Body Silhouette Trajectories Over the Lifespan and Insomnia Symptoms: The Paris Prospective Study 3

Body shape trajectories are associated with birth weight, body mass index and sociodemographic conditions in participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): a multiple correspondence analysis

BACKGROUND

Evaluating lifelong weight trajectories is challenging due to the high costs of studies that follow individuals from childhood to adulthood. The use of silhouette scales has been a new approach to assess the body shape trajectory across life as a proxy for body weight trajectory. Depending on body shape trajectories, individuals may be more prone to develop diseases in adulthood. Therefore, identifying factors related to them is essential for public health. This study aimed to evaluate body shape trajectories across the lifespan and to verify associations between them, birth weight, body mass index, and sociodemographic conditions in a Brazilian cohort.

METHODS

This is a cross-sectional analysis conducted with 14,014 participants of first follow-up data collection of Longitudinal Study of Adult Health (ELSA-Brasil). ELSA-Brasil is a multicentric prospective cohort study initiated in 2008 with civil servants of six public institutions in the Northeast, South and Southeast regions of Brazil. We applied a clustering method to longitudinal data to identify body shape trajectories from 5 to 40 years of age and assessed the associations between these trajectories and birth weight, body mass index and sociodemographic conditions (race, education, maternal education and monthly per capita family income) using multiple correspondence analysis.

RESULTS

We found five body shape trajectories for women and three for men. Low birth weight was associated with a slight to moderate increase in shape. High birth weight was associated with maintaining large body size in both sexes and markedly increased body shape in women. Higher sociodemographic status and white race were associated with marked increases in body shape in men and maintenance of medium body shape in women.

CONCLUSIONS

The study shows that variables related to worse lifetime weight status (evaluated by anthropometry), such as presence of obesity, are also associated with worse body shape trajectories, as assessed with silhouette scales. Our results suggest that body shape trajectories are a good indicator of body weight trajectories and may be used when cohort studies are not possible.

The Obesity-Related Dietary Pattern Is Associated with Higher Risk of Sleep Disorders: A Cross-Sectional Study from NHANES

Evidence on the association between dietary patterns and sleep disorders is limited and controversial. In addition, studies evaluating the effect of dietary patterns on sleep disorders have seldom considered the critical role of obesity. We aimed to explore obesity-related dietary patterns and evaluate their impact on sleep disorders using data from the National Health and Nutrition Examination Survey 2005–2014. In total, 19,892 participants aged over 20 years with two-day dietary recalls were enrolled. Obesity-related dietary patterns explaining most variance in waist circumference and BMI simultaneously were extracted from twenty-six food groups by the using partial least squares method. Sleep disorder and sleep duration, which were defined by self-reported questions, were the primary and the secondary outcome, respectively. Generalized linear models were performed to estimate the association of sleep disorders and sleep duration with dietary patterns. Two types of dietary patterns were identified. The “high fats, refined grains, and meat” pattern was characterized by high intakes of solid fats, cured meat, potatoes, refined grains, meat, cheese, and added sugars. The “low whole grains, vegetables, and fruits” pattern was characterized by low intakes of oils, whole grains, nuts and seeds, milk, fruits, and several vegetables. Participants with the highest adherence to the “high fats, refined grains, and meat” pattern had a higher risk for sleep disorders (OR (95%CI): 1.43 (1.12, 1.84)) and shorter sleep duration (β (95%CI): −0.17 (−0.26, −0.08)) compared to those with the lowest adherence. The corresponding associations for the “low whole grains, vegetables, and fruits” pattern were only significant for sleep duration (β (95%CI): −0.26 (−0.37, −0.15)). Our results found that the dietary pattern characterized by high solid fats, cured meat, potatoes, refined grains, meat, cheese, and added sugars, was associated with a higher risk for sleep disorders and shorter sleep duration.

Group‐based trajectory modeling of body mass index and body size over the life course: A scoping review

Background

Group‐based trajectory modeling has been applied to identify distinct trajectories of growth across the life course. Objectives of this study were to describe the methodological approaches for group‐based modeling of growth across the life course and to summarize outcomes across studies.

Methods

A scoping review with a systematic search of Medline, EMBASE, CINAL, and Web of Science was conducted. Studies that used a group‐based procedure to identify trajectories on any statistical software were included. Data were extracted on trajectory methodology, measures of growth, and association with outcomes.

Results

A total of 59 studies were included, and most were published from 2013 to 2020. Body mass index was the most common measure of growth (n = 43). The median number of identified trajectories was 4 (range: 2–9). PROC TRAJ in SAS was used by 33 studies, other procedures used include TRAJ in STATA, lcmm in R, and Mplus. Most studies evaluated associations between growth trajectories and chronic disease outcomes (n = 22).

Conclusions

Group‐based trajectory modeling of growth in adults is emerging in epidemiologic research, with four distinct trajectories observed somewhat consistently from all studies. Understanding life course growth trajectories may provide further insight for population health interventions.