Surveillance Systems


Guidelines for Evaluating Surveillance Systems
Black women with less than a high school education had the lowest prevalence compared with those who had higher educational levels. The public health importance of the health event Recognition by the system of the individual's contribution Responsiveness of the system to suggestions or comments Time burden relative to available time Federal and state legislative restrictions on data collection and assurance of confidentiality Federal and state legislative requirements for reporting Sensitivity Definition The sensitivity of a surveillance system can be considered on two levels. Responding to the Global Human Resources Crisis. The degree of underestimation varied across sociodemographic subgroups Acceptability Definition Acceptability reflects the willingness of individuals and organizations to participate in the surveillance system. Discussion The timeliness of a surveillance system should be evaluated in terms of availability of information for disease control--either for immediate control efforts or for long-term program planning.

Obesity Trend in Adults and Children

The Epidemiology of Obesity

Generally, simpler systems will be more flexible--fewer components will need to be modified when adapting the system for use with another disease. Acceptability reflects the willingness of individuals and organizations to participate in the surveillance system. In terms of evaluating a surveillance system, acceptability refers to the willingness to use the system by: To assess acceptability, one must consider the points of interaction between the system and its participants Figure 1 , including persons with the condition and those reporting cases.

Interview completion rates and question refusal rates if the system involves interviews with subjects. Acceptability is a largely subjective attribute that encompasses the willingness of persons on whom the system depends to provide accurate, consistent, complete, and timely data.

Some factors influencing the acceptability of a particular system are:. Federal and state legislative restrictions on data collection and assurance of confidentiality. The sensitivity of a surveillance system can be considered on two levels. First, at the level of case reporting, the proportion of cases of a disease or health condition detected by the surveillance system can be evaluated.

Second, the system can be evaluated for its ability to detect epidemics 3. The diseases or conditions will be diagnosed, reflecting the skill of care providers and the sensitivity of diagnostic tests; and.

The case will be reported to the system, given the diagnosis. These three conditions can be extended by analogy to.

For example, the sensitivity of a telephone-based surveillance system of morbidity or risk factors is affected by:. The number of people who have telephones, who are at home when the call is placed, and who agree to participate;. The ability of persons to understand the questions and correctly identify their status; and. The willingness of respondents to report their status. The extent to which these questions are explored depends on the.

The measurement of sensitivity in a surveillance system requires a the validation of information collected by the system and b the collection of information external to the system to determine the frequency of the condition in a community 4.

From a practical standpoint, the primary emphasis in assessing sensitivity--assuming that most reported cases are correctly classified--is to estimate the proportion of the total number of cases in the community being detected by the system. A surveillance system that does not have high sensitivity can still be useful in monitoring trends, as long as the sensitivity remains reasonably constant.

Questions concerning sensitivity in surveillance systems most commonly arise when changes in disease occurrence are noted. Changes in sensitivity can be precipitated by such events as heightened awareness of a disease, introduction of new diagnostic tests, and changes in the method of conducting surveillance.

A search for such surveillance "artifacts" is often an initial step in outbreak investigations. Predictive Value Positive Definition. Predictive value positive PVP is the proportion of persons identified as having cases who actually do have the condition under surveillance 5.

In assessing PVP, primary emphasis is placed on the confirmation of cases reported through the surveillance system. Its effect on the use of public health resources can be considered on two levels.

At the level of an individual case, PVP affects the amount of resources used for case investigations. For example, in some states every reported case of type A hepatitis is promptly investigated by a public health nurse, and family members at risk are referred for prophylactic treatment with immune globulin.

A surveillance system with low PVP--and therefore frequent "false-positive" case reports--would lead to wasted resources. The other level is that of detection of epidemics.

A high rate of erroneous case reports may trigger an inappropriate outbreak investigation. Therefore, the proportion of epidemics identified by the surveillance system that are true epidemics is needed to assess this attribute.

Calculating the PVP may require that records be kept of all interventions initiated because of information obtained from the surveillance system. A record of the number of case investigations done and the proportion of persons who actually had the condition under surveillance would allow the calculation of the PVP at the level of case detection. Personnel activity reports, travel records, and telephone logbooks may all be useful in estimating the PVP at the epidemic detection level.

PVP is important because a low value means that a non-cases are being investigated and b epidemics may be mistakenly identified. PFalse-positiveP' reports may lead to unnecessary intervention, and falsely detected PepidemicsP' may lead to costly investigations and undue concern in the community. A surveillance system with high PVP will lead to fewer wild-goose chases and wasted resources.

An example of a surveillance evaluation that examined PVP was reported by Barker et al. They reviewed hospital charts to determine the proportion of persons admitted with a diagnosis of stroke who had the diagnosis confirmed 6. The PVP for a health event is closely related to the clarity and specificity of the case definition. Good communication between the persons who report cases and the receiving agency also can improve PVP.

The PVP reflects the sensitivity and specificity of the case definition and the prevalence of the condition in the population Table 1. The PVP increases with increasing specificity and prevalence. A surveillance system that is representative accurately describes a the occurrence of a health event over time and b its distribution in the population by place and person. Representativeness is assessed by comparing the characteristics of reported events to all such actual events.

Although the latter information is generally not known, some judgment of the representativeness of surveillance data is possible, based on knowledge of:. Characteristics of the population--e. Natural history of the condition--e. Multiple sources of data--e.

Representativeness can be examined through special studies that. Quality of data is an important part of representativeness. Much of the discussion in this document focuses on the identification and classification of cases.

However, most surveillance systems rely on more than simple case counts. Information commonly collected includes the demographic characteristics of affected persons, details about the health event, and notification of the presence or absence of potential risk factors. The quality and usefulness and representativeness of this information depends on its completeness and validity.

Quality of data is influenced by the clarity of surveillance forms, the quality of training and supervision of persons who complete surveillance forms, and the care exercised in data management. A review of these facets of a surveillance system provides an indirect measure of quality of data. Examining the percentage of unknown or blank responses to items on surveillance forms or questionnaires is straightforward.

Assessing the reliability and validity of responses would require such special studies as chart reviews or re-interviews of respondents. In order to generalize findings from surveillance data to the population at large, the data from a surveillance system should reflect the population characteristics that are important to the goals and objectives of that system. These characteristics generally relate to time, place, and person. An important result of evaluating the representativeness of a surveillance system is the identification of population subgroups that may be systematically excluded from the reporting system.

This process allows appropriate modification of data collection and more accurate projection of incidence of the health event in the target population. For example, an evaluation of reporting of hepatitis in a county in Washington State suggested that cases of type B hepatitis were under-reported among homosexual males and that cases of type non A-non B hepatitis were under-reported among persons given blood transfusions.

The importance of these risk factors as contributors to the occurrence of these diseases was apparently underestimated by the selective under-reporting of certain types of hepatitis cases 9. Errors and bias can make their way into a surveillance system at any stage. Because surveillance data are used to identify high-risk groups, to target interventions, and to evaluate interventions, it is important to be aware of the strengths and limitations of the information in the system.

So far the discussion of attributes has been aimed at the information collected for cases, but in many surveillance systems morbidity and mortality rates are calculated. The denominators for these rate calculations are often obtained from a completely separate data system maintained by another agency, e. Thought should be given to the comparability of categories e.

The major steps in a surveillance system are shown in Figure 2. The time interval linking any two of the steps in this figure can be examined. The interval usually considered first is the amount of time between the onset of an adverse health event and the report of the event to the public health agency responsible for instituting control and prevention measures. Another aspect of timeliness is the time required for the identification of trends, outbreaks, or the effect of control measures.

With acute diseases, the onset of symptoms is usually used. Sometimes the date of exposure is used. With chronic diseases, it may be more useful to look at elapsed time from diagnosis rather than to estimate an onset date. The timeliness of a surveillance system should be evaluated in terms of availability of information for disease control--either for immediate control efforts or for long-term program planning.

For example, a study of a surveillance system for Shigella infections indicated that the typical case of shigellosis was brought to the attention of health officials 11 days after onset of symptoms--a period sufficient for the occurrence of secondary and tertiary transmission.

This suggests that the level of timeliness was not satisfactory for effective disease control In contrast, when there is a long period of latency between exposure and appearance of disease, the rapid identification of cases of illness may not be as important as the rapid availability of exposure data to provide a basis for interrupting and preventing exposures that lead to disease.

In another time frame, surveillance data are being used by public health agencies to track progress toward the Objectives for the Nation and to plan for the Year Objectives. The need for rapidity of response in a surveillance system depends on the nature of the public health problem under surveillance and the objectives of that system.

Recently, computer technology has been integrated into surveillance systems and may promote timeliness 11, This document covers only the resources directly required to operate a surveillance system.

These are sometimes referred to as Pdirect costsP' and include the personnel and financial resources expended in collecting, processing, analyzing, and disseminating the surveillance data. If desired, these measures can be converted to dollar estimates by multiplying the person-time by appropriate salary and benefit figures. Other resources These may include the cost of travel, training, supplies, equipment, and services e.

The application of these resources at all levels of the public health system--from the local health-care provider to municipal, county, state, and Federal health agencies--should be considered. The costs of surveillance systems from two studies are illustrated in Tables 2 and 3 below 7, This approach to assessment of resources includes only those personnel and material resources required for the operation of surveillance and excludes a broader definition of costs that might be considered in a more comprehensive evaluation.

Estimating the overall costs of a surveillance system can be a complex process. The estimates may include the estimation of a indirect costs, such as follow-up laboratory tests or treatment incurred as a result of surveillance; b costs of secondary data sources e. Costs are often judged relative to benefits, but few evaluations of surveillance systems are likely to include a formal cost-benefit analysis, and such analyses are beyond the scope of this document.

More realistically, costs should be judged with respect to the objectives and usefulness of a surveillance system. Examples of resource estimation for surveillance systems operated in Vermont and Kentucky follow. Two methods of collecting surveillance data in Vermont have been compared. The prevalence of obesity and overweight among US children and adults has more than doubled since the s, and the rate continues to rise. Numerous studies have shown that obesity increases morbidity and mortality Obesity has become the second leading preventable cause of disease and death in the United States, second only to tobacco use 1.

Obesity is likely to continue to increase and soon become the leading cause if no effective approaches to controlling it can be implemented. On the other hand, some minority groups such as Asian Americans have a lower prevalence of obesity. Of great concern, our analysis shows that the prevalence of obesity and overweight has increased at an average annual rate of approximately 0.

If a similar increase in trend is assumed, by , the majority of US adults 75 percent: Some population groups will be more seriously affected. For example, by , However, current available data are limited and do not enable us to examine the trends in other minority groups or to understand the factors that have led to the current obesity epidemic. A good understanding of underlying causes that triggered the increase in obesity prevalence in the United States over the past three decades and the factors that have contributed to the disparities across groups is critical in fighting this growing public health crisis and achieving an important national priority to eliminate health disparities.

Although obesity is caused by many factors, in most persons, weight gain results from a combination of excess calorie consumption and inadequate physical activity. To maintain a healthy weight, there must be a balance between energy consumption through dietary intake and energy expenditure through metabolic and physical activity A number of individual-, population-, and international-level factors and environmental determinants might have played a role in the obesity trends, such as changes in people's eating behaviors, physical activity and inactivity patterns, occupation, development of technology, culture exchange, and global trade 16 , 17 , The NHANES data show a dramatic increase in the prevalence of overweight and obesity across all population groups and a declining disparity of obesity across SES groups over the past two decades.

This finding indicates that individual characteristics are not the dominant factor to which the rising obesity epidemic is ascribed. Social environmental factors might have a more profound effect in influencing individuals' body weight status than do individuals' characteristics such as SES.

A growing consensus is that environmental factors have played a pivotal role in influencing people's lifestyles and fueling the obesity epidemic in the United States and worldwide 17 , 68 , The current society provides Americans with abundant food at a relatively low cost and numerous opportunities to reduce energy expenditure at work and at home, which facilitates sedentary behaviors.

Nationally representative survey data examining trends in people's eating patterns between and the s have indicated several patterns likely to put people in the United States at increased risk of obesity, such as increased consumption of total energy, soft drink, and snack foods; more frequent eating at fast-food and other restaurants; and inadequate consumption of vegetables and fruits compared with dietary recommendations 70— The increase in portion size in the United States over the past three decades probably is an important contributor to overconsumption of food and has fueled the growing obesity epidemic.

Although our current understanding of the underlying complex causes of the disparities in obesity between population groups in the United States e. At the community level, disadvantage may constrain people's ability to acquire and maintain healthy diet and exercise behaviors. Differential rates of available local area physical fitness facilities, restaurants, and types of food stores by neighborhood characteristics may help explain why obesity does not affect all population groups equally 79 , A recent study shows significant disparities in the availability of food stores.

African-American and Hispanic neighborhoods had fewer chain supermarkets compared with White and non-Hispanic neighborhoods, by about 50 percent and 70 percent, respectively The availability of supermarkets has been associated with more healthful diets, higher vegetable and fruit consumption, and lower rates of obesity 82 , Shopping at supermarkets versus independent groceries has been associated with more frequent vegetable and fruit consumption The Add Health study shows that lower-SES and minority population groups had less access to physical activity facilities, which in turn was associated with decreased physical activity and increased overweight Population-based policies and programs that emphasize environmental changes are most likely to be successful.

Strategies to tackle obesity need to be incorporated into other existing health promotion programs, particularly those preventing chronic diseases by promoting healthful eating and physical activity. Childhood and adolescence are key times for persons to form lifelong eating and physical activity habits. Overweight children are likely to remain obese as adults. Thus, obesity prevention in schoolchildren is a public health priority.

In addition, because the majority of children spend many of their waking hours in schools, schools should be key partners in the prevention of childhood obesity. It is crucial to tailor treatment and prevention efforts to each particular ethnicity group's specific situation and needs.

Government agencies, industry, public health professionals, and individual persons all need to play an active role in the growing national efforts to combat the obesity epidemic. The surveys were designed by using stratified multistage probability samples. In each survey, standardized protocols were used for all interviews and examinations. Data on weight and height were collected for each person through direct physical examination in a mobile examination center.

Recumbent length was measured in children younger than age 4 years and stature in children aged 2 years or older. BRFSS is the world's largest ongoing telephone health survey system, tracking health conditions and risk behaviors in the United States yearly since Conducted by the 50 state health departments as well as those in the District of Columbia, Puerto Rico, Guam, and the US Virgin Islands, with support from the Centers for Disease Control and Prevention, this system uses standard procedures to collect data through a series of monthly telephone interviews with US adults.

BRFSS provides state-specific information about issues such as obesity, asthma, diabetes, health care access, alcohol use, hypertension, cancer screening, nutrition and physical activity, and tobacco use; that is, it enables geographic differences to be examined The YRBSS was developed in ; the first survey was started in to monitor priority health risk behaviors that contribute markedly to the leading causes of death, disability, and social problems among youth and adults in the US.

YRBSS collected information on risk behaviors e. Add Health is a nationally representative, school-based study of youths grades 7—12, approximately aged 12—17 years followed up with multiple interview waves into young adulthood approximately aged 18—26 years. The study used a multistage, stratified, school-based, clustered sampling design. A stratified sample of 80 high schools and feeder middle schools was selected with probability proportional to size.

Wave I — included 20, adolescents aged 12—19 years and their parents. Wave II included 14, wave I adolescents including school dropouts and excluding graduating seniors. Wave III — included 15, wave I adolescents, now aged 18—26 years and entering the transition to adulthood 76 percent response rate.

In waves I and II, information on self-reported weight and height, and in wave III direct measured weight and height, was collected. Some other studies published since the early s have also examined the complex relation between gender, ethnicity, SES, and obesity among US adults and children. For example, earlier data collected in the CARDIA study from 5, Black men and women and White men and women aged 18—30 years suggested that the association of education with obesity was negative among White women and positive among Black men, with no significant association noted among White men and Black women Another study assessed the contribution of SES in explaining ethnic disparities in obesity among adult women; it concluded that Black ethnicity was an independent SES risk factor for obesity However, patterns of obesity were shown to differ by educational attainment within ethnic groups, which has implications for the segmentation of risk reduction programs When Whites were compared with Hispanics, a matched-pair design study found the highest prevalence of overweight among the least educated Hispanic women In a multiple regression model, the higher body mass index levels of Hispanic women and men relative to their White counterparts were not explained by age, gender, education, city of residence, time of survey, or language spoken A study of cardiovascular disease risk factors, including obesity, based on several national surveys found that for men, the highest prevalence of obesity Black women with or without a high school education had a higher prevalence of obesity Another study showed that socioeconomic deprivation in childhood was a strong predictor of adulthood obesity in African-American women, and the findings were consistent with both critical-period and cumulative-burden models of life-course socioeconomic deprivation and long-term risk for obesity Regarding young people, the — baseline data from the Add Health study show that overweight prevalence decreased with increasing SES among White females and remained elevated and even increased among higher SES African-American females.

Among males, disparity was lowest at the average SES level The Growth and Health Study of the National Heart, Lung, and Blood Institute collected data from younger children aged 9—10 years and showed that higher-SES White girls had a lower prevalence of obesity, but there was no clear relation among Black girls Another study of a nationwide sample of preschool children drawn from 20 large US cities showed that the higher prevalence of obesity among Hispanics relative to Blacks and Whites was not explained by ethnic differences in maternal education, household income, or food security A study compared current portions of food products in the United States with past portions, concluding that the sizes of current marketplace foods almost universally exceed those offered in the past.

The trend toward larger portion sizes in the United States began in the s, and portion sizes increased sharply in the s and have continued to increase. Study results show that, except for sliced white bread, all of the commonly available food portions exceeded the US Department of Agriculture and Food and Drug Administration standard portions, sometimes to a great extent.

For example, the largest excess over US Department of Agriculture standards by percent occurred in the cookie category, while cooked pasta, muffins, steaks, and bagels exceeded standards by percent, percent, percent, and percent, respectively. For french fries, hamburgers, and soda, the current portion sizes are 2—5 times larger than in the past The influence of growing portion size on people's energy intake is magnified by the fact that more people in the United States increasingly eat meals away from home more often than they did in the past Dietary intake data collected from individuals also support a marked trend toward larger portion sizes in the United States.

Based on nationally representative data collected between and , a study reported that the portion sizes of food consumed both at home and outside the home had increased for a large number of foods. Some of the increases were substantial, very often ranging between 50 kcal and kcal per item for commonly consumed food items such as salty snacks, soft drinks, hamburgers, french fries, and Mexican food.

The potential impact of larger portion sizes on people's overconsumption of energy and weight gain can be remarkable. For example, an added 10 kcal per day of extra calories can result in an extra pound 0. The authors thank Drs.

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account. Close mobile search navigation Article navigation. View large Download slide. The Surgeon General's call to action to prevent and decrease overweight and obesity.

Are American children and adolescents of low socioeconomic status at increased risk of obesity? Changes in the association between overweight and family income between and Validity of height and weight self-report in Mexican adults: Effects of age on validity of self-reported height, weight, and body mass index: How valid are self-reported height and weight?

A comparison between CATI self-report and clinic measurements using a large cohort study. A comparison of national estimates of obesity prevalence from the behavioral risk factor surveillance system and the National Health and Nutrition Examination Survey. Establishing a standard definition for child overweight and obesity worldwide: Epidemiology of childhood obesity—methodological aspects and guidelines: Overweight prevalence among youth in the United States: A comparison of international references for the assessment of child and adolescent overweight and obesity in different populations.

Report of a WHO consultation. Race-ethnicity-specific waist circumference cutoffs for identifying cardiovascular disease risk factors. Comparison of abdominal adiposity and overall obesity in predicting risk of type 2 diabetes among men. Reference data for obesity: Guidelines for overweight in adolescent preventive services: Obesity evaluation and treatment: Behavioral Risk Factor Surveillance System: Accessed October 2, Accessed September 2, Obesity is also associated with increased risk for numerous chronic diseases, including diabetes, hypertension, heart disease, and stroke.

Because of the increased risk of death and the increased risk of costly chronic diseases associated with obesity, the obesity epidemic places a large financial burden on the economy. The prevalence of obesity in the U. The epidemic of obesity is not limited to the U. Obesity is affected by a complex interaction between the environment, genetic predisposition, and human behavior.

It is associated with an increased risk of numerous chronic diseases, from diabetes and cancers to many digestive diseases. In addition, the obesity epidemic exerts a heavy toll on the economy with its massive healthcare costs. The problem of overweight and obesity has therefore emerged as one of the most pressing global issues that we will face during the next several decades, and demands attention from the healthcare community, researchers, and policy makers.

The implications for gastrointestinal health care providers is readily apparent and will be addressed in the text of this entire issue of Gastroenterology Clinics. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript.

The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. National Center for Biotechnology Information , U. Gastroenterol Clin North Am. Author manuscript; available in PMC Mar 1.

Nguyen , MD and Hashem B. MS , Houston, Texas , ude. The publisher's final edited version of this article is available at Gastroenterol Clin North Am.

See other articles in PMC that cite the published article. Introduction Obesity has received considerable attention as a major health hazard. Obesity Trend in Adults and Children We will review a few important sources of epidemiological data on obesity in the United States.

Open in a separate window. Overweight Trends in U. Global Trends of Obesity The current epidemic of obesity has been reported in several but not all regions globally. Possible Causes of the Obesity Epidemic Obesity is caused by a complex interaction between the environment, genetic predisposition, and human behavior. Burden of Illness Associated with Obesity Obesity is associated with an increased risk of death.

Summary and Conclusions The prevalence of obesity in the U. Population-based prevention of obesity: US Centers for Disease control and Prevention.