors in early life may need to consider paternal factors.