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Predictors and determinants of albuminuria in people with prediabetes and diabetes based on smoking status: A cross-sectional study using the UK Biobank data

BACKGROUND: Smoking is attributed to both micro- and macrovascular complications at any stage of metabolic deregulation including prediabetes. Current global diabetes prevention programmes appear to be glucocentric, and do not fully acknowledge the ramifications of cardiorenal risk factors in smoker...

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Detalles Bibliográficos
Autores principales: Kar, Debasish, El-Wazir, Aya, Delanerolle, Gayathri, Forbes, Anna, Sheppard, James P., Nath, Mintu, Joy, Mark, Cole, Nicholas, Arnold, J. Ranjit, Lee, Andrew, Feher, Michael, Davies, Melanie J., Khunti, Kamlesh, de Lusignan, Simon, Goyder, Elizabeth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9256818/
https://www.ncbi.nlm.nih.gov/pubmed/35813092
http://dx.doi.org/10.1016/j.eclinm.2022.101544
Descripción
Sumario:BACKGROUND: Smoking is attributed to both micro- and macrovascular complications at any stage of metabolic deregulation including prediabetes. Current global diabetes prevention programmes appear to be glucocentric, and do not fully acknowledge the ramifications of cardiorenal risk factors in smokers and ex-smokers. A more holistic approach is needed to prevent vascular complications in people with prediabetes and diabetes before and after quitting. METHODS: A cross-sectional study was carried out on participants who agreed to take part in the UK Biobank dataset at the time of their first attendances between March 01, 2006, and December 31, 2010. Those who had their urinary albumin concentration (UAC) data available were included, and those who did not have this data, were excluded. A logistic regression model was fitted to explore the relationship between cardiorenal risk factors and albuminuria in people with prediabetes and diabetes, based on smoking status. FINDINGS: A total of 502,490 participants were included in the UK Biobank dataset. Of them, 30.4% (n=152,896) had their UAC level recorded. Compared with non-smokers, the odds of albuminuria in smokers with prediabetes and diabetes were 1.21 (95% CI 1.05 – 1.39, p=0.009), and 1.26 (95% CI 1.10 – 1.44, p=0.001), respectively. The odds declined after quitting in both groups, but it was not statistically significant (p>0.05). Each unit increase in HbA1c was associated with equivalent increased odds of albuminuria in current and ex-smokers, OR 1.035 (95% CI 1.030 – 1.039, p<0.001), and 1.026 (95% CI 1.023 – 1.028, p <0.001), respectively. Compared to females, male ex-smokers were at 15% increased odds of albuminuria. In ex-smokers, each unit increase in waist circumference was associated with 1% increased risk of albuminuria. Compared with the least deprived quintiles, the odds of albuminuria in the most deprived quintiles, in current and ex-smokers were identical, OR 1.18 (95% CI 1.04–1.324, p=0.010), and 1.19 (95% CI 1.11 – 1.27, p<0.001), respectively. INTERPRETATION: Male smokers are at a higher risk of albuminuria after smoking cessation. Monitoring waist circumference in quitters may identify those who are at a higher risk of albuminuria. Combining smoking cessation intervention in smokers with prediabetes in the current diabetes prevention programmes may offset post-cessation weight gain and reduce the risk of albuminuria. FUNDING: University of Sheffield.