The Dutch HbA1c Lifestyle Study (DAF-Study): Seasonal Variation of HbA1c in the Dutch Diabetes Population—Associations with Macronutrient Intake and Physical Activity

Background/Objectives: Seasonal variation in hemoglobin A1c (HbA1c) values has been previously documented, with physical activity (PA) and macronutrient intake (MNI) suggested as potential drivers. This study combines seasonal mean HbA1c values from the Dutch (pre)diabetes population with national survey data on PA and MNI from 2018 to 2021 to identify key associations. Methods: HbA1c data were collected from 24 laboratory organizations in the Netherlands and Dutch Caribbean. MNI and total energy intake data were extracted from the Dutch National Food Consumption Survey, while PA data came from the Dutch National Sports Participation Index Survey. Weighting factors were applied to align PA and MNI data with HbA1c data. Seasonal averages were analyzed for significant differences, and a prediction model compared PA and MNI with actual HbA1c values. Results: Among 5,635,920 HbA1c results, the average HbA1c increased by 0.71 mmol/mol (NGSP 0.06%) over four years, with an overall mean of 52.4 mmol/mol (NGSP 7.0%). Seasonal HbA1c variation showed a dip in summer–autumn and a peak in winter–spring (1.2 mmol/mol; NGSP 0.11%; p < 0.0001). MNI, except for total energy intake (which peaked in summer; p < 0.001), showed no significant trends or association with HbA1c (p = 0.157). PA decreased by 7.2% over the study period, with seasonal peaks in summer–autumn, showing an inverse relationship with HbA1c (p < 0.0001). During the COVID-19 lockdowns, PA significantly decreased, and mean HbA1c values increased more markedly than in previous years. The prediction model confirmed PA as a significant driver of seasonal HbA1c variation (p = 0.004). Conclusions: These findings suggest that PA is the strongest driver of seasonal variation in HbA1c. Public health initiatives and support programs promoting physical activity are essential for improving HbA1c regulation.

Authors

Institutions

Publication Details

Journal
Diabetology
Published
2025-11-03
DOI
https://doi.org/10.3390/diabetology6110135
Primary Topic
Nutritional Studies and Diet
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Dutch HbA1c Lifestyle Study (DAF-Study): Seasonal Variation of HbA1c in the Dutch Diabetes Population—Associations with Macronutrient Intake and Physical Activity

Erwin Kemna, Jacoline Brinkman, Margriet van Kogelenberg, Steef Kurstjens et al.
Diabetology
Nutritional Studies and Diet
article

The Dutch HbA1c Lifestyle Study (DAF-Study): Seasonal Variation of HbA1c in the Dutch Diabetes Population—Associations with Macronutrient Intake and Physical Activity

Erwin Kemna, Jacoline Brinkman, Margriet van Kogelenberg, Steef Kurstjens, Johannes G. Krabbe, Madeleen Bosma, Roseri de Beer, Linda M. Henricks, Silvia C. Endenburg, Karin Mohrmann, Annemarieke E. Loot, Martin P. Schuijt, Jurgen Kooren, Robert Wever, Isabelle A. Linden, Cas Weykamp, Christiaan L. Slim, Henk J.G. Bilo, Mieke Koenders, Pauline Verschuure, Jody van den Ouweland, Martine Deckers, M. van Oostendorp, Iris van Vlodrop, Stefan Coolen, Margo Molhoek
article en

Abstract

Background/Objectives: Seasonal variation in hemoglobin A1c (HbA1c) values has been previously documented, with physical activity (PA) and macronutrient intake (MNI) suggested as potential drivers. This study combines seasonal mean HbA1c values from the Dutch (pre)diabetes population with national survey data on PA and MNI from 2018 to 2021 to identify key associations. Methods: HbA1c data were collected from 24 laboratory organizations in the Netherlands and Dutch Caribbean. MNI and total energy intake data were extracted from the Dutch National Food Consumption Survey, while PA data came from the Dutch National Sports Participation Index Survey. Weighting factors were applied to align PA and MNI data with HbA1c data. Seasonal averages were analyzed for significant differences, and a prediction model compared PA and MNI with actual HbA1c values. Results: Among 5,635,920 HbA1c results, the average HbA1c increased by 0.71 mmol/mol (NGSP 0.06%) over four years, with an overall mean of 52.4 mmol/mol (NGSP 7.0%). Seasonal HbA1c variation showed a dip in summer–autumn and a peak in winter–spring (1.2 mmol/mol; NGSP 0.11%; p < 0.0001). MNI, except for total energy intake (which peaked in summer; p < 0.001), showed no significant trends or association with HbA1c (p = 0.157). PA decreased by 7.2% over the study period, with seasonal peaks in summer–autumn, showing an inverse relationship with HbA1c (p < 0.0001). During the COVID-19 lockdowns, PA significantly decreased, and mean HbA1c values increased more markedly than in previous years. The prediction model confirmed PA as a significant driver of seasonal HbA1c variation (p = 0.004). Conclusions: These findings suggest that PA is the strongest driver of seasonal variation in HbA1c. Public health initiatives and support programs promoting physical activity are essential for improving HbA1c regulation.

DiabetologyVol. 6(11)
Accenture (Switzerland) (CH), University Medical Center Groningen (NL), Leiden University Medical Center (NL), Gelre Hospitals (NL), Medisch Spectrum Twente (NL), Slingeland Ziekenhuis (NL), Eurofins (Netherlands) (NL), OLVG (NL), Canisius-Wilhelmina Ziekenhuis (NL), Elkerliek Ziekenhuis (NL), University of Curaçao (CW), Streekziekenhuis Koningin Beatrix (NL), Ziekenhuis Gelderse Vallei (NL), Ziekenhuis Rivierenland (NL), Stichting Certe Medische Diagnostiek en Advies (NL), Avalon University School of Medicine (CW), Haga Hospital (NL), Siemens Healthcare (United States) (US), Amsterdam University Medical Centers (NL), Star Medisch Diagnostisch Centrum (NL), Rijnstate Hospital (NL), Eindhoven Cancer Registry (NL), St. Anna Hospital (DE), St. Anna Ziekenhuis (NL), Jeroen Bosch Ziekenhuis (NL), University of Amsterdam (NL)
National Science Foundation, Rijksinstituut voor Volksgezondheid en Milieu
Openalex Percentile: Top 58%
Nutritional Studies and Diet
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.