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A large national study reveals that sticking to an 11–12-hour eating window may promote longevity, while shorter or longer eating spans could quietly increase the risk of premature death.

Study: Association of Eating Window With Mortality Among US Adults: Insights From a Nationally Representative Study. Image Credit: Marcin Malicki / Shutterstock

In a recent paper published in the journal Aging Cell, researchers investigated the links between the duration of daily eating windows and mortality from various causes among American adults. They found a U-shaped association. Mortality risk was lowest for those with eating windows of 11–12 hours. Shorter (<8 hours) and longer (≥15 hours) eating windows were associated with higher mortality rates, although the latter showed weaker statistical significance after full adjustment for lifestyle and health factors.

Background

Time-based diets limit eating to certain hours and are popular for their simplicity and possible health benefits. Studies suggest that they improve glucose and lipid levels, boost ketone production, and reduce oxidative stress, thereby supporting better cardiometabolic health.

Most evidence comes from animal or short-term human studies, so we have limited knowledge about the long-term effects on longevity. Many studies focus on specific groups, like people with obesity, diabetes, or younger adults. This limits how widely results apply.

Evidence from U.S. surveys shows older adults tend to have earlier and narrower eating windows, particularly among women and Black individuals. While two recent studies based on the National Health and Nutrition Examination Survey (NHANES) suggested nonlinear associations between eating duration and mortality, they were limited by broad categories or specific age groups, which may obscure the risks associated with very short eating windows.

Mechanistic and observational studies suggest that very short eating windows can lead to nutrient deficiencies or insufficient energy intake, while excessively long ones encourage late-night eating and circadian disruption that impairs glucose tolerance and lipid metabolism. Together, these findings make nonlinear links between eating windows and mortality biologically plausible.

About the Study

Researchers employed a prospective cohort design, based on NHANES data from 2003 to 2018, and linked to mortality records through 2019. After excluding people younger than 20 and those with incomplete or invalid dietary recalls, extreme energy intake, pregnancy, missing demographic or health data, and outlying body mass index (BMI) values, 33,052 adults were included.

Dietary intake was assessed using two 24-hour recalls, and the eating window was defined as the time between the first and last intake of any caloric item within a day. Data from both recalls were averaged to account for daily variation. Mortality outcomes, including all-cause, cardiovascular, and cancer-related deaths, were obtained from the National Death Index.

Covariates included demographics, socioeconomic factors, lifestyle behaviors (smoking, alcohol use, physical activity, and sleep), diet quality (as measured by the Healthy Eating Index), and health status, including chronic conditions. BMI and weight-related perceptions were also taken into consideration.

Associations were examined using two complementary approaches: (1) restricted cubic splines to model nonlinear relationships (treating eating windows as continuous), and (2) predefined categories (e.g., <8h, 12–12.99h as reference, ≥15h). Analyses used survey-weighted Cox regression models to account for NHANES’ complex sampling design.

Key Findings

This study followed 33,052 American adults for a median of 8.1 years, documenting 4,158 deaths, including 1,277 from cardiovascular disease and 989 from cancer. A U-shaped association emerged between the daily eating window and all-cause mortality.

The lowest mortality risk was linked to an eating duration of 11–12 hours per day. Eating for less than 8 hours daily was consistently associated with higher all-cause mortality, showing a 34% greater risk compared to the reference group (12–12.99 hours).

Longer eating windows (15 hours or more) were also associated with a 25% increased risk of developing the condition. However, this association was statistically significant only in White participants and had a confidence interval (1.01–1.55), indicating borderline significance after full adjustment.

Subgroup analyses revealed critical nuances:

• Shorter windows (<8h) drove a ~50–70% increase in cardiovascular mortality among older adults, men, and White participants (HRs ~1.5–1.7).
• No significant mortality risk was observed for shorter windows in younger adults after full adjustment.
• Women showed elevated but statistically nonsignificant mortality risk with shorter windows (p = 0.132), while men retained significance (p = 0.049).
• For cancer mortality, short-window associations faded after full adjustment, with a marginal trend observed only in women. Cardiovascular mortality mirrored these findings, with the lowest risk at 11–12 hours and significantly higher risk for shorter windows, but no strong overall associations with longer windows except among Whites (HRs approaching ~1.5 in spline models).

Sensitivity analyses excluding early deaths, younger participants, and extreme eating patterns confirmed the robustness of these results.

Conclusions

The findings suggest that both very short (less than 8 hours) and very long (15 hours or more) eating windows may increase the risk of mortality. In comparison, a moderate eating duration of 11–12 hours daily is associated with the lowest risk. These results highlight the potential health risks of highly restricted eating patterns, particularly for older adults, men, and White individuals. However, they do not broadly condemn intermittent fasting, emphasizing instead that deviations from moderate windows carry demographic-specific risks.

Strengths of this study include its large, nationally representative cohort, long follow-up period, comprehensive adjustments for diet quality, chronic conditions, socioeconomic factors, and lifestyle behaviors, as well as dual analytical approaches (continuous/categorical). Multiple sensitivity analyses further supported robustness.

However, limitations include reliance on self-reported dietary recalls (only two 24-hour assessments), which may not fully capture habitual patterns; the observational design, which prevents causal inference; lack of data on circadian timing of food intake; and unmeasured confounders, such as shift work details.

In conclusion, moderate eating windows appear most favorable for long-term health, underscoring the need for personalized approaches that avoid extremes in time-restricted eating, especially for high-risk subgroups.

Ana de Bettencourt-Dias, chemistry professor and department chair, was awarded for Distinguished Service in the Advancement of Inorganic Chemistry by the American Chemical Society (ACS).

Specifically, de Bettencourt-Dias was recognized for her contributions to f-element chemistry and spectroscopy and for her service to the wide-reaching programming of the Division of Inorganic Chemistry (DIC). She was named a fellow of the ACS in 2021.

de Bettencourt-Dias has served in several positions within the American Chemical Society, including as chair of the Sierra Nevada section, councilor, program chair and member at large for the DIC, as well as chair and chair elect for the DIC subdivision of Coordination Chemistry and chair and chair elect of DIC. She has been active in the ACS since 2011, “so I have a long institutional memory,” she said.

de Bettencourt-Dias studies rare earth minerals, which are lanthanides and actinides or the “f-elements.” They play a big role in electronics.

“We need to have more effective ways of sourcing the rare earths,” she said. “As a country, we need to be investing in research to recycle that part of discarded electronics.”

As program chair, she has helped grow the f-elements session at ACS conferences from about a dozen talks to 100 talks and is responsible for coordinating the national meetings for the DIC. She takes care to ensure that the programming caters to academics at all stages, from undergraduates to leaders in the field.

de Bettencourt-Dias also helped launch the Periodic TableTalks, a monthly webinar series that started during the height of the COVID-19 pandemic, when she was past chair of the DIC. The series remains popular, with 100-200 people attending the virtual presentations. The presentations are also recorded, and those recordings are used by faculty, especially those at primarily undergraduate institutions, to help bring cutting-edge inorganic chemistry research to their students.

The presenters in each Periodic TableTalk are one established researcher and one early career researcher who have 20 minutes each to present their work, and they, as well as the audience, come from all over the world. These opportunities are valuable for early career and international researchers to get more exposure and experience talking to chemists in their field of interest.

“For early career faculty, when they go out for tenure, we request letters from the larger inorganic community for them,” de Bettencourt-Dias said. “The Periodic TableTalks help to highlight their research and who they are.”

In the future, de Bettencourt-Dias hopes to expand mentorship opportunities for early career faculty, especially as funding opportunities are reduced at the federal level.

The distinguished service award came with $5,000, sponsored by Strem Chemicals, which de Bettencourt-Dias will put toward bringing engaging researchers to the ACS conference.

de Bettencourt-Dias said she feels proud to have been considered for the award amongst a field of scientists at institutions often deemed to be more prestigious and feels fortunate because of how the University has supported her work.

“It’s wonderful to have been considered,” she said.

de Bettencourt-Dias has been recognized by several organizations for her research and service. She was named the Susan Magee and Gary Clemons Professor of Chemistry and a Foundation Professor and won the University’s Outstanding Researcher Award. She is also a fellow of the Royal Society of Chemistry and the American Association for the Advancement of Science.

“These honors are the result of years of dedication to advancing chemistry,” Dean Louisa Hope-Weeks said. “We are proud to have Ana among our talented and innovative faculty members.”

In a conversation with CancerNetwork^® during a visit to Yale Cancer Center in New Haven, Connecticut, David A. Braun, MD, PhD, detailed his group’s work in understanding how somatic alterations may impact responses or resistance to treatment among patients with kidney cancer.

Braun, assistant professor at Yale School of Medicine and principal investigator in the Center of Molecular and Cellular Oncology within the Yale Cancer Center, stated that it is crucial to embrace the complexity of biomarkers in kidney cancer, as individual genetic alterations alone would not determine whether a tumor responds to therapy. As part of dissecting each potential predictor of response or resistance to treatment, Braun described how approaches such as machine learning-based tools may play a role in advancing the field’s understanding of these factors.

Transcript:

Our research group and many others have investigated this question of how somatic alterations might impact responses or resistance to therapy for many years. The hope, initially, was a simple answer, that we would find something like the EGFR mutation in lung cancer; someone has this mutation, [so] they will respond to a drug, and if they do not have this mutation, they will not. What we have realized over the years is that it’s much more complicated than that. The kidney cancer genetic landscape and the immune microenvironment are both important factors, and that’s not necessarily going to be one thing—one genetic alteration—that’s going to make the difference between whether a tumor responds or doesn’t respond to a treatment.

What we start to move towards is embracing that complexity, understanding that it’s the genetic landscape of the cancer, the immune cells that are there, and other factors that altogether work to determine whether a cancer will effectively respond or not. [Many] of our efforts now have been dissecting each of those individual parts and then using a lot of approaches, including machine learning-based approaches, to put it all together.