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Ethnic Differences in the Relationship Between Insulin Sensitivity and Insulin Response
Open accessAbstract
OBJECTIVE: Human blood glucose levels have likely evolved toward their current point of stability over hundreds of thousands of years. The robust population stability of this trait is called canalization. It has been represented by a hyperbolic function of two variables: insulin sensitivity and insulin response. Environmental changes due to global migration may have pushed some human subpopulations to different points of stability. We hypothesized that there may be ethnic differences in the optimal states in the relationship between insulin sensitivity and insulin response. RESEARCH DESIGN AND METHODS: We identified studies that measured the insulin sensitivity index (SI) and acute insulin response to glucose (AIRg) in three major ethnic groups: Africans, Caucasians, and East Asians. We identified 74 study cohorts comprising 3,813 individuals (19 African cohorts, 31 Caucasian, and 24 East Asian). We calculated the hyperbolic relationship using the mean values of SI and AIRg in the healthy cohorts with normal glucose tolerance. RESULTS: We found that Caucasian subpopulations were located around the middle point of the hyperbola, while African and East Asian subpopulations are located around unstable extreme points, where a small change in one variable is associated with a large nonlinear change in the other variable. CONCLUSIONS: Our findings suggest that the genetic background of Africans and East Asians makes them more and differentially susceptible to diabetes than Caucasians. This ethnic stratification could be implicated in the different natural courses of diabetes onset.
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“East Asian populations are characterized by distinct metabolic and anthropometric profiles compared to Western populations, including lower body mass index (BMI), differences in body composition, and unique dietary patterns 11 , 12 .”
From A study of changes in insulin requirements related to the menstrual cycle in Japanese women with type 1 diabetes using the advanced hybrid closed‐loop system (2026) · cites this paper as [11]
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A machine learning model for optimizing treatment of patients with poorly controlled type 2 diabetes
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Metadata
- Authors
- Kodama, K., Tojjar, D., Yamada, S., Toda, K., Patel, C. J., & Butte, A. J.
- Affiliations
- Lucile Packard Children's Hospital (US)
- Lund University (SE)
- Kitasato Institute Hospital (JP)
- Corresponding author
- Kodama, Keiichi
- Butte, Atul J.
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2013-05-15
- Volume
- 36
- Issue
- 6
- Pages
- 1789-1796
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- PMC
- PMC3661854
- OpenAlex
- W2067663978
- Semantic Scholar
- 49e57510095279c6a41076455ff3e7a2ae6f8146
- Cited by
- 599
- References
- 44
- Citations by year
- 2026: 28 · 2025: 56 · 2024: 53 · 2023: 47 · 2022: 63 · 2021: 68 · 2020: 55 · 2019: 47 · 2018: 39 · 2017: 40 · 2016: 34 · 2015: 33 · 2014: 33 · 2013: 2
- FWCI
- 4.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Diabetes Care (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- U.S. National Library of Medicine (R01LM009719, T15LM007033)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Pancreatic function and diabetes
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- insulin sensitivity, insulin response, ethnic differences, canalization, hyperbolic relationship, acute insulin response to glucose, insulin sensitivity index, diabetes susceptibility, African populations, East Asian populations, Caucasian population, glucose tolerance, genetic background
- MeSH terms
- Humans, Insulin, Insulin Resistance, Black People, White People, Asian People
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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