Facts on Caffeine and Soft Drinks Essay

Facts On Caffeine And Soft Drinks Caffeine is found in coffee beans, tea leaves, cocoa beans, and other plants. Caffeine is a safe ingredient that consumers have enjoyed as part of many of our products for more than 100 years. The beverage industry offers both caffeine-free and caffeinated soft drinks. One of the most studied ingredients Caffeine is one of the most comprehensively studied ingredients in the food supply, with centuries of safe consumption in foods and beverages. In 1958, the U. S. Food and Drug Administration (FDA) designated caffeine in cola drinks as “Generally Recognized As Safe” (GRAS).

The FDA considers caffeine safe for all consumers including children. After an extensive review in 1987, the FDA “found no evidence to show that the use of caffeine in carbonated beverages would render these products injurious to health. ” Over 140 countries have specifically considered the safety of caffeine and allow its use in beverages at various levels. Moderate caffeine consumption for adults — the amount contained in three to four 8 oz. cups of coffee or 5-6 cans of caffeinated soft drinks — has not been associated with adverse health effects. Of course, moderate caffeine consumption would be lower for children.

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Pregnant or nursing women, or women trying to become pregnant, should consult a doctor regarding caffeine consumption. Caffeine in the diet The most commonly known sources of caffeine are coffee, cocoa beans, kola nuts, and tea leaves. For children and young adults, the primary sources of caffeine are tea and soft drinks; caffeine intake for adults 25 and over is mostly from coffee. Caffeine in soft drinks Caffeine is an integral part of the complex flavor and overall profile of some soft drinks, which consumers enjoy for refreshment, taste and hydration.

For over 100 years in some cases, the formulas for these drinks have carefully balanced a mix of ingredients, including sweeteners, carbonation, caffeine, and other flavorings to produce the refreshing taste and exhilarating quality that consumers prefer, especially when served cold or with ice. The bitter taste of caffeine is part of the complex flavor profile of these drinks. The amount of caffeine in most caffeine-containing soft drinks is relatively small — about 30 milligrams of caffeine per 8-ounce serving, or less than one-third the amount present in an 8-ounce cup of drip-style coffee (104-192 mg per 8oz).

However, because some people prefer beverages without caffeine, many soft drinks are also available in caffeine-free versions. Is caffeine addictive? Addiction is a loosely used and, at times, loaded word that means different things to different people and is often defined differently by members of the general public. People who say they are “addicted” to caffeine tend to use the term loosely, like saying they are “addicted” to chocolate, running, shopping, working, or television. However, caffeine is not addictive as most experts in the scientific community define the term.

According to the World Health Organization, “There is no evidence whatsoever that caffeine use has even remotely comparable physical and social consequences which are associated with serious drugs of abuse. ” In the most recent version of the Diagnostic and Statistical Manual of Mental Disorders, the authoritative text of the American Psychiatric Association, caffeine is not classified as causing “substance dependence. ” Unlike drugs of abuse, people who choose to consume foods and beverages that contain caffeine can control or moderate their caffeine intake.

Most people who consume caffeine maintain a relatively consistent level of intake. Caffeine is considered a mild stimulant. Scientific studies confirm that although many people enjoy caffeinated products, those who choose to stop consuming or reduce caffeine in their diets can do so without serious medical intervention or serious psychological or physical effects. The side effects that some people experience, such as headaches, tend to be mild and pass within a few days. Is caffeine dehydrating? Some individuals may question whether caffeine is dehydrating.

Recent scientific consensus concludes caffeinated beverages contribute to the body’s hydration needs similarly to non-caffeinated beverages. The U. S. National Academy of Sciences in its February 2004 report on Dietary Reference Intakes for Water, Potassium, Sodium, Chloride and Sulfate state,”… caffeinated beverages appear to contribute to the daily total water intake similar to that contributed by non-caffeinated beverages. ” ————————————————- http://www. beverageinstitute. org/beverages_and_health/FactsOnCaffeineAndSoftDrinks. html Top 10 Reasons to Quit Coffee and Caffeine Consumption 1. Caffeine Sensitivity: There a significant number of people who are sensitive to caffeine and show number of reactions to caffeine such as jitters and sleeplessness. 2. No Weight loss diet: Many people drink coffee instead of having their proper meals hoping to loss weight faster. But it is just the opposite, the truth is many diet programs advise to eliminate caffeine from the diet in order to get better results. There are many documented reasons which show that caffeine interferes with weight loss programs. 3.

Nursing Mothers: Women who drink caffeine on regular basis or have high consumption of caffeine are often told by their doctors to quit caffeine for well being of their baby. 4. Health Reasons: Many people experience headaches and increased level of stress resulted from caffeine consumption. 5. Aging: Caffeine is a known culprit in speeding the aging process. There are many which show the caffeine consumption could speed up the aging process. 6. Stress: Caffeine stimulates hormones like cortisol which not only have drastic impact on our nervous system but also have long term consequences and one of them is aging. . Fatigue: Intake of caffeine gives you an instant jolt of brain alertness but this is a short lived feeling which is soon followed by fatigue and energy loss. 8. Bone loss: Consumption of caffeine accelerates calcium loss and eventually cause bone loss. 9. Heart disease and high blood pressure: Coffee consumption and caffeine intake can make many of us vulnerable to heart diseases and raise blood pressure. 10. Short-term memory loss: Many believe that consumption of coffee and caffeine can result in short-term memory loss or recalling or retaining information. http://www. chaimedia. com/list/500. tml ————————————————- http://psychology. okstate. edu/faculty/leffingwell/bcl/resources/presentations/thompsen_honors. pdf PEDIATRICS Vol. 111 No. 1 January 2003, pp. 42-46 Caffeine Consumption and Weekly Sleep Patterns in US Seventh-, Eighth-, and Ninth-Graders Charles P. Pollak, MD* and David Bright * From the Division of Sleep Medicine, Department of Neurology, Ohio State University, Columbus, Ohio Objective. To survey caffeine use by seventh-, eighth-, and ninth-graders and relate its use to age, sex, sleep characteristics, and day of week Methods.

Students kept a daily, 2-week diary of their sleep times and use of caffeine containing drinks and foods. Data were analyzed by fitted multiple regression models Results. A total of 191 students participated. Caffeine intake ranged between 0 and 800 mg/d. Mean use over 2 weeks ranged up to 379. 4 mg/d and averaged 62. 7 mg/d (corrected for underrepresentation in our sample of boys, who consumed more caffeine). Higher caffeine intake in general was associated with shorter nocturnal sleep duration, increased wake time after sleep onset, and increased daytime sleep Sleep Patterns.

Mean bedtime was 10:57 PM, and mean wake time was at 7:14 AM. Older children delayed bedtime longer on weekends, and younger ones had longer nightly sleep durations. Sleep duration lengthened on weekends, reflecting the combined effects of the circadian timing system and a mechanism that regulates the duration of sleep. Caffeine (soda) consumption also increased on weekends, for reasons that may be primarily social Conclusions. Regardless of whether caffeine use disturbed sleep or was consumed to counteract the daytime effect of interrupted sleep, caffeinated beverages had detectable pharmacologic effects.

Limitation of the availability of caffeine to teenagers should therefore be considered. Key Words: caffeine • sleep • soda • coffee • teenagers • adolescents Abbreviations: WASO, wake time after sleep onset Received for publication Jan 28, 2002; Accepted Jun 13, 2002. ————————————————- http://pediatrics. aappublications. org/cgi/content/abstract/111/1/42? etoc Caffeine Consumption, Sleep, and Affect in the Natural Environments of Depressed Youth and Healthy Controls* Diana J. Whalen, BS1,2, Jennifer S.

Silk, PhD1,2, Mara Semel, MS2, Erika E. Forbes, PhD1,2, Neal D. Ryan, MD2, David A. Axelson, MD2, Boris Birmaher, MD2 and Ronald E. Dahl, MD1,2 1Department of Psychology, University of Pittsburgh and 2Department of Psychiatry, University of Pittsburgh School of Medicine All correspondence concerning this article should be addressed to Jennifer S. Silk, Department of Psychiatry, University of Pittsburgh, 3811 O’Hara St, Pittsburgh, PA, 15260. E-mail: [email protected] edu |    Abstract | Top Abstract Method Results Discussion Acknowledgments References |

Objective Sleep problems are a cardinal symptom of depression in children and adolescents and caffeine use is a prevalent and problematic issue in youth; yet little is known about caffeine use and its effects on sleep in youth with depression. We examined caffeine use and its relation to sleep and affect in youth’s natural environments. Methods Thirty youth with major depressive disorder (MDD) and 23 control youth reported on caffeine use, sleep, and affect in their natural environment using ecological momentary assessment at baseline and over 8 weeks, while MDD youth received treatment.

Results Youth with MDD reported more caffeine use and sleep problems relative to healthy youth. Youth with MDD reported more anxiety on days they consumed caffeine. Caffeine use among youth with MDD decreased across treatment, but sleep complaints remained elevated. Conclusions Findings suggest that both sleep quality and caffeine use are altered in pediatric depression; that caffeine use, but not sleep problems, improves with treatment; and that caffeine may exacerbate daily anxiety among youth with depression.

Key words: caffeine; depression; ecological momentary assessment; sleep. Caffeine is the most widely consumed stimulant in the US and perhaps the world (Barone ; Roberts, 1996). In adults, caffeine can affect arousal (Barry et al. , 2005; Lyvers, Brooks, ; Matica, 2004), attention (Lorist ; Tops, 2003; Yeomans, Ripley, Davies, Rusted, ; Rogers, 2002), reaction time (Childs ; deWit, 2006; Kenemans ; Lorist, 1995), and sleep (for a review, see Boutrel ; Koob, 2004; Drapeau et al. , 2006).

Those same effects on youth, however, have received little empirical study (for a review, see Hughes ; Hale, 1998). Work in this area is a crucial undertaking, given that many youth use caffeine daily and caffeine use is associated with poor sleep and daytime fatigue (National Sleep Foundation, 2006; Rapoport, Berg, Ismond, Zahn, ; Neims, 1984; Rapoport, Elkins, Neims, Zahn, ; Berg, 1981). Understanding caffeine’s effects on sleep is particularly important in clinical disorders, such as depression, in which sleep difficulties are important features.

The aim of the current study was to examine relationships between caffeine use and sleep in healthy and depressed youth using a natural approach to gather real-time information on how youth sleep and utilize caffeine in their daily lives. Epidemiological work suggests that caffeine use in youth is worthy of empirical attention. 75–98% of youth consume at least one caffeinated beverage daily (Morgan, Stults, & Zabnick, 1982; National Sleep Foundation, 2006), with 31% reporting more than two per day (National Sleep Foundation, 2006).

These rates approach the levels consumed by adults (Hughes & Oliveto, 1997). The subjective effects of high caffeine doses on youth are similar to those found in adults, such as nervousness and nausea (for a review, see Hughes & Hale, 1998). Behaviorally, caffeine use in youth has also been shown to improve performance on attention-related tasks. Children show improved performance and decreased self-reported “sluggishness” following moderate levels of caffeine consumption (Bernstein et al. , 1994).

On the other hand, when children who are regular caffeine users are asked to abstain, they report higher levels of negative affect (Goldstein & Wallace, 1997) and show decreased reaction times (Bernstein et al. , 1998), suggesting those complex cycles of caffeine dependence can be set into motion even in childhood and adolescence. Although less widely researched, caffeine may also play a cyclical role in affect regulation. Caffeine can contribute to arousal, anxiety, and irritability, thus exacerbating negative affect states (Brice & Smith, 2002; Childs & deWit, 2006; Smith, Sutherland, & Christopher, 2005).

On the other hand, individuals may attempt to use caffeine as an affect regulator, much as they use other stimulants, such as cigarettes. Caffeine is a widely available, heavily marketed, and socially acceptable stimulant, even in child and adolescent populations. Caffeine may be particularly appealing to depressed youth seeking a “lift” due to fatigue or negative affect. In support of this speculation, self-reported anxious and depressive symptoms have been found to be elevated in adolescents with caffeine dependence (Bernstein et al. 1994; Bernstein, Carroll, Thuras, Cosgrove, & Roth, 2002). To address this question in our sample, we examined whether youth with depression used more caffeine than healthy controls and whether their caffeine use was associated with daily fluctuations in affect. Caffeine use may have an important association with sleep quality. There is also evidence that, like adults (National Sleep Foundation, 2001), youth use caffeine to counteract daytime sleepiness. Caffeine use in youth tends to increase after Wednesday, peak on Saturday, and then decline (Pollack & Bright, 2003).

In fact, adolescents who drank two or more caffeinated beverages a day were more likely to report an insufficient amount of sleep on school nights, a self-described sleep disturbance, and problems related to drowsiness, than those who drank one or less (National Sleep Foundation, 2006). In addition, children who were heavy caffeine users reported an increase in sleep disruption following a day of caffeine consumption (Pollack & Bright, 2003). This finding demonstrates the potential for caffeine consumption to contribute to cycles of sleep disruption in youth. The second focus of our study was on youth’s sleep ehaviors in the natural context. Youth with major depressive disorder (MDD) frequently complain of sleep disturbances, regardless of caffeine use (Bertocci et al. , 2005; Ryan et al. , 1987). A large body of literature implicates sleep dysregulation in adult depression, with several studies suggesting that sleep difficulties precede the onset of depressive disorders (for a review, see Riemann ; Voderholzer, 2003). Sleep complaints are extremely common in children and adolescents with MDD, with as many as 90% reporting significant sleep problems (Ryan et al. , 1987).

Reported sleep problems have included hypersomnia, nighttime awakenings, daytime sleepiness, and circadian reversal (Dahl et al. , 1996). In a previous study, our group found that children and adolescents with depression, compared to controls, reported significantly worse subjective sleep in terms of sleep quality, number of awakenings, minutes awake, and ease of waking (Bertocci et al. , 2005). The current study extends this work by examining group differences in subjective sleep behaviors in the natural environments of healthy and depressed youth over several months, as well as how these sleep behaviors are related to caffeine consumption.

A final, more exploratory goal was to examine whether subjective sleep and caffeine use change across the course of treatment for youth with depression. Although caffeine consumption is not specifically targeted in treatments for depression, it may change as participants stabilize and normalize their affect states and daily activities as a function of treatment via medication or psychosocial therapy. Alternatively, more specific treatments (or adjunctive treatment) addressing these behaviors may need to be developed.

To the extent that sleep and caffeine behaviors are altered in pediatric depression, it will be important to understand whether standard treatments for these disorders impact these behaviors. This study represents a preliminary step toward addressing this question. To address these questions, we utilized Ecological Momentary Assessment (EMA) to objectively measure affect, behavior, and caffeine use in the home environment. EMA is an ecologically valid method of gathering representative real-time data on affect and behavior in natural environments through the use of signaling devices (Axelson et al. 2003; Larson, Csikszentmihalyi, ; Graef, 1980; Shiffman et al. , 2006; Silk, Steinberg, ; Morris, 2003). EMA can provide more accurate and objective data on day-to-day shifts in caffeine consumption and sleep, but has not been applied to examining these behaviors in youth with depression. In fact, most studies have relied on retrospective reports of caffeine intake and sleep habits—methods limited by memory biases. In summary, this study builds on previous research to address four questions: (a) Do youth with depression use more caffeine in their daily lives than healthy youth? (b) Do youth with depression report poorer sleep in their daily lives than healthy youth? ; (c) How is daily caffeine use related to sleep and affect? ; and (d) Do sleep and caffeine use change as youth with MDD go through treatment? We hypothesized that youth with MDD would report greater caffeine use and subjective sleep problems than healthy youth, that caffeine use would be associated with greater sleep problems that night and greater negative affect that day, especially for youth with MDD, and that both sleep and caffeine use would improve throughout treatment.    Method | Top Abstract Method Results Discussion Acknowledgments References | Participants This report includes data from 53 youth participating in a longitudinal clinical assessment study of neurobehavioral factors in pediatric affective disorder (Birmaher et al. , 2000). Participants (34 females) ranged in age from 7–17 years (M = 12. 44, SD = 2. 88). Participants were divided into two groups based on current psychiatric diagnoses: MDD n = 30; and healthy controls n = 23.

Sixty-three percent of participants with depression had a current comorbid anxiety disorder (Separation Anxiety Disorder, Generalized Anxiety Disorder, or Social Phobia) and 43% had a current comorbid behavioral disorder (Conduct Disorder, Oppositional Defiant Disorder, or Attention-deficit Hyperactivity Disorder). The retention rate was 70% and there were no demographic or clinical differences between subjects retained and not retained in the study (Birmaher et al. , 2004). Inclusion Criteria

Youth with MDD met diagnostic criteria according to DSM-III-R (American Psychiatric Association, 1987) or DSM-IV (American Psychiatric Association, 1994) classification. All participants diagnosed with a psychiatric disorder received an 8-week treatment course consisting of Selective Serotonin Reuptake Inhibitors (SSRI’s; n = 9) and/or Cognitive Behavioral Therapy (CBT; n = 8), or both (n = 13). The SSRI’s included citalopram 10–40 mg (n = 8), escitalopram 5 mg (n = 1), and fluoxetine 5–25 mg (n = 10). Medication data were missing for three subjects. Healthy control youth were required to be free of any lifetime psychopathology.

In addition, they were required to have no first-degree relatives with a lifetime episode of any mood or psychotic disorder; no second-degree relatives with a lifetime history of childhood-onset, recurrent, psychotic, or bipolar depression or schizoaffective or schizophrenic disorder; and no ;20% of second-degree relatives could have a lifetime episode of MDD. Exclusion Criteria Since the youth in this study were originally recruited to participate in a broad set of biological protocols including hormonal challenge probes and sleep electroencephalogram (Birmaher et al. 2000, 2004), the following exclusionary criteria applied at the time of the initial interview: (a) the use of any medication with central nervous system effects within the past 2 weeks or any lifetime use of fluoxetine (no subjects were taking serotonin reuptake inhibitors, stimulants, or other antidepressant medications); (b) significant medical illness; (c) extreme obesity (weight ;150% of ideal body weight) or growth failure (height or weight below the third percentile); (d) IQ of 70 or less; (e) inordinate fear of intravenous needles (because of the need to draw blood for biological assays); and (f) specific learning disabilities.

Subjects with depression were also excluded if they had schizophrenic, schizoaffective, and bipolar disorders. Procedures The study was approved by the university’s Institutional Review Board. Participants were recruited from three sources: (a) community advertisements (primarily radio and newspaper ads), (b) inpatient and outpatient clinics at a major medical center in which the youth or their parents were being treated, and (c) referrals from other research studies or other participants in the present study.

Youth and their parents were required to sign assents and informed consents, respectively. Structured diagnostic interviews were administered to establish lifetime and present youth psychiatric diagnoses and familial history of affective disorder. Qualifying participants were invited to participate in a multifaceted protocol that included: (a) for participants with MDD, an 8-week open treatment protocol using CBT and/or SSRI’s; (b) for all participants, a visit to the neurobehavioral laboratory during the baseline weekend of the study (Forbes et al. , 2006; Ladouceur, et al. 2005); and (c) also for all participants, a home assessment protocol that included EMA and measures of sleep in the natural environment collected in biweekly intervals over the 8-week course of the study. The focus of this report is on data collected through the home assessment protocol. Instruments Structured Diagnostic Interviews Each youth and his or her parent(s) were interviewed to determine the youth’s psychiatric history using the Schedule for Affective Disorders and Schizophrenia in School-Age Children—Present and Lifetime version (K-SADS-PL, Kaufmann, Birmaher, Brent, & Rao, 1997).

Parents and youth were interviewed separately, with clinical interviewers integrating data from both informants to arrive at a final diagnosis. To determine familial loading for mood disorders, parents were interviewed using the Structured Clinical Interview for the DSM-IV (Spitzer, Williams, Gibbon, & First, 1990). Other adult first-degree and second-degree relatives were assessed indirectly using a modified version of the Family History Interview (Weissman et al. , 1986), with the youth’s parent(s) and other available relatives serving as informant(s). All interviews were carried out by trained BA- and MA-level research clinicians.

Inter-rater reliabilities for diagnoses assessed during the course of this study were estimated to be k 0. 70. The results of the interview were presented at a consensus case conference with a child psychiatrist, who reviewed the findings and preliminary diagnosis and provided a final diagnosis based on DSM-III-R or DSM-IV criteria. Subjective Sleep Ratings All youth completed one subjective sleep report each day collected in biweekly intervals for five extended weekends (Friday through Monday) beginning at baseline and across the 8-week treatment period (n = 20 per participant).

The subjective sleep reports included the participant’s estimates of (a) sleep quality (the level of restfulness the youth felt upon awakening), (b) ease of waking (the level of difficulty the youth had waking up), (c) the number of minutes to fall asleep, (d) the number of nighttime awakenings, (e) the number of minutes awake during the night, (f) bedtime, (g) total sleep time, and (h) morning wake time (Bertocci et al. , 2005). For some analyses, weekend totals were created by averaging responses that occurred during each day of the assessment weekends.

Ecological Momentary Assessment As part of a larger study, all participants completed an EMA protocol designed to provide real-time data on behavior, emotion, and social context in the child’s natural environment. Participants were given answer-only cellular phones on which they received calls from a trained staff member for five extended weekends beginning at baseline and across an the 8-week treatment period (Axelson et al. , 2003). Participants were called 12 times between 4 p. m. Friday and 10 p. m. Monday each weekend, for a total of 60 calls in 8 weeks.

Participants received two calls on Friday and Monday and four calls on Saturday and Sunday. Each call consisted of a brief structured interview to evaluate current behavior, affect, and social context. The present report focuses on affect ratings and caffeine consumption from the calls obtained during each extended weekend. At each call, participants were asked to rate their current affect on a subset of 5-point scales from the Positive and Negative Affect Schedule for Children (PANAS-C; Laurent et al. , 1999). Ratings were obtained for four negative emotions (“sad,” “angry,” “nervous,” and “upset”).

During the last call of each day, participants were asked, “Have you had any caffeine today? ” followed by “How many servings of caffeine did you have? ” For some analyses, weekend totals were created by averaging responses that occurred during each day of the assessment weekends. Plan of Analyses Data were analyzed using repeated measures linear mixed effects models to account for the nesting of assessments within subjects and across time. Because data on sleep and caffeine use were collected at one call per day, data were analyzed at the level of day rather than call.

Data on affect were averaged across the 2–4 sampling points per day to create corresponding measures of daily affect. All mixed effects models included subject as a random effect and day as a repeated measure. Fixed effects were included for week (0, 2, 4, 6, or 8), diagnostic group, caffeine use, and/or subjective sleep, depending upon the specific hypothesis tested, as described subsequently. Preliminary analyses indicated that there were no significant differences in age (t[51] = –1. 74; NS) or gender (; NS) across diagnostic groups, therefore these variables were not included as covariates in the mixed models.

Effect sizes for primary analyses were calculated using Effect Size Generator-Pro (Devilly, 2005). |    Results | Top Abstract Method Results Discussion Acknowledgments References | Caffeine Consumption Independent samples t-tests revealed no gender differences in caffeine consumption (t[63] = 0. 66; NS; 95% confidence interval [CI] = –2. 52–4. 98); age was correlated with caffeine consumption (r = 0. 34, p ; . 01). Thus, age was included as a covariate in subsequent analyses. A mixed effects model was computed examining the relationship between the numbers of affeinated beverages consumed per day, diagnostic group, and week in the study. We also examined the interaction between diagnosis and week to test for treatment related changes in caffeine use, as only the group with MDD would be expected to show changes over time since the control group was not enrolled in any form of treatment throughout the study. This analysis revealed a main effect for group (F(1,504) = 14. 12; p ; . 001; 95% CI = –. 45 to . 01; d = 1. 06) indicating that youth with depression consumed greater amounts of caffeine per day across the study than healthy controls (Table I).

To determine whether this main effect was driven by comorbid anxiety disorders in the sample, we computed a mixed effects model that added anxiety as a covariate. This analysis revealed a main effect for anxiety (F(1,208) = 15. 27; p ; . 001; 95% CI = . 01 to . 02; d = 1. 1) indicating that youth with depression and comorbid anxiety disorders consumed greater amounts of caffeine per day across the study than those without comorbid anxiety disorders. View this table: [in this window] [in a new window] | Table I. Mean Reports of Sleep and Caffeine Use in the Natural Environment by Diagnostic Group at Baseline and Week 8| There was also an interaction between group and week (F(4, 236) = 2. 56; p ; . 05; 95% CI = Week 0 –. 52 to . 28, Week 1 –. 20 to . 46, Week 3 –. 60 to . 08, Week 5 –. 08 to . 52) in predicting caffeine use. To interpret this interaction, we conducted mixed effects models predicting caffeine use from week separately for each diagnostic group. This analysis indicated that week in the study was a predictor of caffeine use for youth with MDD (F(1, 157) = 11. 85; p ; . 001; 95% CI = Week 0 –. 09 to . 56, Week 1 –. 23 to . 29, Week 3. 04 to . 59, Week 5 –. 35 to . 10; d = . 55) but not for controls (F(1, 43) = 2. 2; NS; 95% CI = Week 0. 02 to . 30, Week 1. 06 to . 36, Week 3 –. 05 to . 19, Week 5 –. 02 to . 26; d = . 44). To examine the direction of this effect, we plotted mean caffeine use across each weekend in the study separately for each diagnostic group. As shown in Fig. 1, caffeine use decreased across the 8-week treatment protocol for youth with MDD, but not controls. There were no significant differences in posttreatment caffeine consumption among youth with MDD receiving CBT, SSRI, or CBT + SSRI treatment (F [2, 27] = 0. 27; NS; 95% CI = 0. 22 to 3. 04). View larger version (13K): [in this window] in a new window] [Download PowerPoint slide] | Figure 1 Changes in caffeine use across treatment. | | Subjective Sleep Reports A series of mixed effects models were computed predicting subjective ratings of sleep quality from diagnostic group, week in the study, and the interaction between diagnosis and week in the study. These analyses revealed main effects for group indicating that youth with MDD reported taking longer to fall asleep (F(1, 548) = 56. 42; p ; . 001; 95% CI = –17. 22 to –4. 94; d = . 64), more nighttime awakenings (F(1, 569) = 64. 13; p ; . 001; 95% CI = –. 75 to –. 20; d = . 5, more difficulty waking up (F(1, 765) = 29. 97; p ; . 001; 95% CI = 1. 22 to 19. 71; d = . 51) and a lower rating of overall subjective sleep quality (F(1, 682) = 51. 12; p ; . 001; 95% CI = . 69 to 17. 88; d = . 67) than healthy controls. These analyses also revealed a general trend for subjective ratings of sleep to improve across the course of this study, with main effects of week for time to fall asleep (F(4, 326) = 3. 49; p ; . 01; 95% CI = Week 0 –0. 43 to 16. 66, Week 1 6. 24 to 22. 48, Week 3 –6. 12 to 4. 98, Week 5 –8. 19 to 2. 89; d = . 53), nighttime awakenings (F(4, 255) = 4. 92; p ; . 01; 95% CI = Week 0. 37 to . 99, Week 1. 13 to . 72, Week 3 –. 22 to . 34, Week 5 –. 36 to . 31; d = . 63), and overall subjective sleep quality (F(4, 263) = 3. 71; p ; . 01; 95% CI = Week 0 –11. 96 to 3. 69, Week 1 –15. 53 to –. 15, Week 3 –3. 54 to 10. 82, Week 5 –6. 33 to 8. 99; d = . 54) (Table I). To determine whether these main effects were driven by comorbid anxiety disorders in the sample, we computed mixed effects models that added anxiety as a covariate. These analyses revealed a main effect for anxiety indicating that depressed youth with comorbid anxiety disorders reported more nighttime awakenings (F(1,307) = 6. 4; p ; . 05; 95% CI = . 00 to . 02; d = . 73), more difficulty waking up (F(1, 385) = 8. 23; p ; . 01; 95% CI = . 08 to . 45; d = . 81), and a lower rating of overall subjective sleep quality (F(1, 373) = 10. 95; p ; . 001; 95% CI = . 11 to . 42; d = . 93) across the study than those without comorbid anxiety disorders. However, there were no weeks by diagnosis interactions predicting any of the sleep variables, suggesting that sleep did not improve as a function of treatment for depression.

Furthermore, t-tests conducted on sleep variables aggregated across the posttreatment weekend indicated that at the end of treatment, youth with MDD reported greater minutes to sleep (t[29] = –2. 29; p ; . 05; 95% CI = –21. 51 to –1. 23; d = . 65) and lower sleep ratings (t[44] = 2. 34; p ; . 05; 95% CI = 1. 89 to 25. 51; d = . 66) than healthy youth. There were no significant differences among youth with MDD receiving CBT, SSRI, or CBT + SSRI treatment in posttreatment subjective sleep rating (F[2, 22] = 0. 32; NS; 95% CI = 58. 44 to 76. 04), minutes to sleep (F[2, 19] = 3. 55; p = . 05; 95% CI = 11. 6 to 30. 66), times awake (F[2, 17] = 0. 57; NS; 95% CI = 1. 87 to 6. 33), and difficulty waking (F[2, 20] = 0. 62; NS; 95% CI = 51. 37 to 71. 50). Relationships Between Caffeine Use and Sleep Next, we examined the relationship between youth’s caffeine use and subjective ratings of their sleep in the natural environment. Because of the potential bidirectional relationships between sleep and caffeine use, we tested two sets of lagged linear mixed effects models: (a) subjective sleep predicting caffeine use the next day, and (b) caffeine use during the day predicting that night’s sleep ratings.

Mixed models included fixed effects for diagnostic group, sleep or caffeine use, and the interaction between the two. There were no significant main effects or interactions in any of the models testing whether subjective sleep predicted caffeine use the next day (all p’s >. 05). There were also no main effects or interactions in the models testing whether caffeine use during the day predicted that night’s sleep ratings (all p’s > . 05), with the exception of a trend for greater caffeine use during the day to predict more nighttime awakenings that night (F(1, 350) = 3. 23; p = . 07; 95% CI = –. 2 to . 00; d = . 19). Relationships Between Caffeine Use and Negative Affect Finally, we examined whether caffeine use was associated with youth’s negative affect. Separate models were computed for each of the four negative affect scales: “sadness,” “anger,” “nervous,” and “upset. ” Mixed effects models included main effects for number of caffeinated beverages and diagnostic group as well as the interaction between caffeine consumption and diagnostic group predicting mean levels of negative affect across the day. Caffeine use was not related to sadness, anger or feeling upset (all p’s >. 5), however, there was an interaction between diagnostic group and caffeine use in predicting youth’s feelings of nervousness (F(1, 638) = 6. 02; p ; . 05; 95% CI = –. 12 to –. 01; d = . 69). To interpret this interaction, we conducted mixed effects models predicting nervousness from caffeine use separately for each diagnostic group. This analysis indicated that daily caffeine use was positively associated with daily nervousness for youth with MDD (coefficient = . 03, t[160] = 2. 99, p ; . 01; 95% CI = . 01 to . 04) but not for controls (coefficient = –. 2, t[46] = –1. 56, p = . 13; 95% CI = –. 04 to . 01). |    Discussion | Top Abstract Method Results Discussion Acknowledgments References | This is the first study of which we are aware to assess both caffeine use and sleep in the natural environments of youth with depression. We found significant differences between healthy and depressed youth in caffeine use and sleep during the baseline weekend before the youth with depression received therapy and/or medication. These differences in caffeine use diminished during the course of treatment. Even though the youth were not xplicitly told to abstain from caffeine during treatment, those with MDD experienced a 4-fold decrease in caffeine consumption across treatment. However, daily sleep did not improve as a function of treatment for depression. The finding that youth with depression used more caffeine than healthy controls at baseline suggests that youth with MDD may use caffeine to help treat symptoms of depression. This is especially interesting given that these differences were found before the youth with MDD began therapy and/or medication. Youth with depression often lack energy and complain of chronic tiredness.

These youth may self-medicate with caffeine to increase alertness (Goldstein, Kaizer, ; Whitby, 1969; Rapoport et al. , 1984). The stimulating effect of caffeine is necessarily followed by a period of withdrawal and return to the original state of low energy, and many youth counter these effects by consuming more caffeine (Goldstein, 1987). This cycle may contribute to increased negative affect and depressive symptoms, particularly during the withdrawal period. However, contrary to our hypotheses, caffeine use and sleep were not directly related to each other.

We found that youth who used more caffeine did not report more trouble sleeping that night, with the exception of a trend for youth who used more caffeine to report more awakenings that night. Surprisingly, youth who had more trouble sleeping did not report using more caffeine the next day. This finding suggests that the youth in our sample were not using caffeine to combat sleepiness specifically associated with poor sleep the previous night, although it is still possible that they were experiencing generalized fatigue and low energy associated with depression.

It is also possible that the timing of caffeine use may impact sleep differently. For example, caffeine use in the evening may be more related to sleep difficulties than caffeine use in the morning. This should be assessed in future studies. Another possibility is that youth with depression were attempting to utilize caffeine as an affect regulator. The finding that, among youth with MDD only, caffeine use was associated with greater nervousness on the same day supports the suggestion that caffeine plays a role in the regulation of anxiety for youth with MDD.

Unfortunately, because we only assessed caffeine use once a day, we are not able to disentangle whether nervous affect led to greater use of caffeine, or whether greater use of caffeine led to greater nervousness among youth with depression. In fact, it is likely that bidirectional relationships exist between caffeine use and nervousness in youth with depression that can lead to a spiraling of irritability and anxious arousal. It seems that comorbid anxiety disorders in the youth with MDD were driving the overall effect of diagnosis. This further supports our speculation that caffeine may be used as an affect regulator.

In addition, healthy youth with higher levels of anxiety may consume higher levels of caffeine. It will be important for future studies to address whether youth are using caffeine because they are anxious, or whether they are anxious because they are using caffeine. Youth may also use caffeine for other reasons unrelated to sleep, such as fitting in with peers or attempting to increase positive emotion or arousal. To tap into youth’s motivation for using caffeine, future research should focus on the type and amount of caffeine youth use in different environments.

For example, adolescents may be more likely to drink soda or coffee when socializing with friends. It would also be interesting to ask youth their reasons for choosing to use or not use caffeine at a given time, as well as to examine parents’ role in influencing their youth’s caffeine consumption. It is important to note that we found group differences in caffeine use even though we did not select youth for the study based on a history of high caffeine consumption. Many studies examining caffeine in youth have selected samples with moderate to high levels of caffeine consumption (Bernstein et al. 1998, 2002; Orbeta, Overpeck, Ramcharren, Kogan, ; Ledsky, 2006). In our study, at baseline, our healthy controls were consuming an average of one caffeinated beverage per weekend and our youth with depression were consuming an average of five per weekend. In comparison, most research on caffeine use in youth has only studied those reporting more than one drink per day or after the laboratory administration of high caffeine doses. Thus, it is possible that we would have found stronger relations between sleep and caffeine use in a sample that was selected specifically for higher rates of caffeine consumption.

It is particularly intriguing that caffeine use in youth with depression improved over the course of treatment, despite the fact that these youth were involved in heterogeneous treatments, including cognitive behavioral therapy and medication management with selective serotonin reuptake inhibitors. This decrease in caffeine use occurred naturally and was not recommended as part of either treatment course. As both type of treatments are presumed to decrease reactivity to and increase ability to cope with negative emotion, this may be one mechanism through which they also contribute to decreased caffeine consumption.

Another possible mechanism is improvements in energy and motivation. Future research using larger samples and more homogeneous treatment modes are, however, needed to replicate and explore this finding. Consistent with previous reports (Bertocci et al. , 2005), the results of this study also show that youth with depression rate their sleep as more disrupted than control youth when asked to subjectively assess their sleep. This finding expands upon previous studies by showing that subjective sleep disturbances are present in the home environment across a 2-month window of time.

Furthermore, we found that although all the youth in the study showed a tendency to rate their sleep as somewhat improved across the 2-month window, there was no improvement specific to being in treatment, and youth with depression still showed several elevated sleep complaints relative to healthy controls following treatment. There are several potential reasons that subjective sleep difficulties persist after treatment for depression. First, after only 8 weeks of treatment, youth in the MDD group may still be in the process of recovery and their sleep patterns may not have returned to normal.

Just as it takes a while for sleep patterns to become dysregulated, it may also take a while for them to become regulated. Second, sleep problems could be trait markers that precede the development of MDD and persist after recovery (Ford ; Patrick, 2001). Finally, it may be necessary to develop adjunctive sleep treatments to enhance the effectiveness of depression treatment programs in eliminating sleep problems in youth with depression. Several limitations of the present study should be addressed.

First, because the MDD sample was relatively small, we were unable to conduct comparison analyses based on the type of treatment received or type of SSRI. The majority of youth with depression in our sample were prescribed SSRI’s and we lacked statistical power to determine whether the types of SSRI’s impact sleep and caffeine use differently. Since anxiety was only assessed in youth with MDD, we were unable to determine whether higher levels of anxiety in healthy youth may impact their caffeine consumption. We included a relatively broad age range and were not able to test interactions between diagnostic group, gender, and development due to ample size limitations. Also, because this project utilized subjective reporting of sleep and caffeine use, there was no objective confirmation of caffeine intake. In addition, youth were required to make their own interpretations on what products contain caffeine, since a list of items containing caffeine was not provided. Finally, we did not collect information on the specific type of caffeine consumed (e. g. , coffee vs. soda) or the exact timing of caffeine consumption, which could have differential effects on affect and sleep, and should be explored in future research. The study also has several strengths.

It utilized an innovative, intensive EMA protocol providing daily use data on caffeine consumption and its links to sleep patterns and daily affect. The study advances previous work in this area by focusing on a rigorously diagnosed clinical sample of youth with depression and utilizing an approach that provides data collected in natural home environments over an extended period of time, and throughout a course of clinical treatment. These findings have potential clinical and methodological implications, suggesting that EMA is a useful approach for understanding sleep and caffeine related-behaviors.

Findings suggest that caffeine consumption may have a role in the clinical presentation of depression, and perhaps anxiety, and that it is sensitive to treatment, but that more work is needed to understand the role of treatment in improving sleep in youth with depression. |    Acknowledgments | Top Abstract Method Results Discussion Acknowledgments References | This research was supported by National Institute of Mental Health (NIMH) Grant P01 MH41712 (N. D. R. , PI, R. E. D. , Co-PI). We are grateful to Laura Trubnick, Michelle Bertocci, and the staff of the Child and Adolescent

Neurobehavioral Laboratory for their invaluable role in assessing the participants in this study. Conflict of interest: None declared. |    Footnotes | *A portion of this data was presented at the Society for Research in Child Development Biennial Meeting, March–April 2007, Boston, MA, USA. The author’s name has been updated. Received May 3, 2007; revision received August 23, 2007; accepted August 24, 2007 ————————————————- http://jpepsy. oxfordjournals. org/cgi/content/full/jsm086v2 Why Sleep Is Important For Your Health Category Rss Feed – http://www.

Journaland. com/rss. php? rss=89 By : Jose Bautista Submitted 2009-08-18 01:03:26 Sleep is very important for your health and when most individuals do not get enough sleep they turn to caffeinated and sugary products for an energy boost. However too much caffeine and sugar is actually damaging to your health in the long run. To be alert during the day and keep you body healthy you need about 8 hours of sleep each night. In order to stay alert during the day people will turn to caffeine and sugary products for energy. This coupled with the lack of sleep does even more damage to your system.

New scientific studies have concluded that consuming too much caffeine and sugar can have detrimental effects on your health. Sugar foods only provide a very short relief to your tiredness. When the sugar wears off you will crash and burn and be worse then you started. Most individuals find themselves to be even sleepier then before and much slower to react. Instead of sugar to keep you alert you should eat foods that combine some protein and carbohydrates. A great example is apple slices with peanut butter. Coffee is regularly consumed for the caffeine to get you going.

However the caffeine in the coffee you drank in the morning will stay in your body for up to 12 hours. The effects of that caffeine can last long after you have finished your coffee. If you have problems sleeping and drink a lot of coffee you should try not drinking coffee. If you feel you still need some caffeine in the morning then try chocolate or soda, as they have smaller amounts of caffeine. Even those that drink decaffeinated coffee are not safe because this type of coffee still has caffeine in it. The caffeine in decaffeinated coffee is equivalent to drinking a 12 ox coke.

Decaffeinated coffee is a good option for individuals that are not sensitive to caffeine. So to be healthy you need to try to cut the caffeine and get a full night’s sleep. If you have trouble falling asleep then exercise can help make you tired. Additionally try cutting down your coffee consumption and get a good night’s rest. Author Resource:- Visit us for more health and diet free resource. ————————————————- http://www. journaland. com/Art/23398/89/Why-Sleep-Is-Important-For-Your-Health. html Caffeine In Coffee and the Effect on our Bodies Health yahhu December 1st. 2008, 3:18pm

Millions of people consume coffee on a daily basis. This rich, smooth taste and the pick-me-up feeling that you can not drink the coffee beat. But what is the caffeine in each cup to our body? Here are the most common side effects of caffeine. Caffeine is a stimulant by the way have a strong effect on the central nervous system. These effects will begin as soon as 15 minutes after drinking up to six hours later. Caffeine can increase blood pressure, your body temperature, heart rate, blood flow to the skin and limbs, blood glucose, gastric acid secretion and as a diuretic. Negative effects of caffeine.

Moderate doses of more than two ounces 6 cups of coffee is very little or no adverse reaction. Excessive caffeine consumption has not been shown to increase the risk of irregular heartbeat, heart disease, high cholesterol, cancer, fibrocistica breast disease or infertility. * It increases your attention and motor activity. * Drinking coffee, contrary to what many think, is not helping when you sober drunk. * The sensitivity to caffeine may vary per person. Some may drink a couple of cups of coffee with almost no side effects. Others are so sensitive to even small doses of caffeine, which is inconvenient. Sensitive drinkers, more than 2 cups oz size of a suitcase at a time, it may be that insomnia, irritability, trembling hands, restlessness, irritability, headache, extra heartbeat and have a difficult time concentrating. * Other side effects, to feel in a temporary increase in blood pressure, respiratory rate and your metabolism. PMS symptoms in May, less conspicuous with caffeine. * Some of the serious long-term side effects of drinking more than ten cups of coffee a day can increase the acidity of stomach problems, design problems and changes in bowel habits. The caffeine may increase your vigilance, particularly in people tired. Caffeinated beverages can help you remain vigilant in the workplace or during the study. * The research by the National Institutes of Health (NIH) has determined there is no difference in how children and adults with caffeine. This means that the long dear the belief that caffeine causes hyperactivity or short attention extends in children is probably not the cause. Just use common sense, from your children to consume foods with a high content of caffeine, like any other food. The caffeine has no effect on reproduction in humans, including pregnant women need to consume products of caffeine in small doses. * The excessive consumption of caffeine can cause lack of sleep, because you might have a tendency to ignore the signs of fatigue from the body. * Too much caffeine can cause anxiety associated with emotions such as sweating, excessive nervousness and agitation. Caffeine is derived from the German word coffee and the French word cafe. You mean coffee. Caffeine is completely absorbed in the body within 30 to 45 minutes and the effects are usually taught in three hours.

Caffeine affects the state of mind, strength, stomach and intestinal cancer, brain activity and the vascular system of the body. E ‘dependence? That depends on who is asked. Some researchers believe that the effects of caffeine withdrawal include a broad spectrum of symptoms such as headache, fatigue, depression, concentration problems, dizziness or sleepiness, irritability and other symptoms similar. The symptoms began within 12-24 hours after abstinence from caffeine products and lasted only 2-9 days. The time that the tests show that some users in May, employees of caffeine.

Other research has found that caffeine is not addictive. Research shows that we have the desire to consume caffeine once again, just for good reasons, such as smell, taste and social aspects of the consumption of caffeine. They believe that caffeine product is only a habit, not a necessity. So if you drink Caffeinated beverages in moderation with which your watch or consume only a small amount to taste, we know what impact it can have on your body. ————————————————- http://www. yahhu. org/health/caffeine-in-coffee-and-the-effect-on-our-bodies. htm Ito ang HTML na salin ng http://web. xtension. uiuc. edu/regions/newsletters/archive/diabetes/pdf/diab-12-06-01-07. pdf. Kusang gumagawa ng mga html na salin ang G o o g l e para sa mga dokumento na nahanap namin sa web. Page 1| December 2006—January 2007 Lack of Sleep Affects Blood Glucose Levels During the holiday season, we often get less sleep than we should or than we would like. Can this affect your diabetes management? Yes! Inadequate sleep results in changes in glucose control in the body. Sleep deprivation (lack of sleep) can result in higher blood glucose levels because of increased production of glucose by the liver.

When sleep is fragmented, there is a release of hormones that can worsen blood glucose levels. Certain hormones related to stress may also become elevated, increasing blood glucose levels or affecting other body functions. What can you do to improve your sleep? Follow these guidelines for healthy sleeping: Sleep and wake at regular times. Sleep in your bed and avoid using the bed for activities such as watching television, balancing a checkbook, or working. Sleep in a quiet, dark room. Avoid strenuous exercise for about three hours before going to bed. Decrease or eliminate caffeine and nicotine.

Allow one hour to “unwind” before bedtime. For instance, have a routine before going to bed that is quieting, like reading a few pages, listening to music, or taking a warm bath. Avoid alcohol around bedtime because it can fragment sleep. Avoid napping after 4 P . M . Contributed by Shalini Manchanda, M. D. , College of Medicine, UIUC To receive this newsletter by mail, contact your local U of I Extension office. Written by Karen Chapman Novakofski Associate Professor of Nutrition www. extension. uiuc. edu Page 2| This information is for educational purposes only.

References to commercial products and trade names, and to web sites not affiliated with University of Illinois Extension, do not constitute endorsement by the University of Illinois and do not imply discrimination against other similar products or web sites that are not listed. Medication Update Insulin is needed to maintain blood glucose levels within a target range. Normally produced by the pancreas, those with diabetes may need to take insulin injections. Another hormone produced by the pancreas is amylin. Amylin works with insulin and helps to control how quickly glucose from meal enters the blood from the intestines. Researchers have found that some people with diabetes have too little amylin as well as too little insulin. A new medication has been approved that is a synthetic form of amylin, called Symlin. Those with diabetes who have difficulty achieving their target blood glucose levels although they follow their medication and dietary prescriptions might benefit from this new medication. Insulin levels usually are decreased, and amylin injections are prescribed before meals. Because amylin lowers blood glucose levels, careful self- monitoring of blood glucose evels is important. People with a history of low blood glucose probably should not take amylin. If you have questions about this new medication, talk to your health care provider or pharmacist. The Diabetes Menu Cookbook: Delicious Special-Occasion Recipes for Family and Friends by Barbara Scott-Goodman, Kalia Doner, and Judd Pilossof; 236 pages, hardcover. Published by John Wiley and Sons, 2006. This newest edition incorporates the most recent nutritional recommendations of the American Diabetes Association and explains the latest changes to the USDA food pyramid and what they mean for you.

My Diabetes Organizer: The Essential Planner and Record- Keeper for People with Type 2 Diabetes by Gina Barbetta and Valerie Rossi; 84 pages, spiral-bound. North Hill Publishing, 2006. Packed with charts, guides, and advice, this organizer helps to simplify the lives of people with diabetes. Patients can keep track of test results, contact information, and medication records. The organizer features 12-month check-up charts, and envelopes and pockets for bills and business cards. 2 The Difference Between Macro- and Micronutrients News and Resources

Food is made of nutrients. Sometimes these nutrients are divided into “macronutrients” and “micronutrients. ” Macronutrients are nutrients that provide calories (energy). Since “macro” means large, macronutrients are nutrients needed in large amounts. There are three categories of macronutrients: Carbohydrates, Proteins, and Fats. While each of these macronutrients provides calories, the amount of calories that each one provides varies. One gram of carbohydrate or protein provides 4 calories per gram. One gram of fat provides 9 calories per gram.

If you looked at the Nutrition Facts label of a food product and it said 12 grams of carbohydrate, 0 grams of fat, and 0 grams of protein per serving, you would know that this food has about 48 calories per serving (12 grams carbohydrate multiplied by 4 calories for each gram of carbohydrate = 48 calories). The only other substance that provides calories is alcohol, which provides 7 calories per gram. Alcohol, however, is not a macronutrient because we do not need it for survival. Micronutrients are nutrients that our bodies need in smaller amounts and include vitamins and minerals.

While micronutrients are needed for health, they do not provide calories. Page 3| 3 Holiday Broccoli Tomato Salad 7 1-cup servings 6? cups broccoli flowerets 1 teaspoon dried dill ? cup sun-dried tomatoes in oil, drained 4 ounces low-fat mozzarella cheese 2 tablespoons oil from tomatoes 1 tablespoon lemon juice Directions 1. Slice flowerets and tomatoes to about same size. Place in bowl. 2. Toss with lemon juice, add oil. 3. Cut cheese into cubes. Add to salad. Toss with dill. Per serving: 110 calories; 6 grams protein; 9 grams cholesterol; 0 grams fiber; 6 grams carbohydrate; 8 grams fat; 63% calories from fat; 113 mg. odium Recipe Corner Dark Chocolate Strawberry Fondue 16 servings, 3 strawberries each 48 strawberries 4 ounces unsweetened chocolate ? cup skim milk 5 tablespoons Splenda ® Directions 1. Place chocolate squares in a microwave-safe bowl and microwave on High in 1-minute increments until melted. 2. Whisk in milk and Splenda ® . 3. Dip strawberries, using about 1 teaspoon of chocolate fondue per berry. Per serving: 52 calories; 1 gram protein; 0 grams cholesterol; 2 grams fiber; 5 grams carbohydrate; 4 grams fat; 70% calories from fat; 6 mg. sodium Page 4| Inside . . . Lack of Sleep Affects Blood Glucose Levels

The Difference Between Macro- and Micronutrients Medication Update Recipes and Resources University of Illinois/U. S. Department of Agriculture/Local Extension Councils Cooperating University of Illinois Extension provides equal opportunities in programs and employment. Researchers in New Zealand analyzed 27 studies that included 1,003 patients to determine the effects of different types of exercise on hemoglobin A1C, a measure of how well a person’s blood glucose is controlled long term. The researchers found hemoglobin A1C levels fell by about 0. 8 percent in cases where the exercise was continued for 12 weeks or longer.

Combining aerobic exercise with resistance training had somewhat more of an effect on the hemoglobin A1C than either type of exercise alone. However, more intense exercise programs did not appear to be more effective. The researchers thought this may be because the more intense programs were more difficult for people to continue as a long-term lifestyle habit. ————————————————- http://docs. google. com/gview? a=v&q=cache:pQFHzM1MVoQJ:web. extension. uiuc. edu/regions/newsletters/archive/diabetes/pdf/diab-12-06-01-07. pdf+lack+sleep+blood+sugar&hl=tl&gl=ph

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