Abbott Laboratories (ABT) Non Operating Interest Expenses (2009 - 2026)
Abbott Laboratories (ABT) recorded Non Operating Interest Expenses of $351 million in Q2 2026, up 190.1% from $121 million a year earlier and up 101.7% from the prior quarter.
Abbott Laboratories (ABT) Non Operating Interest Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Abbott Laboratories' Non Operating Interest Expenses came in at $766 million as of Jun 30, 2026, up 44.5% year-over-year; for FY2025, it was $493 million, down 11.8% from FY2024.
- Annual Non Operating Interest Expenses has a five-year compound annual growth rate of -2.0% (FY2020 to FY2025).
- Across earlier years, Non Operating Interest Expenses came in at $559 million in FY2024 (-12.2%), $637 million in FY2023 (+14.2%), $558 million in FY2022 (+4.7%) and $533 million in FY2021 (-2.4%).
- The Q2 2026 figure is the highest quarterly Non Operating Interest Expenses in data going back to Q2 2009.
- On a year-over-year basis, Non Operating Interest Expenses rose in two of the last eight quarters, with growth averaging 18.3%.
- Peak year-over-year performance for Non Operating Interest Expenses in the last five years was growth of 190.1% in Q2 2026, against a decline of 14.8% in Q3 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $174 million (Q1 2026), $120 million (Q4 2025) and $121 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 401.00 Mn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 351.00 Mn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 107.00 Mn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | - |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 186.00 Mn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 141.00 Mn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 96.00 Mn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | - |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 132.00 Mn |
| 10 | Agilent Technologies | 48.58 Bn | 41.47 Bn | 1.04 Bn | 29.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 351.00 Mn |
| Mar 31, 2026 | 174.00 Mn |
| Dec 31, 2025 | 120.00 Mn |
| Sep 30, 2025 | 121.00 Mn |
| Jun 30, 2025 | 121.00 Mn |
| Mar 31, 2025 | 131.00 Mn |
| Dec 31, 2024 | 136.00 Mn |
| Sep 30, 2024 | 142.00 Mn |
| Jun 30, 2024 | 140.00 Mn |
| Mar 31, 2024 | 141.00 Mn |
| Dec 31, 2023 | 159.00 Mn |
| Sep 30, 2023 | 166.00 Mn |
| Jun 30, 2023 | 159.00 Mn |
| Mar 31, 2023 | 153.00 Mn |
| Dec 31, 2022 | 154.00 Mn |
| Sep 30, 2022 | 141.00 Mn |
| Jun 30, 2022 | 132.00 Mn |
| Mar 31, 2022 | 131.00 Mn |
| Dec 31, 2021 | 131.00 Mn |
| Sep 30, 2021 | 133.00 Mn |
Abbott Laboratories Non Operating Interest Expenses 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=non-operating-interest-expenses&ticker=ABT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "ticker": "ABT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=non-operating-interest-expenses&ticker=ABT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();