Personal light exposure patterns and incidence of type 2 diabetes: analysis of 13 million hours of light sensor data and 670,000 person-years of prospective observation
A study in The Lancet
https://www.thelancet.com/journals/lanepe/article/PIIS2666-7762(24)00110-8/fulltext#%20
found that people who were exposed to the most light between 12:30 AM and 6 AM were 1.5 times more likely to develop type 2 diabetes than those who remained in darkness during that timeframe.
The study builds on growing evidence linking nighttime light exposure to type 2 diabetes risk. But unlike previous large studies that relied on satellite data of outdoor light levels (an indirect measure of light exposure), the recent study looked at personal light exposure — that is, light measured directly on individuals — as recorded by a wrist-worn sensor.
”Those previous studies likely underestimated the effect,” said study author Andrew Phillips, PhD, professor of sleep health at Flinders University in Adelaide, Australia, ”since they did not capture indoor light environments.”
Using data from 85,000 participants from the UK Biobank, the recent study is the largest to date linking diabetes risk to personal light exposure at night.
”This is really a phenomenal study,” said Courtney Peterson, PhD, a scientist at the University of Alabama at Birmingham’s Diabetes Research Center, who was not involved in the study. ”This is the first large-scale study we have looking at people’s light exposure patterns and linking it to their long-term health.”
What the Study Showed
The participants wore the light sensors for a week, recording day and night light from all sources — whether from sunlight, lamps, streetlights, or digital screens. The researchers then tracked participants for 8 years.
”About half of the people that we looked at had very dim levels of light at night, so less than one lux — that basically means less than candlelight,” said Phillips. ”They were the people who were protected against type 2 diabetes.”
Those exposed to more light at night — defined in the study as 12:30 AM-6 AM — had a higher risk for type 2 diabetes. The risk went up as a dose response, Phillips said: The brighter the light exposure, the higher the diabetes risk.
Participants in the top 10% of light exposure — who were exposed to about 48 lux , or the equivalent of relatively dim overhead lighting — were 1.5 times more likely to develop diabetes than those in the dark. That’s about the risk increase you’d get from having a family history of type 2 diabetes, the researchers said.
Even when they controlled for factors like socioeconomic status, smoking, diet, exercise, and shift work, ”we still found there was this very strong relationship between light exposure and risk of type 2 diabetes,” said Phillips.
How Light at Night May Increase Diabetes Risk
The results are not entirely surprising, said endocrinologist Susanne Miedlich, MD, a professor at the University of Rochester Medical Center, Rochester, New York, who was not involved in the study.
Light at night can disrupt the circadian rhythm, or your body’s internal 24-hour cycle. And scientists have long known that circadian rhythm is important for all kinds of biologic processes, including how the body manages blood sugar.
One’s internal clock regulates food intake, sugar absorption, and the release of insulin. Dysregulation in the circadian rhythm is associated with insulin resistance, a precursor to type 2 diabetes.
Phillips speculated that the sleep hormone melatonin also plays a role.
”Melatonin does a lot of things, but one of the things that it does is it manages our glucose and our insulin responses,” Phillips said. ”So if you’re chronically getting light exposure at night, that’s reducing a level of melatonin that, in the long term, could lead to poor metabolic outcomes.”
Previous studies have explored melatonin supplementation to help manage diabetes. ”However, while melatonin clearly regulates circadian rhythms, its utility as a drug to prevent diabetes has not really panned out thus far,” Miedlich said.
Takeaways
Interventional studies are needed to confirm whether strategies like powering down screens, turning off lights, or using blackout curtains could reduce diabetes risk.
That said, ”there’s no reason not to tell people to get healthy light exposure patterns and sleep, especially in the context of diabetes,” said Phillips.
Other known strategies for reducing diabetes risk include intensive lifestyle programs, which reduce risk by up to 58%, and metformin and GLP-1 agonists.
From www.medscape.com
ABSTRACT
Personal light exposure patterns and incidence of type 2 diabetes: analysis of 13 million hours of light sensor data and 670,000 person-years of prospective observation
Summary
Background
Light at night disrupts circadian rhythms, and circadian disruption is a risk factor for type 2 diabetes. Whether personal light exposure predicts diabetes risk has not been demonstrated in a large prospective cohort. We therefore assessed whether personal light exposure patterns predicted risk of incident type 2 diabetes in UK Biobank participants, using ∼13 million hours of light sensor data.
Methods
Participants (N = 84,790, age (M ± SD) = 62.3 ± 7.9 years, 58% female) wore light sensors for one week, recording day and night light exposure. Circadian amplitude and phase were modeled from weekly light data. Incident type 2 diabetes was recorded (1997 cases; 7.9 ± 1.2 years follow-up; excluding diabetes cases prior to light-tracking). Risk of incident type 2 diabetes was assessed as a function of day and night light, circadian phase, and circadian amplitude, adjusting for age, sex, ethnicity, socioeconomic and lifestyle factors, and polygenic risk.
Findings
Compared to people with dark nights (0–50th percentiles), diabetes risk was incrementally higher across brighter night light exposure percentiles (50–70th: multivariable-adjusted HR = 1.29 [1.14–1.46]; 70–90th: 1.39 [1.24–1.57]; and 90–100th: 1.53 [1.32–1.77]). Diabetes risk was higher in people with lower modeled circadian amplitude (aHR = 1.07 [1.03–1.10] per SD), and with early or late circadian phase (aHR range: 1.06–1.26). Night light and polygenic risk independently predicted higher diabetes risk. The difference in diabetes risk between people with bright and dark nights was similar to the difference between people with low and moderate genetic risk.
Interpretation
Type 2 diabetes risk was higher in people exposed to brighter night light, and in people exposed to light patterns that may disrupt circadian rhythms. Avoidance of light at night could be a simple and cost-effective recommendation that mitigates risk of diabetes, even in those with high genetic risk.
Funding
Australian Government Research Training Program.
Research in context
Evidence before this study
We searched PubMed and Google Scholar for studies published up to December 2023, using search terms (“light” OR “light at night” OR “light exposure” OR “circadian”) AND “diabetes”. Small-scale observational studies linked type 2 diabetes and associated pathophysiology with night light exposure recorded by personal and bedroom light sensors. Larger cohort studies linked outdoor night light assessed from satellite data with higher incidence and prevalence of type 2 diabetes, but did not assess personal light exposure. Experimental studies in animals and humans demonstrated that exposure to light patterns that disrupt circadian rhythms caused reduced glucose tolerance, altered insulin secretion and lipid profiles, and weight gain, supporting the role of light exposure in the pathogenesis of type 2 diabetes.
Added value of this study
This was the largest known study to link personal light exposure with risk of type 2 diabetes, analyzing ∼13 million hours of light sensor data and incident diabetes across ∼670,000 person-years of follow-up, in ∼85,000 individuals. Light sensors allowed for approximation of personal day and night light exposure, in contrast with the satellite-derived outdoor night light environments analysed in previous cohort studies. The cohort was well-characterized, and consisted of older individuals who were at higher risk of disrupted circadian rhythms and incident type 2 diabetes. Polygenic risk scores supported independent contributions of genetic susceptibility and light exposure to risk of type 2 diabetes. Circadian rhythm modeling supported circadian disruption as a linking mechanism between light exposure and type 2 diabetes, and demonstrated that computational estimations of circadian rhythms have predictive utility for cardiometabolic health.
Implications of all the available evidence
Exposure to brighter night light, and light patterns that disrupt circadian rhythms, predict higher risk of type 2 diabetes in older adults. Advising people to avoid night light is a simple and cost-effective recommendation that may ease the global health burden of type 2 diabetes.
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https://www.thelancet.com/journals/lanepe/article/PIIS2666-7762(24)00110-8/fulltext#%20
FROM THE ARTICLE
Introduction
Circadian rhythm disruption has been strongly implicated in the development of type 2 diabetes.
Circadian rhythms are disrupted by light exposure at night, which shifts the timing (phase-shift) and weakens the signal (amplitude suppression) of the central circadian pacemaker in the hypothalamus. This central pacemaker orchestrates the timing of metabolic processes required for glucose homeostasis, including circadian rhythms in insulin secretory capacity that peak during the day, and circadian rhythms in glucose secretion that peak at night. Mismatch of internal circadian rhythms with external environmental and behavioral rhythms can cause a pre-diabetic state in healthy humans. Prolonged exposure to internal-external mismatch is associated with higher risk of type 2 diabetes in shift workers and people with social jetlag.
Since light exposure patterns are a modifiable external factor that affects internal circadian physiology, they may also be a modifiable risk factor for the development of type 2 diabetes.
Emerging research demonstrates that light at night is linked with cardiometabolic pathophysiology, including type 2 diabetes. Higher risks for type 2 diabetes, obesity, and hypertension have been observed in people with greater exposure to night light, measured with wrist-worn, and bedside light sensors in small cohort studies, and experimental exposure to light during sleep has been shown to increase next-day insulin resistance.
Experimental work in animal models supports night light exposure and circadian disruption as causal factors in diabetes pathophysiology. Reduced glucose tolerance, altered insulin secretion, and weight gain occur in mice exposed to light during the biological night, after controlling for physical activity and food intake, and circadian clock-mutant mice have altered insulin, glucose, and lipid profiles, and higher obesity, compared with wild type.
Large-scale cohort studies in humans have recently linked night light assessed from satellite data with the incidence and prevalence of type 2 diabetes. However, satellite data do not capture the personal indoor lighting environment, where most people spend over 80% of their time.
To our knowledge, no large-scale study has examined whether objective, personal light exposure is linked with risk of developing type 2 diabetes, or assessed the role of circadian disruption in this relationship. We assessed whether risk of incident type 2 diabetes was associated with exposure to light at night, and with modeled circadian amplitude and phase, in 84,790 UK Biobank participants using 13 million hours of data from wrist-worn light sensors, and type 2 diabetes diagnoses from hospital, primary-care, and death register records across 7.9 ± 1.2 years of follow-up.
Discussion
Across ∼670,000 person-years of observation in ∼85,000 participants, and 13 million hours of personal light sensor data, we found that exposure to brighter light at night predicted higher risk of incident type 2 diabetes across an average of 7.9 ± 1.2 years of follow-up. Modeling indicated that suppressed circadian amplitude and circadian phase that deviated from the group average also predicted higher risk of type 2 diabetes, supporting the role of circadian disruption in the development of type 2 diabetes. Light exposure at night and polygenic risk were independent predictors of incident type 2 diabetes, indicating that reducing night light may attenuate an individual’s risk of type 2 diabetes despite their genetic susceptibility.
We observed a dose-dependent relationship between brighter light exposure at night (00:30 to 06:00) and higher risk of subsequent type 2 diabetes. Compared to individuals with dark environments (the 0–50th percentile), those in the 50–70th, 70–90th, and 90–100th percentiles of light exposure had, respectively, 28–33%, 39–44%, and 53–67% higher risks for developing type 2 diabetes. This relationship between night light and type 2 diabetes was robust to: (i) adjustments for age, sex, ethnicity, socioeconomic status, smoking, alcohol, diet, physical activity, urbanicity, and day light exposure; (ii) additional adjustments for baseline cardiometabolic health, mental health, sleep duration, chronotype, and photoperiod; and (iii) exclusion of shift workers and individuals with pre-diabetic HbA1c or random glucose levels prior to light-tracking. Night light was also a robust predictor of type 2 diabetes within both male and female sub-groups, with no significant difference in this relationship between groups. These findings build on data from longitudinal research that demonstrates higher risk of type 2 diabetes in people exposed to night light, recorded by light sensors.
We confirm these findings in a much larger cohort after controlling for potential confounding factors, and using personal light sensors that capture more than the bedroom environment at night. Our findings are also consistent with studies of satellite-derived night light in larger cohorts.
These studies demonstrate significant but comparatively weaker relationships between night light and type 2 diabetes (e.g., 7% greater diabetes risk per quintile of brighter night light), possibly reflecting the fact that satellite data do not capture personal light exposure across 24 h.
We applied a validated computational model representing the response of the human central circadian clock to light, to identify participants with weekly light patterns that could suppress the amplitude or shift the phase of their central circadian clock.
Risk of incident diabetes was higher in people with light patterns that could suppress circadian amplitude (7% higher risk per standard deviation reduction in amplitude), and in people with light patterns that could advance circadian phase (18–39%) or delay phase (6–30%) compared to the group average. These results are in keeping with experimental and epidemiological work demonstrating that disrupted circadian rhythms, or exposure to zeitgebers capable of disrupting rhythms, are linked to type 2 diabetes and its associated pathophysiology.
Exposure to light that suppresses or shifts central circadian rhythms to an abnormal phase may alter circadian rhythms in insulin secretory capacity and glucose secretion, by either suppressing these rhythms, or shifting their timing relative to behavioral rhythms in nutritional intake, sleep, and physical activity. For example, disrupted circadian melatonin or glucocorticoid rhythms may exhibit elevated concentrations during waking hours, thereby reducing pancreatic insulin secretion and promoting hepatic glucose production at times that coincide with food intake. Persistent circadian misalignment may lead to persistently elevated postprandial glucose levels, initiating the development of type 2 diabetes by increasing the size and inflammation of adipocytes, thereby promoting insulin resistance and the secretion of inflammatory markers (e.g., interleukin-1β) that inhibit pancreatic beta-cell function.
Sleep likely plays an important role in the relationships between light exposure, circadian disruption, and diabetes risk. Sleep and light exposure patterns share a bidirectional relationship, and sleep disruption is an established risk factor for type 2 diabetes.
he relationship between light exposure and diabetes could therefore be partially explained by sleep disruption that co-occurs with night light exposure. Light exposure during the night could lead to disrupted sleep, but awakenings during the night could also lead to greater night light exposure, due to light usage during awakenings. Notably, in our analyses, night light exposure was an independent predictor of type 2 diabetes risk after adjustment for sleep duration. This finding supports night light as a predictor of diabetes risk, independent of sleep duration.
Night light exposure and genetic risk were found to be independent risk factors for developing type 2 diabetes. We derived polygenic risk scores for type 2 diabetes, and confirmed that they were robust predictors of type 2 diabetes diagnoses in the UK Biobank cohort. Higher polygenic scores were associated with 1.6, 2.3, and 4.2 times greater risk of incident diabetes in the second, third, and fourth polygenic risk quartiles, respectively, compared with the lowest-risk quartile. The difference between the 0–50% and 90–100% night light groups was similar to the difference between the 0–25% and 25–50% or the 25–50% and 50–75% polygenic risk categories. This indicates that, while polygenic risk score is a stronger predictor than night light exposure, reducing light exposure at night could attenuate an individual’s susceptibility due to genetic risk of developing diabetes. A robust dose-dependent relationship between brighter light at night and higher diabetes risk was observed after adjustment for polygenic risk. This finding indicates that reduction of night light is a potential beneficial strategy for all individuals, including those with high genetic risk.
This study has several limitations. First, we could not investigate the role of food timing, since temporal dietary information was not available. Food timing can alter peripheral circadian rhythms in humans, impacting glucose tolerance and adiposity,
and may therefore play a key role in the relationships between light, circadian disruption, and diabetes. Second, the cohort studied here had a mean (±SD) age of 62.3 ± 7.85 years, and it is therefore unclear whether our findings generalize to younger cohorts. Third, the computational model of the human circadian pacemaker was originally developed and has primarily been tested in young adults.
Estimated circadian phase and amplitude may therefore not reflect changes in the central circadian clock with age.
Fourth, inter-individual differences in light sensitivity could not be captured. Light intensity required to suppress 50% of melatonin secretion can range from 6 to 350 lux across individuals. These inter-individual differences in sensitivity of the circadian system to light may contribute to higher variability in the estimated effects of light exposure on type 2 diabetes. Fifth, some socioeconomic factors were captured at the area-level, but not individual level, possibly leading to unmeasured confounding. For example, area-level information on participant housing was captured under urbanicity and deprivation factors, but individual-level housing information was not. An individual’s control over their home environment, including the lighting, is a plausible predictor of both night light exposure and type 2 diabetes risk. Sixth, only one week of light data were collected for each individual, and wrist-worn light sensors may have been prone to coverage by individuals’ clothing. However, despite these limitations, brighter night light remained a robust predictor of type 2 diabetes even after comprehensive model adjustments. We also note that light exposure patterns were stable in a sub-sample of 2988 participants with repeat-measures, as reported in our previous work.
Seventh, covariates were collected several years prior to light recordings, and some of these covariates may change over time. Finally, relationships between light exposure patterns and diabetes risk in Models 2–3 may be attenuated by mediating pathways. Model 1 may therefore provide a closer approximation of the casual relationship between light exposure patterns and type 2 diabetes risk; however, large-scale intervention studies are required to establish the true causal relationship.
Current behavioral strategies for prevention and treatment of type 2 diabetes focus on increasing physical activity and improving diet, to reduce visceral adiposity and improve diabetes biomarkers.
Our findings show that maintaining a dark environment during the night may mitigate risk of developing type 2 diabetes, likely due to the disruptive effects of light at night on circadian rhythms. Advising people to turn off their lights at night, or use lights that reduce the circadian impact (dim and “warm” light), is a simple, cost-effective, and easily-implementable recommendation that may promote cardiometabolic health and ease the growing global health burden of type 2 diabetes.
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