# Heat in Luxembourg: Understanding the Risk Without Overinterpreting

A clear guide to reading the national study 1998–2023 and using its results as life context, not as a score assigned to a home.

Canonical: [https://chathome.lu/en/insights/mortalite-chaleur-logement-luxembourg](https://chathome.lu/en/insights/mortalite-chaleur-logement-luxembourg)
Published: 2026-08-10T01:37:38.857Z
Updated: 2026-08-13T10:02:07.503Z

Remember 2.8 age-standardized attributable deaths per 100,000 people/year for extreme heat (95% CI: 1.8–3.8). The separately published factor of 1.93 concerns the odds of an extreme excess mortality episode, not the daily number of deaths. The study measures neither indoor temperature, nor air conditioning, nor the characteristics or value of homes.

## Key takeaways

- Cite Weiss's exact rate: 2.8 age-standardized attributable deaths per 100,000 people/year for extreme heat, 95% CI 1.8–3.8.
- Do not convert the odds ratio of 1.93 into an increase in the daily number of deaths; it concerns the probability of an extreme excess mortality episode.
- Use STATEC's 4,471 deaths in 2024 only as all-cause context; the average of 12.2 per day is not the basis of Weiss's model.
- Do not attach any health or property effect to a housing feature: the study measured neither homes nor interventions.

## Direct Answer

The best currently available national estimate in the studied source is **2.8 age-standardized attributable deaths per 100,000 people per year** for extreme heat episodes in Luxembourg, over the period 1998–2023. The 95% confidence interval ranges from **1.8 to 3.8**.

This result comes from the article by **Jérôme Weiss**, published on March 4, 2025, in the *International Journal of Environmental Research and Public Health* (DOI 10.3390/ijerph22030376; [full text PubMed Central](https://pmc.ncbi.nlm.nih.gov/articles/PMC11941813/); [PubMed record](https://pubmed.ncbi.nlm.nih.gov/40238412/)). It is a **modeled, age-standardized attributable rate**, not a count of death certificates mentioning "heat" and not an observation of 12.6 deaths per year.

## How to Read the Mechanism Without Jargon

The study compares, week by week, deaths from natural causes and national environmental exposures between 1998 and 2023. It defines an **extreme heat day** by a maximum temperature of at least **35 °C** and an average temperature of the previous day of at least **23 °C**.

It publishes two measures because they answer two different questions: the **age-standardized annual attributable rate** estimates an average burden, while the **odds ratio** describes the probability of an extreme excess mortality episode. For heat, this ratio is **1.93** (95% CI: **1.52–2.66**). It should therefore not be applied to the daily number of deaths as a direct percentage.

## The Three Comparable Attributable Rates

| Exposure studied | Standardized attributable rate | 95% confidence interval |
| --- | ---: | ---: |
| Extreme heat | 2.8 deaths/100,000/year | 1.8–3.8 |
| Extreme cold | 1.1 deaths/100,000/year | 0.4–1.8 |
| PM₂.₅ episodes | 6.3 deaths/100,000/year | 2.3–10.3 |

These values are estimates from the same model and can be compared on their common unit. They should not be added together as three independent counts: the article identifies confounding effects between certain pollutants and heat.

## Numerical Example: Reading the Unit Correctly

Take a **fictional standardized population of 200,000 people followed for one year**. The scaling calculation is:

- extreme heat: 2.8 × 2 = **5.6** attributable deaths, scaled interval **3.6–7.6**;
- extreme cold: 1.1 × 2 = **2.2**, interval **0.8–3.6**;
- PM₂.₅: 6.3 × 2 = **12.6**, interval **4.6–20.6**.

Thus, this example only explains the unit "per 100,000 people/year." It does not predict the actual number of deaths in a Luxembourg population of 200,000 people. Age standardization uses a reference structure; it does not transform into a raw national count by simple multiplication by the current population.

## The STATEC Benchmark: 12.2 Deaths per Day, All Causes

The [STATEC](https://statistiques.public.lu/en/actualites/2025/stn16-population-2025.html) recorded **4,471 deaths in 2024**. Since 2024 had 366 days, the descriptive average is **4,471 ÷ 366 = 12.2 deaths per day**, all causes combined.

This average is not the reference level of Weiss's model. It only gives an all-cause order of magnitude for another year; the standardized rate and the odds ratio answer different questions.

## What This Means for a Housing Search

The [WHO](https://www.who.int/news-room/fact-sheets/detail/climate-change-heat-and-health) explains that heat accumulation in the body depends on temperature, humidity, wind, radiation, clothing, and the ability to dissipate heat; it also indicates that certain materials and built environments can amplify exposure.

But the Luxembourg study by Weiss includes **no variables on housing**: no indoor temperature, floor, orientation, insulation, blinds, ventilation, or air conditioning. It tests no residential interventions and measures no real estate value.

In practice, use this study to understand that extreme heat is a measurable national issue. To compare two homes, then ask separate questions about shade, ventilation, floor, and summer comfort, without turning these answers into a medical promise or resale value.

## Continue Without Turning Data into a Health Score

The [housing search](/en/search) allows you to compare the inventory, and the [environment explorer](/en/discover/environment) organizes other territorial data. For a separate question on renovation aid, the [Klimabonus simulator](/en/financial-tools/klimabonus) is a starting point. None of these tools converts a listing feature into medical protection or replaces the official conditions of the relevant scheme.

## The Limitation to Keep in Mind

The analysis is national, aggregated, and weekly. It therefore provides public health context with uncertainty intervals, not an individual diagnosis or a comparison between communes. The useful summary is simple: **over 1998–2023, the national model associates extreme heat episodes with measurable attributable mortality, estimated at 2.8 standardized deaths per 100,000 people/year.**

## Methodology

All Luxembourg estimates for heat, cold, and PM₂.₅ are transcribed from the peer-reviewed article by Jérôme Weiss published in 2025, then verified in PubMed and the full text on PubMed Central. The STATEC calculation is 4,471 ÷ 366 = 12.2158, rounded to 12.2 deaths per day, and remains separate from the study's model. The numerical example scales the published rates to a fictional standardized population solely to explain the unit; it is neither a national count nor a forecast. The WHO is used only for the general physiological mechanism, without deducing the effect of a housing feature in Luxembourg.

## Limitations

Weiss's study uses national weekly mortality and modeled environmental exposures for 1998–2023. Its attributable rates are estimates with confidence intervals, not observed counts by cause or communal scores. The article analyzes neither indoor temperature, housing, cooling interventions, medical treatment, property value, nor renovation costs.

## Sources

- PubMed record for Weiss, Jérôme, Short-Term Effects of Extreme Heat, Cold, and Air Pollution Episodes on Excess Mortality in Luxembourg, PMID 40238412, published 2025-03-04, accessed 2026-08-10: https://pubmed.ncbi.nlm.nih.gov/40238412/
- PubMed Central full text PMCID PMC11941813, accessed 2026-08-10: https://pmc.ncbi.nlm.nih.gov/articles/PMC11941813/
- STATEC, In 2024, population growth slowed due to low fertility and a decline in immigration, 4,471 deaths in 2024, accessed 2026-08-10: https://statistiques.public.lu/en/actualites/2025/stn16-population-2025.html
- World Health Organization, Heat and health, dated 2026-07-31, accessed 2026-08-10: https://www.who.int/news-room/fact-sheets/detail/climate-change-heat-and-health

## Frequently asked questions

### How many deaths does extreme heat cause in Luxembourg?

Jérôme Weiss's study does not establish a raw annual count. It estimates, over 1998–2023, an age-standardized attributable rate of 2.8 deaths per 100,000 people/year, with a 95% confidence interval of 1.8 to 3.8.

### What does the factor 1.93 mean for heat?

It is the multiplier of the odds of an extreme excess mortality episode occurring on an extreme heat day, with a confidence interval of 1.52 to 2.66. It is not a multiplier of the number of daily deaths.

### Does the study prove that air conditioning or blinds reduce mortality?

No. It contains no data on buildings, indoor temperatures, air conditioning, blinds, or other residential interventions. It therefore cannot quantify their effect in Luxembourg.

### How do STATEC figures relate to the study?

STATEC recorded 4,471 deaths from all causes in 2024, or 12.2 per day on average. This benchmark describes another year and another measure; it should not be directly combined with Weiss's odds ratio or standardized rate.