Place across an American life

Low birthweight was 7.4% (95% CI 7.2% to 7.7%)7.4% percent of live births under 2,500 gramsEstimandbirths-weighted mean of county shares (the pooled share), bootstrap interval over countiesInterval95% CI 7.2% to 7.7%n57 countiesWeightsbirths in each countyPopulationlive births in the least deprived tenth of the named counties by county deprivation rankPeriodbirths in 2018 to 2024SourceCDC WONDER natality of births in the least deprived tenth of the counties that CDC WONDER names individually and 9.7% (95% CI 9.2% to 10.3%)9.7% percent of live births under 2,500 gramsEstimandbirths-weighted mean of county shares (the pooled share), bootstrap interval over countiesInterval95% CI 9.2% to 10.3%n58 countiesWeightsbirths in each countyPopulationlive births in the most deprived tenth of the named counties by county deprivation rankPeriodbirths in 2018 to 2024SourceCDC WONDER natality in the most deprived, for births in 2018 to 2024. Life expectancy at birth was 82.3 (95% CI 82.0 to 82.6)82.3 years of life expectancy at birthEstimandpopulation-weighted mean of tract life expectancy in a tenth of tracts (rank bins of the ADI; tracts with tied ranks fall in the same tenth), bootstrap interval over countiesInterval95% CI 82.0 to 82.6n7,820 tractsWeightsACS 2019-2023 tract populationPopulationresidents of tracts in the least deprived tenth of tracts by ADI national percentilePerioddeaths in 2010 to 2015 (USALEEP, area-weighted onto 2020 tracts); ADI 2023; ACS 2019-2023 populationSourceUSALEEP life expectancy years in the least deprived tenth of census tractsCensus tractA small area drawn by the Census Bureau to stand in for a neighborhood. Boundaries are redrawn after each decennial census. and 74.0 (95% CI 73.7 to 74.3)74.0 years of life expectancy at birthEstimandpopulation-weighted mean of tract life expectancy in a tenth of tracts (rank bins of the ADI; tracts with tied ranks fall in the same tenth), bootstrap interval over countiesInterval95% CI 73.7 to 74.3n7,844 tractsWeightsACS 2019-2023 tract populationPopulationresidents of tracts in the most deprived tenth of tracts by ADI national percentilePerioddeaths in 2010 to 2015 (USALEEP, area-weighted onto 2020 tracts); ADI 2023; ACS 2019-2023 populationSourceUSALEEP life expectancy years in the most deprived, for deaths in 2010 to 2015.[1] The share of renter households that spend more than 30%30% percent of household incomeEstimandHUD's line for a housing cost burden: housing costs above this share of household incomeWeightsnone (definition)Populationhouseholds in the HUD CHAS tabulationPeriod2018 to 2022SourceHUD CHAS housing affordability of their income on housing was 44.4% (95% CI 41.9% to 46.7%)44.4% percent of renter households with housing costs above 30% of incomeEstimandpooled share of the tenure's households with the burden over tracts in the tenth, bootstrap over countiesInterval95% CI 41.9% to 46.7%n8,208 tractsWeightshouseholds of the tenure with a computed burdenPopulationrenter households in tracts with an Area Deprivation Index (tenths hold near-equal numbers of tracts; tracts with equal ranks stay together), least deprived tenthPeriod2018 to 2022; Area Deprivation Index 2023SourceHUD CHAS housing affordability in the least deprived tenth of tracts and 47.6% (95% CI 46.6% to 48.4%)47.6% percent of renter households with housing costs above 30% of incomeEstimandpooled share of the tenure's households with the burden over tracts in the tenth, bootstrap over countiesInterval95% CI 46.6% to 48.4%n8,207 tractsWeightshouseholds of the tenure with a computed burdenPopulationrenter households in tracts with an Area Deprivation Index (tenths hold near-equal numbers of tracts; tracts with equal ranks stay together), most deprived tenthPeriod2018 to 2022; Area Deprivation Index 2023SourceHUD CHAS housing affordability in the most deprived, for 2018 to 2022, and the means of all ten tenths stayed within 3.63.6 percentage points, largest minus smallest renter share with housing costs above 30% of income among the ten tenthsEstimandlargest minus smallest of the ten tenth means (a range of estimates, no interval)n10 tenths of tractsWeightshouseholds of the tenure with a computed burdenPopulationrenter households in tracts with an Area Deprivation Index (tenths hold near-equal numbers of tracts; tracts with equal ranks stay together)Period2018 to 2022; Area Deprivation Index 2023SourceHUD CHAS housing affordability points of one another. Among renters with low incomes, at or below 80%80% percent of HUD area median family incomeEstimandthe income line for a low-income household: income at or below this share of HUD's area median family income (HAMFI)Weightsnone (definition)Populationhouseholds in the HUD CHAS tabulationPeriod2018 to 2022SourceHUD CHAS housing affordability of the area median family income, the share was higher in the least deprived tenth, 75.3% (95% CI 72.6% to 78.1%)75.3% percent of low-income renter households with housing costs above 30% of incomeEstimandlow-income households (at or below 80 percent of HAMFI) with a burden over low-income households of the tenure, pooled over tracts in the tenth, bootstrap over countiesInterval95% CI 72.6% to 78.1%n7,840 tractsWeightslow-income households of the tenurePopulationlow-income renter households in tracts with an Area Deprivation Index, least deprived tenthPeriod2018 to 2022; Area Deprivation Index 2023SourceHUD CHAS housing affordability against 62.5% (95% CI 61.6% to 63.3%)62.5% percent of low-income renter households with housing costs above 30% of incomeEstimandlow-income households (at or below 80 percent of HAMFI) with a burden over low-income households of the tenure, pooled over tracts in the tenth, bootstrap over countiesInterval95% CI 61.6% to 63.3%n8,194 tractsWeightslow-income households of the tenurePopulationlow-income renter households in tracts with an Area Deprivation Index, most deprived tenthPeriod2018 to 2022; Area Deprivation Index 2023SourceHUD CHAS housing affordability.

The three comparisons rank places by the Area Deprivation IndexArea Deprivation Index (ADI)A score that ranks neighborhoods by income, education, employment and housing conditions drawn from the American Community Survey. In this book a higher national percentile means a more deprived neighborhood. (ADI), a national percentile built from census measures of income, education, employment and housing.[2] Low birthweight and life expectancy are worse at each step toward the deprived end of the ranking. Renters' cost burden changes little along it, and among low-income renters it runs the other way. The three comparisons come from different records, places and years. ZIP Code Destiny follows comparisons like these from birth through old age. It asks where a pattern holds, where it fails, and how the answer changes when the comparison becomes more specific.

The title names that inquiry. An address places a person among schools, housing, jobs, services and other residents, and it also reflects who can afford to live there or chooses to. The book examines those differences without assuming that a location settles anyone's future. The word "destiny" is a proposition to test, and each chapter reports how much its evidence supports. "ZIP code" is shorthand as well. Most chapters count census tracts, counties, school districts or survey respondents, and the unit is named in every chapter.

The questions that connect the chapters

The life course sets the order of the questions. At birth they concern the health of newborns and survival through the first year. School brings achievement, gaps between groups of students, and exclusion through discipline. The move into adulthood brings college, teen births and the adult incomes of children raised in different neighborhoods.

In the working years an address appears in the data as a home value, a mortgage application, a rent burden, a job or a supply of doctors. Some records describe the people who live in a place, and others describe the employers or institutions located there. Keeping the two apart is part of the work. A county with well-paid jobs need not have residents who hold them, and a neighborhood of expensive homes can have renters who struggle to pay.

Health, early death and well-being add further measures: illness and health behavior beside access to care, the geography of different causes of death, social connection, and people's own ratings of their lives. The later chapters take up disability, retirement income, Medicare and well-being at different ages.

Across these subjects the aim is to find which patterns recur and where they stop. Some outcomes change steadily with neighborhood deprivation, as birthweight and life expectancy do. Others change little with it, as renters' cost burden does, follow another ordering, or change direction when the comparison moves inside a county. Groups in the same place can also reach different outcomes. These departures show what a general account of disadvantage can explain and what it cannot.

The order does not follow one person from a birth certificate to a death certificate. The chapters draw on different populations and periods. Some sources follow birth cohorts into adulthood, some interview different people each year, and some describe a place in a single year. The life course orders the questions without turning these records into one biography.

A view no single source provides

The chapters draw on administrative records, surveys and estimates that other researchers publish. Birth and death records describe the start and the end of life. Education data compare school districts. The Opportunity Atlas reports the adult incomes of children raised in different places, from linked records that its researchers assembled. Housing and lending records describe prices, rents, applications and eviction filings. Employment records separate jobs at workplaces from jobs held by residents. Health and well-being surveys ask about experiences that no tax return or Medicare payment records.

Each source was made for its own purpose, and their boundaries and dates do not always line up. A census tract, a school district and a county can describe different settings even when their names suggest the same place. Each chapter therefore states what its record counts, whom it covers and what comparison it allows. An eviction filing is a petition in court and not a completed eviction (Chapter 4.4, Renting, affordability and eviction). A college earnings figure describes the former students its source covers (Chapter 3.2, College access, price and earnings). A neighborhood estimate of an illness can be a modeled estimateModeled estimateA figure produced by a statistical model instead of a direct count or measurement, usually for small areas where direct data are thin, borrowing strength from surveys, neighboring areas or other data. Neighboring areas can share errors, so single extremes call for caution. and not a count of residents who have it.

The sources are not always independent of one another. The CDC PLACES neighborhood health estimates draw on the Behavioral Risk Factor Surveillance System and on census inputs that the deprivation index also uses, so agreement between them is not an independent confirmation.[3] A change of source can also show what a map cannot, such as whether the adults who report a behavior are the same adults who report a given household income (Chapter 5.2, Health behaviors, person by person). The chapters keep these records apart and do not combine them into one score of a good or a bad place to live.

How the chapters compare places

Many chapters map an outcome to show where it is high or low, and most set it against income or neighborhood deprivation. A distribution shows how widely places differ and whether a national average describes many of them. The ADI supplies the recurring ranking, and the book also examines the ranking itself, what its ingredients emphasize and how it treats expensive places (Chapter 10.2, The anatomy of a deprivation index), and what happens when neighborhoods are combined into counties (Chapter 10.3, A deprivation index at two zooms). A common measure makes the chapters comparable, and it can miss differences that matter, as the renter numbers above suggest.

The next comparison usually narrows the question. A national relationship can reflect the mix of regions in the country, and comparing neighborhoods inside the same county removes that source of difference (Chapter 10.1, Gradients, slopes and variance). Comparing groups along the same ranking shows whether a difference between them persists at every level of it. In County Health Rankings data for births in 2016 to 2022, low birthweight was 12.4% (95% CI 11.9% to 12.8%)12.4% percent of live births under 2,500 gramsEstimandpooled share of births, bootstrap interval over countiesInterval95% CI 11.9% to 12.8%n133 countiesWeightsbirths to mothers of the group in each countyPopulationlive births to non-Hispanic Black mothers in the least deprived quartile of the named counties by deprivation rankPeriodbirths in 2016 to 2022SourceCounty Health Rankings of births to non-Hispanic Black mothers in the least deprived quarter of the counties WONDER names, against 7.6% (95% CI 7.5% to 7.7%)7.6% percent of live births under 2,500 gramsEstimandpooled share of births, bootstrap interval over countiesInterval95% CI 7.5% to 7.7%n145 countiesWeightsbirths to mothers of the group in each countyPopulationlive births to non-Hispanic white mothers in the most deprived quartile of the named counties by deprivation rankPeriodbirths in 2016 to 2022SourceCounty Health Rankings of births to non-Hispanic white mothers in the most deprived quarter (Chapter 1.1, Birthweight and preterm birth). Survey responses from individuals answer a different problem, because a pattern across neighborhood averages need not describe the people inside the neighborhoods (ecological inferenceEcological inferenceDrawing conclusions about individuals from data about places or groups. A pattern across counties need not hold for the people inside them.).

The chapters also show how much a finding depends on measurement and coverage. Counting every county once answers a different question from counting counties by their residents. A missing value is not a zero. An interval around an estimate describes its uncertainty under the stated method, while a band of places describes how widely the places differ. Each chapter explains these points where they change the reading of a result, and its methods section gives the full procedure.

No chapter has to find the pattern of the one before it. Traffic pollution is lower in more deprived tracts across the country and higher in more deprived tracts within a county (Chapter 5.3, Air pollution), a result that revises the national picture and is reported as found.

One comparison followed in detail

Chapter 6.1, Place and the length of a life takes the life expectancy contrast above through the steps that the other chapters apply to their own outcomes. The difference between the least and the most deprived tenths of tracts is 8.3 (95% CI 7.9 to 8.7)8.3 years of life expectancy at birth lower in the most deprived tenth of tractsEstimanddifference between the population-weighted mean life expectancy of the least and the most deprived tenth of tracts, bootstrap interval over counties (draws shared by the two means)Interval95% CI 7.9 to 8.7n7,844 tractsWeightsACS 2019-2023 tract populationPopulationresidents of non-institutional tracts in the 50 states and DC with a life expectancy estimate and an ADI rankPerioddeaths in 2010 to 2015 (USALEEP, area-weighted onto 2020 tracts); ADI 2023; ACS 2019-2023 populationSourceUSALEEP life expectancy years, with an interval from resampling whole counties. Both averages are weighted by population and rest on modeled estimates for non-institutional tracts with the required data, and they describe tracts and not the lifespan of any resident. The chapter asks whether the ordering holds across the middle of the deprivation scale, what a county average leaves out, how far apart nearby neighborhoods are under a stated rule, and how much of the spread among tracts is estimation error. The deprivation measures describe 2019 to 2023, after the deaths behind the estimates, and that timing limits what the comparison can show.

The same chapter separates its description of places from the question of what moving would do to a family. It reports a randomized housing-voucher experiment in its own box, labeled with the study's design, and the book keeps every such study apart from its own comparisons. Life expectancy is one example of the method. It does not stand in for birth, school, housing or well-being, and the book does not use it to rank other parts of life.

How the book is organized

Cradle and climb begins with birth and infancy and moves through school to the start of adult life, with chapters on birth outcomes, test scores, discipline, college, teen births and adult income. The grind covers the working years in four parts: home and money (home values, lending, work, rent and eviction), health and the body (behaviors, chronic conditions, pollution and the supply of care), early death (life expectancy and the causes of death before old age), and connection and well-being (civic life, partnership, distress and how people rate their lives).

The ledger turns to old age and then to the whole map, with chapters on disability, retirement, Medicare and well-being across ages, followed by chapters that group neighborhoods by their measured characteristics and look for places whose outcomes differ from a model's prediction. A type summarizes a set of places, and a model's residual records what the model leaves out, and neither identifies a policy that works. The factory explains how the estimates are made, from gradients and the construction of the deprivation index to geographic scale, the grouping of places, and counts that the sources withhold. A reader can consult it beside any chapter or start there.

Diagram

The book compares places across the life course, then examines how the comparisons are made

The volumes are read in order. Cradle and climb covers Birth, School and The climb. The grind covers Home and money, Health and the body, Early death, and Connection and well-being. The ledger covers Old age, then sets The whole map apart as a synthesis across places. A strip of questions repeats across the volumes: where outcomes differ, how they vary with deprivation, what changes within a place or between groups, and whether the pattern holds for individuals. A separate methods volume, The factory, lists the chapters on how the comparisons are made. The chapters use different datasets and populations, and the diagram does not follow one person through life.

Place across the life course

Reading order

1. Volume 1

   Cradle and climb

   Birth to adult life

   • Birth
   • School
   • The climb

2. Volume 2

   The grind

   The working years, by domain

   • Home and money
   • Health and the body
   • Early death
   • Connection and well-being

3. Volume 3

   The ledger

   Later life and synthesis

   • Old age

   Synthesis

   • The whole map

   Types, change and exceptions

Questions repeated throughout

• Where do outcomes differ?
• How do outcomes vary with deprivation?
• What changes within a place, or between groups?
• Does the pattern hold for individuals?

Volume 4

The factory

How the comparisons are made

• Gradients, slopes and variance
• The anatomy of a deprivation index
• A deprivation index at two zooms
• Families of places
• Suppressed counties in death data

The chapters use different datasets and populations. No one person is followed through life.

The sequence follows the life course, and the subjects are not confined to particular ages. Housing and pollution concern children as well as adults, disability can begin long before retirement, and social connection matters throughout life. The order gives a readable route through related questions and does not assign each exposure to an age.

Reading the book

Reading in order begins with Chapter 1.1, Birthweight and preterm birth. The contents page lists every chapter with its finding, and reading paths connect chapters that ask related questions across the volumes, among them the argument in eight chapters, differences inside one county, race and place, outcomes that do not follow the gradient and methods first.

Three conventions run through every chapter. A map or a chart shows gray where a value is missing or withheld and never draws it as zero. Descriptions of places use verbs that describe, such as "is higher where" and "moves with", and causal verbs appear only in boxes that report a study with a stated design. Each estimate carries its unit, its population, its period and, where it has one, an interval. The reading guide explains these conventions and the kinds of evidence behind each claim. The contents also list planned chapters, which describe questions the book has not yet answered.

What these data cannot show

Most of the book's own analyses describe places. People differ in where they live, and places differ in who lives in them. Comparing more similar places or groups narrows an explanation without ruling out every alternative, and a relationship between neighborhood conditions and an outcome does not show what would happen to a person who moved or what a policy would change. Studies with experiments or other stated designs bear on those questions, and the book reports them separately, for the populations, programs and outcomes they studied.

The numbers that open this introduction come from different units, sources and years: counties for births in 2018 to 2024 (and in 2016 to 2022 for the comparison by mother's race), tracts for deaths in 2010 to 2015, and tracts for housing costs in 2018 to 2022, each ranked on a deprivation index for 2019 to 2023. They are not measurements of the same people. Some places and groups are missing from the records, some values are withheld, some estimates come from models or from data collected years apart, and several chapters describe cohorts born decades ago and not conditions today. Each chapter states these limits because they decide which comparisons are informative and which questions stay open.

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Data sources

• CDC WONDER natalityLow birthweight by county deprivation tenth, 2018 to 2024, as reported in chapter 1.1Years: 2018-2024 · Weights: births · License: Public domain (NCHS, CDC); WONDER data-use restrictions apply
• County Health RankingsLow birthweight by mother's race and county deprivation quartile, births in 2016 to 2022, as reported in chapter 1.1Years: 2024 release · Weights: births · License: CC BY 4.0 (University of Wisconsin Population Health Institute)
• USALEEP life expectancyLife expectancy at birth by tract deprivation tenth, deaths in 2010 to 2015, as reported in chapter 6.1Years: 2010-2015 · Weights: ACS 2019-2023 tract population · License: Public domain (NCHS, CDC)
• HUD CHAS housing affordabilityHousing cost burden of renter households by tract deprivation tenth, 2018 to 2022, as reported in chapter 4.4Years: 2018-2022 · Weights: renter households with a computed burden · License: Public domain (U.S. federal)
• Area Deprivation IndexNeighborhood Atlas Area Deprivation Index 2023, the ranking behind every comparison aboveYears: 2023 release (version 4.0.1; built on ACS 2019-2023) · Weights: as in each chapter · License: Free for non-commercial use; cite the Neighborhood Atlas and Kind and Buckingham

All data sources

Methods

This introduction computes nothing. Each number it prints is copied, with its population, period, weights and interval, from the chapter that estimates it, and the comparisons come from different sources, units and years.

References

1. Arias, Elizabeth; Escobedo, Luis A.; Kennedy, Jiaquan; Fu, Chenxi; Cisewski, Jodi (2018). U.S. Small-area Life Expectancy Estimates Project: Methodology and Results Summary. Vital and Health Statistics, Series 2, Number 181, National Center for Health Statistics. www.cdc.gov/nchs/data/series/sr_02/sr02_181.pdf
2. Kind, Amy J. H.; Buckingham, William R. (2018). Making Neighborhood-Disadvantage Metrics Accessible: The Neighborhood Atlas. New England Journal of Medicine 378(26): 2456-2458. doi:10.1056/NEJMp1802313
3. Greenlund, Kurt J.; Lu, Hua; Wang, Yan; Matthews, Kevin A.; LeClercq, Jennifer M.; Lee, Benjamin; Carlson, Susan A. (2022). PLACES: Local Data for Better Health. Preventing Chronic Disease 19: 210459. doi:10.5888/pcd19.210459

How to cite

@misc{singh2026placeacrossanamericanlife,
  author = {Singh, Vishal},
  title = {Place across an American life},
  year = {2026},
  url = {https://vishalsingh.org/zipcode/place-across-an-american-life},
  note = {In ZIP Code Destiny. Published 11 October 2026.}
}