SciELO - Scientific Electronic Library Online

 
vol.22 suppl.2Evaluation of renal function in the Brazilian adult population, according to laboratory criteria from the National Health SurveySocial inequalities in the food consumption profile of the Brazilian population: National Health Survey, 2013 author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

  • text in Portuguese
  • text new page (beta)
  • English (pdf) | Portuguese (pdf)
  • Article in xml format
  • How to cite this article
  • SciELO Analytics
  • Curriculum ScienTI
  • Automatic translation

Indicators

Related links

Share


Revista Brasileira de Epidemiologia

Print version ISSN 1415-790XOn-line version ISSN 1980-5497

Rev. bras. epidemiol. vol.22  supl.2 Rio de Janeiro  2019  Epub Oct 07, 2019

http://dx.doi.org/10.1590/1980-549720190006.supl.2 

ORIGINAL ARTICLE

Prevalence of diabetes mellitus as determined by glycated hemoglobin in the Brazilian adult population, National Health Survey

Deborah Carvalho MaltaI 
http://orcid.org/0000-0002-8214-5734

Bruce Bartholow DuncanII 
http://orcid.org/0000-0002-7491-2630

Maria Inês SchmidtII 
http://orcid.org/0000-0002-3837-0731

Ísis Eloah MachadoIII 
http://orcid.org/0000-0002-4678-2074

Alanna Gomes da SilvaIII 
http://orcid.org/0000-0003-2587-5658

Regina Tomie Ivata BernalI 
http://orcid.org/0000-0002-7917-3857

Cimar Azeredo PereiraIV 

Giseli Nogueira DamacenaV 
http://orcid.org/0000-0002-7059-3353

Sheila Rizzato StopaVI 
http://orcid.org/0000-0001-8847-665X

Luiz Gastão RosenfeldVII  *

Celia Landman SzwarcwaldV 
http://orcid.org/0000-0002-7798-2095

IDepartment of Nursing for Mothers and Children and Public Health, School of Nursing, Universidade Federal de Minas Gerais - Belo Horizonte (MG), Brazil.

IIGraduate Program in Epidemiology, Universidade Federal do Rio Grande do Sul - Porto Alegre (RS), Brazil.

IIIGraduate Program in Nursing, Universidade Federal de Minas Gerais - Belo Horizonte (MG), Brazil.

IVResearch Center, Instituto Brasileiro de Geografia e Estatística - Rio de Janeiro (RJ), Brazil.

VInstitute of Health Scientific and Technological Communication and Information, Fundação Oswaldo Cruz - Rio de Janeiro (RJ), Brazil.

VID Surveillance Department for Noncommunicable Disease and Health Promotion, Health Surveillance Secretariat, Ministério da Saúde - Brasília (DF), Brazil.

VIICenter for Hematology of São Paulo - São Paulo (SP), Brazil.


ABSTRACT:

Objective:

To analyze the prevalence of diabetes mellitus (DM) according to different diagnostic criteria, in the Brazilian adult population, according to laboratory results from the Brazilian National Health Survey.

Methods:

Analysis of laboratory data from the National Health Survey, collected between 2014 and 2015. The prevalence of diabetes was calculated according to different diagnostic criteria. The prevalence of diabetes was calculated according to the criterion of glycosylated hemoglobin ≥ 6.5% or using medication, using Poisson regression and calculating crude and adjusted PR and 95%CI.

Results:

The prevalence of diabetes according to different criteria varies from 6.6 to 9.4%. Intermediate or pre-diabetes hyperglycemia ranged from 6.8 to 16.9%. Considering laboratory criteria or medication use, the prevalence of DM was 8.4 (95%CI 7.65-9.11). The adjusted PR for gender, age, educational level and region was lower for males (PR 0.75; 95%CI 0.63 - 0.89), increased with age: 30 to 34 years (PR 2.32; 95% CI 1.33 - 4.07), 40 to 59 years PR 8.1; 95%CI 4.86 - 13.46), 60 years old or older (PR 12.6; 95%CI 7.1 - 21.0), and higher educational levels was protective (PR 0.8; 95%CI 0.6 - 0.9). Therewas a higher PR in the Central West Region (PR 1.3; 95%CI 1.04 - 1.7), in overweight people (PR 1.8; 95%CI 1.4 - 2.1), and in obese people (PR 3.3; 95%CI 2.6 - 4.1).

Conclusion:

The prevalence of diabetes was higher in females, people over 30 years of age, in populations with low educational levels, and people who were overweight and obese. The study advances in determining the diabetes situation in the country through laboratory criteria.

Keywords: Diabetes mellitus; Prediabetic state; Glycated hemoglobin A; Clinical laboratory techniques; Noncommunicable diseases; Obesity

RESUMO:

Objetivo:

Analisar as prevalências de diabetes mellitus segundo diferentes critérios diagnósticos, na população adulta brasileira, segundo os resultados laboratoriais da Pesquisa Nacional de Saúde.

Métodos:

Análise dos dados laboratoriais da Pesquisa Nacional de Saúde, coletados entre os anos de 2014 e 2015. Foram calculadas as prevalências de diabetes conforme diferentes critérios diagnósticos. Foram calculadas as prevalências de diabetes segundo o critério de hemoglobina glicosilada ≥ 6,5% ou em uso de medicamentos, empregando regressão de Poisson para o cálculo da razão de prevalência (RP) bruta e ajustada e intervalo de confiança de 95% (IC95%).

Resultados:

A prevalência de diabetes segundo diferentes critérios pode variar 6,6 a 9,4%; e a hiperglicemia intermediária, ou pré-diabetes, de 6,8 a 16,9%. Usando-se o critério laboratorial ou uso de medicamentos, a prevalência de diabetes foi de 8,4%. A RP ajustada para sexo, idade, escolaridade e região foi menor no sexo masculino (RP = 0,75; IC95% 0,63 - 0,89); aumentou com a idade: 30 a 34 anos (RP=2,32; IC95% 1,33 - 4,07), 40 a 59 anos (RP = 8,1; IC95% 4,86 - 13,46), 60 anos ou mais (RP = 12,6; IC95% 7,1 - 21,0); e a escolaridade elevada foi protetora (RP = 0,8; IC95% 0,6 - 0,9). Maior RP foi encontrada na Região Centro-Oeste (RP = 1,3; IC95% 1,04 - 1,7) e naqueles com sobrepeso (RP = 1,8; IC95% 1,4 - 2,1) e obesidade (RP = 3,3; IC95% 2,6 - 4,1).

Conclusão:

A prevalência de diabetes foi maior no sexo feminino, naqueles com idade maior que 30 anos, em população com baixa escolaridade, com excesso de peso e obesidade. Os critérios laboratoriais são mais fidedignos para o conhecimento da situação real do diabetes no país.

Palavras-chave: Diabetes mellitus; Estado pré-diabético; Hemoglobina A glicada; Técnicas de laboratório clínico; Doenças crônicas não transmissíveis; Obesidade

INTRODUCTION

Diabetes mellitus (DM) is characterized by a heterogeneous group of metabolic disorders resulting from hyperglycemia caused by defects in insulin action, insulin secretion, or both1. It is one of four chronic non-communicable diseases (NCDs) identified as a priority for intervention by the World Health Organization (WHO) and the Strategic Action Plan for Tackling NCDs, 2011-20222.

The world population with DM is estimated at 387million people, and of these, about 80% live in low- and middle-income countries, with a growing proportion of people with DM in younger age groups3. Mortality from DM was estimated at 1.5million in 20123. Accordingto the National Health Survey (Pesquisa Nacional de Saúde - PNS) in 2013, the prevalence of self-reported DM for the Brazilian population 18 years of age and over was 6.2%, with 7% in women and 5.4% in men4.

DM can affect quality of life, with an estimated 89million disability-adjusted life years (DALYS) lost worldwide5. Among the complications of DM are macrovascular (ischemic heart disease, stroke and peripheral arterial disease) and microvascular (retinopathy, nephropathy and neuropathy) diseases6. Because of its numerous comorbidities, complications, and disabilities, DM affects the social and professional lives of affected individuals and entails direct and indirect costs to patients, health systems, and society7.

Glycated hemoglobin (HbA1c)8 was proposed for the diagnosis of DM in 2009. It is a fraction of the hemoglobin (Hb) produced in the presence of hyperglycemia and, thus, the higher the rates of free blood glucose, the higher the proportion of HbA1c9. The HbA1c test has the advantage of estimating the average blood glucose concentration from the past 60 to 90 days, unlike the fasting glucose or glucose tolerance test, which only takes measurements at specific times9.

Population studies based on self-report of diabetes have been conducted in the United States10, Brazil 11,12 and in many other countries. They are used because of their ease, low cost and fast collection9. However, self-reporting may result in reduced estimates due to portions of previously undiagnosed cases. As such, laboratory tests are recommended9. With this in mind, HbA1c is especially efficient as it does not require fasting or glucose challenge testing9.

As a result, between 2014 and 2015, the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística - IBGE) and the Ministry of Health added HbA1c as part of the PNS’ laboratory component in order to capture more reliable estimates of the Brazilian population’s health and disease situation. Thus, the aim of this study was to analyze the prevalence of DM according to different diagnostic criteria in the Brazilian adult population, according to laboratory results from the PNS.

METHODS

The present study was a descriptive, epidemiological survey, and used data from PNS laboratory exams from 2014 to 2015. The PNS is a nationwide household-based, cross-sectional survey that uses three-stage probabilistic samples. The primary sampling units were the census tracts or set of tracts. The secondary units were households, and the tertiary units were the adult residents, aged 18 years or older present in the household. Details on the sampling and weighting processes are provided in the PNS publications on the results 13,14.

In the PNS sample, 81,254 households were selected, of which 69,994 were occupied households. The survey was conducted in 64,348 households and 60,202 adult individuals, selected in each household with equal probability, were interviewed. Given that 25% of the census tracts were selected for laboratory testing and assuming a non-response rate of 20%, the expected number of individuals with laboratory data was 12,000 individuals, approximately 13,14. Tofacilitate the logistics of biological material collection, census tracts were selected based on a probability that was inversely proportional to the difficulty of collection. The selection of the subsample was made with a probability proportional to the inverse distance from the municipality where the primary sampling unit was located and the nearest municipality with 80,000 inhabitants or more, in all of the federal units14. Severalfactors decreased the number of individuals indicated for the laboratory tests, such as the hired laboratory having difficulty locating the address, and the selected resident refusing to perform the biological material collection. Thus, the sample consisted of 8,952 people. Post-stratification weights were estimated according to gender, age, educational level, race/color and geographical macro-region, based on data from residents selected for individual interviews in the initial phase of the PNS.

The PNS was approved by the National Research Ethics Commission (Comissão Nacional de Ética em Pesquisa - CONEP) of the National Health Council (Conselho Nacional de Saúde - CNS), of the Ministry of Health. Participation in the research was voluntary and information was guaranteed to remain confidential. The research participants signed an Informed Consent Form and authorized the collection of laboratory tests.

HbA1c was collected in a tube with ethylenediamine tetra-acetic acid (EDTA) and dosed by high pressure liquid chromatography (HPLC) in a laboratory certified by the National Glycohemoglobin Standardization Program. Peripheral blood collection was performed at any time of the day. No fasting was required.

The WHO9 and the American Diabetes Association(ADA)15 recommend a value of HbA1c ≥ 6.5% for the diagnosis of DM. There are still divergences as to the cutoffs adopted for intermediate hyperglycemia: according to the ADA, the criterion is HbA1c between 5.7 and 6.4%15, according to the International Expert Committee (IEC),8 even though the evidence is still not solid, higher values of 6 to 6.4% indicate a higher risk9. The study also included other cutoff points that refer to the categorization of glycemic control levels in DM15 (ie. 6.5 to 6.9%; 7 to 7.4%; 7.5 to 7.9; 8 to 8.9%; and ≥ 9%). These monitoring points are justified by the following criteria: 6.5 to 6.9% (<7% is the control level recommended as “reasonable” by the ADA)15, 7 to 7.4% and 7.5 to 7.9% (<8% is ADA’s less strict control alternative)15, 8 to 8.9%, and ≥ 9 (≥ 9% uniformly recognized as indicating the need for better control)16.

For the analyzes, a comparison of different diagnostic criteria of DM was initially considered: just laboratory (HbA1c ≥ 6.5%); laboratory or reported medication use (insulin or oral hypoglycemic); laboratory or self-reported having a medical diagnosis of DM; and just self-reported having a medical diagnosis of DM. Subsequently, the prevalence of DM was calculated according to the criteria of having a laboratory diagnosis or being on medication for DM, in the strata of the following sociodemographic characteristics: gender, age, education level, race/color, region and body mass index (BMI). Being <25 kg/m2 was considered to be eutrophic or low weight, being between 25 and 29.9 kg/m2 was considered to be overweight and ≥ 30 kg/m2 was considered to be obese.

Analyzes were performed with Data Analysis and Statistical Software (Stata), version 14. The command survey was used to incorporate the post-stratification weights. The bivariate analysis and prevalence calculations were performed with a 95% confidence interval (95% CI). Prevalence ratios (PR) were calculated using the Poisson regression method with robust crude and adjusted variance for age, gender, education level and region.

RESULTS

A total of 8,952 exams were collected. Four hundred and eleven were not included in the analysis due to collection problems such as insufficient material, hemolysis, sample loss and others. Thus, there remained a total of 8,541 exams for HbA1c analysis.

According to the categories for HbA1c analysis, the presence of DM according to the HbA1c criterion ≥ 6.5% was detected in 6.6% of the adults. It was distributed as follows: 1.9% with HbA1c between 6.5 and 6, 9%; 1.1% with HbA1c between 7 and 7.4%; 0.8% with HbA1c between 7.5 and 7.9%; 1.0% with HbA1c between 8 and 8.9%; and 1.8% with HbA1c ≥ 9%. Fully 76.5% of the total population had normo-range HbA1c. 16.9% had intermediate hyperglycemia according to the ADA criterion (HbA1c 5.7 to 6.4%)15 and 6.8% according to the IEC criterion (HbA1c 6 to 6.4%)8 (Table 1).

Table 1. Glycated hemoglobin categories according to sociodemographic characteristics (n= 8,541). Brazil, National Health Survey (PNS), 2014-2015.  

Categories HbA1c % Sample Male % Female % Total %
< 5.7 6.848 78.5 74.7 76.5
5.7 to 5.9 896 9.4 10.7 10.1
6 to 6.4 566 6.5 7.1 6.8
6.5 to 6.9 175 1.3 2.4 1.9
7 to 7.4 88 0.8 1.3 1.1
7.5 to 7.9 57 0.9 0.8 0.8
8 to 8.9 87 1.1 1.0 1.0
≥ 9 188 1.5 2.0 1.8

Among the 6.6% of the population that was identified by the DM laboratory criterion (HbA1c ≥ 6.5%), the following met the ADA control criteria15: 28.8% of the population had values within the rigid control (HbA1c <7%); an additional 28.8% of the population was also within the most flexible level of glycemic control (HbA1c <8%); and 42.4% had HbA1c ≥ 8% (Table 1).

Using different criteria, the prevalence of DM varied from: 6.6% by laboratory criteria; 8.4% by laboratory criteria or medication use; 9.4% for laboratory criteria or self-reporting a previous medical diagnosis of DM; and 7.5% for the medical diagnosis criterion of self-reported DM. Across all of the criteria, the prevalence was highest among women and in individuals over the age of 30, reaching between 14.2 (for laboratory) and 22.6% (for laboratory or self-reported) of those over 60 years of age (Table 2).

Table 2. Prevalence of diabetes diagnosis mellitus according to different criteria. Brazil, National Health Survey (PNS), 2014-2015. 

Variables Laboratory Laboratory or medicine use Laboratory or self-reported Self-reported
% 95%CI % 95%CI % 95%CI % 95%CI
Total 6.6 5.93 - 7.24 8.4 7.65 - 9.11 9.4 8.63 - 10.14 7.5 6.73 - 8.19
Gender
Female 5.59 4.68 - 6.51 6.90 5.90 - 7.91 7.80 6.74 - 8.86 6.39 5.29 - 7.49
Male 7.48 6.55 - 8.41 9.7 8.65 - 10.74 10.79 9.73 - 11.86 8.33 7.35 - 9.31
Age range (years)
18 to 29 1.45 0.73 - 2.17 1.47 0.75 - 2.19 2.01 1.14 - 2.88 1.44 0.53 - 2.35
30 to 44 3.19 2.26 - 4.13 3.48 2.53 - 4.43 4.00 3.02 - 4.99 2.43 1.60 - 3.26
45 to 59 10.46 8.88 - 12.04 12.60 10.88 - 14.32 13.96 12.21 - 15.70 10.81 9.13 - 12.49
60 or older 14.24 12.21 - 16.26 20.59 18.22 - 22.96 22.66 20.25 - 25.07 18.22 15.95 - 20.50

95%CI: 95% confidence interval.

Within the criterion of laboratory (HbA1c ≥ 6.5%) or reporting medication use (insulin or oral hypoglycemic), the prevalence of DM was 9.7% in women (95% CI 8.65 - 10.74) and 6.9% in men (95% CI 5.90 - 7.91); higher in those 30 years of age and older, and it reached 20.6% (95% CI 18.22 - 22.96) in those over 60 years of age; and in the Southeast and Midwest population. A total of 8.5% (95% CI 7.3 - 9.8) of overweight people and 16.9% (95% CI 14.7-19.0) of obese people had DM (Table 3).

Table 3. Prevalence of diabetes mellitus (glycated hemoglobin ≥ 6.5% or medication use), according to sociodemographic characteristics and body mass index. Brazil, National Health Survey (PNS), 2014-2015. 

Variables % 95%CI
Total 8.4 7.6 - 9.1
Gender
Female 9.7 8.6 - 10.7
Male 6.9 5.9 - 7.9
Age range (years)
18 to 29 1.47 0.75 - 2.19
30 to 44 3.48 2.53 - 4.43
45 to 59 12.60 10.88 - 14.32
60 or older 20.59 18.22 - 22.96
Education level
None 12.35 11.03 - 13.66
Elementary school only 7.41 5.62 - 9.20
Completed high school 5.33 4.39 - 6.27
Race/color
White 8.42 7.28 - 9.55
Dark skinned black 10.26 7.47 - 13.05
Light skinned black 7.93 6.95 - 8.91
Other 7.70 3.35 - 12.06
Region
North 6.29 5.25 - 7.33
Northeast 7.64 6.71 - 8.57
Southeast 9.29 7.87 - 10.71
South 7.43 5.87 - 8.98
Center West 9.39 7.55 - 11.24
Body mass index
Underweight/normal 4.03 3.25 - 4.81
Overweight 8.54 7.32 - 9.77
Obese 16.86 14.68 - 19.03

95%CI: 95% confidence interval.

Table 4 shows the crude and adjusted prevalence ratios (PRad) according to age, gender, education level, race/color, region, and BMI. Men had lower PR (PRad = 0.75; 95% CI 0.63-0.89). The prevalence increased with age: 30 to 44 years old (PRad = 2.32; 95% CI 1.33- 4.07), 45 to 59 years old (PRad = 8.1; 95% CI 4.8 - 13.5), 60 years old and older (PRad = 12.7; 95% CI 7.61 - 21.0). The highest educational level was protective (PRad = 0.79; 95% CI 0.64 - 0.97) and prevalence was higher in the Midwest (PRad = 1.34; 95% CI 1.04 - 1.72). The following remained positively associated with DM after the adjustment: being overweight (PRad = 1.78; 95% CI 1.4 - 2.26) and being obese (PRad = 3.3; 95% CI 2.6 - 4.14) were also associated with the presence of diabetes (Table 4).

Table 4. Crude and adjusted prevalence of diabetes mellitus (glycated hemoglobin ≥ 6.5% or medicine use), according to sociodemographic characteristics and body mass index. Brazil, National Health Survey (PNS), 2014-2015. 

Variables PRcrude 95%CI PRadjusted* 95%CI
Gender
Female 1.00 1.00
Male 0.71 0.59 - 0.85 0.75 0.63 - 0.89
Age range (years)
18 to 29 1.00 1.00
30 to 44 2.36 1.35 - 4.13 2.32 1.33 - 4.07
45 to 59 8.56 5.16 - 14.21 8.09 4.86 - 13.46
60 or older 13.99 8.47 - 23.10 12.65 7.61 - 21.00
Education level
None 1.00 1.00
Elementary school only 0.60 0.46 - 0.78 1.07 0.83 - 1.39
Completed high school 0.43 0.35 - 0.53 0.79 0.64 - 0.97
Race/color
White 1.00 1.00
Dark skinned black 1.22 0.90 - 1.65 1.21 0.89 - 1.65
Light skinned black 0.94 0.78 - 1.13 1.09 0.89 - 1.32
Other 0.92 0.51 - 1.64 0.91 0.49 - 1.72
Region
North 1.00 1.00
Northeast 1.21 0.99 - 1.49 1.05 0.86 - 1.28
Southeast 1.48 1.18 - 1.85 1.18 0.95 - 1.48
South 1.18 0.90 - 1.54 0.96 0.74 - 1.25
Center West 1.49 1.16 - 1.93 1.34 1.04 - 1.72
Body mass index
Underweight/normal 1.00 1.00
Overweight 2.12 1.67 - 2.69 1.78 1.41 - 2.26
Obese 4.18 3.32 - 5.27 3.30 2.63 - 4.14

PR: prevalence ratio; * adjusted for age, gender, education level and region; 95%CI: 95% confidence interval.

DISCUSSION

The study found that 6.6% of adults have glycated hemoglobin ≥ 6.5%; and the proportion of intermediate hyperglycemia, or pre-diabetes, was 6.8% when defined by the criteria of the IEC8 and 16.9% when defined by the criteria of the ADA15. The prevalence of DM was higher when simultaneous criteria were adopted, such as the association of laboratory criteria or drug use, or laboratory or self-reported criteria. In all of the criteria, women had a higher prevalence. Prevalence increased with age, reaching about one fifth of the elderly. Using the criterion of altered glycated hemoglobin or medication use, after adjustments for variables such as gender, age, education level and region, PRs were higher for females, the elderly, those with only an elementary level education, those living in the Center-West, and those overweight or obese.

In Brazil, estimates of DM prevalence are generally self-reported. The Telephone Survey Risk Factors and Protection Surveillance System (Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico - Vigitel) estimates that there has been a rise in prevalence in the capital cities of Brazil, increasing from 5.5% in 2006 to 7.6% in 201717. The PNS, using the same criterion, identified a prevalence of 6.2% of the Brazilian population in 2013, which would represent a population contingent of about nine million patients with DM18.

The study also points to the high proportion of hyperglycemia, affecting about one fifth of the elderly. These data demonstrate the importance of controlling hyperglycemia in order to avoid the vascular and systemic effects of DM1.

The study identified a predominance of DM among women. The literature highlights aspects such as gestational diabetes and hormonal changes in menopause, increasing abdominal adiposity, as justifications for a greater frequency among women19,20. However,in several countries such as Australia21, England22 and in Brazil, the Longitudinal Adult Health Study (Estudo Longitudinal de Saúde do Adulto - ELSA)23, using laboratory criteria, detected a higher prevalence of DM among men. Therefore, this topic still needs to be further investigated.

As for age, the elderly have a higher prevalence, which may be justified by the physiological changes inherent in the aging process 24,25. DM in the elderly is related to a higher risk of premature death, a greater association with other comorbidities and major geriatric syndromes, as well as impairments regarding functional capacity, autonomy and quality of life26. It is important to highlight that DM, as well as the metabolic syndrome, which is associated with cardiovascular diseases in adulthood, is increasing in young populations. The increase in the prevalence of obesity in adolescence in recent years, partly due to inadequate diet and physical inactivity, probably explains the progress of the disease in young populations 27,28.

Being overweight affects more than half of the Brazilian adult population and obesity effects about 17.4%. This is suggestive of a lifestyle pattern made up of fatty foods, sugars and physical inactivity29. The study pointed to a strong association between being overweight, being obese and DM. The pathophysiological mechanisms that result in the association between obesity and DM are complex and multifactorial23. These include increased circulating free fatty acids, decreased adiponectin, and adipose tissue secretion of cytokines that ultimately exacerbate insulin resistance and lead to the subsequent exhaustion of pancreatic insulin, aggravating the condition 23.24.

Regarding the higher frequency of DM in low-educated populations, this association has already been found in Brazil30,31,32 and in other countries33. Educational level is an important socioeconomic indicator and implies different risks in the health and disease process, especially due to vulnerable living environments, poor access to health services and the most unfavorable practices with regard to food, physical activity, body care and prevention of diseases 31,33. Although there are still problems regarding access to health services, the PNS indicated that patients with DM have access to medical care (70%), specialist consultations (83.3%) and medicines (80.2%), and more than half receive them through the Popular Pharmacy Program18. Additionally, there are special protocols for the care of those with DM in the Unified Health System (SUS). They aim to give more attention to people with the disease, by offering comprehensive, long-term care34. These data reveal the importance of SUS in reducing health inequities and in providing access to care 18,34.

Among the regions of Brazil, the highest PR was found in the Midwest, similar to self-reported data, which point to more diagnoses of DM in the Midwest, South and Southeast 17,18.

The study also found a high prevalence of pre-diabetes, with a similar behavior of increasing with age, reaching approximately one sixth of the elderly (data not shown). Similarly, studies performed by ELSA-Brasil23 also identified high frequencies of intermediate hyperglycemia, ranging from 16.1 to 52.6%, depending on the definition used. Thesedata increase the need for attention and monitoring of populations, especially those risk factors such as cardiovascular disease, obesity, physical inactivity, and genetic traits. The therapeutic approach of detected cases, the monitoring and control of blood glucose, as the health education process are fundamental for preventing complications and maintaining patients’ quality of life35.

Different levels of HbA1c have also been identified. The ADA15 explains that for individuals already diagnosed with DM, HbA1c should be kept below 7%, which would protect against the onset and progression of microvascular complications of DM and neuropathy. Individuals with long-term DM who already have chronic complications (ocular, renal, atherosclerosis, and neuropathy changes) may have less stringent control targets of HbA1c, up to 8%15. In the present study, about 60% of those with HbA1c ≥ 6.5% had values below 8%, however, these are preliminary data, as no other comorbidities or the use of medication to define DM control were investigated.

Among other study limitations, the rate of failure to obtain laboratory values was high, especially due to the contracted laboratory’s difficulty in locating the addresses. However, post-stratification weights allow us to infer estimates for the general population.

CONCLUSION

This is the first study to analyze the prevalence of DM using laboratory data from a representative sample of the Brazilian population, which will serve as a baseline for future studies.

The study found up to one-tenth of the population had DM, according to the adopted criterion. The proportion of pre-diabetes can reach up to a sixth of the population. Laboratory testing performed by the PNS contributes to health surveillance and health care in SUS and can support the monitoring of the WHO Strategic Action Plan for Tackling NCDs and the goal of reducing premature mortality from NCDs.

REFERENCES

1. World Health Organization, International Diabetes Federation. Definition and diagnosis of diabetes mellitus and intermediate hyperglycaemia: report of a WHO/IDF consultation [Internet]. Genebra: World Health Organization; 2006 [acessado em 05 jun. 2018]. Disponível em: Disponível em: http://www.who.int/iris/handle/10665/43588Links ]

2. Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Análise de Situação de Saúde. Plano de Ações Estratégicas para o Enfrentamento das Doenças Crônicas Não Transmissíveis (DCNT) no Brasil 2011-2022. Brasília: Ministério da Saúde; 2011. [ Links ]

3. International Diabetes Federation. IDF Diabetes Atlas. 8ª ed. International Diabetes Federation; 2017. 145p. [ Links ]

4. Iser BP, Stopa SR, Chueiri OS, Szwarcwald CL, Malta DC, Monteiro HOC, et al. Prevalência de diabetes autorreferido no Brasil: resultados da Pesquisa Nacional de Saúde 2013. Epidemiol Serv Saúde [Internet] 2015 [acessado em 5 jun. 2018]; 24(2): 305-14. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2237-96222015000200305&lng=en http://dx.doi.org/10.5123/S1679-49742015000200013 [ Links ]

5. World Health Organization (WHO). Global status report on noncommunicable diseases [Internet]. Genebra: World Health Organization ; 2014 [acessado em 3 jan. 2018]. Disponível em: Disponível em: http://apps.who.int/iris/bitstream/10665/148114/1/9789241564854_eng.pdf?ua=1Links ]

6. Nagpal J, Bhartia A. Cardiovascular risk profile of subjects with known diabetes from the middle- and high-income group population of Delhi: the DEDICOM survey. Diabet Med [Internet]. 2008 [acessado em 3 jan. 2018]; 25(1): 27-36. Disponível em: Disponível em: https://www.ncbi.nlm.nih.gov/pubmed/18028441 http://dx.doi.org/10.1111/j.1464-5491.2007.02307.x [ Links ]

7. Malta DC, Bernal RTI, Iser BPM, Szwarcwald CL, Duncan BB, Schmidt MI. Fatores associados ao diabetes autorreferido segundo a Pesquisa Nacional de Saúde, 2013. Rev Saúde Pública [Internet]. 2017 [acessado em 4 out. 2018]; 51(Supl. 1): 12s. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102017000200312&lng=en http://dx.doi.org/10.1590/s1518-8787.2017051000011 [ Links ]

8. The International Expert Committee. International expert committee report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care 2009; 32(7): 1327-34. [ Links ]

9. World Health Organization. Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus [Internet]. Genebra: World Health Organization ; 2011 [acessado em 21maio 2013]. Disponível em: Disponível em: http://www.who.int/diabetes/publications/report-hba1c_2011.pdfLinks ]

10. Danaei G, Friedman AB, Oza S, Murray CJ, Ezzati M. Diabetes prevalence and diagnosis in US states: analysis of health surveys. Popul Health Metr 2009; 7: 16. http://dx.doi.org/10.1186/1478-7954-7-16Links ]

11. Malerbi DA, Franco LJ. Multicenter study of the prevalence of diabetes mellitus and impaired glucose tolerance in the urban Brazilian population aged 30-69 yr. The Brazilian Cooperative Group on the Study of Diabetes Prevalence. Diabetes Care 1992; 15(11): 1509-16. https://doi.org/10.2337/diacare.15.11.1509Links ]

12. Goldenberg P, Franco LJ, Pagliaro H, Silva R, Santos CA. Self-reported diabetes mellitus in the city of Sao Paulo: prevalence and inequality. Cad Saúde Pública [Internet]. 1996 [acessado em 3 jan. 2018]; 12(1): 37-45. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X1996000100014 http://dx.doi.org/10.1590/S0102-311X1996000100014 [ Links ]

13. Szwarcwald CL, Malta DC, Pereira CA, Vieira MLFP, Conde WL, Souza Júnior PRB, et al. Pesquisa Nacional de Saúde no Brasil: concepção e metodologia de aplicação. Ciênc Saúde Coletiva [Internet]. 2014 [acessado em 4 jan. 2018]; 19(2): 333-42. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232014000200333 http://dx.doi.org/10.1590/1413-81232014192.14072012 [ Links ]

14. Souza-Júnior PRB, Freitas MPS, Antonaci GA, Szwarcwald CL. Desenho da amostra da Pesquisa Nacional de Saúde 2013. Epidemiol Serv Saúde [Internet]. 2015 [acessado em 5 jan. 2018]; 24(2): 207-16. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2237-96222015000200207&lng=en http://dx.doi.org/10.5123/S1679-49742015000200003 [ Links ]

15. American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2018. Diabetes Care 2018; 41 (Supl.1): S13-S27. https://doi.org/10.2337/dc18-S002Links ]

16. Davies MJ, D’Alessio DA, Fradkin J, Kernan WN, Mathieu C, Mingrone G, et al. Management of Hyperglycemia in Type 2 Diabetes, 2018. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) Diabetes Care 2018; 41(12): 2669-701. https://doi.org/10.2337/dci18-0033Links ]

17. Brasil. Ministério da Saúde. Sistema de Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por inquérito telefônico (Vigitel) 2017. Brasília: Ministério da Saúde ; 2017. [ Links ]

18. Malta DC, Iser BPM, Chueiri PS, Stopa SR, Szwarcwald CL, Schmidt MI, et al. Cuidados em saúde entre portadores de diabetes mellitus autorreferido no Brasil, Pesquisa Nacional de Saúde, 2013. Rev Bras Epidemiol [Internet]. 2015 [acessado em 5 jan. 2018]; 18(Supl. 2): 17-32. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2015000600017&lng=en http://dx.doi.org/10.1590/1980-5497201500060003 [ Links ]

19. Kim C. Does menopause increase diabetes risk? Strategies for diabetes prevention in midlife women. Womens Health 2012; 8(2): 155-67. http://dx.doi.org/10.2217/whe.11.95Links ]

20. Tsai YJ, Wu MP, Hsu YW. Emerging health problems among women: Inactivity, obesity, and metabolic syndrome. Gynecology and Minimally Invasive Therapy. 2014; 3(1): 12-4. https://doi.org/10.1016/j.gmit.2013.07.005Links ]

21. Australian Government. Australian Institute of Health and Welfare. How many Australians have diabetes? [Internet]. Austrália: Australian Institute of Health and Welfare; 2018 [acessado 05 jun. 2018]. Disponível em: Disponível em: https://www.aihw.gov.au/reports/diabetes/diabetes-compendium/contents/how-many-australians-have-diabetesLinks ]

22. Governo da Inglaterra. Public Health England. 3.8million people in England now have diabetes [Internet]. Inglaterra: Governo da Inglaterra; 2016 [acessado em 05 jun. 2018]. Disponível em: Disponível em: https://www.gov.uk/government/news/38-million-people-in-england-now-have-diabetesLinks ]

23. Schmidt MI, Hoffmann JF, Diniz M de FS, Lotufo PA, Griep RH, Bensenor IM, et al. High prevalence of diabetes and intermediate hyperglycemia - The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Diabetol Metab Syndr [Internet]. 2014 [acessado em 5 jan. 2018]; 6(1): 123. Disponível em: Disponível em: https://dmsjournal.biomedcentral.com/articles/10.1186/1758-5996-6-123 https://doi.org/10.1186/1758-5996-6-123 [ Links ]

24. Oliveira JEP, Vencio S. Diretrizes da Sociedade Brasileira de Diabetes, 2013-2014 [Internet]. Sociedade Brasileira de Diabetes; 2014 [acessado em 5 jan. 2018]. Disponível em: Disponível em: http://www.sgc.goias.gov.br/upload/arquivos/2014-05/diretrizes-sbd-2014.pdfLinks ]

25. Passos VM, Barreto SM, Diniz LM, Lima-Costa MF. Type 2 diabetes: prevalence and associated factors in a Brazilian community--the Bambui health and aging study. Sao Paulo Med J [Internet]. 2005 [acessado em 5 jan. 2018]; 123(2): 66-71. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-31802005000200007 http://dx.doi.org/10.1590/S1516-31802005000200007 [ Links ]

26. Silva Ramos RSP, Marques AP de O, Ramos VP, Borba AK de OT, Aguiar AMA de, Leal MCC. Fatores associados ao diabetes em idosos assistidos em serviço ambulatorial especializado geronto-geriátrico. Rev Bras Geriatr Gerontol [Internet]. 2017 [acessado em 23mar. 2018]; 20(3): 363-73. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1809-98232017000300363&lng=en http://dx.doi.org/10.1590/1981-22562017020.160145 [ Links ]

27. Goran MI, Davis J, Kelly L, Shaibi G, Spruijt-Metz D, Monica Soni S, et al. Low Prevalence of Pediatric Type 2 Diabetes: Where’s the Epidemic? J Pediatr [Internet] 2008 [acessado em 5 jan. 2018]; 152(6): 753-55. Disponível em: Disponível em: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2888282/ http://dx.doi.org/10.1016/j.jpeds.2008.02.004 [ Links ]

28. Moraes ACF, Fulaz CS, Netto-Oliveira ER, Reichert FF. Prevalência de síndrome metabólica em adolescentes: uma revisão sistemática. Cad Saúde Pública [Internet] 2009 [acessado em 5 jan. 2018]; 25(6): 1195-202. Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2009000600002 http://dx.doi.org/10.1590/S0102-311X2009000600002 [ Links ]

29. Vidigal FC, Bressan J, Babio N, Salas-Salvadó J. Prevalence of metabolic syndrome in Brazilian adults: a systematic review. BMC Public Health [Internet] 2013 [acessado em 5 jan. 2018]; 13: 1198. Disponível em: Disponível em: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3878341/ http://dx.doi.org/10.1186/1471-2458-13-1198 [ Links ]

30. Malta DC, Andrade SC, Claro RM, Bernal RTI, Monteiro CA. Evolução anual da prevalência de excesso de peso e obesidade em adultos nas capitais dos 26 estados brasileiros e no Distrito Federal entre 2006 e 2012. Rev Bras Epidemiol 2014(Supl.); 267-76. http://dx.doi.org/10.1590/1809-4503201400050021Links ]

31. Lyra R, Silva RS, Montenegro Jr. RM, Matos MVC, Cézar NJB, Maurício-da-Silva L. Prevalence of diabetes and associated factors in an urban adult population of low educational level and income from the Brazilian Northeast wilderness. Arq Bras Endocrinol Metab 2010; 54(6): 560-6. http://dx.doi.org/10.1590/S0004-27302010000600009Links ]

32. Iser BP, Malta DC, Duncan BB, de Moura L, Vigo A, Schmidt MI. Prevalence, correlates, and description of self-reported diabetes in Brazilian capitals - results from a telephone survey. PLoS One 2014; 9(9): e108044. https://doi.org/10.1371/journal.pone.0108044Links ]

33. Phaswana-Mafuya N, Peltzer K, Chirinda W, Musekiwa A, Kose Z, Hoosain E, et al. Self-reported prevalence of chronic non-communicable diseases and associated factors among older adults in South Africa. Glob Health Action 2013; 6: 1-7. https://dx.doi.org/10.3402%2Fgha.v6i0.20936Links ]

34. Stopa SR, Malta DC, Monteiro CN, Szwarcwald CL, Goldbaum M, Cesar CLG. Acesso e uso de serviços de saúde pela população brasileira, Pesquisa Nacional de Saúde 2013. Rev Saúde Pública [Internet]. 2017 [acessado em 7 jan. 2018]; 51(Supl. 1). Disponível em: Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102017000200308&lng=pt http://dx.doi.org/10.1590/s1518-8787.2017051000074 [ Links ]

35. Brasil. Ministério da Saúde. Estratégias para o cuidado da pessoa com doença crônica: diabetes mellitus [Internet]. Brasília: Ministério da Saúde ; 2013 [acessado em 5 jun. 2018]. 160p. Disponível em: Disponível em: http://bvsms.saude.gov.br/bvs/publicacoes/estrategias_cuidado_pessoa_diabetes_mellitus_cab36.pdfLinks ]

Financial support: Health Surveillance Secretariat, Ministry of Health (TED 66).

Received: December 18, 2018; Revised: February 23, 2019; Accepted: March 01, 2019

Corresponding author: Deborah Carvalho Malta. Avenida Professor Alfredo Balena, 190, Santa Efigênia, CEP 30130-100, Belo Horizonte, MG, Brazil. E-mail: dcmalta@uol.com.br

*

in memoriam.

Conflict of interests: nothing to declare

Author contributions: D.C. Malta participated in the design and planning of the PNS laboratory study, the study planning, design, analysis and interpretation of data. They also drafted the first version of the manuscript and approved the final version of the manuscript. B.B. Duncan and M.I. Schmidt participated in the study planning, data analysis and interpretation. They also performed a critical review of the content and approved the final version of the manuscript. C.L Szwarcwald participated in the design and planning of the PNS laboratory study, the study planning, design, analysis and interpretation of data. She also approved the final version of the manuscript. R.T. I. Bernal and I.E. Machado participated in the planning of the study, the statistical analysis, data analysis and interpretation, and they both approved the final version of the manuscript. L.G. Rosenfeld coordinated the field collection, the design and planning of the PNS laboratory study, participated in defining laboratory parameters, designing the study, and editing. A.C Pereira participated in the planning of the PNS laboratory study, designing the study, and helping with the analysis. They also performed a critical review of the content and approved the final version of the manuscript. A.G. Silva, G.N. Damacena and S.R. Stopa contributed to the analysis and interpretation of the data, as well as the critical review of the content and approval of the final version of the manuscript.

Creative Commons License Este é um artigo publicado em acesso aberto sob uma licença Creative Commons