Mismatch of Sleep and Work Timing and Risk of T2D
The findings add to the growing body of evidence suggesting a chronotype-dependent association between work hours and metabolic disease risk among women. To our knowledge, this is the first large cohort study to explicitly probe the hypothesis of circadian misalignment by examining the interaction between chronotype and shift work. We consistently observed in women a significant interaction between chronotype and shift work, suggesting a slightly lower risk of type 2 diabetes among early chronotypes compared with intermediate chronotypes, which appeared to increase with increasing duration of rotating night shift work (no rotating night shift work: MVOR 0.81; <10 years: 0.84; ≥10 years: 1.15). This finding is a possible result of early sleep and wake times, leading to more circadian misalignment during night shifts. By contrast, late chronotypes experienced a significant increase in type 2 diabetes risk when their shift schedule did not involve night work, whereas this association was not observed if they worked any number of years of night shifts independent of the duration of exposure (no rotating night shift work: MVOR 1.51; <10 years: 0.93; ≥10 years: 0.86).
In line with the current findings, a previous cross-sectional analysis reported an up to two- to fivefold increased risk of type 2 diabetes among late compared with early chronotypes. However, covariate adjustment in that study was limited because no information on other important confounders such as diet, physical activity, or family history of diabetes was available.
Building on a large body of literature on shift work tolerance and interindividual differences and more recent findings on the links among the circadian system, sleep, and metabolism, it is believed that in addition to sleep deprivation, circadian misalignment contributes to disease etiology. Thus, chronotype (a measure of internal biological time, which is most readily described through sleep timing) alone may not fully capture associations with disease that are driven by circadian misalignment. Rather, the interaction between chronotype and working times likely represents a better measure of a person's actual level of circadian misalignment. To explicitly address this hypothesis, we made use of the regularly updated shift work information in the NHS2, where from 1989 onward, women indicated how many months in the past 2-year period they worked three or more night shifts per month. The findings support this hypothesis: Early chronotypes had a reduced type 2 diabetes risk when not exposed to night shift work, which tended to increase if they worked longer durations of night shift work. Future studies with more detailed information on number of night shifts worked per month in addition to years of night work may be able to further disentangle possible intensity and duration effects.
A breast cancer case-control study by Hansen and Lassen reported similar interaction patterns between shift work and chronotype: Early chronotypes had an elevated risk for breast cancer if duration and frequency of night shift work was relatively high. Although the study had limited sample sizes, it recorded working times with relatively high precision. In the NHS2, shift work information is continuously assessed through follow-up but with only very limited information about the number of shifts worked per month; hence, more detailed working time assessments are essential in future studies. Such studies should also address the currently largely neglected effects of early morning shifts, which have also been associated with disturbed sleep and increased fatigue; albeit, most studies have focused on the more strenuous night shifts.
Women in the current study who were late chronotypes and without any history of rotating night shift work had a 1.5-fold increased risk of type 2 diabetes; this finding is novel and warrants confirmation. One potential explanation could be that working no night shifts may be indicative of exposure to early morning shifts, which have been shown to be the most strenuous for late chronotypes. Of note, the type 2 diabetes risk of late chronotypes was decreased if their work schedule involved night shifts compared with late chronotypes without night shift work. Because late chronotypes tend to fall asleep later than early types, even on work-free days, it appears plausible that working night shifts is more in line with their circadian phase than for early chronotypes. In a recent analysis, we showed that chronotype-adapted shift schedules (i.e., removing late chronotypes from morning shifts and early chronotypes from night shifts) can improve quality and quantity of workday sleep. In early chronotypes, the data qualitatively suggest an inverse association between daytime-oriented work schedules, which interfered less with the sleep/wake cycle, and longer exposure to rotating night shift work, which showed a consistent, albeit nonsignificant, risk elevation. This observation is in line with the hypothesis that night shift work is especially strenuous for early chronotypes. The results also suggest a different temporal relationship among shift work, sleep, and circadian misalignment and type 2 diabetes etiology in early versus late chronotypes. Overall, the pattern we observed supports the hypothesis that chronotype may also be an important modifier for the association between work schedules and type 2 diabetes risk.
Impaired glucose tolerance, insulin resistance, and elevated levels of oxidative stress and inflammation are among the hypothesized links among shift work, the circadian system, and type 2 diabetes risk. Shift work has been associated with metabolic disturbances, such as high triglyceride and low HDL cholesterol levels, and even though only few prospective studies exist, they have consistently linked shift work to an increased risk of type 2 diabetes. The current findings add to this growing body of literature by suggesting that the effects of shift work on type 2 diabetes risk vary depending on an individual's chronotype.
Diet may be another important explanation for why late chronotypes could have an elevated risk for type 2 diabetes. Late chronotypes appear to have more unhealthy dietary habits, and Reutrakul et al. showed that poor glycemic control is partly related to higher caloric intake. However, it seems unlikely that diet quality in late chronotypes is solely responsible for the elevated risk of type 2 diabetes among non–night shift workers in the current study given that adjustment for diet quality using the AHEI, a score shown to reliably measure relevant dietary information in the context of chronic disease epidemiology, did not alter the estimates. Another facet of diet that has not been addressed in observational studies is the timing of food intake. Animal studies that varied diet quality and feeding and fasting times showed that the effects of poor diet on body weight and metabolism can be overridden by appropriate timing of feeding and fasting periods. Shift work not only induces light exposure and activity but also food intake at potentially all times of day, which may add to the strain associated with shift work.
This study has several strengths, including its large size (crucial for any examination of interactions by stratification) and that we were able to adjust for a wide variety of key health and lifestyle factors, which were potential confounders of the associations of interest. Furthermore, even though our definition of shift work was not detailed, it was continuously assessed since 1989, resulting in a powerful duration of exposure assessment. However, the intensity of exposure cannot be inferred from the continuous data collection in NHS2. In addition, no information on early morning and evening shifts has been gathered. Early morning shifts can induce circadian misalignment and sleep deprivation, especially in late chronotypes. Recommendations of an International Agency for Research on Cancer working group on quantifying shift work exposure stress the importance of assessing both intensity (number and timing of shifts) and duration of exposure. Further studies are needed to disentangle the respective contributions of intensity and duration of exposure to chronic disease epidemiology.
Another limitation of the current study is that chronotype was only assessed once. However, even though chronotype appears to change with age, existing evidence suggests that once adulthood is reached, changes occur at a very slow pace. Hence, it seems unlikely that noteworthy chronotype changes would have occurred within 6 years in this middle-aged cohort of women, which is why we deliberately chose this time frame. If changes had occurred during this time frame, and assuming that with age adult individuals tend to become earlier chronotypes, we anticipate this to have caused a nondifferential chronotype misclassification and therefore likely to have biased the results toward the null. Additionally, we cannot exclude the possibility that type 2 diabetes influences chronotype, but this possibility seems less likely given the similar patterns in both the incidence and the prevalence analyses. Nonetheless, how metabolic disorders may affect circadian phenotypes remains an open question and deserves further investigation.
Although we adjusted for antidepressant medication use, we had no information on potential antipsychotic medication use, another known risk factor for type 2 diabetes. Finally, we were unable to account for the role of sleep quality in this study, another consistent predictor of type 2 diabetes that may be especially important because it has been shown that chronotype modulates both quantity and quality of sleep in shift workers. Future prospective studies with repeated chronotype and objective sleep assessments (i.e., quality, timing, quantity) as well as longer durations of follow-up are needed to address these issues.
In conclusion, the results suggest that if work times interfere with sleep timing, shift and day workers may be at an increased risk for type 2 diabetes. More detailed working time assessments will allow for a better understanding of the interaction between chronotype and work schedules. Together with systematic sleep and chronotype assessments, they may provide a powerful approach to individualized risk assessments in shift workers and ultimately minimize adverse health effects.
Conclusions
The findings add to the growing body of evidence suggesting a chronotype-dependent association between work hours and metabolic disease risk among women. To our knowledge, this is the first large cohort study to explicitly probe the hypothesis of circadian misalignment by examining the interaction between chronotype and shift work. We consistently observed in women a significant interaction between chronotype and shift work, suggesting a slightly lower risk of type 2 diabetes among early chronotypes compared with intermediate chronotypes, which appeared to increase with increasing duration of rotating night shift work (no rotating night shift work: MVOR 0.81; <10 years: 0.84; ≥10 years: 1.15). This finding is a possible result of early sleep and wake times, leading to more circadian misalignment during night shifts. By contrast, late chronotypes experienced a significant increase in type 2 diabetes risk when their shift schedule did not involve night work, whereas this association was not observed if they worked any number of years of night shifts independent of the duration of exposure (no rotating night shift work: MVOR 1.51; <10 years: 0.93; ≥10 years: 0.86).
In line with the current findings, a previous cross-sectional analysis reported an up to two- to fivefold increased risk of type 2 diabetes among late compared with early chronotypes. However, covariate adjustment in that study was limited because no information on other important confounders such as diet, physical activity, or family history of diabetes was available.
Building on a large body of literature on shift work tolerance and interindividual differences and more recent findings on the links among the circadian system, sleep, and metabolism, it is believed that in addition to sleep deprivation, circadian misalignment contributes to disease etiology. Thus, chronotype (a measure of internal biological time, which is most readily described through sleep timing) alone may not fully capture associations with disease that are driven by circadian misalignment. Rather, the interaction between chronotype and working times likely represents a better measure of a person's actual level of circadian misalignment. To explicitly address this hypothesis, we made use of the regularly updated shift work information in the NHS2, where from 1989 onward, women indicated how many months in the past 2-year period they worked three or more night shifts per month. The findings support this hypothesis: Early chronotypes had a reduced type 2 diabetes risk when not exposed to night shift work, which tended to increase if they worked longer durations of night shift work. Future studies with more detailed information on number of night shifts worked per month in addition to years of night work may be able to further disentangle possible intensity and duration effects.
A breast cancer case-control study by Hansen and Lassen reported similar interaction patterns between shift work and chronotype: Early chronotypes had an elevated risk for breast cancer if duration and frequency of night shift work was relatively high. Although the study had limited sample sizes, it recorded working times with relatively high precision. In the NHS2, shift work information is continuously assessed through follow-up but with only very limited information about the number of shifts worked per month; hence, more detailed working time assessments are essential in future studies. Such studies should also address the currently largely neglected effects of early morning shifts, which have also been associated with disturbed sleep and increased fatigue; albeit, most studies have focused on the more strenuous night shifts.
Women in the current study who were late chronotypes and without any history of rotating night shift work had a 1.5-fold increased risk of type 2 diabetes; this finding is novel and warrants confirmation. One potential explanation could be that working no night shifts may be indicative of exposure to early morning shifts, which have been shown to be the most strenuous for late chronotypes. Of note, the type 2 diabetes risk of late chronotypes was decreased if their work schedule involved night shifts compared with late chronotypes without night shift work. Because late chronotypes tend to fall asleep later than early types, even on work-free days, it appears plausible that working night shifts is more in line with their circadian phase than for early chronotypes. In a recent analysis, we showed that chronotype-adapted shift schedules (i.e., removing late chronotypes from morning shifts and early chronotypes from night shifts) can improve quality and quantity of workday sleep. In early chronotypes, the data qualitatively suggest an inverse association between daytime-oriented work schedules, which interfered less with the sleep/wake cycle, and longer exposure to rotating night shift work, which showed a consistent, albeit nonsignificant, risk elevation. This observation is in line with the hypothesis that night shift work is especially strenuous for early chronotypes. The results also suggest a different temporal relationship among shift work, sleep, and circadian misalignment and type 2 diabetes etiology in early versus late chronotypes. Overall, the pattern we observed supports the hypothesis that chronotype may also be an important modifier for the association between work schedules and type 2 diabetes risk.
Impaired glucose tolerance, insulin resistance, and elevated levels of oxidative stress and inflammation are among the hypothesized links among shift work, the circadian system, and type 2 diabetes risk. Shift work has been associated with metabolic disturbances, such as high triglyceride and low HDL cholesterol levels, and even though only few prospective studies exist, they have consistently linked shift work to an increased risk of type 2 diabetes. The current findings add to this growing body of literature by suggesting that the effects of shift work on type 2 diabetes risk vary depending on an individual's chronotype.
Diet may be another important explanation for why late chronotypes could have an elevated risk for type 2 diabetes. Late chronotypes appear to have more unhealthy dietary habits, and Reutrakul et al. showed that poor glycemic control is partly related to higher caloric intake. However, it seems unlikely that diet quality in late chronotypes is solely responsible for the elevated risk of type 2 diabetes among non–night shift workers in the current study given that adjustment for diet quality using the AHEI, a score shown to reliably measure relevant dietary information in the context of chronic disease epidemiology, did not alter the estimates. Another facet of diet that has not been addressed in observational studies is the timing of food intake. Animal studies that varied diet quality and feeding and fasting times showed that the effects of poor diet on body weight and metabolism can be overridden by appropriate timing of feeding and fasting periods. Shift work not only induces light exposure and activity but also food intake at potentially all times of day, which may add to the strain associated with shift work.
This study has several strengths, including its large size (crucial for any examination of interactions by stratification) and that we were able to adjust for a wide variety of key health and lifestyle factors, which were potential confounders of the associations of interest. Furthermore, even though our definition of shift work was not detailed, it was continuously assessed since 1989, resulting in a powerful duration of exposure assessment. However, the intensity of exposure cannot be inferred from the continuous data collection in NHS2. In addition, no information on early morning and evening shifts has been gathered. Early morning shifts can induce circadian misalignment and sleep deprivation, especially in late chronotypes. Recommendations of an International Agency for Research on Cancer working group on quantifying shift work exposure stress the importance of assessing both intensity (number and timing of shifts) and duration of exposure. Further studies are needed to disentangle the respective contributions of intensity and duration of exposure to chronic disease epidemiology.
Another limitation of the current study is that chronotype was only assessed once. However, even though chronotype appears to change with age, existing evidence suggests that once adulthood is reached, changes occur at a very slow pace. Hence, it seems unlikely that noteworthy chronotype changes would have occurred within 6 years in this middle-aged cohort of women, which is why we deliberately chose this time frame. If changes had occurred during this time frame, and assuming that with age adult individuals tend to become earlier chronotypes, we anticipate this to have caused a nondifferential chronotype misclassification and therefore likely to have biased the results toward the null. Additionally, we cannot exclude the possibility that type 2 diabetes influences chronotype, but this possibility seems less likely given the similar patterns in both the incidence and the prevalence analyses. Nonetheless, how metabolic disorders may affect circadian phenotypes remains an open question and deserves further investigation.
Although we adjusted for antidepressant medication use, we had no information on potential antipsychotic medication use, another known risk factor for type 2 diabetes. Finally, we were unable to account for the role of sleep quality in this study, another consistent predictor of type 2 diabetes that may be especially important because it has been shown that chronotype modulates both quantity and quality of sleep in shift workers. Future prospective studies with repeated chronotype and objective sleep assessments (i.e., quality, timing, quantity) as well as longer durations of follow-up are needed to address these issues.
In conclusion, the results suggest that if work times interfere with sleep timing, shift and day workers may be at an increased risk for type 2 diabetes. More detailed working time assessments will allow for a better understanding of the interaction between chronotype and work schedules. Together with systematic sleep and chronotype assessments, they may provide a powerful approach to individualized risk assessments in shift workers and ultimately minimize adverse health effects.
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