This report examined the association between renal failure admissions (RFA) to hospitals in Victoria, Australia and socioeconomic disadvantage across 79 local government areas from 2011-2014. The results showed that RFA rates varied inversely with socioeconomic disadvantage and the most disadvantaged areas had RFA rates 2.4 times higher than the least disadvantaged areas. Areas with high RFA rates also had high rates of other conditions like heart failure and COPD. The variations in RFA rates likely reflect factors like access to adequate care, delayed referral to nephrology services, and lack of understanding about the disease among patients. Addressing chronic kidney disease and renal failure remains a public health challenge.

1. Effects of socioeconomic disadvantage on renal failure
hospital admissions in Victoria
Timothy Ore PhD, Evidence and Evaluation Advisor
Department of Health and Human Services, Innovation Hub and Health System Improvement Branch,
Level 20, 50 Lonsdale Street, Melbourne, Vic. 3000, Australia. Email: timothy.ore@dhhs.vic.gov.au
Received 23 April 2015, accepted 17 July 2015, published online 21 September 2015
Thisreport examinedtheassociationbetween renalfailureadmis-
sions (RFA) to public and private hospitals between 1 July 2011
and 30 June 2014 and socioeconomic disadvantage (SED) across
79 Local Government Areas (LGA) in Victoria.
RFA rates were age-standardised using the direct method to
the 2012 Victorian population. This is a procedure for correcting
differencesinpopulationagestructuresbyapplyingacommonset
of age-specific rates from a reference population to the population
whose rates are to be adjusted. The numerator data (admissions)
was from the Victorian Admitted Episodes Dataset (www.health.
vic.gov.au/hdss/vaed; accessed 9-13 February 2015) and the
denominator data was from the Australian Bureau of Statistics
(ABS) Estimated Resident Population (www.abs.gov.au/abs@.
nsf/Lookup/1367.0;accessed 19February2015).The ABSIndex
of Relative Socioeconomic Disadvantage (www.abs.gov.au/
ausstats/abs@.nsf/Lookup/2033.0.55.001; accessed 19 February
2015) was used for SED.
Over the 3-year period, there were 14 473 RFAs, an average
rate of 9.6 per 10 000 population (95% confidence interval (CI)
7.67–11.47). The mean length of stay was 7.3 days. Most (85%)
patients were aged 50 years. Ninety-nine (0.68%) were under
5 years of age. RFAs had the sixth highest 30-day readmission
(15%). One-tenth of the patients died in hospital.
The RFA rates varied inversely with SED (r = –0.51,
P 0.01). The coefficient of variation was 0.44 and 0.16 for RFA
and all admissions, respectively, indicating that RFAs had greater
variability by LGA than all admissions. The mean RFA rate for
the top percentile LGAs was 2.4-fold greater than that of the
bottom percentile LGA (13.21 (95% CI 11.44–14.93) vs 5.62
(95% CI 4.43–6.95), respectively). The top percentile group was
the most disadvantaged, including Central Goldfields, Loddon
and Mildura. The bottom percentile group include Bayside,
Boroondara and Nillumbik.
LGAs with high RFA rates also had high hospital admission
rates for other conditions, such as heart failure (r = 0.58, P 0.01)
and chronic obstructive pulmonary disease (r = 0.49, P 0.01),
and prevalence of hypertension (r = 0.32, P 0.01) and obesity
(r = 0.26, P 0.05). Residents of disadvantaged communities are
significantly more likely (r = 0.45, P 0.01) to be on a Disability
Support Pension (Table 1).
In conclusion, the variations in RFA rates may reflect multiple
factors, particularly access to adequate care, delayed referral to
Table 1. Inter-correlation coefficients for age-standardised renal failure hospitalisation rates and key variables
*P 0.05, **P 0.01 (two-tailed). SED, socioeconomic disadvantage; REN, age-adjusted renal failure admissions per 10 000 population; HRF, age-adjusted
heart failure admissions per10 000population;COP,age-adjusted chronicobstructivepulmonarydisease admissions per10 000population;OCA,proportionof
the population undertaking mostly heavy labour or physically demanding activity; HYP, prevalence(%) of hypertension; OBE, prevalence(%) of overweightand
obesity; HLS, prevalence (%) of fair or poor self-reported health status; CAN, prevalence (%) of cancer; DSP, proportion of the population on Disability Support
Pension. OCA, HYP, OBE, HLS and CAN data taken from the Victorian Population Health Survey 2011–12, Department of Health, Victoria (www.health.vic.
gov.au/healthstatus/survey/vphs2011-12.htm; accessed 19 February 2015). DSP data were from the Commonwealth Department of Human Services (www.
humanservices.gov.au/dsp; accessed 11–12 March 2015)
SED REN HRF COP OCA HYP OBE HLS CAN DSP
SED 1.00
REN –0.51** 1.00
HRF –0.38** 0.58** 1.00
COP –0.65** 0.49** 0.60** 1.00
OCA –0.55** 0.28** 0.37** 0.73** 1.00
HYP –0.54** 0.32** 0.12 0.43** 0.46** 1.00
OBE –0.58** 0.26* 0.16 0.49** 0.49** 0.691** 1.000
HLS –0.43** 0.27* 0.20 0.07 0.04 0.382** 0.48** 1.00
CAN –0.01 0.22* 0.09 0.20 0.15 0.003 0.07 –0.06 1.00
DSP –0.93** 0.45** 0.40** 0.68** 0.55** 0.526** 0.58** 0.34** 0.11 1.00
Journal compilation Ó AHHA 2015 www.publish.csiro.au/journals/ahr
CSIRO PUBLISHING
Australian Health Review
Letter
http://dx.doi.org/10.1071/AH15077

2. nephrology and patients’ lack of understanding of the disease.
The findings, which are consistent with other studies,1,2
point to a
need for early detection, timely referral to nephrology services
and provision of required dialysis.
IntheUS,theblueprintforpublichealthgoals,HealthyPeople
2020 (www.cdc.gov/nchs/healthy_people/hp2020.htm), aims to
reduce disparities in the occurrence and outcomes of chronic
kidney disease (CKD) by 2020. One-tenth of the adult population
in Australia3
and 16% of the population in the UK4
have
CKD. Fewer than one in 10 Australians with CKD are aware
they have the condition.3
Approximately 21 000 people in Aus-
tralia are on renal replacement therapy.5
Addressing CKD and
renal failure remains a public health challenge.
Competing interests
None declared.
References
1 Hommel K, Rasmussen S, Kamper AL, Madsen M. Regional and social
inequalities in chronic renal replacement therapy in Denmark. Nephrol
Dial Transplant 2010; 25: 2624–32. doi:10.1093/ndt/gfq110
2 Fored CM, Ejerblad E, Fryzek JP, Lambe M, Lindblad P, Nyrén O, Elinder
C.-G. Socioeconomic status and chronic renal failure: a population-based
case-control study in Sweden. Nephrol Dial Transplant 2003; 18: 82–8.
doi:10.1093/ndt/18.1.82
3 Australian Bureau of Statistics (ABS). Australian health survey: biomed-
ical results for chronic diseases, 2011–12. Catalogue No. 4364.0.55.005.
Canberra: ABS; 2013.
4 Stringer S, Sharma P, Dutton M, Jesky M, Ng K, Kaur O, Chapple I,
Dietrich T,FerroC, CockwellP. Thenatural historyof, andrisk factors for,
progressive chronic kidney disease: the Renal Impairment in Secondary
Care (RIISC) study; rationale and protocol. BMC Nephrol 2013; 14: 95.
doi:10.1186/1471-2369-14-95
5 Australia and New Zealand Dialysis and Transplant Registry
(ANZDATA). Summary of Australia and New Zealand dialysis and
transplantation, 2012. Adelaide: Australia and New Zealand Dialysis
and Transplant Registry; 2013.
B Australian Health Review T. Ore
www.publish.csiro.au/journals/ahr