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February 2008
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Research in BriefDetermining the Needs of American Indian Audiences for Cooperative Extension Programs
Staci Emm
Don Breazeale IntroductionAmerican Indians have been in North America for centuries. The Western United States is famous for the Indians that lived in the Great Basin, which includes Nevada, Oregon, Idaho, and Eastern California. American settlers moving west began appearing in the Great Basin between 1820 and 1860. In the beginning, strangers in the area were not a problem, but as time passed, American settlers began to increase in numbers. The Great Basin American Indians, in the 19th Century, were displaced and moved from their territories due to the increase of American settlers. The United States government managed this problem with the creation of American Indian reservations (Intertribal Council of Nevada, 1976). From the beginning, the services to the American Indian people have been difficult and limited to housing, education, health care, food, and other social services. There has been a general lack of dialogue with American Indian Tribes or tribal people (Hiller, 2005). It was in the late 1980's that a non-profit organization, Intertribal Agriculture Council, lobbied for United States legislation to create Cooperative Extension programs on American Indian reservations through U.S. Cooperative State Research Education Extension Service (CSREES). Thus, the Federally Recognized Tribes Extension Program (FRTEP) was created. The program recently expanded with additional monies appropriated by Congress for the FRTEP program. There are 314 federally recognized tribes spread among 33 states in the continental United States (Sterner, 2007). Nevada currently has one FRTEP program, "Nevada Indian Tribes," to provide Cooperative Extension services to four out of the 18 federally recognized American Indian tribes in Nevada. Nevada American Indian Tribal lands make up 22% of the land in farms base in Nevada (Owens, 2003). University of Nevada Cooperative Extension (UNCE) has become more involved in addressing American Indian issues due to its involvement in FRTEP. Because of the lack of involvement with American Indian Tribes, UNCE is currently trying to determine Extension programming needs on Nevada reservations. All good Cooperative Extension programs identify issues through a formal community assessment process. Program planning and action is more effective with accurate and up-to-date information about client needs and preferences (Butler & Howell, 1980). One example in Nevada involves a community needs assessment for the Walker River Paiute Tribe on the Walker River American Indian reservation in west-central Nevada. In order to provide programming, Extension agents need to be knowledgeable of tribal leaders and tribal governance (Hart, 2006). Literature ReviewThe legislation and regulation of American Indian Affairs by the United States government has shifted over many years and generations to reflect a unique situation of understanding and "Trust" responsibility regulation. American Indian affairs, better known as "Indian Affairs," began with writing treaties, establishing Indian reservations, and giving sovereignty by allowing Tribes to be a separate nation within the nation of the United States. Today, legislation and "Indian Affairs" is centuries old and is filled with complex and multifaceted issues. Cooperative Extension programs in the United States and American Indians do not nationally have strong relationships. The FRTEP places Extension agents/educators and Extension programs on reservations. Unfortunately, the FRTEP has only enough funding for 28 American Indian projects on 27 out of the 314 Federally Recognized Tribal reservations in the United States. In addition, Cooperative Extension is finding that the traditional Extension model of servicing this disadvantaged population is not as effective on reservation lands as in other settings (Hiller, 2005). Just as in other countries, Cooperative Extension models need to be adjusted to meet American Indian social, cultural, and economic conditions of the intended program recipients (Seevers, 1997). Programs that are participatory, engage community members, provide local community capacity building, and empower clientele are necessary for effective Cooperative Extension programming (Minkler & Wallerstein, 2003). MethodologyIn August of 2005, the Walker River Paiute Tribe passed Resolution WR-88-2005 approving the University of Nevada Cooperative Extension to conduct a needs assessment by surveying all households on the reservation and compiling and reporting the results. The survey instrument was designed as an "opinion poll" of community expectations, concerns, and risk factors in order to enhance Cooperative Extension programming efforts. To establish content and face validity, a panel of experts reviewed the instrument. A pilot test was run to establish reliability resulting in Chronbach's alpha coefficients ranging from.81 to .98. The survey was completed in 2005 on the Walker River Indian Reservation. The survey was conducted from November 9, 2005 to December 30, 2005 through door-to-door and face-to-face contact. Contact was only possible with 168 households out of the 350 households that were estimated by the Tribe's housing department. Contact was limited primarily by the inability to find residents in the household. The surveying team divided the reservation into three sections using area-frame maps. Potential respondents of a household were asked if they would like to participate by filling out the survey instrument. A total of 107 households participated in the study, and 61 households declined to participate in the study. This represented a 31% response rate from reservation households. Community DemographicsThere were 82% of the 107 respondents that were between 21 and 60 years of age. Fifty-six percent of respondents were female, and 40% were male, with 4% not responding. Approximately 85% of respondents consider themselves American Indian. Figure 1 shows the ethnic breakdown of respondents.
Figure 1. Figure 2 provides information on the number of years respondents lived on the reservation. Almost two-thirds of respondents reported that their family had lived on the reservation for generations, while only 3% reported that their family had lived on the reservation less than one year. Figure 3 gives a breakdown of yearly household income. Sixty-four percent had an income of $35,999 or less, with 28% reporting $10,999 or less, which is below the national poverty level.
Figure 2.
Figure 3. There were 20% of respondents that had undergraduate or a graduate degree. Thirty-two percent graduated from high school, with 36% attending some college. Six percent graduated from 8th grade, and 7% did not answer the question. There were 58% that reported having one child or no children, 25% reported two or three children, 10% reported four or five children in the household. Seven percent did not answer. Community Risk FactorsMeetings with tribal staff and tribal departments identified 17 possible community risk factors for the needs assessment survey instrument. Survey respondents were asked to rate each of the 17 possible risk factors (1 = major problem, 2 = problem, 3 = small problem, 4 = no problem, and 5 = no response). Scarce resources limit Cooperative Extension's ability to work with American Indian audiences (Hiller, 2005). Therefore, only those issues reported as the most important (problem and major problem) were reported in the study described here. Eighty-four percent of respondents identified unemployment as the number one community risk factor. Approximately two-thirds of respondents also reported alcohol abuse, drug abuse, preparing youth for work, reservations laws, and lack of recreation for children as important issues. Figure 4 provides a visual breakdown of these risk factors.
Figure 4. Community ConcernsThere were 11 possible community concerns identified through meetings with tribal staff and departments for the survey instrument. Survey respondents were asked to rate each of the possible community concerns (1 = major problem, 2 = problem, 3 = small problem, 4 = no problem, and 5 = no response). As in the risk factor section, problems and major problems were combined. The number one community concern was the availability of illegal drugs. Other community concerns identified were community disorganization, family conflict, lack of commitment to school, community laws/enforcement, early initiation of problem behavior, and academic failure beginning in elementary school. Figure 5 shows a breakdown of the top seven community concerns that were identified.
Figure 5. Summary of FindingsApproximately 85% of respondents in the study identified themselves as being American Indian. Two-thirds of the respondents have lived on the reservation for generations. It is a relatively low-income population, with just under two-thirds of the respondents reporting less than $35,999 a year in income and 28% reporting under $10,999 a year of income. This is a relatively well educated group, with 88% of people having completed high school or a higher level of education. In fact, 20% have bachelor degrees or higher. The identified risk factors cited by the respondents in order of importance include unemployment, alcohol and drug abuse, inadequate preparation of youth for the work world, inadequate laws to protect residents, and lack of recreation for children. The number one community concern identified by participants was the availability of illegal drugs, followed by community disorganization. Other concerns included family conflict, lack of commitment to school, community law enforcement, early initiation of problem behavior, and academic failure in elementary school. Implications and RecommendationsThe participants in this group indicated that they have a good level of education. However, due to the rural isolation, limited employment opportunities, and availability of drugs and alcohol, residents tend to turn toward substance abuse. This in turn affects youth attitudes about their future opportunities. Thus, economic development may play a very important role in improving reservation quality of life on the reservation. Improving the quality of life on the reservation is directly tied to understanding and eliminating or reducing the community risk factors and concerns cited by residents. Through economic development and increased employment opportunities, tribal residents have the opportunity and incentive to change their substance abuse habits and lifestyle. This in turn can provide more positive role models for reservation youth. Given this situation, Cooperative Extension programming can play a vital role in improving quality of life on the reservation. Through a needs assessment and community situation analysis, Cooperative Extension programs can gain vital demographic information and allow residents a formal process for identifying their community concerns and risk factors. The involvement of the American Indian population in the study will result in more effective Cooperative Extension programs by giving participants greater input and ownership into program planning and implementation. Additional research is needed concerning tribal leaders, tribal governance, and styles and practices in order to collaboratively develop programming to meet the identified needs of the Walker River American Indian population. The needs assessment process utilized in the study reported here should provide important information to other Cooperative Extension personnel working with American Indian reservations as well as with other indigenous populations throughout the world. Because this study was specific to West-Central Nevada, little is known about how this framework might apply to different ethnic and cultural situations. This remains an important opportunity for further study if underrepresented audiences are going to be provided with equal access to Cooperative Extension programming efforts. Regardless of where the American Indian and other indigenous populations are located, focused research and educational programming to strengthen community development efforts can help shape and provide road maps for Extension programming in other comparable communities. ReferencesButler, L. M., & Howell, R. E. (1980). Coping with growth: Community needs assessment techniques, WREP44. Corvallis, OR: Western Rural Development Center. Hart, J. G. (2006). Exploring tribal leadership: Understanding and working with tribal people. Journal of Extension. [On-line], 44(4) Article 4FEA3. Available at: http://www.joe.org/joe/2006august/a3.shtml Hiller, J. (2005). Is 10% good enough? Cooperative Extension work in Indian country. Journal of Extension. [On-line], 43(6) Article 6FEA2. Available at: http://www.joe.org/joe/2005december/a2.shtml Intertribal Council of Nevada. (1976). NUMA: A northern Paiute history. Reno, Nevada: Inter-Tribal Council of Nevada. Minkler, M., & Wallerstein, N. (Eds.) (2003). Community-based participatory research for health. San Francisco, CA: Jossey-Bass. Owens, M. (2003). Nevada agriculture statistics. Reno, Nevada: USDA Nevada Agriculture Statistics Service. Seevers, B., Graham, D., Gamon, J., & Conklin, N. (1997). Education through Cooperative Extension. Albany, New York: Delmar Publishers. Sterner, R. (2007) Colored landform atlas of the United States: Indian tribes listed by state. John Hopkins University Applied Physic Laboratory Oceanography Group. Retrieved July 26, 2007 from: http://www.hanksville.org/sand/contacts/tribal
Public Perceptions on the Ideal Balance between Natural Resource Protection and Use in the Western USA
Robert L. Mahler
Bahman Shafii
Steven Hollenhorst
Barbara J. Andersen
University of Idaho IntroductionTraditionally, people in the Western USA, more than in any other region, have depended on natural resource exploitation and use for their livelihood. Industries including agriculture, forestry, and mining have been vital to the economies of most Western states (Nie, 1999). These industries still comprise more than 40% of the economies of the less populated, more rural Western states, including Alaska, Idaho, Wyoming, Montana, North Dakota, and South Dakota. The 15 Western states have experienced rapid population growth over the past 15 years. The 26% increase in population has greatly changed traditional demographics and resulted in economies less dependent on natural resource exploitation. Surveys from the Pacific Northwest and Rocky Mountain states have shown that residents greatly value natural resource use (Mahler, Simmons, & Sorensen, 2005; Mahler, Simmons, Sorensen, & Miner, 2004; Clay, Ren, Reese, Waskom, Bauder, Mesner, Paige, Reddy, Neibauer, & Mahler, 2007). At the same time, numerous studies have documented increasing interest in resource protection. It is therefore important to understand how the public values both natural resource exploitation/use and natural resource protection (Kunagy, Humphrey, & Firebaugh, 1994; Inglehart, 1977, 1990; Milbrath, 1989). Actions to protect the environment work best when political leaders and educators know their constituents' preferences for environmental quality and resource allocation. In this context, public opinion surveys are a potentially valuable source of information on people's perceptions of environmental quality, their awareness of the causes and severity of environmental problems, and preferred solutions to these problems. While many surveys have been conducted at the national level and in many states, little information has been collected about the environmental perceptions and attitudes of Western state residents. This type of Western survey is particularly important for Extension professionals who are developing programs in water resources, forestry management, and sustainable systems (Nie, 1999; Dunlap, 1993; Hays, 1991). This article evaluates and reports information on how people in the 15 Western states believe natural resource exploitation and natural resource preservation should be balanced. Materials and MethodsData for the analysis provided here were derived from surveys designed in 2002 to assess public attitudes about water issues in the states of the Pacific Northwest, in 2003 for the Pacific Southwest, and in 2004 for the Rocky Mountains. A separate survey was conducted in 2005 in New Mexico. This article deals with the following question that was common to all surveys: Q-Place an X on the line below to show how you see the relative importance of natural resource use and natural resource protection:
The target sample size for each state is shown in Table 1. Surveys were sent to residents of each of the 15 Western states on a proportional population basis. Residents of each state were randomly selected from phonebooks and switchboard.com or by purchasing random addresses from a company specializing in survey sampling. The mail survey process resulted in a completed survey return rate in excess of 50% (Dillman, 2000; Salant & Dillman, 1994).
Survey answers to the resource use/protection question were coded and entered into Microsoft Excel. The continuum line was split into nine equal segments receiving values of 1 (starting on the left side of the continuum) all the way up to 9 (right end):
If a person placed an X at the equal balance spot on the continuum a 5 was recorded. Missing data were assigned the number 0 on the coding system and were excluded from analysis. The continuum data were analyzed using a one-way classification analysis of variance. Classification variables included were the demographic variables from the survey, namely gender, age, education, community size, and state. Each demographic variable was analyzed separately. Within each analysis, single degree of freedom contrasts were used to test hypotheses of interest. All statistical computations were carried out using SAS (2004). Because this survey originated in Idaho many of the state specific comparisons were designed to compare Idaho responses to the other Western states. Results and DiscussionThe average balance values discussed in this section are based on how survey respondents saw their own views on natural resource use and protection compared to their perceptions of the views of the average American. The average value of 5.59 was significantly different (P=0.0001) from the theoretical midpoint of 5.0 on the continuum, indicating a slight preference for protection compared to natural resource use. The demographic factors of gender, age, education level, community size, and state of residence significantly influenced how respondents viewed the ideal balance between natural resource exploitation/use and natural resource protection. GenderFemales considered environmental protection more important than males (5.69 vs. 5.49; Table 2). This finding is consistent with past state, national, and international studies (Zelezny, Chua, & Aldrich, 2000; P=0.0006). Even though the numerical difference between males and females (5.49 vs. 5.69) was small, the large data set (n=3,972) resulted in a statistical difference. It should be noted that both genders believed in a balance between natural resource use and natural resource protection.
AgeAge had a significant impact on how respondents in the Western USA view the appropriate balance between natural resource use and natural resource protection (Table 3). In general, younger respondents had higher balance values--viewing natural resource protection as being more important than natural resource use. However, all age groups had balance values between 5.2 and 5.8.
Three specific contrasts were evaluated for age. Three of the contrasts resulted in significant differences (Table 3). Respondents less than 30 years old were more likely to see natural resource protection as more important than did people over 70 years old (5.68 vs. 5.20; P=0.0001). Respondents less than 50 considered natural resource protection more important than did people older than 50 (P=0.0001). In addition, respondents less than 70 considered natural resource protection to be more important than natural resource use, compared to people older than 70 (P=0.0001). An important observation about the age demographic data is that younger respondents are more likely to consider natural resource protection more important than natural resource use. This age demographic difference may be attributed to a general rise of environmentalism in American culture that pervades our media, education system, and businesses. Previous studies have shown that age has been a key differentiating variable since the 1980s, as younger survey respondents are generally more supportive of environmental issues than other age groups (Mohai & Twight, 1987). Formal EducationHighest level of formal education completed had a significant effect on how respondents viewed the appropriate balance between natural resource use and natural resource protection in the Western USA (Table 4). In general, increasing levels of formal education resulted in respondents being more likely to favor natural resource protection compared to natural resource use. This finding is also consistent with past national surveys (Kunagy, Humphrey, & Firebaugh, 1994; Inglehart, 1977, 1990; Milbrath, 1989; Mohai & Twight, 1987).
Three specific education level contrasts were statistically evaluated. College graduates were more likely than high school graduates to favor natural resource protection over natural resource use (5.67 vs. 5.05; P=0.0001). Respondents who graduated from college were more likely to favor natural resource protection than respondents who had attended some college, but not graduated (5.67 vs. 5.45; P=0.0024). Likewise, respondents with advanced college degrees supported natural resource protection more than natural resource use compared to respondents with four-year college degrees (6.00 vs. 5.67; P=0.0001). The result that people in the Western USA appeared to be more likely to favor natural resource protection with increasing levels of formal education can be explained in two ways. First, people with increased levels of formal education have more exposure to environmental and natural resource issues and thus have a greater appreciation for the protection and conservation of soil, water, air, mineral, and biological resources. Second, people with higher levels of formal education are more likely to have higher incomes and jobs not associated with natural resource extraction. Consequently, natural resource exploitation does not affect their personal income as much as it does people with less education working in extractive industries. Community SizeCommunity size had a significant impact on how respondents in the Western USA view the appropriate balance between natural resource use and natural resource protection (Table 5). In general, respondents from larger communities had higher balance values, viewing natural resource protection as more important than natural resource use. However, residents from all community size groups had balance values between 5.1 and 5.8. This range of values can be interpreted as citizens in all community groups slightly favoring protection over use; however, urban residents were more inclined than rural residents to support protection.
Four community size contrasts evaluated resulted in significant differences due to community size (Table 5). Respondents from communities with more than 100,000 people had significantly higher values than communities with less than 3,500 residents (5.76 vs. 5.17; P=0.0001). Respondents from communities with more than 100,000 also had higher index values than residents in communities with between 25,000 and 100,000 residents (5.76 vs. 5.49; P=0.0031). Significant differences were also observed in smaller communities, as residents of towns between 3,500 and 25,000 had higher index values than residents of communities with less than 3,500 people (5.40 vs. 5.17; P=0.0357). Value differences as a result of community size in the Western USA can be explained based on occupation. Residents of smaller communities are more likely to rely on natural resource extraction for their livelihoods when compared to larger cities. Many smaller Western communities depend on agriculture, forestry, tourism, fishing, and/or mining--all occupations that depend on natural resource exploitation (Switzer, 1997). State of ResidenceState of residence had a significant effect on how respondents viewed the appropriate balance between natural resource use and natural resource protection in the Western USA (Table 6). In general, the states with the highest populations (also the most urban) in the Western USA resulted in respondents being more likely to favor natural resource protection over natural resource use.
Before specific state contrasts are presented, it should be noted that average state balance values ranged from 5.05 to 5.97 in the Western USA. Even though this range is narrow, considering the initial evaluation scale for respondents ranged from 1 to 9, it should be noted that the range in average state balance values was wider than the average balance value ranges for the gender, age, education, and community size demographics. The two general categories of contrasts chosen for evaluation were: (1) comparisons to Idaho's value scores, and (2) comparisons between sub-regions within the Western USA. In the first set of contrasts, Idaho responses were compared to balance values of neighboring states. Idaho's balance value (5.05) was statistically similar to Utah (5.22; P=0.3610), Wyoming (5.07; P=0.9403), and Alaska (5.36, P=0.1535). Conversely, Idaho's balance value was statistically lower than Montana's balance value (5.81; P=0.0004). Idaho's balance value was also statistically lower than the pooled balance value of Washington + Oregon (5.68; P=0.0001). When compared to the other 14 states (pooled) in the Western USA, Idaho's balance value was statistically lower (5.05 vs. 5.59; P=0.0017). Based on the above six contrasts, Idaho resident views about natural resource utilization are similar to residents of Utah, Wyoming, and Alaska. There are obvious similarities among Idaho, Wyoming, and Alaska because the state economies have a significant reliance on natural resource use. Residents of Idaho and Utah share similar politics and ethics. Conversely, Idaho has a lower balance value than do larger and more urban states in the Western USA.
In the second set of comparisons between groups of states composing sub-regions in the Western USA, results are not as clear-cut as the Idaho comparisons. California residents had a similar index value to the combined scores of Oregon + Washington (5.73 vs. 5.68; P=0.4869). Western states were grouped into the following three regions, which were roughly equivalent to the administrative regions of the United States Environmental Protection Agency: Region 8 (CO, MT, ND, NM, SD, UT, WY), Region 9 (AZ, CA, HI, NV), and Region 10 (AK, ID, OR, WA). The Pacific Northwest and the Pacific Southwest had similar balance values. Similarities, rather than differences, were found between the Rocky Mountain states (Region 8) and the Pacific Southwest (Region 9) (P=0.2944). Conversely, people in Region 10 had higher balance values compared to residents of Region 8 (P=0.007). ConclusionAll demographic factors affected how respondents balanced natural resource use/exploitation and natural resource protection. Females considered environmental protection to be more important than did males (5.69 vs. 5.49). Respondents less than 60 years of age considered natural resource protection more important than did people over 60. The more formal education received by a respondent resulted in a greater importance being placed on natural resource protection. In addition, respondents from larger communities tended to consider natural resource protection more important compared to people from smaller communities. State of residence also affected the perceived balance between natural resource use and protection. Data collected in the study reported here are important for three major reasons. First, the data can be used to measure future changes in attitudes from residents in the Western USA. Second, the data helps to dispel traditional beliefs that most people in rural areas of the Western USA have cornucopian perceptions of natural resources. In fact, the vast majority of Westerners surveyed believe in a practical balance between natural resource use and natural resource protection. Third, the data can be used as a starting point to develop educational programs for Western USA residents about natural resource issues and associated policies. ReferencesClay, D. E., Ren, C., Reese, C., Waskom, R., Bauder, J., Mesner, N., Paige, G., Reddy, K., Neibauer, M., & Mahler, R. L., (2007). Linking public attitudes with perceptions of factors impacting water quality and attending learning activities. Journal of Natural Resources and Life Sciences Education 36:36-44. Dillman, D. (2000). Mail and Internet surveys: The tailored design method. John Wiley and Sons, Inc. New York, New York. Dunlap, R. E. (1993). Public opinion: Does public concern for the environment differ in the West? Environmental politics and policy in the West, ed Z. A. Smith. pp 63-85, Dubuque, IA. Kendall Hunt. Hays, S. P. (1991). The new environmental west. Journal of Policy History 3:223-248. Inglehart, R. (1977). The silent revolution: Changing values and political styles among western publics. Princeton: Princeton University Press. Inglehart, R. (1990). Culture shift in advanced industrial society. Princeton: Princeton University Press. Kunagy, C. L., Humphrey, C. R., & Firebaugh, G. (1994). Surging environmentalism: Changing public opinion or changing public? Social Science Quarterly 75(4):804-819. Mahler, R. L., Simmons, R., Sorensen, F., & Miner, J.R. (2004). Priority water issues in the Pacific Northwest. Journal of Extension [On-line], 42(5). Available at: http://www.joe.org/joe/2004october/rb3.shtml Mahler, R. L., Simmons, R., & Sorensen, F. (2005). Drinking water issues in the Pacific Northwest. Journal of Extension [On-line], 43(6). Available at: http://www.joe.org/joe/2005december/rb6.shtml Milbrath, L. W. (1989). Envisioning a sustainable society: Learning our way out. Albany: State University of New York Press. Mohai, P., & Twight, B. W. (1987). Age and environmentalism: An elaboration of the Buttel Model using national survey evidence. Social Science Quarterly 68:798-815. Nie, Martin A. (1999). Environmental Opinion in the American West. Society and Natural Resources 12(2):163-170. Salant, P. & Dillman, D. (1994). How to conduct your own survey. New York, NY: John Wiley and Sons, Inc. New York, New York. SAS Institute Inc. (2004). SAS Online Document 9.1.3. Cary, North Carolina: SAS Institute Inc. Switzer, J. V. (1997). Green backlash: The history and politics of the environmental opposition in the U.S. Boulder, CO. Lynne Rienner. Zelezny, L. C., Chua, P., & Aldrich, C. (2000). Elaborating on gender differences in environmentalism. Journal of Social Issues 56(3):443-457.
Designing a Bone Health and Soy Focus Group Discussion Guide Based on the Health Belief Model
Sharon F. Robinson
Mary K. Bielamowicz
A. Shanna Rodgers
William W. Wong
Karen L. Konzelmann IntroductionOsteoporosis, the most common form of bone disease, affects 10 million Americans over the age of 50 (U.S. Department of Health and Human Services, 2004). According to the Surgeon General, without action to address osteoporosis, 50% of Americans will have or be at risk of developing this disease by the year 2020 (U.S. Department of Health and Human Services, 2004). Therefore, education programs are needed to increase awareness and enhance skills in order to affect behavior changes related to bone health. Diet quality plays a significant role in bone health (Llich & Karstetter, 2000). Soy foods such as soybeans, or edamame, and calcium-fortified tofu and soymilk provide calcium to the diet when consumed. While some emerging research studies support the association between soy foods and bone health (Zhang et al., 2005), the role of soy isoflavones and bone health remains controversial (Weaver & Cheong, 2005). The research reported here assessed osteoporosis and soy knowledge and skills of adult women. If people do not perceive themselves to be at risk for osteoporosis, or they have a limited understanding of available actions for behavior change, it is unlikely that positive health-related changes will occur. Qualitative evaluation, including focus groups, can be useful in assessing client knowledge and skills before designing curricula (Krueger, 1994). To better understand the intended audience, the Health Belief Model was applied during the development of the focus group discussion guide. According to the Health Belief Model change in behavior is dependent upon several factors or constructs (Janz, Champion, & Strecher, 2002), which include perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy. According to the Health Belief Model, behavior change is unlikely to occur if women: underestimate their risk for osteoporosis or its severity, have not addressed their barriers to behavior change and options for change, and/or feel they do not have the capacity to make healthful behavior changes related to osteoporosis risk reduction. The Health Belief Model was selected because its constructs could readily be addressed during curriculum development. Focus group were conducted to:
MethodsDiscussion probes were developed to facilitate focus group discussion based on Health Belief Model constructs. A focus group discussion guide was developed, reviewed by peer experts, and pilot tested. The discussion guide was used to conduct five focus groups with adult women in Montgomery, Williamson, and Dallas counties in Texas. Participants were recruited by Texas Cooperative Extension Family and Consumer Sciences agents. Focus group procedures, including the discussion guide, were approved by the Institutional Review Board of the Texas A&M University System. After signing written consent forms, participants were welcomed to the focus group and introduced to the general format and made aware of the expectations of the proceedings. Discussion probes were used to guide conversations. Focus group sessions lasted approximately 60 minutes and were co-facilitated by a nutrition specialist and an evaluation specialist. Selected discussion probes are shown in Table 1.
ResultsEthnicity of the focus group participants (n=63) was as follows: 84% Caucasian, 6% Hispanic, 6% African American, and 2% Asian. Participant ages were as follows: 11% < 40 years, 32% 40 to 49 years, 19% 50 to 59 years, and 35% over age 59. Focus groups were conducted as guided discussion. During the focus groups, most participants demonstrated an understanding of increased risk of developing osteoporosis as one ages, especially post-menopausal women. Also, several participants mentioned heredity as a factor in osteoporosis development, as they had family members with the disease. Although they mentioned more common risk factors, the participants were unaware of other osteoporosis risk factors such as certain medications, anorexia, and alcohol abuse (Robinson, Cummings, Bielamowicz, & Rodgers, 2005). The participants agreed that they should strive to eat right and maintain a healthy lifestyle to provide good examples for their children, but barriers such as conflicting information and lack of knowledge were mentioned as reasons to why that is sometimes difficult. In regards to soy foods, several participants were unaware of the health benefits of soy and unsure of how to prepare it. Most agreed they would try to incorporate soy into their daily meal plans, given information on how to do so. Selected responses to the discussion guide probes are shown in Table 2.
Discussion and ConclusionThe research reported here was conducted to better understand consumers' knowledge and perceptions related to bone health and soy foods. Curriculum development on bone health was based, in part, on results of these focus groups. Based on the participants' comments, it was determined that many women may have a limited understanding of their perceived susceptibility for osteoporosis. Therefore, a bone health curricula undergoing development was expanded in the section on osteoporosis risk factors to include medications, amenorrhea, smoking and alcohol consumption, which were lesser known risk factors revealed by the focus group research. Perceived barriers to soy consumption were also noted during the focus groups. Therefore, curricula included suggestions on how to use soy as an ingredient in recipes. For example, a smoothie recipe using soymilk and soy yogurt was included in the curricula. Cues to action were also included in the curricula that promoted active health engagement. Education programs are necessary to increase consumer awareness and enhance skills in order to affect change in behaviors. However, the Health Belief Model reveals that the majority of people do not make health-related changes unless they perceive themselves to be at risk. Basing focus group discussion guides on appropriate model constructs, such as the Health Belief Model, may enhance focus group results and their application to curricula development, thus encouraging consumers to strive toward a more healthy lifestyle. Acknowledgments This project was supported by Initiative for Future Agriculture and Food Systems Grant no. 2001-52102-11255 from the USDA Cooperative State Research, Education, and Extension Service. ReferencesJanz, N. K., Champion, V. L., & Strecher, V. J. (2002). The health belief model. In: Health Behavior and Health Education: Theory, Research and Practice 3rd ed. Karen Glanz, Barbara K. Rimer and Frances Marcus Lewis editors. California: Jossey-Bass. Krueger, R. A. (1994). Focus groups: A practical guide for applied research. 2nd ed. London: Sage Publications. Llich, J. Z. & Karstetter, J. E. (2000). Nutrition in bone health revisited: A story beyond calcium. Journal of the American College of Nutrition, 19(6), 715-737. Robinson, S. F., Cummings, S., Bielamowicz, M. K., & Rodgers, A. S. (2005). Focus groups with Texas women indicate lack of awareness of osteoporosis risk factors. Journal American Dietetic Association, 105(8), Supplement 1, 44. U.S. Department of Health and Human Services (HHS). (2004). Bone health and osteoporosis: A report of the Surgeon General. Rockville, MD: U.S. Department of health and Human Services, Office of the Surgeon General. Weaver, C. M., & Cheong, J. M. (2005). Soy isoflavones and bone health: The relationship is still unclear. Journal of Nutrition, 135(5),1243-1247. Zhang, X, Shu, X., Li, H., Yang, G., Li, Q., Gao, Y., & Zheng, W. (2005). Prospective cohort study of soy food consumption and risk of bone fracture among postmenopausal women. Archives of Internal Medicine, 165(16), 1890-1895.
Pots, Pans, and Kitchen Equipment: Do Low-Income Clients Have Adequate Tools for Cooking?
Patti Landers
Cheryl Shults
University of Oklahoma Health Sciences Center IntroductionExtension professionals provide important nutrition education through multiple programs. The survey reported here provides information about low-income families and the cooking equipment they have available to them. Health educators may use these data to develop more appropriate recipes and better curricula about foods and nutrition. The United States Department of Agriculture in cooperation with the states funds two programs to provide nutrition education to low-income families. Initiated in 1969, the Expanded Food and Nutrition Education Program (EFNEP) was designed to educate low-income families and youth about nutrition. Food Stamp Nutrition Education (FSNE) was first funded in 1992, when seven states had nutrition education plans approved by Food and Nutrition Service, with total Federal funding of $661,076. In fiscal 2006, all states had approved FSNE budgets and federal dollars totaled about $241 million. The states provided matching funds to be spent on FSNE. With the tremendous growth in spending for nutrition education among Food Stamp (FS) applicants and beneficiaries, FNS has increased oversight and accountability for effecting behavior change through nutrition education. Half of FS participants receive benefits for 9 months or less. The average length of participation is fewer than 2 years. However, elderly and disabled individuals tend to receive food stamp benefits for longer periods of time. While over 60% leave the program within a year, their average length of participation in the program is slightly under 2 1/2 years. Extension personnel deliver much of the nutrition education for both EFNEP and FSNE. One common model is for a para-professional Nutrition Education Assistant (NEA) to deliver in-home nutrition education. The curriculum includes recipes and may actually demonstrate or lead the individual or group in food preparation. Success of the program is often evaluated based on behavior changes. These might include:
Nutrition educators often talk about the need to develop lessons that are simple and require few resources. The absence of basic kitchen appliances such as ovens and equipment like baking pans, measuring cups, and spoons could certainly limit the types of recipes to be included in the curriculum. In our review, we found no published studies that describe the kitchen inventory in a low-income home. PurposeThe study reported here was designed with three purposes:
Survey and MethodsParticipantsParticipants in the study were low-income clients who had come to one of three Department of Human Services (DHS) county offices to apply for the Food Stamp program. A graduate student went to three DHS county offices to administer the survey. One site was a busy urban office in Oklahoma City, the second was a suburban office in Norman, and the third office was located in rural Kingfisher. Not all participants answered every question. QuestionnaireWe prepared a three-page pictorial and text survey instrument in English and Spanish. It displayed some household appliances and common kitchen tools (Figure 1). The survey also had questions about demographics, including gender and age, shopping frequency, time they were willing to spend in meal preparation, which nutrition education lessons would be helpful, what kinds of recipes participants would most like to have and presence, and use of computers and the Internet. The Institutional Review Board at the University of Oklahoma Health Sciences Center approved the protocol and survey instrument. Respondents placed the completed survey into an envelope. Microsoft Excel was used for data entry and calculating descriptive statistics.
ResultsEighty-five percent of respondents were women. One hundred sixty respondents reported their age, which is illustrated in Figure 2.
Figure 2. Nineteen items in the pictorial survey were used to evaluate the adequacy of kitchen inventory. They did not include the cooler, separate freezer, hot plate, and DVD or VHS player. Table 1 describes kitchen inventories by site. Values are described as percentage of appliances and tools in the kitchen. For example, if a household had all the items except the blender, the score was 95%.
Individuals who elected to answer the Spanish version of the survey reported less kitchen equipment. Fifteen of the 16 respondents lived in the suburban county, with one living in the urban setting. Percent of kitchen equipment ranged from 25% to 96%, with a mean of 49%. Median was 46%, and interquartile range (IQR) was 36% to 49%. Table 2 describes each appliance or item and the percent of respondents who had the tools in their homes.
Figure 3 and Table 3 illustrate how often respondents shopped and how much time they were willing to spend in meal preparation.
Figure 3.
Respondents were asked to check what kind of nutrition education lessons they felt would be beneficial (Figure 4) and which category of recipes they would like to receive (Figure 5). They were allowed to check as few or as many as desired. In addition, respondents rated the importance children being able to help with food preparation as very important (48%), somewhat important (35%), or not important at all (17%).
Figure 4.
Figure 5. Fifty-two percent of respondents indicated they had computers in their home, and 48% said they used the Internet. However, while many had a computer at home, they used the Internet at the library, school, or a relative's home. DiscussionWhile this information may be useful to nutrition educators, there are some limitations. The survey instrument was not validated. While this is desirable, the confidentiality issues with food stamp participants would have made it more difficult to approach the individuals who took the survey in the Department of Human Services offices. If others use the survey and have similar results, it could be validated in that way. Additionally, some basic kitchen equipment may be missing. For example, mixing bowls should be added. It is possible that the equipment was present but not working. Most homes of Food Stamp Program participants or applicants surveyed appear to have satisfactory kitchen equipment and tools for meal preparation. Ninety percent of homes had saucepans, skillets, and microwave ovens. Less than 1% and 3% lacked refrigerators or stoves with ovens, respectively. Inadequate equipment does not appear to be a hindrance to meal preparation. However, one in five households may not have measuring tools. Although the sample size from the rural county was small and could have led to apparent differences between groups, those respondents appeared to have more of the equipment available. It is possible that these rural FS recipients might have had more access to fresh foods from garden produce and therefore more equipment with which to process or prepare it. For example, 44% of rural respondents had stand-alone freezers as compared to 24% and 28% of those from urban or suburban communities, respectively. We did not ask about children in the household. However, because the FS program is aimed at families with children, and 70% of individuals surveyed were between ages 18 and 39, it is likely that they had children. Eighty-three percent felt that it was very or somewhat important for recipes to be structured so that children could help with the cooking. This finding agrees with the Reed and Schuster (2002) recommendations for writing recipes for audiences with limited resources. Most respondents indicated they were willing to spend at least 30 minutes in preparation of a meal, and over half were willing to dedicate as much as an hour to meal preparation. Based on the results of the study reported here, it appears that homemakers in FS eligible families would prefer to receive low-cost recipes that are quick to prepare. These might include soups based on canned stock, bouillon cubes, or milk thickened with instant potato flakes to which canned or frozen vegetables and ground meat, leftover chicken, beef, or grated cheese can be added. Stir-fry and one-dish skillet dinners that can be prepared in 30 minutes or less would also be popular. Survey respondents most desired meat, vegetable, and casserole recipes. Least desired were fish and fruits. This may be because fish and fruit are perceived as expensive and may not be readily available. Forty-three percent of these low-income respondents said they use a computer, but only a third of all respondents had Internet access at home. However, 43% are using the Internet somewhere. This is an increase from a 2002 survey by Tran when only one in five reported Internet use. Nutrition educators should consider publishing lessons and recipes on Web sites. Implications for ExtensionNutrition educators may find information from the survey helpful in developing recipes and planning nutrition education interventions. For example, because over 90% of respondents had microwave ovens in the home, it might be desirable to include both conventional and microwave directions with recipes. Over half of respondents indicated they would spend more than 30 minutes in meal preparation. This is good news for Extension educators who write recipes and curricula that involve significant time for preparation. Respondents acknowledged their desire for lessons in meal planning, using leftovers, and making food last until the end of the month. This validates core lessons included in EFNEP and FSNEP curricula. Over 40% of respondents use the Internet. By making curriculum and recipes available online, former clients may become loyal alumni and continue to increase cooking, nutrition, and meal management skills. ReferencesPoikolainen, A. (2005). Characteristics of food stamp households: fiscal year 2004. Prepared by Mathematica Policy Research, Inc. for the Food and Nutrition Service, USDA. Retrieved June 23, 2006 from: http://www.fns.usda.gov/oane Reed, D. G, & Schuster, E. (2002). Recipe checklist: A tool to aid development of recipes for audiences with limited resources. Journal of Extension [On-line], 40(6). Available at: http://www.joe.org/joe/2002december/tt4.shtml Southwest Museum of Engineering, Communications and Computation. (n.d.). Retrieved October 12, 2006 from: http://www.smecc.org/microwave_oven.htm Accessed 10/12/2006 Tran, T. (2002). Comparison of nutrition education opportunities, interests and barriers to participation among food-stamp participants in Oklahoma. M.S. thesis, University of Oklahoma. U.S. Department of Agriculture Economic Research Service. (n.d.). Federal FSNE funding per participant, 2005. Retrieved July 13, 2006 from: http://www.ers.usda.gov/Briefing/FoodStamps/fsne.htm U.S. Department of Agriculture Food and Nutrition Service. (n.d.). A short history of the Food Stamp Program. Retrieved July 13, 2006 from: http://www.fns.usda.gov/fsp/rules/Legislation/history.htm U.S. Department of Agriculture National Agricultural Library. (n.d.). Approved federal funds for Food Stamp Nutrition Education by fiscal year. Retrieved July 11, 2006 from: http://www.nal.usda.gov/foodstamp United States General Accounting Office. (2004). Nutrition Education: USDA provides services through multiple programs, but stronger linkages among efforts are needed. GAO -04-528. Retrieved July 19, 2006 from: http://www.gao.gov/new.items/d04528.pdf
State 4-H Council: A Look Back on What It Meant to Serve
Chris T. Boleman
Kyle Merten
Gayle Hall IntroductionThere is need for more in-depth evaluations of specific programs in 4-H. Even though there are some studies on the impact of 4-H (Howard, 2001; Boyd, 1991; Ladewig & Thomas, 1987), historically, 4-H Youth Development Programs have fallen short in relation to evaluation and accountability of program impact.
Howard (2001), Boyd (1991), and Ladewig and Thomas (1987) certainly answered some specific questions pertaining to self-fulfillment, leadership, and reflective thoughts about 4-H. However, there are limited evaluations on the impact that specific 4-H leadership positions have had on the development of youth. Texas 4-H decided to conduct this study to determine if serving in a leadership role on the Texas 4-H Council was instrumental in the development of youth. Youth involvement in program development at all levels is an essential aspect of successful 4-H programming. For this reason, the Texas 4-H Council provides representative 4-H youth new opportunities for personal development, which are stated below:
Purpose and Research QuestionsThe study reported here determined the impact serving on Texas 4-H Council had on former members. Three major research questions were asked to address this purpose.
MethodologyThe study was an ex-post facto design using a mailed survey technique. It asked former members to reflect back on their 4-H Council membership and determine the magnitude of life skill development that was enhanced as a result of serving on state council. Surveys were mailed to former 4-H Council members (1987-2006) randomly selected from the past 20 years. The first section of the survey asked participants to evaluate life skill development as a result of being a member of 4-H Council. The life skills asked were: decision making, ability to relate to others, accepting responsibility, self esteem, motivation, organizational skills, problem solve, communicating orally, setting goals, self discipline, and team work. The procedures used for this section followed Rusk, Martin, Talbert, & Balshweid (2002) with modifications by Boleman, Cummings, and Briers (2004). The scale used to measure the magnitude of this development was defined as 1 = Not Influential At All, 2 = Mildly Influential, 3 = Moderately Influential, and 4 = Highly Influential. The second section asked level of education and income questions that follow the same format from the 4-H volunteer screening application form. A forced yes/no question within this section asked if career choice was influenced by serving on 4-H Council (NA was also provided as a choice). A final open-ended question asked respondents to explain the response to the previous question. Content and face validity was evaluated by several faculty members of the 4-H Program (including one former 4-H Council member) and two evaluation specialists in Texas Cooperative Extension. The 11 life skills were also evaluated for internal consistencies using Cronbach's coefficient alpha before responses were analyzed. Cronbach's coefficient alpha was .904, indicating a strong internal consistency measure. After review and slight modifications the survey was deemed ready for mailing. The survey was mailed following Dillman's Technique (2000). This included a preletter and a mailed survey with a self-addressed stamped envelope to return. Thirty-eight of 76 were returned, yielding a response rate of 50.0%. Descriptive statistics were used to summarize data in SPSS 14.0. Frequencies, percentages, central tendency measures, and variability were used to describe these data. To measure relationships, continuous variables were compared using Pearson's product moment correlations. Independent samples t-test were used to measure two variable comparisons. Confidence intervals and tests for statistical significance were set a priori at the 0.05 level. The opened-ended responses were analyzed and coded using qualitative research methodology outlined by Dooley and Murphy (2001). ResultsDemographicsThe mean age of respondents was 27.2 (S.D. = 5.50). Twenty of the respondents were female, and 17 were male. (One did not provide a response.) The median year the respondent served on 4-H Council was 1996. Fourteen of 38 said that their highest level of education was a Masters degree. This was followed by Bachelor degree - 11, some college - 11, Doctorate degree - 3, and Associate degree - 1. Twelve respondents said they had been officers, and 26 said they had not. Research Question 1Table 1 and Figure 1 are included to reveal data from the question pertaining to the role that serving on 4-H Council had on members' life skill development. The two life skills that respondents said were most influential were "develop oral communication" and "ability to relate to others" (Mean = 3.76, S.D. = .63 and .43, respectively). This was followed by "work in teams" (Mean = 3.68, S.D. = .62) and "build self esteem" (Mean = 3.68, S.D. = .66). These four also revealed the highest frequency total for the "highly essential" response as seen in Figure 1. "Develop oral communication" revealed the highest frequency of 32. "Ability to relate to others," "work in teams," and "build self esteem" all had 29 for the "highly essential" choice.
Figure 1. The lowest mean value was "ability to problem solve" and "decision making" (Mean = 3.29, S.D = .77 and .69, respectively). When comparing these results to studies conducted by other researchers, there are consistencies to the development of life skills of 4-H Council members when compared to other studies. For example, in a study conducted by Nash and Sant (2005) on the development of life skills in 4-H animal judging, their findings showed life skill development in the categories of decision-making, teamwork, oral communication, self-motivation, organizational skills, problems solving, and self-discipline. All seven of these are consistent with life skills measured in this study. In another study conducted by Boleman, Cummings, and Briers (2004) on parents' perceptions of life skills gained by youth participating in the 4-H Beef Project, there were consistencies between the 11 life skills developed in this study and through the 4-H Council study. Ward (1996) revealed mean values of over 4.0 in the categories of decision making, ability to relate to others, and help you accept responsibility on a similar Likert scale. All three of these are consistent life skills demonstrated in the 4-H Council study. In addition to these life skills, respondents were asked to provide the single most important trait learned from being on 4-H Council. When analyzing the comments using qualitative analysis technique described by Dooley and Murphy (2001), the underlying theme was "leadership." In further defining these comments and grouping them into like categories, the following list was compiled within leadership, which included: communication, management skills, networking, and confidence. Six of the 34 (17.65%) responses had the word leader or leadership worded in them. An example of one comment was "Leadership skills." Within leadership was "communication." Responses that fell into the communication category ranged from informal communication to public speaking. Eleven out 34 (32.35%) responses dealt with communication. An example of a communication response was, "The most significant thing I gained by being a member of the 4-H council is people skills which helps me in my occupation." Another category within leadership was "management skills." When analyzing management skills in relation to this question, respondents referred to time management, accomplishing goals, and people management. Five out of 34 (14.71%) comments fit in this category. An example of management skill comment found in the survey question is "The experience helped with the development of skills to manage people and tasks." "Networking" is the next category within leadership. Participants stated here they gained new relationships with friends, made new networks, and made new connections, which placed them in the network category. There were eight out of 34 (23.53%) responses that fell into the networking category. An example of a response that fell into the networking category is, "Friends/ connections that helped in college and beyond. A wonderful network of people." The last subcategory within leadership was "confidence." The responses from the participants that were placed in the confidence category included aspects such as confidence in oneself and believing in oneself. There were twelve out of 34 (34.29%) responses that fell into the confidence category. An example of the confidence category is "Confidence and responsibility in everything I do." Table 2 provides more details related to the most significant skill gained from being on 4-H Council.
Research Question 2The second question evaluated the life skill development comparing officer and non-officer 4-H Council members. Overall, all 11 life skills had higher mean values for influence than non-officer mean values. Two of 11 revealed significantly higher mean values (p < .05) when comparing officers to non-officers. These two were "accepting responsibility" (Officer Mean = 3.83, S.D. = .39 and (Non-officer Mean = 3.23, S.D. = .86) and "develop organizational skills" (Officer Mean = 3.67, S.D. = .49 and (Non-officer Mean = 3.15, S.D. = .67). The life skill "self discipline" also approached significant differences, with a p-value of .06. Table 3 lists all comparisons.
Research Question 3The third research question asked former 4-H Council members if serving on council influenced career goals. Twenty-five of 35 (71.4%) said yes it did influence their career goals. A follow-up question asked respondents to provide a description of their occupation. Six major categories of employment were identified after qualitative analysis. The six categories included education, business, government, law, self-employed, and other. The categories with more specific descriptions are below.
It also worth noting that five individuals said they were students. Conclusions4-H Council provides youth with an opportunity to gain life skills in a multitude of ways. Through these data presented, life skills in youth were in fact influenced through 4-H council. The two life skills that respondents stated were most influenced by the 4-H council were "develop oral communication" and "ability to relate to others." (Mean=3.76, S.D.= .63 and .43, respectively). There was little difference when comparing officer to non-officer life skill development. Only two life skills (Accepting Responsibility and Develop Organizational Skills) revealed significant differences. This could be partially attributed to the fact that the majority of state council members also serve as officers on the district council. Further research should be conducted to determine the magnitude of life skill development of youth serving on district 4-H Councils. In addition to the life skills developed from 4-H Council, participants also indicated traits that were learned through 4-H Council. An overall theme that was established from these traits stated by respondents was "leadership." The categories that were broken down under this leadership category consisted of: communication, management skills, networking, and confidence. 4-H Council also served as a stimulus for many of the participants' career goals and professional development. Results showed that 25 of 35 (71.4%) people said 4-H Council influenced their career goals in some aspect. Respondents were also asked to list their respected professions. 4-H Council is an excellent promoter of youth through various aspects of youth development. 4-H Council plays a crucial part in influencing life skills for those who serve on it as well an even larger part for those who were officers. 4-H Council is also a promoter of career goals and professionalism. Finally, by being a part of 4-H Council, participants have the opportunity to explore career goals and develop skills needed to be successful in different career fields. ReferencesBoleman, C. T., Cummings, S. R., & Briers, G. E. (2004). A parents' perceptions of life skills gained by youth participating in the 4-H Beef Project. Journal of Extension (On-line), 42(5). Available at: http://www.joe.org/joe/2004october/rb6.shtml Boleman, C. T., Burkham, A. B., McCorkle, D., & Hanselka, J. (2006). Texas Cooperative Extension. Publication # MKT - 35571. Retrieved January 12, 2006 from: http://texasextension.tamu.edu/ecoimpact/impact.html Boyd, B. L., Herring, D. R., & Briers, G. E. (1992). Developing life skills in youth. Journal of Extension (On-line), 30(4). Available at: http://www.joe.org.joe/1992winter/a4.html Dillman, D. A. (2000). Mail and Internet surveys: The tailored design method (2nd ed.). New York: John Wiley & Sons, Inc. Dooley, K. E., & Murphy, T. H. (2001). College of Agriculture faculty perception of electronic technologies in teaching. Journal of Agricultural Education, Volume 42, pp. 1-10. Howard, J. W. (2001). Impact assessment of the Texas 4-H and youth development program. Doctoral dissertation. Department of Agricultural Education. Texas A&M University. College Station, TX. Ladewig H. W., & Thomas, J. (1987). Does 4-H make a difference? College Station: The Texas A&M University System, Texas Agricultural Extension Service. Nash, S., & Sant, L. (2005). Life-skill development found in 4-H animal judging. Journal of Extension (On-line), 43(2). Available at: http://www.joe.org/joe/2005april/rb5.shtml Rusk, C. P., Martin, C. A., Talbert, B. A., & Balshweid, M. A. (2002). Attributes of Indiana's 4-H Livestock Judging Program. Journal of Extension (On-line) 40(2). Available at: http://www.joe.org/joe/2002april/rb5.html Ward, C. K. (1996). Life skill development related to participation in 4-H animal science projects. Journal of Extension (On-line), 34(2). Available at: http://www.joe.org/joe/1996april/rb2.html
Understanding Basis Risk Associated with Fed Cattle Livestock Risk Protection Insurance
Andrei R. Coelho
Darrell R. Mark
Azzeddine Azzam
University of NebraskaŠLincoln IntroductionIn 2003, USDA's Risk Management Agency (RMA) introduced Livestock Risk Protection Insurance (LRP) for fed cattle. LRP is single-peril price risk insurance that provides an indemnity to insured producers if a regional cash price index falls below some insured coverage price on the end-date of the insurance policy. By providing an indemnity based on a regional cash price index, producers hedging with LRP are exposed to a different type of basis risk than when hedging with traditional futures or options. Rather than being at risk to changes between a local cash selling price and the futures market price (futures basis), producers using LRP insurance are at risk to changes between the local cash selling price and the regional cash price index (LRP basis). One of the intended goals of LRP for fed cattle was to reduce basis risk for producers by indemnifying local cash selling prices on an index more closely related to the cash price. Still, some level of basis risk is present. More important, understanding what determines changes in LRP basis is important for producers using LRP as they develop LRP basis expectations for future cattle selling dates. Further, it is critically important for Extension Educators to recognize the difference between futures basis and LRP basis. Typically, Extension provides historical futures basis data for multiple cash market locations to assist producers in forecasting basis at the conclusion of a hedge. This traditional futures basis is not appropriate for forecasting LRP basis for a future date. Therefore, Extension educators should be prepared to not only explain the differences between futures and LRP basis, but also to provide insight on determinants of LRP basis risk. To date, there has not been any empirical research conducted to examine the factors influencing LRP basis risk. The study reported here explored the relationship between several factors and LRP basis. Research ObjectivesLRP insurance for fed cattle is indemnified on the five-area weekly weighted average cash price for 35-65% choice slaughter steers, FOB feedyard on a live weight basis, reported by USDA's Agricultural Marketing Service. Thus, LRP basis for fed cattle is the difference between a producer's local cash selling price and this five-area cash price (or Actual Ending Value as termed in the LRP policy). This LRP basis will vary according to location, but the variation would be expected to be small if the location was one of the five regions reported in the price (Kansas, Nebraska, Texas/Oklahoma, Colorado, and Iowa/Southern Minnesota). The objective of our research was to develop an understanding of the factors affecting LRP basis and compare those effects to their impacts on futures basis for the five-area region. This information should aid both producers and educators in better understanding LRP basis risk. MethodologyA system of five LRP and five futures basis
equations (one for each region) was developed to determine whether
market fundamentals explain the variation in weekly LRP and futures
basis. These equations took the form: where BASIS is either the futures basis or LRP basis, i represents the region, t represents the week, and j indexes the months from February to December. The explanatory variables representing market fundamentals included in the model are:
Weekly data from 1995 to 2004, totaling 487 useable observations, were used to estimate the effect of these market fundamental factors on LRP and futures basis (LMIC, 2006; USDA, 2005; USDA, 2006). To account for potential correlation of errors across equations, the system of five LRP and five futures basis equations were estimated using Seemingly Unrelated Regression (SUR). Additionally, the parameter estimates were corrected for first-order autocorrelation. Empirical ResultsTables 1 and 2 present the estimated coefficients for the futures basis and LRP basis equations, respectively, for the system of 10 equations estimated together using SUR (parameter estimates corresponding to the monthly binary variables were generally insignificant and are available in Coelho, 2006). The parameter estimates measure the change in basis in $/cwt from a one-unit change in the explanatory variable, ceteris paribus. Percentage units are used for variables measured as the region's share or total relative to the five-region total (e.g., SLBEEF, CASHCORN, and COF). Positive coefficients represent a strengthening or narrowing basis and negative coefficients indicate a weakening or widening basis. Results indicate that several of the independent variables had a statistically significant relationship with futures and LRP basis.
The Choice-to-Select spread is a statistically significant determinant of live futures basis for all five regions (Table 1). The positive parameter estimates indicate that a $1/cwt increase in the Choice-to-Select spread leads to a $0.12-0.19/cwt increase in futures basis. Wald chi-square tests that tested for equal effects of the Choice-to-Select spread on each region were rejected. For Nebraska, Colorado, and Iowa/So. Minnesota, the Choice-to-Select spread also had a statistically significant positive effect on LRP basis (Table 2), and this effect was statistically different across the regions. Thus, LRP basis in the northern states (which typically produce more Choice cattle) strengthened (or cash prices increased in the Northern states relative to the five-region average) as the Choice-to-Select spread widened. This suggests that Northern cattle feeding regions that traditionally produce more Choice cattle receive a premium as the demand for higher quality meat increases. Further, producers and Extension educators in those Northern states should be aware that unexpected changes in the Choice-to-Select spread may cause their actual LRP basis to differ from that expected and could slightly alter the outcome of hedges with LRP. Another factor that tended to affect LRP basis in the Northern feeding areas (Nebraska, Colorado, and Iowa/Southern Minnesota) during the time period of the study was the closure of the Canadian border (Table 2). These states tend to import a larger number of slaughter cattle from Canada, thus cash prices increased more in those areas lacking Canadian supply between 2003 and 2005, which increased LRP basis. While the impacts of the Canadian border on LRP basis were larger in the Northern regions and statistically different across all regions, it also had a statistically significant positive impact on futures basis in all five regions (Table 1). In general, futures basis strengthened (i.e., cash prices increased) in the five-region market given an overall reduction in slaughter cattle supply for U.S. meat processors and stronger domestic demand at that particular time. However, futures basis was affected by a larger magnitude in the Northern states that imported larger numbers of slaughter cattle from Canada. The quantity of cattle slaughtered in one location relative to the five-region total (SLBEEF) had mixed effects on LRP basis in different states (Table 2). Wald chi-square tests for equal effects of SLBEEF on LRP basis across the regions were rejected, confirming these mixed effects. LRP basis in Kansas and Iowa/So. Minnesota increased with SLBEEF, while in Texas/Oklahoma and Colorado, LRP basis weakened as the relative quantity of cattle slaughtered increased. These mixed results could be due to the relative cost of procurement of cattle locally vs. that in other regions. If processors in a particular region procure cattle outside of their region due to prices being higher in their region, it is possible to increase SLBEEF in the region and have higher cash prices (LRP basis) simultaneously. This may have occurred in Kansas and Iowa/Southern Minnesota. Regardless, producers in various regions should adjust LRP basis forecasts accordingly for slaughter in their respective regions. Previous studies have shown that corn price is an important factor affecting live cattle futures basis (Parcell, Schroeder, & Dhuyvetter, 2000). In this case, however, cash corn prices had a statistically significant negative impact on live cattle futures basis only in Nebraska. Corn prices had a negative impact (statistically significant at the .01 level) on LRP basis in both Nebraska and Colorado, indicating that an increase in local cash corn prices relative to the five-region average corn price weakens LRP basis in those two states. Again, Wald chi-square tests rejected the cash corn price effect being the same across the regions for both futures and LRP basis. Results here suggest that Nebraska and Colorado cattle feeders hedging with LRP should adjust their LRP basis forecasts downward as their corn price increases relative to the five-region average. Changes in cattle on feed relative to the five-region cattle on feed had no impact on live cattle futures basis in all five regions. Wald chi-square tests confirmed that COF effects on LRP basis differed across regions. 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