A Life Course Perspective on Body Size and Cardio-metabolic Health

Johnson, William; Kuh, Diana; Hardy, Rebecca

doi:10.1007/978-3-319-20484-0_4

Cited by 3 publications

(4 citation statements)

References 144 publications

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“…Thus, the association between persistently overweight trajectory in childhood and adulthood could be due to tracking of BMI across the life course or reflects the duration of overweight. Similarly, this result also aligned with the life course risk theory of the cumulative risk effect of exposure (high BMI) across the life span 53 . These findings highlight the significance of devising prevention strategies, starting from childhood across the life span, to prevent cardiovascular risk factors and outcomes in adulthood.…”

Section: Discussionsupporting

confidence: 75%

“…Similarly, this result also aligned with the life course risk theory of the cumulative risk effect of exposure (high BMI) across the life span. 53 These findings highlight the significance of devising prevention strategies, starting from childhood across the life span, to prevent cardiovascular risk factors and outcomes in adulthood.…”

Section: Discussionmentioning

confidence: 97%

“…Several factors, including socioeconomic or sociodemographic and behavioural factors, may also be related to high BMI or to CVD risks and outcomes. 53,57 Some studies included in this review adjusted for various variables, including sex, age, physical activity, alcohol, smoking, diet, and alcohol consumption.…”

Section: Discussionmentioning

confidence: 99%

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Life‐course trajectories of body mass index and cardiovascular disease risks and health outcomes in adulthood: Systematic review and meta‐analysis

Kibret,

Strugnell,

Backholer

et al. 2024

Obesity Reviews

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SummaryObjectiveThis systematic review aimed to assess the effect of life course body mass index (BMI) trajectories (childhood to adulthood) on cardiovascular disease (CVD) risk factors and outcomes.MethodsProspective or retrospective cohort studies were identified that assessed the association of BMI trajectories with CVD risks and outcomes from databases published in English. The pooled effect sizes were estimated using a random‐effects model.FindingsSeventeen eligible studies were included in this systematic review. The results revealed that a persistently overweight trajectory from childhood to adulthood was associated with a higher risk of hypertension (RR: 2.49; 95% CI: 1.9, 3.28) and type 2 diabetes (RR: 4.62; 95% CI: 2.36, 9.04) compared with a trajectory characterized by a normal BMI throughout both childhood and adulthood. Similarly, the risk of hypertension (RR: 2.38; 95% CI: 1.70, 3.33) and type 2 diabetes (RR: 3.66; 95% CI: 2.57, 5.19) was higher in those with normal‐to‐overweight trajectory compared with participants with a stable normal weight trajectory.ConclusionThe findings suggest that lifetime BMI trajectories may be influential on health outcomes, and preventive strategies should be designed accordingly. Implementing appropriate preventive strategies at all life stages may reduce CVD risks and adverse outcomes later in life.

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Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 97%

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Life‐course trajectories of body mass index and cardiovascular disease risks and health outcomes in adulthood: Systematic review and meta‐analysis

Kibret,

Strugnell,

Backholer

et al. 2024

Obesity Reviews

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“…Structural MRI is the most widely used neuroimaging method in research and clinical settings because of its excellent safety profile, even in repeat administration, ease of data acquisition and high patient acceptability. Thus, establishing the typical patterns of age- and public health policies relating to cardio-metabolic health (Johnson, et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Cortical Thickness Trajectories across the Lifespan: Data from 17,075 healthy individuals aged 3-90 years

Frangou

Modabbernia

Doucet

et al. 2020

Preprint

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Delineating age-related cortical trajectories in healthy individuals is critical given the association of cortical thickness with cognition and behaviour. Previous research has shown that deriving robust estimates of age-related brain morphometric changes requires largescale studies. In response, we conducted a large-scale analysis of cortical thickness in 17,075 individuals aged 3-90 years by pooling data through the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium. We used fractional polynomial (FP) regression to characterize age-related trajectories in cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma (LMS) method. Inter-individual variability was estimated using meta-analysis and one-way analysis of variance. Overall, cortical thickness peaked in childhood and had a steep decrease during the first 2-3 decades of life; thereafter, it showed a gradual monotonic decrease which was steeper in men than in women particularly in middle-life. Notable exceptions to this general pattern were entorhinal, temporopolar and anterior cingulate cortices. Inter-individual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness.These results reconcile uncertainties about age-related trajectories of cortical thickness; the centile values provide estimates of normative variance in cortical thickness, and may assist in detecting abnormal deviations in cortical thickness, and associated behavioural, cognitive and clinical outcomes.

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Cohort profile: Pacific Islands Families (PIF) growth study, Auckland, New Zealand

et al. 2016

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PurposeThis article profiles a birth cohort of Pacific children participating in an observational prospective study and describes the study protocol used at ages 14–15 years to investigate how food and activity patterns, metabolic risk and family and built environment are related to rates of physical growth of Pacific children.ParticipantsFrom 2000 to 2015, the Pacific Islands Families Study has followed, from birth, the growth and development of over 1000 Pacific children born in Auckland, New Zealand. In 2014, 931 (66%) of the original cohort had field measures of body composition, blood pressure and glycated haemoglobin. A nested subsample (n=204) was drawn by randomly selecting 10 males and 10 females from each decile of body weight. These participants had measurement of body composition by dual-energy X-ray absorptiometry, food frequency, 6 min walk test and accelerometer-determined physical activity and sedentary behaviours, and blood biomarkers for metabolic disease such as diabetes. Built environment variables were generated from individual addresses.Findings to dateCompared to the Centres for Disease Control and Prevention (CDC) reference population with mean SD scores (SDS) of 0, this cohort of 931 14-year-olds was taller, weighed more and had a higher body mass index (BMI) (mean SDS height >0.6, weight >1.6 and BMI >1.4). 7 of 10 youth were overweight or obese. The nested-sampling frame achieved an even distribution by body weight.Future plansCross-sectional relationships between body size, fatness and growth rate, food patterns, activity patterns, pubertal development, risks for diabetes and hypertension and the family and wider environment will be examined. In addition, analyses will investigate relationships with data collected earlier in the life course and measures of the cohort in the future. Understanding past and present influences on child growth and health will inform timely interventions to optimise future health and reduce inequalities for Pacific people.

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A Life Course Perspective on Body Size and Cardio-metabolic Health

Cited by 3 publications

References 144 publications

Life‐course trajectories of body mass index and cardiovascular disease risks and health outcomes in adulthood: Systematic review and meta‐analysis

Life‐course trajectories of body mass index and cardiovascular disease risks and health outcomes in adulthood: Systematic review and meta‐analysis

Cortical Thickness Trajectories across the Lifespan: Data from 17,075 healthy individuals aged 3-90 years

Cohort profile: Pacific Islands Families (PIF) growth study, Auckland, New Zealand

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