Even in neighboring zip codes in the united states, health outcomes can vary widely.

People living just a few blocks apart may have vastly different opportunities to live a long life in part because of their neighborhood. Unfortunately, significant gaps in life expectancy persist across many United States cities, towns, ZIP codes and neighborhoods. The latest estimates of life expectancy reveal differences down to the census tract level. Use the tool below, and interactive map, to explore how life expectancy in America compares with life expectancy in your area, and resources to help everyone have the opportunity to live a longer, healthier life.

The data for census tracts, counties, and states are for 2018; national-level life expectancy estimates are drawn from provisional data for 2020.

How does where we live affect our opportunity to be healthy?

For the first time in our history, the United States is raising a generation of children who may live sicker and shorter lives than their parents. In 2020, we witnessed the steepest plunge in life expectancy since World War II, largely fueled by the coronavirus pandemic. Reversing this trend will of course depend on healthy choices by each of us. But not everyone in America has the same opportunities to be healthy. We know that the drivers of inequitable social, economic, built, and physical conditions within and across place and race can dramatically reduce opportunities for better health and well-being.

According to the most recent data available from the Centers for Disease Control and Prevention, life expectancy at birth in the United States is 77.3 years—74.5 years for men and 80.2 years for women. Between 2019 and 2020, life expectancy decreased by 3.0 years for the Hispanic population (81.8 to 78.8), by 2.9 years for the non-Hispanic black population (74.7 to 71.8) and by 1.2 years for the non-Hispanic White population (78.8 to 77.6).

In 2018, the National Center for Health Statistics released first-of-its-kind neighborhood-level data on life expectancy through the U.S. Small-Area Life Expectancy Estimates Project (USALEEP), in partnership with RWJF and the National Association for Public Health Statistics and Information Systems (NAPHSIS). The data revealed how life expectancy estimates vary greatly even at the census tract level, from block to block.

In a Culture of Health, we all have the opportunity to live the healthiest life possible, regardless of where we live. Browse the resources below to learn more about what shapes our health, and how to take action to help create healthier places to live, learn, work and play.

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DATA SOURCES

Arias E, Escobedo LA, Kennedy J, Fu C, Cisewski J. U.S. Small-area Life Expectancy Estimates Project: Methodology and Results Summary. National Center for Health Statistics. Vital Health Statistics 2 (181). 2018.

Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019.

Xu JQ, Murphy SL, Kochanek KD, Arias E. Mortality in the United States, 2018. NCHS Data Brief, no 355. Hyattsville, MD: National Center for Health Statistics. 2020.

Arias E, Tejada-Vera B, Ahmad F. Provisional life expectancy estimates for January through June, 2020. Vital Statistics Rapid Release; no 10. Hyattsville, MD: National Center for Health Statistics. February 2021.

Related Resources


03.23.2019

[Editor’s Note: this perspective originally appeared in The Aspen Challenge.]

How does one respond to a teenage audience when a girl asks why the neighborhood her friend lives in, just four miles away, has a lower life expectancy than where she lives? That question was asked by many teenagers at the Dallas and Louisville Aspen Challenge Opening Forums when we talked about health disparities.

Did you know that your zip code is the greatest predictor of how long you are expected to live? Not your blood pressure, not your cholesterol levels, not your genetics. Your zip code.

In Dallas, there is an 18-year difference in life expectancy for residents living only six miles apart. In Louisville, the difference is 15 years: Residents of the mainly African American west end live to 67 years on average, while their counterparts in the eastern half of Jefferson County, which is more than 70 percent white, have an average life expectancy of 82 years (both genders combined). That discrepancy of 15 to 18 years could mean whether or not you see your grandchild graduate, be at your great-grandchild’s first birthday, or simply witness daily pleasures with those you love and experience life.

And the crazy part? The people living in both neighborhoods could be exercising, eating, and living life the same way.

These are examples of health inequities, systematic differences in the opportunities groups have to achieve optimal health, leading to unfair and avoidable differences in health outcomes. Health inequities exist between many groups, whether by gender, race, or age, just to name a few. One study found that graduating from college could add five years to life expectancy. And the Centers for Disease Control shows that babies born to masters-level or higher-educated, middle-class black mothers are more likely to die before their first birthday than babies born to poor white mothers with less than a high school education.

At Health Leads, our foundation was built with college students volunteering in health systems to support patients and families accessing the essential needs in their community — things like food, housing, heat, and transportation. We’ve evolved over 20 years and now know that getting families connected to their local food pantries is important, but does not address the root causes of health inequities. We know that closing the gap in these widely varied life expectancy rates means focusing on securing adequate and affordable housing in your community, consistent and reasonable eligibility requirements to public benefits, like WIC, and transportation systems that serve the predominantly minority neighborhood as reliably and conveniently as they do the nearby white neighborhoods.

We’ve trained over 10,000 students in the past 20-plus years. Together, we’ve learned so much about the realities of all the isms (racism, sexism, ageism, povertyism, etc). Many of these students have now become doctors and public health practitioners; they work to shape equitable health policies, create and spread technology for managing essential needs, and so much more. It is imperative that youth continue to be involved in and lead on this work and have an opportunity to better the health of their communities.

That’s why we were thrilled to accept the opportunity with the Aspen Challenge to present the challenge of health inequities to high school students of Dallas and Louisville. While speaking with the students in Louisville, we asked if anyone was interested in a health-related career — and hands went up all over the room. But, we also wanted them to know that it’s not all doom and gloom. They needed to hear that while the odds are often against the non-majority populations, these groups bring a level of resourcefulness, brilliance, and resilience that is unparalleled. Every day, we see our patients tap into assets like family, friends, church, and neighbors — a wide range of assets in their communities that often go unrecognized.

So how do you combine the neighborhood assets, identify gaps, and develop a solution to reduce the health inequities facing neighborhoods in Dallas and Louisville? We believe these high school students can come up with ideas no one else has considered.

We’re excited to see the solutions in the coming weeks and learn from our next generation of leaders.

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Discussion

Which of the following is the greatest predictor of health outcomes for individuals in the United States?

On average, which of the following is the best predictor of one's health? ANSWER: C. Whether or not you are wealthy. The single strongest predictor of health is our position on the class pyramid.

What are the 4 major determinants of health quizlet?

Determinants of health can be classified in many ways such as physical environment, biological, behavioural, and social.

Which of these is correlated with poor health quizlet?

Which of the following is most closely correlated with poor health? Poverty is more closely related to health status even when controlling for age, gender, race, education, and lifestyle behaviors.

Which of the following best defines the term health?

Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.

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