(C) PLOS One This story was originally published by PLOS One and is unaltered. . . . . . . . . . . Childhood body mass index trajectories and associations with adult-onset chronic kidney disease in Denmark: A population-based cohort study [1] ['Julie Aarestrup', 'Center For Clinical Research', 'Prevention', 'Copenhagen University Hospital Bispebjerg', 'Frederiksberg', 'Kim Blond', 'Dorte Vistisen', 'Steno Diabetes Center Copenhagen', 'Herlev', 'Department Of Public Health'] Date: 2022-11 We included 151,506 boys and 148,590 girls from the Copenhagen School Health Records Register, born 1930 to 1987 with information on measured weights and heights at ages 6 to 15 years. Five sex-specific childhood BMI trajectories were analyzed. Information on the main outcomes CKD and ESKD, as well as T2D, came from national health registers. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were estimated using Poisson regression adjusted for year of birth. During a median of 30.8 person-years of follow-up, 5,968 men and 3,903 women developed CKD and 977 men and 543 women developed ESKD. For both sexes, the rates of CKD and ESKD increased significantly with higher child BMI trajectories in comparison with the average BMI trajectory (40% to 43% of individuals) and the below-average BMI trajectory (21% to 23% of individuals) had the lowest rates. When including T2D, most associations were significant and men (IRR = 1.39, 95% CI: 1.13 to 1.72) and women (IRR = 1.54, 95% CI: 1.28 to 1.86) with the obese childhood BMI trajectory (2% of individuals) had significantly higher CKD rates than the average BMI trajectory, whereas for ESKD, the associations were positive, but nonsignificant, for men (IRR = 1.38, 95% CI: 0.83 to 2.31) but significant for women (IRR = 1.97, 95% CI: 1.25 to 3.11) with the obese BMI trajectory. A main study limitation is the use of only hospital-based CKD diagnoses. Data Availability: We can make the data (in de-identified form to the best of our abilities given legal regulations) used in the manuscript available upon request (email address: CSHRR@regionh.dk ) and pending approval from the steering committee at the Center for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Capital Region, Denmark that governs the use of these data. In addition to the high prevalence of overweight in adults, overweight and obesity in children now similarly constitute an enormous global health crisis with more than 124 million children living with obesity [ 10 ]. Despite the presence of early kidney abnormalities and decreased kidney function among children with severe obesity [ 7 ], the potential early origins of CKD are sparsely investigated [ 11 – 16 ]. Among the few studies in this area, some included body size in late adolescence [ 12 , 14 ], and many only provided associations with ESKD [ 11 , 12 , 14 ]. Further, although some studies investigated associations with patterns of BMI development from child- to adulthood [ 13 , 15 , 16 ], the majority of these were limited by including subclinical renal damage as a proxy for CKD [ 15 , 16 ]. Therefore, using a large Danish cohort with repeated measurements of childhood height and weight, we prospectively investigated sex-specific associations between childhood BMI trajectories and weight status at individual childhood ages and adult-onset CKD and ESKD, respectively, and the role of adult-onset type 2 diabetes (T2D) on these associations. The primary risk factors for CKD vary by country; however, diabetes and hypertension are among the established leading causes, particularly in high-income countries [ 2 , 4 ]. Additionally, increasing evidence supports that excess adult adiposity is a substantial and causal contributor to CKD risk [ 5 – 8 ]. Although overweight and obesity are closely related to both diabetes and hypertension, it is suggested that excess adiposity may have effects on CKD risks independent of these 2 major causes of CKD [ 9 ]. The burden of chronic kidney disease (CKD) is rising worldwide due to population aging and an increased prevalence of CKD risk factors [ 1 ]. An estimated 697.5 million individuals, corresponding to a global prevalence of 9.1%, had a diagnosis of CKD in 2017 [ 1 ]. Further, 1.2 million individuals died from CKD in 2017 and the disease is projected to rise in rank as a leading cause of death [ 1 ]. CKD is generally more common in women than men; however, the disease is often more severe among men as indicated by the higher rates of end-stage kidney disease (ESKD) and age-standardized mortality [ 1 ]. Although CKD is recognized as an important health issue, the awareness of the disease remains low among the general population and healthcare providers [ 2 ]. An examination of potential effect modification by T2D on the associations between the childhood body size exposures and outcomes was planned a priori. We included a product term between T2D and the posterior probabilities for childhood BMI trajectory membership and childhood weight status at specific ages, respectively, and tested for potential interactions using the likelihood ratio test, while allowing for an interaction between T2D and age at risk. Further, we conducted analyses that did and did not include T2D modelled as a time-varying covariate to account for the duration of T2D to evaluate if childhood body size provides information about adult-onset CKD and ESKD rates beyond that from T2D. A priori, we chose to estimate sex-specific incidence rate ratios (IRRs) and 95% confidence intervals (CIs) of the associations between childhood body size exposures and adult-onset CKD and ESKD using Poisson regression analyses. The logarithm of time at risk was used as the offset and age (in 1-year time intervals to accommodate that the rates of the outcomes changes with age) and birth year were included as covariates. In analyses on childhood BMI trajectories, posterior probabilities, which have been found to be superior to modal assignment [ 25 ], were used as the exposures to reduce potential effects of misclassification among the trajectories. The average BMI trajectory was used as the reference, and the posterior probabilities were included as 4 continuous variables, leaving out the reference. To further enhance comparability with other studies, we also performed analyses with childhood BMI categorized as under, normal, and overweight (including obesity) at ages 7, 10, and 13 years. We examined potential interactions of birth cohort (modelled using 3 categories: 1930 to 1939, 1940 to 1949, and 1950 to 1987) on the associations between the childhood BMI trajectories ( S2 Table ) and childhood weight status ( S3 Table ), respectively, and CKD using the likelihood ratio test. We did not detect any interactions on associations with CKD (p-values ≥ 0.06), although there were indications that the associations strengthened in magnitude across time in men, but not women, with childhood BMI trajectories above average and with childhood overweight at individual ages, respectively. Due to a low case number, we were not sufficiently powered to conduct similar investigations on associations with ESKD. Individuals eligible for inclusion into this study were born 1930 to 1987, had an identification number, and were alive and living in Denmark at age 30 years or older from January 1, 1977 onwards (n = 311,873) ( S4 Fig ). Exclusions were made for individuals with a diagnosis of CKD (inclusive of hereditary kidney disease) or kidney cancer (n = 507) or diabetes (n = 1,007) before follow-up (i.e., before age 30 years or before 1977), and those with <2 childhood BMI values (n = 10,263). The analytical population consisted of 300,096 individuals (151,506 men, 148,590 women). Follow-up started on January 1, 1977 or at age 30 years, whichever came later, and ended on the date of a diagnosis of CKD or ESKD, hereditary kidney disease, kidney cancer, type 1 diabetes, death, emigration, loss to follow-up, or December 31, 2017, whichever came first. We further censored individuals if they had a first diagnosis of T2D and CKD on the same date. In Denmark, all citizens alive or born after April 2, 1968 were issued a unique government identification number [ 22 ]. These numbers were recorded on the children’s health cards or retrieved for children who finished school before 1968 [ 17 ]. Through these numbers, individual-level linkage of children in the CSHRR to the Danish Vital Statistics Register for vital status information was performed [ 22 ]. Information on adult-onset CKD, including ESKD, was obtained from the Danish National Patient Register, which contains information on discharge diagnoses from all inpatient hospital contacts since 1977 and all outpatient hospital contacts since 1995 [ 23 ]. CKD was defined based upon the first hospital admission or contact using the International Classification of Disease eight revision until 1994 and the 10th revision thereafter ( S1 Table ). Information on T2D diagnoses came from several national health registers, and information on kidney cancer was retrieved through linkage to the Danish Cancer Registry, where information is available from 1943 onwards ( S1 Table ) [ 24 ]. The children in the CSHRR had up to 12 measurements recorded. All children with a minimum of 2 BMI values (≥95% of children had more than 2 values) were included when estimating sex-specific BMI trajectories using latent class trajectory models, which impute missing values under a missing at random assumption [ 18 – 20 ]. We a priori chose to generate BMI trajectories separately by sex to account for differences in growth among boys and girls. The trajectories were modelled using natural splines with knot points positioned at ages 8, 10, and 12 years (corresponding approximately to the 25th, 50th, and 75th percentiles) to best capture the natural growth patterns of children at these ages as well as to evenly space these points across the age span and were adjusted for birth cohort (5-year intervals). Several parameters and fit indices (i.e., proportion in each trajectory, mean posterior probability, Bayesian information criteria, relative entropy, odds of correct classification, visual inspection of the trajectories) were used to identify the optimal number of trajectories [ 19 ]. We tested models with up to 8 different childhood BMI trajectories ( S1 and S2 Figs). The best performing model identified 5 noncrossing BMI trajectories for each sex ( S3 Fig ) and did not include random effects, whereby the variation in BMI level within each trajectory was reduced. These BMI trajectories were termed as below-average, average, above-average, overweight, and obese. Most boys and girls followed the average BMI trajectory, and the fewest belonged to the obese BMI trajectory ( Table 1 ). For each child, a posterior probability, which is a measure of how well a child’s BMI trajectory fits within the identified trajectories, was assigned for each of the 5 trajectories. Furthermore, due to nonlinearity in the associations, at individual childhood ages, BMI values were classified as underweight (