Launching EpiSimulations.net

Network graph of matched case-control sets from a simulated nested case-control study created on EpiSimulations.net

Network graph of matched case-control sets from a simulated nested case-control study created on EpiSimulations.net

Cluster Doctoral students, Andrew Ratanatharathorn and Stephen Mooney and Cluster Faculty member, Andrew Rundle, recently launched EpiSimulations.net, a suite of tools for demonstrating and modeling methodological issues in epidemiology.  The site uses R Shiny to create interactive simulations that allow the user to conduct a series of “what if” experiments to demonstrate epidemiology principles.  The site currently has modules that demonstrate the extent of bias caused in a study by confounding and exposure misclassification, and the intricacies and trade offs involved in matching in a case control study.  Each module has a set of sliders that allow the user to control the simulation parameters and observe the resulting bias in the study’s estimate of the effect of exposure on disease.

Posted in Methods, Teaching Tools | 1 Comment

13th Place and Health Conference

Favela street art - Rio

Favela street art – Rio

Gina Lovasi presented recent urban health work at the “Evidence for Action in Policy and Programs for Urban Health” plenary session of Place and Health, the 13th International Conference on Urban Health in San Francisco.  Gina described two community health diagnosis efforts, designed to address health needs and opportunities in vibrant but vulnerable areas of New York City and Rio de Janeiro by considering the entire community as a ‘patient’ in need of treatment recommendations.  These focused local research translations complemented the global and national perspective presented by co-panelists Eugenie Birch and Waleska Teixeira Caiaffa.  A key take home message: local residents and stakeholders needed information not only about what investments in public spaces could improve health, but also what conditions or processes would maximize those benefits.

Posted in Neighborhood Environments, Social Environments, Urban Health | Leave a comment

Who are smokers today? Implications for public health and research

Kerry Keyes and colleagues recently published a new article looking at changes in the relationship between smoking and psychiatric disorders across successive birth cohorts in the twentieth century.  They find that as rates of smoking decreased through the latter half of the twentieth century, associations between smoking and psychopathology increased.

More from Keyes on this work and its implications below.

The fact that individuals who smoke are different than individuals who don’t smoke has beguiled observational epidemiology since the inception of studies aimed at assessing causal effects of smoking on health. Differences (on average) between smokers and nonsmokers include not only other substance use (e.g. alcohol consumption, caffeine intake), but also personality, temperament, and a myriad of other factors. Even in the early generation of tobacco research, Yurlshalmy (1971) noted that women who did not smoke when pregnant “in general appeared to live at a much slower and moderate pace than the smokers”.

Sandy Dee from Grease

Sandy Dee from Grease

I imagine Sandy Dee versus Rizzo for that particular analogy – though remember what happens when Sandy curls her hair and dons that exceptional black jump suit at the end of Grease – immediately a cigarette appears in her painted red lips.  Not slow and moderate anymore Sandy!

The effects of smoking on health are so profound, consistent, and strong that the confounding of outcomes by factors that differ between smokers and nonsmokers did not (well, after several decades of strong evidence) deter the translation of epidemiological science into prevention implementation. Across the last 30 years, we have seen remarkable decreases in the proportion of the population in the United States who smoke. But this public health success begs a new question, with substantial implications for research – are people who continue to smoke today different than people who smoked 50 years ago? Continue reading

Posted in Anxiety, Depression, Mental Health, Smoking | Leave a comment

IPV in late adolescence and young adulthood and subsequent cardiovascular risk in adulthood.

The Purple Ribbon Campaign was launched to raise awareness about domestic violence

Shakira Suglia and colleagues recently published an article describing the relation between Intimate partner violence (IPV) in adolescence and young adulthood and cardiovascular risk in adulthood. Using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) the risk of developing cardiovascular disease (CVD) over a 30-year time frame was estimated. A Framingham-based prediction model was used to summarize participants’ 30-year risk for CVD using data on age, sex, blood pressure, use of antihypertensive medication, body mass index, and diabetic and smoking status.  Small but statistically significant increases in CVD risk among those exposed to IPV victimization and perpetration were noted. A one-standard deviation increase in IPV victimization was associated with a 0.28% (95% CI: 0.03, 0.54) increase in CVD risk. Similarly, IPV perpetration was also associated with CVD risk (0.33% (95% CI: 0.03, 0.62. Interestingly no differences by sex were detected.

Past work on the relation between intimate partner violence and cardiovascular disease has produced mixed findings.  In a systematic review of that literature, Suglia noted that most studies examining the role of IPV on cardiovascular health are of cross-sectional nature and are limited by self-reported outcomes. The present study addresses those limitations by utilizing a longitudinal study design and relying on objectively measured risk factors of cardiovascular health. In addition, most previous studies have focused solely on female populations and have only considered IPV victimization and not perpetration. In these analyses, which include both males and females, the increased CVD risk was similar for both men and women. Furthermore the co-occurrence of victimization and perpetration was high (17% among males and 26% among females) warranting the need to explore the joint effect of both victimization and perpetration.  In a model jointly exploring these two factors, all violence types were associated with increased CVD risk but only prior experience of both victimization and perpetration reached statistical significance (0.62%, 95% CI: 0.01, 1.22). Given the high prevalence of IPV among adolescents and young adults a greater effort is needed to prevent its occurrence. Efforts to prevent smoking among adolescents are common, preventing other non-traditional risk factors, such as violence, may also aid in the promotion of health and prevention of future cardiovascular disease.

Posted in Cardiovascular Disease, Intimate Partner Violence | Leave a comment

Gender-Based Violence and Mood/Anxiety and Substance Use Disorders

In a recent paperKeyes and colleagues estimated the lifetime prevalence for women experiencing Gender-Based Violence (GBV) as being 25%.  Women who had experienced GBV had 3.6 and 2.5 times the odds, respectively, of meeting lifetime mood/anxiety and substance use disorder criteria. The number of different types of GBV experienced and the number of incidents of GBV were associated with risk for both types of disorders in a dose-response fashion.  When examined simultaneously, number of types of GBV experienced was the stronger predictor of mood/anxiety and substance use disorders. First experience of GBV during childhood and adolescence was associated with a larger increase in the odds of mood/anxiety and substance use disorders than first experiences during adulthood.

The researchers used data from 20,089 women from wave 2 (2004-2005) of the National Epidemiologic Survey of Alcohol and Related Conditions, a nationally representative health surveillance survey.

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The Race of Perpetrators of Mass Shootings Can Affect the Public’s Perceptions About Racial and Ethnic Groups.

Larry Yang and colleagues just published new work showing how the race or ethnicity of perpetrators of mass shootings can affect the public’s perceptions about racial and ethnic groups.  If an individual hearing or reading about the shooting attributes the shooting to racial factors, they are more likely to think negatively about the entire racial group if the perpetrator’s race is different from their own. For example, they found that if a European-American person reads about the Virginia Tech shooting, where the shooter was Korean-American, and attributes the shooting at least in part to the shooter’s race, they think negatively about all Korean-Americans. But a European-American reader’s negative attitudes do not generalize to the shooter’s racial group if the shooter is from the same racial group as the reader. So if a European-American person reads about the Columbine shooting where the shooter was European-American and attributes the shooting at least in part to the shooter’s race, they do not think negatively about all European-Americans.

Also, in another condition where they primed the European American study participants to think the shooting was ‘atypical’ of the shooter’s race (i.e., that the shooting was not typical of all Korean-Americans in the Virginia Tech event), European Americans, instead of attributing the shooting to race and having negative beliefs about Korean Americans, would attribute the shooting to mental illness factors instead.

This research thus suggests that mass shootings, when committed by a person of color and when the act is attributed to their race, might affect attitudes towards that person’s entire race. These findings thus have importance for the shaping of racial attitudes in society.

Posted in Race, Violence | Leave a comment

#Schizophrenia: Use and misuse on Twitter

TwitterBirdStigmatization of individuals with mental illness is a clinical and public health concern and the prevention of stigma is an evolving research field.  Larry Yang and colleagues recently published research showing that social media can provide new avenues for the spread of stigma.  He and his colleagues compared the use of the words #schizophrenia, #schizophrenic, #diabetes, and #diabetic over a forty day period on Twitter.  A total of 1,838 Tweets containing one of these four hashtags were randomly sampled from a data set of Tweets collected over a forty day time period (12 September 2013 to 22 October 2013).  Tweets about schizophrenia were more likely to be negative, medically inappropriate, sarcastic, and used non-medically than tweets about diabetes. The adjective (“schizophrenic”) was even more often negative, medically inappropriate, sarcastic, and used non-medically. These findings have considerable implications for efforts to combat stigma, particularly for youth anti-stigma efforts.

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Social Epi Radio: Show Tunes

SERadio_logo3Musical theater frequently deals with themes of social disparities and hardship – for instance Oliver or Les Misérables.  Lisa Bates and her students in the Department of Epidemiology’s Social Epidemiology Course compiled a list of performances and themes in musicals that are related to major concepts of interest to social epidemiologists.

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Measuring Pedestrian Activity using GPS Data

New work led by Gina Lovasi and Steve Mooney was published in the American Journal of Public Health looking at the effects of building density and tree canopy cover in NYC on the accuracy of GPS data for measuring distances traveled while walking.  GPS way point data were collected using GPS loggers during structured walks in high and low building density and high and low tree cover streets.  The work shows that measures of distances traversed estimated from successive GPS way points tend to overestimate actual distances walked, and more so in areas with high building density and high street tree coverage.

GPS data captured during a walk on low and high building density streets. Images by Daniel Sheehan

GPS data captured during walks on low and high building density streets. Images by Daniel Sheehan

 

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Neighborhood Physical Disorder Maps

The Journal of Maps recently published an article co-authored by Andrew Rundle, Gina Lovasi and Stephen Mooney and others, showing a high resolution map of neighborhood physical disorder in New York City.

Physical disorder – the deterioration of urban spaces owing to social forces favoring neglect and abandonment – has long been of interest to social scientists [1, 2].  Criminologists and sociologists have debated the controversial ‘broken windows’ theory that disorder encourages violent crime [3, 4]. Separately, psychologists and psychiatric epidemiologists have investigated whether living amidst disorder negatively affects mental health, not only directly as stress induced by encountering a chaotic environment triggers earlier cognitive decline [5] but also indirectly as residents adopt coping mechanisms such as alcohol use that themselves trigger longer-term harms [6].

The data underlying the map was collected using neighborhood audits implemented via Street View. In addition to data collection in NYC, the team collected neighborhood physical disorder data from San Jose, California; Detroit, Michigan; and Philadelphia, Pennsylvania.  Below is a heat map of Philadelphia showing the distribution of neighborhood physical disorder across the city.

Neighborhood physical disorder in Philadelphia. Darker ares within Philadelphia have the highest levels of physical disorder.

Neighborhood physical disorder in Philadelphia. Darker areas within Philadelphia have the highest levels of physical disorder.

 

 

Posted in Neighborhood Environments, Physical Disorder, Social Environments | Leave a comment