J Immigrant Minority Health DOI 10.1007/s10903-015-0250-9
ORIGINAL PAPER
Diabetes Risk Factor Knowledge Varies Among Multiracial College Students Lorraine Laccetti Mongiello1 • Nicholas Freudenberg2 • Hollie Jones3
Ó Springer Science+Business Media New York 2015
Abstract All racial/ethnic groups are at higher risk for type 2 diabetes compared to whites, but it is unknown if young adults recognize their risk. Risk knowledge and individual risk perception were examined in 1579 multiracial urban college students. Students have little knowledge of diabetes risk factors; identifying less than three of ten. Considerable variation exists in the understanding of risk; only .02 % of Asian, 14.0 % of Hispanic and 22.8 % of black students recognized that their race increased risk. Among those with C3 risk factors (n = 541) only 39 % perceived their risk. These underestimators had lower knowledge scores (p = .03) than those who acknowledged their risk; indicating that the cause of under-estimating risk may be, at least, in part due to a lack of information. There is a pressing need to heighten understanding of type 2 diabetes risk among young adults to decrease the future burden of this disease. Keywords Type 2 diabetes Asian College students Risk knowledge Risk perception
& Lorraine Laccetti Mongiello [email protected] 1
School of Health Professions, New York Institute of Technology, Old Westbury, NY, USA
2
School of Public Health, City University of New York, New York, NY, USA
3
Psychology Department, Medgar Evers College, New York, NY, USA
Background In the United States, more than 29 million or 12.3 % of adults aged 20 years or older had type 2 diabetes in 2012 [1]. Rates disproportionately impact ethnic minorities and are increasing at an alarming rate among all groups. For example, CDC data show that from 1980 to 2011 the age-adjusted prevalence of diagnosed diabetes increased 148 and 84 % among black males and females respectively [2]. Overall, the American Diabetes Association reports that 7.6 % of non-Hispanic whites, 9.0 % of Asian Americans, 12.8 % of Hispanics, 13.2 % of nonHispanic blacks and 15.9 % of American Indians/Alaskan Natives are diagnosed with the disease [3]. However, rates are likely even higher, especially in some groups. It has been reported that Asian Americans are at least 20–50 % more likely to be diagnosed with diabetes as compared to their white counterparts [4–6]. Additionally, an analysis of over 1.7 million California residents revealed that high rates of diabetes among Pacific Islanders (18.3 %), South Asians (15.9 %), and Filipinos (16.1 %) were obscured by much lower rates among Chinese Americans (8.2 %) and several smaller Asian subgroups [7]. In this study, the aggregated categories of Asians/Pacific Islanders yielded prevalence rates of 12.2 % compared to 7.3 % of whites, 13.7 % of non-Hispanic blacks and 14.0 % of Hispanics [7]. Explanations for the excess diabetes risk in Asians are unclear; but it has been shown that Asians develop diabetes at an earlier age and at lower ranges of body mass index (BMI) than whites [8]. There is evidence that this may be associated with increased insulin resistance [9], lower abdominal obesity [10], cardiorespiratory fitness and physical inactivity [11]. Additionally, South Asian men may need to undertake greater levels of moderate physical activity compared to Caucasian to exhibit a similar health benefit [12].
123
J Immigrant Minority Health
Theoretical/Conceptual Framework College students are making the transition from adolescence to adulthood. During this period, diet and physical activity routines are known to change and students typically form long-lasting detrimental health behaviors [13–19]. In high school, most students live at home, providing fewer food choices and more structure. In comparison, after enrolling in college, young people eat more, are more stressed, have disturbed sleep patterns and their vigorous physical activity levels decline markedly [20–22]. All of these behaviors have been shown to contribute to weight gain in college-aged people [23–25] and potentially increase future prevalence of type 2 diabetes and other chronic diseases. While inactivity, poor dietary choices and other unhealthy habits are frequently observed in college students [26], it is not known if young adults recognize how their current behaviors increase their future risk of type 2 diabetes, nor is it known if these young adults are aware of the non-modifiable risk factors for this disease such as race and family history. It is also not apparent if knowledge of risk factors and personal risk perception differs among racial/ethnic students. Although it is a tenant of health behavior theories that knowledge of risk or a perceived threat motivates people to take action [27], it remains unclear if knowledge of risk factors for diabetes leads to a more realistic perception of one’s individual risk or if risk perception is a parameter distinct from both disease risk knowledge and presence of personal risk factors [28–31]. It is therefore important to learn if awareness of risk factors varies among races, ethnicities and cultures as research in this area is needed to develop models of behavioral change that are relevant to the needs of all young adults and to develop culturally accessible and effective methods of primary prevention and intervention to minimize risk and diminish the future burden of diabetes. Consequently, the goals of this study were to (1) evaluate the overall levels of knowledge of diabetes risk factors and ascertain the difference in knowledge along racial/ethnic and gender characteristics, (2) determine if diabetes risk factor knowledge correlates with one’s perception of individual risk among a multiracial sample of urban college students.
Methods Participants and Data Collection Self-reported data on health behaviors, health care access, health status, diabetes knowledge and diabetes risk factors were collected from 1579 diverse students from three City University of New York (CUNY) campuses. Recruitment
123
Table 1 Demographics of CUNY undergraduates and survey respondents (%) CUNY students
CUNY survey
White
26.1
22.4
Black
28.7
30.8
Hispanic/Latino
26.1
27.1
Asian
17.2
16.8
Chinese
34.0
South Asian
18.1
South East Asian Pacific Islander
6.4 15.5
Korean
10.6
Japanese
1.1
Unknown
14.3
Female
59.0
73.9
Males
41.0
26.1
Born outside U.S.
44.2
43.2
Income \20,000
37.8
34.0
Age: 18–25 years
76.1 %
Age: 26–35 years
15.2 %
Age: 36 and older
8.4 %
and study procedures were reviewed and approved by the CUNY Graduate Center’s Institutional Review Board. Students on each campus were recruited to take a 60 question survey by a research assistant who explained the survey to the students and read the consent form to them. Students were given a copy of the consent form and had the opportunity to ask questions. Participants were not offered any incentive to complete the survey and were not penalized in any way if they chose not to participate. Although the respondents were a convenience sample, the demographic composition of the sample was very similar to the CUNY student body as a whole (Table 1). The only notable difference was gender; the study sample contained a higher proportion of women than does the university. Measures and Analysis Study procedures were reviewed and approved by the CUNY-wide institutional review board. Inferential statistics were used to draw conclusions from the sample population tested using SPSS for Windows (Rel.19.0.0. 2010. Chicago: SPSS Inc.). The diabetes risk knowledge section of the survey included 10 items on established risk factors for diabetes adapted from the validated instrument Risk Perception Survey for Developing Diabetes (RPS-DD) [32]. A diabetes risk factor knowledge score was determined by calculating the sum of correct responses to the following: ‘‘Which statement most closely reflects your view of how each
J Immigrant Minority Health
characteristic affects a person’s risk for diabetes (decreases risk, no effect on risk, increases risk, I don’t know): being native American, being Asian American, being white, being black, being Hispanic, having a relative with diabetes, being older than 65, exercising regularly, having diabetes during pregnancy, being overweight or obese.’’ Students responding ‘‘I don’t know’’ were scored as incorrect. The prevalence and characteristics of students with high and low diabetes risk knowledge scores were analyzed using nonparametric methods. Mann–Whitney U tests and a Kruskal–Wallis test were used to determine if there was a significant difference in knowledge scores depending on age group, income, birthplace, gender, family history and race/ethnicity. To determine whether any of the four ethnic groups were statistically different from each other on their diabetes knowledge’, follow-up Mann–Whitney U tests were conducted to test each pair of racial groups. Using the Chi square test for independence, the data were also examined to determine if students were able to accurately identify the effect that their own race has on diabetes risk (e.g. do Hispanic students know that being Hispanic increases one’s risk for diabetes). Last, the data were examined to ascertain a relationship between one’s individual risk perceptions and risk knowledge score. This was accomplished using a Mann–Whitney U Test. A determination of objective diabetes risk in each subject was based on the ADA Diabetes Risk Test using a simple count of established diabetes risk factors previously demonstrated to predict long-term outcomes [33–35].Those reporting a history of gestational diabetes (GDM) were considered at high risk as GDM is a strong indicator of future diabetes [3]. Students with three or more risk factors (other than race) were also identified as high risk, while those students with less than three risk factors and no history of GDM were considered to be at low risk. Five hundred and forty-one students were identified as being at high risk for diabetes. Thirty-nine percent of these high risk students were optimistic and felt that they were less likely to develop the disease than others. These students were identified as under-estimators, i.e., those who were optimistic about their likelihood of not developing diabetes, but were actually at high risk. Realistic-estimators of their diabetes risk were also identified, these were students at high risk and acknowledged they believed that they were more likely to get diabetes than others.
Table 2 Students responding correctly to diabetes risk factor questions Risk factor
Percent correct
Exercising regularly
78.0
Being overweight or obese
68.0
Being Caucasian (white)
40.4
Having a blood relative with diabetes
35.6
Being 65 years of age or older
21.4
Having diabetes during pregnancy
19.5
Being Black or African-American Being Hispanic or Latino
15.7 12.6
Being American Indian
3.4
Being Asian
1.4
Inactivity (78 %) and obesity (68 %) were the two risk factors that were perceived as increasing the risk of diabetes for the largest proportion of the students. Other risk factors such as family history of diabetes were less known (36 %) among the sample as a whole, but more frequent among those with family incomes greater than $60,000 (p = .001), those younger than 25 years of age (p = .003) and Asian and white students (p \ .001). Comparing age groups, students younger than 25 years of age had a higher mean knowledge score (3.08) than students 25 years and older (2.58) (p \ .001). By birthplace, individuals who were born in the United States had a higher mean knowledge scores (3.15) than individuals who were born outside the country (2.66) (p \ .001). Students from families with income above $60,000 had a higher mean knowledge score (3.40) than their less affluent counterparts (2.99) (p = .001). To determine whether the scores of the four ethnic groups were statistically different from each other, followup Mann–Whitney U tests were conducted to test each pair of racial groups. There was a significant difference between non-Hispanic whites and Hispanics (p \ .001), non-Hispanic whites and non-Hispanic blacks (p \ .001), nonHispanic blacks and Asian and Pacific Islanders (p \ .001) and between Hispanics and Asian and Pacific Islanders (p = .003) (Table 3). There was also a statistically significant relationship (p \ .001) between ethnicity and Table 3 Diabetes risk factor knowledge score by race/ethnicity (maximum score 10.0) Number of students
Results Knowledge of established diabetes risks among the study population were extremely low; out of a possible score of 10, the mean score for the sample was 2.9 (Table 2).
Mean score
SD
Non-Hispanic white
279
3.40
2.02
Asian
258
3.23
1.97
Hispanic
360
2.75
2.06
Non-Hispanic black
540
2.67
2.25
1437
2.92
2.14
Total
123
J Immigrant Minority Health Table 4 Students responding correctly to risk associated with their race (p \ .001) Race/ethnicity
Number
Percent correct
Non-Hispanic black
114
22.8
48
14.0
Hispanic Asian
6
.02
Table 5 Diabetes risk factor knowledge score and risk perception of high risk students (p = .03) Number of students
Mean score
SD
Under-estimator
211
2.71
2.20
Realistic-estimator
330
3.10
2.15
Total
541
2.94
2.18
whether or not a participant answered the risk based on ethnicity item correctly, for their own race (Table 4). In the subset (n = 541) of high risk students, those who underestimated their personal risk had significantly (p = .03) lower knowledge scores (2.71) than participants who realistically estimated their risk (3.10) (Table 5). No statistically significant differences were observed in knowledge score based on either gender or family history of diabetes among the study population.
Discussion The data clearly show that while most students recognized obesity and inactivity risks, few were knowledgeable about risk factors associated with ethnicity and other non-modifiable factors. Blacks and Hispanics who are disproportionately affected by chronic disease received the lowest scores. Previous research also identifies these groups, as having a limited knowledge of health risks [29, 30, 36–41] and it is likely that young adults with lower educational attainment may be even less likely to recognize risk than their college enrolled counterparts. One of the most significant findings from this study was the lack of risk awareness among the Asian students. Although risk varies by region of origin, it has been calculated that the odds of diabetes in Asians Americans are 20–50 % greater than their white counterparts; despite having substantially lower BMIs; in particular, South Asians are at extreme risk for this disease [4, 5]. In a New York City community survey, South Asians were shown to have nearly five times the diabetes prevalence of comparable American-born whites and 2.5 times higher prevalence than other foreign-born other Asians [42]. Kanaya et al. [43] reported that the prevalence of diabetes among American South Asians is 23 % compared to 6 % in
123
whites, 18 % in African Americans, 17 % in Hispanics and 13 % in Chinese Americans. Despite this, almost 20 % of all students surveyed believe that being Asian actually lowers their risk. Only 1.4 % of all students and .02 % of Asian students believed that being of Asian descent increased diabetes risk, 60 % of all Asian students stated that they are less likely to get diabetes than others their age and approximately half of Asians with three or more known risk factors for diabetes did not acknowledge their elevated risk. These findings are similar to a study of primary care physicians, a group trained to recognize chronic disease risk factors, in which only 27 % of white physicians and 56 % of Asian physicians knew that being Asian increased one’s risk of developing diabetes [44]. The bases for disparities in risk knowledge that have been observed here are unclear but it is conceivable that this lack of awareness is related to the development of diabetes in Asians at a body weight considered ‘‘normal’’ by conventional standards. Excess body weight is the most visible risk factor for diabetes; and, nearly 70 % of the students recognized this. Asians in general, and in the study population, weigh less than their non-Asian counterparts and consequently may view themselves as not being at risk [45]. Additionally, although diabetes is spreading more rapidly in Asia than anywhere else in the world, there is poor public awareness and limited opportunities for diagnosis [46]. It is estimated that in China alone there are 92.4 million adults with the disease and that more than 60 % of those with diabetes are undiagnosed [46]. As the majority (54 %) of Asian students in this study were immigrants, this low diagnosis rate in their homelands may lessen their awareness of risk. Of the students in all groups who were identified as being at high risk for diabetes, 39 % did not recognize their risk. These under-estimators had significantly lower (p = .03) diabetes knowledge scores than their counterparts who acknowledged that they were at risk. Thus, this study provides evidence that the cause of under-estimating diabetes risk among CUNY students may be at least, in part, due to a lack of sufficient information about risk factors. In support of this finding, it has been reported that an optimistic perception of future health may not strictly be a coping mechanism, but rather due simply to lack of information or experience with a condition. In a study of Arab-American men, having a family member with diabetes predicted their willingness to engage in diabetes prevention activities [47] and African-Americans with a family history of diabetes were also more aware of diabetes risk factors and more likely to engage in certain health behaviors than were African-Americans without a family history of the disease [48]. Mosca et al. [49] documented a significant increase in the rate of awareness of
J Immigrant Minority Health
cardiovascular disease among women was associated with a greater personal awareness and increased action to lower their risk. In contrast, in a study of awareness of risk for stroke, neither knowledge of risk factors nor the number of risk factors correlated with risk perception [31], suggesting that risk perception is a subjective measure, which is not entirely modulated by disease knowledge or actual risk. The most striking cases of the disconnection between having knowledge of risk factors and associating them with one’s personal risk are the studies of GDM. Kim et al. [50] found that, among 217 well educated, white women with previous GDM, only 16 % believed that they had a high chance of developing diabetes in the future. What makes this remarkable is that 90 % of the women recognized that GDM was a strong risk factor for future diabetes [50]. Similar findings were reported in a large study of Australian women, also with a history of GDM [51]. This indicates that knowledge of diabetes risk factors or warning signs may not necessarily predict perception of risk as it did among the CUNY students. Denial of risk, in the presences of knowledge, lends credence to the theory that risk perception is a psychologically influenced coping mechanism that allows people to be unrealistically optimistic in order to deal with stressful situations, minimize anxiety and eliminate the need to change behavior. Nevertheless, health behavior theories indicate that knowledge of risk for diabetes should encourage people to take action to reduce their risk [27]. It has been shown that improved general awareness of risk is associated with greater personal awareness and increased actions to lower chronic disease. Consider the numerous breast cancer campaigns targeting women, such as ‘‘Race for the Cure’’ and the pink ribbon campaign. They are examples of pervasive education and outreach programs that have greatly altered breast cancer risk perception [52]. As a result of these efforts, women now perceive breast cancer to be one of the biggest health concerns they face today, despite the fact that six times more women die of stroke and heart disease [52]. This unrealistic pessimism regarding risk of breast cancer has been reported in female college students as well [53]. Additionally, in the case of breast cancer, this perception of high self-risk has been shown to be a consistent predictor of mammography screening [52]; indicating that helping people recognize their risk can lead to behavior change. It is reasonable to believe that risk education is a necessary and achievable first step in diabetes prevention programs on campus. For example, health or nutrition classes could be a core requirement for graduation, insuring that all students are exposed to accurate and practical information about preventing disease and maintaining optimal health during college and beyond. Both
experiential and web-based obesity and disease prevention courses and workshops for college students may also be effective, [54–56] and utilizing social media platforms, which are already integrated into many students’ lives, can be useful in delivering health related messages [56]. But education is only the first step, CUNY students face numerous obstacles to minimizing diabetes risks. They report that having busy and stressful lives contribute to inactivity and poor food choices [57]. Additionally, limited disposable income coupled with the high-cost and relative inaccessibility of healthy food options on campus serve as deterrents to a healthy diet [57]. Campus administrators must take into consideration these problems and stressors that students face and create campus environments which allow the healthy choice to become the easy choice, an approach backed by scientific consensus on its relative efficacy [58].
Strengths and Limitations The primary strength of this study is that the student health survey was completed by a large sample of diverse (60 % non-white) students living and attending college in an urban environment. This is in contrast to the majority of research on college health which has been conducted almost exclusively among white students living in dormitories in non-urban locations. This study is limited by the fact that the survey was a convenience sample from only three of 23 campuses, and therefore, may not be representative of all of CUNY or of all urban college students. However, the sample is very closely matched to the demographics of the university, it contains significant portions of America’s major racial/ ethnic groups and all regions of Asia were represented (Table 1); all strengths of this study. It should be noted that the students’ responses to the question of how they perceived the likeliness of getting diabetes may represent one of two things: (1) The respondents’ perceived risk of getting the disease in the short term or (2) their perceived risk of having diabetes at some point in their entire lifetime. Either way, a general perception of risk was obtained and the data represent risk quantification which is worthy of analysis. Also, the risk knowledge questions were adapted from a survey that was validated for older adults.
New Contribution to the Literature The results of this study indicate that overall CUNY students have limited knowledge of the factors that are associated with an increased risk of diabetes and there is
123
J Immigrant Minority Health
considerable variation in the understanding of risk among racial/ethnic groups; with Asian students being least aware. Risk is a complex multidimensional phenomenon and the interpretation of risk varies greatly. An individual’s perceived risk with regard to a particular health condition, such as diabetes, is likely based upon a variety of factors including actual health behavior, education, individual health beliefs, culture, previous experiences and access to health-care. It is clear however, that understanding the cultural, social, economic, motivational and education factors regarding disease risk and behavior change is a critical aspect of designing useful interventions for specific populations. The content and style of risk communication can be enhanced by understanding these factors and addressing them. For example, the case can be made for Asian-specific guidance and interventions. Asian-specific BMI criterion have already been established and should be utilized more universally. It has been observed that Asian immigrants are 50 % less likely to meet activity recommendations than non-Asians born in this country [59]. In the CUNY sample, the Asian students were also significantly less likely to exercise than the three other groups. Compounding this problem is the possibility that some Asian groups may need more than the current physical activity recommendations to reap the same disease protective benefits as their non-Asian counterparts do from exercise [12]. Consequently, it may be warranted to have activity recommendations tailored to this population and it may be more effective to develop interventions which focus on increasing physical activity rather than obesity to decrease diabetes risk. Additionally, from both a clinical and a public health perspective, inactivity is more easily modified than obesity. Knowledge of risk factors for diabetes may not necessarily be sufficient to alter risk perception and change behavior. Nevertheless, without knowledge it is inconceivable that one is likely to recognize their individual risk and take action to reduce the threat. Additionally, an individual who believes that he or she is not at risk will respond differently to health prevention messages than someone who is highly conscious of his or her elevated risk. Therefore, appropriate messages and interventions must be tailored to address different beliefs, specific needs and cultural norms. Efforts must be taken to heighten knowledge and awareness of healthful behaviors among emerging adults and strategies must be implemented to ensure that appropriate food choices and opportunities for physical activity are readily available and affordable for all students. As students are a large, readily available, diverse and some-what captive population, universities and colleges are ideal settings to increase risk awareness at an important life stage in order to reduce the future burden of type 2 diabetes.
123
References 1. Centers for Disease Control and Prevention. National diabetes statistics report: estimates of diabetes and its burden in the United States. Atlanta, GA: U.S. Department of Health and Human Services; 2014. 2. Centers for Disease Control and Prevention (CDC). Diabetes statistics. http://www.cdc.gov/diabetes/statistics/prev/national/fig raceethsex.htm. Accessed 12 Jan 2015. 3. American Diabetes Association. Diabetes statistics. http://www. diabetes.org/diabetes-basics/diabetes-statistics/. Accessed 10 Apr 2010. 4. Kanaya AM, Herrington D, Vittinghoff E, et al. Understanding the high prevalence of diabetes in U.S. South Asians compared with four racial/ethnic groups: the MASALA and MESA studies. Diabetes Care. 2014;37(6):1621–8. 5. Lee JWR, Brancati FL, Yeh HC. Trends in the prevalence of type 2 diabetes in Asians versus whites: results from the United States national health interview survey, 1997–2008. Diabetes Care. 2011;34(2):353–7. 6. Schiller JS, Lucus LJ, Peregoy JA, Summary health statistics for U.S. adults: National Health Interview Survey. National Center for Health Statistics. Vital Health Stat. 2011;10(256):2012. 7. Karter AJ, Schillinger D, Adams AS, et al. Elevated rates of diabetes in Pacific Islanders and Asian subgroups: The Diabetes Study of Northern California (DISTANCE). Diabetes Care. 2013;36(3):574–9. 8. Chiu M, Austin PC, Manuel DG, Shah BR, Tu JV. Deriving ethnic-specific BMI cutoff points for assessing diabetes risk. Diabetes Care. 2011;34(8):1741–8. 9. Tillin T, Hughes AD, Godsland IF, et al. Insulin resistance and truncal obesity as important determinants of the greater incidence of diabetes in Indian Asians and African Caribbeans compared with Europeans: the Southall And Brent REvisited (SABRE) cohort. Diabetes Care. 2013;36(2):383–93. 10. Rush EC, Freitas I, Plank LD. Body size, body composition and fat distribution: comparative analysis of European, Maori, Pacific Island and Asian Indian adults. Br J Nutr. 2009;102(4):632–41. 11. Ghouri N, Purves D, McConnachie A, Wilson J, Gill JM, Sattar N. Lower cardiorespiratory fitness contributes to increased insulin resistance and fasting glycaemia in middle-aged South Asian compared with European men living in the UK. Diabetologia. 2013;56(10):2238–49. 12. Celis-Morales CA, Ghouri N, Bailey ME, Sattar N, Gill JM. Should physical activity recommendations be ethnicity-specific? Evidence from a cross-sectional study of South Asian and European men. PLoS One. 2013;8(12):e82568. 13. Ortega F, Konstabel K, Pasquali E, Ruiz J, Hurtig-Wennlof A, et al. Objectively measured physical activity and sedentary time during childhood, adolescence and young adulthood: a cohort study. PLoS One. 2013;8(4):e60871. 14. Reilly J, Kelly J. Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review. Int J Obes. 2011;35:891–8. 15. Jose K, Blizzard L, Dwyeer T, McKercher C, Alison J. Childhood and adolescent predictors of leisure time physical activity during the transition from adolescence to adulthood: a population based cohort study. Int J Behav Nutr Phys Act. 2011;8(1):54–62. 16. Larson NI, Neumark-Sztainer D, Hannan PJ, Story M. Trends in adolescent fruit and vegetable consumption, 1999–2004: project EAT. Am J Prev Med. 2007;32(2):147–50. 17. Small M, Bailey-Davis L, Morgan N, Maggs J. Changes in eating and physical activity behaviors across seven semesters of college: living on or off campus matters. Health Educ Behav. 2013;40(4):435–41.
J Immigrant Minority Health 18. Gillen MM, Lefkowitz ES. The ‘freshman 15’: trends and predictors in a sample of multiethnic men and women. Eat Behav. 2011;12(4):261–6. 19. Kvaavik E, Andersen LF, Klepp KI. The stability of soft drinks intake from adolescence to adult age and the association between long-term consumption of soft drinks and lifestyle factors and body weight. Public Health Nutr. 2005;8(2):149–57. 20. Nelson TF, Gortmaker SL, Subramanian SV, Cheung L, Wechsler H. Disparities in overweight and obesity among US college students. Am J Health Behav. 2007;31(4):363–73. 21. Strong KA, Parks SL, Anderson E, Winett R, Davy BM. Weight gain prevention: identifying theory-based targets for health behavior change in young adults. J Am Diet Assoc. 2008;108(10):1708–15. 22. Nelson TF, Gortmaker SL, Subramanian SV, Wechsler H. Vigorous physical activity among college students in the United States. J Phys Act Health. 2007;4(4):495–508. 23. Patel SR, Hu FB. Short sleep duration and weight gain: a systematic review. Obesity (Silver Spring). 2008;16(3):643–53. 24. Serlachius A, Hamer M, Wardle J. Stress and weight change in university students in the United Kingdom. Physiol Behav. 2007;92(4):548–53. 25. Vella-Zarb RA, Elgar FJ. The ‘freshman 5’: a meta-analysis of weight gain in the freshman year of college. J Am Coll Health. 2009;58(2):161–6. 26. Wengreen H, Moncur C. Change in diet, physical activity, and body weight among young-adults during the transition from high school to college. Nutr J. 2009;42:32–8. 27. Glanz K, National Cancer Institute (U.S.). Theory at a glance: a guide for health promotion practice. 2nd ed. Bethesda, MD: U.S. Dept. of Health and Human Services, National Cancer Institute; 2005. 28. Smith M, Dickerson J, Sosa E, McKyer E, Ory M. College students’ perceived disease risk versus actual prevalence rates. Am J Health Behav. 2012;36(1):96–106. 29. DeSalvo KB, Gregg J, Kleinpeter M, Pedersen BR, Stepter A, Peabody J. Cardiac risk underestimation in urban, black women. J Gen Intern Med. 2005;20(12):1127–31. 30. Graham GN, Leath B, Payne K, et al. Perceived versus actual risk for hypertension and diabetes in the African American community. Health Promot Pract. 2006;7(1):34–46. 31. Dearborn JL, McCullough LD. Perception of risk and knowledge of risk factors in women at high risk for stroke. Stroke. 2009;40(4):1181–6. 32. Walker EA, Caban A, Schechter CB, et al. Measuring comparative risk perceptions in an urban minority population: the risk perception survey for diabetes. Diabetes Educ. 2007;33(1):103–10. 33. Heikes KE, Eddy DM, Arondekar B, Schlessinger L. Diabetes risk calculator: a simple tool for detecting undiagnosed diabetes and pre-diabetes. Diabetes Care. 2008;31(5):1040–5. 34. Malik VS, Popkin BM, Bray GA, Despres JP, Willett WC, Hu FB. Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care. 2010;33(11):2477–83. 35. American Diabetes Association. Diabetes risk test. http://www. diabetes.org/diabetes-basics/prevention/diabetes-risk-test/. Accessed 10 Nov 2011. 36. Rosal MC, Borg A, Bodenlos JS, Tellez T, Ockene IS. Awareness of diabetes risk factors and prevention strategies among a sample of low-income latinos with no known diagnosis of diabetes. Diabetes Educ. 2011;37(1):47–55. 37. Brezo J, Royal C, Ampy F, Headings V. Ethnic identity and type 2 diabetes health attitudes in Americans of African ancestry. Ethn Dis. 2006;16(3):624–32. 38. Chesla CA, Skaff MM, Bartz RJ, Mullan JT, Fisher L. Differences in personal models among Latinos and European
39.
40.
41.
42.
43.
44.
45.
46. 47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
Americans: implications for clinical care. Diabetes Care. 2000;23(12):1780–5. Mochari-Greenberger H, Mills T, Simpson S, Mosca L. Knowledge, preventive action, and barriers to cardiovascular disease prevention by race and ethnicity in women: an American Heart Association national survey. J Womens Health. 2010;19(7):1243–9. Sivalingam S, Ashraf J, Vallurupalli N, Friderici J, Cook J, Rothberg M. Ethnic differences in the self-recognition of obesity and obesity-related comorbidities: a cross-sectional analysis. JGIM. 2011;26(6):616–20. Tan AU, Hoffman B, Rosas SE. Patient perception of risk factors associated with chronic kidney disease morbidity and mortality. Ethn Dis. 2010;20(2):106–10. Gupta LS, Wu CC, Young S, Perlman SE. Prevalence of diabetes in New York City, 2002–2008: comparing foreign-born South Asians and other Asians with U.S.-born whites, blacks, and Hispanics. Diabetes Care. 2011;34(8):1791–3. Kanaya AM, Wassel CL, Mathur D, et al. Prevalence and correlates of diabetes in South asian Indians in the United States: findings from the metabolic syndrome and atherosclerosis in South asians living in America study and the multi-ethnic study of atherosclerosis. Metab Syndr Relat Disord. 2010;8(2):157–64. Walker EA, Mertz CK, Kalten MR, Flynn J. Risk perception for developing diabetes: comparative risk judgments of physicians. Diabetes Care. 2003;26(9):2543–8. Bates L, Acevedo-Garcia D, Alegrı´a M, Krieger N. Immigration and generational trends in body mass index and obesity in the United States: results of the national Latino and Asian American survey, 2002–2003. AJPH. 2008;98(1):70–7. Yang W, Lu J, Weng J, et al. Prevalence of diabetes among men and women in China. N Engl J Med. 2010;362(12):1090–101. Pinelli NR, Herman WH, Brown MB, Jaber LA. Perceived risk and the willingness to enroll in a diabetes prevention lifestyle intervention in Arab-Americans. Diabetes Res Clin Pract. 2010;90(2):e27–9. Baptiste-Roberts K, Gary TL, Beckles GL, et al. Family history of diabetes, awareness of risk factors, and health behaviors among African Americans. AJPH. 2007;97(5):907–12. Mosca L, Mochari H, Christian A, et al. National study of women’s awareness, preventive action, and barriers to cardiovascular health. Circulation. 2006;113(4):525–34. Kim C, McEwen LN, Piette JD, Goewey J, Ferrara A, Walker EA. Risk perception for diabetes among women with histories of gestational diabetes mellitus. Diabetes Care. 2007;30(9): 2281–6. Morrison MK, Lowe JM, Collins CE. Perceived risk of type 2 diabetes in Australian women with a recent history of gestational diabetes mellitus. Diabet Med. 2010;27(8):882–6. Klein WM, Stefanek ME. Cancer risk elicitation and communication: lessons from the psychology of risk perception. CA J Clin. 2007;57(3):147–67. Wendt S. Perception of future risk of breast cancer and coronary heart disease in female undergraduates. Psychol Health Med. 2005;10(3):253–62. Lytle LA, Moe SG, Nanney MS, Laska MN, Linde JA. Designing a weight gain prevention trial for young adults: the CHOICES study. Am J Health Educ. 2014;45(2):67–75. Dour CA, Horacek TM, Schembre SM, et al. Process evaluation of project WebHealth: a nondieting web-based intervention for obesity prevention in college students. J Nutr Educ Behav. 2013;45(4):288–95. Napolitano MA, Hayes S, Bennett GG, Ives AK, Foster GD. Using Facebook and text messaging to deliver a weight loss program to college students. Obesity (Silver Spring). 2013;21(1):25–31.
123
J Immigrant Minority Health 57. Mongiello LL, Freudenberg N, Spark A. Making the healthy choice the easy choice on campus: a qualitative study. Health Behav Policy Rev. 2015;2(2):110–21. 58. Frieden TR. A framework for public health action: the health impact pyramid. Am J Public Health. 2010;100(4):590–5.
123
59. Kandula NR, Lauderdale DS. Leisure time, non-leisure time, and occupational physical activity in Asian Americans. Ann Epidemiol. 2005;15(4):257–65.
ORIGINAL PAPER
Diabetes Risk Factor Knowledge Varies Among Multiracial College Students Lorraine Laccetti Mongiello1 • Nicholas Freudenberg2 • Hollie Jones3
Ó Springer Science+Business Media New York 2015
Abstract All racial/ethnic groups are at higher risk for type 2 diabetes compared to whites, but it is unknown if young adults recognize their risk. Risk knowledge and individual risk perception were examined in 1579 multiracial urban college students. Students have little knowledge of diabetes risk factors; identifying less than three of ten. Considerable variation exists in the understanding of risk; only .02 % of Asian, 14.0 % of Hispanic and 22.8 % of black students recognized that their race increased risk. Among those with C3 risk factors (n = 541) only 39 % perceived their risk. These underestimators had lower knowledge scores (p = .03) than those who acknowledged their risk; indicating that the cause of under-estimating risk may be, at least, in part due to a lack of information. There is a pressing need to heighten understanding of type 2 diabetes risk among young adults to decrease the future burden of this disease. Keywords Type 2 diabetes Asian College students Risk knowledge Risk perception
& Lorraine Laccetti Mongiello [email protected] 1
School of Health Professions, New York Institute of Technology, Old Westbury, NY, USA
2
School of Public Health, City University of New York, New York, NY, USA
3
Psychology Department, Medgar Evers College, New York, NY, USA
Background In the United States, more than 29 million or 12.3 % of adults aged 20 years or older had type 2 diabetes in 2012 [1]. Rates disproportionately impact ethnic minorities and are increasing at an alarming rate among all groups. For example, CDC data show that from 1980 to 2011 the age-adjusted prevalence of diagnosed diabetes increased 148 and 84 % among black males and females respectively [2]. Overall, the American Diabetes Association reports that 7.6 % of non-Hispanic whites, 9.0 % of Asian Americans, 12.8 % of Hispanics, 13.2 % of nonHispanic blacks and 15.9 % of American Indians/Alaskan Natives are diagnosed with the disease [3]. However, rates are likely even higher, especially in some groups. It has been reported that Asian Americans are at least 20–50 % more likely to be diagnosed with diabetes as compared to their white counterparts [4–6]. Additionally, an analysis of over 1.7 million California residents revealed that high rates of diabetes among Pacific Islanders (18.3 %), South Asians (15.9 %), and Filipinos (16.1 %) were obscured by much lower rates among Chinese Americans (8.2 %) and several smaller Asian subgroups [7]. In this study, the aggregated categories of Asians/Pacific Islanders yielded prevalence rates of 12.2 % compared to 7.3 % of whites, 13.7 % of non-Hispanic blacks and 14.0 % of Hispanics [7]. Explanations for the excess diabetes risk in Asians are unclear; but it has been shown that Asians develop diabetes at an earlier age and at lower ranges of body mass index (BMI) than whites [8]. There is evidence that this may be associated with increased insulin resistance [9], lower abdominal obesity [10], cardiorespiratory fitness and physical inactivity [11]. Additionally, South Asian men may need to undertake greater levels of moderate physical activity compared to Caucasian to exhibit a similar health benefit [12].
123
J Immigrant Minority Health
Theoretical/Conceptual Framework College students are making the transition from adolescence to adulthood. During this period, diet and physical activity routines are known to change and students typically form long-lasting detrimental health behaviors [13–19]. In high school, most students live at home, providing fewer food choices and more structure. In comparison, after enrolling in college, young people eat more, are more stressed, have disturbed sleep patterns and their vigorous physical activity levels decline markedly [20–22]. All of these behaviors have been shown to contribute to weight gain in college-aged people [23–25] and potentially increase future prevalence of type 2 diabetes and other chronic diseases. While inactivity, poor dietary choices and other unhealthy habits are frequently observed in college students [26], it is not known if young adults recognize how their current behaviors increase their future risk of type 2 diabetes, nor is it known if these young adults are aware of the non-modifiable risk factors for this disease such as race and family history. It is also not apparent if knowledge of risk factors and personal risk perception differs among racial/ethnic students. Although it is a tenant of health behavior theories that knowledge of risk or a perceived threat motivates people to take action [27], it remains unclear if knowledge of risk factors for diabetes leads to a more realistic perception of one’s individual risk or if risk perception is a parameter distinct from both disease risk knowledge and presence of personal risk factors [28–31]. It is therefore important to learn if awareness of risk factors varies among races, ethnicities and cultures as research in this area is needed to develop models of behavioral change that are relevant to the needs of all young adults and to develop culturally accessible and effective methods of primary prevention and intervention to minimize risk and diminish the future burden of diabetes. Consequently, the goals of this study were to (1) evaluate the overall levels of knowledge of diabetes risk factors and ascertain the difference in knowledge along racial/ethnic and gender characteristics, (2) determine if diabetes risk factor knowledge correlates with one’s perception of individual risk among a multiracial sample of urban college students.
Methods Participants and Data Collection Self-reported data on health behaviors, health care access, health status, diabetes knowledge and diabetes risk factors were collected from 1579 diverse students from three City University of New York (CUNY) campuses. Recruitment
123
Table 1 Demographics of CUNY undergraduates and survey respondents (%) CUNY students
CUNY survey
White
26.1
22.4
Black
28.7
30.8
Hispanic/Latino
26.1
27.1
Asian
17.2
16.8
Chinese
34.0
South Asian
18.1
South East Asian Pacific Islander
6.4 15.5
Korean
10.6
Japanese
1.1
Unknown
14.3
Female
59.0
73.9
Males
41.0
26.1
Born outside U.S.
44.2
43.2
Income \20,000
37.8
34.0
Age: 18–25 years
76.1 %
Age: 26–35 years
15.2 %
Age: 36 and older
8.4 %
and study procedures were reviewed and approved by the CUNY Graduate Center’s Institutional Review Board. Students on each campus were recruited to take a 60 question survey by a research assistant who explained the survey to the students and read the consent form to them. Students were given a copy of the consent form and had the opportunity to ask questions. Participants were not offered any incentive to complete the survey and were not penalized in any way if they chose not to participate. Although the respondents were a convenience sample, the demographic composition of the sample was very similar to the CUNY student body as a whole (Table 1). The only notable difference was gender; the study sample contained a higher proportion of women than does the university. Measures and Analysis Study procedures were reviewed and approved by the CUNY-wide institutional review board. Inferential statistics were used to draw conclusions from the sample population tested using SPSS for Windows (Rel.19.0.0. 2010. Chicago: SPSS Inc.). The diabetes risk knowledge section of the survey included 10 items on established risk factors for diabetes adapted from the validated instrument Risk Perception Survey for Developing Diabetes (RPS-DD) [32]. A diabetes risk factor knowledge score was determined by calculating the sum of correct responses to the following: ‘‘Which statement most closely reflects your view of how each
J Immigrant Minority Health
characteristic affects a person’s risk for diabetes (decreases risk, no effect on risk, increases risk, I don’t know): being native American, being Asian American, being white, being black, being Hispanic, having a relative with diabetes, being older than 65, exercising regularly, having diabetes during pregnancy, being overweight or obese.’’ Students responding ‘‘I don’t know’’ were scored as incorrect. The prevalence and characteristics of students with high and low diabetes risk knowledge scores were analyzed using nonparametric methods. Mann–Whitney U tests and a Kruskal–Wallis test were used to determine if there was a significant difference in knowledge scores depending on age group, income, birthplace, gender, family history and race/ethnicity. To determine whether any of the four ethnic groups were statistically different from each other on their diabetes knowledge’, follow-up Mann–Whitney U tests were conducted to test each pair of racial groups. Using the Chi square test for independence, the data were also examined to determine if students were able to accurately identify the effect that their own race has on diabetes risk (e.g. do Hispanic students know that being Hispanic increases one’s risk for diabetes). Last, the data were examined to ascertain a relationship between one’s individual risk perceptions and risk knowledge score. This was accomplished using a Mann–Whitney U Test. A determination of objective diabetes risk in each subject was based on the ADA Diabetes Risk Test using a simple count of established diabetes risk factors previously demonstrated to predict long-term outcomes [33–35].Those reporting a history of gestational diabetes (GDM) were considered at high risk as GDM is a strong indicator of future diabetes [3]. Students with three or more risk factors (other than race) were also identified as high risk, while those students with less than three risk factors and no history of GDM were considered to be at low risk. Five hundred and forty-one students were identified as being at high risk for diabetes. Thirty-nine percent of these high risk students were optimistic and felt that they were less likely to develop the disease than others. These students were identified as under-estimators, i.e., those who were optimistic about their likelihood of not developing diabetes, but were actually at high risk. Realistic-estimators of their diabetes risk were also identified, these were students at high risk and acknowledged they believed that they were more likely to get diabetes than others.
Table 2 Students responding correctly to diabetes risk factor questions Risk factor
Percent correct
Exercising regularly
78.0
Being overweight or obese
68.0
Being Caucasian (white)
40.4
Having a blood relative with diabetes
35.6
Being 65 years of age or older
21.4
Having diabetes during pregnancy
19.5
Being Black or African-American Being Hispanic or Latino
15.7 12.6
Being American Indian
3.4
Being Asian
1.4
Inactivity (78 %) and obesity (68 %) were the two risk factors that were perceived as increasing the risk of diabetes for the largest proportion of the students. Other risk factors such as family history of diabetes were less known (36 %) among the sample as a whole, but more frequent among those with family incomes greater than $60,000 (p = .001), those younger than 25 years of age (p = .003) and Asian and white students (p \ .001). Comparing age groups, students younger than 25 years of age had a higher mean knowledge score (3.08) than students 25 years and older (2.58) (p \ .001). By birthplace, individuals who were born in the United States had a higher mean knowledge scores (3.15) than individuals who were born outside the country (2.66) (p \ .001). Students from families with income above $60,000 had a higher mean knowledge score (3.40) than their less affluent counterparts (2.99) (p = .001). To determine whether the scores of the four ethnic groups were statistically different from each other, followup Mann–Whitney U tests were conducted to test each pair of racial groups. There was a significant difference between non-Hispanic whites and Hispanics (p \ .001), non-Hispanic whites and non-Hispanic blacks (p \ .001), nonHispanic blacks and Asian and Pacific Islanders (p \ .001) and between Hispanics and Asian and Pacific Islanders (p = .003) (Table 3). There was also a statistically significant relationship (p \ .001) between ethnicity and Table 3 Diabetes risk factor knowledge score by race/ethnicity (maximum score 10.0) Number of students
Results Knowledge of established diabetes risks among the study population were extremely low; out of a possible score of 10, the mean score for the sample was 2.9 (Table 2).
Mean score
SD
Non-Hispanic white
279
3.40
2.02
Asian
258
3.23
1.97
Hispanic
360
2.75
2.06
Non-Hispanic black
540
2.67
2.25
1437
2.92
2.14
Total
123
J Immigrant Minority Health Table 4 Students responding correctly to risk associated with their race (p \ .001) Race/ethnicity
Number
Percent correct
Non-Hispanic black
114
22.8
48
14.0
Hispanic Asian
6
.02
Table 5 Diabetes risk factor knowledge score and risk perception of high risk students (p = .03) Number of students
Mean score
SD
Under-estimator
211
2.71
2.20
Realistic-estimator
330
3.10
2.15
Total
541
2.94
2.18
whether or not a participant answered the risk based on ethnicity item correctly, for their own race (Table 4). In the subset (n = 541) of high risk students, those who underestimated their personal risk had significantly (p = .03) lower knowledge scores (2.71) than participants who realistically estimated their risk (3.10) (Table 5). No statistically significant differences were observed in knowledge score based on either gender or family history of diabetes among the study population.
Discussion The data clearly show that while most students recognized obesity and inactivity risks, few were knowledgeable about risk factors associated with ethnicity and other non-modifiable factors. Blacks and Hispanics who are disproportionately affected by chronic disease received the lowest scores. Previous research also identifies these groups, as having a limited knowledge of health risks [29, 30, 36–41] and it is likely that young adults with lower educational attainment may be even less likely to recognize risk than their college enrolled counterparts. One of the most significant findings from this study was the lack of risk awareness among the Asian students. Although risk varies by region of origin, it has been calculated that the odds of diabetes in Asians Americans are 20–50 % greater than their white counterparts; despite having substantially lower BMIs; in particular, South Asians are at extreme risk for this disease [4, 5]. In a New York City community survey, South Asians were shown to have nearly five times the diabetes prevalence of comparable American-born whites and 2.5 times higher prevalence than other foreign-born other Asians [42]. Kanaya et al. [43] reported that the prevalence of diabetes among American South Asians is 23 % compared to 6 % in
123
whites, 18 % in African Americans, 17 % in Hispanics and 13 % in Chinese Americans. Despite this, almost 20 % of all students surveyed believe that being Asian actually lowers their risk. Only 1.4 % of all students and .02 % of Asian students believed that being of Asian descent increased diabetes risk, 60 % of all Asian students stated that they are less likely to get diabetes than others their age and approximately half of Asians with three or more known risk factors for diabetes did not acknowledge their elevated risk. These findings are similar to a study of primary care physicians, a group trained to recognize chronic disease risk factors, in which only 27 % of white physicians and 56 % of Asian physicians knew that being Asian increased one’s risk of developing diabetes [44]. The bases for disparities in risk knowledge that have been observed here are unclear but it is conceivable that this lack of awareness is related to the development of diabetes in Asians at a body weight considered ‘‘normal’’ by conventional standards. Excess body weight is the most visible risk factor for diabetes; and, nearly 70 % of the students recognized this. Asians in general, and in the study population, weigh less than their non-Asian counterparts and consequently may view themselves as not being at risk [45]. Additionally, although diabetes is spreading more rapidly in Asia than anywhere else in the world, there is poor public awareness and limited opportunities for diagnosis [46]. It is estimated that in China alone there are 92.4 million adults with the disease and that more than 60 % of those with diabetes are undiagnosed [46]. As the majority (54 %) of Asian students in this study were immigrants, this low diagnosis rate in their homelands may lessen their awareness of risk. Of the students in all groups who were identified as being at high risk for diabetes, 39 % did not recognize their risk. These under-estimators had significantly lower (p = .03) diabetes knowledge scores than their counterparts who acknowledged that they were at risk. Thus, this study provides evidence that the cause of under-estimating diabetes risk among CUNY students may be at least, in part, due to a lack of sufficient information about risk factors. In support of this finding, it has been reported that an optimistic perception of future health may not strictly be a coping mechanism, but rather due simply to lack of information or experience with a condition. In a study of Arab-American men, having a family member with diabetes predicted their willingness to engage in diabetes prevention activities [47] and African-Americans with a family history of diabetes were also more aware of diabetes risk factors and more likely to engage in certain health behaviors than were African-Americans without a family history of the disease [48]. Mosca et al. [49] documented a significant increase in the rate of awareness of
J Immigrant Minority Health
cardiovascular disease among women was associated with a greater personal awareness and increased action to lower their risk. In contrast, in a study of awareness of risk for stroke, neither knowledge of risk factors nor the number of risk factors correlated with risk perception [31], suggesting that risk perception is a subjective measure, which is not entirely modulated by disease knowledge or actual risk. The most striking cases of the disconnection between having knowledge of risk factors and associating them with one’s personal risk are the studies of GDM. Kim et al. [50] found that, among 217 well educated, white women with previous GDM, only 16 % believed that they had a high chance of developing diabetes in the future. What makes this remarkable is that 90 % of the women recognized that GDM was a strong risk factor for future diabetes [50]. Similar findings were reported in a large study of Australian women, also with a history of GDM [51]. This indicates that knowledge of diabetes risk factors or warning signs may not necessarily predict perception of risk as it did among the CUNY students. Denial of risk, in the presences of knowledge, lends credence to the theory that risk perception is a psychologically influenced coping mechanism that allows people to be unrealistically optimistic in order to deal with stressful situations, minimize anxiety and eliminate the need to change behavior. Nevertheless, health behavior theories indicate that knowledge of risk for diabetes should encourage people to take action to reduce their risk [27]. It has been shown that improved general awareness of risk is associated with greater personal awareness and increased actions to lower chronic disease. Consider the numerous breast cancer campaigns targeting women, such as ‘‘Race for the Cure’’ and the pink ribbon campaign. They are examples of pervasive education and outreach programs that have greatly altered breast cancer risk perception [52]. As a result of these efforts, women now perceive breast cancer to be one of the biggest health concerns they face today, despite the fact that six times more women die of stroke and heart disease [52]. This unrealistic pessimism regarding risk of breast cancer has been reported in female college students as well [53]. Additionally, in the case of breast cancer, this perception of high self-risk has been shown to be a consistent predictor of mammography screening [52]; indicating that helping people recognize their risk can lead to behavior change. It is reasonable to believe that risk education is a necessary and achievable first step in diabetes prevention programs on campus. For example, health or nutrition classes could be a core requirement for graduation, insuring that all students are exposed to accurate and practical information about preventing disease and maintaining optimal health during college and beyond. Both
experiential and web-based obesity and disease prevention courses and workshops for college students may also be effective, [54–56] and utilizing social media platforms, which are already integrated into many students’ lives, can be useful in delivering health related messages [56]. But education is only the first step, CUNY students face numerous obstacles to minimizing diabetes risks. They report that having busy and stressful lives contribute to inactivity and poor food choices [57]. Additionally, limited disposable income coupled with the high-cost and relative inaccessibility of healthy food options on campus serve as deterrents to a healthy diet [57]. Campus administrators must take into consideration these problems and stressors that students face and create campus environments which allow the healthy choice to become the easy choice, an approach backed by scientific consensus on its relative efficacy [58].
Strengths and Limitations The primary strength of this study is that the student health survey was completed by a large sample of diverse (60 % non-white) students living and attending college in an urban environment. This is in contrast to the majority of research on college health which has been conducted almost exclusively among white students living in dormitories in non-urban locations. This study is limited by the fact that the survey was a convenience sample from only three of 23 campuses, and therefore, may not be representative of all of CUNY or of all urban college students. However, the sample is very closely matched to the demographics of the university, it contains significant portions of America’s major racial/ ethnic groups and all regions of Asia were represented (Table 1); all strengths of this study. It should be noted that the students’ responses to the question of how they perceived the likeliness of getting diabetes may represent one of two things: (1) The respondents’ perceived risk of getting the disease in the short term or (2) their perceived risk of having diabetes at some point in their entire lifetime. Either way, a general perception of risk was obtained and the data represent risk quantification which is worthy of analysis. Also, the risk knowledge questions were adapted from a survey that was validated for older adults.
New Contribution to the Literature The results of this study indicate that overall CUNY students have limited knowledge of the factors that are associated with an increased risk of diabetes and there is
123
J Immigrant Minority Health
considerable variation in the understanding of risk among racial/ethnic groups; with Asian students being least aware. Risk is a complex multidimensional phenomenon and the interpretation of risk varies greatly. An individual’s perceived risk with regard to a particular health condition, such as diabetes, is likely based upon a variety of factors including actual health behavior, education, individual health beliefs, culture, previous experiences and access to health-care. It is clear however, that understanding the cultural, social, economic, motivational and education factors regarding disease risk and behavior change is a critical aspect of designing useful interventions for specific populations. The content and style of risk communication can be enhanced by understanding these factors and addressing them. For example, the case can be made for Asian-specific guidance and interventions. Asian-specific BMI criterion have already been established and should be utilized more universally. It has been observed that Asian immigrants are 50 % less likely to meet activity recommendations than non-Asians born in this country [59]. In the CUNY sample, the Asian students were also significantly less likely to exercise than the three other groups. Compounding this problem is the possibility that some Asian groups may need more than the current physical activity recommendations to reap the same disease protective benefits as their non-Asian counterparts do from exercise [12]. Consequently, it may be warranted to have activity recommendations tailored to this population and it may be more effective to develop interventions which focus on increasing physical activity rather than obesity to decrease diabetes risk. Additionally, from both a clinical and a public health perspective, inactivity is more easily modified than obesity. Knowledge of risk factors for diabetes may not necessarily be sufficient to alter risk perception and change behavior. Nevertheless, without knowledge it is inconceivable that one is likely to recognize their individual risk and take action to reduce the threat. Additionally, an individual who believes that he or she is not at risk will respond differently to health prevention messages than someone who is highly conscious of his or her elevated risk. Therefore, appropriate messages and interventions must be tailored to address different beliefs, specific needs and cultural norms. Efforts must be taken to heighten knowledge and awareness of healthful behaviors among emerging adults and strategies must be implemented to ensure that appropriate food choices and opportunities for physical activity are readily available and affordable for all students. As students are a large, readily available, diverse and some-what captive population, universities and colleges are ideal settings to increase risk awareness at an important life stage in order to reduce the future burden of type 2 diabetes.
123
References 1. Centers for Disease Control and Prevention. National diabetes statistics report: estimates of diabetes and its burden in the United States. Atlanta, GA: U.S. Department of Health and Human Services; 2014. 2. Centers for Disease Control and Prevention (CDC). Diabetes statistics. http://www.cdc.gov/diabetes/statistics/prev/national/fig raceethsex.htm. Accessed 12 Jan 2015. 3. American Diabetes Association. Diabetes statistics. http://www. diabetes.org/diabetes-basics/diabetes-statistics/. Accessed 10 Apr 2010. 4. Kanaya AM, Herrington D, Vittinghoff E, et al. Understanding the high prevalence of diabetes in U.S. South Asians compared with four racial/ethnic groups: the MASALA and MESA studies. Diabetes Care. 2014;37(6):1621–8. 5. Lee JWR, Brancati FL, Yeh HC. Trends in the prevalence of type 2 diabetes in Asians versus whites: results from the United States national health interview survey, 1997–2008. Diabetes Care. 2011;34(2):353–7. 6. Schiller JS, Lucus LJ, Peregoy JA, Summary health statistics for U.S. adults: National Health Interview Survey. National Center for Health Statistics. Vital Health Stat. 2011;10(256):2012. 7. Karter AJ, Schillinger D, Adams AS, et al. Elevated rates of diabetes in Pacific Islanders and Asian subgroups: The Diabetes Study of Northern California (DISTANCE). Diabetes Care. 2013;36(3):574–9. 8. Chiu M, Austin PC, Manuel DG, Shah BR, Tu JV. Deriving ethnic-specific BMI cutoff points for assessing diabetes risk. Diabetes Care. 2011;34(8):1741–8. 9. Tillin T, Hughes AD, Godsland IF, et al. Insulin resistance and truncal obesity as important determinants of the greater incidence of diabetes in Indian Asians and African Caribbeans compared with Europeans: the Southall And Brent REvisited (SABRE) cohort. Diabetes Care. 2013;36(2):383–93. 10. Rush EC, Freitas I, Plank LD. Body size, body composition and fat distribution: comparative analysis of European, Maori, Pacific Island and Asian Indian adults. Br J Nutr. 2009;102(4):632–41. 11. Ghouri N, Purves D, McConnachie A, Wilson J, Gill JM, Sattar N. Lower cardiorespiratory fitness contributes to increased insulin resistance and fasting glycaemia in middle-aged South Asian compared with European men living in the UK. Diabetologia. 2013;56(10):2238–49. 12. Celis-Morales CA, Ghouri N, Bailey ME, Sattar N, Gill JM. Should physical activity recommendations be ethnicity-specific? Evidence from a cross-sectional study of South Asian and European men. PLoS One. 2013;8(12):e82568. 13. Ortega F, Konstabel K, Pasquali E, Ruiz J, Hurtig-Wennlof A, et al. Objectively measured physical activity and sedentary time during childhood, adolescence and young adulthood: a cohort study. PLoS One. 2013;8(4):e60871. 14. Reilly J, Kelly J. Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review. Int J Obes. 2011;35:891–8. 15. Jose K, Blizzard L, Dwyeer T, McKercher C, Alison J. Childhood and adolescent predictors of leisure time physical activity during the transition from adolescence to adulthood: a population based cohort study. Int J Behav Nutr Phys Act. 2011;8(1):54–62. 16. Larson NI, Neumark-Sztainer D, Hannan PJ, Story M. Trends in adolescent fruit and vegetable consumption, 1999–2004: project EAT. Am J Prev Med. 2007;32(2):147–50. 17. Small M, Bailey-Davis L, Morgan N, Maggs J. Changes in eating and physical activity behaviors across seven semesters of college: living on or off campus matters. Health Educ Behav. 2013;40(4):435–41.
J Immigrant Minority Health 18. Gillen MM, Lefkowitz ES. The ‘freshman 15’: trends and predictors in a sample of multiethnic men and women. Eat Behav. 2011;12(4):261–6. 19. Kvaavik E, Andersen LF, Klepp KI. The stability of soft drinks intake from adolescence to adult age and the association between long-term consumption of soft drinks and lifestyle factors and body weight. Public Health Nutr. 2005;8(2):149–57. 20. Nelson TF, Gortmaker SL, Subramanian SV, Cheung L, Wechsler H. Disparities in overweight and obesity among US college students. Am J Health Behav. 2007;31(4):363–73. 21. Strong KA, Parks SL, Anderson E, Winett R, Davy BM. Weight gain prevention: identifying theory-based targets for health behavior change in young adults. J Am Diet Assoc. 2008;108(10):1708–15. 22. Nelson TF, Gortmaker SL, Subramanian SV, Wechsler H. Vigorous physical activity among college students in the United States. J Phys Act Health. 2007;4(4):495–508. 23. Patel SR, Hu FB. Short sleep duration and weight gain: a systematic review. Obesity (Silver Spring). 2008;16(3):643–53. 24. Serlachius A, Hamer M, Wardle J. Stress and weight change in university students in the United Kingdom. Physiol Behav. 2007;92(4):548–53. 25. Vella-Zarb RA, Elgar FJ. The ‘freshman 5’: a meta-analysis of weight gain in the freshman year of college. J Am Coll Health. 2009;58(2):161–6. 26. Wengreen H, Moncur C. Change in diet, physical activity, and body weight among young-adults during the transition from high school to college. Nutr J. 2009;42:32–8. 27. Glanz K, National Cancer Institute (U.S.). Theory at a glance: a guide for health promotion practice. 2nd ed. Bethesda, MD: U.S. Dept. of Health and Human Services, National Cancer Institute; 2005. 28. Smith M, Dickerson J, Sosa E, McKyer E, Ory M. College students’ perceived disease risk versus actual prevalence rates. Am J Health Behav. 2012;36(1):96–106. 29. DeSalvo KB, Gregg J, Kleinpeter M, Pedersen BR, Stepter A, Peabody J. Cardiac risk underestimation in urban, black women. J Gen Intern Med. 2005;20(12):1127–31. 30. Graham GN, Leath B, Payne K, et al. Perceived versus actual risk for hypertension and diabetes in the African American community. Health Promot Pract. 2006;7(1):34–46. 31. Dearborn JL, McCullough LD. Perception of risk and knowledge of risk factors in women at high risk for stroke. Stroke. 2009;40(4):1181–6. 32. Walker EA, Caban A, Schechter CB, et al. Measuring comparative risk perceptions in an urban minority population: the risk perception survey for diabetes. Diabetes Educ. 2007;33(1):103–10. 33. Heikes KE, Eddy DM, Arondekar B, Schlessinger L. Diabetes risk calculator: a simple tool for detecting undiagnosed diabetes and pre-diabetes. Diabetes Care. 2008;31(5):1040–5. 34. Malik VS, Popkin BM, Bray GA, Despres JP, Willett WC, Hu FB. Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care. 2010;33(11):2477–83. 35. American Diabetes Association. Diabetes risk test. http://www. diabetes.org/diabetes-basics/prevention/diabetes-risk-test/. Accessed 10 Nov 2011. 36. Rosal MC, Borg A, Bodenlos JS, Tellez T, Ockene IS. Awareness of diabetes risk factors and prevention strategies among a sample of low-income latinos with no known diagnosis of diabetes. Diabetes Educ. 2011;37(1):47–55. 37. Brezo J, Royal C, Ampy F, Headings V. Ethnic identity and type 2 diabetes health attitudes in Americans of African ancestry. Ethn Dis. 2006;16(3):624–32. 38. Chesla CA, Skaff MM, Bartz RJ, Mullan JT, Fisher L. Differences in personal models among Latinos and European
39.
40.
41.
42.
43.
44.
45.
46. 47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
Americans: implications for clinical care. Diabetes Care. 2000;23(12):1780–5. Mochari-Greenberger H, Mills T, Simpson S, Mosca L. Knowledge, preventive action, and barriers to cardiovascular disease prevention by race and ethnicity in women: an American Heart Association national survey. J Womens Health. 2010;19(7):1243–9. Sivalingam S, Ashraf J, Vallurupalli N, Friderici J, Cook J, Rothberg M. Ethnic differences in the self-recognition of obesity and obesity-related comorbidities: a cross-sectional analysis. JGIM. 2011;26(6):616–20. Tan AU, Hoffman B, Rosas SE. Patient perception of risk factors associated with chronic kidney disease morbidity and mortality. Ethn Dis. 2010;20(2):106–10. Gupta LS, Wu CC, Young S, Perlman SE. Prevalence of diabetes in New York City, 2002–2008: comparing foreign-born South Asians and other Asians with U.S.-born whites, blacks, and Hispanics. Diabetes Care. 2011;34(8):1791–3. Kanaya AM, Wassel CL, Mathur D, et al. Prevalence and correlates of diabetes in South asian Indians in the United States: findings from the metabolic syndrome and atherosclerosis in South asians living in America study and the multi-ethnic study of atherosclerosis. Metab Syndr Relat Disord. 2010;8(2):157–64. Walker EA, Mertz CK, Kalten MR, Flynn J. Risk perception for developing diabetes: comparative risk judgments of physicians. Diabetes Care. 2003;26(9):2543–8. Bates L, Acevedo-Garcia D, Alegrı´a M, Krieger N. Immigration and generational trends in body mass index and obesity in the United States: results of the national Latino and Asian American survey, 2002–2003. AJPH. 2008;98(1):70–7. Yang W, Lu J, Weng J, et al. Prevalence of diabetes among men and women in China. N Engl J Med. 2010;362(12):1090–101. Pinelli NR, Herman WH, Brown MB, Jaber LA. Perceived risk and the willingness to enroll in a diabetes prevention lifestyle intervention in Arab-Americans. Diabetes Res Clin Pract. 2010;90(2):e27–9. Baptiste-Roberts K, Gary TL, Beckles GL, et al. Family history of diabetes, awareness of risk factors, and health behaviors among African Americans. AJPH. 2007;97(5):907–12. Mosca L, Mochari H, Christian A, et al. National study of women’s awareness, preventive action, and barriers to cardiovascular health. Circulation. 2006;113(4):525–34. Kim C, McEwen LN, Piette JD, Goewey J, Ferrara A, Walker EA. Risk perception for diabetes among women with histories of gestational diabetes mellitus. Diabetes Care. 2007;30(9): 2281–6. Morrison MK, Lowe JM, Collins CE. Perceived risk of type 2 diabetes in Australian women with a recent history of gestational diabetes mellitus. Diabet Med. 2010;27(8):882–6. Klein WM, Stefanek ME. Cancer risk elicitation and communication: lessons from the psychology of risk perception. CA J Clin. 2007;57(3):147–67. Wendt S. Perception of future risk of breast cancer and coronary heart disease in female undergraduates. Psychol Health Med. 2005;10(3):253–62. Lytle LA, Moe SG, Nanney MS, Laska MN, Linde JA. Designing a weight gain prevention trial for young adults: the CHOICES study. Am J Health Educ. 2014;45(2):67–75. Dour CA, Horacek TM, Schembre SM, et al. Process evaluation of project WebHealth: a nondieting web-based intervention for obesity prevention in college students. J Nutr Educ Behav. 2013;45(4):288–95. Napolitano MA, Hayes S, Bennett GG, Ives AK, Foster GD. Using Facebook and text messaging to deliver a weight loss program to college students. Obesity (Silver Spring). 2013;21(1):25–31.
123
J Immigrant Minority Health 57. Mongiello LL, Freudenberg N, Spark A. Making the healthy choice the easy choice on campus: a qualitative study. Health Behav Policy Rev. 2015;2(2):110–21. 58. Frieden TR. A framework for public health action: the health impact pyramid. Am J Public Health. 2010;100(4):590–5.
123
59. Kandula NR, Lauderdale DS. Leisure time, non-leisure time, and occupational physical activity in Asian Americans. Ann Epidemiol. 2005;15(4):257–65.
