Life Course Neighborhood Deprivation Effects on Body Mass Index: Quantifying the Importance of Selective Migration.
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ABSTRACT:
SUBMITTER: Murray ET
PROVIDER: S-EPMC8392830 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In public health research, it has been well established that geographic location plays an important role in influencing health outcomes. In recent years, there has been an increased emphasis on the impact of neighborhood or contextual factors as potential risk factors for childhood obesity. Some neighborhood factors relevant to childhood obesity include access to food sources, access to recreational facilities, neighborhood safety, and socioeconomic status (SES) variables. It is common for neighborhood or area-level variables to be available at multiple spatial scales (SS) or geographic units, such as the census block group and census tract, and selection of the spatial scale for area-level variables can be considered as a model selection problem. In this paper, we model the variation in body mass index (BMI) in a study of pediatric patients of the Virginia Commonwealth University (VCU) Medical Center, while considering the selection of spatial scale for a set of neighborhood-level variables available at multiple spatial scales using four recently proposed spatial scale selection algorithms: SS forward stepwise regression, SS incremental forward stagewise regression, SS least angle regression (LARS), and SS lasso. For pediatric BMI, we found evidence of significant positive associations with visit age and black race at the individual level, percent Hispanic white at the census block group level, percent Hispanic black at the census tract level, and percent vacant housing at the census tract level. We also found significant negative associations with population density at the census tract level, median household income at the census tract level, percent renter at the census tract level, and exercise equipment expenditures at the census block group level. The SS algorithms selected covariates at different spatial scales, producing better goodness-of-fit in comparison to traditional models, where all area-level covariates were modeled at the same scale. These findings underscore the importance of considering spatial scale when performing model selection.
| S-EPMC5877018 | biostudies-literature
Project description:BACKGROUND:Perceived neighborhood characteristics are linked to obesity, however, the mechanisms linking these two factors remain unknown. PURPOSE:This study aimed to examine associations between perceived neighborhood characteristics and body mass index (BMI), establish whether indirect pathways through psychological distress and inflammation are important, and determine whether these associations vary by race/ethnicity. METHODS:Participants were 1,112 adults enrolled in the Texas City Stress and Health Study. Perceived neighborhood characteristics were measured using the Perceived Neighborhood Scale. Psychological distress was measured with the Center for Epidemiological Studies Depression Scale, Perceived Stress Scale and mental health subscale of the Short Form Health Survey-36. Markers of inflammation included C-reactive protein, interleukin-6, and tumor necrosis factor receptor-1. Associations were examined with Structural Equation Modeling. RESULTS:A model linking neighborhood characteristics with BMI through direct and indirect (i.e., psychological distress and inflammation) paths demonstrated good fit with the data. Less favorable perceived neighborhood characteristics were associated with greater psychological distress (B = -0.87, ? = -0.31, p < .001) and inflammation (B = -0.02, ? = -0.10, p = .035). Psychological distress and inflammation were also significantly associated with BMI (Bdistress = 0.06, ? = 0.08, p = .006; Binflammation = 4.65, ? = 0.41, p < .001). Indirect paths from neighborhood characteristics to BMI via psychological distress (B = -0.05, ? = -0.03, p = .004) and inflammation (B = -0.08, ? = -0.04, p = .045) were significant. In multiple group analysis, a model with parameters constrained equal across race/ethnicity showed adequate fit suggesting associations were comparable across groups. CONCLUSION:Our study extends the literature by demonstrating the importance of neighborhood perceptions as correlates of BMI across race/ethnicity, and highlights the role of psychological and physiological pathways.
| S-EPMC7317154 | biostudies-literature
Project description:BackgroundNeighborhood designs often relate to physical activity and to BMI.PurposeDoes neighborhood walkability/bikeability relate to BMI and obesity risk and does moderate-to-vigorous physical activity (MVPA) account for some of the relationship?MethodsCensus 2000 provided walkability/bikeability measures-block group proportions of workers who walk or bike to work, housing age, and population density-and National Health and Nutrition Examination Study (NHANES 2003-2006) provided MVPA accelerometer measures. Regression analyses (2011-2012) adjusted for geographic clustering and multiple control variables.ResultsGreater density and older housing were associated with lower male BMI in bivariate analyses, but there were no density and housing age effects in multivariate models. For women, greater proportions of neighborhood workers who walk to work (M=0.02) and more MVPA was associated with lower BMI and lower obesity risk. For men, greater proportions of workers who bike to work (M=0.004) and more MVPA was associated with lower BMI and obesity risk. For both effects, MVPA partially mediated the relationships between walkability/bikeability and BMI. If such associations are causal, doubling walk and bike-to-work proportions (to 0.04 and 0.008) would have -0.3 and -0.33 effects on the average BMIs of adult women and men living in the neighborhood. This equates to 1.5 pounds for a 64-inch-tall woman and 2.3 pounds for a 69-inch-tall man.ConclusionsAlthough walking/biking to work is rare in the U.S., greater proportions of such workers in neighborhoods relate to lower weight and higher MVPA. Bikeability merits greater attention as a modifiable activity-friendliness factor, particularly for men.
| S-EPMC3690570 | biostudies-literature
Project description:PurposeBoth schools and neighborhoods play important roles in determining adolescent weight status, but little is known about their relative importance, particularly in predicting long-term weight outcomes. We assessed the impacts of both school and neighborhood socioeconomic composition, social connectedness, and built environment during adolescence on weight status in young adulthood.MethodsThe study sample consisted of 14,625 respondents from Waves I and IV of the National Longitudinal Study of Adolescent to Adult Health. Data were analyzed using cross-classified multilevel modeling to examine the joint effect of adolescents' school and neighborhood predictors on body mass index (BMI) 13 years later.ResultsLiving in a neighborhood with lower average parent education during adolescence, and attending a school with lower average parent education, were each associated with higher BMI in young adulthood. Living in a neighborhood with more physical activity resources predicted lower young adult BMI, independent of adolescent weight, parent obesity status, and demographic characteristics. School physical activity resources and perceptions of social connectedness (in the school or neighborhood) were not significantly associated with young adult BMI.ConclusionsThese findings highlight the importance of school and neighborhood socioeconomic composition during adolescence on young adult weight status. Results also suggest that improving neighborhood infrastructure may promote healthy weight.
| S-EPMC6397088 | biostudies-literature
Project description:Genome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs ([Formula: see text]) or genome-wide significant SNPs ([Formula: see text]) for height and body mass index (BMI) in samples of European (EUR; [Formula: see text]) and African (AFR; [Formula: see text]) ancestry. The [Formula: see text] between EUR and AFR was 0.75 ([Formula: see text]) for height and 0.68 ([Formula: see text]) for BMI, and the corresponding [Formula: see text] was 0.82 ([Formula: see text]) for height and 0.87 ([Formula: see text]) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that [Formula: see text] differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.
| S-EPMC7933291 | biostudies-literature
Project description:Depression and obesity are complex global health problems. Recent studies suggest that a genetic predisposition to obesity might be accentuated in people with depression, but these analyses are prone to bias. Here, we tested the hypothesis that depression accentuates genetic susceptibility to obesity and applied negative control experiments to test whether any observed interactions were real or driven by confounding and statistical biases. We used data from up to 378 000 Europeans in UK Biobank, a 73 variant body mass index (BMI) genetic risk score, two depression measures [depression symptoms (DS), major depression (MD)] and an antidepressant usage variable available. We tested whether (i) depression and (ii) antidepressant treatment accentuated genetic susceptibility to obesity. Finally, we performed negative control experiments by sampling individuals at random so that they had BMI distributions identical to depression cases and controls. Depression was associated with an accentuation of an individual's genetic risk of obesity with evidence of interactions for both DS and MD (Pinteraction = 7 × 10-4 and 7 × 10-5 respectively). Antidepressant usage within DS cases accentuated genetic obesity risk (Pinteraction = 9 × 10-4), but not for MD (Pinteraction = 0.13). Negative control experiments suggested that the observed interactions for MD (empirical-P = 0.067) may be driven by statistical biases or confounding factors but were not possible with the larger DS groups. Antidepressant usage interaction also appears to be driven by statistical artefacts (empirical-P = 0.510 using MD and 0.162 using DS). We have highlighted the importance of running negative experiments to confirm putative interactions in gene-environment studies. We provide some tentative evidence that depression accentuates an individual's genetic susceptibility to higher BMI but demonstrated that the BMI distributions within cases and controls might drive these interactions.
| S-EPMC9557895 | biostudies-literature
Project description:BackgroundBody mass index (BMI) during adulthood has been associated with pancreatic ductal adenocarcinoma (PDAC), however, patterns of body size across the adult life course have not been studied extensively. We comprehensively evaluated the association between adiposity across adulthood and PDAC.MethodsWe conducted a prospective analysis of 269 480 (162 735 males, 106 745 females) National Institutes of Health-AARP Diet and Health Study participants, aged 50-71 years (1995-1996) who self-reported height and weight history. Participants were followed through December 31, 2011. We examined associations between BMI (kg/m2) at ages 18, 35, 50, and 50-71 (baseline) years, their trajectories determined from latent-class trajectory modeling, and incident PDAC. Cox proportional hazard models were used to calculate multivariable adjusted hazards ratios (HRs) and 95% confidence intervals (CIs).ResultsDuring up to 15.2 years of follow-up, 3092 (2020 males, 1072 females) patients with incident PDAC were identified. BMI at all 4 ages were statistically significantly associated with increased PDAC (per 5-unit increase, HR = 1.09-1.13) with higher magnitude associations in males than females at ages 35 years and older (Pinteraction < .05). Four BMI trajectories were created. Compared with normal-weight maintainers, normal-to-overweight, normal-to-obese class I, and overweight-to-obese class III trajectories had hazard ratios of 1.15 (95% CI = 1.06 to 1.25), 1.39 (95% CI = 1.25 to 1.54), and 1.48 (95% CI = 1.18 to 1.87), respectively (Pinteraction by sex = .07).ConclusionsHigh BMI and BMI trajectories that result in overweight or obesity during adulthood were positively associated with PDAC, with stronger associations among those with early onset adiposity and those with male sex. Avoidance of excess body weight throughout the adult life course may prevent PDAC.
| S-EPMC9651977 | biostudies-literature
Project description:The objective of this study was to evaluate the association between gestational sleep deprivation and childhood adiposity and cardiometabolic profile. Data were used from two population-based birth cohorts (Rhea study and Amsterdam Born Children and their Development study). A total of 3,608 pregnant women and their children were followed up until the age of 11 years. Gestational sleep deprivation was defined as 6 or fewer hours of sleep per day, reported by questionnaire. The primary outcomes included repeated measures of body mass index (BMI), waist circumference, body fat, serum lipids, systolic and diastolic blood pressure (DBP) levels in childhood. We performed a pooled analysis with adjusted linear mixed effect and Cox proportional hazards models. We tested for mediation by birthweight, gestational age, and gestational diabetes. Gestational sleep deprivation was associated with higher BMI (beta; 95% CI: 0.7; 0.4, 1.0 kg/m2) and waist circumference (beta; 95% CI: 0.9; 0.1, 1.6 cm) in childhood, and increased risk for overweight or obesity (HR; 95% CI: 1.4; 1.1, 2.0). Gestational sleep deprivation was also associated with higher offspring DBP (beta; 95% CI: 1.6; 0.5, 2.7 mmHg). The observed associations were modified by sex (all p-values for interaction < 0.05); and were more pronounced in girls. Gestational diabetes and shorter gestational age partly mediated the seen associations. This is the first study showing that gestational sleep deprivation may increase offspring's adiposity and blood pressure, while exploring possible mechanisms. Attention to glucose metabolism and preterm birth might be extra warranted in mothers with gestational sleep deprivation.
| S-EPMC7734474 | biostudies-literature
Project description:PURPOSE:Recent studies have suggested height as a risk factor for glioma, but less is known regarding body mass index (BMI) or other anthropomorphic measures. We evaluated the association between body habitus and risk of glioma. METHODS:We evaluated the association of measures of height, BMI, waist circumference, and somatotypes with risk of glioma in two prospective cohorts, the Nurses' Health Study and the Health Professionals Follow-Up Study. RESULTS:We documented 508 incident cases of glioma (321 glioblastoma [GBM]). In both cohorts, we found no significant association between adult BMI or waist circumference and risk of glioma, with pooled HR for BMI of 1.08 (95% CI 0.85-1.38 comparing???30 to <?25 kg/m2) and for waist circumference of 1.05 (95% CI 0.80-1.37 highest vs. lowest quintile). Higher young adult BMI (at age 18 in NHS and 21 in HPFS) was associated with modestly increased risk of glioma in the pooled cohorts (pooled HR 1.35, 95% CI 1.06-1.72 comparing???25 kg/m2 vs. less; HR 1.34 for women and 1.37 for men). Analysis of body somatotypes suggested reduced risk of glioma among women with heavier body types at all ages this measure was assessed (HRs ranging from 0.52 to 0.65 comparing highest tertile to lowest tertile), but no significant association among men. Height was associated with increased risk of glioma among women (HR?1.09, 95% CI 1.04-1.14 per inch), but not significantly among men. Within the 8 years prior to diagnosis, cases had no material weight loss compared to non-cases. All results were similar when limited to GBM. CONCLUSION:Adult BMI and waist circumference were not associated with glioma. Higher BMI at age 21 for men and at age 18 for women was modestly associated with risk in the pooled cohort. Based on body somatotypes, however, women with heavier body types during childhood and young adulthood may be at lower risk of glioma, although this association was not observed later in life with measurements of BMI. Greater height was associated with increased risk, and the trend was more pronounced in women.
| S-EPMC6238636 | biostudies-literature
Project description:BackgroundExamining body mass index (BMI) change over life course is crucial for cardiovascular health promotion and prevention. So far, there is very few evidence on the long-term change of BMI from childhood to late life. This study aimed to examine the life-course trajectory patterns of BMI and then to link the trajectory patterns to cardiovascular risk factors in adulthood.MethodsBased on longitudinal data from the China Health and Nutrition Survey, 5276 participants (aged 6-60) at baseline (in 1989) with up to 7 measurements of BMI during 1989-2009 were selected in this study. Cardiovascular risk factors including high blood pressure, high blood glucose and high blood lipids were assessed in 2411 participants in 2009. Latent growth curve modelling was used to analyse the BMI trajectories, and logistic regression was used to examine the associations between trajectory patterns and cardiovascular risk factors.ResultsFour trajectories patterns of BMI over life course (age 6-80) were identified: Normal-Stable (22.4% of the total participants), Low normal-Normal-Stable (44.1%), Low normal-Normal-Overweight (27.2%), and Overweight-Obese (4.3%). Compared to those with Normal-Stable pattern, those with Low normal-Normal-Stable pattern, Low normal-Normal-Overweight pattern and Overweight-Obese pattern had higher risk of high blood pressure (odds ratio range = 1.6-6.6), high blood glucose (1.7-9.1), dyslipidemia (2.6-5.9) and having at least two of the three cardiovascular risk factors (3.9-30.9).ConclusionsHaving a stable BMI within normal range over life course is associated with the lowest cardiovascular risk, whereas remaining overweight and obese over life course is associated with the highest cardiovascular risk.
| S-EPMC6786833 | biostudies-literature