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Conteúdo (article):

Desigualdades sociais na realização de exames preventivos entre mulheres mais velhas (50+): evidências do ELSI-Brasil
Social inequalities in the use of preventive healthcare among older women (50+): evidence from ELSI-Brazil
Desigualdades sociales en la realización de exámenes preventivos entre mujeres mayores (50+): evidencia de ELSI-Brasil

Poliana Fialho de Carvalho, Instituto René Rachou, polianafcarvalho@gmail.com ORCID:0000-0001-6482-6803
Luciana de Souza Braga, Universidade Federal de Minas Gerais, lusouzabraga@ufmg.br ORCID:0000-0003-4499-6316
Maria Fernanda de Lima-Costa, Instituto René Rachou e Universidade Federal de Minas Gerais lima.costa@fiocruz.br, ORCID:0000-0002-3474-2980
Juliana Vaz de Melo Mambrini, Instituto René Rachou, juliana.mambrini@fiocruz.br, ORCID:0000-0002-0420-3062
RESUMO
Considerando o cenário do envelhecimento populacional brasileiro, marcado pela feminização da velhice e pela persistente desigualdade social no acesso e uso dos serviços de saúde, este trabalho tem como objetivo investigar a associação entre variáveis socioeconômicas e realização de exames preventivos de saúde entre mulheres mais velhas (+50), segundo fonte de atenção à saúde. Trata-se de estudo transversal utilizando dados do ELSI-Brasil (2015-16). Os desfechos foram a realização de exame de Papanicolau, mamografia, dosagem de colesterol e glicemia e aferição da pressão arterial, e as exposições de interesse foram escolaridade, cor autorreferida e renda domiciliar per capita. Foram ajustados modelos logísticos, com estimativa de razões de chance (α=5%). Cor autorreferida, escolaridade e renda foram frequentemente associadas aos desfechos, para mulheres com e sem afiliação aos planos privados de saúde, com maior realização dos exames entre as brancas e de maior escolaridade e renda. Implementação de políticas públicas e ações multisetoriais que atuem nos determinantes estruturais da saúde e melhorem as condições de vida e trabalho são essenciais para reduzir as iniquidades em saúde e garantir o direito universal a saúde.
Palavras-chave: Idoso, Uso de serviços de saúde, Saúde da mulher, Mensuração das desigualdades em saúde, Estudos transversais.
ABSTRACT
Considering the scenario of Brazilian population aging, marked by the feminization of old age and persistent social inequality in access to and use of health services, this study aims to investigate the association between socioeconomic variables and preventive healthcare among older women (50+), according to the source of health care. This is a cross-sectional study, based on ELSI-Brazil (2015-16) baseline data. The outcomes were Pap smear; mammography; measurements of cholesterol, blood glucose, and blood pressure; and the exposures of interest were educational level, self-reported skin color, and per capita household income. Odds ratio (OR) were estimated in Logistic regression models. Self-reported skin color, educational level, and per capita household income were frequently associated with outcomes for women with and without private health plans, with a higher prevalence of exams among those who were white and those who had higher educational and income levels. The implementation of public policies and multisectoral actions that tackle the structural determinants of health and improve people’s living and working conditions is essential to reducing health inequalities and ensuring the universal right to health.
Keywords: Aged. Screening Tests. Women\'s health. Measuring health inequalities. Cross-sectional studies.
RESUMEN
Considerando el escenario de envejecimiento de la población brasileña, marcado por la feminización de la vejez y la persistente desigualdad social en salud, este trabajo tiene como objetivo investigar la asociación entre variables socioeconómicas y la realización de exámenes preventivos de salud entre mujeres mayores, según fuente sanitaria. Se trata de un estudio transversal que utiliza datos de ELSI-Brasil (2015-16). Los resultados fueron prueba de Papanicolaou, mamografía, medición del colesterol y la glucosa en sangre y medición de la presión arterial, y las exposiciones de interés fueron la educación, la raza autoinformada y el ingreso familiar per cápita. Se ajustaron los modelos logísticos estimando odds ratios (α=5%). El color, la educación y los ingresos autoinformados se asociaron frecuentemente con los resultados, para mujeres con y sin afiliación a planes de salud privados, y se realizaron más exámenes entre las mujeres blancas y aquellas con mayor educación e ingresos. La implementación de políticas públicas multisectoriales que aborden los determinantes estructurales de la salud y mejoren las condiciones de vida y de trabajo son esenciales para reducir las inequidades en salud y garantizar el derecho universal a la salud.
Palabras clave: Adulto mayor, Uso de servicios de salud, Salud de la mujer, Medición de desigualdades en salud, Estudios transversales.

INTRODUCTION
In the aging process of the Brazilian population, the feminization of old age stands out, primarily as a consequence of women\'s greater life expectancy1. However, despite living longer, they are more subject to the process of weakening their health status, resulting from their social history, which involves discrimination in access to education, work, food, and salary2.
As a consequence of population aging, we have observed an increase in the incidence and prevalence of Noncommunicable Diseases (NCDs)3. Globally, the four main groups of NCDs (cardiovascular diseases, cancer, diabetes, and chronic respiratory diseases) account for 71% of all deaths, with low- and middle-income countries being the most impacted4. In Brazil, these groups of chronic diseases accounted for 54.7% of deaths in 20195.
Addressing NCDs is a challenge for public health and requires the health system to organize itself to offer regular preventive actions, timely diagnoses, and early treatment in order to reduce the incidence of complications and avoid premature deaths. The provision of comprehensive longitudinal care required to address NCDs increases the demand for health services, particularly among older adults, a population group that tends to have a higher number of chronic diseases. Research conducted by Nunes et al. (2018)6, using data from the Brazilian Longitudinal Study of Elderly Health (ELSI-Brazil), showed that the prevalence of multimorbidity was higher among women and increased with age.
The expansion of Family Health Strategy (FHS) teams has improved the performance of several health indicators for the population, with a significant reduction in hospitalizations and mortality due to chronic conditions that are sensitive to Primary Health Care (PHC)7-9. A study conducted in the state of Espírito Santo demonstrated that, after the implementation of the FHS teams, there was a reduction in hospitalizations due to conditions that are sensitive to primary care, especially those related to hypertension among adults and the elderly10. Another initiative that contributed to the control of NCDs was the implementation of the Hyperdia program, an initiative of the FHS launched in 2001, which enabled more systematic monitoring of people with diabetes and hypertension by health teams11.
The FHS has established itself as an important tool for addressing social inequalities in health, mainly by expanding access to PHC services and preventing complications from chronic conditions7-9. However, despite these advances, Brazil is still extremely marked by social inequalities in access to and use of health services, and individuals with greater social disadvantages are less likely to seek and use these services. Evidence suggests that, although the FHS teams have contributed to expanding access to and use of health services, barriers still persist that limit universality and equity in care, reflecting the continued inequalities in the country12,13.
Social inequality in access to health services is also evident in the use of medical examinations among women. The literature indicates that married, white women, women with higher educational levels, and with private health insurance are more likely to have undergone a Pap smear, a preventive exam used to diagnose cervical cancer, the third leading cause of death in women in Brazil14-18. Similar results were observed for mammography, used to detect breast cancer, the neoplasm that most kills women in Brazil19. Studies indicate that women with higher educational and income levels, who live with a partner, who live in urban areas, and who have private health insurance are more likely to undergo the exam14,17,18,20.
For the Pap smear, the Ministry of Health (MoH) protocols recommend performing two exams with a one-year interval between them and, if both are negative, that the frequency be increased to three years, with the target audience being women aged 25 to 64 years21. Regarding mammography, the recommendation is that the exam should be performed every two years for women aged 50 to 69 years21.
In addition to neoplasms, two other groups of NCDs are responsible for a major part of the morbidity and mortality among women: circulatory system diseases, especially cardiovascular diseases, and diabetes. It is well-known that systemic arterial hypertension (SAH) and dyslipidemia constitute modifiable risk factors for the development of cardiovascular diseases and are considered a major public health problem22,23. According to the Brazilian Hypertension Guidelines, healthy individuals with adequate blood pressure values measured in the office and pre-hypertensive patients should have their blood pressure measured at least once a year22,24.
High cholesterol is associated with an increased risk of heart disease and stroke25. There is no consensus regarding the frequency of screening, and it is usually determined according to cardiovascular risk. For individuals with normal results, it is suggested that the measurement be performed every five years. A shorter interval may be recommended for people with values close to the limit26.
As for diabetes mellitus, there is no evidence regarding an ideal frequency for screening; however, the MoH recommends that individuals with risk factors should be tested every three to five years27.
In view of the above, considering the scenario of Brazilian population aging, marked by the feminization of old age and social inequality in access to and use of health services, the present study aimed to investigate the association between socioeconomic variables and preventive healthcare among older women (50 years and older), according to the source of care (exclusive users of SUS or affiliation with a private health plan). Stratification by source of care is necessary due to differences in the organization of the systems, which may be an important confounding factor for the object of study.
This work seeks to fill a gap in the Brazilian context by contributing information that strengthens public health policies in Brazil, helping to ensure comprehensive longitudinal care for women aged 50 and older. Furthermore, the results presented herein can contribute to expanding the availability of preventive services and to the promotion of multisectoral measures that act upon socioeconomic conditions as a strategy to reduce social inequalities in health and guarantee equity.

METHODS
Study population
Cross-sectional study conducted with baseline data from the Brazilian Longitudinal Study of Aging (ELSI-Brazil), collected between 2015 and 2016. To ensure representativeness of urban and rural areas in municipalities of different sizes (small, medium, and large), the ELSI-Brazil sampling process adopted a design with selection stages, involving stratification, according to population size, primary sampling units (municipalities), census tracts, and households. The planned number of interviews was 10,000 (9,412 participated), residing in 70 municipalities, located in the five Brazilian macro-regions. The ELSI-Brazil sample is representative of the non-institutionalized Brazilian population aged 50 and over.
More details on the methodology were described in another publication28 and on the research website (https://elsi.cpqrr.fiocruz.br/). Females aged 50 years or older were eligible for this study, making up all 5,314 female ELSI participants.

Study variables
Dependent variables (Healthcare service use indicators)
The outcomes of interest were indicators of the use of health services by older participants, assessed based on Pap smear and mammogram tests, in accordance with the MoH21 guidelines for the age group, blood glucose and cholesterol levels, and blood pressure measurements22, as described below:
a) Pap smear, for participants aged 50 to 64 years (3 years or less; more than 3 years or never had one)
b) Mammography, for participants aged 50 to 69 years (2 years or less; more than 2 years or never had one)
c) Blood glucose level, for participants aged 50 or over (3 years or less; more than 3 years or never had one)
d) Cholesterol level, for participants aged 50 or over (3 years or less; more than 3 years or never had one)
e) Blood pressure measurement, for participants aged 50 or over (Up to 1 year; more than 1 year or never had one)
The temporality of the outcomes was defined in this way to ensure alignment with current public health policies in Brazil, in addition to reflecting the standard practice of the health system in our context.

Exposure variables (socioeconomic indicators)
a) Self-reported race (white; other (black, brown, yellow, and indigenous))
b) Educational level (< 4 years; 4-7 years; ≥ 8 years of study)
c) Per capita household income (in tertiles: up to R$587.00; from R$587.00 to R$1,050.00; above R$1,050.00)

Adjustment variables
a) Age (50-59; 60-69; 70-79; 80 years and over)
b) Living arrangement (lives alone; does not live alone)
c) Number of chronic diseases, considering self-reported medical diagnosis for high blood pressure, diabetes, heart attack, angina, heart failure, stroke, chronic obstructive pulmonary disease, arthritis or rheumatism, depression, cancer and chronic renal failure (absence of disease; one chronic disease; two or more chronic diseases)

Stratification variable
a) Source of health care (with health insurance; without health insurance).

Data analysis
The sample characteristics were presented using relative frequencies, with their respective 95% confidence intervals (95% CI). In the unadjusted analyses, Pearson\'s Chi-Square test, with Rao-Scott correction, was used to assess the statistical significance of differences between proportions, according to the source of health care.
The magnitudes of the associations between the exposure variables (self-reported race, education, and per capita household income) and the outcomes (Pap smear, mammography, blood glucose and cholesterol levels, and blood pressure measurement) were analyzed using the logistic regression model, with estimated odds ratios and their respective 95% CI. Crude models and models adjusted for potential confounding factors were adjusted in the sample stratified according to the source of health care. The goodness-of-fit of the model adjustment was assessed using the Hosmer-Lemeshow test. All analyses were conducted using Stata® software version 14.1, taking into account the complexity of the sample design and the weight of the individuals. The significance level was set at 5%.

Ethical aspects
ELSI-Brazil was approved by the Fundação Oswaldo Cruz (FIOCRUZ) ethics committee, Minas Gerais, Brazil (protocol number 886.754). All participants registered their consent to participate in the study by signing the Free and Informed Consent Form (FICF).
ELSI-Brazil was funded by the MoH: DECIT/SCTIE (Processes: 404965/2012-1 and TED 28/2017); COPID/DECIV/SAPS (Processes: 20836, 22566, 23700, 25560, 25552, and 27510).

RESULTS
The ELSI-Brazil sample included 5,314 women. Those who met the selection criteria regarding the age group and provided valid responses for the outcomes of interest were included in the study, with the largest loss, of 2.13%, being due to invalid responses for the outcome related to cholesterol measurement. The final study sample consisted of 5,225; 5,201; and 5,265 women for, respectively, the outcomes of blood glucose, cholesterol levels, and blood pressure measurements, and 2,942 and 3,727 women for Pap smear (50 to 64 years) and mammogram (50 to 69 years), respectively.
Affiliation to a private health plan was declared by 25.3% of the participants. According to Table 1, 54.2% of the participants were 60 years of age or older and 57.3% self-identified as black, brown, yellow, or indigenous. Approximately one in 10 lived alone, and 34.5% had less than four years of education. Approximately 39% of the participants reported no chronic disease and 28% self-reported multimorbidity (diagnosis of at least two chronic diseases). Regarding preventive healthcare, approximately 78% had undergone a Pap smear in the last three years and 74% had a mammogram in the last two years. Approximately 90% of the participants had blood glucose and cholesterol tests performed in the last three years, while 94% had their blood pressure measured in the last year. With the exception of the number of chronic diseases, all other variables included in the study were statistically associated with affiliation to a private health plan, with preventive healthcare being more frequent among participants with a health plan.

TABLE 1. Descriptive characteristics of the sample, overall and according to private health plan affiliation (ELSI-Brazil, 2015-2016).

The associations between sociodemographic variables and the performance of preventive healthcare are presented in Tables 2 and 3 for participants with and without health insurance, respectively. For both groups, self-reported race, educational level, and per capita income were associated with most of the analyzed outcomes, with a higher prevalence of exams among white participants, with higher educational levels, and living in households with higher per capita income. Among participants with health insurance, age group and living arrangements were not statistically associated with any of the analyzed outcomes (Table 2). By contrast, for exclusive users of SUS, age group was strongly associated with the use of health services. For Pap smear and mammography exams, a higher frequency was observed among younger participants, whereas for the other exams, there was a higher frequency among older participants (Table 3). It is also important to note that there was a higher frequency of mammography and blood glucose testing among those who did not live alone (Table 3).

TABLE 2. Prevalence (% (95% CI)) of preventive healthcare among older women who have private health insurance, according to sociodemographic variables (ELSI-Brazil, 2015-2016).

TABLE 3. Prevalence (% (95% CI)) of preventive healthcare among older women who do not have private health insurance, according to sociodemographic variables (ELSI-Brazil, 2015-2016).

Tables 4 and 5 show the association between socioeconomic variables and preventive healthcare for participants with and without health insurance, respectively, adjusted for age groups, living arrangements, and number of chronic diseases. Among participants who reported having health insurance, compared to black, brown, yellow, or indigenous individuals, there was a greater chance of having cholesterol levels measured within the last three years among white individuals (OR = 2.00; 95% CI 1.13–3.56). Educational level was significantly associated with having a Pap smear and having cholesterol levels measured. Compared to participants with less than four years of education, having between four and seven years of education and eight years or more was associated with a greater chance of having a Pap smear (OR = 3.88; 95% CI 1.85–8.13 and OR = 3.04; 95% CI 1.62–5.67, respectively). Participants with 8 or more years of education were also more likely to have their cholesterol levels measured (OR = 2.73; 95% CI 1.19–6.27). Finally, participants in the highest tertile of household per capita income were more likely to have their blood glucose levels (OR = 2.51; 95% CI 1.47–4.30) and cholesterol levels (OR = 2.65; 95% CI 1.24–5.64) measured, as compared to those in the lowest tertile. Having had a mammogram in the last two years and having had one’s blood pressure measured in the last year were not statistically associated with the analyzed socioeconomic factors. Detailed results can be seen in Table 4.
For exclusive SUS users, positive and statistically significant associations were identified among self-reported race, educational level, per capita household income, and the use of health services (Table 5). White participants were more likely to have had their blood glucose levels measured within the last three years (OR = 1.30; 95% CI 1.01–1.68). Compared to participants with less than four years of education, those with 4–7 years of education were more likely to have had a mammogram in the last two years (OR = 1.35; 95% CI 1.08–1.69), as well as blood glucose and cholesterol levels measured in the last 3 years (respectively, OR = 1.56; 95% CI 1.16–2.09 and OR = 2.04; 95% CI 1.52–2.74). Having eight or more years of education was also associated with a higher chance of undergoing blood glucose (OR = 1.67; 95% CI 1.27–2.20) and cholesterol (OR = 2.10; 95% CI 1.62–2.72) exams. Regarding income, participants in the second tertile of per capita household income were more likely to undergo a Pap smear (OR = 1.50; 95% CI 1.06–2.10). Participants in the third tertile of income were more likely have a Pap smear (OR = 1.47; 95% CI 1.02–2.12) and blood glucose (OR = 1.55; 95% CI 1.14–2.10) and cholesterol (OR = 1.68; 95% CI 1.23–2.30) exams. The socioeconomic factors analyzed in this study were not associated with blood pressure measurements in the last year. Additional details are presented in Table 5.

TABLE 4. Association (OR (95% CI)) between sociodemographic characteristics and the use of preventive healthcare among older women who have private health insurance (ELSI-Brazil, 2015-2016).

TABLE 5: Association (OR (95% CI)) between sociodemographic characteristics and the use of preventive healthcare among older women who do not have private health insurance (ELSI-Brazil, 2015-2016).

DISCUSSION
The results of this study highlighted the presence of inequalities in preventive healthcare among Brazilian women aged 50 and over, in the investigated outcomes. The main results include (a) the greater frequency of cholesterol (private health plan members) and blood glucose (exclusive SUS users) exams among white women; (b) education as an important determinant for the performance of exams among older Brazilian women with private health insurance (Pap smear and cholesterol) and without private health insurance (mammography, blood glucose, and cholesterol); (c) income as an important determinant for the performance of exams among older Brazilian women with private health insurance (blood glucose and cholesterol) and without private health insurance (Pap smear, blood glucose, and cholesterol).
Socioeconomic markers are determinants of the performance of preventive exams among Brazilian women aged 50 and over. In this age group, NCDs are the most prevalent conditions, and since 2014, neoplasms have been the leading cause of death from NCDs among women in Brazil, overloading the health system and generating high economic costs29-31.
In this context, Brazil implemented the Strategic Action Plan to Combat NCDs (2011-2022), focusing on the prevention and control of such diseases as diabetes, high blood pressure, breast cancer, and cervical cancer. The 2021-2030 plan was recently launched, prioritizing disease prevention and health promotion, with a view to eliminating health inequalities32,33. It is important to emphasize that government actions should prioritize the prevention and reduction of risk factors, poverty, and social inequality, with action on the structural and intermediate determinants of health.
Although strategic action plans exist, evidence suggests that socioeconomic disparities persist in indicators of health service use, particularly those related to race/color, education, and income, regardless of the source of health care.
The Brazilian health system is comprised of SUS, which offers universal and free care, and the private system, based on one’s ability to pay of individuals, families, and employers34. Due to differences in the organization of the systems, the present study opted to use stratification by source of care. Despite the constitutional principles of universality, equity, and comprehensiveness of SUS, the population finds it difficult to schedule appointments and surgeries, and undergo examinations. Important differences can also be observed between exclusive SUS users and individuals with private health insurance34,35. It is important to note that although SUS offers all the exams studied in our work, affiliation with a private insurance plan continues to be a determining factor in performing them14,20,36-38.
Several studies indicate that education is one of the main socioeconomic markers associated with health outcomes39-41. In this study, education also proved to be an important determinant of preventive exams among older Brazilian women, with or without a health insurance plan. The literature shows that, in Brazil, women with higher education and who are affiliated with a health insurance plan are more likely to undergo medical exams, such as Pap smears and mammograms14,20,41,42. Regarding blood glucose levels, evidence also reports a lower prevalence among Brazilians with lower education43. In the USA, the proportion of women who underwent mammograms was 15% lower among those with lower education37. The literature also indicates a positive association between education and cholesterol levels. A study conducted in Poland showed that the chance of undergoing a cholesterol exam is 1.5-fold greater for people with secondary or higher education when compared to people with lower education44. Likewise, the proportion of individuals with lower levels of education who undergo this exam is 15% lower in the USA.37 Similar findings were identified in India, where education played a relevant role in the socioeconomic inequality related to the performance of blood pressure and blood glucose exams among individuals over 30 years of age in the four evaluated districts45. These findings reinforce how important the contribution of education is in the performance of preventive healthcare and point to the need to adopt strategies focused on reducing the inequalities found, such as the promotion of actions aimed at the less educated population.
In the literature, there is no consensus on the relationship between screening test uptake and race/color. In agreement with data from this study, Boccolini and Souza Junior (2016)43, when conducting a study to investigate the factors associated with inequities in the use of health services in Brazil, showed that non-white people were less likely to undergo exams, such as blood glucose levels exams. However, a study conducted in the USA with women aged 50 to 64 years found no significant differences in relation to race/color for undergoing mammograms and Pap smears37. A study that evaluated inequalities in relation to cholesterol testing in the USA showed that 6% of women aged 45 or over had never undergone a cholesterol exam. However, although the proportion of non-screening was higher among non-whites, the disparities between whites and non-whites were eliminated after adjustments for confounding variables46. Despite the lack of consensus, disparities by race/color remain an important determinant in the use of health services among older Brazilian women.
Similar to the findings of this study, data from the literature suggest that income is also considered an important determinant of the use of health services and the performance of tests40,44. Higher income was positively associated with the performance of the Pap smear among Swiss women, aged 20 to 70 years47, and among Brazilian women over 60 years of age living in the city of Juiz de Fora, in the state of Minas Gerais41. In Peru, a study conducted to assess inequalities in the performance of the Pap smear in the last three years among women, aged 30 to 59 years, revealed that the performance of the exam was concentrated among women with a higher wealth index48. In the USA, the proportion of women who performed the Pap smear was 27% lower among those with lower incomes37, and similar results were observed in relation to blood glucose and cholesterol exams. In India, a relevant role of income was observed in the inequality in the performance of blood pressure and blood glucose exams in the population over 30 years of age45. In the population over 50 years of age in Italy, Poland, Spain, France, Switzerland, and Austria, these exams are more frequent in high-income groups49 and in the USA, cholesterol testing was approximately 15% lower among those with lower incomes37.
In general, the findings of this study show that older Brazilian women (50+), black, brown, Asian, or indigenous, with lower income and education, and who use SUS exclusively are those who least undergo preventive exams.

This study has a limitation of information bias, since the outcomes were self-reported and people who are affected by a problem or disease may tend to remember more about undergoing these exams than would those who are not affected. In addition, people who have health problems tend to seek out services more often. However, the number of chronic diseases was included as an adjustment, which minimized a possible effect of this factor. However, this study also brings significant contributions, as it was conducted with a representative sample of the Brazilian population, aged 50 years and over, who are not institutionalized, living in urban and rural areas in municipalities of different sizes (small, medium, and large). Data collection was carried out by interviewers who were duly trained and certified by the project\'s research team in order to guarantee the quality of the collected information. Data analysis was conducted using appropriate statistical methodology, incorporating the effect of complex sampling design and sampling weight.
In short, the results obtained in this study showed that the socioeconomic factors evaluated were significantly associated with the performance of preventive healthcare by older Brazilian women. It is possible that individuals with higher educational levels and income recognize their health needs more and seek out health services and medical care more often, and/or have a greater ease of access. In any case, when factors such as education, self-reported race/color, and income are associated with the use of health care, evidence of inequities appears. In this context, in addition to the provision of health services, public measures and policies aimed at older women with lower income and education and who self-identify as black, brown, yellow, or indigenous, are necessary as a strategy to reduce the inequities present in the use of preventive health services.


FUNDING
This study received funding from the Coordination for the Improvement of Higher Education Personnel, through a Master\'s scholarship. ELSI-Brasil is funded by the Ministry of Health: DECIT/SCTIE (Processes: 404965/2012-1 and TED 28/2017); COPID/DECIV/SAPS (Processes: 20836, 22566, 23700, 25560, 25552 and 27510).


REFERENCES
1. Maximiano-Barreto MA, Andrade L, Campos LB, Portes FA, Generoso FK. A Feminização da velhice: uma abordagem biopsicossocial do fenômeno. Interfaces Científicas – Humanas e Sociais 2019; 8(2):239-52.
2. Lenardt MH, Carneiro NHK, Betiolli SE, Ribeiro DKMN, Walchholz PA. Prevalence of pre-frailty for the componente of gait speed in older adults. Rev Latino-Am Enfermagem. 2013; 21:734-41.
3. Barreto MS, Carreira L, Marcon SS. Envelhecimento populacional e doenças crônicas: Reflexões sobre os desafios para o Sistema de Saúde Pública. Revista Kairós: Gerontologia 2015;18(1):325-39.
4. WHO. Assessing national capacity for the prevention and control of noncommunicable diseases: report of the 2019 global survey. [Internet]. 2020. [acessado 2022 ago 1]. Disponível em: https://www.who.int/publications-detail-redirect/9789240002319
5. Brasil. Plano de ações estratégicas para o enfrentamento das doenças crônicas e agravos não transmissíveis no Brasil 2021-2030. [Internet]. 2021.[acessado 2022 set 9]. Disponível em: https://www.gov.br/saude/pt-br/centrais-de-conteudo/publicacoes/svsa/doencas-cronicas-nao-transmissiveis-dcnt/09-plano-de-dant-2022_2030.pdf/view
6. Nunes BP, Batista SRR, Andrade FB, Souza Junior PRB, Lima-Costa MF, Facchini LA. Multimorbidity: The Brazilian Longitudinal Study of Aging (ELSI-Brazil). Revista de Saúde Pública 2018; 52(suppl 2):10s.
7. Facchini LA, Tomasi E, Dilélio AS. Qualidade da Atenção Primária à Saúde no Brasil: avanços, desafios e perspectivas. Saúde debate 2018;42(spe1):208-23.
8. Macinko J, Dourado I, Aquino R, Bonolo PF, Lima-Costa MF, Medina MG, Mota E, Oliveira VB, Turci MA. Major Expansion Of Primary Care In Brazil Linked To Decline In Unnecessary Hospitalization. Health Affairs 2010;29(12):2149-60.
9. Rasella D, Harhay MO, Pamponet ML, Aquino R, Barreto ML. Impact of primary health care on mortality from heart and cerebrovascular diseases in Brazil: a nationwide analysis of longitudinal data. BMJ 2014; 349(5):g4014.
10. Pazó RG, Frauches DO, Molina MCB, Cade NV. Panorama das internações por condições sensíveis à atenção primária no Espírito Santo, Brasil, 2000 a 2014. Rev Bras Med Fam Comunidade 2017;12 (39):1-12.
11. Brasil. HIPERDIA - Sistema de Cadastramento e Acompanhamento de Hipertensos e Diabéticos. [Internet] 2008. [acessado 2025 jan 7]. Disponível em: http://siab.datasus.gov.br/DATASUS/index.php?area=060304
12. Landmann-Szwarcwald C, Macinko J. A panorama of health inequality es in Brazil. Int J Equity Health 2016; 15(1):174, s12939-016-0462-1.
13. Nunes BP, Flores TR, Garcia LP, Chiavegatto Filho ADP, Thumé E, Facchini LA. Tendência temporal da falta de acesso aos serviços de saúde no Brasil, 1998-2013. Epidemiologia e Serviços de Saúde 2016;25(4):777-87.
14. Theme Filha MM, Leal MC, Oliveira EFV, Esteves-Pereira AP, Gama SGN. Regional and social inequalities in the performance of Pap test and screening mammography and their correlation with lifestyle: Brazilian national health survey, 2013. Int J Equity Health 2016;15(1):136.
15. INCA. Mortalidade. [Internet]. 2022. [acessado 2022 set 7]. Disponível em: https://www.inca.gov.br/controle-do-cancer-do-colo-do-utero/dados-e-numeros/mortalidade
16. Vieira YP, Viero VSF, Vargas BL, Nunes GO, Machado KP, Neves RG, Saes MO. Tendência e desigualdades no rastreamento autorrelatado do câncer de colo de útero nas capitais brasileiras entre 2011 e 2020. Cad. Saúde Pública 2022; 38(9):e00272921.
17. Silva GA, Damacena GN, Ribeiro CM, Alcantara LLM, Souza Júnior PRB, Szwarcwald CL. Exame de Papanicolaou no Brasil: análise da Pesquisa Nacional de Saúde em2013 e 2019. Rev Saude Publica 2023; 57:55.
18. Schäfer AA, Santos LP, Miranda VIA, Tomasi CD, Soratto J, Quadra MR, Meller FO. Desigualdades regionais e sociais na realização de mamografia e exame citopatológico nas capitais brasileiras em 2019: estudo transversal. Epidemiol. Serv. Saude, 2021; 30(4):e2021172.
19. INCA. Estimativa 2020: Incidência de Câncer no Brasil. [Internet]. 2019. [acessado 2022 jul 19]. Disponível em: https://www.inca.gov.br/sites/ufu.sti.inca.local/files/media/document/estimativa-2020-incidencia-de-cancer-no-brasil.pdf .
20. Bezerra HS, Melo TFV, Barbosa JV, Feitosa EELC, Sousa LCM. Avaliação do acesso em mamografias no Brasil e indicadores socioeconômicos: um estudo espacial. Rev. Gaúcha Enferm 2018; 39.
21. Brasil. Protocolos da Atenção Básica: Saúde das Mulheres. [Internet]. 2016. [acessado 2022 nov 11]. Disponível em: https://bvsms.saude.gov.br/bvs/publicacoes/protocolos_atencao_basica_saude_mulheres.pdf
22. Brasil. Estratégias para o cuidado da pessoa com doença crônica: hipertensão arterial sistêmica. Ministério da Saúde, Secretaria de Atenção à Saúde, Departamento de Atenção Básica. [Internet]. 2013. [acessado 2022 nov 11]128. Disponível em: https://aps.saude.gov.br/biblioteca/visualizar/MTIxNA==
23. RIGHI, R. E. Guia Terapeutico para atenção primária. 2° ed. 2008.
24. Ministério da Saúde. Como deve ser o seguimento dos pacientes hipertensos pela Equipe de Saúde da Família? [Internet]. 2016. [acessado 2023 set 17] Disponível em: .
25. Malta DC, Szwarcwald CL, Machado ÍE, Pereira CA, Figueiredo AW, Sá ACMGN, Velasquez-Melendez G, Santos FM, Souza Junior PB, Stopa SR, Rosenfeld LG. Prevalência de colesterol total e frações alterados na população adulta brasileira: Pesquisa Nacional de Saúde. Revista Brasileira de Epidemiologia 2019; v. 22, n. suppl 2, p. E190005.SUPL.2.
26. Brasil. Caderno de Atenção Primária - Rastreamento. Ministério da Saúde. [Internet]. 2010. [acessado 2023 jan 17] Disponível em: .
27. Brasil. Estratégias para o cuidado da pessoa com doença crônica: diabetes mellitus. Ministério da Saúde, Secretaria de Atenção à Saúde, Departamento de Atenção Básica. [Internet]. 2013 [acessado 2023 mar 17]. Disponível em: < https://aps.saude.gov.br/biblioteca/visualizar/MTIxMw==>.
28. Lima-Costa MF , Andrade FB, Souza Jr PRB, Neri AL, Duarte YAO, Castro-Costa E, Oliveira C . The Brazilian Longitudinal Study of Aging (ELSI-Brazil): Objectives and Design. Am J Epidemiol 2018; 187(7):1345-53.
29. Abegunde DO, Mathers CD, Adam T, Ortegon M, Strong K. The burden and costs of chronic diseases in low-income and middle-income countries. The Lancet 2007; v. 370, n. 9603, p. 1929–1938, dez.
30. Malta DC, Bernal RTI, Lima MG, Araújo SSC, Silva MMA, Freitas MIF, Barros MBA. Noncommunicable diseases and the use of health services: analysis of the National Health Survey in Brazil. Revista de Saúde Pública 2017; v. 51, n. suppl 1.
31. Sistema De Informações Sobre Mortalidade. Painel de Monitoramento da Mortalidade Prematura (30 a 69 anos) por DCNT - Mortalidade - Painéis de Monitoramento - Centrais de Conteúdos - DASNT - SVS/MS. [Internet]. 2022. [acessado 2023 jan 17] Disponível em: .
32. Brasil. Plano de Ações Estratégicas Para o Enfrentamento das Doenças Crônicas e Agravos não Transmissíveis no Brasil 2021-2030 [Internet]. 2021. [acessado 2023 jan 08] Disponível em: https://www.gov.br/saude/pt-br/centrais-de-conteudo/publicacoes/svsa/doencas-cronicas-nao-transmissiveis-dcnt/09-plano-de-dant-2022_2030.pdf/view
33. Brasil. Plano de ações estratégicas para o enfrentamento das doenças crônicas não transmissíveis (DCNT) no Brasil 2011-2022. Ministério da Saúde. Brasília. [Internet]. 2011. [acessado 2023 jan 08] Disponível em: < https://bvsms.saude.gov.br/bvs/publicacoes/plano_acoes_enfrent_dcnt_2011.pdf>.
34. Silva AMM, Mambrini JVM, Peixoto SV, Malta DC, Lima-Costa MF. Uso de serviços de saúde por idosos brasileiros com e sem limitação funcional. Revista de Saúde Pública 2017; v. 51, 1 jun.
35. Politi R. Desigualdade na utilização de serviços de saúde entre adultos: uma análise dos fatores de concentração da demanda. Economia Aplicada 2014; v. 18, p. 117–137, mar.
36. Garcia-Subirats I, Vargas I, Mogollón-Pérez AS, Paepe P, Silva MRF, Unger JP, Borrell C, Vázquez ML . Inequities in access to health care in different health systems: a study in municipalities of central Colombia and north-eastern Brazil. International Journal for Equity in Health 2014; v. 13, n. 1, p. 10.
37. Multack M. Use of Clinical Preventive Services and Prevalence of Health Risk Factors among Adults Aged 50–64: National and State-Level Racial/Ethnic, Socioeconomic, and Health Insurance Coverage Status Disparities. [Internet]. 2013 [acessado 2022 nov 11]; 84. Disponível em: https://www.aarp.org/health/health-insurance/info-08-2013/use-of-clinical-preventive-services-and-prevalence-AARP-ppi-health.html
38. Rivera-Hernandez M, Galarraga O. Type of Insurance and Use of Preventive Health Services Among Older Adults in Mexico. Journal of Aging and Health 2015; v. 27, n. 6, p. 962–982, set.
39. Fiocruz. Escolaridade: um macro determinante limitado por diferentes realidades sociais. Determinantes Sociais da Saúde. [Internet]. 2012. [acessado 2023 jan 17]. Disponível em: https://dssbr.ensp.fiocruz.br/escolaridade-um-macro-determinante-limitado-por-diferentes-realidades-sociais/
40. Fonseca DS, Santos CS, Barreto ICF, Gonçalves LGL, Morais LC, Gonçalves LA, Ribeiro MEA, Silva VLC, Schiavon JLO. Câncer de Mama: uma questão social desigual/ Breast cancer: an unequal social issue. Brazilian Journal of Health Review 2020;3(6):19933-43.
41. Novaes CO, Mattos IE. Prevalência e fatores associados a não utilização de mamografia em mulheres idosas. Cad Saúde Pública 2009; 25 (suppl 2): s310-20.
42. Oliveira MM, Andrade SSCA, Oliveira PPV, Silva GA, Silva MMA, Malta DC. Cobertura de exame Papanicolau em mulheres de 25 a 64 anos, segundo a Pesquisa Nacional de Saúde e o Sistema de Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico, 2013. Revista Brasileira de Epidemiologia 2018; 21:e180014.
43. Boccolini CS, Souza Junior PRB. Inequities in Healthcare utilization: results of the Brazilian National Health Survey, 2013. Int J Equity Health 2016;15(1):150.
44. Agrawal S, Makuch S, Lachowicz G, Drózdz M, Dudek K, Mazur G. How Sociodemographic Factors Impact the Utilization of Recommended Clinical Preventive Screening Services in Poland: A Nationwide Cross-Sectional Study. Int J Environ Res Public Health 2021;18 (24): 13225.
45. Sharma SK, Nambiar D, Sankar H, Joseph J, Surendran S and Benny. Decomposing socioeconomic inequality in blood pressure and blood glucose testing: evidence from four districts in Kerala, India. International Journal for Equity in Health 2022; 21:128.
46. Kenik J, Jean-Jacques M, Feinglass J. Explaining racial and ethnic disparities in cholesterol screening. Preventive Medicine 2014; 65:65-9.
47. Burton-Jeangros C, Cullati S, Manor O, Courvoisier DS, Bouchardy C, Guessous I. Cervical cancer screening in Switzerland: cross-sectional trends (1992–2012) in social inequalities. Eur J Public Health 2016; 27(1):167-173.
48. Barrenechea-Pulache A, Avila-Jove E, Hernández-Vásquez A, Runzer-Colmenares FM. Socio-demographic inequalities in the uptake of Papanicolaou tests in Peru: analysis of the 2015-2017 Demographic and Family Health Survey. Epi H 2020; 42, Article ID: e2020043, 9 p.
49. Carrieri V, Wuebker A. Assessing inequalities in preventive care use in Europe. Health Policy 2013; 113(3):247-57.