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Sleep as a potential fundamental contributor to disparities in cardiovascular health.

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      Abstract

      Optimal sleep is integral to health but is commonly not obtained. Despite its wide-ranging public health impact, sleep health is considered only rarely by policy makers, employers, schools, and others whose policies and structures can adversely affect sleep. An inadequate duration of sleep and poor-quality sleep are prevalent in minority and low-income populations, and may be fundamental to racial and socioeconomic status inequities that contribute to a range of health conditions, including cardiovascular disease (CVD). This review examines the relationship between sleep and disparities in CVD. We describe the public health importance of sleep and the role of sleep duration, as well as the two most common disorders (sleep apnea and insomnia) as risk factors for a number of chronic diseases. We use a multilevel model focused on population health and health disparities, which is based on the notion that individual behaviors, such as sleep, are influenced by complex and dynamic interrelations among individuals and their physical and social environments. We also describe modifiable factors that contribute to insufficient sleep and circadian misalignment, propose potential interventions in various sectors (e.g., neighborhoods, schools, workplaces) that can address social structures that contribute to disparities, and recommend areas for future research. Integrating sleep into public health research will identify novel approaches for closing gaps in health disparities.

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      Prevalence of childhood and adult obesity in the United States, 2011-2012.

      More than one-third of adults and 17% of youth in the United States are obese, although the prevalence remained stable between 2003-2004 and 2009-2010. To provide the most recent national estimates of childhood obesity, analyze trends in childhood obesity between 2003 and 2012, and provide detailed obesity trend analyses among adults. Weight and height or recumbent length were measured in 9120 participants in the 2011-2012 nationally representative National Health and Nutrition Examination Survey. In infants and toddlers from birth to 2 years, high weight for recumbent length was defined as weight for length at or above the 95th percentile of the sex-specific Centers for Disease Control and Prevention (CDC) growth charts. In children and adolescents aged 2 to 19 years, obesity was defined as a body mass index (BMI) at or above the 95th percentile of the sex-specific CDC BMI-for-age growth charts. In adults, obesity was defined as a BMI greater than or equal to 30. Analyses of trends in high weight for recumbent length or obesity prevalence were conducted overall and separately by age across 5 periods (2003-2004, 2005-2006, 2007-2008, 2009-2010, and 2011-2012). In 2011-2012, 8.1% (95% CI, 5.8%-11.1%) of infants and toddlers had high weight for recumbent length, and 16.9% (95% CI, 14.9%-19.2%) of 2- to 19-year-olds and 34.9% (95% CI, 32.0%-37.9%) of adults (age-adjusted) aged 20 years or older were obese. Overall, there was no significant change from 2003-2004 through 2011-2012 in high weight for recumbent length among infants and toddlers, obesity in 2- to 19-year-olds, or obesity in adults. Tests for an interaction between survey period and age found an interaction in children (P = .03) and women (P = .02). There was a significant decrease in obesity among 2- to 5-year-old children (from 13.9% to 8.4%; P = .03) and a significant increase in obesity among women aged 60 years and older (from 31.5% to 38.1%; P = .006). Overall, there have been no significant changes in obesity prevalence in youth or adults between 2003-2004 and 2011-2012. Obesity prevalence remains high and thus it is important to continue surveillance.
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        Changes in diet and lifestyle and long-term weight gain in women and men.

         Le Hao,  Frank Hu,  Eric Rimm (2011)
        Specific dietary and other lifestyle behaviors may affect the success of the straightforward-sounding strategy "eat less and exercise more" for preventing long-term weight gain. We performed prospective investigations involving three separate cohorts that included 120,877 U.S. women and men who were free of chronic diseases and not obese at baseline, with follow-up periods from 1986 to 2006, 1991 to 2003, and 1986 to 2006. The relationships between changes in lifestyle factors and weight change were evaluated at 4-year intervals, with multivariable adjustments made for age, baseline body-mass index for each period, and all lifestyle factors simultaneously. Cohort-specific and sex-specific results were similar and were pooled with the use of an inverse-variance-weighted meta-analysis. Within each 4-year period, participants gained an average of 3.35 lb (5th to 95th percentile, -4.1 to 12.4). On the basis of increased daily servings of individual dietary components, 4-year weight change was most strongly associated with the intake of potato chips (1.69 lb), potatoes (1.28 lb), sugar-sweetened beverages (1.00 lb), unprocessed red meats (0.95 lb), and processed meats (0.93 lb) and was inversely associated with the intake of vegetables (-0.22 lb), whole grains (-0.37 lb), fruits (-0.49 lb), nuts (-0.57 lb), and yogurt (-0.82 lb) (P≤0.005 for each comparison). Aggregate dietary changes were associated with substantial differences in weight change (3.93 lb across quintiles of dietary change). Other lifestyle factors were also independently associated with weight change (P 8 hours of sleep), and television watching (0.31 lb per hour per day). Specific dietary and lifestyle factors are independently associated with long-term weight gain, with a substantial aggregate effect and implications for strategies to prevent obesity. (Funded by the National Institutes of Health and others.).
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          Epidemiology of insomnia: what we know and what we still need to learn.

          Epidemiologists have published more than 50 studies of insomnia based on data collected in various representative community-dwelling samples or populations. These surveys provide estimates of the prevalence of insomnia according to four definitions: insomnia symptoms, insomnia symptoms with daytime consequences, sleep dissatisfaction and insomnia diagnoses. The first definition, based on insomnia criteria as defined by the DSM-IV, recognizes that about one-third of a general population presents at least one of them. The second definition shows that, when daytime consequences of insomnia are taken into account, the prevalence is between 9% and 15%. The third definition represents 8-18% of the general population. The last definition, more precise and corresponding to a decision-making diagnosis, sets the prevalence at 6% of insomnia diagnoses according to the DSM-IV classification. These four definitions of insomnia have higher prevalence rates in women than in men. The prevalence of insomnia symptoms generally increases with age, while the rates of sleep dissatisfaction and diagnoses have little variation with age. Numerous factors can initiate or maintain insomnia. Mental disorders and organic diseases are the factors that have been the most frequently studied. The association between insomnia and major depressive episodes has been constantly reported: individuals with insomnia are more likely to have a major depressive illness. Longitudinal studies have shown that the persistence of insomnia is associated with the appearance of a new depressive episode. Future epidemiological studies should focus on the natural evolution of insomnia. Epidemiological genetic links of insomnia are yet to be studied.
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            Author and article information

            Affiliations
            [1 ] Clinical and Translational Science Center, Harvard Catalyst, Harvard Medical School, Boston, Massachusetts 02115; email: Chandra_Jackson@hms.harvard.edu.
            Journal
            Annu Rev Public Health
            Annual review of public health
            1545-2093
            0163-7525
            Mar 18 2015
            : 36
            25785893 10.1146/annurev-publhealth-031914-122838 4736723 NIHMS754754

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