7  Social and Physical Determinants of Health

7.1 Economic Stability

7.1.1 Employment

Occupation and employment affect individual health in various aspects. Those with steady employment tend to have better health outcomes in both mental and physical health conditions than those who are unemployed. Even within employed populations, there are disparities between those with high-paying and low-paying jobs (1).

Putnam and Westchester Counties had the highest percentage of individuals in the labor force (64.7% and 65.4%, respectively) in 2023. Ulster County had the lowest percentage of individuals in the labor force (58.7%), which is lower than both the New York State (NYS) and United States (US) rate Figure 7.1 and Table 7.1. Putnam County continues to have the lowest unemployment rate (4.8% in 2021 and 4.1% in 2023) in the Mid-Hudson (M-H) Region. All of the counties in the M-H Region have a lower unemployment rate than NYS’ rate of 6.2%. Sullivan County has the highest unemployment rate in the region at 6.1% Figure 7.2 and Table 7.2.

Figure 7.1: Percentage in Labor Force, Population 16 Years and Older, 2021–2023
Table 7.1: Percentage in Labor Force, Population 16 Years and Older, 2021–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS US
2021 63.0 63.9 65.2 63.9 56.1 60.1 65.5 63.1 63.6
2022 62.8 63.4 64.7 63.2 58.1 58.9 65.2 62.9 63.5
2023 63.3 63.5 64.7 63.2 59.1 58.7 65.4 63.0 63.5

US Census Bureau; American Community Survey, 2023 American Community Survey 5-year estimates, Table DP03, April 2025 https://data.census.gov/table/ACSDP5Y2023.DP03?q=dp03&g=050XX00US36105,36027,36071,36119,36087,36079,36111_040XX00US36_010XX00US

NoteNote

Y-axis does not begin at zero in order to clearly display trend lines. The American Community Survey asks respondents if they have worked in the past week. If the answer is no, they are asked why they are not working. For those who are not working, they are asked whether they plan to return to work, and when they last worked. Labor Force refers to the total number of people who are either employed or unemployed and actively seeking work, plus members of the US Armed Forces.

Figure 7.2: Percentage of Population Unemployed, 16 Years and Older, 2021–2023
Table 7.2: Percentage of Population Unemployed, 16 Years and Older, 2021–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS US
2021 5.2 5.4 4.8 6.0 8.0 5.1 6.1 6.2 5.5
2022 5.0 5.3 4.4 6.2 7.2 5.1 6.0 6.2 5.3
2023 4.8 5.4 4.1 5.9 6.1 5.1 6.0 6.2 5.2

Source: US Census Bureau; American Community Survey, 2023 American Community Survey 5-year estimates, Table DP03, April 2025 https://data.census.gov/table/ACSDP5Y2023.DP03?q=dp03&g=050XX00US36105,36027,36071,36119,36087,36079,36111_040XX00US36_010XX00US

NoteNote

The American Community Survey asks respondents if they have worked in the past week. If the answer is no, they are asked why they are not working. For those who are not working, they are asked whether they plan to return to work, and when they last worked.

7.1.2 Food Insecurity

Food insecurity can be defined as the disruption of food intake or eating patterns due to lack of money and other resources (2). Access to food plays an essential role in living a healthy lifestyle; those who face food insecurity are often forced to choose between food and other essentials, such as housing, utilities, and medical care.

Children are affected by food insecurity at a higher rate than the general population. Healthy food plays a key role in a child’s development. Children who face hunger are more likely to struggle in school, face developmental impairments, and have more social and behavioral problems than children who do not face hunger (2).

Other populations more vulnerable to food insecurity than the overall population include (2):

  • Senior Populations
  • Those living in rural communities
  • Black Populations
  • Hispanic Populations
  • Those living in poverty

Feeding America used data from the US Census Bureau Current Population Survey (CPS) to generate food insecurity rates. The CPS included two questions relevant for this determination. First, a question asks if a household needed more, less, or the same amount of money to meet their basic food needs. Second, those that respond “more” are asked an additional question about how much more money they need to meet their basic food needs (3).

Putnam County had the lowest food insecurity rate in the M-H Region at 8.9% (2023), as they have for all data listed dating back to 2020. The county with the highest rate of food insecurity was Sullivan County at 14.0%, but this was still lower than NYS’ rate of 14.5% Figure 7.3 and Table 7.3. Childhood food insecurity in the region sees the same trends across counties with Sullivan having the highest rate at 19.9% and Putnam having the lowest at 6.6% Figure 7.4 and Table 7.4.

Figure 7.3: Percentage of Overall Food Insecurity, 2020–2023
Table 7.3: Percentage of Overall Food Insecurity, 2020–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2020 8.7 9.4 6.3 9.7 11.5 11.3 7.9 9.6
2021 7.2 7.8 5.3 8.2 9.9 9.5 6.6 11.4
2022 10.0 11.3 8.4 11.0 13.1 12.8 9.4 13.4
2023 10.8 12.1 8.9 12.0 14.0 13.2 10.7 14.5

Feeding America, June 2025 https://map.feedingamerica.org/district/2023/overall/new-york

NoteNote

Feeding America takes the Current Population Survey (a monthly household survey conducted by the US Census Bureau) data and analyzes the relationships between food insecurity and its determinants (i.e., unemployment, poverty, disability, homeownership, and median income), as well as the percentage of the population that is Black and the percentage of the population that is Hispanic. Coefficient estimates from this analysis, combined with information on the same variables defined at the county and congressional district levels, are generated to estimate food insecurity.

Figure 7.4: Percentage of Food Insecurty, Children 18 Years and Younger, 2020–2023
Table 7.4: Percentage of Food Insecurty, Children 18 Years and Younger, 2020–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2020 12.0 14.8 7.3 15.8 18.3 15.1 11.4 14.6
2021 8.2 10.4 3.6 11.3 15.0 10.6 7.2 15.4
2022 12.0 15.4 6.7 15.5 19.9 14.5 10.5 18.8
2023 11.9 15.6 6.6 16.3 19.9 14.6 10.6 19.0

Feeding America, June 2025 https://map.feedingamerica.org/district/2023/overall/new-york

NoteNote

Feeding America takes the CPS data and analyzes the relationships between food insecurity and its determinants (i.e., unemployment, poverty, disability, homeownership, and median income), as well as the percentage of the population that is Black and the percentage of the population that is Hispanic. Coefficient estimates from this analysis, combined with information on the same variables defined at the county and congressional district levels, are generated to estimate food insecurity.

7.1.3 Housing Instability

A study published in the Journal of the American Public Health Association found that homeless individuals utilized the emergency room almost four times more than other low-income residents (4). Housing and health are closely related. Poor health is often both the cause and effect of unstable, poor, or non-existent housing. Mental health also plays a large role in the causes and effects of homelessness.

Housing alone does not guarantee better health outcomes in all areas; quality of housing is also important. For example, children who live in public housing are two times more likely to have asthma than other children due to a higher prevalence of mold in public housing (5).

The median percentage of household income spent on housing in the M-H Region is estimated to be 28.0% by United States Department of Housing and Urban Development (HUD) (6). Households that spend greater than 30.0% of their income on housing are considered cost burdened. Households that are severely cost burdened (spending greater than 50.0% of income on housing) are shown to spend 75.0% less on health care compared to similar households that are living in affordable housing (7).

Rockland County had both the highest percentage of cost burdened renter occupied units and the highest percentage of severely cost burdened households in the region at 59.6% and 22.0%, respectively. Sullivan County had the lowest percentage of cost burdened renter occupied units (48.7%) and lowest percentage of severely cost burdened households (15.0%) Figure 7.5 and Figure 7.6. All counties exceeded the New York State average for cost-burdened renter-occupied units, with the exception of Sullivan County. However, when examining the percentage of severely cost-burdened households, only Orange and Rockland counties exceeded the state average.

Figure 7.5: Percentage of Cost Burdened Renter Occupied Units, 2021–2023
Table 7.5: Percentage of Cost Burdened Renter Occupied Units, 2021–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021 52.3 56.5 52.7 58.3 48.0 55.3 53.2 51.6
2022 52.4 56.1 53.2 58.9 48.4 55.3 53.5 51.7
2023 52.0 56.2 56.5 59.6 48.7 56.6 53.0 51.5

Source: US Census Bureau; American Community Survey, 2023 American Community Survey 5-year estimates, Table DP04, April 2025 https://data.census.gov/table/ACSDP5Y2023.DP04?q=dp04&g=050XX00US36105,36027,36071,36119,36087,36079,36111_040XX00US36

NoteNote

The American Community Survey asks respondents if they own or rent the house, apartment, or mobile home they live in. If rented, they ask for the monthly rent. Cost burdened is defined as the percentage of renter occupied units in which gross rent is 30% or more of household income.

Figure 7.6: Percentage of Severely Cost Burdened Households, 2016–2023
Table 7.6: Percentage of Severely Cost Burdened Households, 2016–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2016–2020 16.0 19.0 16.0 22.0 14.0 18.0 20.0 19.0
2017–2021 16.0 19.0 16.0 22.0 15.0 18.0 19.0 19.0
2018–2022 16.0 20.0 16.0 22.0 15.0 18.0 20.0 19.0
2019–2023 16.0 20.0 17.0 22.0 15.0 18.0 19.0 19.0

University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, June 2025 sourced from US Census Bureau, American Community Survey, five-year estimates https://www.countyhealthrankings.org/health-data/new-york?year=2025&measure=Severe+Housing+Cost+Burden*

NoteNote

Severely cost burdened is defined as the percentage of households that spend 50% or more of their household income on housing.

The number of individuals living in HUD-subsidized housing in the Mid-Hudson Region remained relatively stable from 2021 to 2024. Rockland and Orange counties reported the highest totals, with Rockland increasing from 21,732 to 23,735 residents and Orange from 18,258 to 19,129. Putnam County consistently had the lowest number of HUD-subsidized residents but experienced a gradual increase each year. Sullivan County was the only county in the region to see a steady decline, dropping from 5,018 in 2021 to 4,445 in 2024 Table 7.7.

Table 7.7: Number of people living in HUD-Subsidized Housing in the Past 12 Months, 2021–2024
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021 7,442 18,258 945 21,732 5,018 5,484 40,230 1,025,652
2022 7,641 18,745 929 22,170 5,228 5,479 40,412 985,104
2023 7,630 19,000 992 23,411 4,846 5,418 40,415 987,957
2024 7,484 19,129 1,012 23,735 4,445 4,980 40,137 1,000,730

US Department of Housing and Urban Development, July 2025 https://www.huduser.gov/portal/datasets/assthsg.html#codebook_2009-2024

NoteNote

Includes all federal housing assistance programs administered by the US Department of HUD, including: Public Housing, Housing Choice Vouchers, Moderate Rehabilitation, Project-Based Section 8, Rent Supplement/Rent Assistance Program, S236/Below Market Interest Rate, 202/Project Rental Assistance Contract, and 811/Project Rental Assistance Contract.

7.1.4 Poverty

The U.S. Census Bureau defines a family, and every individual in it, as being in poverty when their income is less than the family’s threshold (8). For 2024, a single adult under age 65 falls below poverty at an income of less than $16,320, while a one-person family unit aged 65 and older has a slightly lower threshold of $15,045. Thresholds rise with each additional family member and child; for example, a family of three, close to the average family size in New York State (3.18 average family size), faces a poverty threshold of approximately $25,273 (9). For larger families, the threshold increases substantially, reaching $60,645 for families of nine or more Table 7.8. These benchmarks serve as the federal standard for identifying individuals and families whose earnings are insufficient to meet basic needs (8).

Table 7.8: Poverty Threshold for 2024 by Size of Family and Number of Related Children 18 Years and Younger
Related children under 18 years
Size of family unit None One Two Three Four Five Six Seven Eight Nine or more
One person (unrelated individual):
Under age 65 $16,320
Aged 65 and older $15,045
Two people:
Householder under age 65 $21,006 $21,621
Aged Householder aged 65 and older $18,961 $21,540
Three people $24,537 $25,249 $25,273
Four people $32,355 $32,884 $31,812 $31,922
Five people $39,019 $39,586 $38,374 $37,436 $36,863
Six people $44,879 $45,057 $44,128 $43,238 $41,915 $41,131
Seven people $51,638 $51,961 $50,849 $50,075 $48,631 $46,948 $45,100
Eight people $57,753 $58,263 $57,215 $56,296 $54,992 $53,337 $51,614 $51,177
Nine people or more $69,473 $69,810 $68,882 $68,102 $66,822 $65,062 $63,469 $63,075 $60,645 $60,645

US Census Bureau, Poverty Thresholds by Size of Family and Number of Children, 2021, April 2025 https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html

Poverty and health are closely linked. People experiencing poverty often have an increased risk of chronic and mental health conditions, mortality, and lower life expectancies (10).

The New York State Community Action Association’s Annual Poverty Report (2024) offers an in-depth breakdown of poverty rates, demographics, and economic conditions at the county level across New York State (11).

“Poverty is both a cause and consequence of poor health” (12)

Counties in the M-H Region continue to show wide variation in poverty rates, ranging from a low of 6.5% in Putnam County to a high of 15.6% in Rockland County. As of 2023, Rockland, Sullivan, and Ulster counties all reported poverty rates above the New York State average of 13.7%. In contrast, Putnam, Dutchess, Westchester, and Orange counties remained below the state average Figure 7.7 and Table 7.9.

Figure 7.7: Percentage of Population in Poverty, 2021–2023
Table 7.9: Percentage of Population in Poverty, 2021–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021 8.8 11.7 6.0 14.9 14.1 13.2 8.2 13.5
2022 8.6 13.0 6.3 15.1 14.8 14.7 8.5 13.6
2023 8.3 13.0 6.5 15.6 15.2 14.3 8.9 13.7

US Census Bureau; American Community Survey, 2023 American Community Survey 5-year estimates, Table S1701, April 2025 https://data.census.gov/table/ACSST5Y2023.S1701?q=s1701&g=050XX00US36105,36027,36071,36119,36087,36079,36111_040XX00US36

NoteNote

The American Community Survey asks respondents their income in the past 12 months including joint income. This is for income that is received on a regular basis before payments for taxes, social security, etc. If a family’s total income is less than the official poverty threshold for a family of that size and composition, they are considered to be in poverty.

Poverty continues to vary significantly across racial and ethnic groups in the Mid-Hudson Region. Hispanic families had the highest poverty rates in Orange, Putnam, Rockland, Ulster, and Westchester counties, with Ulster County reaching 24.4%. In Sullivan County, non-Hispanic Black families experienced the highest poverty rate at 30.5%, the highest across all counties and groups. In Dutchess County, non-Hispanic Black and Hispanic families also had elevated poverty rates at 14.2% and 11.2%, respectively Figure 7.8 and Table 7.10.

Figure 7.8: Percentage of Families below Poverty by Race and Ethnicity, 2018–2022
Table 7.10: Percentage of Families below Poverty by Race and Ethnicity, 2018–2022
Race and Ethnicity Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
White (non-Hispanic) 3.3 7.9 2.8 11.1 8.2 4.9 2.6 5.7
Black (including Hispanic) 14.2 12.5 0.0 8.6 30.5 14.1 10.8 16.5
Asian (including Hispanic, excluding Pacific Islander) 7.5* 10.3* 23.4* 1.8* 13.3* 4.8* 5.4 11.1
Hispanic (any race) 11.2 11.3 6.6 12.8 14.3 24.4 10.4 17.1
Total 5.3 9.2 3.8 10.3 10.5 7.1 5.7 9.7

Source: NYS County Health Indicators by Race and Ethnicity Dashboard, June 2025 sourced from US Census Bureau, Small Area Income and Poverty Estimates https://www.health.ny.gov/community/health_equity/reports/county/

NoteNote

The Census Bureau collects racial and ethnic data in accordance with guidelines provided by the US Office of Management and Budget (OMB) and these data are based on self-identification. For ethnicity, the OMB standards classify individuals in one of two categories: “Hispanic or Latino” or “Not Hispanic or Latino.” The Census Bureau uses the term “Hispanic or Latino” interchangeably with the term “Hispanic,” and also refer to this concept as “ethnicity.” People who identify with more than one race may choose to provide multiple races in response to the race question.

7.1.5 Economically Disadvantaged

Children from economically disadvantaged families can face numerous challenges that influence their development, academic achievement, and overall health. Poverty can affect their cognitive development and educational attainment. The lack of access to resources and opportunities can impact their long-term social and economic mobility (13).

In 2023–2024, Sullivan County had the region’s highest share of economically disadvantaged students (61.4%), while Putnam had the lowest (32.5%) Figure 7.9 and Table 7.11. All counties rose since 2021–2022; the largest gains occurred in Rockland (43.9% to 51.0%), Dutchess (39.2% to 43.3%), and Putnam (28.5% to 32.5%). Compared with NYS (59.2%), Sullivan is above the state average; all other Mid-Hudson counties remain below it. Ulster was higher than Orange and Rockland through 2022–2023 (52.5% vs. 49.0% and 48.1%) but dropped below both in 2023–2024 (48.8% vs. 49.5% and 51.0%).

Figure 7.9: Enrollment Rate of Economically Disadvantaged Students, 2021–2023
Table 7.11: Enrollment Rate of Economically Disadvantaged Students, 2021–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021-2022 39.2 47.0 28.5 43.9 60.4 48.6 38.9 56.2
2022-2023 43.1 49.0 32.1 48.1 62.7 52.5 39.6 59.1
2023-2024 43.3 49.5 32.5 51.0 61.4 48.8 39.7 59.2

Source: NYS Education Department, June 2025 https://data.nysed.gov/enrollment.php?year=2024&county=13

NoteNote

Students who participate in, or whose family participates in, economic assistance programs, such as the Free or Reduced-Price Lunch Programs; Social Security Insurance; Supplemental Nutrition Assistance Program; Foster Care; Refugee Assistance (cash or medical assistance); Earned Income Tax Credit; Home Energy Assistance Program; Safety Net Assistance; Bureau of Indian Affairs; or Family Assistance: Temporary Assistance for Needy Families. If one student in a family is identified as low income, all students from that household (economic unit) may be identified as low income.

7.1.6 Asset Limited, Income Constrained, Employed (ALICE)

Asset Limited, Income Constrained, Employed (ALICE) households are those earning above the Federal Poverty Level but below the ALICE Threshold, the income needed to afford the basics where they live, as calculated in the Household Survival Budget (14). The ALICE measure is location and household-specific and covers six essentials: housing, childcare, food, transportation, health care, and technology. These constraints force households to make difficult trade-offs across these necessities, see Table 15 for a sample budget.

The 2023 ALICE Household Survival Budget for New York State shows that the income needed to cover basic necessities ranges from $35,652 per year for a single adult ($17.80/hour) to $104,472 for two adults with two children in childcare ($52.20/hour). A two-adult, two-child household without paid childcare requires $83,664 annually. Housing and childcare are the largest drivers for families with two children in care, those two items total $3,782 per month. These amounts define the ALICE Threshold; county-level percentages below this threshold. Table 7.12

Table 7.12: ALICE Household Survival Budget, New York State, 2023
Single Adult One Adult, One Child One Adult, One in Child Care Two Adults Two Adults, Two Children Two Adults, Two in Child Care Single Adult 65+ Two Adults 65+
Housing $1,103.00 $1,189.00 $1,189.00 $1,189.00 $1,437.00 $1,437.00 $1,103.00 $1,189.00
Child Care $0.00 $423.00 $1,126.00 $0.00 $844.00 $2,345.00 $0.00 $0.00
Food $516.00 $873.00 $783.00 $946.00 $1,587.00 $1,400.00 $475.00 $870.00
Transportation $401.00 $535.00 $506.00 $617.00 $957.00 $899.00 $346.00 $508.00
Health Care $196.00 $452.00 $452.00 $452.00 $775.00 $775.00 $543.00 $1,086.00
Technology $86.00 $86.00 $86.00 $116.00 $116.00 $116.00 $86.00 $116.00
Miscellaneous $230.00 $356.00 $414.00 $332.00 $572.00 $697.00 $255.00 $377.00
Taxes $439.00 $461.00 $625.00 $529.00 $684.00 $1,037.00 $510.00 $861.00
Monthly Total $2,971.00 $4,375.00 $5,181.00 $4,181.00 $6,972.00 $8,706.00 $3,318.00 $5,007.00
ANNUAL TOTAL $35,652.00 $52,500.00 $62,172.00 $50,172.00 $83,664.00 $104,472.00 $39,816.00 $60,084.00
Hourly Wage $17.83 $26.25 $31.09 $25.09 $41.83 $52.24 $19.91 $30.04

United for ALICE, June 2025 https://www.unitedforalice.org/the-cost-of-basics/new-york

NoteNote

The ALICE (Asset Limited, Income Constrained, Employed) household survival budget estimates the minimum cost of household necessities (housing, childcare, food, transportation, health care, and technology) plus taxes, and a contingency fund (miscellaneous) equal to 10% of the budget.

Across the M-H Region, the share of households below the ALICE Threshold ranges from 37% in Dutchess (lowest) to 50% in Rockland (highest). Rockland is the only county above the New York State average of 47%; Orange (43%), Sullivan (45%), Ulster (42%), Putnam (38%), Westchester (38%), and Dutchess (37%) all fall below the state average. Sullivan has the region’s highest poverty rate (15%), while Rockland has the highest ALICE share (38%), which drives its overall total. In every county, ALICE households outnumber those in poverty, often by two to five times, showing that many financially constrained households earn above the Federal Poverty Level but still cannot afford basic needs Figure 7.10 and Table 7.13.

Figure 7.10: ALICE Threshold Percentage, 2023
Table 7.13: ALICE Threshold Percentage, 2023
Category Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
ALICE 31.0 33.0 32.0 38.0 30.0 32.0 28.0 33.0
Poverty 6.0 10.0 6.0 12.0 15.0 10.0 10.0 14.0
Above ALICE Threshold 62.0 57.0 63.0 50.0 54.0 58.0 61.0 52.0

United for ALICE, June 2025 https://www.unitedforalice.org/county-reports/new-york#10/41.1237/-73.7330

NoteNote

The ALICE (Asset Limited, Income Constrained, Employed) threshold represents the percentage of households in the United States that are struggling financially, falling below a threshold that includes those in poverty and those who are asset limited, income constrained, and employed. ALICE households earn above the Federal Poverty Level, but not enough to afford the basic necessities in their communities. Nationally, over 40% of households fall below the ALICE threshold.

7.2 Education

7.2.1 High School Graduation

High school completion is strongly linked to better health and longevity (15). People who don’t complete high school face limited employment prospects, lower wages, and a higher risk of poverty factors that contribute to worse health outcomes and a higher risk of death later in life (15). Graduation likelihood is shaped by individual, family, school, and community conditions; school climate and safety, access to supportive adults, and disciplinary practices are all associated with on-time graduation (16).

In 2023, graduation rates in the M-H Region ranged from 76% in Sullivan (lowest) to 91% in Putnam and Westchester (highest). Most counties exceeded the NYS average of 86%, Dutchess (87%), Orange (89%), Putnam (91%), Ulster (87%), and Westchester (91%), while Rockland matched the state rate (86%) and Sullivan fell below. From 2021–2023, rates were generally stable or edged down slightly, with the largest declines in Sullivan (82% to 76%), Rockland (90% to 86%), and Putnam (94% to 91%). Figure 7.11 and Table 7.14.

Figure 7.11: High School Graduation Rate, 2021–2023
Table 7.14: High School Graduation Rate, 2021–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021 87.0 89.0 94.0 90.0 82.0 87.0 91.0 86.0
2022 86.0 89.0 94.0 88.0 78.0 87.0 92.0 87.0
2023 87.0 89.0 91.0 86.0 76.0 87.0 91.0 86.0

NYS Education Department, June 2025 https://data.nysed.gov/lists.php?type=county

NoteNote

Graduation rate data are reported for a 9th grade cohort, as of the 4th year of high school - August. Graduates include students who received a local diploma or a local diploma with Regents endorsement (Regents diploma).

In accordance with federal regulation, there is a two-part requirement regarding racial and ethnic designation. First, all students must be reported as Hispanic/Latino or not Hispanic/Latino. Second, all students must be reported with at least one race. Students who are reported as Hispanic/Latino, regardless of their race, will be counted as Hispanic/Latino for reporting purposes. Students who are reported as not Hispanic/Latino will be counted in the race category in which they are reported. Non-Hispanic students who are reported with more than one race category will be reported as Multiracial. 

Racial and ethnic disparities in graduation rates persist across the M-H Region. In six of seven counties, White students graduate at higher rates than both Black and Hispanic students; the exception is Putnam, where Black students post the region’s highest rate (97%), exceeding White (95%) and Hispanic (80%) peers. The largest gaps occur between White and Hispanic students, 21 points in Sullivan (84% vs. 63%) and then 15 points in Putnam (95% vs 80%) and Rockland (96% vs. 81%). Disparities between White and Black students are greatest in Sullivan (18 points; 84% vs. 66%) and Dutchess (14 points; 92% vs. 78%), while Rockland (96% vs 90%) and Ulster (90% vs 84%) show one of the smallest White and Black gaps at 6 points. Figure 7.12 and Table 7.15.

Figure 7.12: High School Graduation Rate, by Race and Ethnicity, 2023
Table 7.15: High School Graduation Rate, by Race and Ethnicity, 2023
Race and Ethnicity Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
Asian or Native Hawaiian/Other Pacific Islander 91.0 96.0 100.0 97.0 s s 97.0 93.0
Black or African American 78.0 85.0 97.0 86.0 66.0 84.0 83.0 81.0
White 92.0 93.0 95.0 94.0 84.0 90.0 96.0 91.0
Multiracial 80.0 88.0 s s 68.0 74.0 94.0 84.0
Hispanic 79.0 83.0 80.0 74.0 63.0 80.0 85.0 81.0

Source: NYS Education Department, June 2025 https://data.nysed.gov/gradrate.php?year=2023&state=yes

NoteNote

s: Data are suppressed due to not meeting reporting criteria. Race or races with which the student primarily identifies are indicated by the student or the parent/guardian.

7.2.2 Early Childhood Education and Development

The early years of a child’s life are very important for their health and development (17). WHO’s 2024 handbook operationalizes Nurturing Care—what to deliver (parenting content), where to deliver it (health/social/education platforms), and how to deliver it well (training, quality assurance, M&E, and scaling) (18). WHO characterizes nurturing care as a stable environment that promotes health and optimal nutrition, protects children from threats, and gives them opportunities for early learning, through affectionate interactions and relationships (19). Components of nurturing care include adequate nutrition, responsive caregiving, security and safety, opportunities for early learning, and good health (19).

Early-life stress and adverse events are linked to lasting mental and physical health impacts. Stressors, including poverty, physical abuse, family instability, and unsafe neighborhoods are associated with inadequate coping skills, difficulty regulating emotions, and reduced social functioning (20).

7.2.3 Adverse Childhood Experiences

Adverse Childhood Experiences (ACEs) are potentially traumatic events that occur during childhood such as “experiencing violence, abuse, or neglect; having a family member attempt or die by suicide; and witnessing violence in the home” (21). Elements of a child’s environment that weaken their sense of safety, stability, and bonding such as substance misuse, mental health complications, or family instability (including divorce or incarceration of parents and relatives) contribute to ACEs (21). ACEs can have lasting effects on health, behavior, and life potential, including obesity, diabetes, depression, suicide attempts, sexually transmitted infections (STIs), heart disease, cancer, stroke, Chronic Obstructive Pulmonary Disease (COPD), broken bones, smoking, alcoholism, drug use, graduation rates, academic achievement, lost time from work, etc. Growing research shows that toxic stress as a result of ACEs can damage “the most basic levels of the nervous, endocrine, and immune system,” and can modify the physical structure of DNA (21).

The ACE items are a surveillance tool, not a diagnosis. They estimate how common early-life adversities are among adults. The questionnaire includes questions about: physical, emotional and sexual abuse; physical and emotional neglect; and household dysfunction (substance use, mental illness, mother treated violence, parental separation or divorce, and incarcerated household member). Each item screens for a type of adversity before age 18. When combined, they produce an ACE count (how many types a person reports), which is summarized as a threshold associated with measurably higher risk for poor health, mental health, and social outcomes across the life span.

7.2.4 Attainment of Higher Education

Continuing education after high school, especially enrolling in and completing college, improves employment prospects and job quality, reduces the risk of unemployment or underemployment, and raises lifetime earnings (22). A Social Security Administration analysis linking survey and administrative earnings records estimates that men with a bachelor’s degree earn about $900,000 more in median lifetime earnings than high school graduates and women about $630,000 more; for graduate degrees, the gaps rise to $1.5 million (men) and $1.1 million (women). Even after adjusting for key socio-demographic factors, differences remain substantial (about $655,000 for men and $450,000 for women with a bachelor’s degree) (23). These gains translate into better-paying jobs with fewer safety hazards and greater access to material and psychosocial resources (e.g., higher-quality housing, higher social status) and are associated with improved health and a lower risk of premature death (22).

Westchester leads the region in degree completion, with the highest shares of residents holding a bachelor’s (26.0%) and a graduate/professional degree (26.5%), both above NYS (22.0% and 17.5%). Putnam (24.2%) and Rockland (23.2%) also exceed the state for bachelor’s attainment, while Dutchess (21.0%), Ulster (20.2%), Orange (18.2%), and Sullivan (17.0%) fall below. Figure 7.13 and Table 7.16.

Figure 7.13: Rate of Higher Education Attainment, 2023
Table 7.16: Rate of Higher Education Attainment, 2023
Education Level Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
Some college, no degree 16.9 19.1 16.5 16.2 17.9 17.1 12.6 14.9
Associate's degree 10.1 10.3 8.4 7.8 10.3 9.6 6.4 8.9
Bachelor's degree 21.0 18.2 24.2 23.2 17.0 20.2 26.0 22.0
Graduate or professional degree 18.7 14.1 19.3 18.9 12.7 16.9 26.5 17.5

Source: US Census Bureau; American Community Survey, 2020 American Community Survey 5-Year Estimates, Table S1501, April 2025 https://data.census.gov/table/ACSST5Y2023.S1501?q=s1501&g=050XX00US36105,36027,36071,36119,36087,36079,36111_040XX00US36

NoteNote

The American Community Survey asks respondents what the highest degree or level of school the person has completed.

7.2.5 Language and Literacy

Literacy includes listening, speaking, reading, and writing skills, along with the ability to understand and work with numbers. Low literacy and language skills are associated with poorer outcomes in educational attainment, employment, and health. While limited English proficiency and low literacy differ from health literacy, both are barriers to accessing health care, resulting in lower utilization of health services (24).

Rockland County had the highest percentage of people aged five years and over who spoke English “less than very well” at 20.0% in 2023. Ulster County had the lowest percentage at 3.4% Figure 7.14 and Table 7.17. Except for Rockland County, all other counties were lower than the NYS rate (13.3%).

Figure 7.14: Percentage of Population that Speaks English “Less Than Very Well”, 5 Years and Older, 2021–2023
Table 7.17: Percentage of Population that Speaks English “Less Than Very Well”, 5 Years and Older, 2021–2023
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021 4.7 10.6 5.3 18.6 5.9 2.9 12.7 13.1
2022 4.8 11.3 5.6 18.8 7.3 3.0 12.2 13.1
2023 5.4 12.2 6.0 20.0 8.0 3.4 12.4 13.3

Source: US Census Bureau; American Community Survey, 2023 American Community Survey 5-Year Estimates, Table S1601, April 2025 https://data.census.gov/table/ACSST5Y2020.S1601?q=s1601&g=050XX00US36105,36027,36071,36119,36087,36079,36111_040XX00US36&tid=ACSST5Y2020.S1601

NoteNote

The American Community Survey asks respondents how well the person speaks English. If the response is “well,” “not well,” or “not at all,” the person is categorized as speaking English “less than very well.”

7.3 Social and Community Context

7.3.1 Civic Participation

Civic participation includes activities in which groups or individuals interact with their community, such as voting, volunteering, and community gardening. Activities can be formal or informal and often benefit society or other group members. Civic participation has been shown to improve health by expanding social networks and social trust, which can increase physical activity and improve mental health (25).

Disconnected youth are teenagers and young adults between the ages of 16 and 19 who are neither working nor attending school (26). This metric is an indicator for how young people are faring while transitioning into adulthood. This vulnerable population is cut off from resources, people, and experiences that help them gain knowledge, skills (27), capital (28), and a sense of purpose (25).

Sullivan County had the highest percentage of disconnected youth ages 16–19 (24.0% in 2019–2023), while Westchester County had the lowest (5.0%); the NYS rate was 7.0% Figure 7.15 and Table 7.18. Since 2016–2020, Sullivan rose from 17.0% to 24.0% (peaking at 25.0% in 2018–2022). Ulster moved from 6.0% to 9.0%. Orange remained near 8–10% (8.0% most recent), Rockland ranged 4–6% (6.0% most recent), and Westchester stayed low at 4.0–5.0%.

Figure 7.15: Percentage of Disconnected Youth, 16–19 Years Old, 2014–2023
Table 7.18: Percentage of Disconnected Youth, 16–19 Years Old, 2014–2023
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2014–2018 4.0 8.0 4.0 5.0 12.0 6.0 6.0 6.0
2015–2019 5.0 8.0 s 5.0 12.0 6.0 6.0 6.0
2016–2020 5.0 10.0 s 5.0 17.0 6.0 4.0 6.0
2017–2021 6.0 8.0 s 4.0 17.0 6.0 4.0 6.0
2018–2022 7.0 8.0 s 6.0 25.0 9.0 5.0 7.0
2019–2023 6.0 8.0 s 6.0 24.0 9.0 5.0 7.0

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, June 2025 sourced from US Census Bureau, American Community Survey, five-year estimates https://www.countyhealthrankings.org/health-data/new-york?year=2025&measure=Disconnected+Youth*

NoteNote

s: Data are suppressed due to unreliable or missing data.

7.3.2 Discrimination

National Institutes of Health (NIH) defines discrimination as a socially structured action that is unjustified or unfair and harms individuals or groups, often protecting more powerful and privileged groups to the detriment of others (29). CDC notes that discrimination and racism harm health via barriers to resources and by triggering physiological stress pathways linked to worse outcomes (30).

Discrimination can be assessed through both everyday experiences and major life events (31). Residential segregation is a prominent example of structural discrimination, shaped by policies and practices that limit housing opportunities for certain racial and ethnic groups (32). Such discrimination can occur when individuals are refused rental housing or denied credit unfairly (33). The consequences of residential segregation extend far beyond housing itself, influencing access to quality education, nutritious food, safe environments for physical activity, reliable transportation, and health care (32). These inequities contribute to persistent disparities in health status across population groups (34).

In the US, residential segregation between non-Hispanic Black and non-Hispanic White populations is a key determinant of health disparity, leading to poor health outcomes including mortality and reproductive and chronic diseases (34).

Data produced by County Health Rankings & Roadmaps around residential segregation uses the American Community Survey to measure the distribution of non-Hispanic Black and non-Hispanic White residents across census tracks. The index is used to measure residential segregation; zero represents complete integration, while 100 is complete segregation. The index score can also represent the percentage of either non-Hispanic Black or non-Hispanic White residents who would have to move to a different geographic area in order to produce a distribution that matches that of the larger area (34).

Across the Mid-Hudson Region, residential segregation between Black and White residents remains lower than the statewide level but continues to vary by county. For the most recent period (2019–2023), Westchester County had the highest index score at 63.0, though it was still below the New York State average of 75.0. Sullivan County recorded the lowest score in the region at 43.0, indicating greater levels of residential integration. Putnam County and Orange County showed steady increases in segregation in recent years. In contrast, Ulster County declined to 43.0 (2018–2022), tying with Sullivan for the lowest score. Overall, the Mid-Hudson Region continues to show lower segregation levels compared with the state as a whole, though disparities remain across counties. Figure 7.16 and Table 7.19.

Figure 7.16: Index Score of Residential Segregation, 2013–2023
Table 7.19: Index Score of Residential Segregation, 2013–2023
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2013-2017 52.0 44.0 39.0 58.0 46.0 49.0 62.0 74.0
2016–2020 50.0 45.0 44.0 55.0 50.0 50.0 59.0 74.0
2017–2021 47.0 47.0 38.0 58.0 55.0 46.0 59.0 74.0
2018–2022 46.0 49.0 45.0 56.0 51.0 43.0 60.0 74.0
2019–2023 49.0 48.0 49.0 58.0 43.0 s 63.0 74.0

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, June 2025 sourced from US Census Bureau, American Community Survey, five-year estimates https://www.countyhealthrankings.org/health-data/new-york?year=2025&measure=Residential+Segregation+-+Black%2FWhite*&tab=1

NoteNote

s: Data are suppressed due to unreliable or missing data. Index of dissimilarity where higher values indicate greater residential segregation between Black and White County residents.

7.4 Health Care Access and Usage

“The National Academies of Sciences, Engineering, and Medicine define access to health care as the ’timely use of personal health services to achieve the best possible health outcomes.” (35) Barriers to health care include lack of access to transportation, lack of health insurance coverage, and inadequate providers per capita.

Cost is a prominent barrier to receiving health services and can deter people from seeking preventative care. The Survey of Income and Program Participation in 2023 showed that 16.4% of US households carried medical debt, meaning that people were unable to pay medical costs up front or when they received care (36).

Within the M-H Region, the highest percentage of adults who did not receive medical care due to cost was reported in Putnam County at 9.9%. Sullivan County had the lowest percentage (4.9%) of adults who did not receive medical care due to cost. The M-H Region (7.4%), Rockland County (8.4%), Sullivan County (4.9%), Ulster County (5.3%), and Westchester County (8.3%) all had a similar or lower percentage than NYS (8.4%). Sullivan County (-76.6%) and Ulster County (-52.7%) had a significant percentage change observed between 2016 and 2021, indicating potential gains in both access to care and utilization. Figure 7.17 and Table 7.20.

Figure 7.17: Percentage of Adults Who Did Not Receive Medical Care Due to Cost, 2016, 2018, and 2021
Table 7.20: Percentage of Adults Who Did Not Receive Medical Care Due to Cost, 2016, 2018, and 2021
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2016 8.6 11.1 13.5 11.8 20.9 11.2 12.4 11.5
2018 7.7 8.5 11.4 11.8 11.3 12.7 7.5 11.3
2021 8.7 5.0* 9.9 8.4 4.9 5.3 8.3 8.4

Source: NYS Community Health Indicator Reports Dashboard, June 2025 sourced from NYSDOH Behavioral Risk Factor Surveillance System https://apps.health.ny.gov/public/tabvis/PHIG_Public/chirs/#sdh

NoteNote

*: The percentage is unstable. Note: The percentage is age-adjusted. An adult is a person aged 18 years or older. The Behavioral Risk Factor Surveillance System asks respondents, “Was there a time in the past 12 months when you needed to see a doctor but could not because you could not afford it?”

7.4.1 Health Insurance Coverage

Health insurance coverage is one of the largest factors affecting health care access. Uninsured people are less likely to receive preventative services and treatments than those who are insured, including care for chronic conditions, dental care, immunizations, and well-child visits (37). Several government programs, such as Medicaid and the Children’s Health Insurance Program, help provide low and no-cost health insurance to eligible individuals.

Health insurance coverage is one of the largest factors affecting health care access. Uninsured people are less likely to receive preventative services and treatments than those who are insured, including care for chronic conditions, dental care, immunizations, and well-child visits (35). Several government programs, such as Medicaid and the Children’s Health Insurance Program, help provide low- and no-cost health insurance to eligible children. The US Census Bureau’s Small Area Health Insurance Estimates (SAHIE) program produces annual estimates of health insurance coverage for children under age 19 and adults ages 18 to 64. According to these estimates, adults are more likely than children to be without health insurance in the M-H Region.

Sullivan County has the highest rate of children without health insurance (3.5%), and Putnam County has the lowest rate (2.4%). Dutchess (2.6%), Orange (2.7%), and Putnam Counties all have rates lower than NYS (2.8%). Rockland County (2.8%) and Westchester County (2.8%) have the same rate as NYS. Sullivan County has shown the greatest gains in coverage between 2020 and 2023, with a 14.6% decrease over the past four years Figure 7.18 and Table 7.21.

Figure 7.18: Percentage of Children Without Health Insurance, 2020–2023
Table 7.21: Percentage of Children Without Health Insurance, 2020–2023
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2020 2.4 2.3 2.5 2.4 4.1 2.5 2.7 2.5
2021 2.7 2.8 2.5 2.3 3.2 2.8 3.2 2.6
2022 2.3 2.8 2.5 3.0 3.4 2.7 2.3 2.5
2023 2.6 2.7 2.4 2.8 3.5 3.0 2.8 2.8

Source: US Census Bureau, Small Area Health Insurance Estimates, July 2025 https://www.census.gov/datatools/demo/sahie/#/?AGECAT=1&state_county=36000,36027,36071,36079,36087,36105,36111,36119&s_searchtype=sc&tableYears=2022&map_yearSelector=2022

NoteNote

Note: This indicator includes children under 19 years old.

Dutchess County (94.4%) and Putnam County (94.9%) have the highest rate of adults with health insurance, and Ulster County has the lowest rate (92.0%). Adults in Dutchess County, Putnam County, and Westchester County (93.6%) all have a greater percentage of residents with insurance than NYS (93.2%). Figure 7.19 and Table 7.22.

Figure 7.19: Percentage of Adults with Health Insurance, 2020–2023
Table 7.22: Percentage of Adults with Health Insurance, 2020–2023
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2020 94.5 93.2 95.1 93.3 92.6 92.6 93.2 92.7
2021 94.2 93.5 94.6 93.3 92.4 92.7 93.0 92.6
2022 94.6 93.3 95.0 93.6 92.9 91.8 93.6 93.2
2023 94.4 93.0 94.9 92.3 92.5 92.0 93.6 93.2

Source: US Census Bureau; Small Area Health Insurance Estimates, 2023, August 2025 https://www.census.gov/datatools/demo/sahie/#/?state_county=36000,36027,36071,36079,36087,36105,36111,36119&s_searchtype=sc&s_measures=ic_snc&RACECAT=0&AGECAT=1&map_yearSelector=2018&tableYears=2018

NoteNote

Note: This indicator includes adults aged 18–64 years old. Y-axis does not begin at zero in order to clearly display trend lines.

7.4.2 Health Professional Shortage Areas

Medically Underserved Area (MUA) and Medically Underserved Population (MUP) designations identify geographic areas and populations with a lack of access to primary care services (38).

MUAs have a shortage of primary care health services for residents within a geographic area. Some examples include a whole county, urban census tracts, or civil divisions. MUPs have a shortage of primary care health services for a specific population subset within an established geographic area. These groups may face economic, cultural, or linguistic barriers to health care (38).

An Index of Medical Underservice (IMU) score is calculated. An IMU score ranges between 0 (highest need) and 100 (lowest need). In order to qualify as an MUA or MUP, the score must be less than or equal to 62.0. Areas with lower scores often have limited access to health care professionals, experience hindered health care access, and face longer wait times and delayed care and diagnosis (38).

In special circumstances, a State Governor or designee can identify a specific population group within a state facing unusual local conditions that hinder access to primary care services, even if the group doesn’t meet the standard criteria for MUP designation, and they can be designated as a shortage area. After conducting a needs assessment and determining what areas are eligible for designation, the State would then submit an application for review by the Secretary of Health and Human Services. These MUPs do not have an IMU score as they follow a separate application process (38). Westchester and Orange Counties have the highest number of MUAs and MUPs. Putnam County had no designations. Table 7.23.

Table 7.23: Medically Underserved Areas and Populations
Area Name Designation Type IMU Score Designation Date
Dutchess Low Income - Poughkeepsie MUP Low Income 59 05/25/2001
Dutchess Migrant & Seasonal Farm Worker - East Dutchess MUP Low Income 45 04/16/2001
Dutchess Medicaid Eligible and Medically Indigent - Beacon Service Area MUP Other Population Governor's Exception N/A 07/06/1993
Orange Orange County Service Area Medically Underserved Area 56 05/04/1994
Orange Village of Walden Service Area Medically Underserved Area 61 06/29/1999
Orange Village of Kiryas Joel Service Area Medically Underserved Area 45 07/21/1993
Orange Low Income - Middletown Service Area MUP Low Income 58 04/08/1994
Rockland Village of New Square Service Area Medically Underserved Area 46 08/03/1993
Rockland Low Income - Haverstraw MUP Low Income 62 07/27/2006
Sullivan Low Income - Western Sullivan Service Area MUP Low Income 59 05/31/2002
Sullivan Low Income - Monticello MUP Low Income 61 06/24/2004
Sullivan and Ulster Low Income - Wawarsing/Fallsburg Service Area MUP Low Income 62 06/18/2002
Ulster Plattekill Town - County Medically Underserved Area 59 05/07/1981
Westchester Westchester Service Area - Elmsford Medically Underserved Area 62 07/05/1994
Westchester Westchester Service Area - Mount Vernon Medically Underserved Area 54 04/06/1978
Westchester Low Income - Mount Kisco MUP Other Population Governor's Exception N/A 02/28/2003
Westchester Westchester Service Area - Peekskill Medically Underserved Area 59 05/04/1994
Westchester Medicaid Eligible and Medically Indigent - Port Chester MUP Other Population Governor's Exception N/A 04/08/1993
Westchester Westchester Service Area - Yonkers Medically Underserved Area 41 10/07/1988

Source: Health Resources and Services Administration Data Warehouse, June 2025 https://data.hrsa.gov/tools/shortage-area/mua-find

NoteNote

Note: An area or population can receive an Index of Medical Underservice (IMU) score between 0–100. An area or population with an IMU of 62.0 or below qualifies for designation as a Medically Underserved Area and Medically Underserved Population (MUP).

Primary care is effective for preventative care, early detection and treatment of disease, and chronic disease management (39). Dental care and mental health care are other disciplines that provide preventative care, as well as diagnosis, management, and treatment of diseases and disorders.

When measuring the ratio of population to provider, a higher ratio means less providers per capita, implying less access.

Sullivan County (3,070:1) had the highest ratio of residents to primary care providers. and the number of providers continues to decrease since 2019. Westchester County had the best resident to provider ratio (760:1). Westchester and Rockland (1,880:1) had better ratios than NYS (1,240:1). Figure 7.20 and Table 7.24.

Figure 7.20: Ratio of Residents to Primary Care Providers, 2019–2022
Table 7.24: Ratio of Residents to Primary Care Providers, 2019–2022
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2019 1,500:1 1,450:1 2,090:1 1,100:1 2,900:1 1,480:1 720:1 1,180:1
2020 1,440:1 1,440:1 1,970:1 1,130:1 2,710:1 840:1 720:1 1,170:1
2021 1,410:1 1,500:1 1,880:1 1,180:1 3,070:1 1,680:1 760:1 1,240:1

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, June 2025 sourced from Area Health Resources Files 2022–2023, and the American Medical Association https://www.countyhealthrankings.org/health-data/new-york?year=2024&measure=Primary+Care+Physicians&tab=1

NoteNote

Note: To interpret this indicator, the value provided is the number of residents to 1 primary care provider. This measure from the County Health Rankings are released each year but data are used from prior years where available.

Sullivan County had the highest ration of resisdents to dentists (2,410:1). Westchester County had the best resident to dentist ratio (910:1). Westchester and Rockland (1,060:1) had better ratios than NYS (1,200:1). Putnam County, Sullivan County, and Ulster County have seen improvements in the ratio between 2019 and 2022, with more dentists being available to residents. Figure 7.21 and Table 7.25.

Figure 7.21: Ratio of Residents to Dentists, 2019–2022
Table 7.25: Ratio of Residents to Dentists, 2019–2022
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2019 1,370:1 1,420:1 1,670:1 980:1 2,430:1 1,570:1 890:1 1,170:1
2020 1,380:1 1,460:1 1,700:1 1,020:1 2,370:1 1,480:1 900:1 1,190:1
2021 1,410:1 1,490:1 1,660:1 1,060:1 2,490:1 1,490:1 930:1 1,220:1
2022 1,400:1 1,500:1 1,610:1 1,060:1 2,410:1 1,470:1 910:1 1,200:1

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, June 2025 sourced from Area Health Resources Files 2022–2023, and the National Provider Identifier Downloadable File https://www.countyhealthrankings.org/health-data/new-york?year=2022&measure=Dentists&tab=1

NoteNote

Note: To interpret this indicator, the value provided is the number of residents to 1 dentist. This measure from the County Health Rankings are released each year but data are used from prior years where available.

Sullivan County had the highest ration of resisdents to mental health providers (510:1). Westchester County had the best resident to mental health provider ratio (230:1). Westchester, Putnam (260:1), and Ulster (270:1) Counties had better ratios than NYS (310:1). All M-H Region Counites have seen improvements in the ratio between 2019 and 2022, with more mental health providers being available to residents. Figure 7.22 and Table 7.26.

Figure 7.22: Ratio of Residents to Mental Health Providers, 2021–2024
Table 7.26: Ratio of Residents to Mental Health Providers, 2021–2024
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021 320:1 390:1 260:1 340:1 510:1 270:1 230:1 310:1
2022 310:1 390:1 240:1 330:1 490:1 260:1 230:1 300:1
2023 300:1 370:1 230:1 300:1 450:1 250:1 220:1 280:1
2024 290:1 350:1 210:1 290:1 450:1 240:1 200:1 260:1

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, June 2025 sourced from National Provider Identification Registry, Centers for Medicaid and Medicare Services https://www.countyhealthrankings.org/health-data/new-york?year=2022&measure=Mental+Health+Providers&tab=1

NoteNote

Note: To interpret this indicator, the value provided is the number of residents to 1 mental health provider. This measure from the County Health Rankings are released each year but data are used from prior years where available.

7.4.3 Access to Primary Care

Receiving regular primary care services is essential for chronic disease management and for the early detection and treatment of disease (39). Having a usual source of care allows for the development of a continuous patient–provider relationship, which can lead to receipt of more preventive care and services as recommended. Lack of insurance, low numbers of providers per capita, limited access to transportation, inability to take time off from work, language-related barriers, and a lack of culturally competent physicians can all hinder access to regular primary care services (39).

Putnam County had the highest percentage of adults who reported having a regular primary care provider (90.5%), while Sullivan County had the lowest percentage (76.9%) Figure 7.23 and Table 7.27. Orange County (88.9%), Putnam, Ulster County (89.5%), and Westchester County (84.9%) exceeded or were similar to the NYS rate (85.0%).

Figure 7.23: Percentage of Adults Who Have a Regular Health Care Provider, 2016, 2018, and 2021

US Census Bureau; American Community Survey, 2023 American Community Survey , Table, 2025

Table 7.27: Percentage of Adults Who Have a Regular Health Care Provider, 2016, 2018, and 2021
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester Mid-Hudson NYS
2016 82.8 81.8 86.7 84.1 84.6 82.5 79.2 N/A 82.6
2018 85.7 80.7 89.0 83.8 75.0 78.3 81.4 N/A 79.1
2021 81.6 88.9 90.5 84.1 76.9 89.5 84.9 86.5 85.0

Source: NYS Community Health Indicator Reports Dashboard, July 2025 sourced from NYSDOH Behavioral Health Risk Factor Surveillance Survey https://webbi1.health.ny.gov/SASStoredProcess/guest?_program=/EBI/PHIG/apps/dashboard/pa_dashboard&p=it&ind_id=pa4_0

NoteNote

Note: The percentage is age-adjusted. An adult is a person aged 18 years or older. The Behavioral Risk Factor Surveillance System asks respondents, “Do you have one person or a group of doctors that you think of as your personal health care provider?” Data unavailable for the Mid-Hudson Region in 2016 and 2018.

7.4.4 Health Care Usage

The American College of Emergency Physicians defines an urgent care center as “a walk-in clinic focused on the delivery of medical care for minor illnesses and injuries in an ambulatory medical facility outside of a traditional hospital-based or freestanding emergency department” (40). Urgent care centers provide quality health care for non–life-threatening illnesses and injuries and are frequently used when primary care physician offices are closed (41).

Emergency departments (ED) are available 24 hours a day, 7 days a week and are intended for the treatment of life-threatening illnesses and injuries requiring immediate attention, including heart attack symptoms, poisoning, pregnancy-related complications, and uncontrollable bleeding (41). ED visits are increasingly being used for nonemergent outpatient care due to lack of health insurance, the absence of a current primary care practitioner, and limited timely alternatives for care (42).

For those admitted to the hospital, many inpatient visits could be avoided if there were access to timely primary and preventive care. Potentially preventable hospitalizations (PPH) are inpatient stays for ambulatory care–sensitive conditions that might have been avoided with high-quality primary and preventive care. Other factors, such as overall access to care, socioeconomic status, and chronic disease prevalence and management, can also contribute to PPH admissions. By identifying avoidable conditions with high admission rates, the health care system can assess where changes can be made to improve efficiency and quality of care (43).

In the M-H Region there is a significant variation among PPH rates. Putnam County had the lowest rate (60.2)and Orange County had the highest rate (106.3). Orange and Sullivan County had rates exceeding NYS excluding NYC (92.7) and NYS (97.3). Figure 7.24 and Table 7.28.

Figure 7.24: Potentially Preventable Hospitalizations, Age-Adjusted Rate per 10,000 Population, 2020–2022
Table 7.28: Potentially Preventable Hospitalizations, Age-Adjusted Rate per 10,000 Population, 2020–2022
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS excl NYC NYS
2020–2022 86.4 106.3 60.2 76.7 100.9 95.7 77.1 92.7 97.3

Source: NYS County Health Indicators by Race and Ethnicity Dashboard, July 2025 sourced from NY Statewide Planning and Research Cooperative System https://www.health.ny.gov/community/health_equity/reports/county/

NoteNote

Note: The number of potentially preventable hospitalizations includes residents aged 18 years and older. The Prevention Quality Indicators (PQI) are a set of measures developed by the federal Agency for Healthcare Research and Quality to assess the quality of outpatient care for “ambulatory care–sensitive conditions.” This indicator is defined as the combination of the 10 PQIs that pertain to adults: Short-term Complication of Diabetes, Long-term Complication of Diabetes, Chronic Obstructive Pulmonary Disease (COPD) or Asthma in Older Adults, Hypertension, Heart Failure, Community-Acquired Pneumonia, Urinary Tract Infection, Uncontrolled Diabetes, Asthma in Younger Adults, and Lower-Extremity Amputation Among Patients with Diabetes. Because the PQIs estimate the number of potentially avoidable hospital admissions, a lower rate is desirable.

Looking at potentially preventable hospitalizations (PPH) by race is an important step in identifying health disparities and targeting interventions to improve access to health care and, ultimately, outcomes.

In the M-H Region, Black non-Hispanic residents tend to experience significantly higher rates of PPH than White non-Hispanic residents. Dutchess County is the only county where White non-Hispanic residents consistently experience higher PPH rates. Otherwise, there are no consistent trends across the region. Orange County and Westchester County show a general decrease in the rate difference over time, while Sullivan County shows an increase between 2019 and 2022 Figure 7.25 and Table 7.29. When interpreting Figure 7.25, a negative rate difference indicates that White non-Hispanic residents have a higher PPH rate than Black non-Hispanic residents, which suggests that Black non-Hispanic residents have fewer admissions that would be considered preventable.

Figure 7.25: Potentially Preventable Hospitalizations, Rate Difference Between Black Non-Hispanics and White Non-Hispanics, 2016–2022
Table 7.29: Potentially Preventable Hospitalizations, Rate Difference Between Black Non-Hispanics and White Non-Hispanics, 2016–2022
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester Mid-Hudson NYS excl NYC NYS
2019 -37.5 115.9 -42.1* 58.5 111.0 51.5 145.3 95.3 20.2 117.6
2020 -20.1 108.9 -21.2* 62.4 75.9 31.5 115.1 78.7 19.7 99.0
2021 -15.4 77.6 s 49.7 41.9 46.7 106.9 71.4 22.2 103.3
2022 -21.9 69.1 -12.3 53.9 154.3 82.3 102.7 71.1 21.7 101.5

Source: NYS Prevention Agenda Tracking Dashboard, August 2025 sourced from NY Statewide Planning and Research Cooperative System https://apps.health.ny.gov/public/tabvis/PHIG_Public/pa/reports/#county

NoteNote

*: The rate is unstable. s: Data are suppressed due to not meeting reporting criteria. Note: Rates are age-adjusted, per 10,000 adults aged 18+. The rate of potentially preventable hospitalization is calculated for both Black and White non-Hispanics. Then, the difference is the Black non-Hispanic rate minus the White non-Hispanic rate.

Non-Hispanic White residents tend to experience higher rates of PPH compared to Hispanic residents in the M-H Region. The only County to consistently have a trend with White Non-Hispanic residents experiencing more PPH was Rockland County. Putnam and Dutchess Counties consistently had lower PPH rates among Hispanic residents. In 2022, all M-H Region Counties had lower rates than NYS. When compared to NYS without NYC (7.1), Westchester County (8.2) and Rockland County (12.2) had higher rates [see Figure 26]. When interpreting Figure 26 a negative rate means that White non-Hispanic residents have a higher rate of PPH compared to the Hispanic residents which suggests that Hispanic residents are not having as many admissions that would be considered preventable

Figure 7.26: Potentially Preventable Hospitalizations, Rate Difference Between Hispanics and White Non-Hispanics, 2016–2022
Table 7.30: Potentially Preventable Hospitalizations, Rate Difference Between Hispanics and White Non-Hispanics, 2016–2022
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester Mid-Hudson NYS excl NYC NYS
2019 -18.0 -6.4 -22.3 29.6 2.4 -8.5 -8.9 -10.8 0.8 36.3
2020 -12.6 10.9 -22.7 28.1 -21.3 5.6 7.0 1.2 8.1 29.7
2021 -18.3 -8.7 -25.5 18.1 -12.0 8.1 7.5 -1.6 4.1 30.1
2022 -1.0 -7.7 -20.8 12.2 0.8 -3.0 8.2 -0.8 7.1 29.5

Source: NYS Prevention Agenda Tracking Dashboard, July 2025 sourced from NY Statewide Planning and Research Cooperative System https://apps.health.ny.gov/public/tabvis/PHIG_Public/pa/reports/#county

NoteNote

Note: Rates are age-adjusted, per 10,000 adults aged 18+. The rate of potentially preventable hospitalization is calculated for both Hispanics and White non-Hispanics. Then, the difference is the Hispanic rate minus the White non-Hispanic rate.

7.4.5 Health Literacy

Healthy People 2030 addresses both personal and organizational health literacy. Personal health literacy is defined as “the degree to which individuals have the ability to find, understand, and use information and services to inform health-related decisions and actions for themselves and others.” Organizational health literacy is defined as “the degree to which organizations equitably enable individuals to find, understand, and use information and services to inform health-related decisions and actions for themselves and others.” (44)

Limited health literacy negatively affects health and is associated with “less participation in health-promotion and disease-detection activities, riskier health choices, more work accidents, diminished management of chronic diseases, poor adherence to medication, increased hospitalization and rehospitalization, increased morbidity, and premature death.” (45) It is important to note that the responsibility of health literacy does not fall solely on the patient. It is also the responsibility of the service provider and their institution to ensure that resources and information being shared are communicated in an appropriate, understandable way. Improving provider-patient communication can lead to shared decision-making and improved health outcomes.

Increasing health literacy in populations has positive effects on society, including the notion that “health literate individuals participate more actively in economic prosperity, have higher earnings and rates of employment, are more educated and informed, contribute more to community activities, and enjoy better health and well-being.” (45)

7.5 Neighborhood and Built Environment

7.5.1 Access to Foods that Support Healthy Eating Patterns

Healthy dietary patterns are essential to living a healthy lifestyle. According to the Dietary Guidelines for Americans 2020–2025, the core elements of a healthy dietary pattern include vegetables, fruits, whole grains, low-fat dairy or fortified dairy alternatives, protein foods, and plant-based oils (46). A healthy diet lowers the risk of chronic diseases such as obesity, type 2 diabetes, and heart disease (47). It is also essential for managing chronic conditions and preventing complications for people with chronic diagnoses (48).

When measuring food access, travel time to supermarkets, availability of healthy foods, and food prices all play a role (49). For people without a personal vehicle, convenient public transportation, or a supermarket within walking distance, finding fresh, healthy options can be a challenge. High grocery prices can deter people with lower socioeconomic status from purchasing healthy options, which can minimize food access. Low-income communities tend to have more difficulty accessing food, and a study in Detroit found that people living in predominantly Black low-income neighborhoods travel an average of 1.1 miles farther to the closest supermarket than people living in predominantly White low-income neighborhoods (50).

The County Health Rankings and Roadmaps measure of the food environment accounts for proximity to healthy foods and income. The index is a scale that ranges from zero (worst) to 10 (best). Limited access to healthy foods estimates the percentage of the population that is low income and does not live close to a grocery store, and food insecurity estimates the percentage of the population that did not have access to a reliable source of food during the past year (51). Ulster County had the lowest food environment index (8.1), while Westchester (9.3) and Putnam (9.0) counties had the highest. The majority of counties fell below NYS’ score of 8.7 except for Westchester and Putnam counties Figure 7.27 and Table 7.31.

Figure 7.27: Index of Factors that Contribute to a Healthy Food Environment, 2018, 2019, and 2022
Table 7.31: Index of Factors that Contribute to a Healthy Food Environment, 2018, 2019, and 2022
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2018 8.6 8.6 8.2 8.7 8.2 8.0 9.2 9.0
2019 8.6 8.5 9.0 8.7 8.3 8.1 9.3 9.0
2022 8.7 8.4 9.0 8.6 8.3 8.1 9.3 8.7

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, July 2025 sourced from US Department of Agriculture - Food Environment Atlas and Feeding America - Map the Meal Gap https://www.countyhealthrankings.org/health-data/new-york?year=2025&measure=Food+Environment+Index&tab=1

NoteNote

The County Health Rankings measure of the food environment accounts for proximity to healthy foods and income. The index is a scale that ranges from 0 (worst) to 10 (best). Limited access to healthy foods estimates the percentage of the population that is low income and does not live close to a grocery store. Food insecurity estimates the percentage of the population that did not have access to a reliable source of food during the past year.

Limited access to healthy foods and food insecurity are indicators which are both equally weighted in the Food Environment Index. To see a county comparison of food insecurity, see Figure 7.3 and Table 7.3 from above.

The “limited access to healthy foods” indicator measures the percentage of the population that is low-income and does not live close to a grocery store. “Low income” is defined as census tracts where the poverty rate is 20% or greater, or the median family income is at or below 80% of the state’s median income. “Low access” areas are defined as census tracts where at least 500 people, or 33% of the population, live more than 1 mile (urban area) or 10 miles (rural area) from a supermarket or large grocery store (50).

Many M-H Counties experienced a decrease in the percentage of the population with low income and low access to food, which is a positive trend. Putnam County had the highest percentage of residents with limited access to healthy food (6.7%) and was almost five times that of Westchester County (1.4%). Most of the counties in the M-H Region fall above NYS (2.0%) excluding Westchester County. Figure 7.28 and Table 7.32.

Figure 7.28: Percentage of Population with Limited Access to Healthy Foods, 2015 and 2019
Table 7.32: Percentage of Population with Limited Access to Healthy Foods, 2015 and 2019
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2015 6.1 6.4 7.5 3.7 2.2 7.5 1.4 3.7
2019 5.7 6.0 6.7 4.4 2.9 6.1 1.4 2.0

Source: US Department of Agriculture - Food Environment Atlas, July 2025 https://gisportal.ers.usda.gov/portal/apps/experiencebuilder/experience/?page=Full-FEA-Map

NoteNote

Percentage of population who are low-income and do not live close to a grocery store.

7.5.2 Crime and Violence

Crime and violence are major public health issues at multiple levels. Violent crime can affect the quality of life for those it reaches, including victims of violent crimes, witnesses of violent crimes, and residents who hear about violent crimes in their communities. Studies have shown that people who fear crime in their communities engage in less physical activity and, as a result, may have higher Body Mass Indexes (BMIs) and higher levels of obesity (52).

Exposure to violence can also have negative impacts on mental health, with consequences that particularly affect children and adolescents. Violence exposure can increase behavioral problems, depression, anxiety, Post-Traumatic Stress Disorder (PTSD), and risky behavior, such as substance use, risky sexual behavior, and unsafe driving (37).

The NYS Division of Criminal Justice Services collects crime reports from police and sheriffs’ departments and submits them to the Federal Bureau of Investigation (FBI) as New York’s official crime statistics. Violent crime totals include reports of murder, rape, robbery, and aggravated assault.

The M-H Region saw fluctuations in violent crime rates between 2018 and 2021. In 2021 all M-H Counties remained below the NYS without NYC rate and the NYS rate. Putnam County consistently had the lowest violent crime rate in the M-H Region from 2018 through 2021. Orange County has the highest rate (192.4 per 100,000). Sullivan County had the highest rates in 2018 and 2019 but has shown a consistent decrease over the four years. Figure 7.29 and Table 7.33.

Figure 7.29: Violent Crimes, Rate per 100,000 Population, 2018–2021
Table 7.33: Violent Crimes, Rate per 100,000 Population, 2018–2021
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS excl NYC NYS
2018 186.4 210.7 55.4 113.5 264.2 161.1 173.6 204.0 351.0
2019 194.8 190.9 49.9 115.5 249.9 145.6 169.3 199.4 359.4
2020 198.0 174.6 37.9 104.9 196.7 128.5 164.4 206.2 365.7
2021 180.7 192.4 48.5 97.9 168.8 130.9 151.5 201.3 384.4

Source: NYS Division of Criminal Justice Services, Uniform Crime and Incident-Based Reporting System, July 2025 https://www.criminaljustice.ny.gov/crimnet/ojsa/countycrimestats.htm

NoteNote

Murder, rape, robbery, and aggravated assault are classified as violent crimes.

7.5.3 Environmental Conditions

Three environmental conditions that negatively impact population health include air pollution, poor water quality, and extreme heat (53). A study reported by the United States Environmental Protection Agency shows socially vulnerable populations, including racial and ethnic minorities, are disproportionately affected by environmental hazards (54).

7.5.3.1 Air Pollution

Air pollution has been linked to several poor health outcomes, particularly those related to the respiratory system. Negative consequences resulting from exposure to fine particulate matter in the air include, but are not limited to, decreased lung function, chronic bronchitis, and premature death (55). Air particulate matter can come from a variety of sources, such as automobiles, industry, and forest fires.

Across all M-H Region Counties and New York State, the average daily density of fine particulate matter generally declined between 2014 and 2020. Westchester County consistently has the highest levels, it also experienced a decline since 2014. Sullivan County and Orange County fluctuate between having the lowest levels. Only Sullivan County and Orange County have periodically had levels lower than NYS. Figure 7.30 and Table 7.34.

Figure 7.30: Average Daily Density of Fine Particulate Matter, 2014, 2016, 2018, and 2020
Table 7.34: Average Daily Density of Fine Particulate Matter, 2014, 2016, 2018, and 2020
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2014 9.3 9.0 9.3 9.7 8.4 8.9 10.4 8.5
2016 7.9 6.2 8.0 8.5 7.3 7.5 9.0 6.6
2018 7.7 6.4 7.9 8.8 7.2 7.4 9.3 6.9
2020 8.3 8.1 8.2 8.4 6.9 8.0 8.8 6.9

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, July 2025 sourced from US Environmental Protection Agency’s Air Quality System - Environmental Public Health Tracking Network https://www.countyhealthrankings.org/health-data/new-york?year=2025&measure=Air+Pollution%3A+Particulate+Matter&tab=1

NoteNote

This is a measure of the average daily density of fine particulate matter. Fine particulate matter is defined as particles of air pollutants with an aerodynamic diameter less than 2.5 micrometers.

7.5.4 Water Quality

Maintaining water quality can be challenging. Sources of water contamination include:

  • Sewage releases.
  • Naturally occurring chemicals and minerals, such as arsenic, radon, and uranium.
  • Local land use practices, such as fertilizers, pesticides, livestock, and concentrated feeding operations.
  • Manufacturing processes, such as heavy metals and cyanide.
  • Malfunctioning on-site wastewater treatment systems, such as septic systems (56).

Runoff can pose a risk to water quality and the health of people exposed to it. When it rains, water flows over impervious surfaces, such as pavement, and can pick up contaminants. Pollution can originate across large land areas or from a single point, such as an industrial pipe. Runoff can pick up sediment, nutrients, bacteria, pesticides, or petroleum byproducts from sources such as farms, waste, and roadways (57). “The presence of certain contaminants in our water can lead to health issues, including gastrointestinal illness, reproductive problems, and neurological disorders. Infants, young children, pregnant women, the elderly, and people with weakened immune systems may be especially at risk for illness.” (58)

7.5.4.1 Lead Poisoning

Lead affects every system of the body, and there is no safe blood lead level. Children are especially vulnerable to the negative impacts of lead exposure, which can lead to slowed growth and development, damage to the brain and nervous system, behavioral problems, and hearing and speech problems (59).

Lead exposure can occur from ingesting, coming in contact with, or breathing in lead dust or lead fumes (60).

Sources of lead can include lead-based paints in homes built before 1978, consumer products such as certain jewelry or toys, aviation gas, working with stained glass, and water pipes that contain lead (61). For children, lead-based paint is the most common source of lead exposure (62). Populations at higher risk for lead exposure include children from low-income households, children less than six years old, immigrant and refugee children from less developed countries, pregnant people, and adults working in industries that expose them to lead (63).

New York State (NYS) requires health care providers to obtain a blood lead level for all children at age one and again at age two (64). Westchester County had the highest testing rate in the M-H Region, with 60.2% of children born in 2019 tested. Sullivan County had the lowest testing rate at 36.6%. Only Westchester County exceeded NYS’ testing rate in all four years Figure 7.31 and Table 7.35.

Figure 7.31: Percentage of Children Tested for Lead Before 36 Months of Age, 2013, 2016, 2017, and 2019
Table 7.35: Percentage of Children Tested for Lead Before 36 Months of Age, 2013, 2016, 2017, and 2019
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester Mid-Hudson NYS
2013 57.2 53.4 61.3 71.3 36.4 51.7 65.5 61.6 62.8
2016 58.8 52.3 62.4 60.3 46.1 53.5 64.3 59.4 63.3
2017 60.7 51.0 60.8 57.0 44.4 55.3 63.6 58.4 62.4
2019 53.3 41.4 58.0 43.8 36.6 49.5 60.2 50.9 59.3

Source: NYS Community Health Indicator Reports Dashboard, July 2025 sourced from NYS Child Health Lead Poisoning Prevention Program https://apps.health.ny.gov/public/tabvis/PHIG_Public/chirs/reports/#county

NoteNote

This is a measure of the percentage of children in a single birth cohort tested at least twice for lead before 36 months of age.

7.5.5 Quality of Housing

According to Healthy People 2030, housing quality refers to the physical condition of a person’s home as well as the quality of the social and physical environment in which the home is located, including aspects of air quality, home safety, space per individual, and the presence of mold, asbestos, or lead. Poor housing quality is associated with negative health outcomes, including poor mental health, chronic disease, and injury (65). Housing continues to face a prolonged crisis in which both affordability and quality remain pressing concerns (65). Beyond inflated rents and high mortgage payments, many households live in poor-quality housing that can cost more to heat, lack air conditioning, have inadequate plumbing, or have insufficient kitchen facilities. Fluctuating temperatures make it difficult to maintain safe indoor environments, contributing to adverse health outcomes. For individuals striving to maintain healthy lifestyles, the absence of a stove or refrigerator can hinder the ability to store and prepare fresh foods while also complicating the safe storage of temperature-sensitive medications. Inadequate plumbing further restricts personal and environmental hygiene. Low-income families are disproportionately affected by these conditions, underscoring persistent social and economic disparities in housing access and quality (65).

For this measure, severe housing problems are the percentage of households with one or more of the following housing problems: lack of complete kitchen facilities, lack of complete plumbing facilities, overcrowding, and severely cost-burdened households.

Rockland County had the highest percentage (26.0%) of households with severe housing problems, three percent higher than that of NYS (23.0%). Putnam and Sullivan Counties had the lowest percentage (17.0% and 16.0%, respectively) of households with severe housing problems. Figure 7.32 and Table 7.36.

Figure 7.32: Percentage of Households with Severe Housing Problems, 2017–2021
Table 7.36: Percentage of Households with Severe Housing Problems, 2017–2021
Year Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS US
2017–2021 17.0 21.0 17.0 26.0 16.0 18.0 22.0 23.0 17.0

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps, July 2025 sourced from US Census Bureau, Comprehensive Housing Affordability Strategy data https://www.countyhealthrankings.org/health-data/newyork?year=2025&measure=Severe+Housing+Problems&tab=1https%3A%2F%2Fwebbi1.health.ny.gov%2FSASStoredProcess%2Fguest %3F_program%3D%2FEBI%2FPHIG%2Fapps%2Fchir_dashboard%2Fchir_dashboard&p=it&ind_id=Cg27

NoteNote

Severe housing problems is the percentage of households with one or more housing problems: lack of complete kitchen facilities; lack of complete plumbing facilities; overcrowding; or the household is severely cost burdened.

7.5.6 Transportation

Transportation can include walking, driving, biking, or utilizing public transportation, such as subways and buses (66). Access to transportation can affect all aspects of life including the ability to find or keep employment, the quantity and quality of food that can be accessed, and access to health care. Studies have shown that those with access to a car are less likely to miss appointments or delay care when compared to those relying on other forms of transportation (67).

Westchester County had the highest percentage of households with no available vehicles at 14.2%. Putnam County had the lowest percentage of households with no available vehicles at 4.2%. All counties within the M-H Region were below the NYS rate with residents having more access to vehicles. Figure 7.33 and Table 7.37.

Figure 7.33: Percentage of Households with No Vehicles Available, 2021–2023
Table 7.37: Percentage of Households with No Vehicles Available, 2021–2023
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021 7.2 8.9 4.7 10.4 10.4 6.8 14.3 28.9
2022 7.2 8.6 4.1 9.9 9.9 7.2 14.2 29.0
2023 7.0 8.6 4.2 9.7 8.8 7.5 14.2 29.0

Source: US Census Bureau; American Community Survey, 2023 American Community Survey 5-Year Estimates, Table DP04, April 2025 https://data.census.gov/table/ACSDP5Y2022.DP04?q=dp04&g=050XX00US36105,36027,36071,36119,36087,36079,36111_040XX00US36

NoteNote

The American Community Survey asks respondents how many automobiles, vans, and trucks of one-ton capacity or less are kept at home for use by members of the household.

7.5.7 Modes of Transportation

In addition to privately owned vehicles, modes of transportation can include walking, mass public transportation, and biking. Benefits of choosing mass public transportation, walking, and biking include protecting the environment by producing far less air pollution than cars and engaging in physical activity (66). However, these modes require individuals to rely more heavily on proper infrastructure, investment, and city planning to make travel safe and effective. Car-dependent cities and communities make it more difficult to use alternative modes of transportation to complete necessary daily tasks, such as going to the grocery store or getting to school, due to a lack of safe sidewalks and public transportation options (67). The transportation method people most often use to get to work can be an indicator of how car dependent an area is and how conducive it is to alternative modes of transportation.

The majority of residents in the M-H Region report driving alone to work as their most common means of commuting. Sullivan County had the highest percentage of commuters driving alone to work (74.1%). Westchester County had a significantly larger share of commuters using public transportation than the rest of the M-H Region (17.8%), as well as the lowest percentage of commuters driving alone to work (51.9%). M-H Region residents were less likely to use public transportation or walk to work compared to NYS. An emerging trend of working from home was noted, with Putnam County (13.7)m Ulster County (15.3%) and Westchester County (17.3%) have the highest percentages in the M-H Region and exceeding NYS. Figure 7.34 and Table 7.38.

Figure 7.34: Percentage of Workers by Mode of Transportation to Work, 2023
Table 7.38: Percentage of Workers by Mode of Transportation to Work, 2023
Category Drove Alone Carpooled Public transportation Walked Taxicab, motorcycle, bicycle, or other means Worked from home
Dutchess 71.4 7.5 3.7 2.3 1.7 13.4
Orange 69.8 9.6 4.4 3.1 2.0 11.1
Putnam 70.6 7.6 5.6 1.5 1.0 13.7
Rockland 66.6 8.5 6.2 3.1 2.8 12.7
Sullivan 74.1 8.8 1.2 2.4 1.9 11.6
Ulster 71.7 6.7 2.1 2.4 1.8 15.3
Westchester 51.9 7.2 17.8 3.7 2.1 17.3
NYS 50.0 6.3 22.4 5.3 2.6 13.3

Source: US Census Bureau; American Community Survey, 2023 American Community Survey 5-Year Estimates, Table B08141, April 2025 https://data.census.gov/table/ACSDT5Y2023.B08141?q=b08141&g=050XX00US36105,36027,36071,36119,36087,36079,3611 1_040XX00US36&tid=B08141

NoteNote

The American Community Survey asks respondents how they usually got to work last week. For respondents who use multiple transportation modes they are restricted to the single method of transportation used for the longest distance.

7.5.8 Average Commute Time

Average commute time, whether long or short, can be attributed to several factors. Long commute times can indicate a lack of job opportunities in an area, slow transit options, and a higher transportation cost burden on households and individuals. It can also negatively impact the community as it contributes to pollution (68).

Putnam County consistently has the longest mean travel time to work (39 minutes) among the M-H Region and exceeds NYS. Westchester County (35 minutes) and Orange County (34 minutes) also exceeded NYS (33 minutes). The remaining counties in the M-H Region had commute times lower than NYS. Figure 7.35 and Table 7.39.

Figure 7.35: Mean Travel Time to Work, 2021–2023
Table 7.39: Mean Travel Time to Work, 2021–2023
Period Dutchess Orange Putnam Rockland Sullivan Ulster Westchester NYS
2021 32.0 34.1 39.2 31.2 28.6 28.6 34.8 33.3
2022 32.3 34.1 39.9 31.0 28.1 28.1 34.8 33.2
2023 31.4 34.2 39.5 30.3 27.8 27.8 34.7 32.8

Source: US Census Bureau; American Community Survey, 2023 American Community Survey 5-Year Estimates, Table DP03, April 2025 https://data.census.gov/table/ACSDP5Y2023.DP03?q=DP03&g=050XX00US36105,36027,36071,36119,36087,36079,36111_040XX00US36

NoteNote

The American Community Survey asks respondents in the workforce how many minutes it usually takes them to get from home to work. The travel time refers to a one-way trip on a typical day. This includes time spent waiting for public transportation, picking up passengers in carpools, and time spent in other activities related to getting to work. Sullivan County and Ulster County do have the same data according to the Census.

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