Dataset Information

Socioeconomic and other social stressors and biomarkers of cardiometabolic risk in youth: a systematic review of less studied risk factors.

ABSTRACT:

Background

Socioeconomic disadvantage and other social stressors in childhood have been linked with cardiometabolic diseases in adulthood; however the mechanisms underlying these observed associations and the timing of their emergence are unclear. The aim of this review was to evaluate research that examined relationships between socioeconomic disadvantage and other social stressors in relation to less-studied cardiometabolic risk factors among youth, including carbohydrate metabolism-related factors, lipids, and central adiposity.

Methods

We searched PubMed and ISI Web of Science to identify relevant publications between 2001 and 2013.Studies were selected based on 4 criteria: (1) the study examined an association between at least one social or economic stressor and one relevant outcome prior to age 21; (2) the sample originated from a high-income country; (3) the sample was not selected based on a health condition; and (4) a central aim was to evaluate the effect of the social or economic stressor on at least one relevant outcome. Abstracts were screened and relevant publications were obtained and evaluated for inclusion criteria. We abstracted data from selected articles, summarized them by exposures and outcomes, and assigned an evidence grade.

Results

Our search identified 37 publications from 31 studies. Socioeconomic disadvantage was consistently associated with greater central adiposity. Research to date does not provide clear evidence of an association between childhood stressors and lipids or carbohydrate metabolism-related factors.

Conclusions

This review demonstrates a paucity of research on the relationship of socioeconomic disadvantage and other social stressors to lipid and carbohydrate metabolism-related factors in youth. Accordingly, it is not possible to form strong conclusions, particularly with regard to stressors other than socioeconomic disadvantage. Findings are used to inform priorities for future research. An improved understanding of these pathways is critical for identifying novel prevention targets and intervention opportunities to protect the long-term health of children and adolescents.

SUBMITTER: Slopen N

PROVIDER: S-EPMC3656855 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Socioeconomic and other social stressors and biomarkers of cardiometabolic risk in youth: a systematic review of less studied risk factors.

Slopen Natalie N Goodman Elizabeth E Koenen Karestan C KC Koenen Karestan C KC Kubzansky Laura D LD

PloS one 20130517 5

<h4>Background</h4>Socioeconomic disadvantage and other social stressors in childhood have been linked with cardiometabolic diseases in adulthood; however the mechanisms underlying these observed associations and the timing of their emergence are unclear. The aim of this review was to evaluate research that examined relationships between socioeconomic disadvantage and other social stressors in relation to less-studied cardiometabolic risk factors among youth, including carbohydrate metabolism-re ...[more]

PMID: 23691213

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Project description:Background:Although obesity affects approximately one in five youths, only a fraction is treated in pediatric weight management clinics. Characteristics distinguishing youth with obesity who seek weight management treatment from those who do not are largely unknown. Yet identification of specific health characteristics which differentiate treatment-seeking from non-treatment seeking youth with obesity may shed light on underlying motivations for pursuing treatment. Objectives:Compare the cardiometabolic profiles of an obesity treatment-seeking sample of youth to a population-based sample of youth with obesity, while controlling for body mass index (BMI). Methods:This cross-sectional study included participants, ages 12-17 years, with obesity from the Pediatric Obesity and Weight Evaluation Registry (POWER) and National Health and Nutrition Examination Survey, representing the treatment-seeking and population samples, respectively. Mean differences were calculated for systolic and diastolic blood pressure percentiles, total cholesterol, low-density and high-density lipoprotein-cholesterol, triglycerides, fasting glucose, glycated hemoglobin and alanine aminotransferase, while adjusting for age, sex, race/ethnicity, insurance status, and multiple of the 95th BMI percentile. Results:The POWER and National Health and Nutrition Examination Survey cohorts included 1,823 and 617 participants, respectively. The POWER cohort had higher systolic blood pressure percentile (mean difference 17.4, 95% confidence interval [14.6, 20.1], p < 0.001), diastolic blood pressure percentile (21.8 [19, 24.5], p < 0.001), triglycerides (42.3 [28, 56.5], p < 0.001) and alanine aminotransferase (7.5 [5.1, 9.8], p < 0.001) and lower fasting glucose (-6.9 [-8.2, -5.6], p < 0.001) and high-density lipoprotein-cholesterol (-2.3 [-3.8, -0.9], p < 0.002). There were no differences in total cholesterol or low-density lipoprotein-cholesterol or clinical differences in glycated hemoglobin. Conclusion:For a given BMI, obesity treatment-seeking youth are more adversely affected by cardiometabolic risk factors than the general population of youth with obesity. This suggests that treatment-seeking youth may represent a distinct group that is at particularly high risk for the development of future cardiometabolic disease.

Project description:Importance:Inadequate sleep duration and quality increase the risk of obesity. Sleep timing, while less studied, is important in adolescents because increasing evening preferences (chronotypes), early school start times, and irregular sleep schedules may cause circadian misalignment. Objective:To investigate associations of chronotype and social jet lag with adiposity and cardiometabolic risk in young adolescents. Design, Setting, and Participants:Starting in 1999, Project Viva recruited pregnant women from eastern Massachusetts. Mother-child in-person visits occurred throughout childhood. From January 23, 2012, to October 16, 2016, 804 adolescents aged 12 to 17 years completed 5 days or more of wrist actigraphy, questionnaires, and anthropometric measurements. A cross-sectional analysis using these data was conducted from April 31, 2018, to May 1, 2019. Exposures:Chronotype, measured via a continuous scale with higher scores indicating greater evening preferences, and social jet lag, measured as the continuous difference in actigraphy sleep midpoint in hours from midnight on weekends vs weekdays, with higher values representing more delayed sleep timing on weekends. Main Outcomes and Measures:Adiposity, measured via anthropometry and dual-energy x-ray absorptiometry. For a subset of 479 adolescents with blood samples, cardiometabolic risk scores were computed as the mean of 5 sex- and cohort-specific z scores for waist circumference, systolic blood pressure, inversely scaled high-density lipoprotein cholesterol, and log-transformed triglycerides and homeostatic model of insulin resistance. Results:Among the 804 adolescents in the study, 418 were girls and 386 were boys, with a mean (SD) age of 13.2 (0.9) years. In multivariable models adjusted for age, puberty, season, and sociodemographics, associations of chronotype and social jet lag with adiposity varied by sex. For girls, greater evening preference was associated with a 0.58-cm (95% CI, 0.12-1.03 cm; P?=?.04 for interaction) higher waist circumference and 0.16 kg/m2 (95% CI, 0.01-0.31 kg/m2; P?=?.03 for interaction) higher fat mass index as measured by dual-energy x-ray absorptiometry; each hour of social jet lag was associated with a 1.19-cm (95% CI, 0.04-2.35 cm; P?=?.21 for interaction) higher waist circumference and 0.45 kg/m2 (95% CI, 0.09-0.82 kg/m2; P?=?.01 for interaction) higher fat mass index as measured by dual-energy x-ray absorptiometry. Associations of social jet lag and evening chronotypes persisted for many measures of adiposity after adjustment for sleep duration and other lifestyle behaviors. By contrast, no associations were observed in boys. There were no associations with the cardiometabolic risk score for either sex, although statistical power was low for this outcome. Conclusions and Relevance:Evening chronotypes and social jet lag were associated with greater adiposity in adolescent girls but not adolescent boys. Interventions aimed at improving sleep schedules may be useful for obesity prevention, especially in girls.

Project description:BACKGROUND:The effect of socioeconomic status (SES) on rates of sports specialization and injury among youth athletes has not been described previously. HYPOTHESIS:Young athletes from lower socioeconomic status will have lower rates of sports specialization and subsequently lower risk of overuse injuries. STUDY DESIGN:Cohort study. LEVEL OF EVIDENCE:Level 3. METHODS:Injured athletes aged 7 to 18 years were recruited from 2 hospital-based sports medicine clinics and compared with uninjured athletes presenting for sports physicals at primary care clinics between 2010 and 2013. Participants completed surveys on training patterns. Electronic medical records provided injury details as well as patient zip code, race, and health insurance type. SES was estimated from zip codes. The sample was divided into SES tertiles. Analysis of variance and multivariate regression were used for continuous variables, and multivariate logistic regression analyses were conducted to explore relationships between risk factors and injury. RESULTS:Of 1190 athletes surveyed, 1139 (96%) had satisfactory SES data. Compared with low-SES athletes, high-SES athletes reported more hours per week spent playing organized sports (11.2 ± 6.0 vs 10.0 ± 6.5; P = 0.02), trained more months per year in their main sport (9.7 ± 3.1 vs 7.6 ± 3.7; P < 0.01), were more often highly specialized (38.9% vs 16.6%; P < 0.01), and had increased participation in individual sports (64.8% vs 40.0%; P < 0.01). The proportion of athletes with a greater than 2:1 ratio of weekly hours in organized sports to free play increased with SES. Accounting for age and weekly organized sports hours, the odds of reporting a serious overuse injury increased with SES (odds ratio, 1.5; P < 0.01). CONCLUSION:High-SES athletes reported more serious overuse injuries than low-SES athletes, potentially due to higher rates of sports specialization, more hours per week playing organized sports, higher ratio of weekly hours in organized sports to free play, and greater participation in individual sports. CLINICAL RELEVANCE:As SES increases, young athletes report higher degrees of sports specialization, greater participation in individual sports, and more serious overuse injuries.

Project description:BACKGROUND AND OBJECTIVES:Whether BMI captures adiposity and cardiometabolic risk in Down syndrome (DS), a condition associated with obesity, short stature, and altered body proportions, is not known. We compared cardiometabolic risk measures in youth with DS and typically developing matched controls. METHODS:Youth with (n = 150) and without (n = 103) DS of comparable age (10-20 years), sex, race, ethnicity, and BMI percentile underwent whole-body dual-energy X-ray absorptiometry, fasting glucose, insulin, lipids, lipoprotein particles, inflammatory factors, and when BMI percentile ?85, an oral glucose tolerance test. RESULTS:Sixty-four percent of youth with DS had BMI percentile ?85. Among these, no difference in glucose, insulin, or insulin resistance was detected, but prediabetes was more prevalent with DS (26.4% vs 10.3%; P = .025) after adjustment for demographics, pubertal status, and BMI z score (odds ratio = 3.2; P = .026). Among all participants, those with DS had higher low-density lipoprotein cholesterol (median 107 [interquartile range 89-128] vs 88.5 [79-103] mg/dL; P < .00005), triglycerides (89.5 [73-133] vs 71.5 [56-104] mg/dL; P < .00005), non-high-density lipoprotein cholesterol (non-HDL-C; 128 [104-153] vs 107 [92-123] mg/dL; P < .00005), and triglycerides/HDL-C (2.2 [1.6-3.4] vs 1.7 [1.1-2.5] mg/dL; P = .0003) and lower levels of HDL-C (41 [36.5-47] vs 45 [37-53] mg/dL; P = .012). DS youth had higher high-sensitivity C-reactive protein, interleukin-6, small low-density lipoprotein particles (LDL-P), and total LDL-P, but similar LDL-P size. Youth with DS had less visceral fat (VFAT), fat mass, and lean mass for BMI z score, but greater VFAT at higher fat mass. However, VFAT did not fully explain the increased prevalence of dyslipidemia or prediabetes in youth with DS. CONCLUSIONS:Despite similar insulin resistance, youth with DS had greater prevalence of dyslipidemia and prediabetes than typically developing youth, which was not fully explained by VFAT.

Dataset Information

Socioeconomic and other social stressors and biomarkers of cardiometabolic risk in youth: a systematic review of less studied risk factors.

Background

Methods

Results

Conclusions

Publications

Socioeconomic and other social stressors and biomarkers of cardiometabolic risk in youth: a systematic review of less studied risk factors.

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