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Health Serv Res. 2009 October; 44(5 Pt 2): 1796–1817.
PMCID: PMC2758407

Geographic Variation in Public Health Spending: Correlates and Consequences

Abstract

Objectives

To examine the extent of variation in public health agency spending levels across communities and over time, and to identify institutional and community correlates of this variation.

Data Sources and Setting

Three cross-sectional surveys of the nation's 2,900 local public health agencies conducted by the National Association of County and City Health Officials in 1993, 1997, and 2005, linked with contemporaneous information on population demographics, socioeconomic characteristics, and health resources.

Study Design

A longitudinal cohort design was used to analyze community-level variation and change in per-capita public health agency spending between 1993 and 2005. Multivariate regression models for panel data were used to estimate associations between spending, institutional characteristics, health resources, and population characteristics.

Principal Findings

The top 20 percent of communities had public health agency spending levels >13 times higher than communities in the lowest quintile, and most of this variation persisted after adjusting for differences in demographics and service mix. Local boards of health and decentralized state-local administrative structures were associated with higher spending levels and lower risks of spending reductions. Local public health agency spending was inversely associated with local-area medical spending.

Conclusions

The mechanisms that determine funding flows to local agencies may place some communities at a disadvantage in securing resources for public health activities.

Keywords: Public health spending, population health, practice variation

Geographic variation in health care spending within the United States has long been a source of policy concern because it implies large inefficiencies and inequities in resource use (Wennberg and Gittelsohn 1973). The greater-than-twofold differences in health care spending observed across U.S. communities persist after accounting for differences in medical care prices (Welch et al. 1993; Skinner and Fisher 1997;), socioeconomic status (SES), and illness burden (Wennberg and Cooper 1998; Fisher et al. 2000;). Moreover, several recent studies suggest that residents of high-spending regions do not enjoy superior health outcomes compared with their counterparts in low-spending regions (Fisher et al. 2003a,b;). Medical care represents only one class of resources used to improve health and control disease, and studies suggest that these resources account for only about half of the gains in life expectancy realized during the past half-century (Brown et al. 1991; Trust for America's Health [TFAH] 2006; Sensenig 2007;). By comparison, public health resources support activities designed to promote health and prevent disease and disability at the population level, such as efforts to monitor community health status, investigate and control disease outbreaks, educate the public about health risks and prevention strategies, enforce public health laws and regulations like those concerning tobacco use or food preparation, and inspect and assure the safety and quality of water, air, and other resources necessary for good health (Institute of Medicine [IOM] 1988). These activities may account for gains in health and life expectancy that are not attributable to medical care. As such, geographic variation in public health resources may contribute to gaps and inequities in population health. Relatively little is known, however, about the extent and nature of geographic variation in public health spending.

Although no uniform system of accounts exists to track public health spending at national, state, or local levels, available estimates suggest that less than 5 percent of the nation's health-related spending is devoted to public health activities (Brown et al. 1991; TFAH 2006; Sensenig 2007;). Public health activities are supported through a patchwork of local, state, federal, and nongovernmental funding mechanisms that vary widely across states and communities (Gerzoff, Gordon, and Richards 1996; Gordon, Gerzoff, and Richards 1997; TFAH 2006;). These mechanisms give rise to large geographic disparities in spending for public health services. The National Association of State Budget Officers (NASBO) estimated that state governments' per-capita spending on public health activities varied by a factor of >30 in 2003, ranging from >U.S.$400 per person in Alaska and Hawaii to <U.S.$75 per person in Iowa, Arkansas, Idaho, and Utah (NASBO 2005). Estimates of variation in local public health agency spending are even larger, ranging from <U.S.$1 per capita to >U.S.$200 per capita in 2005, with the median local public health agency spending about U.S.$30 per person (National Association of County and City Health Officials [NACCHO] 2006).

On balance, very little empirical evidence exists about the extent and nature of geographic variation in public health spending (Carande-Kulis, Getzen, and Thacker 2007). The lack of uniform data on public health spending has hampered research on this topic. The NASBO and more recently the TFAH have used information from state budget documents to produce estimates of state governmental spending on public health activities, but differences in state accounting and reporting conventions cause significant errors and inconsistencies in estimates (NASBO 2005; TFAH 2006;). Other studies have classified the public health expenditures of individual state or local governments using standardized accounting protocols, but these individual assessments do not support systematic comparisons of spending across communities and over time (Barry et al. 1998; Budetti and Lapolla 2008;). Estimates of federal, state, and local governmental expenditures on public health activities are included in the National Health Expenditure Accounts maintained by the U.S. Centers for Medicare and Medicaid Services (CMS), using data collected by the U.S. Census of Governments. These estimates, however, are widely considered to be incomplete because they include expenditures for a relatively narrow set of governmental activities and because they exclude expenditures on personal health services commonly provided by public health agencies, such as immunizations, chronic disease screening, and communicable disease control (Sensenig 2007). Completely lacking in the literature are estimates of the resources expended on public health activities by nongovernmental organizations such as community hospitals, community-based organizations, health insurers, and employers (Mays, Halverson, and Kaluzny 1998; Mays et al. 2000;).

This paper uses a recently compiled longitudinal dataset on local governmental public health agencies to examine how public health spending levels vary across communities and change over time. Following similar studies of variation in medical spending, we focus on three primary questions of interest: (1) what are the demographic, socioeconomic, and institutional characteristics of high-spending and low-spending communities? (2) What characteristics are associated with growth and decline in spending levels over time? (3) What types of communities are most likely to experience reductions in public health spending? Answers to these questions will help policy makers at all levels of government anticipate resource needs and make better decisions about how to allocate scarce public health resources.

This study focuses on spending at the local level because local public health agencies—rather than their state and federal counterparts—assume primary responsibility for directly implementing public health activities in most communities (DeFriese et al. 1981; Halverson et al. 1996;). Most federal and state grants for public health activities, and significant private funding, are channeled through local public health agencies (Mays et al. 2004b; NACCHO 2006;). Moreover, these agencies frequently work to mobilize and coordinate the public health activities of other organizations in the community (Mays, Halverson, and Kaluzny 1998; IOM 2002;). As such, these agencies provide valuable settings in which to study the determinants and consequences of public health spending in the United States.

CONCEPTUAL FRAMEWORK

The amount of resources expended for public health services in a given community is determined through a complex interaction of economic conditions and fiscal capacities, delivery system characteristics, community health needs, and policy priorities (Tiebout 1956; Sacks and Harris 1964; Handler, Issel, and Turnock 2001;). Local and state economic conditions are particularly important drivers of spending levels because many communities depend heavily on state and local tax bases to fund their public health activities (NACCHO 2006). Economically disadvantaged communities face limited tax bases and many competing demands for these resources, making it difficult to support a full array of public health activities (Hajat, Brown, and Fraser 2001; Bernet 2007;).

Characteristics of the delivery system for public health services introduce additional sources of variation in spending (Handler and Turnock 1996; Mays et al. 2004a,b;). Governmental public health agencies vary widely in their statutorily defined powers and scope of activities, which are established by both state and local law. A few common activities are performed by the vast majority of local public health agencies in the United States, such as communicable disease surveillance and control, chronic disease screening, and food service inspection. For many other activities like tobacco control, responsibility rests with the local public health agency in some communities, with the state agency in other communities, and with a separate public or private organization in still other communities (NACCHO 2006). Agencies that have statutory responsibility for a broad scope of public activities are likely to require more resources than agencies with a narrower mission.

In some communities nongovernmental organizations play important roles in performing selected public health activities, potentially reducing the need for governmental spending (Halverson, Mays, and Kaluzny 2000; Mays et al. 2000; Mays, Halverson, and Stevens 2001;). Conversely, the shortage of nongovernmental providers in some communities may create the need for public health agencies to provide an expanded range of services beyond traditional public health activities. In particular, agencies that operate in medically underserved areas may provide clinical services such as immunizations, prenatal care, and other primary care services for patients who lack access to mainstream medical providers. Agencies that are heavily involved in clinical service delivery may generate higher spending levels due to the higher input costs of providing these services.

Delivery system characteristics may also influence the efficiency of public health practice, resulting in spending variation. For example, public health agencies serving large communities may realize economies of scale in performing public health activities requiring high fixed costs, such as surveillance systems and laboratory capacities (Mays et al. 2006). Conversely, agencies serving rural jurisdictions with low population densities may spend more to perform epidemiological investigations, health education campaigns, or tobacco control enforcement actions compared with agencies serving more geographically concentrated populations. The potential for economies of scale may lead some agencies to pool their resources through mergers, regional alliances, or joint operating agreements.

Population characteristics that determine health risks and needs within the community represent another class of factors likely to influence public health spending patterns. These characteristics include social and economic determinants of health such as income and employment, educational attainment, race and ethnicity, age, and language and culture (Adler and Newman 2002; Mechanic 2002, 2005, 2007). Agencies serving low-SES populations are likely to require more resources to prevent and control health risks than their counterparts that serve less vulnerable populations. Whether this need for more resources translates into an ability to obtain more resources remains an open empirical question.

Finally, political dynamics may influence local public health spending decisions. Predominant political ideologies and cultures within a state or community are likely to shape attitudes about the appropriate role of government in protecting health and preventing disease and injury, and these attitudes may explain some of the geographic variation in public health spending observed across communities (Morone 1997; Oliver 2006;). These views are mediated by state and local political institutions and administrative structures, which shape the extent to which public health issues reach the policy agenda. Two related, institutional characteristics are of particular interest when examining the political economy of local public health practice: (1) the existence of a local governing board of health with the authority to establish policy priorities, and (2) the degree to which public health decision making authority is decentralized and delegated from the state to the local governmental level. Local governing boards of health are hypothesized to generate enhanced public and political support for local public health agencies, because their membership frequently includes individuals who have political access, professional credibility, and/or technical expertise that can be used to attract and maintain resources (Mays et al. 2004a, b, 2006). Likewise, decentralized local governmental authority is hypothesized to facilitate resource decisions that are informed of and responsive to community needs (Tiebout 1956; Stigler 1957; DeFriese et al. 1981; Gordon 1983;). On the other hand, centralized state authority may allow communities to benefit from economies of scale and the ability to coordinate resources across multiple local jurisdictions (Aikin, Hutchinson, and Strumpf 2006). The empirical evidence on this issue remains limited and mixed.

METHODS

Study Population

A longitudinal, retrospective cohort design was used to analyze public health expenditures among the nation's nearly 3,000 local public health agencies between 1993 and 2005. The study population included all organizations operating during this time period who met the NACCHO definition of a local health department: an administrative or service unit of a local or state government that has responsibility for performing public health functions for a geopolitical jurisdiction smaller than a state (NACCHO 2006). All U.S. states except Rhode Island contained agencies that met this definition. In 2005, approximately 73 percent of these agencies served county jurisdictions or combined city–county jurisdictions, with the remaining agencies serving city or township jurisdictions (16 percent) or multicounty or regional jurisdictions (11 percent).

Data Sources

NACCHO collected expenditure data along with organizational and operational characteristics of local public health agencies through census surveys fielded in 1993, 1997, and 2005. A total of 2,888 agencies meeting the NACCHO definition were identified in 1993. The survey response rate was 72 percent in 1993, 88 percent in 1997, and 80 percent in 2005. A core set of variables reflecting annual agency expenditures, revenue sources, staffing levels, jurisdiction population size, and services offered were collected in each year of the survey. Observations were linked across the 3 years of the survey using identifying information on each public health agency, resulting in a panel dataset containing observations on 6,566 agency-years.

Using identifying information about each local public health agency's jurisdiction and the county or counties in which it operates, we linked the NACCHO survey data with contemporaneous, county-level data from several other sources. For public health agencies serving jurisdictions of more than one county, we aggregated county-level data to the multicounty jurisdiction. Because county-level data may provide a poor approximation of the subcounty jurisdictions served by city and township agencies (15 percent of agencies), we tested the sensitivity of results to including these agencies in the analyses and found no evidence of bias. County-level data on population characteristics and health resources were obtained from the Area Resource File. County-level variables reflecting direct federal public health expenditures were constructed from the Consolidated Federal Funds Report. For simplicity we defined federal public health spending to include all federal grant-in-aid programs administered by the U.S. Centers for Disease Control and Prevention. These expenditure data do not include federal funding given to state agencies that are subsequently passed through to local recipients, but such pass-through funding is included in the agency expenditure data collected on the NACCHO survey. State-level data on public health expenditures were obtained from the U.S. Census Bureau's 1993, 1997, and 2005 Census of Governments using expenditure function category 32 that excludes hospital care and most other medical care expenditures. Finally, county-level data on annual medical care spending per Medicare beneficiary were obtained from the CMS and linked with other data using county identifiers. The medical spending estimate reflects total annual Medicare reimbursements for all covered services per Medicare beneficiary. As a robustness check, we also used the county-level Medicare Adjusted Average Per Capita Cost estimate as a risk-adjusted indicator of medical care spending in the county.

Measures and Model Specification

Public Health Spending Measures

The dependent variable of interest in this analysis is the measure of per-capita local public health agency spending. This variable was measured as an agency's total annual expenditures divided by the total population residing within the jurisdiction of the agency. In keeping with prior studies, the total jurisdiction population estimate was used as the denominator for this measure because most of the activities performed by a local public health agency are public goods (e.g., disease surveillance, restaurant inspections, health education) designed to protect and promote health for the community at large rather than for individual service users (Gerzoff, Gordon, and Richards 1996; Gordon, Gerzoff, and Richards 1997;). The 1997 and 2005 NACCHO surveys collected jurisdiction population estimates, and so these data were used to construct the estimates of spending per capita in those years. The 1993 survey did not collect detailed population estimates, and so we estimated the jurisdiction population size for that year using Census data. Each spending measure was adjusted to 2005 dollars using a weighted average of the general Consumer Price Index (CPI) and the medical care CPI, recognizing that most public health agencies provide a blend of personal medical services and population-based services (NACCHO 2006). We used a weight that reflected each agency's share of revenues from Medicaid, Medicare, and private health insurance.

Explanatory Variables

The explanatory variables used in this analysis reflect characteristics of the public health agency, the area population, and the community that are hypothesized to influence public health spending, as described in the conceptual framework. A single indicator variable was used to identify agencies that operated under the authority of a local board of health. We classified the administrative control of each agency as either decentralized local government control or centralized state government control. For decentralized agencies, we further specified type of local government agency as county, city/township, or a combined government district. The scope of services offered by the local public health agency was characterized using a series of 75 variables indicating whether a specific service was delivered by the agency. We grouped these services into six categories representing clinical preventive services, population-based activities, medical treatment services, specialty services, regulatory enforcement and licensing activities, and other environmental health services (see Appendix SA2 for variable classifications). For each service category, we constructed a variable indicating the proportion of services in that category that were performed by the public health agency. As a final public health characteristic, we measured staffing level as the total number of full-time equivalent staff employed by the local public health agency. In keeping with prior studies and to avoid multicollinearity with population size, we scaled this variable by the population size of the jurisdiction to indicate staffing levels per 100,000 population (Tilson and Gebbie 2004; Gebbie and Turnock 2006;). We also included variables to capture local medical resources in the community that may offset the need for public health resources, along with variables reflecting population characteristics associated with health risks and needs within the community (Table 1).

Table 1
Characteristics of Local Public Health Agencies and Communities by Quintile of Spending per Capita

Statistical Analysis

All analyses used the local public health agency and the community it serves as the unit of analysis. To identify the correlates of high-spending and low-spending agencies/communities, we grouped communities into quintiles based on the measure of local public health spending per capita in 2005, and tested for differences in delivery system characteristics and community characteristics across the quintiles. Next, multivariate regression models for panel data were used to estimate associations between local public health spending and the array of public health system characteristics, health resources, and community characteristics included in the analysis. We estimated two different versions of these models: (1) a reduced-form model that does not include measures reflecting the scope of services offered by the public health agency; and (2) an expanded model that includes these variables. The expanded model assumes that an agency's service offerings are determined exogenously and therefore their association with public health spending can be estimated directly. For parsimony, some of the covariates listed in Table 1 were dropped from the regression models due to lack of association with the spending variable.

Two alternative model specifications were tested to account for autocorrelation due to repeated observations on the same agencies over time: (1) a random-effects model that assumes that the agency-specific correlation coefficients are randomly distributed and uncorrelated with the other characteristics included in the model; and (2) a fixed-effects model that allows the agency-specific coefficients to be correlated with other covariates. The two specifications yielded qualitatively similar results, and so we present estimates from the random-effects models in this paper. We also tested models that included state-fixed effects and found that results are robust when these effects are excluded. We estimated each model using a logarithmic specification in order to reduce skewness and outliers in the public health spending measure. Standard errors were estimated using the robust method to account for clustering of agencies within states (White 1980).

Logistic regression models were used to identify the types of communities most likely to experience reductions in public health spending between 1993 and 2005. For these models, the independent variables were defined to include (1) the baseline 1993 values of the explanatory variables used in the spending model above; and (2) measures reflecting the absolute difference (change) in values of the explanatory variables between 1993 and 2005. We used coefficients from the logistic regression models to construct estimates of the marginal effect of each independent variable on the probability of experiencing a reduction in public health spending.

RESULTS

Local public health spending reached U.S.$29.57 per capita for the median community in 2005, virtually unchanged from the 1996 median of U.S.$29.51 and slightly higher than the 1993 median of U.S.$26.26 per capita. The aggregate rate of growth in local public health spending during the 1993–2005 period was <1 percent per year in constant dollars. Overall, 65 percent of communities experienced positive growth in per-capita public health spending over the 1993–2005 period, with an average increase of U.S.$3.73 per capita. The coefficient of variation in public health spending increased significantly from 0.95 in 1993 to 1.04 and 2005, indicating a trend toward greater variation in spending.

Differences between High-Spending and Low-Spending Communities

Public health agency spending levels varied widely across communities and over the 12-year period of study. In the lowest 20 percent of communities, spending averaged <U.S.$8 per capita in 2005 and declined by U.S.$5 per capita between 1993 and 2005 (Table 1). By contrast, in the top 20 percent of communities spending averaged nearly U.S.$102 per capita and grew by more than U.S.$18 per capita between 1993 and 2005. Communities in the top quintile had spending levels >13 times higher than communities in the lowest quintile.

Public health agencies in the highest quintile of spending provided a broader scope of clinical preventive services, population-based services, medical treatment services, and specialty services compared with their lower-spending counterparts (p<.05). However, there were no significant differences in the scope of regulatory and environmental health services performed by high-spending and low-spending agencies. Agencies in the highest quintile of spending received larger shares of their revenue from clinical service reimbursements (e.g., Medicaid, Medicare, and private insurance payments) and smaller shares of their revenue from local government sources, compared with agencies in lower spending quintiles (p<.05). Agencies in the highest quintile of spending were more likely to operate as decentralized units of county government, compared with lower-spending agencies (p<.05).

Medical care resources varied inversely with the level of public health agency spending. Low-spending agencies served communities with larger numbers of physicians per capita and were more likely to be served by a federally qualified health center, compared with agencies in higher spending quintiles (p<.05). Medical care spending also varied inversely with public health agency spending (Figure 1). Medical spending per Medicare beneficiary was 11 percent higher in communities within the lowest quintile of public health agency spending, compared with communities within the highest quintile of agency spending (p<.05). This inverse association existed for both inpatient and outpatient Medicare spending and persisted when risk-adjusted Medicare spending estimates were used (data not shown).

Figure 1
Public Health Agency and Medicare Spending Levels in 2005, by Quintile of Public Health Spending

Sources of Variation in Public Health Spending

Multivariate analysis of public health agency spending patterns indicated that structural and institutional characteristics of the public health system were among the strongest predictors of per-capita spending levels. Spending was >14 percent higher among agencies governed by a local board of health compared with agencies without such boards (p<.001), after controlling for other characteristics in the reduced-form model (Table 2). Similarly, spending was >25 percent higher among decentralized local public health agencies, compared with agencies operating under centralized state authority. Significant differences in spending were also noted across alternative types of local government agencies.

Table 2
Regression Estimates of Factors Associated with Public Health Agency Spending

When variables reflecting the scope of services offered by the local public health agency were included in an expanded model, three of these variables emerged as significant predictors of local public health spending (Table 2). Clinical preventive services had the strongest association with spending, such that a 10 percent increase in the proportion of services offered by an agency was associated with a 6.8 percent increase in spending, after controlling for other variables in the model (p<.01). Consistent with these estimates, we found higher spending levels among agencies that derived larger shares of their revenue from clinical service reimbursements (p<.01). The three nonclinical categories of service—population-based services, regulatory services, and environmental health services—were not statistically associated with spending levels after controlling for other variables in the model, although the environmental health variable approached significance (p<.10). Among the population and community characteristics examined, per-capita income and metropolitan area location were most strongly associated with spending, but these inverse associations were mediated largely by agency service offerings.

Factors Associated with Reductions in Spending

In total, 35 percent of communities experienced reductions in spending during the 1993–2005 study period, with the average loss of >U.S.$11 per capita in constant dollars. Logistic regression estimates indicated that decentralized public health agencies and agencies governed by a local board of health were significantly less likely to experience reductions in per-capita spending compared with their counterparts (Table 3). Agencies serving more populous communities in the baseline year of 1993 were less likely to experience reductions in per-capita spending over the study period (p<.05), but subsequent population growth during the study period placed agencies at greater risk of reductions (p<.01). Communities with higher proportions of racial minority residents were more likely to experience spending reductions (p<.05).

Table 3
Factors Associated with Reductions in Public Health Spending, 1993–2005

DISCUSSION

Local public health agency spending varies widely across communities. This variation has increased over time, and it persists after accounting for sociodemographic differences in the populations served and for differences in the scope of services offered by agencies. The Dartmouth Atlas of Health Care estimated that per-capita medical care spending varied by a factor of 1.6 between communities in the highest and lowest quintiles of the distribution (Wennberg and Cooper 1998). By comparison, public health agency spending varied by a factor of 13.3, and this interquintile variation remained high at 7.3 after adjusting for differences in population characteristics and service mix. This finding suggests that local public health resources may be distributed more unevenly than that of medical care.

The patterns of variation in local public health agency spending appear quite distinct from that of medical care, such that higher levels of agency spending are associated with lower levels of medical care spending and resources in the community. Several possible mechanisms may contribute to these patterns. First, public health resources may offset the need for medical care in some communities by preventing or limiting disease and injury. Second, high levels of disease burden within a community may simultaneously increase demand for curative medical care and diminish demand for public health activities, which may receive less priority in the face of acute-care needs. Third, low rates of health insurance coverage and limited availability of mainstream medical care providers may suppress access to medical care while simultaneously increasing demand for services from public health agencies—particularly those agencies that offer clinical services. Finally, high levels of spending on medical care may limit the amount of public resources available to invest in public health activities. Importantly, our measure of medical spending is limited because it reflects only spending for Medicare beneficiaries, which accounted for about 20 percent of personal health care spending nationally in 2005 (CMS 2009). Further research on the mechanisms of interaction between public health and medical care resources is needed to identify opportunities for coordinated resource deployment.

Public health governance and administrative structures emerged as two of the strongest correlates of public health agency spending. Local boards of health and decentralized administrative structures are associated with higher levels of spending, larger increases in spending over time, and reduced vulnerability to spending reductions. These findings are consistent with the hypothesis that local governance and local administrative control engender political and community support for public health activities and encourage entrepreneurship in securing resources. Policies to develop and support local governing and administrative bodies may be effective in expanding public health capacity.

Overall, about 15 percent of the observed variation in local public health agency spending is explained by differences in service mix, while 8 percent is attributable to differences in agency structural characteristics, and another 8 percent is attributable to differences in population characteristics. Two-thirds of the variation in public health agency spending remains unaccounted for in this study. This residual variation is comparable to the unexplained variation found in studies in medical care spending, which range from about 50 to 75 percent of total variation in spending (Congressional Budget Office 2008).

Residual variation in public health spending likely stems from a combination of factors, including imperfections in the spending data used here and unmeasured factors that determine resource needs and availability. Of particular note, the spending measures used in this analysis reflect the resources of local public health agencies and therefore do not capture the resources invested in public health activities by other governmental and private organizations. Prior studies have estimated that these other institutions contribute >25 percent of the local public health activities performed in the average U.S. community (Halverson et al. 1996; Halverson, Mays, and Kaluzny 2000; Mays et al. 2004a;). Some of the residual variation in local public health agency spending may be attributable to these contributions that offset the need for agency effort. Residual variation may also reflect unmeasured differences in population health needs, the costs of producing and delivering public health services, and the effectiveness of agency leadership and management.

The large residual variation in local public health spending also suggests that considerable uncertainty exists among policy makers and administrators about optimal levels of investment in public health activities. Clear evidence and professional consensus has yet to emerge about the mix of programs and services that communities need to protect health and about the levels of human, financial, and other resources needed to assure this availability (IOM 2003). Expanded research to develop this evidence and translate it through guidelines and decision supports for public health practice are needed to reduce uncertainty and improve resource allocation decisions (Scutchfield and Patrick 2007).

Ultimately the ability to detect and correct wasteful, harmful, and inequitable variations in public health spending depends on capturing more detailed data about spending patterns and their effects. The aggregate spending measures used in this analysis reflect total resources used across all categories of spending and therefore do not reveal how resources are distributed across the many programs and services maintained at the community level. By measuring spending levels in specific programmatic areas such as tobacco control, obesity prevention, and communicable disease control, it becomes possible to identify more precise patterns of resource use and to assess the relative value of each type of spending. This fact underscores the need for improved data systems to track not only medical care spending (Cutler, Rosen, and Vijan 2006) but also public health expenditures at national, state, and local levels.

Acknowledgments

Joint Acknowledgment/Disclosure Statement: This research was supported by grant #56469 from the Robert Wood Johnson Foundation's Changes in Health Care Financing and Organization Program, Special Topic Solicitation on Public Health Systems Research, administered by AcademyHealth. Dr. Mays was also supported by the National Cancer Institute's Community Networks Program (CA114607). We gratefully acknowledge the assistance of Carolyn Leep and colleagues at the National Association for County and City Health Officials for providing data from the National Profile of Local Health Departments and technical assistance regarding use of these data.

Disclosures: None.

Disclaimers: None.

Supporting Information

Additional supporting information may be found in the online version of this article:

Appendix SA1: Author Matrix.

Appendix SA2: Services Used to Construct Composite Measures of Service Offerings.

Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.

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