Screening for Type 2 Diabetes in Overweight Adolescents in a High School Setting

type 2 diabetes screening in adolescents 125

Screening for Type 2 Diabetes in Overweight Adolescents in a High School Setting Laurent Legault MD, Robert Pincott MD, Constantin Polychronakos MD Montreal Children’s Hospital, McGill University, Montreal, Quebec, Canada

A B S T R A C T OBJECTIVE

The primary objective was to evaluate a screening strategy for type 2 diabetes among overweight adolescents in a high school setting. METHODS

Adolescents from 2 high schools were invited to be screened for type 2 diabetes.Those who participated were weighed and had their body mass index (BMI) calculated; if BMI was >90th percentile for age and sex, they were invited to have a 2-hour postprandial blood glucose (BG) test done. Adolescents with known diabetes were excluded from the study. R E S U LT S

Of 1095 adolescents who participated from 2 schools, 18% from high school A and 22% from high school B had a BMI >90th percentile. In school A, only 18% of tested subjects were white, while in the other, 87% were white. No individual had an abnormal postprandial BG reading. BG meter values were highly correlated with biochemical values (r=0.89). CONCLUSIONS

High school screening for type 2 diabetes in overweight adolescents did not identify a single case of undiagnosed disease and could reflect a fairly low prevalence of type 2 diabetes in

Address for correspondence: Laurent Legault Montreal Children’s Hospital 2300 Tupper Street, Room C-1239 Montreal, Quebec Canada H3H 1P3 Telephone: (514) 412-4400 (ext. 22864) Fax: (514) 412-4405 E-mail: [email protected]

R É S U M É OBJECTIF

Le principal objectif était d’évaluer une stratégie de dépistage du diabète de type 2 en milieu scolaire chez des adolescents en surpoids. MÉTHODES

Des adolescents de deux écoles secondaires ont été invités à subir une épreuve de dépistage du diabète de type 2. Ceux qui ont accepté ont été pesés et leur indice de masse corporelle (IMC) a été calculé. Si leur IMC était supérieur au 90e percentile pour l’âge et le sexe, ils étaient invités à subir une épreuve de glycémie 2 heures pc. Les adolescents chez qui le diabète avait déjà été diagnostiqué étaient exclus de l’étude. R É S U LTAT S

Au total, 1095 adolescents des deux écoles ont participé. L’IMC était supérieur au 90e percentile chez 18 % des sujets de l’école A et 22 % des sujets de l’école B. À l’école A, seulement 18 % des sujets ayant subi une épreuve de glycémie étaient de race blanche et à l’école B, 87 % étaient de race blanche. La glycémie postprandiale n’était anormale chez aucun des sujets. Il y avait une forte corrélation entre les résultats obtenus avec un indicateur de glycémie et les valeurs biochimiques (r = 0,89). CONCLUSIONS

Le dépistage du diabète de type 2 chez des adolescents en surpoids d’écoles secondaires n’a révélé aucun cas de diabète, ce qui pourrait signifier que la prévalence du diabète de type 2 chez les adolescents de notre région est passablement faible. Les indicateurs de glycémie pourraient se révéler utiles pour mettre au point d’autres stratégies de dépistage. M OT S C L É S

adolescents, obésité, dépistage

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the adolescent population in our area. BG meters could be useful for developing further screening strategies. K E Y WO R D S

Adolescents, obesity, screening INTRODUCTION Type 2 diabetes is a major public health issue with a huge cost burden, and it is increasingly prevalent in youth (1); indeed, the prevalence of type 2 diabetes in adolescents has tripled in certain urban settings (2). In adults, risk factors for type 2 diabetes include obesity, ethnicity other than white and a positive family history of the disease (3). The fairly recent emergence of type 2 diabetes in younger individuals may explain why a significant number of patients in certain settings present with complications at diagnosis, suggesting that pediatric type 2 diabetes may be linked to a more rapid onset of complications associated with the disease (e.g. cardiovascular disease, retinopathy, nephropathy and neuropathy) (3). It is hoped that early identification and subsequent treatment could prevent or delay the onset of complications, although this has not yet been proven. Several adult studies (4-6) have shown that unlike type 1 diabetes, type 2 diabetes can be delayed and possibly even avoided. However, the fact that type 2 diabetes may be a preventable disease may not justify large-scale screening. Any screening strategy should limit the number of testing procedures (especially if invasive) and focus on higher-risk candidates. One major barrier to mass screening for type 2 diabetes has been the fact that the vast majority of patients (both adult and youth) are asymptomatic (1,2). Nevertheless, one risk factor identified in all screening studies is excess weight; at least 80% of adults with type 2 diabetes are overweight, and excess weight is an even more important contributor to the development of type 2 diabetes in children (1,2). Obesity, therefore, may be a useful criterion for screening. Except among the well-studied Pima Indians (7), the true prevalence of type 2 diabetes in the pediatric population has not yet been established, because population- or school-based studies have not been done. Different screening strategies have been used, resulting in prevalence rates that range from 0.5% using a non-targeted, school-based approach in which every child was offered testing (8) to 4% when looking specifically at very obese children (9). Reports have come mostly from the United States (US), where the ethnic composition of the population and severity of obesity differ from the population of Quebec. However, a more recent study from Germany of a cohort of obese adolescents reported similar rates of diabetes (10).To our knowledge, no similar studies exist in Quebec or Canada except among the Aboriginal population (11,12). The Canadian Diabetes Association (CDA) Clinical Practice Guidelines for the Prevention and Management of Diabetes in Canada state that obese children ≥10 years of age

with 2 additional risk factors (e.g. ethnicity, family history of type 2 diabetes/exposure to diabetes in utero, acanthosis nigricans, polycystic ovary syndrome, hypertension, dyslipidemia) may be considered for screening (13). A fasting plasma glucose sample is the preferred test, but the CDA also states that an oral glucose tolerance test (OGTT) can be considered (13). Indeed, most published studies have used an OGTT and identified individuals with diabetes based on the 2-hour postprandial value. As many people with diabetes are unaware that they have the disease, the usefulness of family history as a criterion for screening may be limited. As well, the highest rates of diabetes have typically been found in selected populations chosen only on the basis of obesity (9). In this context, we chose to focus on overweight as the single most important criterion for screening these adolescents.Although obesity is usually defined by a body mass index (BMI) >95th percentile (based on the US Centers for Disease Control [CDC] growth curves) we chose a BMI cutoff of >90th percentile to ensure all ethnic groups were included, as the CDC curves are not ethnicity-specific. North American statistics establish the prevalence of obesity in the adolescent population at approximately 15% (14,15). However, population-based screening for diabetes is difficult to do, and reports from obesity clinics may suffer from a referral bias. Therefore, in an effort to gain insight into the prevalence of type 2 diabetes in the Quebec adolescent population, a school-based screening program targeting overweight individuals was conducted. METHODS Objectives This pilot study had 3 objectives: i) to estimate the prevalence of type 2 diabetes among adolescents with a BMI >90th percentile for age in a high school setting using blood glucose (BG) concentration as measured by a portable BG meter; ii) to estimate the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of BG meter results for a 2-hour postprandial glucose ≥11.1 mmol/L in the same population; and iii) to determine risk factors for diabetes in the same population. The study was approved by the local institutional review board and by authorities from both high school boards. Study population Two major high schools in the greater Montreal area were

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included in this pilot study. These schools were chosen because of their size (between 1000 and 1500 students per school), their relative proximity to the study centre and the fact that 1 of the schools (high school A) is known for its multicultural makeup (>50 ethnic communities represented), thus favouring the presence of at least 2 risk factors in many of the students. Students at the second high school (high school B) were primarily white, making it more representative of Quebec’s population. Inclusion and exclusion criteria All students in the 2 high schools were invited to participate. Only those students with a BMI >90th percentile for age were eligible. Students with previously diagnosed diabetes were excluded. Procedure Parents received written information about the study and an invitation for their child to participate. In high school A, the school allowed us access only to those interested in moving forward with the entire protocol, whereas high school B, run by a different school board, granted access to all potential adolescents, but then let parents decide whether to pursue the BG testing portion of the study. All students willing to participate had their height and weight measured in order to calculate BMI (kg/m2). At the same visit in high school A, waist measurements, having been established as a good marker of abdominal adipose distribution and potentially associated with diabetes risk (16), were done with a flexible tape at the midpoint between the lowest rib and the iliac crest.Waistcircumference data are reported only for high school A, as the technique was not standardized for high school B and most adolescents were not measured. BG levels were assessed using a FreeStyle BG meter (Abbott Diabetes Care, Mississauga, Ontario, Canada), chosen for its portability and quick reporting capability.As well, its capillary measurements have been shown to correlate extremely well with venous sampling (17). Students meeting the above criteria were invited to have their BG measured using the meter.A simultaneous venous sample was drawn to validate the accuracy of the meter readings. All blood samples were confirmed in the laboratory to assess possible false positive or negative values. Calculations were done to assess whether using a BG meter in this setting ensured an acceptable level of precision for the objective of this project. Weight and height measurements were taken at recess or during lunch time, and BG tests were done at afternoon recess, 2 hours after the students’ last meal. The research team verified that the student had eaten a meal, but the content of the meal was not assessed. If a student had not eaten lunch, the test was rescheduled. A diagnosis of diabetes was to be confirmed if the 2-hour postprandial BG value was ≥11.1 mmol/L on the biochemical sample. A repeat sample was to be done in any student

with a 2-hour postprandial BG value >7.8 mmol/L on the biochemical sample. Testing was to be repeated on another day, as per the study protocol. If 1 sample was ≥11.1 mmol/L and the other <11.1 mmol/L, the student was to be offered an OGTT. A questionnaire designed to identify risk factors (family history, activity profiles, nutritional habits) that could eventually lead to better-targeted screening strategies was distributed to all high school A families with the study information package. Students at high school A who underwent BG testing completed the questionnaire or had their parents do so. Administrators at high school B declined to distribute the questionnaire. Analyses Based on Canadian and US data, we estimated that 15% of the student body would meet our eligibility criteria. Primary analyses included calculations of the prevalence of type 2 diabetes in this high-risk population as an estimate of the upper limits of prevalence of type 2 diabetes in the Quebec school population.To determine risk factors for diabetes, univariate analysis was performed using a chi-square test, with crude odds ratios calculated for each variable (including waist circumference). RESULTS In high school A, 550/1500 students (36%) returned questionnaires, and 272 (50%) of those agreed to participate. Of those participants, 119 respondents (44%) had a positive family history of type 2 diabetes. Of the 49 students (18%) who had a BMI >90th percentile, 40 (82%) agreed to Table 1. Characteristics of study participants High school A

High school B

BMI >90th percentile, n (%)

49 (18)

181 (22)

Waist circumference, cm, mean±SD (range)

86.4±9.1 (74–104)

Not measured

4.1–7.1

4.1–8.1

Age, years, mean±SD

15.82±1.51

15.69±1.31

BMI, kg/m2, mean±SD

27.63±3.73

26.76±2.97

Ethnicity white/other, n

7/33

36/5

Female/male, n

19/21

21/20

119 (44)

Information not gathered

2-hour postprandial BG, range, mmol/L

Family history of diabetes, n (%) BG = blood glucose BMI = body mass index SD = standard deviation

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DISCUSSION North American data on screening for type 2 diabetes in youth are limited.We present the results of a screening strategy using a 2-hour postprandial BG sample in a high-risk cohort of overweight adolescents, many from at-risk ethnic groups or with a positive family history of type 2 diabetes. The optimal strategy and target population for type 2 diabetes screening remain controversial. Studies from obesity clinic cohorts report diabetes prevalence ranging from 4 to 6% in adolescents (9,10), but these are selected populations. We chose to concentrate on high-risk subjects for the sake of efficiency, but without referral bias. We chose to target high school students and test only those with a BMI >90th percentile for age and gender. We chose 1 high school well known for its multicultural makeup, and another that was more representative of the provincial population. In high school A, 82% of the students who returned a questionnaire declared an ethnicity other than white, and 44% had a positive family history of diabetes, yet no student was found to have a 2-hour postprandial BG level ≥11.1 mmol/L. In fact, none had a postprandial value >7.1 mmol/L. Similar results were found in high school B using the same strategy.This was a more homogeneous population—87% of students were white. The highest meter value in this school was 8.1 mmol/L, which was then repeated and found to be normal. Consistent with recent Canadian data, 18% and 22% of students in high school A and high school B, respectively, had a BMI >90th percentile. There is no question that the incidence of type 2 diabetes is

Figure 1. Correlation of BG meter readings and biochemical concentrations of BG BG meter value (mmol/L) 8.0

Biochemical BG value (mmol/L)

proceed with BG testing (Table 1). Seven of the 40 (18%) were white, 16 (40%) were Asian, 8 (20%) were Hispanic, 4 (10%) were African-Canadian and 5 (12%) were North African or Middle Eastern. There were no statistical differences in age, BMI or gender ratio between the group tested (n=40) and the group not tested (n=9). No student was found to have diabetes.The maximum BG meter reading was 7.1 mmol/L. In high school B, 823/975 students (84%) were weighed and measured.The ethnic composition of this group was 87% white; mean age and gender distribution were similar to high school A. Of the participating students, 181/823 (22%) had a BMI >90th percentile, of whom 41 (22%) elected to have the BG testing performed. No student was found to have diabetes.The maximum BG meter reading was 8.1 mmol/L. The individual with that value was subsequently found to have normal fasting and 2-hour postprandial values on repeat biochemical sample. The correlation between meter and biochemical values was high (Figure 1) (r=0.89, p<0.05). Correlations between BMI z scores, waist circumference measurements and biochemical glucose values were not significant. Sensitivity, specificity, PPV and NPV were impossible to calculate, given the absence of positive results.

7.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

Correlation: r=0.89 p <0.05

6.0 5.0 4.0 3.0 2.0

BG = blood glucose

increasing in both the general population and in adolescents. Most reports, however, have been published by American researchers (1,3,4), and Canadian data are limited. One Canadian group reported an increase in type 2 diabetes prevalence in its clinic (18), and 2 groups who tried to identify undiagnosed type 2 diabetes in Aboriginal Canadians found no undiagnosed cases (11,12). Our study is the first Canadian screening initiative targeting high-risk adolescents who are not Aboriginal. We targeted adolescents with the most common risk factor, namely overweight, and in 1 high school we were able to include ethnicity as an additional risk factor. While recent reports have called for school screening (19), only Japan has implemented it in a systematic fashion, using the presence of glucosuria to prompt further measures (20). This measure has been shown to be quite efficient, as that country has seen a significant increase in the prevalence of type 2 diabetes in youth. This project had a number of limitations. First and foremost, because participation was voluntary, we were unable to gather information on all potentially eligible subjects. Nevertheless, the tested groups in both high schools were representative of the general population, as the number of students with a BMI >90th percentile was well within the expected range. As well, tested and nontested groups were found to be statistically similar in terms of BMI, age and gender distribution. Ultimately, for the practical purpose of planning future screening, only the results from those willing to participate will be useful. Second, dropout rates were quite high as we progressed through the screening process, with most dropouts occurring between the weighing and the BG testing phases. In high school A, 82% of students elected to have their BG tested; in high school B, only 22% in had their BG tested. This differ-

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ence stemmed from the different success rates of the recruitment teams and the limitations put on those teams by the respective school boards. Third, while this study evaluated a postprandial BG testing strategy, it cannot be expected to yield the same results as an OGTT. Precautions were taken to make sure the adolescents had lunch on the testing day, but carbohydrate content of meals was not estimated.This study was not intended to be an “in the field” OGTT—the methodology used was intended to be quick and efficient, and deliberately avoided using a fasting BG sample. This methodology did not allow us to identify individuals with impaired glucose tolerance (IGT) or impaired fasting glucose (IFG); by definition, IGT can be diagnosed only with an OGTT, while IFG can be identified only with a fasting BG sample. Identification of these dysglycemic states could lead to further workup and potentially the initiation of preventive strategies, although there are no data in pediatric populations to validate the strategies used in adult protocols (4). Our objective was to find a quick and easy way to identify overweight adolescents with type 2 diabetes, and our results appear consistent with those reported in other settings using the more labour-intensive OGTT (21,22). This study also had some strengths. It targeted individuals with the most important risk factor for type 2 diabetes: overweight. We did not use a fasting BG sample, which has been shown in individuals screened with an OGTT to be less sensitive than the 2-hour value for detection of diabetes. For example, every case of diabetes in an American pediatric series (9) was diagnosed with a postprandial sample (in the context of an OGTT) and would have been missed by a fasting sample. Our study also targeted, for the vast majority of students in high school A, a population that included a variety of at-risk ethnic backgrounds. Having targeted in high school B a group overwhelmingly comprised of white adolescents (87%), a group typically not considered at high risk, it was reassuring to find that we obtained similar results in high school A, a group seemingly at higher risk because of its high multicultural makeup, which attests to the validity of the findings. In fact, our results are quite similar to a recent study in which the overall prevalence of type 2 diabetes detected by screening a large cohort of adolescents was <0.5% (8). Moreover, 2 recent reports from the US, 1 targeting patients from an obesity clinic (21) and the other from an 8th grade cohort (22), found very few undiagnosed cases of diabetes using an OGTT (0% and 0.5%, respectively). It is, therefore, not surprising that we did not identify any adolescents with undiagnosed diabetes, and may put into question the need for large-scale screening programs in pediatric populations. Although a portable meter is not currently recommended for screening purposes, the convenience of these meters and the excellent correlation between meter and biochemical values emphasize the need to further explore the use of meters for screening purposes. Our findings are consistent with those of another Canadian group, which used a differ-

ent brand of meter (12). As none of the adolescents we studied came close to diabetic blood glucose values, validation of meters as a screening tool for diabetes awaits further reports. As certain ethnic groups are at higher risk of diabetes, there is no doubt that the genetic composition of different adolescent populations will influence the prevalence of type 2 diabetes. This likely explains why prevalence data vary greatly from 1 setting to the next.A recent gathering of pediatric diabetes healthcare professionals in Canada revealed that 5 to 10% of the pediatric population with diabetes is comprised of individuals with type 2 diabetes (EAC Sellers, unpublished data, 2003), a far cry from reports of up to 30% in the American literature (1,3). Except for a very distinct population in the province of Manitoba (23), reports from Canada are remarkably similar in the relative number of individuals (i.e. 5 to 10% of all patients with diabetes), but somewhat dissimilar in their ethnic breakdown (i.e. a high Asian representation in British Columbia, African-Canadians in Quebec and South/East Asians in Ontario). Given that the prevalence of type 2 diabetes is likely not yet high in our adolescent population, one might also wonder about the emphasis put on the screening of adolescents from certain ethnic backgrounds given that a significant number of adolescents with type 2 diabetes is white and would not, according to current CDA guidelines, be necessarily considered for screening. In our diabetes clinic, 40% of people with type 2 diabetes are white. Recent reports from Germany seem to point to a not-so-drastic trend towards individuals from ethnic backgrounds other than white.The paradigm that type 2 diabetes in youth is mostly a disease of minorities does not seem to apply to all settings (9,24). We hypothesize that while certain individuals are at higher risk for type 2 diabetes, their ethnic background will vary from one environment to the next (i.e. proportion of Asians, African-Canadians) and may reflect, in part, their respective socioeconomic status. Obesity in Canada tracks to lower socioeconomic status (14), and data from our clinic confirm that type 2 diabetes in youth also tracks to lower socioeconomic status, a fact that is known in adult type 2 diabetes. In this case, then, the type 2 diabetes population of a certain area may reflect, to some extent, socioeconomic trends within that same population. Finally, there is also no doubt that overweight adolescents at are risk for many other potential health problems (e.g. metabolic syndrome, steatohepatitis, sleep apnea), but this study was not designed to address those other important issues. CONCLUSION High school screening of overweight adolescents yielded no unknown cases of diabetes. This finding may reflect a lowerthan-suspected prevalence in children who are not Aboriginal. The Canadian Paediatric Society has recently undertaken a survey among pediatric caregivers of all non-type 1 diabetes cases seen in their practices.The optimal strategy for identifying children with asymptomatic type 2 diabetes and better CANADIAN JOURNAL OF DIABETES. 2007;31(2):125-130.

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ascertaining the true prevalence of the disease in the pediatric population remains to be defined. ACKNOWLEDGEMENTS This work was supported by the Montreal Children’s Hospital Research Institute Pilot Project Fund and the McConnell Foundation.We wish to acknowledge the help of Elise Mok in the design of this project. AUTHOR DISCLOSURES No dualities of interest declared. AUTHOR CONTRIBUTIONS LL and CP contributed to the conception, design, analysis and interpretation of the data. LL and RP contributed to the acquisition of data. All authors reviewed the manuscript critically for intellectual content and gave final approval of the version to be published. REFERENCES 1. Rosenbloom AL, Joe JR,Young RS, et al. Emerging epidemic of type 2 diabetes in youth. Diabetes Care. 1999;22:345-354. 2. Pinhas-Hamiel O, Dolan LM, Daniels SR, et al. Increased incidence of non-insulin-dependent diabetes mellitus among adolescents. J Pediatr. 1996;128(5 Pt 1):608-615. 3. Type 2 diabetes in children and adolescents. American Diabetes Association. Diabetes Care. 2000;23:381-389. 4. American Diabetes Association and National Institute of Diabetes, Digestive and Kidney Diseases. The prevention or delay of type 2 diabetes. Diabetes Care. 2002;25:742-749. 5. Chiasson JL, Gomis R, Hanefeld M, et al. The STOP-NIDDM Trial: an international study on the efficacy of an alpha-glucosidase inhibitor to prevent type 2 diabetes in a population with impaired glucose tolerance: rationale, design, and preliminary screening data. Study to Prevent Non-Insulin-Dependent Diabetes Mellitus. Diabetes Care. 1998;21:1720-1725. 6. Buchanan TA, Xiang AH, Peters RK, et al. Preservation of pancreatic beta-cell function and prevention of type 2 diabetes by pharmacological treatment of insulin resistance in high-risk Hispanic women. Diabetes. 2002;51:2796-2803. 7. Bobo N, Evert A, Gallivan J, et al: Diabetes in Children Adolescents Work Group of the National Diabetes Education Program. An update on type 2 diabetes in youth from the National Diabetes Education Program. Pediatrics. 2004;114: 259-263. 8. 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;146:751-758. 9. Sinha R, Fisch G, Teague B, et al. Prevalence of impaired glucose tolerance among children and adolescents with marked obesity. N Engl J Med. 2002;346:802-810. 10. Wiegand S, Maikowski U, Blankenstein H, et al.Type 2 diabetes and impaired glucose tolerance in European children and adolescents with obesity — a problem that is no longer restricted

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