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Previous work has established a surprisingly high prevalence of acanthosis nigricans (AN) and its association with increased risk of type 2 diabetes in a Southwestern practice-based research network (PBRN). Our objective was to establish whether this high AN prevalence would be present in other areas.
We examined prevalence of type 2 diabetes and its risk factors and of AN among patients ages 7–65 seen by one of 86 participating clinicians in a national PBRN consortium, during a one-week data collection period. In a sub-sample of non-diabetic matched pairs with and without AN, we compared fasting glucose, insulin, and lipids.
AN was present in 19.4% of 1730 patients, including all age ranges studied. AN was most prevalent among persons with more diabetes risk factors. Patients with AN were twice as likely as those without AN to have type 2 diabetes (35.4% vs. 17.6%, p<.001). In multivariable analysis, the prevalence ratio for diabetes was 2.1 (95% CI = 1.3–3.5) in non-Hispanic whites with AN and 1.4 (95% CI = 1.1–1.7) in minority patients with AN. In a sub-sample of 11 matched pairs, those with AN had higher insulin and insulin resistance.
We found high rates of AN in primary care practices across the country. Patients with AN likely have multiple diabetes risk factors and are more likely to have diabetes.
The landmark Diabetes Prevention Program study demonstrated that lifestyle interventions can prevent or delay the onset of type 2 diabetes by as much as 58%.(1) These results underline the importance of early identification of patients at high risk for development of diabetes so that lifestyle modification can be attempted. Traditionally, identification of high risk patients has been based on risk factors such as family history, overweight or obesity, and minority ethnicity. However, in areas where these risk factors have high prevalence, they may not be effective in eliciting action to prevent diabetes. (2)
More recently, attention has turned to acanthosis nigricans (AN) as a possible marker of increased risk for development of diabetes. AN, a dermatologic condition characterized by hyperpigmentation, hyperkeratosis and papillomatosis, has been shown in many cases to be associated with hyperinsulinemia (Figure 1).(3–9) Typical areas of involvement include the posterior neck, the axilla, the elbows, and the knees, with the neck being involved 93–99% of the time when AN is present.(10, 11)
AN offers an intriguing possibility for motivating lifestyle change. In populations where many patients have a family history of diabetes, are overweight or obese, and/or are of minority descent, the value of these traditional risk factors in promoting lifestyle modification is uncertain. Because they are quite common and because they have no clear temporal or immediate relationship to the development of diabetes, their effectiveness in motivating behavior change is not clear. A readily apparent, rapidly identifiable physical examination marker identifying patients at increased risk for type 2 diabetes, such as AN, might help to stimulate discussions of lifestyle modifications in the primary care setting, as anecdotal reports have suggested.(2, 12) Since AN may improve with lifestyle changes leading to reduction in insulin levels, it also may potentially enhance motivation for change.(12)
Previous work established a surprisingly high prevalence of AN, and that it is an independent risk factor for type 2 diabetes among patients in a Southwestern practice-based research network (PBRN).(12) Young persons aged 7–39 were found to have an overall AN prevalence of 19.2%, including 17% in children. In this sample of largely Hispanic and Native American persons, AN was associated with an increased risk of having diabetes, independent of age, body mass index, and number of traditional risk factors. Because this previous work was conducted in only one state and among a somewhat restricted population, and because other reports of AN prevalence have used similarly restricted samples (3–9, 13), we conducted a study to explore the prevalence of AN more broadly across a large multiethnic, national PBRN consortium.
We conducted a cross-sectional study of the prevalence of traditional diabetes risk factors and of AN among persons aged 7–65 years presenting for primary care. In addition, in a matched sub-sample of these primary care patients with and without AN, we explored the association of AN with insulin resistance, fasting hyperglycemia, and lipid levels. Institutional review boards at each of the participating networks’ sponsoring institutions approved the study protocol.
The study was conducted in PRIME Net (PRImary care MultiEthnic Network), a national consortium of 8 PBRNs that focuses on research addressing the health and health care of medically underserved populations (http://hsc.unm.edu/som/primenet/). The 8 networks include: Research Involving Outpatients Settings Network (RIOS Net – New Mexico); Colorado Area Research Network (CaReNet – Colorado); Southeast Regional Clinicians Network (SERCN – 11 Southeastern states); Southern Primary Care Urban Network (SPUR-Net – Houston); Collaborative Research Network (CRN – Northern California); Southwestern Ohio Area Research Network (SOAR-Net – Southwestern Ohio); Metro-Net (Detroit); and LA-Net (Los Angeles). The clinician members of these networks are located in urban, suburban and rural settings and the patient populations seen in these practices present with patterns of diagnoses typical of primary care.(14) Four of the networks – RIOS Net, CaReNet, SPUR-Net, and SERCN – participated in this study.
We recruited clinicians from each of the four networks through a combination of electronic messaging and personal contacts.
Each participating clinician gathered data on all patients aged 7–65 years, presenting for care during a one week equivalent data collection period (if a clinician was unavailable during part of the planned data collection week, the data collection period was extended to adjust for the unavailability). The age range was selected to assure the sample reflected: 1) insulin resistance increases with puberty, and 2) peak incident cases of type 2 diabetes. We excluded patients if they were pregnant, acutely ill, or unable to give informed consent for participation. For patients who declined to participate or were not eligible, the clinician or research assistant used a non-participation log to indicate which of several possible reasons led to non-participation.
Clinicians used either a personal digital assistant (PDA) running PenDragon® Forms software or paper data collection forms at the time of the patient encounter to record data regarding history relevant to diabetes risk, biophysical parameters, and presence of AN. History items queried included family history of diabetes and personal history of diabetes, hypertension, and hyperlipidemia. Clinicians recorded height and weight routinely taken as part of the patient’s visit for calculation of BMI status. All patient data were collected, stored and analyzed anonymously. Prior to finalizing the data collection instrument, we piloted it among a group of 8 clinicians (none of whom participated in subsequent data collection). The final data collection instrument is available at: http://hsc.unm.edu/som/primenet/an_instruments.shtml.
Prior to beginning data collection, each participating clinician completed training on AN that focused on assuring valid diagnosis of AN in patients to be enrolled in the study.(15) The web-based training module included information about AN (appearance, classification, usual anatomic locations of the lesions, association with metabolic parameters, possible management strategies following diagnosis of AN) and a number of photographs of AN. Following the didactic portion of the module, clinicians completed an assessment of their understanding of AN, including diagnosing 10 photographs as either AN or not AN. (The complete training and assessment module can be viewed at http://hsc.unm.edu/som/primenet/an_cme.shtml.) To assure accurate diagnosis of AN, each clinician was required to score 100% on the assessment before beginning data collection. If a clinician scored less than this standard, s/he reviewed errors and retook the assessment. Each participating clinician received CME credit for the training.
In addition, we provided each clinician a manual of written protocols, on-site initial training by study research coordinators in study procedures, and telephone consultation with the coordinators. In some cases, the research coordinators assisted in obtaining patient consent/assent. As a participation incentive, clinicians kept the PDAs used in the study, after data were removed.
We selected a subsample of patients for further study, including patients with AN randomly sampled from the parent study and then matched to comparison patients without AN. The subsample of patients was aged 22–65 years, with and without AN, and matched for gender, age range, ethnicity/race, and body mass index range, and had given prior recontact permission through a written consent process. With patient consent, we drew samples for fasting glucose, insulin levels, lipids, and free fatty acids from these subjects, and measured their blood pressure and waist circumference using standard approaches to these measurements. We excluded diabetic patients and patients taking steroid medication or medication for treatment of hypertension, diabetes or impaired glucose tolerance, or dyslipidemia from this phase of the study. Recalled patients received $50 for their participation in this portion of the study.
We transmitted data via secure internet connections to a central server in Albuquerque, exported them into an Excel worksheet, and analyzed them using SAS version 9.1.3. We calculated descriptive statistics, including frequency distributions, for all variables. Bivariate relationships of AN to the following variables were evaluated: age; gender; ethnicity/race; family history of diabetes; personal history of T2DM, hypertension, dyslipidemia; and BMI status. Responses of “don’t know” to the family or personal history variables were set as missing during the analysis. We estimated differences in prevalence of multiple diabetes risks between those with and without AN using the Mantel-Haenszel χ2 test for trend. Log-binomial regression modeling (16) was conducted to determine prevalence ratios for the outcome, T2DM. Analysis showed ethnicity/race to be an effect modifier, so models were calculated separately for non-Hispanic whites and minority ethnicity/race, which included African Americans, Hispanics, and others (Asian or mixed minorities). Final models contain age, gender, family history of T2DM, hypertension, dyslipidemia, AN, and BMI status.
Paired t-tests or Wilcoxon Signed Rank tests, when appropriate, were used to compare glucose, insulin, lipids, and insulin resistance by the homeostasis model assessment (HOMA-IR) between those with and without AN.
Eighty six clinicians (20 from RIOS Net, 30 from Spur-Net, 14 from CaReNet, and 22 from SERCN) contributed patient data to the study. Clinicians in the study were primarily in Family Practice (72%), with the remainder in General Internal Medicine or Pediatrics. Seventy-eight percent were MD/DOs, while physician assistants/nurse practitioners made up the rest of the sample. Spur-Net clinicians used paper-based data collection; all other networks used the PDAs for data collection. These clinicians reported on encounters with a total of 2,264 patients, of whom 244 either declined participation or were not solicited (e.g, as a result of being acutely ill). Of the remaining 2,020 patients, 290 were subsequently dropped from the analysis due to incomplete data or eligibility reasons, leaving a total of 1,730 patients for analysis. Table 1 shows that these patients represented a full spectrum of ages. [Table 1 about here] Reflecting the nature of primary care patient populations, they were predominantly female, and more commonly middle-aged and older. Approximately 70% were from a minority group, consistent with the makeup of the PRIME Net consortium. Two hundred and six of the patients (12%) were from CaReNet, 406 (23%) were from RIOS Net, 372 (22%) were from SERCN, and 746 (43%) were from Spur-Net.
Tables 2 and and33 [Table 2 about here] display our findings with regard to prevalence of diabetes and its risk factors and of acanthosis nigricans, stratified by age and ethnicity. Twenty-one percent of these patients seen in primary care had a diagnosis of T2DM, with expected variation by age and ethnicity. We found high prevalence rates of family history of diabetes (63.7% of all the persons in the sample), of overweight or obesity (74.8 % of the sample), and of hypertension (39.3% of the sample) and dyslipidemia (37.7%) (Table 3). [Table 3 about here.] These overall rates of hypertension and dyslipidemia were high despite the fact that among children in the sample these conditions were almost absent. Prevalence of overweight/obesity also showed age variation, but even among children the prevalence was 49%. On the other hand, AN, which was present in 19.4% of the sample, was equally prevalent among all ages, including children, 18.2% of whom had AN. Rates of AN were lower among non-Hispanic whites (p<0.001).
We also evaluated differences by sex for the prevalence of diabetes and of risk factors listed in Tables 2 and and3.3. After adjusting for multiple comparisons, we found there were no significant differences by sex (data not presented).
When we examined the relationship of presence of AN to the number of risk factors for diabetes present in a patient, we found a trend toward higher prevalence of AN with greater number of diabetes risk factors (Mantel-Haenszel p<0.001). The rate of AN was 22.0% among those with three T2DM risk factors, 28.1% among those with four risk factors, and 38.1% among those with five risk factors. The relationship of presence of AN and number of risk factors for diabetes was strongest in the 20–39 years age group. (Table 4) [Table 4 about here] Patient sex was not a significant predictor in this relationship.
We found that among all patients combined T2DM was significantly more likely to be present in a patient with AN (35% of whom had T2DM) than in patients without AN, 18% of whom had T2DM (p<0.001). (Table 5) [Table 5 about here] This relationship held true across all race/ethnic groups, with prevalence rate ratios varying from 1.49 in Hispanic persons to 3.58 in non-Hispanic whites for prevalence of T2DM in those with, compared with those without AN. There were no significant differences by sex.
Using log-binomial regression analysis, we studied the relationship of T2DM prevalence among adults to each of several predictor variables (T2DM risk factors, age, gender, AN), while controlling for the presence of all the other predictor variables. (Table 6) [Table 6 about here] In the overall sample of adults, older age, male gender, family history of diabetes, hypertension, and dyslipidemia were each found to be independent risk factors for presence of T2DM. While BMI grouping is highly significantly associated with prevalence of T2DM in univariate analysis, it did not emerge as a significant predictor in multivariate analysis, where the variance was explained by other variables with which BMI grouping was associated. Stratification by race/ethnicity resulted in some differences in significant relationships from the overall group. Age in non-Hispanic whites and male gender in both subgroups did not reach significant differences, likely due to reduced sample size of the subgroups (possible type 2 error).
AN was a statistically significant independent predictor of presence of T2DM for the sample as a whole and for each of the ethnicity groupings. Of note, the prevalence ratio was greater for non-Hispanic whites (2.10) than for persons of minority ethnicity (1.47).
Eleven matched pairs of patients with and without AN provided fasting blood samples for further analysis. Table 7 [Table 7 about here] shows that only measures of fasting insulin and insulin resistance approached statistically significant association with AN (significance level, .005 after Bonferroni correction for multiple comparisons). Measures of lipids, glucose, waist circumference, and blood pressure were not associated with AN. None of the other biological parameters examined approached statistical significance.
We found an alarming prevalence of acanthosis nigricans across all primary care population groups studied. The prevalence was highest among members of minority groups, and included the entire age spectrum studied, from 7–65 years old. However, even among non-Hispanic white persons, the overall prevalence was 6%. While the exact relationship of AN to diabetes is not yet fully understood, its association with hyperinsulinemia – both in our subsample and in published literature – suggests the possibility that the growing epidemic of diabetes could be on the verge of a dramatic turn for the worse among the groups represented in our sample. The consistency of our results across the geographic regions participating in the study emphasize the importance and generalizability of those results.
In addition to the high prevalence of AN, our study had several key findings:
Together these findings underline the emerging importance of AN in patient care. The relationships between AN and diabetes and between AN and a diabetes precursor condition – hyperinsulinemia and insulin resistance – establish the opportunity to use this visible marker of diabetes risk in diabetes case identification and preventive counseling. Earlier publications suggest that both of these actions (case identification and preventive counseling) are enhanced by the diagnosis of AN.(2,12)
An unexplained finding in our study was the lower prevalence of AN among non-Hispanic whites in our sample. In a companion publication (15), we noted that our participating clinicians initially had greater difficulty diagnosing AN in fair-skinned persons, though with training this difficulty resolved. It is possible that classification bias may have led to underestimation of the rate of AN in non-Hispanic white persons, but this seems unlikely to explain the full difference in rates observed. Other studies have reported similarly lower rates of AN (3.1 – 4.2%) among non-Hispanic whites. (12,13)
Our findings of high prevalence of AN are consistent with the results of an earlier study showing comparable rates of AN among a large sample of Hispanic and Native American persons in New Mexico.(12) The high prevalence of AN among children in both studies is notable. Other studies have documented comparable rates of AN among African American, Hispanic, Native American, and non-Hispanic white children in Chicago primary care practices(13) and in New Mexico middle schools.(6) The current study, with a sample drawn from four geographic regions, establishes that high prevalence of AN is not unique to limited areas.
Investigators have begun to explore the relationship of AN to biophysical and metabolic parameters. While some of these studies have used selected samples (e.g., obese children, single Native American tribe, etc.), all have found a relationship to high levels of insulin, as we did.(3, 4, 6–9, 17–20) Unlike our findings, some studies have also shown a relationship to triglyceride level, though this relationship does not appear to have been subjected to multivariable regression analysis to control for the relationship between insulin and triglyceride levels.(19, 20)
The composite picture created by our study and those previously published suggests that future research in this area should now focus on the natural history of AN as a precursor for T2DM in primary care populations. What can clinicians tell the patient who does not have T2DM, but has AN, with regard to the probability of future development of diabetes (particularly those patients with standard risk factors, such as a positive family history)? What will the time course be from development of AN to onset of diabetes? More work is needed to test the value of treating hyperinsulinemia with either lifestyle modification or pharmaceuticals in patients with AN.(21, 22) In addition, following reports of impacts of AN diagnosis on diabetes case identification and preventive counseling, further research is needed to document these observations and to explore methods for maximizing the effect of AN diagnosis on either action.
As noted above, classification bias is possible when a variety of examiners identify cases and when the appearance of AN varies somewhat by ethnic/racial group. We took steps to standardize AN diagnosis and to assure clinician ability to correctly diagnose AN (AN web-based training), and it therefore seems unlikely that any such bias would have resulted in substantial misestimation of AN rates. Our PBRN consortium focuses on medically underserved communities and over represents minority, low-income persons. These primary care practices see high rates of patients with risk factors for chronic diseases and are therefore useful laboratories to study issues related to disease prevention.(23) However, it is possible that rates of AN in other communities and populations may differ from those we have observed. It is also important to recall that our sample, having been drawn from primary care, may not validly reflect rates of AN in the broader population. However, Mukhtar and colleagues (6) demonstrated similar rates of AN in a largely Hispanic, population based sample in New Mexico, suggesting our sample may not differ substantially from the larger population in this regard. Our subsample of 11 matched pairs may have been small enough to lead to a type 2 error in the non-significant biophysical comparisons between the patients with and without AN. However, none of the non-significant comparisons approached significance levels, and our findings were consistent with those published elsewhere (see above), suggesting that our findings were externally valid.
From a geographically diverse sample of primary care patients, this study presents consistent evidence of high rates of AN and of the association of AN with risk of diabetes and with hyperinsulinemia and insulin resistance. Because AN is a rapidly identifiable marker of risk of diabetes, its presence provides primary care clinicians with a new tool for diabetes case identification and preventive counseling. Further work is needed to clarify the relationship of AN to subsequent development of diabetes and its prevention.
The authors express their appreciation to the clinicians and patients of the PRIME Net networks, who willingly gave their time to participate in this project. The authors also appreciate the key contributions to the study made by Toye Metoyer; Sherry Holcomb; Douglas Fernald, MA; Anthony Adams; Viola Benavidez; Angela N. Cortez; and Javan Quintela. WORD COUNT: 3362
FUNDING SOURCES: This project was funded in whole or in part with Federal funds from the National Institutes of Health, under Contract No. HHSN268200425211C, "Re-Engineering the Clinical Research Enterprise” and from Grant No. D54HP00032-07-00 from the Health Resources and Services Administration.
CONFLICT OF INTEREST: All authors state that they have no potential, perceived, or real competing and/or conflicts of interest.
The published version of this article can be accessed on the Journal of the American Board of Family Medicine website at: http://jabfm.org/cgi/reprint/23/4/476