Assessment of the precision of a health survey on hypertension prevalence

Assessment of the precision of a health survey on hypertension prevalence | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of the precision of a health survey on hypertension prevalence Reinaldo José Gianini, Natália Ferreira Caneto, Natalia Murate Ferreira, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4277753/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Aug, 2024 Read the published version in BMC Public Health → Version 1 posted 4 You are reading this latest preprint version Abstract Background Population surveys are important for planning public policies and constitute an efficient way of obtaining representative data. In the health field, studies have been conducted with different objectives, such as identifying arterial hypertension (AH), which is a chronic noncommunicable disease (NCD), and determining its prevalence and associated risk factors. Objectives To evaluate the performance of a population health survey carried out in the municipality of Sorocaba between August 2021 and June 2023 to estimate the prevalence of AH. Methods The performance indicator analyzed refers to the precision (design effect - deff) of the AH prevalence in adults (≥ 18 years) and the exposure to its main risk factors. The total sample included 1,080 individuals from the urban region, which is considered sufficient to estimate a deff of 1.5. This is a study whose clusters are represented by census sectors, with data collected during household visits through interviews using a standardized questionnaire and blood pressure and biometric parameter measurements. The deff calculation formula used was weighted variance/raw variance. The study was approved by the Research Ethics Committee, CAAE 30538520-1-0000-5373. Results The data obtained varied between a deff equal to 0.44 for the prevalence of chronic obstructive pulmonary disease and a deff equal to 1.49 for the use of sympatholytic medication, with a deff for the prevalence of AH equal to 1.12. Conclusion There was good precision of the results. There was excellent receptivity and collaboration among the interviewees. The cost‒benefit in developing this research was very adequate. The technique for selecting households in the respective clusters (census sectors), based on detailed mapping and demographic information from Instituto Brasileiro de Geografia e Estatística - IBGE, proved to be practical and efficient and can be reproduced in other municipalities and for other NCDs. Hypertension Prevalence Cluster sampling Health surveys Data accuracy Epidemiology Background Population health surveys are epidemiological tools applied to construct reliable health information and are carried out with probabilistic and representative samples; these surveys may be international, national, regional or local 1 . When primary data are obtained, the methodology is defined by the researcher, who has control over the data collection and application of the instrument, usually through a questionnaire. On the other hand, when secondary data are collected, the information bases are public and were originally created for administrative, financial or epidemiological purposes 2 . In health, they deal with the description and analysis of the prevalence of diseases and their risk factors, including reported or diagnosed morbidity. They evaluate, through questionnaires, the functioning of health care from the user's point of view; to obtain knowledge about morbidity and lifestyles; to obtain reliable estimates about the prevalence of a given event; to research risk and protective factors; to monitor conditions of health; to develop health systems; and to exercise surveillance of various chronic diseases and their determinants 3 , 4 . The need for health surveys arises from the limitations of continuous or defined periodicity recording health data, which can be classified as timely, partial, incomplete, unsatisfactory, fragmented, outdated or not allowing disaggregation 5 , 6 . The National Health Survey (PNS), one of the main Brazilian population surveys, uses a probabilistic cluster sample that allows for resource savings and is obtained in 3 selection stages: primary units – census tracts; secondary units – households; and tertiary units – individuals aged 18 or over. In 2013, the PNS included 6081 sectors, 81767 households and 62986 individuals 7 . Surveys can be performed via telephone, mail, the internet, home visits or interviews. For diagnosed morbidity, these methods include subsample clinical examinations and biological specimen collection 8 . In developed countries, population-based surveys have been conducted since the 1960s. In the case of Brazil, the Ministry of Health has made substantial investments in the area since the 1990s, such as financing the National Research Health Supplement by Household Sample (PNAD) from 1967, which became continuous in 2012 9 . Other important surveys in Brazil were from the National Cancer Institute (INCA) 10 ; from the Municipality of São Paulo 11 ; ISA SP CAPITAL 12 ; and VIGITEL, annually since 2006 13 . At the international level, the following surveys were performed: the National Health Interview Survey (USA) 14 ; the European Health Interview 15 ; the General Health Survey for England 16 ; the National Population Health Survey 17 (Canada); and the World Health Survey 18 . Regarding the prevalence of arterial hypertension (AH) in adults ≥ 18 years old, the 2013 PNS reported a prevalence of 21.4% (95% CI 20.8–22.0) using self-reported criteria, 22.8% (95% CI 22.1–23.4) for measured AH, and 32.3% (95% CI 31.7–33.0) for measured hypertension and/or reported medication use. The prevalence for adults ≥ 75 years old was 55% 19 . For complex methods, such as the one used in the PNS, it is recommended to calculate the design effect, also known as deff, which is an important estimator, both in planning the sample size and in evaluating the precision of the results obtained from a survey. The design effect - deff is the ratio between the weighted variance and the raw variance, with the weighted variance considering the different weights of the clusters included in the sample (intercluster variance) and the raw variance considering only the different individual weights (intracluster variance) 20 . A design effect (deff) lower than 2 21 is recommended. Studying the prevalence of chronic noncommunicable diseases in Brazilian populations, such as AH, has epidemiological value, as long as the statistical criteria established for defining the prevalence and associated risk factors are valid. To this end, calculating the effect design - deff can help in defining the performance of the methodology used. Objectives To evaluate the performance of a population health survey carried out in the municipality of Sorocaba from 2021–2023, the objective of which was to estimate the prevalence of AH. The performance indicator refers to the precision (design effect - def) of the AH prevalence in adults and the exposure to their main risk factors. Methods The survey aimed to analyze the urban resident population of the municipality of Sorocaba, which is aged ≥ 18 years and estimated at 535,843 individuals in 2022, with the total population of this municipality being estimated at 723,682 individuals in the same year 22 . Sampling was performed in clusters composed of 6 strata represented by the regionalized division of the Municipal Health Department of Sorocaba: Center South, East, Center North, North, Northwest and Southwest Regions. In each stratum, 10 census sectors were selected, and in each census sector, data were collected from 18 individuals divided into 6 domains: 6 over 60 years of age, 3 men and 3 women; 6 individuals aged 40 to 59 years, 3 of each sex; and 6 individuals aged 18 to 39 years, 3 of each sex. The total sample included 1,080 individuals, satisfying the following parameters: expected prevalence of arterial hypertension = 33.7% with an estimated error of 3.65%; significance level of 0.05 considering a two-sided test with Z = 1.96; design effect (deff) = 1.5; and loss of information (nonresponse) = 10%. The selection of 60 census sectors was conducted according to the following procedure: listing all sectors belonging to a given region in descending order according to the size of the population of each sector, calculating the interval to be used in systematic random sampling (total sectors of the region/10), drawing the sector from the first interval and systematically repeating the interval to select the 9 remaining sectors in that region. The selection of households was carried out using the following procedure: mapping the residential streets of the census sector, defining the route, calculating the interval between households to be selected (total households/18), drawing the first household to be included and systematically repeating the interval for the selection of the remaining 17 individuals. To ensure data collection, the recruitment of individuals followed the order of the rarest domain to the most frequent, namely, elderly males, elderly females, young males, young females, adult males and adult females. Collection was extended on holidays, Saturdays and Sundays to ensure the inclusion of workers. As this is a survey sample, the weight of the sampling unit was composed of the following: 1. Individual weight = total individuals from the same domain in the census sector/number of individuals from the same domain sampled; 2. Sector weight = stratum population/sampled sector population x number of sampled sectors; 3. Weight of the region = total population/population of the region x number of regions; 4. The final weight of each sample unit = (1 × 2 × 3). For data collection, a standardized form containing sociodemographic data and risk factors for AH was used as an instrument. In addition to the correct measurements of blood pressure (BP), age and sex of the individuals selected for the sample, additional information was collected, such as skin color/race/ethnicity, marital status, education, occupation/type of work, religion, family income in reais, number of people in the family, family morbidity history, use of health services, chronic diseases and comorbidities, medical treatment, practice of physical activity, ingestion of alcoholic beverages, and smoking. Data were collected from August 2021 to June 2023 during household visits through interviews using a standardized questionnaire with open or multiple alternative questions. In addition, blood pressure was measured in accordance with the recommendations of the Brazilian AH Guidelines 2020. Participants who had an average systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg were considered to have AH or who had a BP below these limits and were receiving regular treatment with antihypertensive medications 23 , 24 , 25 . The STATA 16.0 program and its survey command were used for the analyses. The calculation of the design effect, deff, was carried out using the stat effects command with the deff option after svy mean command for continuous quantitative variables, or svy , proportion for qualitative variables 26 . The formula for calculating the design effect - def used was weighted variance/raw variance 20 . This project was submitted and approved by the Research Ethics Committee (CEP) of the Faculty of Medical and Health Sciences (FCMS) of the Pontifical Catholic University of São Paulo (PUC-SP), CAAE 30538520-1-0000-5373. Results In the period between the second half of 2021 and the first half of 2023, data were collected from 1,080 individuals in 60 sectors as planned. The intracluster weights assigned to the individuals interviewed ranged from 1.7 to 161. All sectors planned for collection were included. The sector weights ranged from 1.93 to 159.1. The region weights ranged from 0.14 to 3.35. The greatest data loss was for family income (34%); however, for the other variables, this loss did not exceed 0.4%. The interviewers, always in pairs, strictly followed the collection protocol, trying to cover the entire area of ​​the census sector. Vertical or horizontal condominiums were included, applying the same proportionality rule (draw) for choosing the residential unit. Nonregular situations, such as collective housing or clusters of precarious housing, were registered, analyzed and included, and the same sample selection rule was applied. The interviewers, students of the Scientific Initiation Program of Medicine, supervised by professors, followed the construction of the database in STATA, based on data collected in an EXCEL spreadsheet, and they participated in the first analyses. Table 1 shows that for the design effect (deff according to sociodemographic variables), the deff values of the social and demographic variables were less than 1.5, which was the value estimated in the sample planning, indicating better precision of the results. The “no religion” category/Religion variable has the highest deff (1.34), and the Age variable has the lowest deff (1.00). Also noteworthy is the deff of 1.02 for occupation, indicating good accuracy in information about activity or inactivity. Table 1 – Design effect value – deff, according to sociodemographic variables. Sorocaba-SP/2021-23 Variable Type of variable Category* deff Marital Status Polytomous Qualitative Separated 1.31 Ethnicity Polytomous Qualitative Asians 1.30 Gender Dichotomous Qualitative Man or woman 1.19 Age Quantitative Years 1.00 Religion Polytomous Qualitative No religion 1.34 Education Polytomous Qualitative High school, incomplete 1.33 Family monthly income Quantitative Brazilian Reais 1.29 Number of people in the household Quantitative total number of people in the household 1.23 Occupation Qualitative Active or inactive 1.02 *For polytomous variables, the category with the highest deff is described. Table 2 shows that for the design effect value, defined according to variables related to lifestyle, the highest deff was for the use of depressant drugs (1.39). Deffs lower than 1 were observed for time spent smoking (0.89) and time as an ex-smoker (0.85). Ex-smokers and individuals with Ex-alcoholism have deff values ​​close to or equal to 1. Table 2 – Design effect value – deff, according to variables related to lifestyle. Sorocaba-SP/2021-23 Variable Type of variable Category deff Smoking Dichotomous qualitative Yes or not 1.16 Time of smoking Quantitative years 0.89 Ex-smoker Dichotomous qualitative Yes or not 1.06 Time as ex-smoker Quantitative years 0.85 alcoholism Dichotomous qualitative Yes or not 1.22 Alcohol amount Quantitative Grams per day 1.19 Ex-alcoholism Dichotomous qualitative Yes or not 1.00 Use of Illicit drugs Dichotomous qualitative Yes or not 1.36 Use of Depressant drugs Dichotomous qualitative Yes or not 1.39 Use of Stimulant drugs Dichotomous qualitative Yes or not 1.26 Use of Disruptive drugs Dichotomous qualitative Yes or not 1.38 Physical activity Dichotomous qualitative Yes or not 1.22 Quantity of physical activity Quantitativa Hour per week 1.27 Level of physical activity Quantitative Stress load 1.26 Low sodium diet Dichotomous qualitative Yes or not 1.19 Salt shaker on the table Dichotomous qualitative Yes or not 1.23 Table 3 shows that according to the variables related to family and personal morbid history, the deff varied from 0.44 for chronic obstructive pulmonary disease (COPD) to 1.30 for asthma, and they had values ​equal to or close to 1 for comorbidities, dyslipidemia, hyperhypertension and hypothyroidism. Table 3 Value of the design effect - deff according to variables related to family and personal morbidity antecedents. Sorocaba-SP/2021-23 Variable Type of variable Category deff Family member with some morbidity Dichotomous qualitative Yes or not 1.11 Family member with stroke Dichotomous qualitative Yes or not 1.17 Family member with acute myocardial infarction Dichotomous qualitative Yes or not 1.18 Family member with diabetes mellitus Dichotomous qualitative Yes or not 1.21 Family member with high blood pressure Dichotomous qualitative Yes or not 1.17 Comorbidities (interviewee) Dichotomous qualitative Yes or not 1.01 Dyslipidemia (interviewed) Dichotomous qualitative Yes or not 1.00 Ischemic Heart Disease (interviewed) Dichotomous qualitative Yes or not 0.87 Stroke (interviewed) Dichotomous qualitative Yes or not 0.84 Chronic Kidney Disease (interviewed) Dichotomous qualitative Yes or not 0.88 Chronic Obstructive Pulmonary Disease (interviewed) Dichotomous qualitative Yes or not 0.87 Type 2 diabetes mellitus (interviewed) Dichotomous qualitative Yes or not 0.91 Asthma (interviewed) Dichotomous qualitative Yes or not 1.30 Chronic Obstructive Pulmonary Disease (interviewed) Dichotomous qualitative Yes or not 0.44 Hypothyroidism (interviewed Dichotomous qualitative Yes or not 1.10 Hyperthyroidism (interviewed Dichotomous qualitative Yes or not 1.04 Gastritis (interviewed) Dichotomous qualitative Yes or not 1.16 Osteoporosis (interviewed Dichotomous qualitative Yes or not 0.58 Common Mental Disorder (interviewed Dichotomous qualitative Yes or not 1.19 Table 4 shows that according to variables related to the clinical examination, the deff varied from 0.88 for arm circumference to 1.25 for body mass index, and the deff was very satisfactory for HA, at 1.12. Height, mean systolic blood pressure and metabolic syndrome factors presented deff values ​​close to 1. Table 4 Design effect value – deff, according to variables related to the clinical examination. Sorocaba-SP/2021-23 Variable Type of variable Category deff Weight quantitative kilos 1.24 Height quantitative centimeters 1.06 Arm circumference quantitative centimeters 0.88 Abdominal circumference quantitative centimeters 1.19 Average Systolic Blood Pressure quantitative mmHg 1.08 Average Diastolic Blood Pressure quantitative mmHg 1.18 Average Heart Rate quantitative beats/minute 1.17 Body mass index quantitative kg/m 2 1.25 Hypertension qualitative > or < 140/90 mmHg 1.12 Metabolic Syndrome Factors qualitative Yes or not 1.02 Stress qualitative Yes or not 1.20 As shown in Table 5 , for the effect of the design (deff according to variables related to the drug treatment of AH), the deff varied from 0.88 for the use of angiotensin II converting enzyme inhibitors (ACEI) or calcium channel blockers (BCCA) to 1.42 for the use of sympatholytics, which was the highest deff in this sample. A previous diagnosis of AH and the time of last consultation presented a difference close to 1. Table 5 – Design effect value – deff, according to variables related to the drug treatment of arterial hypertension. Sorocaba-SP/2021-23 Variable Type of variable Cathegory deff Medical insurance qualitative Yes or not 1.21 Diagnosis of hypertension qualitative Yes or not 1.01 Hypertension treatment qualitative Yes or not 0.97 Use of angiotensin II AT1 receptor blockers qualitative Yes or not 0.93 Use of angiotensin II converting enzyme inhibitors qualitative Yes or not 0.88 Use of calcium channel blockers qualitative Yes or not 0.88 Use of thiazide diuretics qualitative Yes or not 0.92 Beta blocker use qualitative Yes or not 0.93 Loop diuretic use qualitative Yes or not 0.98 Use of spironolactone qualitative Yes or not 0.92 Use of sympatholytic qualitative Yes or not 1.42 Use of direct-acting vasodilators qualitative Yes or not 0.98 Time since last consultation quantitative months 1.07 Recent search for health services qualitative Yes or not 1.38 Discussion This is considered successful research, representative of the urban population of Sorocaba, which requires much effort, but few resources are available given the strategy of developing it as a scientific initiation program with students supervised by medical teachers and with the use of software already available at the institution. Regarding the urban population aged 18 or over, it can be inferred that the selection bias was practically null, not only by analyzing the data but also by comparing it with other surveys 20 , 27–30 . Regarding precision, the research proved to be very satisfactory, given that the design effects (deff) were less than 1.5 for all variables analyzed, and in particular for arterial hypertension, deff = 1.12 in our study; for example, in the study by Alves 20 , it was 1.37 for the group of adolescents and 1.52 for the group of elderly people. From the data, it can be inferred that one of the axes of precision was objective information, subject to verification, notably variables related to clinical examination, as opposed to subjective information such as variables related to lifestyle. The other axis of precision refers to the frequency of the event in the population and its intracluster and intercluster variance. If the clusters are more similar than expected for a random distribution of a given variable, the design effect may be less than 1. Furthermore, if the variable is widely distributed in the population, there is a small cluster effect, and the prevalence of the event studied differs significantly inside strata, so it is likely that the design effect is less than 1 27 . It can occur in both very frequent and rare events, which explains the design effects of osteoporosis (0.58) and COPD (0.44), respectively. It is important to note that information on family income was highly lost, that information on drug use was probably influenced by modesty or fear, and that information on seeking health services was compromised by the respondents' memories. The comorbidities of the interviewees could have been diagnosed in some situations. For example, in patients with diabetes, asthma and COPD, capillary blood glucose tests and spirometry are used. Furthermore, considering that it is a resident population and that the bond established in the first contact was of high quality, it would be possible to schedule new visits to obtain more information, including various clinical protocols, such as adherence to treatment. Conclusion A survey was performed with the urban population of Sorocaba between 2021 and 2023 with the main objective of measuring the prevalence of AH in adults. There was good precision in the results, with a design effect of -DF of 1.12 for this variable, receptivity and collaboration of interviewees, and an adequate cost‒benefit ratio in carrying out the research. The technique for selecting households in the respective clusters (census sectors), based on detailed mapping and demographic information from the IBGE, proved to be practical and efficient. Declarations Consent to participate : Every human participant has given their consent to participate. Ethics approval : This project was submitted and approved by the Research Ethics Committee (Comitê de Ética em Pesquisa) of the Faculdade de Ciências Médicas e da Saúde of the Pontifícia Universidade Católica de São Paulo, CAAE 30538520-1-0000-5373. Funding : This research received funding from Pontifícia Universidade Católica de São Paulo, numbered as 17807 and 15504. Competing interests : There are NO competing interests. References Silva VSTM, Pinto LF. Nationwide population-based household surveys in health: a narrative review. Ciênc. saúde coletiva. 2021;26(09):4045-4058. https://doi.org/10.1590/1413-81232021269.28792020. Viacava F. Health information: the relevance of health surveys. Ciênc. saúde coletiva. 2002;7(4):607-21. https://doi.org/10.1590/S1413-81232002000400002 Malta DC, Leal MC, Costa MFL. Inquéritos Nacionais de Saúde: experiência acumulada e proposta para o inquérito de saúde brasileiro. 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Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda International Journal of Health Geographics 2020; (19):34 https://doi.org/10.1186/s12942-020-00230-4 USAID. Sampling and household listing manual. Demographic and health survey methodology. ICF International, Calverton, USA 2012 Grais RF et al. Don’t spin the pen: two alternatives methods for second-stage sampling in urban cluster surveys. Emerging themes in epidemiology 4:8, 2007. Doi 10.1186/1742-7622-4-8 Silva NN e Roncalli AG. Sampling plan, weighting process and design effects of the Brazilian Oral Health Survey. Rev Saude Publica 2013:47(supl.3) :3-11. DOI:10.1590/S0034-8910.2013047004362 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 12 Aug, 2024 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 23 Apr, 2024 Submission checks completed at journal 22 Apr, 2024 Editor assigned by journal 22 Apr, 2024 First submitted to journal 16 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4277753","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":294529310,"identity":"db97df01-83a6-475c-b93e-212eed7f1ba2","order_by":0,"name":"Reinaldo José Gianini","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYFACxgYGhgJmMOsBkODhI06LAVgLswFICxtxNkG0sEmASUKKzdub2x78MLCWk4/uPVb5NcdOho2B+eGjG3i0yJw52G7YY5BubHjnXNpt2W3JQIexGRvn4NEiIZHYJsFjcDhx44wcs9uS25iBWnjYpPFqkX/YJvkHqqVYcls9EVokGNukQbbMl8gxY/y47TARWngS26RlgH4xkMgxlmbcdpyHjZmQX9iPP5N8UwEMsRk5hh9/bqu252dvfvgYnxY4MDgAjEseEIuZGOUgIN8ATAg/iFU9CkbBKBgFIwoAAHxpP/3HCEunAAAAAElFTkSuQmCC","orcid":"","institution":"Pontifícia Universidade Católica de São Paulo","correspondingAuthor":true,"prefix":"","firstName":"Reinaldo","middleName":"José","lastName":"Gianini","suffix":""},{"id":294529311,"identity":"2a6014e2-9035-47a4-8530-fb9b9f1e2e78","order_by":1,"name":"Natália Ferreira Caneto","email":"","orcid":"","institution":"Pontifícia Universidade Católica de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Natália","middleName":"Ferreira","lastName":"Caneto","suffix":""},{"id":294529312,"identity":"43a19bba-6fd6-4d3f-8f00-2fcafd760d9a","order_by":2,"name":"Natalia Murate Ferreira","email":"","orcid":"","institution":"Pontifícia Universidade Católica de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Natalia","middleName":"Murate","lastName":"Ferreira","suffix":""},{"id":294529313,"identity":"3c9b5597-bdd4-4ef4-9f08-7abee0f5a74c","order_by":3,"name":"Leticia Gouvea Rodrigues","email":"","orcid":"","institution":"Pontifícia Universidade Católica de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Leticia","middleName":"Gouvea","lastName":"Rodrigues","suffix":""},{"id":294529314,"identity":"84913fd7-9290-4896-b809-8b206eb9eab3","order_by":4,"name":"Beatriz Zurma Parri","email":"","orcid":"","institution":"Pontifícia Universidade Católica de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Beatriz","middleName":"Zurma","lastName":"Parri","suffix":""},{"id":294529315,"identity":"4812fac0-5c24-40cf-989d-903c202be372","order_by":5,"name":"Cibele Isaac Saad Rodrigues","email":"","orcid":"","institution":"Pontifícia Universidade Católica de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Cibele","middleName":"Isaac Saad","lastName":"Rodrigues","suffix":""}],"badges":[],"createdAt":"2024-04-16 18:29:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4277753/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4277753/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-024-19626-z","type":"published","date":"2024-08-12T15:58:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63071312,"identity":"926e0a91-d32a-41de-be4d-218e38ba3585","added_by":"auto","created_at":"2024-08-22 20:06:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":528193,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4277753/v1/0d9c0100-4ee6-45b2-b85d-3a27c63f9a5b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of the precision of a health survey on hypertension prevalence","fulltext":[{"header":"Background","content":"\u003cp\u003ePopulation health surveys are epidemiological tools applied to construct reliable health information and are carried out with probabilistic and representative samples; these surveys may be international, national, regional or local\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. When primary data are obtained, the methodology is defined by the researcher, who has control over the data collection and application of the instrument, usually through a questionnaire. On the other hand, when secondary data are collected, the information bases are public and were originally created for administrative, financial or epidemiological purposes \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. In health, they deal with the description and analysis of the prevalence of diseases and their risk factors, including reported or diagnosed morbidity. They evaluate, through questionnaires, the functioning of health care from the user's point of view; to obtain knowledge about morbidity and lifestyles; to obtain reliable estimates about the prevalence of a given event; to research risk and protective factors; to monitor conditions of health; to develop health systems; and to exercise surveillance of various chronic diseases and their determinants \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe need for health surveys arises from the limitations of continuous or defined periodicity recording health data, which can be classified as timely, partial, incomplete, unsatisfactory, fragmented, outdated or not allowing disaggregation \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe National Health Survey (PNS), one of the main Brazilian population surveys, uses a probabilistic cluster sample that allows for resource savings and is obtained in 3 selection stages: primary units \u0026ndash; census tracts; secondary units \u0026ndash; households; and tertiary units \u0026ndash; individuals aged 18 or over. In 2013, the PNS included 6081 sectors, 81767 households and 62986 individuals \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSurveys can be performed via telephone, mail, the internet, home visits or interviews. For diagnosed morbidity, these methods include subsample clinical examinations and biological specimen collection \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn developed countries, population-based surveys have been conducted since the 1960s. In the case of Brazil, the Ministry of Health has made substantial investments in the area since the 1990s, such as financing the National Research Health Supplement by Household Sample (PNAD) from 1967, which became continuous in 2012 \u003csup\u003e9\u003c/sup\u003e. Other important surveys in Brazil were from the National Cancer Institute (INCA) \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e; from the Municipality of S\u0026atilde;o Paulo \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e; ISA SP CAPITAL \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e; and VIGITEL, annually since 2006 \u003csup\u003e13\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAt the international level, the following surveys were performed: the National Health Interview Survey (USA)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e; the European Health Interview\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e;\u003c/sup\u003e the General Health Survey for England \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e; the National Population Health Survey\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e (Canada); and the World Health Survey \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRegarding the prevalence of arterial hypertension (AH) in adults\u0026thinsp;\u0026ge;\u0026thinsp;18 years old, the 2013 PNS reported a prevalence of 21.4% (95% CI 20.8\u0026ndash;22.0) using self-reported criteria, 22.8% (95% CI 22.1\u0026ndash;23.4) for measured AH, and 32.3% (95% CI 31.7\u0026ndash;33.0) for measured hypertension and/or reported medication use. The prevalence for adults\u0026thinsp;\u0026ge;\u0026thinsp;75 years old was 55% \u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor complex methods, such as the one used in the PNS, it is recommended to calculate the design effect, also known as deff, which is an important estimator, both in planning the sample size and in evaluating the precision of the results obtained from a survey. The design effect - \u003cem\u003edeff\u003c/em\u003e is the ratio between the weighted variance and the raw variance, with the weighted variance considering the different weights of the clusters included in the sample (intercluster variance) and the raw variance considering only the different individual weights (intracluster variance) \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. A design effect (deff) lower than 2 \u003csup\u003e21\u003c/sup\u003e is recommended.\u003c/p\u003e \u003cp\u003eStudying the prevalence of chronic noncommunicable diseases in Brazilian populations, such as AH, has epidemiological value, as long as the statistical criteria established for defining the prevalence and associated risk factors are valid. To this end, calculating the effect design - deff can help in defining the performance of the methodology used.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo evaluate the performance of a population health survey carried out in the municipality of Sorocaba from 2021\u0026ndash;2023, the objective of which was to estimate the prevalence of AH. The performance indicator refers to the precision (design effect - def) of the AH prevalence in adults and the exposure to their main risk factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003eThe survey aimed to analyze the urban resident population of the municipality of Sorocaba, which is aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years and estimated at 535,843 individuals in 2022, with the total population of this municipality being estimated at 723,682 individuals in the same year \u003csup\u003e22\u003c/sup\u003e. Sampling was performed in clusters composed of 6 strata represented by the regionalized division of the Municipal Health Department of Sorocaba: Center South, East, Center North, North, Northwest and Southwest Regions. In each stratum, 10 census sectors were selected, and in each census sector, data were collected from 18 individuals divided into 6 domains: 6 over 60 years of age, 3 men and 3 women; 6 individuals aged 40 to 59 years, 3 of each sex; and 6 individuals aged 18 to 39 years, 3 of each sex. The total sample included 1,080 individuals, satisfying the following parameters: expected prevalence of arterial hypertension\u0026thinsp;=\u0026thinsp;33.7% with an estimated error of 3.65%; significance level of 0.05 considering a two-sided test with Z\u0026thinsp;=\u0026thinsp;1.96; design effect (deff)\u0026thinsp;=\u0026thinsp;1.5; and loss of information (nonresponse)\u0026thinsp;=\u0026thinsp;10%. The selection of 60 census sectors was conducted according to the following procedure: listing all sectors belonging to a given region in descending order according to the size of the population of each sector, calculating the interval to be used in systematic random sampling (total sectors of the region/10), drawing the sector from the first interval and systematically repeating the interval to select the 9 remaining sectors in that region.\u003c/p\u003e \u003cp\u003eThe selection of households was carried out using the following procedure: mapping the residential streets of the census sector, defining the route, calculating the interval between households to be selected (total households/18), drawing the first household to be included and systematically repeating the interval for the selection of the remaining 17 individuals. To ensure data collection, the recruitment of individuals followed the order of the rarest domain to the most frequent, namely, elderly males, elderly females, young males, young females, adult males and adult females. Collection was extended on holidays, Saturdays and Sundays to ensure the inclusion of workers.\u003c/p\u003e \u003cp\u003eAs this is a survey sample, the weight of the sampling unit was composed of the following: 1. Individual weight\u0026thinsp;=\u0026thinsp;total individuals from the same domain in the census sector/number of individuals from the same domain sampled; 2. Sector weight\u0026thinsp;=\u0026thinsp;stratum population/sampled sector population x number of sampled sectors; 3. Weight of the region\u0026thinsp;=\u0026thinsp;total population/population of the region x number of regions; 4. The final weight of each sample unit = (1 \u0026times; 2 \u0026times; 3).\u003c/p\u003e \u003cp\u003eFor data collection, a standardized form containing sociodemographic data and risk factors for AH was used as an instrument. In addition to the correct measurements of blood pressure (BP), age and sex of the individuals selected for the sample, additional information was collected, such as skin color/race/ethnicity, marital status, education, occupation/type of work, religion, family income in reais, number of people in the family, family morbidity history, use of health services, chronic diseases and comorbidities, medical treatment, practice of physical activity, ingestion of alcoholic beverages, and smoking.\u003c/p\u003e \u003cp\u003eData were collected from August 2021 to June 2023 during household visits through interviews using a standardized questionnaire with open or multiple alternative questions. In addition, blood pressure was measured in accordance with the recommendations of the Brazilian AH Guidelines 2020. Participants who had an average systolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg and/or diastolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg were considered to have AH or who had a BP below these limits and were receiving regular treatment with antihypertensive medications \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe STATA 16.0 program and its survey command were used for the analyses. The calculation of the design effect, deff, was carried out using the \u003cem\u003estat effects\u003c/em\u003e command with the deff option after \u003cem\u003esvy mean\u003c/em\u003e command for continuous quantitative variables, or \u003cem\u003esvy\u003c/em\u003e,\u003c/p\u003e \u003cp\u003e \u003cem\u003eproportion\u003c/em\u003e for qualitative variables \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The formula for calculating the design effect - def used was weighted variance/raw variance \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e This project was submitted and approved by the Research Ethics Committee (CEP) of the Faculty of Medical and Health Sciences (FCMS) of the Pontifical Catholic University of S\u0026atilde;o Paulo (PUC-SP), CAAE 30538520-1-0000-5373.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn the period between the second half of 2021 and the first half of 2023, data were collected from 1,080 individuals in 60 sectors as planned. The intracluster weights assigned to the individuals interviewed ranged from 1.7 to 161. All sectors planned for collection were included. The sector weights ranged from 1.93 to 159.1. The region weights ranged from 0.14 to 3.35. The greatest data loss was for family income (34%); however, for the other variables, this loss did not exceed 0.4%. The interviewers, always in pairs, strictly followed the collection protocol, trying to cover the entire area of ​​the census sector. Vertical or horizontal condominiums were included, applying the same proportionality rule (draw) for choosing the residential unit. Nonregular situations, such as collective housing or clusters of precarious housing, were registered, analyzed and included, and the same sample selection rule was applied. The interviewers, students of the Scientific Initiation Program of Medicine, supervised by professors, followed the construction of the database in STATA, based on data collected in an EXCEL spreadsheet, and they participated in the first analyses.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that for the design effect (deff according to sociodemographic variables), the deff values of the social and demographic variables were less than 1.5, which was the value estimated in the sample planning, indicating better precision of the results. The \u0026ldquo;no religion\u0026rdquo; category/Religion variable has the highest deff (1.34), and the Age variable has the lowest deff (1.00). Also noteworthy is the deff of 1.02 for occupation, indicating good accuracy in information about activity or inactivity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Design effect value \u0026ndash; deff, according to sociodemographic variables. Sorocaba-SP/2021-23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edeff\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolytomous Qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolytomous Qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAsians\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous Qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMan or woman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolytomous Qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo religion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolytomous Qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh school, incomplete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily monthly income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBrazilian Reais\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of people in the household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal number of people in the household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eActive or inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*For polytomous variables, the category with the highest deff is described.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that for the design effect value, defined according to variables related to lifestyle, the highest deff was for the use of depressant drugs (1.39). Deffs lower than 1 were observed for time spent smoking (0.89) and time as an ex-smoker (0.85). Ex-smokers and individuals with Ex-alcoholism have deff values ​​close to or equal to 1.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Design effect value \u0026ndash; deff, according to variables related to lifestyle. Sorocaba-SP/2021-23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edeff\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime of smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eyears\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime as ex-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eyears\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ealcoholism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol amount\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrams per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-alcoholism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of Illicit drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of Depressant drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of Stimulant drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of Disruptive drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuantity of physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitativa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHour per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStress load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow sodium diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt shaker on the table\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that according to the variables related to family and personal morbid history, the deff varied from 0.44 for chronic obstructive pulmonary disease (COPD) to 1.30 for asthma, and they had values ​equal to or close to 1 for comorbidities, dyslipidemia, hyperhypertension and hypothyroidism.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eValue of the design effect - deff according to variables related to family and personal morbidity antecedents. Sorocaba-SP/2021-23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edeff\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily member with some morbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily member with stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily member with acute myocardial infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily member with diabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily member with high blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities (interviewee)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic Heart Disease (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Kidney Disease (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Obstructive Pulmonary Disease (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2 diabetes mellitus (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Obstructive Pulmonary Disease (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypothyroidism (interviewed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperthyroidism (interviewed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastritis (interviewed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOsteoporosis (interviewed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommon Mental Disorder (interviewed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDichotomous qualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that according to variables related to the clinical examination, the deff varied from 0.88 for arm circumference to 1.25 for body mass index, and the deff was very satisfactory for HA, at 1.12. Height, mean systolic blood pressure and metabolic syndrome factors presented deff values ​​close to 1.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDesign effect value \u0026ndash; deff, according to variables related to the clinical examination. Sorocaba-SP/2021-23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edeff\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekilos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecentimeters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArm circumference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecentimeters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbdominal circumference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecentimeters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Systolic Blood Pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Diastolic Blood Pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Heart Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ebeats/minute\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt; or \u0026lt;\u0026thinsp;140/90 mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic Syndrome Factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, for the effect of the design (deff according to variables related to the drug treatment of AH), the deff varied from 0.88 for the use of angiotensin II converting enzyme inhibitors (ACEI) or calcium channel blockers (BCCA) to 1.42 for the use of sympatholytics, which was the highest deff in this sample. A previous diagnosis of AH and the time of last consultation presented a difference close to 1.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Design effect value \u0026ndash; deff, according to variables related to the drug treatment of arterial hypertension. Sorocaba-SP/2021-23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCathegory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edeff\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis of hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of angiotensin II AT1 receptor blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of angiotensin II converting enzyme inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of calcium channel blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of thiazide diuretics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta blocker use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoop diuretic use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of spironolactone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of sympatholytic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of direct-acting vasodilators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime since last consultation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emonths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecent search for health services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equalitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is considered successful research, representative of the urban population of Sorocaba, which requires much effort, but few resources are available given the strategy of developing it as a scientific initiation program with students supervised by medical teachers and with the use of software already available at the institution.\u003c/p\u003e \u003cp\u003eRegarding the urban population aged 18 or over, it can be inferred that the selection bias was practically null, not only by analyzing the data but also by comparing it with other surveys \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, 27\u0026ndash;30\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRegarding precision, the research proved to be very satisfactory, given that the design effects (deff) were less than 1.5 for all variables analyzed, and in particular for arterial hypertension, deff\u0026thinsp;=\u0026thinsp;1.12 in our study; for example, in the study by Alves \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003c/sup\u003e it was 1.37 for the group of adolescents and 1.52 for the group of elderly people. From the data, it can be inferred that one of the axes of precision was objective information, subject to verification, notably variables related to clinical examination, as opposed to subjective information such as variables related to lifestyle. The other axis of precision refers to the frequency of the event in the population and its intracluster and intercluster variance. If the clusters are more similar than expected for a random distribution of a given variable, the design effect may be less than 1. Furthermore, if the variable is widely distributed in the population, there is a small cluster effect, and the prevalence of the event studied differs significantly inside strata, so it is likely that the design effect is less than 1 \u003csup\u003e27\u003c/sup\u003e. It can occur in both very frequent and rare events, which explains the design effects of osteoporosis (0.58) and COPD (0.44), respectively.\u003c/p\u003e \u003cp\u003eIt is important to note that information on family income was highly lost, that information on drug use was probably influenced by modesty or fear, and that information on seeking health services was compromised by the respondents' memories.\u003c/p\u003e \u003cp\u003eThe comorbidities of the interviewees could have been diagnosed in some situations. For example, in patients with diabetes, asthma and COPD, capillary blood glucose tests and spirometry are used. Furthermore, considering that it is a resident population and that the bond established in the first contact was of high quality, it would be possible to schedule new visits to obtain more information, including various clinical protocols, such as adherence to treatment.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eA survey was performed with the urban population of Sorocaba between 2021 and 2023 with the main objective of measuring the prevalence of AH in adults. There was good precision in the results, with a design effect of -DF of 1.12 for this variable, receptivity and collaboration of interviewees, and an adequate cost‒benefit ratio in carrying out the research. The technique for selecting households in the respective clusters (census sectors), based on detailed mapping and demographic information from the IBGE, proved to be practical and efficient.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e: Every human participant has given their consent to participate.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eEthics approval\u003c/strong\u003e: This project was submitted and approved by the Research Ethics Committee (Comit\u0026ecirc; de \u0026Eacute;tica em Pesquisa) of the Faculdade de Ci\u0026ecirc;ncias M\u0026eacute;dicas e da Sa\u0026uacute;de of the Pontif\u0026iacute;cia Universidade Cat\u0026oacute;lica de S\u0026atilde;o Paulo, CAAE 30538520-1-0000-5373.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e: This research received funding from Pontif\u0026iacute;cia Universidade Cat\u0026oacute;lica de S\u0026atilde;o Paulo, numbered as 17807 and 15504.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting \u0026nbsp;interests\u003c/strong\u003e: There are NO competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSilva VSTM, Pinto LF. Nationwide population-based household surveys in health: a narrative review. Ci\u0026ecirc;nc. sa\u0026uacute;de coletiva. 2021;26(09):4045-4058. https://doi.org/10.1590/1413-81232021269.28792020.\u003c/li\u003e\n\u003cli\u003eViacava F. Health information: the relevance of health surveys. Ci\u0026ecirc;nc. sa\u0026uacute;de coletiva. 2002;7(4):607-21. https://doi.org/10.1590/S1413-81232002000400002\u003c/li\u003e\n\u003cli\u003eMalta DC, Leal MC, Costa MFL. Inqu\u0026eacute;ritos Nacionais de Sa\u0026uacute;de: experi\u0026ecirc;ncia acumulada e proposta para o inqu\u0026eacute;rito de sa\u0026uacute;de brasileiro. Rev bras epidemiol. 2008;11(supl1):159-67. https://doi.org/10.1590/S1415-790X2008000500017\u003c/li\u003e\n\u003cli\u003eBrand\u0026atilde;o JRM, Gianini RJ, Novaes HMD, Goldbaum M. The family health system: analysis of a health survey in S\u0026atilde;o Paulo, Brazil. 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Epidemiol Serv Sa\u0026uacute;de 2015; 24(2): 297-304. http://dx.doi.org/10.5123/S1679-49742015000200012.\u003c/li\u003e\n\u003cli\u003eAlves MCGP, Escuder MML, Goldbaum M, Barros MBA, Fisberg RM, Cesar CLG. Sampling plan in health surveys, city of S\u0026atilde;o Paulo, Brazil, 2015.. Rev. Sa\u0026uacute;de P\u0026uacute;blica. 2018;52. https://doi.org/10.11606/S1518-8787.2018052000471\u003c/li\u003e\n\u003cli\u003eBarata RB, Moraes JC, Antonio PRA, Dominguez M. Immunization coverage\u003c/li\u003e\n\u003cli\u003esurvey: empirical assessment of the cluster sampling method proposed by the World Health Organization. Rev Panam Salud Publica 2005;17(3):184-90. https://doi.org/10.1590/S1020-49892005000300006\u003cbr\u003e 22. Instituto Brasilerio de Geografia e Estatistica. Censo 2022. IBGE. https://www.ibge.gov.br/estatisticas/sociais/trabalho/22827-censo-demografico-2022.html\u003c/li\u003e\n\u003cli\u003eBarroso WKS, Rodrigues CIS, Bortolotto LA, Mota-Gomes MA, Brand\u0026atilde;o AA, Feitosa ADM, et al. Diretrizes Brasileiras de Hipertens\u0026atilde;o Arterial \u0026ndash; 2020. Arq Bras Cardiol. 2021;116(3): 516-658. : https://doi.org/10.36660/abc.20201238\u003c/li\u003e\n\u003cli\u003eRodrigues CIS (coord) \u0026ndash; Diretrizes brasileiras de hipertens\u0026atilde;o VI. Diagn\u0026oacute;sticoeclassifica\u0026ccedil;\u0026atilde;o.Braz.J.Nephrol2010;32(suppl1). https://doi.org/10.1590/S0101-28002010000500004 \u003c/li\u003e\n\u003cli\u003e\u003cem\u003eMalachias MVB\u003c/em\u003e, \u003cem\u003eSouza WKSB\u003c/em\u003e, \u003cem\u003ePlavnik FL\u003c/em\u003e, \u003cem\u003eRodrigues\u003c/em\u003e CIS, Brand\u0026atilde;o AA, Neves MFT, et al. 7\u0026ordf; Diretriz Brasileira de. Hipertens\u0026atilde;o Arterial. Arq Bras Cardiol. 2016;107(3 Suppl 3):1-103.\u003c/li\u003e\n\u003cli\u003eSTATA 16.0 (R). Copyright 1985-2019 StataCorp LLC. Statistics/Data Analysis. Texas USA\u003c/li\u003e\n\u003cli\u003eThomson DR . Rhoda DA,. Tatem AJ,Castro MC. Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda International Journal of Health Geographics 2020; (19):34 https://doi.org/10.1186/s12942-020-00230-4\u003c/li\u003e\n\u003cli\u003eUSAID. Sampling and household listing manual. Demographic and health survey methodology. ICF International, Calverton, USA 2012\u003c/li\u003e\n\u003cli\u003eGrais RF et al. Don\u0026rsquo;t spin the pen: two alternatives methods for second-stage sampling in urban cluster surveys. Emerging themes in epidemiology 4:8, 2007. Doi 10.1186/1742-7622-4-8\u003c/li\u003e\n\u003cli\u003eSilva NN e Roncalli AG. Sampling plan, weighting process and design effects of the Brazilian Oral Health Survey. 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DOI:10.1590/S0034-8910.2013047004362\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hypertension, Prevalence, Cluster sampling, Health surveys, Data accuracy, Epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-4277753/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4277753/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePopulation surveys are important for planning public policies and constitute an efficient way of obtaining representative data. In the health field, studies have been conducted with different objectives, such as identifying arterial hypertension (AH), which is a chronic noncommunicable disease (NCD), and determining its prevalence and associated risk factors.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo evaluate the performance of a population health survey carried out in the municipality of Sorocaba between August 2021 and June 2023 to estimate the prevalence of AH.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe performance indicator analyzed refers to the precision (design effect - deff) of the AH prevalence in adults (\u0026ge;\u0026thinsp;18 years) and the exposure to its main risk factors. The total sample included 1,080 individuals from the urban region, which is considered sufficient to estimate a deff of 1.5. This is a study whose clusters are represented by census sectors, with data collected during household visits through interviews using a standardized questionnaire and blood pressure and biometric parameter measurements. The deff calculation formula used was weighted variance/raw variance. The study was approved by the Research Ethics Committee, CAAE 30538520-1-0000-5373.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe data obtained varied between a deff equal to 0.44 for the prevalence of chronic obstructive pulmonary disease and a deff equal to 1.49 for the use of sympatholytic medication, with a deff for the prevalence of AH equal to 1.12.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThere was good precision of the results. There was excellent receptivity and collaboration among the interviewees. The cost‒benefit in developing this research was very adequate. The technique for selecting households in the respective clusters (census sectors), based on detailed mapping and demographic information from Instituto Brasileiro de Geografia e Estat\u0026iacute;stica - IBGE, proved to be practical and efficient and can be reproduced in other municipalities and for other NCDs.\u003c/p\u003e","manuscriptTitle":"Assessment of the precision of a health survey on hypertension prevalence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-24 19:51:22","doi":"10.21203/rs.3.rs-4277753/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-23T11:32:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-22T05:05:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-22T05:05:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-04-16T18:21:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"71e43818-18c2-4625-9b9a-1febca4f0fea","owner":[],"postedDate":"April 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-22T19:36:36+00:00","versionOfRecord":{"articleIdentity":"rs-4277753","link":"https://doi.org/10.1186/s12889-024-19626-z","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2024-08-12 15:58:01","publishedOnDateReadable":"August 12th, 2024"},"versionCreatedAt":"2024-04-24 19:51:22","video":"","vorDoi":"10.1186/s12889-024-19626-z","vorDoiUrl":"https://doi.org/10.1186/s12889-024-19626-z","workflowStages":[]},"version":"v1","identity":"rs-4277753","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4277753","identity":"rs-4277753","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}