Characterization of users at risk of developing diabetes: a cross-sectional study

Caracterización de usuarios en riesgo de desarrollar diabetes: un estudio transversal

ABSTRACT

Objective:

To characterize the profile of users at risk of developing diabetes mellitus type 2 according to sociodemographic and clinical variables.

Method:

Cross-sectional study, descriptive, quantitative approach conducted with 266 users of Basic Care. Inferential statistics analysis, calculating the crude prevalence ratio with confidence interval of 95% and Kruskal-Wallis test, and application of the multivariate technique simple Correspondence Analysis.

Results:

It was noted that 83.1% were women and 36.4% frequented the Family Health Unit from 1 to 5 years. Regarding the factors associated with diabetes mellitus type 2, 66.5% of the users were overweight and 77.9% were rated with central obesity. The great majority, 77.4%, did not practice physical activities and 21.1% had altered glycemia.

Conclusion:

The results showed that many risk factors for developing diabetes mellitus type 2 were among the population of the study.

Descriptors:
Diabetes Mellitus Type 2; Risk Factors; Primary Prevention; Nursing; Primary Health Care

RESUMEN

Objetivo:

Caracterizar el perfil de usuarios en riesgo de desarrollar diabetes mellitus tipo 2 de acuerdo con las variables sociodemográficas y clínicas.

Método:

Estudio transversal, descriptivo, de abordaje cuantitativo realizado con 266 usuarios de la Atención Básica. Análisis estadístico inferencial, con el cálculo de las razones de prevalencias brutas con intervalo de confianza del 95% y la prueba de Kruskal-Wallis, y la aplicación de la técnica multivariada Análisis de Correspondencia simple.

Resultados:

Se constató que el 83,1% eran mujeres y el 36,4% frecuentaban la Unidad de Salud de la Familia de 1 a 5 años. Sobre los factores asociados a la diabetes mellitus tipo 2, el 66,5% de los usuarios estaba con sobrepeso; el 77,9% fue clasificado con obesidad central; la gran mayoría, el 77,4% no practicaba actividad física y el 21,1% tenía la glucemia alterada.

Conclusión:

Los resultados mostraron que diversos factores de riesgo para el desarrollo de la diabetes mellitus tipo 2 estuvieron presentes en la población del estudio.

Descriptores:
Diabetes Mellitus Tipo 2; Factores de Riesgo; Prevención Primaria; Enfermería; Atención Primaria a la Salud

RESUMO

Objetivo:

Caracterizar o perfil de usuários em risco de desenvolver diabetes mellitus tipo 2 de acordo com as variáveis sociodemográficas e clínicas.

Método:

Estudo transversal, descritivo, de abordagem quantitativa realizado com 266 usuários da Atenção Básica. Análise estatística inferencial, com o cálculo das razões de prevalências brutas com intervalo de confiança de 95% e o teste de Kruskal-Wallis e a aplicação da técnica multivariada Análise de Correspondência simples.

Resultados:

Constatou-se que 83,1% eram mulheres e 36,4% frequentavam a Unidade de Saúde da Família de 1 a 5 anos. Quanto aos fatores associados ao diabetes mellitus tipo 2, 66,5% dos usuários estavam com excesso de peso 77,9% foram classificados com obesidade central; a grande maioria, 77,4% não praticava exercício físico, 21,1% possuíam glicemia alterada.

Conclusão:

Os resultados mostraram que vários fatores de risco para o desenvolvimento do diabetes mellitus tipo 2 estiveram presentes na população do estudo.

Descritores:
Diabetes Mellitus Tipo 2; Fatores de Risco; Prevenção Primária; Enfermagem; Atenção Primária à Saúde

INTRODUCTION

Diabetes mellitus (DM) is a worldwide disease that does not choose the age or social condition of the individual, causing lifestyle and body changes in the person affected⁽¹⁾. It is considered a major problem for the Public Health in the 21st century, resulting in prevalence and incidence worldwide concern⁽²⁾.

International Diabetes Federation data indicate that in 2015, in Brazil, there was a predominance of 14.3 million people with DM and it is estimated that for the year 2040 the population will be of 23.2 million⁽³⁾.

Diabetes mellitus type 2 (DM2) is 90% to 95% of the global population cases and its factors are related to overweight and heredity⁽⁴⁾. It is considered a chronic disease, with trend in young adults that have sedentary lifestyle and dietary change, consuming processed and fatty foods⁽⁵⁾.

For the International Diabetes Federation, the risk factor for DM2 are: excessive height, family history of diabetes, unhealthy diet, increasing age, high blood pressure, ethnicity, physical inactivity, glucose intolerance, gestational DM history and malnutrition during pregnancy⁽⁶⁾.

The Ministry of Health recommends the tracking of people at risk of developing DM2, in the Basic Health Care, carried out by the nurse in the nursing appointment⁽⁷⁾.

The Basic Health Care, also called Primary Health Care, is an articulated set of health actions that operates in the determinants and conditioning of health, individually and collectively, adding health promotion, protection and rehabilitation actions. It is guided by the principles of the Unified Health System (SUS): universality, equity and integrality; and is the first entrance to the health services, using the Basic Health Units as working strategy⁽⁸⁾.

The Basic Health Units/ Family Health Units (UBS/USF) are centers installed close to the residences and workplaces. They play an important role in ensuring people access to a quality health care, against health population needs⁽⁸⁾.

Researches focused on identifying risk factors for DM2 were conducted with college student^(5,9), children⁽¹⁰⁾, teenagers⁽¹¹⁾ and adults⁽¹²⁾, which shows the concern of scholars about this subject.

The interest in making a study about the profile that characterizes the population at risk of developing diabetes mellitus 2 in Basic Health care is based on the need to identify characteristics and behavior of risk, providing subsidies for planning and implementation of directed intervention policies that make it possible to prevent the disease development. It is stated that the sociodemographic and clinical characteristics are factors that increase the risk of developing diabetes mellitus type 2 in users of the Basic Care.

OBJECTIVE

To characterize the profile of users at risk of developing DM2 according to sociodemographic and clinical variables.

METHOD

Ethical aspects

The study considered all ethical precepts of the Resolution 466/2012 and Resolution 311/2007 of the COFEN, being approved by the Research Ethics Committee (CEP) of the Health Sciences Department, of Universidade Federal da Paraíba (UFPB), Brazil. All participants signed and informed consent formed in two copies.

Design, study location and period

This is a cross-sectional study, descriptive, with quantitative approach, conducted in 21 Family Health Units in the city of João Pessoa, Paraíba, Brazil, from April to June 2016.

Samples, inclusion and exclusion criteria

To select the participants, it was used the non-probability sampling technique by convenience. To identify the sample size was used the significance level of 5%. The sampling error was set at 6%. According to the IBGE (Brazilian Institute of Geography and Statistics) data, individuals between 20 and 59 years old, in 2014, represented 56%, excluding the prevalence of people with diabetes that, according to the 2014 VIGITEL data, was of 6.9%. Therefore, in the category of the study interest was considered the prevalence of 52.3%⁽¹³⁾.

The target population of the study comprised 134,091 people, being the sample size n calculated by:

$\mathit{n}=\frac{\mathit{N}·\mathit{p}·\mathit{q}·{\left({\mathit{Z}}_{\frac{\mathit{\alpha }}{2}}\right)}^2}{\mathit{p}·\mathit{q}{\left({\mathit{Z}}_{\frac{\mathit{\alpha }}{2}}\right)}^2+\left(\mathit{N}-1\right){\mathit{E}}^2}=\frac{134.091·0,523·\left(1-0,523\right)·{\left(1,96\right)}^2}{0,523·\left(1-0,523\right)·{\left(1,96\right)}^2+\left(134.091-1\right)·0,{06}^2}=265,7$

Where N is the population size, p is the prevalence of people aged between 20 and 59 years and other than people with DM, refers to the accumulated value according to normal distribution table that considers the significance level adopted, which was of 5% in this study. E, is the sampling error that, in this study, was of 6%. Through the calculation, the sample size was 266 people.

To obtain the sample, was considered the following inclusion criteria: to be between 20 and 59 years old, registered in the USB and be there at the time of collection. Excluded from the sample: pregnant women, individuals living in the countryside and with confirmed diagnosis of diabetes mellitus.

Study protocol

For data collection, it was used a form containing sociodemographic (gender, color/race, age, marital status, education, profession, income, income value and time that they frequent the unit), anthropometric and clinical (weight, height, physical inactivity, Body Mass Index (BMI), central obesity and altered glycemia) aspects. Trained staff conducted the interviews in a private place previously agreed between the research team and the participants.

It was also used a digital scale with capacity of 150 kg and accuracy of 0.1 kg to measure the weight and a non-elastic tape measure with maximum range of 2m, fixed to the wall, to measure the height. The users were told to remove their shoes, keep upright, still and with flattened hands over their thighs and head adjusted to the Frankfurt plan. It was measured the abdominal circumference with a non-elastic tape measure placed over the skin at the midpoint between the last rib and the upper edge of the iliac crest at the end of expiration, as recommended by the Ministry of Health⁽¹⁴⁾. To analyze the results, was considered: physical inactivity (understood as physical practice under 30 minutes per day and less than 5 times per week)⁽¹⁵⁾, overweight (overweight category with BMI between 25.0 and 29.9 kg/m2 and obese category with BMI over 30 kg/m2), central obesity (waist circumference over 102 cm in men and over 88 cm in women)⁽⁶⁾ and altered glycemia over 110 mg/dl. According to the World Health Organization recommendation released by the Ministry of Health, the BMI is defined as the body mass divided by the square of the body height⁽¹⁶⁾. The glycemia value was reported by the participants, being proved by laboratory tests for the last six months added to the medical reports. According to the Ministry of Health, the plasma glycemia is shown as altered in values from 110 to 126 mg/dl⁽⁷⁾.

Analysis of results and statistics

The obtained data were listed in a spreadsheet of the software Microsoft Excel, through double typing and further validation, in order to control possible mistakes and then exported to the software Statistical Package for Science Social (SPSS), version 20.0. To present and analyze the results it was used the descriptive statistics for frequency calculation, in absolute value and percentage. To compare associated characteristics at risk of DM2, it was used the inferential statistics, calculating the crude prevalence ratio (PR) with confidence interval of 95% (CI). In case of relation between time of USF and age, it was used the Kruskal-Wallis test and applied the multivariate technique simple correspondence analysis for double entrance tables (two variable cross).

RESULTS

According to the sociodemographic variables listed in table 1, the data show that of 266 interviewed users, 83.1% were women, 59.4% aged less than 45 years, 42.0% have full high school, 51.0% self-reported brown, 54.1% were single/divorced/widowed/separated, 74.5% had income, 57.0% had a monthly income value from 1 to 3 minimum wages, 36.4% frequent the USF for the period from 1 to 5 years, 49% have a profession classified as others.

Table 1
Distribution of users in the Family Health Units, according to sociodemographic characteristics, in the city of João Pessoa, Paraíba State, Brazil, 2016

Variables	n	%	RP*	CI** - 95%
Gender
Female	221	83.1	1	-
Male	45	16.9	0.84	0.72 - 0.99
Age
<45	158	59.4	1	-
45 to 54	76	28.5	1.36	1.12 - 1.65
55 to 59	32	12.2	1.88	1.26 - 2.80
Education
Illiterate/Literate/Incomplete Elementary Education	66	25.0	1	-
Full Elementary Education/Incomplete High School	51	19.0	0.83	0.66 - 1.06
Full High School	111	42.0	0.89	0.72 - 1.11
Incomplete Higher Education/Full Higher Education	38	14.0	0.81	0.63 - 1.03
Ethnicity
White	85	32.0	1	-
Black	31	12.0	1.29	0.91 - 1.82
Brown	136	51.0	0.91	0.77 - 1.07
Marital status
Single/Divorced/Widowed/Separated	144	54.1	1	-
Married/common-law marriage	122	45.9	1.05	0.90 - 1.22
Income
Without income	68	25.5	1	-
With Income	198	74.5	0.85	0.85 - 1.20
Amount
Less than 1 minimum wage	47	18.0	1	-
One to Three	151	57.0	1.10	0.91 - 1.33
USF time***
< 1 year	38	14.2	1	-
1 to 5	97	36.4	0.88	0.70 - 1.13
6 to 10	59	22.1	0.88	0.68 - 1.13
11 to 15	47	18.0	1.11	0.81 - 1.52
>15	25	9.3	1.22	0.81 - 1.84
Profession
Civil Servant	38	14.2	1	-
Self-employed	52	19.5	0.90	0.68 - 1.19
Others	129	49.0	0.88	0.69 - 1.14

• Note:
• ^*
  PR - Prevalence Ratio;
• ^**
  CI - Confidence Interval;
• ^***
  USF - Family Health Unit.

Regarding the factors associated with DM2, 66.5% of the users were overweight, being 34.5% classified as overweight and 32.0% as obesity. In relation to waist circumference, 77.9% were classified as central obesity. The great majority, 77.4%, did not practice physical activities and 21.1% had high glycemia as presented in table 2. To explain the relation between time of USF and age, it was used the Kruskal-Wallis test in the Table 3.

Table 2
Distribution of users in the Family Health Units, according to clinical characteristics, in the city of João Pessoa, Paraíba State, Brazil, 2016

Clinical variables	n	%	RP*	CI** - 95%
BMI***
< 25	89	33.5	1	-
25 to 30	92	34.5	1.22	1.11 a 1.41
> 30	85	32.0	2.49	1.90 a 3.26
Waist circumference
M < 94 / F < 80	59	21.9	1	-
M 94 a 102 / F 80 a 88	62	23.4	1.07	1.01 a 1.16
M > 102 / F > 88	145	54.5	1.90	1.62 a 2.23
Physical activity
1 = Yes	60	22.6	1	-
2 = No	206	77.4	1.26	1.09 a 1.45
Hyperglycemia
1 = No	210	78.9	1	-
2 = Yes	56	21.1	2.04	1.46 a 2.84

• Note:
• ^*
  PR - Prevalence Ratio;
• ^**
  CI - Confidence Interval;
• ^***
  BMI - Body Mass Index; M - Male; F - Female.

Table 3
Comparison of users age with time and frequency in the Family Health Units, in the city of João Pessoa, Paraíba State, Brazil, 2016

Time of USF*	People	Age		K-W***
		Average	SD**	p value
< 1 year	38	36.84	10.17	0.004
1 to 5	97	40.52	11.09
6 to 10	59	41.19	8.52
11 to 15	47	42.85	10.94
> 15	25	46.84	10.63

• Note: USF* - Family Health Unit; SD** - Standard Deviation; K-W*** - Kruskal-Wallis Test.

To prove the test above, it was applied the multivariate technique simple correspondence analysis for double entrance tables (two variable cross).

It may be observed in Table 4 that the simple correspondence analysis shows 100% explanation for the variability in this crossing with only two dimensions (since the number of dimensions is equal to the minimum [age group category less 1, number of USF time category less 1] = minimum [2,4] = 2). Greater importance of the dimension 1 may also be noticed.

Table 4
Analysis of correspondence for crossing the time in the Family Health Units by Age Group, in the city of João Pessoa, Paraíba State, Brazil, 2016

Size	Singular value	Inertia	Chi-square	% Inertia
1	0.327	0.107	< 0.001	87.5
2	0.123	0.015		12.5
Total	-	0.122		100.0

According to the Figure 1, the higher age group is related to a higher time of USF, confirming the results of the Kruskal-Wallis test presented in the Table 3.

Figure 1
Percentage map of the Correspondence Analysis for the crossing of USF time by age group at risk of developing diabetes mellitus type 2, in the city of João Pessoa, Paraíba State, Brazil, 2016

DISCUSSION

The current study aimed to characterize profiles of people at risk of developing diabetes mellitus type 2 in the city of João Pessoa, Paraíba State. The importance of this characterization may be pointed out as basic strategy for actions that may affect the health/disease process of the USF users.

Regarding sociodemographic data, the results refer to the major attendance of women at the USF. This data was attested in another study^(17-18), fact that may indicate that women have a greater self-care regarding health and are considered the main users of the Unified Health System (SUS). However, the study shows a concern regarding men that also need health care, but do not have attendance in the units, fact that may leads to an increase of chronic diseases in men and a need for greater care offered by the health service^(19-20).

In relation to gender, this study points out that there is no considerable statistics probability. This information is in disagreement with another study that observed a higher risk of DM2 in men due to a higher responsibility of women regarding their self-care⁽²¹⁾. However, it was supported by systematic review about prevalence and incidence of risk factors for DM2 in Vietnam, in which the gender factor did not show considerable difference and pointed out the lack of consistency in the association between gender and diabetes requires further investigation⁽²²⁾. Nevertheless, national and international studies respectively, revealed that men have higher risk of developing DM2^(2,23).

Among the participants of the current research, most of them was adults under 45 years. This age group meets the literature with work related to the identification of risk for DM2, in southern Brazil, with basic care users under 45 years (49.7%)⁽¹⁹⁾ and in Azores, Portugal, also with users in the same age group (56%)⁽²⁴⁾. The Ministry of Health classifies the age group over or equal to 45 years as a risk for developing DM2⁽⁷⁾. This may be seen in other studies that also classifies this age group as a risk for developing the disease⁽²⁵⁾. In this study, it was observed that the higher the age, the more likely to develop DM2.

Regarding education, it was identified the prevalence of full high school among the participants studied, which may indicate a protection for DM2 risk, since literature states that the lower the education, the greater the trend of the disease development^(2,4,23). The National Health Survey of 2013, including education data in its evaluation, confirmed higher percentage of people with lower education level among those who were registered in the USFs. This profile was observed in all regions of Brazil, however, the southeast showed the highest variation between levels⁽²⁵⁾. In the current study, the education variable showed no considerable statistics relation for the risk of DM2.

With respect to ethnicity, brown was majority in the study. According to the Brazilian Society of Diabetes⁽⁴⁾ there is no distinction of risk for diabetes mellitus between white/brown/black. In a study conducted among bank clerks in Santa Catarina State, Brazil, was not found considerable statistics results p=0.456 related to ethnicity and the development of DM2⁽²⁶⁾. This fact attests the current study. An international study conducted in an adult community in Boston, US, showed PR=2.98 for black and PR=1.48 for white, in regard to develop DM2⁽²⁷⁾.

Concerning marital status, it may be observed that single/divorced/widowed/separated were those who had the highest prevalence in the study. A study carried out in Rize, Turkey, among 930 adults by cluster sampling, was related to the prevalence of risk factors for DM2 to the married/stable union population. It was justified in the study by the higher incidence of obesity in this group⁽²⁸⁾. This result may be confirmed in the study with the bank clerks of Santa Catarina State, Brazil⁽²⁶⁾. In the current study, there was no considerable statistics relation.

Concerning the family income, it was considered the minimum wage (R$880.00) in the period the study was carried out. The National Household Sample Survey (NHSS) disclosed that the Brazilian average per capita income in 2015 reached R$1,113, ranging from R$509.00 in the Maranhão State to R$2,252 in the Federal District. In Paraíba State this per capita income is R$776.00 according to the research⁽²⁹⁾. This study observed a higher income than was estimated for the population of the Paraíba State. It has already been found in international literature, in Australia, that lower socioeconomic and education levels were considerably associated with higher chances of developing DM2⁽²⁵⁾. However, in the current study, the income did not show considerable statistics value for the risk of DM2.

In terms of users frequency time to the services offered by the health units studied, it was found that, the period from 1 to 5 years accounted for the highest percentage. These frequency data did not showed considerable statistics relation. On the other hand, it may interfere with the fact that the higher frequency time in the units, the more care would be received by users, considerably reducing the chances of DM2. For a better understanding, it was made an association between the frequency time in the health units and the age of the participants through the Kruskal-Wallis test, presented in Table 3. It was confirmed that the people average age have increased as the USF time increased. According to the nonparametric test Kruskal-Wallis, there is a considerable difference in the average age by USF time, being likely the older the people, the higher the time in the service frequency. This conclusion may be observed by using the multivariate technique of simple correspondence analysis for double entrance tables (two variable cross).

Then, it will may be inferred that this association between age and time of frequency in the health units is related to confidence in the basic care service, causing the user to continue looking for it. Thereby, referring to a though of prevention and protection regarding diabetes if the health providers be aware of the risk factors presented by the users and keep a continuous care. However, these findings should be better studied, what seem to be a challenge for future research.

In terms of profession, it was not observed in the study a considerable statistics relation with DM2 probability, but it was already found in the literature a positive relation between the risk for DM2 and profession. This relation was observed among nurses by a study that pointed out this characteristic as being related to the working process of nursing, which may interfere in the sociodemographic and psychosocial variables⁽³⁰⁾.

Concerning clinical factors analyzed and associated with DM2, the overweight and obesity was a considerable statistics value in relation to the risk likelihood of developing DM2. These results respond to international^(31-32) and national^(20,23) studies that prove this relation. An integrative review that studied the relation among risk factors for DM2 in the Arab world proved that obesity was the main risk factor for rapid increase of DM2 in this region⁽³³⁾.

In terms of waist circumference and the risk for DM2, it was observed that the higher the waist circumference, the higher the probability of developing the disease. In a study conducted in the city of Pinal Del Rio, Cuba, in the Primary Health Care, was observed the waist circumference increase as a risk for DM2 in both gender⁽³⁴⁾. In southern Brazil, in a study among basic care users it was observed that the waist circumference between 94-102 cm in men and 80-88 cm in women was a considerable statistics value in likelihood of risk for DM2⁽²⁰⁾.

Physically inactive people were the sample majority and had considerable statistics PR value of 1.26 for developing DM2. A survey conducted in the city of Concordia, Santa Catarina State, Brazil, among workers of an industry showed that, in the high-risk group for DM2, all of them were sedentary⁽³⁵⁾. This information is in line with another study carried out in the city of Jundiaí, São Paulo State, Brazil⁽²³⁾. The physical activity practice as benefit to the health and the body is widely disclosed in the social networks and the media, however, a study in southeastern Brazil pointed out that the disclosure of this information is not clear, nor is encouraged by the professionals in the Primary Health Care⁽³⁶⁾.

According to what was reported by the population studied, 21.1% had glycemia rise. This percentage was higher than what was observed in other review⁽²³⁾ about the investigation of DM risk, conducted among student parents of a private school in the city of Jundiaí, Brazil, which represented 18%. However, in a cross-sectional study for DM2 risk evaluation carried out among Australians, the level of high glycemia corresponded to 32%⁽³⁷⁾. In the current study, there was considerable statistics relation PR=2.04 for DM2. Fact that was attested in other study⁽³⁶⁾. Changes in glycemia are a great alert to health care professionals, mainly to the nurse in the follow-up of patients at risk of developing DM2. For many times, the DM2 appears silently and the uncontrolled glycemia may be the first parameter to indicate a possible diagnosis of diabetes, being a factor that must be better studied.

Study limitations

The limits of the study were the cross-sectional design that did not allowed the relation of cause and effect. In addition, because the male users have a low attendance to the Primary Health Care and many refused to respond to the survey, there was a limitation in the stratified analysis by gender.

Contributions to nursing, health and public policy

This study shows that many risk factors for developing DM2 were present among the population of the study. In the face of these findings, it is highlighted the importance of carrying out health education and interventions by health professionals to encourage changes in habits, as it provides users access to knowledge about their health-disease process. Thereby, encouraging positive attitudes in its care, slowing or preventing the onset of diabetes. It should be pointed out that the nurse must be able to identify people at risk for DM2, considering their sociodemographic and clinical characteristics, as well as the context in which they are inserted.

CONCLUSION

The data obtained in this study characterized a predominantly female population, aged less than 45 years, with full high school, brown, single/divorced/widowed/separated, with income of 1 to 3 minimum wages, with health units attendance of 1 to 5 years and profession classified as others.

The analysis of the prevalence ratio, applied to all sociodemographic and clinical factors investigated, are statistically considerable as follows: old age, BMI, increased waist circumference, physical inactivity and elevated glucose. In view of their patients knowledge, it is up to the health managers and professionals the greater efficiency in the health services management, emphasizing the healthy lifestyle promotion, such as regular practice of physical activities, weight control and healthy eating.

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Publication Dates

• Publication in this collection
  2018

History

• Received
  03 July 2017
• Accepted
  03 Oct 2017