A new large-scale U.S. study, presented at the American College of Cardiology’s Annual Scientific Session (ACC.26) in March 2026, reinforces a long-standing pattern: cold temperatures pose a far greater mortality risk than heat, particularly for cardiovascular health.

Researchers analyzed ~14.2 million cardiovascular deaths (heart attacks, strokes, coronary disease, etc.) among adults 25+ across 819 U.S. counties (covering roughly 80% of the population) from 2000–2020.

Optimal temperature for lowest cardiovascular mortality: ~74°F (23°C).

Risk rises on both sides of that point, but the curve is sharply lopsided — far steeper on the cold side.

Cold temperatures linked to ~40,000 excess CV deaths per year (6.3% of all cardiovascular deaths) → ~800,000 total over 20 years.

Hot temperatures linked to only ~2,000 excess deaths per year (0.33%) → ~40,000 total.

Ratio: Cold responsible for ~20 times as many excess cardiovascular deaths as heat.

Most excess deaths occurred on moderately cold days (not extreme freezes), simply because those days are far more common.

Physiologically, cold triggers blood-vessel constriction, higher blood pressure, increased clotting risk, and greater strain on the heart — especially dangerous for the elderly or those with preexisting cardiovascular conditions. Moderate cold affects far more people over more days than brief heat spikes.

This data undercuts the narrative that warming is the dominant temperature-related health threat. In cold-winter states like Minnesota (where the prior discussion on climate spending originated), reliable, affordable heating and energy infrastructure are life-saving public-health measures.

Policies that raise energy costs — whether through aggressive emissions penalties, “climate superfunds,” or rushed grid changes — can inadvertently increase vulnerability to the far larger cold-related risk.

Adaptation priorities should reflect the actual burden: winter resilience (home insulation, heating assistance, reliable baseload power) saves far more lives today than speculative long-term heat-mitigation projects.

As populations age and chronic heart disease rises, protecting against the empirically greater killer (cold) is evidence-based risk management, not climate denial.

The study reinforces a consistent global and U.S. pattern: cold months kill far more people than warmer ones, by roughly an order of magnitude. Honest public-health and energy policy would weigh this reality alongside any warming projections.

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ScienceDirect

Title: Cardiovascular disease mortality attributable to monthly non-optimal temperature in the united states: a county-level analysis

Journal: American Journal of Preventive Cardiology

Article number: 101514
Available online: 24 March 2026
DOI: 10.1016/j.ajpc.2026.101514

Lead author: Pedro Rafael Vieira de Oliveira Salerno, MD (Icahn School of Medicine at Mount Sinai / NYC Health + Hospitals/Elmhurst), with co-authors including Ricardo J. Estrada-Mendizabal, Weichuan Dong, Avery Hum, Zhuo Chen, Colin Carpenter, Mohamed Bassiony, Sanjay Rajagopalan, Sadeer Al-Kindi, and Salil V. Deo.

This is a short report (not a full-length original research article), which explains why the ScienceDirect page may show limited free content beyond the title, authors, keywords, and license information. The complete text, figures (including the exposure-response curve), tables, and detailed methods/results are likely behind the publisher’s paywall or available via institutional access, ResearchGate, or author request.

A closely related 2026 paper by overlapping authors (analyzing 1,514 counties and ~33.4 million all-cause adult deaths) reported even larger absolute numbers: ~72,000 cold-attributable and ~6,100 heat-attributable deaths annually, with social vulnerability (via CDC Social Vulnerability Index) amplifying risks in both directions — more vulnerable counties had higher MMTs and elevated cold- and heat-related rates.

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The U-shaped mortality curve (also called a J-shaped or V-shaped curve in some contexts) is a standard concept in environmental epidemiology.

It describes the nonlinear relationship between daily ambient temperature and the risk of death (mortality).

Researchers plot temperature on the x-axis (cold on the left, hot on the right) and relative risk of death (or excess mortality rate) on the y-axis.

The curve forms a U (or skewed J) with the lowest point at the optimal (or minimum mortality) temperature — the temperature where death rates are lowest.

Risk rises symmetrically or asymmetrically as temperatures deviate in either direction.

Bottom (nadir): The “sweet spot” or minimum mortality temperature (MMT). In the recent 2026 U.S. ACC cardiovascular study of 14.2 million deaths, this was ~74°F (23°C).

Left arm (cold side): Mortality risk increases as temperatures fall below the MMT. This arm is often longer and gentler at first (moderate cold) but can steepen in extremes.

Right arm (heat side): Risk increases as temperatures rise above the MMT. This arm is frequently steeper per degree (extreme heat is more immediately dangerous day-to-day).

The curve is asymmetric (“lopsided”) in most real-world data — the cold side is broader and accounts for far more total deaths because moderate cold days occur much more frequently than extreme heat days.