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Introduction Irregular sleep duration may disrupt circadian rhythms necessary for optimal cardiovascular function. Yet, few studies have examined irregular sleep duration in relation to cardiovascular health, particularly among diverse cohorts of reproductive-age women. This study examined associations between sleep duration irregularities across the menstrual cycle and cardiovascular disease biomarkers in a cohort of healthy, premenopausal women. Methods We utilized the BioCycle micro-longitudinal cohort study of 259 regularly menstruating women aged 18–44 years. This measurement-intense study collected cardiovascular disease biomarkers at key reproductive time-points along the menstrual cycle (approximately days 2,7,12,13,14,18,22,27 of a 28-day cycle) across two cycles. Specifically, we assessed serum high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol, triglycerides, and C-reactive protein (CRP). Women recorded sleep duration in daily diaries concurrently. We computed a system of four mathematical measures, the L-moments, robust versions of location, dispersion, skewness, and kurtosis for series of recorded sleep durations. Using linear mixed models with random intercepts and inverse probability weighting we estimated associations between irregular sleep duration and cardiovascular disease biomarkers in all women and within a subset of non-white women. Adjusted analysis accounted for baseline characteristics and time-varying hormonal changes across the menstrual cycle. Results Woman-specific mean sleep duration ranged from 4.4 to 10.6 hours. A one-hour increase in dispersion of sleep duration was associated with a lower mean LDL and higher mean HDL for non-white women (-19.4%, 95%CI -30.9,-6.0% and 24.7%, 95%CI 8.2,43.0, respectively). Unbalanced (skewed) sleep duration, frequent short or long hours, was associated with higher mean CRP for all women and non-white women (99.3%, 95%CI 17.2,238.9 and 126.7%, 95%CI 3.1,398.2, respectively), but lower total cholesterol (-10.9%, 95%CI -19.9,-1.0). Finally, irregular sleep durations, extreme short and long sleep bouts (kurtosis), were associated with reduced mean HDL for all women, and non-white women (-17.1%, 95%CI -31.1,-0.2 and -25.4%, 95%CI -39.5,-8.0, respectively). Conclusion This micro-longitudinal study of premenopausal women found associations between irregularities in sleep duration and differences in CRP, LDL, HDL and total cholesterol, but not with triglycerides. These data suggest that even in young and healthy women, irregularities in sleep duration could have a potential impact on cardiometabolic health. Support (If Any) Dr. Dunietz was supported by a Mentored Research Scientist Development Award from the National Heart, Lung, and Blood Institute (K01 HL144914). This work was supported in part by the Intramural Research Program of the NIH, Eunice Kennedy Shriver National Institute of Child Health and Human Development (authors KAM, JRF, EFS, SLM; The BioCycle Study was funded under the following intramural contracts: HHSN275200403394C HHSN275201100002I, and Task 1 HHSN27500001).

ObjectiveInitiatives to reduce neighborhood-based health disparities require access to meaningful, timely, and local information regarding health behavior and its determinants. We examined the validity of Twitter as a source of information for neighborhood-level analysis of dietary choices and attitudes.Materials and MethodsWe analyzed the “healthiness” quotient and sentiment in food-related tweets at the census tract level, and associated them with neighborhood characteristics and health outcomes. We analyzed keywords driving the differences in food healthiness between the most and least-affluent tracts, and qualitatively analyzed contents of a random sample of tweets.ResultsSignificant, albeit weak, correlations existed between healthiness and sentiment in food-related tweets and tract-level measures of affluence, disadvantage, race, age, U.S. density, and mortality from conditions associated with obesity. Analyses of keywords driving the differences in food healthiness revealed foods high in saturated fat (eg, pizza, bacon, fries) were mentioned more frequently in less-affluent tracts. Food-related discussion referred to activities (eating, drinking, cooking), locations where food was consumed, and positive (affection, cravings, enjoyment) and negative attitudes (dislike, personal struggles, complaints).DiscussionTweet-based healthiness scores largely correlated with offline phenomena in the expected directions. Social media offer less resource-intensive data collection methods than traditional surveys do. Twitter may assist in informing local health programs that focus on drivers of food consumption and could inform interventions focused on attitudes and the food environment.ConclusionsTwitter provided weak but significant signals concerning food-related behavior and attitudes at the neighborhood level, suggesting its potential usefulness for informing local health disparity reduction efforts.

Risk factors can drive socioeconomic inequalities in cardiovascular disease (CVD) through differential exposure and differential vulnerability. In this paper, we show how econometric decomposition directly enables simultaneous, policy-oriented assessment of these 2 mechanisms. We specifically estimate contributions of neighborhood environment and proximal risk factors to socioeconomic inequality in CVD incidence via these mechanisms. We followed 5,608 participants in the Multi-Ethnic Study of Atherosclerosis (2000-2012) to their first CVD event (median length of follow-up, 12.2 years). We used a summary measure of baseline socioeconomic position (SEP). Covariates included baseline demographics, neighborhood characteristics, and psychosocial, behavioral, and biomedical risk factors. Using Poisson models, we decomposed the difference (inequality) in incidence rates between low- and high-SEP groups into contributions of 1) differences in covariate means (differential exposure) and 2) differences in CVD risk associated with covariates (differential vulnerability). Notwithstanding large uncertainty in neighborhood estimates, our analysis suggested that differential exposure to poorer neighborhood socioeconomic conditions, adverse social environment, diabetes, and hypertension accounted for most of the inequality. Psychosocial and behavioral contributions were negligible. Further, neighborhood SEP, female sex, and white race were more strongly associated with CVD among low-SEP (vs. high-SEP) participants. These differentials in vulnerability also accounted for nontrivial portions of the inequality and could have important implications for intervention.

Chahal et al. (Am J Epidemiol. 2018;187(10):2073-2079) assessed the risk of placental abruption due to physical exertion using a case-crossover design. The authors found an increased risk of placental abruption following increased physical exertion in the hour prior to the abruption. The risk was greater among women who were primarily sedentary during pregnancy or prior to becoming pregnant compared with those who were more physically active. The authors used a case-crossover design to assess the association of an intermittent exposure on an acute event. Chahal et al. address the limitations of the study, including the inability to control for time-varying confounders as well as the potential for recall bias. The public health implications of the study must be carefully evaluated given that physical activity prior to and during pregnancy can lead to healthy outcomes and is likely recommended. While the current study is unable to determine the type of physical exertion associated with placental abruption, future studies are recommended to determine the type of activity that presents increased risk. Additionally, studies among larger samples and in other countries will help determine the generalizability of the results.

The lipophilic index (LI), a mean measure of fatty acid melting points, has been proposed to capture overall fatty acid profile and may play an important role in the etiology of coronary heart disease. We aimed to determine the association between LI in diet and in adipose tissue and metabolic risk factors for myocardial infarction (MI) and risk of MI. We used a population-based, matched case-control study of nonfatal first acute MI conducted in Costa Rica between 1994 and 2004, with 1,627 case-control pairs. The LI is defined as the mean of the melting points of specific fatty acids in diet or adipose tissue. LIs in diet and adipose tissue were significantly associated with higher plasma triglyceride concentrations, low-density lipoprotein cholesterol concentrations, and low-density:high-density lipoprotein cholesterol ratio. Comparing extreme quintiles for the LI in diet or adipose tissue, the odds ratios for MI were 1.57 (95% confidence interval: 1.22, 2.02; P for trend < 0.001) for dietary LI and 1.30 (95% confidence interval: 1.00, 1.69; P for trend = 0.02) for adipose tissue LI in the multivariable models. We hypothesize that a higher LI in diet and in adipose tissue represents decreased fatty acid fluidity and could play an important role in the etiology of coronary heart disease.

Reduced rank regression and partial least-squares regression (PLS) are proposed alternatives to principal component analysis (PCA). Using all 3 methods, the authors derived dietary patterns in Costa Rican data collected on 3,574 cases and controls in 1994-2004 and related the resulting patterns to risk of first incident myocardial infarction. Four dietary patterns associated with myocardial infarction were identified. Factor 1, characterized by high intakes of lean chicken, vegetables, fruit, and polyunsaturated oil, was generated by all 3 dietary pattern methods and was associated with a significantly decreased adjusted risk of myocardial infarction (28%-46%, depending on the method used). PCA and PLS also each yielded a pattern associated with a significantly decreased risk of myocardial infarction (31% and 23%, respectively); this pattern was characterized by moderate intake of alcohol and polyunsaturated oil and low intake of high-fat dairy products. The fourth factor derived from PCA was significantly associated with a 38% increased risk of myocardial infarction and was characterized by high intakes of coffee and palm oil. Contrary to previous studies, the authors found PCA and PLS to produce more patterns associated with cardiovascular disease than reduced rank regression. The most effective method for deriving dietary patterns related to disease may vary depending on the study goals.

Coffee seems to have distinct acute and long-term effects on health, which can be modified by genetic background. Coffee consumption is potentially protective against the development of type 2 diabetes, but given the lack of a solid biological basis for this association, and the possible adverse cardiovascular effects of coffee, recommendations for optimal coffee intake are difficult to establish.

Little is documented about the performance of the food frequency questionnaire (FFQ) in US minority groups and in populations in developing countries. The authors applied a novel technique, the method of triads, to assess the validity and reproducibility of the FFQ among Hispanics. The subjects were men (n = 78) and women (n = 42) living in Costa Rica. Seven 24-hour dietary recalls and two FFQ interviews (12 months apart) were conducted between 1995 and 1998 to estimate dietary intake during the past year. Plasma and adipose tissue samples were collected from all subjects. Validity coefficients, which measure the correlation between observed and "true" dietary intake, were also estimated. The median validity coefficients for tocopherols and carotenoids estimated by dietary recall, the average of the two FFQs, and plasma were 0.71, 0.60, and 0.52, respectively. Compared with adipose tissue, plasma was a superior biomarker for carotenoids and tocopherols. Adipose tissue was a poor biomarker for saturated and monounsaturated fatty acids but performed well for polyunsaturated fatty acids (validity coefficients, 0.45-1.01) and lycopene (validity coefficient, 0.51). This study also showed that biomarkers did not perform better than the FFQ and that they should be used to complement the FFQ rather than substitute for it.