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Aim: To explore how diabetes and chronic kidney disease (CKD) interact to influence quality-of-life in a community-based setting. Background(s): Quality-of-life is an important outcome for clinical care. Both CKD and diabetes are associated with poorer quality-of-life. Less well understood is the joint impact of both diseases. Method(s): A prospective, longitudinal cohort study of community-based Australians aged >=25yr who participated in the Australian Diabetes, Obesity and Lifestyle study. Quality-of-life was measured by SF-36 its physical(PCS) and mental(MCS) sub-scores. Univariate and multivariate linear mixed effect regressions were performed. Result(s): Of the 11,247 participants at baseline 841 had CKD, 737 had diabetes and 271 had both. Those with both had significantly lower PCS (mean PCS 38(+/-12) compared to 44(+/-11) for CKD, and 45(+/-11) for diabetes (p<0.001)). We found the combined impact of both diseases is greater for those with eGFR >60(p=0.04). There was no difference in MCS between groups (mean MCS 50(+/-10) for all). The PCS components most impaired for those with CKD and diabetes (compared with either disease alone) were physical functioning and vitality (p<0.001 for both). Those with diabetes at baseline who subsequently developed CKD had lower baseline PCS than those who did not (difference in PCS of -3.8(95%CI:-0.9,-6.8,p=0.01). In our adjusted linear mixed effects models, baseline PCS was lower for those with both CKD and diabetes compared to either disease alone(p<0.001). Follow-up data was suggestive of a more rapid decline in PCS in this population, however lacked power to detect a significant difference. Conclusion(s): The combination of CKD and diabetes has a powerful adverse impact on quality-of-life, and participants with both diseases had significantly poorer quality-of-life than those with just one condition.

Aim: To explore how diabetes and chronic kidney disease (CKD) interact to influence quality-of-life in a community-based setting. Background(s): Quality-of-life is an important outcome for clinical care. Both CKD and diabetes are associated with poorer quality-of-life. Less well understood is the joint impact of both diseases. Method(s): A prospective, longitudinal cohort study of community-based Australians aged >=25yr who participated in the Australian Diabetes, Obesity and Lifestyle study. Quality-of-life was measured by SF-36 its physical(PCS) and mental(MCS) sub-scores. Univariate and multivariate linear mixed effect regressions were performed. Result(s): Of the 11,247 participants at baseline 841 had CKD, 737 had diabetes and 271 had both. Those with both had significantly lower PCS (mean PCS 38(+/-12) compared to 44(+/-11) for CKD, and 45(+/-11) for diabetes (p<0.001)). We found the combined impact of both diseases is greater for those with eGFR >60(p=0.04). There was no difference in MCS between groups (mean MCS 50(+/-10) for all). The PCS components most impaired for those with CKD and diabetes (compared with either disease alone) were physical functioning and vitality (p<0.001 for both). Those with diabetes at baseline who subsequently developed CKD had lower baseline PCS than those who did not (difference in PCS of -3.8(95%CI:-0.9,-6.8,p=0.01). In our adjusted linear mixed effects models, baseline PCS was lower for those with both CKD and diabetes compared to either disease alone(p<0.001). Follow-up data was suggestive of a more rapid decline in PCS in this population, however lacked power to detect a significant difference. Conclusion(s): The combination of CKD and diabetes has a powerful adverse impact on quality-of-life, and participants with both diseases had significantly poorer quality-of-life than those with just one condition.

Aim: To determine the impact of biomedical and behavioural factors on progression of chronic kidney disease (CKD) and death. Background(s): CKD is highly prevalent, costly and associated with progression to end-stage kidney disease and death. Tailored management of CKD patients, particularly for those at highest risk of progression or death, would foster improved outcomes. Method(s): We evaluated the relationship between biomedical and behavioral factors and CKD progression or death in participants aged >=25 years who participated in the baseline AusDiab study (1999/2000) and participated in at least one of the two follow-up phases (2004/2005 and/or 2011/2012) or had a registered death. CKD was defined as eGFR >=60 mL/min/1.73 m2 with albuminuria or eGFR <60 mL/min/1.73 m2. We constructed a mixed linear regression model to predict annual eGFR decline and a logistic regression model to determine likelihood of death. Result(s): Baseline data were available for 1137 participants with CKD. Follow-up eGFR was available for 486(43%) and 257(23%) participants in 2005 and 2012 respectively. 161(14%) participants had died by 2005 and 608(53%) had died by 2012. Annual age and sex adjusted eGFR decline was driven by: macroalbuminuria (-1.7 mL/min/1.73 m2, p< 0.001), microalbuminuria (-0.6 mL/min/1.73 m2, p = 0.04), age >65 (-0.8 mL/min/1.73 m2, p < 0.001) and diabetes (-0.6 mL/min/1.73 m2, p = 0.008). Behavioural factors including smoking, alcohol consumption, obesity, sedentary lifestyle and dietary protein were not significant. The odds of all-cause death at both 5 and 12 years were increased by: age >65 years, microalbuminuria, macroalbuminuria, diabetes, male sex and lower eGFR (in a dose-response relationship). Being overweight or obese reduced the odds of death at 5, but not 12, years. Conclusion(s): Our work confirms known impact of albuminuria, diabetes, age and advanced eGFR as key predictors of progression. No behavioural factors were found to be significant.

Background: Costs associated with chronic kidney disease (CKD) are not well documented. Understanding such costs is important to inform economic evaluations of prevention strategies and treatment options. Aim: To estimate the costs associated with CKD in Australia. Methods: We used data from the 2004/2005 AusDiab study, a national longitudinal population-based study of non-institutionalised Australian adults aged ≥25 years. We included 6138 participants with CKD, diabetes and healthcare cost data. The annual age and sex-adjusted costs per person were estimated using a generalised linear model. Costs were inflated from 2005 to 2012 Australian dollars using best practice methods. Results: Among 6138 study participants, there was a significant difference in the per-person annual direct healthcare costs by CKD status, increasing from $1829 (95% confidence interval (CI): $1740–1943) for those without CKD to $14 545 (95% CI: $5680–44 842) for those with stage 4 or 5 CKD (P < 0.01). Similarly, there was a significant difference in the per-person annual direct non-healthcare costs by CKD status from $524 (95% CI: $413–641) for those without CKD to $2349 (95% CI: $386–5156) for those with stage 4 or 5 CKD (P < 0.01). Diabetes is a common cause of CKD and is associated with increased health costs. Costs per person were higher for those with diabetes than those without diabetes in all CKD groups; however, this was significant only for those without CKD and those with early stage (stage 1 or 2) CKD. Conclusion: Individuals with CKD incur 85% higher healthcare costs and 50% higher government subsidies than individuals without CKD, and costs increase by CKD stage. Primary and secondary prevention strategies may reduce costs and warrant further consideration.