Resmed (RMD) Total Non-Current Liabilities (2010 - 2026)
Resmed's Total Non-Current Liabilities came in at $939.9 million for fiscal Q1 2027 (quarter ended Sep 30, 2026), up 0.9% from $931.59 million a year earlier but down 4.6% from the prior quarter.
Resmed (RMD) Total Non-Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2026 (ended Jun 30, 2026), Resmed's Total Non-Current Liabilities was $985.45 million, down 17.0% from FY2025.
- Total Non-Current Liabilities carries a five-year compound annual growth rate of 1.2% (FY2021 to FY2026).
- Going back by fiscal year, Total Non-Current Liabilities was $1.19 billion in FY2025 (+8.2%), $1.1 billion in FY2024 (-41.1%), $1.86 billion in FY2023 (+78.2%) and $1.05 billion in FY2022 (+12.4%).
- The five-year range for quarterly Total Non-Current Liabilities is $931.59 million (fiscal Q1 2026) to $2.21 billion (fiscal Q2 2023).
- Year-over-year, Total Non-Current Liabilities increased in two of the last eight quarters, with an average decline of 13.6%.
- The fastest year-over-year change in Total Non-Current Liabilities over five years came in fiscal Q2 2023 (growth of 127.9%), and the weakest in fiscal Q4 2024 (a decline of 41.1%).
- Business Quant data shows RMD's Total Non-Current Liabilities at $985.45 million (Q4 2026), $941.16 million (Q3 2026) and $934.38 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 265.71 Bn | 242.23 Bn | 5.13 Bn | 54.88 Bn |
| 2 | Abbott Laboratories | 189.37 Bn | 163.23 Bn | 7.39 Bn | - |
| 3 | Danaher | 164.78 Bn | 144.43 Bn | 3.84 Bn | 33.44 Bn |
| 4 | Intuitive Surgical | 157.85 Bn | 138.13 Bn | 2.08 Bn | - |
| 5 | Medtronic | 129.66 Bn | 94.91 Bn | 6.34 Bn | 38.93 Bn |
| 6 | Stryker | 121.82 Bn | 108.01 Bn | 4.25 Bn | 20.68 Bn |
| 7 | Boston Scientific | 63.42 Bn | 58.86 Bn | 3.43 Bn | 17.15 Bn |
| 8 | Edwards Lifesciences | 59.49 Bn | 42.69 Bn | 1.35 Bn | 2.26 Bn |
| 9 | Becton Dickinson | 58.38 Bn | 55.53 Bn | 2.32 Bn | 23.92 Bn |
| 10 | Resmed | 33.31 Bn | 27.76 Bn | 870.57 Mn | 939.90 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 939.90 Mn |
| Jun 30, 2026 | 985.45 Mn |
| Mar 31, 2026 | 941.16 Mn |
| Dec 31, 2025 | 934.38 Mn |
| Sep 30, 2025 | 931.59 Mn |
| Jun 30, 2025 | 1.19 Bn |
| Mar 31, 2025 | 1.08 Bn |
| Dec 31, 2024 | 1.04 Bn |
| Sep 30, 2024 | 1.12 Bn |
| Jun 30, 2024 | 1.10 Bn |
| Mar 31, 2024 | 1.41 Bn |
| Dec 31, 2023 | 1.66 Bn |
| Sep 30, 2023 | 1.72 Bn |
| Jun 30, 2023 | 1.86 Bn |
| Mar 31, 2023 | 2.02 Bn |
| Dec 31, 2022 | 2.21 Bn |
| Sep 30, 2022 | 1.05 Bn |
| Jun 30, 2022 | 1.05 Bn |
| Mar 31, 2022 | 959.20 Mn |
| Dec 31, 2021 | 967.84 Mn |
Resmed Total Non-Current Liabilities API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=RMD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "RMD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=RMD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();