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the other hand, if the insulin algorithm was less aggressive there would have been less opportunity for glucagon action; the value of glucagon is at least partly dependent on the insulin algorithm. The true incremental value of glucagon will be shown in the unrestricted outpatient setting where the control system must cope with a greater variety and intensity of challenges to glucose stability. A challenge for glucagon use is the availability of a stable formulation approved for chronic use in a pump. Studies such as Haidar and colleagues’ will encourage the pharmaceutical industry to build on progress already made towards availability of stable, pumpable glucagon.10 The exploration of multiple strategies for automated glycaemic control, including those that use insulin alone or both insulin and glucagon, will lead to more and better options for patients with type 1 diabetes. Haidar and colleagues should be congratulated for taking the fork and advancing our understanding of the role of glucagon in this endeavor.
board membership with Tandem Diabetes; received support for an investigator-initiated study from Abbott Diabetes Care; received technical advice and loaned equipment from Dexcom, Tandem Diabetes, SweetSpot Diabetes, International Biomedical, Abbott Diabetes Care, Insulet Corporation, and Medtronic. 1
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Steven J Russell Massachusetts General Hospital, Boston, MA 02114, USA
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I have a patent pending on aspects of a distinct dual-hormone bionic pancreas; received honoraria or travel expenses for lectures from Tandem Diabetes, Sanofi Aventis, Eli Lilly, and Dexcom; consulted for Medtronic; a scientific advisory
Beck RW, Tamborlane WV, Bergenstal RM, Miller KM, DuBose SN, Hall CA. The T1D exchange clinic registry. J Clin Endocrinol Metab 2012; 97: 4383–89. Peyser T, Dassau D, Breton M, Skyler JS. The artificial pancreas: current status and future prospects in the management of diabetes. Ann NY Acad Sci 2014; 1311: 102–23. Haidar A, Duval C, Legault L, Rabasa-Lhoret R. Pharmacokinetics of insulin aspart and glucagon in type 1 diabetes during closed-loop operation. J Diabetes Sci Technol 2013; 7: 1507–12. El-Khatib FH, Russell SJ, Nathan DM, Sutherlin RG, Damiano ER. A bi-hormonal closed-loop blood glucose control device for type 1 diabetes. Sci Transl Med 2010; 2: 27ra27. Cryer PE. Minireview: Glucagon in the pathogenesis of hypoglycemia and hyperglycemia in diabetes. Endocrinology 2012; 153: 1039–48. Engle JM, El Youssef J, Massoud RG, Yuen KC, Kagan R, Ward WK. Novel use of glucagon in a closed-loop system for prevention of hypoglycemia in type 1 diabetes. Castle JR. Diabetes Care 2010; 33: 1282–87. Haidar A, Legault L, Dallaire M, et al. Glucose-responsive insulin and glucagon delivery (dual-hormone artificial pancreas) in adults with type 1 diabetes: a randomized crossover controlled trial. CMAJ 2013; 185: 297–305. Russell SJ, El-Khatib FH, Sinha M, et al. Outpatient glycemic control with a bionic pancreas in type 1 diabetes. New Engl J Med 2014; 371: 313–25. Haidar A, Legault L, Messier V, Mitre TM, Leroux C, Rabasa-Lhoret R. Comparison of dual-hormone artificial pancreas, single-hormone artificial pancreas, and conventional insulin pump therapy for glycaemic control in patients with type 1 diabetes: an open-label randomised controlled crossover trial. Lancet Diabetes Endocrinol 2014; published online Nov 27. http://dx.doi.org/10.1016/S2213-8587(14)70226-8. Cersosima E, Cummins MJ, Kinzell JH, et al. A phase 2 comparative safety PK/PD study of stable nonaqueous glucagon (G-Pen) vs. Lilly glucagon for treatment of severe hypo-glycemia. Diabetes 2014; 63 (suppl 1A): 1–LB.
There are complex interconnections of variables such as work hours, occupation type, and socioeconomic status with physiology that can affect the risk of diabetes. Results of investigations into associations between long working hours and incident type 2 diabetes have been inconsistent. In The Lancet Diabetes & Endocrinology, Mika Kivimäki and colleagues combine published and unpublished data in a meta-analysis (n=222 120) to show that working long hours is associated with increased risk of incident diabetes in people with low socioeconomic status.1 Their study design and methods have several advantages: large sample size, consistent exposure definition, control for health behaviours and other potential confounders, and analysis to test for bias due to the method used to determine diabetes incidence. Importantly, the investigators enable clear comparisons with previous reports by presenting serially adjusted analyses largely replicating previous findings. www.thelancet.com/diabetes-endocrinology Vol 3 January 2015
However, the investigators’ discussions of residual confounders focused primarily on the possibility that confounding might explain the higher diabetes risk in the low socioeconomic groups; whereas, residual confounding by protective factors could lead to an underestimation of the effect of the exposure in the workers in the high socioeconomic status group. Workers in this group have additional capital, social, or other resources at their disposal that might mitigate the effects of long working hours. For example, they are able to contract out activities such as child care and household chores, thereby buying more weekly hours. Unresolved issues of measurement and residual confounding make us guarded about the study’s conclusions, especially the assertion that the lack of an association in workers in the high socioeconomic status group negates the possibility that working long hours per se is toxic. In occupational health studies, work hours
Colin Hawkins/Science Photo Library
Long working hours can be toxic
Published Online September 25, 2014 http://dx.doi.org/10.1016/ S2213-8587(14)70201-3 See Articles page 27
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are an essential component of exposure assessments. Fundamentally, the acuity of the work exposure above and beyond the duration of habitual paid work hours (eg, intensity of physical or mental work, schedule flexibility, and commute burden) is often not measured in epidemiological studies.2 Unmeasured differences in how workers of different socioeconomic groupings achieve total weekly hours might affect the risk of diabetes. Reviews with national samples show that workers in the high socioeconomic status group have greater schedule control, meaning that they are able to spread their hours throughout the week.3 Meanwhile, workers in lower socioeconomic status groups might achieve the same number of hours by working overtime,3 a form of long working hours in hourly paid employees and with potential health consequences. For example, injury rates associated with working overtime (61%) are higher than for working 12 h a day (37%) or 60 h a week (23%).4 Longer daily schedules or schedules that are disruptive, such as early morning arrival, late night departure, and non-continuous hours might involve far less control in workers in the low socioeconomic status group, and involve disruptions of circadian rhythms or sleep and other health behaviors. Kivimaki and colleagues’ finding of an association only in the low socioeconomic status group suggests a possible role of sleep as a mediator; both inadequate sleep quality and quantity are strongly predictive of incident type 2 diabetes.5 A recent study showed that the association between short sleep duration and diabetes can be partly attenuated by inclusion of socioeconomic status.6 Working more consistent and less disruptive hours might explain the lack of associations for the individuals in the high socioeconomic status group. A related idea is the role of social jet lag—long working hours and short sleep during the weekdays combined with delayed sleep times on the weekend—that disrupts the circadian timing system and adversely affects metabolism.7 Laboratory studies have identified mechanisms by which disruption of the circadian system increases the risk of diabetes.8 Night work, a cause of circadian disruption, is also associated with higher risks of type 2 diabetes. In a prospective 5-year follow-up of workers with prediabetes, night workers had a five times greater rate of conversion to frank diabetes. Of note, stress and an administrative role were associated with a greater risk of diabetes, whereas being an office worker 4
and non-smoker, among other factors, were protective in the same sample.9 Kivimäki and colleagues’ elegantly designed study provides a solid foundation for both epidemiological and intervention work on diabetes risks. The results remained robust even after controlling for obesity and physical activity, which are often the focus of diabetes risk prevention, suggesting that work factors affecting health behaviours and stress might need to be addressed as part of diabetes prevention. *Orfeu M Buxton, Cassandra A Okechukwu Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA (OMB); Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA (OMB); Department of Social and Behavioral Sciences, Harvard School of Public Health, Kresge Building, Boston, MA, USA (OMB, CAO); and Department of Biobehavioral Health, Pennsylvania State University, 219 Biobehavioral Health Bldg, University Park, PA 16802, USA (OMB)
[email protected] OMB reports grants from Sepracor (now Sunovion) and Cephalon (now Teva); personal fees from Takeda Pharmaceuticals North America, Dinsmore, Matsutani America, Wake Forest University Medical Center, American Academy of Craniofacial Pain, National Institute of Heart, Lung and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases, National Postdoctoral Association, Oklahoma State University, Oregon Health Sciences University, SUNY Downstate Medical Center, American Diabetes Association, and New York University outside of the submitted work. CAO declares no competing interests. Support was provided by grants from the National Institutes of Health (R01HL107240, OMB) and National Institute for Occupational Safety and Health and Centers for Disease Control and Prevention (U19OH008861, CAO). Copyright © Buxton et al. Open Access article distributed under the terms of CC BY-NC-SA. 1
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Kivimäki M, Virtanen M, Kawachi I, et al. Long working hours, socioeconomic status, and the risk of incident type 2 diabetes: a meta-analysis of published and unpublished data from 222 120 individuals. Lancet Diabetes Endocrinol 2014; published online Sept 25. http://dx.doi.org/10.1016/S2213-8587(14)70178-0. Jahoda M. Employment and unemployment: a social-psychological analysis. Volume 1: CUP Archive; 1982. Lyness KS, Gornick JC, Stone P, Grotto AR. It’s all about control worker control over schedule and hours in cross-national context. Am Sociol Rev 2012; 77: 1023–49. Dembe AE, Erickson JB, Delbos RG, Banks SM. The impact of overtime and long work hours on occupational injuries and illnesses: new evidence from the United States. Occup Environ Med 2005; 62: 588–97. Cappuccio FP, D’Elia L, Strazzullo P, Miller MA. Quantity and quality of sleep and incidence of type 2 diabetes: a systematic review and meta-analysis. Diabetes Care 2010; 33: 414–20. Jackson CL, Redline S, Kawachi I, Hu FB. Association between sleep duration and diabetes in black and white adults. Diabetes Care 2013; 36: 3557–65. Roenneberg T, Kantermann T, Juda M, Vetter C, Allebrandt KV. Light and the human circadian clock. Handb Exp Pharmacol 2013; 217: 311–31. Buxton OM, Cain SW, O’Connor SP, et al. Adverse metabolic consequences in humans of prolonged sleep restriction combined with circadian disruption. Sci Transl Med 2012; 4: 129ra43. Toshihiro M, Saito K, Takikawa S, Takebe N, Onoda T, Satoh J. Psychosocial factors are independent risk factors for the development of type 2 diabetes in Japanese workers with impaired fasting glucose and/or impaired glucose tolerance. Diabet Med 2008; 25: 1211–17.
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