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Erica Frank

Bio: Erica Frank is an academic researcher from Stanford University. The author has contributed to research in topics: Population & Socioeconomic status. The author has an hindex of 6, co-authored 8 publications receiving 2106 citations.

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Journal ArticleDOI
TL;DR: Higher education may be the best SES predictor of good health, and 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.
Abstract: 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...

1,946 citations

Journal ArticleDOI
11 Dec 1991-JAMA
TL;DR: It is suggested that physicians still need to increase smoking cessation counseling to all patients, particularly adolescents and other young smokers, minorities, and those without cigarette-related disease.
Abstract: Objectives. —To determine the percentage of smokers reporting that a physician had ever advised them to smoke less or to stop smoking, and the effect of time, demographics, medical history, and cigarette dependence on the likelihood that respondents would state that a physician had ever advised them to stop smoking. Design and Setting. —Data were collected from the Stanford Five-City Project, a communitywide health education intervention program. The two treatment and three control cities were located in northern and central California. As there was no significant difference between treatment and control cities regarding cessation advice, data were pooled for these analyses. Participants. —There were five cross-sectional, population-based Five-City Project surveys (conducted in 1979-1980, 1981-1982, 1983-1984, 1985-1986, and 1989-1990); these surveys randomly sampled households and included all residents aged 12 to 74 years. Main Outcome Measures. —Improved smoking advice rates over time in all towns was an a priori hypothesis. Results. —Of the 2710 current smokers, 48.8% stated that their physicians had ever advised them to smoke less or stop smoking. Respondents were more likely to have been so advised if they smoked more cigarettes per day, were surveyed later in the decade, had more office visits in the last year, or were older. In 1979-1980, 44.1% of smokers stated that they had ever been advised to smoke less or to quit by a physician, vs 49.8% of smokers in 1989-1990 ( P Conclusion. —These findings suggest that physicians still need to increase smoking cessation counseling to all patients, particularly adolescents and other young smokers, minorities, and those without cigarette-related disease. ( JAMA . 1991;266:3139-3144)

161 citations

Journal ArticleDOI
23 Sep 1992-JAMA
TL;DR: Improvements in this population's cholesterol-related knowledge and behavior and plasma cholesterol levels began in 1985-1986, suggesting that the extensive cholesterol interventions that began in the middle 1980s in the United States created positive cholesterol- related changes at the community level.
Abstract: Objectives. —To determine whether cholesterol-related knowledge and behavior and plasma cholesterol levels were stable until the inception of large-scale national interventions in the middle to late 1980s, whether they subsequently improved, and whether these levels varied by subgroups. Design, Setting, and Participants. —Data were collected from 4173 adults aged 25 through 74 years in the two control cities (San Luis Obispo and Modesto, Calif) of the Stanford Five-City Project. Five separate, community-based surveys were conducted in 1979-1980,1981-1982,1983-1984,1985-1986, and 1989-1990. Results. —Cholesterol-related knowledge and behavior and plasma cholesterol levels improved (P=.0001) in both cities after the early 1980s. Those who were more educated, female, older, or nonsmokers had significantly higher knowledge and behavior scores, and those who were younger, more educated, or normotensive had significantly lower plasma cholesterol levels. Conclusion. —Improvements in this population's cholesterol-related knowledge and behavior and plasma cholesterol levels began in 1985-1986, suggesting that the extensive cholesterol interventions that began in the middle 1980s in the United States created positive cholesterol-related changes at the community level. (JAMA. 1992;268:1566-1572)

55 citations

Journal ArticleDOI
TL;DR: Analysis of five cross-sectional surveys demonstrated improvements in respondents' general cardiovascular disease risk factor knowledge and behaviors, and cholesterol-related knowledge and behavior showed particularly marked improvements.
Abstract: This study surveyed 4158 adults residing in two control cities of the Stanford Five-City Project. Analysis of five cross-sectional surveys (conducted in 1979 through 1990) demonstrated improvements in respondents' general cardiovascular disease risk factor knowledge and behaviors. Cholesterol-related knowledge and behavior showed particularly marked improvements.

27 citations


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Journal ArticleDOI
10 Nov 1993-JAMA
TL;DR: The most prominent contributors to mortality in the United States in 1990 were tobacco, diet and activity patterns, alcohol, microbial agents, toxic agents, firearms, sexual behavior, motor vehicles, and illicit use of drugs.
Abstract: 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)

5,468 citations

Journal ArticleDOI
14 Dec 2005-JAMA
TL;DR: Evidence shows that conclusions about nonsocioeconomic causes of racial/ethnic differences in health may depend on the measure-eg, income, wealth, education, occupation, neighborhood socioeconomic characteristics, or past socioeconomic experiences used to "control for SES," suggesting that findings from studies that have measured limited aspects of SES should be reassessed.
Abstract: Problems with measuring socioeconomic status (SES)—frequently included in clinical and public health studies as a control variable and less frequently as the variable(s) of main interest—could affect research findings and conclusions, with implications for practice and policy.Wecritically examine standard SES measurement approaches, illustrating problems with examples from new analyses and the literature. For example, marked racial/ethnic differences in income at a given educational level and in wealth at a given income level raise questions about the socioeconomic comparability of individuals who are similar on education or income alone. Evidence also shows that conclusions about nonsocioeconomic causes of racial/ethnic differences in health may depend on the measure—eg, income, wealth, education, occupation, neighborhood socioeconomic characteristics, or past socioeconomic experiences—used to “control for SES,” suggesting that findings from studies that have measured limited aspects of SES should be reassessed. We recommend an outcome- and social group–specific approach to SES measurement that involves (1) considering plausible explanatory pathways and mechanisms, (2) measuring as much relevant socioeconomic information as possible, (3) specifying the particular socioeconomic factors measured (rather than SES overall), and (4) systematically considering how potentially important unmeasured socioeconomic factors may affect conclusions. Better SES measures are needed in data sources, but improvements could be made by using existing information more thoughtfully and acknowledging its limitations.

1,974 citations

Journal ArticleDOI
TL;DR: Reducing SES disparities in health will require policy initiatives addressing the components of socioeconomic status (income, education, and occupation) as well as the pathways by which these affect health.
Abstract: Socioeconomic status (SES) underlies three major determinants of health: health care, environmental exposure, and health behavior. In addition, chronic stress associated with lower SES may also increase morbidity and mortality. Reducing SES disparities in health will require policy initiatives addressing the components of socioeconomic status (income, education, and occupation) as well as the pathways by which these affect health. Lessons for U.S. policy approaches are taken from the Acheson Commission in England, which was charged with reducing health disparities in that country.

1,879 citations

Journal ArticleDOI
TL;DR: It is concluded that high educational attainment improves health directly and it improves health indirectly through work and economic conditions, social-psychological resources, and health lifestyle.
Abstract: University of Illinois, Urbana The positive association between education and health is well established, but explanations for this association are not. Our explanations fall into three categories: (1) work and economic conditions, (2) social-psychological resources, and (3) health lifestyle. We replicate analyses with two samples, cross-sectionally and over time, using two health measures (self-reported health and physical functioning). The first data set comes from a national probability sample of U.S. households in which respondents were interviewed by telephone in 1990 (2,031 respondents, ages 18 to 90). The second data set comes from a national probability sample of U.S. households in which respondents ages 20 to 64 were interviewed by telephone first in 1979 (3,025 respondents), and then again in 1980 (2,436 respondents). Results demonstrate a positive association between education and health and help explain why the association exists. (1) Compared to the poorly educated, well educated respondents are less likely to be unemployed, are more likely to work full-time, to have fulfilling, subjectively rewarding jobs, high incomes, and low economic hardship. Full-time work, fulfilling work, high income, and low economic hardship in turn significantly improve health in all analyses. (2) The well educated report a greater sense of control over their lives and their health, and they have higher levels of social support. The sense of control, and to a lesser extent support, are associated with good health. (3) The well educated are less likely to smoke, are more likely to exercise, to get health check-ups, and to drink moderately, all of which, except check-ups, are associated with good health. We conclude that high educational attainment improves health directly, and it improves health indirectly through work and economic conditions, social-psychological resources, and health lifestyle. he positive association between education and health is well established, but explanations for this association are not. Well educated people experience better health than the poorly educated, as indicated by high levels of self-reported health and physical functioning and low levels of morbidity, mortality, and disability. In contrast, low educational attainment is associated with high rates of infectious disease, many chronic noninfectious diseases, self-reported poor health, shorter survival when sick, and shorter life expectancy (Feldman, Makuc, Kleinman, and Cornoni-Huntley 1989; Guralnik, Land, Fillenbaum, and Branch 1993; Gutzwiller, LaVecchia, Levi, Negri, and Wietlisbach 1989; Kaplan, Haan, and Syme 1987; Kitagawa and Hauser 1973; Liu, Cedres, and Stamler 1982; Morris 1990; Pappas, Queen,

1,747 citations

Journal ArticleDOI
TL;DR: Assessment of the geographic and social distribution of PA facilities and how disparity in access might underlie population-level PA and overweight patterns in US adolescents found inequality in availability ofPA facilities may contribute to ethnic and SES disparities in PA and obese patterns.
Abstract: CONTEXT. Environmental factors are suggested to play a major role in physical activity (PA) and other obesity-related behaviors, yet there is no national research on the relationship between disparity in access to recreational facilities and additional impact on PA and overweight patterns in US adolescents. OBJECTIVE. In a nationally representative cohort, we sought to assess the geographic and social distribution of PA facilities and how disparity in access might underlie population-level PA and overweight patterns. DESIGN, SETTING, AND PARTICIPANTS. Residential locations of US adolescents in wave I (1994–1995) of the National Longitudinal Study of Adolescent Health (N = 20745) were geocoded, and a 8.05-km buffer around each residence was drawn (N = 42857 census-block groups [19% of US block groups]). PA facilities, measured by national databases and satellite data, were linked with Geographic Information Systems technology to each respondent. Logistic-regression analyses tested the relationship of PA-related facilities with block-group socioeconomic status (SES) (at the community level) and the subsequent association of facilities with overweight and PA (at the individual level), controlling for population density. MAIN OUTCOME MEASURES. Outcome measures were overweight (BMI ≥ 95th percentile of the Centers for Disease Control and Prevention/National Center for Health Statistics growth curves) and achievement of ≥5 bouts per week of moderate-vigorous PA. RESULTS. Higher-SES block groups had a significantly greater relative odds of having 1 or more facilities. Low-SES and high-minority block groups were less likely to have facilities. Relative to zero facilities per block group, an increasing number of facilities was associated with decreased overweight and increased relative odds of achieving ≥5 bouts per week of moderate-vigorous PA. CONCLUSIONS. Lower-SES and high-minority block groups had reduced access to facilities, which in turn was associated with decreased PA and increased overweight. Inequality in availability of PA facilities may contribute to ethnic and SES disparities in PA and overweight patterns.

1,722 citations