Chronic condition risk factor change over time in a remote Indigenous community.

INTRODUCTION: This study sought to determine change in chronic condition risk factors in a remote Indigenous community following a 3-year period of community-led health promotion initiatives. METHODS: Data were compared between two cross-sectional surveys of Indigenous Australian community residents before and after health promotion activities, and longitudinal analysis of participants present at both surveys using multilevel mixed-effects regression. RESULTS: At baseline, 294 (53% women; mean age 35 years) participated and 218 attended the second survey (56% women, mean age 40 years), and 87 attended both. Body composition, blood pressure and urinary albumin-to-creatinine ratio remained stable between baseline and follow-up. After adjusting for age and sex, haemoglobin A1c significantly increased (from 57 to 63 mmol/mol (7.5% to 8.1%), p=0.021) for those with diabetes. Increases were also observed for total cholesterol (from 4.4 to 4.6 mmol/L, p=0.006) and triglycerides (from 1.5 to 1.6 mmol/L, p=0.019), and high-density lipoprotein cholesterol levels improved (from 0.98 to 1.02 mmol/L, p=0.018). Self-reported smoking prevalence was high but stable between baseline (57%) and follow-up (56%). Similar results were observed in the longitudinal analysis to the cross-sectional survey comparison. CONCLUSION: Community-led health promotion initiatives may have had some benefits on chronic condition risk factors, including stabilisation of body composition, in this remote Indigenous community. Given that less favourable trends were observed for diabetes and total cholesterol over a short time period and smoking prevalence remained high, policy initiatives that address social and economic disadvantage are needed alongside community-led health promotion initiatives.

External validation and comparison of four cardiovascular risk prediction models with data from the Australian Diabetes, Obesity and Lifestyle study.

OBJECTIVES: To evaluate the performance of the 2013 Pooled Cohort Risk Equation (PCE-ASCVD) for predicting cardiovascular disease (CVD) in an Australian population; to compare this performance with that of three frequently used Framingham-based CVD risk prediction models. DESIGN: Prospective national population-based cohort study. SETTING: 42 randomly selected urban and non-urban areas in six Australian states and the Northern Territory. PARTICIPANTS: 5453 adults aged 40-74 years enrolled in the Australian Diabetes, Obesity and Lifestyle study and followed until November 2011. We excluded participants who had CVD at baseline or for whom data required for risk model calculations were missing. MAIN OUTCOME MEASURES: Predicted and observed 10-year CVD risks (adjusted for treatment drop-in); performance (calibration and discrimination) of four CVD risk prediction models: 1991 Framingham, 2008 Framingham, 2008 office-based Framingham, 2013 PCE-ASCVD. RESULTS: The performance of the 2013 PCE-ASCVD model was slightly better than 1991 Framingham, and each was better the two 2008 Framingham risk models, both in men and women. However, all four models overestimated 10-year CVD risk, particularly for patients in higher deciles of predicted risk. The 2013 PCE-ASCVD (7.5% high risk threshold) identified 46% of men and 18% of women as being at high risk; the 1991 Framingham model (20% threshold) identified 17% of men and 2% of women as being at high risk. Only 16% of men and 11% of women identified as being at high risk by the 2013 PCE-ASCVD experienced a CV event within 10 years. CONCLUSIONS: The 2013 PCE-ASCVD or 1991 Framingham should be used as CVD risk models in Australian. However, the CVD high risk threshold for initiating CVD primary preventive therapy requires reconsideration.

Contribution of cardiometabolic risk factors to estimated glomerular filtration rate decline in Indigenous Australians with and without albuminuria - the eGFR Follow-up Study.

AIM: We assessed associations between cardiometabolic risk factors and estimated glomerular filtration rate (eGFR) decline according to baseline albuminuria to identify potential treatment targets in Indigenous Australians. METHODS: The eGFR Follow-up Study is a longitudinal cohort of 520 Indigenous Australians. Linear regression was used to estimate associations between baseline cardiometabolic risk factors and annual Chronic Kidney Disease Epidemiology Collaboration eGFR change (mL/min per 1.73m2 /year), among those classified with baseline normoalbuminuria (urine albumin-to-creatinine ratio (uACR) <3 mg/mmol; n = 297), microalbuminuria (uACR 3-30 mg/mmol; n = 114) and macroalbuminuria (uACR ≥30 mg/mmol; n = 109). RESULTS: After a median of 3 years follow-up, progressive declines of the age- and sex-adjusted mean eGFR were observed across albuminuria categories (-2.0 [-2.6 to -1.4], -2.5 [-3.7 to -1.3] and -6.3 [-7.8 to -4.9] mL/min per 1.72m2 /year). Although a borderline association was observed between greater baseline haemoglobin A1c and eGFR decline in those with macroalbuminuria (P = 0.059), relationships were not significant in those with microalbuminuria (P = 0.187) or normoalbuminuria (P = 0.23). Greater baseline blood pressure, C-reactive protein, waist-to-hip ratio and lower high-density lipoprotein cholesterol showed non-significant trends with greater eGFR decline in the presence of albuminuria. CONCLUSION: Over a 3 year period, marked eGFR decline was observed with greater baseline albuminuria. Cardiometabolic risk factors were not strong predictors for eGFR decline in Indigenous Australians without albuminuria. Longer follow-up may elucidate the role of these predictors and other mechanisms in chronic kidney disease progression in this population.

Comparison of creatinine and cystatin C based eGFR in the estimation of glomerular filtration rate in Indigenous Australians: The eGFR Study.

BACKGROUND: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation that combines creatinine and cystatin C is superior to equations that include either measure alone in estimating glomerular filtration rate (GFR). However, whether cystatin C can provide any additional benefits in estimating GFR for Indigenous Australians, a population at high risk of end-stage kidney disease (ESKD) is unknown. METHODS: Using a cross-sectional analysis from the eGFR Study of 654 Indigenous Australians at high risk of ESKD, eGFR was calculated using the CKD-EPI equations for serum creatinine (eGFRcr), cystatin C (eGFRcysC) and combined creatinine and cystatin C (eGFRcysC+cr). Reference GFR (mGFR) was determined using a non-isotopic iohexol plasma disappearance technique over 4h. Performance of each equation to mGFR was assessed by calculating bias, % bias, precision and accuracy for the total population, and according to age, sex, kidney disease, diabetes, obesity and c-reactive protein. RESULTS: Data were available for 542 participants (38% men, mean [sd] age 45 [14] years). Bias was significantly greater for eGFRcysC (15.0mL/min/1.73m2; 95% CI 13.3-16.4, p<0.001) and eGFRcysC+cr (10.3; 8.8-11.5, p<0.001) compared to eGFRcr (5.4; 3.0-7.2). Accuracy was lower for eGFRcysC (80.3%; 76.7-83.5, p<0.001) but not for eGFRcysC+cr (91.9; 89.3-94.0, p=0.29) compared to eGFRcr (90.0; 87.2-92.4). Precision was comparable for all equations. The performance of eGFRcysC deteriorated across increasing levels of c-reactive protein. CONCLUSION: Cystatin C based eGFR equations may not perform well in populations with high levels of chronic inflammation. CKD-EPI eGFR based on serum creatinine remains the preferred equation in Indigenous Australians.

Cystatin C estimated glomerular filtration rate and all-cause and cardiovascular disease mortality risk in the general population: AusDiab study.

AIMS: Uncertainties about the role of cystatin C-based estimated glomerular filtration rate (eGFR) in the prediction of cardiovascular disease (CVD) beyond traditional CVD risk factors remain. We assessed contributions of eGFR to CVD and mortality in the general population. METHODS: Using 14 year follow-up data on 9353 adults without a reported history of CVD from the Australian Diabetes, Obesity and Lifestyle study, we assessed the contributions of eGFR (assessed by cystatin C (eGFRcysC ) and serum creatinine (eGFRcr ) and albuminuria (uACR) to total and CVD mortality. RESULTS: After adjusting for age, sex, CVD risk factors and uACR, compared with an eGFRcysC >90 mL/min per 1.73 m2 , eGFRcysC <60 mL/min per 1.73 m2 was associated with 56% and 73% increases in the risks for all-cause and CVD mortality, respectively. The respective changes for the c-statistic when eGFRcysC was added to a risk prediction model were 0.003 (95% confidence interval: 0.001 to 0.005) and 0.002 (95% confidence interval: -0.001 to 0.006). The net proportion of non-events assigned a lower-risk category significantly improved with the addition of eGFR (non-event net reclassification index eGFRcr : 1.0% and eGFRcysC : 1.5%) for all-cause mortality, but for CVD mortality, improvements were only significant when eGFR was combined with uACR. The net proportion of events assigned a higher-risk category was not significantly improved. CONCLUSION: In our community-based cohort, reduced eGFRcysC was associated with all-cause and CVD mortality. The addition of chronic kidney disease measures to risk prediction models improved overall risk stratification among those at low risk as opposed to those at high baseline risk of mortality.