Public Health Bnefs
cally Mentally Ill Veterans Program was funded by the US Department of Veterans Affairs. This paper is based on presentations at the annual meeting ofthe Society for Traumatic Stress Studies, San Francisco, CA, October25, 1989, and the annual meeting of the American Psychiatric Association, New York, NY, May 15, 1990.
References 1. Farr RK, Koegel P, Bumam A: A Study of Homelessness and Mental Illness in the Skid Row Area of Los Angeles. Los Angeles, CA: Los Angeles County Department of Mental Health, 1986. 2. Gelberg L, Linn LS, Leake: Mental health, alcohol and drug use and criminal history among homeless adults. Am J Psychiatry 1988; 145:191-196.
3. Streuning EL, Pittman J, Rosenblatt A: Characteristics of homeless veterans in the New York City shelter system. In: Rosenblatt A (ed): Homelessness. Albany, NY: Rockefeller Institute of Government (in press). 4. Department of Veteran Affairs: Annual Report 1987. Washington DC: Department of Veterans Affairs, 1989. 5. Laufer R, Frey Wouters E, Yager T: Postwar trauma, social and psychological problems of Vietnam veterans in the aftermath of the Vietnam War. In: Legacies of Vietnam, Comparative Adjustment of Veterans and Their Peers. Washington DC: US Govt Printing Office, 1981. 6. Kulka R, Schlenger W, Fairbank J, Hough R, Jordan B, Marmar C, Weiss D: National
7.
8. 9.
10.
Vietnam Veterans Readjustment Study. Research Triangle Park, NC: Research Triangle Institute, 1988. Rossi P: Down and Out in America, The Causes of Homelessness. Chicago, IL: University of Chicago Press, 1989. Department of Veteran Affairs: 1987 Survey of Veterans. Washington DC: Department of Veterans Affairs, 1989. Myths and Realities: A Study of Attitudes toward Vietnam Era Veterans. Report submitted by the Veterans Administration to the Committee on Veterans Affairs, US Senate, Washington, DC, 1980. Lifton RJ: Home from the War: Vietnam Veterans, Neither Victims nor Executioners. New York: Simon and Schuster, 1973.
Determinants of Late Stage Diagnosis of Breast and Cervical Cancer: The Impact of Age, Race, Social Class, and Hospital Type ...
"
"I'l-,"M 1'.1-K-'l,--,-3,l'l'l"
0
L
- -- - X-MML..I.
'U
%?:,-ee-
Jeanne Mandelblatt, MD, Howard Andrews, PhD, Jon Kemer, PhD, Ann Zauber, PhD, and Wdliam Bumetu, MD
Intrwoducton Age and race have each individually been associated with cancer stage.1-5 However, previous studies have not controlled for the effects of social class and health care setting. This paper presents findings from logistic regression analyses to quantify the individual and combined effects of age, race, socioeconomic class, and type of health care setting on breast and cervical cancer stage.
Metods Cancer Data-Tumor Registry The study sample consisted of all cases of breast and cervical cancer among New York City (NYC) residents that were
reported to the New York State Department of Health Tumor Registry between 1980 and 1985. More than 90 percent of incident cases are reported to the registry from NYC.6 In the study period, there were 22,111 breast cancer, 2,930 invasive cervical cancer, and 6,408 cervical carcinoma in-situ cases with known stages reported. Stage was unknown for 7.5 percent and 2.6 percent of the breast and cervical cases, respectively. Missing stage
was associated with age (p < .0001) and missing marital status (p < .01) for both cancers. Age was classified into five-year categories. Race was reported as either Black or White. There were insufficient data to include Hispanic origin in the analysis. Marital status was dichotomized as "ever"1 versus "never" married. Hospital type was classed as "public" for the 11 NYC municipal hospitals and "non-public" for the remaining facilities.
Demographic Vanables-Census Data Because individual information on socioeconomic class is not available in registry data, 1980 United States census Address reprint requests to Jeanne Mandelblatt, MD, Assistant Professor, Division of Cancer Control, Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, Box 60, 1275 York Avenue, New York, NY 10021. Drs. Kerner and Zauber are also with that Department at the Cancer Center; Dr. Andrews is with New York State Psychiatric Institute, New York City; Dr. Burnett is Director, Tumor Registry, New York State Department of Health, Albany. This paper, submitted to the Journal July 12, 1990, was revised and accepted for publication December 5, 1990.
May 1991, Vol. 81, No. 5
Public Health Briefs
first model predicted the outcome of late stage (regional and distant) compared to early stage (localized and in-situ). As a result of recent advances in the treatment of regional disease, a second model was developed comparing distant to regional disease. For cervical cancer, the outcome of the first model was late stage (regional and distant) versus early stage (localized) invasive cancer. In addition, invasive and in-situ disease were compared in a second model as a measure of the success of Pap screening. For all models the independent variables were age, race, marital status, hospital type, income, and education. Logistic regression models were developed using SAS programs. Table 1 presents summary statistics for the cases included in the models.
Results
data on the median family income and the percent of adults with a high school education in the census tract of residence of the case were used as social class measures.
May 1991, Vol. 81, No. 5
Logistic Regression Models Two models were developed for each cancer based on groupings with similar treatment patterns. For breast cancer, the
The logistic regression analysis indicated that, controlling for the other variables, the following factors were associated with late stage breast cancer: postmenopausal age, Black race, low education, and public hospital use (Table 2). Lower income was also weakly associated with late stage (p < .055). In the second model, age, public hospital use, marital status, and low education were each associated with an increased risk of distant disease. Regression coefficients and intercepts from each model were used to calculate the odds of late stage disease for combinations of variables (Table 3). For example, the odds of having distant, compared to regional, breast cancer were 4.77 times higher for a Black woman who was age 70 to 74, unmarried, in the lowest income and education groups, andwho used the public hospital system, compared to a White married woman age 40 to 44, in the highest income and education groups, using a non-public hospital. For invasive cervical cancer, age and public hospital setting were each associated with an increased risk of late stage disease (Table 4). In the second model, age, race, hospital setting, income, and education were each associated with invasive disease. The composite odds of a 70 to 74 year old, unmarried Blackwoman in the lowest income and educational group who used the public hospital system having late stage invasive cervical cancer were 2.54 times greater than for a White, married, 40 to 44 year old woman in the highest income and educational levels and using a non-public hospital (Table 5). The odds for
American Journal of Public Health 647
Public Health Bnefs
have the potential to decrease avoidable cancer morbidity and mortality. O
Acknowledgments The authors would like to thank the New York City Health and Hospitals Corporation for their support of earlier versions of this project. Portions of this paper were presented at the American Public Health Association 116th Annual Meeting, October 19, 1989, Chicago, Illinois.
References
a woman of the same profile having invasive compared to in-situ disease were 39.75 times higher than for her younger, White, non-disadvantaged counterpart.
Discussion This study demonstrates that elderly, Black, lower socioeconomic status (SES) women who use public hospitals are at extremely high risk of having their breast and cervical cancers diagnosed at late stages. While our findings are consistent with and extend the findings of prior researchers,1-5 there are two caveats that should be considered in evaluating our conclusions. First, in our analysis missing stage was associated with age. However, since older women with advanced disease are less likely to be staged than younger women,7,8 the missing stage information is likely to underestimate the observed effect of age on stage.
648 American Journal of Public Health
Second, since the NY State Tumor Registiy does not contain social class indicators, we assigned to each woman the median income and educational level of her community of residence. While we have no way to determine the relationship of the individual and community SES indicators, several studies of cancer incidence and/or mortality have used grouplevel data to define socioeconomic status9-15 and have drawn similar conclusions to studies that use individual information.16-19 Group data can also capture characteristics of the individual's social "context" which may provide information about class gradients that may not be reflected by individual characteristics.20'21 It is possible that hospital type is serving as such a "contextual" measure in our analysis. Our findings suggest that cancer control interventions targeted to elderly disadvantaged women, particularly those of color and those who use public hospitals,
1. Horm JW, Astire AJ, Young JL, Poilack ES: Cancer Incidence and Mortality in the United States. SEER 1973-81. NIH Pub. No. 85-1837, Bethesda, MD: NIH, 1985. 2. Holmes FF, Hearne E: Cancer stage-to age relationship: Implications for cancer screening in the elderly. J Am Geriatr Soc 1981; 29:55-57. 3. Goodwin JS, Samet JM, Key CR, Humble C, Kutvirt D, Hunt C: Stage at diagnosis of cancer varies with the age of the patient. JAGS 1986; 34:20-26. 4. Freeman HP, Wasfie TJ: Cancer of the breast in poor black women. Cancer 1989; 63:2562-2569. 5. Polednak AP: Breast cancer in Black and White women in New York State. Case distribution and incidence rates by clinical stage at diagnosis. Cancer 1986; 58:807815. 6. Bumett W: Cancer incidence and mortality by county: New York State. Albany: New York State Dept of Health, 1982. 7. Samet J, Hunt WC, Key C, Humble CG, Goodwin JS: Choice ofcancer therapyvaries with age of patient. JAMA 1986; 255:3385-3390. 8. Chu J, Diehr P, Feigl P, Glaetke G, Begg C, Clickson A, et al: The effect of age on care of women with breast cancer in community hospitals. J Gerontol 1987; 42:185-189. 9. Clementsen J, Nielsen A: The social distribution of cancer in Copenhagen, 1943 to 1947. Br J Cancer 1951; 5:159-171. 10. Cohart EM: Socioeconomic distribution of cancer of the female sex organs in New Haven. Cancer 1955; 8:34-41. 11. Dorn HF, Cutler SJ: Morbidity from cancer in the United States: Parts I and II. Public Health Monogr 1959; 56:1-287. 12. Graham S, Levin M, Lilienfeld AM: The socioeconomic distribution of cancer of various sites in Buffalo, NY, 1948-52. Cancer 1960; 13:180-191. 13. Seidman H: Cancer death rates by site and sex for religious and socioeconomic groups in New York City. Environ Res 1970; 3:234-250. 14. Hoover R, Manson TJ, McKay FW, Fraumeni JF Jr: Geographic patterns of cancer mortality in the United States. In: Fraumeni JF Jr (ed): Persons at High Risk of Cancer-An Approach to Cancer Etiology and Control. New York: Academic Press, 1975; 343-360. 15. Dayal HH, Power RN, Chiu C: Race and social economic status in survival from breast cancer. J Chronic Dis 1970; 23:105116.
May 1991, Vol. 81, No. 5
Public Health Bnefs 16. Logan WP: Social class variations in mortality. Public Health Rep 1954; 69:12171223. 17. The Registrar General's decennial supplement, England and Wales, 1961: Occupational mortality tables. London: His Majesty's Stationery Office, 1971. 18. The Registrar General's decennial supplement, England and Wales, 1970-72: Occupational mortality. Series D, No. 1. London: Her Majesty's Stationery Office, 1978. 19. Lilienfeld AM, Levin ML, Kessler II: Cancer in the United States. Cambridge, MA: Harvard University Press, 1972. 20. KriegerN: Race, class, and health: Studies of breast cancer and hypertension; Doctoral dissertation, University of CaliforniaBerkeley, 1989. 21. Bassett T, Krieger N: Social class and Black-White differences in breast cancer survival. Am J Public Health 1986; 76:1400-1403.
May 1991, Vol. 81, No. 5
American Journal of Public Health 649
cally Mentally Ill Veterans Program was funded by the US Department of Veterans Affairs. This paper is based on presentations at the annual meeting ofthe Society for Traumatic Stress Studies, San Francisco, CA, October25, 1989, and the annual meeting of the American Psychiatric Association, New York, NY, May 15, 1990.
References 1. Farr RK, Koegel P, Bumam A: A Study of Homelessness and Mental Illness in the Skid Row Area of Los Angeles. Los Angeles, CA: Los Angeles County Department of Mental Health, 1986. 2. Gelberg L, Linn LS, Leake: Mental health, alcohol and drug use and criminal history among homeless adults. Am J Psychiatry 1988; 145:191-196.
3. Streuning EL, Pittman J, Rosenblatt A: Characteristics of homeless veterans in the New York City shelter system. In: Rosenblatt A (ed): Homelessness. Albany, NY: Rockefeller Institute of Government (in press). 4. Department of Veteran Affairs: Annual Report 1987. Washington DC: Department of Veterans Affairs, 1989. 5. Laufer R, Frey Wouters E, Yager T: Postwar trauma, social and psychological problems of Vietnam veterans in the aftermath of the Vietnam War. In: Legacies of Vietnam, Comparative Adjustment of Veterans and Their Peers. Washington DC: US Govt Printing Office, 1981. 6. Kulka R, Schlenger W, Fairbank J, Hough R, Jordan B, Marmar C, Weiss D: National
7.
8. 9.
10.
Vietnam Veterans Readjustment Study. Research Triangle Park, NC: Research Triangle Institute, 1988. Rossi P: Down and Out in America, The Causes of Homelessness. Chicago, IL: University of Chicago Press, 1989. Department of Veteran Affairs: 1987 Survey of Veterans. Washington DC: Department of Veterans Affairs, 1989. Myths and Realities: A Study of Attitudes toward Vietnam Era Veterans. Report submitted by the Veterans Administration to the Committee on Veterans Affairs, US Senate, Washington, DC, 1980. Lifton RJ: Home from the War: Vietnam Veterans, Neither Victims nor Executioners. New York: Simon and Schuster, 1973.
Determinants of Late Stage Diagnosis of Breast and Cervical Cancer: The Impact of Age, Race, Social Class, and Hospital Type ...
"
"I'l-,"M 1'.1-K-'l,--,-3,l'l'l"
0
L
- -- - X-MML..I.
'U
%?:,-ee-
Jeanne Mandelblatt, MD, Howard Andrews, PhD, Jon Kemer, PhD, Ann Zauber, PhD, and Wdliam Bumetu, MD
Intrwoducton Age and race have each individually been associated with cancer stage.1-5 However, previous studies have not controlled for the effects of social class and health care setting. This paper presents findings from logistic regression analyses to quantify the individual and combined effects of age, race, socioeconomic class, and type of health care setting on breast and cervical cancer stage.
Metods Cancer Data-Tumor Registry The study sample consisted of all cases of breast and cervical cancer among New York City (NYC) residents that were
reported to the New York State Department of Health Tumor Registry between 1980 and 1985. More than 90 percent of incident cases are reported to the registry from NYC.6 In the study period, there were 22,111 breast cancer, 2,930 invasive cervical cancer, and 6,408 cervical carcinoma in-situ cases with known stages reported. Stage was unknown for 7.5 percent and 2.6 percent of the breast and cervical cases, respectively. Missing stage
was associated with age (p < .0001) and missing marital status (p < .01) for both cancers. Age was classified into five-year categories. Race was reported as either Black or White. There were insufficient data to include Hispanic origin in the analysis. Marital status was dichotomized as "ever"1 versus "never" married. Hospital type was classed as "public" for the 11 NYC municipal hospitals and "non-public" for the remaining facilities.
Demographic Vanables-Census Data Because individual information on socioeconomic class is not available in registry data, 1980 United States census Address reprint requests to Jeanne Mandelblatt, MD, Assistant Professor, Division of Cancer Control, Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, Box 60, 1275 York Avenue, New York, NY 10021. Drs. Kerner and Zauber are also with that Department at the Cancer Center; Dr. Andrews is with New York State Psychiatric Institute, New York City; Dr. Burnett is Director, Tumor Registry, New York State Department of Health, Albany. This paper, submitted to the Journal July 12, 1990, was revised and accepted for publication December 5, 1990.
May 1991, Vol. 81, No. 5
Public Health Briefs
first model predicted the outcome of late stage (regional and distant) compared to early stage (localized and in-situ). As a result of recent advances in the treatment of regional disease, a second model was developed comparing distant to regional disease. For cervical cancer, the outcome of the first model was late stage (regional and distant) versus early stage (localized) invasive cancer. In addition, invasive and in-situ disease were compared in a second model as a measure of the success of Pap screening. For all models the independent variables were age, race, marital status, hospital type, income, and education. Logistic regression models were developed using SAS programs. Table 1 presents summary statistics for the cases included in the models.
Results
data on the median family income and the percent of adults with a high school education in the census tract of residence of the case were used as social class measures.
May 1991, Vol. 81, No. 5
Logistic Regression Models Two models were developed for each cancer based on groupings with similar treatment patterns. For breast cancer, the
The logistic regression analysis indicated that, controlling for the other variables, the following factors were associated with late stage breast cancer: postmenopausal age, Black race, low education, and public hospital use (Table 2). Lower income was also weakly associated with late stage (p < .055). In the second model, age, public hospital use, marital status, and low education were each associated with an increased risk of distant disease. Regression coefficients and intercepts from each model were used to calculate the odds of late stage disease for combinations of variables (Table 3). For example, the odds of having distant, compared to regional, breast cancer were 4.77 times higher for a Black woman who was age 70 to 74, unmarried, in the lowest income and education groups, andwho used the public hospital system, compared to a White married woman age 40 to 44, in the highest income and education groups, using a non-public hospital. For invasive cervical cancer, age and public hospital setting were each associated with an increased risk of late stage disease (Table 4). In the second model, age, race, hospital setting, income, and education were each associated with invasive disease. The composite odds of a 70 to 74 year old, unmarried Blackwoman in the lowest income and educational group who used the public hospital system having late stage invasive cervical cancer were 2.54 times greater than for a White, married, 40 to 44 year old woman in the highest income and educational levels and using a non-public hospital (Table 5). The odds for
American Journal of Public Health 647
Public Health Bnefs
have the potential to decrease avoidable cancer morbidity and mortality. O
Acknowledgments The authors would like to thank the New York City Health and Hospitals Corporation for their support of earlier versions of this project. Portions of this paper were presented at the American Public Health Association 116th Annual Meeting, October 19, 1989, Chicago, Illinois.
References
a woman of the same profile having invasive compared to in-situ disease were 39.75 times higher than for her younger, White, non-disadvantaged counterpart.
Discussion This study demonstrates that elderly, Black, lower socioeconomic status (SES) women who use public hospitals are at extremely high risk of having their breast and cervical cancers diagnosed at late stages. While our findings are consistent with and extend the findings of prior researchers,1-5 there are two caveats that should be considered in evaluating our conclusions. First, in our analysis missing stage was associated with age. However, since older women with advanced disease are less likely to be staged than younger women,7,8 the missing stage information is likely to underestimate the observed effect of age on stage.
648 American Journal of Public Health
Second, since the NY State Tumor Registiy does not contain social class indicators, we assigned to each woman the median income and educational level of her community of residence. While we have no way to determine the relationship of the individual and community SES indicators, several studies of cancer incidence and/or mortality have used grouplevel data to define socioeconomic status9-15 and have drawn similar conclusions to studies that use individual information.16-19 Group data can also capture characteristics of the individual's social "context" which may provide information about class gradients that may not be reflected by individual characteristics.20'21 It is possible that hospital type is serving as such a "contextual" measure in our analysis. Our findings suggest that cancer control interventions targeted to elderly disadvantaged women, particularly those of color and those who use public hospitals,
1. Horm JW, Astire AJ, Young JL, Poilack ES: Cancer Incidence and Mortality in the United States. SEER 1973-81. NIH Pub. No. 85-1837, Bethesda, MD: NIH, 1985. 2. Holmes FF, Hearne E: Cancer stage-to age relationship: Implications for cancer screening in the elderly. J Am Geriatr Soc 1981; 29:55-57. 3. Goodwin JS, Samet JM, Key CR, Humble C, Kutvirt D, Hunt C: Stage at diagnosis of cancer varies with the age of the patient. JAGS 1986; 34:20-26. 4. Freeman HP, Wasfie TJ: Cancer of the breast in poor black women. Cancer 1989; 63:2562-2569. 5. Polednak AP: Breast cancer in Black and White women in New York State. Case distribution and incidence rates by clinical stage at diagnosis. Cancer 1986; 58:807815. 6. Bumett W: Cancer incidence and mortality by county: New York State. Albany: New York State Dept of Health, 1982. 7. Samet J, Hunt WC, Key C, Humble CG, Goodwin JS: Choice ofcancer therapyvaries with age of patient. JAMA 1986; 255:3385-3390. 8. Chu J, Diehr P, Feigl P, Glaetke G, Begg C, Clickson A, et al: The effect of age on care of women with breast cancer in community hospitals. J Gerontol 1987; 42:185-189. 9. Clementsen J, Nielsen A: The social distribution of cancer in Copenhagen, 1943 to 1947. Br J Cancer 1951; 5:159-171. 10. Cohart EM: Socioeconomic distribution of cancer of the female sex organs in New Haven. Cancer 1955; 8:34-41. 11. Dorn HF, Cutler SJ: Morbidity from cancer in the United States: Parts I and II. Public Health Monogr 1959; 56:1-287. 12. Graham S, Levin M, Lilienfeld AM: The socioeconomic distribution of cancer of various sites in Buffalo, NY, 1948-52. Cancer 1960; 13:180-191. 13. Seidman H: Cancer death rates by site and sex for religious and socioeconomic groups in New York City. Environ Res 1970; 3:234-250. 14. Hoover R, Manson TJ, McKay FW, Fraumeni JF Jr: Geographic patterns of cancer mortality in the United States. In: Fraumeni JF Jr (ed): Persons at High Risk of Cancer-An Approach to Cancer Etiology and Control. New York: Academic Press, 1975; 343-360. 15. Dayal HH, Power RN, Chiu C: Race and social economic status in survival from breast cancer. J Chronic Dis 1970; 23:105116.
May 1991, Vol. 81, No. 5
Public Health Bnefs 16. Logan WP: Social class variations in mortality. Public Health Rep 1954; 69:12171223. 17. The Registrar General's decennial supplement, England and Wales, 1961: Occupational mortality tables. London: His Majesty's Stationery Office, 1971. 18. The Registrar General's decennial supplement, England and Wales, 1970-72: Occupational mortality. Series D, No. 1. London: Her Majesty's Stationery Office, 1978. 19. Lilienfeld AM, Levin ML, Kessler II: Cancer in the United States. Cambridge, MA: Harvard University Press, 1972. 20. KriegerN: Race, class, and health: Studies of breast cancer and hypertension; Doctoral dissertation, University of CaliforniaBerkeley, 1989. 21. Bassett T, Krieger N: Social class and Black-White differences in breast cancer survival. Am J Public Health 1986; 76:1400-1403.
May 1991, Vol. 81, No. 5
American Journal of Public Health 649
