OBJECTIVE: The existence of catch-up lung function growth and its predictors is uncertain. We aimed to identify lung function trajectories and their predictors in a population-based birth cohort. METHODS: We applied group-based trajectory modelling to z-scores of forced expiratory volume in 1 second (zFEV(1)) and z-scores of forced vital capacity (zFVC) from 1151 children assessed at around 4, 7, 9, 10, 11, 14 and 18 years. Multinomial logistic regression models were used to test whether potential prenatal and postnatal predictors were associated with lung function trajectories. RESULTS: We identified four lung function trajectories: a low (19% and 19% of the sample for zFEV(1) and zFVC, respectively), normal (62% and 63%), and high trajectory (16% and 13%) running in parallel, and a catch-up trajectory (2% and 5%) with catch-up occurring between 4 and 10 years. Fewer child allergic diseases and higher body mass index z-score (zBMI) at 4 years were associated with the high and normal compared with the low trajectories, both for zFEV(1) and zFVC. Increased children’s physical activity during early childhood and higher zBMI at 4 years were associated with the catch-up compared with the low zFEV(1) trajectory (relative risk ratios: 1.59 per physical activity category (1.03-2.46) and 1.47 per zBMI (0.97-2.23), respectively). No predictors were identified for zFVC catch-up growth. CONCLUSION: We found three parallel-running and one catch-up zFEV(1) and zFVC trajectories, and identified physical activity and body mass at 4 years as predictors of zFEV(1) but not zFVC catch-up growth.

Patients with cancer were excluded from pivotal randomized clinical trials of COVID-19 vaccine products, and available observational evidence on vaccine effectiveness (VE) focused mostly on mild, and not severe COVID-19, which is the ultimate goal of vaccination for high-risk groups. Here, using primary care electronic health records from Catalonia, Spain (SIDIAP), we built two large cohorts of vaccinated and matched control cancer patients with a primary vaccination scheme (n = 184,744) and a booster (n = 108,534). Most patients received a mRNA-based product in primary (76.2%) and booster vaccination (99.9%). Patients had 51.8% (95% CI 40.3%-61.1%) and 58.4% (95% CI 29.3%-75.5%) protection against COVID-19 hospitalization and COVID-19 death respectively after full vaccination (two-doses) and 77.9% (95% CI 69.2%-84.2%) and 80.2% (95% CI 63.0%-89.4%) after booster. Compared to primary vaccination, the booster dose provided higher peak protection during follow-up. Calibration of VE estimates with negative outcomes, and sensitivity analyses with slight different population and COVID-19 outcomes definitions provided similar results. Our results confirm the role of primary and booster COVID-19 vaccination in preventing COVID-19 severe events in patients with cancer and highlight the need for the additional dose in this population.

OBJECTIVE: Factors that shape individuals’ vulnerability to the effects of air pollution on COVID-19 severity remain poorly understood. We evaluated whether the association between long-term exposure to ambient NO(2), PM(2.5), and PM(10) and COVID-19 hospitalisation differs by age, sex, individual income, area-level socioeconomic status, arterial hypertension, diabetes mellitus, and chronic obstructive pulmonary disease. METHODS: We analysed a population-based cohort of 4,639,184 adults in Catalonia, Spain, during 2020. We fitted Cox proportional hazard models adjusted for several potential confounding factors and evaluated the interaction effect between vulnerability indicators and the 2019 annual average of NO(2), PM(2.5), and PM(10). We evaluated interaction on both additive and multiplicative scales. RESULTS: Overall, the association was additive between air pollution and the vulnerable groups. Air pollution and vulnerability indicators had a synergistic (greater than additive) effect for males and individuals with low income or living in the most deprived neighbourhoods. The Relative Excess Risk due to Interaction (RERI) was 0.21, 95 % CI, 0.15 to 0.27 for NO(2) and 0.16, 95 % CI, 0.11 to 0.22 for PM(2.5) for males; 0.13, 95 % CI, 0.09 to 0.18 for NO(2) and 0.10, 95 % CI, 0.05 to 0.14 for PM(2.5) for lower individual income and 0.17, 95 % CI, 0.12 to 0.22 for NO(2) and 0.09, 95 % CI, 0.05 to 0.14 for PM(2.5) for lower area-level socioeconomic status. Results for PM(10) were similar to PM(2.5). Results on multiplicative scale were inconsistent. CONCLUSIONS: Long-term exposure to air pollution had a larger synergistic effect on COVID-19 hospitalisation for males and those with lower individual- and area-level socioeconomic status.