Participation in the special supplemental nutrition program for women, infants, and children is not associated with early childhood socioemotional development: Results from a longitudinal cohort study

AbstractSocioemotional development in early childhood has long-term impacts on health status and social outcomes, and racial and socioeconomic disparities in socioemotional skills emerge early in life. The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is an early childhood nutrition intervention with the potential to ameliorate these disparities. Our objective was to assess the impact of WIC on early socioemotional development in a longitudinal study. We examined the association between WIC participation and scores on the Brief Infant Toddler Social Emotional Assessment (BITSEA) in 327 predominantly African American mother–child dyads who were participants in the longitudinal Conditions Affecting Neurocognitive Development in Early Life (CANDLE) Study (Memphis, TN). To account for selection bias, we used within-child fixed effects to model the variability in each child's BITSEA scores over two measurement occasions (ages 12 and 24months). Final models were adjusted for time-varying characteristics including child age, maternal stress, mental health, child abuse potential, marital status, and food stamp participation. In fully adjusted models, we found no statistically significant effect of WIC on change in socioemotional development (β=0.22 [SD=0.39] and β=−0.58 [SD=0.79] for BITSEA Competence and Problem subdomains, respectively). Using rigorous methods and a longitudinal study design, we found no significant association between WIC and socioemotional development in a high needs population. This finding suggests that early childhood interventions that more specifically target socioemotional development are necessary if we are to reduce racial disparities in socioemotional skills and prevent poor social and health outcomes across the life course

Maternal metabolic factors during pregnancy predict early childhood growth trajectories and obesity risk: the CANDLE Study.

BackgroundWe investigated the individual and additive effects of three modifiable maternal metabolic factors, including pre-pregnancy overweight/obesity, gestational weight gain (GWG), and gestational diabetes mellitus (GDM), on early childhood growth trajectories and obesity risk.MethodsA total of 1425 mother-offspring dyads (953 black and 472 white) from a longitudinal birth cohort were included in this study. Latent class growth modeling was performed to identify the trajectories of body mass index (BMI) from birth to 4 years in children. Poisson regression models were used to examine the associations between the maternal metabolic risk factors and child BMI trajectories and obesity risk at 4 years.ResultsWe identified three discrete BMI trajectory groups, characterized as rising-high-BMI (12.6%), moderate-BMI (61.0%), or low-BMI (26.4%) growth. Both maternal pre-pregnancy obesity (adjusted relative risk [adjRR] = 1.96; 95% confidence interval [CI]: 1.36-2.83) and excessive GWG (adjRR = 1.71, 95% CI: 1.13-2.58) were significantly associated with the rising-high-BMI trajectory, as manifested by rapid weight gain during infancy and a stable but high BMI until 4 years. All three maternal metabolic indices were significantly associated with childhood obesity at age 4 years (adjRR for pre-pregnancy obesity = 2.24, 95% CI: 1.62-3.10; adjRR for excessive GWG = 1.46, 95% CI: 1.01-2.09; and adjRR for GDM = 2.14, 95% = 1.47-3.12). In addition, risk of rising-high BMI trajectory or obesity at age 4 years was stronger among mothers with more than one metabolic risk factor. We did not observe any difference in these associations by race.ConclusionMaternal pre-pregnancy obesity, excessive GWG, and GDM individually and jointly predict rapid growth and obesity at age 4 years in offspring, regardless of race. Interventions targeting maternal obesity and metabolism may prevent or slow the rate of development of childhood obesity

Computed Tomographic Measurements of Thigh Muscle Cross-Sectional Area and Attenuation Coefficient Predict Hip Fracture: The Health, Aging, and Body Composition Study

Fatty infiltration of muscle, myosteatosis, increases with age and results in reduced muscle strength and function and increased fall risk. However, it is unknown if increased fatty infiltration of muscle predisposes to hip fracture. We measured the mean Hounsfield unit (HU) of the lean tissue within the midthigh muscle bundle (thigh muscle HU, an indicator of intramuscular fat), its cross-sectional area (CSA, a measure of muscle mass) by computed tomography (CT), bone mineral density (BMD) of the hip and total-body percent fat by dual X-ray absorptiometry (DXA), isokinetic leg extensor strength, and the Short Physical Performance Battery (SPPB) in 2941 white and black women and men aged 70 to 79 years. Sixty-three hip fractures were validated during 6.6 years of follow-up. Proportional hazards regression analysis was used to assess the relative risk (RR) of hip fracture across variations in thigh muscle attenuation, CSA, muscle strength, and physical function for hip fracture. In models adjusted by age, race, gender, body mass index, and percentage fat, decreased thigh muscle HU resulted in increased risk of hip fracture [RR/SD = 1.58; 95% confidence interval (CI) 1.10–1.99], an association that continued to be significant after further adjustment for BMD. In models additionally adjusted by CSA, muscle strength, and SPPB score, decreased thigh muscle HU but none of the other muscle parameters continued to be associated with an increased risk of hip fracture (RR/SD = 1.42; 95% CI 1.03–1.97). Decreased thigh muscle HU, a measure of fatty infiltration of muscle, is associated with increased risk of hip fracture and appears to account for the association between reduced muscle strength, physical performance, and muscle mass and risk of hip fracture. This characteristic captures a physical characteristic of muscle tissue that may have importance in hip fracture etiology. © 2010 American Society for Bone and Mineral Researc

Relationships of dietary patterns with body composition in older adults differ by gender and PPAR-γ Pro12Ala genotype

Dietary patterns may better capture the multifaceted effects of diet on body composition than individual nutrients or foods. The objective of this study was to investigate the dietary patterns of a cohort of older adults, and examine relationships of dietary patterns with body composition. The influence of a polymorphism in the peroxisome proliferator-activated receptor-γ (PPAR-γ) gene was considered. The Health, Aging and Body Composition (Health ABC) Study is a prospective cohort study of 3,075 older adults. Participants’ body composition and genetic variation were measured in detail. Food intake was assessed with a semi-quantitative food frequency questionnaire (Block Dietary Data Systems, Berkeley, CA), and dietary patterns of 1,809 participants with complete data were derived by cluster analysis. Six clusters were identified, including a ‘Healthy foods’ cluster characterized by higher intake of low-fat dairy products, fruit, whole grains, poultry, fish and vegetables. An interaction was found between dietary patterns and PPAR-γ Pro12Ala genotype in relation to body composition. While Pro/Pro homozygous men and women in the ‘Healthy foods’ cluster did not differ significantly in body composition from those in other clusters, men with the Ala allele in the ‘Healthy foods’ cluster had significantly lower levels of adiposity than those in other clusters. Women with the Ala allele in the ‘Healthy foods’ cluster differed only in right thigh intermuscular fat from those in other clusters. Relationships between diet and body composition in older adults may differ by gender and by genetic factors such as PPAR-γ Pro12Ala genotype

Assessment of gene-by-sex interaction effect on bone mineral density

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed expression quantitative trait loci (eQTL) analysis and bioinformatics network analysis. We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS) and femoral neck (FN) BMD in 25,353 individuals from 8 cohorts. In a second stage, we followed up the 12 top single-nucleotide polymorphisms (SNPs; p < 1 × 10(-5) ) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 and p = 3.0 × 10(-5) ; female effect = -0.007 and p = 3.3 × 10(-2) ), and 11 suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (p < 5 × 10(-8) ) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found to influence BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. © 2012 American Society for Bone and Mineral Research.Medtronic NIH R01 AG18728 R01HL088119 R01AR046838 U01 HL084756 R01 AR43351 P01-HL45522 R01-MH-078111 R01-MH-083824 Nutrition and Obesity Research Center of Maryland P30DK072488 NIAMS/NIH F32AR059469 Instituto de Salud Carlos III-FIS (Spanish Health Ministry) PI 06/0034 PI08/0183 Canadian Institutes of Health Research (CIHR) NHLBI HHSN268201200036C N01-HC-85239 N01-HC-85079 N01-HC-85086 N01-HC-35129 N01 HC15103 N01 HC-55222 N01-HC-75150 N01-HC-45133 HL080295 HL087652 HL105756 NIA AG-023629 AG-15928 AG-20098 AG-027058 N01AG62101 N01AG62103 N01AG62106 1R01AG032098-01A1 National Center of Advancing Translational Technologies CTSI UL1TR000124 National Institute of Diabetes and Digestive and Kidney Diseases DK063491 EUROSPAN (European Special Populations Research Network) European Commission FP6 STRP grant 018947 LSHG-CT-2006-01947 Netherlands Organisation for Scientific Research Erasmus MC Centre for Medical Systems Biology (CMSB) Netherlands Brain Foundation (HersenStichting Nederland) US National Institute for Arthritis, Musculoskeletal and Skin Diseases National Institute on Aging R01 AR/AG41398 R01 AR050066 R21 AR056405 National Heart, Lung, and Blood Institute's Framingham Heart Study N01-HC-25195 Affymetrix, Inc. N02-HL-6-4278 Canadian Institutes of Health Research from Institute of Aging 165446 Institute of Genetics 179433 Institute of Musculoskeletal health 221765 Intramural Research Program of the NIH, National Institute on Aging National Institutes of Health HHSN268200782096C Hong Kong Research Grant Council HKU 768610M Bone Health Fund of HKU Foundation KC Wong Education Foundation Small Project Funding 201007176237 Matching Grant CRCG Grant Osteoporosis and Endocrine Research Fund Genomics Strategic Research Theme of The University of Hong Kong Netherlands Organisation of Scientific Research NWO Investments 175.010.2005.011 911-03-012 Research Institute for Diseases in the Elderly 014-93-015 Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) 050-060-810 Erasmus Medical Center and Erasmus University, Rotterdam Netherlands Organization for the Health Research and Development (ZonMw) Research Institute for Diseases in the Elderly (RIDE) Ministry of Education, Culture and Science Ministry for Health, Welfare and Sports European Commission (DG XII) Municipality of Rotterdam German Bundesministerium fur Forschung und Technology 01 AK 803 A-H 01 IG 07015

Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci.

Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Okul öncesi çocuklarda cinsiyet-spesifik büyüme profillerinin modellemesi

Objective: In pediatric clinical trials and cohort stu ies, actual height, weight and head circumference of children at a specific age may be required for certain developmental assessments such as energy expenditure. This necessitates the choice of a growth model with desired characteristics to predict height weight accurately. Material and Methods: we compared Logistic and Gompertz models, which are most commonly used growth curve models literature, using different parameterization and in a race and gender specific fashion on actual participant data from the CANDLE study, which is a prospective birth cohort of motherCounty, Tennessee, USA. We compared these competitive models and different parameterizations in terms of the size of the as well as prediction standard error, for each anthropometric mea urement, namely, height, weight, and head circumference. We also assessed the impact of missing data on these models. have shown that Gompertz model with the first or rameter defined with a subject-specific random effect is the best model in terms of prediction accuracy. Although the same Gompertz model fitted on each individual profile without a random effect also has similar prediction accuracy, it has in error of estimation as expected, thus, not recommended to be used. Conclusion: We conclude that Gompertz model with only the first or the second parameter defined with a random effect performs the best with and without missing data for heig circumference growth in the first four years of life.Amaç: Klinik denemelerde ve kohort ların belli yaştaki boy, kilo ve baş çevresi, enerji harcaması gibi belli gelişim değerlendirmeleri için gerekebilir. Bu durum, boyu ve kiloyu doğru ölçmede istenilen özelliklere sahip büyüme modell rinin seçimini gerektirir. Gereç ve Yöntemler: vermek için, çocuk gelişimi literatüründe en sıkça kullanılan Logistic ve Gompertz büyüme modellerini farklı parametri zasyonlarla, ırk ve cinsiyete dayalı olarak, ABD Tennessee Eyaleti, Shelby ilçesinden ‘the CANDLE’ çalı doğum kohortunun verilerini kullanarak kar rakip modelleri, farklı parametrizasyonlar altında, antropometrik ölçüm icin (boy, kilo ve ba büyüklüğü ve tahmin standart hatası açısından kar kayıp gözlemlerin bu modeller üzerindeki etkisini de Bulgular: Birinci veya ikinci parametresi denek etki olarak tanımlanan Gompertz modelinin, tahmin do açısından en iyi model olduğunu gösterdik. Her bir denek için, rastgele-etki parametresi olmadan kurulan aynı Gompertz modeli de, benzer bir tahmin doğruluğuna sahip olmakla birlikte, beklendiği gibi şişirilmiş standart hata verdi tavsiye edilmedi. Sonuç: Sadece birinci veya ikinci parametresi denek-spesifik rastgele-etki olarak tanımlanan Gompertz modelinin, yaşamın ilk dört yılında, boy, kilo ve ba lemesinde, kayıp gözlem altında bile, en iyi performansı gösterdi sonucuna vardık