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Tracking the Accelerating Epidemic: Its Causes and Outcomes

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1 Tracking the Accelerating Epidemic: Its Causes and Outcomes
AusDiab The Australian Diabetes, Obesity and Lifestyle Study Tracking the Accelerating Epidemic: Its Causes and Outcomes

2 Baseline data from AusDiab 2000
The AusDiab survey carried out in 1999–2000 provides benchmark Australian prevalence data 2000 findings, Australians  25 years old: – 7.4% had diabetes (doubled since 1981) – 16.3% had pre-diabetes (IFG/IGT*) – 59.6% were mildly overweight or obese – 28.8% had hypertension – 51.2% had total cholesterol ≥ 5.5 mmol/L, and 20.5% had elevated triglycerides (≥ 2.0 mmol/L) – 2.5% had proteinuria, 6.4% had haematuria and 1.1% had elevated serum creatinine * IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance.

3 Aims of the five-year follow-up
Describe the natural history of: Type 2 diabetes Pre-diabetes (IFG/IGT*) Associated cardiovascular disease, risk factors and complications Identify risk factors associated with worsening glucose tolerance status and diabetic complications Measure the progression of renal disease in diabetic and non-diabetic populations * IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance.

4 Definitions for ‘prevalence’ and ‘incidence’
1999–2000 data: Prevalence – the proportion of people within a population who have a certain disease or condition at a particular time 2004–05 data: Incidence – number of new cases of a disease or condition arising in a population over a period of time

5 Diabetes and pre-diabetes

6 Diabetes mellitus Is a metabolic disorder with multiple causes characterised by chronically elevated blood glucose levels Predisposes individuals to: Cardiovascular disease – Visual loss Amputations – Renal failure Has many risk factors including obesity, hypertension and dyslipidaemia

7 Classification values for the oral glucose tolerance test
Plasma glucose (mmol/L) Fasting glucose 2-hour glucose Diabetes ≥ 7.0 or ≥ 11.1 Impaired glucose tolerance (IGT) < 7.0 and 7.8–11.0 Impaired fasting glucose (IFG) 6.1–6.9 < 7.8 Normal glucose tolerance (NGT) < 6.1 Glucose tolerance World Health Organization. Department of noncommunicable disease surveillance, 1999

8 Diabetes in Australia: The last 20 years
1000 e) AusDiab 800 d) Aust Bureau Statistics c) Aust Bureau Statistics 600 Thousands b) Nat Heart Foundation 400 a) Busselton 200 ’80 ’82 ’84 ’86 ’88 ’90 ’92 ’94 ’96 ’98 ’00 Year

9 Age- and gender-specific prevalence (%) of diabetes
Percentage Age group (years)

10 Age-specific prevalence (%) of IFG
Percentage Age group (years) IFG ─ impaired fasting glucose

11 Age-specific prevalence (%) of IGT
Percentage Age group (years) IGT ─ impaired glucose tolerance

12 IGT ─ impaired glucose tolerance; IFG ─ impaired fasting glucose.
Weighted prevalence (%) of associated conditions stratified by glucose tolerance status Glucose tolerance status Associated condition Diabetes IFG IGT Normal Hypertension* Obesity (BMI  30 kg/m²) LDL ( 3.5 mmol/L) HDL ( 1.0 mmol/L) Triglycerides ( 2.0 mmol/L) * On treatment, or systolic pressure  140 mmHg, or diastolic pressure  90 mmHg IGT ─ impaired glucose tolerance; IFG ─ impaired fasting glucose.

13 Incidence of diabetes according to gender
Incidence (% per year)

14 Incidence of diabetes according to baseline age
Incidence (% per year) Baseline age (years)

15 Incidence of diabetes according to baseline glucose tolerance status
Incidence (% per year) Baseline glucose tolerance NGT ─ normal glucose tolerance; IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance.

16 Incidence of IGT and IFG
Incidence (% per year) IGT ─ impaired glucose tolerance; IFG ─ impaired fasting glucose.

17 Incidence of diabetes according to baseline body mass index
Incidence (% per year) Baseline BMI status Body mass index (BMI: weight/height2) was categorised into three groups: (i) normal: BMI < 25.0 kg/m2; (ii) overweight: 25.0─29.9 kg/m2; and (iii) obese: ≥ 30.0 kg/m2.

18 Baseline waist circumference categories
Incidence of diabetes according to baseline waist circumference categories Incidence (% per year) Baseline waist circumference categories Waist circumference: (i) normal: < 94.0 cm for males, < 80.0 cm for females; (ii) overweight: 94.0─101.9 cm for males, 80.0─87.9 cm for females; (iii) obese: ≥ cm for males, ≥ 88.0 cm for females.

19 Incidence of diabetes according to baseline physical activity
Incidence (% per year) Baseline physical activities categories

20 Incidence of diabetes according to baseline hypertension status
Incidence (% per year) Baseline hypertension status Hypertension (high blood pressure) was defined as having a blood pressure ≥ 140/90 mmHg and/or taking blood-pressure lowering medication.

21 Incidence of diabetes according to baseline dyslipidaemia status
Incidence (% per year) Dyslipidaemia status at baseline Dyslipidaemia was defined as those with triglycerides ≥ 2.0 mmol/L or high-density lipoprotein cholesterol levels < 1.0 mmol/L.

22 Incidence of diabetes according to baseline metabolic syndrome status
Incidence (% per year) NOTES The annual incidence of diabetes in those who had the metabolic syndrome according to the International Diabetes Federation definition (see slide 49), was greater than those who did not have metabolic syndrome at baseline. This annual incidence was four times greater for females and three times greater for males. Baseline metabolic syndrome status Metabolic syndrome was defined according to the definition by the International Diabetes Federation.

23 Diabetes  Key findings
Every year 0.8% of Australian adults develop diabetes Every day in Australia approximately 275 adults develop diabetes Those with pre-diabetes were 10–20 times more likely to develop diabetes than those with normal blood glucose levels Obesity, hypertension, dyslipidaemia, physical inactivity and the metabolic syndrome each increased the risk for developing diabetes

24 Obesity

25 Body mass index classification
Body mass index (kg/m2) Normal < 25.0 Overweight – 29.9 Obese ≥ 30.0

26 Classification of abdominal obesity by waist circumference
Waist circumference (cm) Males Females Normal < < 80.0 Overweight – – 87.9 Obese ≥ ≥ 88.0

27 Age-specific prevalence (%) of obesity* by BMI & waist circumference
Age (years) Classification Total BMI Males Females Persons Waist Males Females Persons * BMI  30 kg/m²; Waist circumference: males  102 cm; females  88 cm

28 Mean weight change over five years according to baseline age
Mean change in weight (kg) - 0.3 - 2.2 25 – 34 35 – 44 45 – 54 55 – 64 65 – 74 ≥ 75 Total Baseline age (years)

29 Mean body mass index change over five years according to baseline age
1.0 1.0 Mean change in BMI (kg/m2) - 0.2 25 – 34 35 – 44 45 – 54 55 – 64 65 – 74 ≥ 75 Total Baseline age (years)

30 Mean change in waist circumference (cm)
Mean waist circumference change over five years according to baseline age 3.0 3.0 2.0 Mean change in waist circumference (cm) 25 – 34 35 – 44 45 – 54 55 – 64 65 – 74 ≥ 75 Total Baseline age (years)

31 Mean weight change (kg)
Mean weight change over five years according to baseline body mass index status Mean weight change (kg) 1.0 Baseline BMI status

32 Mean waist circumference change (cm)
Mean waist circumference change over five years according to baseline BMI status 2.0 Mean waist circumference change (cm) Baseline BMI status

33 Incidence of obesity according to baseline body mass index status
Incidence (% per year) 2.0 Baseline BMI status

34 Proportion of individuals classified by body mass index in 2004–05 according to baseline body mass index status BMI status at baseline BMI in 2004–05 n Normal n (%) Overweight Obese 2,369 1,831 (77.3) 530 (22.4) 8 (0.34) 2,560 194 (7.6) 1,917 (74.9) 449 (17.5) 1,356 6 (0.4) 120 (8.9) 1,230 (90.7) Total 6,285 2,031 2,567 1,687 Body mass index (BMI: weight/height2) was categorised into three groups: (i) normal: BMI < 25.0 kg/m2; (ii) overweight: 25.0─29.9 kg/m2; and (iii) obese: ≥ 30.0 kg/m2.

35 Waist circumference categories in 2004–05
Proportion of individuals classified by waist circumference in 2004–05 according to baseline waist circumference categories Waist circumference categories at baseline Waist circumference categories in 2004–05 n Normal n (%) Overweight Obese 2,496 1,752 (70.2) 628 (25.2) 116 (4.7) 1,637 301 (18.4) 771 (47.1) 565 (34.5) 2,163 44 (2.0) 238 (11.0) 1,881 (87.0) Total 6,296 2,097 2,562 Waist circumference: (i) normal: < 94.0 cm for males, < 80.0 cm for females; (ii) overweight: 94.0─101.9 cm for males, 80.0─87.9 cm for females; (iii) obese: ≥ cm for males, ≥ 88.0 cm for females.

36 Obesity  Key findings People aged < 65 years showed an average weight increase of 1.8 kg over five years People aged ≥ 65 years showed a loss in weight of 0.8 kg over the same period Waist circumference  average gain over five years was 2.1 cm; greater in females than males Younger people gained more weight and had a greater increase in waist circumference than did older people Twice as many overweight people became obese as reverted to normal

37 Hypertension

38 Role of hypertension High blood pressure is a risk factor for cardiovascular and renal disease For individuals with diabetes, high blood pressure is a risk factor for microvascular complications as well as cardiovascular disease The baseline study found that 28.8% of adults ≥ 25 years of age were classified as hypertensive (BP ≥ 140/90 mmHg or taking BP lowering medication)

39 Classification of blood pressure
Systolic blood Diastolic blood Blood-pressure pressure (mmHg) pressure (mmHg) lowering medication Normal < 140 and < 90 and No Hypertension ≥ 140 or ≥ 90 or Yes Guidelines Subcommittee. J Hypertens 1999; 17: 15183.

40 Prevalence (%) of adequate blood pressure
Prevalence (%) of adequate blood pressure* control among people on anti-hypertensive therapy Age (years) 25–34 35–44 45–54 55–64 65– Total Males Females Persons *Systolic pressure  140 mmHg, and a diastolic pressure  90 mmHg, and on anti-hypertensive medication

41 Hypertension status in 2004–05
Proportion of individuals classified with hypertension in 200405 according to baseline hypertension Hypertension status in 2004–05 Hypertension status at baseline n Normal BP n (%) Hypertension 4,353 3,749 (86.1) 604 (13.9) 1,965 354 (18.0) 1,611 (82.0) Total 6,318 4,103 2,215

42 Incidence of hypertension according to baseline age
Incidence (% per year) Baseline age (years)

43 Baseline glucose tolerance status
Incidence of hypertension according to baseline glucose tolerance status Incidence (% per year) Baseline glucose tolerance status NGT ─ normal glucose tolerance; IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance; DM – diabetes mellitus

44 Incidence of hypertension according to baseline body mass index status
Incidence (% per year) Baseline BMI status BMI: Body mass index; where (i) normal was a BMI of < 25.0 kg/m2; (ii) overweight was a BMI of 25.0─29.9 kg/m2; and (iii) obese was a BMI of ≥ 30.0 kg/m2.

45 Incidence of hypertension according to baseline smoking status
Incidence (% per year) Baseline smoking status

46 Hypertension  Key findings
3.0% of adults develop hypertension every year The risk increases with age from 1.0% per year at 2534 years of age to 8.4% per year at 6574 years of age Those at greatest risk are people: With diabetes and pre-diabetes (females higher risk than males) Who are overweight or obese (females higher risk than males) Who smoke (males higher risk than females)

47 Metabolic syndrome

48 Significance of the metabolic syndrome
The metabolic syndrome is characterised by central or abdominal obesity, and a clustering of cardiovascular risk factors, such as: Abnormal glucose tolerance Raised triglycerides Decreased HDL-cholesterol Hypertension Hyperinsulinaemia (with underlying insulin resistance) The metabolic syndrome confers a higher risk of diabetes and cardiovascular disease

49 Classification of the metabolic syndrome
Component Threshold Waist circumference Europids: ≥ 94 cm males, ≥ 80 cm females South and South-East Asians: ≥ 90 cm males, ≥ 80 cm females Plus two or more of the following: Raised triglycerides ≥ 1.7 mmol/L or specific treatment for this lipid abnormality Reduced HDL-C < 1.03 mmol/L in males; < 1.29 mmol/L in females or specific treatment for this lipid abnormality Raised blood pressure Systolic ≥ 130 mmHg or diastolic ≥ 85 mmHg or treatment of previously diagnosed hypertension Raised plasma glucose Fasting plasma glucose ≥ 5.6 mmol/L or previously diagnosed type 2 diabetes Alberti KG et al. Lancet 2005; 366: 105962.

50 Incidence of the metabolic syndrome according to gender
3.0 Incidence (% per year)

51 Incidence of the metabolic syndrome according to baseline age
Incidence (% per year) Baseline age (years)

52 Baseline waist circumference categories
Incidence of the metabolic syndrome according to baseline waist circumference categories Incidence (% per year) Baseline waist circumference categories Waist circumference: (i) normal: < 94.0 cm for males, < 80.0 cm for females; (ii) overweight: 94.0─101.9 cm for males, 80.0─87.9 cm females; (iii) obese: ≥ cm for males, ≥ 88.0 cm for females.

53 Baseline physical activity status
Incidence of the metabolic syndrome according to baseline physical activity Incidence (% per year) Baseline physical activity status

54 Incidence of the metabolic syndrome according to baseline glucose tolerance status
Incidence (% per year) Baseline glucose tolerance status NGT ─ normal glucose tolerance; IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance; DM – diabetes mellitus

55 Metabolic syndrome  Key findings
The risk of developing the metabolic syndrome: Was six times greater in people who were obese than those who were normal weight Was two times greater in people with diabetes than those with normal glucose tolerance Was greater in physically inactive people Increased with increasing age Was greater for males than females

56 Chronic kidney disease

57 Significance of chronic kidney disease
Individuals with chronic kidney disease are at increased risk of end-stage renal failure, and premature cardiovascular disease1,2 The incidence of end-stage kidney disease is 95 cases/million population per annum3 Diabetes is a leading cause – responsible for 30% of all new cases3 1. Anavekar NS et al. N Engl J Med 2004; 351: 1285 Go AS et al. N Engl J Med 2004; 351: 1296 McDonald SP et al. The 28th report of the Australia and New Zealand Dialysis and Transplant Registry 2006.

58 Definitions Estimated impaired glomerular filtration rate, eGFR, defined as < 60 mL/min/1.73 m2 Abnormal albuminuria defined as spot urine albumin:creatinine ≥ 2.5 mg/mmol for males and ≥ 3.5 mg/mmol for females

59 Incidence of impaired glomerular filtration rate according to gender
Incidence (% per year)

60 Incidence of impaired glomerular filtration rate according to baseline age
Incidence (% per year) Baseline age (years)

61 Incidence of impaired glomerular filtration rate according to baseline glucose tolerance status
Incidence (% per year) Baseline glucose tolerance status NGT ─ normal glucose tolerance; IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance; DM ─ diabetes mellitus.

62 Baseline hypertension status
Incidence of impaired glomerular filtration rate according to baseline hypertension status Incidence (% per year) Baseline hypertension status Hypertension (high blood pressure) was defined as having a blood pressure ≥ 140/90 mmHg and/or taking blood-pressure lowering medication.

63 Incidence of albuminuria according to gender
1.0 Incidence (% per year)

64 Incidence of albuminuria according to baseline age
Incidence (% per year) Baseline age (years)

65 Baseline glucose tolerance status
Incidence of albuminuria according to baseline glucose tolerance status Incidence (% per year) Baseline glucose tolerance status NGT ─ normal glucose tolerance; IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance; DM – diabetes mellitus

66 Incidence of albuminuria according to baseline hypertension status
Incidence (% per year) Baseline hypertension status Hypertension (high blood pressure) was defined as having a blood pressure ≥ 140/90 mmHg and/or taking blood-pressure lowering medication.

67 Chronic kidney disease  Key findings
Approximately 1% of adults developed chronic kidney disease each year Approximately 1% of adults developed albuminuria each year People with hypertension have three times the risk of developing impaired GFR and albuminuria People with diabetes have five times the risk of developing albuminuria, and twice the risk of developing reduced kidney function

68 Mortality

69 Mortality rates AusDiab 2005 examined the 5-year all-cause mortality rates for males and females, for different age groups and for different levels of glucose tolerance The relative mortality risk was calculated for independent risk factors Over a median time of 5.2 years there were 355 deaths (208 males, 147 females). This represents a mortality rate of 6.1 per 1,000 person years

70 Total mortality according to baseline glucose tolerance status
Mortality rate (per 1000 py) Baseline glucose tolerance NGT ─ normal glucose tolerance; IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance; NDM ─ newly diagnosed diabetes; KDM ─ previously diagnosed diabetes.

71 All-cause mortality hazard ratio Baseline glucose tolerance status
Relative risk of mortality for people with pre-diabetes and diabetes compared with people with NGT* NGT IGT IFG NDM KDM All-cause mortality hazard ratio Baseline glucose tolerance status * After accounting for other risk factors. Bars represent 95% confidence intervals NGT ─ normal glucose tolerance; IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance; NDM ─ newly diagnosed diabetes; KDM ─ previously diagnosed diabetes.

72 Relative risk of mortality associated with various risk factors*
4 3 All–cause mortality hazard ratio 2 1 CVD KDM Smoking Hypertension Albuminuria Impaired GFR Baseline risk factors * After accounting for other risk factors. Bars represent 95% confidence intervals

73 Baseline glucose tolerance status among those dying of cardiovascular disease
21% 33% 13% 13% 20% NGT ─ normal glucose tolerance; KDM – previously diagnosed diabetes; NDM – newly diagnosed diabetes IFG ─ impaired fasting glucose; IGT ─ impaired glucose tolerance.

74 Prevalence (%) of smoking status among Australian residents
Percentage Smoking status

75 * Age standardised to the 1991 Australian population
Trends in the age-standardised* prevalence (%) of hypertension: 1980 – 2000 Percentage Year * Age standardised to the 1991 Australian population ABS. Population by age and sex. Canberra: ABS, 1999

76 Mortality  Key findings
Over five years: People with previously known diabetes were twice as likely to die as were those with normal glucose tolerance People with previously known diabetes had a similar risk of mortality to smokers and people with previous cardiovascular disease Pre-diabetes was associated with a 4555% increase in mortality risk Over two-thirds of all cardiovascular disease deaths occurred in people with diabetes or pre-diabetes

77 Survey methods and response rates

78 Sampling frame for the AusDiab follow-up 2004 – 05
Individuals participating in the baseline survey n = 11,247 Individuals ineligible for invitation n = 459 Requested no further contact = 128 Deceased = 310 Excluded* = 21 Total individuals eligible for invitation to AusDiab 2004–05 n = 10,788 * ‘Excluded’ – included participants who had moved into a nursing facility classified for high care, or were ineligible due to chronic or terminal illness

79 Response rates to the AusDiab survey 2004 –5
Eligible participants 10,788 Cancelled 1,990 On-site attendance 6,400 Attendance at external pathology laboratory 137 Health conditions telephone questionnaire only 2,261 Participated in AusDiab survey 2004–05 8,798

80 Response rates by state or territory
State Number On-site Pathology Self-reported Overall eligible testing laboratory medical responders attendance* conditions only n n (%) n (%) n (%) n (%) VIC 1, (57.5) 52 (3.6) 337 (23.6) 1,210 (84.7) WA 1, (64.9) 28 (1.8) 210 (13.8) 1,228 (80.5) NSW 1, (59.7) 14 (1.0) 323 (22.1) 1,209 (82.9) TAS 1,700 1,102 (64.8) 2 (0.1) 296 (17.4) 1,400 (82.4) SA 1, (55.6) 29 (1.7) 467 (27.5) 1,441 (84.8) NT 1, (58.4) 5 (0.4) 189 (15.7) 895 (74.5) QLD 1, (54.6) 7 (0.4) 433 (24.8) 1,394 (79.7) ACT (60.0) 0 (0) 6 (24.0) 21 (84.0) Total 10,788 6,400 (59.3) 137 (1.3) 2,261 (21.0) 8,798 (81.6) * External pathology laboratory facilities were either not available or were limited in TAS, SA, NT and QLD

81 Sponsors The AusDiab study gratefully acknowledges the generous support given by: National Health and Medical Research Council (NHMRC) Australian Government Department of Health and Aging Abbott Australasia Alphapharm AstraZeneca Aventis Pharma Bio-Rad Laboratories Bristol-Myers Squibb City Health Centre – Diabetes Service, Canberra Department of Health and Community Services, Northern Territory Department of Health and Human Services, Tasmania Department of Health, NSW Department of Health, WA Department of Health, SA Department of Human Services, VIC Diabetes Australia Diabetes Australia Northern Territory Eli Lilly Australia Estate of the Late Edward Wilson GlaxoSmithKline Highpoint Shopping Centre Jack Brockhoff Foundation Janssen-Cilag Kidney Health Australia Marian & EH Flack Trust Menzies Research Institute Merck Sharp & Dohme Multiplex Novartis Pharmaceuticals Novo Nordisk Pharmaceuticals Pfizer Pty Ltd Pratt Foundation Queensland Health Roche Diangonostics Australia Royal Prince Alfred Hospital, Sydney Sanofi-Synthelabo

82 Principal Investigators Associate Investigators
Contributors Principal Investigators Paul Z Zimmet AO International Diabetes Institute Robert Atkins AM Department of Epidemiology and Preventive Medicine, Monash University Timothy Welborn AO Department of Medicine, University of Western Australia Jonathan Shaw International Diabetes Institute Associate Investigators Stan Bennett Australian Institute of Health and Welfare Damien Jolley Monash Institute of Health Services Research, Monash University Terry Dwyer AM Murdoch Children’s Research Institute Stephen Colagiuri Department of Endocrinology, Prince of Wales Hospital Pat Phillips Department of Endocrinology, Queen Elizabeth Hospital Kerin O’Dea Department of Medicine, University of Melbourne Collaborators Liz Bingham Department of Health and Human Services, Tasmania Steve Chadban Royal Prince Alfred Hospital and University of Sydney Terry Coyne School of Population Health, University of Queensland John McNeil Department of Epidemiology and Preventive Medicine, Monash University Neville Owen School of Population Health, University of Queensland Kevan Polkinghorne Department of Nephrology, Monash Medical Centre Robyn Tapp Department of Epidemiology and Preventive Medicine, Monash University Hugh Taylor Centre for Eye Research Australia Andrew Tonkin Department of Epidemiology and Preventive Medicine, Monash University Tien Wong Centre for Eye Research Australia

83 AusDiab report authors
D Dunstan P Zimmet T Welborn R Sicree T Armstrong R Atkins A Cameron J Shaw S Chadban E Barr D Magliano P Zimmet K Polkinghorne R Atkins D Dunstan S Murray J Shaw

84 AusDiab Staff AusDiab Project Manager: Shirley Murray
Epidemiologists: Elizabeth Barr, Adrian Cameron, David Dunstan, Dianna Magliano, Richard Sicree. IDI Field Staff: Annaliese Bonney, Nicole Meinig, Theresa Whalen. IDI Support Staff: Travis Clarke, Gay Filby, Sue Fournel, Hasan Jahangir, Larna Prout, Carol Robinson, Marc Seifman, Debbie Shaw, Lisa Southgate, Ray Spark, Kajen Vivekananthan, Jonathan Zimmerman. Other contributors: Theresa Dolphin, Irene Tam, Gabriella Tikellis, Adam Meehan, Genevieve Healy, Sarah White.

85 AusDiab information For more information and publications visit:
Reports and newsletters available: AusDiab Report 2001 AusDiab Report 2006 Newsletter September 2004 Newsletter September 2006 http//:www.diabetes.com.au/research.php?regionID=181&page=ausdiab_home


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