American Journal of Epidemiology

Pregnancy complications and cardiovascular disease share some common determinants. It has previously been hypothesized that family history of cardiovascular disease would be associated with low birth weight. Records from 120,317 Scottish births, 1992–2006, were linked to hospital admission and death certificate data for 71,681 pairs of maternal grandparents. There was a negative relation between the birth weight of the baby and the risk of either grandparent's experiencing ischemic heart disease (for a 1-kg increase in birth weight, hazard ratio = 0.86, 95% confidence interval: 0.83, 0.89) or cerebrovascular disease (hazard ratio = 0.82, 95% confidence interval: 0.77, 0.87). Further analysis demonstrated that the associations were explained by increased risks of both delivering a small-for-gestational-age infant and delivering preterm among women whose parents had experienced cardiovascular disease. Adjustment for the mother's characteristics at the time of the birth attenuated the relation, but significant associations persisted: With a 1-kg increase in birth weight, the adjusted hazard ratio for ischemic heart disease = 0.93 (95% confidence interval: 0.89, 0.96) and for cerebrovascular disease = 0.93 (95% confidence interval: 0.89, 0.96). Familial aggregation of common determinants of pregnancy complications and cardiovascular disease is the likely explanation for the relation between an infant's birth weight and the risk of cardiovascular disease in other family members.

Ophthalmologic abnormalities have been described in patients with dementia, but the extent to which poor vision and treatment for visual disorders affect cognitive decline is not well defined. Linked data from the Health and Retirement Study and Medicare files (1992–2005) were used to follow the experiences of 625 elderly US study participants with normal cognition at baseline. The outcome was a diagnosis of dementia, cognitively impaired but no dementia, or normal cognition. Poor vision was associated with development of dementia (P = 0.0048); individuals with very good or excellent vision at baseline had a 63% reduced risk of dementia (95% confidence interval (CI): 20, 82) over a mean follow-up period of 8.5 years. Participants with poorer vision who did not visit an ophthalmologist had a 9.5-fold increased risk of Alzheimer disease (95% CI: 2.3, 39.5) and a 5-fold increased risk of cognitively impaired but no dementia (95% CI: 1.6, 15.9). Poorer vision without a previous eye procedure increased the risk of Alzheimer disease 5-fold (95% CI: 1.5, 18.8). For Americans aged 90 years or older, 77.9% who maintained normal cognition had received at least one previous eye procedure compared with 51.7% of those with Alzheimer disease. Untreated poor vision is associated with cognitive decline, particularly Alzheimer disease.

Most research regarding posttraumatic stress disorder (PTSD) and suicide has focused on suicidal ideation or attempts; no known study of the association between PTSD and completed suicide in a population-based sample has been reported. This study examined the association between PTSD and completed suicide in a population-based sample. Data were obtained from the nationwide Danish health and administrative registries, which include data on all 5.4 million residents of Denmark. All suicides between January 1, 1994, and December 31, 2006, were included, and controls were selected from a sample of all Danish residents. Using this nested case-control design, the authors examined 9,612 suicide cases and 199,306 controls matched to cases on gender, date of birth, and time. Thirty-eight suicide cases (0.40%) and 95 controls (0.05%) were diagnosed with PTSD. The odds ratio associating PTSD with suicide was 9.8 (95% confidence interval: 6.7, 15). The association between PTSD and completed suicide remained after controlling for psychiatric and demographic confounders (odds ratio = 5.3, 95% confidence interval: 3.4, 8.1). Additionally, persons with PTSD and depression had a greater rate of suicide than expected based on their independent effects. In conclusion, a registry-based diagnosis of PTSD based on International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, is a risk factor for completed suicide.

Whether insomnia, a known correlate of depression, predicts depression longitudinally warrants elucidation. The authors examined 555 Wisconsin Sleep Cohort Study participants aged 33–71 years without baseline depression or antidepressant use who completed baseline and follow-up overnight polysomnography and had complete questionnaire-based data on insomnia and depression for 1998–2006. Using Poisson regression, they estimated relative risks for depression (Zung scale score ≥50) at 4-year (average) follow-up according to baseline insomnia symptoms and polysomnographic markers. Twenty-six participants (4.7%) developed depression by follow-up. Having 3–4 insomnia symptoms versus none predicted depression risk (age-, sex-, and comorbidity-adjusted relative risk (RR) = 3.2, 95% confidence interval: 1.1, 9.6). After multiple adjustments, frequent difficulty falling asleep (RR = 5.3, 95% confidence interval: 1.1, 27.9) and polysomnographically assessed (upper or lower quartiles) sleep latency, continuity, and duration (RRs = 2.2–4.7; P’s ≤ 0.05) predicted depression. Graded trends (P-trend ≤ 0.05) were observed with increasing number of symptoms, difficulty falling asleep, and difficulty returning to sleep. Given the small number of events using Zung ≥50 (depression cutpoint), a limitation that may bias multivariable estimates, continuous depression scores were analyzed; mean values were largely consistent with dichotomous findings. Insomnia symptoms or markers increased depression risk 2.2- to 5.3-fold. These results support prior findings based on self-reported insomnia and may extend similar conclusions to objective markers. Heightened recognition and treatment of insomnia may prevent subsequent depression.

Soft drinks and other sweetened beverages may contribute to risk of type 2 diabetes and obesity. However, research has not addressed higher risk and Asian populations. The authors examined the association between soft drinks and juice and the risk of type 2 diabetes among Chinese Singaporeans enrolled in a prospective cohort study of 43,580 participants aged 45–74 years and free of diabetes and other chronic diseases at baseline. The incidence of physician-diagnosed type 2 diabetes was assessed by interview and validated; 2,273 participants developed diabetes during follow-up. After adjustment for potential lifestyle and dietary confounders, participants consuming ≥2 soft drinks per week had a relative risk of type 2 diabetes of 1.42 (95% confidence interval (CI): 1.25, 1.62) compared with those who rarely consumed soft drinks. Similarly, consumption of ≥2 juice beverages per week was associated with an increased risk (relative risk (RR) = 1.29, 95% CI: 1.05, 1.58). The association was modified by 5-year weight gain for ≥2 soft drinks per week among those who gained ≥3 kg (RR = 1.70, 95% CI: 1.34, 2.16) compared with those who gained less weight (RR = 1.20, 95% CI: 1.03, 1.41). Relatively frequent intake of soft drinks and juice is associated with an increased risk for development of type 2 diabetes in Chinese men and women.

Typical applications of marginal structural time-to-event (e.g., Cox) models have used time on study as the time scale. Here, the authors illustrate use of time on treatment as an alternative time scale. In addition, a method is provided for estimating Kaplan-Meier–type survival curves for marginal structural models. For illustration, the authors estimate the total effect of highly active antiretroviral therapy on time to acquired immunodeficiency syndrome (AIDS) or death in 1,498 US men and women infected with human immunodeficiency virus and followed for 6,556 person-years between 1995 and 2002; 323 incident cases of clinical AIDS and 59 deaths occurred. Of the remaining 1,116 participants, 77% were still under observation at the end of follow-up. By using time on study, the hazard ratio for AIDS or death comparing always with never using highly active antiretroviral therapy from the marginal structural model was 0.52 (95% confidence interval: 0.35, 0.76). By using time on treatment, the analogous hazard ratio was 0.44 (95% confidence interval: 0.32, 0.60). In time-to-event analyses, the choice of time scale may have a meaningful impact on estimates of association and precision. In the present example, use of time on treatment yielded a hazard ratio further from the null and more precise than use of time on study as the time scale.

In the current era of diet-gene analyses, large sample sizes are required to uncover the etiology of complex diseases. As such, consortia form and often combine available data. Food frequency questionnaires, which commonly use 2 different types of responses about the frequency of intake (predefined responses and open-ended responses), may be pooled to achieve the desired sample size. The common practice is to categorize open-ended responses into the predefined response categories. A problem arises when the predefined categories are noncontiguous: possible open-ended responses may fall in gaps between the predefined categories. Using simulated data modeled from frequency of intake among 1,664 controls in a lung cancer case-control study at The University of Texas M. D. Anderson Cancer Center (Houston, Texas, 2000–2005), the authors describe the effect of different categories of open-ended responses that fall in between noncontiguous, predefined response sets on estimates of the mean difference in intake and the odds ratios. A significant inflation of false positives appears when comparing mean differences of intake, while the bias in estimating odds ratios may be acceptably small. Therefore, if pooling data cannot be restricted to the same type of response, inferences should focus on odds ratio estimation to minimize bias.

Positivity, or the experimental treatment assignment assumption, requires that there be both exposed and unexposed participants at every combination of the values of the observed confounders in the population under study. Positivity is essential for inference but is often overlooked in practice by epidemiologists. This issue of the Journal includes 2 articles featuring discussions related to positivity. Here the authors define positivity, distinguish between deterministic and random positivity, and discuss the 2 relevant papers in this issue. In addition, the commentators illustrate positivity in simple 2 x 2 tables, as well as detail some ways in which epidemiologists may examine their data for nonpositivity and deal with violations of positivity in practice.

Confounding associated with social stratification or other selection processes has been called structural confounding. In the presence of structural confounding, certain covariate strata will contain only subjects who could never be exposed, a violation of the positivity or experimental treatment effect assumption. Thus, structural confounding can prohibit the exchangeability necessary for meaningful causal contrasts across levels of exposure. The authors explored the presence and magnitude of structural confounding by estimating the independent effects of neighborhood deprivation and neighborhood racial composition (segregation) on rates of preterm birth in Wake and Durham counties, North Carolina (1999–2001). Tabular analyses and random-intercept fixed-slope multilevel logistic models portrayed different structural realities in these counties. The multilevel modeling results suggested some nonsignificant effect of residence in tracts with high levels of socioeconomic deprivation or racial residential segregation on adjusted odds of preterm birth for white and black women living in these counties, and the confidence limit ratios indicated fairly consistent levels of precision around the estimates. The results of the tabular analysis, however, suggested that many of these regression modeling findings were off-support and based on no actual data. The implications for statistical and public health inference, in the presence of no data, are considered.

In a retrospective cohort study of 18,880 full-term, cephalic singletons born in San Francisco, California, during 1976–2001, the authors used multivariable logistic regression (MVLR) and propensity score analysis (PSA) to examine the association between persistent fetal occiput posterior (OP) position and perinatal outcomes. The principles and applications of these techniques are compared and discussed. Pregnancies with OP positions at delivery were compared with those with occiput anterior positions. Perinatal outcomes were examined as adjusted odds ratios determined by MVLR and PSA and as risk differences determined by propensity score matched bootstrapping based on covariate distance. Persistent OP position was associated with operative delivery and maternal morbidity. The odds ratio estimates based on PSA were somewhat larger than those obtained with standard MVLR, and the confidence intervals were narrower. When statistical inference was evaluated with the permutation test, the results were more consistent with the PSA. These analyses demonstrate that PSA is likely to provide more precise estimates of exposure associations and more reliable statistical inferences than MVLR. The authors show that PSA can be extended with Mahalanobis distance matching to obtain estimates of risk difference between exposed and unexposed subjects that avoid violations of the experimental treatment assignment (positivity) assumption that is required for valid causal inference.

The peroxisome proliferator-activated receptor- gene (PPARG) has been implicated in the etiology of type 2 diabetes mellitus and has been investigated in numerous epidemiologic studies. In this Human Genome Epidemiology review, the authors assessed this relation in an updated meta-analysis of 60 association studies. Electronic literature searches were conducted on September 14, 2009. Population-based cohort, case-control, cross-sectional, or genome-wide association studies reporting associations between the PPARG Pro12Ala gene variant (rs1801282) and type 2 diabetes were included. An updated literature-based meta-analysis involving 32,849 type 2 diabetes cases and 47,456 controls in relation to the PPARG Pro12Ala variant was conducted. The combined overall odds ratio, calculated by per-allele genetic model random-effects meta-analysis for type 2 diabetes and the Pro12Ala polymorphism, was 0.86 (95% confidence interval: 0.81, 0.90). The analysis indicated a moderate level of heterogeneity attributable to genuine variation in gene effect size (I2 = 37%). This may reflect the variation observed between ethnic populations and/or differences in body mass index. Work on PPARG Pro12Ala should now focus on the observed heterogeneity in the magnitude of the association between populations. Further investigations into gene-gene and gene-environment interactions may prove enlightening.

Contrary to a cardioprotective effect of moderate regular alcohol consumption, accumulating evidence points to a detrimental effect of irregular heavy drinking occasions (>60 g of pure alcohol or ≥5 drinks per occasion at least monthly) on ischemic heart disease risk, even for drinkers whose average consumption is moderate. The authors systematically searched electronic databases from 1980 to 2009 for case-control or cohort studies examining the association of irregular heavy drinking occasions with ischemic heart disease risk. Studies were included if they reported either a relative risk estimate for intoxication or frequency of ≥5 drinks stratified by or adjusted for total average alcohol consumption. The search identified 14 studies (including 31 risk estimates) containing 4,718 ischemic heart disease events (morbidity and mortality). Using a standardized protocol, the authors extracted relative risk estimates and their variance, in addition to study characteristics. In a random-effects model, the pooled relative risk of irregular heavy drinking occasions compared with regular moderate drinking was 1.45 (95% confidence interval: 1.24, 1.70), with significant between-study heterogeneity (I2 = 53.9%). Results were robust in several sensitivity analyses. The authors concluded that the cardioprotective effect of moderate alcohol consumption disappears when, on average, light to moderate drinking is mixed with irregular heavy drinking occasions.

Statistical analysis in epidemiologic studies is often hindered by missing data, and multiple imputation is increasingly being used to handle this problem. In a simulation study, the authors compared 2 methods for imputation that are widely available in standard software: fully conditional specification (FCS) or "chained equations" and multivariate normal imputation (MVNI). The authors created data sets of 1,000 observations to simulate a cohort study, and missing data were induced under 3 missing-data mechanisms. Imputations were performed using FCS (Royston's "ice") and MVNI (Schafer's NORM) in Stata (Stata Corporation, College Station, Texas), with transformations or prediction matching being used to manage nonnormality in the continuous variables. Inferences for a set of regression parameters were compared between these approaches and a complete-case analysis. As expected, both FCS and MVNI were generally less biased than complete-case analysis, and both produced similar results despite the presence of binary and ordinal variables that clearly did not follow a normal distribution. Ignoring skewness in a continuous covariate led to large biases and poor coverage for the corresponding regression parameter under both approaches, although inferences for other parameters were largely unaffected. These results provide reassurance that similar results can be expected from FCS and MVNI in a standard regression analysis involving variously scaled variables.

There is increasing interest in estimating and drawing inferences about risk or prevalence ratios and differences instead of odds ratios in the regression setting. Recent publications have shown how the GENMOD procedure in SAS (SAS Institute Inc., Cary, North Carolina) can be used to estimate these parameters in non-population-based studies. In this paper, the authors show how model-adjusted risks, risk differences, and risk ratio estimates can be obtained directly from logistic regression models in the complex sample survey setting to yield population-based inferences. Complex sample survey designs typically involve some combination of weighting, stratification, multistage sampling, clustering, and perhaps finite population adjustments. Point estimates of model-adjusted risks, risk differences, and risk ratios are obtained from average marginal predictions in the fitted logistic regression model. The model can contain both continuous and categorical covariates, as well as interaction terms. The authors use the SUDAAN software package (Research Triangle Institute, Research Triangle Park, North Carolina) to obtain point estimates, standard errors (via linearization or a replication method), confidence intervals, and P values for the parameters and contrasts of interest. Data from the 2006 National Health Interview Survey are used to illustrate these concepts.

Studying the relation between the residential environment and health requires valid, reliable, and cost-effective methods to collect data on residential environments. This 2002 study compared the level of agreement between measures of the presence of neighborhood businesses drawn from 2 common sources of data used for research on the built environment and health: listings of businesses from commercial databases and direct observations of city blocks by raters. Kappa statistics were calculated for 6 types of businesses&mdash;drugstores, liquor stores, bars, convenience stores, restaurants, and grocers&mdash;located on 1,663 city blocks in Chicago, Illinois. Logistic regressions estimated whether disagreement between measurement methods was systematically correlated with the socioeconomic and demographic characteristics of neighborhoods. Levels of agreement between the 2 sources were relatively high, with significant (P < 0.001) kappa statistics for each business type ranging from 0.32 to 0.70. Most business types were more likely to be reported by direct observations than in the commercial database listings. Disagreement between the 2 sources was not significantly correlated with the socioeconomic and demographic characteristics of neighborhoods. Results suggest that researchers should have reasonable confidence using whichever method (or combination of methods) is most cost-effective and theoretically appropriate for their research design.

Selection bias is a concern in cohort studies in which selection into the cohort is related to the studied outcome. An example is chronic infection with hepatitis C virus, where the initial infection may be asymptomatic for decades. This problem leads to selection of more severely ill individuals into registers of such infections. Cohort studies often adjust for this bias by introducing a time window between entry into the cohort and entry into the study. This paper describes and assesses a novel method to improve adjustment for this type of selection bias. The size of the time window is decided by calculating a standardized incidence ratio as a continuous function of the size of the time window. The resulting graph is used to decide on an appropriate window size. The method is evaluated by using the Swedish register of hepatitis C virus infections for 1990&ndash;2006. The complications studied were non-Hodgkin lymphoma and liver cancer. Selection bias differed for the studied outcomes, and a time window of a minimum of 2 months and 12 months, respectively, was judged to be appropriate. The novel method may have advantages compared with an interval-based method, especially in cohort studies with small numbers of events.

Organochlorines are environmentally persistent contaminants that readily cross the placenta, posing a potential risk to the developing fetus. Evidence for neurodevelopmental effects at low levels of these compounds is growing, though few studies have focused on behavioral outcomes. The authors investigated the association between prenatal polychlorinated biphenyl (PCB) and p,p'-dichlorodiphenyl dichloroethylene (p,p'-DDE) levels and behaviors associated with attention deficit hyperactivity disorder (ADHD), measured with the Conners&rsquo; Rating Scale for Teachers (CRS-T), in a cohort of 607 children aged 7&ndash;11 years (median age, 8.2 years) born in 1993&ndash;1998 to mothers residing near a PCB-contaminated harbor in New Bedford, Massachusetts. The median umbilical cord serum level of the sum of 4 prevalent PCB congeners (118, 138, 153, and 180) was 0.19 ng/g serum (range, 0.01&ndash;4.41 ng/g serum). The authors found higher risk for ADHD-like behaviors assessed with the CRS-T at higher levels of PCBs and p,p'-DDE. For example, the authors found higher risk of atypical behavior on the Conners&rsquo; ADHD Index for the highest quartile of the sum of 4 PCB congeners versus the lowest quartile (risk ratio = 1.76, 95% confidence interval: 1.06, 2.92) and a similar relation for p,p'-DDE. These results support an association between low-level prenatal organochlorine exposure and ADHD-like behaviors in childhood.

The association of sex hormone levels with mortality over a median of 16 years of follow-up was evaluated in a prospective cohort study. The study included 1,114 US men who participated in phase 1 (1988&ndash;1991) of the Third National Health and Nutrition Examination Survey Mortality Study and had no history of cardiovascular disease or cancer at baseline. Multivariable adjusted hazard ratios for all-cause mortality associated with a decrease in hormone concentration equal to the difference between the 90th and 10th percentiles of the sex hormone distributions were estimated by using proportional hazards regression. The hazard ratios associated with low free testosterone and low bioavailable testosterone levels were 1.43 (95% confidence interval (CI): 1.09, 1.87) and 1.52 (95% CI: 1.15, 2.02), respectively, for follow-up between baseline and year 9; they were 0.94 (95% CI: 0.51, 1.72) and 0.98 (95% CI: 0.56, 1.72), respectively, for follow-up between year 9 and year 18. Men with low free and bioavailable testosterone levels may have a higher risk of mortality within 9 years of hormone measurement. Future studies should be conducted to fully characterize the association of low free and bioavailable testosterone concentrations and mortality in men and to describe the mechanism underlying the association.

The authors conducted a nested case-control study of serum inflammatory markers and risk of symptomatic benign prostatic hyperplasia (BPH), using data from the placebo arm of the Prostate Cancer Prevention Trial (1993&ndash;2003). Incident BPH (n = 676) was defined as treatment, report of 2 International Prostate Symptom Score (IPSS) values >14, or 2 increases of &ge;5 from baseline values with at least one value &ge;12. Controls (n = 683) were men who reported no BPH treatment or IPSS values >7 over the 7-year trial. Baseline serum was analyzed for C-reactive protein, tumor necrosis factor (monomer), soluble tumor necrosis factor receptors I and II (sTNF-RI and sTNF-RII), interleukin 6, and interferon . Controlled for age and race, a high C-reactive protein concentration was associated with increased BPH risk (for quartile 4 vs. quartile 1, odds ratio (OR) = 1.40, 95% confidence interval (CI): 1.04, 1.88); this was attenuated after control for body mass index (OR = 1.30, 95% CI: 0.95, 1.75). Low sTNF-RII and high interleukin 6 concentrations were associated with increased BPH risk (for quartile 4 vs. quartile 1, sTNF-RII: OR = 0.61, 95% CI: 0.46, 0.82; interleukin 6: OR = 1.79, 95% CI: 1.32, 2.42); these associations were only in men aged <65 years. Results suggest that systemic inflammation or lower levels of soluble receptors that bind inflammatory cytokines increase BPH risk.

The authors examined the relation between individual and neighborhood socioeconomic status (SES) and type 2 diabetes incidence among African-American women in the prospective Black Women's Health Study. Participants have completed mailed biennial follow-up questionnaires since 1995. US Census block group characteristics were used to measure neighborhood SES. Incidence rate ratios were estimated in clustered survival regression models. During 12 years of follow-up of 46,382 participants aged 30&ndash;69 years, 3,833 new cases of type 2 diabetes occurred. In models that included both individual and neighborhood SES factors, incidence rate ratios were 1.28 (95% confidence interval: 1.15, 1.43) for &le;12 years of education relative to &ge;17 years, 1.57 (95% confidence interval: 1.30, 1.90) for household income <$15,000 relative to >$100,000, and 1.65 (95% confidence interval: 1.46, 1.85) for lowest quintile of neighborhood SES relative to highest. The associations were attenuated after adjustment for body mass index, suggesting it is the key intermediate factor in the pathway between SES and diabetes. The association of neighborhood SES with diabetes incidence was present even among women who were more educated and had a higher family income. Efforts to reduce the alarming rate of diabetes in African-American women must focus on both individual lifestyle changes and structural changes in disadvantaged neighborhoods.

Patterns of lung cancer incidence suggest that gender-associated factors may influence lung cancer risk. Given the association of parity with risk of some women's cancers, the authors hypothesized that childbearing history may also be associated with lung cancer. Women enrolled in the Lung Cancer Susceptibility Study at Massachusetts General Hospital (Boston, Massachusetts) between 1992 and 2004 (1,004 cases, 848 controls) were available for analysis of the association between parity and lung cancer risk. Multivariate logistic regression was used to estimate adjusted odds ratios and 95% confidence intervals. After results were controlled for age and smoking history, women with at least 1 child had 0.71 times the odds of lung cancer as women without children (odds ratio = 0.71, 95% confidence interval: 0.52, 0.97). A significant linear trend was found: Lung cancer risk decreased with increasing numbers of children (P < 0.001). This inverse association was stronger in never smokers (P = 0.12) and was limited to women over age 50 years at diagnosis (P = 0.17). Age at first birth was not associated with risk. The authors observed a protective association between childbearing and lung cancer, adding to existing evidence that reproductive factors may moderate lung cancer risk in women.

The authors examined the association between weight patterns during middle age and incident type 2 diabetes mellitus using a subset (n = 1,476) of the Framingham Heart Study original cohort limited-access data set (1948&ndash;2003). Participants diagnosed with diabetes before age 50 years were excluded. A functional principal components analysis of body mass index from age 40 years to age 50 years was used to define weight patterns in terms of overall weight status (normal weight, overweight, or obese), weight change (weight loss, stable weight, or weight gain), and weight cycling. Overall overweight and obesity were associated with higher rates of diabetes (for overall overweight, crude hazard ratio (HR) = 3.2, 95% confidence interval (CI): 2.3, 4.6; for overall obesity, crude HR = 8.8, 95% CI: 6.0, 12.8). Weight cycling was also associated with higher rates of diabetes (crude HR = 1.6, 95% CI: 1.2, 2.1). Neither weight loss nor weight gain was associated with incident diabetes. After adjustment for overall weight status, weight cycling was no longer associated with higher rates of diabetes. This study underscores the importance of obesity in diabetes risk and the importance of preventing the development of overweight and obesity earlier in life.

Although both inflammatory and atherosclerosis markers have been associated with coronary heart disease (CHD) risk, data directly comparing their predictive value are limited. The authors compared the value of 2 atherosclerosis markers (ankle-arm index (AAI) and aortic pulse wave velocity (aPWV)) and 3 inflammatory markers (C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor- (TNF-)) in predicting CHD events. Among 2,191 adults aged 70&ndash;79 years at baseline (1997&ndash;1998) from the Health, Aging, and Body Composition Study cohort, the authors examined adjudicated incident myocardial infarction or CHD death ("hard" events) and "hard" events plus hospitalization for angina or coronary revascularization (total CHD events). During 8 years of follow-up between 1997&ndash;1998 and June 2007, 351 participants developed total CHD events (197 "hard" events). IL-6 (highest quartile vs. lowest: hazard ratio = 1.82, 95% confidence interval: 1.33, 2.49; P-trend < 0.001) and AAI (AAI &le; 0.9 vs. AAI 1.01&ndash;1.30: hazard ratio = 1.57, 95% confidence interval: 1.14, 2.18) predicted CHD events above traditional risk factors and modestly improved global measures of predictive accuracy. CRP, TNF-, and aPWV had weaker associations. IL-6 and AAI accurately reclassified 6.6% and 3.3% of participants, respectively (P&rsquo;s &le; 0.05). Results were similar for "hard" CHD, with higher reclassification rates for AAI. IL-6 and AAI are associated with future CHD events beyond traditional risk factors and modestly improve risk prediction in older adults.

The relation between alcohol consumption and incident hypertension is unclear, and most observational studies have not accounted for socioeconomic factors. This study examined the association between alcohol consumption in a diverse group of young adults and incident hypertension over 20 years. Participants (n = 4,711) were from the Coronary Artery Risk Development in Young Adults Study cohort, recruited in 1985 (aged 18&ndash;30 years) from Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and Oakland, California. The 20-year incidence of hypertension for never, former, light, moderate, and at-risk drinkers was 25.1%, 31.8%, 20.9%, 22.2%, and 18.8%, respectively (P < 0.001). Race, gender, age, family history of hypertension, body mass index, income, education, and difficulty paying for basics and medical care were associated with hypertension. Adjustment using Cox proportional hazard models revealed no association between baseline alcohol consumption and incident hypertension, except among European-American women in whom any current alcohol consumption was associated with lower risk of incident hypertension. The lack of association between alcohol and hypertension in the majority of this socioeconomically diverse cohort is not definitive. Future studies should include social factors, such as income and education, and consider additional characteristics that may modify or confound associations between alcohol and blood pressure.

The association between psychosocial risk factors and retinal microvascular signs was examined in the Multi-Ethnic Study of Atherosclerosis. Subjects were recruited from Baltimore, Maryland; Chicago, Illinois; Forsyth County, North Carolina; Los Angeles County, California; New York, New York; and St. Paul, Minnesota. Levels of depressive symptoms, trait anger, trait anxiety, chronic burdens, emotional support, and cynical distrust were assessed by questionnaire (from July 2000 to July 2002). Digital retinal images (from August 2002 to January 2004) from 6,147 participants were used to evaluate retinopathy and retinal vascular caliber. After controlling for potential confounding factors, the authors found that subjects without access to emotional support (Enriched Social Support Instrument score of <19 vs. &ge;19) had 60% greater odds of retinopathy (odds ratio = 1.6, 95% confidence interval (CI): 1.3, 2.0). Subjects with high Spielberger trait-anxiety scale scores (&ge;22 vs. &le;14) and subjects with high depressive symptoms (Center for Epidemiology Studies Depression Scale score, &ge;16 vs. <16) were also more likely to have retinopathy (odds ratio = 1.4, 95% CI: 1.1, 1.9 and odds ratio = 1.5, 95% CI: 1.2, 1.9), respectively. In this cross-sectional study, lack of emotional support, increased trait anxiety, and more depressive symptoms were associated with retinopathy signs, independently of other known risk factors.

Higher urinary albumin excretion predicts future cardiovascular disease, hypertension, and chronic kidney disease. Physical activity improves endothelial function so activity may reduce albuminuria. Among diabetics, physical activity decreases albuminuria. In nondiabetics, prior studies have shown no association. The authors explored the cross-sectional association between physical activity and albuminuria in 3,587 nondiabetic women in 2 US cohorts, the Nurses&rsquo; Health Study I in 2000 and the Nurses&rsquo; Health Study II in 1997. Physical activity was expressed as metabolic equivalents per week. The outcome was the top albumin/creatinine ratio (ACR) decile. Multivariate logistic regression was used. Secondary analyses explored the ACR association with strenuous activity and walking. The mean age was 58.6 years. Compared with women in the lowest physical activity quintile, those in the highest quintile had a multivariate-adjusted odds ratio for the top ACR decile of 0.65 (95% confidence interval (CI): 0.46, 0.93). The multivariate-adjusted odds ratio for the top ACR decile for those with greater than 210 minutes per week of strenuous activity compared with no strenuous activity was 0.61 (95% CI: 0.37, 0.99), and for those in the highest quintile of walking compared with the lowest quintile, it was 0.69 (95% CI: 0.47, 1.02). Greater physical activity is associated with a lower ACR in nondiabetic women.