Skip Navigation Links
Centers for Disease Control and Prevention
 CDC Home Search Health Topics A-Z

Preventing Chronic Disease: Public Health Research, Practice and Policy

View Current Issue
Issue Archive
Archivo de números en español








Emerging Infectious Diseases Journal
MMWR


 Home 

Volume 2: No. 4, October 2005

ORIGINAL RESEARCH
A Diabetes Prevention Assessment Tool for American Indians


TABLE OF CONTENTS


Translation available Este resumen en español
  Ce résumé est en français
  這是英文摘要
  这是英文摘要
Print this article Print this article
E-mail this article E-mail this article:



Send feedback to editors Send feedback to editors
Download this article as a PDF Download this article as a PDF (302K)

You will need Adobe Acrobat Reader to view PDF files.


Navigate This Article
Abstract
Introduction
Methods
Results
Discussion
Acknowledgments
Author Information
References
Tables


Christopher A. Taylor, PhD, RD, Kathryn S. Keim, PhD, RD, Dale R. Fuqua, PhD, Christine A. Johnson, PhD

Suggested citation for this article: Taylor CA, Keim KS, Fuqua DR, Johnson CA. A diabetes prevention assessment tool for American Indians. Prev Chronic Dis [serial online] 2005 Oct [date cited]. Available from: URL: http://www.cdc.gov/pcd/issues/2005/
oct/05_0015.htm
.

PEER REVIEWED

Abstract

Introduction
American Indians have a disproportionately higher risk of developing type 2 diabetes. Few data are available about the perceptions of diabetes among American Indians, and no culturally appropriate tools are available for assessment of perceptions related to health and diabetes.

Methods
A diabetes prevention assessment tool was developed to measure perceptions of health and diabetes among American Indians. Predominant themes from qualitative interviews were used to develop the items for the tool. Data were collected at two autumn powwows, or intertribal dances, in Oklahoma. Reliability testing was performed using 185 surveys from American Indian adults not living on reservations. Principal axis factor analysis was performed to identify possible relationships among the items.

Results
Five themes, or factors, were found to categorize the perceptions of health: 1) lifestyles, 2) barriers to healthy lifestyles, 3) personal responsibility, 4) self-care behaviors, and 5) culturally defined well-being. Two factors classified the perceptions of diabetes: 1) a cognitive factor, related to personal experience, and 2) an affective factor, related to emotions.

Conclusion
Our diabetes assessment tool identified factors that should be considered when developing health promotion and diabetes prevention programs for American Indians. A valid assessment tool for the American Indian population could provide valuable, formative data that would increase understanding of the culturally related obstacles to health promotion and diabetes prevention.

Back to top

Introduction

Diabetes has become one of the most prevalent chronic diseases in the United States; approximately 8.2% of the population has been diagnosed with the disease (1). Minority populations, especially American Indians, have a disproportionately higher rate of diabetes (2-5). Indian Health Service (IHS) data for the Oklahoma area (Oklahoma, Kansas, and a portion of Texas) — the IHS area with the most American Indians — have shown that the age-adjusted rate for diabetes is approximately 60 per 1000 individuals (4), indicating that American Indians are 2.43 times more likely to have diabetes than the general population (6).

Despite the clear impact of culture on health beliefs and lifestyle behaviors (7-10), limited data are available on the culturally related perceptions of health and diabetes among American Indians. Various researchers have studied the American Indian perceptions of health and diabetes through the lens of Western medicine (8-13). Their reports indicate that American Indian views of health and diabetes differ considerably from the central dogma of Western medicine, which classifies health in terms of physiologic symptoms (10-12). In one study, researchers found that Diné (also known as Navajo) Indians placed little emphasis on the long-term effects of asthma, a chronic condition involving airway inflammation (10). Diné families who had children with asthma described asthma as a series of individual bouts of severe reactions requiring emergency medical attention (10). In other words, a child was thought to be cured of asthma if the child was not currently having reactions that required medical attention. Children often endured bouts of acute asthma with no medical treatment because families thought it would train the body to handle the condition. Similarly, our qualitative interviews of American Indian women (12) and men (C.A.T., unpublished data, 2002) in Oklahoma revealed that American Indians defined health by the presence or absence of physical symptoms of disease. In the absence of physical discomfort or limitations, they considered themselves to be healthy.

Some researchers have reported finding a sense of hopelessness and resignation among American Indians living on reservations about the inevitability of developing diabetes (8,14-16). From 1981 through 1983, Lang interviewed Dakota Sioux Indians to research the impact of diabetes on American Indian culture (13). Themes of disease pervasiveness, concerns for quality of life, and feelings of inevitability were found. Interviews with Pima (14) and Seminole American Indians (15) showed that they, too, felt developing diabetes was inevitable. Overall, the feelings of inevitability are a barrier to health promotion and diabetes prevention, especially when the physical cues in the form of diabetes symptoms are absent (9,12). The impact of these cultural perceptions on health is important. In several studies, the differences between American Indian health perceptions and Western ideology were not addressed, so the health promotion and diabetes prevention efforts among American Indians were not extremely effective (8,10,14).

Much of the research on health and diabetes perceptions among American Indians has been conducted in the reservation setting. Oklahoma does not have a reservation system and thus is a different research environment. A greater understanding of perceptions of health and diabetes among American Indians who do not live on reservations is paramount to the success of health promotion and diabetes prevention programs nationwide (7,17-20). Furthermore, the primary focus of existing tools for measuring diabetes perception is care of individuals who already have diabetes, not diabetes prevention.

A culturally appropriate instrument that measures perceptions of health and diabetes would provide helpful data for defining the relationship between perceptions and behavior. Understanding the relationship is critical for the development of targeted health promotion and diabetes prevention programs (21). If the onset of diabetes could be prevented or delayed, the improvements in quality of life and health care costs would be considerable (22-25).

Back to top

Methods

Assessment tool development

In a previous study, 79 American Indian women (12) and 20 American Indian men (C.A.T., unpublished data, 2002) were interviewed to identify cultural perceptions of health and diabetes. We used qualitative data from the interviews to create items, or statements, for our assessment tool, which increased its content validity because it included issues more germane to the respondents (26). Using dominant themes and text from the interviews, we created the Keeping the Balance Diabetes Assessment Tool, a four-part questionnaire measuring diabetes knowledge and perceptions of health, diabetes, and the social environment with a focus on diabetes prevention.

We created an initial list of items, or statements, to address four major categories: 1) perceptions of health, 2) perceptions of diabetes, 3) knowledge about the etiology of diabetes, and 4) the role of social interactions in health maintenance. When creating the items for the questionnaire, we attempted to use the original wording of the respondents from the interviews (12) to increase content validity. Each item was a statement about health, diabetes, or the social environment and was measured using a 6-point Likert-type scale (with 1 indicating strongly agree and 6 indicating strongly disagree).

Experts with experience in questionnaire development, American Indian research, or American Indian clinical practice were recruited by personal invitation and through a research and an American Indian health care e-mail Listserv. Eleven experts responded to our request and volunteered to provide online feedback and rewording suggestions so that the items would accurately measure a single concept. The panel of experts reviewed the items for cultural appropriateness, clarity, conciseness, and the ability to measure the intended concept. We used the panel's comments to create the final version of the instrument.

Sample and data collection

Men and women aged 18 to 65 years who were at least 25% American Indian according to a self-report were eligible to participate. Individuals were not excluded if they had diabetes or other chronic diseases. Key informants at two tribal health clinics identified two powwows in northeast Oklahoma where we could use the assessment tool. After receiving invitations to the powwows, a research team attended them in September 2003 and collected data.

At the first powwow, 81 volunteers completed the assessment tool; 116 volunteers completed the assessment tool at the second powwow. Two participants were excluded because they did not meet study criteria. Ten participants were excluded after providing incomplete responses or abnormally patterned responses (e.g., choosing all A's for every answer). Using SPSS (SPSS Inc, Chicago, Ill), data analysis was performed using 185 (94%) of the 197 completed questionnaires. The Oklahoma State University Institutional Review Board approved the study protocol.

Each volunteer provided signed informed consent before participating. The self-administered questionnaire was presented to eligible volunteers and followed by a brief demographic questionnaire. To increase participation, volunteers who completed both questionnaires received $10.

Data analysis

Items from two scales (31 health perceptions items and 21 diabetes perceptions items) were analyzed using principal axis factor analysis. Factor analysis is used to assess item correlations and identify common relationships among similar items, allowing the items to be categorized into various themes, or factors (27). The resulting factors are named based on the overall theme of their corresponding items. Data were excluded pairwise for items with missing or multiple responses. Data from the social interaction scale are not discussed in this article.

The principal factor analysis for each scale involved a standardized approach, and each scale (health and diabetes) was analyzed independently. The correlation matrix, Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy, and Bartlett’s tests of sphericity were evaluated for the factorability of the correlation matrix (i.e., to determine whether the items could indeed be classified into a few categories) (27). KMO values greater than 0.6 indicated that the correlation matrix had sufficient structure to result in a factorable solution. A significant Bartlett’s test of sphericity indicated that the correlation matrix was significantly different from an identity matrix (a correlation matrix in which items correlate perfectly with themselves and not at all with other items).

To clarify the factor pattern, a rotation analysis of the factors was performed. The eigenvalues (measures of variance) greater than 1 in conjunction with the scree plot (a plot of the eigenvalues and the factors) were assessed to determine the number of factors to use in the rotation analysis (27). The analysis was performed with an oblique rotation (direct oblimin, Δ = 0), which allows the factors to correlate. The correlations between the linear factors were evaluated and if little correlation resulted, the analysis was repeated using an orthogonal (varimax) rotation. Items accounting for at least 16% of the variance on a factor (with loadings greater than an absolute value of 0.4) were considered to load, or be sufficiently correlated with, a particular factor (27). All items loading on a factor were then used as the basis for naming the factor. Cronbach a was computed for all items loading on each factor. Values higher than an absolute value of 0.7 were considered to have acceptable internal consistency (28).

Back to top

Results

At the two powwows, 197 volunteers completed the assessment tool. Data analysis was performed on 185 questionnaires. Approximately two thirds of the volunteers were female, with a mean age of 37 years and a mean of 69% American Indian ancestry. Of the 185 participants, 48 (26%) reported having had a previous diagnosis of diabetes.

Factor analysis: health perceptions

Evaluation of the correlation matrix indicated relationships among the items. The KMO (0.71) and Bartlett’s test of sphericity (P <.001) indicated a factorable correlation matrix. The initial factors extracted from the 31 items measuring the health perceptions indicated a potential for extracting three, four, or five overall factors using the scree plot (Figure) and the eigenvalues (Table 1). We found that five factors best categorized the perceptions of health, which accounted for 33.1% of the total variance. An oblique rotation resulted in little correlation among the factors, so a varimax rotation was performed and interpreted.

Figure 1 is a scree plot line graph. The y axis is eigenvalues from 0 to 5.0, and the x axis is the number of factors from 1 to 31. The graph has two plotted lines: one showing the 31 items measuring health perceptions and one showing the 21 items measuring diabetes perceptions. The slope of the line indicates a potential for extracting three, four, or five overall factors."

Figure. Scree plots with results from factor analyses of health and diabetes perceptions.

Items with factor loadings greater than or equal to an absolute value of 0.4 further clarified the factor's theme. The factor loadings for each of the five factors are presented in Table 2. The five items classified by the first factor (lifestyles) were related to health maintenance behaviors, whereas the second factor (barriers) comprised five obstacles to maintaining good health. Culturally related personal responsibility for health and wellness characterized the third factor (personal responsibility). The fourth factor was characterized by self-care behaviors and their association with health, and the fifth factor (cultural wellness) included items related to the association between health and mental and physical well-being.

Cronbach a internal consistency coefficients (Table 1) were modest for the five factors of health perceptions.

Factor analysis: diabetes perceptions

Analysis of the correlation matrix, KMO (0.79), and Bartlett’s test of sphericity (P <.001) for the 21 items related to diabetes perceptions suggested that the correlation matrix was factorable. Examination of the initial eigenvalues (Table 1) and the scree plot (Figure) suggested that two factors would best categorize the 21 items. A varimax rotation was performed because the oblique rotation resulted in weak correlations between the two factors. Two factors explained 32% of the variance of the diabetes perceptions. Factor loadings for both factors are provided in Table 2. Nine items related to knowledge of and personal experience with diabetes loaded on the first factor (cognitive). The second factor (affective) comprised eight items related to concerns about and fear of diabetes and its complications. One item, the perception of diabetes as a death sentence, loaded on both factors: cognitive (0.45) and affective (0.44). Because this item related to personal experience but also caused an emotional response, it was allowed to load on both factors.

Cronbach a internal consistency coefficients (Table 1) were desirable for the two factors of diabetes perceptions.

Back to top

Discussion

Understanding culturally related health factors is critical for health promotion and diabetes prevention efforts among minority populations (8,9,29,30). The paucity of data on health perceptions of American Indians who do not live on reservations prompted our previous interviews (12); our technique of using responses from interviews to create an assessment tool has also been used in research on health perceptions about type 2 diabetes among African Americans (31-35).

Health perceptions

Of the factors identified for the health perceptions items, we discovered that two factors (lifestyle behaviors and self-care) involved the impact of behavior on health, a theme found in previous research studies (15,29). In our previous qualitative interviews, we found that participants believed that overall good health was related to a healthy lifestyle, even though they also felt that developing diabetes was inevitable (12). Responses to the lifestyle questions accounted for the greatest amount of variance (9.5%) in the health perceptions items in the assessment tool, indicating that respondents believed healthy lifestyle behaviors were essential for maintaining good health. In addition, the self-care factor had items related to the importance of taking an active role in health maintenance. Hatton (11) reported similar themes among urban American Indians, who believed that health maintenance was directly related to performing certain self-care tasks. In our study, the barriers factor comprised perceived difficulty in changing lifestyle behaviors and the perceived financial and time investments required for health maintenance, which conflict with the beliefs that self-care behaviors affect health.

Another dominant theme from our previous interviews was that the respondents relied on physical symptoms as indicators of their health status (12). Participants believed that their behaviors did not need to change if they had no physical symptoms of illness. The personal responsibility factor and self-care factor in this study included similar items, such as those measuring the cues to change lifestyle behaviors and variables used to define personal health status. The perception that a person is healthy if the person does not have a disease (a culturally defined definition of wellness) likely affects health promotion and diabetes prevention efforts.

Diabetes perceptions

Racial and ethnic minorities are a medically underserved population in the United States (9,36). The differences in health status between American Indians and the general U.S. population are becoming more pronounced as rates of various chronic diseases, including diabetes, begin reaching epidemic levels in American Indians (37). In some southwestern American Indian tribes, as many as 50% of adults older than age 35 years are affected (22). The high diabetes rate and its long-term complications (38-41) likely shape the cognitive and affective factors in the assessment tool items measuring diabetes perceptions.

Strong feelings of hopelessness and fear (affective factors) related to the effects of diabetes were evident during our previous interviews (12) and in research with other minority groups (14-16,42). In fact, Arizona Pima Indians have developed a cultural defense mechanism now known as surrender, which stems from the perceived futility of diabetes prevention (14) and hinders the initiation of diabetes prevention behaviors.

The items that loaded on the cognitive factor likely reflect diabetes knowledge obtained from personal experience. In another study, personal experiences of individual Dakota Sioux Indians collectively shaped an entire tribe’s cultural perceptions of health and diabetes (13). Experience has also shaped the attitudes of Mexican Americans about health and illness and has affected their social functioning and physical and mental health (42). Our previous interviews revealed that the personal experiences of American Indians with diabetes shaped their perceptions of diabetes prevention, treatment, and etiology (12).

Even though they recognized the relationship between healthy lifestyles and good health, participants in our study believed that their lifestyle behaviors did not have to change until their diabetes resulted in perceivable signs and symptoms. Likewise, in another study, researchers found that African American women did not consider diabetes to be a serious disease and thought medication alone was the cure (43). These findings were similar to findings from our study; participants believed that diabetes treatment involved only medication if they had no diabetes symptoms.

Items measuring the susceptibility of American Indians to developing diabetes and the fear of diabetes and its long-term complications characterized the affective factor. In a similar study involving Mexican Americans, researchers found that women judged the severity of diabetes by the extent of resulting physiologic damage (42). Diabetes was a frightening disease because of the extensive damage it could cause. Likewise, American Indian women thought of diabetes in terms of its complications, such as kidney failure and blindness (12). African American women thought that a lack of physical symptoms indicated they no longer had diabetes (43), but concerns about diabetes were strongly linked to emotional factors, including fears about diabetes, denial, and concerns about insulin therapy and required lifestyle changes (44).

Limitations

Our study has several limitations. The sample was derived through nonprobability methods and may have decreased the generalizability of the findings, but these sampling methods are often needed to identify individuals from an at-risk population (11). The smaller sample size could account for the lower internal consistencies for some of the health factors and the loading of the “death sentence” item on the cognitive and affective diabetes factors. In addition, in future versions of the assessment tool, the wording of the items may need to be changed.

As mentioned, the internal consistency coefficients for three of the health perceptions factors (Cronbach a = 0.50–0.55) were lower than desired, possibly because of the partialing of variance — and the factoring of residualized variance — inherent in the factor analysis method or the smaller sample size. Furthermore, the sample size may not have been large enough to account for the variance associated with the health and diabetes perceptions. Methodologically, complications arose as we tried to determine the number of factors to rotate for health perceptions. Despite the lower Cronbach a values, the five factors provided a sound theoretical explanation of health perceptions. Additional testing of the assessment tool in larger samples is needed to determine the relevance of the items and the stability of the factor structure.

Implications for the future

Previous studies have identified several health-related beliefs that seem to be common among various tribes: 1) the perception that health is the responsibility of the individual, 2) the perception that health and disease are natural parts of life, and 3) the understanding that spirituality plays a role in health (29). However, identifying differences among tribes and the extent to which individuals subscribe to their tribe’s cultural beliefs are important when developing health promotion activities (9,29,30,45). This assessment tool could help clinical and public health professionals obtain data about health and diabetes perceptions among individuals or groups. The resulting data from this study could provide important information for health professionals who are attempting to create culturally appropriate health care counseling and health education programs, which should be customized for specific groups and designed according to the variables that influence the group’s behavior (7,46-48).

As mentioned, we found similarities between our research and the findings from other studies, all of which demonstrate relationships among the factors associated with health and diabetes perceptions. Future research must expand the exploration of health and diabetes perceptions so that health professionals can design successful health promotion and diabetes prevention programs.

Back to top

Acknowledgments

Special thanks to the Central Oklahoma Tribal Association and the Standing Bear Foundation for invitations to their powwows. In addition, thank you to the volunteers who provided invaluable feedback about the items in our tool. The project was supported by Kappa Omicron Nu’s Omicron Nu Research Fellowship. Research was conducted in the Department of Nutritional Sciences, Oklahoma State University, Stillwater, Okla.

Back to top

Author Information

Corresponding Author: Christopher A. Taylor, PhD, RD, Medical Dietetics Division, The Ohio State University, 453 West 10th Ave, 306A Atwell Hall, Columbus, OH 43210-1234. Telephone: 614-688-7972. E-mail: ctaylor@amp.osu.edu.

Author Affiliations: Kathryn S. Keim, PhD, RD, Department of Clinical Nutrition, Rush University, Chicago, Ill; Dale R. Fuqua, PhD, School of Educational Studies, Oklahoma State University, Stillwater, Okla; Christine A. Johnson, PhD, Bureau for Social Research, Oklahoma State University, Stillwater, Okla.

Back to top

References

  1. Gregg EW, Cadwell BL, Cheng YJ, Cowie CC, Williams DE, Geiss L, et al. Trends in the prevalence and ratio of diagnosed to undiagnosed diabetes according to obesity levels in the US. Diabetes Care 2004;27:2806-12.
  2. Gohdes D, Kaufman S, Valway S. Diabetes in American Indians. An overview. Diabetes Care 1993;16:239-43.
  3. Jackson MY. Nutrition in American Indian health: past, present, and future. J Am Diet Assoc 1986;86(11):1561-5.
  4. Shalala DE, Trujillo MH, Hartz GJ, Paisano EL. Trends in Indian health, 1998-1999. Rockville (MD): U.S. Department of Health and Human Services; 2000.
  5. Smith CJ, Nelson RG, Hardy SA, Manahan EM, Bennett PH, Knowler WC. Survey of the diet of Pima Indians using quantitative food frequency assessment and 24-hour recall. Diabetic Renal Disease Study. J Am Diet Assoc 1996;96:778-84.
  6. Valway S, Freeman W, Kaufman S, Welty T, Helgerson SD, Gohdes D. Prevalence of diagnosed diabetes among American Indians and Alaska Natives, 1987. Estimates from a national outpatient data base. Diabetes Care 1993;16(1):271-6.
  7. Carter JS, Gilliland SS, Perez GE, Levin S, Broussard BA, Valdez L, et al. Native American Diabetes Project: designing culturally relevant education materials. Diabetes Educ 1997;23(2):133-4, 139.
  8. Huttlinger K, Krefting L, Drevdahl D, Tree P, Baca E, Benally A. "Doing battle": a metaphorical analysis of diabetes mellitus among Navajo people. Am J Occup Ther 1992;46(8):706-12.
  9. Sobralske MC. Perceptions of health: Navajo indians. Top Clin Nurs 1985;7(3):32-9.
  10. Van Sickle D, Wright AL. Navajo perceptions of asthma and asthma medications: clinical implications. Pediatrics 2001;108(1):E11-8.
  11. Hatton DC. Health perceptions among older urban American Indians. West J Nurs Res 1994;16(4):392-403.
  12. Taylor CA, Keim KS, Sparrer AC, Van Delinder J, Parker SP. Social and cultural barriers to diabetes prevention in Oklahoma American Indian women.  Prev Chronic Dis [serial online]. 2004 Apr [cited 2005 May 1].
  13. Lang GC. "Making sense" about diabetes: Dakota narratives of illness. Med Anthropol 1989;11(3):305-27.
  14. Kozak D. Surrendering to diabetes: an embodied response to perceptions of diabetes and death in the Gila River Indian community. Omega 1997;35:347-59.
  15. Judkins RA. American Indian Medicine and contemporary health problems. IV. Diabetes and perception of diabetes among Seneca Indians. N Y State J Med 1978;78(8):1320-3.
  16. Shanklin DS, Usher CL, Wildfire JB. Nutrition education needs and services among American Indians participating in a federal food assistance program. J Nutr Educ 1992;24:298-304.
  17. Stegmayer P, Lovrien FC, Smith M, Keller T, Gohdes DM. Designing a diabetes nutrition education program for a Native American community. Diabetes Educ 1988;14(1):64-6.
  18. Pelican S, Proulx JM, Wilde J, Del Vecchio A. Dietary guidance workshop helps tribal program cooks make changes. J Am Diet Assoc 1995;95(5):591-2.
  19. Lawn J, Lawn P. Nutrition education for Native treatment centres. Arctic Med Res 1991;Suppl:758-60.
  20. Algert SJ. Teaching elementary school children about healthy Native American foods. J Nutr Educ Behav 2003;35(2):105-6.
  21. Chandola T, Jenkinson C. Validating self-rated health in different ethnic groups. Ethn Health 2000;5(2):151-9.
  22. Rhoades ER, Hammond J, Welty TK, Handler AO, Amler RW. The Indian burden of illness and future health interventions. Public Health Rep 1987;102(4):361-8.
  23. Clark CM, Fradkin JE, Hiss RG, Lorenz RA, Vinicor F, Warren-Boulton E. Promoting early diagnosis and treatment of type 2 diabetes: the National Diabetes Education Program. JAMA 2000;284(3):363-5.
  24. Caro JJ, Ward AJ, O’Brien JA. Lifetime costs of complications resulting from type 2 diabetes in the U.S. Diabetes Care 2002;25(3):476-81.
  25. Valdmanis V, Smith DW, Page MR. Productivity and economic burden associated with diabetes. Am J Public Health 2001;91(1):129-30.
  26. Stewart B, Olson D, Goody C. Converting focus group data on food choices into a quantitative instrument. J Nutr Educ 1994;26:34-6.
  27. Stevens JP. Applied multivariate statistics for the social sciences. 4th ed. Mahwah (NJ): Lawrence Erlbaum; 2002.
  28. Windsor R, Baranowski T, Clark N, Cutter G. Evaluation of health promotion, health education, and disease prevention programs.  Mountain View (CA): Mayfield Publishing Company; 1994. p. 234-9.
  29. Pichette EF. Cultural identification of American Indians and its impact on rehabilitation services. J Rehab 1999;65:3-10.
  30. Pichette EF, Berven NL, Menz FE, La Fromboise TD. Effects of cultural identification and disability status on perceived community rehabilitation needs of American Indians. J Rehab 1997;63:38-45.
  31. Stover JC, Skelly AH, Holditch-Davis D, Dunn PF. Perceptions of health and their relationship to symptoms in African American women with type 2 diabetes. Appl Nurs Res 2001;14(2):72-80.
  32. Elasy TA, Samuel-Hodge CD, DeVellis RF, Skelly AH, Ammerman AS, Keyserling TC. Development of a health status measure for older African-American women with type 2 diabetes. Diabetes Care 2000;23:325-9.
  33. Keyserling TC, Ammerman AS, Samuel-Hodge CD, Ingram AF, Skelly AH, Elasy TZ, et al. A diabetes management program for African American women with type 2 diabetes. Diabetes Educ 2000;26(5):796-805.
  34. Samuel-Hodge CD, Headen SW, Skelly AH, Ingram AF, Keyserling TC, Jackson EJ, et al. Influences on day-to-day self-management of type 2 diabetes among African-American women: spirituality, the multi-caregiver role, and other social context factors. Diabetes Care 2000;23(7):928-33.
  35. Skelly AH, Samuel-Hodge C, Elasy T, Ammerman AS, Headen SW, Keyserling TC. Development and testing of culturally sensitive instruments for African American women with type 2 diabetes. Diabetes Educ 2000;26:769-74,776-7.
  36. Carter JS, Pugh JA, Monterrosa A. Non-insulin-dependent diabetes mellitus in minorities in the United States. Ann Intern Med 1996;125(3):221-32.
  37. Roubideaux Y. Perspectives on American Indian health. Am J Public Health 2002;92(9):1401-3.
  38. Carter JS, Gilliland SS, Perez GE, Skipper B, Gilliland FD. Public health and clinical implications of high hemoglobin A1c levels and weight in younger adult Native American people with diabetes. Arch Intern Med 2000;160(22):3471-6.
  39. Newman JM, DeStefano F, Valway SE, German RR, Muneta B. Diabetes-associated mortality in Native Americans. Diabetes Care 1993;16(1):297-9.
  40. Shalala DE, Trujillo MH, Hartz GJ, D’Angelo AJ. Regional differences in Indian health, 1998-1999. Rockville (MD): U.S. Department of Health and Human Services; 2000.
  41. Taylor TL. Health problems and use of services at two urban American Indian clinics. Public Health Rep 1988;103(1):88-95.
  42. Alcozer F. Secondary analysis of perceptions and meanings of type 2 diabetes among Mexican American women. Diabetes Educ 2000;26(5):785-95.
  43. Hopper S. Diabetes as a stigmatized condition: the case of low-income clinic patients in the United States. Soc Sci Med [Med Anthropol] 1981;15B:11-9.
  44. Anderson RM, Funnell MM, Arnold MS, Barr PA, Edwards GJ, Fitzgerald JT. Assessing the cultural relevance of an education program for urban African Americans with diabetes. Diabetes Educ 2000;26(2):280-9.
  45. Parks CA, Hesselbrock MN, Hesselbrock VM, Segal B. Gender and reported health problems in treated alcohol dependent Alaska natives. J Stud Alcohol. 2001;62(3):286-93.
  46. Contento IR, Michela JL, Goldberg CJ. Food choice among adolescents: population segmentation by motivations. J Nutr Educ 1988;20:289-98.
  47. Murphy A. Doing the best evaluation possible. In: Doner L, editor. Charting the course for evaluation: how do we measure the success of nutrition education and promotion in food assistance programs? Washington (DC): U.S. Department of Agriculture; 1997. p. 28-30.
  48. Devine CM, Wolfe WS, Bisogni CA, Frongillo EA Jr. Life-course events and experiences: associations with fruit and vegetable consumption in 3 ethnic groups. J Am Diet Assoc 1999;99:303-14.

Back to top

 



Tables

Return to your place in the textTable 1. Initial Eigenvalues, Percentage of Variance, and Internal Consistencies for Perceptions of Health and Diabetes Factors Among American Indians in Oklahoma
Factors Eigenvalue Cumulative Percentage of Variance Cronbach a
Health perceptions
Lifestyles 4.67 9.5 0.794
Barriers 3.20 18.0 0.756
Personal responsibility 2.29 23.4 0.500
Self-care 1.63 28.6 0.549
Cultural wellness 1.58 33.1 0.527
Diabetes perceptions
Cognitive 4.54 17.9 0.831
Affective 3.12 32.0 0.773
Return to your place in the textTable 2. Factor Loadings on Perceptions of Health and Diabetes Among American Indians in Oklahoma
Factors Description Loading Mean (SD)a
Health perceptions
Lifestyles Start early to take care of health. 0.787 1.8 (1.0)
Start early to eat healthy. 0.744 2.0 (1.1)
Start early to be physically active. 0.736 1.9 (1.0)
Starchy foods are bad. 0.532 2.6 (1.3)
A lot of fat is bad. 0.489 2.1 (1.2)
Barriers It is hard to change your diet. 0.740 3.3 (1.5)
It is hard to be more active. 0.669 3.5 (1.4)
It is hard to eat healthy. 0.579 3.5 (1.4)
Good health takes money. 0.539 3.4 (1.6)
Good health takes time. 0.497 3.1 (1.5)
Personal responsibility I go to the doctor when I feel sick. 0.532 3.5 (1.6)
My heath shouldn’t burden others. 0.498 2.2 (1.1)
Only I can take care of my health. 0.471 2.0 (1.3)
I take care of my health when I feel sick. 0.459 2.9 (1.6)
Self-care I prevent problems when I care for my health. 0.660 1.6 (0.9)
I will be healthy if I take care of myself. 0.631 1.6 (0.8)
I will stay healthy if I visit the doctor regularly. 0.405 2.3 (1.3)
Cultural wellness Unhealthy people are irritable. 0.554 3.1 (1.5)
Unhealthy people are depressed. 0.547 3.0 (1.4)
I am healthy if I do not have a disease. 0.413 2.4 (1.4)
Diabetes perceptions
Cognitive I can control diabetes by medicine without changing my diet. 0.712 3.7 (1.6)
I can control diabetes by medicine without changing my physical activity level. 0.673 3.7 (1.5)
My behavior doesn't need to change until I get diabetes. 0.656 4.1 (1.4)
I avoid screening so that I will not have to treat my diabetes. 0.630 4.5 (1.4)
Diabetes is taking insulin shots. 0.593 3.5 (1.5)
Diabetes is inevitable for American Indians. 0.583 4.6 (1.4)
You can tell that someone has diabetes by looking at them. 0.540 4.7 (1.4)
I won’t think about diabetes until it happens to me. 0.400 4.2 (1.5)
Diabetes is a death sentence. 0.450 3.6 (1.6)
Affective Diabetes is scary. 0.679 2.2 (1.3)
Diabetes ruins health. 0.602 3.0 (1.4)
I am afraid of diabetes. 0.583 2.7 (1.5)
Diabetes requires a lot of changes. 0.529 2.6 (1.4)
Diabetes attacks your organs. 0.491 2.5 (1.3)
People with diabetes need to eat different foods. 0.511 2.7 (1.4)
American Indians are at higher risk for getting diabetes. 0.467 1.9 (1.2)
Diabetes is a death sentence. 0.439 3.6 (1.6)

aResponses according to a 6-point Likert-type scale. 1 indicates strongly agree; 2, agree; 3, somewhat agree; 4, somewhat disagree; 5, disagree; and 6, strongly disagree.

Back to top

 



 



The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors’ affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.


 Home 

Privacy Policy | Accessibility

CDC Home | Search | Health Topics A-Z

This page last reviewed March 30, 2012

Centers for Disease Control and Prevention
National Center for Chronic Disease Prevention and Health Promotion
 HHS logoUnited States Department of
Health and Human Services