Abstracts

Introduction

Asthma is a chronic disease that affects 235 million people all over the world ¹1. World Health Organization. Asthma. 2017. http://http://www.who.int/news-room/fact-sheets/detail/asthma (accessed on 02/Jul/2018).
http://http://www.who.int/news-room/fact... ; and that is being consistently associated with other non-communicable chronic diseases (NCCD) ²2. Gershon AS, Guan J, Wang C, Victor JC, To T. Describing and quantifying asthma comorbidity [corrected]: a population study. PLoS One 2012; 7:e34967. with which it appears to share physiopathological mechanisms that need to be better explored ³3. Cazzola M, Segreti A, Calzetta L, Rogliani P. Comorbidities of asthma: current knowledge and future research needs. Curr Opin Pulm Med 2013; 19:36-41.^,44. Sutherland ER. Linking obesity and asthma. Ann N Y Acad Sci 2014; 13:31-41..

Obesity is an important risk factor for NCCD, which is being associated with asthma from birth to adulthood ⁵5. Mebrahtu TF, Feltbower RG, Greenwood DC, Parslow RC. Childhood body mass index and wheezing disorders: a systematic review and meta-analysis. Pediatr Allergy Immunol 2015; 26:62-72.^,66. Liu PC, Kieckhefer GM, Gau BS. A systematic review of the association between obesity and asthma in children. J Adv Nurs 2013; 69:1446-65.^,77. Papoutsakis C, Priftis KN, Drakouli M, Prifti S, Konstantaki E, Chondronikola M, et al. Childhood overweight/obesity and asthma: is there a link? A systematic review of recent epidemiologic evidence. J Acad Nutr Diet 2013; 113:77-105.^,88. Flaherman V, Rutherford GW. A meta-analysis of the effect of high weight on asthma. Arch Dis Child 2006; 91:334-9.^,99. Beuther DA, Sutherland ER. Overweight, obesity, and incident asthma: a meta-analysis of prospective epidemiologic studies. Am J Respir Crit Care Med 2007; 175:661-6.. Overweight during childhood increases the risk to develop asthma during this phase of life ⁵5. Mebrahtu TF, Feltbower RG, Greenwood DC, Parslow RC. Childhood body mass index and wheezing disorders: a systematic review and meta-analysis. Pediatr Allergy Immunol 2015; 26:62-72.^,66. Liu PC, Kieckhefer GM, Gau BS. A systematic review of the association between obesity and asthma in children. J Adv Nurs 2013; 69:1446-65.^,77. Papoutsakis C, Priftis KN, Drakouli M, Prifti S, Konstantaki E, Chondronikola M, et al. Childhood overweight/obesity and asthma: is there a link? A systematic review of recent epidemiologic evidence. J Acad Nutr Diet 2013; 113:77-105.^,1010. McCallister M, Medrano R, Wojcicki J. Early life obesity increases the risk for asthma in San Francisco born Latina girls. Allergy Asthma Proc 2018; 39:273-80.^,1111. Lang JE, Bunnell HT, Hossain MJ, Wysocki T, Lima JJ, Finkel TH, et al. Being overweight or obese and the development of asthma. Pediatrics 2018; 142:pii: e20182119. or in the future ⁸8. Flaherman V, Rutherford GW. A meta-analysis of the effect of high weight on asthma. Arch Dis Child 2006; 91:334-9.^,1212. Ulrik CS, Lophaven SN, Andersen ZJ, Sorensen TI, Baker JL. BMI at school age and incident asthma admissions in early adulthood: a prospective study of 310,211 children. Clin Epidemiol 2018; 10:605-12.. Overweight and obesity have also been associated with asthma in adults, with a dose-response effect on body mass index (BMI) ⁹9. Beuther DA, Sutherland ER. Overweight, obesity, and incident asthma: a meta-analysis of prospective epidemiologic studies. Am J Respir Crit Care Med 2007; 175:661-6..

Studies focusing on obesity and asthma frequently consider overweight at a given time ¹³13. Cottrell L, Neal WA, Ice C, Perez MK, Piedimonte G. Metabolic abnormalities in children with asthma. Am J Respir Crit Care Med 2011; 183:441-8.^,1414. Matos SM, Jesus SR, Saldiva SR, Prado MS, D'Innocenzo S, Assis AM, et al. Overweight, asthma symptoms, atopy and pulmonary function in children of 4-12 years of age: findings from the SCAALA cohort in Salvador, Bahia, Brazil. Public Health Nutr 2011; 14:1270-8.^,1515. Ma J, Xiao L, Knowles SB. Obesity, insulin resistance and the prevalence of atopy and asthma in US adults. Allergy 2010; 65:1455-63.^,1616. Cetlin AA, Gutierrez MR, Bettiol H, Barbieri MA, Vianna EO. Influence of asthma definition on the asthma-obesity relationship. BMC Public Health 2012; 12:844.. Few prospective studies on the association between obesity and asthma have adjusted the model for birth variables using regression models ¹⁷17. Jeong Y, Jung-Choi K, Lee JH, Lee HY, Park EA, Kim YJ, et al. Body weight at birth and at age three and respiratory illness in preschool children. J Prev Med Public Health 2010; 43:369-76.^,1818. Zhang Z, Lai HJ, Roberg KA, Gangnon RE, Evans MD, Anderson EL, et al. Early childhood weight status in relation to asthma development in high-risk children. J Allergy Clin Immunol 2010; 126:1157-62..

The association between obesity and asthma involves a complex and temporal relationship between maternal prenatal weight, birth weight, childhood and even adulthood weight ¹⁹19. Peters U, Dixon AE, Forno E. Obesity and asthma. J Allergy Clin Immunol 2018; 141:1169-79.^,2020. Lang JE. Obesity and childhood asthma. Curr Opin Pulm Med 2019; 25:34-43.. Structural equation modeling (SEM) is a useful tool for the study of epidemiological multicausality phenomena ²¹21. Byrne B. Structural equation modeling with Mplus: basic concepts, applications and programming. New York: Routledge; 2012..

Modeling the structure between lifetime overweight and asthma may contribute to a better understanding of the temporal aspects and direct and indirect pathways present in this relationship. Thus, this study modeled the pathways in the association of lifetime overweight and asthma in adults in the 1978/1979 Ribeirão Preto Birth Cohort, São Paulo, Brazil, using SEM.

Method

Study design

This was a prospective cohort study entitled From Perinatal Health to Young Adult Health: a Study of the 1978/1979 Birth Cohort conducted in the Hospitals of Ribeirão Preto, São Paulo.

Ribeirão Preto is a city located 320km northeast from the state capital of São Paulo, in the Southeast region of Brazil, a wealthy industrialized region with a municipal human development index (M-HDI) of 0.626 in 1991 and 0.733 in 2000, occupying the sixth place in the ranking of the 645 municipalities in the State of São Paulo and 22^nd place in the national ranking of the 5,561 municipalities of the country ²²22. Programa das Nações Unidas para o Desenvolvimento; Instituto de Pesquisa Econômica Aplicada; Fundação João Pinheiro. Índice de Desenvolvimento Humano Municipal 2000. http://www.atlasbrasil.org.br/2013/pt/ranking (accessed on 11/Jun/2018).
http://www.atlasbrasil.org.br/2013/pt/ra... ^,2323. Fundação Sistema Estadual de Análise de Dados. Informações dos municípios paulistas. São Paulo: Fundação Sistema Estadual de Análise de Dados; 2005..

Participants and sample

The baseline information (first follow-up) for the 1978/1979 Ribeirão Preto cohort was obtained with 9,067 interviews held with mothers immediately after delivery, corresponding to 98% of the live newborns delivered at the eight maternities from Ribeirão Preto, from June 1, 1978 to May 31, 1979. The proportion of mothers who were discharged from the hospital before they could be interviewed was 2.5%, and less than 1% refused the interview. The newborns whose mothers did not reside in Ribeirão Preto (N = 2,094) on the date of delivery were excluded ²⁴24. Cardoso VC, Simoes VM, Barbieri MA, Silva AA, Bettiol H, Alves MT, et al. Profile of three Brazilian birth cohort studies in Ribeirao Preto, SP and São Luis, MA. Braz J Med Biol Res 2007; 40:1165-76..

Thus, 6,973 newborns remained in the study, 6,827 of them being singletons and 146 being twins ²⁴24. Cardoso VC, Simoes VM, Barbieri MA, Silva AA, Bettiol H, Alves MT, et al. Profile of three Brazilian birth cohort studies in Ribeirao Preto, SP and São Luis, MA. Braz J Med Biol Res 2007; 40:1165-76.. A total of 257 of the 6,827 singletons died during the first year of life ²⁵25. Almeida LEA, Barbieri MA, Gomes UA, Reis PM, Chiaratti TM, Vasconcelos V, et al. Birthweight, social class and infant mortality in Ribeirão Preto, São Paulo. Cad Saúde Pública 1992; 8:190-8. and 86 died by 20 years of age. Thus, 6,484 were left at 20 years of age ²⁶26. Oliveira ZA, Bettiol H, Gutierrez MR, Silva AA, Barbieri MA. Factors associated with infant and adolescent mortality. Braz J Med Biol Res 2007; 40:1245-55..

During the second follow-up of this cohort in 1987/1989, 2,861 children (43.5% of the original cohort) were evaluated at 9-11 years of age, in private, state and municipal public schools ²⁴24. Cardoso VC, Simoes VM, Barbieri MA, Silva AA, Bettiol H, Alves MT, et al. Profile of three Brazilian birth cohort studies in Ribeirao Preto, SP and São Luis, MA. Braz J Med Biol Res 2007; 40:1165-76..

The third follow-up occurred in 1996/1997 and involved only males assessed at the time of recruitment for compulsory military service (n = 2,048) ²⁴24. Cardoso VC, Simoes VM, Barbieri MA, Silva AA, Bettiol H, Alves MT, et al. Profile of three Brazilian birth cohort studies in Ribeirao Preto, SP and São Luis, MA. Braz J Med Biol Res 2007; 40:1165-76..

In the fourth follow-up, 2002-2004, one third of the cohort was sought, and 5,665 individuals among who were alive at 20 years of age were located. In this phase, 2,063 provided data for the questionnaires and for laboratory tests (Figure 1), corresponding to 31.8% of the original cohort ²⁴24. Cardoso VC, Simoes VM, Barbieri MA, Silva AA, Bettiol H, Alves MT, et al. Profile of three Brazilian birth cohort studies in Ribeirao Preto, SP and São Luis, MA. Braz J Med Biol Res 2007; 40:1165-76..

Data for the participants were used for analysis of lifetime overweight and its association with adult asthma in the three follow-up periods of the cohort: baseline, 2^nd follow-up (school age, 9-11 years) and 4^th follow-up (adult age, 23-25 years). The 3^rd follow-up was not used in the present study since it included only 18-year-old males.

Thus, a total participants at the 4th follow-up of the cohort were included. This sample size permitted us to estimate, for the main outcomes of interest, prevalence values within the 50% range with 1.8% relative precision, and prevalence values of about 10% with 1.1% relative precision, with a 95% confidence interval (95%CI). Methodological details regarding this cohort are available in previous studies ²⁴24. Cardoso VC, Simoes VM, Barbieri MA, Silva AA, Bettiol H, Alves MT, et al. Profile of three Brazilian birth cohort studies in Ribeirao Preto, SP and São Luis, MA. Braz J Med Biol Res 2007; 40:1165-76.^,2727. Barbieri MA, Bettiol H, Silva AA, Cardoso VC, Simoes VM, Gutierrez MR, et al. Health in early adulthood: the contribution of the 1978/79 Ribeirão Preto birth cohort. Braz J Med Biol Res 2006; 39:1041-55..

Data collection

Data collection for the cohort included interviews, the application of structured questionnaires, anthropometric exams, examination of medical records, and the bronchial hyperresponsiveness test.

At birth (baseline), the following information was used: maternal schooling (years of study), maternal occupation, family income (in minimum wages), newborn sex (male and female), and birth weight (grams) and length (cm).

Birth weight and length were measured by trained personnel using appropriate instruments. The newborns were weighed without clothes on a baby weighing scale with 10g precision calibrated weekly. Length at birth was measured with the newborn lying in the supine position on a neonatometer ²⁸28. Barbieri M, Gomes U, Barros Filho A, Bettiol H, Almeida L, Silva AA. Perinatal health in Ribeirao Preto, Brazil: a question of method. Cad Saúde Pública 1989; 5:376-87. and the data were checked in order to obtain the newborns’ weight per length score (z-score).

At school age, information was obtained about the students’ current weight (kg) and height (meters) measured according to the recommended techniques ²⁹29. Lohman T, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign: Human Kintetics; 1988. and obtained by duly trained personnel in order to determine the growth scores (z-score) of the BMI for age. At the time of weight measurement, students wore a school uniform and were instructed to remove shoes, socks, and to empty their pockets ²⁹29. Lohman T, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign: Human Kintetics; 1988.. To measure the weight, the scales used in the schools were used when they were in use; the weight measurement was performed to the nearest 100g. When the school did not have a scale or it was defective, a scale was used by the Department of Child Care and Pediatrics, Faculty of Medicine of Ribeirão Preto, University of São Paulo specially assigned for this purpose ³⁰30. Bettiol H, Sabbag Filho D, Haeffner LS, Barbieri MA, Silva AA, Portela A, et al. Do intrauterine growth restriction and overweight at primary school age increase the risk of elevated body mass index in young adults? Braz J Med Biol Res 2007; 40:1237-43..

To measure the students’ height, we used anthropometers manufactured exclusively for the research, whose measurements were taken in centimeters, to the nearest 0.5cm ³⁰30. Bettiol H, Sabbag Filho D, Haeffner LS, Barbieri MA, Silva AA, Portela A, et al. Do intrauterine growth restriction and overweight at primary school age increase the risk of elevated body mass index in young adults? Braz J Med Biol Res 2007; 40:1237-43.. The students were instructed to remove all props from their hair, shoes, and socks, and were placed in an upright, anatomical position, arms freely loosened along the trunk, looking straight into the horizon ²⁹29. Lohman T, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign: Human Kintetics; 1988..

At adult age, the following information was obtained: adult’s age (years), schooling (years of study), occupation, family income (minimum wages), current weight (kg), height (meters) and report of maternal and paternal obesity - history of parental obesity, by the participant.

Adult weight and height were measured by trained personnel according to standard techniques, with the subject barefoot and wearing light clothing ³¹31. Cameron N. The measurement of human growth. New York: Sheridan House; 1984.. Anthropometric measurements were obtained with a periodically calibrated Filizola precision scale and with an anthropometer standing against the wall for measurements in the orthostatic position ³²32. Rezende F, Rosado L, Franceschinni S, Rosado G, Ribeiro R, Marins JC. Revisão crítica dos métodos disponíveis para avaliar a composição corporal em grandes estudos populacionais e clínicos. Arch Latinoam Nutr 2007; 57:327-34..

Information about medical diagnosis of asthma, wheezing during the last 12 months, sensation of tightness in the chest and shortness of breath during the last 12 months was obtained by applying the Respiratory Health Survey²⁷27. Barbieri MA, Bettiol H, Silva AA, Cardoso VC, Simoes VM, Gutierrez MR, et al. Health in early adulthood: the contribution of the 1978/79 Ribeirão Preto birth cohort. Braz J Med Biol Res 2006; 39:1041-55. questionnaire containing questions on these symptoms and diagnosis.

Bronchial hyperresponsiveness was also measured by the methacholine bronchoprovocation test. The test was applied using methacholine chloride (Sigma, St. Louis, USA) diluted in phosphate buffered saline according to international criteria ³³33. Crapo RO, Casaburi R, Coates AL, Enright PL, Hankinson JL, Irvin CG, et al. Guidelines for methacholine and exercise challenge testing-1999. This official statement of the American Thoracic Society was adopted by the ATS Board of Directors, July 1999. Am J Respir Crit Care Med 2000; 161:309-29.. The procedure was carried out by a trained and experienced technician, a physiotherapist and a doctor at the laboratory of Pneumology Service of the University Hospital, Faculty of Medicine of Ribeirão Preto, University of São Paulo ²⁷27. Barbieri MA, Bettiol H, Silva AA, Cardoso VC, Simoes VM, Gutierrez MR, et al. Health in early adulthood: the contribution of the 1978/79 Ribeirão Preto birth cohort. Braz J Med Biol Res 2006; 39:1041-55..

Data processing and statistical analysis

Due to the occurrence of losses on follow-up, the baseline and school phase variables were compared between the adults that attended or did not attend the 4^th cohort follow-up, using chi-square test. It was observed that participants born to unskilled manual working mothers (p = 0.001) with 0 to 4 years of schooling (p < 0.0001), whose families had a monthly income of 0 to 1.9 minimum wages (p < 0.0001) attended less the 4^th follow-up period of the study. On this basis, the sample was weighted by calculating the probability of participants attending the 4^th cohort follow-up as a function of the birth variables significantly associated in the chi-square test using a logistic regression model. The inverse of this probability of selection was then calculated and this variable was used to weigh the SEM estimates using the Stata software, version 14.0 (https://www.stata.com).

Latent variable

Latent variables result from the combination of various observed variables (indicator variable). The use of latent variables permits a better statistical estimate by representing the theoretical concepts in a more appropriate manner. Furthermore, in a latent variable only common variance shared by different indicators persists, resulting in the estimated effects free from the bias originated by measurement errors ³⁴34. Kline RB. Principles and practice of structural equation modeling. New York: Guilford Press; 2011..

The indicators for the all latent variables were selected based on the convergent loadings (> 0.50) that formed this construct in exploratory factorial analyses (EFA). Model fit was assessed based on the following fit indices: (a) p-value < 0.05 in the chi-square test (χ²); (b) p > 0.05 and upper 90% confidence interval limit < 0.08 for the Root Mean Square Error of Approximation (RMSEA); (c) Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) values > 0.95; and (d) Weighted Least Square Mean and Variance Adjusted (WLSMV) value < 1 ³⁴34. Kline RB. Principles and practice of structural equation modeling. New York: Guilford Press; 2011..

Then, confirmatory factorial analysis (CFA) was carried out in order to verify the factors previously determined by EFA ³⁴34. Kline RB. Principles and practice of structural equation modeling. New York: Guilford Press; 2011., adopting the same criteria used in the EFA, with the inclusion of discriminant validity, i.e., the correlations between the indicators should not be excessively high (> 0.90), since each indicator should measure a distinct aspect of the latent variable ³⁴34. Kline RB. Principles and practice of structural equation modeling. New York: Guilford Press; 2011.. The modindices (modification index) command was used to obtain suggestions of changes in the proposed latent variable ²¹21. Byrne B. Structural equation modeling with Mplus: basic concepts, applications and programming. New York: Routledge; 2012.. Exploratory and confirmatory factorial analyses were carried out using the Mplus software, version 7.0 (https://www.statmodel.com/).

Latent variable: prenatal (baseline) socioeconomic situation

The latent variable “prenatal socioeconomic situation” (prenatal SES) consisted of the following variables: (a) maternal schooling (1 = 0 to 4 years; 2 = 5 to 8 years; 3 = 9 to 11 years, and 4 = 12 or more years of study); (b) maternal occupation (1 = unskilled manual worker; 2 = semi-skilled and skilled manual worker; 3 = non-manual worker, according to the International Standard Classification of Occupation (ISCO) ³⁵35. Olsen J, Frische G. Social differences in reproductive health. A study on birth weight, stillbirths and congenital malformations in Denmark. Scand J Soc Med 1993; 21:90-7.; (c) monthly family income based on the Brazilian national minimum wage in force during the 1978/1979 period, categorized as: 1 = 0 to 1.9 minimum wages; 2 = 2 to 2.9 minimum wages; 3 = 3 to 4.9 minimum wages; 4 = 5 or more minimum wages.

Latent variable: current socioeconomic situation of the adult (4th cohort follow-up)

The latent variable socioeconomic situation of the adult (current adult SES) consisted of the following variables: (a) adult’s schooling (1 = 0 to 4 years; 2 = 5 to 8 years; 3 = 9 to 11 years and 4 = 12 or more years of study); (b) adult’s occupation (1 = unskilled manual worker; 2 = semi-skilled manual worker; 3 = skilled manual worker; and 4 = non-manual worker) ³⁵35. Olsen J, Frische G. Social differences in reproductive health. A study on birth weight, stillbirths and congenital malformations in Denmark. Scand J Soc Med 1993; 21:90-7.; (c) monthly family income based on the Brazilian national minimum wage in force during the 2002/2004 period, categorized as: 1 = less than 1 minimum wage; 2 = 1 to 2.9 minimum wages; 3 = 3 to 4.9 minimum wages; 4 = 5 to 9.9 minimum wages; and 5 = 10 or more minimum wages.

Observed variables indicating lifetime obesity

The following observed variables represent lifetime overweight: (a) 1^st follow-up (baseline): weight per length z-score (categorized as: 0 = underweight, z-score < -2; 1 = normal weight, z-score ≥ -2 and ≤ +1, and 2 = overweight, z-score > +1) ³⁶36. Multicentre Growth Reference Study Group. WHO Child Growth Standards based on length/height, weight and age. Acta Paediatr Suppl 2006; 450:76-85.; (b) 2^nd follow-up (school age): BMI for schoolchild at age 9-11 years (categorized as: 0 = malnutrition, z-score < -2; 1 = normal weight, z-score ≥ -2 and ≤ +1, and 2 = overweight, z-score > +1) ³⁶36. Multicentre Growth Reference Study Group. WHO Child Growth Standards based on length/height, weight and age. Acta Paediatr Suppl 2006; 450:76-85.; (c) 4^th follow-up (adult age): adult’s BMI (categorized as: 0 = malnutrition, < 18.5kg/m²; 1 = normal weight, 18.5-24.99kg/m²; and 2 = overweight, ≥ 25kg/m²) ³⁷37. World Health Organization. Physical status: the use and interpretation of anthropometry. Geneva: World Health Organization; 1995. and report of history of parental obesity by the participant (categorized as 0 = no report of parental obesity; 1 = yes, report of maternal or paternal obesity; or 2 = yes, report of both maternal and paternal obesity).

Outcome: asthma

Asthma was a continuous latent variable deduced from the correlation between five indicators in EFA: (a) self-report of a medical diagnosis of asthma (1 = yes or 0 = no); (b) presence of wheezing in the last 12 months (1 = yes or 0 = no); (c) measurement of bronchial hyperresponsiveness (categorized as: 1 = ≤ 4mg/mL to indicate bronchial hyperresponsiveness or obstructive pattern with compatible spirometry or 0 = > 4mg/mL, absence of bronchial hyperresponsiveness); (d) sensation of chest tightening sometimes when waking up during the last 12 months (1 = yes or 0 = no); (e) shortness of breath during the day at rest over the last 12 months (1 = yes or 0 = no); shortness of breath during the night over the last 12 months (1 = yes or 0 = no). From these indicators, those with convergent loads in EFA (above 0.50) were selected. This latent variable was evaluated in CFA, adopted according to the measures analyzed previously.

Proposed theoretical model

In the proposed theoretical model, the “prenatal SES” would be a more distal determinant (exogenous latent variable), exerting its effects on the development of asthma outcome and on all the remaining dependent variables of the model. Parental obesity, as a proxy indicator of the interaction of genotypic-phenotypic components in the history of obesity in the family environment, potentially affects the other variables related to overweight (at birth, schoolchild and adult life). In a temporal sequence, lifetime overweight variables (parental obesity, overweight at birth and schoolchild and adult overweight) may be associated with asthma in adult life. Finally, as a more proximal determinant, “current adult SES” would be associated with an increased risk of overweight and asthma during adulthood (Figure 2).

Structural equation modeling (SEM)

SEM is an epidemiological tool used to test hypotheses on relationships between latent variables (non-observed variables) and observed variables, permitting the analysis of a set of structural equations ³⁸38. Muthén LK, Muthén BO. Mplus: statistical analysis with latent variables. User's guide. Los Angeles: Muthén & Muthén; 2010..

The WLSMV estimator, theta parameterization for the control of residual variances ³⁸38. Muthén LK, Muthén BO. Mplus: statistical analysis with latent variables. User's guide. Los Angeles: Muthén & Muthén; 2010., was used in SEM, in addition to weighting the estimates by loss of follow-up. To determine whether the model showed good fit, the same estimates previously described for CFA were considered ²¹21. Byrne B. Structural equation modeling with Mplus: basic concepts, applications and programming. New York: Routledge; 2012.^,3434. Kline RB. Principles and practice of structural equation modeling. New York: Guilford Press; 2011.. The chi-square, degrees of freedom and p-value were evaluated but were not adopted as parameters for model fitting due to their sensitivity to sample size.

The command for the verification of modification indices (modindices) was used to test if suggestions could improve model fit. Modindices values higher than 10 were used to generate a new model ²¹21. Byrne B. Structural equation modeling with Mplus: basic concepts, applications and programming. New York: Routledge; 2012., as long as these pathways were plausible from a theoretical viewpoint.

The effect of observed variables and latent variables on the outcomes were analyzed as standardized coefficients (SC), being considered significant when p-value < 0.05. The total, direct and indirect effects were estimated ³⁸38. Muthén LK, Muthén BO. Mplus: statistical analysis with latent variables. User's guide. Los Angeles: Muthén & Muthén; 2010..

Results

The characteristics of the adults from the cohort and of their parents are listed in Tables 1 and 2. Among the adults, the prevalence of bronchial hyperresponsiveness was 20.7% (n = 427), the prevalence of medical diagnosis of asthma was 15.2% (n = 313) and the prevalence of wheezing over the last 12 months was 19.4% (n = 401) (Table 2).

The initial latent variable “Asthma” in EFA showed convergent loads higher than 0.50 for the following indicators: medical diagnosis of asthma (standardized coefficient - SC = 0.745), wheezing (SC = 0.553) and measurement of bronchial hyperresponsiveness (SC = 0.702), with these three indicators being used in the formation of the latent variable “Asthma” in the SEM analysis (data not shown in tables).

In the SEM model, each indicator of the latent variables “prenatal SES” and “current adult SES” had factorial loadings above 0.60 and all the indicators of these latent variables had significant p-values (p < 0.0001) (Table 3; Figure 2).

Higher “prenatal SES” values were associated with parental obesity (SC_direct = 0.101, p = 0.009) and with overweight at birth (SC_total = 0.131, p < 0.0001, and SC_direct = 0.126, p < 0.0001) (Table 4).

Higher “prenatal SES” values (SC_total = 0.183, p < 0.0001, and SC_direct = 0.155, p < 0.0001) and parental obesity (SC_total = 0.170, P = 0.001, and SC_direct = 0.166, p = 0.001) were associated with overweight at school age. “Prenatal SES” also had a positive indirect effect on overweight at school age, with this effect being mediated by parental obesity (SC_indirect = 0.017, p = 0.039) (Table 4).

Parental obesity (SC_total = 0.211, p < 0.0001, and SC_direct = 0.115, p = 0.007) and overweight at school age (SC_total = 0.565, p < 0.0001, and SC_direct = 0.565, p < 0.0001) were associated with adult overweight, whereas lower “current adult SES” values protected against adult overweight (SC_direct = -0.171, p = 0.016). Parental obesity also had a positive indirect effect on adult overweight, with this effect being mediated by overweight at school age (SC_indirect = 0.094, p = 0.001) (Table 4).

An association was also observed between “prenatal SES” and “current adult SES” (SC_direct = 0.779, p < 0.0001) (data not shown in the tables).

Among the lifetime overweight indicators studied here, parental obesity was associated with asthma continuous variables during adult life (SC_total = 0.105, p = 0.047). And, at the other extreme, underweight at birth was positively associated with adult’s asthma continuous variables (SC_total = -0.124, p = 0.009 e SC_direct = -0.131; p = 0.007) (Table 5).

Higher “prenatal SES values” (SC_total = -0.105, P = 0.009) and higher “current adult SES” (SC_total = -0.179, p = 0.041 e SC_direct = -0.182, p = 0.039) had a protective effect in adult’s asthma continuous variables (Table 5).

Discussion

In the present study, parental obesity and overweight at school age were associated with overweight in adults, whereas a higher “current adult SES” protected them against this outcome. Parental obesity and underweight at birth were variables related to asthma. While the larger “SES of prenatal” and larger “SES of the adult” were protective of asthma in adult life.

Parental obesity was associated with adult obesity, having a direct effect as well as an indirect effect via overweight at school age. These findings are consistent with the literature, which shows that a higher maternal ³⁹39. Botton J, Heude B, Maccario J, Borys JM, Lommez A, Ducimetiere P, et al. Parental body size and early weight and height growth velocities in their offspring. Early Hum Dev 2010; 86:445-50.^,4040. Knight B, Shields BM, Hill A, Powell RJ, Wright D, Hattersley AT. The impact of maternal glycemia and obesity on early postnatal growth in a nondiabetic Caucasian population. Diabetes Care 2007; 30:777-83. or paternal ⁴¹41. Regnault N, Botton J, Forhan A, Hankard R, Thiebaugeorges O, Hillier TA, et al. Determinants of early ponderal and statural growth in full-term infants in the EDEN mother-child cohort study. Am J Clin Nutr 2010; 92:594-602.^,4242. Linabery AM, Nahhas RW, Johnson W, Choh AC, Towne B, Odegaard AO, et al. Stronger influence of maternal than paternal obesity on infant and early childhood body mass index: the Fels Longitudinal Study. Pediatr Obes 2013; 8:159-69. BMI is associated with a higher childhood BMI. Maternal obesity has already been associated with obesity of the child during adult life ⁴³43. Rooney K, Ozanne SE. Maternal over-nutrition and offspring obesity predisposition: targets for preventative interventions. Int J Obes (Lond) 2011; 35:883-90.^,4444. Drake AJ, Reynolds RM. Impact of maternal obesity on offspring obesity and cardiometabolic disease risk. Reproduction 2010; 140:387-98.. Meta-analysis findings have also revealed an association between a high childhood BMI and adult obesity ⁴⁵45. Simmonds M, Burch J, Llewellyn A, Griffiths C, Yang H, Owen C, et al. The use of measures of obesity in childhood for predicting obesity and the development of obesity-related diseases in adulthood: a systematic review and meta-analysis. Health Technol Assess 2015; 19:1-336.. Parental obesity appears as a marker for the complex interaction between genetic, epigenetic and environmental factors, thus illustrating the joint contribution of them and/or family shared trajectories ⁴²42. Linabery AM, Nahhas RW, Johnson W, Choh AC, Towne B, Odegaard AO, et al. Stronger influence of maternal than paternal obesity on infant and early childhood body mass index: the Fels Longitudinal Study. Pediatr Obes 2013; 8:159-69..

Higher “prenatal SES” values were a risk factor for parental obesity, for birth overweight and for overweight at school age, while higher “current adult SES” values were a protective factor against adult overweight. These distinct effects of latent SES variables on overweight outcomes at different time points in cohort follow-ups reflect the nutritional transition that has been occurring over the last decades ⁴⁶46. Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev 2012; 70:3-21.. In Brazil obesity was shifting towards groups with greater social vulnerability ⁴⁷47. Goncalves H, Barros FC, Buffarini R, Horta BL, Menezes AMB, Barros AJD, et al. Infant nutrition and growth: trends and inequalities in four population-based birth cohorts in Pelotas, Brazil, 1982-2015. Int J Epidemiol 2019; 48 Suppl 1:i80-i8..

The effect of parental obesity asthma in adult life may be explained by the development of synergic interactions between genes and environment, with the children of obese individuals being genetically predisposed to excess weight gain within obesogenic domestic environments ⁴⁸48. Fuentes Pacheco A, Carrillo Balam G, Archibald D, Grant E, Skafida V. Exploring the relationship between local food environments and obesity in UK, Ireland, Australia and New Zealand: a systematic review protocol. BMJ Open 2018; 8:e018701.. Taken together, these factors may result in other inflammatory and/or chronic diseases, asthma being one of them ⁴⁹49. Bagby SP, Martin D, Chung ST, Rajapakse N. From the outside in: biological mechanisms linking social and environmental exposures to chronic disease and to health disparities. Am J Public Health 2019; 109(S1):S56-S63..

Even if parental obesity was the only variable related to lifetime overweight with an effect on adult’s continuous asthma variable, the association of parental obesity with the intermediate outcomes of schoolchild nutritional status and of adult nutritional status may help explain why previous studies have detected an association of these last variables with asthma ⁶6. Liu PC, Kieckhefer GM, Gau BS. A systematic review of the association between obesity and asthma in children. J Adv Nurs 2013; 69:1446-65.^,99. Beuther DA, Sutherland ER. Overweight, obesity, and incident asthma: a meta-analysis of prospective epidemiologic studies. Am J Respir Crit Care Med 2007; 175:661-6.^,1616. Cetlin AA, Gutierrez MR, Bettiol H, Barbieri MA, Vianna EO. Influence of asthma definition on the asthma-obesity relationship. BMC Public Health 2012; 12:844.^,5050. Xu XF, Li YJ, Sheng YJ, Liu JL, Tang LF, Chen ZM. Effect of low birth weight on childhood asthma: a meta-analysis. BMC Pediatr 2014; 14:275..

At the other extreme regarding weight, underweight at birth was associated to asthma in adult life. Meta-analysis studies have shown an association of both low birthweight ⁵⁰50. Xu XF, Li YJ, Sheng YJ, Liu JL, Tang LF, Chen ZM. Effect of low birth weight on childhood asthma: a meta-analysis. BMC Pediatr 2014; 14:275. and high birthweight8 with the future risk of asthma using weight for gestational age. The present study added knowledge to this theme, since it classified the nutritional status at birth according to an anthropometric indicator, permitting the verification of underweight and overweight, as well as the pathways triggered from them over time.

Intrauterine mechanisms that affect immunity or pulmonary development have been suggested as possible explanations for this effect of fetal underweight on asthma ⁵¹51. Forno E, Young OM, Kumar R, Simhan H, Celedon JC. Maternal obesity in pregnancy, gestational weight gain, and risk of childhood asthma. Pediatrics 2014; 134:e535-46.. However, the epigenetic mechanism of the sparing phenotype, by which the intrauterine environment of nutritional restriction increases the chance of adult obesity ⁵²52. Lillycrop KA. Effect of maternal diet on the epigenome: implications for human metabolic disease. Proc Nutr Soc 2011; 70:64-72.^,5353. Godfrey KM, Barker DJ. Fetal programming and adult health. Public Health Nutr 2001; 4:611-24., may not be an explanation for our asthma findings since the effect of underweight at birth on asthma continuous variables was direct, without a pathway that would go through overweight.

The effect of “prenatal SES” and “current adult SES” on the risk of asthma corroborates findings from other studies which showed that the indicators related to a lower socioeconomic level are associated with a higher risk of asthma, using observed variables such as education, occupation, income, and material goods ⁵⁴54. Caldeira RD, Bettiol H, Barbieri MA, Terra-Filho J, Garcia CA, Vianna EO. Prevalence and risk factors for work related asthma in young adults. Occup Environ Med 2006; 63:694-9.^,5555. Almqvist C, Pershagen G, Wickman M. Low socioeconomic status as a risk factor for asthma, rhinitis and sensitization at 4 years in a birth cohort. Clin Exp Allergy 2005; 35:612-8.^,5656. Corvalan C, Amigo H, Bustos P, Rona RJ. Socioeconomic risk factors for asthma in Chilean young adults. Am J Public Health 2005; 95:1375-81.. The present study contributes to this knowledge by showing that inequality situations represented by lower values of the latent variable SES, with a lower determination error and observed at two time points in life were associated with adult’s asthma continuous variables.

These results showed that “current adult SES” exerted a proximal and direct protective effect on adult’s asthma continuous variables, a fact that may be explained by the access to healthier dietary choices due to higher income and schooling ⁵⁷57. Uphoff E, Cabieses B, Pinart M, Valdes M, Anto JM, Wright J. A systematic review of socioeconomic position in relation to asthma and allergic diseases. Eur Respir J 2015; 46:364-74.^,5858. Hedlund U, Eriksson K, Ronmark E. Socio-economic status is related to incidence of asthma and respiratory symptoms in adults. Eur Respir J 2006; 28:303-10., to labor activity or to living in urban environments with lower risks for asthma ⁵⁴54. Caldeira RD, Bettiol H, Barbieri MA, Terra-Filho J, Garcia CA, Vianna EO. Prevalence and risk factors for work related asthma in young adults. Occup Environ Med 2006; 63:694-9..

A limitation of this study was that the prenatal obesity variable was reported by the participants during the 4^th cohort follow-up, without a precise indication of the beginning of this condition. However, parental obesity was used as a proxy for the interaction of genotype-phenotype components in the history of the family environment ⁵⁹59. Huang T, Hu FB. Gene-environment interactions and obesity: recent developments and future directions. BMC Med Genomics 2015; 8 Suppl 1:S2.. In this respect, in thisstudy parental overweight was found to be the starting point for other indicators of lifetime overweight in the offspring.

It was not possible here to confirm the association between parental obesity and schoolchild overweight with childhood asthma ⁶6. Liu PC, Kieckhefer GM, Gau BS. A systematic review of the association between obesity and asthma in children. J Adv Nurs 2013; 69:1446-65. since these data were not available for the cohort. However, more distal variables linked to weight such as parental obesity and underweight at birth were associated with adult asthma.

Strong points of this study were the pioneering approach to the exploration of this set of variables as indicators of overweight in a manner interrelated with asthma during adult life, the use of a birth cohort of Brazilian children involving a large sample analyzed at three distinct times, i.e., birth, school age and adulthood, and the use of weighting by the inverse of the probability of participating in the follow-ups, minimizing the possibility of selection biases due to sample losses and increasing the external validity of the study.

We also emphasize the SEM analysis with the formation of latent variables for “prenatal SES” and “current adult SES”, permitting the formation of these variables of complex definition and reducing the measurement errors. In addition, SEM permitted to estimate the total, direct and indirect effects, for a better interpretation of the results obtained, signaling these effects in the temporal relationships between lifetime overweight and asthma in adulthood.

Another strong point of this study was the continuous variable “Asthma”, which included the variable observed with the bronchial hyperresponsiveness test by methacholine bronchoprovocation associated with other symptoms of the disease ⁶⁰60. National Institute for Health and Care Excellence. Asthma: diagnosis and monitoring of asthma in adults, children and young people. London: National Institute for Health and Care Excellence; 2017.. Other symptoms of asthma were included in the latent variable reducing the error of determination in the diagnosis of the disease. So far, only one study has used a latent variable for the construction of this asthma variable and was conducted on a target public differing from the present study, i.e., in children ⁶¹61. Nascimento J, Ribeiro CCC, Batista RFL, de Britto Alves M, Simoes VMF, Padilha LL, et al. The first 1000 days of life factors associated with "childhood asthma symptoms": Brisa Cohort, Brazil. Sci Rep 2017; 7:16028..

Parental obesity was the starting point for the overweight pathways in childhood and adulthood, with an evident transgenerational effect. A greater weight at childhood continued to be a risk for overweight during adulthood. The effect of “prenatal SES” was a marked risk for parental obesity and for overweight at birth and during childhood. On the other hand, SES at the fourth follow-up of the cohort was a protective factor against adult overweight, characterizing the nutritional transition that has been occurring in Brazil over the last few decades.

Regarding weight pathways in asthma, parental obesity and underweight at birth were risk factors for asthma continuous variables during adulthood. SES at the two follow-up times of the cohort was a protective factor against adult asthma. Taken together, these data suggest that public policies should focus on appropriate weight within the family environment and at birth as a form of preventing lifetime obesity and asthma.

Acknowledgments

The authors acknowledge the study participants, the research team for the collection of the information. They acknowledge the support of the Faculty of Medicine of Ribeirão Preto, University of São Paulo (FMRP-USP) for the conduction and execution of this study.

References

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