Follow-up study of the LINC cohort: Chemical exposures and health of adolescents

Throughout our lives we are exposed to a variety of synthetic environmental
chemicals present in food, water, medicines, the air we breathe, cosmetics and
health care products, shoes, clothing, building materials, food packaging, and
other consumer products. These chemicals can potentially interfere with
physiological and behavioural development, including disrupting normal
functioning of the endocrine system (i.e., endocrine disrupting chemicals). As
a result, exposure to chemicals during sensitive developmental stages such as
the perinatal and childhood periods, has been linked to a wide range of adverse
health outcomes, including cardiometabolic diseases, cancer, fertility problems
and neurodevelopmental disorders. However, studies that examine the effects of
chemicals prospectively are limited and often focus on specific exposed
populations or individual chemical compounds. Therefore, it is crucial to study
a broad set of chemical exposures in the general population in order to
characterize health impacts and inform chemical health risk assessments and
regulations.

This study aims to address knowledge gaps regarding health effects of chemical
mixtures in childhood/adolescence and their underlying mechanisms. We aim to
conduct a follow-up study with children from the LINC birth cohort. The LINC
study is a prospective birth cohort study (METC VUmc number: NL31941.029.10)
which recruited pregnant women in 2011-2015 in the areas of Zwolle, Purmerend
and Den Helder. The primary objective of the follow-up is to answer the
research question *What is the effect of environmental chemicals on the
development and health of children?*. We will assess neuropsychological
development, pubertal development, cardiometabolic outcomes, and
respiratory/allergic-related health outcomes of the children/adolescents in the
LINC cohort. The secondary objectives of LINC are to (i) assess exposure
patterns over time and during sensitive windows of exposure; and to (ii) study
associations between chemical exposures and the gut microbiome and mediating
role of the gut microbiome.

A prospective, non-invasive observational assessment will be carried out in
which we will investigate the current exposure levels and developmental
outcomes of the children in the LINC cohort in 2024-2026, visiting children
when they are around 12-13 years (potential range 11-14 years). During the
follow-up, children will undergo anthropometric measurements, provide a morning
saliva sample, urine samples and a fecal sample, and the children and their
parents or caregivers will complete questionnaires. Children will wear a
silicone wristband, a passive wearable sampler, for 1 week. Current chemical
exposure levels will be measured in urine samples and the wristband, the
microbiome composition will be measured in a fecal sample, and steroid hormone
levels will be measured in the saliva sample.

Little to no risks are expected for participation in the study. Participants
will be asked to fill out questionnaires, and collect 1 saliva sample, 3 urine
samples on one day, and 1 fecal sample. The child will wear a silicone
wristband for one week. Overall, due to the non-invasive design, we expect this
to be a small-to-modest burden. A conceivable but negligible risk is the raised
awareness of exposure to chemicals in the daily environment of participants,
which can potentially lead to concern and stress. However, we will put the
exposures (generally low yet ubiquitous) and health risks (generally low in
magnitude) in context in communicating the relevance of the research and
results. Lastly, we do not expect that group relatedness will hamper inferences
of the epidemiological studies. Siblings are excluded from the study. The
children may exhibit some similarity in exposure, health outcome and covariate
profiles compared to the variability present in the Dutch population of
children*given that mothers/children were and will be recruited in three cities
(Zwolle, Purmerend and Den Helder) in a specific period of time*however, we
will use statistical models which account for covariates and relatedness as
appropriate.