Posted: 14 June 2005
Recent abstracts Re: Diabetes, diet, dairy, alcohol, tobacco, exercise: confounding variable is formaldehyde from methanol from aspartame, smoke, wines and liquors, pectins in fruits and vegetables
In humans, ingested or inhaled methanol is always quickly largely converted into formaldehyde and thence largely into formic acid.
These are both potent cumulative toxins that must affect every cell type, thus aggravating every disease process.
Adequate folic acid levels protect humans by expediting the elimination of formaldehyde.
Although there is a fairly high level of awareness about the dangers of formaldehyde from laboratory and medical education exposure, from direct and secondary tobacco exposure, and many new buildings and mobile homes, there is widespread ignorance about the open secret that substantial sources of methanol include aspartame, wood smoke, dark wines and liquors (in which the conversion of methanol into formaldehyde is the major cause of the infamous "morning after" hangover), and degradation by bacteria in the colon of pectins from fruits and vegetables.
Remarkably, a recent expert review emphasizes that very little is known about the actual disposition and accumulation in human tissues of these toxins from chronic exposures to methanol, particularly for long-term, heavy exposure in vulnerable groups. (Bourchard M, 2001)
Therefore, these toxins and their sources are uncontrolled, confounding variables for research on diabetes, diet, alcohol, tobacco, and exercise.
FOLLOWING ARE KEY LINKS AND REVIEWS:
Short review: research on aspartame (methanol, formaldehyde, formic acid) toxicity
Research on aspartame (methanol, formaldehyde, formic acid) toxicity
Alcohol Clin Exp Res. 1997 Aug; 21(5): 939-43.
Endogenous production of methanol after the consumption of fruit.>br> Lindinger W, Taucher J, Jordan A, Hansel A, Vogel W.
Institut fur Ionenphysik, Leopold Franzens Universitat Innsbruck, Austria
After the consumption of fruit, the concentration of methanol in the human body increases by as much as an order of magnitude. This is due to the degradation of natural pectin (which is esterified with methyl alcohol) in the human colon.
In vivo tests performed by means of proton-transfer-reaction mass spectrometry show that consumed pectin in either a pure form (10 to 15 g) or a natural form (in 1 kg of apples) induces a significant increase of methanol in the breath (and by inference in the blood) of humans. The amount generated from pectin (0.4 to 1.4 g) [ 400 to 1400 mg ] is approximately equivalent to the total daily endogenous production (measured to be 0.3 to 0.6 g/day) [ 300 to 600 mg ] or that obtained from 0.3 liters of 80-proof brandy (calculated to be 0.5 g). [ 500 mg ] This dietary pectin may contribute to the development of nonalcoholic cirrhosis of the liver. PMID: 9267548
Alcohol Clin Exp Res. 1995 Oct; 19(5): 1147-50.
Methanol in human breath.
Taucher J, Lagg A, Hansel A, Vogel W, Lindinger W.
Institut fur Ionenphysik, Universitat Innsbruck, Austria.
Using proton transfer reaction-mass spectrometry for trace gas analysis of the human breath, the concentrations of methanol and ethanol have been measured for various test persons consuming alcoholic beverages and various amounts of fruits, respectively.
The methanol concentrations increased from a natural (physiological) level of approximately 0.4 ppm up to approximately 2 ppm a few hours after eating about 1/2 kg of fruits, and about the same concentration was reached after drinking of 100 ml brandy containing 24% volume of ethanol and 0.19% volume of methanol. PMID: 8561283
Methanol (formaldehyde, formic acid) disposition: Bouchard M et al, full plain text, 2001: Substantial sources are degradation of fruit pectins, liquors, aspartame, smoke
"That substantial amounts of methanol metabolites or by-products are retained for a long time is verified by Horton et al. (1992) who estimated that 18 h following an iv injection of 100 mg/kg of 14C-methanol in male Fischer-344 rats, only 57% of the dose was eliminated from the body.
From the data of Dorman et al. (1994) and Medinsky et al. (1997), it can further be calculated that 48 h following the start of a 2-h inhalation exposure to 900 ppm of 14C-methanol vapors in female cynomolgus monkeys, only 23% of the absorbed 14C-methanol was eliminated from the body.
These findings are corroborated by the data of Heck et al. (1983) showing that 40% of a 14C-formaldehyde inhalation dose remained in the body 70 h postexposure."
"Exposure to methanol also results from the consumption of certain foodstuffs (fruits, fruit juices, certain vegetables, aspartame sweetener, roasted coffee, honey) and alcoholic beverages (Health Effects Institute, 1987; Jacobsen et al., 1988)."
"However, the severe toxic effects are usually associated with the production and accumulation of formic acid, which causes metabolic acidosis and visual impairment that can lead to blindness and death at blood concentrations of methanol above 31 mmol/l (Røe, 1982; Tephly and McMartin, 1984; U.S. DHHS, 1993).
Although the acute toxic effects of methanol in humans are well documented, little is known about the chronic effects of low exposure doses, which are of interest in view of the potential use of methanol as an engine fuel and current use as a solvent and chemical intermediate.
Gestational exposure studies in pregnant rodents (mice and rats) have also shown that high methanol inhalation exposures (5000 or 10,000 ppm and more, 7 h/day during days 6 or 7 to 15 of gestation) can induce birth defects (Bolon et al., 1993; IPCS, 1997; Nelson et al., 1985)."
"The corresponding average elimination half-life of absorbed methanol through metabolism to formaldehyde was estimated to be 1.3, 0.7-3.2, and 1.7 h."
"Inversely, in monkeys and in humans, a larger fraction of body burden of formaldehyde is rapidly transferred to a long-term component. The latter represents the formaldehyde that (directly or after oxidation to formate) binds to various endogenous molecules..."
"Animal studies have reported that systemic methanol is eliminated mainly by metabolism (70 to 97% of absorbed dose) and only a small fraction is eliminated as unchanged methanol in urine and in the expired air (< 3-4%) (Dorman et al., 1994; Horton et al., 1992).
Systemic methanol is extensively metabolized by liver alcohol dehydrogenase and catalase-peroxidase enzymes to formaldehyde, which is in turn rapidly oxidized to formic acid by formaldehyde dehydrogenase enzymes (Goodman and Tephly, 1968; Heck et al., 1983; Røe, 1982; Tephly and McMartin, 1984).
Under physiological conditions, formic acid dissociates to formate and hydrogen ions.
Current evidence indicates that, in rodents, methanol is converted mainly by the catalase-peroxidase system whereas monkeys and humans metabolize methanol mainly through the alcohol dehydrogenase system (Goodman and Tephly, 1968; Tephly and McMartin, 1984).
Formaldehyde, as it is highly reactive, forms relatively stable adducts with cellular constituents (Heck et al., 1983; Røe, 1982)."
The whole body loads of methanol, formaldehyde, formate, and unobserved by-products of formaldehyde metabolism were followed.
Since methanol distributes quite evenly in the total body water, detailed compartmental representation of body tissue loads was not deemed necessary."
"According to model predictions, congruent with the data in the literature (Dorman et al., 1994; Horton et al., 1992), a certain fraction of formaldehyde is readily oxidized to formate, a major fraction of which is rapidly converted to CO2 and exhaled, whereas a small fraction is excreted as formic acid in urine.
However, fits to the available data in rats and monkeys of Horton et al. (1992) and Dorman et al. (1994) show that, once formed, a substantial fraction of formaldehyde is converted to unobserved forms.
This pathway contributes to a long-term unobserved compartment.
The latter, most plausibly, represents either the formaldehyde that (directly or after oxidation to formate) binds to various endogenous molecules (Heck et al., 1983; Røe, 1982) or is incorporated in the tetrahydrofolic-acid-dependent one-carbon pathway to become the building block of a number of synthetic pathways (Røe, 1982; Tephly and McMartin, 1984).
That substantial amounts of methanol metabolites or by-products are retained for a long time is verified by Horton et al. (1992) who estimated that 18 h following an iv injection of 100 mg/kg of 14C-methanol in male Fischer-344 rats, only 57% of the dose was eliminated from the body.
From the data of Dorman et al. (1994) and Medinsky et al. (1997), it can further be calculated that 48 h following the start of a 2-h inhalation exposure to 900 ppm of 14C-methanol vapors in female cynomolgus monkeys, only 23% of the absorbed 14C-methanol was eliminated from the body.
These findings are corroborated by the data of Heck et al. (1983) showing that 40% of a 14C-formaldehyde inhalation dose remained in the body 70 h postexposure.
In the present study, the model proposed rests on acute exposure data, where the time profiles of methanol and its metabolites were determined only over short time periods (a maximum of 6 h of exposure and a maximum of 48 h postexposure).
This does not allow observation of the slow release from the long-term components.
It is to be noted that most of the published studies on the detailed disposition kinetics of methanol regard controlled short-term (iv injection or continuous inhalation exposure over a few hours) methanol exposures in rats, primates, and humans (Batterman et al., 1998; Damian and Raabe, 1996; Dorman et al., 1994; Ferry et al., 1980; Fisher et al., 2000; Franzblau et al., 1995; Horton et al., 1992; Jacobsen et al., 1988; Osterloh et al., 1996; Pollack et al., 1993; Sedivec et al., 1981; Ward et al., 1995; Ward and Pollack, 1996).
Experimental studies on the detailed time profiles following controlled repeated exposures to methanol are lacking."
"Thus, in monkeys and plausibly humans, a much larger fraction of body formaldehyde is rapidly converted to unobserved forms rather than passed on to formate and eventually CO2."
"However, the volume of distribution of formate was larger than that of methanol, which strongly suggests that formate distributes in body constituents other than water, such as proteins.
The closeness of our simulations to the available experimental data on the time course of formate blood concentrations is consistent with the volume of distribution concept (i.e., rapid exchanges between the nonblood pool of formate and blood formate)."
"Also, background concentrations of formate are subject to wide interindividual variations (Baumann and Angerer, 1979; D'Alessandro et al., 1994; Franzblau et al., 1995; Heinrich and Angerer, 1982; Lee et al., 1992; Osterloh et al., 1996; Sedivec et al., 1981)."
Toxicological Sciences 64, 169-184 (2001)
Copyright (c) 2001 by the Society of Toxicology
BIOTRANSFORMATION AND TOXICOKINETIC
A Biologically Based Dynamic Model for Predicting the Disposition of Methanol and Its Metabolites in Animals and Humans
Michèle Bouchard *, # (1) firstname.lastname@example.org
Robert C. Brunet, # email@example.com
Pierre-Olivier Droz, #
Gaétan Carrier* firstname.lastname@example.org
* Department of Environmental and Occupational Health, Faculty of Medicine, Université de Montréal, P.O. Box 6128, Main Station, Montréal, Québec, Canada, H3C 3J7
# Institut Universitaire romand de Santé au Travail, rue du Bugnon 19, CH-1005, Lausanne, Switzerland, and
# Département de Mathématiques et de Statistique and Centre de Recherches Mathématiques, Faculté des arts et des sciences, Université de Montréal, P.O. Box 6128, Main Station, Montréal, Québec, Canada, H3C 3J7
Nurses Health Study can quickly reveal the extent of aspartame (methanol, formaldehyde, formic acid) toxicity
The Nurses Health Study is a bonanza of information about the health of probably hundreds of nurses who use 6 or more cans daily of diet soft drinks -- they have also stored blood and tissue samples from their immense pool of subjects.
Dark wines and liquors, as well as aspartame, provide similar levels of methanol, above 100 mg daily, for long-term heavy users. Methanol is inevitably largely turned into formaldehyde, and thence largely into formic acid.
The immediate health effects for dark wines and liquors are the infamous "morning after" hangover, for which many informed experts cite as the major cause the conversion of the methanol impurity, over one part in ten thousand (red wine has 128 mg/L methanol), into formaldehyde and formic acid. Everyone knows the complex progression of symptoms at this level of long-term, chronic toxicity.
Aspartame reactors have a very similar progression.
Fully 11% of aspartame is methanol-- 1,120 mg aspartame in 2 L diet soda, almost six 12-oz cans, gives 123 mg methanol (wood alcohol). If 30% of the methanol is turned into formaldehyde, the amount of formaldehyde is 18 times the 1999 USA EPA limit for daily formaldehyde in drinking water, 2 mg in 2 L water.
Faults in 1999 July EPA 468-page formaldehyde profile: Elzbieta Skrzydlewska PhD, Assc. Prof., Medical U. of Bialystok, Poland, abstracts -- ethanol, methanol, formaldehyde, formic acid, acetaldehyde, lipid peroxidation, green tea, aging, Lyme disease
Nature 414, 782 - 787 (13 December 2001); doi:10.1038/414782a Global and societal implications of the diabetes epidemic PAUL ZIMMET*, K. G. M. M. ALBERTI? & JONATHAN SHAW*
* International Diabetes Institute, 260 Kooyong Road, Caulfield, Victoria 3162, Australia http://www.diabetes.com.au/home.htm PZimmet@idi.org.au ? Royal College of Physicians, 11 St Andrews Place, Regent's Park, London NW1 4LE, UK email@example.com Professor Sir George Alberti http://www.rcplondon.ac.uk Royal College of Physicians
Changes in human behaviour and lifestyle over the last century have resulted in a dramatic increase in the incidence of diabetes worldwide. The epidemic is chiefly of type 2 diabetes and also the associated conditions known as 'diabesity' and 'metabolic syndrome'.
In conjunction with genetic susceptibility, particularly in certain ethnic groups, type 2 diabetes is brought on by environmental and behavioural factors such as a sedentary lifestyle, overly rich nutrition and obesity.
The prevention of diabetes and control of its micro- and macrovascular complications will require an integrated, international approach if we are to see significant reduction in the huge premature morbidity and mortality it causes.
"Man may be the captain of his fate, but he is also the victim of his blood sugar" Wilfrid Oakley [Trans. Med. Soc. Lond. 78, 16 (1962)]
From: "Robert Cohen" firstname.lastname@example.org
Subject: NOTMILK - Milk/Diabetes Update
Date: Thursday, June 02, 2005 3:24 AM
A June, 2005 publication adds fuel to the milk/diabetes connection. Continue to consume dairy products and you too may become a victim of diabetes, the "milk disease."
STUDY TITLE: Avoiding milk is associated with a reduced risk of insulin resistance.
JOURNAL CITATION: Diabet Med. 2005 Jun; 22(6): 808-11.
OBJECTIVE: To examine the association of milk consumption with insulin resistance and the metabolic syndrome.
METHOD: The association was examined in 4024 British women aged 60-79 who were randomly selected from primary care centers in 23 towns.
RESULTS: Women who never drank milk had lower homeostasis model assessment insulin resistance (HOMA) scores, triglyceride concentrations and body mass indices, and higher high-density lipoprotein (HDL)-cholesterol concentrations, than those who drank milk.
CONCLUSION: Individuals who do not drink milk may be protected against insulin resistance and the metabolic syndrome.
This new study supports a study published earlier this year.
The March, 2005 issue of the European Journal of Clinical Nutrition (2005 Mar; 59(3): 393-8) reported that a high intake of dairy products (but not meat) increased insulin resistance in 8-year-old boys.
In the milk-drinking group, insulin resistance doubled when compared to the control group which consumed no milk.
The key phrase is "Insulin Resistance." What is that?
Eur J Clin Nutr. 2005 Mar; 59(3): 393-8.
High intakes of milk, but not meat, increase s-insulin and insulin resistance in 8-year-old boys.
Hoppe C, Molgaard C, Vaag A, Barkholt V, Michaelsen KF.
Department of Human Nutrition and Centre for Advanced Food Studies, The Royal Veterinary and Agricultural University, Frederiksberg, Denmark. Cho@kvl.dk
OBJECTIVE: Our objective was to examine if a high animal protein intake from milk or meat increased s-insulin and insulin resistance in healthy, prepubertal children. A high animal protein intake results in higher serum branched chain amino acids (BCAA; leucine, isoleucine and valine) concentrations, which are suggested to stimulate insulin secretion. Furthermore, milk possesses some postprandial insulinotrophic effect that is not related to its carbohydrate content.
DESIGN: A total of 24 8-y-old boys were asked to take 53 g protein as milk or meat daily. At baseline and after 7 days, diet was registered, and insulin, glucose, and amino acids were determined. Insulin resistance and beta cell function were calculated with the homeostasis model assessment.
RESULTS: Protein intake increased by 61 and 54% in the milk- and meat-group, respectively. In the milk-group, fasting s-insulin concentrations doubled, which caused the insulin resistance to increase similarly. In the meat-group, there was no increase in insulin and insulin resistance. As the BCAAs increased similarly in both groups, stimulation of insulin secretion through BCAAs is not supported.
CONCLUSIONS: Our results indicate that a short-term high milk, but not meat, intake increased insulin secretion and resistance. The long-term consequences of this are unknown. he effect of high protein intakes from different sources on glucose-insulin metabolism needs further studying. PMID: 15578035
Diabet Med. 2005 Jun; 22(6): 808-11.
Avoiding milk is associated with a reduced risk of insulin resistance and the metabolic syndrome: findings from the British Women's Heart and Health Study.
Lawlor DA, Ebrahim S, Timpson N, Davey Smith G.
Department of Social Medicine, University of Bristol, Canynge Hall, Bristol, UK.
[ Timpson Nic J Research Student NJTimpson@bris.ac.uk ]
Objective: To examine the association of milk consumption with insulin resistance and the metabolic syndrome.
Methods: The association was examined in 4024 British women aged 60-79 who were randomly selected from primary care centres in 23 towns.
Results: Women who never drank milk had lower homeostasis model assessment insulin resistance (HOMA) scores, triglyceride concentrations and body mass indices, and higher high-density lipoprotein (HDL)-cholesterol concentrations, than those who drank milk.
The age-adjusted odds ratio for the metabolic syndrome comparing non-milk drinkers with drinkers was 0.55 (0.33, 0.94), which did not attenuate with adjustment for potential confounders. Diabetes was less common in non-milk drinkers.
Conclusion: Individuals who do not drink milk may be protected against insulin resistance and the metabolic syndrome.
However, randomized controlled trials are required to establish whether milk avoidance is causally associated with these outcomes.
Affiliations: Department of Social Medicine, University of Bristol, Canynge Hall, Bristol, UK D.A.Lawlor@bristol.ac.uk ; SEbrahim@cdc.gov Correspondence: D. A. Lawlor, Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol, BS8 2PR, UK.
Free full text
Insulin resistance and depressive symptoms in middle aged men: findings from the Caerphilly prospective cohort study
Debbie A Lawlor, senior lecturer in epidemiology and public health (1)
Yoav Ben-Shlomo, senior lecturer in clinical epidemiology (1)
Shah B J Ebrahim, professor in epidemiology of ageing (1)
George Davey Smith, professor of clinical epidemiology (1)
Stephen A Stansfeld, professor of psychiatry (2)
John W G Yarnell, reader in epidemiology and public health (3)
John E J Gallacher, senior lecturer in environmental epidemiology (4)
Professor SBJ Ebrahim (0117) 928 7350 Shah.Ebrahim@bristol.ac.uk
(0117) 928 Y.Ben-Shlomo@bristol.ac.uk
(0117) 928 7329 George.Davey-Smith@bristol.ac.uk ]
Insulin resistance may protect against depression, possibly through an effect on circulating free fatty acid concentrations and brain serotonin concentration, (1, 2) although a recent study contradicted these findings. (3)
Studies to date have either used indirect measures of insulin resistance, (1) or they have been cross sectional. (2, 3) We assessed the association of insulin resistance with depressive symptoms in a prospective cohort.
Participants, methods, and results
The Caerphilly cohort study has been described in detail before. (4) In phase I (1979-83), 2512 (89% of eligible) men aged 45-59 years from Caerphilly in Wales provided fasting blood samples. Insulin resistance (homoeostasis model assessment (HOMA) score) was derived from fasting insulin and glucose. (5)
HOMA scores were not calculated for men with diabetes or high fasting glucose (? 7.0 mmol/l). In phases II (1984-88), III (1989-93), and IV (1993-7), depressive symptoms were measured by the 30 item general household questionnaire (GHQ). This was validated at phase II in a subgroup (n = 97) by comparison with a clinical interview schedule given by a psychiatrist blinded to the GHQ score. (4) Based on receiver operating characteristics, we defined men scoring five or above as having mild to moderate psychological distress. (4)
At phase I, 2203 (88%) of the men had assessment of insulin resistance or diabetes status. Of the surviving men, the numbers with GHQ data at phases II, III, and IV were 1619/2025 (80%), 1236/1845 (67%), and 1088/1675 (65%).
Insulin resistance and high GHQ score were not associated at any phase of follow up (table).
Diabetes at baseline was associated with a tendency to reduced odds of high GHQ at follow up, but, owing to small numbers, these estimates are imprecise. Additional adjustment for smoking, physical activity, alcohol consumption, and adult and childhood social class did not substantively alter any of the findings.
Insulin resistance and GHQ scores were not associated in linear regression models with GHQ as a continuous outcome (all P values > 0.2).
When fasting insulin was used there was no evidence of an association with GHQ. In cross sectional analyses (exposures and outcomes measured at phase II) there was no association between any HOMA scores, fasting insulin, or diabetes and GHQ score. We also found no associations between body mass index, systolic blood pressure, high density lipoprotein cholesterol, or (logged) triglyceride concentration and GHQ in either prospective or cross sectional analyses (all P values > 0.3).
Insulin resistance was not associated with reduced depressive symptoms in a prospective study of middle aged men.
This contradicts our earlier findings in a cross sectional study of older women, in which there was an inverse association with both clinically diagnosed depression and use of antidepressant drugs, (2) and the findings of a second cross sectional study which found a positive association between insulin resistance and depression assessed using the Beck's depression inventory. (3)
These contradictory findings may be due to the cross sectional nature of the earlier studies.
A large prospective study, in which reverse causality would be unlikely, found that indicators of insulin sensitivity were associated with suicide risk. (1)
Taken together these findings indicate that insulin resistance may protect against only severe depression.
Our assessment of depression was based on GHQ rather than clinical assessment, and if insulin resistance is only protective against severe depression then this measure may be inadequate to detect an association. Also, any measurement error in our assessment of depression would tend to dilute the results.
We validated the score, however, against a clinical interview in a subgroup. (4)
The contradictory results concerning the association of insulin resistance with depression and suicide warrant further research. Future studies might include trials of the effects on insulin resistance of treating depression. Observational studies should ideally use standardised diagnostic criteria for depression and prospectively assess the association of insulin resistance with differing severities.
What is already known on this topic
Cross sectional studies and those using indirect measurements indicate that insulin resistance may protect against depression.
What this study adds
Insulin resistance was not associated with reduced depressive symptoms in a prospective study of middle aged men
This article was posted on bmj.com on 31 January 2005:
The Caerphilly study was done by the former Medical Research Council Epidemiology Unit (South Wales) and was funded by the Medical Research Council of the United Kingdom.
The department of social medicine, University of Bristol, is custodian for the Caerphilly database. We thank the men who participated in the study.
Contributors: YB-S, GDS, SE, and DAL developed the study idea. SAS validated the GHQ data. JY initiated the Caerphilly study, and YB-S, JEJG, and JWGY are responsible for the continued management of the study. DAL did the analysis and wrote the first draft of the paper, and all authors contributed to the final version. DAL and YB-S are guarantors.
Funding: DAL receives a UK Department of Health Career Scientist Award.
Competing interests: None declared.
Ethical approval: Phases I-III of the Caerphilly study were approved by Cardiff Local Research Ethics Committee and later phases by Gwent Research Ethics Committee.
Golomb BA, Tenkanen L, Alikoski T, Niskanen T, Manninen V, Huttunen M, et al. Insulin sensitivity markers: predictors of accidents and suicides in Helsinki Heart Study screenees. J Clin Epidemiol 2002; 55: 767-73. [PubMed][Full Text]
Lawlor DA, Davey Smith G, Ebrahim S. Association of insulin resistance with depression: cross sectional findings from the British women's heart and health study. BMJ 2003; 327: 1383-4. [ Free Full text in PMC]
Stansfeld SA, Gallacher JEJ, Sharp DS, Yarnell JWG. Social factors and minor psychiatric disorder in middle-aged men: a validation study and a population survey. Psychol Med 1991; 21: 157-67. [PubMed]
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412-9. [PubMed]
Figures and Tables
Table 1. Insulin resistance and diabetes at baseline (1979-83) and GHQ score (indicative of depressive symptoms) at different phases of follow up in middle aged men in the Caerphilly prospective cohort study
Arch Intern Med. 2005 May 9; 165(9): 997-1003.
Dairy consumption and risk of type 2 diabetes mellitus in men: a prospective study.
Choi HK, Willett WC, Stampfer MJ, Rimm E, Hu FB.
Department of Medicine, Massachusetts General Hospital, Boston, Mass 02114, USA. HChoi@partners.org
BACKGROUND: Diet and lifestyle modifications can substantially reduce the risk of type 2 diabetes. While a strong inverse association has been reported between dairy consumption and the insulin resistance syndrome among young obese adults, the relation between dairy intake and type 2 diabetes is unknown.
METHODS: We prospectively examined the relation between dairy intake and incident cases of type 2 diabetes in 41,254 male participants with no history of diabetes, cardiovascular disease, and cancer at baseline in the Health Professionals Follow-up Study.
RESULTS: During 12 years of follow-up, we documented 1243 incident cases of type 2 diabetes. Dairy intake was associated with a modestly lower risk of type 2 diabetes.
Dairy intake was associated with a modestly lower risk of type 2 diabetes. After adjusting for potential confounders, including body mass index, physical activity, and dietary factors, the relative risk for type 2 diabetes in men in the top quintile of dairy intake was 0.77 (95% confidence interval [CI], 0.62-0.95; P for trend, .003) compared with those in the lowest quintile. Each serving-per-day increase in total dairy intake was associated with a 9% lower risk for type 2 diabetes (multivariate relative risk, 0.91; 95% CI, 0.85-0.97).
The corresponding relative risk was 0.88 (95% CI, 0.81-0.94) for low-fat dairy intake and 0.99 (95% CI, 0.91-1.07) for high-fat dairy intake. The association did not vary significantly according to body mass index (< 25 vs > or = 25 kg/m(2); P for interaction, .57).
CONCLUSION: Dietary patterns characterized by higher dairy intake, especially low-fat dairy intake, may lower the risk of type 2 diabetes in men. PMID: 15883237
Free full text
J Am Board Fam Pract. 2005 May-Jun; 18(3): 205-10.
Dietary calcium intake and obesity.
Schrager S. Sarina Schrager, MD
Department of Family Medicine, University of Wisconsin-Madison, 777 S. Mills St., Madison, WI 53715, USA. SBSchrag@wisc.edu
Obesity is increasing in the United States in epidemic proportions. Epidemiologic data suggest that people with high calcium intake have a lower prevalence of overweight, obesity, and insulin resistance syndrome. Studies in transgenic mice have demonstrated that calcium influences adipocyte metabolism.
High calcium intake depresses levels of parathyroid hormone and 1,25-hydroxy vitamin D. These decreased hormone levels cause decreases in intracellular calcium, thereby inhibiting lipogenesis and stimulating lipolysis. High dietary calcium intakes also increases excretion of fecal fat and may increase core body temperature.
Calcium from dairy products seems to have more of an impact than calcium from dietary supplements.
Primary care providers should include recommendations about adequate calcium intake in standard dietary counseling about weight management. PMID: 15879568
Nutr Metab Cardiovasc Dis. 2004 Dec; 14(6): 334-43.
Prudent diet and the risk of insulin resistance.
Villegas R, Salim A, Flynn A, Perry IJ. A.Flynn@ucc.ie Department of Epidemiology and Public Health, Distillery House, North Mall, University College Cork, Cork, Ireland.
Prof. Ivan J Perry I.Perry@ucc.ie +353-21-4904235
BACKGROUND AND AIM: Diet is a potentially modifiable risk factor for diabetes. Dietary patterns may exert greater effects on health than individual foods, nutrients or food groups.
Data on associations between dietary patterns and the risk of insulin resistance and type 2 diabetes are sparse. The aim of the study was to examine associations between dietary patterns and the risk of insulin resistance.
METHODS AND RESULTS: We performed a cross sectional study involving a group of 1018 men and women, sampled from 17 general practice lists in the South of Ireland, with a response rate of 69%.
Participants completed a detailed health and lifestyle questionnaire and provided fasting blood samples for analysis of glucose, insulin and lipids. Dietary intake was assessed using a food frequency questionnaire.
The food frequency questionnaire was a modification of the UK arm of the European Prospective Investigation into cancer, EPIC study, which was based on that used in the US Nurses' Health Study. Dietary patterns were assessed by K cluster analysis. Insulin resistance was estimated on the basis of fasting glucose and insulin, using the glucose homeostasis model (HOMA scores). Insulin resistance was defined as the upper quartile of the HOMA scores.
Three dietary patterns were identified by cluster analysis (traditional Irish diet, a prudent diet and an alcohol and convenience foods diet).
Participants in clusters 1 (traditional Irish diet) and 3 (high alcohol and convenience foods) had a lower intake of more 'healthy' food groups (such as fruit, vegetables, low fat dairy products, poultry, fish and whole grain products) and higher intake of foods richer in total and SFA content (such as high fat dairy products, butter, meat and meat products).
Cluster 2 (prudent dietary pattern) was characterized by a higher intake of food groups that are typically recommended in health promotion programs and a lower intake of meat (red meat), meat products, sweets, high fat dairy and white bread (white bread and unrefined cereal).
The prudent diet had the lowest HOMA scores in analysis of covariance. The prevalence of insulin resistance in the prudent diet was lower than that in the traditional diet (OR=0.53; 95%CI, 0.33-0.85 in fully adjusted analysis). CONCLUSION: A prudent diet may be associated with enhanced insulin sensitivity and a lower risk of type 2 diabetes. PMID: 15853117
Ir Med J. 2004 Nov-Dec; 97(10): 300-3.
Prevalence and lifestyle determinants of the metabolic syndrome.
Villegas R, Creagh D, Hinchion R, O'Halloran D, Perry IJ. I.Perry@ucc.ie
Department of Epidemiology and Public Health, North Mall, University College Cork, Ireland.
Participants with the metabolic syndrome are at risk of developing type 2 diabetes and coronary heart disease.
The aim of this study was to determine the role of lifestyle risk factors in the development of the metabolic syndrome with particular reference to physical activity, smoking and alcohol consumption.
We performed a cross sectional study of the prevalence of CVD risk factors and glucose intolerance, including type 2 diabetes involving a group of 1473 men and women were sampled from 17 general practice lists in the South of Ireland.
A total of 1018 attended for screening, giving a response rate of 69%. Participants completed a detailed health and lifestyle questionnaire and provided fasting blood samples for analysis of glucose, insulin and lipids.
The metabolic syndrome was defined according to the current WHO criteria.
The prevalence of the metabolic syndrome was 21.0% (95% C.I. 18.7% to 24.1%). In multivariate analyses with the metabolic syndrome as the dependent variable we observed a significant, independent inverse association with physical activity level (OR = 0.60; 95% CI, 0.39-0.90 for medium and OR = 0.51; 95% CI, 0.28-0.93) for high level of activity relative to the low level of activity group).
Ex-drinkers had a higher prevalence of the syndrome in multivariate analysis relative to occasional drinkers, (OR = 2.38; 95% CI, 1.08-5.26). Prevalence of the metabolic syndrome was not significantly associated with current alcohol consumption or with smoking status.
These data highlight the importance of physical inactivity in the aetiology of the metabolic syndrome. PMID: 15696875
Nutr Metab Cardiovasc Dis. 2004 Oct; 14(5): 233-40.
Alcohol intake and insulin resistance. A cross-sectional study.
Villegas R, Salim A, O'Halloran D, Perry IJ. Department of Epidemiology and Public Health, Distillery House, North Mall, University College Cork, Cork, Ireland.
BACKGROUND AND AIM: The development of insulin resistance is a critical step in the pathogenesis of type 2 diabetes.
The effect of alcohol intake on insulin sensitivity/resistance is not well defined. The aim of this study was to examine the association between alcohol intake and insulin resistance in a sample of middle-aged men and women with data on a wide range of potential confounding factors, including diet.
METHODS: We performed a cross sectional study involving a group of 1018 men and women, sampled from 17 general practice lists in the South of Ireland, with a response rate of 69%.
Participants completed a detailed health and lifestyle questionnaire and a food frequency questionnaire and provided fasting blood samples for analysis of glucose and insulin.
Insulin resistance was estimated on the basis of fasting glucose and insulin, using the glucose homeostasis model (HOMA scores). Insulin resistance was defined as the upper quartile of the HOMA scores.
RESULTS: We found evidence of a U-shaped relationship between alcohol intake and insulin resistance fitted as a continuous variable (HOMA scores) with lowest levels in light drinkers (between 0.5 to 0.99 units per day) relative to the other drinking categories.
However no significant association between alcohol intake and HOMA score was observed in fully adjusted analyses, including adjustment for dietary saturated fat and fruit and vegetables intake.
In logistic regression analysis with insulin resistance (categorical) as the dependent variable, we observed that ex-drinkers were at higher risk of insulin resistance compared to occasional drinkers independently of age, sex, BMI and waist circumference, (OR=2.4, 95% CI, 1.1-5.7, p=0.04). On further adjustment for potential confounders including diet this association was also attenuated and was non-significant.
CONCLUSIONS: The reported effects of alcohol intake on insulin resistance may be confounded by other aspects of lifestyle, especially diet. PMID: 15673056
Free full text
J Epidemiol Community Health. 2002 Jul; 56(7): 542-8.
Alcohol consumption and the incidence of type II diabetes.
Wannamethee SG, Shaper AG, Perry IJ, Alberti KG. Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London, UK. Goya@pcps.ucl.ac.uk
S G Wannamethee (1) Goya@pcps.ucl.ac.uk
A G Shaper (1) AGShaper@wentworth.u-net.com
I J Perry (2) I.Perry@ucc.ie
K G M M Alberti (3)
METHODS: Prospective study of 5221 men aged 40-59 years with no history of coronary heart disease, diabetes, or stroke drawn from general practices in 18 British towns.
RESULTS: During the mean follow up of 16.8 years there were 198 incident cases of type II diabetes.
Occasional drinkers were the reference group.
A non-linear relation was seen between alcohol intake and age adjusted risk of diabetes, with risk lowest in light and moderate drinkers and highest in heavy drinkers (quadratic trend p=0.03).
Further adjustment for body mass index decreased risk in heavy drinkers. After additional adjustment for physical activity, smoking, and (undiagnosed) pre-existing coronary heart disease, only moderate drinkers showed significantly lower risk than occasional drinkers (RR=0.66 95% CI 0.44 to 0.99).
Alcohol intake was inversely associated with serum insulin and positively associated with HDL-cholesterol.
Adjustment for these factors reduced the "protective" effect in moderate drinkers (adjusted RR=0.73 95% CI 0.48 to 1.10) but the quadratic trend remained significant (p=0.02).
CONCLUSION: There is a non-linear relation between alcohol intake and the risk of type II diabetes.
Serum insulin and HDL-cholesterol explained a small amount (20%) of the reduction in risk of type II diabetes associated with moderate drinking.
The adverse effect of heavy drinking seemed to be partially mediated through its effect on body weight. PMID: 12080164