Risk Factors for Diabetic Retinopathy - Diabetes Care - American ...

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isk Factors for Diabetic Retinopathy: A Populatioii'Based Study in Rochester, Minnesota

D. J. BALLARD, MD, L. J. MELTON III, MD, M. S. DWYER, MD, J. C. TRAUTMANN, MD, C.-P. CHU, MS, W. M. O'FALLON, PhD, AND P. J. PALUMBO, MD

Retinopathy is an important sequela of diabetes mellitus, but clinical risk factors for this condition have rarely been assessed in a geographically defined population. In this population-based study, the 1135 Rochester, Minnesota, residents with diabetes mellitus initially diagnosed between 1945 and 1969 (incidence cohort) were followed through their complete medical records in the community to January 1, 1982. Because most of the cases of diabetic retinopathy in Rochester residents developed in patients with non-insulin-dependent diabetes mellitus (NIDDM), risk factors for diabetic retinopathy were examined in this group (N = 1031). A proportional hazards model identified the following risk factors for diabetic retinopathy in NIDDM: elevated initial fasting blood glucose level, marked obesity, and earlier age at onset of diabetes. Stratified analyses indicated that duration of diabetes was also significantly associated with an increased risk of retinopathy. Two secular trends, increasing detection of "mild" NIDDM and decreasing risk of diabetic retinopathy, had a major effect on retinopathy risk assessment. These data also suggest that insulin therapy is not an independent risk factor for diabetic retinopathy. DIABETES CARE 1986; 9:334-42.

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n an earlier report we1 documented the incidence and estimated the prevalence of retinopathy in a large cohort of Rochester, Minnesota, residents initially diagnosed with diabetes mellitus in the period 1945-1969. We noted that the incidence rates for any diabetic retinopathy and for proliferative retinopathy alone were greater among patients with insulin-dependent diabetes mellitus (IDDM) than with non-insulin-dependent diabetes mellitus (NIDDM), although the latter group accounted for a larger actual number of cases of diabetic retinopathy. The influence of other factors on the risk of retinopathy was not addressed. The objective of our investigation was to examine in a population-based incidence cohort of diabetic individuals the relationship between various clinical characteristics at the time of initial diagnosis of diabetes and the risk of subsequent diabetic retinopathy. METHODS

The population of Rochester, Minnesota, is well suited for investigations into the natural history of diabetes mellitus because comprehensive unit medical records for the residents are available and because these records are accessible through

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a centralized index of diagnoses made by essentially all medical care providers utilized by the local population. This index includes the diagnoses made among outpatients seen in clinic and office consultations, emergency room visits, house calls, and nursing home care, as well as diagnoses recorded among hospital inpatients and at death. The potential of this data system for population-based studies has been described previously.2'3 The original medical records of the patients identified through the index were retrieved and reviewed for an initial diagnosis of diabetes in the 25-yr period 1945-1969. The diagnostic criteria used for diabetes mellitus have been reported in detail previously4 and required fasting hyperglycemia on two deteminations >120 mg/dl (Folin-Wu method) for 1945-1958 or > 110 mg/dl (autoanalyzer ferrocyanide reductase technique) for 1959-1969 on whole venous blood. Blood glucose values from other institutions where Rochester patients sought medical care were interpreted in light of the method being employed. An oral glucose tolerance test was generally carried out when an equivocal fasting or postprandial blood glucose determination was obtained. At the Mayo Clinic the oral glucose tolerance test was performed by administering 1 g glucose/k body wt and determining blood glucose concentrations at 0, 1, 2, and 3 h after the loading

DIABETES CARE, VOL. 9 NO. 4, JULY-AUGUST 1986

RISK FACTORS FOR DIABETIC RETINOPATHY/D. J. BALLARD AND ASSOCIATES

%

N

Yo

N

37 63

10 17

50 50

501 503

nonproliferative, maculopathy, or proliferative types. Nonproliferative retinopathy included microaneurysms, dot and flame hemorrhages, and soft and hard exudates. Maculopathy was defined as nonproliferative retinopathy causing a marked loss of visual acuity due to edema of the macula and was recorded only if specifically diagnosed. Proliferative retinopathy included neovascularization of the disc and elsewhere, and vitreous hemorrhage believed due to diabetic neovascularization. Most eye examinations included a specific diagnosis of the type of retinopathy, if present, that was found. In instances where no actual diagnosis was made by the ex-

0 11 11 33 44

0 3 3 9 12

3 18 25 28 26

26 180 253 282 263

TABLE 2 Incidence density of retinopathy by clinical characteristics of Rochester, Minnesota, residents at time of diagnosis of NIDDM, 1945-1969, followed for retinopathy to 1982

8 41 52 89

2 11 14 24

9 25 66 78

85 253 666 785

15 19 33 33 37 4 59 15

4 5 9 9 10 1 16 4

9 28 33 30 26 8 45 30

86 283 335 300 257 83 453 302

37 30 33

10 8 9

14 14 73

139 136 729

TABLE 1 Clinical characteristics of Rochester, Minnesota, residents with* and withoutt retinopathy at time of diagnosis of NIDDM, 1945-1969

Retinopathy at diagnosis Characteristic Sex Men Women Age (yr) 70 Fasting blood glucose (mg/dl) >300 200-299 160/95 mmHg or was on antihypertensive drug therapy at diagnosis of diabetes. Patients were also classified as smokers or nonsmokers as of the date of diagnosis of diabetes. The cumulative incidence of retinopathy was calculated with the Kaplan-Meier product limit method.9 Cumulative incidence curves were compared with the Peto-Peto Wilcoxon test statistic.10 Retinopathy incidence density was determined by person-years analysis." The statistical significance of differences in cumulative incidence and in incidence rates was assessed with the method of Fleiss12 and with the Armitage Test for Linear Trend.13 The relative influence of various clinical characteristics on the risk of subsequent ret' inopathy was evaluated with proportional hazards models,1415 with x2-tests for the coefficients of the proportional hazards models and for the model likelihood ratio. RESULTS

Clinical characteristics at diagnosis of diabetes. The clinical char-

acteristics at the time of initial diagnosis of NIDDM are shown in Table 1. Only 27 of 1031 (2.6%) NIDDM patients had retinopathy diagnosed before or within 30 days of initial diagnosis of diabetes. Although the low prevalence of diabetic retinopathy at diagnosis of diabetes precludes a rigorous comparison, NIDDM patients with retinopathy at diagnosis of diabetes were: more likely to be female (P = .19), older (P = .13), more like to have higher fasting blood glucose levels (P = .19), more likely to have glycosuria (P = .19), more likely to have macrovascular disease (P = . 18) or hypertension (P = .16), less likely to be smokers (P = .22), and more likely to be placed on insulin as initial therapy (P < .01). Univariate analyses. To determine the influence of these various factors on the risk of subsequent retinopathy, we first



TABLE 4 Cumulative incidence (%) of retinopathy at various periods of follow-up by clinical characteristics of Rochester, Minnesota, residents at time of diagnosis of NIDDM, 1945-1969, followed for retinopathy to 1982 Duration of follow-up (yr) Proliferative retinopathy

Any retinopathy Characteristic Sex Men Women Age (yr)

300 200-299 9 5 % had at least one such funduscopic examination by a consultant ophthalmologist in addition to examinations by their primary care physicians. Additionally, if detection bias was a major factor in this study, one would expect an increasing retinopathy risk due to increasing awareness on the part of ophthalmologists of an elevated risk of retinopathy in diabetic individuals. 27 There are, however, many potential confounding variables that could influence the secular trend of decreasing retinopathy risk that we cannot assess, such as the influence of improved blood glucose and blood pressure control and possible, though unlikely, decreasing sensitivity of ophthalmologic examinations. Although it is not possible to definitively address the actual magnitude of potential detection bias in this retrospective cohort study, it seems improbable that any such bias totally accounted for the relationships that we observed between five factors (fasting blood glucose level, age at diagnosis, relative weight at diagnosis, year of diagnosis, duration of diabetes) and retinopathy risk. Finally, loss to follow-up and emigration are extremely unlikely to have distorted our findings, because 704 of the 1004 NIDDM patients in the cohort were followed until death, whereas the median length of follow-up for the 241 survivors who remained in the community was 18 yr and for the 59 survivors who emigrated from Rochester was 16 yr. Our findings indicate that major advances in the prevention of diabetic retinopathy in the population will have to be concerned primarily with NIDDM individuals. Patients who appear to be at greatest risk for this untoward outcome are those < 6 0 yr of age at diagnosis of diabetes who have fasting blood glucose levels > 2 0 0 mg/dl and who are markedly obese. Whereas we cannot recommend a specific time interval for screening NIDDM individuals for retinopathy, newly diagnosed patients without the risk factors identified in this study have a 10-yr cumulative retinopathy risk of < 1 0 % , compared with 40% for high-risk patients. However, by 20 yr duration, cumulative retinopathy risk is > 2 0 % , even in the low-risk groups and > 6 0 % in the high-risk groups, and approaches 40% overall. As we have discussed, the diabetes literature is comprised almost exclusively of prevalence studies, in which antecedent characteristics cannot be distinguished from consequent findings. 27 To more accurately interpret the results of these prevalence studies, we are now conducting a study of the risk factors for the prevalence of diabetic retinopathy, which we will compare with the results from this incidence study. ACKNOWLEDGMENTS: We thank Kay Hurless for computer programming and Mary Ramaker for assistance in preparing the manuscript. This investigation was supported in part by research grants from the American Diabetes Association, the National Institutes of Health (AM-30582), and the Juvenile Diabetes Foundation International (JDF-#5).

From the Department of Medical Statistics and Epidemiology (D.J.B., L.J.M., M.S.D., C.-P.C, W.M.O.), Department of Ophthalmology (J.C.T.), and Division of Endocrinology, Department of Internal Medicine (P.J.P.), Mayo Clinic and Mayo Foundation, Rochester, Minnesota 55905. Send reprint requests to Dr. Melton at the above address. REFERENCES 1 Dwyer, M. S., Melton, L. J., Ill, Ballard, D. J., Palumbo, P. J., Trautmann, J. C , and Chu, C.-P.: Incidence of diabetic retinopathy and blindness: a population-based study in Rochester, Minnesota. Diabetes Care 1985; 8:316-22. 2 Kurland, L. T., Elveback, L. R., andNobrega, E T.: Population studies in Rochester and Olmsted County, Minnesota, 1900-1968. In The Community as an Epidemiologic Laboratory: A Casebook of Community Studies. Kessler, I. I., and Levin, M. L., Eds. Baltimore, The Johns Hopkins Univ. Press, 1970:47-70. 3 Kurland, L. T , and Molgaard, C. A.: The patient record in epidemiology. Sci. Am. 1981; 245:54-63. 4 Palumbo, P. J., Elveback, L. R., Chu, C.-P, Connolly, D. C , and Kurland, L. T : Diabetes mellitus: incidence prevalence, survivorship, and causes of death in Rochester, Minnesota, 1945-1970. Diabetes 1976; 25:566-73. 5 National Diabetes Data Group: Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes 1979; 28:1039-57. 6 Melton L. J., Ill, Palumbo, P. J., Dwyer, M. W., and Chu, C. -P.: Impact of recent changes in diagnostic criteria on the apparent natural history of diabetes mellitus. Am. J. Epidemiol. 1983; 117:55965. 7 West, K. M.: Epidemiology of Diabetes and Its Vascular Lesions. New York, Elsevier/North-Holland, 1978:403-28. 8 Melton, L. J., Ill, Palumbo, P. J., and Chu, C.-P: Incidence of diabetes mellitus by clinical type. Diabetes Care 1983; 6:75-86. 9 Kaplan, E. L., and Meier, P.: Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 1958; 53:457— 81. 10 Peto, R., and Peto, J.: Asymptotically efficient rank invariant test procedures (with discussion). J. R. Stat. Soc. Ser. A 1972; 135:185-206. 11 Kleinbaum, D. G., Kupper, L. L , and Morgenstern, H.: Epidemiologic research: principles and quantitative methods. Belmont, CA, Lifetime Learning Publications, 1982:96-116. 12 Fleiss, J. L.: Statistical Methods for Rates and Proportions, 2nd ed. New York, Wiley, 1981. 13 Armitage, P.: Tests for linear trends in proportions and frequencies. Biometrics 1955; 11:375-86. 14 Cox, D. R.: Regression models and life-tables (with discussion). J. R. Stat. Soc. Ser. B 1972; 34:187-202. 15 Harrell, F. E.: The PHGLM Procedure. SAS Supplemental Library. Cary, NC, SAS Inst., 1983:267-9416 Klein, R., Klein, B. E. K., Moss, S. E., Davis, M. D., and DeMets, D. L.: The Wisconsin epidemiology study of diabetic retinopathy. II. Prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years. Arch. Ophthalmol. 1984; 102:520— 26. 17 Klein, R., Klein, B. E. K., Moss, S. E., Davis, M. D., and DeMets, D. L.: The Wisconsin epidemiologic study of diabetic retinopathy. III. Prevalence and risk of diabetic retinopathy when age at diagnosis is 30 or more years. Arch. Ophthalmol. 1984; 102:527— 32.


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