Faculty Bibliography

PURPOSE/OBJECTIVE:The veterans administration diabetes risk (VADR) cohort facilitates studies on temporal and geographic patterns of pre-diabetes and diabetes, as well as targeted studies of their predictors. The cohort provides an infrastructure for examination of novel individual and community-level risk factors for diabetes and their consequences among veterans. This cohort also establishes a baseline against which to assess the impact of national or regional strategies to prevent diabetes in veterans. PARTICIPANTS/METHODS:The VADR cohort includes all 6 082 018 veterans in the USA enrolled in the veteran administration (VA) for primary care who were diabetes-free as of 1 January 2008 and who had at least two diabetes-free visits to a VA primary care service at least 30 days apart within any 5-year period since 1 January 2003, or veterans subsequently enrolled and were diabetes-free at cohort entry through 31 December 2016. Cohort subjects were followed from the date of cohort entry until censure defined as date of incident diabetes, loss to follow-up of 2 years, death or until 31 December 2018. FINDINGS TO DATE/UNASSIGNED:The incidence rate of type 2 diabetes in this cohort of over 6 million veterans followed for a median of 5.5 years (over 35 million person-years (PY)) was 26 per 1000 PY. During the study period, 8.5% of the cohort were lost to follow-up and 17.7% died. Many demographic, comorbidity and other clinical variables were more prevalent among patients with incident diabetes. FUTURE PLANS/UNASSIGNED:This cohort will be used to study community-level risk factors for diabetes, such as attributes of the food environment and neighbourhood socioeconomic status via geospatial linkage to residence address information.

Importance:The prevalence of leading risk factors for morbidity and mortality in the US significantly varies across regions, states, and neighborhoods, but the extent these differences are associated with a person's place of residence vs the characteristics of the people who live in different places remains unclear. Objective:To estimate the degree to which geographic differences in leading risk factors are associated with a person's place of residence by comparing trends in health outcomes among individuals who moved to different areas or did not move. Design, Setting, and Participants:This retrospective cohort study estimated the association between the differences in the prevalence of uncontrolled chronic conditions across movers' destination and origin zip codes and changes in individuals' likelihood of uncontrolled chronic conditions after moving, adjusting for person-specific fixed effects, the duration of time since the move, and secular trends among movers and those who did not move. Electronic health records from the Veterans Health Administration were analyzed. The primary analysis included 5 342 207 individuals with at least 1 Veterans Health Administration outpatient encounter between 2008 and 2018 who moved zip codes exactly once or never moved. Exposures:The difference in the prevalence of uncontrolled chronic conditions between a person's origin zip code and destination zip code (excluding the individual mover's outcomes). Main Outcomes and Measures:Prevalence of uncontrolled blood pressure (systolic blood pressure level >140 mm Hg or diastolic blood pressure level >90 mm Hg), uncontrolled diabetes (hemoglobin A1c level >8%), obesity (body mass index >30), and depressive symptoms (2-item Patient Health Questionnaire score ≥2) per quarter-year during the 3 years before and the 3 years after individuals moved. Results:The study population included 5 342 207 individuals (mean age, 57.6 [SD, 17.4] years, 93.9% men, 72.5% White individuals, and 12.7% Black individuals), of whom 1 095 608 moved exactly once and 4 246 599 never moved during the study period. Among the movers, the change after moving in the prevalence of uncontrolled blood pressure was 27.5% (95% CI, 23.8%-31.3%) of the between-area difference in the prevalence of uncontrolled blood pressure. Similarly, the change after moving in the prevalence of uncontrolled diabetes was 5.0% (95% CI, 2.7%-7.2%) of the between-area difference in the prevalence of uncontrolled diabetes; the change after moving in the prevalence of obesity was 3.1% (95% CI, 2.0%-4.2%) of the between-area difference in the prevalence of obesity; and the change after moving in the prevalence of depressive symptoms was 15.2% (95% CI, 13.1%-17.2%) of the between-area difference in the prevalence of depressive symptoms. Conclusions and Relevance:In this retrospective cohort study of individuals receiving care at Veterans Health Administration facilities, geographic differences in prevalence were associated with a substantial percentage of the change in individuals' likelihood of poor blood pressure control or depressive symptoms, and a smaller percentage of the change in individuals' likelihood of poor diabetes control and obesity. Further research is needed to understand the source of these associations with a person's place of residence.

OBJECTIVE:This paper compares the accuracy of predicting suicide from Social Determinants of Health (SDoH) or history of illness. POPULATION STUDIED/METHODS:5 313 965 Veterans who at least had two primary care visits between 2008 and 2016. STUDY DESIGN/METHODS:The dependent variable was suicide or intentional self-injury. The independent variables were 10 495 International Classification of Disease (ICD) Version 9 codes, age, and gender. The ICD codes included 40 V-codes used for measuring SDoH, such as family disruption, family history of substance abuse, lack of education, legal impediments, social isolation, unemployment, and homelessness. The sample was randomly divided into training (90 percent) and validation (10 percent) sets. Area under the receiver operating characteristic (AROC) was used to measure accuracy of predictions in the validation set. PRINCIPAL FINDINGS/RESULTS:Separate analyses were done for inpatient and outpatient codes; the results were similar. In the hospitalized group, the mean age was 67.2 years, and 92.1 percent were male. The mean number of medical diagnostic codes during the study period was 37; and 12.9 percent had at least one SDoH V-code. At least one episode of suicide or intentional self-injury occurred in 1.89 percent of cases. SDoH V-codes, on average, elevated the risk of suicide or intentional self-injury by 24-fold (ranging from 4- to 86-fold). An index of 40 SDoH codes predicted suicide or intentional self-injury with an AROC of 0.64. An index of 10 445 medical diagnoses, without SDoH V-codes, had AROC of 0.77. The combined SDoH and medical diagnoses codes also had AROC of 0.77. CONCLUSION/CONCLUSIONS:In predicting suicide or intentional self-harm, SDoH V-codes add negligible information beyond what is already available in medical diagnosis codes. IMPLICATIONS FOR PRACTICE/CONCLUSIONS:Policies that affect SDoH (eg, housing policies, resilience training) may not have an impact on suicide rates, if they do not change the underlying medical causes of SDoH.