Survival Among Patients With Pancreatic Cancer and Long-Standing or Recent-Onset Diabetes Mellitus


Abstract

Purpose Long-standing diabetes is a risk factor for pancreatic cancer, and recent-onset diabetes in the several years before diagnosis is a consequence of subclinical pancreatic malignancy. However, the impact of diabetes on survival is largely unknown.

Patients and Methods We analyzed survival by diabetes status among 1,006 patients diagnosed from 1986 to 2010 from two prospective cohort studies: the Nurses’ Health Study (NHS) and Health Professionals Follow-Up Study (HPFS). We validated our results among 386 patients diagnosed from 2004 to 2013 from a clinic-based case series at Dana-Farber Cancer Institute (DFCI). We estimated hazard ratios (HRs) for death using Cox proportional hazards models, with adjustment for age, sex, race/ethnicity, smoking, diagnosis year, and cancer stage.

Results In NHS and HPFS, HR for death was 1.40 (95% CI, 1.15 to 1.69) for patients with long-term diabetes (> 4 years) compared with those without diabetes (P< .001), with median survival times of 3 months for long-term diabetics and 5 months for nondiabetics. Adjustment for a propensity score to reduce confounding by comorbidities did not change the results. Among DFCI patient cases, HR for death was 1.53 (95% CI, 1.07 to 2.20) for those with long-term diabetes compared with those without diabetes (P = .02), with median survival times of 9 months for long-term diabetics and 13 months for nondiabetics. Compared with nondiabetics, survival times were shorter for long-term diabetics who used oral hypoglycemics or insulin. We observed no statistically significant association of recent-onset diabetes (< 4 years) with survival.

Conclusion Long-standing diabetes was associated with statistically significantly decreased survival among patients with pancreatic cancer enrolled onto three longitudinal studies.

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Healthy Diet, Healthy Aging.


Middle-aged women following a healthy Mediterranean-type diet — with an emphasis on fruits, vegetables, whole grains and fish, moderate amounts of alcohol, and little red meat — have much greater odds of healthy aging later on, a new study reports.

“In this study, women with healthier dietary patterns at midlife were 40% more likely to survive to age 70 or over free of major chronic diseases and with no impairment in physical function, cognition or mental health,” said lead study author, Cécilia Samieri, PhD, Institut pour la Santé Publique et le Developpement, Université Bordeaux, France.

This new study adds to growing research on the health benefits of the Mediterranean diet recently reported. Various studies have shown that this diet may contribute to reduced fasting glucose concentrations and lipid levels in those at risk for diabetes, may lower the risk for cardiovascular events and stroke, and improve cognition.

The new study was published in the November 5 issue of Annals of Internal Medicine.

The analysis included 10,670 participants in the Nurses’ Health Study, which began in 1976 when female nurses aged 30 to 55 years completed a mail-in survey. Since then, study participants have been closely followed on a regular basis.

In 1980, participants completed a food-frequency questionnaire (FFQ) that asked how often on average they consumed standard portions of various foods. This questionnaire was repeated in 1984 and 1986 and then every 4 years.

To assess dietary quality at midlife, researchers averaged information from the 1984 and 1986 FFQs. They calculated scores on 2 diet indexes:

  • Alternative Healthy Eating Index-2010 (AHEI-2010): This index considers greater intake of vegetables, fruits, whole grains, nuts, legumes, and polyunsaturated fatty acids (PUFAs); lower intake of sugar-sweetened beverages, red or processed meats, trans fats, and sodium; and moderate intake of alcoholic beverages. Total AHEI-2010 scores range from 0 (nonadherence) to 110 (perfect adherence).

  • Alternate Mediterranean diet (A-MeDi): Developed to assess adherence to the traditional Mediterranean diet, this index includes 9 components that are similar to those in the AHEI-2010. Total A-MeDi scores range from 0 (nonadherence) to 9 (perfect adherence).

In 1992, 1996, and 2000, participants completed the Medical Outcomes Short-Form 36 Health Survey, a questionnaire that evaluates 8 health concepts, including mental health and physical functioning. Scores from the Telephone Interview for Cognitive Status, an adaptation of the Mini-Mental State Examination, were used to evaluate cognitive health. From 1995 to 2001, a cognitive study was administered to participants aged 70 years or older.

Investigators separated “healthy” from “usual” aging on the basis of 4 health domains. Overall, 11.0% of the participants were considered healthy (and so were free of chronic diseases, such as cancers, myocardial infarction, and diabetes, and with no limitation in cognitive function, mental health, and physical function), and the remaining participants were considered usual agers.

Several health domains were typically impaired among the “usual” agers, said Dr. Samieri. “For example, 33% had both chronic diseases and limitations in cognitive, physical, or mental health; 64% had only limitations in cognitive, physical, or mental health; and 3.4% had only 1 or more chronic diseases.”

The analysis revealed that greater adherence at midlife to AHEI-2010 and A-MeDi was strongly associated with greater odds of healthy aging (P for trend < .001 for AHEI-2010; P for trend = .002 for A-Medi).

For example, compared with women in the worst quintile of diet scores, women in the highest quintile of the AHEI-2010 and A-MeDi scores had 34% (95% confidence interval [CI], 9% – 66%) and 46% (95% CI, 17% – 83%) greater odds of healthy aging, respectively.

Individual Components

When they analyzed individual dietary components, researchers found statistically significant associations of greater intake of fruits (odds ratio [OR] for upper versus lower quintiles, 1.46) and alcohol (OR, 1.28), and lower intakes of sweetened beverages (OR, 1.28) and PUFAs (OR, 1.38) with healthy aging (P for trend ≤ .04).

The authors noted that they could not exclude participants with impaired cognition, mental health, and physical function in midlife, and although probably few women had severe impairments at baseline, reverse causation in these participants may still be possible. Because they didn’t follow participants through to death or onset of a condition that would classify them as no longer healthy, researchers couldn’t prospectively estimate risks for transitioning from healthy to usual aging. As well, measurement errors may have occurred in the assessment of dietary patterns.

Other possible limitations were that the study was observational and, because it included mostly white women, its results may not be generalizable to other populations.

Middle age is probably the most relevant period of exposure for preventing chronic conditions of aging that develop over many years.

“It’s largely accepted that cumulative exposures to environmental risk factors over the lifespan are probably more important than late-life exposures to determine health in older ages,” said Dr. Samieri. “Several mechanisms of age-related chronic diseases, for example, atherosclerosis in cardiac diseases, brain lesions in dementia, start in midlife.”

Various researchers have reported on other newly documented health benefits of the Mediterranean diet, including the following:

Colonoscopies Could Prevent 40% of Colorectal Cancers.


Katie Couric was right about colonoscopies. They aren’t fun, but they lower cancer risk and save lives.

After the popular talk-show host underwent a colonoscopy on live TV to raise awareness about the disease that claimed her husband’s life, more Americans underwent the uncomfortable procedure to screen for colorectal tumors. But studies raised questions about how effective the process was in reducing incidence of disease and lowering deaths from the cancer, particular for people with growths in the upper intestines that are generally less accessible by the colonoscopy scope.

But according to the latest results from a Harvard School of Public Health (HSPH) study, 40% of colorectal cancers might be prevented if more people get regular colonoscopy screening, which existing guidelines recommend for those over 50, every 10 years.

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In the study, which appears in the New England Journal of Medicine, researchers looked at data from close to 89,000 participants who were a part of either the Nurses’ Health Study or the Health Professionals Follow-up Study, both long-term trials that followed men and women over several decades and recorded a number of health measures. The participants filled out data about their colon cancer screenings with either colonoscopy or sigmoidoscopy, which screens for lesions only in the lower part of the colon, every two years from 1988 to 2008. Overall, there were 1,815 cases of colorectal cancer and 474 deaths.

Those getting either procedure had a lower risk of developing cancer or dying from it compared to those were weren’t screened, but only people who had colonoscopies also benefited from fewer cancers in the upper part of the colon, which sigmoidoscopies generally can’t reach. If all of the participants had been screened, the study authors say, they would have developed 40% fewer colon cancers.

The findings are reassuring, since, as TIME reported last year, experts have been debating which type of screening procedure is more accurate and predictive.

 “Each year, more than 1.2 million people are diagnosed with colorectal cancer worldwide. Our findings could help improve and strengthen the current guidelines for colorectal cancer screening,” said lead study author Reiko Nishihara, a research fellow in the Department of Nutrition at HSPH in a statement.

Earlier studies have documented that colonoscopies can reduce the number of colon cancers, but only recently have studies confirmed that the screening, which also involves removal of suspicious growths or tumors, can actually save lives. Now the data supporting the life-saving benefits of colonoscopy looks even stronger.


Source:
http://healthland.time.com

Fruit consumption and risk of type 2 diabetes: results from three prospective longitudinal cohort studies.


Abstract

Objective To determine whether individual fruits are differentially associated with risk of type 2 diabetes.

Design Prospective longitudinal cohort study.

Setting Health professionals in the United States.

Participants 66 105 women from the Nurses’ Health Study (1984-2008), 85 104 women from the Nurses’ Health Study II (1991-2009), and 36 173 men from the Health Professionals Follow-up Study (1986-2008) who were free of major chronic diseases at baseline in these studies.

Main outcome measure Incident cases of type 2 diabetes, identified through self report and confirmed by supplementary questionnaires.

Results During 3 464 641 person years of follow-up, 12 198 participants developed type 2 diabetes. After adjustment for personal, lifestyle, and dietary risk factors of diabetes, the pooled hazard ratio of type 2 diabetes for every three servings/week of total whole fruit consumption was 0.98 (95% confidence interval 0.96 to 0.99). With mutual adjustment of individual fruits, the pooled hazard ratios of type 2 diabetes for every three servings/week were 0.74 (0.66 to 0.83) for blueberries, 0.88 (0.83 to 0.93) for grapes and raisins, 0.89 (0.79 to 1.01) for prunes, 0.93 (0.90 to 0.96) for apples and pears, 0.95 (0.91 to 0.98) for bananas, 0.95 (0.91 to 0.99) for grapefruit, 0.97 (0.92 to 1.02) for peaches, plums, and apricots, 0.99 (0.95 to 1.03) for oranges, 1.03 (0.96 to 1.10) for strawberries, and 1.10 (1.02 to 1.18) for cantaloupe. The pooled hazard ratio for the same increment in fruit juice consumption was 1.08 (1.05 to 1.11). The associations with risk of type 2 diabetes differed significantly among individual fruits (P<0.001 in all cohorts).

Conclusion Our findings suggest the presence of heterogeneity in the associations between individual fruit consumption and risk of type 2 diabetes. Greater consumption of specific whole fruits, particularly blueberries, grapes, and apples, is significantly associated with a lower risk of type 2 diabetes, whereas greater consumption of fruit juice is associated with a higher risk.

Discussion

In three prospective cohorts of US men and women, we found that the associations with risk of type 2 diabetes differed significantly among individual fruits: greater consumption of blueberries, grapes, apples, bananas, and grapefruit were significantly associated with a reduced risk of type 2 diabetes. Most of these associations were quite consistent among three cohorts. Additionally, differences in the glycemic index/glycemic load values of fruits did not account for the association of specific fruits with risk of type 2 diabetes. Moreover, greater fruit juice consumption was associated with an increased risk, and substitution of whole fruits for fruit juice was associated with a lower risk, except for strawberries and cantaloupe.

Results in relation to other studies

In eight previous prospective studies, the association between total fruit consumption and risk of type 2 diabetes was examined,2 3 4 5 6 7 8 9 and the results were mixed. Similar to previous analyses in the Nurses’ Health Study3 and the Finnish Mobile Clinic Health Examination Survey study,2 the current findings supported an inverse association between total fruit consumption and risk of type 2 diabetes, but not in other studies.4 5 6 7 8 9 In contrast to total fruit consumption, evidence on consumption of individual fruits or fruit groups with risk of type 2 diabetes is limited and incomplete. In four prospective studies, consumption of citrus fruit was not associated with a lower risk of type 2 diabetes.5 6 7 8 Apple consumption was inversely associated with risk in the Women’s Health Study29 and in the Finnish study,30 but not in the Iowa Women’s Health Study.31 In addition, greater consumption of berries was associated with a lower risk in the Finnish study,2 but not in the Iowa Women’s Health Study.31 In our previous analyses that focused on anthocyanin rich fruits, intakes of blueberries, strawberries, and apples were associated with a lower risk of type 2 diabetes.32 Consistently, in a clinical trial, increased consumption of berries improved glycemic control among people with diabetes.33 Our current investigation extended the evidence in this regard and found novel, inverse associations for grapes, bananas, and grapefruit.

The different associations of individual fruits with diabetes risk may be due to the heterogeneous composition of these foods. Firstly, blueberries, apples, and red or black grapes contain high levels of anthocyanins.12 In mice with diabetes, bilberry extract rich in anthocyanins can activate adenosine monophosphate-activated protein kinase, enhance glucose uptake and utilization in white adipose tissue and skeletal muscle, and reduce glucose production in the liver.34 Our previous analyses also showed that levels of anthocyanin intake were inversely associated with risk of type 2 diabetes.32 In the current study, further adjustment for anthocyanins did not substantially change the associations for individual fruits, suggesting that the inverse associations of individual fruits are likely due to other constituents of these foods. Both red and white grapes contain high levels of resveratrol in skin.35 In mice, a high fat diet with 0.04% resveratrol increased insulin sensitivity at 24 months compared with the same diet without resveratrol.36 However, randomized controlled trials examining the effects of supplementation of resveratrol on glucose metabolism have generated inconsistent results.37 38 39 Prunes, peaches, plums, apricots, and apples contain chlorogenic acid,40 41 42 43 which may potentially mediate the beneficial effects of coffee consumption on diabetes risk.44 In rats, chlorogenic acid reduces glucose dependent insulinotropic peptide secretion by slowing glucose absorption in the intestine.45Moreover, chlorogenic acid increases muscle glucose uptake in mice with diabetes.46Finally, grapefruits contain high amounts of naringin.12 In rats, naringin inhibits dipeptidyl peptidase 4 similarly to sitagliptin, a dipeptidyl peptidase 4 inhibitor used for the treatment of diabetes.47 Inhibition of dipeptidyl peptidase 4 increases glucagon-like peptide 1, which subsequently leads to improved glucose tolerance.48 In contrast to these specific fruits mentioned above, cantaloupe was associated with an increased risk of type 2 diabetes in the current analysis. Melons have lower levels of phytochemicals than the aforementioned fruits.12 None the less, little evidence exists regarding the effects of melons on glucose metabolism. Although other fruits may also be beneficial for glucose metabolism, significant associations between other specific fruits and risk of type 2 diabetes were not found in the current and previous investigations.5 6 7 8

The glycemic index/glycemic load values of fruits did not seem to be the factor that determined their association with type 2 diabetes in the current study, although in a clinical trial, increased consumption of low glycemic index fruits improved glycemic control among people with diabetes.33 In recent meta-analyses, a higher dietary glycemic index/glycemic load was associated with a greater risk of type 2 diabetes.4950 In the Nurses’ Health Study and Health Professionals Follow-up Study, the associations between dietary glycemic index and risk of type 2 diabetes were positive, although the associations for dietary glycemic load were not significant.51 52 53 None the less, the contribution of total fruit consumption to dietary glycemic load was rather small (about 10%) in these populations. Of individual fruits, the top three contributors to dietary glycemic load were bananas (3-4%), apples (2%), and grapes (1%). In contrast, the relatively high glycemic load values of fruit juices13 along with reduced levels of beneficial nutrients through juicing processes11 12 (for example, the glycemic load values per serving are 6.2 for raw oranges and 13.4 for orange juice, and fibre levels per serving are 3.1 g and 0.5 g, respectively) may explain the positive associations between fruit juice consumption and risk of type 2 diabetes. Moreover, the difference in the viscosity of foods is also an important factor affecting postprandial blood glucose dynamics. Fluids pass through the stomach to the intestine more rapidly than solids even if nutritional content is similar.54 For example, fruit juices lead to more rapid and larger changes in serum levels of glucose and insulin than whole fruits.55 56 Although these mechanisms may potentially explain the diverse associations for individual fruits, further research is apparently needed to confirm our findings on specific fruits in relation to type 2 diabetes and to further elucidate underlying mechanisms.

Strengths and limitations of this study

The present study has several limitations. Firstly, measurement errors were inevitable in the estimates of fruit consumption, especially for individual fruits with lower consumption levels.17 18 Adjustment for energy intake and use of cumulatively averaged intake levels can reduce the magnitude of measurement errors to some extent.26 Generally, random errors in exposure assessments attenuate true associations toward the null. Secondly, the possibility of false positive findings may exist because we examined the associations of multiple fruits in the current investigation without adjusting for multiple comparisons based on a priori hypotheses. Meanwhile, most associations were consistent across three cohorts, and the associations for blueberries, grapes, and apples remained statistically significant even after applying the Bonferroni correction, a conservative method correcting for multiple comparisons. Thirdly, in our food frequency questionnaires, intakes of some individual fruits (apples and pears; peaches, plums, and apricots) were combined because these fruits have similar nutrient profiles. Therefore we could not determine whether the associations for these combined fruits can be ascribed to a specific individual fruit. Fourthly, we cannot exclude the possibility of recall bias in the assessments of diet based on the food frequency questionnaires. However, the prospective study design and exclusion of participants with chronic diseases at baseline should minimize such bias. Fifthly, although in the multivariable analysis we considered a multitude of lifestyle and dietary factors, including other individual fruits, residual or unmeasured confounding may still exist. Finally, our study populations primarily consist of health professionals with European ancestry. Thus our findings may not be generalized to other populations.

Conclusions

Our findings suggest that there is significant heterogeneity in the associations between individual fruits and risk of type 2 diabetes. Greater consumption of specific whole fruits, particularly blueberries, grapes, and apples, was significantly associated with a lower risk of type 2 diabetes, whereas greater fruit juice consumption was associated with a higher risk. The differences in the associations between individual fruits were not accounted for by variation in the glycemic index/glycemic load values of individual fruits. Overall, these results support recommendations on increasing consumption of a variety of whole fruits, especially blueberries, grapes, and apples, as a measure for diabetes prevention.

What is already known on this topic

  • Total fruit consumption is not consistently associated with a lower risk of type 2 diabetes
  • The possible heterogeneity among individual fruits regarding the associations with risk of type 2 diabetes has not been examined
  • The associations with risk of type 2 diabetes are different among individual fruits
  • Greater consumption of specific whole fruits, particularly blueberries, grapes, and apples, is significantly associated with a lower risk of type 2 diabetes, whereas increased consumption of fruit juices has the opposite association
  • In addition, the associations of individual fruits are not determined by their glycemic index or glycemic load values

What this study adds

 

 

Source: BMJ

 

History of Kidney Stones and the Risk of Coronary Heart Disease.


Importance  Kidney stone disease is common and may be associated with an increased risk of coronary heart disease (CHD). Previous studies of the association between kidney stones and CHD have often not controlled for important risk factors, and the results have been inconsistent.

Objective  To examine the association between a history of kidney stones and the risk of CHD in 3 large prospective cohorts.

Design, Setting, and Participants  A prospective study of 45 748 men and 196 357 women in the United States without a history of CHD at baseline who were participants in the Health Professionals Follow-up Study (HPFS) (45 748 men aged 40-75 years; follow-up from 1986 to 2010), Nurses’ Health Study I (NHS I) (90 235 women aged 30-55 years; follow-up from 1992 to 2010), and Nurses’ Health Study II (NHS II) (106 122 women aged 25-42 years; follow-up from 1991 to 2009). The diagnoses of kidney stones and CHD were updated biennially during follow-up.

Main Outcomes and Measures  Coronary heart disease was defined as fatal or nonfatal myocardial infarction (MI) or coronary revascularization. The outcome was identified by biennial questionnaires and confirmed through review of medical records.

Results  Of a total of 242 105 participants, 19 678 reported a history of kidney stones. After up to 24 years of follow-up in men and 18 years in women, 16 838 incident cases of CHD occurred. After adjusting for potential confounders, among women, those with a reported history of kidney stones had an increased risk of CHD than those without a history of kidney stones in NHS I (incidence rate [IR], 754 vs 514 per 100 000 person-years; multivariable hazard ratio [HR], 1.18 [95% CI, 1.08-1.28]) and NHS II (IR, 144 vs 55 per 100 000 person-years; multivariable HR, 1.48 [95% CI, 1.23-1.78]). There was no significant association in men (IR, 1355 vs 1022 per 100 000 person-years; multivariable HR, 1.06 [95% CI, 0.99-1.13]). Similar results were found when analyzing the individual end points (fatal and nonfatal MI and revascularization).

Conclusions and Relevance  Among the 2 cohorts of women, a history of kidney stones was associated with a modest but statistically significantly increased risk of CHD; there was no significant association in a separate cohort of men. Further research is needed to determine whether the association is sex-specific.

Souirce: JAMA

Prenatal Exposure to Air Pollution Associated with Autism.


Prenatal exposure to air pollution is associated with increased risk for autism spectrum disorders in childhood, according to a case-control study in Environmental Health Perspectives.

Using data from the Nurses’ Health Study II, researchers matched 325 children with autism to 22,000 control children without autism. Contemporary EPA-modeled air pollution concentrations were identified for the children’s addresses at birth.

After adjustment for socioeconomic status and other potential confounders, the highest quintile of exposures to diesel, lead, manganese, mercury, methylene chloride, and overall metals was associated with increased risk for autism spectrum disorders, compared with the lowest quintile (odds ratios, 1.5 to 2.0). The associations were stronger among boys than girls, but that may be related to the low number of girls with autism in the study, the authors note.

They conclude that the results “strongly support previous evidence of associations” between air pollution and autism spectrum disorders.

Source: Environmental Health Perspectives 

Interlinks between sleep and metabolism.


sleep

Lack of sleep is increasingly associated with weight gain and metabolic problems. Interfaces between the pathways that regulate circadian timing and metabolism might underlie these adverse health effects. Jill Jouret reports.

Getting a good night’s sleep is a basic, but often eluded, prescription for good health. Modern lifestyles provide opportunities for 24 h activity, and minimising sleep is often thought to be a harmless, efficient, or merely necessary means to accommodate schedules. However, feeling tired at night is more than an instruction to rest. Behaviour and physiology are intricately linked to light and dark cycles, and an internal timing mechanism has evolved to ensure that physiological processes occur at optimum times in a 24 h cycle. Maintaining the synchrony of this endogenous circadian clock seems to have wide-ranging health implications.

Although the mechanisms are not fully clear, evidence is mounting that insufficient sleep and disruption in circadian rhythms contribute to pathogenesis of metabolic disorders, cardiovascular disease, and cancer. Worldwide, metabolic syndrome is on the rise, as is the introduction of artificial light and activity into night-time hours. Epidemiological and clinical studies have shown that short-duration and poor-quality sleep predict development of type 2 diabetes and obesity, suggesting that sleep, circadian rhythms, and metabolic systems are interconnected.

In mammals, circadian rhythms are generated centrally by the suprachiasmatic nuclei in the anterior hypothalamus. Light perception by the retina synchronises these single-celled oscillators, generating rhythmic outputs that regulate sleep and wakefulness, feeding and energy expenditure, and glucose homoeostasis. This central clock also sends signals via direct innervation and humoral factors to clock components in peripheral tissues, thus maintaining the circadian timing of an array of physiological processes. Transcription—translation feedback loops implicating specific clock genes lead to a roughly 24 h cycle.

Molecular links between circadian and metabolic pathways have been identified and many hormones implicated in metabolism and energy balance exhibit circadian oscillation—eg, expression and secretion of leptin, a hormone that signals satiety, peaks at night. The complex signalling systems that govern glucose homoeostasis and metabolism of fatty acids, cholesterol, bile acids, and toxins receive inputs from the local and central circadian clocks, allowing cells to anticipate metabolic reactions in a 24 h period. In-vitro studies show that metabolic cues can be transmitted to core components of the circadian clock. Such crosstalk suggests a mechanism by which eating (and possibly sleeping) patterns could shift innate circadian timing.

study published in March, 2013, by a group at the University of Surrey (Guildford, UK) highlighted the interconnection between sleep, circadian rhythmicity, and metabolism. Whole-blood RNA samples were taken from participants after a week of restricted nightly sleep (5·7 h) and also after a week of adequate sleep (8·5 h). Transcriptome analysis showed that 711 genes were upregulated or downregulated by insufficient sleep, including genes associated with circadian rhythms and metabolism.

Sleep restriction also reduced the total number of genes with circadian expression profiles, implying that even a week of poor sleep can disrupt the body’s intricate physiological timing.

Melatonin, a key regulator of sleep, could be an important link connecting circadian timing and insulin signalling. Melatonin production is suppressed by light, and peaks around 3—5 h after sleep onset; it regulates the sleep—wake cycle by lowering body temperature and causing drowsiness, and also inhibits insulin secretion by pancreatic β cells. A 2013 case-control studywithin the Nurses’ Health Study cohort showed that, compared with women in the highest category of melatonin secretion, women in the lowest category had about a twice the risk of developing type 2 diabetes (after controlling for demographic, lifestyle, and other risk factors). Previous studies have shown that single nucleotide polymorphisms of the melatonin receptor are also associated with an increased risk of type 2 diabetes.

More clinical research is needed to characterise this association between sleep, melatonin concentrations, and type 2 diabetes, and to elucidate, for example, whether melatonin supplementation has a role in treatment. Irregular and extended working hours are a reality for many industries, and epidemiological studies have shown lower melatonin concentrations in night-shift workers than in day-shift workers and an increasing risk of type 2 diabetes with number of years of shift work. For this substantial proportion of the workforce, more solutions are needed to prevent people from falling into economically driven health traps.

Insufficient sleep is a risk factor for weight gain and obesity, in addition to type 2 diabetes, and understanding the underlying mechanisms could help to guide novel weight-loss strategies. A study published on April 2, 2013, showed that eating behaviours, particularly night-time eating, contributed to weight gain during sleep loss. Whole-room calorimetry measured daily energy expenditure in adults undergoing 5-day cycles of inadequate (5 h) or adequate (9 h) nightly sleep. Energy expenditure was about 5% higher with insufficient sleep, but increased food intake more than compensated for this energetic cost. In the sleep-loss condition, participants ate a smaller breakfast but consumed 42% more calories as after-dinner snacks, leading to weight gain. The study investigators suggested that participants’ eating patterns during sleep loss resulted from a delayed circadian phase—ie, a later onset of melatonin secretion at night, assessed by hourly blood samples from an intravenous catheter—which might have led to a circadian drive for more food intake. Furthermore, the time between waking and melatonin offset was longer in the 5 h sleep condition; thus, participants awoke during an earlier circadian phase (while still in biological night) and might have been less hungry for breakfast. Previous studies have suggested that disrupted signalling of satiety and hunger hormones leads to the overeating associated with insufficient sleep; however, in both the 5 h and 9 h conditions, excessive food intake was accompanied by appropriate increases in the satiety hormones leptin and peptide YY and decreases in ghrelin, which stimulates hunger.

Future studies should examine how sleep deprivation leads to delays in circadian phase and how circadian timing of meals affects energy metabolism. For the millions of people whose working week necessitates a disrupted sleep schedule, a physiological drive for more food intake, the availability of high-calorie foods, and exhaustion leading to less physical activity overall could be a potent formula for weight gain.

Whether for work, play, or travel, voluntary sleep curtailment has become endemic; however, restricted sleep seems to interfere with the crosstalk between complex physiological and circadian networks that have evolved to couple our bodily functions with the Earth’s 24 h rotation. Many more issues deserve investigation, such as the differential effects on health of acute versus chronic sleep deprivation, and how light exposure mediates the effects of sleep loss. As more evidence emerges of the circadian orchestration of metabolism, perhaps the time has come for sleep to figure more prominently in treatment and public health guidelines.

Source: Lancet

 

Low Melatonin Levels Linked to Diabetes, Study Finds.


Image112EMR-Melatonin-Cherry26jul00f1Having low levels of melatonin, a hormone that regulates sleep, may put you at risk for type 2 diabetes, according to a new study.

By Amir Khan, Everyday Health Staff Writer

People with low levels of melatonin, a hormone that helps regulate sleep and circadian rhythm, may be at a higher risk for type 2 diabetes than people with high levels, according to a new study published in the Journal of the American Medical Association.

Researchers from Brigham and Women’s Hospital in Boston looked at 370 women who developed diabetes while taking part in the Nurses’ Health Study, a long-term study on women’s health, alongside 370 healthy controls, and found that study participants with low levels of melatonin were at approximately twice the risk of developing type 2 diabetes when compared to participants with high levels, even after the researchers adjusted for other diabetes risk factors such as smoking, diet, and exercise.

“This is the first time that an independent association has been established between nocturnal melatonin secretion and type 2 diabetes risk,” Ciaran McMullan, MD, study author and researcher in the renal division at Brigham and Women’s Hospital, said in a statement. “Hopefully this study will prompt future research to examine what influences a person’s melatonin secretion and what is melatonin’s role in altering a person’s glucose metabolism and risk of diabetes.”

Previous research done in rats has shown that taking a melatonin supplement protected them against diabetes, the researchers said, but they could not say for sure that it would have the same effect in humans.

Melatonin is produced in the pineal gland, which is located in the center of the brain, and can be measured through a blood, urine or saliva test. The hormone is only produced in the dark, and low levels have been linked to various conditions, including breast cancerovarian cancer, andinsomnia.

“Melatonin receptors have been found throughout the body in many tissues including pancreatic islet cells,” the researchers wrote in the study, “reflecting the widespread effects of melatonin on physiological functions such as energy metabolism and the regulation of body weight.”

While the researchers could not say for sure that there was a causal link between low melatonin levels and type 2 diabetes, they said previous research has shown that melatonin can play a role helping to regulate sugar levels in the body. When melatonin levels are low, the researchers continued, your blood sugar levels could be thrown off, raising your risk for diabetes.

In addition, they said that since melatonin helps regulate sleep and circadian rhythm, it’s possible that people with low melatonin levels wake up frequently during the night and sleep fewer hours, which could increase their risk.

“Sleep disruption may also be associated with diabetes,” the researchers wrote in the study. “For example, men who reported sleeping less than five hours per night were twice as likely to develop diabetes as those who reported sleeping seven hours per night.”

Although this is the first study to link melatonin to diabetes risk, some doctors use melatonin to treat patients who are already diagnosed with the condition. Michael Wald, MD, director of nutritional services at Integrated Medicine of Mount Kisco in Mount Kisco, NY, routinely gives his diabetic patients melatonin, and said it helps bring their blood sugar levels back into line.

“Several studies have noted that diabetes often have insomnia and it is this subgroup of diabetes that may benefit the most from melatonin supplementation,” said Dr. Wald. “In diabetics with low melatonin, taking slow-release melatonin seems to improve blood sugar levels. The diabetic blood sugar test, called hemoglobin A1c, is reduced in diabetics who take between 1 to 2 mg of melatonin two hours before bedtime.”

Giving patients melatonin, he added, not only helps their blood sugar levels, but also helps them sleep better, which can reduce the risks of other diseases as well.

“By improving sleep quality, melatonin may reduce the risk of many diseases that are associated with poor sleep quality,” Wald said, “including, but not limited to, cardiovascular disease, sleep apnea, nerve problems, depression and pain.”