The Pathophysiology of Diabetes and Prediabetes: Understanding the Relative Roles of Impaired Beta-Cell Function and Insulin Resistance in Asian Indians 公开
Staimez, Lisa Rachel (2013)
Published
Abstract
Type 2 diabetes is a wide-reaching, global disease, strongly linked to obesity, unhealthy nutrition, and physical inactivity. Both insulin resistance and beta-cell dysfunction are known causes of the disease, yet questions exist regarding the roles of these two factors in the pathophysiology of diabetes. Asian Indians, a high-risk population for diabetes, have phenotypic characteristics that appear related to poor beta-cell function as well as insulin resistance, and thus, Asian Indians may be an informative population in detangling pathophysiological questions surrounding these two factors. This study examined 1,285 individuals without known diabetes who were screened in the Diabetes Community Lifestyle Improvement Program in Chennai, India. Individuals had a 75g OGTT with glucose and insulin measured at 0, 30, and 120 min. Measures included insulin resistance (HOMA-IR), insulin sensitivity (1/fasting insulin), and beta-cell function (DIo = [ΔI0-30 /ΔG0-30] x [1/fasting insulin]), and HbA1c (%). Cross sectional and longitudinal analyses consisted of polytomous logistic regression, multiple linear regression, and piecewise spline analysis. Major findings included: (1) decreases in beta-cell function were marked between normoglycemic (NGT) individuals and those with prediabetes; changes in the rate of decline for beta-cell function were detected at 5.0, 5.25, 6.25 mmol/L (90, 95, 113 mg/dL) for fasting glucose and 5.25, 5.75, and 7.5 mmol/L (95, 104, and 135 mg/dL) for two-hour postchallenge glucose; the tandem increases of insulin resistance were less dramatic between NGT and prediabetes, increasing steadily across the spectrum of glycemia; (2) beta-cell dysfunction is a critical factor for those with early dysglycemia (i.e., isolated impaired fasting glucose or isolated impaired glucose tolerance), above and beyond insulin resistance; and (3) among individuals with prediabetes at baseline, both beta-cell function and insulin resistance were significantly associated with glycemia at one year. Data from this large, community-based study of Asian Indians suggest that reduced beta-cell function is prominent at glycemic levels that are clinically defined as normoglycemia. Validation in representative, multi-ethnic cohorts is needed to corroborate these findings. Future lifestyle intervention studies should test the effects of improved diet, increased physical activity, and reduced body weight on both insulin resistance and beta-cell function for diabetes prevention and control.
Table of Contents
Chapter 1: Introduction.. 1
Chapter 2: Background.. 5
Prevalence of Diabetes and Prediabetes. 5
Pathophysiology of Diabetes. 7
Insulin Resistance. 8
Poor Pancreatic Beta-Cell Function. 9
Nutrition-Related Risk Factors for Diabetes. 11
Diet 11
Physical activity. 13
Body Mass Index. 14
Abdominal Obesity. 14
Evidence from Lifestyle Interventions. 15
Chapter 3: A Systematic Review of Overweight, Obesity, and Type 2 Diabetes Among Asian American Subgroups. 16
Chapter 4: Dissertation Methods. 36
Study Participants. 36
Study Procedures. 39
Key Variables. 40
Data Analysis. 41
Chapter 5: Evidence of Reduced Beta-Cell Function in Asian Indians with Mild Dysglycemia.. 42
Chapter 6: Beta-cell function and insulin resistance in prediabetes and normoglycemia.. 50
Abstract. 50
Introduction. 52
Research Methods. 54
Study Participants. 54
Study Procedures. 55
Key Variables. 56
Data Analysis. 57
Results. 58
Change Points of Oral Disposition Index in Normoglycemia and Prediabetes. 58
Change Points of HOMA-IR in Normoglycemia and Prediabetes. 60
Discussion. 60
Acknowledgements. 68
Chapter 6 Tables and Figures. 69
Chapter 7: Longitudinal Evidence for the Role of Reduced Beta-Cell Function on Glycemia in Asian Indians With Mild Dysglycemia.. 80
Abstract. 80
Introduction. 82
Research Methods. 83
Study Participants. 83
Study Procedures. 85
Key Variables. 86
Data Analysis. 86
Results. 87
Discussion. 89
Chapter 7 Tables and Figures. 97
Chapter 8: Discussion.. 104
Summary of Findings. 104
Limitations. 110
Strengths. 112
Implications and Future Research. 113
Conclusions. 116
References. 117
List of Tables
Table 6-1. Best fit models for fasting glucose and estimated DIo among D-CLIP participants with normal or elevated fasting glucose (n=1,159) 70
Table 6-2. Best fit models for two-hour glucose and estimated DIo among D-CLIP participants with normal or elevated two-hour glucose (n=1029) 73
Table 6-3. Summary of results for piecewise linear spline regression.. 79
Table 7-1. One Year Change in Table Form, n=474. 97
Table 7-2. Exploratory, standardized models of fasting glucose at 1 year (n= 474) 98
Table 7-3. Final standardized models of fasting glucose at 1 year follow up after interaction testing and confounding assessment (n= 474) 99
Table 7-4. Exploratory standardized models of two-hour glucose at 1 year (n= 474) 100
Table 7-5. Final standardized models of 2-hour glucose at 1 year follow up after interaction testing and confounding assessment (n= 474) 101
Table 7-6. Exploratory standardized models of outcome HbA1c at 1 year (n= 474) 102
Table 7-7. Final standardized models of HbA1c at 1 year follow up after interaction testing and confounding assessment (n= 474) 103
List of Figures
Figure 2-1. Early susceptibility to impaired beta-cell function and development of type 2 diabetes mellitus 10
Figure 2-2. Synergy of diet and genetic susceptibility on diabetes risk among white men in the Health Professionals Follow-Up Study. 12
Figure 4-1. Flow diagram of study sample and exclusions across Dissertation Aims 1, 2, and 3 38
Figure 4-2. D-CLIP timeline and time periods for Dissertation Aims 1, 2, and 3. 39
Figure 6-1. Estimated DIo (95% CI) from fasting glucose in 1,159 individuals in the D-CLIP trial 69
Figure 6-2. Estimated DIo (95% CI) from categorical fasting glucose in 1,159 individuals in the D-CLIP trial 69
Figure 6-3. Best fit linear model of DIo (95% CI) from fasting glucose: change points at 5.0, 5.25, and 6.25 mmol/L. 71
Figure 6-4. Estimated DIo (95% CI) from two-hour glucose in 1,029 individuals in the D-CLIP trial 72
Figure 6-5. Estimated DIo (95% CI) from categorical two-hour glucose in 1,029 individuals in the D-CLIP trial. 72
Figure 6-6. Best fit model of estimated DIo (95% CI) with change points 5.5 and 5.75 mmol/L 74
Figure 6-7. Another good model of estimated DIo (95% CI) with change points 5.5, 5.75, and 7.5 mmol/L 74
Figure 6-8. Estimated DIo (95% CI) from HbA1c in 967 individuals in the D-CLIP trial - simple linear model 75
Figure 6-9. Estimated DIo (95% CI) from categorized HbA1c in 967 individuals in the D-CLIP trial 75
Figure 6-10. Estimated HOMA-IR (95% CI) from fasting glucose in 1,159 individuals in the D-CLIP trial 76
Figure 6-11. Estimated HOMA-IR (95% CI) from categorical fasting glucose in 1,159 individuals in the D-CLIP trial. 76
Figure 6-12. Estimated HOMA-IR (95% CI) from 2-hour glucose in 1,029 individuals in the D-CLIP trial 77
Figure 6-13. Estimated HOMA-IR (95% CI) from categorical 2-hour glucose in 1,029 individuals in the D-CLIP trial. 77
Figure 6-14. Estimated HOMA-IR (95% CI) from HbA1c in 967 individuals in the D-CLIP trial 78
Figure 6-15. Estimated HOMA-IR (95% CI) from HbA1c in 967 individuals in the D-CLIP trial 78
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CurrentDiabetesReviews_2013.pdf () | 2018-08-28 11:07:17 -0400 |
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Staimez_DaibetesCare_ 2013.pdf () | 2018-08-28 11:07:23 -0400 |
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