Metabolikus szindróma gyermekkorban

Metabolikus szindróma gyermekkorban Molnár Dénes

Pécsi Tudományegyetem Klinikai Központ Gyermekklinika

- IDEFICS konzorcium nevébenA gyermekorvosi alapellátás XVII. tudományos konferenciája

2015. május 14–17., Siófok

Funded by the EC, FP 6, Contract No. 016181 (FOOD)

Metabolikus szindróma  Rövid történelmi áttekintés  Definíció, prevalencia, problemák  IDEFICS eredmények

 Quo vadis metabolikus szindróma?

2

Történelmi háttér  1923 The combination of hypertension, hyperglycemia and hyperuricemia –, Kylin Ztrbl Inn Med 44: 105

 1966 Trysyndrome metabolique – Camus Rev Rhumat 33: 10

 1968 Wealthy syndrome – Mehnert & Kuhlmann Deutsch Med J 19: 567

 1980 Das Metabolische Syndrome Hanefeld &Leonhardt Deutsch Ges Wes 36: 545 3

Történelmi háttér 1988 Reaven - Syndrome X

– alap az inzulin rezisztenia - Diabetes 37: 1595

Későbbi elnevezések: GHO syndr. (gl. intol., hypert. & obesity) Deadly quartet Metabolic cardiovascular syndrome

4

Jelenlegi terminológia

Metabolikus szindróma 5

Gyermekkori elhízás következményei

Ebbeling CB et al. Lancet 2002; 360: 473-482

MS leggyakrabban használt komponensei  Elhízás  Hipertónia  Dyslipidaemia (emelkedett triglycerid és/vagy alacsony HDLkoleszterin szint)  Inzulin rezisztencia – hiperinzulinémia – glukóz intolarencia és/vagy 2-es tíypusú diabetes

Hansen BC. Ann N Y Acad Sci 1999; 892: 1-24

MS különböző definíciói

efinition VII.

Criteria

Lee et al J Pediatr 152:177-84, 2008

Age

8-19 (participated in various metabolic studies)

Definition

(Weiss)

(Cook)

(Ford)

(Cruz)

Waist cc

-

>=90th percentile for age, sex

>=90th percentile for age, sex

>=90th percentile for age, sex, race

BMI

Z score >= 2 age and sex specific

-

-

>=85th percentile for age

RR

>=95th percentile for age, sex and height



>90th percentile for age, sex and height

Glucose fasting

Impaired glucose tolerance

>= 6.1 mmol/l or impaired glucose tolerance

>=6.1mmol/l or impaired glucose tolerance

Impaired glucose tolerance

HDL-chol

<=5th percentile for age, sex and race

<=40 mg/dL

<=40 mg/dL

<=10th percentile for age, sex

LDL-chol

-

-

-

-

Triglyceride

>=95th percentile for age, sex and race

>=110 mg/dL

>=110 mg/dL

>=90th percentile for age and sex

Prevalence

18.7

21

25.1

13.4

8

Vizsgált elhízott gyermekek antropometriai jellemzői Polish

Greek

Italian

French

Hungarian

(n = 90)

(n = 145)

(n = 274)

(n = 283)

(n = 449)

Whole group (n = 1241)

Boys/Girls

39/51

74/71

135/139

91/192

221/228

560/681

Age (years)

12.9 (3.3)

11.3 (2.5)

12.1 (1.6)

14.5 (1.6)

12.9 (2.7)

12.9 (2.5)

Weight (kg)

78.7 (24.5)

70.4 (20.9)

63.9 (13.9)

102.4 (19.9)

80.5 (21.7)

80.53 (24.1)

Height (cm)

158.4 (16.0)

151.3 (14.6)

153.6 (9.4)

164.5 (8.4)

159.4 (13.5)

158.2 (12.8)

BMI (kg/m 2)

30.8 (4.9)

30.1 (4.9)

26.8 (3.6)

37.7 (5.9)

31.1 (4.8)

31.5 (6.1)

Data 9 are expressed as mean (SD).

Bokor S…..Molnar D Int J Pediatr Obes 3(Suppl 2): 3, 2008

Vizsgált MS definíciók

Waist circumference (cm)

Ferranti et al

WHO

≥ 3 of 5 criteria

Impaired glucose regulation* + ≥ 2 of criteria

≥ 3 of 5 criteria

IDF

High waist circumference + ≥ 2 of 4 criteria

high waist circumference: > 90th percentile for age and gender (20) ≥ 6.1

Glucose (mmol/l)

Insulin (μU/ml)

-

Triglyceride (mmol/l)

≥ 1.1

HDL-cholesterol (mmol/l)

< 1.3, < 1.2 older than 15 years

Blood pressure (mmHg)

NCEP

Top quartile of insulin among nondiabetic subjects

≥ 5.6

-

-

≥ 1.7 < 0.9 in ♂ < 1.0 in ♀

≤ 1.03 in ♂ ≤ 1.29 in ♀

< 1.03 in ♂ < 1.29 in ♀

systolic and/or diastolic BP > 95th percentile for age gender and height (19)

NCEP: National Cholesterol Education Program, WHO: World Health Organisation, IDF: International Diabetes 10 Federation. *Impaired glucose regulation: glucose intolerance, IFG or diabetes mellitus and/or insulin resistance

MS prevalencia (%) 40% 35% 30% 25% 20% 15% 10% 5% 0%

Ferranti et al.

WHO

NCEP

IDF

MS definition: Ferranti et al., National Cholesterol Education Program (NCEP) : 3 or more of the criteria’s; WHO, International Diabetes Federation (IDF)

11

Bokor S…..Molnar D Int J Pediatr Obes 3(Suppl 2): 3, 2008

MS prevalencia a 4 definíció szerint 15% 5%

30%

8% 55%

MS or not?? 17%

Without MS according to 4 definitions MS according to 1 definition MS according to 2 definitions MS according to 3 definitions MS according to 4 definitions

Bokor S…..Molnar D Int J Pediatr Obes 3(Suppl 2): 3, 2008 12

További kérdések  MS diagnózisának stabilitása Goodman et al. (Circulation 115: 2316-22, 2007) szerint A páciensek fele kategóriát vált a követés során – a negatívok pozitívvá válnak és fordítva

13

IDF új definíciót alakított ki gyermekek számára The Lancet 369: 2059-61, 2007

Age 6 to <10 years  Obesity >=90th percentile as assessed by waist cc  Metabolic syndrome cannot be diagnosed Age 10- <16 years  Abdominal obesity >=90th percentile (or adult cutoff if lower) as assessed by waist cc + 2 or more of the following:  Triglyceride >= 1.7 mmol/l  HDL-C < 1.03 mmol/l  SBP >= 130 mm Hg or DBP >= 85 mm Hg  Glucose >= 5.6 mmol/l (oral glucose tolerance test recommended) or known type 2 diabetes mellitus Age > 16 years  Use existing IDF criteria for adults

14

Miért nem sikerül konszenzusra jutni a a MS meghatározását illetően? Konszenzus hiányának okai:  A gyermekkori fejlődéssel járó fiziológiai változások hiányos ismerete (gyermek- és pubertáskor – testösszetétel, laboratóriumi paraméterek)  Nem és életkor specifikus referencia értékek hiánya – derékkörfogat, HDL-kol., triglycerid, insulin, HOMA, stb.  A MS meghatározásának nehézségei felhívják a figyelmet, hogy a MS mint koncepció igen érdekes, de mint diagnosztikus eszköz, óvatosan kezelendő.

15

Metabolikus szindróma meghatározása gyermekkorban

Background:

A gyermekgyógyászoknak új megközelítést kell alkalmazniuk a MS meghatározásához. Felnőttekben alkalmazott meghatározások nem adaptálhatóak gyermekkorra. A MS egyes komponensei akkor vehetők figyelembe, ha a megfelelő referencia értékek rendelkezésre állnak és azok egészségügyi kockázatai tisztázottak.

The diagnostic criteria of the metabolic syndrome (MS) have been applied in studies of obese adults to estimate the metabolic risk-associated with obesity, even though no general consensus exists concerning its definition and clinical value. We reviewed the current litera ture on the MS, focusing on those studies that used the MS diagnostic criteria to analyze children, and we observed extreme heterogeneity for the sets of variables and cutoff values chosen. Objectives:

To discuss concerns regarding the use of the existing definition of the MS (as defined in adults) in children and adolescents , analyzing the scientific evidence needed to detect a clustering of cardiovascular risk-factors. Finally, we propose a new methodological approach for estimating metabolic risk-factor clustering in children and adolescents. Results:

Major concerns were the lack of information on the background derived from a child's family and personal history; the lack of consensus on insulin levels, lipid parameters, markers of inflammation or steato-hepatitis; the lack of an additive relevant effect of the MS definition to obesity per se. We propose the adoption of 10 evidence-based items from which to quantify metabolic risk-factor clustering, collected in a multilevel Metabolic Individual Risk-factor And CLustering Estimation (MIRACLE) approach, and thus avoiding the use of the current MS term in children. Conclusion:

Pediatricians should consider a novel and specific approach to assessing children/adolescents and should not simply derive or adapt definit ions from adults. Evaluation of insulin and lipid levels should be included only when specific references for the relation of age, gend er, pubertal status and ethnic origin to health risk become available. This new approach could be useful for improving the overall quality of patient evaluation and for optimizing the use of the limited resources available facing to the obesity epidemic.

Brambilla P et al. Int J Obes 2007; 31: 591-600

IDEFICS: Identification and prevention of Dietaryand lifestyle-induced health EFfects In Children and infantS

17

IDEFICS: 31 partner 11 országból

18

Belgium

Ghent

Cyprus

Strovolos

Estonia

Tallin

Hungary

Pécs

Germany

Bremen

Italy

Avellino

Spain

Zaragoza

Sweden

Gothenburg

IDEFICS tanulmány struktúrája

Intervention T0 survey:

T1 survey:

T2 survey:

2007/08 sch yr

2009/10 sch yr

2010 autumn

16 228 children

13 795 children

10 268 children

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IDEFICS kohorsz

 16228, 2-9 éves gyermeket vizsgáltak az alap-felmérésben  További 2517, 2-10.9 éves gyermek kerult bevonásra a második felmérés során  Így a végleges csoport legnagyobb létszáma 18169 gyermek volt  Az alábbiakban ismertetett analízisek elemszáma varábilis volt, tekintettel arra, hogy a szülők és a gyermekek szabadon választhattak, mely vizsgálati modulban vesznek részt

20

IDEFICS eredmények

 A MS egyes komponenseire vonatkozó európai standardok kerültek kialakításra

21

Chittaranjan S Yajnik, and John S Yudkin: The Y-Y paradox 

The two authors share a near identical body-mass index (BMI), but as dual X-ray absorptiometry imagery shows that is where the similarity ends. The first author (figure, right) has substantially more body fat than the second author (figure, left). Lifestyle may be relevant: the second author runs marathons whereas the first author's main exercise is running to beat the closing doors of the elevator in the hospital every morning. The contribution of genes to such adiposity is yet to be determined, although the possible relevance of intrauterine under-nutrition is supported by the first author's low birthweight. The image is a useful reminder of the limitations of BMI as a measure of adiposity across populations. 22

Brit vs. IDEFICS/Europai percentilisek

2. 205 9.2 52.0 59. 54. 51. 54.9 9 32

59.2

51.3 53.9

59.5

9.5 HD McCarthy1*, KV Jarrett1 and HF Crawley: The development of waist circumference percentiles in British

children aged 5.0 ± 16.9 y. European Journal of Clinical Nutrition (2001) 55, 902–907 23

US vs. IDEFICS percentilisek (fiúk; 50 percentilis, életkor 5,7,10 év)

52.8 vs. 52.0

56.4 vs. 54.9

Cook, Auinger, Huang,: Growth Curves for Cardio-Metabolic Risk Factors in Children and

Adolescents. J Pediatr. 2009 September ; 155(3): S6.e15–S6.e26. doi:10.1016/j.jpeds.2009.04.051. 24

63.3 vs. 59.2

110

Girls

100 90

US UK Spain Canada Adults

80 70 60 50 40 2

4

6

8

10

12

14

16

18



Különböző refrencia standardok a derékkörfogatra (90 percentilis értékek) 110

Boys

100 90

US UK Spain Canada Adults

80 70 60 50 40 2

4

Age (years)

Luis A. Moreno Aznar [email protected] Brambilla P et al. Int J Obes 2007; 591-600 GENUD Research Group Universidad de31: Zaragoza

6

8

10

12

Age (years)

14

16

18

Csípő körfogat percentilis görbéi normál súlyú európai fiúkban és lányokban

26

Csípő-magasság hányados girls

Age 27

Int J Obes (2014) 38, S15–S25; doi:10.1038/ijo.2014.131

boys

Age

Plazma inzulin

28

HOMA-IR index

Reference limit for adults: < 2* 29

* Keskin et al.: Pediatrics. 2005 Apr;115(4)..

Plazma glukóz

Reference limit for adults: 5.6 mmol/l (100 mg/dl)* 30

* Alberti et al.: Lancet. 2005 Sep 24-30;366(9491):1059-62.

HDL-koleszterin - lányok 0,68 mmol/l Percentile: 2-2.5y 2.5-3y 3-3.5y 3.5-4y 4-4.5y 4.5-5y 5-5.5y 5.5-6y 6-6.5y 6.5-7y 7-7.5y 7.5-8y 8-8.5y 8.5-9y 9-9.5y 9.5-10y 10-10.5y 10.5-10.9y

5th 22.3 23.4 24.4 25.5 26.5 27.5 28.4 29.3 30.2 31.1 31.8 32.4 32.9 33.1 33.3 33.5 33.6 33.6

10th 26.4 27.5 28.7 29.9 31.0 32.1 33.0 34.1 35.0 35.9 36.7 37.3 37.7 38.0 38.1 38.2 38.3 38.3

25th 33.2 34.6 35.9 37.2 38.5 39.7 40.8 42.0 43.0 44.0 44.8 45.5 45.9 46.1 46.1 46.1 46.0 45.9

50th 40.7 42.2 43.8 45.3 46.7 48.1 49.3 50.6 51.7 52.8 53.7 54.3 54.7 54.8 54.7 54.6 54.4 54.2

75th 48.5 50.3 52.0 53.7 55.3 56.8 58.2 59.6 60.8 62.0 62.9 63.5 63.9 63.9 63.7 63.5 63.2 62.8

90th 56.4 58.3 60.3 62.2 64.0 65.6 67.1 68.6 70.0 71.2 72.1 72.8 73.1 73.0 72.7 72.4 71.9 71.4

International Journal of Obesity (201438, S67–S75; doi:10.1038/ijo.2014.137 31 0,99 mmol/l

95th 61.4 63.6 65.6 67.6 69.6 71.3 72.8 74.4 75.8 77.1 78.1 78.7 79.0 78.9 78.5 78.1 77.6 76.9

HDL-koleszterin fiúk 0,74 mmol/l Percentile: 2-2.5y 2.5-3y 3-3.5y 3.5-4y 4-4.5y 4.5-5y 5-5.5y 5.5-6y 6-6.5y 6.5-7y 7-7.5y 7.5-8y 8-8.5y 8.5-9y 9-9.5y 9.5-10y 10-10.5y 10.5-10.9y 32

5th 24.4 25.4 26.3 27.3 28.2 29.2 30.1 31.0 31.9 32.7 33.4 33.9 34.2 34.5 34.7 35.0 35.4 35.8

10th 28.7 29.7 30.8 31.8 32.8 33.8 34.8 35.8 36.8 37.6 38.3 38.8 39.1 39.3 39.5 39.8 40.2 40.6 1,05 mmol/l

25th 35.7 37.0 38.1 39.3 40.5 41.6 42.7 43.8 44.9 45.8 46.4 46.9 47.2 47.3 47.5 47.7 48.0 48.4

50th 43.5 44.8 46.2 47.5 48.8 50.0 51.2 52.5 53.6 54.6 55.3 55.7 55.9 56.0 56.1 56.2 56.5 56.8

75th 51.5 53.0 54.5 56.0 57.4 58.8 60.1 61.4 62.7 63.7 64.4 64.8 65.0 65.0 65.0 65.1 65.2 65.5

90th 59.5 61.2 62.9 64.4 66.0 67.5 68.9 70.4 71.7 72.8 73.5 73.9 74.0 73.9 73.8 73.8 73.9 74.2

95th 64.7 66.5 68.2 69.8 71.5 73.1 74.6 76.1 77.5 78.6 79.3 79.7 79.7 79.6 79.4 79.4 79.5 79.7

A vizsgált gyermekkori MS definíciók Definition

Excess adiposity WC  90th percentile

Blood pressure

SBP or DBP  90th Triacylglycerols  110 mg/dl percentile or HDL cholesterol ≤ 40 mg/dl

Impaired fasting glucose  110 mg/dl

Viner et al.

BMI  95th percentile

SBP  95th percentile

Hyperinsulinemia  15 mU/l or Impaired fasting glucose  110 mg/dl

IDF*

WC  90th percentile

SBP  130 mmHg or DBP  85 mmHg

Cook et al.

Blood lipids

Triacylglycerols  150 mg/dl or HDL cholesterol <35 mg/dl or High total cholesterol 95th percentile Triacylglycerols  150 mg/dl or HDL cholesterol  40 mg/dl

Blood glucose/ insulin


Cook S et al.. Prevalence of a metabolic syndrome phenotype in adolescents: findings from the third National Health and Nutrition Examination Survey, 1988–1994. Arch Pediatr Adolesc Med 2003; 157: 821-827. Viner RM et al.. Prevalence of the insulin resistance syndrome in obesity. Arch Dis Child 2005; 90: 10-14. Zimmet P et al.; IDF Consensus Group: The metabolic syndrome in children and adolescents – an IDF consensus report. Pediatr Diabetes 2007; 8: 299-306. *IDF=International Diabetes Federation

Az egyes komponensek fontosága (súlya) a különböző definíciók szerint 30%

Cook et al.32 25%

20% Girls

15%

Boys 10%

5%

0% WC

BP

Lipids

Glucose

Ahrens W & Moreno LA et al. Int J Obes 2014; 38: S4-S14

MetS


Viner et al.33 25%

20% Girls

15%

Boys 10%

5%

0% BMI

BP

Lipids

Glucose


MetS


IDF34 25%

20% Girls

15%

Boys 10%

5%

0% WC

BP

Lipids

Glucose


MetS

IDEFICS által javasolt új meghatározás Definition

Excess adiposity WC  90th percentile

Blood pressure

SBP or DBP  90th Triacylglycerols  110 mg/dl percentile or HDL cholesterol ≤ 40 mg/dl


Viner et al.

BMI  95th percentile

SBP  95th percentile

Hyperinsulinemia  15 mU/l or Impaired fasting glucose  110 mg/dl

IDF*


SBP  130 mmHg or DBP  85 mmHg

Triacylglycerols  150 mg/dl or HDL cholesterol <35 mg/dl or High total cholesterol 95th percentile Triacylglycerols  150 mg/dl or HDL cholesterol  40 mg/dl

SBP  90th percentile or DBP  90th percentile SBP  95th percentile or DBP  95th percentile

Triacylglycerols  90th percentile or HDL cholesterol ≤ 10th percentile Triacylglycerols  95th percentile or HDL cholesterol ≤ 5th percentile

HOMA-insulin resistance  90th percentile or Fasting glucose  90th percentile

Cook et al.

IDEFICS- WC  90th monitoring percentile level IDEFICSaction level


Blood lipids

*IDF=International Diabetes Federation

Blood glucose/ insulin


HOMA-insulin resistance  95th percentile or Fasting glucose  95th percentile

Az egyes komponensek fontosága (súlya) az IDEFICS meghatározás szerint 30%

IDEFICS-monitoring level 25%

20% Girls

15%

Boys 10%

5%

0% WC

BP

Lipids

Glucose


MetS

Az egyes komponensek fontosága (súlya) az IDEFICS meghatározás szerint 30%

IDEFICS-action level 25%

20%

Girls

15%

Boys

10%

5%

0% WC

BP

Lipids

Glucose


MetS

MS gyakorisága az IDEFICS populációban IDEFICS monitoring level No MetS N %

MetS N

%

IDEFICS action level No MetS N %

MetS N

%

Male Normal/thin Overweight Obese Total

4882 654 325 5861

98,4 86,4 70,3 94,9

77 103 137 317

1,6 13,6 29,7 5,1

4948 729 408 6085

99,8 96,3 88,3 98,5

11 28 54 93

0,2 3,7 11,7 1,5

4687 768 326 5781

98,6 85,5 66,7 94,1

67 130 163 360

1,4 14,5 33,3 5,9

4744 851 417 6012

99,8 94,8 85,3 97,9

10 47 72 129

0,2 5,2 14,7 2,1

98,5 85,9 68,5 94,5

144 233 300 677

1,5 14,1 31,5 5,5

9692 1580 825 12 097

99,8 95,5 86,8 98,2

21 75 126 222

0,2 4,5 13,2 1,8

Female Normal/thin Overweight Obese Total

All Normal/thin 9569 Overweight 1422 Obese 651 40 Total 11 642

MS gyakorisága normál/sovány, túlsúlyos és elhízott gyermekekben 100% 80%

60%

Obese Overweight Normal/ thin

40% 20% 0%

MetS MetS MetS action MetS action monitoring - monitoring + +

41


Folyamatos MS pontrendszer Continuous MetS score calculated according to Eisenmann as the sum of component z-scores:

 Adiposity: WC (waist circumference (cm))  Blood pressure: mean of SBP and DBP (systolic / diastolic blood pressure (mm Hg))  Blood lipids: mean of TRG and negative HDL (triglycerides / HDL cholesterol (mg/dl))  Insulin resistance: HOMA (homeostasis model assessment)

zSBP + zDBP zTRG – zHDL MetS score = zWC + + + zHOMA 2 2

42

Eisenmann JC. Cardiovasc Diabetol 2008; 7: 17 Ahrens W & Moreno LA et al. Int J Obes 2014; 38: S4-S14

Négy példa a MS pontrendszerre Measured values Subject Sex Age WC

SBP

Standardised residuals (z-scores)

DBP TRG HDL HOMA

zWC

zSBP

zDBP

1

M

6.5 59.5 109.0 67.5

48

38

0.65

1.66

2

F

5.8 60.4

92.0

52.5

50

52

1.59

2.20 -0.96 -1.77

3

F

5.2 53.0

94.0

58.0

45

61

4

M

5.5 57.5

99.0

66.0

78

45

43

0.85

MetS zHDL zHOMA score

0.29 -1.22 -0.15

3.05

0.17 0.10

1.39

2.26

1.00

0.58 -0.51 -0.81 -0.73 0.88

0.68

-0.07

0.99

1.64 -0.13

0.71

3.43


0.72

zTRG

0.59

1.15 -0.54

MS pontszám kor-specifikus referencia görbéi lányokban és fiúkban

44


Konklúzió 

Nemre és életkorra specifikus standardokat dolgoztunk ki a kardiometabolikus rizikófaktorokra 11 évnél fiatalabb gyermekek részére



Új MS definícót javasoltunk, mely segítheti a klinikai döntést



Megjegyzés: A javasolt határértékek statisztikai alapúak és nincsenek kapcsolatban a későbbi betegségek, szövődmények (infarktus, hipertónia, stb.) rizikójával.



Folyamatos MS pontrendszer is kidolgozásra került mely elősegítheti a rizikóbecslést és a követéses vizsgálatok értékelését.

A bemutatott eredmények az Int J Obes 2014, Suppl2-ben megjelent publikációkon alapulnak

Quo vadis METS?  A tradicionális markerek mellett új komponenseket is be kell vonni a MS definíciójába?  Oxidatív stressz indikátorok  Alacsony szintű, krónikus gyulladás indikátorai  Adipokinek  Cytokinek  Microalbuminuria?

46

Az IDEFICS Konzorcium

47

47

Previous achievements

48

International Obesity Task Force (IOTF) body mass index cut-offs for overweight and obesity in youth Girls

30

30

28

28

26

25 30

24 22 20

26

22 20 18

16

16 2

4

6

8

10

12

14

16

18

20

25 30

24

18 0

Boys

32

BMI (kg/m2)

BMI (kg/m2)

32

0

2

4

Age (years)

Luis A. Moreno Aznar [email protected] (Cole TJ et al. BMJ 2000; 320: GENUD Research Group Universidad de1240-1243) Zaragoza

6

8

10

12

Age (years)

14

16

18

20

Table 1. Names given to the clustering of metabolic syndrome disorders Terms Hypertension-hyperglycaemia-hyperuricaemia Kylin, 1923 syndrome (Hypertoni-Hyperglycemi-Hyperurikemi syndrom) Metabolic trisyndrome (trisyndrome Camus, 1966 metabolique) Plurimetabolic syndrome Avogaro and Crepaldi, 1967 Syndrome of affluence (wohlstandssyndrom) Mehnert and Kuhlmann, 1968 Metabolic syndrome (metabolische syndrom) Hanefeld and Leonhardt, 1981 Syndrome X Reaven, 1988 Deadly quartet Kaplan, 1989 Insulin resistance syndrome DeFronzo and Ferrannini, 199; Haffner, 1992

50

Lipoprotein metabolism

Lusis AJ et al. Circulation 2004; 110: 1868-1873

Natural history of type 2 diabetes Obesity

Insulin sensitive

Diet Sedentary lifestyle

NORMOGLYCEMIA

Genetics Perinatal factors

Insulin resistance Compensatory hyperinsulinaemia

b-cell decompensation Relative insulin deficiency

POSTPRANDIAL HYPERGLYCEMIA

IMPAIRED FASTING GLUCOSE

b-cell failure

DIABETES MELLITUS

Ludwig & Ebbeling. JAMA 2001; 286: 1427-1430

Vascular complications

Insulin resistance  Homeostatic model assessment (HOMA): the product of the fasting plasma insulin level (mU/ml) and the fasting plasma glucose level (mmol/l), divided by 22.5.  Lower insulin-resistance values indicate a higher insulin

sensitivity, whereas higher values indicate a lower insulin sensitivity.

Metabolic syndrome in children

 Cardiovascular risk factors tend to cluster Webber LS et al. Prev Med 1979; 8: 407-418

Chu NF et al. Am J Clin Nutr 1998; 67: 1141-1146.

 8.9 % of obese children have the metabolic syndrome Csábi G et al. Eur J Pediatr 2000; 159: 91-94.

 Factor analysis of metabolic syndrome components show 2-4 factors Chen W et al. Am J Epidemiol 1999; 150: 667-674 Moreno LA et al. Horm Metab Res 2002; 34: 394-399

Definition of MS. Criteria

Golley Int J Obes 30:853-60, 2006

Age

6-9 (overweight, obese)

Definition

(EGIR) hyperinsulinem ia + 2 or more

(NCEP) >=3

(WHO) hyperinsuline mia + 2 or more

(WHO) hyperinsuline mia + 2 or more

(EGIR) hyperinsulin emia + 2 or more

(NCEP) >=3

Waist cc

Male: 94, Female:80

Male: 94, Female:80

-

-

>=91th pc

>=91th pc

BMI

-

-

>=85th pc

>=85th pc

-

-

RR

SBP: >140

SBP: >130

>= 95th pc for height




Glucose fasting

6.1 mmol/L

6.1 mmol/L

6.1-7.9 mmol/L

6.1-7.9 mmol/L

6.1-7.9 mmol/L

6.1-7.9 mmol/L

Total chol

-

-

-

-

-

-

HDL-chol

1 mmol/L

1 mmol/L

1.2 mmol/L

0.8 mmol/L

0.8 mmol/L

0.8 mmol/L

LDL-chol

-

-

-

-

-

-

Triglyceride

2 mmol/L

1.7 mmol/L

M: 0.9 , F: 1 mmol/L

1.8 mmol/L

1.8 mmol/L

1.8 mmol/L

Prevalence

4

0

59

39

39

3

55

56

Number of MetS risk variables and elasticity of common carotid artery

Increasing stiffness

Bogalusa Study

Ep = Peterson's elastic modulus YEM = relative wall thickness-adjusted Young's elastic modulus Urbina EM et al. Atherosclerosis 2004; 176: 157-164

Prevalence of MetS in normal weight/ thin, overweight and obese children MetS monitoring -

MetS monitoring +

MetS action -

100%

100%

90%

90%

80%

80%

70%

70%

60%

60%

50%

50%

40%

40%

30%

30%

20%

20%

10%

10%

0%

0% Normal/ thin

Overweight

Obese

MetS monitoring level = 5.5% 58

Normal/ thin

MetS action +

Overweight

Obese

MetS action level = 1.8%


Correlation between waist circumference and visceral fat assessed by magnetic resonance imaging 160

Y = 1.1*X - 52.9 R2 = 0.64, p < 0.0001 RMSE = 14 cm2 (33%)

140

VAT (cm2)

120 100 80 60 40 20 0 0

40

80 120 WC (cm)

160

Luis A. Moreno Aznar [email protected] Brambilla P, Bedogni G, Moreno LA et al. Int J Obes 2006; 30: 23-30 GENUD Research Group Universidad de Zaragoza

Metabolikus szindróma gyermekkorban

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