Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts

Howe, Laura D; Tilling, Kate; Matijasevich, Alícia; Petherick, Emily; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S.; Barros, Aluísio J. D.; Martin, Richard M.; Kramer, Michael S.; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A.

doi:10.1177/0962280213503925

Cited by 173 publications

(236 citation statements)

References 41 publications

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“…their own trajectory [21]. These models can easily handle unbalanced data with a different number of measurements per child assessed at different points in time.…”

Section: Resultsmentioning

confidence: 99%

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Associations between early body mass index trajectories and later metabolic risk factors in European children: the IDEFICS study

et al. 2015

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Faster growth seems to be a common factor in several hypotheses relating early life exposures to subsequent health. This study aims to investigate the association between body mass index (BMI) trajectories during infancy/childhood and later metabolic risk in order to identify sensitive periods of growth affecting health. In a first step, BMI trajectories of 3301 European children that participated in the multi-centre Identification and Prevention of Dietary and Lifestyle-induced Health Effects in Children and Infants (IDEFICS) study were modelled using linear-spline mixed-effects models. The estimated random coefficients indicating initial subject-specific BMI and rates of change in BMI over time were used as exposure variables in a second step and related to a metabolic syndrome (MetS) score and its single components based on conditional regression models (mean age at outcome assessment: 8.5 years). All exposures under investigation, i.e. BMI at birth, rates of BMI change during infancy (0 to <9 months), early childhood (9 months to <6 years) and later childhood (≥6 years) as well as current BMI z-score were significantly associated with the later MetS score. Associations were strongest for the rate of BMI change in early childhood (1.78 [1.66; 1.90]; β estimate and 99 % confidence interval) and current BMI z-score (1.16 [0.96; 1.38]) and less pronounced for BMI at birth (0.62 [0.47; 0.78]). Results slightly differed with regard to the single metabolic factors. Starting from birth rapid BMI growth, especially in the time window of 9 months to <6 years, is significantly related to later metabolic risk in children. Much of the associations of early BMI growth may further be mediated through the effects on subsequent BMI growth.

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“…their own trajectory [21]. These models can easily handle unbalanced data with a different number of measurements per child assessed at different points in time.…”

Section: Resultsmentioning

confidence: 99%

“…Focus will be put on the different periods of BMI growth (infancy, early childhood, later childhood) applying linearspline mixed effects models [21] in order to identify sensitive time windows during which growth may have a stronger effect on the later metabolic risk.…”

Section: Introductionmentioning

confidence: 99%

Associations between early body mass index trajectories and later metabolic risk factors in European children: the IDEFICS study

et al. 2015

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“…Life course trajectories of cardiovascular risk factors were modeled using linear spline mixed‐effects models,31 except for CRP, which had a limited number of repeated measurements and was modeled using a linear spline regression model with a cluster‐robust estimate of variance (Huber/White sandwich estimate). The linear spline mixed‐effects models included subject‐specific (random) intercepts and slopes to account for up to 3 repeated dependent observations per woman and facilitated estimation of within‐woman trajectories 32.…”

Section: Methodsmentioning

confidence: 99%

Life Course Trajectories of Cardiovascular Risk Factors in Women With and Without Hypertensive Disorders in First Pregnancy: The HUNT Study in Norway

Haug

Horn

Markovitz

et al. 2018

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BackgroundWomen with hypertensive pregnancy disorders have adverse levels of cardiovascular risk factors. It is unclear how this adverse risk factor profile evolves during adult life. We compared life course trajectories of cardiovascular risk factors in women with preeclampsia or gestational hypertension in their first pregnancy to normotensive women.Methods and ResultsWe linked information on cardiovascular risk factors from the population‐based HUNT (Nord‐Trøndelag Health Study) surveys with pregnancy information from the Medical Birth Registry of Norway. Trajectories of cardiovascular risk factors were constructed for 22 308 women with a normotensive first pregnancy; 1092 with preeclampsia, and 478 with gestational hypertension in first pregnancy. Already before first pregnancy, women with preeclampsia in their first pregnancy had higher measures of adiposity, blood pressure, heart rate, and serum lipids and glucose compared with women with a normotensive first pregnancy. After first pregnancy, there was a parallel development in cardiovascular risk factor levels, but women with a normotensive first pregnancy had a time lag of >10 years compared with the preeclampsia group. There were no clear differences in risk factor trajectories between women with gestational hypertension and women with preeclampsia.ConclusionsWomen with hypertensive pregnancy disorders in their first pregnancy had an adverse cardiovascular risk factor profile before pregnancy compared with normotensive women, and the differences persisted beyond 50 years of age. Hypertensive disorders in pregnancy signal long‐term increases in modifiable cardiovascular risk factors, and may be used to identify women who would benefit from early prevention strategies.

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“…After adding various covariates, diarrhea burden was added to the model as an interaction term with age for each of the time periods. The advantages and disadvantages of the linear spline approach compared with other growth modeling methods such as fractional polynomials, more complex spline functions, and other nonlinear models have recently been discussed [64]. …”

Section: Indicators Of Growthmentioning

confidence: 99%

Practical Application of Linear Growth Measurements in Clinical Research in Low- and Middle-Income Countries

et al. 2017

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Background/Aims: Childhood stunting is a prevalent problem in low- and middle-income countries and is associated with long-term adverse neurodevelopment and health outcomes. In this review, we define indicators of growth, discuss key challenges in their analysis and application, and offer suggestions for indicator selection in clinical research contexts. Methods: Critical review of the literature. Results: Linear growth is commonly expressed as length-for-age or height-for-age z-score (HAZ) in comparison to normative growth standards. Conditional HAZ corrects for regression to the mean where growth changes relate to previous status. In longitudinal studies, growth can be expressed as ΔHAZ at 2 time points. Multilevel modeling is preferable when more measurements per individual child are available over time. Height velocity z-score reference standards are available for children under the age of 2 years. Adjusting for covariates or confounders (e.g., birth weight, gestational age, sex, parental height, maternal education, socioeconomic status) is recommended in growth analyses. Conclusion: The most suitable indicator(s) for linear growth can be selected based on the number of available measurements per child and the child’s age. By following a step-by-step algorithm, growth analyses can be precisely and accurately performed to allow for improved comparability within and between studies.

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Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts

Cited by 173 publications

References 41 publications

Associations between early body mass index trajectories and later metabolic risk factors in European children: the IDEFICS study

Associations between early body mass index trajectories and later metabolic risk factors in European children: the IDEFICS study

Life Course Trajectories of Cardiovascular Risk Factors in Women With and Without Hypertensive Disorders in First Pregnancy: The HUNT Study in Norway

Practical Application of Linear Growth Measurements in Clinical Research in Low- and Middle-Income Countries

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