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Revista de Saúde Pública

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

Rev. Saúde Pública vol.53  São Paulo  2019  Epub May 06, 2019

http://dx.doi.org/10.11606/s1518-8787.2019053000727 

Original Article

Prevalence and factors associated to chronic kidney disease in older adults

Thatiana Lameira Maciel AmaralI 
http://orcid.org/0000-0002-9197-5633

Cledir de Araújo AmaralII 
http://orcid.org/0000-0002-7221-5364

Maurício Teixeira Leite de VasconcellosIII 
http://orcid.org/0000-0003-1658-2589

Gina Torres Rego MonteiroI  IV 
http://orcid.org/0000-0002-9900-1825

I Universidade Federal do Acre . Centro de Ciências da Saúde e do Desporto . Programa de Pós-Graduação em Saúde Coletiva . Rio Branco , AC , Brasil

II Instituto Federal de Educação, Ciência e Tecnologia do Acre . Campus Rio Branco. Rio Branco , AC , Brasil

III Fundação Instituto Brasileiro de Geografia e Estatística . Escola Nacional de Ciências Estatísticas . Rio de Janeiro , RJ , Brasil

IV Fundação Oswaldo Cruz . Escola Nacional de Saúde Pública Sérgio Arouca . Rio de Janeiro , RJ , Brasil

ABSTRACT

OBJECTIVE

To verify the prevalence of chronic kidney disease and the factors associated to it in older adults (≥ 60 years).

METHODS

This is a population-based research conducted in 2014, involving 1,016 older adults living in urban and rural areas of the municipality of Rio Branco, Acre. Chronic kidney disease was defined by glomerular filtration rate < 60 ml/min/1.73 m 2 , estimated by the equations of the Chronic Kidney Disease Epidemiology Collaboration, and the presence of albuminuria > 29 mg/g. Association measure were estimated by gross and adjusted odds ratio (OR), with a confidence level of 95% (95%CI).

RESULTS

The overall prevalence of chronic kidney disease was 21.4% in older adults, with the associated factors age, diabetes (OR = 3.39; 95%CI 2.13–5.40), metabolic syndrome (OR = 2.49; 95%CI 1.71–3.63), self-assessment of poor health (OR = 1.79; 95%CI 1.10–2.91), arterial hypertension (OR = 1.82; 95%CI 1.04–3.19) and obesity (OR = 1.69; 95%CI 1.02–2.80).

CONCLUSIONS

The prevalence of chronic kidney disease was high in older adults, being associated with age, self-assessment of health as bad or very bad, obesity, diabetes and metabolic syndrome.

Key words: Aged; Renal Insufficiency, Chronic, epidemiology; Risk Factors; Comorbidity; Health Surveys

INTRODUCTION

The pattern of morbimortality due to chronic kidney disease (CKD) in underdeveloped and developing countries is changing due to the transition of infectious diseases to chronic non-communicable diseases 1 . Prevalence projections of CKD in the U.S. for 2020 and 2030, between individuals over 30 years, estimate that the disease will go from 13.2% in 2010 to 14.4% in 2020 and to 16.7% in 2030 2 .

The prevalence of CKD changes with age, reaching higher values among older people, and may vary from 25.1% in Nicaragua, in the age group of 60 to 70 years 3 , to 30.8% in Canada, among those aged ≥ 65 years 4 . The reduction in the glomerular filtration rate (GFR) for less than 60 ml/min/1.73 m 2 might be attributed to aging, which causes progressive structural and functional changes in the kidneys, or as consequence of the presence of comorbidities and of the exposition of risk factors throughout life 5 .

Among older adults, the presence of CKD represents an increased risk for multiple events adverse to health that may culminate in death, and the early detection of the reduced GFR and albuminuria is important to assist in the therapeutic decision-making and consequent reduction of complications 6 . Thus, this study aimed to estimate the prevalence of CKD and the factors associated to it in older adults (60 years or more), using part of the data from the Estudo das Doenças Crônicas (Edoc – Study of Chronic Diseases).

METHODS

The Edoc is composed of two household surveys: the Edoc-A, on adults (18 to 59 years-old), and the Edoc-I, on older adults (60 years or more), all living in Rio Branco, Acre. Individuals with cognitive impairments that could preclude communication or understanding of the questions were excluded. Sampling plans were selected in two stages, census enumerations areas (CEAs) and households, being the first common to the two researches. The CEAs were selected with probability proportional to the number of private households in the 2010 Demographic Census (CD2010) of the Brazilian Institute of Geography and Statistics (IBGE). The households were selected by systematic sampling with random starts and distinct ranges per survey. In the households selected for Edoc-I, all the older adult residents were interviewed.

The sample size was estimated considering the prevalence of renal function changes of 40% in older adults 7 , with confidence level of 95% and absolute error of 3% for the simple random sampling of proportions. Considering that the sampling plan is conglomerated by CEA, a sampling plan effect of 1.95 was arbitrated to determine the sample size, which received an increase of 12.5% to compensate the expected non-responses. This procedure resulted in a sample of 1,148 older adults. By dividing this sample size by the number of older adults per household, according to CD2010, and by defining the selection of 73 households per CEA, a sample size of CEAs of 40 was obtained. The effective sample was 1,016 older adults.

The sampling weights were calculated by the inverse of the inclusion probabilities in each stage and were subsequently calibrated for populational data by sex and age groups, using a post-stratification estimator, in order to address these typical biases of the household surveys and to correct differential non-responses 8 . The population data used in the calibration of the sampling weights were estimated for July 1, 2014, using the linear trend method 9 that the IBGE applies in its population estimations per municipality. This study included all who performed laboratory assessments of serum creatinine, that is, 983 older adults (578 women and 405 men), that correspond to a subsample of complete information on the topic. For more details about the sampling plan of the Edoc, estimation and calibration of sample weights and subsamples, see the article by Amaral et al. 10 .

A total of 33 participants were excluded from the analysis of renal function due to the lack of information on serum creatinine. Each household with a participant resident filled a form containing general information on housing, sanitation and family. Individually, a structured form was used in thematic modules with socioeconomic, demographic, behavioral and health information.

In the physical assessment, the anthropometric data included the measurement of weight, height and circumferences of the waist, hips, arm and calf, all in duplicate, and the average of the measurements was considered.

Blood pressure (BP) was measured according to the protocol recommended by the Brazilian Society of Cardiology, which recommends measuring 30 minutes or more after the last drank dose of caffeine or smoked cigarette, in triplicate: one after five minutes of initial rest and two others in intervals of two minutes 11 .

The biological material was analyzed in the same laboratory to ensure the standardization of methods. Blood samples were obtained by peripheral blood collection, with prior antisepsis of the antecubital fossa of the participants. The serum extracted was stored for biochemical dosage of triglycerides, total cholesterol and fractions: high-density lipoprotein (HDL) and low-density lipoprotein (LDL). Serum creatinine was dosed by traceable enzymatic method of isotope dilution mass spectrometry (IDMS) in an automatic analyzer (Labmax 240 Premium). To analyze serum glycemia, a 4 ml blood sample was used, stored in a vacuum tube containing 2 mg/ml of sodium fluoride centrifuged before analysis. The serum glycemia was dosed by the glucose oxidase method (Labtest Diagnostica).

For the urine sample, 50 ml of the midstream of first morning urine of each individual were collected, subsequently processed for physicochemical and microscopic analysis of the sediment.

Urinary creatinine was dosed by the enzymatic Trinder method (Kit Creatinina Enzimática, Labtest), and albuminuria by the immunoturbidimetric method (Kit Turbiquest Plus, Labtest). Albuminuria is defined with a ratio of albumin to creatinine of 30 mg/g or more, being the value of 30 to 299 considered A2, or moderately increased, and the value ≥ 300 mg/g considered A3, or markedly increased.

The systemic arterial hypertension (SAH) was defined as diastolic blood pressure (DBP) ≥ 90 mmHg, systolic blood pressure (SBP) ≥ 140 mmHg and/or current use of anti-hypertensive medication 11 .

The presence of diabetes was defined according to the criteria of the American Diabetes Association (ADA): fasting plasma glucose ≥ 126 mg/dL or use of oral hypoglycemic or insulin 12 .

Dyslipidemia was defined by abnormal levels of one or more of the following lipid blood components: triglycerides ≥ 150 mg/dL, total cholesterol ≥ 200 mg/dL, LDL ≥ 160 mg/dL, HDL in men < 40 mg/dL and in women < 50 mg/dL, in addition to the history of use of medications to reduce these values. For individuals aged less than 20 years, the cut-off points are: triglycerides ≥ 130 mg/dL, total cholesterol ≥ 170 mg/dL, LDL ≥ 130 mg/dL and HDL ≤ 45 mg/dL 13 .

For the diagnosis of metabolic syndrome (MS), the I Brazilian Guideline of Diagnosis and Treatment of Metabolic Syndrome was used, which requires the presence of at least three of the following elements: waist diameter > 102 cm for men and > 88 cm for women; triglycerides ≥ 150 mg/dL; HDL < 40 mg/dL for men and < 50 mg/dL for women; SBP ≥ 130 mmHg, DBP ≥ 85 mmHg or use of anti-hypertensive; fasting glycemia ≥ 110 mg/dL or use of hypoglycemic 14 .

The dependent variable of the study (CKD) was defined according to the formulas of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), when GFR < 60 ml/min/1.73 m2 and/or albuminuria > 29 mg/g 15 .

The use of equations to estimate the GFR provides adjustments for the substantial variations regarding sex, age, body surface and ethnicity, characteristics that interfere in the production of creatinine. To this end, the validated equations of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) were used, described below:

Female:

Black skin color ≤ 0.7 = 166 × (serum creatinine/0.7) -0.329 × 0.993 age

Black skin color > 0.7 = 166 × (serum creatinine/0.7) -1.209 × 0.993 age

White skin color ≤ 0.7 = 144 × (serum creatinine/0.7) -0.329 × 0.993 age

White skin color > 0.7 = 144 × (serum creatinine/0.7) -1.209 × 0.993 age

Male:

Black skin color ≤ 0.9 = 163 × (serum creatinine/0.9) -0.411 × 0.993 age

Black skin color > 0.9 = 163 × (serum creatinine/0.9) -1.209 × 0.993 age

White skin color ≤ 0.9 = 141 × (serum creatinine/0.9) -0.411 × 0.993 age

White skin color > 0.9 = 141 × (serum creatinine/0.9) -1.209 × 0.993 age

The category “black skin color” included the individuals who self-declared black or brown.

In 2012, the categories of risk were defined for the progression of chronic kidney disease based on serum creatinine, with correction by formulas for obtaining GFR, and in albuminuria. In addition, the stage 3 of the CKD was divided in 3a and 3b. An important emphasis of the guidelines is the adoption of categories of CKD prognosis, classifying from low to high risk of progression of the acute renal injury for CKD and other complications 15 .

The data was analyzed using the Complex samples routines of the Statistical Package for the Social Sciences software (SPSS), version 20.0, for Windows. The natural weight of the design, the sample selection stratum, the primary sampling unit code (CEA) and the calibrated weight were maintained in the data files.

The data were analyzed in a descriptive and exploratory way to assess the distribution and characterize the studied population. The qualitative variables were described in absolute numbers and proportions. To analyze the differences between categorical variables, we used Pearson’s chi-squared test.

A bivariate analysis was also performed in order to explore the association of the different variables with the object of study. Models of odds ratio estimated the magnitude of association between the dependent variable CKD and the independent variables. For multiple analysis, the variables included were the ones that showed a p value lower than 0.10 in the crude analysis, and the magnitude of the variables adjusted by the other significant variables was analyzed. The backward method was used in the selection of the variables in the multivariate analysis. Age and sex interactions with CKD were tested, with no effect changes observed. The significance level considered was α = 0.05.

All analysis considered the effect of the sampling design and the calibrated weights of the observations, and the results of the observations are demonstrated by “n” and the results considering the calibrated weights for extrapolation for the population by “expanded n (N)”. To this end, the pseudo maximum likelihood method (PML) was used, considering the sampling weights and the structural information of the sampling plan. The interferences were assessed by Wald statistics based on the sampling plan, along with the F distribution.

This study meets the requirements of Resolution CNS 466/2012, which addresses ethics in research involving human beings, and was approved by the Research Ethics Committee of the Universidade Federal do Acre, under CAAE: 17543013.0.0000.5010.

RESULTS

The prevalence of CKD was of 21.4%, with verified decreased GFR in 13.0% of older adults and the presence of albuminuria in 11.6%. The prevalence of the prognosis with mild, moderate and high risk was, respectively, 14.5%, 4.9% and 2.1% (Table 1).

Table 1 Prevalence by category of risk of the prognosis of CKD evolution assessed by GFR (estimated by the CKD-EPI formula) and albuminuria in older adults from Rio Branco, state of Acre, 2014. 

Categories of risk of CKD Total Albuminuria CKD (GFR* and albuminuria)

A1 (< 30) A2 (30–299) A3 (≥ 300)





n N (%) n N (%) n Exp N (%) n N (%) n N (%)
1 ≥ 90 296 7,982 (34.0) 270 a 7,252 (31.2) a 19 b 518 (2.2) b 4 c 116 (0.5) c 23 634 (2.7)
2 60–89 547 12,407 (53.0) 486 a 10,982 (47.3) a 45 b 1,059 (4.6) b 11 c 260 (1.1) c 56 1,319 (5.7)
3a 45–59 106 2,271 (9.7) 85 b 1,778 (7.7) 15 c 358 (1.6) c 6 d 135 (0.6) d 106 2,217 (9.7)
3b 30–44 26 552 (2.4) 19 c 385 (1.7) c 4 d 93 (0.4) d 3 d 73 (0.3) d 26 552 (2.4)
4 15–29 4 93 (0.4) 4 d 93 (0.4) d - - - - 4 93 (0.4)
5 < 15 4 111 (0.5) 1 d 24 (0.1) d 2 d 54 (0.2) d 1 d 33 (0.1) d 4 111 (0.5)
Total 983 23,416 (100.0) 865 20,514 (88.4) 85 2,082 (9.0) 25 617 (2.6) 219 4,979 (21.4)

N: expanded n from sampling weights and design; %: proportion from N; CKD: chronic kidney disease; GFR: glomerular filtration rate

* CKD-EPI formula: Chronic Kidney Disease Epidemiology Collaboration (ml/min/1.73 m 2 ).

a Low.

b Mild.

c Moderate.

d High.

The presence of CKD was higher among octogenarian individuals, with a prevalence of almost 40.0%, and among those declared widows/widowers, who showed a prevalence of 25.9%, with statistically significant differences (Table 2).

Table 2 Prevalence of CKD according to sociodemographic characteristics and life habits of older adults in Rio Branco, state of Acre, 2014. 

Variable Total CKD p

Yes No



n N n N % n N %
Sex 0.519
Female 577 12,496 123 2,570 20.6 454 9,926 79.4
Male 406 10,920 96 2,409 22.1 310 8,511 77.9
Age group (years) < 0.001
60–69 475 13,394 75 2,134 15.9 400 11,260 84.1
70–79 339 6,687 80 1,586 23.7 259 5,101 76.3
80 and more 169 3,335 64 1,259 37.8 105 2,076 62.2
Skin color 0.158
White 241 5,601 62 1,374 24.5 179 4,227 75.5
Brown 634 15,221 140 3,217 21.1 494 12,004 78.9
Other 108 2,594 17 388 15.0 91 2,206 85.0
Education level* 0.804
Higher education 38 954 10 231 24.2 28 723 75.8
High school 112 2,828 21 528 18.7 91 2,300 81.3
Elementary school 360 8,721 76 1,807 20.7 284 6,914 79.3
Illiterate/Literate 465 10,712 109 2,344 21.9 356 8,368 78.1
Marital status* 0.011
Married 365 9,144 80 1,994 21.8 285 7,150 78.2
Single 178 4,356 28 591 13.6 150 3,765 86.4
Widow/Widower 317 6,793 85 1,754 25.8 232 5,039 74.2
Separated/Divorced 117 2,980 25 616 20.7 92 2,365 79.3
Physical activity 0.153
Yes 149 3,654 26 593 16.2 123 3,061 83.8
No 834 19,762 193 4,386 22.2 641 15,376 77.8
Smoking 0.148
Non-smoker 282 6,696 71 1,618 24.2 211 5,078 75.8
Ex-smoker 537 12,541 119 2,689 21.4 418 9,852 78.6
Smoker 164 4,179 29 672 16.1 135 3,507 83.9
Consumption of alcoholic beverage 0.149
No 857 20,138 185 4,131 20.5 672 16,007 79.5
Yes 80 2,175 23 600 27.6 57 1,575 72.4

N: expanded n from sampling weights and design; %: proportion from N; χ 2 = p: Pearson’s chi-squared test; CKD: chronic kidney disease

* The differences in relation to the total are due to the lack of information in the variable.

In the analysis of the health conditions of older adults with CKD, 29.5% reported considering their health bad or very bad, 26.4% were classified as obese, 24.0% had SAH and 22.7% had dyslipidemia. Diabetes obtained the highest prevalence, 41.5%, and metabolic syndrome was present in 30.3% of the people classified as having a CKD. The use of medications was reported by 22.6% of these older adults (Table 3).

Table 3 Prevalence of CKD according to health conditions in older adults in Rio Branco, state of Acre, 2014. 

Variable Total CKD p

Yes No



n N n N % n N %
Self-assessment of health 0.014
Very good/Regular 824 19,774 170 3,906 19.8 654 15,868 80.2
Bad/Very bad 159 3,642 49 1,073 29.5 110 2,569 70.5
BMI (kg/m 2 )* 0.031
< 25.0 333 7,844 59 1,275 16.3 274 6,569 83.7
25.0–29.9 367 8,816 83 1,944 22.1 284 6,872 77.9
≥ 30.0 248 5,932 69 1,565 26.4 179 4,367 73.6
Hypertension* 0.008
No 231 5.571 32 728 13.1 199 4,843 86.9
Yes 744 17,618 186 4,231 24.0 558 13,387 76.0
Diabetes* < 0.001
No 820 19,501 152 3,381 17.3 668 16,120 82.7
Yes 161 3,848 67 1,599 41.5 94 2,249 58.5
Dyslipidemia* 0.032
No 198 4,753 32 743 15.6 166 4,010 84.4
Yes 784 18,629 187 4,236 22.7 597 14,393 77.3
Metabolic syndrome* < 0.001
No 618 14,842 105 2,385 16.1 513 12,458 83.9
Yes 356 8,363 111 2,536 30.3 245 5,827 69.7
Other self-reported CVD (CHF, MI, CVA, arrhythmia)* 0.462
No 830 19,834 182 4,132 20.8 648 15,702 79.2
Yes 138 3,219 34 766 23.8 104 2,453 76.2
Use of medicines 0.034
No 231 5,934 42 1,020 17.2 189 4,914 82.8
Yes 752 17,482 177 3,960 22.6 575 13,522 77.4
Hospitalization in the past 12 months* 0.055
No 791 18,869 167 3,843 20.4 624 15,026 79.6
Yes 158 3,769 49 1,077 28.6 109 2,692 71.4

N: expanded n from the sampling weights and design; %: proportion from N; χ 2 = p: Pearson’s chi-squared test; BMI: body mass index; CVD: cardiovascular diseases; CHF: congestive heart failure; MI: myocardial infarction; CVA: cerebrovascular accident

* The differences in relation to the total are due to the lack of information in the variable.

Statistically significant differences were observed in the distribution of CKD in the variables self-assessment of health, obesity according to the BMI, SAH, diabetes and dyslipidemia. Except for the self-assessment of health, all are components of metabolic syndrome, also related. The current use of medications also showed statistically significant difference in the presence of CKD (Table 3).

The assessment of odds ratio with the introduction of potentially confusing variables observed a statistically significant association between CKD and age group, self-assessment of health, obesity, hypertension, diabetes and metabolic syndrome, even after adjustment. The model for MS analysis did not include the variables SAH and DM, since they already belong to the definer set of the syndrome (Table 4).

Table 4 Factors associated to CKD in older adults from Rio Branco, state of Acre, 2014. 

Variable OR crude (95%CI) OR adjusted (95%CI)
Age group (years)
60–69 1 1
70–79 1.64 (1.12–2.40) 1.83 (1.25–2.68)
80 and more 3.20 (2.24–4.57) 3.99 (2.70–5.91)
Self-assessment of health
Very good/Regular 1 1
Bad/Very bad 1.70 (1.12–1.58) 1.79 (1.10–2.91)
BMI (kg/m 2 )
< 25.0 1 1
25.0–29.9 1.46 (0.95–2.24) 1.37 (0.90–2.08)
≥ 30.0 1.85 (1.11–3.08) 1.69 (1.02–2.80)
Use of medicines
No 1 1
Yes 1.41 (1.03–1.94) 0.70 (0.43–1.14)
Arterial hypertension
No 1 1
Yes 2.10 (1.22–3.63) 1.82 (1.04–3.19)
Diabetes
No 1 1
Yes 3.39 (2.34–4.91) 3.39 (2.13–5.40)
Dyslipidemia
No 1 1
Yes 1.59 (1.04–2.43) 1.43 (0.87–2.37)
Metabolic syndrome*
No 1 1
Yes 2.27 (1.61–3.21) 2.49 (1.71–3.63)

BMI: body mass index; OR: odds ratio; OR crude: crude analysis; OR adjusted: adjusted analysis by the variables with each other

* In the analysis of metabolic syndrome, BMI, dyslipidemia, arterial hypertension and diabetes.

DISCUSSION

The prevalence of CKD was high in older adults, being associated with age, self-assessment of health as bad or very bad, obesity, diabetes and metabolic syndrome, even after adjustments. In this research, the incorporation of objective criteria to standardize the staging of CKD (use of GFR according to the formula CKD-EPI and the classification of albuminuria) favored the comparison with different locations 15 .

The prevalence of CKD increases with advancing age 16 . The aging process results in reduced GFR, which is a normal biological phenomenon linked to cellular and organ senescence, resulting from the change in the volume of the kidney, with reduced number of nephrons, change in the vasoactive response and changes in the activity of the renin-angiotensin systems, associated to the cellular oxidative stress 17 . Another functional abnormality of aging is the increased permeability of the glomerular basement membrane, which allows the excretion of a larger number of proteins, including albumin, another factor that influences the increase of the prevalence of renal injury in older people 18 . The decline of renal function, which seems to start early in the second decade of life 19 , was observed in this study, with increased prevalence of CKD in each surveyed age group, reaching 37.8% in octogenarians.

The high prevalence of older adults with CKD, especially those with 70 years or more, according to the criteria of the Kidney Disease: Improving Global Outcomes (KDIGO) 2012, has been questioned by researches who defend a new definition of CKD for older adults, not classifying individuals in stage 3a as sick, but only those with GFR < 45 ml/min/1,73 m 2 and the presence of albuminuria 20 . This proposal would reduce the prevalence of renal injury in this study.

It is worth noting that two-thirds of the elderly population show reduced GFR without complications related to health in most cases; however, the presence of chronic conditions such as hypertension and diabetes, associated to aging, may lead to the sharp decline of renal function, with increased prevalence of CKD 21 . Different mechanisms are related with the physiopathology of CKD associated to SAH, including the deregulation of sodium content, renin-angiotensin system and the endothelial function 22 , which become more expressive with age.

In a national survey performed with 7,552 subjects in Italy, the prevalence of CKD in the age group from 60 to 69 years was 8.7%, and in the group from 70 to 79, it was approximately 17.0%, with hypertension associated to the disease (OR = 1.55) 23 . In a population study in Poland with 2,413 participants, the prevalence in the age group of 60 to 79 years was 15.3%, with a nearly twice as likely chance of the hypertensive individual being classified as having CKD 24 . In this study, hypertension was also positively associated with CKD.

In addition to hypertension, among the morbidities assessed in this research, diabetes obtained a greater association with CKD, which was also observed in other researches 23,24 . Among diabetics, the mechanisms involved in the renal lesion result in glomerular hyperfiltration with proteinuria — in most cases, glomerulosclerosis with reduced GFR 25 . In a study on mortality due to CKD in Rio Branco, diabetes and SAH were among the associated leading causes of death 26 .

In this study, bad and very bad self-assessment of health was also related to CKD. This assessment is useful as an overall measure of the health status in the general population, being consistent with the real state of health. In a population-based research performed in China, with individuals with 18 years or more, the presence of CKD resulted in a four times greater change of self-report to a poor health condition (OR = 4.41; 95%CI 3.20–6.07) 27 .

Obesity increases the risk of occurrence of diseases considered risk factors for the development of CKD, such as SAH and diabetes, in addition to acting in the progression of the stages of CKD by hyperfiltration, to meet the demands of the body weights and of the increase of the intra-glomerular pressure, which damages renal structures 28 . Among the older adults of this research, obesity defined by BMI, was associated with CKD.

The data analysis of 9,100 adults of the Chronic Renal Disease in Turkey (CREDIT) evidenced the association of CKD to obesity, determined by the BMI, and to metabolic syndrome (OR = 1.32; 95%CI 1.11–1.57) 29 . In this research, even after adjustment, the presence of CKD increased more than twice the chance the individual has of having metabolic syndrome.

One of the limitations of this research is the possible attenuation of the associations observed, due to the effect of survival among older adults. Another factor is the definition of CKD by the estimation of the GFR and albuminuria from a blood and urine punctual sample, since it is recognized that the confirmation of the disease occurs when the abnormality in GFR or albuminuria for a period of three months. In addition, the choice of more than one individual of a same household may result in the reduction of variability. It is necessary to emphasize, also, that the exclusion of individuals without physical or cognitive capacity to participate in the study may lead to errors in the estimation of the GFR, since these are more likely to reduce this rate.

Finally, the importance of population surveys stands out as an important source of information on the health of the older adult population, aimed at the definition of risk factors and the prevention of diseases or their complications. Finding the disease in its early stages among older adults must be a priority in Northern Brazil, which has an aging index that went from 8.2% in 1970 to 24.6% in 2010, in addition to the increase of chronic morbidities such as diabetes, SAH and obesity 30 , factors associated to CKD.

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Funding: Conselho Nacional de Desenvolvimento Científico e Tecnológico [CNPq – Call MCTI/CNPQ/MS-SCTIE-DECIT 06/2013, for support to strategic research for the Health System by the Rede Brasileira de Avaliação de Tecnologias em Saúde (REBRATS – Brazilian Network of Assessment of Health Technologies), Process 401081/2013-3]; Fundação de Amparo à Pesquisa do Acre [FAPAC – Call PPSUS 001/2013, of the Research Program for SUS: shared health management (MS/CNPq/FAPAC/SESACRE), Process 6068-14-0000029].

Received: March 31, 2018; Accepted: June 13, 2018

Correspondence: Thatiana Lameira Maciel Amaral Campus Universitário Centro de Ciências da Saúde e do Desporto BR 364 km 4 Distrito Industrial Caixa postal 500 69920-900 Rio Branco, AC, Brasil E-mail: thatianalameira27@gmail.com

Authors’ Contribution: Conception and planning of the study: TLMA, CAA, GTRM. Data collection, analysis and interpretation: TLMA, CAA, GTRM, MTLV. Drafting or review of the manuscript: TLMA, CAA, GTRM, MTLV. All the authors approved the final version and take public responsibility for the content of the article.

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

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