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Severe asthma is associated with metabolic syndrome in Brazilian adolescents

2018; Elsevier BV; Volume: 141; Issue: 5 Linguagem: Inglês

10.1016/j.jaci.2018.01.026

1097-6825

Fábio Chigres Kuschnir, Mara Morelo Rocha Félix, Maria Cristina Caetano Kuschnir, Kátia Vergetti Bloch, Érica Azevedo de Oliveira Costa Jordão, Dirceu Solé, Antônio José Lêdo Alves da Cunha, Moysés Szklo,

Chronic Obstructive Pulmonary Disease (COPD) Research

Asthma is a serious health problem in developing countries, with increasing prevalence over the last decades, especially among children and adolescents.1GINA Science CommitteeGlobal Strategy for Asthma Management and Prevention.2016Google Scholar In Brazil, according to the International Study of Asthma and Allergies in Childhood, the prevalence of active asthma in children aged 6 to 7 years and adolescents aged 13 to 14 years was, respectively, 24.3% and 19%, one of the highest among Latin American countries.2Mallol J. Crane J. von Mutius E. Odhiambo J. Keil U. Stewart A. et al.The International Study of Asthma and Allergies in Childhood (ISAAC) phase three: a global synthesis.Allergol Immunopathol (Madr). 2013; 41: 73-85Crossref PubMed Scopus (388) Google Scholar Metabolic syndrome (MS) is an important health issue associated with increased cardiovascular risk. The Study of Cardiovascular Risk in Adolescents (Portuguese acronym “ERICA”) involving Brazilian students showed a 2.6% prevalence of MS.3Kuschnir M.C.C. Bloch K.V. Szklo M. Klein C.H. Barufaldi L.A. Abreu Gde A. et al.ERICA: prevalence of metabolic syndrome in Brazilian adolescents.Rev Saude Publica. 2016; 50: 11sPubMed Google Scholar The association between asthma and MS components such as insulin resistance and high blood pressure (BP) has been observed regardless of body mass index (BMI).4Perez M.K. Piedimonte G. Metabolic asthma: is there a link between obesity, diabetes, and asthma?.Immunol Allergy Clin North Am. 2014; 34: 777-784Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar, 5Cottrell L. Neal W.A. Ice C. Perez M.K. Piedimonte G. Metabolic abnormalities in children with asthma.Am J Respir Crit Care Med. 2011; 183: 441-448Crossref PubMed Scopus (146) Google Scholar More recently, a study with adolescents found association between insulin resistance and MS, with worsened lung function in overweight/obese individuals.6Forno E. Han Y.-Y. Muzumdar R.H. Celedón J.C. Insulin resistance, metabolic syndrome, and lung function in US adolescents with and without asthma.J Allergy Clin Immunol. 2015; 136: 304-311.e8Abstract Full Text Full Text PDF PubMed Scopus (31) Google Scholar Thus, hyperinsulinemia and dyslipidemia, which are silent precursors of diabetes and cardiovascular disease, could be associated with development of asthma.4Perez M.K. Piedimonte G. Metabolic asthma: is there a link between obesity, diabetes, and asthma?.Immunol Allergy Clin North Am. 2014; 34: 777-784Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar Considering that asthma and MS are both inflammatory conditions, our hypothesis was that MS and its components could be more prevalent among patients with asthma. To investigate this association, we performed a cross-sectional study using data from ERICA, a multicenter, school-based countrywide study in a complex sample of adolescents aged 12 to 17 years. The study stratified the sample by region and grouped according to schools and classes, with representativeness to the set of cities with more than 100,000 inhabitants of the country.7Bloch K.V. Szklo M. Kuschnir M.C.C. Abreu Gde A. Barufaldi L.A. Klein C.H. et al.The study of cardiovascular risk in adolescents–ERICA: rationale, design and sample characteristics of a national survey examining cardiovascular risk factor profile in Brazilian adolescents.BMC Public Health. 2015; 15: 94Crossref PubMed Scopus (129) Google Scholar Detailed descriptions of subject recruitment and data collection have been reported previously.7Bloch K.V. Szklo M. Kuschnir M.C.C. Abreu Gde A. Barufaldi L.A. Klein C.H. et al.The study of cardiovascular risk in adolescents–ERICA: rationale, design and sample characteristics of a national survey examining cardiovascular risk factor profile in Brazilian adolescents.BMC Public Health. 2015; 15: 94Crossref PubMed Scopus (129) Google Scholar Data were collected by a self-administered questionnaire using a personal digital assistant, including questions about sociodemographic characteristics, lifestyle, and asthma. A total of 72,508 students from public and private schools were assessed and submitted to anthropometric, weight, height, waist circumference (WC), and BP measurements. Fasting blood samples were collected from a subsample of 40,732 participants for measurements of glucose, insulin, total cholesterol, high-density lipoprotein–cholesterol, low-density lipoprotein–cholesterol, and triglycerides (TGs). The homeostasis model assessment-estimated insulin resistance (HOMA-IR) was also estimated. Participants fasting for less than 12 hours, refusing phlebotomy, pregnant, or disabled were excluded.7Bloch K.V. Szklo M. Kuschnir M.C.C. Abreu Gde A. Barufaldi L.A. Klein C.H. et al.The study of cardiovascular risk in adolescents–ERICA: rationale, design and sample characteristics of a national survey examining cardiovascular risk factor profile in Brazilian adolescents.BMC Public Health. 2015; 15: 94Crossref PubMed Scopus (129) Google Scholar Current asthma (CA) was defined by the presence of at least 1 attack in response to the question “In the last 12 months, how many attacks of wheezing you had? and severe asthma (SA) defined by 4 or more asthma attacks according to previously established criteria.8Lai C.K.W. Beasley R. Crane J. Foliaki S. Shah J. Weiland S. et al.Global variation in the prevalence and severity of asthma symptoms: phase three of the International Study of Asthma and Allergies in Childhood (ISAAC).Thorax. 2009; 64: 476-483Crossref PubMed Scopus (743) Google Scholar Metabolic abnormalities were defined according to International Diabetes Federation Consensus 2005.9Alberti K.G.M.M. Zimmet P. Shaw J. Metabolic syndrome–a new world-wide definition: a Consensus Statement from the International Diabetes Federation.Diabet Med. 2006; 23: 469-480Crossref PubMed Scopus (2810) Google Scholar All procedures for anthropometric measurements, BP evaluation, and biochemical determinations are described in the article's Methods section in the Online Repository at www.jacionline.org. All analyzes were performed using SURVEY procedure in STATA 14.0 software (StataCorp, College Station, Tex). Detailed description of statistical analysis is in this article's Methods section. This study was conducted according to the principles of the Declaration of Helsinki and was approved by the Ethics Committee of the Federal University of Rio de Janeiro (no. 45/2008).7Bloch K.V. Szklo M. Kuschnir M.C.C. Abreu Gde A. Barufaldi L.A. Klein C.H. et al.The study of cardiovascular risk in adolescents–ERICA: rationale, design and sample characteristics of a national survey examining cardiovascular risk factor profile in Brazilian adolescents.BMC Public Health. 2015; 15: 94Crossref PubMed Scopus (129) Google Scholar Between 2013 and 2014, 37,410 adolescents were evaluated (see Fig E1 in this article's Online Repository at www.jacionline.org). Mean age was 14.6 ± 1.6 years; 50.1% were females. Regarding skin color/ethnicity, 58.1% were black/brown and about 40% white. The prevalence of CA and SA was 13.8% (95% CI, 12.4-15.2) and 2.09% (95% CI, 1.95-2.24), respectively. MS was present in 2.3% of the populations sampled (95% CI, 2.14-2.45). Main sociodemographic and metabolic characteristics of participants according to presence or absence of asthma are summarized in Table I. Adolescents with nonsevere asthma were more likely to be female, white skin color, current smoker, and student from a private school than those without disease. Except for the latter, there were no significant differences in relation to these variables between those without asthma and those with SA. In this group of adolescents, the means of BMI, WC, and TGs differed significantly from those without the disease.Table IGeneral characteristics of study participants according to presence of asthmaCharacteristicNo asthma (n = 32,705)CA (n = 4,705)Nonsevere asthma (n = 3,913)SA (n = 792)Mean or %95% CIMean or %95% CIP valueMean or %95% CIP valueAge (y)14.614.5-14.614.614.5-14.8.6314.714.3-15.2.552Female49.048.5-49.458.354.7-61.8.000∗Chi-square test.51.542.2-60.7.781White38.636.7-40.645.941.1-50.8.002∗Chi-square test.44.834.7-55.4.33Private school21.217.1-26.127.519.4-37.3.035∗Chi-square test.31.721.8-43.7.029∗Chi-square test.Current smoker1.691.43-2.03.62.4-5.5.012∗Chi-square test.4.22.4-7.4.065Sedentary lifestyle48.047.0-49.043.938.3-49.8.17445.435.7-55.5.695BMI (kg/m2)21.321.2-21.421.721.3-21.9.0722.221.3-23.1.048†t test with survey data (reference: no asthma).WC (cm)72.071.7-72.472.571.5-73.5.41674.672.1-77.1.036†t test with survey data (reference: no asthma).HDL (mg/dL)47.246.6-47.947.846.9-48.6.20846.344.9-47.6.145TG (mg/dL)77.476.2-78.779.276.4-81.9.28384.878.8-90.8.021†t test with survey data (reference: no asthma).Glucose (mg/dL)86.485.9-86.886.185.1-87.1.58786.284.8-87.6.843Insulin (mU/L)9.49.1-9.79.79.1-10.3.28310.39.0-11.5.163Results are shown as means for continuous variables and percentages (%) for categorical variables.HDL, High-density lipoprotein.∗ Chi-square test.† t test with survey data (reference: no asthma). Open table in a new tab Results are shown as means for continuous variables and percentages (%) for categorical variables. HDL, High-density lipoprotein. Table II presents the relationship between the prevalence of components of MS and CA/SA. Only increased prevalence of altered WC was significantly associated with CA (prevalence ratio [PR], 1.19; 95% CI, 1.00-1.43). However, significant associations between SA and obesity (PR, 1.28; 95% CI, 1.02-1.62), increased WC (PR, 1.74; 95% CI, 1.16-2.61), hyperglycemia (PR, 1.78; 95% CI, 1.05-2.98), hyperinsulinemia (PR, 1.55; 95% CI, 1.03-2.33), and HOMA-IR (PR, 1.02; 95% CI, 1.01-1.04) were observed. SA was also significantly associated with MS (PR, 2.43; 95% CI, 1.39-4.27), and this association remained after adjustment for age, sex, current smoking, and BMI by Poisson regression (PR, 1.71; 95% CI, 1.03-2.82) (see Table E1 in this article's Online Repository at www.jacionline.org).Table IIPrevalence of adiposity measures, metabolic abnormalities, and MS according to asthma statusCharacteristicCASAPR95% CIP valuePR95% CIP valueObesity1.080.99-1.18.0871.281.02-1.62.034∗Poisson regression.Increased WC1.191.00-1.43.047∗Poisson regression.1.741.16-2.61.007∗Poisson regression.Hyperglycemia1.180.79-1.77.4171.781.05-2.98.029∗Poisson regression.Low HDL1.020.90-1.16.7141.350.94-1.92.102Hypertriglyceridemia0.950.73-1.24.7161.720.91-3.26.095High BP0.680.51-0.89.007∗Poisson regression.1.160.68-1.99.585Hyperinsulinemia1.120.91-1.37.2931.551.03-2.33.034∗Poisson regression.HOMA-IR1.010.99-1.03.1081.021.01-1.04.002∗Poisson regression.MS0.940.67-1.31.7192.431.39-4.27.002∗Poisson regression.HDL, High-density lipoprotein; HDL-C, high-density lipoprotein–cholesterol.Obesity: Z score > 2; increased WC: >P90; hyperglycemia: serum glucose ≥100 mg/dL; low HDL: <40 mg/dL or P90) was present and at least 2 of the following criteria: (1) high BP, (2) hypertriglyceridemia, (3) low HDL-C, and (4) hyperglycemia.∗ Poisson regression. Open table in a new tab HDL, High-density lipoprotein; HDL-C, high-density lipoprotein–cholesterol. Obesity: Z score > 2; increased WC: >P90; hyperglycemia: serum glucose ≥100 mg/dL; low HDL: <40 mg/dL or P90) was present and at least 2 of the following criteria: (1) high BP, (2) hypertriglyceridemia, (3) low HDL-C, and (4) hyperglycemia. To our knowledge, this is the first study of asthma and MS and its components in a representative sample of Brazilian adolescents. CA was associated with increased WC but not with MS. However, SA was significantly associated with MS, and this association remained after adjustment for age, sex, current smoking, and BMI. In addition, significant associations were observed between SA and obesity, increased WC, hyperglycemia, and hyperinsulinemia. Elevated WC seems to be an important factor linking MS to asthma in our sample. Besides that, insulin resistance, another known component of MS, was associated with SA, which may represent a subgroup of patients with SA with metabolic abnormalities without alteration of BMI. Surprisingly, a protective association between elevated BP and CA, not observed in adolescents with SA, was found. This finding may reflect only a statistical effect but deserves further analysis. Our study has some limitations. Cross-sectional design does not allow establishing the temporality of relationships to infer causality between MS and its components and SA. In addition, known correlated factors of asthma were not included, for example, family and personal history of atopy and medication use for asthma control. Unfortunately, we could not perform objective measures of pulmonary function because of sample size and logistic issues, and this may have led to a misdiagnosis of asthma, especially among obese individuals. However, a large and representative sample and utilization of standardized procedures by uniformly trained personnel represent considerable strengths of our findings. In conclusion, MS, some of its components, and insulin resistance were significantly associated with SA in Brazilian adolescents, independent of BMI. Thus, further research is needed to establish causality and possible common pathophysiological mechanisms, as well as the consequent clinical and therapeutic implications, between these 2 conditions. Anthropometric measurements were performed with the student wearing light clothes and bare feet. Height was measured to the nearest 1 mm using a calibrated stadiometer (portable stadiometer Alturexata, Minas Gerais, Brazil) with millimeter resolution and height up to 213 cm. Weight was measured to the nearest 50 g using a digital scale (model P150m, 200 kg of capacity and 50 g of precision, Líder, São Paulo, Brazil).E1Lohman T.G. Roche A.F. Martorell R. Anthropometric Standardization Reference Manual. Human Kinetics Books, Champaign, Ill1988: 177Google Scholar BMI was calculated using the following formula: BMI (kg/m2) = weight in kilograms divided by the height in meters squared. To determine weight categories of adolescents, World Health Organization reference curves, with the index BMI/age, according to sex, was used. The cutoff points were as follows: very low weight, Z score less than −3; low weight, Z score −3 or more and less than −1; normal weight, Z score −1 or more and 1 or less; overweight, Z score more than 1 and 2 or less; obesity, Z score more than 2.E2de Onis M. Onyango A.W. Borghi E. Siyam A. Nishida C. Siekmann J. Development of a WHO growth reference for school-aged children and adolescents.Bull World Health Organ. 2007; 85: 660-667Crossref PubMed Scopus (5052) Google Scholar WC was measured to the nearest 1 mm using a fiberglass anthropometric tape, with millimeter resolution and length of 1.5 m (Sanny, São Paulo, Brazil). Measurement was done horizontally, at half the distance between iliac crest and lower costal margin.E3Obesity: preventing and managing the global epidemic. Report of a WHO consultation.World Health Organ Tech Rep Ser. 2000; 894 (1-253): i-xiiPubMed Google Scholar BP measurements were based on the 4th Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents, published in 2004.E4National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and AdolescentsThe fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents.Pediatrics. 2004; 114: 555-576Crossref PubMed Scopus (5842) Google Scholar Systolic and diastolic BP and pulse were measured using the automatic oscillometric device Omron 705-IT (Omron Healthcare, Bannockburn, Ill). Three BP measurements were taken, with the mean of the final 2 being used in the hypertension classification. Systemic BP was considered high if the systolic BP was greater than or equal to 130 mm Hg, and the diastolic BP was greater than or equal to 85 mm Hg.E5Stergiou G.S. Yiannes N.G. Rarra V.C. Validation of the Omron 705 IT oscillometric device for home blood pressure measurement in children and adolescents: the Arsakion School Study.Blood Press Monit. 2006; 11: 229-234Crossref PubMed Scopus (137) Google Scholar The blood samples were processed and plasma and serum separated within 2 hours after collection and kept between 4°C and 10°C, and then sent to the study's central reference laboratory for analysis. Biochemical determinations were performed using serum samples obtained under fasting conditions. The Friedewald equation was used to calculate low-density lipoprotein–cholesterol. HOMA-IR value was used as a measure of insulin resistance and was calculated as follows: fasting insulin (mU/L) × (fasting glucose (mg/dL) × 0.0555)/22.5. All measurements were performed in automatic analyzers at reference laboratory following uniform standard procedures and quality controls, as detailed elsewhere.E6Forno E. Han Y.-Y. Muzumdar R.H. Celedon J.C. Insulin resistance, metabolic syndrome, and lung function in US adolescents with and without asthma.J Allergy Clin Immunol. 2015; 136: 304-311Abstract Full Text Full Text PDF PubMed Scopus (107) Google Scholar In this study, metabolic abnormalities were defined according to International Diabetes FederationConsensus 2005.E7Alberti K.G.M.M. Zimmet P. Shaw J. Metabolic syndrome–a new world-wide definition. A Consensus Statement from the International Diabetes Federation.Diabet Med. 2006; 23: 469-480Crossref PubMed Scopus (4422) Google Scholar MS was considered when abdominal obesity (WC > P90) was present and at least 2 of the following criteria were met: (1) high BP (≥130/85 mm Hg); (2) hypertriglyceridemia (TGs ≥ 150 mg/dL); (3) low high-density lipoprotein–cholesterol (<40 mg/dL or <50 mg/dL for 16-17-year-old females); (4) hyperglycemia (serum glucose ≥ 100 mg/dL). The cutoff points that were used for these tests are presented in Table I. This variable was defined by the time in minutes of weekly physical activity, being classified, respectively, as sedentary (<300 min/wk) and active (≥300 min/wk).E8Cureau F.V. da Silva T.L.N. Bloch K.V. Fujimori E. Belfort D.R. de Carvalho K.M.B. et al.ERICA: leisure-time physical inactivity in Brazilian adolescents.Rev Saude Publica. 2016; 50: 4sCrossref PubMed Google Scholar Current smokers were defined as those who smoked cigarettes at least 1 day in the last 30 days.E9Figueiredo V.C. Szklo A.S. Costa L.C. Kuschnir M.C.C. da Silva T.L.N. Bloch K.V. et al.ERICA: smoking prevalence in Brazilian adolescents.Rev Saude Publica. 2016; 50: 12sCrossref PubMed Google Scholar Primary sampling units and strata for the complex design of ERICA were taken into account for data analysis. Sampling weights, stratification, and clusters provided in ERICA data set were incorporated into the analysis to obtain proper estimates and SE. Descriptive statistics were reported by frequency, means, and SD. Bivariate analysis between asthma and components of MS was performed using chi-square test, PR, and its respective 95% 95% CIs. Then, those significant associations (P < .20) were included in multivariate models adjusted by potential confounders or interaction factors, such as age, sex, race, physical activity, smoking, and school type (private or public) by Poisson regression. For analysis of finals models, P value of less than .05 was considered to be statistical significant. All analyzes were performed using SURVEY procedure in STATA 14.0 software (StataCorp, College Station, Tex).Table E1Parameters of multivariate analysis∗Poisson regression, adjusted for age, sex, current smoking, and BMI. for the association of SA with MS and with its componentsCharacteristicSAPR95% CIIncreased WC1.460.85-2.51Hyperglycemia1.771.08-2.91Hyperinsulinemia1.291.01-1.64MS1.711.03-2.82∗ Poisson regression, adjusted for age, sex, current smoking, and BMI. Open table in a new tab Table E2Classification criteria: Cutoff points used for blood testing resultsE6Forno E. Han Y.-Y. Muzumdar R.H. Celedon J.C. Insulin resistance, metabolic syndrome, and lung function in US adolescents with and without asthma.J Allergy Clin Immunol. 2015; 136: 304-311Abstract Full Text Full Text PDF PubMed Scopus (107) Google ScholarExaminationMethod∗Brazilian Society of Pathology.Cuttoff pointsDesirableBorderlineHighCholesterol (mg/dL)Enzymatic kinetics<150150-169≥170LDL-C (mg/dL)Enzymatic colorimetric assay<100100-129≥130HDL-C (mg/dL)Enzymatic colorimetric assay≥45——TGs (mg/dL)Enzymatic kinetics<100100-129≥130Glucose (mg/dL)Hexoquinase method70-99100-125.9≥126Insulin (mU/L)Chemiluminescence<1515-20≥20LDL-C, Low-density cholesterol; HDL-C, high-density cholesterol.∗ Brazilian Society of Pathology. Open table in a new tab LDL-C, Low-density cholesterol; HDL-C, high-density cholesterol.