Population growth is concentrated in the South, but varies across markets
Local demographic composition diverges significantly from national averages
How is the demographic composition of the U.S. changing?
Birth rates are declining as the population ages
Mobility is declining, with moves concentrated in the Sunbelt
Net migration is decreasing across every U.S. metro area
What is the health economy context?
Demographics are reshaping where care is needed, who pays for it and who seeks it
Demographics and migration shape market-level demand
How do demographics impact health economy stakeholders?
Life sciences companies and providers need to prepare for a growing senior population
Slower population growth and affordability pressures may exacerbate disparities in access to care
While many health economy stakeholders know the mantra that "healthcare is local," few fully understand the factors that drive that variation. Population demographics – including age, sex, income, education and ethnicity – are among the most influential and dynamic factors that shape demand for healthcare. A patient’s demographic characteristics impact their care-seeking behaviors, ability to pay, care delivery preferences, health-related needs and trust in the healthcare system. As a result, demographic factors are a foundational input to evidence-based strategy.
Importantly, the demographics of a given population are unique to each market and change unevenly across regions, states, counties, cities and ZIP codes. Amid tepid growth in overall healthcare demand but worsening patient acuity, stakeholders must closely examine how populations are evolving to accurately anticipate future disease burden, ensure equitable access to care and sustain their own financial stability. In an era of constant demographic transformation, the ability to anticipate and adapt to demographic change will be essential for providers, payers, life sciences, policymakers and industry leaders alike.
Demographics refer to the statistical characteristics of a population and can be used to understand social, economic and healthcare trends. Many demographic segments exist, including age, sex, income, educational attainment, race and ethnicity and geographic location. Within healthcare, these characteristics contribute to important concepts like disease burden and access to care. For example, older adults have a disproportionate burden of chronic conditions (e.g., heart disease, diabetes and dementia), while infants and young children are more vulnerable to conditions like respiratory syncytial virus (RSV). Income is one of the strongest predictors of access to care, as low-income individuals are more likely to delay or forgo care due to cost. Race and ethnicity further compound these disparities. For example, Black women in the U.S. have maternal mortality rates more than three times higher than White women.1 These demographic disparities reflect not only differences in underlying health status, but also variation in access to high-quality care, continuity of coverage and provider bias. Insurance coverage and payer type further shape access, as uninsured and Medicaid populations face higher rates of unmet need. Geographic location adds another layer, as rural populations often contend with more pronounced provider shortages and longer travel distances to accessing specialty care. Understanding how these demographic factors intersect is essential for meeting the needs of distinct populations.
Demographics can be analyzed at every level of geography, from national trends down to the region, state, county, city or ZIP code. With more specificity comes more variation, which has major implications for how healthcare stakeholders assess issues related to demand, disease burden, access to care and payer mix.
To this point, nationally, the U.S. population grew 0.5% – from 340.0M to 341.8M – between 2024 and 2025. Based on this datapoint alone, a health system strategy might be built upon the assumption that demand is relatively flat within the respective market or markets. However, population-level demographic changes at the state level begin to reveal the importance of localized analysis. Between 2024 and 2025, state-level population growth ranged from as low as -0.3% in Vermont to as high as 1.5% in South Carolina (Figure 1).
Examining state-level growth rates reveals a broader geographic spread, with the fastest growing states spanning both the South and West – South Carolina (1.5%), Idaho (1.4%), North Carolina (1.3%), Texas (1.2%) and Utah (1.0%) (Figure 2). In terms of real numbers, the states with the highest population growth were concentrated in the South, led by Texas, Florida, North Carolina, Georgia and South Carolina, all which had population increases exceeding 75,000. In contrast, the population of Vermont declined by 0.3% and Hawaii, West Virginia and New Mexico declined by 0.1%. These states also had the largest numeric population declines, along with California.
There is also meaningful variation that occurs within a state. For example, Myrtle Beach-Conway-North Myrtle Beach, SC (3.2%) and Spartanburg, SC (2.8%) both grew faster than South Carolina overall (1.5%). Variation can work in the opposite direction as well – even within fast-growing states like Texas (1.2%), market-level trends diverge, with Austin-Round Rock-San Marcos, TX increasing by 2.1%, but Plainview, TX declining by 1.1%.
These findings reveal that population growth is concentrated in a subset of states – particularly in the South – even as overall U.S. population growth slows. At the same time, differences between numeric and percentage growth highlight how large states drive absolute population gains, while smaller states might experience faster relative growth. Most importantly, these different layers highlight how national trends can mask substantial variation at the state and market level – reinforcing that demographics must be evaluated locally rather than inferred from crude averages.
Like population growth, other demographic characteristics can, and should, be analyzed across varying levels of geographic specificity. For example, while the overall U.S. and the South have a relatively similar age distribution, the South has a slightly higher proportion of child and adolescent residents (ages 0-19) and a slightly lower proportion of those ages 20-44 (Figure 3). More specifically, North Carolina has an older population (39.4), relative to the South overall (38.8). At a more localized level, the Charlotte-Gastonia-Concord, NC-SC core-based statistical area (CBSA) has a higher concentration of adults ages 20-44 and 45-64 than in North Carolina – 60.0% vs. 58.2%. Compared to the Charlotte CBSA, Mecklenburg County, NC has fewer seniors (i.e., ages 65 and older), resulting in an average age that is 5.0 years younger. In North Carolina ZIP code 28202, adults ages 20-44 account for a majority (64.3%) of the population, 30.9 percentage points higher than the state-level distribution. These variations in age distribution highlight how demographic characteristics change as the geographic unit of analysis becomes increasingly localized – shaping not just the level of healthcare demand, but the type, intensity and setting of services required, as younger populations might drive demand for outpatient, behavioral health and reproductive services, while older populations might require more chronic disease management, specialty care and inpatient utilization.
Certain demographic factors are also likely to vary more than others. For example, across Washington, South Carolina and Arizona, three geographically diverse states, the proportion of men ranges from 48.8% in South Carolina to 50.4% in Washington, while the proportion of residents earning more than $100,000 annually ranges from 35.1% in South Carolina to 49.7% in Washington (Figure 4). Educational attainment follows a similar pattern, with 41.1% of Washington residents holding a bachelor’s or graduate degree, compared to 33.3% in South Carolina and 34.7% in Arizona.
In this example, the observed differences in income and education will likely be a larger differentiator in patterns of healthcare demand than the proportion of men in each state. Higher-income and more highly educated populations may be better positioned to utilize more preventive, elective and specialty services, reflective of a higher likelihood of discretionary income, more comprehensive health insurance coverage and potentially a higher degree of health literacy. In contrast, lower-income and less-educated populations are more likely to delay care, rely on acute care and experience.2,3 Ultimately, understanding the relationship between demographic characteristics and healthcare demand is driven by a complex interaction of demographic and socioeconomic conditions – shaping who seeks care, when they access it and the types of services required across markets.
Population demographics are continuously evolving due to a variety of factors, including migration, birth and death rates, economic conditions, housing trends, government policies, cultural shifts and environmental changes. These changes shape the demographic composition of every market and influence local healthcare demand. For all health economy stakeholders, understanding the drivers of these demographic shifts is essential – especially as they try to adapt to evolving population needs.
Birth and death rates also influence the demographic composition of localities, given that a declining birth rate can shrink the younger population over time, while an aging population and rising life expectancy can increase the share of older adults. This, in turn, fundamentally alters the composition of healthcare demand. From 2014 to 2024, the U.S. birth rate declined, decreasing from 12.5 births per 1,000 people to 10.7, a 14.7% decrease. A decline in the number of births was observed in every state, ranging from -24.8% in D.C. to -6.7% in Connecticut (Figure 5).
Nationally, between 2004 and 2024, the annual number of births decreased from 4.1M to 3.6M, while the annual number of deaths increased from 2.4M to 3.1M (Figure 6). In turn, the birth to death ratio has dropped from 1.7 to 1.2 in the same period. As births decline and deaths increase, the population becomes smaller and older, a trend reflected by growing senior populations in every state.
Reflective of this, between 2014 and 2024, the senior population grew 32.5% nationally, but growth varied considerably across states (Figure 7). Alaska had the most significant growth in its senior population, increasing 56.5%, whereas West Virginia had the smallest increase at 17.6%.
Notably, from 1960 to 2024, the senior share of the entire U.S. population increased from 8.8% to 17.9% (Figure 8). Between 2023 and 2024, the senior population increased by 3.1% to 61.2M, while the population under age 18 declined by 0.2% to 73.1M.4 Although children still outnumber older adults, the gap is narrowing, with older adults now outnumbering children in 11 states and nearly half of all U.S. counties. This shift toward an older population, combined with fewer births, will reduce demand for pediatric and maternity services, while increasing demand for Medicare-funded services, including chronic disease management, cardiovascular care and post-acute care. As a result, health economy stakeholders will face sustained pressure on payer mix as the share of commercially insured patients declines and the proportion of government-sponsored coverage continues to grow.
One of the most significant drivers of local demographic change is migration, or the movement of people within and across regions due to economic opportunities, housing affordability, climate and lifestyle preferences. Migration patterns in the U.S. have continued to shift in recent years, with overall mobility declining and fewer individuals relocating annually.
Between 2014 and 2024, the share of individuals remaining in the same home increased from 85.1% to 88.2%, while total mobility declined across nearly all movement types (Figure 9). Moves within the same county decreased from 8.7% to 5.9% and moves to a different county within the same state declined slightly from 3.3% to 3.0%. Interstate migration also nominally declined from 2.3% to 2.1%.
Among those who are moving states, where they are going has changed. The U-Haul Growth Index, which tracks one-way moves, shows that between 2018 and 2025, Texas and Florida consistently ranked among the top inbound states (Figure 10). As of 2025, seven out of the 10 top inbound states were located in the South and three in the West (i.e., the Sunbelt). However, prior to 2022, there was more regional heterogeneity, with Northeastern and Midwestern states like Ohio, Vermont, Maine and New Hampshire ranking in the top 10. Taken together, this data suggests an increasing number of relocations away from the Northeast and Midwest.
To better understand how these shifts are playing out, the following definitions distinguish the key metrics of population change as defined by the Census Bureau.
U.S. population growth is slowing after a brief post-pandemic rebound, reflecting a sharp decline in net international migration.5 Between 2024 and 2025, the U.S. population grew by 1.8M people, or 0.5%, down from 1.0% growth the prior year and marking one of the slowest growth rates since the COVID-19 pandemic.6 Of the 387 U.S. metropolitan CBSAs, 310 saw slower growth between 2024 and 2025 than the previous year.7 This deceleration is largely driven by a significant drop in net international migration, which declined from 2.7M in 2024 to 1.3M in 2025, a 53.8% decrease. The decrease in net international migration impacted every CBSA, particularly large urban counties and border counties. The three metropolitan CBSAs with the largest declines in population growth rates from 2023-2024 to 2024 to 2025 are all located along the U.S.-Mexico border: Laredo, Texas (3.2% to 0.2%), Yuma, Arizona (3.3% to 1.4%) and El Centro, California (1.2% to -0.7%).8
Examining net migration specifically – which isolates domestic and international migration from natural population change (e.g., births and deaths) – reveals a deeper look into where and how these shifts are playing out at the market level. Nationally, the total number of immigrants living in the U.S. declined in 2025 for the first time in 50 years, decreasing by more than 1M between January and June.9 Despite leading the country in net migration in 2025, Houston-Pasadena-The Woodlands, TX netted -50,305 international migrants between 2024 and 2025 and Dallas-Fort Worth-Arlington, TX netted -60,574 (Figure 11). These metros remained net migration leaders, reflecting how domestic in-migration is carrying population growth in Sunbelt markets. Several high-net-migration CBSAs (e.g., Atlanta-Sandy Springs-Roswell, GA, Austin-Round Rock-San Marcos, TX, Raleigh-Cary, NC and Seattle-Tacoma-Bellevue, WA) saw a domestic migration increase between 2024 and 2025, potentially offsetting international migration losses. In contrast, CBSAs with the most negative net migration faced compounding losses from negative net domestic migration. Notably, the New York-Newark-Jersey City, NY-NJ CBSA netted 257,729 residents – 238,529 international migrants and 19,200 domestic migrants between 2024 and 2025 alone.
This divergence has implications for healthcare demand and payer mix. International migrants have historically supplied a meaningful share of working-age population individuals, with an average immigrant age of 47.7 – the demographic most likely to have employer-sponsored insurance.10 As international migration contracts, markets relying on domestic in-migration to sustain growth are drawing from a pool that skews older and may increasingly include individuals transitioning toward Medicare eligibility. For health economy stakeholders, the distinction between where migration is occurring and who is migrating is as important as the volume – shaping not just the size of the population, but its age structure, insurance coverage and long-term demand trajectory.
Declining domestic mobility, immigration and a widening gap between births and an aging population compound one another, reshaping the demographic composition of nearly every U.S. market. The shifts are altering the where, who and how of healthcare demand, concentrating growth in select geographics, where some locations have increased aging-related utilization and decreased demand for reproductive services. Understanding how these shifts occur, but also where they are most pronounced and how they interact, is essential for stakeholders to align capacity, workforce and service mix with changing local needs. As these demographic forces continue to unfold, they will have downstream implications for healthcare demand, access and financial sustainability.
Demographic shifts and migration patterns alter the composition and needs of the healthcare system, shaping population-level demand for services, patient preferences, trust in the healthcare system, payer mix and revenue streams of all health economy stakeholders.
Beyond studying existing trends, it is also important to use a data-driven approach to anticipate future demand. Through 2029, population growth is projected to concentrate in the South and Mountain West, with sustained growth in states such as Texas, Florida and Utah (Figure 12). These patterns are consistent with recent domestic migration trends, where individuals have relocated to regions with lower housing costs, lower state income tax and stronger job growth. For example, Census and IRS migration data show net inflows into Sunbelt states alongside outflows from higher-cost coastal markets.11,12 As people relocate, they change the demographic composition of destination markets, shifting age distribution, income mix and insurance coverage. These changes influence not only the amount of care utilized but also the service mix and the payer mix. Markets with rapid population inflows may see increased demand for primary care, obstetrics and elective services among working-age adults, while markets with slower growth or population loss may see demand increasingly concentrated in Medicare-funded services. Accurately identifying where growth is occurring and which populations are driving that growth is necessary for aligning capacity, workforce and service line investments.
Demographic shifts also affect the financial sustainability of healthcare systems by altering payer mix. Commercial insurance plans, including employer-sponsored, Marketplace, direct-purchase and TRICARE, reimburse providers at higher rates than government programs such as Medicare and Medicaid, making it imperative for healthcare organizations to maintain a high share of commercially insured revenue to offset losses from patients with other insurance sources. Yet, this is becoming increasingly challenging as the U.S. population ages and the employer-sponsored share of the population is flat to declining – remaining unchanged from 2023 to 2024 (Figure 13). While the number and share of Medicare beneficiaries increases, enrollment is growing disproportionately in Medicare Advantage, which is projected to account for 64% of Medicare beneficiaries by 2034. As the population continues to age and more individuals enroll in Medicare, the number of commercially insured Americans will continue to drop, impacting provider revenue and financial stability.
Demographic characteristics are also correlated with trust in the healthcare system, which in turn influences healthcare utilization. While trust has declined since the COVID-19 pandemic, White adults, individuals with higher incomes, college or graduate degree holders and those over age 65 are more likely to trust physicians and hospitals compared to other groups (Figure 14). Markets with higher shares of racial minorities, lower-income populations or younger adults may experience greater distrust of the healthcare system, leading to lower engagement with medical services and preventive care.
Population demographics directly influence the volume and type of healthcare services utilized in a market, meaning population growth or decline does not inherently align with demand. Projected surgical incidence rates from 2025 to 2030 vary in their alignment with population trends, reflecting differences in age distribution, disease prevalence and baseline health status across markets. For example, while the population Orlando-Kissimee-Sanford, FL is projected to grow, surgical demand is projected to decline, indicating that migration may be concentrated among younger or healthier individuals not requiring high-acuity services (Figure 15). In contrast, the population of Rochester, New York is projected to decline, while surgical demand is projected to increase, likely due to a growing older population with higher rates of chronic disease. These patterns demonstrate that service-line-level demand is driven by the clinical needs of a population (e.g., disease prevalence or aging prevalence) rather than population size alone. For health economy stakeholders, incorporating incidence rates alongside demographic trends is necessary to accurately forecast utilization and avoid over- or under-investment in specific service lines.
Even if demand for a certain service line will experience tepid growth nationally, there will be variation at the individual market level. Nationally, the five-year compound annual growth rate (CAGR) for heart/vascular surgical services between 2025 and 2030 is 0.7%. In the Dallas-Fort Worth-Arlington, TX CBSA, demand is projected to grow more than twice the national rate, with a CAGR of 1.9%, whereas the Chicago-Naperville-Elgin, IL CBSA has a CAGR of -0.3% (Figure 16). Similarly, national demand for primary care has a CAGR of 0.4%, compared to 1.2% in both Dallas-Fort Worth-Arlington, TX and Atlanta-Sandy Springs-Roswell, GA. Meanwhile, demand for primary care services is projected to decline in Chicago-Naperville-Elgin, IL and New York-Newark-Jersey City, NY-NJ, with five-year CAGRs of -1.7% and -0.1%, respectively. Market-level demand can vary by service line. For instance, oncology services are projected to trend below the national average in Atlanta-Sandy Springs-Roswell, GA, but trend above the national average for heart/vascular surgical services. These variations highlight the necessity of localized market analysis, rather than relying on national trends alone.
The number of projected births remains insufficient to offset the rising number of Medicare beneficiaries as the Baby Boomer generation ages, leading to a progressively smaller commercially insured population. However, this dynamic is now compounded by a slowing population growth and declining immigration – historically a key source of younger, working-age individuals, thus with a higher likelihood of being commercially insured. As a result, the TAM for commercially insured patients is not only shrinking as a share of the population but also growing more slowly in absolute terms. In particular, the employer-sponsored share of the population is flat to declining, remaining unchanged from 2023 to 2024, while the share of Medicare Advantage beneficiaries increased by 0.7 percentage points in the same period. The number and share of Medicare beneficiaries will continue to increase as the population ages.
This structural shift will force health systems to reassess traditional growth strategies. Rather than benefiting from population growth, providers will increasingly compete for a finite – and in some markets, stagnant – pool of commercially insured patients. With more new entrants (e.g., direct-to-consumer platforms for at-home wellness tests, weight management or behavioral health services) in the care delivery market, traditional providers face heightened competition from consumer-focused brands with stronger loyalty and transparent pricing models, further pressuring commercial reimbursement rates.
To remain competitive, organizations must shift from growth-oriented strategies to share capture and retention strategies, leveraging demographic, psychographic and consumer loyalty data to better identify, engage and retain high-value patients. Strategic patient retention, targeted outreach and care navigation will be essential to sustaining revenue and market position.
How can organizations refine their strategies to capture share in markets with limited population growth? How can providers diversify revenue streams as demographic tailwinds weaken? How can payers maintain profitability in a market with slower growth and a declining commercially insured base?
How can the healthcare system adapt its workforce, infrastructure and care models to meet the needs of a more rapidly aging population? How should life sciences companies rebalance portfolios to align with demographic demand? What strategies can payers employ to ensure sustainability as Medicare enrollment accelerates?
How can stakeholders address widening disparities in access and outcomes in both high-growth and low-growth markets? What care delivery and reimbursement models can improve access for underserved populations? How can policymakers and industry leaders ensure that demographic shifts do not further entrench inequities?
The growing Medicare population not only affects payer mix but also reshapes healthcare demand, requiring new strategies to address the needs of older adults. Declining birth rates and reduced immigration are accelerating the aging of the U.S. population, increasing the concentration of seniors in many markets faster than previously projected.
Despite clear indicators of this shift, the healthcare system remains largely unprepared. Workforce shortages present a significant challenge. While the number of adults ages 65 and older grew by 71.4% between 2000 and 2026, the number of geriatricians declined by 27.0%, leaving a widening gap in specialized care.13 At the same time, fewer nursing homes are opening, and an increasing number are restricting new admissions, further constraining access to long-term care.14
Moreover, it remains unclear whether pharmaceutical manufacturers are prioritizing the types of treatments most relevant to an aging population, such as therapies for chronic disease, neurodegeneration and functional decline. In the post-pandemic era, large biopharmaceutical manufacturers have focused on oncology, diabetes and obesity, raising questions about alignment between pipeline investments and future demographic-driven demand.15
How can the healthcare system adapt its workforce, infrastructure and care models to meet the needs of a more rapidly aging population? How should life sciences companies rebalance portfolios to align with demographic demand? What strategies can payers employ to ensure sustainability as Medicare enrollment accelerates?
As overall population growth slows and migration patterns shift, demographic disparities in healthcare access and outcomes may widen, particularly in markets experiencing stagnation or population decline. Slower growth can reduce investment in certain regions, while affordability challenges continue to limit access to care for lower-income populations, even in growing markets.
For instance, Black individuals have disproportionately higher cancer mortality rates (176.0 and 166.5, respectively) in comparison to White individuals (151.2).16 Black individuals also face higher cardiovascular mortality rates relative to White individuals.17 Additionally, type 2 diabetes is more prevalent in low-income ZIP codes than in high-income ZIP codes in major markets like Atlanta.18 These disparities stem from a combination of structural barriers, including access constraints, affordability challenges and differences in healthcare engagement.
As demographic growth becomes more uneven and, in some cases, slows altogether, addressing these disparities will become more urgent. Markets with limited population growth may struggle to sustain services, while rapidly growing markets may face capacity constraints that disproportionately affect vulnerable populations.
How can stakeholders address widening disparities in access and outcomes in both high-growth and low-growth markets? What care delivery and reimbursement models can improve access for underserved populations? How can policymakers and industry leaders ensure that demographic shifts do not further entrench inequities?
Demographic shifts reshaping the U.S. population – including slowing population growth, declining immigration, aging Baby Boomers, falling birth rates and uneven migration patterns – are already influencing healthcare demand. These trends are not occurring uniformly across markets, and national averages often obscure the local dynamics that drive utilization, payer mix and service-line-level demand. As a result, understanding the demographic composition of individual markets – and how it is changing over time – is a strategic necessity for all health economy stakeholders.
Across providers, payers, life sciences companies and policymakers, responding to these shifts will require more proactive, data-driven strategies grounded in assessing local market dynamics. As growth in the commercially insured population slows, the senior population expands and gaps in who can most readily access care widen, stakeholders that invest in granular demographic insights will be better positioned to align capacity, ensure patient retention, design systems that better meet patient needs, remain competitive and maintain financial viability in an increasingly competitive health economy.