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Race/Ethnicity, Gender, Weight Status, and Colorectal Cancer Screening

Race/Ethnicity, Gender, Weight Status, and Colorectal Cancer Screening Hindawi Publishing Corporation Journal of Obesity Volume 2011, Article ID 314619, 6 pages doi:10.1155/2011/314619 Research Article Race/Ethnicity, Gender, Weight Status, and Colorectal Cancer Screening 1 2 3 Heather Bittner Fagan, Ronald E. Myers, Constantine Daskalakis, 4 5 4 Randa Sifri, Arch G. Mainous III, and Richard Wender Department of Family & Community Medicine, Christiana Care Health System, Wilmington Annex, Room 328, Wilmington, DE 19801, USA Division of Population Science, Department of Medical Oncology, Thomas Jefferson University, 1025 Walnut Street, Jefferson Medical College Building, Suite 1014, Philadelphia, PA 19107, USA Division of Biostatistics, Thomas Jefferson University, 1015 Chestnut Street, Suite M100, Philadelphia, PA 19107, USA Department of Family & Community Medicine, Jefferson Medical College, Thomas Jefferson University, 1015 Walnut Street, Suite 401, Philadelphia, PA 19107, USA Department of Family Medicine, Medical University of South Carolina, 295 Calhoun Street, Charleston, SC 29425, USA Correspondence should be addressed to Heather Bittner Fagan, hbittner-fagan@christianacare.org Received 7 September 2011; Accepted 1 November 2011 Academic Editor: Francesco Saverio Papadia Copyright © 2011 Heather Bittner Fagan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. The literature on colorectal cancer (CRC) screening is contradictory regarding the impact of weight status on CRC screening. This study was intended to determine if CRC screening rates among 2005 National Health Interview Survey (NHIS) respondent racial/ethnic and gender subgroups were influenced by weight status. Methods. Univariable and multivariable logistic regression analyses were performed to determine if CRC screening use differed significantly among obese, overweight, and normal- weight individuals in race/ethnic and gender subgroups. Results. Multivariable analyses showed that CRC screening rates did not differ significantly for individuals within these subgroups who were obese or overweight as compared to their normal-weight peers. Conclusion. Weight status does not contribute to disparities in CRC screening in race/ethnicity and gender subgroups. 1. Introduction The literature on CRC screening and weight status in large, nationally representative samples is contradictory. In Colorectal cancer (CRC) is highly preventable with screen- the 1997 Cancer Prevention Nutrition cohort, Chao et al. ing, yet it remains the third leading cause of cancer death in observed lower rates of CRC screening in overweight men, both men and women [1]. CRC screening is uniformly rec- overweight women, obese men, and obese women in com- ommended in men and women as well as blacks and whites parison to their normal weight peers [6]. In an analysis of over the age of 50. However, almost half of eligible individu- the 1999 Behavioral Risk Factor Surveillance Survey (BRFSS) als do not complete CRC screening within the recommended data, Rosen and Schneider found no difference in overall interval [2]. Compared to non-Hispanic whites, Hispanics CRC screening, endoscopy screening, or FOBT screening and blacks are less likely to have had a CRC screening test [3]. among men regardless of weight status, but these authors Gender and weight status have also been reported to affect observed that morbidly obese women had a lower rate of CRC screening. Obese individuals have higher morbidity overall screening, endoscopy, and FOBT [7]. In 2001, another and mortality for many cancers including colorectal cancer study using BRFSS data reported that men who were over- (CRC) [4, 5]. Currently, there is controversy about the weight or obese (class I) were more likely to have undergone contributions of weight status, race/ethnicity, and gender to endoscopic screening, while obese women (class I and II) observed CRC screening rates. were less likely to have screened endoscopically [8]. Obesity 2 Journal of Obesity had no effect on fecal occult blood testing (FOBT) in either testing and test date. The outcome variable of overall CRC gender [8]. screening status (up to date or not) was defined as up to In the 2000 National Health Interview survey (NHIS) date in individuals who had one of the following screening data, Wee et al. found a trend towards increased screening in tests: colonoscopy within the last 10 years, sigmoidoscopy in the overweight population compared to their normal weight last 5 years, or FOBT within the last year [13]. We required counterparts, but this analysis did not examine obesity and a person to have complete answers to at least one of the overweight separately in relation to CRC screening, nor aforementioned screening test questions. did the analysis address the relationship of race/ethnicity and gender with screening [9]. Using the 2005 NHIS data 2.3. Independent Variables set, Leone et al. reported lower screening in obese white 2.3.1. Weight Status. Obesity was defined according to BMI women compared to survey respondents who were not obese which was calculated as weight in kilograms divided by the (overweight and normal weight). However, they did not find square of height in meters. BMI was categorized as under- a similar association among black women [10]. That analysis weight (<18.5), normal weight (18.5–24.9), overweight (25– did not report on men or Hispanics and did not assess 29.9), and obesity (≥30) [14]. When possible, obese weight the independent effects of overweight and normal weight status was subdivided into BMI 30–34.9 (Class I), BMI 35– status on screening. In a recent report that used Medicare 39.9 (Class II), and BMI ≥ 40 (Class III). claims data and Veterans Health Administration data, Chang et al. reported that obesity and overweight status had no sta- 2.4. Covariates. We examined the potential confounding tistically significant impact on CRC screening [11]. Although variables of age (50–59, 60–69, 70–79), marital status (mar- that study provided insight into the impact of weight ried, unmarried), education (<12 y, high school graduate, status, the analysis did not separately examine the effects some college, college graduate), annual income (<20 K, of race/ethnicity and gender. Many smaller studies have >20 K), regular source of medical care (yes/no), insurance examined this relationship but did control for other variables status (yes/no), office visits in the last year (none, 1, 2–5, ≥6), known to influence CRC screening, such as socioeconomic personal history of cancer (yes/no), alcohol consumption status, physician recommendation, and access to care. (heavy, light, none), health status (fair/poor, excellent/good), This paper seeks to address limitations of prior analyses smoking status (current, former, never), physician recom- by examining race/ethnicity and gender, along with weight mendation (yes/no), number of comorbidities (0, 1, 2-3, 4-5, status, in CRC screening. This analysis uniquely includes 6 or more), and physical recreational activity as metabolic Hispanics and reports weight status in terms of normal, over- equivalents per week (none, <675 mets, ≥675 mets). weight, and obese. Thus, findings presented here provide a more comprehensive view of factors which may impact CRC 2.5. Statistical Analysis. In univariable analyses, we com- screening use than has been reported in the literature to date puted the proportion of subjects who had CRC screening [7–10]. across levels of each of the variables listed above (and shown in Table 1), as well as associated unadjusted odds ratios. We 2. Materials and Methods then fit two multivariable logistic regression models. The first model included main effects for all the variables shown in This study analyzed the data from the 2005 National Health Table 1 and yielded adjusted odds ratios. The second model Interview Survey, a nationally representative, cross-sectional, included the same main effects, as well as interaction terms household survey of the civilian noninstitutionalized popu- for gender by race/ethnicity, gender by weight status, and lation of the United States [12]. race/ethnicity by weight status, which allowed us to assess whether either gender or race/ethnicity modified the associ- 2.1. Participants. NHIS respondents in this study were indi- ation between weight status and CRC screening. All logistic viduals aged 50 to 80 years old [13]. We excluded individuals regression models accounted for the complex sampling who had missing data on weight status and covariates (n = design of the NHIS via appropriate weighting (Proc Surveyl- 6392) as well as underweight (BMI ≤ 18.5) individuals ogistic in SAS 9.2). (n = 108). Based on an NHIS recoded variable, we selected those individuals who self-identified as white (non- Hispanic), black, or Hispanic. 3. Results and Discussion The sampling plan follows a multistage area probability 3.1. Results. The final sample included 7,088 individuals. design that permits the representative sampling of house- Overall, CRC screening was up to date in approximately holds and noninstitutional group quarters (e.g., college dor- 56% of respondents. Weighted CRC screening rates among mitories) and oversamples of blacks, Hispanics, and Asians. NHIS respondents were as follows: white males (58%), white This complex survey design allows for population estimates females (58%), black males (44%), black females (48%), of the United States [12]. Hispanic males (39%), and Hispanic females (37%). Table 1 presents several known predictors of CRC screen- 2.2. Dependent Variables ing including both the unadjusted analysis and the anal- 2.2.1. Colorectal Cancer Screening. We examined the self- ysis adjusted for main effects only. In the adjusted anal- reported variables related to endoscopy and stool blood yses, demographic variables significantly associated with Journal of Obesity 3 Table 1: Colorectal cancer screening according to selected covariates (n = 7088). Variable CRC screening rate (weighted) Unadjusted odds ratio [CI ] Adjusted odds ratio [CI ] 95 95 Overall 55.8 Weight status Normal weight 56.3 Overweight 55.7 0.97 [0.86–1.11] 1.00 [0.84–1.21] Obese 55.5 0.98 [0.85–1.12] 0.91 [0.75–1.12] Gender Female 55.7 0.99 [0.89–1.10] 0.86 [0.73–1.02] Male 56.0 Race Hispanic 38.2 Black 46.1 1.38 [1.06–1.81] 1.26 [0.87–1.82] White 58.5 2.28 [1.85–2.80] 1.25 [0.96–1.63] Age 50–59 47.2 60–69 62.7 1.87 [1.67–2.11] 1.69 [1.41–2.02] 70–79 65.0 2.08 [1.79–2.41] 1.71 [1.39–2.10] Marital status Unmarried 51.6 Married 57.5 1.27 [1.15–1.41] 1.02 [0.86–1.20] Education <12 years 44.6 High school graduate 53.3 1.41 [1.21–1.70] 1.03 [0.83–1.28] Some college 55.6 1.56 [1.32–1.84] 1.01 [0.79–1.29] College graduate 65.3 2.33 [1.96–2.78] 1.42 [1.09–1.85] Annual income <20 K 45.0 >20 K 58.0 1.69 [1.48–1.93] 1.31 [1.05–1.63] Regular source of medical care No 28.5 Yes 57.4 3.38 [2.57–4.44] 1.11 [0.78–1.57] Insured No 22.7 Yes 57.9 3.78 [3.02–4.73] 1.57 [1.16–2.14] Office visits in last year None 24.4 One 43.3 2.37 [1.78–3.16] 1.21 [0.83–1.77] 2–5 visits 58.4 4.35 [3.39–5.59] 1.60 [1.14–2.27] ≥6 visits 64.9 5.74 [4.44–7.42] 2.05 [1.42–2.96] Physician recommendation Yes 81.9 43.49 [36.82–51.36] 36.97 [31.18–43.84] No 9.4 Health status Fair/Poor 56.5 Excellent/Good 52.8 1.16 [1.01–1.33] 1.12 [0.91–1.38] Comorbidities 0 43.7 1 55.3 1.60 [1.38–1.85] 1.18 [0.94–1.48] 2-3 62.4 2.14 [1.85–2.48] 1.28 [0.99–1.65] 4-5 62.3 2.13 [1.73–2.62] 1.20 [0.85–1.70] 6 or more 73.4 3.55 [2.29–5.53] 2.28 [1.14–4.56] 4 Journal of Obesity Table 1: Continued. Variable CRC screening rate (weighted) Unadjusted odds ratio [CI ] Adjusted odds ratio [CI ] 95 95 Personal history cancer ever No 69.3 Yes 53.5 1.96 [1.67–2.30] 1.15 [0.92–1.43] Alcohol consumption Heavy 51.6 Light 59.1 1.23 [0.93–1.63] 1.01 [0.72–1.41] None 54.0 0.91 [0.69–1.20] 1.03 [0.73–1.45] Smoke Current 55.0 Former 62.6 2.28 [1.93–2.70] 1.27 [1.03–1.58] Never 42.4 1.67 [1.43–1.94] 1.26 [1.03–1.54] Recreational physical activity (METS) None/unable to exercise 48.1 <675 59.4 1.58 [1.39–1.79] 0.97 [0.81–1.17] ≥675 69.9 1.84 [1.61–2.09] 1.19 [0.98–1.44] Reference category Adjusted for all covariates listed in first column Recoded from NHIS data, has a usual place of care which is not the emergency room Saw physician in last 12 months and received a recommendation for either colonoscopy or endoscopy Heavy ≥14 drinks/week, light = 1–14 drinks/week increased screening included age greater than 60, college isolates the relationship of weight and CRC screening from education, and higher income. Access variables positively multiple known predictors and examines this relationship associated with CRC screening included being insured and more comprehensively by incorporating race, gender, and increasing number of doctor visits in the last year. A strong ethnicity. Other work using smaller datasets may have been association between physician recommendation and a CRC unable to account for all potential covariates, and only very screening was observed (OR 36.97, P< 0.001). large datasets could accommodate a subgroup analysis such as this. Access to care is strongly associated with CRC screen- Obesity was categorized further as obesity class I, II, ing. The strength of the association of physician recom- and III, and there was no effect (data not shown). This mendation and CRC screening is striking and may indicate classification could not be carried through in subgroups due that physician recommendation is necessary for screening. to sample size. We also examined endoscopy and FOBT The literature indicates that this effect appears to persist as separate outcomes and found no differences (data not regardless of race and gender [9]. More work is needed shown). to understand barriers and predictors of physician recom- Table 2 addresses the hypothesis of this study and shows mendation in subgroups who are at risk for not being the multivariable model for the relationship of weight status screened. and CRC which adjusted for the covariates in Table 1 as Findings presented here may be directly compared to well as interactions between weight status with gender a recent analysis which also examined the relationship of and race/ethnicity. There were no significant associations obesity and CRC screening in the NHIS 2005 data set [10]. In between weight status and CRC screening in Hispanic men, contrast to our findings, these authors found that obese white Hispanic women, black men, black women, white men, and women were less likely to screen. Our analysis is distinct white women, with the gender by weight status and race/ in several ways. First, we included any individual who had ethnicity by weight status interactions not significant (P = complete data for either the set of questions for FOBT or 0.512 and 0.654, resp.). for endoscopy. So, for example, individuals who were up to date on endoscopy were counted as up to date for colorectal 3.2. Discussion. Obese and overweight individuals are as cancer screening, regardless of missing data on FOBT and likely to receive CRC screening as their normal weight peers vice versa. While this is not the convention in handling of regardless of gender, race, or Hispanic ethnicity. This finding missing data, the population that would have been excluded contradicts other literature which suggests a relationship from our analysis (if we required complete data for both between weight status and CRC screening. This study agrees sets of questions) was distinct in screening behavior and with the recent analysis of Chang et al., who found no several known predictors of screening. Second, we separated evidence that obese or overweight patients were less likely to Hispanics from the white and black subgroups. We believed receive recommended care, including CRC screening, when that this group warranted separate consideration because of compared with their normal weight peers [11]. Our model the low rate of screening in Hispanics and the relative lack Journal of Obesity 5 Table 2: Adjusted model for colorectal cancer screening according analysis of our subgroups. Although all cells met the NHIS to race/gender and ethnicity (n = 7088). suggested requirements (less than 30% standard error), the wide confidence intervals suggest that sample size may have CRC Adjusted 95% confidence Weight status been a restriction in groups such as Hispanics. Additionally, screening rate odds ratios interval we could not examine subclasses of obesity (i.e., obesity I, II, Stratum specific III) in our groups of interest due to sample size. for race/gender CRC screening reduces mortality and prevents colorectal White males cancer. However, rates of screening are unacceptably low 58.6 (n = 2491) overall and in minority subgroups. The rising prevalence of Normal 59.7 1.00 obesity and the higher burden of cancer risk in obese individ- Overweight 57.9 0.90 0.68–1.18 uals make this an especially important population subgroup Obese 59.0 0.83 0.61–1.13 in terms of race/ethnicity, gender, and other characteristics. Black males 43.8 (n = 392) 4. Conclusions Normal 45.5 1.00 Overweight 44.2 1.07 0.62–1.85 There is no relationship between increasing weight and Obese 42.1 1.06 0.56–2.02 CRC screening in this nationally representative sample. Regardless of the lack of association of obesity and CRC Hispanic males 39.4 (n = 323) screening, obesity remains a risk factor for increased mor- bidity/mortality related to CRC. Therefore, future work is Normal 37.6 1.00 needed to understand and mitigate risk in the obese pop- Overweight 35.0 0.71 0.37–1.37 ulation especially as this group comes to represent an ever- Obese 52.1 0.97 0.47–2.03 increasing percentage of the US population. White females 58.3 (n = 2955) Normal 58.3 1.00 References Overweight 59.9 1.11 0.84–1.46 [1] American Cancer Society, “Cancer facts and figures 2011,” vol. Obese 56.5 0.91 0.68–1.21 2011, 2011. Black females [2] American Cancer Society, “Cancer prevention and early de- 48.0 (n = 496) tection facts and figures 2010,” vol. 2011, 2011. [3] American Cancer Society, “Cancer prevention and early Normal 36.2 1.00 detection facts and figures 2011,” vol. 2011, 2011. Overweight 53.6 1.32 0.75–2.31 [4] N. Cossrow and B. Falkner, “Race/ethnic issues in obesity and Obese 48.1 1.16 0.64–2.10 obesity-related comorbidities,” Journal of Clinical Endocrinol- Hispanic females ogy and Metabolism, vol. 89, no. 6, pp. 2590–2594, 2004. 37.1 (n = 431) [5] P. Gordon-Larsen, L. S. Adair, and B. M. Popkin, “The rela- Normal 32.6 1.00 tionship of ethnicity, socioeconomic factors, and overweight in U.S. adolescents,” Obesity Research, vol. 11, no. 1, pp. 121– Overweight 34.6 0.88 0.47–1.64 129, 2003, Erratum appears in Obesity Research, vol. 11, no. 4, Obese 43.3 1.06 0.54–2.10 p. 597, 2003. Adjusted for all variables in Table 1, as well as interaction terms of race, [6] A. Chao, C. J. Connell, V. Cokkinides, E. J. Jacobs, E. E. Calle, gender, and Hispanic ethnicity. and M. J. Thun, “Underuse of screening sigmoidoscopy and colonoscopy in a large cohort of US adults,” American Journal of Public Health, vol. 94, no. 10, pp. 1775–1781, 2004. of literature on barriers to screening in this group. Also, our [7] A. B. Rosen and E. C. Schneider, “Colorectal cancer screening analysis reports on men. Finally, this analysis is distinct in disparities related to obesity and gender,” Journal of General that it isolates the overweight group from the normal weight Internal Medicine, vol. 19, no. 4, pp. 332–338, 2004. group. Table 2 supports this decision and shows that the [8] M. Heo, D. B. Allison, and K. R. Fontaine, “Overweight, obe- sity, and colorectal cancer screening: disparity between men rate of CRC screening in overweight individuals is distinct and women,” BMC Public Health, vol. 4, article 53, 2004. from both the normal weight group and the obese group in [9] C.C.Wee,E.P.McCarthy, andR.S.Phillips,“Factorsassoci- several of our subgroups. For example, the rate of screening ated with colon cancer screening: the role of patient factors in overweight black females is 54%, compared to 36% in and physician counseling,” Preventive Medicine, vol. 41, no. normal weight black females and 48% in obese black females. 1, pp. 23–29, 2005. Black females do not see themselves as overweight until a [10] L. A. Leone, M. K. Campbell,J.A.Satia,J.M.Bowling,and M. higher BMI, compared to their white counterparts, and this P. Pignone, “Race moderates the relationship between obesity may explain the difference between overweight and obese and colorectal cancer screening in women,” Cancer Causes and [15]. Control, vol. 21, no. 3, pp. 373–385, 2010. The cross-sectional design of our study precludes deter- [11] V. W. Chang, D. A. Asch, and R. M. Werner, “Quality of care mination of cause. BMI and CRC screening are self-reported among obese patients,” Journal of the American Medical As- and therefore may be distorted. Sample size is a challenge in sociation, vol. 303, no. 13, pp. 1274–1281, 2010. 6 Journal of Obesity [12] Centers for Disease Control and Prevention (CDC), “National health interview survey (NHIS)—description,” vol. 2011, [13] American Cancer Society, “American cancer society guidelines for the early detection of cancer,” vol. 2011, 2011. [14] Centers for Disease Control and Prevention (CDC), “About BMI for adults,” vol. 2011, 2011. [15] L. A. Anderson,A.A.Eyler,D.A.Galuska,D.R.Brown,and R. C. Brownson, “Relationship of satisfaction with body size and trying to lose weight in a national survey of overweight and obese women aged 40 and older, United States,” Preventive Medicine, vol. 35, no. 4, pp. 390–396, 2002. 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Race/Ethnicity, Gender, Weight Status, and Colorectal Cancer Screening

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Hindawi Publishing Corporation Journal of Obesity Volume 2011, Article ID 314619, 6 pages doi:10.1155/2011/314619 Research Article Race/Ethnicity, Gender, Weight Status, and Colorectal Cancer Screening 1 2 3 Heather Bittner Fagan, Ronald E. Myers, Constantine Daskalakis, 4 5 4 Randa Sifri, Arch G. Mainous III, and Richard Wender Department of Family & Community Medicine, Christiana Care Health System, Wilmington Annex, Room 328, Wilmington, DE 19801, USA Division of Population Science, Department of Medical Oncology, Thomas Jefferson University, 1025 Walnut Street, Jefferson Medical College Building, Suite 1014, Philadelphia, PA 19107, USA Division of Biostatistics, Thomas Jefferson University, 1015 Chestnut Street, Suite M100, Philadelphia, PA 19107, USA Department of Family & Community Medicine, Jefferson Medical College, Thomas Jefferson University, 1015 Walnut Street, Suite 401, Philadelphia, PA 19107, USA Department of Family Medicine, Medical University of South Carolina, 295 Calhoun Street, Charleston, SC 29425, USA Correspondence should be addressed to Heather Bittner Fagan, hbittner-fagan@christianacare.org Received 7 September 2011; Accepted 1 November 2011 Academic Editor: Francesco Saverio Papadia Copyright © 2011 Heather Bittner Fagan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. The literature on colorectal cancer (CRC) screening is contradictory regarding the impact of weight status on CRC screening. This study was intended to determine if CRC screening rates among 2005 National Health Interview Survey (NHIS) respondent racial/ethnic and gender subgroups were influenced by weight status. Methods. Univariable and multivariable logistic regression analyses were performed to determine if CRC screening use differed significantly among obese, overweight, and normal- weight individuals in race/ethnic and gender subgroups. Results. Multivariable analyses showed that CRC screening rates did not differ significantly for individuals within these subgroups who were obese or overweight as compared to their normal-weight peers. Conclusion. Weight status does not contribute to disparities in CRC screening in race/ethnicity and gender subgroups. 1. Introduction The literature on CRC screening and weight status in large, nationally representative samples is contradictory. In Colorectal cancer (CRC) is highly preventable with screen- the 1997 Cancer Prevention Nutrition cohort, Chao et al. ing, yet it remains the third leading cause of cancer death in observed lower rates of CRC screening in overweight men, both men and women [1]. CRC screening is uniformly rec- overweight women, obese men, and obese women in com- ommended in men and women as well as blacks and whites parison to their normal weight peers [6]. In an analysis of over the age of 50. However, almost half of eligible individu- the 1999 Behavioral Risk Factor Surveillance Survey (BRFSS) als do not complete CRC screening within the recommended data, Rosen and Schneider found no difference in overall interval [2]. Compared to non-Hispanic whites, Hispanics CRC screening, endoscopy screening, or FOBT screening and blacks are less likely to have had a CRC screening test [3]. among men regardless of weight status, but these authors Gender and weight status have also been reported to affect observed that morbidly obese women had a lower rate of CRC screening. Obese individuals have higher morbidity overall screening, endoscopy, and FOBT [7]. In 2001, another and mortality for many cancers including colorectal cancer study using BRFSS data reported that men who were over- (CRC) [4, 5]. Currently, there is controversy about the weight or obese (class I) were more likely to have undergone contributions of weight status, race/ethnicity, and gender to endoscopic screening, while obese women (class I and II) observed CRC screening rates. were less likely to have screened endoscopically [8]. Obesity 2 Journal of Obesity had no effect on fecal occult blood testing (FOBT) in either testing and test date. The outcome variable of overall CRC gender [8]. screening status (up to date or not) was defined as up to In the 2000 National Health Interview survey (NHIS) date in individuals who had one of the following screening data, Wee et al. found a trend towards increased screening in tests: colonoscopy within the last 10 years, sigmoidoscopy in the overweight population compared to their normal weight last 5 years, or FOBT within the last year [13]. We required counterparts, but this analysis did not examine obesity and a person to have complete answers to at least one of the overweight separately in relation to CRC screening, nor aforementioned screening test questions. did the analysis address the relationship of race/ethnicity and gender with screening [9]. Using the 2005 NHIS data 2.3. Independent Variables set, Leone et al. reported lower screening in obese white 2.3.1. Weight Status. Obesity was defined according to BMI women compared to survey respondents who were not obese which was calculated as weight in kilograms divided by the (overweight and normal weight). However, they did not find square of height in meters. BMI was categorized as under- a similar association among black women [10]. That analysis weight (<18.5), normal weight (18.5–24.9), overweight (25– did not report on men or Hispanics and did not assess 29.9), and obesity (≥30) [14]. When possible, obese weight the independent effects of overweight and normal weight status was subdivided into BMI 30–34.9 (Class I), BMI 35– status on screening. In a recent report that used Medicare 39.9 (Class II), and BMI ≥ 40 (Class III). claims data and Veterans Health Administration data, Chang et al. reported that obesity and overweight status had no sta- 2.4. Covariates. We examined the potential confounding tistically significant impact on CRC screening [11]. Although variables of age (50–59, 60–69, 70–79), marital status (mar- that study provided insight into the impact of weight ried, unmarried), education (<12 y, high school graduate, status, the analysis did not separately examine the effects some college, college graduate), annual income (<20 K, of race/ethnicity and gender. Many smaller studies have >20 K), regular source of medical care (yes/no), insurance examined this relationship but did control for other variables status (yes/no), office visits in the last year (none, 1, 2–5, ≥6), known to influence CRC screening, such as socioeconomic personal history of cancer (yes/no), alcohol consumption status, physician recommendation, and access to care. (heavy, light, none), health status (fair/poor, excellent/good), This paper seeks to address limitations of prior analyses smoking status (current, former, never), physician recom- by examining race/ethnicity and gender, along with weight mendation (yes/no), number of comorbidities (0, 1, 2-3, 4-5, status, in CRC screening. This analysis uniquely includes 6 or more), and physical recreational activity as metabolic Hispanics and reports weight status in terms of normal, over- equivalents per week (none, <675 mets, ≥675 mets). weight, and obese. Thus, findings presented here provide a more comprehensive view of factors which may impact CRC 2.5. Statistical Analysis. In univariable analyses, we com- screening use than has been reported in the literature to date puted the proportion of subjects who had CRC screening [7–10]. across levels of each of the variables listed above (and shown in Table 1), as well as associated unadjusted odds ratios. We 2. Materials and Methods then fit two multivariable logistic regression models. The first model included main effects for all the variables shown in This study analyzed the data from the 2005 National Health Table 1 and yielded adjusted odds ratios. The second model Interview Survey, a nationally representative, cross-sectional, included the same main effects, as well as interaction terms household survey of the civilian noninstitutionalized popu- for gender by race/ethnicity, gender by weight status, and lation of the United States [12]. race/ethnicity by weight status, which allowed us to assess whether either gender or race/ethnicity modified the associ- 2.1. Participants. NHIS respondents in this study were indi- ation between weight status and CRC screening. All logistic viduals aged 50 to 80 years old [13]. We excluded individuals regression models accounted for the complex sampling who had missing data on weight status and covariates (n = design of the NHIS via appropriate weighting (Proc Surveyl- 6392) as well as underweight (BMI ≤ 18.5) individuals ogistic in SAS 9.2). (n = 108). Based on an NHIS recoded variable, we selected those individuals who self-identified as white (non- Hispanic), black, or Hispanic. 3. Results and Discussion The sampling plan follows a multistage area probability 3.1. Results. The final sample included 7,088 individuals. design that permits the representative sampling of house- Overall, CRC screening was up to date in approximately holds and noninstitutional group quarters (e.g., college dor- 56% of respondents. Weighted CRC screening rates among mitories) and oversamples of blacks, Hispanics, and Asians. NHIS respondents were as follows: white males (58%), white This complex survey design allows for population estimates females (58%), black males (44%), black females (48%), of the United States [12]. Hispanic males (39%), and Hispanic females (37%). Table 1 presents several known predictors of CRC screen- 2.2. Dependent Variables ing including both the unadjusted analysis and the anal- 2.2.1. Colorectal Cancer Screening. We examined the self- ysis adjusted for main effects only. In the adjusted anal- reported variables related to endoscopy and stool blood yses, demographic variables significantly associated with Journal of Obesity 3 Table 1: Colorectal cancer screening according to selected covariates (n = 7088). Variable CRC screening rate (weighted) Unadjusted odds ratio [CI ] Adjusted odds ratio [CI ] 95 95 Overall 55.8 Weight status Normal weight 56.3 Overweight 55.7 0.97 [0.86–1.11] 1.00 [0.84–1.21] Obese 55.5 0.98 [0.85–1.12] 0.91 [0.75–1.12] Gender Female 55.7 0.99 [0.89–1.10] 0.86 [0.73–1.02] Male 56.0 Race Hispanic 38.2 Black 46.1 1.38 [1.06–1.81] 1.26 [0.87–1.82] White 58.5 2.28 [1.85–2.80] 1.25 [0.96–1.63] Age 50–59 47.2 60–69 62.7 1.87 [1.67–2.11] 1.69 [1.41–2.02] 70–79 65.0 2.08 [1.79–2.41] 1.71 [1.39–2.10] Marital status Unmarried 51.6 Married 57.5 1.27 [1.15–1.41] 1.02 [0.86–1.20] Education <12 years 44.6 High school graduate 53.3 1.41 [1.21–1.70] 1.03 [0.83–1.28] Some college 55.6 1.56 [1.32–1.84] 1.01 [0.79–1.29] College graduate 65.3 2.33 [1.96–2.78] 1.42 [1.09–1.85] Annual income <20 K 45.0 >20 K 58.0 1.69 [1.48–1.93] 1.31 [1.05–1.63] Regular source of medical care No 28.5 Yes 57.4 3.38 [2.57–4.44] 1.11 [0.78–1.57] Insured No 22.7 Yes 57.9 3.78 [3.02–4.73] 1.57 [1.16–2.14] Office visits in last year None 24.4 One 43.3 2.37 [1.78–3.16] 1.21 [0.83–1.77] 2–5 visits 58.4 4.35 [3.39–5.59] 1.60 [1.14–2.27] ≥6 visits 64.9 5.74 [4.44–7.42] 2.05 [1.42–2.96] Physician recommendation Yes 81.9 43.49 [36.82–51.36] 36.97 [31.18–43.84] No 9.4 Health status Fair/Poor 56.5 Excellent/Good 52.8 1.16 [1.01–1.33] 1.12 [0.91–1.38] Comorbidities 0 43.7 1 55.3 1.60 [1.38–1.85] 1.18 [0.94–1.48] 2-3 62.4 2.14 [1.85–2.48] 1.28 [0.99–1.65] 4-5 62.3 2.13 [1.73–2.62] 1.20 [0.85–1.70] 6 or more 73.4 3.55 [2.29–5.53] 2.28 [1.14–4.56] 4 Journal of Obesity Table 1: Continued. Variable CRC screening rate (weighted) Unadjusted odds ratio [CI ] Adjusted odds ratio [CI ] 95 95 Personal history cancer ever No 69.3 Yes 53.5 1.96 [1.67–2.30] 1.15 [0.92–1.43] Alcohol consumption Heavy 51.6 Light 59.1 1.23 [0.93–1.63] 1.01 [0.72–1.41] None 54.0 0.91 [0.69–1.20] 1.03 [0.73–1.45] Smoke Current 55.0 Former 62.6 2.28 [1.93–2.70] 1.27 [1.03–1.58] Never 42.4 1.67 [1.43–1.94] 1.26 [1.03–1.54] Recreational physical activity (METS) None/unable to exercise 48.1 <675 59.4 1.58 [1.39–1.79] 0.97 [0.81–1.17] ≥675 69.9 1.84 [1.61–2.09] 1.19 [0.98–1.44] Reference category Adjusted for all covariates listed in first column Recoded from NHIS data, has a usual place of care which is not the emergency room Saw physician in last 12 months and received a recommendation for either colonoscopy or endoscopy Heavy ≥14 drinks/week, light = 1–14 drinks/week increased screening included age greater than 60, college isolates the relationship of weight and CRC screening from education, and higher income. Access variables positively multiple known predictors and examines this relationship associated with CRC screening included being insured and more comprehensively by incorporating race, gender, and increasing number of doctor visits in the last year. A strong ethnicity. Other work using smaller datasets may have been association between physician recommendation and a CRC unable to account for all potential covariates, and only very screening was observed (OR 36.97, P< 0.001). large datasets could accommodate a subgroup analysis such as this. Access to care is strongly associated with CRC screen- Obesity was categorized further as obesity class I, II, ing. The strength of the association of physician recom- and III, and there was no effect (data not shown). This mendation and CRC screening is striking and may indicate classification could not be carried through in subgroups due that physician recommendation is necessary for screening. to sample size. We also examined endoscopy and FOBT The literature indicates that this effect appears to persist as separate outcomes and found no differences (data not regardless of race and gender [9]. More work is needed shown). to understand barriers and predictors of physician recom- Table 2 addresses the hypothesis of this study and shows mendation in subgroups who are at risk for not being the multivariable model for the relationship of weight status screened. and CRC which adjusted for the covariates in Table 1 as Findings presented here may be directly compared to well as interactions between weight status with gender a recent analysis which also examined the relationship of and race/ethnicity. There were no significant associations obesity and CRC screening in the NHIS 2005 data set [10]. In between weight status and CRC screening in Hispanic men, contrast to our findings, these authors found that obese white Hispanic women, black men, black women, white men, and women were less likely to screen. Our analysis is distinct white women, with the gender by weight status and race/ in several ways. First, we included any individual who had ethnicity by weight status interactions not significant (P = complete data for either the set of questions for FOBT or 0.512 and 0.654, resp.). for endoscopy. So, for example, individuals who were up to date on endoscopy were counted as up to date for colorectal 3.2. Discussion. Obese and overweight individuals are as cancer screening, regardless of missing data on FOBT and likely to receive CRC screening as their normal weight peers vice versa. While this is not the convention in handling of regardless of gender, race, or Hispanic ethnicity. This finding missing data, the population that would have been excluded contradicts other literature which suggests a relationship from our analysis (if we required complete data for both between weight status and CRC screening. This study agrees sets of questions) was distinct in screening behavior and with the recent analysis of Chang et al., who found no several known predictors of screening. Second, we separated evidence that obese or overweight patients were less likely to Hispanics from the white and black subgroups. We believed receive recommended care, including CRC screening, when that this group warranted separate consideration because of compared with their normal weight peers [11]. Our model the low rate of screening in Hispanics and the relative lack Journal of Obesity 5 Table 2: Adjusted model for colorectal cancer screening according analysis of our subgroups. Although all cells met the NHIS to race/gender and ethnicity (n = 7088). suggested requirements (less than 30% standard error), the wide confidence intervals suggest that sample size may have CRC Adjusted 95% confidence Weight status been a restriction in groups such as Hispanics. Additionally, screening rate odds ratios interval we could not examine subclasses of obesity (i.e., obesity I, II, Stratum specific III) in our groups of interest due to sample size. for race/gender CRC screening reduces mortality and prevents colorectal White males cancer. However, rates of screening are unacceptably low 58.6 (n = 2491) overall and in minority subgroups. The rising prevalence of Normal 59.7 1.00 obesity and the higher burden of cancer risk in obese individ- Overweight 57.9 0.90 0.68–1.18 uals make this an especially important population subgroup Obese 59.0 0.83 0.61–1.13 in terms of race/ethnicity, gender, and other characteristics. Black males 43.8 (n = 392) 4. Conclusions Normal 45.5 1.00 Overweight 44.2 1.07 0.62–1.85 There is no relationship between increasing weight and Obese 42.1 1.06 0.56–2.02 CRC screening in this nationally representative sample. Regardless of the lack of association of obesity and CRC Hispanic males 39.4 (n = 323) screening, obesity remains a risk factor for increased mor- bidity/mortality related to CRC. Therefore, future work is Normal 37.6 1.00 needed to understand and mitigate risk in the obese pop- Overweight 35.0 0.71 0.37–1.37 ulation especially as this group comes to represent an ever- Obese 52.1 0.97 0.47–2.03 increasing percentage of the US population. White females 58.3 (n = 2955) Normal 58.3 1.00 References Overweight 59.9 1.11 0.84–1.46 [1] American Cancer Society, “Cancer facts and figures 2011,” vol. Obese 56.5 0.91 0.68–1.21 2011, 2011. Black females [2] American Cancer Society, “Cancer prevention and early de- 48.0 (n = 496) tection facts and figures 2010,” vol. 2011, 2011. [3] American Cancer Society, “Cancer prevention and early Normal 36.2 1.00 detection facts and figures 2011,” vol. 2011, 2011. Overweight 53.6 1.32 0.75–2.31 [4] N. Cossrow and B. Falkner, “Race/ethnic issues in obesity and Obese 48.1 1.16 0.64–2.10 obesity-related comorbidities,” Journal of Clinical Endocrinol- Hispanic females ogy and Metabolism, vol. 89, no. 6, pp. 2590–2594, 2004. 37.1 (n = 431) [5] P. Gordon-Larsen, L. S. Adair, and B. M. Popkin, “The rela- Normal 32.6 1.00 tionship of ethnicity, socioeconomic factors, and overweight in U.S. adolescents,” Obesity Research, vol. 11, no. 1, pp. 121– Overweight 34.6 0.88 0.47–1.64 129, 2003, Erratum appears in Obesity Research, vol. 11, no. 4, Obese 43.3 1.06 0.54–2.10 p. 597, 2003. Adjusted for all variables in Table 1, as well as interaction terms of race, [6] A. Chao, C. J. Connell, V. Cokkinides, E. J. Jacobs, E. E. Calle, gender, and Hispanic ethnicity. and M. J. Thun, “Underuse of screening sigmoidoscopy and colonoscopy in a large cohort of US adults,” American Journal of Public Health, vol. 94, no. 10, pp. 1775–1781, 2004. of literature on barriers to screening in this group. Also, our [7] A. B. Rosen and E. C. Schneider, “Colorectal cancer screening analysis reports on men. Finally, this analysis is distinct in disparities related to obesity and gender,” Journal of General that it isolates the overweight group from the normal weight Internal Medicine, vol. 19, no. 4, pp. 332–338, 2004. group. Table 2 supports this decision and shows that the [8] M. Heo, D. B. Allison, and K. R. Fontaine, “Overweight, obe- sity, and colorectal cancer screening: disparity between men rate of CRC screening in overweight individuals is distinct and women,” BMC Public Health, vol. 4, article 53, 2004. from both the normal weight group and the obese group in [9] C.C.Wee,E.P.McCarthy, andR.S.Phillips,“Factorsassoci- several of our subgroups. For example, the rate of screening ated with colon cancer screening: the role of patient factors in overweight black females is 54%, compared to 36% in and physician counseling,” Preventive Medicine, vol. 41, no. normal weight black females and 48% in obese black females. 1, pp. 23–29, 2005. Black females do not see themselves as overweight until a [10] L. A. Leone, M. K. Campbell,J.A.Satia,J.M.Bowling,and M. higher BMI, compared to their white counterparts, and this P. Pignone, “Race moderates the relationship between obesity may explain the difference between overweight and obese and colorectal cancer screening in women,” Cancer Causes and [15]. Control, vol. 21, no. 3, pp. 373–385, 2010. The cross-sectional design of our study precludes deter- [11] V. W. Chang, D. A. Asch, and R. M. Werner, “Quality of care mination of cause. BMI and CRC screening are self-reported among obese patients,” Journal of the American Medical As- and therefore may be distorted. Sample size is a challenge in sociation, vol. 303, no. 13, pp. 1274–1281, 2010. 6 Journal of Obesity [12] Centers for Disease Control and Prevention (CDC), “National health interview survey (NHIS)—description,” vol. 2011, [13] American Cancer Society, “American cancer society guidelines for the early detection of cancer,” vol. 2011, 2011. [14] Centers for Disease Control and Prevention (CDC), “About BMI for adults,” vol. 2011, 2011. [15] L. A. Anderson,A.A.Eyler,D.A.Galuska,D.R.Brown,and R. C. Brownson, “Relationship of satisfaction with body size and trying to lose weight in a national survey of overweight and obese women aged 40 and older, United States,” Preventive Medicine, vol. 35, no. 4, pp. 390–396, 2002. 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