Lifetime overweight and adult asthma: 1978/1979 Ribeirão Preto Birth Cohort, São Paulo, Brazil Sobrepeso ao longo da vida e asma na idade adulta: Coorte de Nascimento de 1978/1979, Ribeirão Preto, São Paulo, Brasil Sobrepeso a lo largo de la vida y asma en adultos: Cohorte de Nacimientos de 1978

Studies focusing on obesity and asthma frequently consider the weight at a given time; thus, modeling pathways through lifetime overweight may contribute to elucidate temporal aspects in this relationship. This study modeled the pathways in the association of lifetime overweight with asthma in adult life, using data from the 1978/1979 Birth Cohort, Ribeirão Preto, São Paulo, Brazil (n = 2,063) at birth (baseline), school age (9/11 years) and adult age (23/25 years). A theoretical model was proposed to explore the effects of lifetime overweight on asthma in adult life analyzed by structural equation modeling. Parental obesity (SC – standardized coefficenttotal = 0.211, p < 0.001; SCdirect = 0.115, p = 0.007) and overweight at school age (SCtotal = 0.565, p < 0.0001; SCdirect = 0.565, p < 0.0001) were associated with overweight in adult life. Parental obesity (SCdirect = 0.105, p = 0.047) and nutritional status at birth (SCtotal = -0.124, p = 0.009; SCdirect = -0.131, p = 0.007) were associated with asthma in adult life. A higher “current adult socieconomic situation” was inversely associated to overweight (SCdirect = -0.171, p = 0.020) and to asthma in adult life (SCtotal = -0.179, p = 0.041; SCdirect = -0.182, p = 0.039). Parental obesity showed a transgenerational effect in weight, triggering to childhood and adulthood overweight. Parallel to underweight at birth, parental obesity was also a risk to asthma in adult life. While, the socioeconomic status in adult life protected from both, overweight and asthma. Overweight; Life Cycle Stages; Structural Equation Modeling; Asthma This article is published in Open Access under the Creative Commons Attribution license, which allows use, distribution, and reproduction in any medium, without restrictions, as long as the original work is correctly cited.


Introduction
Asthma is a chronic disease that affects 235 million people all over the world 1 ; and that is being consistently associated with other non-communicable chronic diseases (NCCD) 2 with which it appears to share physiopathological mechanisms that need to be better explored 3,4 .
Obesity is an important risk factor for NCCD, which is being associated with asthma from birth to adulthood 5,6,7,8,9 . Overweight during childhood increases the risk to develop asthma during this phase of life 5,6,7,10,11 or in the future 8,12 . Overweight and obesity have also been associated with asthma in adults, with a dose-response effect on body mass index (BMI) 9 .
Studies focusing on obesity and asthma frequently consider overweight at a given time 13,14,15,16 . Few prospective studies on the association between obesity and asthma have adjusted the model for birth variables using regression models 17,18 .
The association between obesity and asthma involves a complex and temporal relationship between maternal prenatal weight, birth weight, childhood and even adulthood weight 19,20 . Structural equation modeling (SEM) is a useful tool for the study of epidemiological multicausality phenomena 21 .
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.

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 22,23 .

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 24 .
Thus, 6,973 newborns remained in the study, 6,827 of them being singletons and 146 being twins 24 . A total of 257 of the 6,827 singletons died during the first year of life 25 and 86 died by 20 years of age. Thus, 6,484 were left at 20 years of age 26 .
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 24 .
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) 24 .
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 24 .
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][10][11] Cad. Saúde Pública 2020; 36(2):e00041519   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 24,27 .

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 28 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 29 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 29 . 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 30 .
To measure the students' height, we used anthropometers manufactured exclusively for the research, whose measurements were taken in centimeters, to the nearest 0.5cm 30 . 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 29 .
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 31 . 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 32 .
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 Survey 27 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 33 . 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 27 .

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 Cad. Saúde Pública 2020; 36(2):e00041519 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 34 .
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 (χ 2 ); (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 34 .
Then, confirmatory factorial analysis (CFA) was carried out in order to verify the factors previously determined by EFA 34 , 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 34 . The modindices (modification index) command was used to obtain suggestions of changes in the proposed latent variable 21 . Exploratory and confirmatory factorial analyses were carried out using the Mplus software, version 7.0 (https://www.statmodel.com/).

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 (nonobserved variables) and observed variables, permitting the analysis of a set of structural equations 38 .
The WLSMV estimator, theta parameterization for the control of residual variances 38 , 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 21,34 . The chisquare, 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 21 , 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 38 .

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 Cad. Saúde Pública 2020; 36(2):e00041519 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).
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).

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 39,40 or paternal 41,42 BMI is associated with a higher childhood BMI. Maternal obesity has already been associated with obesity of the child during adult life 43,44 . Meta-analysis findings have also revealed an association between a high childhood BMI and adult obesity 45 . 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 42 .
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 46 . In Brazil obesity was shifting towards groups with greater social vulnerability 47 .
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 48 . Taken together, these factors may result in other inflammatory and/or chronic diseases, asthma being one of them 49   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 6,9,16,50 .
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 50 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 51 . However, the epigenetic mechanism of the sparing phenotype, by which the intrauterine environment of nutritional restriction increases the chance of adult obesity 52,53 , 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 54,55,56 . 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 57,58 , to labor activity or to living in urban environments with lower risks for asthma 54 .
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. How-Cad. Saúde Pública 2020; 36(2):e00041519 ever, parental obesity was used as a proxy for the interaction of genotype-phenotype components in the history of the family environment 59 . 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 6 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 60 . 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 61 .
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.