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Revista de Saúde Pública

Print version ISSN 0034-8910On-line version ISSN 1518-8787

Rev. Saúde Pública vol.52  São Paulo  2018  Epub Sep 03, 2018

http://dx.doi.org/10.11606/s1518-8787.2018052000471 

Original Article

Sampling plan in health surveys, city of São Paulo, Brazil, 2015

Maria Cecilia Goi Porto AlvesI 

Maria Mercedes Loureiro EscuderI 

Moises GoldbaumII 

Marilisa Berti de Azevedo BarrosIII 

Regina Mara FisbergIV 

Chester Luiz Galvão CesarIV 

IInstituto de Saúde. Secretaria de Estado da Saúde de São Paulo. São Paulo, SP, Brasil

IIUniversidade de São Paulo. Faculdade de Medicina. Departamento de Medicina Preventiva. São Paulo, SP, Brasil

IIIUniversidade Estadual de Campinas. Faculdade de Ciências Médicas. Departamento de Medicina Preventiva e Social. Campinas, SP, Brasil

IVUniversidade de São Paulo. Faculdade de Saúde Pública. Departamento de Epidemiologia. São Paulo, SP, Brasil


ABSTRACT

OBJECTIVE

To evaluate the sampling plan of the Health Survey of the City of São Paulo (ISA-Capital 2015) regarding the accuracy of estimates and the conformation of domains of study by the Health Coordinations of the city of São Paulo, Brazil.

METHODS

We have described the population, domains of study, and sampling procedures, including stratification, calculation of sample size, and random selection of sample units, of the Health Survey of the City of São Paulo, 2015. The estimates of proportions were analyzed in relation to precision using the coefficient of variation and the design effect. We considered suitable the coefficients below 30% at the regional level and 20% at the city level and the estimates of the design effect below 1.5. We considered suitable the strategy of establishing the Health Coordinations as domains after verifying that, within the coordinations, the estimates of proportions for the age and sex groups had the minimum acceptable precision. The estimated parameters were related to the subjects of use of services, morbidity, and self-assessment of health.

RESULTS

A total of 150 census tracts were randomly selected, 30 in each Health Coordination, 5,469 households were randomly selected and visited, and 4,043 interviews were conducted. Of the 115 estimates made for the domains of study, 97.4% presented coefficients of variation below 30%, and 82.6% were below 20%. Of the 24 estimates made for the total of the city, 23 presented coefficient of variation below 20%. More than two-thirds of the estimates of the design effect were below 1.5, which was estimated in the sample size calculation, and the design effect was below 2.0 for 88%.

CONCLUSIONS

The ISA-Capital 2015 sample generated estimates at the predicted levels of precision at both the city and regional levels. The decision to establish the regional health coordinations of the city of São Paulo as domains of study was adequate.

DESCRIPTORS Health Surveys, methods; Stratified Sampling; Cluster Sampling; Sample Size; Data Collection; Statistical Analysis

RESUMO

OBJETIVO

Avaliar o plano de amostragem do Inquérito de Saúde do Município de São Paulo (ISA-Capital 2015) em relação à precisão das estimativas e à conformação de domínios de estudo pelas coordenadorias de saúde do município de São Paulo.

MÉTODOS

Descrição de população e domínios de estudo, procedimentos de amostragem, incluindo estratificação, cálculo do tamanho da amostra e sorteio de unidades amostrais do Inquérito de Saúde do Município de São Paulo, 2015. As estimativas de proporções foram analisadas em relação à precisão, por meio do coeficiente de variação e do efeito do delineamento. Foram considerados adequados coeficientes menores do que 30% no nível regional e 20% no municipal, e efeitos do delineamento menores do que 1,5. Para considerar adequada a estratégia de estabelecimento das Coordenadorias de Saúde como domínios, foi verificado que, dentro das coordenadorias, as estimativas de proporções para grupos de idade e sexo tinham a precisão mínima aceitável. Os parâmetros estimados referiram-se aos temas: uso de serviços, morbidade e autoavaliação em saúde.

RESULTADOS

Foram sorteados 150 setores censitários, 30 em cada Coordenadoria de Saúde, sorteados e visitados 5.469 domicílios ocupados, e realizadas 4.043 entrevistas. Das 115 estimativas feitas para os domínios de estudo, 97,4% apresentaram coeficientes de variação menores do que 30% e 82,6% menores do que 20%. Das 24 estimativas feitas para o total do município, 23 apresentaram coeficiente de variação menor do que 20%. Mais de dois terços das estimativas do efeito do delineamento foram inferiores a 1,5, valor previsto no cálculo do tamanho da amostra, e o efeito do delineamento foi menor do que dois para 88%.

CONCLUSÕES

A amostra do ISA-Capital 2015 gerou estimativas situadas nos patamares previstos de precisão, tanto as de nível municipal como regional. Foi acertada a decisão de estabelecer as coordenadorias regionais de saúde do município de São Paulo como domínios de estudo.

DESCRITORES Inquéritos Epidemiológicos, métodos; Amostragem Estratificada; Amostragem por Conglomerados; Tamanho da Amostra; Coleta de Dados; Análise Estatística

INTRODUCTION

It is important to know the sampling plans used in epidemiological surveys and the evaluation of the alternatives applied to improve the practice of household surveys. There are few publications on this subject in the Brazilian literature to support new experiences1-6. It is particularly interesting the provision of subsidies to improve sampling designs in time trend studies, which are based on data from successive surveys. More such studies have been carried out in recent years7-10.

In cities in the State of São Paulo, Brazil, health surveys called ISA have been carried out since 2001. The objective is to evaluate the health status of the population living in the city, according to their living conditions, addressing aspects related to lifestyle, acute and chronic morbidities, preventive practices, and use of health services11. They are conducted by a team of researchers from public universities of São Paulo and the State Department of Health of São Paulo. Editions were carried out in 2003a, 2008b, and 2015c, in the city of São Paulo with most support from the City Health Department, and in 2001, 2008d, and 2014/2015 in the city of Campinase.

In these surveys, probabilistic sampling is used, always seeking inferences to the study population based on measures of precision. Although they are similar, the sampling plans used in the different years of the ISA-Capital have different aspects. Their adoption was motivated by the desire to improve the process of data collection based on acquired experiences, preserving the possibility of comparison between the different editions.

The planning of the 2015 survey was based on the interest to produce information on smaller areas of the city, which are more homogeneous in relation to the epidemiological profile. Consistent with this objective, the City Health Department, the main funder of the project, intended to reinforce the use of results by regional managers. This confluence of interests culminated in the definition of regional Health Coordinations of the city of São Paulof as domains of study in the ISA-Capital 2015.

The objective of this study was to evaluate the sampling plan of the ISA-Capital 2015 regarding the precision of estimates and the conformation of the domains of study by the Health Coordinations of the city of São Paulo, Brazil.

METHODS

Below, we describe the sampling plan of ISA-Capital 2015, highlighting the following aspectcs: population and domains of study and sampling procedures, including calculation of sample size, and random selection of sample units. In addition, we present the results of the application of the sampling plan, considering the households visited and the interviews obtained.

The estimates obtained with the ISA-Capital 2015 sample for the parameters of interest were analyzed for precision using the coefficient of variation. Estimates with coefficients below 20% for the city level and below 30% for the regional were considered sufficiently precise. Thus, we would consider as suitable the establishment of the Health Coordinations as the domains of study if the estimates of proportions according to the age and sex domains had minimum acceptable precision within the coordinations, indicated by coefficients of variation below 30%.

We also evaluated the measures of effect of design, widely used as measures of efficiency of complex sampling designs12,13. Those below 1.5 were considered suitable, which was adopted in the planning of the sample. We also verified the frequency of estimates below 2.0, which is frequently adopted in sampling plans3,4,6,14.

The parameters estimated in this study were the prevalence of persons who reported the following: use of health service in the last 30 days, hospitalization in the last year, visit to the dentist in the last year, hypertension, allergy, health problem in the last 15 days, and excellent or good self-assessment of health. These parameters were related to the following subjects: use of services, morbidity, and self-assessment of health, usually studied in health surveys. The reference to allergy was selected because it was the only morbidity in which the estimates for adolescents were greater than 10% for the most part.

The reference population of the ISA-Capital 2015 consisted of individuals aged 12 years or more living in permanent private households in the urban area of the city of São Paulo (Table 1, block 1)g. For the delimitation of the population, the survey used the census tracts classified in the 2010 Census as urban situation – urbanized area, non-urbanized area, and isolated urbanized area – and ‘common’ and ‘special subnormal’ types.

Table 1 Reference population, planned sample of persons and households, and person/household ratio according to age and sex groups and Health Coordination. São Paulo, State of São Paulo, Brazil, ISA-Capital 2015. 

Coordination Age (years)/Sex Total
12 to 19 20 to 59 60 or more
Men Women
Block 1 – Population in 2010 (aggregate of urban census tracts)
North 268,489 613,562 684,973 266,052 1,833,076
Central-West 155,753 464,696 518,726 238,299 1,377,474
Southeast 277,068 755,332 848,308 403,229 2,283,937
South 335,585 706,625 784,700 217,103 2,044,013
East 304,317 617,650 682,615 206,808 1,811,390
Total 1,341,212 3,157,865 3,519,322 1,331,491 9,349,890
Block 2 – Sample that would be obtained with proportional sharing by age/sex domain
North 124 285 318 123 850
Central-West 96 287 320 147 850
Southeast 103 281 316 150 850
South 140 294 326 90 850
East 143 290 320 97 850
Total 606 1,436 1,600 608 4,250
Block 3 – Planned sample
North 153 234 261 203 850
Central-West 150 223 249 228 850
Southeast 150 219 246 234 850
South 176 247 275 152 850
East 179 242 267 162 850
Total 808 1,165 1,298 980 4,250
Block 4 – Person/household ratio
North 0.3994 0.9128 1.0191 0.3958 -
Central-West 0.2724 0.8126 0.9071 0.4167 -
Southeast 0.3151 0.8591 0.9649 0.4586 -
South 0.4410 0.9286 1.0312 0.2853 -
East 0.4598 0.9332 1.0313 0.3125 -
Total - - - - -
Block 5 – Households required for the planned interviews
North 383 256 256 513 513
Central-West 551 274 275 547 551
Southeast 476 255 255 510 510
South 399 266 267 533 533
East 389 259 259 518 518
Total 2,198 1,311 1,311 2,621 2,625
Block 6 – Households to be randomly selected according to non-response
North 709 475 474 950 950
Central-West 1,020 508 508 1,013 1,020
Southeast 881 472 472 945 944
South 739 493 494 987 987
East 721 480 479 960 959
Total 4,071 2,428 2,428 4,855 4,861
Block 7 – Households required by census tracts
North 23.6 15.8 15.8 31.7 31.7
Central-West 34.0 16.9 16.9 33.8 34.0
Southeast 29.4 15.7 15.7 31.5 31.5
South 24.6 16.4 16.5 32.9 32.9
East 24.0 16.0 16.0 32.0 32.0
Total 27.1 16.2 16.2 32.4 32.4
Block 8 – Inverse of the planned sampling fractions
North 947.61 1415.91 1417.19 707.72
Central-West 560.71 1125.27 1124.95 564.39
Southeast 997.44 1862.46 1862.14 930.53
South 1029.64 1544.85 1540.87 771.29
East 918.05 1378.23 1380.57 689.36

ISA: Health Survey of the City of São Paulo

Stratified sampling was used and clusters were selected in two stages: census tracts and households.

The strata were formed by the five Health Coordinations of the city of São Paulo: North, Central-West, Southeast, South, and East, which were domains of study. For the sample planning, we also considered the age and sex groups as domains: adolescents (12 to 19 years), male adults (men aged 20 to 59 years), female adults (women aged 20 to 59 years), and older adults (60 years or more). We defined 20 domains of study, both geographic and demographic.

For operational reasons, the total sample size would be 4,250 persons. In order for the Health Coordinations to have the same potential for data analysis, 850 persons were assigned to each one. The sample would have the distribution presented in Table 1 (block 2) if the distribution by the age and sex domains were proportional to the population of these domains in each Coordination. However, the participation of the “adolescent” and “older adult” groups was changed in the sample for more precise estimates in these domains. A 50% larger adolescent population was considered, as well as a 100% larger older population, and a new distribution of the sample was carried out. The numbers of interviews was increased to 150 for two domains: adolescents of the Central-West and Southeast Coordinations (Table 1, block 3).

This number could allow the estimation of proportions of 0.50, with a sampling error of 0.10, considering a 95% confidence level and a design effect of 1.5. The calculation was carried out from the algebraic expression that determines the minimum sample size to estimate proportions under complex samples13,15: n=P×(1P)(d/z)2×deff , where n is the sample size, P is the parameter to be estimated, z = 1.96 is the value in the reduced normal curve related to the 95% confidence level of the confidence intervals, d is the sampling error, and deff is the effect of the design.

The expected mean number of persons per household (ratio between persons and households) was calculated in each domain from the 2010 Census data (Table 1, block 4) to determine the number of households that interviews should be conducted. The number of households was obtained by dividing the sample size of each domain by the respective ratio between persons and households (Table 1, block 5).

However, in order to reached the minimum number of interviews in the presence of non-response (vacant or closed households, refusals, or households with a resident unable to respond), the inclusion of a larger number of households in the sample was planned (Table 1, block 6). A non-response rate of 40% and a percentage of vacant households of 10% were considered.

The interviewees were randomly selected using two-stage sampling. In the first stage, 30 census tracts were randomly selected in each Coordination, with probability proportional to size, measured by the number of permanent private households counted in the 2010 Census, sorted by the average per capita income of the households in the tract.

In the second stage, the households were selected using two different random selections. In tracts classified by the IBGEg as “common”, the households were systematically selected, based on the list of households carried out in the field. In the census tracts classified as “special subnormal” (which corresponds to favela slums in the city of São Paulo), segments of households were created (mean size of six households). These segments were the second stage of selection, in which the random selection of six segments per tract was planned.

The households were randomly selected corresponding to the rarest domain (adolescents in the Central-West region and older adults in the other four Coordinations) in each tract, and this sample was called the main sample. From the main sample, sub-samples were randomly selected with sizes defined for the other age and sex domains (Table 1, block 7). This type of random selection is equivalent to obtaining four concomitant samples, related to the four domains of study.

There was no intra-household random selection. All persons belonging to the domain for which the household was selected were included in the sample. In the data collection equipment of the interviewers, it was indicated the domains to be searched in each household of the sample.

The overall sampling fractions in each Coordination were:

    –. in the rarest domain: f=30×MiM×bMi

    –. in the other domains: f=30×MiM×bMi×bdomíniob

where Mi is the number of households in tract i (data from the 2010 Census), M is the total number of households in the Coordination (data from the 2010 Census), b is the number of households in the rarest domain, i.e., the main sample, and bdomain is the number of households required for each of the three less rare domains.

The second-stage sampling fraction was fixed, which increased (or decreased) the number of households randomly selected in relation to what was planned if the census tract had grown (or decreased) since the 2010 Census. With this option, the second-stage sampling fraction can be rewritten as: b(Mi'/Ml)Mi' , where Mi' is the number of households in tract i obtained in the listing of households, performed in the field.

In order to compensate for the differences between the probabilities of the random selection of the individuals in the sample, design weights were introduced in the data analysis step, expressed as the inverse of the sampling fractions, F=1/f (Table 1, block 8)16. This weight can be interpreted as the number of persons in the population “represented” for each person randomly selected.

RESULTS

The fieldwork of ISA-Capital began in the second half of 2014, but 80.0% of the interviews were conducted in 2015, between January and December. A total of 5,942 households were effectively selected and visited. Of these, 8.0% were vacant households, which amounted to 5,469 occupied houses (Table 2). Information could be obtained in 76.4% of the occupied households about the residents and the presence of persons belonging to the age and sex groups of interest. In these households, 73.4% of the eligible residents were interviewed.

Table 2 Occupied households visited, interviews conducted, and mean interviews by census tract, according to age and sex groups and Health Coordination. São Paulo, State of São Paulo, Brazil, ISA-Capital 2015. 

Coordination Age (years)/sex Total
12 to 19 20 to 59 60 or more
Men Women
Occupied households (among those randomly selected and visited)
North 660 449 437 791 1,004
Central-West 989 500 502 924 1,186
Southeast 949 506 495 889 1,192
South 760 498 513 900 1,124
East 647 426 402 732 963
Total 4,005 2,379 2,349 4,236 5,469
Interviews conducted
North 161 200 229 187 777
Central-West 113 135 160 201 609
Southeast 150 182 231 260 823
South 244 231 301 199 975
East 191 205 291 172 859
Total 859 953 1,212 1,019 4,043
Interviews conducted by tract
North 5.4 6.7 7.6 6.2 25.9
Central-West 3.8 4.5 5.3 6.7 20.3
Southeast 5.0 6.1 7.7 2.0 27.4
South 8.1 7.7 10.0 6.6 32.5
East 6.4 6.8 9.7 5.7 28.6
Total 5.7 6.4 8.1 6.8 27.0

ISA: Health Survey of the City of São Paulo

The number of households randomly selected was higher than that considered necessary for the interviews (n = 4,831), provided for in the sampling plan. Nevertheless, the number of interviews was smaller than planned. The minimum of 150 interviews was not reached in two domains (adolescents and adult males in the Central-West Coordination). The Coordinations that had a smaller number of interviews were North (9.0% smaller) and Central-West (28.0% smaller). The target number of interviews for the total of the city was reached for adolescents and older adults and it was further from what was proposed for the group of adult males (18.0% smaller).

Of the 115 estimates made for the domains of study, 97.4% presented coefficients of variation below 30.0%, and 82.6% were below 20.0% (Tables 3 and 4). Of the few estimates that did not reach the desired level of precision (three estimates), one was obtained with a small sample of interviews, below 150, and one estimate was below 0.10, which means an event of very small frequency. All prevalence estimates above 0.30 showed low coefficients of variation; the inverse happened for the estimates below 0.10; none reached the desired levels of accuracy. Of the 24 estimates made for the city, almost all (23 estimates) showed a coefficient of variation below 20%.

Table 3 Number of interviews, prevalence estimates, confidence intervals, coefficients of variation, and effects of design, among men and women aged 20 to 59 years. São Paulo, State of São Paulo, Brazil, ISA-Capital 2015. 

Indicators Domain Men Women
Region n p 95%CI cv deff n p 95%CI cv deff
Use of a health service in the last 30 days North 198 20.6 14.2–26.9 15.6 1.246 228 36.3 30.0–42.7 8.9 1.016
Central-West 135 24.4 17.0–31.8 15.4 1.026 158 35.7 27.0–44.4 12.3 1.319
Southeast 181 29.9 20.5–39.2 15.8 1.920 231 36.4 29.8–43.0 9.2 1.106
South 229 18.6 13.6–23.7 13.8 0.990 301 35.6 27.1–44.0 12.0 2.391
East 205 29.3 21.4–37.3 13.7 1.595 291 39.9 33.3–46.4 8.3 1.320
Total 948 24.6 21.2–28.0 7.0 2.171 1,209 36.8 33.5–40.1 4.5 1.770
Visit to the dentist in the previous year North 198 59.6 50.0–69.2 8.2 1.927 228 71.4 66.1–76.6 3.7 0.775
Central-West 134 70.4 62.3–78.5 5.8 1.062 159 77.0 68.4–85.7 5.7 1.705
Southeast 182 65.6 57.5–73.8 6.3 1.366 230 70.6 61.9–79.2 6.2 2.114
South 229 52.2 45.4–59.1 6.6 1.096 300 60.2 53.6–66.8 5.5 1.390
East 203 58.5 51.3–65.7 6.2 1.094 290 59.8 52.8–66.7 5.9 1.480
Total 946 60.5 56.8–64.2 3.1 1.373 1,207 66.9 63.6–70.3 2.5 1.551
Excellent or good self-assessment of health North 199 80.6 74.1–87.1 4.1 1.385 229 64.9 55.8–74.0 7.1 2.118
Central-West 134 84.7 78.4–91.0 3.8 1.050 160 77.5 71.6–83.4 3.9 0.824
Southeast 182 81.6 73.7–89.6 4.9 1.965 231 73.5 66.2–80.8 5.0 1.599
South 229 77.1 71.8–82.3 3.4 0.913 300 65.8 59.2–72.5 5.1 1.505
East 205 77.4 72.3–82.6 3.3 0.779 291 66.6 61.2–71.9 4.1 0.959
Total 949 79.9 77.0–82.8 1.8 1.815 1,211 69.1 65.9–72.4 2.4 1.884
Health problem in the last 15 days North 199 16.4 12.3–20.5 12.7 0.628 229 24.7 19.1–30.2 11.4 0.976
Midwest 135 15.9 11.2–20.6 15.0 0.567 160 20.1 14.4–25.8 14.4 0.827
Southeast 182 13.4 8.5–18.2 18.2 0.929 231 26.6 19.8–33.4 12.9 1.395
South 231 9.5 5.2–13.9 22.9 1.271 301 13.9 8.4–19.4 20.1 1.964
East 205 21.8 16.5–27.0 12.2 0.848 291 21.0 15.8–26.2 12.5 1.195
Total 952 15.2 13.0–17.3 7.3 1.281 1,212 21.2 18.6–23.9 6.3 1.615
Hypertension North 200 13.6 7.0–20.1 24.5 1.882 228 23.3 17.1–29.5 13.4 1.239
Central-West 134 10.6 4.1–17.1 31.0 1.525 159 11.1 3.8–18.5 33.5 2.233
Southeast 182 13.8 9.3–18.2 16.4 0.780 231 15.5 10.3–20.6 16.9 1.205
South 231 14.0 9.9–18.2 15.1 0.861 301 20.5 15.5–25.4 12.2 1.154
East 204 15.7 10.9–20.6 15.7 0.928 291 18.0 13.1–22.9 13.8 1.206
Total 951 13.8 11.4–16.1 8.6 1.133 1,210 18.1 15.6–20.6 7.0 1.301
Allergy North 199 16.8 9.5–24.2 22.1 1.969 228 19.9 13.7–26.1 15.8 1.402
Central-West 134 15.2 8.2–22.0 23.1 1.275 160 18.5 11.2–25.8 20.0 1.448
Southeast 181 13.3 8.4–18.4 18.6 0.961 229 17.7 13.1–22.3 13.1 0.842
South 230 5.3 1.3–8.8 32.3 1.353 300 10.1 5.2–15.0 24.5 2.011
East 205 14.0 9.9–18.2 14.8 0.732 291 15.6 12.0–19.2 11.8 0.741
Total 949 12.6 10.1–15.0 9.7 1.281 1,208 16.0 13.7–18.4 7.4 1.246

ISA: Health Survey of the City of São Paulo; cv: coefficient of variation; deff: effect of the design

Table 4 Number of interviews, prevalence estimates, confidence intervals, coefficients of variation, and effects of design in adolescents aged 12 to 19 years and older adults aged 60 years or more. São Paulo, State of São Paulo, Brazil, ISA-Capital 2015. 

Indicators Domain Adolescents Older adults
Region n p 95%CI cv deff n p 95%CI cv deff
Use of a health service in the last 30 days North 158 24.2 18.2–30.2 12.5 0.782 187 42.5 37.2–47.7 6.3 0.541
Central-West 112 21.4 11.3–31.5 23.8 1.710 199 39.5 32.6–46.4 8.8 0.999
Southeast 149 24.5 17.6–31.5 14.4 0.992 260 41.4 32.5–50.3 10.9 2.179
South 242 19.6 15.1–24.1 11.7 0.804 199 43.7 36.0–51.3 8.8 1.200
East 189 22.1 16.1–28.1 13.7 1.005 170 37.1 29.5–44.7 10.4 1.078
Total 850 22.3 19.5–25.1 6.4 0.628 1,015 41.0 37.4–44.5 4.4 0.855
Visit to the dentist in the previous year North 158 65.5 56.5–74.4 6.9 1.421 178 42.3 33.3–51.4 10.8 1.512
Central-West 113 79.3 68.9–89.6 6.6 1.863 197 61.1 50.5–71.7 8.8 2.387
Southeast 150 59.7 50.5–68.9 7.8 1.341 258 47.7 36.3–59.0 12.0 3.380
South 243 60.5 52.7–68.3 6.5 1.580 196 41.8 32.1–51.5 11.7 1.921
East 188 57.6 51.1–64.2 5.7 0.832 166 37.7 29.3–46.1 11.3 1.264
Total 852 62.3 58.5–66.2 3.1 1.345 995 46.4 41.5–51.2 5.3 1.535
Self-assessment of excellent or good health North 161 87.5 83.5–91.5 2.3 0.608 186 60.2 49.7–70.8 8.9 2.225
Central-West 113 82.4 75.0–89.8 4.5 1.092 201 74.2 67.0–81.3 4.9 1.367
Southeast 150 80.3 73.6–86.9 4.2 1.082 260 67.2 60.9–73.4 4.7 1.176
South 243 84.8 80.2–89.3 2.7 0.999 199 56.8 49.0–64.6 7.0 1.259
East 191 81.3 74.0–88.6 4.6 1.712 172 52.0 43.5–60.5 8.2 1.256
Total 858 83.3 80.6–86.1 1.7 0.777 1,018 62.7 59.0–66.5 3.0 0.997
Health problem in the last 15 days North 161 16.6 10.7–22.4 17.8 1.010 187 24.9 16.9–32.9 16.2 1.622
Central-West 113 13.2 6.3–20.2 26.4 1.194 201 13.9 8.0–19.8 21.6 1.504
Southeast 150 19.7 11.4–28.0 21.3 1.656 258 20.4 15.3–25.5 12.7 1.057
South 243 10.4 4.9–15.9 26.6 2.000 199 26.6 13.7–39.5 24.5 4.303
East 191 19.5 13.7–25.4 15.1 1.049 172 30.2 22.8–37.7 12.5 1.159
Total 858 16.03 13.0–19.0 9.42 0.922 1,017 22.9 19.3–26.5 8.0 1.216
Hypertension North 161 187 49.2 41.2–57.2 8.3 1.232
Central-West 113 201 56.7 44.4–69.0 11.0 3.168
Southeast 149 259 62.3 55.8–68.7 5.2 1.159
South 242 199 46.8 38.2–55.4 9.3 1.509
East 191 171 55.2 50.1–60.4 4.7 0.465
Total 856 1.14 0.3–2.0 37.33 1.371 1,017 54.8 51.0–58.7 3.5 1.525
Allergy North 161 25.6 19.3–31.9 12.5 0.869 187 14.0 8.9–19.1 18.4 1.028
Central-West 113 24.4 12.1–36.6 25.5 2.373 201 23.5 14.6–32.4 19.2 2.258
Southeast 149 18.5 9.7–27.3 24.0 1.958 260 17.3 12.5–22.1 14.0 1.065
South 244 8.9 4.2–13.6 26.7 1.704 198 8.9 4.2–13.7 27.0 1.407
East 191 25.9 20.0–31.9 11.6 0.901 171 20.4 13.8–27.0 16.3 1.154
Total 858 19.8 16.6–23.0 8.3 1.439 1,017 16.8 14.0–19.6 8.4 1.455

ISA: Health Survey of the City of São Paulo; cv: coefficient of variation; deff: effect of the design

More than two-thirds (69.0%) of the estimates of the design effect were below 1.5, which was estimated in the sample size calculation, and the design effect was below 2.0 for 88.0%.

The mean number of interviews per tract for the age and sex groups for the set of Coordinations ranged from 5.7 to 8.1.

DISCUSSION

The ISA-Capital 2015 sample generated estimates at the predicted levels of precision at both the city and regional levels, which indicates that the decision to establish the regional health coordinations of the city of São Paulo as domains of study was adequate.

There is no single criterion adopted universally to establish a limit for the values of coefficient of variation. Several factors must be considered. The knowledge on whether a particular coefficient of variation is too high or too low requires experience on similar data17. The Fundação Sistema Estadual de Análise de Dados (SEAD), responsible for several surveys in the State of São Paulo, guides its decision according to the frequency of the survey and the nature of the phenomenon under study. It does not adopt a single policy for the dissemination of the results of the research it carries outh. Thus, different limits for the coefficient of variation were stipulated in the various surveys conductedi. When disclosing the results of the Household Expenditure Survey of 2015/2016, the National Statistical Institute of Portugal proposed that estimates with coefficients of variation between 20% and 30% should be carefully used and those with coefficients above 30% should be disregardedj. These limits, as well as those proposed in other health studies3,6, coincide with those adopted in our study.

The number of households effectively selected was higher than planned. The use of constant fractions in the random selection in the second sampling step may be responsible for this result. With this strategy, the 38% increase in the number of households between the Census and the survey data collection was reflected in the number of households sampled. The equiprobability of the sample was kept by the random selection with probability proportional to size, sacrificing control over its final size.

In addition, sampling fractions were changed in the tracts not yet visited when the follow-up of the field work detected that the non-response rates were greater than expected. This further increased the number of households randomly selected. These increases were offset by the use of weights in the data analysis.

The follow-up of the field work by the team responsible for the survey was carried out through spreadsheets, whose models were improved throughout the various editions of the ISA project. The detailing of the response rates at the household and resident levels by census tract together with the interviews allowed problems to be detected as soon as they occurred. This helped the introduction of adjustments in the sampling plan.

The number of interviews was lower than planned, which shows that population participation in the survey was lower than expected. All households were visited at least three times, at different times and days, which did not prevent high non-response rates.

Although the sample size of the ISA-Capital 2015 is similar to previous editions, the field work was extended for a longer period, mainly due to the greater number of census tracts selected (150 in 2015, 80 in 2008, and 60 in 2003). This was a necessity created by the option of adopting the Health Coordinations as domains of study, setting the number of tracts to 30 in each one. It can be understood as the cost of obtaining regional estimates in this edition of the ISA.

The increase in the number of census tracts meant a smaller number of interviews by tract: 5.7 to 8.1, on average, by age and sex domain. These numbers are far from the optimal number of interviews in each primary sampling unit. This number seeks the balance between precision and cost, considering the ratio between the costs of including a new conglomerate and a new household in the sample, in addition to the degree of intra-cluster homogeneity18,k. For a 20-fold cost of including a new conglomerate compared to including a new interview19, and considering a degree of homogeneity of 0.05l, the indicated number of interviews for each tract would be 20. However, the decrease in the concentration of interviews by tract, although increasing the cost, had the advantage of increasing precision. This contributed to the small effect of design. The random selection of cluster as opposed to simple selection often increases the variance of the estimates according to the intraclass correlation, which is a characteristic of the population that cannot be changed by the sampling process. However, the inclusion of fewer elements per cluster in the sample can reduce the impact of intraclass correlation on variance, leading to smaller estimates for the design effect.

The random selection adopted in the ISA-Capital, in which the four samples related to the four age and sex domains are obtained simultaneously, relativizes the importance of the increase in cost. The number of interviews per tract, considering the four domains, was between 20.3 and 32.5, depending on the Coordination.

One of the consequences of using weights in the data analysis step is the increase of the estimates of the design effect, and the increase is proportional to the variation between applied weights20. In the first ISA editions, sample size was the same for all age and sex domains. This resulted in very different weights, which impacted the design effect when more than one domain was analyzed together. The 2015 survey sought the closer proportional distribution of the sample by the age and sex domains in each Coordination, avoiding the previously observed discrepancy between weights.

One of the characteristics common to all issues of the ISA-Capital is the non-use of intra-household selection. In terms of efficiency, the strategy of interviewing all residents belonging to the age and sex group of interest is superior to that in which only one of the residents of the household is randomly selected for the interview21. To apply it, the option of the ISA is to select randomly a main sample and, from it, obtain subsamples of households, according to the need of each domain defined based on the mean number of persons per household indicated in the Census. With the adequate number of households for each domain, there is no need for an intra-household selection.

Based on data from previous editions of the ISA, Alves et al.22 have shown that it is particularly advantageous to use segments as an alternative to full address listing when applied to the random selection of households in favela slums. In the ISA-Capital 2015, in addition to being used in favela slums, this strategy was also applied in the last tracts to fasten the field work. Among the advantages associated with the use of segments, we can highlight the speed in locating and identifying households.

The estimates of prevalence within Health Coordinations, for the most part, were considered suitable for all age and sex groups defined as a domain in the ISA-Capital 2015. This result allows the use of data from the survey by health managers in the city of São Paulo, who will have regional information that is sufficiently precise to assess issues related to reported morbidity and the use of services. However, it is important to be aware of the use of results related to rare events, especially when done with small samples.

It was a good choice to follow this path so that the sample in this edition of ISA-Capital could have the data disaggregated by Health Coordinations. The comparison of the results of different regions of the city can help in the understanding of the determinants of the epidemiological situation of the resident population and aspects related to the use of health services available in the area. The government of the city of São Paulo has prepared reports that analyze the data related to the various subjects addressed in the researchm. This production shows the potential contribution of the survey in the analysis of health problems of the population of the city and the adequacy of the coping strategies adopted. The repetition of surveys in the city meets the interest of studying trends in several measures related to the health of the population living in it.

Funding: The ISA-Capital 2015 was supported by the Health Department of the City of São Paulo (Process 0.235.936-0, of 2013).

aCesar CLG, Carandina L, Alves MCGP, Barros MBAB, Goldbaum M. Inquéritos de Saúde no Município de São Paulo - ISA-Capital 2003. São Paulo: USP/FSP; 2003 [cited 2017 Apr 4]. Available from: http://www.fsp.usp.br/isa-sp/old/index_arquivos/Page3157.htm

bCesar CLG, Carandina L, Alves MCGP, Barros MBAB, Goldbaum M. Inquéritos de Saúde no Município de São Paulo - ISA-Capital 2008. São Paulo: USP/FSP; 2008 [cited 2017 Apr 4]. Available from: http://www.fsp.usp.br/isa-sp/old/index_arquivos/Page1494.htm

cSeminário Inquérito de Saúde: ISA-Capital 2015; 31 mar 2016; São Paulo, SP. São Paulo: FSP-USP; c2010 [cited 2017 Apr 4]. Available from: http://www.fsp.usp.br/site/eventos/mostrar/5523

dUNICAMP, Faculdade de Ciências Médicas, Centro Colaborador em Análise da Situação de Saúde. Inquérito de Saúde do Município de Campinas – ISACamp 2008. Campinas: CCAS; 2008 [cited 2017 Apr 4]. Available from: http://www.fcm.unicamp.br/fcm/ccas-centro-colaborador-em-analise-de-situcao-de-saude/isacamp/2008

eUNICAMP, Faculdade de Ciências Médicas, Centro Colaborador em Análise da Situação de Saúde. Inquérito de Saúde do Município de Campinas – ISACamp 2014/2015. Campinas: CCAS; 2014 [cited 2017 Apr 4]. Available from: http://www.fcm.unicamp.br/fcm/ccas-centro-colaborador-em-analise-de-situcao-de-saude/isacamp/2014

fPrefeitura de São Paulo. Secretaria Municipal de Saúde: organização. São Paulo; c2017 [cited 2018 Feb 1]. Available from: http://www.prefeitura.sp.gov.br/cidade/secretarias/saude/organizacao/

gInstituto Brasileiro de Geografia e Estatística. Censo Demográfico 2000: agregado por setores censitários dos resultados do universo. 2.ed. Rio de Janeiro: IBGE; 2003 [cited 2017 Apr 4]. Available from: ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2000/Dados_do_Universo/Agregado_por_Setores_Censitarios

hDini NP. Pesquisa por amostragem: política de divulgação de estimativas com baixa precisão amostral. Rio de Janeiro: IBGE; s.d. [cited 2017 Apr 4]. Available from: https://www.ibge.gov.br/confest_e_confege/pesquisa_trabalhos/CD/mesas_redondas/294-1.pdf

iInstituto Brasileiro de Geografia e Estatística. Pesquisa de Condições de Vida - PCV 2006. Rio de Janeiro: IBGE; 2006 [cited 2017 Apr 22]. Available from: http://produtos.seade.gov.br/produtos/pcv/pdfs/aspectos_metodologicos_pcv2006.pdf

jInstituto Nacional de Estatística (PT). Orçamentos Familiares: inquérito às despesas das famílias – 2015-2016. Lisboa: INE; 2017 [cited 2017 Apr 22]. Available from: https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_publicacoes&PUBLICACOESpub_boui=277098526&PUBLICACOESmodo=2&xlang=pt

kWhere C1 is the cost of an additional tract and C2 is an additional interview, and ρ is the degree of intra-cluster homogeneity.

jValue based on results observed in a previous survey carried out in the city of São Paulo (ISA-Capital), in which most of the health variables studied presented values below 0.05.

mPrefeitura de São Paulo, Secretaria Municipal de Saúde. Publicações sobre ISA-Capital - SP. São Paulo; 2014 [cited 2017 Apr 4]. Available from: http://www.prefeitura.sp.gov.br/cidade/secretarias/saude/epidemiologia_e_informacao/isacapitalsp/index.php?p=177260

Acknowledgments

To the field team and coordinators: Margaret Harrison de Santis Dominguez, Mariângela Pereira Nepomuceno Silva, Fernanda Mello Zanetta, and Cleiton Eduardo Fiório.

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Received: September 12, 2017; Accepted: October 10, 2017

Correspondence: Maria Cecilia Goi Porto Alves, Rua Santo Antônio, 590, 01314-000 São Paulo, SP, Brazil E-mail: ceciliagoi2@gmail.com

Authors’ Contribution: Planning and design of the study, analysis and interpretation of the data, critical review of the study: MCGPA, MMLE. Planning and critical review of the study: MG, MBAB, RMF, CLGC. All authors have approved the final version of the study and assume public responsibility for its content.

Conflict of Interest: The authors declare no conflict of interest.

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