Cantankerous-Sectional Surveys

Cantankerous-sectional surveys appraise the prevalence of disease and the prevalence of risk factors at the aforementioned
point in time
and provide a “snapshot” of diseases and risk factors simultaneously in a defined population. For example, Us government agencies periodically send out large surveys to random samples of the US population, asking about health status and risk factors and behaviors at that point in time. The Health Interview Survey (HIS) and the National Health and Nutrition Test Survey (NHANES) are good examples.

The health questionnaires y’all are asked to fill out when you lot get to a new dr. or being candy for a new job, or prior to entry into armed forces service are similar to cross-exclusive surveys in that they ask about the wellness bug that you have (heart disease? diabetes? asthma?) and your current behaviors and risk factors (eastward.g., How onetime are you lot? Exercise y’all smoke? What is your occupation?).

Cross-exclusive surveys inquire people their

current

status with respect to both exposures and diseases. They are oftentimes referred to equally “prevalence studies,” considering they assess the prevalence of exposures and health outcomes at a indicate in time. They have 2 primary disadvantages.

Key points to remember most cross-exclusive surveys:

  • Data on exposure condition and health consequence status are collected from each respondent at the same point in time.
  • They provide a “snapshot” of prevalence at a point in time.
  • They assess the needs of the population, i.e., the burden of diseases, and the frequency of wellness related behaviors (e.g., smoking, exercise, seat chugalug utilise, etc.) at a signal in time.
  • Cantankerous-exclusive surveys assesses prevalence at a point in fourth dimension in random samples of a population. While they assess prevalence at a point in fourth dimension, they tin can be repeated at different points in time to assess trends, every bit illustrated in the image below. Which shows that the prevalence of obesity in the US population increased from 12% to 35% from 1960 to 2001.
  • It is of import to note that cross-sectional surveys are non repeated in the same individuals, i.e., in that location is no follow up. They are cantankerous-sectional pictures of a population, not longitudinal follow-up studies in which individuals are followed over time.
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Limitations of Cross-sectional Surveys:

  • The temporal human relationship betwixt exposure and disease outcomes can be unclear, i.e., which came first.
  • Cross-exclusive studies tend to identify prevalent cases of long duration , since people who die quickly or recover rapidly or who are no longer employed in a particular occupation are less likely to exist identified.

These limitations are discussed below.

Temporal Human relationship Betwixt Exposure and Event

Consider the following example in which a survey was conducted among white male farm workers. The survey asked many questions, simply among them were the questions: “Have you been told y’all have coronary heart disease (CHD)?” And “How would y’all allocate your level of concrete activity?” The table beneath summarizes the findings.

Table – Electric current Activeness and Coronary Heart Disease Among Male Farm Workers

# of Respondents

# Respondents

With CHD

Prevalence of CHD

per 1,000

Currently Not Active

89

14

157

Currently Agile

90

3

38

Annotation that the investigators

did non

follow these subjects over a menses of fourth dimension, then they did not assess the “incidence” of heart affliction. Instead, they asked the subjects questions designed to determine the prevalence of heart illness, i.e., the proportion of the study population that had heart disease at this particular point in time. When they divided the sample into physically active and inactive farmers and computed the prevalence of eye illness in each of these, they constitute that CHD was much more than prevalent among the inactive farmers. However, this was a cross-sectional written report that related the prevalence of disease to the prevalence of activity at a point in time. They did not follow subjects over time to track the development of heart illness (i.e., the incidence). Consequently, the temporal relationship between the hazard gene of interest (concrete inactivity) and the outcome (CHD) is unclear.

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Had the farmers been physically active prior to developing CHD? Or, did they begin to limit their physical activeness after they developed CHD? It is unclear. Consequently concrete inactivity could take been either a cause of center disease, or it could have been a consequence of CHD.

Large cross-exclusive surveys are important for monitoring health condition and health care needs of the population over time, and they are sometimes useful for suggesting possible associations between take chances factors and diseases. Nevertheless, the temporal relationship between the risk gene and disease is often unclear. Under these circumstances, they can generate hypotheses, but these associations demand to be tested by appropriate analytical studies.

However, note that under some circumstances, the temporal human relationship is clear on a cross-sectional survey. For example, if 1 conducted a survey of salaries of male and female person professors to run into if sex activity was associated with salary inequities, we could regard this as an belittling written report, because information technology is articulate that sex was established long before salary level. In this situation the temporal human relationship between the “exposure” of involvement (sex) and result (bacon paid) is clear; we know that gender was established before the bacon was negotiated. And so, in a sense cantankerous-exclusive studies (and ecological studies can be thought of equally an intermediate category between descriptive and analytic studies.

Identification of Cases of Long Duration

A second limitation of cross-exclusive studies is that they are more probable to identify cases of long elapsing, and this can bias the results.

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Instance:
Isocyanates are chemicals that tin cause occupational asthma that gets progressively worse over time. In a cross-sectional written report of isocyanates and occupational asthma, the prevalence of asthma was lower in manufacturing plant workers with >five years employment vs. those with <5 years employment, considering those with isocyanate exposure and asthma were more likely to leave.

Below is a hypothetical time line showing the credible prevalence of occupational respiratory bug in workers exposed to isocyanates and unexposed workers. After one twelvemonth of working the prevalence of respiratory problems is 2-fold greater in the isocyanate workers, merely by seven years the prevalence is similar, because the isocyanate workers who developed respiratory problems left and found other work.

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