Duration: 10/01/2008 to 09/30/2014

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

Statement of Issues and Justification

National & Regional Priorities This project focuses on the dynamic interactions among individual, family, community, and policy contexts on the physical and mental health outcomes for rural low-income families and extends the previous research conducted within the multistate projects NC223 and NC1011. In order to understand the health of rural families we must examine the relationships and interactions among policy, communities, and families and how these processes change over time. This is consistent with the USDA North Central region priority "Social Change and Development" as well as other national priorities calling for research that emphasizes understanding these interactions within the rural context. USDA has a long history of recognizing the distinct needs of rural people and places; including "Rural Development" as a significant area within the National Research Initiative (NRI) Competitive Grants Program. NRI priorities also include health issues such as the need to stem the rise in obesity by understanding the individual and environmental influences on this national problem. Other federal agencies are now following suit by prioritizing rural issues. In addition to the Federal Office of Rural Health Policy, the U.S. Department of Health and Human Services (HHS, 2002) identified the importance of addressing the needs of Rural America. In a July 2002 report of the Rural Task Force, "strengthening rural families" was listed as one of its five primary goals (HHS, 2002). One facet of family life that contributes to strong families and sustainable communities is health. Thus, more work is needed to understand how changing demographics and federal and state policies relating to health, public assistance and agriculture affect family health across time. Issues of Importance Good mental and physical health is important for quality of life. However, research shows that all residents of the United States do not experience good health. In particular, the incidence, prevalence, morbidity, and mortality rates for disease in rural populations are significantly higher than those in the general population (Gamm et al, 2003; Meit, 2004). A report by the National Center on Health Statistics (2001) demonstrates these disparities. Compared to their urban counterparts, rural adults are more likely to report physical inactivity, obesity, limitations in daily activity, and tooth loss. Death rates and causes of death are also disparate. Rural areas have higher infant, child, and adolescent mortality rates than urban areas. Rural adults also are more likely to die from cardiovascular disease, motor vehicle accidents, and suicide (NCHS, 2001). The previous multistate projects (NC223 and NC1011) focused on general family well-being, which included some health indicators. Health, however, was not the primary focus and therefore a limited amount of health related information was collected, constraining the nature and depth of possible health-related conclusions. Despite this, research findings to date clearly indicate that health is a crucial element of rural family well-being that requires further exploration. For example, Simmons, Huddleston-Casas, and Berry (2007) found that rural low-income postpartum women were unlikely to recognize their depression. Another study found that health insurance status and having a regular doctor enabled rural low-income women to access a physician when needed (Simmons, Anderson, & Braun, 2008). These data suggest that more detailed health information will provide further insight into the challenges facing rural low-income families. In addition, because NC223/1011 designated family location according to rural-urban continuum codes (Butler & Beale, 1994), the projects were uniquely positioned to capture the nuances of individual, family, community, and policy influences on rural health. Few national data sets make this distinction, in favor of broad categories such as metropolitan and non-metropolitan or urban, suburban, and rural. However, these broad categories do not allow for a more in-depth understanding of how local variations in geographic regions affect family health and well-being. The current project will continue to use a precise measure of rurality (see methods) in order to draw on the previous data as well as collect additional data to help explain the physical and mental health of diverse rural low-income families. Rural communities and families have unique issues and needs compared to their urban counterparts. Poverty rates are consistently higher in rural areas (ERS, 2007), and persistent, long-term poverty is much more common for rural families than urban families (Deavers & Hoppe, 1992; Imig, Bokemeier, Keefe, Struthers, & Imig, 1997; ERS, 2007). In addition, rural families experience less access to services (e.g., health care, child care, social services) and a less stable economic base (HHS, 2002). Further, rural communities are changing demographically with their populations becoming more diverse. For example, immigration from abroad accounted for one-quarter of the nonmetro population growth during 2003-2004 (ERS, 2005). But race and ethnicity is just one of many characteristics of the diversity of families living in rural communities. Other examples include race, age, disability, and family structure. Taken together, it is evident that examination of the rural context, as well as the diversity of families within the rural context, will provide a more complete understanding of the health of low-income rural families. Currently, we have very limited information on the interactions of individual, family, community, and policy contexts and the resulting impacts on physical and mental health. Understanding the interactions occurring across contexts is most clearly delineated from an ecological systems perspective (Bronfenbrenner, 1979). The ecological framework organizes the contexts within which families function into a discrete series of nested systems encompassing societal norms and values, institutional structures, interactions between families and other systems, and the family system itself. Collectively referred to as the ecosystem, these systems are interdependent; they exhibit mutual influence. Most research on families focuses on only one system level and does not look at the interactions among the levels, but research generated from NC223/1011 has demonstrated that multiple contexts influence individual and family well-being. This project will examine all of the system levels to determine impacts on the physical and mental health outcomes of individuals living in rural low-income families. Health Outcomes We intend to examine a number of health outcomes for both adults and children. Drawing on and then adding to the NC223/1011 dataset, we will examine: (a) duration and severity of chronic health conditions of adult(s) and children (e.g., obesity, diabetes, asthma, arthritis, and cardiovascular disease); (b) health effects on daily living (e.g., lost days of work and school, perceptions of impact); (c) mental health status for both adults and children (e.g., general mental health, depression, anxiety, behavior problems, and substance use/abuse); and (d) access to care (e.g., source of health care, perceptions of available care in the community, descriptions of primary, specialty, and emergency services utilization). Family & Individual Context Family and individual level characteristics (e.g., ethnicity, age, disability) and practices have a major impact on the mental and physical health of family members. At the most basic level, heredity is an important characteristic in disease transmission. Individuals with a family history of cardiovascular disease (Patel et al., 2007), certain cancers (Martin et al, 2007; Rijn, 2007; Willems, 2007), and diabetes (Eisenbarth, 2007) are at higher risk for developing the disease themselves. Additionally, health practices in families, such as dietary choices, exercise habits, and health care utilization are all influenced by experiences within the family of origin. Community Context There are important community factors that affect health care access and subsequent health as well. One factor is the limited physician supply (Schur & Franco, 1999). Rural Americans constitute 20% of the U.S. population, but only 9% of physicians practice in rural counties (Ricketts, 1999). Specialty physicians are also lacking (Rosenblatt & Hart, 1999). New and more advanced medical technologies spread slowly in rural areas, so the communities' health needs go unmet (Ricketts, 1999). In addition, rural public health systems are insufficient. Data show that rural public health personnel are more likely to work part-time and less likely to have formal public health training (Rosenblatt, Casey, & Richardson, 2002). Rural mental health care systems demonstrate similar challenges. There are few qualified professionals and limited service outreach (Spoth, 1997; Wagenfeld, Murray, Mohatt, & DeBruyn, 1994). There also has been very little programmatic research on preventive mental health interventions (Spoth, 1997). Consequently, rural mental health systems are modeled after urban systems with little attention to the unique needs of rural residents (Arons, 2000). These infrastructure issues are compounded by the social stigma associated with having and receiving treatment for a mental illness (Arons, 2000). Beyond community factors affecting health care access, opportunities for healthy living also contribute to individual and family health outcomes. We intend to examine opportunities within communities for active play and recreation for children and adults. Recent research has linked nature and green space to improved outdoor play and recreational opportunities and participation in organized sports, yet these areas need additional research attention. Policy Context The mental and physical health of individuals and families has been addressed both directly and indirectly through policy efforts directed at the health of low income individuals and families (e.g., Medicaid, State Child Health Insurance Programs, childhood vaccination). Additionally, policies intended to contribute to family well-being, thus influencing mental and physical health, will be included (e.g., Temporary Assistance to Needy Families, Food Stamps, childcare assistance, housing assistance, Earned Income Tax Credit). States with unique policy efforts will be encouraged to examine those policies as well. For example, a policy impacting nutritional standards of food in school vending machines may be a state-specific effort. In addition, beyond policies enacted at the federal and state level, effects of the administration of the programs provided by these policies occurring at the county and community level will be assessed. For example, each state sets its own criteria for children's eligibility for free or reduced health care. Interactions among Contexts This project will examine the interactions among contexts in order to gain a better understanding of the health outcomes of diverse rural families. Examples of research questions that capture interactions between contexts include: If a community lacks sufficient family physicians, when and how do they decide to use emergency room services? Is there an interplay between housing accommodations (location, manufactured housing as a part of location), ownership, and access to health care? What is the relationship of neighborhood type and quality (i.e., mobile home versus subsidized housing) to children's outdoor activities? Have there been outreach programs in the community to address nutrition, physical activity, and obesity and how have families responded to these programs? To what extent does acculturation act as a barrier to healthier food and lifestyle choices? Technical Feasibility A major challenge for this project is to investigate the interactions between systems. Therefore, to successfully complete this study, we must use a research approach that is consistent with our ecological theoretical perspective (O'Brien, 2005); that is, a multidisciplinary approach that emphasizes process, outcomes, and context. Testing trends and predictors of physical and mental health requires that we accurately measure the health outcomes and the individual, family, community, and policy influences. Accurate quantitative measures are available to measure some variables (e.g., physical and mental health, regional unemployment, family income), but in order to achieve a contextualized in-depth picture of each family we also need rich qualitative data about each family. Qualitative techniques for interviewing and developing case descriptions (Creswell, 2008; Yin, 2003) can provide these details. By combining the complementary perspectives of the quantitative and qualitative datasets, a mixed methods approach permits a more complete understanding of the interactions between context and health outcomes (Creswell & Plano Clark, 2007; Greene & Caracelli, 1997; Tashakkori & Teddlie, 2003). Many important contextual and health variables are known and will be measured in order to test relationships. However, our design also needs to be consistent with understanding the contexts of health outcomes. We recognize that some important variables may be currently unknown and that each family's context is unique; we cannot know in advance which variables are more salient, especially for minority families. The data collection, therefore, will include a rigorous qualitative component to capture individual families' perspective and context in order to develop a more complete systemic picture of the interactions and influences on health outcomes over time. The research team has a history of using their complementary strengths to develop research questions, design, and conduct quantitative and qualitative analyses to produce a more holistic study. To date, the research team has spanned distance and time by using such technologies as sharing of data files using a File Transfer Protocol (FTP) site, a website, audio-conference calls and annual on-site meetings, and Macromedia Breeze as a dissemination system. The current team members are uniquely positioned to build upon the current infrastructure and begin a new multistate project. Advantages of a Multistate Effort A multistate approach to studying the health of diverse rural low-income families has many advantages and each state offers a unique setting. The study of many states representing different geographic regions allows for a comparison of contextual factors such as access to health care, seasonally available food, emphasis and opportunities for recreation, tobacco use, and economic well-being. The study of several states provides a deeper understanding of how these factors act and interact to influence outcomes. Each state is also characterized by a different population profile. Race/ethnicity, immigration status, age of population, and acculturation are all important to health outcomes. Comparison of these diverse populations from several states will enhance our understanding of how these factors influence health in rural low-income families. A multistate approach will also provide a valuable opportunity to study the effect of policy on families' health. Policy varies both between and within states; this variation is essential to the study of interactions between policy and other contexts for health. No one state can capture the diversity of a national sample; a multistate approach provides a cost-effective alternative to a national rural sample by capturing variation in factors that influence the health of rural families. Additionally, the use of a common protocol for both the quantitative and qualitative components allows the development of a rich multistate dataset. Expected Impacts This project will be uniquely positioned to increase understanding around health in rural America. This study will add to the body of knowledge regarding the well-being of rural communities and diverse rural low-income families. A better understanding of rural family health can lead to better quality of life and therefore sustainable rural communities. Families who are not healthy are not able to contribute to their communities, socially or economically. The study will provide data for customizing programs and public policy to meet the needs of rural America. It also will expand the capacity of the land-grant system to educate and train graduate student researchers; enrich the curricula of courses in sociology, economics, family studies, nutrition and health; inform the programming that Cooperative Extension offers to families and communities across each state; and extend expertise of the system to citizens in support of the prosperity of rural America. This project can have both regional and national impacts because there are multiple layers of data collection (i.e., community, regional and national level).

Related, Current and Previous Work

This project is informed by and grew out of the collective experience and knowledge gained from the multistate projects NC223/1011 "Rural Families Speak" that studied the general well-being of rural low-income families. We will discuss our previous work and other related literature under broad topic areas of health, economic well-being, food security, family, community, and policy. Based on our theoretical perspective, ecological systems, we will examine constructs within these topical areas at each of the system levels. Health Analyses from NC223/1011 revealed that both mental and physical health status as well as access to health care services are key factors associated with rural families' well-being. Poor mental health was a key issue, with 53% of mothers having clinically significant depressive symptoms (Simmons, Huddleston-Casas, Berry, 2007). Women with clinically depressive symptoms were less likely to access a physician when needed (Carlton & Simmons, under review). Additionally, health status and employment status were linked. Unemployed mothers were more likely to have clinically depressive symptoms (Simmons & Braun, 2005) and for longer periods of time (Dolan et al., 2005b). Similarly, women working more than one job were significantly more likely to have more depressive symptoms and report alcohol use (Maring & Braun, 2007). Depression and economic well-being were linked over time, creating a recursive cycle between poverty and low socioeconomic status (Simmons et al., 2008). Physical health influenced rural mothers' ability to maintain employment; unemployed women had more chronic health conditions than employed women (Simmons & Braun, 2005). Health insurance was a key factor for participants in NC223/1011. Having health insurance was a key enabling factor for accessing health services, but only 67% of participants had any type of health insurance (Bauer, 2004). Women with health insurance went to the doctor more often (Simmons, Anderson, & Braun, 2008), and were less likely to delay or forgo filling prescriptions (Carlton & Simmons, under review). Although 74% of mothers at Wave 1 had public dental insurance, few rural providers accepted this type of insurance; thus, only 55% reported receiving dental care in the previous year (Simmons & Braun, 2005). Although health outcomes were not the primary focus of the NC223/1011 projects, the results to date indicate that mental and physical health issues play a crucial role in the well-being of rural low-income families. This research needs to be extended with focused measurement of mental and physical health outcomes for adults and children. The current project will collect measures of adult and child health that allow us to develop a holistic picture of the health status of these families and the individual, family, community, and policy interactions affecting health status. Economic well being Labor force participation is essential for rural families in achieving and maintaining economic self-sufficiency. Rural mothers face barriers to securing and maintaining employment. Their own health, health of other family members, support networks, transportation and child care all converge to enable or hinder labor force participation. Much of the published work from the NC223/1011 projects examined the human capital resources of this rural low-income sample. Labor force participation and barriers to work, ability to make ends meet, use of social supports, use of the Earned Income Tax Credit, and knowledge of community resources were all factors that affected economic well-being. Specifically, social support was a key predictor of human capital and subsequent economic well being (Simmons et al., 2007) and home ownership contributed to economic well-being (Berry, 2003). Although social support was a key factor for family resiliency, borrowing money from family and friends decreased economic well-being by increasing economic strain (Bird, 2006). Barriers to continuous participation in the labor force were health of the individual and family members and good jobs (Berry et al., in press), and availability of affordable child care (Katras, Zuiker, & Bauer, 2004), transportation, and housing (Berry, 2003). Perception of economic well-being was important to the well-being of rural mothers. Marghi (2004) found that positive impressions of economic well-being and income adequacy were associated with lower levels of depressive symptoms. Similarly, a decline in economic situation and the perception of inadequate income was associated with variability in depressive symptomology (Piescher, 2004). Wasberg (2007) noted the number of medical conditions was negatively related to having adequate income and positively related to problems making ends meet. Food security Findings from NC223/1011 indicate that low food security is stable over time; low food secure families at Wave 1 remained low food secure over 3 years later (Olson et al., 2006). Low food security is linked to poverty (Nord et al., 2007) and living in a food desert  places where few or no food resources are available (Lang & Rayner, 2002). In some food deserts, community institutions and social support systems mediate potential low food security and poor diets. These communities have leaders and organizations engaged in solving community problems. Such civic structure provides capacity for increasing food supplies, food security, healthy diets, and the overall population health (Morton et al., 2002). Low food security is also linked to family ability to meet housing needs (Greder & Allen, 2007) and social support networks (Anderson & Swanson, 2002; Greder & Allen, 2007; Greder & Brotherson, 2002). Recent studies regarding food security have also led to conflicting evidence regarding the links between low food security and childhood overweight (Garasky et al., 2007) and adult obesity (Bove & Olson, 2006). Some studies suggest that parental physical activity patterns (Omelas et al., 2007), behaviors, and attitudes may mediate this connection (Strauss & Knight, 1999). Data needs to be collected to better understand these links among rural low-income families, especially ethnically diverse families in remote rural areas. Data consistently reveals a higher rate of low and very low food security among African Americans, Latinos, and Native Americans as compared to Whites (Nord, 2007). Young children of color in low-income, low food secure households are at greater developmental risk than their counterparts living in low-income but food-secure households (Joint Center for Political and Economic Studies, 2006), further indicating the need to attend to diversity within the rural community context. Family Rural families extract much of their resilience from their social support systems. Strong social support networks protect rural women against stress, symptoms of depression, and food insecurity (Swanson et al., in process; Seiling et al., 2006; Seiling et al., 2005). Social support systems facilitate educational achievement, employment, and access to leisure and recreation by providing information about jobs and assisting with other formal and informal resources (Seiling, 2006, 2005, 2004; Seiling, Bauer & Dyk, 2001). Family or neighbors provide child care especially when access to formal care in the community is limited (Reschke & Walker, 2003; Reschke et al., 2006; Seo, Stafford, & Seiling, 2005), and rural mothers gain access to housing and transportation through their support systems (Dolan et al., 2005a; Katras et al., under review). However, the emotional and instrumental support provided by family and friends is not without costs of increased family tensions, demands on time, and sharing of limited resources. Parenting stressors and behaviors influence child physical and mental health (Parke, 2004). Parental support is positively related to children's activity levels (Gustafson & Rhodes, 2006). Intergenerational transfer of psychosocial risk factors (i.e., depression and aggression) is mediated by parenting factors, as well as contextual factors such as family poverty and early and single parenthood (Serbin & Karp, 2004). NC223/1011 identified resiliency factors but specific parenting and child outcome interactions were not addressed. The current project will include measures of family characteristics influencing positive child mental and physical health. Community Although limited work has been done relating community data to health outcomes, two studies have investigated these links. Simmons, Anderson, and Braun (2008) found women living in counties with high primary care physician rates were less likely to use emergency departments. Carlton and Simmons (under review) found women who believed primary care physicians were available in their communities were less likely to report not going to a physician when needed. Examination in NC223/1011 of family involvement in recreational activities demonstrated that these rural families spend much of their leisure time outdoors (Churchill, 2005, 2007). Other research has demonstrated that exposure to nature (green spaces) may lead to decreases in attention deficit disorder symptoms (Taylor, Kuo, & Sullivan, 2001) and increases in cognitive functioning among children (Wells, 2000). To build upon this research, the current project will assess the "naturalness" of the family's living space (see Wells, 2000) as well as family involvement in outdoor green spaces and the number of parks within the county. Policy The work of the NC223/1011 team suggests that local and state rural development policy efforts need to strengthen the community resources upon which rural families draw. Katras et al. (under review) found that poor health (her own, her partner's and/or her children's) was the most common problem affecting employment among mothers who remained dependent upon TANF benefits. The role of health has yet to be factored into public policy regarding receipt of TANF benefits. Working families facing health issues may benefit from access to Food Stamps, transitional Medicaid, and child care assistance to supplement earnings (Simmons, Dolan, & Braun, 2007). Increasing access to health insurance and to a regular physician may improve health status and consequently, decrease health care costs (Simmons, Anderson, & Braun, 2008). The need for improved mental health services in rural communities is highlighted by the high prevalence of both depression and poverty and the association between the two (Simmons, Anderson, & Braun, 2008). The issues of access to physicians and mental health professionals also exist for access to dental care. Distances to service sites, lack of dentists who accept their dental health plan, and costs associated with dental care were identified as barriers to good dental health (Anderson et al., 2007). Policies and programs that support access to low-cost reliable vehicles, fuel subsidies, or other transportation options would help to alleviate some access issues. The current project will investigate the relationship among access to ancillary benefit programs and the physical and mental health of rural low income families. Review of CRIS and Other Multistate Projects A review of CRIS using the keywords, rural, women, family, and health identified 85 unique projects, excluding those based on NC223/1011. The majority of these projects focus on a single population (e.g., Mexican-American, rural immigrant Latinas) or a single health variable (e.g., drug addiction, obesity). A few projects incorporate a more ecological perspective including multiple variables and system levels: "Understanding family relationships among women in the context of race and culture" (Goodwin); "Risk and resiliency in youth, families, and communities and positive development promotional strategies and interventions" (Perkins); "Rural communities and quality of life" (Cumber) ; Community perceptions of social and ecological change: A cross-national comparison (Hammer); Enhancing human security: Child support, family savings, and health care access and quality (Arends-Kuenning, et al); Community conditions and individual and family well-being (McLaughlin & Snyder). None of these projects, however, incorporated the multistate aspect that is being proposed. Four active multistate projects were identified which examine similar topics or populations (NC1100, NC1013, W1167, W1001). None of these projects encompass the scope of topics or populations proposed here. For example, NC1100 is limited to the North Central region and NC1013 is focused strictly on savings behavior. W1167 targets specific groups of women and media images for these women, not their overall mental and physical health. W1001 uses extant data from the Census 2000 and other sources to examine population change. The proposed project will use an ecological perspective to identify multiple influences on mental and physical health in diverse rural low-income women. The inclusion of diverse families (e.g., ethnicity, age, family form, disability) from across the United States makes this project more representative of the entire US rural population allowing greater impact. Need for additional research The analyses of the NC223/1011 project thus far have begun to illuminate the issues facing rural low income families. The dataset has provided a broad brush stroke for painting the picture of the issues and barriers rural mothers face in obtaining well-being. Health has emerged as having particular importance for families and has been found to relate to other systemic factors including employment and economic status, health insurance status, and access to health services providers. Rural families face barriers to being healthy that could be personal, familial, community-based or policy-driven. Having a better understanding of the confluence of these factors will enhance the ability to create policy and programs to promote healthy rural low-income families. More information is needed to identify the systemic levels of influence on health status and decision-making about health. For example, what prevents women from seeking the care they need? How do women with and without health insurance navigate health systems? What is the influence of SCHIP on the heath of rural children? How do competing health needs within a family get prioritized? How do long term health issues, or chaotic health, of family members influence family economic well-being? Finally, we have no information on how state health policies affect decision-making and health status for rural families. The proposed project will look at diverse rural low-income families with the aim of identifying the elements that lead to positive physical and mental health. This new project will build on the strengths and key constructs and measures identified and used in the NC223/1011 dataset, and enhance our understanding of these topics by including additional measures in the areas of adult and child health and contexts expected to influence health.

Objectives

1. Overall research objective: To determine the interactions of individual, family, community, and policy contexts on physical and mental health outcomes in diverse rural low-income families.
   
2. To examine individual and family level characteristics which impact physical and mental health in diverse rural low-income families.
   
3. To examine community contexts that impact family mental and physical health in diverse rural low-income families.
   
4. To examine policies that impact family mental and physical health in diverse rural low-income families.
   
5. To examine the interactions of individual, family, community, and policy on mental and physical health in diverse rural low-income families.
   

Methods

Procedures for Objective 1 Our overall project objective requires that we quantitatively measure predictors and outcomes and also qualitatively understand processes and contexts. We want to develop a complete picture of the impacts of and contextual interactions among individuals, families, communities and policies for physical and mental health in diverse rural low-income families. Therefore, this project will utilize a mixed methods approach. Mixed methods research involves the collection, analysis, and integration of quantitative and qualitative data to provide a better understanding of a phenomenon than could be achieved with either approach alone (Creswell & Plano Clark, 2007). Specifically, we will use a triangulation mixed methods design to collect complementary quantitative and qualitative data. The specific procedures are discussed under Objectives 2-4. The investigation started by NC223/1011 will serve as a springboard for this new project. NC223/1011 data will continue to be analyzed to identify additional questions that need to be addressed in the proposed project. The community data set will be expanded and analyses that expand our understanding of the community context will be a priority (see Objective 3 below). Procedures for Objective 2 Quantitative Procedures Many definitions of "rural" can inform this project and each definition has implications for policy (Coburn, 2007). The NC223/1011 projects studied families in counties with Rural-Urban Continuum Code (Beale Codes, RUCC) values of 6, 7, or 8. Codes 6 and 7 indicate non-metropolitan counties with an urban population of 2,500 to 19,000, while a code of 8 indicates no town of more than 2,500 people in the county. These codes provide a minimum level of rurality for this project. In addition, rurality in terms of access to larger economies is important due to its relationship with the accessibility of services available to families. This project will utilize the Urban Influence Codes (UIC) to identify all counties in participating states that have a value of 4-10 (nonmetropolitan counties not adjacent to a large metropolitan area). Each state will select 2 counties based on accessibility, diversity, and community considerations that meet this definition (UIC = 4-10 and RUCC = 6-9). By using both criteria, this study will maintain continuity with the NC223/1011 dataset while further delineating the extent of the families' rurality. Using these dual criteria, the majority of counties included in the previous projects can continue to be included in the proposed project. Participating families must live within the selected rural communities. We will target adult female primary caregivers of at least one child between the ages of 5-12 years and who have an income for the previous year that is 200% or less of the federal poverty line. These criteria will identify rural low-income families that can be compared with the NC223/1011 datasets. The state-by-state sampling technique of the previous project has posed some problems as the criteria differed across states and thus the bias differed. During the final planning stages of Year 1, the research team will finalize the sampling plan to meet the needs of the states, but also to ensure the collection of a generalizable sample. We anticipate using a stratified sampling plan where each state uses a common procedure for randomly identifying potential participant families using location of households. The team recognizes the difficulty and expense of random sampling and will seek external funding to facilitate this process. States will be encouraged to select communities with ethnically diverse families and to specifically target diverse families. We expect to over sample non-majority rural families as in the previous projects to allow analyses that examine questions of diversity. Each state will document response rates and gather brief demographic information of those who elect not to participate so that comparisons between responders and non-responders can be assessed and any response bias identified. Using the common sampling plan, each state will recruit 30 participants from two communities for a total of 60 participants per state. This will result in a manageable amount of data and allow for statistical comparisons within states and an overall database of at least 600 individual families (assuming at least 10 participating states). Acknowledging that experience is shaped at least partly by individual's racial/ethnicity backgrounds, the team will recruit to produce a final sample consisting of 40-60% minority (e.g., African American, Native American, Latino, or Asian) participants. To facilitate comparison to NC223/1011 data, participant zip codes and county FIPS codes will be identified and entered into the dataset. States may choose to revisit families interviewed for NC223/1011 and these participants will be designated within the dataset. It is assumed that the total number of these participants will be too small for extensive quantitative analysis, but may be used for exploratory analyses. Each participating primary caregiver will provide informed consent and complete a structured survey interview with a member of the research team. Interviews will be conducted at locations agreed upon by the participant and researcher. Although increasing the cost of data collection, the interviews will be conducted face-to-face (instead of by mail or telephone). Prior experiences suggest that members of these rural communities will not respond well to mailed surveys. In order to maintain consistency of data collection efforts, training sessions will be held at the annual conference meetings and via webcasts as needed. Each research team will acquire a laptop computer to be used for collecting the survey data. This will allow the data to be entered at the time of data collection, therefore saving data entry expenses and reducing errors associated with transferring data from paper to computer database. All measures and instruments will be converted to an electronic format (led by the central data management location at the University of Nebraska) and loaded onto the laptop. This will allow participants to click and record their responses on the computer. The researcher will read and record responses for any individuals who are not comfortable with the computer or with reading the items and responses for themselves. The survey will include measures and items addressing the main project constructs. When possible, previously developed and standardized measures will be used that have been shown to have adequate validity and reliability. The adult primary caregiver will be the one to respond to the survey, and she will answer questions related to herself, the target child (one child age 5-12, randomly selected if more than one child in the household meets this criteria), and the family overall. The constructs, key measures, and sample research questions are listed in Table 1. It is expected that each interview will take approximately 1-2 hours to complete and participants will receive a small compensation for their time. This project design will be sensitive to potential ethical issues. Necessary approvals from all participating Institutional Review Boards will be secured within each state. All participants will be fully informed as to the purpose of the research, what they will be asked to do, and their right to refuse participation or to withdraw at any time. Confidentiality of the participants will be an utmost priority in terms of how participants are recruited, how data is collected, and how data is stored and reported. Computers with participant data will be transported and stored in locked carriers, and the files will be password-protected. To understand the influence and interactions of contexts in the lives of participating families, we need to collect data at multiple points in time. Therefore, we will implement two waves of survey data collection during the 5 years (and develop a proposal to request funding for additional waves after Year 5). The first wave of quantitative data collection will occur during Year 2 and we will return to the same families for a second wave in Year 4 (see timeline in Table 2). Our decision to return to the families in Year 4 is based on the following reasons: (a) more than one point is necessary to examine influences of some variables; (b) one major event can make a difference in the families' lives and these data will allow us to measure changes that have occurred; (c) two years between waves will allow sufficient time for analysis and manuscript development from wave 1 data; and (d) researchers will be available to collect and analyze qualitative data (described below) in Year 3 to support the quantitative datasets. Although attrition will be a concern, we believe we can track families using the demonstrated strategies from NC223/1011. These strategies allowed us to maintain as many as 90% of families in some states. For example, we will collect at least three contact numbers and addresses for the families, including those of relatives and friends as appropriate. Families will receive follow-up mailings between data waves to continue tracking address changes and remind families of our intention to follow-up with them in Year 4. We will send semiannual newsletters about the project and what we have learned from their participation. NC223/1011 had an attrition rate of 23% across two waves and we expect to be able to obtain similar results. The research team will develop a codebook for the quantitative data. State research teams will export their data from the survey software and import directly into an SPSS database. All data will be shared through one central data management location housed by the University of Nebraska (see section on organizational governance), similar to the data hosting conducted by the University of Minnesota for NC223/1011. Complete data sets with identifying information removed will be available to project members through a password protected ftp site. The quantitative analyses will be guided by our objectives and quantitative research questions. Initial hypothesis testing will be performed using simple tests to examine the relationship of individual and family-level characteristics with health outcomes. The availability of two time points means we will also examine how initial individual and family characteristics are associated with changes in health over time. Appropriate analyses (such as repeated measures, hierarchical linear modeling [HLM] for nested data, and path models) will be conducted considering individual and family-level characteristics at Wave 2 in addition to Wave 1. Qualitative Procedures While much can be learned using standard measures, we recognize they cannot convey a full picture of the systemic interactions related to these diverse rural families. Each family has its own unique qualities, perceptions, and experiences, and we need to understand these aspects in addition to the quantitative results. Therefore, each state will engage in multiple case study research during Year 3. A case study is an in-depth study of a system bounded by place and time (Creswell, 2007). A multiple case study is best suited to learn about individual cases as well as common themes and patterns that emerge across multiple cases (Yin, 2003). For the purposes of this study, we consider the individual families (primary caregiver and children) as cases bounded by a community) and 24 months. We will explore the complexity and context of the cases guided by the following research questions related to the families' physical and mental health: What happens to the family during this time? How does the family perceive their physical and mental health? What individual, family, community and policy contexts are influencing the family? A small number of families will be selected as a subset of the quantitative dataset to allow for in-depth qualitative investigations. Each state will conduct case studies with 8 families (4 from each of 2 communities during a 12-month time between the quantitative data collection waves. The selection of the families for the qualitative component of this study will be guided by maximum variation sampling (Patton, 2002) to capture a diverse set of experiences and perceptions. Parameters for the selection criteria will be established for all states in Year 2, but generally families will be selected based on variation in health status, ethnicity, gender of child, and utilization of community or national resources. We will inform all participants at the time of initial recruitment that they may be invited to participate in additional interviews. Once individuals are identified as potential participants for the qualitative component, they will be contacted and informed consent information will be discussed. Each research team will acquire a digital tape recorder to be used for collecting the qualitative interview data. Consistent with case study research (Creswell, 2008), we will collect multiple sources of data for each participating case. The primary data source will be 3 in-depth semi-structured interviews with the primary care giver (using a common interview protocol in all states) to cover a range of topics (see Table 1) and to follow-up on previous conversations and initial quantitative results. Data will be digitally recorded and backed up on the research team's laptop. In order to maintain consistency of data collection and analysis efforts, training sessions will be held at the annual conference meetings and via webcasts as needed. Each state will transcribe the qualitative data verbatim and enter it into a MAXqda 2007 database by case. Information that could potentially identify participants will be replaced with pseudonyms. Each state also will conduct a preliminary qualitative analysis of each case. Descriptive coding will be used to produce a case description for each family. In addition, the states will establish a list of topics related to the project objectives and each research team will complete topic coding (Richards & Morse, 2007) of the case study data. The trustworthiness and credibility of the data will be ensured by the use of multiple data sources, relying on rich description and quotes, and actively examining the data for disconfirming evidence (Creswell & Miller, 2000). The qualitative databases will also be assembled into one secure project database managed at a central location to facilitate cross-state analyses. Procedures for Objective 3: The research teams will collect quantitative data on the community contexts of the participating families. Key community-level variables are outlined in Table 1. In addition to collecting these variables from each family, this project will utilize and add to the community database created as part of NC1011. This supplemental SPSS dataset will allow us to examine the relationships of different community contexts to individual mental and physical health outcomes. The research teams also will collect qualitative data about the communities as part of their case studies to describe the community contexts for each family. To ensure consistency across states, the team will identify a short list of key community providers (e.g., community public health officer) and develop a standard protocol that will be used to collect qualitative community-based data for each community during Year 3. These secondary sources of data will help to provide further context about the communities. Procedures for Objective 4: The research teams will collect quantitative data for each family about policy-related variables as indicated in Table 1. These variables will be included in the SPSS dataset will allow us to examine the relationships of different policy contexts to individual mental and physical health. The qualitative case studies will also include the examination of relevant policy contexts for each family. This will include descriptions of their perceptions of and experiences with policies such as TANF, SCHIP, etc. In addition, our understanding of the implications of policy in the lives of these families will be augmented with supplemental data collected from community members integral in providing policy-based services to the families (as described above). Procedures for Objective 5: The richness of the data and the complexity of the objectives necessitates that different analytical methods be employed for both the quantitative and qualitative datasets. An understanding of the interactions among system levels will emerge by examining the implications of each system for each family and then looking across the families in both the quantitative and qualitative datasets. While much will be learned individually from the separate quantitative and qualitative datasets, a strength of this project is that the interactions of the different system levels on mental and physical health can also be examined by integrating the two datasets. Where feasible, the SPSS database and qualitative databases will be linked. In particular, the quantitative variables for the case study families can be imported into MAXqda and used to query the data (e.g., Do families on TANF discuss access to health care differently than those who are not on TANF?). Also, quantitative code frequencies can be produced by MAXqda and imported into the SPSS data set for the 80-120 case study families permitting quantitative analyses based on the qualitative data (e.g., Is there a significant relationship between the types of support discussed and the primary caregiver's depression level?). While many possibilities exist for integrating these two datasets for specific research questions, the overall strategy will be to triangulate the results of the two datasets to develop a more complete and accurate picture of the interactions among different system levels on mental and physical health of diverse rural low-income families. By having two complementary datasets based around the same issues and constructs, we will be able to bring the two sets of results together for comparison (do the findings agree?) and to develop a better understanding (how do the qualitative findings illustrate the quantitative results?). In addition, due to overlap among some variables and, to a lesser extent, some participants between the new dataset and NC223/1011, some analyses across the two projects will be possible.

Measurement of Progress and Results

Outputs

• Quantitative multistate data set containing predictor and outcome variables for approximately 600 families over two waves of data collection
• Qualitative multistate data set containing approximately 80 transcribed interviews from primary caregivers and community stakeholders
• Quantitative multistate data set containing community variables for each community participating in the study
• Qualitative multistate data set containing transcribed interviews with community professionals
• Qualitative and quantitative dataset linking NC223/1011 data with new project data
• Refereed journal articles and conference presentations (approximately 6 from each working group for a total of 30 publications and presentations)
• Training of masters' and doctoral students, approximately 15 students
• Development of training materials for community leaders to use to enhance the lives of diverse rural low-income families
• Presentation of webcasts to inform county-based extension educators and other local community professionals of the research findings and implications for practice
• Policy and information briefs focused on the findings of the project

Outcomes or Projected Impacts

• Improved understanding of the experiences of diverse rural low income families in relation to all aspects of the research project
• Improved policy for strengthening the mental and physical health and economic well-being of diverse rural low-income families based upon their unique community needs
• New and strengthened relationships with state and county organizations to improve physical and mental health and economic well-being of diverse rural low-income families
• Development of master's and doctoral trained researchers in multi-method data collection and analysis focused on rural low-income families
• Better informed county-based extension educators and their community partners regarding rural low-income families' physical and mental health and economic well-being
• Locally developed curricula by county-based extension educators and their community partners to inform other professionals about rural low-income families' physical and mental health needs and strengths of diverse rural low-income families, and strategies to help them meet their needs
• Improved understanding of the interrelationships among community structure, family mental and physical health outcomes and economic well-being
• This project will be uniquely positioned to increase understanding regarding mental and physical health and economics in rural America and the role that community plays in the overall well-being of rural, low-income residents. A better understanding of what promotes and inhibits rural family health can lead to improved quality of life for rural families, thus strengthening the vitality and sustainability of rural communities. Unhealthy families are not able to fully socially and economically contribute to their communities. These outcomes and impacts correspond to USDA Strategic Plan 2005-2010 Goals number 3 and 5: "Support Increased Economic Opportunities and Improved Quality of Life in Rural America" and "Improve the Nation's Nutrition and Health" and USDA North Central region priority "Social Change and Development." This project will assist in improving quality of life in rural America by demonstrating those factors which successfully contribute to positive mental and physical health and economic well-being within a family's ecological context.

Milestones

(0): Table 2

Projected Participation

View Appendix E: Participation

Outreach Plan

Team members will organize themselves into topical working groups (see organization and governance), an effective strategy employed by the NC223/1011 research team. The goal of each working group will be dissemination of findings appropriate to their respective professional communities. The extension and the public policy working groups will be specifically responsible for outreach to practitioners and policy makers. Potential outreach products are: refereed publications, national and international conference presentations, policy and information briefs, web-based materials, and electronic conferences. All of these products have been produced by the NC223/1011 team and the continuing team members, therefore, have extensive experience with these types of products and dissemination methods. In addition, a website will be maintained to post research findings and links to publications on a regular basis. The website and policy briefs will allow the project to be disseminated quickly to those interested in the findings. Team members are committed to working with graduate and undergraduate students to complete theses, dissertations, presentations, and referred publications, and, in general, training researchers who understand rural low income families and communities, and complex research projects. Several of the researchers involved in the current project began as graduate students on NC223 or NC1011. This tradition of involving students is a key component of the outreach plan.

Organization/Governance

The organization of the multistate project will be in accordance with the Guidelines for Multistate Research Activities. The initial organization of the team will be led by the core group of states writing the project (NE, KY, IA, NC, HI, TN). This core group will organize the first annual meeting of the potential participants (see Appendix E) at which elections will be held for the executive committee. The executive committee will consist of a chair, vice-chair for data, vice-chair for outreach, and a secretary. In addition, there will be a vice-chair for funding. This latter position will be responsible for connecting and managing team resources to secure external funding. Each executive committee member will serve a 2-year term and the members' terms will be staggered in order to maintain continuity of leadership. As stated above, working groups will be formed around topics of interest (e.g., child health outcomes, family physical health, family mental health, economic security) in addition to the extension and policy working groups. The latter two working groups will report to the vice-chair for outreach on a regular basis in order to maximize the project's impact. The executive committee will maintain contact with the Administrative Advisor and CSREES representative consistently for the project. For data collection and management purposes, each state will be responsible for purchasing a laptop(s), MAXqda software, and a digital recorder. Each state will be responsible for cleaning the quantitative data and transcribing and verifying the qualitative data. As in NC223/1011, this data will then be sent to a central location (University of Nebraska) where the multistate data set will be compiled and managed. This process of local verification and then central management will ensure a valid and reliable data set accessible to all participants. Another successful technique from NC223/1011 that will be continued with this project is the maintenance of a secure FTP site from which data can be accessed by the individual researchers. The working groups and individual states can also use this site to store and share documents. Working groups will also maintain contact via regular teleconference calls.

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Attachments

Land Grant Participating States/Institutions

CA, HI, IA, IL, KY, LA, MA, MD, MN, NC, NE, NH, NJ, OH, OR, TN, TX, WA, WY

Non Land Grant Participating States/Institutions

Ohio University, Pennsylvania - Pennsylvania State, Stephen F. Austin State University