Ambient particulate matter (PM) has been associated with mortality and morbidity for cardiovascular disease (CVD). MicroRNAs control gene expression at a post-transcriptional level. Altered microRNA expression has been reported in processes related to CVD and PM exposure, e.g. systemic inflammation, endothelial dysfunction and atherosclerosis. Polymorphisms in microRNA-related genes could influence response to PM.
We investigated the association of exposure to ambient particles in several time windows (4-hours to 28-days moving averages) and blood-leukocyte expression changes in fourteen candidate microRNAs, in 153 elderly males from the Normative Aging Study (examined 2005–2009). Potential effect modification by six single nucleotide polymorphisms (SNPs) in three microRNA-related genes was investigated. Fine PM (PM2.5), black carbon, organic carbon and sulfates were measured at a stationary ambient monitoring site. Linear regression models, adjusted for potential confounders, were used to assess effects of particles and SNP-by-pollutant interaction. An in silico pathways analysis was performed on target genes of miRNAs associated with the pollutants.
We found a negative association for pollutants in all moving averages and miR-1, -126, -135a, -146a, -155, -21, -222 and -9. The strongest associations were observed with the 7-day moving averages for PM2.5 and black carbon and with the 48-hour moving averages for organic carbon. The association with sulfates was stable across the moving averages. The in silico pathway analysis identified 18 pathways related to immune response shared by at least two miRNAs; in particular, the “HMGB1/RAGE signaling pathway” was shared by miR-126, -146a, -155, -21 and -222.
No important associations were observed for miR-125a-5p, -125b, -128, -147, -218 and -96. We found significant SNP-by-pollutant interactions for rs7813, rs910925 and rs1062923 in GEMIN4 and black carbon and PM2.5 for miR-1, -126, -146a, -222 and -9, and for rs1640299 in DGCR8 and SO42− for miR-1 and -135a.
Exposure to ambient particles could cause a downregulation of microRNAs involved in processes related to PM exposure. Polymorphisms in GEMIN4 and DGCR8 could modify these associations.
High serum calcium levels have been associated with cognitive decline in older adults. These associations have not been studied in younger adults. The possible association of vitamin D with cognitive function, independent of calcium, is unknown.
A cross-sectional study of associations of serum ionized calcium and 25-hydroxyvitamin D levels with cognitive function in younger adults (20–59 years) and older adults (60–90 years) was conducted using data from the US third National Health and Nutrition Examination Survey (NHANES III).
Neither serum ionized calcium nor 25-hydroxyvitamin D was associated with cognitive function in either age group. For example, the confounder-adjusted mean difference in reaction time in young adults was 0.00 (95% confidence interval = −0.07 to 0.06) per 1 SD calcium.
Our results do not support an important role for calcium or vitamin D in cognitive performance in adults.
Ambient particles are associated with cardiovascular events, and recently with total plasma homocysteine. High total plasma homocysteine is a risk for human health. However, the biological mechanisms are not fully understood. One of putative pathways is through oxidative stress. We aimed to examine whether associations of PM2.5 and black carbon with homocysteine were modified by genotypes including HFE H63D, C282Y, CAT (rs480575, rs1001179, rs2284367 and rs2300181), NQO1 (rs1800566), GSTP1 I105V, GSTM1, GSTT1(deletion vs non-deletion) and HMOX-1 (any short vs both long). We attempted to replicate identified genes in an analysis of heart rate variability, and in other outcomes reported in the literature.
Study subjects were 1000 white non-Hispanic men in the Boston area, participating in a cohort study of aging. PM2.5, black carbon, total plasma homocysteine and other covariates were measured at several points in time between 1995 and 2006. We fit mixed models to examine effect modification of genes on associations of pollution with total plasma homocysteine.
Interquartile range (IQR) increases in PM2.5 and black carbon (7-day moving averages) were associated with 1.5% (95% confidence interval = 0.2% to 2.8%) and 2.2% (0.6% to 3.9%) increases in total plasma homocysteine, respectively. GSTT1 and HFE C282Y modified effects of black carbon on total plasma homocysteine, and HFE C282Y and CAT (rs2300181) modified effects of PM2.5 on homocysteine. Several genotypes marginally modified effects of PM2.5 and black carbon on various endpoints. All genes with significant interactions with particulate air pollution had modest main effects on total plasma homocysteine.
Effects of PM2.5 and black carbon on various endpoints appeared to be mediated by genes related to oxidative stress pathways.
Recent theory in causal inference has provided concepts for mediation analysis and effect decomposition that allow one to decompose a total effect into a direct and an indirect effect. Here, it is shown that what is often taken as an indirect effect can in fact be further decomposed into a “pure” indirect effect and a mediated interactive effect, thus yielding a three-way decomposition of a total effect (direct, indirect, and interactive). This three-way decomposition applies to difference scales and also to additive ratio scales and additive hazard scales. Assumptions needed for the identification of each of these three effects are discussed and simple formulae are given for each when regression models allowing for interaction are used. The three-way decomposition is illustrated by examples from genetic and perinatal epidemiology, and discussion is given to what is gained over the traditional two-way decomposition into simply a direct and an indirect effect.
Researchers often recruit proxy respondents, such as relatives or caregivers, for epidemiologic studies of older adults when study participants are unable to provide self-reports (e.g., due to illness or cognitive impairment). In most studies involving proxy-reported outcomes, proxies are recruited only to report on behalf of participants who have missing self-reported outcomes; thus, either a proxy report or participant self-report, but not both, is available for each participant. When outcomes are binary and investigators conceptualize participant self-reports as gold standard measures, substituting proxy reports in place of missing participant self-reports in statistical analysis can introduce misclassification error and lead to biased parameter estimates. However, excluding observations from participants with missing self-reported outcomes may also lead to bias. We propose a pattern-mixture model that uses error-prone proxy reports to reduce selection bias from missing outcomes, and we describe a sensitivity analysis to address bias from differential outcome misclassification. We perform model estimation with high-dimensional (e.g., continuous) covariates using propensity-score stratification and multiple imputation. We apply the methods to the Second Cohort of the Baltimore Hip Studies, a study of elderly hip-fracture patients, to assess the relation between type of surgical treatment and perceived physical recovery. Simulation studies show that the proposed methods perform well. We provide SAS programs in the eAppendix to enhance the methods’ accessibility.
Adverse respiratory effects in children with asthma are associated with exposures to nitrogen dioxide (NO2). Levels indoors can be much higher than outdoors. Primary indoor sources of NO2 are gas stoves, which are used for cooking by one-third of US households. We investigated effects of indoor NO2 exposure on asthma severity among an ethnically and economically diverse sample of children, controlling for season and indoor allergen exposure.
Children aged 5–10 years with active asthma (n=1,342), were recruited through schools in urban and suburban Connecticut and Massachusetts (2006–2009) for a prospective, year-long study with seasonal measurements of NO2 and asthma severity. Exposure to NO2 was measured passively for four, month-long, periods with Palmes tubes. Asthma morbidity was concurrently measured by a severity score and frequency of wheeze, night symptoms and use of rescue medication. We used adjusted, hierarchical ordered logistic regression models to examine associations between household NO2 exposure and health outcomes.
Every 5 ppb increase in NO2 exposure above a threshold of 6 ppb was associated with a dose-dependent increase in risk of higher asthma severity score (odds ratio= 1.37 [95% confidence interval= 1.01 – 1.89]), wheeze (1.49 [1.09 – 2.03]), night symptoms (1.52 [1.16 – 2.00]) and rescue medication use (1.78 [1.33 – 2.38]).
Asthmatic children exposed to NO2 indoors, at levels well below the US Environmental Protection Agency outdoor standard (53 ppb), are at risk for increased asthma morbidity. Risks are not confined to inner-city children, but occur at NO2 concentrations common in urban and suburban homes.
The usual-frequency case-crossover method, comparing exposure before an event with typical exposure of the same person, is widely used to estimate the risk of injury related to acute alcohol use. Prior results suggest that risk estimates might be biased upward compared with other methods.
Using data from 15 emergency-room studies in 7 countries, we compared the usual-frequency case-crossover method with case-control analysis, using non-injury patients as controls. Control-crossover analysis was performed to examine potential bias and to adjust risk estimates.
The cross-study pooled odds ratio (OR) of injury related to drinking was 4.7 (2.6–8.5) in case-crossover analysis and 2.1 (1.6–2.7) in case-control analysis. A control-crossover analysis found an indication of bias (OR=2.2 [1.8–2.8]), which was larger among less frequent drinkers.
Findings suggest that the potential overestimation of injury risk based on the usual-frequency case-crossover method might be best explained by recall bias in usual-frequency estimates.
Smoking during pregnancy has been associated with asthma, obesity, and decreased cognitive functioning in the offspring. To study the role of in utero smoking exposure in offsprings’ adult health outcomes, it may be necessary to rely upon reports by the offspring themselves.
We studied 34,949 mother-daughter pairs participating in the Nurses’ Health Study II for whom data on the daughter’s early passive cigarette smoke exposure had been obtained from both mother and daughter. We calculated sensitivity and specificity of daughter’s early exposure to smoke (using mother’s report as the gold standard), as well as κ statistics. Mother and daughter reports were also analyzed as risk factors for asthma and birthweight to demonstrate face validity.
Sensitivity of daughters’ reported prenatal exposure ranged from 74% to 85%, while specificity was between 90% and 95% (κ = 0.72– 0.81). Daughter’s reported childhood exposure as a proxy for mother’s report of smoking during pregnancy had a sensitivity of 89% and specificity of 88%. Results were similar for daughter’s report of father’s smoking during her childhood. Maternal smoking during pregnancy is consistently associated with reductions in offspring birthweight, and with asthma risk in offspring. The daughter’s risk of being very low (<1500 g) or low birthweight (<2500 g) or of having asthma were similar when exposure was defined according to mother’s report, daughter’s report of fetal smoke exposure, and daughter’s report of mother’s smoking during childhood.
Daughter’s report of mother’s smoking prenatally and in childhood are good proxy measures for mother’s own report of smoking during pregnancy.
Food items on a self-administered food frequency questionnaire (FFQ) may be left blank because the food was not consumed, because of difficulties remembering the frequency or amount of intake, or due to an oversight.
We explored the predictors and frequency of consumption of omitted food items on an FFQ used in the Nurses’ Health Study II. Of 87,676 women who returned a mailed 147-item FFQ in 1999, 34% completed the entire questionnaire, whereas 66% left at least 1 food item blank. Ten or more foods were omitted by 5% of participants. Foods were more likely omitted by women who were older, more physically active, and had more children. We resurveyed 2876 participants who had left between 1 and 70 food items blank and asked them to fill in the blanks. Overall, 2485 participants provided complete responses.
In the resurvey, 64% of the formerly omitted foods were marked as consumed never or less than once per month, 20% as 1–3 times per month, 8% as once per week, and 9% as more than once per week. Commonly consumed foods and beverages were less likely omitted because they were not consumed than rarely consumed foods. The best estimate for the true intake value of an omitted food was 0.82 times the average population intake.
When calculating nutrient intake, the assumption that items missing represent zero intake is reasonable. However, foods consumed more often in the population at large are less likely than rarely consumed foods to be left blank because they were not consumed.
Previous analyses from the National Health and Nutrition Examination Survey (NHANES III) have found that elevated blood lead levels may be associated with cardiovascular mortality, cancer mortality, and all-cause mortality. The 5-aminolevulinic acid dehydratase (ALAD) G177C genetic polymorphism (rs 1800435) affects lead toxicokinetics and may alter the adverse effects of lead exposure. We examined whether the ALAD G177C single nucleotide polymorphism (SNP) affects the relationship between lead and mortality.
We analyzed a subset of 3349 genotyped NHANES III participants at least 40 years of age. Using Cox proportional hazards regression, we estimated the relative risk of all-cause, cardiovascular disease, and cancer mortality by ALAD genotype, and by blood lead levels (<5 μg/dL vs. ≥5 μg/dL). We also tested whether the ALAD genotype modified the relationship between blood lead level and mortality.
The adjusted overall relative risk for participants with the variant ALADCG/CC genotype was decreased for all-cause mortality (hazards ratio = 0.68; [95% confidence interval = 0.50–0.93]) compared with persons having the common GG genotype. There was some suggestion that higher lead levels were associated with cancer mortality (1.48 [0.92–2.38]). We observed no convincing interaction effect between ALAD genotype and blood lead level on mortality risk.
The ALADCG/CC genotype may be associated with decreased mortality from all causes and from cancer. This association does not seem to be affected by lead exposure.
Although it is clear that there are short-term effects of sodium intake on blood pressure, little is known about the most relevant timing of sodium exposure for the onset of hypertension. This question can only be addressed in cohorts with repeated measures of sodium intake.
Using up to 7 measures of dietary sodium intake and blood pressure between 1991 and 2009, we compared baseline, the mean of all measures, and the most recent sodium intake in association with incident hypertension, in 6578 adults enrolled in the China Health and Nutrition Survey aged 18 to 65 free of hypertension at baseline. We used survival methods that account for the interval-censored nature of this study, and inverse probability weights to generate adjusted survival curves and time-specific cumulative risk differences; hazard ratios were also estimated.
For mean and most recent measures, the probability of hypertension-free survival was the lowest among those in the highest intake sodium group compared to all other intake groups across the entire follow-up. In addition, the most recent sodium intake measure had a positive dose-response association with incident hypertension [Risk Difference at 11 years of follow-up = 0.04 (95%CI −0.01, 0.09), 0.06 (0.00, 0.13), 0.18 (0.12, 0.24) and 0.20 (0.12, 0.27) for the second to fifth sodium intake groups compared to the lowest group respectively]. Baseline sodium intake was not associated with incident hypertension.
These results suggest caution when using baseline sodium intake measures with long-term follow up.
China; sodium intake; incident hypertension; interval-censored; adjusted survival curves
While epidemiologic and clinical research often aims to analyze predictors of specific endpoints, time-to-the-specific-event analysis can be hampered by problems with cause ascertainment. Under typical assumptions of competing risks analysis (and missing-data settings), we correct the cause-specific proportional hazards analysis when information on the reliability of diagnosis is available. Our method avoids bias in effect estimates at low cost in variance, thus offering a perspective for better-informed decision-making. The ratio of different cause-specific hazards can be estimated flexibly for this purpose. It thus complements an all-cause analysis. In a sensitivity analysis, this approach can reveal the likely extent and direction of the bias of a standard cause-specific analysis when the diagnosis is suspect. These two uses are illustrated in a randomized vaccine trial and an epidemiologic cohort study respectively.
Previous studies on the relationship of neighborhood disadvantage with alcohol use or misuse have often controlled for individual characteristics on the causal pathway, such as income—thus potentially underestimating the relationship between disadvantage and alcohol consumption.
We used data from the Coronary Artery Risk Development in Young Adults study of 5115 adults aged 18–30 years at baseline and interviewed 7 times between 1985 and 2006. We estimated marginal structural models using inverse probability-of-treatment and censoring weights to assess the association between point-in-time/cumulative exposure to neighborhood poverty (proportion of census tract residents living in poverty) and alcohol use/binging, after accounting for time-dependent confounders including income, education, and occupation.
The log-normal model was used to estimate treatment weights while accounting for highly-skewed continuous neighborhood poverty data. In the weighted model, a one-unit increase in neighborhood poverty at the prior examination was associated with a 86% increase in the odds of binging (OR = 1.86 [95% confidence interval = 1.14–3.03]); the estimate from a standard generalized-estimating-equations model controlling for baseline and time-varying covariates was 1.47 (0.96–2.25). The inverse probability-of-treatment and censoring weighted estimate of the relative increase in the number of weekly drinks in the past year associated with cumulative neighborhood poverty was 1.53 (1.02–2.27); the estimate from a standard model was 1.16 (0.83–1.62).
Cumulative and point-in-time measures of neighborhood poverty are important predictors of alcohol consumption. Estimators that more closely approximate a causal effect of neighborhood poverty on alcohol provided a stronger estimate than estimators from traditional regression models.
Exposure-response information about particulate air-pollution constituents is needed to protect sensitive populations. Particulate matter <2.5 mm (PM2.5) components may induce oxidative stress through reactive-oxygen-species generation, including primary organics from combustion sources and secondary organics from photochemically oxidized volatile organic compounds. We evaluated differences in airway versus systemic inflammatory responses to primary versus secondary organic particle components, particle size fractions, and the potential of particles to induce cellular production of reactive oxygen species.
A total of 60 elderly subjects contributed up to 12 weekly measurements of fractional exhaled nitric oxide (NO; airway inflammation biomarker), and plasma interleukin-6 (IL-6; systemic inflammation biomarker). PM2.5 mass fractions were PM0.25 (<0.25 µm) and PM0.25–2.5 (0.25–2.5 µm). Primary organic markers included PM2.5 primary organic carbon, and PM0.25 polycyclic aromatic hydrocarbons and hopanes. Secondary organic markers included PM2.5 secondary organic carbon, and PM0.25 water soluble organic carbon and n-alkanoic acids. Gaseous pollutants included carbon monoxide (CO) and nitrogen oxides (NOx; combustion emissions markers), and ozone (O3; photochemistry marker). To assess PM oxidative potential, we exposed rat alveolar macrophages in vitro to aqueous extracts of PM0.25 filters and measured reactive-oxygen-species production. Biomarker associations with exposures were evaluated with mixed-effects models.
Secondary organic markers, PM0.25–2.5, and O3 were positively associated with exhaled NO. Primary organic markers, PM0.25, CO, and NOx were positively associated with IL-6. Reactive oxygen species were associated with both outcomes.
Particle effects on airway versus systemic inflammation differ by composition, but overall particle potential to induce generation of cellular reactive oxygen species is related to both outcomes.
The cause of historically higher rates of invasive pneumococcal disease among blacks than whites has remained unknown. We tested the hypothesis that sickle cell trait or hemoglobin C trait is an independent risk factor for invasive pneumococcal disease.
Eligible children were born in Tennessee (1996–2003), had a newborn screen, enrolled in TennCare aged <1 year, and resided in a Tennessee county with laboratory-confirmed, pneumococcal surveillance. Race/ethnicity was ascertained from birth certificates. Children were followed through 2005 until loss of enrollment, pneumococcal disease episode, 5th birthday or death. We calculated incidence rates by race/ethnicity and hemoglobin type before and after pneumococcal conjugate vaccine (PCV7) introduction. Poisson regression analyses compared IPD rates among blacks with sickle cell trait or hemoglobin C trait to whites and blacks with normal hemoglobin, controlling for age, gender, time (pre-PCV7, transition year or post-PCV7) and high-risk conditions (i.e. heart disease).
Over 10 years, 415 invasive pneumococcal disease episodes occurred during 451,594 observed child-years. Before PCV7 introduction, disease rates/100,000 child-years were 2941 for blacks with sickle cell disease, 258 for blacks with sickle cell trait or hemoglobin C trait and 188, 172, and 125 for blacks, whites, and Hispanics with normal hemoglobin. Post-PCV7, rates declined for all groups. Blacks with sickle cell trait or hemoglobin C trait had 77% (95% CI 22%–155%) and 42% (95% CI 1%–100%) higher rates than whites and blacks with normal hemoglobin.
Black children with sickle cell trait or hemoglobin C trait have an increased risk of invasive pneumococcal disease.
In recent years (2000 to 2007), ambient levels of fine particulate matter (PM2.5) have continued to decline as a result of interventions, but the decline has been at a slower rate than previous years (1980 to 2000). Whether these more recent and slower declines of PM2.5 levels continue to improve life expectancy and whether they benefit all populations equally is unknown.
We assembled a dataset for 545 U.S. counties consisting of yearly county-specific average PM2.5, yearly county-specific life expectancy, and several potentially confounding variables measuring socioeconomic status, smoking prevalence and demographic characteristics for the years 2000 and 2007. We used regression models to estimate the association between reductions in PM2.5 and changes in life expectancy for the period 2000 to 2007.
A decrease of 10 µg/m3 in the concentration of PM2.5 was associated with an increase in mean life expectancy of 0.35 years SD= 0.16 years, p = 0.033). This association was stronger in more urban and densely populated counties.
Reductions in PM2.5 were associated with improvements in life expectancy for the period 2000 to 2007. Air pollution control in the last decade has continued to have a positive impact on public health.
Economic disadvantage is associated with depression and suicide. We sought to determine whether economic disadvantage reduces the effectiveness of depression treatments received in primary care.
We conducted differential-effects analyses of the Prevention of Suicide in Primary Care Elderly: Collaborative Trial (PROSPECT), a primary care-based randomized, controlled trial for late-life depression and suicidal ideation conducted between 1999 and 2001, which included 514 patients with major depression or clinically significant minor depression.
The intervention effect, defined as change in depressive symptoms from baseline, was stronger among persons reporting financial strain at baseline (differential effect size= −4.5 Hamilton Depression Rating Scale points across the study period; 95% confidence interval = −8.6 to −0.3). We found similar evidence for effect modification by neighborhood poverty, although the intervention effect weakened after the initial 4 months of the trial for participants residing in poor neighborhoods. There was no evidence of substantial differences in the effectiveness of the intervention on suicidal ideation and depression remission by economic disadvantage.
Economic conditions moderated the effectiveness of primary care-based treatment for late-life depression. Financially strained individuals benefitted more from the intervention; we speculate this was because of the enhanced treatment management protocol, which lead to a greater improvement in the care received by these persons. People living in poor neighborhoods experienced only temporary benefit from the intervention. Thus, multiple aspects of economic disadvantage affect depression treatment outcomes; additional work is needed to understand the underlying mechanisms.
Randomized trials have examined short-term effects of lifestyle interventions for diabetes prevention only among high-risk individuals. Prospective studies have examined the associations between lifestyle factors and diabetes in healthy populations but have not characterized the intervention. We estimated long-term effects of “hypothetical” lifestyle interventions on diabetes in a prospective study of healthy women, using the parametric g-formula.
Using data from the Nurses’ Health Study, we followed 76,402 women from 1984 to 2008. We estimated the risk of type 2 diabetes under 8 “hypothetical” interventions: quitting smoking, losing weight by 5% every 2 years if overweight/obese, exercising at least 30 minutes a day, eating less than 3 servings a week of red meat, eating at least 2 servings a day of whole grain, drinking 2 or more cups of coffee a day, drinking 5 or more grams of alcohol a day and drinking less than 1 serving of soda a week.
The 24-year risk of diabetes was 9.6% under no intervention and 4.3% when all interventions were imposed (55% lower risk [95% confidence interval= 47% to 63%]). The most effective interventions were weight loss (24% lower risk), physical activity (19%) and moderate alcohol use (19%). Overweight/obese women would benefit the most, with 10.8 percentage points reduction in 24-year risk of diabetes. The validity of these estimates relies on absence of unmeasured confounding, measurement error, and model misspecification.
A combination of dietary and non-dietary lifestyle modifications, begun in mid-life or later in relatively healthy women, could have prevented at least half of the cases of type 2 diabetes in this cohort of US women.
There is great interest in understanding the role of weight dynamics over the life cycle in predicting the incidence of disease and death. Beginning with a Medline search, we identify, classify and evaluate the major approaches that have been used to study these dynamics. We identify four types of models: additive models, duration-of-obesity models, additive-weight-change models, and interactive models. We develop a framework that integrates the major approaches and shows that they are often nested in one another, a property that facilitates statistical comparisons.
Our criteria for evaluating models are two-fold: the model's interpretability and its ability to account for observed variation in health outcomes. We apply two sets of nested models to data on adults aged 50-74 years at baseline in two national probability samples drawn from NHANES. One set of models treats obesity as a dichotomous variable and the other treats it as a continuous variable. In three out of four applications, a fully interactive model does not add significant explanatory power to the simple additive model. In all four applications, little explanatory power is lost by simplifying the additive model to a duration model in which the coefficients of weight at different ages are set equal to one another. Other versions of a duration-of-obesity model also perform well, underscoring the importance of obesity at early adult ages for mortality at older ages.
Associations between blood pressure (BP) and ambient air pollution
have been inconsistent. No studies have used ambulatory BP monitoring and
outdoor home air-pollutant measurements with time-activity-location data. We
address these gaps in a study of 64 elderly subjects with coronary artery
disease, living in retirement communities in the Los Angeles basin.
Subjects were followed up for 10 days with hourly waking ambulatory
BP monitoring (n = 6539 total measurements), hourly electronic diaries for
perceived exertion and location, and real-time activity monitors
(actigraphs). We measured hourly outdoor home pollutant gases, particle
number, PM2.5, organic carbon, and black carbon. Data were
analyzed with mixed models controlling for temperature, posture, actigraph
activity, hour, community, and season.
We found positive associations of systolic and diastolic BP with air
pollutants. The strongest associations were with organic carbon (especially
its estimated fossil-fuel- combustion fraction), multiday average exposures,
and time periods when subjects were at home. An interquartile increase in
5-day average organic carbon (5.2 μg/m3)
was associated with 8.2 mm Hg higher mean systolic BP (95% confidence
interval = 3.0–13.4) and 5.8 mm Hg higher mean diastolic BP
(3.0–8.6). Associations of BP with 1–8 hour average air
pollution were stronger with reports of moderate to strenuous physical
exertion but not with higher actigraph motion. Associations were also
stronger among 12 obese subjects.
Exposure to primary organic components of fossil fuel combustion near
the home were strongly associated with increased ambulatory BP in a
population at potential risk of heart attack. Low fitness or obesity may
increase the effects of pollutants.
Gestational exposure to famine has been associated with several chronic diseases in adulthood, but few studies in humans have related prenatal famine exposure to health-related quality of life. We used the circumstances of the Dutch Famine of 1944-1945 (during which official rations were =900 kcal/day for 24 weeks) to assess whether exposure to famine prior to conception or at specified stages of pregnancy was related to self-reported health-related quality of life and depressive symptoms in adulthood.
We studied 923 individuals including persons born in western Holland between January 1945 and March 1946, persons born in the same 3 institutions in 1943 and 1947 and same-sex siblings of persons in series 1 or 2. Between 2003 and 2005 (mean age 59 y), we assessed self-reported quality of life with the Short Form 36 questionnaire and derived mental and physical component scores. Depressive symptoms were assessed with the Center for Epidemiologic Studies Depression scale.
Mean mental and physical component scores were 52.4 (SD = 9.4) and 48.9 (9.0), respectively. The mean depression score was 11.6 (7.4). Age-, sex- and schooling-adjusted estimates for mutually adjusted exposures were -2.48 for the mental component score with exposure before conception (95% confidence interval = -4.46 to 0.50) and 0.07 with exposure during pregnancy (-1.15 to 1.29). Adjusted estimates for the physical component score were 1.26 with exposure before conception (-0.67 to 3.19) and -0.73 with exposure during pregnancy (1.94 to 0.48). Adjusted estimates for the depression score were 2.07 with exposure before conception (0.60 to 3.54) and 0.96 with exposure during pregnancy (0.09 to 1.88). There was no evidence of heterogeneity of effects by specific periods of pregnancy exposed to famine.
A mother's exposure to famine prior to conception of her offspring was associated with lower self-reported measures of mental health and quality of life in her adult offspring.
Obesity is a risk factor for renal cell (or renal) cancer. The increasing prevalence of obesity may be contributing to the rising incidence of this cancer over the past several decades. The effects of early-age obesity and change in body mass index (BMI) on renal cancer have been studied less thoroughly, and the influence of race has never been formally investigated.
Using data gathered as part of a large case-control study of renal cancer (1,214 cases and 1,234 controls), we investigated associations with BMI at several time points, as well as with height. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were computed using logistic regression modeling. Race- and sex-stratified analyses were conducted to evaluate subgroup differences.
Obesity (BMI ≥ 30 kg/m2) early in adulthood (OR=1.6 [95% CI=1.1 to 2.4]) and 5 years before diagnosis (1.6 [1.1 to 2.2]) was associated with renal cancer. The association with early-adult obesity was stronger among whites than blacks (Test for interaction, P=0.006), while the association with obesity near diagnosis was marginally stronger in women than men (Test for interaction, P=0.08). The strongest association with renal cancer was observed for obese whites both in early adulthood and prior to interview (2.6 [1.5 to 4.4]); this association was not present among blacks. Estimates of the annual excess rate of renal cancer (per 100,000 persons) attributed to both overweight and obesity (BMI > 25 kg/m2) ranged from 9.9 among black men to 5.6 among white women.
Obesity, both early and later in life, is associated with an increased risk of renal cancer. The association with early obesity appears to be stronger among whites than blacks.
Causal inference; infectious disease; infectiousness; interference; principal stratification; vaccine efficacy
Existing methods for estimation of mortality attributable to influenza are limited by methodological and data uncertainty. We have used proxies for disease incidence of the three influenza co-circulating subtypes (A/H3N2, A/H1N1 and B) that combine data on influenza-like illness consultations and respiratory specimen testing to estimate influenza-associated mortality in the US between 1997 and 2007.
Weekly mortality rate for several mortality causes potentially affected by influenza was regressed linearly against subtype-specific influenza incidence proxies, adjusting for temporal trend and seasonal baseline, modeled by periodic cubic splines.
Average annual influenza-associated mortality rates per 100,000 individuals were estimated for the following underlying causes of death: for pneumonia and influenza, 1.73 (95% confidence interval= 1.53 to 1.93); for chronic lower respiratory disease, 1.70 (1.48 to 1.93); for all respiratory causes, 3.58 (3.04 to 4.14); for myocardial infarctions, 1.02 (0.85 to 1.2); for ischemic heart disease, 2.7 (2.23 to 3.16); for heart disease, 3.82 (3.21 to 4.4); for cerebrovascular deaths, 0.65 (0.51 to 0.78); for all circulatory causes, 4.6 (3.79 to 5.39); for cancer, 0.87 (0.68 to 1.05); for diabetes, 0.33 (0.26 to 0.39); for renal disease, 0.19 (0.14 to 0.24); for Alzheimer disease, 0.41 (0.3 to 0.52); and for all causes, 11.92 (10.17 to 13.67). For several underlying causes of death, baseline mortality rates changed after the introduction of the pneumococcal conjugate vaccine.
The proposed methodology establishes a linear relation between influenza incidence proxies and excess mortality, rendering temporally consistent model fits, and allowing for the assessment of related epidemiologic phenomena such as changes in mortality baselines.