Publicação
Is residential greenness associated with individual levels of glycated haemoglobin in the Portuguese population?
| Resumo: | ABSTRACT - Background: Type 2 diabetes mellitus (T2DM) is a chronic and preventable disease with multiple risk factors. A higher residential greenness has been shown to be associated with a lower prevalence of T2DM in several epidemiological studies. Nevertheless, there is still a lack of evidence regarding the use of more objective outcomes such as Glycated haemoglobin (HbA1c). Therefore, in this study we explored the association between residential greenness and HbA1c in adults without a previous diagnosis of diabetes. Methods: Health data from a representative sample of the Portuguese adult population, the National Health Examination Survey (INSEF) 2015 was used. Residential greenness was obtained using the annual average normalized difference vegetation index (NDVI) of 2014 on a 300 m circular buffer around each participant´s residence and categorized into tertiles. A linear regression was used to estimate the association by adjusting for selected confounding variables. Sensitivity analysis with a 1000 m buffer and effect modification analysis with sex and rural/urban living were also performed. Results: In the fully adjusted models results show that living in the greenest areas significantly reduced the average HbA1c levels (Exp(β) = 0.985; 95% CI: 0.971, 0.999) compared to the least green areas. The association was weaker and not statistically significant for areas with medium greenery (Exp(β) = 0.994; 95% CI: 0.975, 1.012). Results remained the same with a larger buffer size and no evidence of effect modification was found. Conclusions: This study provides evidence of a protective association between greenness and HbA1c, suggesting that public health interventions in the built environment can have beneficial effects on T2DM prevention. |
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| Autores principais: | Resendes, Daniel Saldanha Aguiar |
| Assunto: | NDVI HbA1c Diabetes Portugal Greenness Population-based Vegetação Populacional |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | ABSTRACT - Background: Type 2 diabetes mellitus (T2DM) is a chronic and preventable disease with multiple risk factors. A higher residential greenness has been shown to be associated with a lower prevalence of T2DM in several epidemiological studies. Nevertheless, there is still a lack of evidence regarding the use of more objective outcomes such as Glycated haemoglobin (HbA1c). Therefore, in this study we explored the association between residential greenness and HbA1c in adults without a previous diagnosis of diabetes. Methods: Health data from a representative sample of the Portuguese adult population, the National Health Examination Survey (INSEF) 2015 was used. Residential greenness was obtained using the annual average normalized difference vegetation index (NDVI) of 2014 on a 300 m circular buffer around each participant´s residence and categorized into tertiles. A linear regression was used to estimate the association by adjusting for selected confounding variables. Sensitivity analysis with a 1000 m buffer and effect modification analysis with sex and rural/urban living were also performed. Results: In the fully adjusted models results show that living in the greenest areas significantly reduced the average HbA1c levels (Exp(β) = 0.985; 95% CI: 0.971, 0.999) compared to the least green areas. The association was weaker and not statistically significant for areas with medium greenery (Exp(β) = 0.994; 95% CI: 0.975, 1.012). Results remained the same with a larger buffer size and no evidence of effect modification was found. Conclusions: This study provides evidence of a protective association between greenness and HbA1c, suggesting that public health interventions in the built environment can have beneficial effects on T2DM prevention. |
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