2008 16th eco
Upcoming SlideShare
Loading in...5
×
 

Like this? Share it with your network

Share

2008 16th eco

on

  • 131 views

 

Statistics

Views

Total Views
131
Views on SlideShare
131
Embed Views
0

Actions

Likes
0
Downloads
0
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

2008 16th eco Presentation Transcript

  • 1. Relationship between White Blood Cell number and Total Body Fat as well as Visceral Fat, in Smoking and Non-smoking subjects. Chala E, Kapantais E. Diabetes, Obesity and Metabolism Department, Metropolitan Hospital Neo Faliro, Athens Greece
  • 2. IntroductionHuman adipose tissue is characterized by the ability to produce andrelease inflammatory proteins collectively known asadipokines, such as TNF-a, Interleukin-6, Interleukin-8 andmonocyte chemoattractant protein-1. Visceral adipose tissue seemsto be more closely associated with the inflammatory state thansubcutaneuous adipose tissue, since higher amounts of Interleukin-6, Interleukin-8 and monocyte chemoattractant protein-1 arereleased from the visceral adipose tissue depot.In clinical practice, activation of the immune system andinflammation may be detected by an increase in a number ofmarkers. Among them, white blood cell count is undoubtedly notonly the easiest to obtain and the least expensive but also the mostrobust, so that if a relationship could be shown between whiteblood cells number and obesity, this would further prove theconnection of obesity and low-grade inflammation.
  • 3. IntroductionWhite blood cells, as markers of inflammation are very sensitivebut are not specific, since a number of conditions other thaninflammation could lead to an increase in their number:corticosteroid treatment, leukemia and other hematologicdisorders, trauma or tissueinjury, malignancies, nausea, vomiting, stress of any kind suchas excitement, exercise, pain etc. Smoking has also been shownto have an influence on white blood cell count. It is noteworthythat smokers, on average, exhibit an elevated peripheral whiteblood cell count, about 30% higher than non-smokers.
  • 4. AimAim of our study was to investigate:A) The existence of any relationship between white blood cell count, as a marker of low-grade inflammation, and obesity, as expressed by total body fat and by visceral fat.B) The effect of smoking on this relationship.
  • 5. Subjects-MethodsFor this purpose, we studied retrospectively 582 subjects (247 malesand 335 females), all recruited from the Outpatient Clinic of ourdepartment. The characteristics of the subjects studied are shown intable 1.Since white blood cell count is not a specific marker of inflammation,weexcluded from the study conditions known to have an influence onWhite Blood Cells. (table 2). We also excluded persons with White BloodCells>11.000/mm3 since our aim was low grade systemic inflammation inotherwise healthy and not overtly stressed of infected subjects.
  • 6. Subjects-MethodsAfter an overnight fasting, blood was drawn andanthropometric measurements were performed (table 3).
  • 7. Males Females (247) (335) Age (years) 47.4 13.7 44.4 13.4 BMI (kg/m2) 34.5 6.0 33.7 6.5Smoking (Yes/No) 82/165 135/200 (Table 1: Subjects studied)
  • 8. • Medications affecting White Blood Cells• Infections• Liver dysfunction• Sedimentation Rate >40/1h• White Blood Cells >11000/mm3• Thyroid dysfunction• Type 1 diabetics• Uncontrolled type 2 diabetics (Table 2: Exclusion criteria)
  • 9. Fasting Blood Anthropometric Measurements Measurements Hematology BMISedimentation Rate Waist Circumference Biochemistry WHR HbA1c % Total Body Fat (BIA) Insulin Sagittal Abdominal Diameter(Table 3: Fasting blood measurement and anthropometric measurements)
  • 10. Males Females pAge (years) 47.4 13.7 44.4 13.4 0.008BMI (kg/m2) 34.5 6.0 33.7 6.5 NSWaist Circumference (cm) 114.8 13.1 101.6 13.8 0.000WHR 1.09 0.08 0.93 0.11 0.000Sagittal Abdominal Diameter (cm) 27.18 3.88 24.23 3.83 0.000Total Body Fat % (BIA) 35.94 6.46 43.90 7.23 0.000Visceral Fat (kg) 7.647 2.647 3.799 1.309 0.000White Blood Cells (x1000/mm3) 7.39 1.58 7.00 1.50 0.002Hematocrit (%) 45.1 3.2 39.9 3.0 0.000Platelets (x1000/mm3) 238 51 273 65 0.000Sedimentation Rate (mm/1h) 10.1 8.3 16.3 8.5 0.000Plasma Glucose (mg/dl) 127 51 106 37 0.000Plasma Insulin (μIU/ml) 15.75 12.44 13.23 9.99 0.02HbA1c (%) 6.77 1.81 6.35 1.59 0.02HOMA-IR 4.85 4.07 3.58 3.13 0.000 (t-test and non-parametric test were used as appropriate)
  • 11. Results 11,0 10,0 White Blood Cells 9,0 8,0 7,0 6,0 5,0 4,0 n=247 n=335 male female sex (m /f) Males had higher WBC than females(7.394 1.584 vs. 6.995 1.495, p=0.002)
  • 12. Results 12 11 10White Blood Cells 9 8 7 6 5 no smoker 4 smoker N= 165 82 200 135 male female Smokers had higher WBC than non-smokers, in both sexes (Males: 7.849 ± 1.566 vs. 7.168 ± 1.548, p=0.001 Females: 7.321 ±1.353 vs. 6.775 ± 1.549, p=0.001)
  • 13. Results 82 out of 247 males and 135 out of 335 females were smokers (X2=3.065, p=0.08)Male smokers were more fanatic than female ones: Males: 22.23 ± 15.55 cigarettes/day Females: 17.44 ± 12.40 cigarettes/day (p=0.028)
  • 14. Results Males-smokers Females-smokers 11 11 10 10 9 9 White Blood Cells 8 8 7 7 6 6 5 5 4 4 0 20 40 60 80 100 0 10 20 30 40 50 60 70 cigarettes/day cigarettes/day In male smokers, there was In female smokers, a positive relationship between no relationship was found betweenWBC and number of cigarettes per day. WBC and number of cigarettes per day. (r=0.244, p=0.027) (r=0.101, p=0.246)
  • 15. Results Males: Non-smoking Males: Smoking 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 20 30 40 50 60 20 30 40 50 60 Body Mass Index (kg/m2) Body Mass Index (kg/m2)In male non-smokers, there was a positive In male smokers, no relationship relationship between WBC and BMI. was found between WBC and BMI. (r=0.186, p=0.017) (r=0.110, p=0.326)
  • 16. Results Females: Non-smoking Females: Smoking 12 11 10 10 White Blood Cells 9 8 8 7 6 6 4 5 2 4 10 20 30 40 50 60 70 10 20 30 40 50 60 Body Mass Index (kg/m2) Body Mass Index (kg/m2) In female non-smokers, there was In female smokers, no relationshipa positive relationship between WBC and BMI. was found between WBC and BMI. (r=0.306, p=0.000) (r=0.162, p=0.061)
  • 17. Results Males: Non-smoking Males: Smoking 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 10 20 30 40 50 60 70 10 20 30 40 50 60 70 Total Body Fat % (BIA) Total Body Fat % (BIA)In male non-smokers, there was In male smokers, no relationshipa positive relationship between was found between WBC and Total Body Fat % (BIA) WBC and Total Body Fat % (BIA). (rs=0.156, p=0.045) (rs=0.211, p=0.058)
  • 18. Results Females: Non-smoking Females: Smoking 12 12 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 10 20 30 40 50 60 10 20 30 40 50 60 Total Body Fat % (BIA) Total Body Fat % (BIA)In female non-smokers, there was In female smokers, there was a positive relationship between a positive relationship between WBC and Total Body Fat % (BIA). WBC and Total Body Fat % (BIA). (r=0.288, p=0.000) (r=0.180, p=0.037)
  • 19. Results Males: Non-smoking Males: Smoking 11 11 10 10 9 White Blood Cells 9 8 8 7 7 6 6 5 5 4 4 80 90 100 110 120 130 140 150 80 90 100 110 120 130 140 150 Waist Circumference (cm) Waist Circumference (cm)In male non-smokers, there was In male smokers, no relationshipa positive relationship between was found between WBC and Waist Circumference WBC and Waist Circumference. (r=0.198, p=0.012) (r=0.151, p=0.176)
  • 20. Results Females: Non-smoking Females: Smoking 12 12 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 60 70 80 90 100 110 120 130 140 150 60 70 80 90 100 110 120 130 140 150 Waist Circumference (cm) Waist Circumference (cm)In female non-smokers, there was In female smokers, no relationship a positive relationship between was found between WBC and Waist Circumference. WBC and Waist Circumference. (r=0.291, p=0.000) (r=0.112, p=0.201)
  • 21. Results Males: Non-smoking Males: Smoking 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 18 20 23 25 28 30 33 35 38 40 18 20 23 25 28 30 33 35 38 40 Sagittal Abdominal Diametre (cm) Sagittal Abdominal Diametre (cm) In male non-smokers, there was In male smokers, no relationship a positive relationship between was found betweenWBC and Sagittal Abdominal Diameter WBC and Sagittal Abdominal Diameter. (r=0.177, p=0.025) (r=0.141, p=0.206)
  • 22. Results Females: Non-smoking Females: Smoking 12 12 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 15 20 25 30 35 40 15 20 25 30 35 40 Sagittal Abdominal Diametre (cm) Sagittal Abdominal Diametre (cm) In female non-smokers, there was In female smokers, there was a positive relationship between a positive relationship betweenWBC and Sagittal Abdominal Diameter WBC and Sagittal Abdominal Diameter (r=0.289, p=0.000) (r=0.177, p=0.042)
  • 23. Results Males: Non-smoking Males: Smoking 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 0 2 4 6 8 10 12 14 16 0 2 4 6 8 10 12 14 16 Visceral fat (kg) Visceral fat (kg)In male non-smokers, there was In male smokers, no relationshipa positive relationship between was found between WBC and kg of Visceral Fat. WBC and kg of Visceral Fat. (r=0.164, p=0.038) (r=0.141, p=0.206)
  • 24. Results Females: Non-smoking Females: Smoking 12 12 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8 Visceral fat (kg) Visceral fat (kg)In female non-smokers, there was In female smokers, there was a positive relationship between a positive relationship between WBC and kg of Visceral Fat. WBC and kg of Visceral Fat. (r=0.288, p=0.000) (r=0.177, p=0.042)
  • 25. Results Males: Non-smoking Males: Smoking 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 0 4 8 12 16 20 0 4 8 12 16 20 HOMA-IR HOMA-IRIn male non-smokers, no relationship In male smokers, no relationshipwas found between WBC and HOMA-IR. was found between WBC and HOMA-IR. (rs=0.080, p=0.308) (rs=0.123, p=0.271)
  • 26. Results Females: Non-smoking Females: Smoking 12 12 11 11 10 10 White Blood Cells 9 9 8 8 7 7 6 6 5 5 4 4 0 4 8 12 16 20 0 4 8 12 16 20 HOMA-IR HOMA-IR In female non-smokers, In female smokers,there was a positive relationship no relationship was found between WBC and HOMA-IR. between WBC and HOMA-IR. (rs=0.285, p=0.000) (rs=0.161, p=0.063)
  • 27. Results Multiple regression analysis(Dependent variable: White Blood Cell count) Males R=0.277, R square=0.077, F=9.979, p=0.000 Smoking (no/yes): beta=0.217, p=0.001 % Total Body Fat (ΒΙΑ): beta=0.189, p=0.003 Females R=0.401, R square=0.161, f=20.683, p=0.000 Age: beta= -0.270, p=0.000 Smoking (no/yes): beta=0.166, p=0.001 Sagittal Abdominal Diameter: beta=0.306, p=0.000
  • 28. Conclusions• Smoking is an important inducer of low grade systemic inflammation as expressed by WBC, mainly in males.• In non-smoking males as well as in smoking and non-smoking females, WBC are related to obesity and more importantly to its distribution as it is expressed by sagittal abdominal diameter and by kg of visceral fat.
  • 29. DiscussionSmoking seems to be a very important inducer of low-gradesystemic inflammation. It has been proposed that nicotine-induced catecholamine release might be the mechanism for thiseffect. Other studies support the hypothesis that cigarettesmoking causes bone marrow stimulation, probably throughproinflammatory factors released from alveolarmacrophages, such as TNF-a, IL-1, IL-8 and granulocyte-macrophage colony stimulating factor. It is of note that the samerelationship between smoking and increased leukocyte count hasbeen shown in adolescents, indicating that there appears to be arapid effect of smoking on white blood cells count that is unlikelyto be due to smoking induced chronic disease as seen in adultsmokers.
  • 30. DiscussionDespite the fact that in our study, there was a higher percentageof smokers between women than in men, in men, who are morefanatic smokers, smoking overwhelms obesity when it comes tolow-grade inflammation.Women, who are more amateurs when it comes to smoking, retainthe relationship between low-grade systemic inflammation asexpressed by White Blood Cells, and obesity, especially of centraldistribution, irrespectively of smoking status.
  • 31. Suggested Bibliography• Lidia Arcavi, Neal L. Benowitz. Cigarette smoking and infection. Arch Intern Med 2004;164:2206-2216• Marjolein Visser et al. Elevated c-reactive protein levels in overweight and obese adults. JAMA 1999;282:2131-2135• Barbora Vozarova et al. High white blood cell count is associated with a worsening of insulin sensitivity and predicts the development of type 2 diabetes. Diabetes 2002; 51:455-461• Stuart P. Weisberg et al. Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest; 112:1796-1808• Desai MY et al. Association of body mass index, metabolic syndrome and leukocyte count. Am J Cardiol 2006; 97:865-868.• Pratley RE et al. Relation of the white blood cell count to obesity and insulin resistance: effect of race and gender. Obesity Research 1995; 3:563-571