Clinical variables considered risk factors for the metabolic syndrome: a cross-sectional study

ABSTRACT

Objective

To identify the main risk factors for metabolic syndrome and its relationship with the perception of quality of life in Brazilian fishing colonies.

Methods

We included 77 participants aged > 18 years. Metabolic syndrome and quality of life were the main study outcomes. We considered a significance level < 0.05 and all procedures were approved by the ethics committee.

Results

Most participants are male, single, economic class D-E, working hours of 6 to 8 hours, length of service from 1 to 5 years, and dedicated exclusively to fishing.

Conclusion

Abdominal perimeter and blood pressures were the most frequent criteria and the greatest contribution to metabolic syndrome. Although quality of life had a higher score for the social relationship domain, in this study, the physical domain was the only one associated with another observation, in which we observed a significant correlation with systolic blood pressure.

Keywords:
Health Policy; Anthropometry; Public Health; Quality of Life; Vulnerable Populations

RESUMO

Objetivo

Identificar os principais fatores de risco para a síndrome metabólica e sua relação com a percepção da qualidade de vida em colônias pesqueiras brasileiras.

Métodos

Incluímos 77 participantes com idade > 18 anos. Síndrome metabólica e qualidade de vida foram os principais desfechos do estudo. Consideramos nível de significância < 0,05 e todos os procedimentos foram aprovados pelo comitê de ética.

Resultados

A maioria dos participantes é do sexo masculino, solteiros, classe econômica D-E, carga horária trabalhada de 6 a 8 horas, tempo de serviço de 1 a 5 anos e dedicados exclusivamente à pesca. Conclusão: Perímetro abdominal e pressão arterial foram os critérios mais frequentes e de maior contribuição para a síndrome metabólica. Apesar de a qualidade de vida apresentar maior escore para o domínio relações sociais, neste estudo, o domínio físico foi o único associado a outra observação, na qual observamos correlação significativa com a pressão arterial sistólica.

Palavras-chaves:
Política de Saúde; Populações Vulneráveis; Saúde Pública; Síndrome Metabólica; Qualidade de Vida

RESUMEN

Objetivo

Identificar los principales factores de riesgo del síndrome metabólico y su relación con la percepción de la calidad de vida en las colonias pesqueras brasileñas.

Métodos

se incluyeron 77 participantes mayores de 18 años. El síndrome metabólico y la calidad de vida fueron los principales resultados del estudio. Se consideró un nivel de significancia <0.05 y todos los procedimientos fueron aprobados por el comité de ética.

Resultados

La mayoría de los participantes son hombres, solteros, clase económica D-E, jornada laboral de 6 a 8 horas, antigüedad de 1 a 5 años y dedicados exclusivamente a la pesca.

Conclusión

La circunferencia de la cintura y la presión arterial fueron los criterios más frecuentes y la mayor contribución al síndrome metabólico. Aunque la calidad de vida tuvo una puntuación más alta para el dominio de relaciones sociales, en este estudio, el dominio físico fue el único asociado con otra observación, en la que observamos una correlación significativa con la presión arterial sistólica.

Palabras clave:
Calidad de Vida; Poblaciones Vulnerables; Política de Salud; Salud Pública; Síndrome Metabólico

INTRODUCTION

Noncommunicable diseases are responsible for 38 million deaths worldwide, 16 million occur between 30-70 age, 85% in developing countries. In Brazil, they are related to high morbidity and mortality rates and 70% of health expenditures; among them is a metabolic syndrome, abdominal obesity (verified via the perimeter in cm), dyslipidemia, dysglycemia, and hypertension,¹ with the prevalence of 20 to 35% and more observed in males.^2,3

Unfavorable conditions, socioeconomic and demographic vulnerabilities (such as inaccessibility to health services, drinking water, and sanitary sewage) are related to various diseases and cause impacts on the quality of life.⁴ These susceptibility conditions are present in communities inhabited by artisanal fishermen (workers who earn income from extractive fishing followed by the fish trade); these fishermen are exposed to factors that weaken health and affect the quality of life, such as: precarious work environments, excessive workload, occupational stress, sleep disorders, and high energy expenditure.⁴

However, there is a scarcity of studies on metabolic syndrome and quality of life in vulnerable populations, and this makes it difficult to design health policy to promote, protect and/or recover the health of this population; itis in this perspective that the justification for conducting this study is supported. Our aim was to identify the main risk factors (Glycemia, Blood pressure, Triglycerides, HDL-cholesterol, Abdominal perimeter, Body Mass Index) for metabolic syndrome and its relationship with the perception of quality of life in Brazilian fishing colonies.⁵

METHODS

A cross-sectional epidemiological study conducted according to the guidelines of the STrengthening the Reporting of OBservational studies in Epidemiology.⁶ Sociodemographic characteristics were used as exposure variables and metabolic syndrome was the outcome variable.⁷

In the state of Tocantins (northern Brazil), there are 36 fishing colonies registered with the Institute of Rural Development of the State of Tocantins. Among them, the colonies were selected “Z22” and “Porto Real”, located in the vicinity of the Tocantins River basin—the second largest river in Brazil (172.828km²).⁵

We held meetings with the presidents of the fishermen's colonies (2019) and explained the details of the research. We started the collection (abdominal perimeter, blood pressure, fasting glycemia, triglycerides and HDL serum cholesterol, body mass index, WHOQOL-bref and sociodemographic questionnaire) only after signing the free and informed consent form of each participant. The study is in accordance with the Declaration of Helsinki and all procedures were previously approved by the ethics committee for research with human (Resolutions 196/1996 and 466/2012) beings of a higher education institution (graduate and postgraduate) in Brazil (number: 3219733). All artisanal fishermen were invited ≥ 18 years registered in the selected colonies: 132 fishermen (men and women, 77 of the Z-22 colony, located in the municipality of Ipueiras-TO and 55 in the Porto Real colony, located in the city of Porto Nacional-TO). Participation in the study was voluntary.

Metabolic syndrome and quality of life were the main outcomes of this study; additionally, we verified the presence of metabolic disorders (abdominal obesity, hypertriglyceridemia, dyslipidemia, low HDL, hypertension, and fasting hyperglycemia), and according to the National Cholesterol Education Program-Adult Treatment Panel III.⁸ The perception of quality of life was evaluated through the World Health Organization Quality of Life(WHOQOL-bref).

We considered socioeconomic, demographic, anthropometric data (abdominal perimeter and BMI), biochemical analyses (glucose, HDL-cholesterol, and triglycerides), blood pressure, and WHOQOL-bref scores. Metabolic syndrome and perception of quality of life are outcome variables; the others are exposure variables.

To determine metabolic syndrome, the diagnostic criteria established by the National Cholesterol Education Program-Adult Treatment Panel III (Table 1), which defined the presence of three of the five components adopted and that do not distinguish ethnicity, making them convenient for the sample studied. BMI was classified according to the world health organization: low weight (≤ 18.5), recommendable (18.5-24.9), overweight (25-29.9), obesity I (30-34.9), obesity II (35-39.9), and obesity III (≥ 40).⁹

Table 1
Diagnostic criteria for metabolic syndrome (NCEP-ATP III).

Variables	Values
Triglycerides (mg/dL)	> 150
HDL-cholesterol (mg/dL)
Man	< 40
Woman	< 50
Blood pressure (mmHg)	≥ 130/85
Abdominal perimeter (cm)
Man	≥ 102
Woman	≥ 88
Glucose (mg/dL)	≥ 110

• Source: elaborated by the authors

WHOQOL-bref instrument comprises 26 facets (one item per each facet) clustered into four domains:¹⁰ (i) Physical Health (7 facets, pain and discomfort; energy and fatigue; sleep and rest; mobility; activities of everyday life; dependence on medication or treatments; work capacity), (ii) Psychological (6 facets, positive feelings; thinking, learning, concentration memory; self-esteem; body image and appearance; negative feelings; spirituality/religion/personal beliefs), (iii) Social Relationships (3 facets, personal relationships; sexual activity; social support), and (iv) Environment (8 facets, physical security and protection; home environment; financial resources; health and social care: availability and quality; opportunities to acquire new information and skills; participation in recreation/leisure opportunities; physical environment: pollution/noise/climate; transport),¹¹ and 2 items of a general nature: (i) first, an item asking how the respondent would rate his/her quality of life (labeled as “overall QOL”), and (ii) second, an item asking how the respondent would rate his/her satisfaction with his/her health (labeled as “overall health”). All WHOQOL-bref facets are measured using a five-point Likert scale (1 to 5), with the F1.4, F11.3 and F8.1 measured on an inverted scale.¹² The main characteristics of the WHOQOL-bref instrument are as follows: (i) it is cross-cultural; (ii) it can be applied to individuals living in different contexts; (iii) it is capable of capturing individuals’ own views of their well-being; and (iv) it should be self-administered if participants reveal enough reading skills.¹³

The characterization of socioeconomic status was performed through the Brazilian Economic Classification questionnaire;¹⁴ we added questions of characterization of the participants (gender and age). Biochemical measurements were collected by venous puncture and after fasting from 8 to 10 hours, 5 mL of blood in a tube without anticoagulant, glucose measurement by colorimetric enzymatic method, and triglyceride HDL cholesterol measurement by colorimetric enzymatic method with automated spectrophotometer reading.^15,16

All participants had a diagnosis of arterial hypertension issued by medical report, also, we measured blood pressure using an aneroid sphygmomanometer and stethoscope, according to the recommendations of the VII Brazilian Hypertension Guideline; the abdominal perimeter by means of anthropometric tape, according to the recommendation of the World Health Organization (between the last rib and the iliac crest); height with a Dry Wall Stator 206; and body mass with an Omron HBF 514.

To minimize the bias of data collection and tabulation, all measurements were performed by a previously trained team and the database was filled out with independent double typing and validation by a third independent researcher.

There were no studies that estimated the prevalence of metabolic syndrome in artisanal fishermen, considering as a parameter to calculate the sample size the variation in prevalence (14.9 to 65.3%) found by Vidigal et al.¹⁷ in a systematic review on the prevalence of metabolic syndrome in adults, we, therefore, estimated a minimum sample size of 50 participants.

We used the Shapiro Wilk test to verify the normality of the data, in which the quantitative ones were presented by means and standard deviation. We used the Pearson test to verify the relationship between metabolic syndrome and the perception of quality of life (α = 0.05).

RESULTS

We included 132 participants, however, there was a sample loss of 55 participants who did not agree to: collect biochemical samples, answer the questionnaires, sign the free and informed consent form, attend on the day of collection. The final sample consisted of 77 artisanal fishermen registered in the Z-22 colonies, located in the municipality of Ipueiras-TO, and Porto Real colony, located in the city of Porto Nacional-TO.

Most of the participants were male, single, economy class D-E, workload worked from 6 to 8 hours, the service time of 1 to 5 years, dedicated exclusively to fishing. Table 2 presented the details of demographic and economic characteristics.

Table 2
Demographic and economic characteristics of the sample – Brazilian fishermen residing in the state of Tocantins (n = 77).

Variables	n	%
Sex
male	47	61.04
female	30	38.96
Companion (not)	44	59.46
Son (total)*
0	10	13.89
1	6	8.33
2	11	15.28
≥ 3	45	62.50
Economic class
B2	4	5.19
C1	10	12.99
C2	29	37.66
D-E	34	44.16
Workload (hours)*
6-8	27	40.91
10-12	18	27.27
> 12	21	31.82
Rest (hours)*
0	15	21.13
1	32	45.07
2	24	33.80
Service time (years)*
< 1	14	18.92
1-5	23	31.08
6-10	21	28.38
11-19	10	13.51
> 20	6	8.11
Workplaces *
1	57	82.61
2	11	15.94
3	1	1.45

• Source: elaborated by the authors
• ^*
  Observation in which only a part of the sample responded to the variable.

We observed that: abdominal perimeter and blood pressures were the most frequent criteria and the greatest contribution to the diagnosis of metabolic syndrome (Table 3); and the perception of quality of life had the highest score in the social relations domain (Table 4).

Table 3
Variables of risk factors for the onset of metabolic syndrome – Brazilian fishermen residing in the state of Tocantins (n = 77).

Variables	n	%	Mean (SD)
Glycemia (mg/dL) #			109.62 (43.42)
Ideal	49	74.24
Risk	17	25.76
Blood pressure (mmHg)			124.65 (16.50); a 78.66 (12.70) b
Ideal	41	53.25
Risk	36	46.75
Triglycerides (mg/dl) #			148.93 (94.34)
Ideal	49	66.22
Risk	24	33.78
HDL-cholesterol (mg/dl) #			47.20 (10.58)
Ideal	46	62.16
Risk	28	37.84
Abdominal perimeter (cm)			96.83 (10.85)
Ideal	39	50.65
Risk	38	49.35
Body Mass Index (kg/m2)			27.31 (4.92)
Low weight	1	1.30
Lean	27	35.06
Overweight	30	38.96
Obesity	19	24.68

• Source: elaborated by the authors
• SD: Standard Deviation.
• ^#
  Observations with sample loss – the absence of the participant in the collection of blood samples; ^a Systolic Blood Pressure; ^b Diastolic Blood Pressure.

Table 4
Descriptive data of the quality-of-life domains of the sample – Brazilian fishermen residing in the state of Tocantins (n = 77).

Domains	Mean	SD	Minimal	Maximum
Physical (score)	15.51	2.19	7.43	20.00
Psychological (score)	15.63	2.12	10.40	19.33
Social relations (score)	15.92	2.37	9.33	20.00
Environment (score)	13.01	2.13	9.50	18.50
Self-assessment (score)	14.63	2.49	10.00	20.00
Overall quality of life (score)	14.72	1.81	8.17	18.77

• Source: elaborated by the authors
• SD: Standard Deviation.

In addition (Table 5), we observed a significant correlation between the physical domain and systolic blood pressure (weak correlation magnitude).

Table 5
Relationship between risk factors for the onset of metabolic syndrome with quality of Life – Brazilian fisherman residing in the state of Tocantins (n = 77).

Variables	Physical		Psychological		Social relations		Environment		Self-assessment
	r	p *	r	p	r	p	r	p	r	p
Glycemia	-0.544	0.6669	0.0173	0.8912	-0.006	0.9584	0.1344	0.2857	0.0708	0.5754
Triglycerides	0.1002	0.4199	-0.0297	0.8115	-0.0910	0.4673	0.0726	0.5591	-0.0649	0.6016
HDL	0.0278	0.8231	0.0545	0.6616	-0.0319	0.7993	-0.2096	0.0887	0.1098	0.3763
SBP	0.2705	0.0235	0.1413	0.2432	0.0887	0.4685	0.0317	0.7945	0.0346	0.7760
DBP	0.2010	0.0952	-0.0018	0.9880	-0.0815	0.5057	0.0235	0.8469	-0.0161	0.8947
BP	-0.0020	0.9868	-0.0815	0.5025	0.1652	0.1748	0.2142	0.0749	-0.1997	0.0974
BMI	-0.0131	0.9144	-0.1032	0.3952	0.1820	0.1344	0.1878	0.1196	-0.1234	0.3087

• Source: elaborated by the authors
• SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; BP: Blood Pressure; BMI: Body Mass Index.
• r: Pearson test; * Significance level (p < 0,05).

DISCUSSION

By estimating the prevalence of metabolic syndrome and analyzing the factors associated with metabolic syndrome in artisanal fishermen, we found a prevalence of metabolic syndrome of 32.47%, being more prevalent in males, and who have only family income from fishing. Regarding the risks of developing the metabolic syndrome, 74.24% had ideal glycemic values, 49.35% had their abdominal perimeter at risk and 46.75% had a risk for arterial hypertension. Regarding the perception of quality of life, we found that the social relationship was better evaluated by fishermen and the environment had the lowest score. We observed a positive and statistically significant relationship between the physical domain and systolic blood pressure when relating quality of life to the risk of developing metabolic syndrome.

Metabolic syndrome is a serious public health problem affecting about 25% of the world population, its presence is associated with the development of cardiovascular problems, accounting for 7% of mortality and 17% of deaths related to chronic diseases.¹⁸ The overall prevalence of metabolic syndrome found in this study was 32.47%, higher than the overall prevalence.

The population of fishermen registered in The Z22 Colonies located in Ipueiras and Porto real in Porto Nacional, Tocantins, presented a moderate risk (32.47%) for the development of cardiovascular diseases, according to the classification adopted by the NCEP-ATP. The prevalence can, therefore, be altered according to the classification criteria used (this shows the fragility of the evidence in this context, which leaves room for different interpretations).

Although few studies have evaluated the metabolic syndrome in artisanal fishermen, a study conducted in the Pontal da Barra community, in the municipality of Maceió-AL conducted with fishermen, had a prevalence of 49% of the population studied with metabolic syndrome, using the same criteria used in the present study.¹⁹

Social determinants, especially poverty, have a great correlation with the frequency and intensity of risk factors for non-communicable diseases and diseases, being an important risk factor in the evolution of cardiovascular diseases in the most vulnerable populations.¹ The high prevalence of metabolic syndrome in this study may be justified in part by the socioeconomic and demographic vulnerability to which they are exposed, as well as low schooling and difficult access to health services, conditions that directly influence the development of diseases.

Variables with the highest prevalence, in this study, were: increased abdominal perimeter (man ≥ 102; woman ≥ 88), high blood pressure (≥ 130/85), low HDL-C levels (Man < 40, woman <50), and increased triglyceride level (>150). Eating habits may be related to the nutritional context of this population, which is, therefore, something that deserves further studies.²⁰

BMI and abdominal perimeter of the fishermen are altered. It was observed that the abdominal perimeter was the variable with the highest predicting power for the development of metabolic syndrome. Abdominal fat contributes to the high risk of myocardial infarction and has been the most prevalent indicator in the diagnosis of metabolic syndrome.²¹

In a study conducted by Pires et al.²² in northern Angola, high BMI and central obesity have been strongly associated with cardiovascular diseases. These authors reinforce the importance of strategies for prevention, early diagnosis, and access to drug treatment for cardiovascular comorbidities. The increase in the circumference/perimeter of the abdomen (central obesity) is related to socioeconomic and cultural changes around the world (those caused significant changes in food consumption and in the number of activities, with a predominant increase in sedentary women).²³

Metabolic syndrome is firmly correlated with social determinants because it influences food, physical activity, and unhealthy lifestyle habits, and may contribute to the onset of chronic diseases.²⁴ This fact can be explained by the high prevalence of pre-obesity and obesity found in this study, corroborating the fact that obesity is a triggering factor of metabolic syndrome in this population.

We observed that hypertension had a considerable prevalence (46.75%), and this finding corroborates a study carried out by Barbosa et al.¹⁹, with fishermen, as it showed that 38% of the studied population were hypertensive and 32% were pre-hypertensive. Considered one of the most prevalent diseases in the world population, hypertension configures itself as a public health problem, being the main risk factor for cardiovascular morbidity and mortality and its consequences represent a high frequency in emergency services in Brazil and is a challenge for primary care the health.²⁵

Although the Brazilian Society of Diabetes describes that diabetics are at high risk for chronic diseases, in our study, the low percentage of diabetics (25.76%), as well as in the study by Barbosa et al.¹⁹ (5%), diabetes does not seem to represent one of the important findings as a risk factor for metabolic syndrome.

However, central obesity seems to be the preponderant factor for the development of metabolic syndrome, which in turn is related to the development of type II diabetes mellitus and changes in blood pressure, which reflects on the quality of life of the population and, therefore,, attention is needed for the search for ways that can prevent or minimize the damage caused by this morbidity.²⁶

Regarding the lipid profile of fishermen, 66.22% had triglycerides within the normal range. When analyzing HDL cholesterol, 62.16% presented a value within the desirable range. These findings can be justified by the eating habits of this population, who have a fish-based diet, which has a low saturated fat content.

As for the perception of quality of life of artisanal fishermen, we found that the scores in the social relation's domain had higher evaluation (15.92) and the environment domain, which concerns physical safety, home environment, financial resources, health care among others had a lower rating (13.01). These results can be explained, in part, by the oscillation of living conditions throughout the year linked to the fishing period, working conditions, and commercialization of fish.²⁷ Also, the quality of life of this population is affected in different ways, e.g., fishermen spend a lot of time working (on the river), their homes have a precarious environment (poor safety and hygiene), and health care is difficult to access.⁵

When evaluating the correlation between the risk factors for metabolic syndrome and the quality of life domains, only a low correlation was obtained with blood pressure and the physical domain of quality of life. The physical domain comprises the facets of pain and discomfort, energy and fatigue, sleep and rest, mobility, activities of daily living, dependence on medication or treatment, and ability to work.²⁸

Although the occupation of artisanal fishermen is among the oldest professions, there is a gap in the literature on studies that assess the health conditions of these individuals. The results obtained in this study are important for a better understanding of fishermen's health and allow for a reorientation of public health promotion policies for similar populations.

When considering the indicators for metabolic syndrome, predominantly associated with lifestyle, it is observed that, despite artisanal fishermen being considered a rural, traditional, riverside population, their lifestyles seem to have changed over the years, favoring the development of non-communicable diseases and conditions, so commonly observed in large urban centers, especially those related to: food consumption, physical exercise, and sedentary behavior.

CONCLUSION

The extrapolation of these results should be viewed with caution; it is recommended to consider, in addition to socio-cultural aspects, the possibility of migration of habits and lifestyles over the years. The implications of these findings for clinical practice support the use of health indicators (body composition, body proportionality, and hemodynamic/metabolic variables) to monitor patients.

The limitations of this study are related to the sample for convenience, absence of information on diet pattern and food consumption and with regard to losses due to non-attendance at any of the stages of the research; in addition, we believe that abdominal perimeter is a limited variable (despite being the most used in studies on metabolic syndrome), as it does not consider body proportionality (i.e., shorter individuals have smaller perimeters, which does not mean lower risks). Finally, we recommend further studies, in this context, that include measurements of central obesity considering height, in order to individualize the body proportionality of each participant (e.g., the waist-to-height ratio).^29–35

In conclusion, abdominal perimeter and blood pressures were the most frequent criteria and the greatest contribution to the diagnosis of metabolic syndrome. Although quality of life had a higher score for the social relationships domain, in this study, the physical domain was the only one associated with another observation, in which there was a significant correlation with systolic blood pressure.

ACKNOWLEDGMENTS

We thank the Fishing Colonies for their trust, support, and participation in this project; also, to the Dean of Postgraduate (PROPESQ), and the Universidade Federal do Tocantins for their support and encouragement to research

• FINANCIAL SUPPORT This article was partially supported by Sistema de Gestão da Programação Embrapa no Macroprograma 4 (code: 04.13.09.001.00), named to Erika da Silva Maciel (Coordenadora). Research project title: Avaliação da percepção da qualidade de vida e fatores associados em comunidades pesqueiras do estado do Tocantins – Brasil.

REFERÊNCIAS

• ¹
  Malta DC, Bernal RTI, Lima MG, Caribé SSA, Silva MMA, Freitas MIF et al. Doenças crônicas não transmissíveis e a utilização de serviços de saúde: análise da Pesquisa Nacional de Saúde no Brasil. Rev Saude Publica. 2017;51(1):1s-10s.
• ²
  Santos FAA, Back IDC, Giehl MWC, Fassula AS, Boing AF, González-Chica DA. Nível de atividade física de lazer e sua associação com a prevalência de síndrome metabólica em adultos: estudo de base populacional. Rev Bras Epidemiol. 2020 jul;23:1-13. http://dx.doi.org/10.1590/1980-549720200070
  » http://dx.doi.org/10.1590/1980-549720200070
• ³
  Li Y, Zhao L, Yu D, Wang Z, Ding G. Metabolic syndrome prevalence and its risk factors among adults in China: a nationally representative cross-sectional study. PLoS ONE. 2018 Jun;13(6):e0199293. http://dx.doi.org/10.1371/journal.pone.0199293
  » http://dx.doi.org/10.1371/journal.pone.0199293
• ⁴
  Luisi C, Figueiredo FWS, Sousa LVA, Quaresma FRP, Maciel ES, Adami F. Prevalence of and factors associated with metabolic syndrome in afro-descendant communities in a situation of vulnerability in Northern Brazil: a cross-sectional study. Metab Syndr Relat Disord. 2019 maio;17(4):204-9. http://dx.doi.org/10.1089/met.2018.0107 PMid:30888909.
  » http://dx.doi.org/10.1089/met.2018.0107
• ⁵
  Silva BKR, Dos Santos Figueiredo FW, Da Silva Maciel E, Quaresma FRP, Adami F. Factors associated with perceived quality of life in artisanal fishermen: a cross-sectional study. BMC Res Notes. 2019 ago;12(1):479. http://dx.doi.org/10.1186/s13104-019-4525-4 PMid:31375121.
  » http://dx.doi.org/10.1186/s13104-019-4525-4
• ⁶
  von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. Int J Surg. 2014 dez;12(12):1495-9. http://dx.doi.org/10.1016/j.ijsu.2014.07.013 PMid:25046131.
  » http://dx.doi.org/10.1016/j.ijsu.2014.07.013
• ⁷
  Luisi C, Figueiredo FWDS, Sousa LVDA, Quaresma FRP, MacIel EDS, Adami F. Prevalence of and factors associated with metabolic syndrome in afro-descendant communities in a situation of vulnerability in Northern Brazil: a cross-sectional study. Metab Syndr Relat Disord. 2019;17(4):204-9. http://dx.doi.org/10.1089/met.2018.0107 PMid:30888909.
  » http://dx.doi.org/10.1089/met.2018.0107
• ⁸
  Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112(17):2735-52. http://dx.doi.org/10.1161/CIRCULATIONAHA.105.169404 PMID: 16157765.
  » http://dx.doi.org/10.1161/CIRCULATIONAHA.105.169404
• ⁹
  Kind S, Brighenti-Zogg S, Mundwiler J, Schüpbach U, Leuppi JD, Miedinger D et al. Factors associated with cardiorespiratory fitness in a swiss working population. J Sports Med (Hindawi Publ Corp). 2019;2019:5317961. http://dx.doi.org/10.1155/2019/5317961 PMid:31355290.
  » http://dx.doi.org/10.1155/2019/5317961
• ¹⁰
  Bortolotto CC, Mola CL, Tovo-Rodrigues L. Quality of life in adults from a rural area in Southern Brazil: a population-based study TT - Qualidade de vida em adultos de zona rural no Sul do Brasil: estudo de base populacional. Rev Saude Publica. 2018;52:1-11. http://dx.doi.org/10.11606/S1518-8787.2018052000261
  » http://dx.doi.org/10.11606/S1518-8787.2018052000261
• ¹¹
  Fleck MPA, Louzada S, Xavier M, Chachamovich E, Vieira G, Santos L et al. Aplicação da versão em português do instrumento abreviado de avaliação da qualidade de vida “WHOQOL-bref”. Rev Saude Publica. 2000 abr;34(2):178-83. http://dx.doi.org/10.1590/S0034-89102000000200012 PMid:10881154.
  » http://dx.doi.org/10.1590/S0034-89102000000200012
• ¹²
  Goes M, Lopes M, Marôco J, Oliveira H, Fonseca C. Psychometric properties of the WHOQOL-BREF(PT) in a sample of elderly citizens. Health Qual Life Outcomes. 2021;19(1):1-12. http://dx.doi.org/10.1186/s12955-021-01783-z PMid:34001152.
  » http://dx.doi.org/10.1186/s12955-021-01783-z
• ¹³
  Uddin MN, Islam FMA. Psychometric evaluation of an interview-administered version of the WHOQOL-BREF questionnaire for use in a cross-sectional study of a rural district in Bangladesh: an application of Rasch analysis. BMC Health Serv Res. 2019;19(1):216. http://dx.doi.org/10.1186/s12913-019-4026-0 PMid:30953506.
  » http://dx.doi.org/10.1186/s12913-019-4026-0
• ¹⁴
  Marques AP. Manual de goniometria [Internet]. 2ª ed. São Paulo: Manole; 2003 [citado 2021 ago 23]. Disponível em: https://books.google.com/books?id=hV0iCgAAQBAJ&pgis=1
  » https://books.google.com/books?id=hV0iCgAAQBAJ&pgis=1
• ¹⁵
  Maciel ES, Silva BKR, Figueiredo FWS, Pontes-Silva A, Quaresma FRP, Adami F et al. Physical inactivity level and lipid profile in traditional communities in the Legal Amazon: a cross-sectional study. BMC Public Health. 2022;22(1):542. http://dx.doi.org/10.1186/s12889-022-12973-9 PMid:35303858.
  » http://dx.doi.org/10.1186/s12889-022-12973-9
• ¹⁶
  Sousa LVA, Maciel ES, Quaresma FRP, de Abreu ACG, Paiva LS, Fonseca FLA et al. Quality of Life and Metabolic Syndrome in Brazilian quilombola communities: a cross-sectional study. J Hum Growth Dev. 2018;28(3):316-28. http://dx.doi.org/10.7322/jhgd.152182
  » http://dx.doi.org/10.7322/jhgd.152182
• ¹⁷
  de Carvalho Vidigal F, Bressan J, Babio N, Salas-Salvadó J. Prevalence of metabolic syndrome in Brazilian adults: a systematic review. BMC Public Health. 2013 dez;13(1):1198. PMid:24350922.
• ¹⁸
  Saboya PP, Bodanese LC, Zimmermann PR, Gustavo AS, Macagnan FE, Feoli AP et al. Intervenção de estilo de vida na síndrome metabólica e seu impacto na qualidade de vida: um estudo controlado randomizado. Arq Bras Cardiol. 2016;108(1):60-9. PMid:27982160.
• ¹⁹
  Barbosa SE, Silva DL, Trindade-Filho EM, Mourão ARC. Risco de doenças cardiovasculares em pescadores de uma comunidade. Rev Pesqui em Fisioter. 2020 ago;10(3):376-84. http://dx.doi.org/10.17267/2238-2704rpf.v10i3.2857
  » http://dx.doi.org/10.17267/2238-2704rpf.v10i3.2857
• ²⁰
  Rubino F, Nathan DM, Eckel RH, Schauer PR, Alberti KGMM, Zimmet PZ et al. Metabolic surgery in the treatment algorithm for Type 2 Diabetes: a joint statement by international diabetes organizations. Surg Obes Relat Dis. 2016 jul;12(6):1144-62. http://dx.doi.org/10.1016/j.soard.2016.05.018 PMid:27568469.
  » http://dx.doi.org/10.1016/j.soard.2016.05.018
• ²¹
  Pitanga FJG, Lessa I. Indicadores antropométricos de obesidade como instrumento de triagem para risco coronariano elevado em adultos na Cidade de Salvador - Bahia. Arq Bras Cardiol. 2005 jul;85(1):26-31. http://dx.doi.org/10.1590/S0066-782X2005001400006 PMid:16041451.
  » http://dx.doi.org/10.1590/S0066-782X2005001400006
• ²²
  Pires JE, Sebastião YV, Langa AJ, Nery SV. Hypertension in Northern Angola: Prevalence, associated factors, awareness, treatment and control. BMC Public Health. 2013 jan;13(1):90. http://dx.doi.org/10.1186/1471-2458-13-90 PMid:23363805.
  » http://dx.doi.org/10.1186/1471-2458-13-90
• ²³
  Muruci G, Muruci GR, Francisco I, Alves MAR. Prevalência dos componentes associados a síndrome metabólica no Brasil e revisão crítica dos fatores dietéticos associados à prevenção e ao tratamento. Rev Rede Cuid em Saúde. 2015 Jan;9(1):1-15.
• ²⁴
  Salaroli LB, Barbosa GC, Mill JG, Molina MCB. Prevalência de síndrome metabólica em estudo de base populacional, Vitória, ES - Brasil. Arq Bras Endocrinol Metabol. 2007 out;51(7):1143-52. http://dx.doi.org/10.1590/S0004-27302007000700018 PMid:18157391.
  » http://dx.doi.org/10.1590/S0004-27302007000700018
• ²⁵
  Portela PP, Mussi FC, Gama GGG, Santos CAST. Fatores associados ao descontrole da pressão arterial em homens. Acta Paul Enferm. 2016 maio/jun;29(3):307-15. http://dx.doi.org/10.1590/1982-0194201600043
  » http://dx.doi.org/10.1590/1982-0194201600043
• ²⁶
  Bezerra DP. Estilo de vida e consumo alimentar associado ao estado nutricional de pescadores [artigo científico]. Santa Cruz: Universidade Federal do Rio Grande do Norte; 2017.
• ²⁷
  Pessoa WA No, Brasil MVO, Melo AN, Moura EA, Barros RN. Sistema de Relações de Produtores de Tilápia à Luz da Teoria Visionária de Filion. Connexio - Rev Cient da Esc Gestão e Negócios. 2017;6(1):1-20.
• ²⁸
  Vahedi S. World Health Organization Quality-of-Life Scale (WHOQOL-BREF): analyses of their item response theory properties based on the Graded Responses Model. Iran J Psychiatry. 2010;5(4):140-53. PMid:22952508.
• ²⁹
  Ashwell M, Gunn P, Gibson S. 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. 2012;13(3):275-86. http://dx.doi.org/10.1111/j.1467-789X.2011.00952.x PMid:22106927.
  » http://dx.doi.org/10.1111/j.1467-789X.2011.00952.x
• ³⁰
  Browning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 05 could be a suitable global boundary value. Nutr Res Rev. 2010;23(2):247-69. http://dx.doi.org/10.1017/S0954422410000144 PMid:20819243.
  » http://dx.doi.org/10.1017/S0954422410000144
• ³¹
  Ezzatvar Y, Izquierdo M, Ramírez-Vélez R, del Pozo Cruz B, García-Hermoso A. Accuracy of different cutoffs of the waist-to-height ratio as a screening tool for cardiometabolic risk in children and adolescents: a systematic review and meta-analysis of diagnostic test accuracy studies. Obes Rev. 2022;23(2):e13375. http://dx.doi.org/10.1111/obr.13375 PMid:34751482.
  » http://dx.doi.org/10.1111/obr.13375
• ³²
  Lo K, Wong M, Khalechelvam P, Tam W. Waist-to-height ratio, body mass index and waist circumference for screening paediatric cardio-metabolic risk factors: a meta-analysis. Obes Rev. 2016;17(12):1258-75. http://dx.doi.org/10.1111/obr.12456 PMid:27452904.
  » http://dx.doi.org/10.1111/obr.12456
• ³³
  Martin-Calvo N, Moreno-Galarraga L, Martinez-Gonzalez MA. Association between body mass index, waist-to-height ratio and adiposity in children: a systematic review and meta-analysis. Nutrients. 2016;8(8):512. http://dx.doi.org/10.3390/nu8080512 PMid:27556485.
  » http://dx.doi.org/10.3390/nu8080512
• ³⁴
  Peer N, Lombard C, Steyn K, Levitt N. Waist-to-height ratio is a useful indicator of cardio-metabolic risk in South Africa. Fam Pract. 2020;37(1):36-42. PMid:31504474.
• ³⁵
  Nevill AM, Stewart AD, Olds T, Duncan MJ. A new waist-to-height ratio predicts abdominal adiposity in adults. Res Sports Med. 2020;28(1):15-26. http://dx.doi.org/10.1080/15438627.2018.1502183 PMid:30044132.
  » http://dx.doi.org/10.1080/15438627.2018.1502183

Edited by

ASSOCIATED EDITOR Maria Catarina Salvador da Motta https://orcid.org/0000-0002-3278-5645

SCIENTIFIC EDITOR Ivone Evangelista Cabral https://orcid.org/0000-0002-1522-9516

Publication Dates

• Publication in this collection
  11 July 2022
• Date of issue
  2022

History

• Received
  23 Aug 2021
• Accepted
  12 May 2022