Skip to main content Accessibility help
×
Home
Hostname: page-component-cf9d5c678-7bjf6 Total loading time: 0.4 Render date: 2021-07-27T18:44:31.694Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true, "newUsageEvents": true }

Cut-off points of anthropometric markers associated with hypertension in the Brazilian population: National Health Survey, 2013

Published online by Cambridge University Press:  02 April 2019

Ana Paula Alves de Souza
Affiliation:
Faculdade de Nutrição, Universidade Federal de Mato Grosso, Avenida Fernando Corrêa da Costa 2367, Bloco CCBS I, Cuiabá, MT78060-900, Brazil
Paulo Rogério Melo Rodrigues
Affiliation:
Faculdade de Nutrição, Universidade Federal de Mato Grosso, Avenida Fernando Corrêa da Costa 2367, Bloco CCBS I, Cuiabá, MT78060-900, Brazil
Ana Paula Muraro
Affiliation:
Instituto de Saúde Coletiva, Universidade Federal de Mato Grosso, Cuiabá, MT, Brazil
Naiara Ferraz Moreira
Affiliation:
Faculdade de Ciências da Saúde, Universidade Federal da Grande Dourados, Dourados, MS, Brazil
Rosely Sichieri
Affiliation:
Instituto de Medicina Social, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
Rosângela Alves Pereira
Affiliation:
Instituto de Nutrição Josué de Castro, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
Márcia Gonçalves Ferreira
Affiliation:
Faculdade de Nutrição, Universidade Federal de Mato Grosso, Avenida Fernando Corrêa da Costa 2367, Bloco CCBS I, Cuiabá, MT78060-900, Brazil Instituto de Saúde Coletiva, Universidade Federal de Mato Grosso, Cuiabá, MT, Brazil
Corresponding
E-mail address:
Rights & Permissions[Opens in a new window]

Abstract

Objective

To identify cut-off points for waist circumference (WC), waist-to-height ratio (WHtR) and BMI associated with hypertension in the Brazilian adult and elderly population.

Design

Cross-sectional study. The receiver-operating characteristic (ROC) curve was used to determine the cut-off points of WC, WHtR and BMI in the prediction of hypertension. Those who had systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg and those who reported use of antihypertensive medication were considered hypertensive.

Setting

Brazil.

Participants

Participants from the National Health Survey, the Brazilian household-based survey conducted in 2013, of both sexes and age ≥20 years.

Results

Cut-off points for WC and WHtR increased with age in both sexes. WC cut-off limits ranged between 88·0 and 95·9 cm in men and between 85·0 and 93·2 cm in women. For WHtR, cut-off scores ranged from 0·51 to 0·58 for men and from 0·53 to 0·61 for women. Additionally, the area under the ROC curve (AUC) for all age and sex groups was greater than 0·60 while the lower limit of the AUC 95 % CI for both WC and WHtR was not less than 0·50. The performance of BMI was similar to that of indicators of fat location.

Conclusions

All analysed anthropometric indicators had similar performance in identifying hypertension in the Brazilian population.

Type
Research paper
Copyright
© The Authors 2019 

In 2013, 339 672 deaths (29·8 %) in Brazil were due to CVD(1). Among factors contributing to CVD, hypertension is one of the most important, since it is considered the main risk factor for the development of cardiovascular complications. In addition, it represents one of the chronic conditions most commonly treated by primary-care physicians and other health-care professionals in Brazil(1). The prevalence of hypertension among Brazilian adults, in 2015, was estimated at 23 %(2).

Among the risk factors for the development of hypertension, overweight and obesity have become a growing concern(Reference Booth, Prevost and Gulliford3) because body fatness, especially visceral adiposity, is associated with metabolic inflammation, dyslipidaemia, insulin resistance and increased risk of developing CVD(Reference Tchernof and Despres4). Although overweight is an independent risk factor for systemic arterial hypertension, intra-abdominal fat deposition may increase the risk of elevated blood pressure level(Reference Dorresteijn, Visseren and Spiering5). Individuals with normal blood pressure levels, who develop central adiposity, are more exposed to the risk of developing hypertension(Reference Ren, Su and Wang6).

BMI has been the total adiposity index most widely used in epidemiological studies(7). In addition, due to the close relationship between abdominal fat accumulation and cardiovascular risk, the use of anthropometric indicators of central adiposity also has great applicability in population studies. Among these markers of fat location, waist circumference (WC), waist-to-hip ratio and waist-to-height ratio (WHtR) have been widely used(8).

However, there is still controversy in the literature over the predictive role of anthropometric indicators, with different performance among them depending on the population (ethnicity, sex and age) and the outcome being evaluated(Reference Zhu, Wang and Heshka9). WC is commonly considered an important indicator of the development of obesity-related morbidities, and it is correlated with visceral adipose tissue depots and metabolic alterations in some populations(Reference De Koning, Anwar and Merchant10). However, for the Brazilian population, some studies have found that WC is a predictor of overall fatness because of a high correlation with total adiposity(Reference Pereira, Sichieri and Marins11, Reference Lemos-Santos, Valente and Gonçalves-Silva12).

WHtR has been proposed as a more sensitive marker to estimate central adiposity(Reference Ashwell and Gibson13). Some Brazilian studies have reported good performance of WHtR in the prediction of cardiovascular risks with specific populations, not representative of the general population of the country(Reference Pitanga and Lessa14Reference Corrêa, Tomasi and Thumé16).

The definition of cut-off points for anthropometric indicators is pertinent, since it may aid the screening of hypertension based on easily measurable and low-cost markers(17). The cut-off limits used to indicate elevated WC or WHtR are based on international studies and their predictive ability for systemic arterial hypertension have not yet been explored in studies with nationally representative Brazilian samples. In addition, as changes in body composition with ageing may affect the risk of developing hypertension(17Reference Sun19), it is important to evaluate how this increase occurs in the Brazilian population given its dynamic specificities, such as multiracialism and age composition(20).

Thus, the present study analysed the sensitivity and specificity of anthropometric indices in different age and sex strata in a representative sample of the Brazilian adult and elderly population examined in the first National Health Survey, 2013(Reference Souza-Júnior, Freitas and Antonaci21, Reference Damacena, Szwarcwald and Malta22), which is considered to be the most comprehensive health research conducted in Brazil to date.

Methods

Study population

The present study is a cross-sectional study analysing data from the 2013 Brazilian National Health Survey (PNS; translated from the original in Portuguese (Pesquisa Nacional de Saúde)), a nationwide household-based survey conducted in 2013 on health, lifestyle and chronic diseases. The sampling plan for the PNS was developed from the master sample of the Integrated System for Household Surveys of the Brazilian Institute of Geography and Statistics. Thus, the PNS sample has a geographic coverage that includes the census tracts of the geographical operating base of the 2010 Brazilian population census(Reference Souza-Júnior, Freitas and Antonaci21).

The sampling plan was defined by conglomerates, configured in three stages: (i) primary sampling units, i.e. census tracts or set of sectors; (ii) secondary units, represented by households; and (iii) tertiary units, which corresponded to residents aged 18 years or over. Adjustments were made to sample size by considering the design effect values, and sample weights were defined for the primary sampling units, households and all residents; also, a weight value was assigned to the resident selected to answer the individual interview.

A non-response rate of 20 % was estimated and the estimated total sample size was approximately 80 000 households. A total of 81 167 households were visited, of which 69 994 were occupied, where 64 348 household interviews and 60 202 individual interviews were conducted. Further details on the development process and sampling plan can be found in other publications(Reference Souza-Júnior, Freitas and Antonaci21, Reference Damacena, Szwarcwald and Malta22).

The present study analysed data from 57 230 individuals, aged at least 20 years old, for whom there was information on blood pressure measurements or who reported using antihypertensive medication. Individuals between 18 and 19 years old included in the PNS represented 4·8 % of the sample and were not analysed in the present study because the performance of anthropometric markers in detecting hypertension in this age group differs from that in adults and elderly people, thus requiring a specific approach in the interpretation and discussion of the results.

Data collection

Data collection was carried out in 2013, through the application of a structured questionnaire using a handheld device (personal digital assistant). The survey consisted of three modules: domicile, residents of the household and individual. After the initial contact between the researcher and a resident of the selected household, a list was made of all residents aged ≥18 years, who answered the household questionnaire. Additionally, one adult was randomly selected to answer an individual interview. Physical measures (blood pressure, weight, height and waist circumference) were taken in accordance with an anthropometry procedures manual designed for the PNS(23).

Measurements

Education level was grouped into the following categories: no education and incomplete elementary education; complete elementary education and incomplete high school; complete high school and incomplete college education; and complete college education. The variable race/skin colour was classified according to the categorization proposed by the Brazilian Institute of Geography and Statistics(20) and grouped as: white; black; mixed; and others.

Blood pressure was measured by the oscillometric method, by using an MA 100 G-TECH automatic device, on the left arm, with the participants sitting comfortably, with feet flat on the floor and a clamp at the level of the heart. The participants were instructed to empty their bladder and not to practise any physical activity, smoke or drink before the blood pressure measurement. Three measurements were taken, with an interval of 2 min between each measurement(23, Reference Malta, Santos and Perillo24). The mean between the second and third measurements was used in the present study. Hypertension was defined according to the VI Brazilian Guideline for Hypertension, which considers hypertension as the sustained elevation of blood pressure levels corresponding to ≥140 mmHg for systolic blood pressure and/or ≥90 mmHg for diastolic blood pressure in individuals aged at least 18 years, in the absence of antihypertensive medication(1). In the PNS, individuals with normal or high blood pressure levels who reported using antihypertensive medication over the last two weeks prior to the interview were also considered hypertensive.

The following anthropometric variables were evaluated: weight, height and WC. Weight was recorded in kilograms and measured by means of portable digital scales with 150 kg capacity; height was measured with a portable stadiometer. WC was measured with a flexible and inextensible tape measure at the waist level, at the midpoint between the last rib and the iliac crest. The reading was made to the nearest centimetre, where the tape crossed the zero point, between expiration and inspiration(23). Based on WC (in centimetres) and height (in centimetres) measurements, WHtR was calculated by dividing the former by the latter.

BMI (weight/height2) was used to classify weight status according to age group. For adults, BMI cut-off points used were <18·5 kg/m2 (underweight); ≥18·5 and <25·0 kg/m2 (normal weight); ≥25·0 and <30·0 kg/m2 (overweight) and ≥30·0 kg/m2 (obesity)(17). For the elderly (60 years or older), the following BMI cut-offs proposed by The Nutrition Screening Initiative(Reference Wellman25) and recommended by the WHO(17) were used: <22·0 kg/m2 (underweight), ≥22·0 and <27·0 kg/m2 (normal weight) and ≥27·0 kg/m2 (overweight).

Statistical analysis

The cut-off points for WC, WHtR and BMI, as well as sensitivity and specificity, were determined by sex (male, female) and age group (20–30, 31–40, 41–50, 51–60 and >60 years old) using receiver-operating characteristic curves. Statistical analyses were performed with R Studio version 3.4. Sensitivity results (Se), on the vertical axis, and the complement of specificity (Sp), on the horizontal axis, were calculated for several cut-off points to allow identification of the best cut-off point for the anthropometric indicators being evaluated. The statistical software package SPSS Statistics version 17.0 was used to estimate the areas under the receiver-operating characteristic curves (AUC) and their 95 % CI. A statistically significant result was considered when the lower limit of the 95 % CI did not include the value 0·50. Prevalence of hypertension and its 95 % CI were also estimated, while considering the study design and sample weights, by sex and age group.

Ethical aspects

The PNS project was approved by the National Research Ethics Commission (report number 10853812.7.0000.0008), assuring participants the right to voluntary participation, anonymity and possibility of withdrawal at any moment of the study, by signing a free and informed consent form.

Results

From the total of 60 202 individuals aged ≥18 years examined in the PNS, 732 had no information on blood pressure measurement and 2240 were younger than 20 years old, and thus did not comply with the criteria to be included in the present study. Thus, the data analysed in the present study refer to 57 230 individuals, 52·7 % of whom were female, 24·3 % were between 20 and 30 years old, 40·2 % had no education or only incomplete elementary education, 47·7 % self-reported themselves as having white skin colour, 33·6 % were hypertensive and 17·1 % were obese (Table 1).

Table 1 Distribution of the study population by sociodemographic, economic and health characteristics. National Health Survey, Brazil, 2013 (n 57 230)

All proportions took sample weights into account.

* Five missing cases.

Hypertension identified by blood pressure measurement (classified according to the Sociedade Brasileira de Cardiologia(1)) or by report of use of antihypertensive medication.

The prevalence of hypertension increased with age in both sexes. Among women, the prevalence ranged from 5·8 (95 % CI 4·9, 6·7) % in the 20–30 years age group to 68·4 (95 % CI 66·4, 70·3) % among those >60 years old. For men, the prevalence ranged from 13·0 (95 % CI 11·5, 14·7) % among those aged 20–30 years to 65·6 (95 % CI 63·2, 68·0) % among those aged >60 years (Table 2).

Table 2 Prevalence of hypertensionFootnote * in the Brazilian population by sex and age group. National Health Survey, Brazil, 2013 (n 57 230)

All proportions took sample weights into account.

* Hypertension identified by blood pressure measurement (classified according to the Sociedade Brasileira de Cardiologia(1)) or by report of use of antihypertensive medication.

The cut-off points identified for WC in males ranged from 88·0 cm in the age group of 20–30 years (AUC=0·665, 95 % CI 0·643, 0·688, Se=61·4 %, Sp=62·1 %) to 95·9 cm for those >60 years old (AUC=0·606, 95 % CI 0·589, 0·623, Se = 57·8 %, Sp=57·9; Table 3). For females, the variation of cut-off points was from 85·0 cm in the age range of 20–30 years (AUC=0·653, 95 % CI 0·624, 0·683, Se=61·7 %, Sp=62·0 %) to 93·2 cm for those aged >60 years (AUC=0·619, 95 % CI 0·605, 0·634, Se=59·0 %, Sp=58·5 %; Table 4).

Table 3 Cut-off points, areas under the receiver-operating characteristic curve (AUC), sensitivity and specificity for waist circumference (WC), waist-to-height ratio (WHtR) and BMI in the prediction of hypertension for males by age group (years). National Health Survey, Brazil, 2013 (n 24 879)

Table 4 Cut-off points, areas under the receiver-operating characteristic curve (AUC), sensitivity and specificity for waist circumference (WC), waist-to-height ratio (WHtR) and BMI in the prediction of hypertension for females by age group (years). National Health Survey, Brazil, 2013 (n 32 351)

For men, WHtR cut-off points ranged from 0·51 in the 20–30 years age group (AUC=0·655, 95 % CI 0·633, 0·678, Se=62·2 %, Sp=62·2 %) to 0·58 for those >60 years old (AUC=0·603, 95 % CI 0·585, 0·620, Se=58·0 %, Sp=58·0 %; Table 3). Among women, the variation was from 0·53 in the 20–30 years age group (AUC=0·656, 95 % CI 0·627, 0·685, Se=62·5 %, Sp=62·5 %) to 0·61 for those aged >60 years (AUC=0·626, 95 % CI 0·611, 0·641, Se=59·1 %, Sp=59·2 %; Table 4).

The analysis of cut-off points for BMI by sex and age groups showed similar performance to that of indicators of fat location. In males, cut-off values ranged from 25·35 kg/m2 in the 20–30 years age group (AUC=0·652, 95 % CI 0·629, 0·674, Se=61·4 %, Sp=61·5 %) to 25·50 kg/m2 for those >60 years old (AUC=0·581, 95 % CI 0·564, 0·598, Se=56·1 %, Sp=56·1 %; Table 3). In females, the variation was from 25·23 kg/m2 in the age group 20–30 years (AUC=0·641, 95 % CI 0·612, 0·671, Se=60·3 %, Sp=60·3 %) to 26·48 kg/m2 for age >60 years (AUC=0·598, 95 % CI 0·583, 0·613, Se=57·1 %, Sp=57·2 %; Table 4).

Discussion

The present study analysed data of a population-based nationwide survey and identified cut-off points and the predictive ability of WC, WHtR and BMI to predict the occurrence of hypertension among Brazilian adults and elderly. All three anthropometric indicators showed good performance in the detection of hypertension, and all AUC 95 % CI lower limits were greater than 0·50.

Previous studies have shown that anthropometric indicators of fat located in the central region of the body are better predictors of cardiometabolic risk, including hypertension, in comparison to BMI(Reference De Koning, Anwar and Merchant10, Reference Ashwell, Gunn and Gibson26). The best performance of these markers can be explained by their association with visceral fat, which is considered a better predictor of risk than total adiposity(Reference De Koning, Anwar and Merchant10). However, the predictive capacity of the anthropometric markers of fat location varies by race/ethnicity and the outcome being evaluated(Reference Zhu, Wang and Heshka9).

The Brazilian population, for example, shows great ethnic diversity, which may explain the differences found in the pattern of body fat distribution in comparison to Caucasian populations, as indicated by correlations found between BMI and fat location measures. In two Brazilian studies that evaluated the performance of fat location indicators with cardiometabolic outcomes, WC was not identified as a good marker of risk and was highly correlated with BMI(Reference Peixoto, Benicio and Latorre27, Reference Haun, Pitanga and Lessa28).

Few studies have evaluated the predictive capacity of anthropometric markers for the prediction of hypertension in Brazil. One of the pioneering studies was conducted by Pereira et al., who analysed the performance of these markers as predictors of hypertension in a population-based study including adults and elderly in the city of Rio de Janeiro. The authors concluded that among the markers of fat location, waist-to-hip ratio was the best predictor of hypertension and it was also less correlated with BMI than WC and WHtR(Reference Pereira, Sichieri and Marins11).

Although some Brazilian studies have shown the superiority of waist-to-hip ratio as a marker of risk for chronic diseases(Reference Pereira, Sichieri and Marins11, Reference Lemos-Santos, Valente and Gonçalves-Silva12), the greater interference in the privacy of the individual to obtain the hip measurement compared with waist circumference has limited its use in epidemiological studies, such as the PNS.

In the present study, the AUC were very similar for the WC, WHtR and BMI cut-off limits, and therefore it is difficult to recognize which is the best marker. In addition, associations between these cut-off limits and the presence of hypertension showed similar performance in both sexes and in all age groups.

As for WC, since the internationally recommended cut-off points were determined based on studies with predominantly white populations, specific guidelines have been established for different ethnicities. Thus, countries such as China and Japan defined new cut-off points, set at 80 cm for women and 85 cm for men(Reference Lear, James and Ko29). In Brazil, studies evaluating the cut-off points of WC based on hypertension screening in adults found values ranging from 89·5 to 96·0 cm for men and from 86·2 to 94·0 cm for women(Reference Silva, Petroski and Peres30, Reference De Oliveira, Ulbrich and Neves31). These values are, in general, higher than those found in the present study, which showed variations in each decade of life, with the greatest differences identified at 40 years old or older in men and 50 years old or older in women.

The hypothesis that WC cut-off points should be the same in all age groups may not be adequate, because of the many physiological changes that occur with ageing. According to a systematic review by Chang et al. which included twenty-five studies conducted in different countries, there is still no agreement on the best cut-off points of WC for elderly individuals, with cut-off points ranging from 90 to 102 cm for men and from 79 to 95·6 cm for women(Reference Chang, Beason and Hunleth32). Also, prediction of hypertension by WC decreases as age increases, according to the resulting sensitivity and specificity values.

In the analysis of WC by sex, it was found that for men in the younger age groups (20–30 and 30–40 years) the best WC cut-off limits for hypertension prediction were lower than that established by the WHO, i.e. >94 cm(17). In these age groups, the cut-off points of WC were 88·0 and 93·3 cm, respectively, meaning that in the younger male population, there is already an increased risk for hypertension for values lower than the recommended ones. However, with increasing age, WC values were more similar to the recommended ones, reaching 95·9 cm in the male population with the oldest age group (>60 years old).

Also for women, the WC cut-off points for hypertension prediction were higher than that established by the WHO, i.e. >80 cm(17), in all age groups, mainly for women over 50 years old, among whom the anthropometric indicators of obesity usually do not perform well in the screening of cardiovascular risks(Reference Pitanga and Lessa14).

In the present study, WC performance among women was similar to that observed for men, showing a tendency to reduced power to predict hypertension in older age groups, especially for those over 60 years old. One possible explanation for this finding is that for the same WC measure in older women, there is more visceral fat than in younger women; hence the discriminatory power of this indicator is changed, especially after menopause(Reference Foucan, Hanley and Deloumeaux33).

In general, among older people, anthropometric measurements may not adequately quantify body fat because of age-related changes in body composition, such as loss of muscle mass, increased body fat, redistribution of adipose tissue and height reduction(Reference Harris, Visser and Everhart18). Therefore, the prediction of disease by anthropometric indicators in older people seems to vary according to the factors associated with biological changes related to age, such as age-related arterial stiffening(Reference Sun19), previous diseases in childhood and in adult life, lifestyle and socio-economic factors(17, Reference Song, Jousilahti and Stehouwer34).

Based on the results of the present study, it can be suggested that the currently recommended WC cut-off points would be more appropriate for Brazilian men after 40 years of age, at least with regard to screening of hypertension. Moreover, it is possible that the risk of hypertension among younger men may be underestimated with the use of the WC cut-off limit of 94 cm(17). Nevertheless, the largest discrepancies with the current recommended WC cut-off of 80 cm(17) were found for women in all age groups, for whom the use of this limit may overestimate the risk of hypertension.

As regards the WHtR anthropometric indicator, Ashwell et al.(Reference Ashwell, Gunn and Gibson26), unlike the findings of the present study, found that this indicator is better than WC in the prediction of cardiometabolic risk factors in a systematic review of studies involving adults from different ethnic groups, including a Brazilian study. It should be emphasized that the outcome evaluated in the Brazilian study included in the review was not hypertension but increased coronary risk. However, the area under the receiver-operating characteristic curve (0·69, 95 % CI 0·67, 0·71) in the WHtR analysis for hypertension was similar to the one found in the present study. Two Brazilian studies evaluating the capacity of WHtR to predict hypertension found favourable results for the efficacy of this indicator for screening purposes, in both sexes(Reference Luz, Barbosa and d’Orsi15, Reference Silva, Petroski and Peres30).

The cut-off points for WHtR identified in the present study, in both sexes and in all age groups, were greater than 0·50, the value usually proposed in the literature(Reference Lee, Lim and Baek36) and similar to those identified in other Brazilian studies, which found values ranging from 0·50 to 0·55 among men and from 0·49 to 0·55 among women(Reference Silva, Petroski and Peres30, Reference Corrêa, Tomasi and Thumé16).

Most international studies have found values slightly smaller than those found in the current study. In Korea, for example, it was found that the most appropriate cut-off point for males was 0·49 and for females, 0·51(Reference Lee, Lim and Baek36), which is lower than the cut-off point of 0·55 estimated in a study with Spaniards to detect cardiovascular risks in both sexes(Reference Cristo Rodríguez Pérez, Del De Leon and Jaime-Aguirre37). It should be noted that these studies took the WC measurement at waist level, the midpoint between the last rib and the iliac crest. Different locations proposed in studies to measure WC may interfere with the identification of cut-off points for WC as well as for WHtR, hence comparisons can be difficult(Reference Vasques, Rosado and Rosado38).

In the present study, BMI showed similar performance to that of fat location markers in the prediction of hypertension, in both sexes and in all age groups, with a reduction in sensitivity and specificity values as age increased. The BMI cut-off points estimated to predict hypertension among individuals up to 60 years old were compatible with the overweight condition, while for individuals over 60 years old, the identified cut-off value is in the BMI normal range for age.

Based on the present results, BMI showed sensitivity and specificity values for the different cut-off points by sex and age similar to those found for WC and WHtR. In addition, BMI is the anthropometric indicator most frequently used in health services and in Brazilian surveys.

In the present study, in all sex and age groups, moderate values were estimated for AUC, sensitivity and specificity for the cut-off points of the anthropometric markers analysed. Nevertheless, the AUC values for the three anthropometric markers analysed herein were similar to those observed in a systematic review conducted by Ashwell et al.(Reference Ashwell, Gunn and Gibson26). Likewise, in a longitudinal 5-year study about the performance of anthropometric markers for detecting hypertension in Chinese adults, Ren et al.(Reference Ren, Su and Wang6) showed moderate sensitivity and specificity for the cut-off points identified and AUC values ranging from 0·57 to 0·72, suggesting that other factors may also contribute to the prediction of hypertension such as socio-economic status, lifestyle, and combinations of genes that are associated with hypertension and gene–environment interactions that may lead to blood pressure variation.

One limitation of the present study is the lack of information on hip circumference, which would allow an evaluation of the performance of waist-to-hip ratio in predicting hypertension, which has been considered the fat location marker with the best predictive power for hypertension in the Brazilian population(Reference Pereira, Sichieri and Marins11).

On the other hand, the present study has the strength of analysing a nationwide representative sample of the Brazilian population using direct anthropometric measures, since previous studies conducted on this matter in Brazil have been limited to specific cities.

Conclusion

In conclusion, the present study showed that, for Brazilian adults and elderly, WC, WHtR and BMI had similar performance in the prediction of hypertension. Additionally, the identified cut-off points for WHtR were similar to those reported in the literature. For both men and women, the limits estimated for WC and BMI were different from those recommended internationally, meaning that their application may lead to under- or overestimation of the hypertension risk, depending on the age group under consideration.

Acknowledgements

Acknowledgements: The authors are thankful to the Ministry of Health of Brazil and the Secretary of Health Surveillance for supporting the National Health Survey 2013. Financial support: This work was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Brazil, through a Master grant (A.P.A.S; Finance Code 001). However, CAPES had no role in the design, analysis or writing of this manuscript and the authors have no conflicts of interest to be reported. Conflict of interest: None. Authorship: A.P.A.S. contributed to the literature review, statistical analysis, interpretation of data and drafting of the manuscript. A.P.M., N.F.M. and R.S. contributed in the interpretation of data and critical revision of the manuscript for important intellectual content. R.A.P. contributed in the article design, interpretation of data and critical revision of the manuscript for important intellectual content. P.R.M.R. and M.G.F. contributed in the article concept, design, statistical analysis, interpretation of results, writing and critical revision of the manuscript for important intellectual content. Ethics of human subject participation: This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the National Research Ethics Commission, Brazil (report number 10853812.7.0000.0008). Written informed consent was obtained from all subjects.

References

1. Sociedade Brasileira de Cardiologia (2016) 7a Diretriz Brasileira De Hipertensão Arterial. Arq Bras Cardiol 107, 1103.Google Scholar
2. World Health Organization (2018) Noncommunicable Diseases Country Profiles. Geneva: WHO.Google Scholar
3. Booth, HP, Prevost, AT & Gulliford, MC (2016) Severity of obesity and management of hypertension, hypercholesterolaemia and smoking in primary care: population-based cohort study. J Hum Hypertens 30, 4045.CrossRefGoogle ScholarPubMed
4. Tchernof, A & Despres, JP (2013) Pathophysiology of human visceral obesity: an update. Physiol Rev 93, 359404.CrossRefGoogle ScholarPubMed
5. Dorresteijn, JAN, Visseren, FLJ & Spiering, W (2012) Mechanisms linking obesity to hypertension. Obes Rev 13, 1726.CrossRefGoogle Scholar
6. Ren, Q, Su, C, Wang, H et al. (2016) Prospective study of optimal obesity index cut-off values for predicting incidence of hypertension in 18–65-year-old Chinese adults. PLoS One 11, e0148140.CrossRefGoogle ScholarPubMed
7. World Health Organization (2000) Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. WHO Technical Report Series no. 894. Geneva: WHO.Google Scholar
8. World Health Organization (2011) Waist Circumference and Waist–Hip Ratio. Report of a WHO Expert Consultation, Geneva, 8–11 December 2008. Geneva: WHO.Google Scholar
9. Zhu, S, Wang, Z, Heshka, S et al. (2002) Waist circumference and obesity-associated risk factors among whites in the Third National Health and Nutrition Examination Survey: clinical action thresholds. Am J Clin Nutr 76, 743749.CrossRefGoogle ScholarPubMed
10. De Koning, L, Anwar, T, Merchant, JP et al. (2007) Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: meta-regression analysis of prospective studies. Eur Heart J 28, 850856.CrossRefGoogle ScholarPubMed
11. Pereira, RA, Sichieri, R & Marins, VMR (1999) Razão cintura/quadril como preditor de hipertensão arterial. Cad Saude Publica 15, 333344.CrossRefGoogle Scholar
12. Lemos-Santos, MGF, Valente, JG, Gonçalves-Silva, RM et al. (2004) Waist circumference and waist-to-hip ratio as predictors of serum concentration of lipids in Brazilian men. Nutrition 20, 857862.CrossRefGoogle ScholarPubMed
13. Ashwell, M & Gibson, S (2016) Waist-to-height ratio as an indicator of ‘early health risk’: simpler and more predictive than using a ‘matrix’ based on BMI and waist circumference. BMJ Open 6, e010159.CrossRefGoogle ScholarPubMed
14. Pitanga, FJG & Lessa, I (2006) Razão cintura-estatura como discriminador do risco coronariano de adultos. Rev Assoc Med Bras 52, 157161.CrossRefGoogle Scholar
15. Luz, RH, Barbosa, AR & d’Orsi, E (2016) Waist circumference, body mass index and waist-height ratio: are two indices better than one for identifying hypertension risk in older adults? Prev Med 93, 7681.CrossRefGoogle ScholarPubMed
16. Corrêa, MM, Tomasi, E, Thumé, E et al. (2017) Razão cintura-estatura como marcador antropométrico de excesso de peso em idosos brasileiros. Cad Saude Publica 33, e00195315.CrossRefGoogle Scholar
17. World Health Organization (1995) Physical Status: The Use and Interpretation of Anthropometry. Report of a WHO Expert Committee. WHO Technical Report Series no. 854. Geneva: WHO.Google Scholar
18. Harris, TB, Visser, M, Everhart, J et al. (2000) Waist circumference and sagittal diameter reflect total body fat better than visceral fat in older men and women. The health, aging and body composition study. Ann N Y Acad Sci 904, 462473.CrossRefGoogle ScholarPubMed
19. Sun, Z (2015) Aging, arterial stiffness and hypertension. Hypertension 65, 252256.CrossRefGoogle ScholarPubMed
20. Instituto Brasileiro de Geografia e Estatística (2011) Características Étnico-Raciais da População: Um Estudo das Categorias de Classificação de Cor ou Raça: 2008. Rio de Janeiro, RJ: IBGE, Coordenação de População de Indicadores Sociais.Google Scholar
21. Souza-Júnior, PRB, Freitas, MPS, Antonaci, GA et al. (2015) Desenho da amostra da Pesquisa Nacional de Saúde 2013. Epidemiol Serv Saude 24, 207216.CrossRefGoogle Scholar
22. Damacena, GN, Szwarcwald, CL, Malta, DC et al (2015) O processo de desenvolvimento da Pesquisa Nacional de Saúde no Brasil, 2013. Epidemiol Serv Saude 24, 197206.CrossRefGoogle Scholar
23. Instituto Brasileiro de Geografia e Estatística & Ministério da Saúde (2013) Pesquisa Nacional de Saúde – PNS 2013: Manual de Antropometria. Rio de Janeiro, RJ: IBGE, Boletim de Serviço; available at https://biblioteca.ibge.gov.br/visualizacao/instrumentos_de_coleta/doc3426.pdf Google Scholar
24. Malta, DC, Santos, NB, Perillo, RD et al. (2016) Prevalence of high blood pressure measured in the Brazilian population, National Health Survey, 2013. Sao Paulo Med J 134, 163170.CrossRefGoogle ScholarPubMed
25. Wellman, NS (1994) The Nutrition Screening Initiative. Nutr Rev 52, 8 Pt 2, S44S47.CrossRefGoogle ScholarPubMed
26. Ashwell, M, Gunn, P & Gibson, S (2012) Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev 13, 275286.CrossRefGoogle ScholarPubMed
27. Peixoto, MRG, Benicio, MHD, Latorre, MRDO et al. (2006) Circunferência da cintura e índice de massa corporal como preditores da hipertensão arterial. Arq Bras Cardiol 87, 462470.CrossRefGoogle Scholar
28. Haun, DR, Pitanga, FJG & Lessa, I (2009) Razão cintura/estatura comparado a outros indicadores antropométricos de obesidade como preditor de risco coronariano elevado. Rev Assoc Med Bras 55, 705711.CrossRefGoogle Scholar
29. Lear, SA, James, PT, Ko, GT et al. (2010) Appropriateness of waist circumference and waist-to-hip ratio cutoffs for different ethnic groups. Eur J Clin Nutr 64, 4261.CrossRefGoogle ScholarPubMed
30. Silva, DAS, Petroski, EL & Peres, MA (2013) Accuracy and measures of association of anthropometric indexes of obesity to identify the presence of hypertension in adults: a population-based study in Southern Brazil. Eur J Nutr 52, 237246.CrossRefGoogle ScholarPubMed
31. De Oliveira, CM, Ulbrich, AZ, Neves, FS et al. (2017) Association between anthropometric indicators of adiposity and hypertension in a Brazilian population: Baependi Heart Study. PLoS One 12, e0185225.CrossRefGoogle Scholar
32. Chang, SH, Beason, TS, Hunleth, JM et al. (2012) A systematic review of body fat distribution and mortality in older people. Maturitas 72, 175191.CrossRefGoogle ScholarPubMed
33. Foucan, L, Hanley, J, Deloumeaux, J et al. (2002) Body mass index (BMI) and waist circumference (WC) as screening tools for cardiovascular risk factors in Guadeloupean women. J Clin Epidemiol 55, 990996.CrossRefGoogle ScholarPubMed
34. Song, X, Jousilahti, P, Stehouwer, CD et al. (2015) Cardiovascular and all-cause mortality in relation to various anthropometric measures of obesity in Europeans. Nutr Metab Cardiovasc Dis 25, 295304.CrossRefGoogle ScholarPubMed
35. Hsieh, SD & Yoshinaga, H (1995) Abdominal fat distribution and coronary heart disease risk factors in men – waist/height ratio as a simple and useful predictor. Int J Obes Relat Metab Disord 19, 585589.Google ScholarPubMed
36. Lee, JW, Lim, NK, Baek, TH et al. (2015) Anthropometric indices as predictors of hypertension among men and women aged 40–69 years in the Korean population: the Korean Genome and Epidemiology Study. BMC Public Health 15, 140.CrossRefGoogle ScholarPubMed
37. Cristo Rodríguez Pérez, M Del De Leon, AC, Jaime-Aguirre, A et al. (2010) El cociente perímetro abdominal/estatura como índice antropométrico de riesgo cardiovascular y de diabetes. Med Clin (Barc) 134, 386391.Google Scholar
38. Vasques, ACJ, Rosado, EFPL & Rosado, GP (2009) Diferentes aferições do diâmetro abdominal sagital e do perímetro da cintura na predição do HOMA-IR. Arq Bras Cardiol 93, 511518.CrossRefGoogle Scholar
Figure 0

Table 1 Distribution of the study population by sociodemographic, economic and health characteristics. National Health Survey, Brazil, 2013 (n 57 230)

Figure 1

Table 2 Prevalence of hypertension* in the Brazilian population by sex and age group. National Health Survey, Brazil, 2013 (n 57 230)

Figure 2

Table 3 Cut-off points, areas under the receiver-operating characteristic curve (AUC), sensitivity and specificity for waist circumference (WC), waist-to-height ratio (WHtR) and BMI in the prediction of hypertension for males by age group (years). National Health Survey, Brazil, 2013 (n 24 879)

Figure 3

Table 4 Cut-off points, areas under the receiver-operating characteristic curve (AUC), sensitivity and specificity for waist circumference (WC), waist-to-height ratio (WHtR) and BMI in the prediction of hypertension for females by age group (years). National Health Survey, Brazil, 2013 (n 32 351)

You have Access
2
Cited by

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Cut-off points of anthropometric markers associated with hypertension in the Brazilian population: National Health Survey, 2013
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Cut-off points of anthropometric markers associated with hypertension in the Brazilian population: National Health Survey, 2013
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Cut-off points of anthropometric markers associated with hypertension in the Brazilian population: National Health Survey, 2013
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *