Risk factors for chronic kidney disease
What is a risk factor?
Risk factors are attributes, characteristics or exposures that increase the likelihood of a person developing a disease or health disorder.
Behavioural risk factors are health-related behaviours that individuals have the most ability to modify. Behavioural risk factors for chronic kidney disease (CKD) include:
- smoking
- diet
- physical activity
- alcohol consumption.
Biomedical risk factors are bodily states that have an impact on a person’s risk of disease. Biomedical risk factors for CKD include:
- diabetes
- high blood pressure (also known as hypertension)
- established cardiovascular disease, including heart attack, heart failure and stroke
- overweight and obesity.
Some biomedical risk factors can be influenced by health behaviours. Others, such as type 1 diabetes, occur independently of behaviours.
Fixed risk factors cannot be modified. Fixed risk factors for CKD include:
- ageing
- family history of kidney failure
- history of acute kidney injury.
Other risk factors such as use of certain medications, kidney stones, foetal and maternal factors, infections, and environmental factors are increasingly being recognised as threats to kidney health (Luyckx et al. 2017) (Tesfaw et al 2025).
For most behavioural and biomedical risk factors there is no known threshold at which risk begins. The relationship between risk and disease is continuous – there is an increasing effect as exposure to the risk factor increases. Having multiple risk factors further escalates risk.
Controlling or managing risk factors can help reduce the risk of CKD. The progression of CKD can also be slowed by controlling risk factors and by appropriate disease treatment and management.
For information about population trends for key risk factors, see the risk factor dashboard.
Risk factors among adults with chronic kidney disease
This section compares levels of key CKD risk factors among adults with and without biomedical signs of CKD. The populations with and without CKD were obtained from the 2022–24 National Health Measures Survey (NHMS) (AIHW analysis of ABS, 2025).
In 2022–24, many adults who had biomedical signs of CKD, also experienced other health risk factors or conditions, including:
- diabetes (18%)
- heart, stroke or vascular disease (17%)
- uncontrolled high blood pressure (38%)
- dyslipidaemia (76%)
- current smoking (8.2%)
- overweight or obesity (79%)
- at‑risk waist circumference (83%).
After adjusting for differences in population age structure, adults who had biomedical signs of CKD had higher rates of several risk factors compared with adults without CKD. Age‑standardised rates were:
- 2.9 times as high for diabetes
- 1.9 times as high for heart, stroke or vascular disease
- 1.5 times as high for uncontrolled high blood pressure
- 1.2 times as high for dyslipidaemia
- 1.2 times as high for current smoking
- 1.1 times as high for overweight and obesity
- 1.2 times as high for at‑risk waist circumference.
These higher risk factor levels among adults who may have developed CKD highlight the need for secondary prevention to limit the disease’s further development and increased severity. Secondary prevention focuses on the early detection and best practice management of a disease or disorder to reduce deterioration and long-term effects. This includes identifying people at risk of ill-health through screening programs, general health examinations, as well as the identification of complications and co-morbidities. Chronic Kidney Disease (CKD) Management in Primary Care guidelines from Kidney Health Australia (2024) includes lifestyle changes that can have a positive effect on CKD outcomes and delay the progression of disease.
Figure 1: Risk factors among adults with and without biomedical signs of chronic kidney disease, 2022–24
At risk waist circumference and overweight and obesity were the most of selected comment risk factors for both groups
| Risk factor | With biomedical signs of chronic kidney disease | Without biomedical signs of chronic kidney disease |
|---|---|---|
| Diabetes |
13.5%
(CI [9.3-17.8]) |
4.6%
(CI [3.8-5.5]) |
| Self-reported heart, stroke and vascular disease |
9%
(CI [5.9-12.2]) |
4.7%
(CI [3.9-5.5]) |
| Uncontrolled high blood pressure(b) |
31.9%
(CI [26-37.9]) |
20.9%
(CI [19-22.8]) |
| Dyslipidemia |
68.8%
(CI [59.6-78]) |
56.5%
(CI [54.1-58.9]) |
| Current smoking |
9.6%
(CI [5.3-13.8]) |
8%
(CI [6.6-9.4]) |
| Overweight or obese(c) |
73.1%
(CI [65.9-80.3]) |
65.5%
(CI [63.1-67.8]) |
| At-risk waist circumference(d) |
75.6%
(CI [68.9-82.4]) |
65.4%
(CI [63.2-67.6]) |
| Risk factor | With biomedical signs of chronic kidney disease | Without biomedical signs of chronic kidney disease |
|---|---|---|
| Diabetes |
17.9%
(CI [14.9-20.9]) |
4.8%
(CI [4-5.7]) |
| Self-reported heart, stroke and vascular disease |
17.2%
(CI [13.9-20.5]) |
4.7%
(CI [4-5.4]) |
| Uncontrolled high blood pressure(b) |
38.1%
(CI [32.3-43.9]) |
21.1%
(CI [19.2-23.1]) |
| Dyslipidemia |
76.5%
(CI [70.3-82.7]) |
58.2%
(CI [55.9-60.6]) |
| Current smoking |
8.2%
(CI [5.6-10.8]) |
|
| Overweight or obese(c) |
79.2%
(CI [75.1-83.3]) |
65.9%
(CI [63.3-68.4]) |
| At-risk waist circumference (d) |
82.6%
(CI [78.2-86.9]) |
66%
(CI [63.6-68.3]) |
| Current smoking |
8%
(CI [6.7-9.4]) |
(a) Age-standardised to the 2001 Australian Standard Population.
(b) Uncontrolled high blood pressure' is defined as measured systolic blood pressure of 140 mmHg or more, or diastolic blood pressure of 90 mmHg or more
(c) Overweight or obese defined as a Body Mass Index (kg/m²) ≥ 25.
(d) At risk waist circumference defined as a measured waist circumference greater than 94 cm for men and 80 cm for women
Notes
- CI = A statistical term describing a range (interval) of values within which we can be 'confident' that the true value lies, usually because it has a 95% or higher chance of doing so.
- Percentages are calculated using risk factor-specific denominators, as eligibility and data availability vary between measures (for example, fasting blood samples were required for dyslipidemia estimates).
- In 2022–24, 39% of respondents aged 18 years and over did not have their height, weight or both measured. For these respondents, imputation was used to obtain waist circumference and BMI scores.
- The ABS 2022–24 National Health Survey uses the Standard for Sex, Gender, Variations of Sex Characteristics and Sexual Orientation Variables, 2020 to collect the Sex at birth variable used in this data table. Due to small numbers and the need to protect privacy, people who reported sex at birth as a term other than male or female are not reported separately or included in the total Persons category. Sex recorded at birth refers to what was determined by sex characteristics observed at birth or infancy.
- In 2022–24, 28% of respondents aged 5 years over participated in the biomedical component, and not all provided fasting blood and urine samples. Missing biomedical data was not imputed. Results should be interpreted with this in mind. For more information about how measures were derived, see National Health Measures Survey methodology
Source:
AIHW analysis of ABS 2025.
For more information on these and other CKD risk factors, see:
- Diabetes
- High blood pressure
- Heart, stroke and vascular disease
- Overweight and obesity
- Smoking
- Insufficient physical activity
- Poor diet
- Alcohol
Visit Risk factors for more information on this topic.
ABS (Australian Bureau of Statistics) (2025), National Health Measures Survey, 2022–24 AIHW analysis of detailed microdata, accessed 1 December 2025.
Kidney Health Australia (2024) Chronic Kidney Disease (CKD) Management in Primary Care (5th edition). Kidney Health Australia, Melbourne, 2024.
Luyckx VA, Tuttle KR, Garcia-Garcia G, Gharbi MB, Heerspink HJL, Johnson DW, Liu ZH, Massy ZA, Moe O, Nelson RG, Sola L, Wheeler DC and White SL (2017) 'Reducing major risk factors for chronic kidney disease', Kidney International Supplements, 7(2):71–87.
Tesfaw LM, Tiong MK, Osborne NJ, Williams GM, Darssan D. (2025) Climate effect on the incidence of kidney failure patients in Australia. BMC Med. 2025 Nov 26;23(1):681. doi: 10.1186/s12916-025-04532-x.