Assessment of inequities by geolocation: mediterranean diet and type 2 diabetes
Abstract
Background: High adherence to Mediterranean diet is a strong, independent predictor of improved glycemic control, reduced cardiovascular risk, and optimized lipid profiles in type 2 diabetes (T2D) patients. By representing geographical data, we seek to detect inequalities in adherence to the Mediterranean diet in Extremadura (Spain).
Methods: As part of JACARDI (Joint Action on Cardiovascular diseases and diabetes), the MAP-IT pilot project surveyed people with diabetes using validated questionnaires to capture information not found in standard clinical records, enriched the results and drew them in maps. It aimed to identify differences across health areas in the region of Extremadura. In this analysis, we focused specifically on dietary habits in people having T2D and the factors influencing those differences. To analyse adherence to the Mediterranean diet, the MEDAS questionnaire was used, dividing the sample into good and poor adherence groups. After geospatial representation, a multivariate logistic regression model was constructed, with dietary adherence as the dependent variable.
Results: Among 309 people with T2D (mean age 59.7, SD 16.3; 57.9% women), 41.1% had poor Mediterranean diet adherence without significant differences between health areas. However, a North–South pattern was found, with poorer adherence concentrated in the North (p=0.053). Adjusting for financial ease homogenized central/southern areas, but northern areas still showed poorer adherence. In a logistic regression including location, education, social deprivation index, financial scale, and area income, only social deprivation index (p=0.02) was significantly associated with poor adherence; financial scale (p=0.06) and low education (p=0.07) were borderline.
Conclusions: Geolocating data helps interpret results and target improvements to reduce inequalities. For Mediterranean diet adherence, awareness campaigns and social isolation prevention could mitigate the problem in Extremadura.
Key messages: • Geolocating dietary data reveals north–south adherence patterns in Extremadura, guiding targeted inequality-reducing campaigns.
• Poor Mediterranean diet adherence in type 2 diabetes is linked to social deprivation, not just geography (41.1% poor adherence).
Related
- Transitions from cigarette smoking by geolocation among US adults: Results from waves 1-6 of the Population Assessment of Tobacco and Health (PATH) study 2013–2021
- Promoting the Mediterranean Diet in the Workplace: An Observational Cross-Sectional Study
- The relationship between smartphone addiction, Mediterranean diet adherence, body composition, and quality of life among university students: a cross-sectional study
- Cardiometabolic risk factors and Mediterranean diet adherence in patients with premature atherosclerotic cardiovascular disease in Iran
- Gut Microbiome-Mediated Neuroprotective Effect of the Mediterranean Diet: A Narrative Review of Cognitive Aging, Alzheimer’s Disease, and Parkinson’s Disease
BibTeX
@article{lorido2026assessment,
title = {{Assessment of inequities by geolocation: mediterranean diet and type 2 diabetes}},
author = {J C Arevalo Lorido and I Fernández-Morillo and B Morillo Merino and J L González-Sánchez and C Báez-Moñino},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.1109},
url = {https://doi.org/10.1093/eurpub/ckag169.1109},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Assessment of inequities by geolocation: mediterranean diet and type 2 diabetes
AU - J C Arevalo Lorido
AU - I Fernández-Morillo
AU - B Morillo Merino
AU - J L González-Sánchez
AU - C Báez-Moñino
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.1109
UR - https://doi.org/10.1093/eurpub/ckag169.1109
AB - Background: High adherence to Mediterranean diet is a strong, independent predictor of improved glycemic control, reduced cardiovascular risk, and optimized lipid profiles in type 2 diabetes (T2D) patients. By representing geographical data, we seek to detect inequalities in adherence to the Mediterranean diet in Extremadura (Spain). Methods: As part of JACARDI (Joint Action on Cardiovascular diseases and diabetes), the MAP-IT pilot project surveyed people with diabetes using validated questionnaires to capture information not found in standard clinical records, enriched the results and drew them in maps. It aimed to identify differences across health areas in the region of Extremadura. In this analysis, we focused specifically on dietary habits in people having T2D and the factors influencing those differences. To analyse adherence to the Mediterranean diet, the MEDAS questionnaire was used, dividing the sample into good and poor adherence groups. After geospatial representation, a multivariate logistic regression model was constructed, with dietary adherence as the dependent variable. Results: Among 309 people with T2D (mean age 59.7, SD 16.3; 57.9% women), 41.1% had poor Mediterranean diet adherence without significant differences between health areas. However, a North–South pattern was found, with poorer adherence concentrated in the North (p=0.053). Adjusting for financial ease homogenized central/southern areas, but northern areas still showed poorer adherence. In a logistic regression including location, education, social deprivation index, financial scale, and area income, only social deprivation index (p=0.02) was significantly associated with poor adherence; financial scale (p=0.06) and low education (p=0.07) were borderline. Conclusions: Geolocating data helps interpret results and target improvements to reduce inequalities. For Mediterranean diet adherence, awareness campaigns and social isolation prevention could mitigate the problem in Extremadura. Key messages: • Geolocating dietary data reveals north–south adherence patterns in Extremadura, guiding targeted inequality-reducing campaigns. • Poor Mediterranean diet adherence in type 2 diabetes is linked to social deprivation, not just geography (41.1% poor adherence).
SN - 1101-1262
SN - 1464-360X
ER -