Rob M. van Dam

Intensive insulin therapy and mortality among critically ill patients: a meta-analysis including NICE-SUGAR study data

Background: Hyperglycemia is associated with increased mortality in critically ill patients. Randomized trials of intensive insulin therapy have reported inconsistent effects on mortality and increased rates of severe hypoglycemia. We conducted a meta-analysis to update the totality of evidence regarding the influence of intensive insulin therapy compared with conventional insulin therapy on mortality and severe hypoglycemia in the intensive care unit (ICU). Methods: We conducted searches of electronic databases, abstracts from scientific conferences and bibliographies of relevant articles. We included published randomized controlled trials conducted in the ICU that directly compared intensive insulin therapy with conventional glucose management and that documented mortality. We included in our meta-analysis the data from the recent NICE-SUGAR (Normoglycemia in Intensive Care Evaluation — Survival Using Glucose Algorithm Regulation) study. Results: We included 26 trials involving a total of 13 567 patients in our meta-analysis. Among the 26 trials that reported mortality, the pooled relative risk (RR) of death with intensive insulin therapy compared with conventional therapy was 0.93 (95% confidence interval [CI] 0.83–1.04). Among the 14 trials that reported hypoglycemia, the pooled RR with intensive insulin therapy was 6.0 (95% CI 4.5–8.0). The ICU setting was a contributing factor, with patients in surgical ICUs appearing to benefit from intensive insulin therapy (RR 0.63, 95% CI 0.44–0.91); patients in the other ICU settings did not (medical ICU: RR 1.0, 95% CI 0.78–1.28; mixed ICU: RR 0.99, 95% CI 0.86–1.12). The different targets of intensive insulin therapy (glucose level ≤ 6.1 mmol/L v. ≤ 8.3 mmol/L) did not influence either mortality or risk of hypoglycemia. Interpretation: Intensive insulin therapy significantly increased the risk of hypoglycemia and conferred no overall mortality benefit among critically ill patients. However, this therapy may be beneficial to patients admitted to a surgical ICU.

Adiponectin Levels and Risk of Type 2 Diabetes A Systematic Review and Meta-analysis

CONTEXT The association of obesity with development of type 2 diabetes may be partly mediated by altered secretion of adipokines by adipose tissue. Greater adiposity down-regulates secretion of adiponectin, an adipokine with anti-inflammatory and insulin-sensitizing properties. The strength and consistency of the relation between plasma adiponectin and risk of type 2 diabetes is unclear. OBJECTIVE To systematically review prospective studies of the association of plasma adiponectin levels and risk of type 2 diabetes. DATA SOURCES A systematic search of the MEDLINE, EMBASE, and Science Citation Index Expanded databases using adiponectin and diabetes and various synonyms and reference lists of retrieved articles up to April 10, 2009. STUDY SELECTION We included prospective studies with plasma adiponectin levels as the exposure and incidence of type 2 diabetes as the outcome variable. DATA EXTRACTION Two reviewers independently extracted data and assessed study quality. Generalized least-squares trend estimation was used to assess dose-response relationships. Pooled relative risks and 95% confidence intervals were calculated using random-effects models to incorporate between-study variation. RESULTS Thirteen prospective studies with a total of 14 598 participants and 2623 incident cases of type 2 diabetes were included in the meta-analysis. Higher adiponectin levels were monotonically associated with a lower risk of type 2 diabetes. The relative risk of type 2 diabetes was 0.72 (95% confidence interval, 0.67-0.78) per 1-log microg/mL increment in adiponectin levels. This inverse association was consistently observed in whites, East Asians, Asian Indians, African Americans, and Native Americans and did not differ by adiponectin assay, method of diabetes ascertainment, duration of follow-up, or proportion of women. The estimated absolute risk difference (cases per 1000 person-years) per 1-log microg/mL increment in adiponectin levels was 3.9 for elderly Americans and 30.8 for Americans with impaired glucose tolerance. CONCLUSION Higher adiponectin levels are associated with a lower risk of type 2 diabetes across diverse populations, consistent with a dose-response relationship.

Dietary Patterns and Risk for Type 2 Diabetes Mellitus in U.S. Men

The prevalence of type 2 diabetes mellitus is rapidly increasing in the United States (1, 2) and worldwide (3). Ecologic studies (4), migration studies (4, 5), and analyses of secular trends (4, 6) suggest that adoption of a western diet may be associated with increased incidence of type 2 diabetes. However, these studies could not separate the effects of diet from those of other risk factors, such as obesity and physical activity. Studies of the relation between diet and incidence of type 2 diabetes on an individual level have predominantly focused on intake of macronutrients and fiber (7). However, these dietary factors alone probably explain only part of the effect of diet on glucose metabolism. Other nutrients, additives, contaminants, and unknown compounds and the physical properties of foods and interactions between nutrients (for example, with respect to bioavailability) may play a role in the deterioration of glucose metabolism. Hence, the examination of effects of food consumption may be an important complementary approach. Recently, the analysis of patterns of food consumption by using factor analysis has emerged as a useful tool for elucidating relationships between diet and health (8-11). The overall dietary pattern may affect health more than individual foods and nutrients do. Furthermore, dietary patterns reflect the way foods are consumed in reality, which may provide insight into possibilities for dietary changes and may facilitate the translation of findings to public health recommendations. Recent dietary intervention studies have indicated that interventions focused on dietary patterns can decrease blood pressure (12) and reduce cardiovascular complications (13). Data on dietary patterns and risk for type 2 diabetes are sparse. Although two cross-sectional studies of dietary patterns and diabetes have been conducted (11, 14), these studies incompletely controlled for confounding by other lifestyle factors. Therefore, we prospectively examined the association between major dietary patterns and risk for type 2 diabetes in a large prospective study of U.S. professional men with extensive, repeatedly obtained information on diet and other lifestyle factors. Methods Participants The Health Professionals Follow-up Study started in 1986, when 51 529 male health professionals (dentists, veterinarians, pharmacists, optometrists, osteopathic physicians, and podiatrists) completed a detailed mailed questionnaire on medical history, diet, and other potential risk factors for major diseases. The participants lived in all 50 U.S. states, were predominantly white, and were 40 to 75 years of age in 1986. We excluded from the current analysis 1595 men who did not satisfy the a priori criteria of reporting daily energy intake of 3.3 to 17.6 MJ (800 to 4200 kcal/24 h) and leaving fewer than 70 responses blank of the 131 food items on the diet questionnaire (<5% had >11 blanks). We also excluded men who reported having diabetes, cardiovascular disease (myocardial infarction, angina pectoris, coronary artery surgery, or stroke), or cancer (except nonmelanoma skin cancer) at baseline because having these diagnoses may affect diet or reporting of diet. After exclusions, the study sample comprised 42 504 men, who were followed for incidence of type 2 diabetes and other diseases for 12 years (1986 to 1998). Every 2 years, the participants received questionnaires by mail that asked for updated information on exposures and newly diagnosed diseases. The follow-up rate for potential person-years was about 97% for nonfatal events. We identified deaths by reports from family members, coworkers, or postal authorities or through systematic searches of the National Death Index. Assessment of Dietary Patterns To assess dietary intake, we used a 131-item semiquantitative food-frequency questionnaire in 1986, 1990, and 1994. The questionnaire specified for each food a commonly used unit or portion size, and the participants were asked to indicate how often, on average, they had consumed a given amount of the specified food during the past year. Each such item provided nine possible responses, ranging from never or less than once a month to 6 or more times per day. To reduce within-respondent variation and to best represent long-term dietary habits, we averaged the dietary intakes from all available dietary questionnaires up to the start of each follow-up interval (the average of the 1986 and 1990 dietary intakes was related to incidence of type 2 diabetes between 1990 and 1994) (15). To identify dietary patterns, we applied factor analysis to data from the food-frequency questionnaire. First, we grouped the food items on the questionnaire into 37 predefined food groups. We combined food items that were similar in nutrient profile and culinary use (for example, spinach, iceberg or head lettuce, and romaine or leaf lettuce were combined into green leafy vegetables). We classified a food item individually if its composition differed substantially from that of other foods (for example, eggs or pizza) or if we suspected that it represents a particular dietary habit (for example, wine or French fries). Second, we applied the principal components program for factor analysis of SAS software (16) with varimax rotation to the 37 food groups. Factor analysis aggregates correlated variables. The obtained factors are linear combinations of the included variables, explaining as much of the variation in the original variables as possible. Our analysis retained two factors based on the eigenvalue of the factors, the Scree test, and the interpretability of the derived factors, and we labeled these diets as the prudent pattern and the western pattern (9). Third, for each participant, we calculated a prudent pattern score and a western pattern score by summing the standardized intake of foods, weighted by the factor loadings of the foods (17). We used these scores to rank participants according to the degree to which they conformed to each dietary pattern. We divided dietary pattern scores into quintiles; thus, on this basis of his scores, each participant was grouped in a prudent-pattern quintile and a western-pattern quintile. To test the validity and reproducibility of the assessment of the dietary pattern scores by the food-frequency questionnaire, we examined a subgroup of 127 participants (9). The Pearson correlation coefficient (corrected for week-to-week variation in the diet records) for a comparison between the responses to the food-frequency questionnaire and the diet records was 0.52 for the prudent dietary pattern and 0.74 for the western dietary pattern. Assessment of Nondietary Exposures The 1986 questionnaire and each biennial follow-up questionnaire assessed weight, smoking status, and physical activity. Participants provided information on age, diagnosis of hypertension and hypercholesterolemia, and height in 1986 and on family history of diabetes in 1987. The criterion for family history of type 2 diabetes was having at least one first-degree relative with a diagnosis of diabetes after 30 years of age. For each participant, we determined a physical activity level, measured in weekly metabolic equivalent hours, on the basis of reported time spent on various activities, which we weighted according to intensity level (18). The validity of self-reported weight (19) and physical activity (18) in this cohort has been reported previously. Ascertainment of Type 2 Diabetes Mellitus We mailed a supplementary questionnaire on symptoms, diagnostic tests, and medication use to participants who indicated on any biennial follow-up questionnaire that he had received a diagnosis of diabetes mellitus. Confirmation of diabetes required at least one of the following: 1) an elevated plasma glucose level (fasting plasma glucose level 7.8 mmol/L [ 140 mg/dL]; random plasma glucose level 11.1 mmol/L [ 200 mg/dL]; or plasma glucose level after 2 hours or more during an oral glucose tolerance test 11.1 mmol/L [ 200 mg/dL]) plus at least one classic symptom [excessive thirst, polyuria, weight loss, or hunger]; 2) at least two elevated plasma glucose levels measured on different occasions; or 3) treatment with insulin or oral hypoglycemic medication. We excluded men who reported having type 1 diabetes on the supplementary questionnaire. These criteria for diabetes are consistent with those from the World Health Organization in 1985 (20). We did not use the current diabetes classification of the American Diabetes Association (21) because among the men in our study, most cases of diabetes were diagnosed before these criteria were published. The validity of our assessment of type 2 diabetes was verified with medical records in a subsample of 71 participants. A physician blinded to the information on the supplementary questionnaire reviewed the records according to the diagnostic criteria. Of the 71 participants classified as having type 2 diabetes, 12 had incomplete medical recordsfor example, absent laboratory data (n = 2) or only one set of laboratory data (n = 9). We confirmed the classification of type 2 diabetes in 57 (97%) of the other 59 other men in the subsample. One participant denied having diabetes, and another participant lacked evidence of diabetes in his submitted records. Statistical Analysis We used pooled logistic regression analyses with 2-year intervals to estimate the adjusted relative risk for each quintile compared with the lowest quintile of intake. With short time intervals and low rates of events, this approach gives results very similar to those of Cox proportional-hazards analyses (22). Participants who died or received a diagnosis of diabetes during a 2-year cycle were censored at the end of that 2-year period and were not entered in any subsequent 2-year cycle. We used the cumulative average of available dietary assessments up to the start of each 2-year follow-up interval (15). We stopped updating a participants dietary data

Physical Activity of Moderate Intensity and Risk of Type 2 Diabetes A systematic review

OBJECTIVE—To systematically evaluate the evidence for an association between physical activity of moderate intensity and risk of type 2 diabetes. RESEARCH DESIGN AND METHODS—We searched EMBASE and Medline through March 2006 and examined reference lists of retrieved articles. We excluded studies that did not assess physical activity of moderate intensity independent of activities of vigorous intensity (more than six times the resting metabolic rate). Information on study design, participant characteristics, assessment of physical activity, and outcomes and estimates of associations were extracted independently by two investigators. We calculated summary relative risks (RRs) using a random-effects model for the highest versus the lowest reported duration of activities. RESULTS—We identified 10 prospective cohort studies of physical activity of moderate intensity and type 2 diabetes, including a total of 301,221 participants and 9,367 incident cases. Five of these studies specifically investigated the role of walking. The summary RR of type 2 diabetes was 0.69 (95% CI 0.58–0.83) for regular participation in physical activity of moderate intensity as compared with being sedentary. Similarly, the RR was 0.70 (0.58–0.84) for regular walking (typically ≥2.5 h/week brisk walking) as compared with almost no walking. The associations remained significant after adjustment for BMI. Similar associations were observed in men and women and in the U.S. and Europe. CONCLUSIONS—These findings indicate that adherence to recommendations to participate in physical activities of moderate intensity such as brisk walking can substantially reduce the risk of type 2 diabetes.

Abdominal Obesity and the Risk of All-Cause, Cardiovascular, and Cancer Mortality Sixteen Years of Follow-Up in US Women

Background— Accumulating evidence indicates that abdominal adiposity is positively related to cardiovascular disease (CVD) risk and some other diseases independently of overall adiposity. However, the association of premature death resulting from these diseases with abdominal adiposity has not been widely studied, and findings are inconsistent. Methods and Results— In a prospective cohort study of 44 636 women in the Nurses’ Health Study, associations of abdominal adiposity with all-cause and cause-specific mortality were examined. During 16 years of follow-up, 3507 deaths were identified, including 751 cardiovascular deaths and 1748 cancer deaths. After adjustment for body mass index and potential confounders, the relative risks across the lowest to the highest waist circumference quintiles were 1.00, 1.11, 1.17, 1.31, and 1.79 (95% confidence interval [CI], 1.47 to 1.98) for all-cause mortality; 1.00, 1.04, 1.04, 1.28, and 1.99 (95% CI, 1.44 to 2.73) for CVD mortality; and 1.00, 1.18, 1.20, 1.34, and 1.63 (95% CI, 1.32 to 2.01) for cancer mortality (all P<0.001 for trend). Among normal-weight women (body mass index, 18.5 to <25 kg/m2), abdominal obesity was significantly associated with elevated CVD mortality: Relative risk associated with waist circumference ≥88 cm was 3.02 (95% CI, 1.31 to 6.99) and for waist-to-hip ratio >0.88 was 3.45 (95% CI, 2.02 to 6.92). After adjustment for waist circumference, hip circumference was significantly and inversely associated with CVD mortality. Conclusions— Anthropometric measures of abdominal adiposity were strongly and positively associated with all-cause, CVD, and cancer mortality independently of body mass index. Elevated waist circumference was associated with significantly increased CVD mortality even among normal-weight women.

Dietary Patterns and Risk of Mortality From Cardiovascular Disease, Cancer, and All Causes in a Prospective Cohort of Women

Background— The impact of overall dietary patterns that reflect actual eating behaviors on mortality caused by cardiovascular or other chronic diseases is largely unknown. Methods and Results— We prospectively evaluated the relation between dietary patterns and risk of cardiovascular, cancer, and all-cause mortality among 72 113 women who were free of myocardial infarction, angina, coronary artery surgery, stroke, diabetes mellitus, or cancer and were followed up from 1984 to 2002. Dietary patterns were derived by factor analysis based on validated food frequency questionnaires administered every 2 to 4 years. Two major dietary patterns were identified: High prudent pattern scores represented high intakes of vegetables, fruit, legumes, fish, poultry, and whole grains, whereas high Western pattern scores reflected high intakes of red meat, processed meat, refined grains, french fries, and sweets/desserts. During 18 years of follow-up, 6011 deaths occurred, including 1154 cardiovascular deaths and 3139 cancer deaths. After multivariable adjustment, the prudent diet was associated with a 28% lower risk of cardiovascular mortality (95% confidence interval [CI], 13 to 40) and a 17% lower risk of all-cause mortality (95% CI, 10 to 24) when the highest quintile was compared with the lowest quintile. In contrast, the Western pattern was associated with a higher risk of mortality from cardiovascular disease (22%; 95% CI, 1 to 48), cancer (16%; 95% CI, 3 to 30), and all causes (21%; 95% CI, 12 to 32). Conclusion— Greater adherence to the prudent pattern may reduce the risk of cardiovascular and total mortality, whereas greater adherence to the Western pattern may increase the risk among initially healthy women.

Income inequality, mortality, and self rated health: meta-analysis of multilevel studies

Objective To provide quantitative evaluations on the association between income inequality and health. Design Random effects meta-analyses, calculating the overall relative risk for subsequent mortality among prospective cohort studies and the overall odds ratio for poor self rated health among cross sectional studies. Data sources PubMed, the ISI Web of Science, and the National Bureau for Economic Research database. Review methods Peer reviewed papers with multilevel data. Results The meta-analysis included 59 509 857 subjects in nine cohort studies and 1 280 211 subjects in 19 cross sectional studies. The overall cohort relative risk and cross sectional odds ratio (95% confidence intervals) per 0.05 unit increase in Gini coefficient, a measure of income inequality, was 1.08 (1.06 to 1.10) and 1.04 (1.02 to 1.06), respectively. Meta-regressions showed stronger associations between income inequality and the health outcomes among studies with higher Gini (≥0.3), conducted with data after 1990, with longer duration of follow-up (>7 years), and incorporating time lags between income inequality and outcomes. By contrast, analyses accounting for unmeasured regional characteristics showed a weaker association between income inequality and health. Conclusions The results suggest a modest adverse effect of income inequality on health, although the population impact might be larger if the association is truly causal. The results also support the threshold effect hypothesis, which posits the existence of a threshold of income inequality beyond which adverse impacts on health begin to emerge. The findings need to be interpreted with caution given the heterogeneity between studies, as well as the attenuation of the risk estimates in analyses that attempted to control for the unmeasured characteristics of areas with high levels of income inequality.

Combined impact of lifestyle factors on mortality: prospective cohort study in US women

Objective To evaluate the impact of combinations of lifestyle factors on mortality in middle aged women. Design Prospective cohort study. Setting Nurses’ health study, United States. Participants 77 782 women aged 34 to 59 years and free from cardiovascular disease and cancer in 1980. Main outcome measure Relative risk of mortality during 24 years of follow-up in relation to five lifestyle factors (cigarette smoking, being overweight, taking little moderate to vigorous physical activity, no light to moderate alcohol intake, and low diet quality score). Results 8882 deaths were documented, including 1790 from cardiovascular disease and 4527 from cancer. Each lifestyle factor independently and significantly predicted mortality. Relative risks for five compared with zero lifestyle risk factors were 3.26 (95% confidence interval 2.45 to 4.34) for cancer mortality, 8.17 (4.96 to 13.47) for cardiovascular mortality, and 4.31 (3.51 to 5.31) for all cause mortality. A total of 28% (25% to 31%) of deaths during follow-up could be attributed to smoking and 55% (47% to 62%) to the combination of smoking, being overweight, lack of physical activity, and a low diet quality. Additionally considering alcohol intake did not substantially change this estimate. Conclusions These results indicate that adherence to lifestyle guidelines is associated with markedly lower mortality in middle aged women. Both efforts to eradicate cigarette smoking and those to stimulate regular physical activity and a healthy diet should be intensified.

Comparison of Self‐reported and Measured BMI as Correlates of Disease Markers in U.S. Adults

Objective: The purpose of this study is to evaluate the validity of BMI based on self‐reported data by comparison with technician‐measured BMI and biomarkers of adiposity.

Bidirectional Association Between Depression and Type 2 Diabetes Mellitus in Women

BACKGROUND Although it has been hypothesized that the diabetes-depression relation is bidirectional, few studies have addressed this hypothesis in a prospective setting. METHODS A total of 65 381 women aged 50 to 75 years in 1996 were observed until 2006. Clinical depression was defined as having diagnosed depression or using antidepressants, and depressed mood was defined as having clinical depression or severe depressive symptoms, ie, a 5-item Mental Health Index (MHI-5) score of 52 or less. Self-reported type 2 diabetes mellitus was confirmed by means of a supplementary questionnaire validated by medical record review. RESULTS During 10 years of follow-up (531 097 person-years), 2844 incident cases of type 2 diabetes mellitus were documented. Compared with referents (MHI-5 score of 86-100) who had the best depressive symptom scores, participants with increased severity of symptoms (MHI-5 scores of 76-85 or 53-75, or depressed mood) showed a monotonic elevated risk of developing type 2 diabetes (P for trend = .002 in the multivariable-adjusted model). The relative risk for individuals with depressed mood was 1.17 (95% confidence interval [CI], 1.05-1.30) after adjustment for various covariates, and participants using antidepressants were at a particularly higher relative risk (1.25; 95% CI, 1.10-1.41). In a parallel analysis, 7415 cases of incident clinical depression were documented (474 722 person-years). Compared with nondiabetic subjects, those with diabetes had a relative risk (95% CI) of developing clinical depression after controlling for all covariates of 1.29 (1.18-1.40), and it was 1.25 (1.09-1.42), 1.24 (1.09-1.41), and 1.53 (1.26-1.85) in diabetic subjects without medications, with oral hypoglycemic agents, and with insulin therapy, respectively. These associations remained significant after adjustment for diabetes-related comorbidities. CONCLUSION Our results provide compelling evidence that the diabetes-depression association is bidirectional.