Letters
Author Contributions: Dr Ford had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Ford, Maynard. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Ford. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Ford. Administrative, technical, or material support: Maynard. Study supervision: Ford. Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. Disclaimer: The findings and conclusions reported in this article are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention. 1. Lean MJ, Han TS. Waist worries. Am J Clin Nutr. 2002;76(4):699-700. 2. NHLBI Obesity Education Initiative Expert Panel on the Indentification, Evaluation, and Treatment of Obesity in Adults. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report. Bethesda, MD: National Heart, Lung, and Blood Institute; 1998. 3. Ford ES, Li C, Zhao G, Tsai J. Trends in obesity and abdominal obesity among adults in the United States from 1999-2008. Int J Obes (Lond). 2011;35(5): 736-743. 4. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. http://www.cdc.gov/nchs/nhanes.htm. Accessed November 21, 2013. 5. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA. 2014;311(8):806-814. 6. Elobeid MA, Desmond RA, Thomas O, Keith SW, Allison DB. Waist circumference values are increasing beyond those expected from BMI increases. Obesity (Silver Spring). 2007;15(10):2380-2383.
COMMENT & RESPONSE
Diabetes Prevalence Among Youth To the Editor The SEARCH investigators assessed the burden of diagnosed diabetes among youth.1 We wish to discuss 2 important limitations of the SEARCH study design. First, the SEARCH study design cannot account for undiagnosed type 2 diabetes and therefore underestimates disease burden. The authors acknowledged this limitation but speculated that the number of cases was small based on only 2 specific citations: the first citation was from a geographically homogenous sample and the second was from a sample of sixth graders, thus underestimating the rates among older adolescents. Alternatively, our recent report2 among a nationally representative sample of adolescents aged 12 to 19 years suggests that 34% of adolescents with type 2 diabetes are undiagnosed. Although this may be an overestimate due to lack of repeat laboratory testing, the results suggest a potentially meaningful burden of undiagnosed type 2 diabetes in adolescents. Second, we disagree with the statement made by Dr Dabelea and colleagues 1 that the populations giving rise to SEARCH diabetes cases “reasonably represented the US population.” Because the authors deemed racial/ethnic and income distributions to be similar between the SEARCH and US populations, the reasoning follows that diabetes rates are also similar and implies that racial- or ethnic-specific rates (and disparities) are constant across regions.
However, structural and societal factors linked to discrimination and stigma can differentially influence racial- or ethnic-specific rates across regions. The implications for the interpretation of the SEARCH results, which are heavily based on samples from the West and Midwest with no Southern representation aside from 4 counties in South Carolina, are important. Without considering the true underlying factors that drive known disparities, crude raceor ethnic-specific analyses should not be generalized to all members of those groups. A national surveillance system for monitoring diabetes among youth that is capable of precisely estimating undiagnosed diabetes and regional variation in rates of total diabetes is needed and would pay long-term dividends for population health. Ryan T. Demmer, PhD, MPH Aleksandra M. Zuk, RN, MPH Michael Rosenbaum, MD Author Affiliations: Department of Epidemiology, Columbia University, New York, New York (Demmer); University of Toronto, Dalla Lana School of Public Health, Toronto, Ontario, Canada (Zuk); Department of Pediatrics, Columbia University, New York, New York (Rosenbaum). Corresponding Author: Ryan T. Demmer, PhD, MPH, Columbia University, Department of Epidemiology, 722 W 168th St, New York, NY 10032 (rtd2106 @columbia.edu). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Rosenbaum reported receiving grant support from the National Center for Advancing Translational Sciences, National Institutes of Health. No other disclosures were reported. Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. 1. Dabelea D, Mayer-Davis EJ, Saydah S, et al; SEARCH for Diabetes in Youth Study. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA. 2014;311(17):1778-1786. 2. Demmer RT, Zuk AM, Rosenbaum M, Desvarieux M. Prevalence of diagnosed and undiagnosed type 2 diabetes mellitus among US adolescents: results from the continuous NHANES, 1999-2010. Am J Epidemiol. 2013;178(7):1106-1113.
In Reply Accurate estimation of the prevalence of childhood diabetes is challenging. Dr Demmer and colleagues raised 2 issues: undiagnosed diabetes and geographic representativeness. The SEARCH study design cannot estimate undiagnosed diabetes and, while not an issue for type 1 diabetes, the SEARCH study design will underestimate total type 2 diabetes burden. We expect this underestimation to be small, based on the only 2 available studies, which were mentioned by Demmer and colleagues. Nevertheless, they represent the only studies of screening that confirmed undiagnosed type 2 diabetes in youth. In the Princeton Study that included 2501 adolescents in grades 5 through 12,1 seven adolescents with “near diabetes” were identified but only 1 was confirmed as having type 2 diabetes, for a true prevalence of 0.04%. In the HEALTHY Study of 6358 children,2 only 1 of 6 youths with elevated fasting glucose was confirmed as having type 2 diabetes, for a true prevalence of 0.02%. These estimates compare with an unweighted prevalence of elevated fasting glucose of
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JAMA September 17, 2014 Volume 312, Number 11
Copyright 2014 American Medical Association. All rights reserved.
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1153
Letters
0.17% in the study using National Health and Nutrition Examination Survey (NHANES) data by Demmer et al.3 Applying the fraction of confirmed to total undiagnosed diabetes from these studies (2/13 = 0.15) to the Demmer et al3 estimate of 0.17%, the prevalence of true undiagnosed diabetes in NHANES is 0.03%, in line with the 2 other studies. A much larger screening effort is required to determine whether the undiagnosed fraction of type 2 diabetes in youths is similar to that seen in adults.4 Geographic areas included in the SEARCH study were not based on random sampling, and although the sites are geographically diverse and capture some of the regional variability in both type 1 and type 2 diabetes risk in US youths,5 it may not be fully representative of this variation at the national level. Although the concern with geographic representativeness is understandable, we believe the SEARCH study captures the majority of potential geographic differences by reporting racial/ethnic prevalence in a study population that is also quite representative of the racial/ ethnic, sex, education, and income distributions in the United States. Demmer and colleagues note that a national surveillance system is needed for monitoring diabetes among youths to precisely estimate undiagnosed diabetes and regional variation in rates of total diabetes. Such a system does not exist and is needed. Although adequate for adults, the ongoing NHANES infrastructure, with a very small sample of 30 youths with type 1 and 28 with type 2 diabetes from 1999-2010,3 is not able to provide geographic, racial/ethnic, or national estimates of trends with much precision. The SEARCH study investigators have spent the last 15 years establishing an alternate infrastructure. Our prevalence estimates are based on more than 6000 patients with diagnosed diabetes identified from a geographically diverse and racially and ethnically representative denominator of approximately 3 million youths. Our conclusion remains that prevalence of both type 1 and type 2 diabetes has increased substantially between 2001 and 2009 and that ongoing research is needed to identify reasons for these trends. Dana Dabelea, MD, PhD Elizabeth J. Mayer-Davis, PhD Author Affiliations: Department of Epidemiology, Colorado School of Public Health, Aurora (Dabelea); Department of Nutrition, University of North Carolina, Chapel Hill (Mayer-Davis). Corresponding Author: Dana Dabelea, MD, PhD, Department of Epidemiology, Colorado School of Public Health, 13001 E 17th Pl, Aurora, CO 80045 ([email protected]). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. 1. Dolan LM, Bean J, D’Alessio D, et al. Frequency of abnormal carbohydrate metabolism and diabetes in a population-based screening of adolescents. J Pediatr. 2005;146(6):751-758. 2. Kaufman FR, Hirst K, Linder B, et al; HEALTHY Study Group. Risk factors for type 2 diabetes in a sixth-grade multiracial cohort: the HEALTHY study. Diabetes Care. 2009;32(5):953-955.
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3. Demmer RT, Zuk AM, Rosenbaum M, Desvarieux M. Prevalence of diagnosed and undiagnosed type 2 diabetes mellitus among US adolescents: results from the continuous NHANES, 1999-2010. Am J Epidemiol. 2013;178(7):1106-1113. 4. Cowie CC, Rust KF, Ford ES, et al. Full accounting of diabetes and pre-diabetes in the US population in 1988-1994 and 2005-2006. Diabetes Care. 2009;32(2):287-294. 5. Liese AD, Lawson A, Song HR, et al. Evaluating geographic variation in type 1 and type 2 diabetes mellitus incidence in youth in four US regions. Health Place. 2010;16(3):547-556.
Recurrence Rates in Autism Spectrum Disorders To the Editor The recent report by Dr Sandin and colleagues1 contributes to a converging body of recent research specifying recurrence rates in autism spectrum disorders (ASD) by analyzing data from a large epidemiological birth cohort in Sweden. The results included a large-scale confirmation that the sex of the proband does not predict familial recurrence risk, indicating that the Carter effect (increased familial recurrence among subsets of cases [eg, females] who have been hypothesized to require higher than usual genetic loading to express the disorder), which was observed for subclinical autistic-like traits in a sample from the United Kingdom and Sweden, 2 may not apply to a majority of clinical autistic syndromes. Another important observation was the lack of a discrepancy in recurrence rates between dizygotic twins and nontwin siblings, tempering concerns raised by previously reported elevations among dizygotic twins that implicated intrauterine environmental factors in autism risk. With regard to heritability, however, both the estimation of total heritability (0.50) and the estimation of nonshared environmental influence (0.50) reported in the study warrant caution because they were based on one of the lower monozygotic twin concordance rates ever reported (tetrachoric correlation of 0.55) and on a relatively small number of clinically affected monozygotic twins (n = 62 total). The correlation was substantially higher when exclusively considering male monozygotic twin pairs (0.70). Sandin et al1 did not separately estimate heritability or nonshared environmental influence for ASD in nontwins or males, the latter particularly relevant given the fact that ASD is 3 times more common in males and there is accumulating evidence that penetrance of many ASD genetic susceptibilities is reduced in females.3 Any extent to which the method of ASD ascertainment led to underrepresentation of the true monozygotic concordance would falsely lower the estimation of heritability and falsely raise the estimation of the influence of nonshared environmental influence. Although Sandin et al1 drew parallels between their results and those of the California Autism Twin Study,4 the respective studies report highly contrasting (essentially incompatible) types of environmental influence; notably, the Swedish study revealed no evidence for the presence of common (shared) environmental influences, which it was well powered to detect. Moreover, regarding its assertion of nonshared environmental influence, the role of de novo mutation (a significant influence on sporadic autism except when involving mono-
JAMA September 17, 2014 Volume 312, Number 11
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a J H Quillen College User on 05/27/2015
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Author Contributions: Dr Ford had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Ford, Maynard. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Ford. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Ford. Administrative, technical, or material support: Maynard. Study supervision: Ford. Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. Disclaimer: The findings and conclusions reported in this article are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention. 1. Lean MJ, Han TS. Waist worries. Am J Clin Nutr. 2002;76(4):699-700. 2. NHLBI Obesity Education Initiative Expert Panel on the Indentification, Evaluation, and Treatment of Obesity in Adults. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report. Bethesda, MD: National Heart, Lung, and Blood Institute; 1998. 3. Ford ES, Li C, Zhao G, Tsai J. Trends in obesity and abdominal obesity among adults in the United States from 1999-2008. Int J Obes (Lond). 2011;35(5): 736-743. 4. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. http://www.cdc.gov/nchs/nhanes.htm. Accessed November 21, 2013. 5. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA. 2014;311(8):806-814. 6. Elobeid MA, Desmond RA, Thomas O, Keith SW, Allison DB. Waist circumference values are increasing beyond those expected from BMI increases. Obesity (Silver Spring). 2007;15(10):2380-2383.
COMMENT & RESPONSE
Diabetes Prevalence Among Youth To the Editor The SEARCH investigators assessed the burden of diagnosed diabetes among youth.1 We wish to discuss 2 important limitations of the SEARCH study design. First, the SEARCH study design cannot account for undiagnosed type 2 diabetes and therefore underestimates disease burden. The authors acknowledged this limitation but speculated that the number of cases was small based on only 2 specific citations: the first citation was from a geographically homogenous sample and the second was from a sample of sixth graders, thus underestimating the rates among older adolescents. Alternatively, our recent report2 among a nationally representative sample of adolescents aged 12 to 19 years suggests that 34% of adolescents with type 2 diabetes are undiagnosed. Although this may be an overestimate due to lack of repeat laboratory testing, the results suggest a potentially meaningful burden of undiagnosed type 2 diabetes in adolescents. Second, we disagree with the statement made by Dr Dabelea and colleagues 1 that the populations giving rise to SEARCH diabetes cases “reasonably represented the US population.” Because the authors deemed racial/ethnic and income distributions to be similar between the SEARCH and US populations, the reasoning follows that diabetes rates are also similar and implies that racial- or ethnic-specific rates (and disparities) are constant across regions.
However, structural and societal factors linked to discrimination and stigma can differentially influence racial- or ethnic-specific rates across regions. The implications for the interpretation of the SEARCH results, which are heavily based on samples from the West and Midwest with no Southern representation aside from 4 counties in South Carolina, are important. Without considering the true underlying factors that drive known disparities, crude raceor ethnic-specific analyses should not be generalized to all members of those groups. A national surveillance system for monitoring diabetes among youth that is capable of precisely estimating undiagnosed diabetes and regional variation in rates of total diabetes is needed and would pay long-term dividends for population health. Ryan T. Demmer, PhD, MPH Aleksandra M. Zuk, RN, MPH Michael Rosenbaum, MD Author Affiliations: Department of Epidemiology, Columbia University, New York, New York (Demmer); University of Toronto, Dalla Lana School of Public Health, Toronto, Ontario, Canada (Zuk); Department of Pediatrics, Columbia University, New York, New York (Rosenbaum). Corresponding Author: Ryan T. Demmer, PhD, MPH, Columbia University, Department of Epidemiology, 722 W 168th St, New York, NY 10032 (rtd2106 @columbia.edu). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Rosenbaum reported receiving grant support from the National Center for Advancing Translational Sciences, National Institutes of Health. No other disclosures were reported. Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. 1. Dabelea D, Mayer-Davis EJ, Saydah S, et al; SEARCH for Diabetes in Youth Study. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA. 2014;311(17):1778-1786. 2. Demmer RT, Zuk AM, Rosenbaum M, Desvarieux M. Prevalence of diagnosed and undiagnosed type 2 diabetes mellitus among US adolescents: results from the continuous NHANES, 1999-2010. Am J Epidemiol. 2013;178(7):1106-1113.
In Reply Accurate estimation of the prevalence of childhood diabetes is challenging. Dr Demmer and colleagues raised 2 issues: undiagnosed diabetes and geographic representativeness. The SEARCH study design cannot estimate undiagnosed diabetes and, while not an issue for type 1 diabetes, the SEARCH study design will underestimate total type 2 diabetes burden. We expect this underestimation to be small, based on the only 2 available studies, which were mentioned by Demmer and colleagues. Nevertheless, they represent the only studies of screening that confirmed undiagnosed type 2 diabetes in youth. In the Princeton Study that included 2501 adolescents in grades 5 through 12,1 seven adolescents with “near diabetes” were identified but only 1 was confirmed as having type 2 diabetes, for a true prevalence of 0.04%. In the HEALTHY Study of 6358 children,2 only 1 of 6 youths with elevated fasting glucose was confirmed as having type 2 diabetes, for a true prevalence of 0.02%. These estimates compare with an unweighted prevalence of elevated fasting glucose of
jama.com
JAMA September 17, 2014 Volume 312, Number 11
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a J H Quillen College User on 05/27/2015
1153
Letters
0.17% in the study using National Health and Nutrition Examination Survey (NHANES) data by Demmer et al.3 Applying the fraction of confirmed to total undiagnosed diabetes from these studies (2/13 = 0.15) to the Demmer et al3 estimate of 0.17%, the prevalence of true undiagnosed diabetes in NHANES is 0.03%, in line with the 2 other studies. A much larger screening effort is required to determine whether the undiagnosed fraction of type 2 diabetes in youths is similar to that seen in adults.4 Geographic areas included in the SEARCH study were not based on random sampling, and although the sites are geographically diverse and capture some of the regional variability in both type 1 and type 2 diabetes risk in US youths,5 it may not be fully representative of this variation at the national level. Although the concern with geographic representativeness is understandable, we believe the SEARCH study captures the majority of potential geographic differences by reporting racial/ethnic prevalence in a study population that is also quite representative of the racial/ ethnic, sex, education, and income distributions in the United States. Demmer and colleagues note that a national surveillance system is needed for monitoring diabetes among youths to precisely estimate undiagnosed diabetes and regional variation in rates of total diabetes. Such a system does not exist and is needed. Although adequate for adults, the ongoing NHANES infrastructure, with a very small sample of 30 youths with type 1 and 28 with type 2 diabetes from 1999-2010,3 is not able to provide geographic, racial/ethnic, or national estimates of trends with much precision. The SEARCH study investigators have spent the last 15 years establishing an alternate infrastructure. Our prevalence estimates are based on more than 6000 patients with diagnosed diabetes identified from a geographically diverse and racially and ethnically representative denominator of approximately 3 million youths. Our conclusion remains that prevalence of both type 1 and type 2 diabetes has increased substantially between 2001 and 2009 and that ongoing research is needed to identify reasons for these trends. Dana Dabelea, MD, PhD Elizabeth J. Mayer-Davis, PhD Author Affiliations: Department of Epidemiology, Colorado School of Public Health, Aurora (Dabelea); Department of Nutrition, University of North Carolina, Chapel Hill (Mayer-Davis). Corresponding Author: Dana Dabelea, MD, PhD, Department of Epidemiology, Colorado School of Public Health, 13001 E 17th Pl, Aurora, CO 80045 ([email protected]). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. 1. Dolan LM, Bean J, D’Alessio D, et al. Frequency of abnormal carbohydrate metabolism and diabetes in a population-based screening of adolescents. J Pediatr. 2005;146(6):751-758. 2. Kaufman FR, Hirst K, Linder B, et al; HEALTHY Study Group. Risk factors for type 2 diabetes in a sixth-grade multiracial cohort: the HEALTHY study. Diabetes Care. 2009;32(5):953-955.
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3. Demmer RT, Zuk AM, Rosenbaum M, Desvarieux M. Prevalence of diagnosed and undiagnosed type 2 diabetes mellitus among US adolescents: results from the continuous NHANES, 1999-2010. Am J Epidemiol. 2013;178(7):1106-1113. 4. Cowie CC, Rust KF, Ford ES, et al. Full accounting of diabetes and pre-diabetes in the US population in 1988-1994 and 2005-2006. Diabetes Care. 2009;32(2):287-294. 5. Liese AD, Lawson A, Song HR, et al. Evaluating geographic variation in type 1 and type 2 diabetes mellitus incidence in youth in four US regions. Health Place. 2010;16(3):547-556.
Recurrence Rates in Autism Spectrum Disorders To the Editor The recent report by Dr Sandin and colleagues1 contributes to a converging body of recent research specifying recurrence rates in autism spectrum disorders (ASD) by analyzing data from a large epidemiological birth cohort in Sweden. The results included a large-scale confirmation that the sex of the proband does not predict familial recurrence risk, indicating that the Carter effect (increased familial recurrence among subsets of cases [eg, females] who have been hypothesized to require higher than usual genetic loading to express the disorder), which was observed for subclinical autistic-like traits in a sample from the United Kingdom and Sweden, 2 may not apply to a majority of clinical autistic syndromes. Another important observation was the lack of a discrepancy in recurrence rates between dizygotic twins and nontwin siblings, tempering concerns raised by previously reported elevations among dizygotic twins that implicated intrauterine environmental factors in autism risk. With regard to heritability, however, both the estimation of total heritability (0.50) and the estimation of nonshared environmental influence (0.50) reported in the study warrant caution because they were based on one of the lower monozygotic twin concordance rates ever reported (tetrachoric correlation of 0.55) and on a relatively small number of clinically affected monozygotic twins (n = 62 total). The correlation was substantially higher when exclusively considering male monozygotic twin pairs (0.70). Sandin et al1 did not separately estimate heritability or nonshared environmental influence for ASD in nontwins or males, the latter particularly relevant given the fact that ASD is 3 times more common in males and there is accumulating evidence that penetrance of many ASD genetic susceptibilities is reduced in females.3 Any extent to which the method of ASD ascertainment led to underrepresentation of the true monozygotic concordance would falsely lower the estimation of heritability and falsely raise the estimation of the influence of nonshared environmental influence. Although Sandin et al1 drew parallels between their results and those of the California Autism Twin Study,4 the respective studies report highly contrasting (essentially incompatible) types of environmental influence; notably, the Swedish study revealed no evidence for the presence of common (shared) environmental influences, which it was well powered to detect. Moreover, regarding its assertion of nonshared environmental influence, the role of de novo mutation (a significant influence on sporadic autism except when involving mono-
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Copyright 2014 American Medical Association. All rights reserved.
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