Faculty Bibliography

Important work rooted in psychological theory posits that health behavior change occurs through a series of discrete stages. Our work builds on the field of social computing by identifying how social media data can be used to resolve behavior stages at high resolution (e.g. hourly/daily) for key population subgroups and times. In essence this approach opens new opportunities to advance psychological theories and better understand how our health is shaped based on the real, dynamic, and rapid actions we make every day. To do so, we bring together domain knowledge and machine learning methods to form a hierarchical classification of Twitter data that resolves different stages of behavior. We identify and examine temporal patterns of the identified stages, with alcohol as a use case (planning or looking to drink, currently drinking, and reflecting on drinking). Known seasonal trends are compared with findings from our methods. We discuss the potential health policy implications of detecting high frequency behavior stages.

BACKGROUND:Prior work suggests that obesity may confer a survival advantage among persons with cardiovascular disease (CVD). This obesity "paradox" is frequently studied in the context of prevalent disease, a stage in the disease process when confounding from illness-related weight loss and selective survival are especially problematic. Our objective was to examine the association of obesity with mortality among persons with incident CVD, where biases are potentially reduced, and to compare these findings with those based on prevalent disease. METHODS:We used data from the Health and Retirement Study, an ongoing, nationally representative longitudinal survey of U.S. adults age 50 years and older initiated in 1992 and linked to Medicare claims. Cox proportional hazard models were used to estimate the association between weight status and mortality among persons with specific CVD diagnoses. CVD diagnoses were established by self-reported survey data as well as Medicare claims. Prevalent disease models used concurrent weight status, and incident disease models used pre-diagnosis weight status. RESULTS:We examined myocardial infarction, congestive heart failure, stroke, and ischemic heart disease. A strong and significant obesity paradox was consistently observed in prevalent disease models (hazard of death 18-36% lower for obese class I relative to normal weight), replicating prior findings. However, in incident disease models of the same conditions in the same dataset, there was no evidence of this survival benefit. Findings from models using survey- vs. claims-based diagnoses were largely consistent. CONCLUSION/CONCLUSIONS:We observed an obesity paradox in prevalent CVD, replicating prior findings in a population-based sample with longer-term follow-up. In incident CVD, however, we did not find evidence of a survival advantage for obesity. Our findings do not offer support for reevaluating clinical and public health guidelines in pursuit of a potential obesity paradox.

A cohort of frequently incarcerated individuals in the New York City jail system was identified through "hot spotting" analysis. This group demonstrated higher levels of substance use, mental illness, and homelessness than the general jail population, and was typically incarcerated on minor criminal charges. To understand this population better, in-depth interviews (n = 20) were conducted at three Rikers Island correctional facilities with people who had entered the jail system at least 18 times in a six-year period. Findings showed that life circumstances, chronic homelessness, mental illness, and substance use resulted in repeated institutionalization across multiple settings. Participants described an "institutional circuit" that promoted a state of permanent instability characterized by rotating involvement with custodial institutions. Exiting the institutional circuit requires the ability to navigate complex bureaucratic systems; however, without structural reorganization in social service delivery and an emphasis on permanent housing, participants in this group are unlikely to break the cycle.

Because there is no standard reporting of injuries in jails and prisons, the national burden of head trauma during incarceration is unclear. We report on a case of repeated head trauma in the New York City (NYC) jail system, data on the incidence of head trauma and mild traumatic brain injury (mTBI), and compare those findings with national estimates. The case report revealed 64 injurious events over two years, 44% resulting in a head injury and 25% resulting in emergency hospitalization. During the 42 months of this analysis, 10,286 incidents of head trauma occurred in the NYC jail system. Mild TBI occurred in 1,507 of these instances. The rate of head trauma and mTBI was 269.0 and 39.4 per 1,000 person-years, respectively. The lack of reporting head trauma in correctional settings means that national prevalence estimates of these critical health outcomes miss the vulnerable cohort of incarcerated individuals.

Jails represent a critical component of the public health response to HCV elimination. We report on outcomes of 104 patients receiving HCV treatment from January 1, 2014 to June 30, 2016 in a large urban jail setting. Our data demonstrate that treatment in jails is feasible, but many barriers remain.

Introduction: Metabolic syndrome poses an increased burden of disease, warranting heightened public health attention. This study assessed effects of birthplace on cardiometabolic profile among blacks with metabolic syndrome and sleep apnea risk, while exploring potential gender-based effects. Methods: This analysis is based on data from 610 black patients (mean age= 63 +/- 11 years female=65%) with evidence of metabolic syndrome and were at risk for sleep apnea using the ARES. Participants from four community-based clinics in Brooklyn, NY provided sociodemographic, medical, and clinical data. Clinical data included body mass index (BMI), blood pressure (BP), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), and fasting plasma glucose (FPG) or hemoglobin (HbA1c) for those who had a diagnosis of diabetes. General Linear Model (GLM) was used to assess effects of birthplace and gender on cardiometabolic parameters, adjusting for age effects. Results: Of the sample, 61.6 % were foreign-born blacks (FBB) and 38.4 % were US-born blacks (USB). FBB had significantly lower BMI compared with USB (32.76 +/- 0.35 vs. 35.41 +/- 0.44, F=22.57), but had significantly higher systolic blood pressure (136.70 +/- 0.77 vs. 132.83 +/- 0.98; F=9.60) and fasting glucose levels than did USB (146.46 +/- 3.37 vs. 135.02 +/- 4.27; F=4.40). Men had higher diastolic BP (76.67 +/- 0.65 vs. 75.05 +/- 0.45; F=4.20), glucose (146.53 +/- 4.48 vs. 134.95 +/- 3.07; F=4.55) and triglyceride levels (148.10 +/- 4.51 vs. 130.60 +/- 3.09; F=10.25) compared with women, but women had higher LDL-cholesterol (109.24 +/- 1.49 vs. 98.49 +/- 2.18; F=16.60) and HDLcholesterol levels (50.71 +/- 0.66 vs. 42.77 +/- 0.97; F=46.01) than did men. Conclusion: FBB have lower levels of obesity, similar rates of hypertension, dyslipidemia, stroke history, but higher rates of diabetes, history of heart disease, and systolic BP compared with USB. Findings may have implications for addressing effects of birthplace and gender on cardiovascular disease outcomes