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PubMed1996

Petrosal sinus sampling for diagnosis of Cushing's disease: evidence of false negative results.

OBJECTIVE: While inferior petrosal sinus (IPS) sampling correctly diagnoses pituitary-dependent Cushing's syndrome if a significant ratio of plasma ACTH between the IPS and the peripheral blood is demonstrated, little has been said about the significance of a negative ratio in Cushing's disease (e.g. a false-negative result). This study evaluates the results of IPS sampling in patients with Cushing's disease, and compares them with both imaging findings and transsphenoidal examination. DESIGN: The results of IPS sampling were retrospectively compared with both imaging findings and transsphenoidal examination. IPS samples were obtained before and 2, 5 and 10 minutes after intravenous administration of 100 micrograms of CRH. PATIENTS: Thirty-two patients with Cushing's disease were evaluated. All subsequently underwent transphenoidal examination of the pituitary gland. MEASUREMENTS: The ratio of the ACTH concentrations at the IPS and in the peripheral blood (IPS:P ratio), and the ratio of the ACTH concentrations between the IPSs (interpetrosal ratio) were calculated. Radiographic evaluation of the pituitary gland was performed with magnetic resonance imaging (MRI, 29 cases) or computed tomography imaging (CT, 3 cases). RESULTS: Transsphenoidal examination of the pituitary gland revealed a microadenoma in 27 cases. Radiological imaging showed a signal compatible with a microadenoma in 22 cases (68.8%), and correctly located the tumour at the side found at surgery in 14 of the 22 cases with positive transsphenoidal findings (MRI 13 cases, CT 1 case, overall 63.6%). Successful bilateral catheterization was accomplished in 30 patients (93.8%). Samples before and after CRH stimulation were drawn in 24 cases. No major complications were observed with the technique. IPS catheterization correctly predicted Cushing's disease (by means of a significant IPS: P ACTH ratio) in 27 of the 30 patients (90%) with basal sampling, and in 23 of the 24 cases with samples drawn before and after CRH administration (95.8%). Taking into account the 12 patients with a lateral microadenoma shown at transsphenoidal examination, IP sinus ACTH ratio was in agreement with the side recorded by the neurosurgeon in 8/12 cases (66.7%). MRI correctly located the tumour in 8/12 patients (66.7%). One patient showed no significant IPS: P ACTH ratio in any set of samples. His MRI showed no sign of a microadenoma. Two years later, another pituitary MRI evaluation showed a midline hypodense signal. The transsphenoidal examination revealed a microadenoma and the post-operative plasma cortisol and urinary free cortisol fell to 293 nmol/l and 100 nmol/24 h, respectively. CONCLUSIONS: Only when a significant IPS:P ACTH ratio is present can Cushing's disease be established by IPS sampling. The absence of a significant IPS: P ACTH ratio does not necessarily imply ectopic secretion of ACTH, nor does it exclude Cushing's disease. The results of lateralization by IPS sampling do not remove the need for a thorough transsphenoidal examination of the contents of the sella turcica.

Adenoma↗
PubMed2003

Misrepresenting random sampling? A systematic review of research papers in the Journal of Advanced Nursing.

AIM: This paper discusses the theoretical limitations of the use of random sampling and probability theory in the production of a significance level (or P-value) in nursing research. Potential alternatives, in the form of randomization tests, are proposed. BACKGROUND: Research papers in nursing, medicine and psychology frequently misrepresent their statistical findings, as the P-values reported assume random sampling. In this systematic review of studies published between January 1995 and June 2002 in the Journal of Advanced Nursing, 89 (68%) studies broke this assumption because they used convenience samples or entire populations. As a result, some of the findings may be questionable. DISCUSSION: The key ideas of random sampling and probability theory for statistical testing (for generating a P-value) are outlined. The result of a systematic review of research papers published in the Journal of Advanced Nursing is then presented, showing how frequently random sampling appears to have been misrepresented. Useful alternative techniques that might overcome these limitations are then discussed. REVIEW LIMITATIONS: This review is limited in scope because it is applied to one journal, and so the findings cannot be generalized to other nursing journals or to nursing research in general. However, it is possible that other nursing journals are also publishing research articles based on the misrepresentation of random sampling. The review is also limited because in several of the articles the sampling method was not completely clearly stated, and in this circumstance a judgment has been made as to the sampling method employed, based on the indications given by author(s). CONCLUSION: Quantitative researchers in nursing should be very careful that the statistical techniques they use are appropriate for the design and sampling methods of their studies. If the techniques they employ are not appropriate, they run the risk of misinterpreting findings by using inappropriate, unrepresentative and biased samples.

Data Collection↗
PubMed1989

The safety and efficacy of chorionic villus sampling for early prenatal diagnosis of cytogenetic abnormalities.

Chorionic villus sampling is a method of prenatal diagnosis in the first trimester of pregnancy in which tissue for genetic study is aspirated from the developing placenta by means of a catheter inserted transcervically under the guidance of ultrasonography. In this seven-center study, we compared the safety and efficacy of chorionic villus sampling in 2278 women with those of amniocentesis at 16 weeks' gestation in 671 women. Both groups were made up primarily of well-educated private patients; they were recruited in the first trimester of pregnancy and had viable pregnancies verified by ultrasound examination. Cytogenetic diagnoses resulted from 97.8 percent of the chorionic villus sampling procedures and 99.4 percent of the amniocenteses (P less than 0.05); aneuploidy was found in 1.8 and 1.4 percent, respectively, of the cases in which diagnoses were made. Of the women who underwent chorionic villus sampling, 17 (0.8 percent) subsequently had an amniocentesis because the diagnosis was ambiguous. Two of the diagnoses of aneuploidy (one tetraploidy, one trisomy 22) were later proved to be incorrect. On the basis of pediatric examination of the infants subsequently born to the women in the sample, there were no errors in the determination of sex or the identification of the major trisomies (21, 18, and 13). The rate of combined losses due to spontaneous and missed abortions, termination of abnormal pregnancies, stillbirths, and neonatal deaths was 7.2 percent in the group that underwent chorionic villus sampling and 5.7 percent in the group that had amniocentesis. After adjustment for slight differences in gestational and maternal age, the total loss rate for the women in the chorionic villus sampling group exceeded that for the amniocentesis group by only 0.8 percentage points (80 percent confidence interval, -0.6 to 2.2). The rate of loss of chromosomally normal fetuses after chorionic villus sampling was 10.8 percent among women in whom three or four attempts were made to place the transcervical catheter, as compared with 2.9 percent in those in whom only one attempt was necessary (P less than 0.01). There were no serious maternal infections among the women in this study or among an additional 1990 women who underwent chorionic villus sampling (upper 95 percent confidence limit, 0.08 percent). We conclude that chorionic villus sampling is a safe and effective technique for the early prenatal diagnosis of cytogenetic abnormalities, but that it probably entails a slightly higher risk of procedure failure and of fetal loss than does amniocentesis.

Abortion, Spontaneous↗
PubMed2003

Sample size calculations in surgery: are they done correctly?

BACKGROUND: Randomized controlled trials (RCTs) are considered the gold standard for evidence-based clinical research, but prior work has suggested that there may be poor reporting of sample sizes in the surgical literature. Sample size calculations are essential for planning a study to minimize both type I and type II errors. We hypothesized that sample size calculations may not be performed consistently in surgery studies and, therefore, many studies may be "underpowered." To address this issue, we reviewed RCTs published in the surgical literature to determine how often sample size calculations were reported and to analyze each study's ability to detect varying degrees of differences in outcomes. METHODS: A comprehensive MEDLINE search identified RCTs published in Annals of Surgery, Archives of Surgery, and Surgery between 1999 and 2002. Each study was evaluated by two independent reviewers. Sample size calculations were performed to determine whether they had 80% power to detect differences between treatment groups of 50% (large) and 20% (small), with one-sided test, alpha = 0.05. For the underpowered studies, the degree to which sample size would need to be increased was determined. RESULTS: One hundred twenty-seven RCT articles were identified; of these, 48 (38%) reported sample size calculations. Eighty-six (68%) studies reported positive treatment effect, whereas 41 (32%) found negative results. Sixty-three (50%) of the studies were appropriately powered to detect a 50% effect change, whereas 24 (19%) had the power to detect a 20% difference. Of the studies that were underpowered, more than half needed to increase sample size by more than 10-fold. CONCLUSIONS: The reporting of sample size calculations was not provided in more than 60% of recently published surgical RCTs. Moreover, only half of studies had sample sizes appropriate to detect large differences between treatment groups.

Data Interpretation, Statistical↗
PubMed2006

Sampling foods for mycotoxins.

It is difficult to obtain precise and accurate estimates of the true mycotoxin concentration of a bulk lot when using a mycotoxin-sampling plan that measures the concentration in only a small portion of the bulk lot. A mycotoxin-sampling plan is defined by a mycotoxin test procedure and a defined accept/reject limit. A mycotoxin test procedure is a complicated process and generally consists of several steps: (1) a sample of a given size is taken from the lot, (2) the sample is ground (comminuted) in a mill to reduce its particle size, (3) a subsample is removed from the comminuted sample, and (4) the mycotoxin is extracted from the comminuted subsample and quantified. Even when using accepted test procedures, there is uncertainty associated with each step of the mycotoxin test procedure. Because of this variability, the true mycotoxin concentration in the lot cannot be determined with 100% certainty by measuring the mycotoxin concentration in a sample taken from the lot. The variability for each step of the mycotoxin test procedure, as measured by the variance statistic, is shown to increase with mycotoxin concentration. Sampling is usually the largest source of variability associated with the mycotoxin test procedure. Sampling variability is large because a small percentage of kernels are contaminated and the level of contamination on a single seed can be very large. Methods to reduce sampling, sample preparation and analytical variability are discussed.

Food Analysis↗
PubMed2006

Design of a sampling plan to detect ochratoxin A in green coffee.

The establishment of maximum limits for ochratoxin A (OTA) in coffee by importing countries requires that coffee-producing countries develop scientifically based sampling plans to assess OTA contents in lots of green coffee before coffee enters the market thus reducing consumer exposure to OTA, minimizing the number of lots rejected, and reducing financial loss for producing countries. A study was carried out to design an official sampling plan to determine OTA in green coffee produced in Brazil. Twenty-five lots of green coffee (type 7 - approximately 160 defects) were sampled according to an experimental protocol where 16 test samples were taken from each lot (total of 16 kg) resulting in a total of 800 OTA analyses. The total, sampling, sample preparation, and analytical variances were 10.75 (CV = 65.6%), 7.80 (CV = 55.8%), 2.84 (CV = 33.7%), and 0.11 (CV = 6.6%), respectively, assuming a regulatory limit of 5 microg kg(-1) OTA and using a 1 kg sample, Romer RAS mill, 25 g sub-samples, and high performance liquid chromatography. The observed OTA distribution among the 16 OTA sample results was compared to several theoretical distributions. The 2 parameter-log normal distribution was selected to model OTA test results for green coffee as it gave the best fit across all 25 lot distributions. Specific computer software was developed using the variance and distribution information to predict the probability of accepting or rejecting coffee lots at specific OTA concentrations. The acceptation probability was used to compute an operating characteristic (OC) curve specific to a sampling plan design. The OC curve was used to predict the rejection of good lots (sellers' or exporters' risk) and the acceptance of bad lots (buyers' or importers' risk).

Coffee↗
PubMed2000

Theoretical investigation of the interrelationships between stationary and personal sampling in exposure estimation.

In exposure estimation, personal sampling is the method of choice as it is a nearby representative of the contaminant concentration in the breathing zone. Due to the versatility of the stationary sampling in obtaining much higher sensitivity, in its adaptability to telemetering observations, it may also be an attractive sampling method for many circumstances. However, the two sampling methods differ in many theoretically important ways that go beyond the obvious differences. The theoretical investigation of the stationary and personal sampling methods vis-à-vis sampling for exposure estimation shows that the area sampling can be used to represent personal sampling under restricted conditions. Under the restricted conditions, an area of concentration within specified bounds may be determined in relation to a reasonably well-defined source. The extension of the theory to multiple or ill-defined sources pose potential complications that may be intractable through a theoretical analysis. These limitations and restrictions are inherent to the underlying premises of the two methods; therefore they are not amenable to easy correction. Even though these restrictions may suggest only a limited role for area sampling in exposure assessment, the theory shown also suggests areas of further applied and theoretical research to extend the proper use of area sampling in exposure assessment.

Environmental Exposure↗
PubMed2003

Bioaerosol data distribution: probability and implications for sampling in evaluating problematic buildings.

Airborne fungal contamination in the indoor environment is a substantial contributor to indoor air quality (IAQ) problems, yet there are no set numerical standards by which to evaluate air sampling data. Intuitively appealing is the operational model that the indoor air should not be significantly different from the outdoor air, but determining what is "significant" as well as where to sample and how many samples to collect to determine significance have not been firmly established. The purpose of this study was to determine the number of samples and their locations necessary to determine significant differences in airborne fungi between the ambient and indoor environments. Sampling results from several hundred air samples for culturable fungi from various sites were used to derive a probability of detection in the outdoor air for problematic or "marker" fungal species. Under the assumption that indoor fungal growth results in an increase in the probability of detection for a given fungal species, mathematical probability dictates the number of samples necessary in the indoor (target zone) and in the outdoor (reference zone) air to demonstrate significance. Ultimately, it is the sparse distribution of the problematic species that drives the number of required samples to demonstrate a significant difference, which varies depending upon the level of significance desired. Therefore, the number of samples in each zone can be adjusted to reach a target difference in detection frequency, or an investigator can assess a sampling scheme to identify the differences in detection frequency that show significance.

Aerosols↗
PubMed1999

Sample size-based indication of normality in lognormally distributed populations.

Occupational and environmental hygiene sampling strategies are usually dictated by factors that limit sample sizes to relatively small numbers. Often, parameters estimated from small sample sizes are then used to make further estimates of the occurrence of extreme events, which are governed by the underlying exposure distribution. We investigated the limitations superimposed by the number of samples in distinguishing an asymmetric (Lognormal) distribution through the rejection of a hypothesized symmetric (Normal) distribution. Sets of 5 to 250 synthetic samples from underlying Lognormal distributions with unit median were generated for 24 separate geometric standard deviations (GSDs), ranging from 1.25 to 7.00. Each simulated combination was repeated in blocks of 200 and each block was repeated tenfold. The synthetic samples were then tested for goodness of fit for Normality by using the Shapiro and Wilk's W Test. Results indicated that the number of samples required to distinguish between Normal and Lognormal distributions was inversely related to GSD. When GSD = 1.25, 169 samples were required for 90 percent distinction at alpha = 0.05. The criteria for success for GSD of 2.00 and 4.00 were 25 and 15 samples, respectively. These results led to the conclusion that the general inability to distinguish an underlying distribution may impose serious difficulties in the estimation of extreme events associated with occupational and environmental hygiene-related sampling.

Environmental Monitoring↗
PubMed2002

Commentary: Trade-offs in the development of a sample design for case-control studies.

The recent article, "Comparison of Telephone Sampling and Area Sampling: Response Rates and Within-Household Coverage" (Am J Epidemiol 2001;153:1119-27), raised a number of issues related to two sampling methodologies that can be used for selecting population-based controls for case-control studies: random digit dialing (RDD) and area probability sampling. Some of these issues are discussed in this commentary in more detail to help in making sample design decisions, including the need to take the analysis plan into account when developing a sample design. Data from the paper are used to illustrate how the choice of sample design can affect analyses. Relative costs associated with the two methodologies as well as variance and bias concerns are also discussed in detail. Sample coverage issues, including those associated with list-assisted RDD, are considered, as are some advantages of the list-assisted approach. A discussion of the use of concurrent screening and sampling with an RDD approach as an alternative to periodically selecting fixed sample sizes is provided.

Case-Control Studies↗
PubMed1998

On the sampling variance of intraclass correlations and genetic correlations.

Widely used standard expressions for the sampling variance of intraclass correlations and genetic correlation coefficients were reviewed for small and large sample sizes. For the sampling variance of the intraclass correlation, it was shown by simulation that the commonly used expression, derived using a first-order Taylor series performs better than alternative expressions found in the literature, when the between-sire degrees of freedom were small. The expressions for the sampling variance of the genetic correlation are significantly biased for small sample sizes, in particular when the population values, or their estimates, are close to zero. It was shown, both analytically and by simulation, that this is because the estimate of the sampling variance becomes very large in these cases due to very small values of the denominator of the expressions. It was concluded, therefore, that for small samples, estimates of the heritabilities and genetic correlations should not be used in the expressions for the sampling variance of the genetic correlation. It was shown analytically that in cases where the population values of the heritabilities are known, using the estimated heritabilities rather than their true values to estimate the genetic correlation results in a lower sampling variance for the genetic correlation. Therefore, for large samples, estimates of heritabilities, and not their true values, should be used.

Analysis of Variance↗
PubMed2002

What patient population does visit-based sampling in primary care settings represent?

BACKGROUND: Evaluations of outpatient interventions often rely on consecutive sampling of clinic visitors, and assume that study results generalize to the population of patients cared for. OBJECTIVE: The representativeness of such visit-based sampling compared with the population of patients seen during the same year, in terms of sociodemographic and clinical characteristics of the user groups that visit-based sampling yielded were assessed. METHODS: One thousand five hundred forty-six continuing patients visiting the primary care firms in an urban VA medical center were consecutively sampled, and visit frequencies were compared for these patients with subsets of the patient population. Administrative and survey data was then used to describe the types of patients visit-based sampling most represented compared with the types of patients sampled less frequently. RESULTS: The average sampled patient visited the firms significantly more often than patients in the reference population (18.7 vs. 9.5). Sampled patients were significantly older (>55 years), in poorer health (higher prevalence of cancer, stroke, hypertension), less likely to smoke, and more likely to be single than the average patient visiting the firms (P<0.05). Adjusting for age and sickness, frequent visitors were more apt to have experienced continuity of care during the prior year, to prefer VA care, and to be unemployed. CONCLUSIONS: Consecutive visit-based sampling actually selected patients with a visit pattern more typical of the patient population visiting four or more times a year. Studies using sampling of consecutive visitors will typically under-represent low users of care and should account for the degree to which results may not generalize to the broader practice population.

Adult↗
PubMed2005

Chorionic villus sampling and amniocentesis.

PURPOSE OF REVIEW: The advantages and disadvantages of common invasive methods for prenatal diagnosis are presented in light of new investigations. RECENT FINDINGS: Several aspects of first-trimester chorionic villus sampling and mid-trimester amniocentesis remain controversial, especially fetal loss rate, feto-maternal complications, and the extension of both sampling methods to less traditional gestational ages (early amniocentesis, late chorionic villus sampling), all of which complicate genetic counseling. A recent randomized trial involving early amniocentesis and late chorionic villus sampling has confirmed previous studies, leading to the unquestionable conclusion that transabdominal chorionic villus sampling is safer. The old dispute over whether limb reduction defects are caused by chorionic villus sampling gains new vigor, with a paper suggesting that this technique has distinctive teratogenic effects. The large experience involving maternal and fetal complications following mid-trimester amniocentesis allows a better estimate of risk for comparison with chorionic villus sampling. SUMMARY: Transabdominal chorionic villus sampling, which appears to be the gold standard sampling method for genetic investigations between 10 and 15 completed weeks, permits rapid diagnosis in high-risk cases detected by first-trimester screening of aneuploidies. Sampling efficiency and karyotyping reliability are as high as in mid-trimester amniocentesis with fewer complications, provided the operator has the required training, skill and experience.

Amniocentesis↗
PubMed2001

Inverse adaptive cluster sampling.

Consider a population in which the variable of interest tends to be at or near zero for many of the population units but a subgroup exhibits values distinctly different from zero. Such a population can be described as rare in the sense that the proportion of elements having nonzero values is very small. Obtaining an estimate of a population parameter such as the mean or total that is nonzero is difficult under classical fixed sample-size designs since there is a reasonable probability that a fixed sample size will yield all zeroes. We consider inverse sampling designs that use stopping rules based on the number of rare units observed in the sample. We look at two stopping rules in detail and derive unbiased estimators of the population total. The estimators do not rely on knowing what proportion of the population exhibit the rare trait but instead use an estimated value. Hence, the estimators are similar to those developed for poststratification sampling designs. We also incorporate adaptive cluster sampling into the sampling design to allow for the case where the rare elements tend to cluster within the population in some manner. The formulas for the variances of the estimators do not allow direct analytic comparison of the efficiency of the various designs and stopping rules, so we provide the results of a small simulation study to obtain some insight into the differences among the stopping rules and sampling approaches. The results indicate that a modified stopping rule that incorporates an adaptive sampling component and utilizes an initial random sample of fixed size is the best in the sense of having the smallest variance.

Animals↗
PubMed1989

Precision and reproducibility of quantitative coronary angiography with applications to controlled clinical trials. A sampling study.

Most computer methods that quantify coronary artery disease from angiograms are designed to analyze frames recorded during the end-diastolic portion of the cardiac cycle. The purpose of this study was to determine if end diastole is the best portion of the cardiac cycle to sample, or if other sampling schemes produce more precise and/or reproducible estimates of coronary disease. 20 cinecoronary angiograms were selected at random from a controlled clinical trial testing the effects of plasma lipid lowering on atherosclerosis. Sampling schemes included sequential and random sampling of two to five frames within the complete cardiac cycle, systole, and diastole. Three vessel measures and percent stenosis were evaluated for each sampling scheme. From the sampling experiment, it was determined that sampling sequentially end diastole yielded the most precise estimates (i.e., exhibiting minimum variability within a cycle) of the vessel measures. With regard to reproducibility (i.e., similar values across cycles), sampling randomly within the cycle was best. Overall, the average diameter of a vessel segment was the most precise and the most reproducible of the measures. Sample size calculations are given for each of these measures under the best sampling scheme.

Algorithms↗
PubMed2006

Sample-size requirements for developing strategies, based on the pupal/demographic survey, for the targeted control of dengue.

Several methods to determine the sample size required for a reliable and practical assessment of the number of Aedes aegypti pupae in a community in Puerto Rico have been explored. Because the pupae were highly aggregated, the data were fitted to a negative binomial distribution. Classical statistical-inference methods for sample-size determination demanded the sampling of >3,000 premises for a reliable estimation of the mean number of pupae/person (with a 15% error). This number was reduced to 1,000-1,200 premises after applying a finite-population correction. Database sub-sampling simulations, with increasing sample sizes, showed that the variability in the mean relative abundance of container types and in the mean number of pupae/container substantially decreased after sampling 186 and 310 premises, respectively. Sequential sampling was applied to test the hypotheses that the number of female pupae/person was at least 0.19 (considered the dengue epidemic threshold) or no greater than 0.10 (arbitrarily set as the safe level). After sampling only 25 premises in the first survey and 125 in the second, it was determined that the densities of female pupae were above the epidemic threshold. Thus, sequential sampling provided substantial reductions in the sample size required to determine if vector control was needed. Validation of the Ae. aegypti thresholds required for dengue transmission could confer viability and efficiency to dengue-vector surveillance and control programmes.

Aedes↗
PubMed2004

Sample size for detecting differentially expressed genes in microarray experiments.

BACKGROUND: Microarray experiments are often performed with a small number of biological replicates, resulting in low statistical power for detecting differentially expressed genes and concomitant high false positive rates. While increasing sample size can increase statistical power and decrease error rates, with too many samples, valuable resources are not used efficiently. The issue of how many replicates are required in a typical experimental system needs to be addressed. Of particular interest is the difference in required sample sizes for similar experiments in inbred vs. outbred populations (e.g. mouse and rat vs. human). RESULTS: We hypothesize that if all other factors (assay protocol, microarray platform, data pre-processing) were equal, fewer individuals would be needed for the same statistical power using inbred animals as opposed to unrelated human subjects, as genetic effects on gene expression will be removed in the inbred populations. We apply the same normalization algorithm and estimate the variance of gene expression for a variety of cDNA data sets (humans, inbred mice and rats) comparing two conditions. Using one sample, paired sample or two independent sample t-tests, we calculate the sample sizes required to detect a 1.5-, 2-, and 4-fold changes in expression level as a function of false positive rate, power and percentage of genes that have a standard deviation below a given percentile. CONCLUSIONS: Factors that affect power and sample size calculations include variability of the population, the desired detectable differences, the power to detect the differences, and an acceptable error rate. In addition, experimental design, technical variability and data pre-processing play a role in the power of the statistical tests in microarrays. We show that the number of samples required for detecting a 2-fold change with 90% probability and a p-value of 0.01 in humans is much larger than the number of samples commonly used in present day studies, and that far fewer individuals are needed for the same statistical power when using inbred animals rather than unrelated human subjects.

Animals↗
PubMed2001

Establishing the prevalence of hypertension. Influence of sampling criteria.

OBJECTIVE: To compare the prevalence of systemic hypertension in two different populations: a representative sample of the adult urban population of Porto Alegre, and individuals who sought blood pressure measurement in a hypertension prevention and control campaign. METHODS: A cross-sectional study was carried out involving a representative sample of the adult urban population of Porto Alegre and a population sample obtained from a hypertension prevention and control campaign, which included all the individuals who sought the blood pressure assessment unit at the Hospital das Clínicas in Porto Alegre. The following parameters were investigated: history of hypertension, use of antihypertensive drugs, age, and sex. Adjustments for age and sex in the prevalence rates were performed to make them comparable. RESULTS: Hypertension prevalence, defined as values > or =160/95 mmHg or treatment with antihypertensive drugs, was higher in the campaign sample (42%) as compared with the population sample (24%). Among those who were aware of their hypertensive condition and were under medication, 54% of the campaign sample and 62% of the representative population sample maintained their pressure levels <160/90 mmHg. CONCLUSION: Prevalence rates of hypertension differed a lot in the campaign sample and in the representative population sample, showing that the sampling criterion may influence assessment of risk factors and bias the association between risk factors and health aggravations.

Adolescent↗