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Contraception Deserts: Assessing the Geography of Reproductive Healthcare and Family Planning Resource Accessibility in North Carolina

Rebecca Kreitzer, Candis Watts Smith, and Tracee Saunders1

University of North Carolina at Chapel Hill Department of Public Policy

Prepared for the Gender & Political Psychology Conference, Tulane University, October 2017

Please do not circulate. Abstract: Our goal is to determine the extent to which affordable family planning resources are equitably accessible across the United States as well as the political determinants of this distribution. In order to accomplish this goal, we must take a first step of mapping out what we call contraception deserts, or places that are characterized by inequitable distribution of family planning resources. Here, inequitable means that people who are in need of affordable resources are unable to attain them as easily as well-resourced individuals. We measure equity in terms of a spatial (e.g. geographic, time to travel) component as well as non-spatial components (e.g. race, class, age, sex). In this paper, we develop the concept and measurement of contraception deserts; map out the spaces of inaccessibility in the state of North Carolina; and report who is most likely to live in and outside the geography of opportunity.

1 Tracee Saunders is a prospective Ph.D. graduate student who is interested in developing research that analyzes dynamics at the intersection of American politics, state and local political institutions, social inequality, and geography. Her interests are well illustrated by the subject matter studied and methodological strategies employed in this paper.

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Contraception Deserts: Assessing the Geography of Reproductive Healthcare and Family Planning Resource Accessibility in North Carolina

Much-needed attention has been directed toward women’s access to abortion providers across

the United States; this research reveals that there are places where some families have to travel

upwards of 500 miles to gain access to this medically safe and but politically controversial

procedure Marty 2014. Though there has been a consistent decrease in abortions since the 1980s,

the CDC notes that in 2013, over 660,000 women got an abortion. However, there is yet another

set of less studied but highly impactful policies concerning reproductive health matters aside

from abortion, namely access to family planning resources like contraception. In the United

States, two-thirds of women of reproductive age use some form of contraception, which is

largely used to prevent unintended pregnancy, and over 20 million women are in need of

publicly-funded contraception services Guttmacher Institute 2016. This paper focuses on the

degree to which access to high quality, evidence-based, affordable family planning resources is

equitable.

Between the 1950s and the early 2000s, public policy concerning access to contraception

garnered widespread bipartisan support—separate and apart from abortion—but the politics of

abortion and contraception have converged in recent years Aiken and Scott 2016. Policies aimed

to restrict access to abortion have increasingly intertwined policies concerning access to other

family planning and reproductive health resources, such as contraception. For instance, between

2010 and 2014, state legislatures have developed around 230 abortion restrictions, but during

that same time, nine states have also prohibited certain types of family planning providers from

receiving state and federal funds (Fischer, Royer and White 2017). Just as we see a growing

number of “abortion free zones” across the United States, it is not too far to imagine the

development and growth of what we are calling contraception deserts, or localities across the

United States where there is inadequate and, perhaps more importantly, inequitable access to

affordable reproductive healthcare and family planning resources Kreitzer and Smith 2016.

Considering that scholars of geography, city planning, and public health reveal that

access to healthcare is dictated by the confluence of space, race, and class, we aim to uncover

both the spatial and non-spatial determinants of contraception deserts. Spatial determinants

concern the geographical barriers that may exist for people to access resources, such as travel

time. Non-spatial or aspatial access concerns non-geographic barriers such as socioeconomic

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status, race, and age Wang and Luo 2005. “Successful integration of spatial and nonspatial

factors is critical to design an effective method of assessing healthcare access” Wang and Luo

2005. Our first goal is to ascertain the extent to which spatial accessibility to family planning

resources is equitable. Our second goal is to develop a measure of contraception deserts. We

center the idea that since spatial and non-spatial accessibility factors interact and intersect to

exacerbate inequality, the two dimensions ought to be simultaneously considered if we want to

develop an accurate depiction of the geography of opportunity.

It is well known that access to healthcare is not uniform across the American landscape.

What’s more, while private medical practices are not required to even attempt to provide equal

access to health care, a government providing those services must. As such, we focus on access

to Title X-funded clinics and begin this paper with an explanation of this program. Thereafter,

we briefly discuss the literature concerning the geography of health and the multidimensional

concept of accessibility. We shift our focus to the concept and measurement that we are

developing, contraceptive deserts, using North Carolina as a case study. We then explain our

two-part methodological strategy: (a) first, we employ the two-step floating catchment area

(2FCA) method, which allows us to measure the geographic barriers to access to Title X-funded

clinics, and (b) we use a factor analytic method to illuminate the aspatial characteristics of these

spaces. Ultimately, our findings reveal that contraception deserts in the North Carolina do exist,

and they are generally characterized as largely poor and Black or Latinx, and exist in both rural

and urban pockets across the state.

Family Planning Policy in the U.S.

Family planning policy has not only become increasingly salient in the American political

sphere, but its path has diverged quite dramatically over the past decade or so. In the mid-20th

Century, policy makers across the two major political parties largely supported policies that

provided easy, equitable access to affordable contraception Meier and McFarlane 2001. This

widespread bipartisan support for family planning culminated in President Nixon passing Title X

of the Public Health Service Act in 1970. Title X is the only federal program dedicated

exclusively to family planning and related preventive and reproductive health care services. To

be sure, the extent to which low-income families have access to affordable reproductive health

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care is determined by a confluence of state policies and budgets and federal laws and funding

efforts. However, over the past decade or so, political polarization at both the state and federal

levels has served to polarize policy makers on all sorts of issues, including ones that they have

traditionally agreed upon, like access to voluntary, affordable contraception Layman, et al. 2006,

Aiken and Scott 2016.

Title X-funded clinics have a particular set of characteristics that is important for us to

consider. First, each clinic is required to offer “a broad range of acceptable and effective

medically approved contraceptive methods and related services” Office of Population Affiairs

2014. Aside from a complete exclusion of abortion procedures as an option, there are a plethora

of combinations and permutations of resources that each clinic provides. One clinic, for instance,

may offer condoms, birth control pills, and natural family planning methods while another may

offer all of those along with Long Acting Reversal Contraceptive devices (LARC), vasectomies,

and dental dams. “A broad range” can be implemented differently across the Title-X grantees

and clinics, but because grantees have to apply and win grants, there is at least a basic standard

that all Title X clinics must abide by. Second, the services must be provided on a “voluntary and

confidential basis;” confidentiality is also guaranteed to unemancipated minors. Third, Title X-

funded clinics also deliver preventive health services, such as cervical and breast cancer

screening, HIV prevention education, testing and referral, and pregnancy diagnosis and referral.

Although Title X was initially intended “to assist in making comprehensive voluntary

family planning services available to all persons desiring such services,” the implementation has

largely focused on low-income and young women Meier and McFarlane 2001. Title X requires

that services be provided regardless of income, but grantees can choose to require a fee on a

sliding scale to those whose incomes are above the poverty level (Ibid, 84). As such, many of the

uninsured women of reproductive age (15-44 years) rely on Title X clinics Fanarjian, et al. 2012.

Taken together, Title X-funded clinics are required to provide a set of large range of high quality,

affordable family planning resources. Given that this program is publically funded, citizens are

entitled to expect the resources to be equitably distributed.

How Does It Work?

Unlike programs like Medicaid, Title X is administered by ten regional offices of the U.S. Public

Health Service, rather than by state or welfare departments, and organizations must apply for

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funds. Grants are awarded on a competitive basis Meier and McFarlane 2001. Organizations,

including states, must “win” their grant from the federal government. Each state has at least one

Title X grantee, and in about half of the states, the state is the sole grantee. In other states, there

are multiple grantees or the state sub-contracts the funds and tasks to other organizations

National Family Planning & Reproductive Health Association 2016.

Generally speaking, states as opposed to non-profit organizations are the most likely to

win these grants due to path dependency and the difficulty of handling and administering these

grants. Thus, states have a great deal of power in how well family planning services are

distributed, and there is a great deal of state-by-state variation in the ways in which Title X funds

may be used effectively and efficiently. First, there is variation in the extent to which states rely

on Title X funds for family planning policy. For example, Wisconsin adopted a measure that

prohibits the state from providing family planning funds, including Title X funds, to agencies

that also provide abortions; there have been at least four other states (IL, MN, PA, and VA) that

have also considered such a measure Nash, et al. 2013.

Relatedly, in 2011, Texas drastically cut the state’s funding for family planning and

reproductive health by two-thirds (but in 2013 increased it again to some degree) Aiken and

Scott 2016, thus Title X because a more essential pillar of care in that state. The 2011 budget

cuts in Texas led to the closure of 76 women’s health clinics across the state of Texas. As a

consequence, 55% of women reported at least one barrier (e.g. lack of transportation, inability to

pay) in accessing reproductive health care services, and women who reported three or more

barriers tended to be Hispanic, poor, and have lower levels of education Texas Policy Evaluation

Project 2015.

With this in mind, it is important to consider distribution of these clinics across space on

a state-by-state basis, as state level politics may have a great deal of influence on the extent to

which these resources are equitably distributed. We begin by analyzing access to these federally-

funded clinics in one state, North Carolina.

A Geography of Health

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One’s zip code has a high degree of predictive power for health outcomes. Indeed, recent

research has exposed the fact that life expectancy can differ by twenty years in neighborhoods

only five miles apart from one another Health 2015. Scholars have long recognized that health is

not just a matter of individual choices (e.g. eating well, exercising) but also due to a geography

of opportunity.

For instance, one might be familiar with the concept of food deserts, a term which is used

to describe areas where residents do not have access to an affordable and healthy diet. The

scholarship on food deserts provides evidence that it is not just individuals’ behavior and

attitudes that influence their health outcomes but also the structure of the built environment, such

as the number of supermarkets, fast food chains, parks and green spaces, and availability of

public transportation Smith and Morton 2009, Gordon, et al. 2011. What’s more, this literature

further highlights the high degree of correlation between race, class, and space as well as the

confluence of these three factors on health outcomes. Food deserts tend to exist in inner city

and/or rural areas characterized by high-poverty and underserved minority populations. Indeed,

the U.S. government is cognizant of the intersection of health disparities and geography, as

government agencies rely on two systems to identify areas that do not have a sufficient number

of physicians: Health Professional Shortage Areas (HPSA) and the Medically Underserved Areas

or Populations (MUA/MUP). Put simply, the calculus behind the measures incorporate aspects of

supply of doctors and demand for their services, the health of the population (e.g. infant

mortality rate, population over 65), and population need for subsidized care (e.g. poverty

rate)Luo 2004, Ricketts, et al. 2007.

For our purposes here, it is important to illuminate the fact that Black and Hispanic

women have higher unintended pregnancy rates than White women; these disparities become

greater when we examine the role of income and education Colker 1991, Wildsmith, et al. 2010,

Finer and Zolna 2011, Mosher, et al. 2012. Additionally, research shows that one of the “most

sweeping barriers” to access of contraception is that “the lives of many women and poor women

in particular are chaotic and not conducive to careful family planning” Association of

Reproductive Health and National Campaign to Prevent Teen and Unplanned Preganancy 2008.

Rather than focusing on the attitudes and behaviors of women, we examine the extent to which

the built environment combines with race and class to influence differential access to

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contraception, and more specifically access to Title X-funded clinics given the high standard of

care and resources required by the federal government.

Contraception Deserts

The concept and measure of contraception desert is a new way to think about the political-spatial

dynamics of access to reproductive health care resources. We define a contraception desert as

spaces of inequitable access to a wide-range of affordable, effective family planning resources.

Access is a multidimensional variable. Sociologist Ronald Anderson and his colleagues

provide a helpful framework of accessibility to health care, which has two dimensions: potential

access and realized access Andersen, et al. 1983. Realized access focuses on the rates of use and

subjective levels of satisfaction with the health care system. The second dimension is potential

access. Potential access concerns the characteristics of the delivery system, such as the

availability of health care professionals and facilities as well as spatial factors, such as

geographic location and distance/ease to travel. Potential access also concerns aspatial or non-

spatial factors, such as the characteristics of the individuals in the area (e.g. age, race, income,

insurance coverage, health status). We focus on the former, potential access, because this

dimension is concerned with the structural components that may influence whether members of a

community have the prospect to successfully access resources.

A large proportion of scholarship that seeks to highlight accessibility to health providers

or healthy food tends to examine spatial factors in isolation. That is to say, they tend to examine

how far or close a resource is, doctor-to-patient ratios, or the terrain of a space which may create

geographical barriers to resources, separate and apart from non-spatial factors. The previously

mentioned measures that state and federal governments rely on, Health Professional Shortage

Areas (HPSA) and MUA/MUP are excellent examples of a spatial measures. These measures can

be understood as regional availability measures, which use administrative boundaries like zip

codes or counties as the basic spatial units for calculating the population-to-provider ratios

(PPR). The PPR is typically calculated by simply dividing the number of providers (the supply)

by the population size (the demand) in a given area, such as a county or zip code. Federal

agencies prefer to calculate and prioritize PPR because this are easy to understand, intuitive, and

standard Ricketts, et al. 2007.

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While the greatest benefit of this approach is that this figure is easy to estimate and

intuitive to understand, there are a number of important drawbacks. To begin, even within

HSPSA and MUA/MUP designations, there is considerable disagreement about what ratio

triggers a designation. Most significantly, these measures ignore the spatial distribution of the

supply of providers and demand of the population within the formal geographic boundary, which

are likely to be uneven. One can easily imagine a hypothetical district in which most of the

population lives and physicians provide services in a small corner of the district. Relatedly,

traditional approaches to measuring shortage areas do not acknowledge cross-border health

seeking behavior. That is, a person living in the heavily populated corner of the hypothetical

district may seek health care in a neighboring district.

Nonetheless, this research and these measures are important to keep at the forefront of

our mind “because identifying where the truly underserved populations are located is the

essential first step toward any meaningful and effective” policy intervention Luo 2004. But, it

should be duly noted that the intersection spatial and aspatial factors is what ultimately serves to

exacerbate inequality. Secondly, there are new methodological strategies that not only allow us

to consider these two dimensions but also to do more complex, detailed spatial calculations of

spatial distributions of both the population and clinics, and to do so without relying on

administrative boundaries that citizens cross all the time to access resources; we employ one of

these strategies below.

Our measure and concept of contraception deserts is essentially a measure of whether

there is “equity of access,” which “may be said to exist when services are distributed on the

basis of people’s need for them” Andersen, et al. 1983. This measure integrates both spatial and

non-spatial factors enabling us to provide a more accurate depiction of potential access to family

planning and reproductive healthcare resources. To be precise, we designate a space a

contraception desert when it has met two basic criteria. First, spatial access to affordable,

effective family planning resources must be low. That is to say, one must travel beyond a

reasonable distance or amount of time in order to access resources. Unfortunately, it is likely that

there are millions of families who live in areas where they must travel a longer than necessary

time or distance, there are some people who have the means and resources to overcome this

problem; traveling farther or for longer is an inconvenience but not a prohibitive barrier. To

reiterate, contraception deserts is a measure of inequity. As such, the second criterion is that

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those areas with low potential spatial access must also be areas where high-needs families are

most likely to reside. This means that contraception deserts are, by definition, places where those

who are in need of subsidized family planning resources are unable to access them.

In order to meet the goal of developing a measure that encompasses both spatial and non-

spatial dynamics, we have to integrating methodological strategies: the two-step floating

catchment area method, principle components analysis and factor analysis.

Methods

2SFCA: Measuring Spatial Access As mentioned, previous approaches to identifying health shortage areas relied heavily on

administrative boundaries, and did not take into account unequal spatial distribution of

physicians and the population within the administrative boundary or the propensity of people to

seek health services across administrative boundaries. One approach that has recently gained

traction among public health scholars and applied geographers is the two-step floating catchment

area (2SFCA) method. This approach was developed by Luo (2004) is based on the previous

work on spatial decomposition by Radke and Mu (2000); it overcomes these limitations by using

a smaller unit of analysis (census tracts or blocks instead of counties or zip codes) to solve the

issue of unequal spatial distribution and by using a radius of reasonable distance around

providers that can cross administrative borders, thus posing a significant advancement over

previous approaches of spatial accessibility.

To be specific, instead of using administrative boundaries to calculate the provider to

physician ratio, the basic FCA model draws a X-minute polygon (X= some reasonable distance

measured in minutes or miles) around the centroid of a census tract to create a “catchment area.”

A similar polygon “floats” from tract to tract, and the provider-to-patient ratio is then calculated

for each tract (Luo 2004). The underlying assumption of this method is that all services within

the catchment area are fully available to all residents in that catchment. This is not necessarily

the case as providers on the edge of one catchment may be more than X-minutes away from

some residents in the catchment, and some providers on the edge of a catchment may provide

services to residents of a nearby catchment (and thus be less available to provide services to

residents in their own catchment).

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Radke and Mu (2000) overcome this problem by repeating the process of creating

“floating catchments” twice: once based on provider locations and once based on population

locations. This is now widely known as the “two-step floating catchment area” method.

Basically, step one creates an initial ratio to each service area centered at a provider (supply)

location and step two adds up the initial ratios in the overlapping service areas to measure

provider accessibility at population (demand) localities, taking into account there may be

multiple suppliers in a demand locality. The second catchment uses the population centroid

within a tract (instead of the geographic centroid itself) to account for the fact that there is not an

equal population distribution across census geographic space, and that most residents may be on

the edge of a tract instead of the center.

Step One: Identify each provider location and the determine all of the population locations that are within the reasonable travel distance from that provider location. You then compute the physician to population ratio within that catchment. Step Two: For each of the population locations, search all of the provider locations within the threshold travel distance, and sum up the physician to provider ratios at those locations. A larger ratio indicates better spatial accessibility.

Identifying a Reasonable Travel Distance

What is the reasonable amount of time for someone to drive to obtain family planning services?

The federal guideline for maximum distance to a primary care provider for the purpose of

determining a Health Professional Shortage Area is 30 minutes (US Health and Human Services

1993). The standard of 30 minutes is also commonly used in other studies of healthcare

accessibility and distance (Bosanac et al 1976, Fortney et al 2000, Sherman et al 2005). While 30

minutes as a standard is common in the literature, a “reasonable” driving distance may be longer

or shorter based on the services provided. For instance, an appropriate reasonable driving

distance to a cancer treatment facility may be further away than a reasonable distance to a

pharmacy (Luo and Qi 2009).

We believe that family planning services lie somewhere in the middle of that spectrum.

Most healthy people only see a primary care physician annually. While contraceptive dispensing

patterns vary by insurer and method, many plans limit supply of oral contraception to one to

three months. Other methods, such as the Depovera shot must be administered every three

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months. Previous research indicates that providing women with a longer lasting supply of oral

contraception increases contraceptive use (Steenland et al 2013), and decreases rates of

unintended pregnancy (Foster 2011).

In 2015, Oregon became the first state to pass a law requiring insurers to provide longer

supplies of contraception. This law mandates that insurance cover the first 3 months when

initially prescribed, and then cover a 12-month supply. Since then, laws requiring coverage for

12 months of oral contraception have been enacted in 11 states and D.C. (Kaiser Family

Foundation 2017). However, in 49 states women must return to a family planning clinic quarterly

or monthly unless they are utilizing a long-acting reversible contraception (LARC). While 14.4%

of women aged 15-44 used LARC, 59.7% used oral contraception, the contraceptive ring or path,

or injectable contraception (Kaiser Family Foundation 2017).

North Carolina, however, is not one of the states that have increased access to

contraception by providing longer prescriptions. For this reason, we map accessibility to family

planning using a reasonable driving distance of 15 minutes. We repeat our analysis with a 30-

minute threshold to create a second-more conservative identification of contraception deserts.

Measuring Non-Spatial Barriers to Access The extant literature consistently demonstrates that population characteristics like race, ethnicity,

age, employment, income and rural residence shape access to primary care (Ricketts et al 2007,

Agency for Healthcare Research and Quality 2010). While some scholars standardize these

relevant demographic variables and combine them to create a composite index (Field 2000),

these variables tend to be multicollinear and such a scale assumes equal weight for each

component (Wang and Luo 2005). Other scholars use factor analysis to consolidate these

variables into a few relevant independent factors (Wang and Luo 2005, McGrail and Humphreys

2009). We take this approach here.

We use the 2015 American Communities Survey to compile relevant demographic data at

the census tract level that are most likely to constrain potential access at the individual level. We

include several measures to capture poverty, including the percent of the population with income

less than 100% of the federal poverty level, percent homeownership, percent of houses lacking

basic amenities, more than 1 person living per room, percent on Medicaid, and without a vehicle.

We capture racial and ethnic variables with the percent Black and percent Latinx. We also

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include the percent of the population with limited English because linguistic isolation is

associated with lower awareness of social services. Finally, we include a variable for the percent

of female-headed households. Additional information about these variables, including their

construction and descriptive statistics, are in Appendix Tables 1 and 2.

Then, we use principle components analysis (PCA). The purpose of PCA is to show the

relative importance of our predicted components based on their eigenvalues. In deciding which

components to include, there is typically a tradeoff between pursuing a higher total variance

explained (achieved by including more components) and ease of interpretation (which is

generally easier with fewer components). We follow the common rule that only eigenvalues

greater than 1 are important, leaving us with two factors. Fortunately for us, these two factors

explain nearly all of the total variance (.9596) (Appendix Table 3). We show the factor loadings

in matrix format for only those factors with an eigenvalue greater than 1 in Appendix Table 4.

Finally, we display the loading structure for the two non-spatial factors in Table 1 using factor

analysis. We use these two factors in the integrated 2SFCA.

Table 1. Factor Structure of Aspatial Determinants of Potential Access

Variable Factor 1 Factor 2 Uniqueness Medicaid 0.8343 0.2290 0.2515 <100% Federal Poverty Level 0.8150 0.2361 0.2801 Female HOH 0.8007 0.1350 0.3235 No Vehicle 0.7955 0.0756 0.3614 Black 0.7293 0.0127 0.3837 Homeownership -0.5970 -0.3188 0.5419 Latinx 0.4760 0.8214 0.2953 Limited English 0.1956 0.7844 0.3464 Lacking Basic Utilities 0.2963 -0.1335 0.8944 More than 1 person per room 0.0710 0.4303 0.8098 % of total variance explained 73.45% 22.51%

Bolded Factor Loadings represent values >|0.5|

Factor one is the dominant factor, explaining a remarkable 73.45% of the total variance.

This factor captures six variables: percent receiving Medicaid, population in poverty, female

head of household, percent without a vehicle, percent Black, and percent homeownership. All of

these variables are positively signed with the exception of homeownership, a lower rate of which

is associated with poverty. The second factor explains considerably less variance (22.51%). This

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factor is strongly explained by only two variables: percent Latinx and percent of the population

with limited English.

Implementing the Integrated 2SFCA Method For our study, we used the ArcGIS network analyst tool to calculate polygons around all Title X

clinic points. The area in the first catchment represents all people who can reach a clinic within

15(30) minutes.2 The second catchment area is drawn around the population-weighted centroid

of a census tract. Census tracts generally have a population between 1,200 and 8,000 people,

which an optimal size of 4,000 people. They usually cover a contiguous area, but the spatial size

of tracts varies widely depending on population density (U.S. Census Bureau). The intersection

of these two catchment areas is then calculated to ensure that populations are not counted twice.

We then combined the clinic location, census tract population, demographic data and factor

analysis using the census geographic identifier.

Based on this information, we create several new variables. The weighted population

reflects the number of people that have access to a given clinic. This is calculated as the product

of the percentage of a census tract that is included by the catchment areas and the total

population of the census tract. The clinic count reflects the number of clinics that a census tract

has access to, and the frequency reflects the number of census tracts for which a given clinic is

responsible (the number of census tracts that contribute population to a given clinic). We then

create a measure of clinic availability by summing the weighted population by clinic locations.

For instance, if a hypothetical census tract has access to 3 clinics in which clinic one services

23,444 people, clinic two services 31,000 and clinic three services 15,000 people then the clinic

availability would be 23,444+31,000+15,000.

The provider-to-population ratio is then summed by the population locations, creating a

measure of tract accessibility, which represents the availability of clinics that are reachable from

a residential location. More succinctly stated, the spatial accessibility score is essentially the

following ratio filtered by a threshold travel time of 15(30) minutes:

𝑛𝑢𝑚𝑏𝑒𝑟𝑜𝑓𝑐𝑙𝑖𝑛𝑖𝑐𝑠𝑎𝑐𝑐𝑒𝑠𝑠𝑖𝑏𝑙𝑒𝑡𝑜𝑎𝑔𝑖𝑣𝑒𝑛𝑡𝑟𝑎𝑐𝑡

𝑡𝑜𝑡𝑎𝑙𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑜𝑓𝑝𝑒𝑜𝑝𝑙𝑒𝑓𝑜𝑟𝑤ℎ𝑖𝑐ℎ𝑎𝑐𝑙𝑖𝑛𝑖𝑐𝑖𝑠𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑖𝑏𝑙𝑒=

∑𝑐𝑙𝑖𝑛𝑖𝑐𝑐𝑜𝑢𝑛𝑡∑𝑐𝑙𝑖𝑛𝑖𝑐𝑎𝑣𝑎𝑖𝑙𝑎𝑏𝑖𝑙𝑖𝑡𝑦

2 Because of data availability, we use the location of clinics instead of the number of physicians at a given location. Both provider location and physician location are used in other analyses using 2SFCA.

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The total population in the denominator takes into account the percentage of a census tract’s area

that is encompassed by a catchment area and multiples the percentage of times the population of

that census tract to get a better measure of how many people will go to that clinic. Finally, the

tract accessibility score is merged with the census tract shapefile for mapping and analysis.

Results: Identifying Contraception Deserts in North Carolina

We first map the spatial accessibility to Title X-funded clinics. Figures 1 and 2 show the relative

spatial accessibility of Title X clinics using the two-step floating catchment area method with 15

and 30-minute catchment areas, respectively. In these figures, the darker areas indicate areas

with better spatial access. It is clear from these initial images that access to affordable

contraception across the state is not equitable, with coastal and mountain regions having higher

spatial access scores than urban areas in the center of the state.3

There are two important caveat we should note about this method. The first is that this

approach does assume an equal distribution of population across the state, an assumption that

clearly is unmet. The largest metropolitan areas in the North Carolina are in the center of the

state, with rural areas being primarily on the ends of the state. The second weakness is that the

spatial accessibility ratio can be problematic for rural areas. Rural areas that have relatively low

populations have spatial accessibility scores so high that regardless of their designation as high

needs through the factor analysis, they cannot be considered a contraception desert. North

Carolina has several rural areas that are relatively sparsely populated. What’s more, North

Carolina has the largest proportion of Blacks who live in rural areas in the entire country. As a

result, we are almost certainly underestimating the occurrence of contraception deserts in rural

areas, and thus our measure of inequity is a conservative one.

This set of caveats becomes obvious in our figures. Here, we see that sparsely populated

rural areas have high spatial access scores because of the population to provider ratio, given the

3 This is in large part an artifact of the abovementioned caveat – that sparsely populated rural areas have high spatial access scores because of the population to provider ratio, given the relative locations of the clinic itself and the population centroid. For instance, one area with a particularly high spatial access score is Hyde County, near the coast. According to the 2010 Census, the county is the second-largest county in North Carolina based on area, with 57% of the county comprised of water, but the second-least populated. Residents in this area, of which 62% are white, likely receive services from the Hyde County Health Department, which provides services four days a week.

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relative locations of the clinic itself and the population centroid. For instance, one area with a

particularly high spatial access score is Hyde County, near the coast. According to the 2010

Census, the county is the second-largest county in North Carolina based on area, with 57% of the

county comprised of water, but the second-least populated. Residents in this area, of which 62%

are white, likely receive services from the Hyde County Health Department, which provides

services four days a week.

Figure 1 Spatial Accessibility, 15 Minute Catchment Area

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Figure 2 Spatial Accessibility, 30 minute Catchment Area

Next, we move to the integrated 2SFCA maps to designate contraception deserts. The

integrated analysis includes both spatial and non-spatial barriers to affordable family planning

resources. Contraception deserts are areas where spatial access is severely limited, or spatial

access is quite constrained and the people who live in those areas are in marginalized groups. We

operationalize contraception deserts using the following criteria. First, we designate an area as a

contraception desert if census tracts are not captured by either the first or second catchment area.

If less than 50% of the population within a census tract has access to a clinic by the first

catchment, then they are considered “not caught” by the catchment and receive a spatial access

score of 0. Or, if a census tract’s population weighted centroid is not encompassed by the second

catchment area, the census tract has access to 0 clinics within 15(30) minutes and receives a

spatial access score of 0. We also designate a space a contraception desert if tracts have a spatial

accessibility score of less than 3/100,000 (two standard deviations below the mean of all spatial

accessibility scores) and rank as high needs. Here, high needs means that either of the tract’s

non-spatial indicators are one or more standard deviations above the mean.

17

The locations of contraception deserts in North Carolina is mapped in Figures 3 and 4,

with 15 and 30-minute catchment areas respectively. The areas colored in dark blue have poor

spatial access, and the areas in light blue have marginally poor spatial access but serve a high-

needs community. There are far fewer areas identified in the 30-minute catchment area analysis

as contraception deserts, but keep in mind the underestimation of deserts in rural areas. Even in

this very conservative estimation of access inequality, one should note that the area around

Charlotte (the largest city in the state) and several coastal communities still face limited access.

Figure 3 Contraception Deserts, 15 Minute Service Areas

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Figure 4 Contraception Deserts, 30 Minute Designation

At first glance, it seems that North Carolina is doing well; there is nothing comparable to the

500-hundred mile abortion free zone that another state has seen. But, it should be noted that

percent of the population that lives in these contraception deserts is not trivial. Tables 2a and 2b

provide summary statistics, of sorts.

The first row of Table 2A identifies the tracts colored in dark blue on the Figures 3 and 4,

and represents the tracts with no spatial access. The second row identifies the tracts colored in

light blue, with marginally limited spatial access but a high-needs population. Summing together

the numbers in the last column, we find that an astonishing 25.2% of the states’ population (est.

10,146,788) lives in a contraception desert. 1.2 million people live in areas with no spatial

access, and an additional 1.3 million people live in high needs areas with relatively low spatial

access.

The number of people living in a contraception desert is still remarkable even when using

a 30-minute catchment. More than half a million people, or 10% of the state population, live in

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an identified tract. Given that our method likely underestimates tracts in rural areas, our findings

suggest a significant population lives in areas with spatial and non-spatial barriers to family

planning.

Table 2A Contraception Deserts Identified by the Integrated Approach, 15-minutes

Contraception Deserts

Criteria Primary Secondary

Tracts No. %

Area mi2 %

Population No. %

Geographic Area + Integrated Designation

Spatial Access = 0 Spatial Access < 3/100,000 and High Need

297 0.137 295 0.1362

6397.35 0.1188 725.827 0.0135

1,245,975 12.27 1,315,385 12.96

Table 2B Contraception Deserts Identified by the Integrated Approach, 30-minutes

Contraception Deserts

Criteria Primary Secondary

Tracts No. %

Area mi2 %

Population No. %

Geographic Areas + Integrated Designation

Spatial Access = 0 Spatial Access < 3/100,000 and High Need

21 0.0097 98 0.0452

185.387 0.0034 251.03 0.00466

49,805 04.91 461,865 04.55

Discussion

By using a methodological strategy that allows us to develop a theoretically-driven measure of

contraception deserts, we are able to provide evidence not only that spaces of inequitable access

to family planning and reproductive healthcare resources exist, but also how large they are, how

prevalent they are, who they are most likely to affect, and what proportion of the population is

likely to be affected by these inequities.

There is good reason to predict that North Carolina’s results may not be representative of

other states. To begin, unlike most other states, there is a county health department in nearly

every one of North Carolina’s 100 counties, each of which provide services at least a few days a

week. What’s more, in North Carolina, Title X sub-grantees must apply to the state in order to

get funds. The implications for this is that since the state actually has high standards for meeting

the expectations set by the federal government, each clinic does have a wide range of

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contraception available. In our conversation with the former Title X coordinator of North

Carolina, Sydney Atkins, she noted that though some counties were reluctant to provide LARC

due to “old school doctors,” but the coordinating office required them to do so. Consequently,

when you can get to a clinic, you will be well-resourced. Taken together, despite the fact that

Title X funds have decreased over the years, the North Carolina Title X offices (one housed with

the state, the other housed with Planned Parenthood) have made an effort to spread the resources

as well as they can. But even with great effort and attention to detail, there are still areas of

inaccessibility.

We can put our findings in perspective. According to research by Grindlay and Grossman

(2016), nearly one-third of women at risk for unintended pregnancy that tried to obtain a

prescription for contraception in 2011 reported experiencing trouble doing so. Few Title X

clinics relative to the population and geography likely contributes to this. In future work, we will

extend our analysis beyond North Carolina to map access to contraception across the country. In

contrast to North Carolina, there are only 90 Title X clinics operate in Texas, which has 5 times

the landmass and nearly 3 times the population. Pennsylvania has only 4 Title X clinics in total,

and Wisconsin only 17. There is potential for an incredible range of variation across the 50

states, and our goal moving forward is to capture and report that. In future iterations of this

project, we may also incorporate some modifications and enhancements to the 2SFCA approach,

such as incorporating a distance decay function around the population centroid or using a larger

catchment area for rural communities.

This paper is motivated by the goal of mapping out contraception deserts across the

United States and to develop expectations of the political determinants of the size and scope of

these spaces of inequity. Access to affordable reproductive health care occurs due to a

confluence of federal and state policies, but it is state variation that interests us. Because a great

deal of inequality is a matter of state level elites’ policy choices, we seek to discern the role of

politics in the development, maintenance, or reduction of equitable access to contraception and

related reproductive health care as we move forward with this research endeavor. This paper

represents the first small step taken toward the larger goal.

21

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