A review of 144 published studies of the relationship between socioeconomic status (SES) and obesity reveals a strong inverse relationship among women in developed societies. The relationship is inconsistent for men and children in developed societies. In developing societies, however, a strong direct relationship exists between SES and obesity among men, women, and children. A review of social attitudes toward obesity and thinness reveals values congruent with the distribution of obesity by SES in different societies. Several variables may mediate the influence of attitudes toward obesity and thinness among women in developed societies that result in the inverse relationship between SES and obesity. They include dietary restraint, physical activity, social mobility, and inheritance.

Socioeconomic Status and Obesity: A Review of the Literature

A new predictive equation for resting energy expenditure in healthy individuals.

Exploratory data analysis involves the use of statistical techniques to identify patterns that may be hidden in a group of numbers. One of these techniques is the "box plot," which is used to visually summarize and compare groups of data. The box plot uses the median, the approximate quartiles, and the lowest and highest data points to convey the level, spread, and symmetry of a distribution of data values. It can also be easily refined to identify outlier data values and can be easily constructed by hand. We apply box plots to tabular data from two recently published articles to show how readers can use box plots to improve the interpretation of data in complex tables. The box plot, like other visual methods, is more than a substitute for a table: It is a tool that can improve our reasoning about quantitative information. We recommend that the box plot be used more frequently.

The box plot: a simple visual method to interpret data

BACKGROUND. Since large-scale health surveys usually have complicated sampling schemes, there is often a question as to whether the sampling design must be considered in the analysis of the data. A recent disagreement concerning the analysis of a body iron stores-cancer association found in the first National Health and Nutrition Examination Survey and its follow-up is used to highlight the issues. METHODS. We explain and illustrate the importance of two aspects of the sampling design: clustering and weighting of observations. The body iron stores-cancer data are reanalyzed by utilizing or ignoring various aspects of the sampling design. Simple formulas are given to describe how using the sampling design of a survey in the analysis will affect the conclusions of that analysis. RESULTS. The different analyses of the body iron stores-cancer data lead to very different conclusions. Application of the simple formulas suggests that utilization of the sample clustering in the analysis is appropriate, but that a...

Epidemiologic studies utilizing surveys: accounting for the sampling design.

Since 1981, the Centers for Disease Control has collaborated with State health departments and the District of Columbia to conduct random digit-dialed telephone surveys of adults concerning their health practices and behaviors. This State-based surveillance system, which yields data needed in planning, initiating, and supporting health promotion and disease prevention programs, is described in this paper. Standard methods and questionnaires were used to assess the prevalence of personal health practices and behaviors related to the leading causes of death, including seatbelt use, high blood pressure control, physical activity, weight control, cigarette smoking, alcohol use, drinking and driving, and preventive health practices. Between 1981 and 1983, 29 States (includes the District of Columbia) conducted one-time telephone surveys. Beginning in 1984, most States began collecting data continuously throughout the year, completing approximately 100 interviews per month (range 50-250), with an average of 1,200 completed interviews per year (range 600-3,000). The raw data were weighted to the age, race, and sex distribution for each State from the 1980 census data. This weighting accounts for the underrepresentation of men, whites, and younger persons (18-24 years) in the telephone surveys and, for many health practices, provides prevalence estimates comparable with estimates obtained from household surveys. Nearly all (86 percent) of the States distributed selected survey results to other State agencies, local health departments, voluntary organizations, hospitals, universities, State legislators, and the press. The majority (60 percent) of States used information from the surveys to set State health objectives, prepare State health planning documents, and plan a variety of programs concerning antismoking, the prevention of chronic diseases, and health promotion. Further, nearly two-thirds (65 percent) used results to support legislation, primarily related to the use of tobacco and seatbelts. Most of the States (84 percent) reported that alternative sources for such data (prevalence of behavioral risk factors) were unavailable. Currently in 1988, over 40 State health departments are conducting telephone surveys as part of the Behavioral Risk Factor Surveillance System. This system has proved to be (a) flexible--it provides data on emerging public health problems, such as smokeless tobacco use and AIDS, (b) timely--it provides results within a few months after the data are collected, and (c) affordable--it operates at a fraction of the cost of comparable statewide in-person surveys. The system enables State public health agencies to continue to plan,initiate, and guide statewide health promotion and disease prevention programs and monitor their progress over time.

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Design, characteristics, and usefulness of state-based behavioral risk factor surveillance: 1981-87.

Alcohol contributes more than 10 per cent of the total caloric intake of adult drinkers in the United States. However, the effect of alcohol on body weight has not been adequately studied in the general population. The association between weight and frequency of alcohol consumption was examined in two national cross-sectional surveys: the Second National Health and Nutrition Examination Survey (HANESII; n = 10,929) and the Behavioral Risk Factor Surveys (BRFS; n = 18,388). Linear multiple regression was used to estimate the independent effect of alcohol on weight, adjusting for smoking, age, diet practices, physical activity, race, education, and height. Among men, alcohol had only a slight effect on weight in either survey. However, among women, alcohol was associated with a substantial reduction in weight, which was as large as the effect of smoking. Compared with nondrinkers, women who consumed alcohol 7-13 times per week had the greatest reduction in weight: -3.6 kg (95% confidence limits [CL] = -5.6,...

https://ajph.aphapublications.org/doi/pdfplus/10.2105/AJPH.77.10.1324

F. L. Trowbridge

Papers

Alcohol and body weight in United States adults.

Overweight adults in the United States: the behavioral risk factor surveys

Alcohol and body weight in United States adults

Indicators of nutritional status for use in screening and surveillance.