Evolution or revolution? The health of New Yorkers under Mayor Bloomberg

Peter Muenning, Daniel Vail and Ryan K. Masters

hss_cohort9-ryan-mastersdaniel121757476_title0hWhen Michael Bloomberg was elected Mayor of New York City (NYC), he set forth an ambitious agenda to efficiently sync municipal agencies. Improving New Yorkers’ health was part of his motivation. For example, expanding parks and bike lanes would not only improve people’s quality of life and expand transportation options, their presence would also encourage healthy behaviours. So, why not create cross-agency agendas that allow parks with bike lanes to be created on city streets? Innovative thinkers were hired and were given an unusual amount of political capital and logistical support to implement their plans.

Sadly, very little was done to actually evaluate the programs that were implemented. When the Bloomberg administration promoted the idea that life expectancy had greatly increased as a result of its coordinated policymaking, some people scratched their heads. Sam Preston and Irma Elo argued that improvements in life expectancy in NYC could be explained by a large inflow of healthy foreign migrants. They made this argument by eloquently showing the influence that immigrants had on the city’s life expectancy.

Even in the absence of immigration or Bloomberg’s coordinated plans, we should have observed a large bump in life expectancy due to gentrification (because rich people live a lot longer than the poor people they push out of the city). While smoking rates declined in the city after the implementation of anti-smoking policies, this decline could be explained by the outflow of smokers and the inflow of non-smokers.

In our paper, “The effects of New York City’s coordinated public health programs on mortality through 2011,” we matched New Yorkers to similar Americans and followed them before and after Bloomberg’s mayoral years. We found that after nearly 3 mayoral terms, there are no clear signs of improvement in New Yorker’s health or longevity that can be clearly attributed to coordinated policies.

If the policies failed to work, it might be because the cityscape has not changed to the extent that Bloomberg and his commissioners had envisioned. The city’s most ambitious ideas met political opposition. For example, the city’s plan to introduce congestion pricing—a tax on vehicles entering downtown Manhattan—was shot down by car advocates as well as corrupt powerbrokers. These groups also greatly limited the number of protected bike lanes that could be installed. The revenue from congestion pricing was meant to pay for the infrastructure improvements that were planned, further limiting the reach and ambition of the city’s infrastructure plans. For example, after all was said and done, virtually all pedestrian plazas were built in Manhattan and Brooklyn because they had to be maintained by costly business improvement districts.

But the failure to materialise a 21st century vision for New York City was not just a story of political opposition. Surprisingly, programs were not rolled out in a random fashion, and comprehensive data were not collected. Instead of using user cell phone data, old fashioned sensors were used to determine where new bike lanes were needed. While people can subjectively attest to the overwhelming success of pedestrian plazas and innovations like the Highline Park, there is no spatiotemporal data to quantify their success. Without data showing that these programs work, it becomes difficult to advocate for further improvements.

This lack of data also makes it difficult to tease one effect out from the next. In our study, we observe that declines in smoking were followed by an increase in lung cancer rates. In fact, longevity gains seen in NYC due to virtually any cause either increased or sputtered during the Bloomberg years. It may be that things would have been much worse without Bloomberg, but we will never know because we didn’t have the data on individual programs or initiatives. For instance, it could be that the increases in lung cancer were due to the September 11 terrorist attacks, which released 300 tons of asbestos into the air, and would have been worse without cigarette taxes and smoking bans in public places.

Likewise, there is a simple reason why overall mortality gains sputtered under Bloomberg. Between 1990 and 2000, the healthy foreign-born population increased by 700,000 people, but only 200,000 more were added between 2000 and 2010. Likewise, the Great Recession slowed gentrification.  In our quasi-experimental models, we mostly account for migration and wealth. We also manage to look at period trends in specific causes of death that are independent of age or cohort effects. But these powerful research tools can only improve on guesswork. Hopefully, cities that look to transform themselves in the future—and we hope there are many—will do so with strong scientific evaluation so we can know for sure what our intuition tells us; the future of public health is (almost) here.

Read more:

Muenning P, Master R, Vail D and Hakes, J. The effects of New York City’s coordinated public health programmes on mortality through 2011. International Journal of Epidemiology 2016: doi: 10.1093/ije/dyw290.


Ryan Masters is assistant professor of sociology and faculty associate in the Population Program and Health & Society Program in the Institute of Behavioral Science at the University of Colorado Boulder. His work examines social differences in U.S. health and mortality trends.

Daniel Vail is a medical student at the Stanford University School of Medicine. Before attending medical school he worked as a quantitative analyst in the Department of Epidemiology, Columbia University Mailman School of Public Health.
Peter Muennig is a Professor of Health Policy and Management at Columbia University. He studies the cost-effectiveness of policy options to maximize population health. He has published well over 100+ article and 4 books.

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