Prepregnancy maternal BMI and trajectories of BMI-for-age in children up to four years of age: findings from the 2015 Pelotas (Brazil) birth cohort.

BACKGROUND: The aims of the study were to: (a) describe BMI-for-age trajectories in children up to four years of age; (b) evaluate the association between prepregnancy maternal BMI and the BMI-for-age trajectories. METHODS: Data from 3218 (75.3% of the original cohort) children from the Pelotas 2015 Birth Cohort were analyzed. Prepregnancy BMI (kg/m2) was measured on the perinatal interview. Z-scores of BMI-for-age were calculated for children at three months, 1, 2 and 4 years. Trajectories were identified using a semi-parametric group-based modeling approach. Multinomial logistic regression was used to test the association between prepregnancy BMI (weight excess: BMI ≥ 25 kg/m2) and BMI-for-age trajectories. RESULTS: Four trajectories of the BMI-for-age, in z-score, were identified and represent children in the "increasing", "adequate", "stabilized" and "risk for weight excess" group. A total of 196 children (7.1%) belonged to the group that was at risk of weight excess. Adjusted analyses showed that children whose mothers presented prepregnancy weight excess had 2.36 (95%CI 1.71; 3.24) times more risk of belonging to group "risk for weight excess" when compared to those children whose mothers presented underweight/normal weight before pregnancy. CONCLUSION: The risk of weight excess in children up to 4 years of age were greater in mothers who presented prepregnancy weight excess.

Influence of maternal excess weight before pregnancy on breast-feeding and weaning: pooled analyses of four population-based cohorts born between 1982 and 2015.

To investigate the associations of maternal excess weight before pregnancy with (1) weaning at 3 months of age, (2) duration of exclusive breast-feeding at 6 months of age, (3) duration of any breast-feeding at 12 months of age and (4) to compare the magnitude of these associations over four decades. Data were from participants in the Pelotas (Brazil) Birth Cohorts born in 1982 (n 5334), 1993 (n 1442), 2004 (n 4092) and 2015 (n 4102). Maternal pre-pregnancy weight was collected after the delivery and breast-feeding status was assessed when children were 3 and 12 months old. Only in the most recent cohort (2015), women with excess weight (BMI ≥ 25 kg/m2) before pregnancy had higher risk of discontinuing exclusive breast-feeding within the first 6 months postpartum than women with normal weight (hazard ratio = 1·22 (95 % CI 1·15, 1·30)). Duration of any type of breast-feeding until 12 months of age was not affected by pre-pregnancy weight. Excess weight before pregnancy is associated with exclusive breast-feeding only in the most recent birth cohort coinciding with increases in excess weight and breast-feeding over time.

Trajectories and determinants of weight gain in two cohorts of young adult women born 16 years apart.

BACKGROUND: The aims were to compare: (1) baseline weights and weight gain trajectories; (2) sociodemographic, behavioural and health characteristics driving weight gain; and (3) estimated average weight in 20 years' time, in two cohorts of young women. METHODS: Data were from 16066 participants in two population-based cohorts of young adult women, born in 1973-78 ("GenX") and 1989-95 ("millennials"). Weight was reported at baseline (age 18-23 in both cohorts) and 4 years later. High weight gain was defined as >2.5% per year. Data were analysed in 2020. RESULTS: Women born in 1989-95 were almost 4 kg heavier at age 18-23 and gained weight over 4 years 1.7 times faster than those born in 1973-78. Prevalence of high weight gain was 34.2% in the 1989-95 cohort and 24% in the 1973-78 cohort. In both cohorts, older age, higher education and high physical activity were associated with lower odds of high weight gain, and more hours in paid work, poorer self-rated health and higher baseline BMI were associated with higher odds of high weight gain. Five factors (outer regional areas, one child, ex or current smoker, high stress and depression) were determinants of high weight gain in the 1989-95 cohort, but not in the 1973-78 cohort. Based on average weight at age 21 and annual percentage weight gain, we estimate that women born in 1989-95 will, on average, be 16.7 kg heavier at age 41 (93.2 kg), than women in the 1973-78 cohort (76.5 kg). CONCLUSION: High weight gain was evident in every sociodemographic group in both cohorts but most evident in millennial women with high levels of stress and depression. Without effective weight gain prevention strategies we estimate that more than 50% of the millennial women will be in the obese BMI category in 20 years. This will have serious economic, health and societal consequences.

Validity assessment of a portable anthropometer to measure length in 24-month children from the 2015 Pelotas Birth Cohort.

OBJECTIVE: This study aimed to assess the validity of a portable anthropometer against the gold standard among 2-year-old infants from the 2015 Pelotas (Brazil) Birth Cohort. DESIGN: Birth cohort study. SETTING: A fixed Harpenden® infant anthropometer was considered as the gold standard for measuring infant length due to its greater precision and stability. The portable SANNY® (model ES2000) anthropometer was the instrument to be validated. The acceptable mean difference in length between the anthropometers was 0·5 cm. In order to compare length estimates, the interviewers carried out two length measures for each of the anthropometers (fixed and portable) and for each child. The mean of the two lengths was calculated for each anthropometer, and their difference was calculated. PARTICIPANTS: A subsample of 252 24-month-old members of the 2015 Pelotas (Brazil) birth cohort study. RESULTS: Children's mean age was 23·5 months. According to Bland-Altman plot, there were no differences in overall lengths between the portable and the fixed anthropometers, or in lengths according to sex. There was a high overall concordance between the length estimates of the fixed and portable anthropometers (ρ = 0·94; 95 % CI 0·92, 0·95). CONCLUSIONS: The portable anthropometer proved to be accurate to measure the length of 24-month-old infants, being applicable to studies using the same standardised protocol used in the present study.

Contextual and individual inequalities of multimorbidity in Brazilian adults: a cross-sectional national-based study.

OBJECTIVES: The study aims to evaluate the magnitude of multimorbidity in Brazilian adults, as well to measure their association with individual and contextual factors stratified by Brazilian states and regions. METHODS: A national-based cross-sectional study was carried out in 2013 with Brazilian adults. Multimorbidity was evaluated by a list of 22 physical and mental morbidities (based on self-reported medical diagnosis and Patient Health Questionnaire-9 for depression). The outcome was analysed taking ≥2 and ≥3 diseases as cut-off points. Factor analysis (FA) was used to identify disease patterns and multilevel models were used to test association with individual and contextual variables. RESULTS: The sample comprised 60 202 individuals. Multimorbidity frequency was 22.2% (95% CI 21.5 to 22.9) for ≥2 morbidities and 10.2% (95% CI 9.7 to 10.7) for ≥3 morbidities. In the multilevel adjusted models, females, older people, those living with a partner and having less schooling presented more multiple diseases. No linear association was found according to wealth index but greater outcome frequency was found in individuals with midrange wealth index. Living in states with higher levels of education and wealthier states was associated with greater multimorbidity. Two patterns of morbidities (cardiometabolic problems and respiratory/mental/muscle-skeletal disorders) explained 92% of total variance. The relationship of disease patterns with individual and contextual variables was similar to the overall multimorbidity, with differences among Brazilian regions. CONCLUSIONS: In Brazil, at least 19 million adults had multimorbidity. Frequency is similar to that found in other Low and and Middle Income Countries. Contextual and individual social inequalities were observed.