Faculty Bibliography

BACKGROUND:Community violence may affect a broad range of health outcomes through physiologic stress responses and changes in health behaviors among residents. However, existing research on the health impacts of community violence suffers from problems with bias. METHODS:We examined the relations of acute changes in community violence with hospital visits and deaths due to stress-responsive diseases (mental, respiratory, and cardiac conditions) in statewide data from California 2005-2013. The community violence exposure was measured as both binary spikes and continuous acute changes. We applied a combined fixed-effects and time-series design that separates the effects of violence from those of community- and individual-level confounders more effectively than past research. Temporal patterning was removed from community violence rates and disease rates in each place using a Kalman smoother, resulting in residual rates. We used linear regression with place fixed-effects to examine within-place associations of acute changes in community violence with residual rates of each outcome, controlling for local time-varying covariates. RESULTS:We found acute increases in hospital visits and deaths due to anxiety disorders (0.31 per 100,000; 95% confidence interval [CI] = 0.02, 0.59), substance use (0.47 per 100,000; 95% CI = 0.14, 0.80), asthma (0.56 per 100,000; 95% CI = 0.16, 0.95), and fatal acute myocardial infarction (0.09 per 100,000; 95% CI = 0.00, 0.18) co-occurring with violence spikes. The pattern of findings was similar for the exposure of continuous acute violence changes. CONCLUSIONS:Although the associations were small, the identified increases in stress-responsive conditions suggest the possibility of health impacts of acute changes in community violence.

BACKGROUND:Self-harm is a leading cause of morbidity and mortality. Exposure to community violence is an important and potentially modifiable feature of the social environment that may affect self-harm, but studies to date are limited in the samples and outcomes examined. METHODS:We conducted a population-based, nested case-control study. Cases were all deaths and hospital visits due to self-harm in California, 2006-2013. We frequency-matched California resident population-based controls from the American Community Survey to cases on age, gender, race/ethnicity, and year of survey/injury. We assessed past-year community violence using deaths and hospital visits due to interpersonal violence in the community of residence. We estimated risk difference parameters that were defined to avoid extrapolation and to capture associations between changes in the distribution of community violence and the population-level risk of self-harm. RESULTS:After adjustment for confounders, setting past-year community violence to the lowest monthly levels observed within each community over the study period was associated with a 30.1 (95% confidence interval = 29.6, 30.5) per 100,000 persons per year lower risk of nonfatal self-harm but no difference in the risk of fatal self-harm. Associations for a parameter corresponding to a hypothetical violence prevention intervention targeting high-violence communities indicated a 5% decrease in nonfatal self-harm at the population level. In sensitivity analyses, results were robust. CONCLUSIONS:This study strengthens evidence on the relationship between community violence and self-harm. Future research should investigate reasons for differential associations by age and gender and whether community violence prevention programs have meaningful impacts on self-harm.

BACKGROUND:To inform discussions on rates, burden and priority-setting in relation to police violence, we quantified the number and rate of years of life lost (YLLs) due to police violence by race/ethnicity and age in the USA, 2015-2016. METHODS:. YLLs are the difference between an individual's age at death and their corresponding standard life expectancy at age of death. RESULTS:There were 57 375 and 54 754 YLLs due to police violence in 2015 and 2016, respectively. People of colour comprised 38.5% of the population, but 51.5% of YLLs. YLLs were greatest among those aged 25-34 years, and the number of YLLs at younger ages was greater among people of colour than whites. CONCLUSIONS:The number of YLLs due to police violence is substantial. YLLs highlight that police violence disproportionately impacts young people, and the young people affected are disproportionately people of colour. Framing police violence as an important cause of deaths among young adults provides another valuable lens to motivate prevention efforts.

Background/UNASSIGNED:Gun shows are an important source of firearms, but no adequately powered studies have examined whether they are associated with increases in firearm injuries. Objective/UNASSIGNED:To determine whether gun shows are associated with short-term increases in local firearm injuries and whether this association differs by the state in which the gun show is held. Design/UNASSIGNED:Quasi-experimental. Setting/UNASSIGNED:California. Participants/UNASSIGNED:Persons in California within driving distance of gun shows. Measurements/UNASSIGNED:Gun shows in California and Nevada between 2005 and 2013 (n = 915 shows) and rates of firearm-related deaths, emergency department visits, and inpatient hospitalizations in California. Results/UNASSIGNED:Compared with the 2 weeks before, postshow firearm injury rates remained stable in regions near California gun shows but increased from 0.67 injuries (95% CI, 0.55 to 0.80 injuries) to 1.14 injuries (CI, 0.97 to 1.30 injuries) per 100 000 persons in regions near Nevada shows. After adjustment for seasonality and clustering, California shows were not associated with increases in local firearm injuries (rate ratio [RR], 0.99 [CI, 0.97 to 1.02]) but Nevada shows were associated with increased injuries in California (RR, 1.69 [CI, 1.16 to 2.45]). The pre-post difference was significantly higher for Nevada shows than California shows (ratio of RRs, 1.70 [CI, 1.17 to 2.47]). The Nevada association was driven by significant increases in firearm injuries from interpersonal violence (RR, 2.23 [CI, 1.01 to 4.89]) but corresponded to a small increase in absolute numbers. Nonfirearm injuries served as a negative control and were not associated with California or Nevada gun shows. Results were robust to sensitivity analyses. Limitation/UNASSIGNED:Firearm injuries were examined only in California, and gun show occurrence was not randomized. Conclusion/UNASSIGNED:Gun shows in Nevada, but not California, were associated with local, short-term increases in firearm injuries in California. Differing associations for California versus Nevada gun shows may be due to California's stricter firearm regulations. Primary Funding Source/UNASSIGNED:National Institutes of Health; University of California, Berkeley; and Heising-Simons Foundation.

OBJECTIVES/OBJECTIVE:To describe recent trends in suicide throughout California and to compare rates and methods of suicide ("means") across demographic groups. METHODS:Data from statewide mortality records were used to estimate age-adjusted rates of suicide from 2005 to 2013, overall and by means, age, gender, race/ethnicity, urbanicity, and county. RESULTS:The suicide rate increased 12.6% between 2005 and 2013, from 11.2 to 12.6 per 100 000 population, but this overall trend masks substantial heterogeneity across subgroups. In particular, rapid increases were observed for individuals of multiple races/ethnicities. Means of suicide changed, trending away from firearms toward suffocation and drug poisoning. CONCLUSIONS:High-risk groups and means of suicide are changing rapidly in California, so appropriate public health programming should prioritize population-based strategies.

BACKGROUND:During pregnancy, most women do not meet gestational weight gain (GWG) guidelines, potentially resulting in adverse maternal and infant health consequences. Social environment determinants of GWG have been identified, but evidence on the relationship between neighbourhood violence and GWG is scant. Our study aims to examine the relationship between neighbourhood violence and GWG outside the recommended range. METHODS:We used statewide vital statistics and health care utilization data from California for 2006-12 (n = 2 364 793) to examine the relationship of neighbourhood violence (quarters of zip-code rates of homicide and assault) in the first 37 weeks of pregnancy with GWG (categorized using the Institute of Medicine's pregnancy weight gain guidelines). We estimated risk ratios (RR) and marginal risk differences, and analyses were stratified by maternal race/ethnicity and prepregnancy body mass index. RESULTS:Residence in neighbourhoods with the highest quartile of violence was associated with more excessive GWG (adjusted RR 1.04, 95% confidence interval CI 1.03, 1.05), compared to the lowest quartile of violence; violence was not associated with inadequate GWG. On the difference scale, this association translates to 2.3% more women gaining weight excessively rather than adequately if all women were exposed to high violence compared to if all women were exposed to low violence. Additionally, associations between neighbourhood violence and excessive GWG were larger in non-white women than in white women. CONCLUSIONS:These findings support the hypothesis that violence can affect weight gain during pregnancy, emphasizing the importance of neighbourhood violence as a public health issue.

To determine if cold-water swimmers have substantial differences in BMI, which might have a protective effect against heat loss during swims in cold water without wetsuits, and to determine if obesity is more or less prevalent in cold-water swimmers, we compared the body mass index (BMI) values of 103 recreational open-water swimmers (mean age 54.3 ±10.8 years) to data from various population groups. Swimmers swam consistently throughout the winter months, in the San Francisco Bay (water temperature range: 9.6° C [49.3 ° F] to 12.6° C [54.7 ° F]), without wetsuits. After matching for age and sex, the average BMI of cold-water swimmers (25.9 kg/m²) was lower than the corresponding predicted U.S. average BMI (29.2 kg/m²; p<.001), the predicted California state average BMI (28.0 kg/m²; p<.001), and the predicted San Francisco city average BMI (26.6 kg/m²; p=.047). The average BMI value for cold-water swimmers (25.9 kg/m²) was not significantly different from values of North American masters pool swimmers (25.1 kg/m²; p=.15) or international masters pool swimmers (25.3 kg/m²; p=.16). 10.7% of cold-water swimmers were classified as obese (BMI > 30 kg/m²) vs. 35.7%, 25.8%, and 11.8% of the U.S., California, and San Francisco populations, respectively. The lower or similar BMI values of our swimmers suggest that successful recreational swimming in cold water is influenced by factors other than body habitus, such as acclimatization, heat production while swimming, and most importantly, limiting immersion time. The relatively low prevalence of obesity in our swimmers suggests that cold-water swimming could contribute to a healthy lifestyle.

Propensity score methods, such as subclassification, are a common approach to control for confounding when estimating causal effects in non-randomized studies. Propensity score subclassification groups individuals into subclasses based on their propensity score values. Effect estimates are obtained within each subclass and then combined by weighting by the proportion of observations in each subclass. Combining subclass-specific estimates by weighting by the inverse variance is a promising alternative approach; a similar strategy is used in meta-analysis for its efficiency. We use simulation to compare performance of each of the two methods while varying (i) the number of subclasses, (ii) extent of propensity score overlap between the treatment and control groups (i.e., positivity), (iii) incorporation of survey weighting, and (iv) presence of heterogeneous treatment effects across subclasses. Both methods perform well in the absence of positivity violations and with a constant treatment effect with weighting by the inverse variance performing slightly better. Weighting by the proportion in subclass performs better in the presence of heterogeneous treatment effects across subclasses. We apply these methods to an illustrative example estimating the effect of living in a disadvantaged neighborhood on risk of past-year anxiety and depressive disorders among U.S. urban adolescents. This example entails practical positivity violations but no evidence of treatment effect heterogeneity. In this case, weighting by the inverse variance when combining across propensity score subclasses results in more efficient estimates that ultimately change inference. Copyright © 2016 John Wiley & Sons, Ltd.

A substitution estimator can be used to predict how shifts in population exposures might change health. We illustrated this method by estimating how an upper limit on alcohol outlet density might alter binge drinking in the New York Social Environment Study (n = 4000), and provided statistical code and sample data. The largest differences in binge drinking were for an upper limit of 70 outlets per square mile; there was a -0.7% difference in binge drinking prevalence for New York City overall (95% confidence interval [CI] = -0.2%, -1.3%) and a -2.4% difference in binge drinking prevalence for the subset of communities the intervention modified (95% CI = -0.5%, -4.0%). A substitution estimator is a flexible tool for estimating population intervention parameters and improving the translation of public health research results to practitioners.