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Abstract Context Polycystic ovary syndrome (PCOS), a condition of androgen excess in women, is associated with cardiometabolic risk factors; however, this association is not fully characterized in a population-based sample of premenopausal women and high-risk groups such as Hispanics/Latinas. Objective We examined the association of PCOS signs and metabolic syndrome (MetS) in premenopausal Hispanic/Latina women. Methods This cross-sectional analysis includes 1427 women age 24 to 44 years from the Hispanic Community Health Study/Study of Latinos. PCOS signs included menstrual cycle greater than 35 days or irregular, self-reported PCOS, and oral contraceptive use to regulate periods or acne, and a composite of 1 or more PCOS signs. We calculated odds ratios (OR) and 95% CI for MetS, accounting for sociodemographic factors and the complex survey design; an additional model included body mass index (BMI). Results The mean age was 34 years and 30% reported any PCOS sign. The odds of MetS were higher in women reporting cycles greater than 35 days or irregular (OR 1.63; CI: 1.07-2.49) vs cycles 24 to 35 days, self-reported PCOS (OR 2.49; CI: 1.38-4.50) vs no PCOS, and any PCOS sign (OR 1.58; CI: 1.10-2.26) vs none. We found no association between OC use to regulate periods or acne and MetS (OR 1.1; CI: 0.6-1.8). When adjusting for BMI, only the association of self-reported PCOS and MetS was attenuated (OR 1.78; CI: 0.92-3.44). Conclusions In Hispanic/Latina women, irregular menstrual cycles, self-reported PCOS, and any PCOS sign were associated with MetS and could indicate women at metabolic disease risk.

In the present study, we aimed to identify the changes or stability in the structure of dietary patterns and tracking, trends and factors related to the adherence to these dietary patterns in China from 1991 to 2009. We analysed dietary data collected during seven waves of the China Health and Nutrition Survey and included 9253 adults with complete dietary data for three or more waves. Dietary intake assessment was carried out over a 3 d period with 24 h recalls and a household food inventory. Using factor analysis in each wave, we found that the structure of the two dietary patterns identified remained stable over the studied period. The traditional southern dietary pattern was characterised by high intakes of rice, fresh leafy vegetables, low-fat red meat, pork, organ meats, poultry and fish/seafood and low intakes of wheat flour and maize/coarse grains and the modern high-wheat dietary pattern was characterised by high intakes of wheat buns/breads, cakes/cookies/pastries, deep-fried wheat, nuts/seeds, starchy root/tuber products, fruits, eggs/egg products, soya milk, animal-based milk and instant noodles/frozen dumplings. Temporal tracking (maintenance of a relative position over time) was higher for the traditional southern dietary pattern, whereas adherence to the modern high-wheat dietary pattern had an upward trend over time. Higher income, education and urbanicity levels were positively associated with both the dietary patterns, but the association became weaker in the later years. These results suggest that even in the context of rapid economic changes in China, the way people chose to combine their foods remained relatively stable. However, the increasing popularity of the modern high-wheat dietary pattern, a pattern associated with several energy-dense foods, is a cause of concern.

Hispanic/Latino populations have a high prevalence of cardiovascular risk factors and may be at risk for sleep-disordered breathing (SDB). An understanding of SDB among these populations is needed given evidence that SDB increases cardiovascular risk. To quantify SDB prevalence in the U.S. Hispanic/Latino population and its association with symptoms, risk factors, diabetes, and hypertension; and to explore variation by sex and Hispanic/Latino background. Cross-sectional analysis from the baseline examination of the Hispanic Community Health Study/Study of Latinos. The apnea-hypopnea index (AHI) was derived from standardized sleep tests; diabetes and hypertension were based on measurement and history. The sample of 14,440 individuals had an age-adjusted prevalence of minimal SDB (AHI ≥ 5), moderate SDB (AHI ≥ 15), and severe SDB (AHI ≥ 30) of 25.8, 9.8, and 3.9%, respectively. Only 1.3% of participants reported a sleep apnea diagnosis. Moderate SDB was associated with being male (adjusted odds ratio, 2.7; 95% confidence interval, 2.3-3.1), obese (16.8; 11.6-24.4), and older. SDB was associated with an increased adjusted odds of impaired glucose tolerance (1.7; 1.3-2.1), diabetes (2.3; 1.8-2.9), and hypertension. The association with hypertension varied across background groups with the strongest associations among individuals of Puerto Rican and Central American background. SDB is prevalent in U.S. Latinos but rarely associated with a clinical diagnosis. Associations with diabetes and hypertension suggest a large burden of disease may be attributed to untreated SDB, supporting the development and evaluation of culturally relevant detection and treatment approaches.

Background Hispanics living in the USA may have unrecognized potential birthplace and lifestyle influences on the gut microbiome. We report a cross-sectional analysis of 1674 participants from four centers of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), aged 18 to 74 years old at recruitment. Results Amplicon sequencing of 16S rRNA gene V4 and fungal ITS1 fragments from self-collected stool samples indicate that the host microbiome is determined by sociodemographic and migration-related variables. Those who relocate from Latin America to the USA at an early age have reductions in Prevotella to Bacteroides ratios that persist across the life course. Shannon index of alpha diversity in fungi and bacteria is low in those who relocate to the USA in early life. In contrast, those who relocate to the USA during adulthood, over 45 years old, have high bacterial and fungal diversity and high Prevotella to Bacteroides ratios, compared to USA-born and childhood arrivals. Low bacterial diversity is associated in turn with obesity. Contrasting with prior studies, our study of the Latino population shows increasing Prevotella to Bacteroides ratio with greater obesity. Taxa within Acidaminococcus, Megasphaera, Ruminococcaceae, Coriobacteriaceae, Clostridiales, Christensenellaceae, YS2 (Cyanobacteria), and Victivallaceae are significantly associated with both obesity and earlier exposure to the USA, while Oscillospira and Anaerotruncus show paradoxical associations with both obesity and late-life introduction to the USA. Conclusions Our analysis of the gut microbiome of Latinos demonstrates unique features that might be responsible for health disparities affecting Hispanics living in the USA.

Background Measures to assess neighborhood environments are needed to better understand the salient features that may enhance outdoor physical activities, such as walking and bicycling for transport or leisure. The purpose of this study was to derive constructs to describe neighborhoods using both primary (neighborhood audit) and secondary (geographic information systems) data. Methods We collected detailed information on 10,770 road segments using an audit and secondary data. The road segment sample was randomly split into an exploratory (60%) and validation sample (40%) for cross-validation. Using the exploratory sample (n = 6,388), seven a priori constructs were assessed separately (functionality, safety, aesthetics, destinations, incivilities, territorality, social spaces) by urbanicity using multi-group confirmatory factor analysis (CFA). Additionally, new a posteriori constructs were derived using exploratory factor analysis (EFA). For cross-validation (n = 4,382), we tested factor loadings, thresholds, correlated errors, and correlations among a posteriori constructs between the two subsamples. Two-week test-retest reliability of the final constructs using a subsample of road segments (n = 464) was examined using Spearman correlation coefficients. Results CFA indicated the a priori constructs did not hold in this geographic area, with the exception of physical incivilities. Therefore, we used EFA to derive a four-factor solution on the exploratory sample: arterial or thoroughfare, walkable neighborhood, physical incivilities, and decoration. Using CFA on the validation sample, the internal validity for these a posteriori constructs was high (range 0.43 to 0.73) and the fit was acceptable. Spearman correlations indicated the arterial or thoroughfare factor displayed near perfect reliability in both urban and rural segments (r = 0.96). Both the physical incivilities factor and the walkable neighborhood factor had substantial to near perfect reliability in both urban and rural segments (r = 0.77 to 0.78 and r = 0.79 to 0.82, respectively). The decoration factor displayed moderate reliability in urban segments (r = 0.50; 95% CI: 0.38–0.60) and lower reliability in rural segments (r = 0.39; 95% CI: 0.25–0.52). Conclusion The results of our analyses yielded four reliably and objectively measured constructs that will be used to explore associations with physical activity in urban and rural North Carolina. These constructs should be explored in other geographic areas to confirm their usefulness elsewhere.

We examined the association between dietary patterns and diabetes using the strengths of two methods: principal component analysis (PCA) to identify the eating patterns of the population and reduced rank regression (RRR) to derive a pattern that explains the variation in glycated Hb (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR) and fasting glucose. We measured diet over a 3 d period with 24 h recalls and a household food inventory in 2006 and used it to derive PCA and RRR dietary patterns. The outcomes were measured in 2009. Adults (n 4316) from the China Health and Nutrition Survey. The adjusted odds ratio for diabetes prevalence (HbA1c≥6·5 %), comparing the highest dietary pattern score quartile with the lowest, was 1·26 (95 % CI 0·76, 2·08) for a modern high-wheat pattern (PCA; wheat products, fruits, eggs, milk, instant noodles and frozen dumplings), 0·76 (95 % CI 0·49, 1·17) for a traditional southern pattern (PCA; rice, meat, poultry and fish) and 2·37 (95 % CI 1·56, 3·60) for the pattern derived with RRR. By comparing the dietary pattern structures of RRR and PCA, we found that the RRR pattern was also behaviourally meaningful. It combined the deleterious effects of the modern high-wheat pattern (high intakes of wheat buns and breads, deep-fried wheat and soya milk) with the deleterious effects of consuming the opposite of the traditional southern pattern (low intakes of rice, poultry and game, fish and seafood). Our findings suggest that using both PCA and RRR provided useful insights when studying the association of dietary patterns with diabetes.

The prevalence of type 2 diabetes is increasing among the Hispanic/Latino population. Type 2 diabetes incidence rates vary between neighborhoods, but no single aspect of the neighborhood environment is known to cause type 2 diabetes. Using data from the Hispanic Community Health Study/Study of Latinos cohort of 16,415 Hispanic/Latino adults in four major US cities, we conducted a neighborhood environment-wide association study to identify neighborhood measures or clusters of measures associated with diabetes incidence. Two-hundred and four neighborhood measures were calculated at the census tract level or within a 1-km buffer of participants’ residential addresses. Independent covariate-adjusted and survey-weighted Poisson regressions were run for each neighborhood measure and incident diabetes. Principal component analysis of neighborhood measures was conducted to reduce dimensionality. No coherent pattern of neighborhood measures or principal component scores were associated with diabetes incidence within the cohort, though established individual-level risk factors such as age and family history were strongly associated with diabetes incidence. Results from our analysis did not indicate specific neighborhood measures, clusters, or patterns. Individual, rather than neighborhood, factors distinguish incident diabetes cases from non-cases.

To describe sleep characteristics of shift workers compared with day workers from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sueño ancillary study and test the hypothesis that shift work is associated with shorter sleep duration, worse sleep quality, greater sleep variability, and other sleep/health-related factors. Employed adults (N = 1253, mean age 46.3 years, 36.3% male) from the Sueño study were included. Measures of sleep duration, timing, regularity, and continuity were calculated from 7 days of wrist-activity monitoring. Participants provided information on demographics, employment, work schedule (day, afternoon, night, split, irregular, and rotating), sleepiness, depressive symptoms, medications, caffeine, and alcohol use. Survey linear regression adjusting for age, sex, background, site, number of jobs, and work hours was used. In age and sex-adjusted models, all shift work schedules were associated with delayed sleep timing. Night and irregular schedules were associated with shorter sleep duration, greater napping, and greater variability of sleep. Afternoon and rotating shifts were associated with lower sleep regularity. In fully adjusted models, night and irregular schedules remained associated with shorter sleep duration, later sleep midpoint, and greater variability in sleep measures compared with day schedules. Split schedules were associated with, less time in bed, less sleep fragmentation, and less wake during the sleep period than day schedules. Work schedule significantly affects sleep-wake with substantial differences between day work and other types of schedule. Detailed assessment of work schedule type not just night shift should be considered as an important covariate when examining the association between sleep and health outcomes.

Background Higher levels of moderate-to-vigorous physical activity have been associated with a lower risk of diabetes, but less is known about how daily step counts (steps/day) are associated with diabetes risk. Therefore, we examined the association of steps/day and step intensity with incident diabetes. Methods We included 6634 adults from the population-based prospective cohort Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (2008–2017). Cox proportional hazard models that accounted for complex survey design and sampling weights were used to estimate the association of baseline accelerometer-assessed steps/day and step intensity with 6-year risk of incident diabetes as hazard ratios (HR) and 95% confidence intervals (CI). We further examined whether the percent of intense steps at a given accumulation of steps/day was associated with diabetes risk, and if associations were modified by specific cohort characteristics. Results The average age of cohort members was 39 years and 52% were female. Adults had an average of 8164 steps/day and spent 12 min/day in brisk ambulation ( > 100 steps/min). Over 6 years of follow-up, there were 1115 cases of diabetes. There was a suggestive lower risk of diabetes with more steps/day– adults had a 2% lower risk per 1000 steps/day (HR = 0.98 (95% CI 0.95, 1.00)). Inverse associations between average steps/day and diabetes incidence were observed across many cohort characteristics, but most importantly among adults at high risk for diabetes – those who were older, or had obesity or prediabetes. Adults who accumulated 17 min/day in brisk ambulation compared to < 2 min/day had a 31% lower risk of diabetes (HR = 0.69 (95% CI 0.53, 0.89)). A greater percent of intense steps for a given accumulation of steps/day was associated with further risk reduction. Conclusion Adults who accumulate more daily steps may have a lower risk of diabetes. Accumulating more steps/day and greater step intensity appear to be important targets for preventing diabetes.

Background A posteriori dietary patterns (DPs) are critical for capturing actual dietary behaviour. However, assessing their reproducibility across (sub)populations requires novel modelling approaches beyond descriptive statistics. Multi-study factor analysis derives DPs that are shared among all studies/subpopulations and those specific to a study or subpopulation of interest. Bayesian implementation of the multi-study factor analysis (BMSFA) is more flexible than frequentist as it imposes fewer assumptions and improves factor selection. Methods We applied BMSFA to 24-h dietary recalls from the baseline visit (2008–2011) of the US Hispanic Community Health Study/Study of Latinos ( n  = 16,415). The analysis was conducted on 42 common nutrients to identify shared and subpopulation-specific DPs. Subpopulations were defined based on the cross-classification of ethnic background (Cuban, Dominican Republic, Mexican, Puerto Rican, Central and South American) and study site (Bronx, Chicago, Miami, San Diego) resulting in 12 Ethnic Background Site (EBS) categories. Regression analysis characterized DPs in terms of food groups, overall diet quality, socio-demographic/lifestyle factors, adjusting for survey design. Results We identified four shared DPs across all EBS categories: Plant-based foods , Processed foods, Dairy products , and Seafood . Additionally, twelve EBS-specific DPs were identified—one for each EBS category. Most EBS-specific DPs were further grouped into overarching profiles: Animal vs. vegetable source, Animal source only , and Poultry vs. dairy products , to capture nuances within animal-based DPs. Puerto Rican background participants from Chicago expressed a strikingly different DP from all others (i.e., high on beta-carotene and low on starch/iron/thiamin). Higher overall diet quality was observed with increasing categories of Plant-based foods , Seafood , and the “Puerto Rican background – Chicago” EBS-specific DP, whereas increasing categories of Dairy products , Processed foods , and the remaining EBS-specific DPs were related to lower diet quality. Compared to non-US-born participants, US-born individuals had significantly higher adjusted mean scores in absolute value for most DPs. Specifically, they exhibited lower adherence to the Plant-based foods and Dairy products DPs but higher adherence to Processed foods , Seafood , and six EBS-specific DPs. Conclusions The BMSFA successfully captured sources of dietary homogeneity and heterogeneity among US Hispanic/Latino adults across ethnic backgrounds and study sites. The study highlighted the crucial role of nativity on DPs.