Cost Analysis of the Positive Health Check Intervention to Suppress HIV Viral Load and Retain Patients in HIV Clinical Care.

CONTEXT: Digital video-based behavioral interventions are effective tools for improving HIV care and treatment outcomes. OBJECTIVE: To assess the costs of the Positive Health Check (PHC) intervention delivered in HIV primary care settings. DESIGN, SETTING, AND INTERVENTION: The PHC study was a randomized trial evaluating the effectiveness of a highly tailored, interactive video-counseling intervention delivered in 4 HIV care clinics in the United States in improving viral suppression and retention in care. Eligible patients were randomized to either the PHC intervention or the control arm. Control arm participants received standard of care (SOC), and intervention arm participants received SOC plus PHC. The intervention was delivered on computer tablets in the clinic waiting rooms. The PHC intervention improved viral suppression among male participants. A microcosting approach was used to assess the program costs, including labor hours, materials and supplies, equipment, and office overhead. PARTICIPANTS: Persons with HIV infection, receiving care in participating clinics. MAIN OUTCOME MEASURES: The primary outcome was the number of patients virally suppressed, defined as having fewer than 200 copies/mL by the end of their 12-month follow-up. RESULTS: A total of 397 (range across sites [range], 95-102) participants were enrolled in the PHC intervention arm, of whom 368 participants (range, 82-98) had viral load data at baseline and were included in the viral load analyses. Of those, 210 (range, 41-63) patients were virally suppressed at the end of their 12-month follow-up visit. The overall annual program cost was $402 274 (range, $65 581-$124 629). We estimated the average program cost per patient at $1013 (range, $649-$1259) and the cost per patient virally suppressed at $1916 (range, $1041-$3040). Recruitment and outreach costs accounted for 30% of PHC program costs. CONCLUSIONS: The costs of this interactive video-counseling intervention are comparable with other retention in care or reengagement interventions.

State-Level Health Care Expenditures Associated With Disability.

OBJECTIVE: Given the growth in national disability-associated health care expenditures (DAHE) and the changes in health insurance-specific DAHE distribution, updated estimates of state-level DAHE are needed. The objective of this study was to update state-level estimates of DAHE. METHODS: We combined data from the 2013-2015 Medical Expenditure Panel Survey, 2013-2015 Behavioral Risk Factor Surveillance System, and 2014 National Health Expenditure Accounts to calculate state-level DAHE for US adults in total, per adult, and per (adult) person with disability (PWD). We adjusted expenditures to 2017 prices and assessed changes in DAHE from 2003 to 2015. RESULTS: In 2015, DAHE were $868 billion nationally (range, $1.4 billion in Wyoming to $102.8 billion in California) accounting for 36% of total health care expenditures (range, 29%-41%). From 2003 to 2015, total DAHE increased by 65% (range, 35%-125%). In 2015, DAHE per PWD were highest in the District of Columbia ($27 839) and lowest in Alabama ($12 603). From 2003 to 2015, per-PWD DAHE increased by 13% (range, -20% to 61%) and per-capita DAHE increased by 28% (range, 7%-84%). In 2015, Medicare DAHE per PWD ranged from $10 067 in Alaska to $18 768 in New Jersey. Medicaid DAHE per PWD ranged from $9825 in Nevada to $43 365 in the District of Columbia. Nonpublic-health insurer per-PWD DAHE ranged from $7641 in Arkansas to $18 796 in Alaska. CONCLUSION: DAHE are substantial and vary by state. The public sector largely supports the health care costs of people with disabilities. State policy makers and other stakeholders can use these results to inform the development of public health programs that support and provide ongoing health care to people with disabilities.

National Health Care Expenditures Associated With Disability.

BACKGROUND: In 2003, national disability-associated health care expenditures (DAHE) were $398 billion. Updated estimates will improve our understanding of current DAHE. OBJECTIVE: The objective of this study was to estimate national DAHE for the US adult population and analyze spending by insurance and service categories and to assess changes in spending over the past decade. RESEARCH DESIGN: Data from the 2013-2015 Medical Expenditure Panel Survey were used to estimate DAHE for noninstitutionalized adults. These estimates were reconciled with National Health Expenditure Accounts (NHEA) data and adjusted to 2017 medical prices. Expenditures for institutionalized adults were added from NHEA data. MEASURES: National DAHE in total, by insurance and service categories, and percentage of total expenditures associated with disability. RESULTS: DAHE in 2015 were $868 billion (at 2017 prices), representing 36% of total national health care spending (up from 27% in 2003). DAHE per person with disability increased from $13,395 in 2003 to $17,431 in 2015, whereas nondisability per-person spending remained constant (about $6700). Public insurers paid 69% of DAHE. Medicare paid the largest portion ($324.7 billion), and Medicaid DAHE were $277.2 billion. More than half (54%) of all Medicare expenditures and 72% of all Medicaid expenditures were associated with disability. CONCLUSIONS: The share of health care expenditures associated with disability has increased substantially over the past decade. The high proportion of DAHE paid by public insurers reinforces the importance of public programs designed to improve health care for people with disabilities and emphasizes the need for evaluating programs and health services available to this vulnerable population.

Estimating State-Level Health Burden of Diabetes: Diabetes-Attributable Fractions for Diabetes Complications.

INTRODUCTION: Limited information is available on the health burden of diabetes at the state level. This study estimated state-specific attributable fractions and the number of cases attributable to diabetes for diabetes-related complications. METHODS: For each state, diabetes-attributable fractions for nine diabetes complications were estimated: three self-reported complications from the 2013 Behavioral Risk Factor Surveillance System, hospitalizations with three complications from 2011 to 2014 State Inpatient Databases, and three complications from 2013 Medicare data. Attributable fractions were calculated using RR and diabetes prevalence and the total number of cases using attributable fractions and total number of complications. Adjusted RR of each complication for people with and without diabetes by age and sex was estimated using a generalized linear model. Analyses were conducted in 2015-2016. RESULTS: Median state-level diabetes-attributable fractions for self-reported complications were 0.14 (range, 0.10-0.19) for mobility limitations; 0.13 (range, 0.04-0.21) for limitations in instrumental activities of daily living; and 0.12 (range, 0.06-0.20) for severe visual impairment or blindness. Median state-level diabetes-attributable fractions for diabetes-associated hospitalizations were 0.19 (range, 0.08-0.24) for congestive heart failure; 0.08 (range, 0.02-0.16) for myocardial infarction; and 0.62 (range, 0.46-0.73) for lower extremity amputations. Median state-level diabetes-attributable fractions for complications among Medicare beneficiaries were 0.17 (range, 0.14-0.23) for coronary heart disease; 0.28 (range, 0.24-0.33) for chronic kidney disease; and 0.22 (range, 0.08-0.32) for peripheral vascular disease. CONCLUSIONS: Diabetes carries a significant health burden, and results vary across states. Efforts to prevent or delay diabetes or to improve diabetes management could reduce the health burden because of diabetes.

Economic Costs Attributable to Diabetes in Each U.S. State.

OBJECTIVE: To estimate direct medical and indirect costs attributable to diabetes in each U.S. state in total and per person with diabetes. RESEARCH DESIGN AND METHODS: We used an attributable fraction approach to estimate direct medical costs using data from the 2013 State Health Expenditure Accounts, 2013 Behavioral Risk Factor Surveillance System, and the Centers for Medicare & Medicaid Services' 2013-2014 Minimum Data Set. We used a human capital approach to estimate indirect costs measured by lost productivity from morbidity (absenteeism, presenteeism, lost household productivity, and inability to work) and premature mortality, using the 2008-2013 National Health Interview Survey, 2013 daily housework value data, 2013 mortality data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research, and mean wages from the 2014 Bureau of Labor Statistics. Costs were adjusted to 2017 U.S. dollars. RESULTS: The estimated median state economic cost was $5.9 billion, ranging from $694 million to $55.5 billion, in total and $18,248, ranging from $15,418 to $30,915, per person with diabetes. The corresponding estimates for direct medical costs were $2.8 billion (range $0.3-22.9) and $8,544 (range $6,591-12,953) and for indirect costs were $3.0 billion (range $0.4-32.6) and $9,672 (range $7,133-17,962). In general, the estimated state median indirect costs resulting from morbidity were larger than costs from mortality both in total and per person with diabetes. CONCLUSIONS: Economic costs attributable to diabetes were large and varied widely across states. Our comprehensive state-specific estimates provide essential information needed by state policymakers to monitor the economic burden of the disease and to better plan and evaluate interventions for preventing type 2 diabetes and managing diabetes in their states.

Cost Effectiveness of Strategies for Recruiting Low-Income Families for Behavioral Parent Training.

The goal of this study was to assess cost, effectiveness, and cost-effectiveness of recruitment strategies used to engage low-income families of young children with disruptive behavior disorder to participate in a Behavioral Parent Training (BPT) program. For this analysis, we used data on labor and non-labor resources associated with 13 recruitment strategies implemented in February 2014 through February 2016. We assessed the effectiveness of each strategy as the number of families that enrolled into the study. Cost-effectiveness of each recruitment strategy was expressed as cost per family enrolled; analysis was conducted in 2016. We calculated the cost of total recruitment effort for 13 strategies during the 2-year period to be $11,496 with an average cost of $885 per recruitment strategy or $255 per enrolled family. Across strategies, total costs ranged from $25 to $2,540. "University mass e-mail" and "school flyers" resulted in the most phone screens (34 each); however, only 10% of these families enrolled in the study (3 and 4 families, respectively). "Craigslist" was the most effective strategy with 30 families screened and 11 of them enrolling. Three strategies did not yield any participants. The four strategies with the lowest cost per family enrolled were "Facebook page," "Craigslist," "university mass e-mail," and "organization/agency" (< $90). In conclusion, we found that some recruitment strategies were more successful at engaging low-income families to participate in a BPT program than others. Our results indicate that using a combination of recruitment strategies may be the optimal approach for recruiting low-income families.

Costs of community-based interventions from the Community Transformation Grants.

Limited data are available on the costs of evidence-based community-wide prevention programs. The objective of this study was to estimate the per-person costs of strategies that support policy, systems, and environmental changes implemented under the Community Transformation Grants (CTG) program. We collected cost data from 29 CTG awardees and estimated program costs as spending on labor; consultants; materials, travel, and services; overhead activities; partners; and the value of in-kind contributions. We estimated costs per person reached for 20 strategies. We assessed how per-person costs varied with the number of people reached. Data were collected in 2012-2015, and the analysis was conducted in 2015-2016. Two of the tobacco-free living strategies cost less than $1.20 per person and reached over 6 million people each. Four of the healthy eating strategies cost less than $1.00 per person, and one of them reached over 6.5 million people. One of the active living strategies cost $2.20 per person and reached over 7 million people. Three of the clinical and community preventive services strategies cost less than $2.30 per person, and one of them reached almost 2 million people. Across all 20 strategies combined, an increase of 10,000 people in the number of people reached was associated with a $0.22 reduction in the per-person cost. Results demonstrate that interventions, such as tobacco-free indoor policies, which have been shown to improve health outcomes have relatively low per-person costs and are able to reach a large number of people.

Projected Costs of Informal Caregiving for Cardiovascular Disease: 2015 to 2035: A Policy Statement From the American Heart Association.

INTRODUCTION: In a recent report, the American Heart Association estimated that medical costs and productivity losses of cardiovascular disease (CVD) are expected to grow from $555 billion in 2015 to $1.1 trillion in 2035. Although the burden is significant, the estimate does not include the costs of family, informal, or unpaid caregiving provided to patients with CVD. In this analysis, we estimated projections of costs of informal caregiving attributable to CVD for 2015 to 2035. METHODS: We used data from the 2014 Health and Retirement Survey to estimate hours of informal caregiving for individuals with CVD by age/sex/race using a zero-inflated binomial model and controlling for sociodemographic factors and health conditions. Costs of informal caregiving were estimated separately for hypertension, coronary heart disease, heart failure, stroke, and other heart disease. We analyzed data from a nationally representative sample of 16 731 noninstitutionalized adults ≥54 years of age. The value of caregiving hours was monetized by the use of home health aide workers' wages. The per-person costs were multiplied by census population counts to estimate nation-level costs and to be consistent with other American Heart Association analyses of burden of CVD, and the costs were projected from 2015 through 2035, assuming that within each age/sex/racial group, CVD prevalence and caregiving hours remain constant. RESULTS: The costs of informal caregiving for patients with CVD were estimated to be $61 billion in 2015 and are projected to increase to $128 billion in 2035. Costs of informal caregiving of patients with stroke constitute more than half of the total costs of CVD informal caregiving ($31 billion in 2015 and $66 billion in 2035). By age, costs are the highest among those 65 to 79 years of age in 2015 but are expected to be surpassed by costs among those ≥80 years of age by 2035. Costs of informal caregiving for patients with CVD represent an additional 11% of medical and productivity costs attributable to CVD. CONCLUSIONS: The burden of informal caregiving for patients with CVD is significant; accounting for these costs increases total CVD costs to $616 billion in 2015 and $1.2 trillion in 2035. These estimates have important research and policy implications, and they may be used to guide policy development to reduce the burden of CVD on patients and their caregivers.

Intervention Costs From Communities Putting Prevention to Work.

INTRODUCTION: In 2010, the Centers for Disease Control and Prevention funded 50 communities to participate in the Communities Putting Prevention to Work (CPPW) program. CPPW supported community-based approaches to prevent or delay chronic disease and promote wellness by reducing tobacco use and obesity. We collected the direct costs of CPPW for the 44 communities funded through the American Recovery and Reinvestment Act (ARRA) and analyzed costs per person reached for all CPPW interventions and by intervention category. METHODS: From 2011 through 2013, we collected quarterly data on costs from the 44 CPPW ARRA-funded communities. We estimated CPPW program costs as spending on labor; consultants; materials, travel, and services; overhead activities; and partners plus the value of in-kind donations. We estimated communities' costs per person reached for each intervention implemented and compared cost allocations across communities that focused on reducing tobacco use, or obesity, or both. Analyses were conducted in 2014; costs are reported in 2012 dollars. RESULTS: The largest share of CPPW total costs of $363 million supported interventions in communities that focused on obesity ($228 million). Average costs per person reached were less than $5 for 84% of tobacco-related interventions, 88% of nutrition interventions, and 89% of physical activity interventions. Costs per person reached were highest for social support and services interventions, almost $3 for tobacco­use interventions and $1 for obesity prevention interventions. CONCLUSIONS: CPPW cost estimates are useful for comparing intervention cost per person reached with health outcomes and for addressing how community health intervention costs vary by type of intervention and by community size.

Productivity Costs Associated With Breast Cancer Among Survivors Aged 18-44 Years.

INTRODUCTION: No study has quantified productivity losses associated with breast cancer in younger women aged 18-44 years. This study estimated productivity costs, including work and home productivity losses, among younger women who reported ever receiving a breast cancer diagnosis. METHODS: A two-part regression model and 2000-2010 National Health Interview Survey data were used to estimate the number of work and home productivity days missed because of breast cancer, adjusted for socioeconomic characteristics and comorbidities. Estimates for younger women were compared with those for women aged 45-64 years. Data were analyzed in 2013-2014. RESULTS: Per capita, younger women with breast cancer had annual losses of $2,293 (95% CI=$1,069, $3,518) from missed work and $442 (95% CI=$161, $723) from missed home productivity. Total annual breast cancer-associated productivity costs for younger women were $344 million (95% CI=$154 million, $535 million). Older women with breast cancer had lower per capita work loss productivity costs of $1,407 (95% CI=$899, $1,915) but higher total work loss productivity costs estimated at $1,072 million (95% CI=$685 million, $1,460 million) than younger women. CONCLUSIONS: Younger women with a history of breast cancer face a disproportionate share of work and home productivity losses. Although older women have lower per capita costs, total productivity costs were higher for older women because the number of older women with breast cancer is higher. The results underscore the importance of continued efforts by the public health community to promote and support the unique needs of younger breast cancer survivors.

Costs of Chronic Diseases at the State Level: The Chronic Disease Cost Calculator.

INTRODUCTION: Many studies have estimated national chronic disease costs, but state-level estimates are limited. The Centers for Disease Control and Prevention developed the Chronic Disease Cost Calculator (CDCC), which estimates state-level costs for arthritis, asthma, cancer, congestive heart failure, coronary heart disease, hypertension, stroke, other heart diseases, depression, and diabetes. METHODS: Using publicly available and restricted secondary data from multiple national data sets from 2004 through 2008, disease-attributable annual per-person medical and absenteeism costs were estimated. Total state medical and absenteeism costs were derived by multiplying per person costs from regressions by the number of people in the state treated for each disease. Medical costs were estimated for all payers and separately for Medicaid, Medicare, and private insurers. Projected medical costs for all payers (2010 through 2020) were calculated using medical costs and projected state population counts. RESULTS: Median state-specific medical costs ranged from $410 million (asthma) to $1.8 billion (diabetes); median absenteeism costs ranged from $5 million (congestive heart failure) to $217 million (arthritis). CONCLUSION: CDCC provides methodologically rigorous chronic disease cost estimates. These estimates highlight possible areas of cost savings achievable through targeted prevention efforts or research into new interventions and treatments.

Helping the Noncompliant Child: An Assessment of Program Costs and Cost-Effectiveness.

Disruptive behavior disorders (DBD) in children can lead to delinquency in adolescence and antisocial behavior in adulthood. Several evidence-based behavioral parent training (BPT) programs have been created to treat early onset DBD. This paper focuses on one such program, Helping the Noncompliant Child (HNC), and provides detailed cost estimates from a recently completed pilot study for the HNC program. The study also assesses the average cost-effectiveness of the HNC program by combining program cost estimates with data on improvements in child participants' disruptive behavior. The cost and effectiveness estimates are based on implementation of HNC with low-income families. Investigators developed a Microsoft Excel-based costing instrument to collect data from therapists on their time spent delivering the HNC program. The instrument was designed using an activity-based costing approach, where each therapist reported program time by family, by date, and for each skill that the family was working to master. Combining labor and non-labor costs, it is estimated that delivering the HNC program costs an average of $501 per family from a payer perspective. It also costs an average of $13 to improve the Eyberg Child Behavior Inventory intensity score by 1 point for children whose families participated in the HNC pilot program. The cost of delivering the HNC program appears to compare favorably with the costs of similar BPT programs. These cost estimates are the first to be collected systematically and prospectively for HNC. Program managers may use these estimates to plan for the resources needed to fully implement HNC.

Collecting costs of community prevention programs: communities putting prevention to work initiative.

BACKGROUND: Community-based programs require substantial investments of resources; however, evaluations of these programs usually lack analyses of program costs. Costs of community-based programs reported in previous literature are limited and have been estimated retrospectively. PURPOSE: To describe a prospective cost data collection approach developed for the Communities Putting Prevention to Work (CPPW) program capturing costs for community-based tobacco use and obesity prevention strategies. METHODS: A web-based cost data collection instrument was developed using an activity-based costing approach. Respondents reported quarterly expenditures on labor; consultants; materials, travel, and services; overhead; partner efforts; and in-kind contributions. Costs were allocated across CPPW objectives and strategies organized around five categories: media, access, point of decision/promotion, price, and social support and services. The instrument was developed in 2010, quarterly data collections took place in 2011-2013, and preliminary analysis was conducted in 2013. RESULTS: Preliminary descriptive statistics are presented for the cost data collected from 51 respondents. More than 50% of program costs were for partner organizations, and over 20% of costs were for labor hours. Tobacco communities devoted the majority of their efforts to media strategies. Obesity communities spent more than half of their resources on access strategies. CONCLUSIONS: Collecting accurate cost information on health promotion and disease prevention programs presents many challenges. The approach presented in this paper is one of the first efforts successfully collecting these types of data and can be replicated for collecting costs from other programs.

Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in the United States and is responsible for 17% of national health expenditures. As the population ages, these costs are expected to increase substantially. METHODS AND RESULTS: To prepare for future cardiovascular care needs, the American Heart Association developed methodology to project future costs of care for hypertension, coronary heart disease, heart failure, stroke, and all other CVD from 2010 to 2030. This methodology avoided double counting of costs for patients with multiple cardiovascular conditions. By 2030, 40.5% of the US population is projected to have some form of CVD. Between 2010 and 2030, real (2008$) total direct medical costs of CVD are projected to triple, from $273 billion to $818 billion. Real indirect costs (due to lost productivity) for all CVD are estimated to increase from $172 billion in 2010 to $276 billion in 2030, an increase of 61%. CONCLUSIONS: These findings indicate CVD prevalence and costs are projected to increase substantially. Effective prevention strategies are needed if we are to limit the growing burden of CVD.

A captive audience: bringing the WISEWOMAN program to South Dakota prisoners.

PURPOSE: This analysis compares the baseline heart disease risk profile of WISEWOMAN participants screened in the South Dakota Women's Prison with the general WISEWOMAN population in South Dakota and explores the potential benefits of lifestyle intervention programs to reduce heart disease risk factors among women during incarceration. METHODS: Using baseline data for WISEWOMAN participants in South Dakota, we compared participants who were enrolled in prison (n = 261) with nonincarcerated participants enrolled throughout the state (n = 1,427). Using regression analysis and adjusting for demographics, we assessed differences in baseline prevalence of risk factors (hypertension, high cholesterol, smoking, and obesity), awareness and treatment of hypertension and high cholesterol, and attendance at lifestyle intervention sessions. RESULTS: Incarcerated participants had significantly lower (p < .01) total cholesterol (183 mg/dL) than nonincarcerated participants (199 mg/dL). However, a significantly higher (p < .03) percentage of incarcerated women (85%) than nonincarcerated women (54%) with high cholesterol were unaware of their condition. Despite the smoke-free status of the prison, 24% of incarcerated participants reported smoking. Attendance at lifestyle intervention sessions was significantly higher among incarcerated participants than among nonincarcerated participants with intervention take-up rates of 53% among incarcerated versus 23% among nonincarcerated women (p < .01) and intervention completion rates of 43% and 4% (p < .01). CONCLUSIONS: The results illustrate the need for screening and education programs in prisons. WISEWOMAN screenings helped identify undiagnosed cases of abnormal blood pressure and cholesterol, and educational interventions provided women with opportunities to improve their health. Such programs may also improve discharge planning and linkages between released women and community health providers.

The impact of medication use in a multicomponent intervention: results from the WISEWOMAN program.

PURPOSE: To assess the impact of medication use on improvements in coronary heart disease (CHD) risk among WISEWOMAN participants. DESIGN: Pre-post analysis. SETTING: WISEWOMAN projects operating at the local level in 8 states. SUBJECTS: WISEWOMAN participants with baseline and one-year follow-up data with at least one abnormal risk factor at baseline (N=2385; 24% of women with baseline visits). INTERVENTION: WISEWOMAN provides low-income uninsured women with CHD risk factor screenings, lifestyle interventions, access to medications, and referral services. MEASURES: One-year changes in blood pressure, cholesterol, and 10-year CHD risk by medication status. ANALYSIS: Regression analysis was used to estimate risk factor changes by medication status (newly medicated women, women medicated at baseline, or not medicated women) and quantify the percentage of improvements in risk factors attributed to medication use. RESULTS: Participants experienced statistically significant improvements in systolic (12.6 mm Hg) and diastolic (9.7 mm Hg) blood pressure, total (25.7 mg/dl) and HDL (4.9 mg/dl) cholesterol, and 10-year CHD risk (11.6%). Medication use was responsible for 4% to 5% of the reduction in blood pressure, 32% of the reduction in total cholesterol, 3% of the increase in HDL cholesterol, and 31 % of the reduction in 10-year CHD risk. CONCLUSIONS: Some of the improvements in CHD risk factors can be attributed to medication use; however, the majority of improvements are likely driven by a combination of other factors, including screenings, risk factor counseling, and lifestyle interventions.

Racial/ethnic disparities in coronary heart disease risk factors among WISEWOMAN enrollees.

BACKGROUND: We used the baseline data collected for the Well-integrated Screening and Evaluation for Women Across the Nation (WISEWOMAN) participants to provide a snapshot of cardiovascular disease (CVD) risk on enrollment and to address racial/ethnic disparities in the following CVD risk factors: body mass index (BMI), systolic and diastolic blood pressure, high-density lipoprotein (HDL) and total cholesterol, diabetes and smoking prevalence, 10-year coronary heart disease (CHD) risk, and treatment and awareness of high cholesterol, hypertension, and diabetes. METHODS: We used linear regression analysis to (1) assess the presence of racial/ethnic disparities and test whether existing disparities can be explained by (2) differences in individual characteristics or by (3) differences in individual and community characteristics. RESULTS: Our results reveal a high degree of CVD risk among the WISEWOMAN participants and statistically significant racial/ethnic disparities in risk factors. Black participants were at the greatest risk of CVD, and Hispanic and Alaska Native participants were healthier in terms of CVD risk than white participants. Some racial/ethnic disparities were explained by differences in individual and community characteristics, but other disparities persisted even after controlling for these factors. CONCLUSIONS: Because differences in community characteristics explain many of the racial/ethnic disparities in CVD risk factors, eliminating disparities may require community-wide interventions. Successful WISEWOMAN projects are likely to not only reduce CVD risk factors overall but also to lessen racial/ethnic disparities in these risk factors.

Spatial analysis of body mass index and smoking behavior among WISEWOMAN participants.

BACKGROUND: The WISEWOMAN program focuses on reducing cardiovascular disease (CVD) risk factors by providing screening and lifestyle interventions for many low-income and uninsured women. To provide the most effective interventions possible, it is important to understand the characteristics of WISEWOMAN participants and their communities. METHODS: We used baseline data collected for WISEWOMAN participants from five states (Connecticut, Michigan, Nebraska, North Carolina, and South Dakota) who had enrolled in WISEWOMAN between January 2001 and December 2002 in order to examine body mass index (BMI) and smoking behavior for evidence of spatial clustering. We then examined whether neighborhood characteristics in clusters of high-risk factors differed from neighborhood characteristics in other locations. RESULTS: Six percent of the WISEWOMAN participants lived in ZIP codes with high-BMI clusters, and 4% lived in ZIP codes with high-smoking clusters. High-BMI and high-smoking clusters occurred, however, in different locations from each other. The high-BMI-clustered ZIP codes were, on average, located in more disadvantaged areas. Most of the differences between the high-smoking-clustered ZIP codes and the remaining ZIP codes were not statistically significant. CONCLUSIONS: Our analysis revealed spatial clustering in CVD risk factors among WISE-WOMAN participants. We also found evidence of a correlation between high-BMI clusters and low socioeconomic status of the surrounding community. A more in-depth analysis of the relationship between risk factors (e.g., BMI) and community characteristics in clustered locations will provide further information concerning the role of the community in affecting individual behavior and should allow for tailoring interventions to reduce these risk factors more effectively.