Suppose x is an unknown vector in Ropfm (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements n can be dramatically smaller than the size m. Thus, certain natural classes of images with m pixels need only n=O(m1/4log5/2(m)) nonadaptive nonpixel samples for faithful recovery, as opposed to the usual m pixel samples. More specifically, suppose x has a sparse representation in some orthonormal basis (e.g., wavelet, Fourier) or tight frame (e.g., curvelet, Gabor)-so the coefficients belong to an lscrp ball for 0<ples1. The N most important coefficients in that expansion allow reconstruction with lscr2 error O(N1/2-1p/). It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients. Moreover, a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing. The nonadaptive measurements have the character of "random" linear combinations of basis/frame elements. Our results use the notions of optimal recovery, of n-widths, and information-based complexity. We estimate the Gel'fand n-widths of lscrp balls in high-dimensional Euclidean space in the case 0<ples1, and give a criterion identifying near- optimal subspaces for Gel'fand n-widths. We show that "most" subspaces are near-optimal, and show that convex optimization (Basis Pursuit) is a near-optimal way to extract information derived from these near-optimal subspaces

Compressed sensing

Detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III)

Appendix I: List of Statistical Fact Sheets. URL: http://www.americanheart.org/presenter.jhtml?identifier=2007

We wish to thank Drs Brian Eigel and Michael Wolz for their valuable comments and contributions. We would like to acknowledge Tim Anderson and Tom Schneider for their editorial contributions and Karen Modesitt for her administrative assistance.

Disclosures 



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# Summary {#article-title-2}

Each year, the American Heart Association, in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics on heart disease, stroke, other vascular diseases, and their risk factors and presents them in its Heart Disease and Stroke Statistical Update. The Statistical Update is a valuable resource for researchers, clinicians, healthcare policy makers, media professionals, the lay public, and many others who seek the best national data available on disease …

Heart Disease and Stroke Statistics—2010 Update A Report From the American Heart Association

Objective. —To identify and quantify the major external (nongenetic) factors that contribute to death in the United States. Data Sources. —Articles published between 1977 and 1993 were identified through MEDLINE searches, reference citations, and expert consultation. Government reports and compilations of vital statistics and surveillance data were also obtained. Study Selection. —Sources selected were those that were often cited and those that indicated a quantitative assessment of the relative contributions of various factors to mortality and morbidity. Data Extraction. —Data used were those for which specific methodological assumptions were stated. A table quantifying the contributions of leading factors was constructed using actual counts, generally accepted estimates, and calculated estimates that were developed by summing various individual estimates and correcting to avoid double counting. For the factors of greatest complexity and uncertainty (diet and activity patterns and toxic agents), a conservative approach was taken by choosing the lower boundaries of the various estimates. Data Synthesis. —The most prominent contributors to mortality in the United States in 1990 were tobacco (an estimated 400000 deaths), diet and activity patterns (300 000), alcohol (100 000), microbial agents (90 000), toxic agents (60 000), firearms (35 000), sexual behavior (30 000), motor vehicles (25 000), and illicit use of drugs (20 000). Socioeconomic status and access to medical care are also important contributors, but difficult to quantify independent of the other factors cited. Because the studies reviewed used different approaches to derive estimates, the stated numbers should be viewed as first approximations. Conclusions. —Approximately half of all deaths that occurred in 1990 could be attributed to the factors identified. Although no attempt was made to further quantify the impact of these factors on morbidity and quality of life, the public health burden they impose is considerable and offers guidance for shaping health policy priorities. (JAMA. 1993;270:2207-2212)

https://jamanetwork.com/journals/JAMA/articlepdf/409171/jama_270_18_038.pdf

Actual causes of death in the United States.

Author(s): Go, Alan S; Mozaffarian, Dariush; Roger, Veronique L; Benjamin, Emelia J; Berry, Jarett D; Borden, William B; Bravata, Dawn M; Dai, Shifan; Ford, Earl S; Fox, Caroline S; Franco, Sheila; Fullerton, Heather J; Gillespie, Cathleen; Hailpern, Susan M; Heit, John A; Howard, Virginia J; Huffman, Mark D; Kissela, Brett M; Kittner, Steven J; Lackland, Daniel T; Lichtman, Judith H; Lisabeth, Lynda D; Magid, David; Marcus, Gregory M; Marelli, Ariane; Matchar, David B; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Mussolino, Michael E; Nichol, Graham; Paynter, Nina P; Schreiner, Pamela J; Sorlie, Paul D; Stein, Joel; Turan, Tanya N; Virani, Salim S; Wong, Nathan D; Woo, Daniel; Turner, Melanie B; American Heart Association Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2013 Update A Report From the American Heart Association

BACKGROUND. Socioeconomic status (SES) is usually measured by determining education, income, occupation, or a composite of these dimensions. Although education is the most commonly used measure of SES in epidemiological studies, no investigators in the United States have conducted an empirical analysis quantifying the relative impact of each separate dimension of SES on risk factors for disease. METHODS. Using data on 2380 participants from the Stanford Five-City Project (85% White, non-Hispanic), we examined the independent contribution of education, income, and occupation to a set of cardiovascular disease risk factors (cigarette smoking, systolic and diastolic blood pressure, and total and high-density lipoprotein cholesterol). RESULTS. The relationship between these SES measures and risk factors was strongest and most consistent for education, showing higher risk associated with lower levels of education. Using a forward selection model that allowed for inclusion of all three SES measures after adjust...

Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease.

Context.—Cardiovascular disease (CVD) risk factors are higher among ethnic minority
women than among white women in the United States. However, because ethnic
minority women are disproportionately poor, socioeconomic status (SES) may
substantially explain these risk factor differences.Objective.—To determine whether differences in CVD risk factors by ethnicity could
be attributed to differences in SES.Design.—Third National Health and Nutrition Examination Survey conducted between
1988 and 1994.Setting.—Eighty-nine mobile examination centers.Participants.—A total of 1762 black, 1481 Mexican American, and 2023 white women,
aged 25 to 64 years, who completed both the home questionnaire and medical
examination.Main Outcome Measures.—Ethnicity and years of education (SES) in relation to systolic blood
pressure, cigarette smoking, body mass index (BMI, a measure of weight in
kilograms divided by the square of height in meters), physical inactivity,
non–high-density lipoprotein cholesterol (non–HDL-C [the difference
between total cholesterol and HDL-C]), and non–insulin-dependent diabetes
mellitus.Results.—As expected, most CVD risk factors were higher among ethnic minority
women than among white women. After adjusting for years of education, highly
significant differences in blood pressure, BMI, physical inactivity, and diabetes
remained for both black and Mexican American women compared with white women
(P<.001). In addition, women of lower SES from
each of the 3 ethnic groups had significantly higher prevalences of smoking
and physical inactivity and higher levels of BMI and non–HDL-C than
women of higher SES (P<.001).Conclusions.—These findings provide the greatest evidence to date of higher CVD risk
factors among black and Mexican American women than among white women of comparable
SES. The striking differences by both ethnicity and SES underscore the critical
need to improve screening, early detection, and treatment of CVD-related conditions
for black and Mexican American women, as well as for women of lower SES in
all ethnic groups.

https://jamanetwork.com/journals/jama/articlepdf/187788/JOC72047.pdf

Ethnic and Socioeconomic Differences in Cardiovascular Disease Risk Factors: Findings for Women From the Third National Health and Nutrition Examination Survey, 1988-1994

Importance Bipolar disorder is associated with premature mortality, but the specific causes and underlying pathways are unclear. Objective To examine the physical health effects of bipolar disorder using outpatient and inpatient data for a national population. Design, Setting, and Participants National cohort study of 6 587 036 Swedish adults, including 6618 with bipolar disorder. Main Outcomes and Measures Physical comorbidities diagnosed in any outpatient or inpatient setting nationwide and mortality (January 1, 2003, through December 31, 2009). Results Women and men with bipolar disorder died 9.0 and 8.5 years earlier on average than the rest of the population, respectively. All-cause mortality was increased 2-fold among women (adjusted hazard ratio [aHR], 2.34; 95% CI, 2.16-2.53) and men (aHR, 2.03; 95% CI, 1.85-2.23) with bipolar disorder, compared with the rest of the population. Patients with bipolar disorder had increased mortality from cardiovascular disease, diabetes mellitus, chronic obstructive pulmonary disease (COPD), influenza or pneumonia, unintentional injuries, and suicide for both women and men and cancer for women only. Suicide risk was 10-fold among women (aHR, 10.37; 95% CI, 7.36-14.60) and 8-fold among men (aHR, 8.09; 95% CI, 5.98-10.95) with bipolar disorder, compared with the rest of the population. Substance use disorders contributed only modestly to these findings. The association between bipolar disorder and mortality from chronic diseases (ischemic heart disease, diabetes, COPD, or cancer) was weaker among persons with a prior diagnosis of these conditions (aHR, 1.40; 95% CI, 1.26-1.56) than among those without a prior diagnosis (aHR, 2.38; 95% CI, 1.95-2.90; P interaction  = .01). Conclusions and Relevance In this large national cohort study, patients with bipolar disorder died prematurely from multiple causes, including cardiovascular disease, diabetes, COPD, influenza or pneumonia, unintentional injuries, and suicide. However, chronic disease mortality among those with more timely medical diagnosis approached that of the general population, suggesting that better provision of primary medical care may effectively reduce premature mortality among persons with bipolar disorder.

https://jamanetwork.com/journals/jamapsychiatry/articlepdf/1714400/yoi130040.pdf

Comorbidities and Mortality in Bipolar Disorder A Swedish National Cohort Study

ObjectiveSchizophrenia is associated with premature mortality, but the specific causes and pathways are unclear. The authors used outpatient and inpatient data for a national population to examine the association between schizophrenia and mortality and comorbidities.MethodThis was a national cohort study of 6,097,834 Swedish adults, including 8,277 with schizophrenia, followed for 7 years (2003–2009) for mortality and comorbidities diagnosed in any outpatient or inpatient setting nationwide.ResultsOn average, men with schizophrenia died 15 years earlier, and women 12 years earlier, than the rest of the population, and this was not accounted for by unnatural deaths. The leading causes were ischemic heart disease and cancer. Despite having twice as many health care system contacts, schizophrenia patients had no increased risk of nonfatal ischemic heart disease or cancer diagnoses, but they had an elevated mortality from ischemic heart disease (adjusted hazard ratio for women, 3.33 [95% CI=2.73–4.05]; for me...

https://ajp.psychiatryonline.org/doi/pdf/10.1176/appi.ajp.2012.12050599

Comorbidities and mortality in persons with schizophrenia: a Swedish national cohort study.

Objective: To determine whether socioeconomic and food-related physical characteristics of the neighbourhood are associated with body mass index (BMI; kg/m 2 ) independently of individual-level sociodemographic and behavioural characteristics. Design and methods: Observational study using (1) individual-level data previously gathered in five cross-sectional surveys conducted by the Stanford Heart Disease Prevention Program between 1979 and 1990 and (2) neighbourhood-level data from (a) the census to describe socioeconomic characteristics and (b) data obtained from government and commercial sources to describe exposure to different types of retail food stores as measured by store proximity, and count of stores per square mile. Data were analysed using multilevel modelling procedures. The setting was 82 neighbourhoods in agricultural regions of California. Participants: 7595 adults, aged 25–74 years. Results: After adjusting for age, gender, ethnicity, individual-level socioeconomic status, smoking, physical activity and nutrition knowledge, it was found that (1) adults who lived in low socioeconomic neighbourhoods had a higher mean BMI than adults who lived in high socioeconomic neighbourhoods; (2) higher neighbourhood density of small grocery stores was associated with higher BMI among women; and (3) closer proximity to chain supermarkets was associated with higher BMI among women. Conclusion: Living in low socioeconomic neighbourhoods, and in environments where healthy food is not readily available, is found to be associated with increased obesity risk. Unlike other studies which examined populations in other parts of the US, a positive association between living close to supermarkets and reduced obesity risk was not found in this study. A better understanding of the mechanisms by which neighbourhood physical characteristics influence obesity risk is needed.

/pdf/socioeconomic-and-food-related-physical-characteristics-of-ikl3bexynn.pdf

Marilyn A. Winkleby

Papers

Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease.

Ethnic and Socioeconomic Differences in Cardiovascular Disease Risk Factors: Findings for Women From the Third National Health and Nutrition Examination Survey, 1988-1994

Comorbidities and Mortality in Bipolar Disorder A Swedish National Cohort Study

Comorbidities and mortality in persons with schizophrenia: a Swedish national cohort study.

Socioeconomic and food-related physical characteristics of the neighbourhood environment are associated with body mass index