Natural history of kidney disease based on smoking and glycaemic status: a conceptual framework for updating the current diabetes prevention programme (DPP) model.

Background
Although smoking is associated with vascular complications before and after the onset of diabetes, smoking cessation is not a core component of the NHS Diabetes Prevention Programme (DPP). Without smoking cessation, the existing model of DPP may not reduce the risk of vascular complications in smokers, including chronic kidney disease (CKD). This thesis uses albuminuria as a surrogate marker to examine the relationship between smoking status and CKD.
Methods
Meta-analyses and meta-regression were conducted to elucidate the relationship between smoking status and albuminuria (defined as >20 mg/l in spot urine sample). A total of 30 studies were identified for inclusion in the narrative synthesis, and 13 were included in the meta-analysis. A cross-sectional study (n=502,490) explored the prevalence of albuminuria in people with prediabetes and diabetes. A logistic regression model examined the predictors and determinants of albuminuria based on smoking and glycaemic status. Further analyses were conducted on a longitudinal cohort (n= 20,346) to explore the factors associated with the progression and regression of albuminuria. Results are expressed in odds ratios and 95% CIs.
Results
After analysing 13 studies (n=21476), using study-level data, a random effect meta-analysis showed that, compared with non-smokers, the odds of albuminuria in current smokers with T2DM was 2.13 (1.32-3.45) compared to non-smokers (defined as those who never smoked) with T2DM. However, individual study odds ratios varied from 0.75 to 1.45. Factors that influenced the between-study variation included duration of T2DM, mean age of the study participants and pack-years smoked.
The cross-sectional study (n=502,490) showed that the prevalence of albuminuria in smokers with prediabetes and diabetes was approximately 35% and 50%, respectively. After adjusting for confounding variables, variables significantly associated with albuminuria in people with prediabetes were sex 1.42 (1.28-1.58), (males vs females); HbA1c (per mmol/mol) 1.06 (1.02-1.10), hypertension (yes vs no) 1.57 (1.40-1.75), IHD (yes vs no) 1.41 (1.20-1.65), smoking (smokers vs non-smokers) 1.21 (1.05-1.39).
The odds of albuminuria in ex-smokers with T2DM compared to non-smokers (never smokers) with T2DM was 1.07 (0.96-1.19)
The longitudinal cohort study (n=6505) showed that after a median follow-up of 51 months, each year of ageing and each mmol/mol rise in HbA1c increased the odds of progression of albuminuria by 20% and 3%, respectively. Changes in BMI, SBP, Creatinine, Cholesterol and smoking status had no statistically significant impact on the progression.
Conclusion
Current smokers with T2DM and prediabetes are at an increased odds of albuminuria compared to nonsmokers (excluding ex-smokers) with T2DM and prediabetes. An increase in HbA1c was associated with an increase in odds, but changes in BMI were not. This suggests that smoking status and glycaemic control are the most important risk factors for current smokers; however, more research is needed on the implications for HbA1c and weight control after smoking cessation.