Clusters of carbohydrate-rich foods and associations with type 2 diabetes incidence : a prospective cohort study
(2023) In Nutrition Journal 22(1).- Abstract
Background: About one in ten adults are living with diabetes worldwide. Intake of carbohydrates and carbohydrate-rich foods are often identified as modifiable risk factors for incident type 2 diabetes. However, strong correlation between food variables can make it difficult to identify true associations. The purpose of this study was to identify clusters of carbohydrate-rich foods and analyse their associations with type 2 diabetes incidence in the Malmö Diet and Cancer Study cohort in southern Sweden. Methods: Dietary intake of 26 622 participants was assessed using a validated three-part diet history method: a 7-day food diary, a 168-item food frequency questionnaire, and a 60-minute interview. K-means clustering analysis identified... (More)
Background: About one in ten adults are living with diabetes worldwide. Intake of carbohydrates and carbohydrate-rich foods are often identified as modifiable risk factors for incident type 2 diabetes. However, strong correlation between food variables can make it difficult to identify true associations. The purpose of this study was to identify clusters of carbohydrate-rich foods and analyse their associations with type 2 diabetes incidence in the Malmö Diet and Cancer Study cohort in southern Sweden. Methods: Dietary intake of 26 622 participants was assessed using a validated three-part diet history method: a 7-day food diary, a 168-item food frequency questionnaire, and a 60-minute interview. K-means clustering analysis identified five clusters from 21 food variables. The Cox proportional hazard regression model was applied to calculate hazard ratios (HR) and 95% confidence intervals (CI) of the association between clusters and incident type 2 diabetes. Results: The cluster analysis resulted in five clusters; high vegetables/low added sugar, high sugar-sweetened beverages, high juice, high fruit, and high refined carbohydrates/low fruit & vegetables (reference). During mean follow-up of 18 years, 4046 type 2 diabetes cases were identified. After adjustment for potential confounding (including lifestyle, body mass index, and diet), a high fruit cluster (HR 0.86; 95% CI 0.78, 0.94) was inversely associated with type 2 diabetes compared to the reference cluster. No other significant associations were identified. Conclusions: A dietary pattern defined by a high intake of fruits was associated with a lower incidence of type 2 diabetes. The findings provide additional evidence of a potential protective effect from fruit intake in reducing type 2 diabetes risk. Future studies are needed to explore this association further.
(Less)
- author
- Olsson, Kjell LU ; González-Padilla, Esther LU ; Janzi, Suzanne LU ; Stubbendorff, Anna LU ; Borné, Yan LU ; Ramne, Stina LU ; Ericson, Ulrika LU and Sonestedt, Emily LU
- organization
- publishing date
- 2023-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Diet, Epidemiology, K-means clustering, Malmö Diet and Cancer Study, Nutrition, Type 2 Diabetes
- in
- Nutrition Journal
- volume
- 22
- issue
- 1
- article number
- 71
- publisher
- BioMed Central (BMC)
- external identifiers
-
- scopus:85179929988
- pmid:38111004
- ISSN
- 1475-2891
- DOI
- 10.1186/s12937-023-00906-0
- language
- English
- LU publication?
- yes
- id
- 78d6c496-306a-4f18-b8dc-90593828b085
- date added to LUP
- 2024-01-03 15:16:36
- date last changed
- 2024-09-20 03:01:09
@article{78d6c496-306a-4f18-b8dc-90593828b085, abstract = {{<p>Background: About one in ten adults are living with diabetes worldwide. Intake of carbohydrates and carbohydrate-rich foods are often identified as modifiable risk factors for incident type 2 diabetes. However, strong correlation between food variables can make it difficult to identify true associations. The purpose of this study was to identify clusters of carbohydrate-rich foods and analyse their associations with type 2 diabetes incidence in the Malmö Diet and Cancer Study cohort in southern Sweden. Methods: Dietary intake of 26 622 participants was assessed using a validated three-part diet history method: a 7-day food diary, a 168-item food frequency questionnaire, and a 60-minute interview. K-means clustering analysis identified five clusters from 21 food variables. The Cox proportional hazard regression model was applied to calculate hazard ratios (HR) and 95% confidence intervals (CI) of the association between clusters and incident type 2 diabetes. Results: The cluster analysis resulted in five clusters; high vegetables/low added sugar, high sugar-sweetened beverages, high juice, high fruit, and high refined carbohydrates/low fruit & vegetables (reference). During mean follow-up of 18 years, 4046 type 2 diabetes cases were identified. After adjustment for potential confounding (including lifestyle, body mass index, and diet), a high fruit cluster (HR 0.86; 95% CI 0.78, 0.94) was inversely associated with type 2 diabetes compared to the reference cluster. No other significant associations were identified. Conclusions: A dietary pattern defined by a high intake of fruits was associated with a lower incidence of type 2 diabetes. The findings provide additional evidence of a potential protective effect from fruit intake in reducing type 2 diabetes risk. Future studies are needed to explore this association further.</p>}}, author = {{Olsson, Kjell and González-Padilla, Esther and Janzi, Suzanne and Stubbendorff, Anna and Borné, Yan and Ramne, Stina and Ericson, Ulrika and Sonestedt, Emily}}, issn = {{1475-2891}}, keywords = {{Diet; Epidemiology; K-means clustering; Malmö Diet and Cancer Study; Nutrition; Type 2 Diabetes}}, language = {{eng}}, number = {{1}}, publisher = {{BioMed Central (BMC)}}, series = {{Nutrition Journal}}, title = {{Clusters of carbohydrate-rich foods and associations with type 2 diabetes incidence : a prospective cohort study}}, url = {{http://dx.doi.org/10.1186/s12937-023-00906-0}}, doi = {{10.1186/s12937-023-00906-0}}, volume = {{22}}, year = {{2023}}, }