Published Online: November 07, 2011
Andy I. Choi, MD, MAS; Andrew J. Karter, PhD; Jennifer Y. Liu, MPH; Bessie A. Young, MD, MPH; Alan S. Go, MD; and Dean Schillinger, MD
Objectives: To determine whether ethnic differences in the incidence of albuminuria are present in patients with diabetes, and to identify social, behavioral, and provider factors that explain ethnic differences.
Study Design: Survey follow-up design with a race-stratified baseline survey (2005-2006) in diabetic patients from a nonprofit, fully integrated healthcare system in Northern California. We followed the 10,596 respondents (30% whites, 20% blacks, 23% Hispanics, 14% Asians, and 13% Filipinos) without evidence of prevalent albuminuria at baseline.
Methods: Incident albuminuria was defined by positive dipstick urinalysis (>1) or urine albumin to creatinine level (>30 mg/g), and confirmed with repeat testing at least 3 months later.
Results: The 27,292 person-years of observation yielded 981 incident albuminuria events. Agestandardized rates of albuminuria (per 1000 person-years) ranged from 13.6 (95% confidence interval [CI] 10.5-17.0) in whites to 27.8 (CI 18.2- 38.3) in blacks. In fully adjusted Cox models, the hazard ratio for blacks (1.22, 95% CI 1.09-1.38), Asians (1.35, 95% CI 1.13-1.61), and Filipinos (1.93, 95% CI 1.61-2.32), but not Hispanics, was significantly greater than it was for whites. In some cases, point estimates changed markedly from the base model when fully adjusted for potential confounders. Moreover, adjustment for an array of potentially mediating factors explained only a small proportion of the observed ethnic disparities.
Conclusions: Despite uniform medical care coverage, Filipinos, blacks, and Asians with diabetes developed albuminuria at higher rates than white and Hispanic adults.
(Am J Manag Care. 2011;17(11):737-745)
Despite uniform medical care coverage, Filipinos, blacks, and Asians with diabetes developed albuminuria at higher rates than whites.
After adjustment for confounding, the incidence of albuminuria was 93% greater in Filipinos, 35% greater in Asians, and 22% higher in blacks compared with whites; the difference between Hispanics and whites was not significant.
Racial differences were not explained by a wide range of potentially mediating factors.
Albuminuria is a potent predictor of future microvascular and macrovascular complications; thus, these findings have clinical implications for risk stratification and future efforts to reduce ethnic disparities in renal disease.
Diabetes afflicts 8% of the US population, and its prevalence is expected to double over the next 2 decades.1 Diabetes is at least 2 to 4 times more common among ethnic minorities than it is among non-Hispanic whites.2 Furthermore, minorities have higher mortality rates and microvascular complications of diabetes, such as end-stage renal disease (ESRD).3 Collectively, these statistics have placed diabetes at the center of the president’s Healthy People 2020 initiative to eliminate health disparities.4
Albuminuria is an extremely common consequence of diabetes, with a prevalence of 30% to 50%.5 Microalbuminuria and macroalbuminuria are strongly associated with angiographically determined coronary atherosclerosis, cardiovascular events, kidney failure, and mortality in patients with diabetes, as well as in the general population, independent of conventional cardiovascular risk factors and the estimated glomerular filtration rate (eGFR).6,7 Although the natural history of diabetic nephropathy is relatively well described, prior studies have rarely examined ethnic variations in the development of albuminuria or identified factors that may explain ethnic differences in the risk of incident albuminuria. The majority of work in this field has focused on ESRD, for which ethnic disparities are established. 3 However, ESRD patients represent less than 1% of the diabetic population; therefore, strategies targeting ESRD are limited to a small subset of patients.8 Understanding ethnic differences in rates of albuminuria and the underlying causes for these differences is likely to advance public health objectives for diabetes treatment, because albuminuria is very common and is strongly associated with adverse events, and kidney disease is the complication of diabetes with the greatest effect on minority groups.3,7
We conducted a prospective, longitudinal cohort study to evaluate ethnic differences in incident albuminuria in a fully insured, ethnically diverse, well-characterized cohort of diabetic patients. Our secondary goal was to identify social, behavioral, and provider-level factors that could explain observed ethnic differences in albuminuria in this population.
MATERIALS AND METHODS
The Diabetes Study of Northern California (DISTANCE) is a National Institute of Diabetes and Digestive and Kidney Diseases– sponsored study of diabetes conducted at Kaiser Permanente Northern California (Kaiser).9 This nonprofit, integrated group practice provides comprehensive healthcare to an ethnically diverse population of more than 3 million people, approximately 30% of the population of Northern California. The DISTANCE cohort comprised an ethnically stratified, random sample of diabetic patients (type 1 and type 2) receiving care from Kaiser. In 2005 to 2006, participants of DISTANCE completed a detailed assessment of demographic, clinical, behavioral, socioeconomic, psychosocial, medical knowledge, and quality of care indicators (62% survey response rate). The complete survey is available at www.distancesurvey.org. The survey was offered in multiple languages including English, Spanish, Cantonese, Mandarin, and Tagalog using certified translations of an English script, and through multiple modalities, including computer-assisted telephone interview, self-administered written format, and the Internet, to maximize accessibility of the survey.
Survey data were supplemented with clinical information from the Kaiser electronic medical record that comprehensively captures inpatient and outpatient utilization, laboratory testing, clinical measurements (blood pressure, height, and weight), pharmacy data (including prescribed medications and filled prescriptions), processes of care, procedures, and diagnoses. Patient data are linked to the California Death Registry to ascertain death information and the United States Renal Data System for ESRD status.8 Neighborhood socioeconomic status was determined by linkage of participant residential addresses with the year 2000 US Census data at the census-tract level.
We included all DISTANCE participants who self-identified their ethnicity as white (non-Hispanic), black (non-Hispanic), Hispanic, Asian, or Filipino. All individuals entered the study at the time of survey (index date). We excluded (1) participants belonging to other ethnic groups, those who were multiethnic, or those with missing ethnicity; (2) those without continuous membership at Kaiser (allowing <3 months’ gap); (3) individuals with prevalent albuminuria, defined as microalbuminuria measured on any urine dipstick testing (>1) or urine albumin to creatinine ratio (>30 mg/g) within 2 years prior to the index date; (4) patients with ESRD (defined as receipt of chronic dialysis therapy or kidney transplantation)10; and (5) participants who did not have an additional measurement of albuminuria (urinary albumin excretion or urine dipstick testing) after the index date.
The primary outcome for the analysis was time from study entry to incident albuminuria. Albuminuria was defined according to National Kidney Foundation guidelines as having urinary albumin excretion levels at or above the threshold for “microalbuminuria” (>1 on dipstick testing or >30 mg/g on urine albumin to creatinine ratio testing), confirmed on a second consecutive occasion at least 3 months later. The first positive urine test result was used at the date of censor (ie, microalbuminuria incidence date).
Self-reported ethnicity, our primary predictor, was categorized as white, black, Asian, Hispanic, or Filipino. Filipinos were not included in the Asian category given the unique social, cultural, and linguistic characteristics of this group.11 All baseline covariates were derived from the DISTANCE survey or the electronic medical record, using validated algorithms based on laboratory, vital sign, and clinical data closest to the survey date and within the preceding 2 years.3,9,12 We included demographics (age, sex); clinical characteristics (blood pressure, low-density lipoprotein, glycosylated hemoglobin [A1C], body mass index, eGFR); comorbid conditions (hypertension, hyperlipidemia); macrovascular disease (heart failure, coronary heart disease, peripheral vascular disease, or cerebrovascular accident); microvascular disease (retinopathy); diabetes characteristics (diabetes duration, receipt of insulin therapy); and current treatment (angiotensin-converting enzyme inhibitor or angiotensin receptor blocker). We calculated eGFR using the Modification of Diet in Renal Disease formula based on age, sex, race, and standardized serum creatinine.13
We also selected variables that could be potential mediators of ethnic differences in the development of albuminuria based on the Institute of Medicine’s definition of disparities as the difference in treatment or access not justified by the differences in health status or preferences of the groups.14 These included socioeconomic factors (education [highest degree attained], income, and neighborhood deprivation index15); language (limited English proficiency and nativity); behaviors (smoking status [current, never, past], adequate exercise [by self-report], self-monitoring of blood glucose levels, and adherence [oral diabetes medication adherence and antihypertensive adherence over the prior year]); and provider factors (poor provider communication,16 patient/ provider race and sex concordance). The closed pharmacy system at Kaiser provides near-complete ascertainment of pharmacy utilization and facilitates assessment of medication adherence. We also adjusted relevant clinical factors including use of lipid-lowering and antihypertensive medications (and initiation of new treatments during follow-up), change in systolic blood pressure, change in A1C, and a validated index of medication adherence, “Continuous, multiple- interval measure of medication gaps,” which estimates the percentage of days during follow-up without adequate supply of medications.17
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