This program evaluation examines the effectiveness of a school-based dental clinic. A repeated-measures design was used to longitudinally examine secondary data from participants (N = 293). Encounter intensity was developed to normalize data. Multivariate analysis of variance and Kruskal–Wallis test were used to investigate the effect of encounter intensity on the change in decay, restorations, and treatment urgency. A Pearson’s correlation was used to measure the strengths of association. Encounter intensity had a statistically significant effect on change in decay (p =.005), restorations (p =.000), and treatment urgency (p =.001). As encounter intensity increased, there was a significant association with the decrease in decay (−.167), increase in restorations (.221), and reduction in referral urgency (−.188). Incorporating dental care into a school-based health center resulted in improved oral health in underserved children while overcoming barriers that typically restrict access. The collaboration of school nurses with the school-based dental clinic was an important element for maximizing student access to dental care.

Objective Cartilage fatigue, due to mechanical work, may account for the early development of degenerative joint disease (DJD) in the temporomandibular joint (TMJ), and why women are three times more likely to be afflicted. This study tested for gender differences in mechanical energy densities in women and men with healthy TMJs. Design Eighteen women and eighteen men gave informed consent. Research diagnostic criteria including imaging were used to ensure that subjects’ TMJs were normal, without disc displacement or signs of DJD. Numerical modeling determined TMJ loads (Fnormal). Jaw tracking and three-dimensional dynamic stereometry characterized individual-specific data of stress-field dynamic mechanics during 10 symmetrical jaw closing cycles. These data were used to estimate tractional forces (Ftraction). Energy densities were then calculated, where: Energy Density = W/Q (W = work done or mechanical energy input = Ftraction*distance of stress-field translation, Q = volume of cartilage). Two-way analysis of variance (ANOVA) and follow-up two-group comparisons tested mean energy densities for ipsilateral and contralateral TMJs in women vs men. Results Mean energy densities ± standard deviations in ipsilateral and contralateral TMJs in women were 9.0 ± 9.7 and 8.4 ± 5.5 mJ/mm3, respectively, and were significantly larger (P = 0.004 and 0.001, respectively) compared to ipsilateral and contralateral TMJs in men, which were 5.6 ± 4.2 and 6.3 ± 4.2 mJ/mm3, respectively. Conclusions Energy densities were significantly larger in healthy TMJs of women than men. Larger TMJ energy densities during normal jaw functions could predispose earlier mechanical fatigue of the TMJ disc.

Background The pleckstrin and Sec7 domain-containing 3 (PSD3) gene has been linked to immune diseases. We examined whether the genetic variants within the PSD3 gene are associated with obesity, type 2 diabetes (T2D), and high-density lipoprotein (HDL) cholesterol level. Methods Multiple logistic regression model and linear regression model were used to examine the associations of 259 single nucleotide polymorphisms (SNPs) within the PSD3 gene with obesity and T2D as binary traits, and HDL level as a continuous trait using the Marshfield data, respectively. A replication study of obesity was conducted using the Health Aging and Body Composition (Health ABC) sample. Results 23 SNPs were associated with obesity (p < 0.05) in the Marshfield sample and rs4921966 revealed the strongest association (p = 3.97 × 10−6). Of the 23 SNPs, 20 were significantly associated with obesity in the meta-analysis of two samples (p < 0.05). Furthermore, 6 SNPs revealed associations with T2D in the Marshfield data (top SNP rs12156368 with p = 3.05 × 10−3); while two SNPs (rs6983992 and rs7843239) were associated with both obesity and T2D (p = 0.0188 and 0.023 for obesity and p = 8.47 × 10−3 and 0.0128 for T2D, respectively). Furthermore, 11 SNPs revealed associations with HDL level (top SNP rs13254772 with p = 2.79 × 10−3) in the Marshfield data; meanwhile rs7009615 was associated with both T2D (p = 0.038) and HDL level (p = 4.44 × 10−3). In addition, haplotype analyses further supported the results of single SNP analysis. Conclusions Common variants in PSD3 were associated with obesity, T2D and HDL level. These findings add important new insights into the pathogenesis of obesity, T2D and HDL cholesterol.

Aims The associations of moderate alcohol consumption, sleep duration, and tobacco smoking with coronary heart disease (CHD) among patients with type 2 diabetes mellitus (T2D) are not clearly clarified. The aims of the study were to evaluate the associations of lifestyle factors, hypertension, obesity, depression and sleep duration with CHD development among patients with T2D, and particularly, to examine the gender differences in risk factors for CHD. Methods A total of 2335 T2D adults were selected from the 2012 National Health Interview Survey. Weighted univariate and multiple logistic regression analyses were used to estimate the odds ratios with 95% confidence intervals. Results The CHD prevalence among patients with T2D was 14.2% (18.1% and 10.4% for males and females, respectively), which increased with age (10.3% and 19.6% for age groups 18–64 and 65+, respectively). After adjusting for other factors, weighted logistic regression analyses showed that CHD among patients with T2D was significantly associated with being male, older age, past smoking, long sleep duration, hypertension, and high cholesterol level. Furthermore, the significant association of older age, past smoking, hypertension and high cholesterol level were observed particularly in males, while the association of long sleep duration with CHD was only observed in females. Hypertension was associated with CHD for both genders. Conclusions Gender, age, past smoking, long sleep duration, hypertension and high cholesterol level were significantly associated with CHD among T2D patients; however, such associations differed by gender. Such gender disparities should be considered in the prevention and treatment of T2D.

Introduction There is limited research on the relation between weight misperceptions and health-related quality of life (HRQoL) among U.S. adolescents. Methods Baseline data (n = 1509) collected in 2012 from the Team Up for Healthy Living project were used. Measures included BMI percentiles calculated from measured height and weight; self-perception of weight status; and the 23-item PedsQL™ Inventory. Multiple linear regression was performed after adjustment for covariates to examine associations between weight misperception and HRQoL. Results Compared to accurate weight perception, weight underestimation was associated with higher total HRQoL (β = 2.41), physical health (β = 2.77), and emotional (β = 2.83), social (β = 2.47) and psychosocial functioning (β = 2.38) (all p < 0.05). Weight overestimation was associated with lower social functioning (β = −13.13, p < 0.05). Stratified by gender, associations were observed only in males. Discussion Weight underestimation had greater association with HRQoL than weight overestimation; and varied by gender. Better understanding of these associations will assist in improving the health of adolescents in Southern Appalachia.

Objectives: To estimate prevalence and identify correlates of age of smoking initiation among adolescents in Africa. Methods: Data (n = 16,519) were obtained from nationally representative Global Youth Tobacco Surveys in nine West African countries. Study outcome was adolescents’ age of smoking initiation categorized into six groups: ≤7, 8 or 9, 10 or 11, 12 or 13, 14 or 15 and never-smoker. Explanatory variables included sex, parental or peer smoking behavior, exposure to tobacco industry promotions, and knowledge about smoking harm. Weighted multinomial logit models were conducted to determine correlates associated with adolescents’ age of smoking initiation. Results: Age of smoking initiation was as early as ≤7 years; prevalence estimates ranged from 0.7 % in Ghana at 10 or 11 years age to 9.6 % in Cote d’Ivoire at 12 or 13 years age. Males, exposures to parental or peer smoking, and industry promotions were identified as significant correlates. Conclusions: West African policymakers should adopt a preventive approach consistent with the World Health Organization Framework Convention on Tobacco Control to prevent an adolescent from initiating smoking and developing into future regular smokers.

Objectives: This study aimed to examine the association of Per and Polyfluoroalkyl substances (PFAS) and markers of chronic inflammation and oxidative stress. Methods: Using data (n = 6652) from the National Health and Nutrition Examination Survey (NHANES) 2005–2012, generalized linear models were used to examine the association between PFAS and inflammatory (ferritin, alkaline phosphatase, C-reactive protein, absolute neutrophil count and lymphocyte count) and oxidative stress (serum bilirubin, albumin and iron) per unit exposure to PFAS while adjusting for covariates. Study participants were those ≥20 years of age. Outcome variables were markers of chronic inflammation and oxidative stress and exposure variables were PFAS. Resullts: Percentage change in Perfluorohexane sulfonic acid (PFHxS), Perfluorononanoic acid (PFNA), Perfluorooctanoic acid (PFOA), Perfluorooctane sulfonic acid (PFOS), and Perfluorodecanoic acid (PFDA) were all significantly associated with percentage increases in lymphocyte counts, beta (95% confidence interval); 0.04(0.02,0.05), 0.04(0.02,0.05), 0.05(0.03, 0.07), 0.04(0.03,0.05), 0.03(0.13,1.23) and with percentage increases in serum iron 0.07(0.05,0.09), 0.04(0.02,0.07), 0.10(0.07,0.12), 0.05(0.03,0.07), 0.04(0.02,0.06) and increased serum albumin 0.02(0.02,0.02), 0.02(0.02,0.03), 0.03(0.03,0.04), 0.02(0.017, 0.025), 0.01 (0.01, 0.05). Only PFHxS, PFNA, PFOA and PFOS were associated with percentage increases in serum total bilirubin 0.04(0.03,0.05), 0.02(0.00,0.03), 0.06(0.04,0.08), 0.03(0.02,0.05). Similar results were obtained for categorical quintile analysis with PFOA showing a significant trend (P < 0.001) with lymphocyte count, serum iron, serum total bilirubin and serum albumin. Trend for neutrophil count was not significant (p = 0.183). Conclusion: Per and Polyfluoroalkyl substances are associated with markers of chronic inflammation and oxidative stress. Increased exposure leads to increase in serum concentration of these markers meaning these chemicals are associated with both chronic inflammation and oxidative stress.

Background: Environmental exposures acting through different mechanisms have been linked with a number of cancers. Perfluoroalkyl chemicals (PFCs) are endocrine disrupting chemicals affecting estrogen homeostasis. Objectives: We examined the association between PFCs and a group of estrogen related cancers and explored if increased non-occupational exposure was associated with increased odds of developing these cancers. We also explored which of these chemical exposures was more correlated with each cancer. Methods: Using data from the National Health and Nutrition Examination Survey (NHANES), we selected participants ≥ 20 years of age. Our outcome variable was presence or absence of breast, prostate, ovarian and uterine cancer (yes/no); our exposure variables were serum PFCs. Logistic regression models were used in investigating the association between PFCs and cancer types and between quartiles of PFCs exposure concentrations and presence or absence of cancer while adjusting for covariates. Discriminant analysis was used to assess the correlation between individual PFCs compounds and individual cancer types. Results: PFCs were associated with increased odds of ovarian cancer; PFOA: 1.02(1.01, 1.02), PFOS: 1.01 (1.012, 1.013), PFHS 1.031 (1.030, 1.033), PFDE: 1.29(1.27, 1.30) and increased odds of breast cancer; PFOA: 1.089(1.089, 1.09), PFOS: 1.011(1.011, 1.011), PFNA: 1.031(1.030, 1.033), PFHS: 1.02 (1.02, 1.02), PFDE: 1.19(1.18, 1.19). PFCs were not associated with increased odds of prostate or uterine cancers. Comparing the odds in quartile 4 to quartile 1 for ovarian cancer, PFOA: 1.77(1.75,1.79), PFOS: 2.25(2.22, 2.28), PFHS: 1.86(1.84, 1.88), PFDE: 2.11(2.09, 2.14). For breast cancer, PFOA: 2.30(2.28, 2.31), PFOS: 1.47(1.46, 1.48), PFNA: 1.04(1.03, 1.05), PFHS:7.07(6.97,7.17), PFDE: 1.38(1.37, 1.39). PFOA was more correlated with breast cancer (0.7) and PFHS was more correlated with ovarian cancer (0.9). Discussion: PFCs were associated with increased odds of ovarian and breast cancers with a positive dose-response relationship. PFOA was more correlated with breast cancer and PFHS more with ovarian cancer.

Adverse Childhood Experiences (ACEs) such as exposure to abuse, dysfunction, and neglect have been shown to affect adult health outcomes. The Behavioral Risk Factor Surveillance System (BRFSS) captures national data on risk factors and chronic disease and first included ACE items in 2009. The purpose of this study was to determine whether specific ACEs predicted depressive disorders or poor general health in adulthood. ACEs included: living with someone who suffered from a mental illness, and primary exposure (physical abuse) and secondary exposure (interpersonal violence in home) to violence. BRFSS data from 2009- 2012 were included. Analyses were performed using SPSS and SAS. Descriptive statistics were completed for ACEs, race, gender, history of depressive disorder (DD), and general health status (GH). Logistic regression analyses were conducted to predict DD and GH, controlling for race, gender, and age. Odds ratios (OR) and 95% confidence intervals (CI) were reported. A total of 1,148 individuals were including in the analyses, with 31.4% having DD, 26.9% reported poor GH, 27.4% lived with someone who had a mental illness, 31.3% exposed to primary violence, and 30.2% exposed to secondary violence. Individuals who lived with someone who suffered from a mental illness were three times more likely to have DD (OR 3.28, CI 2.40-4.47) compared to those who did not, however, this exposure did not significantly affect GH. Those exposed to primary violence were 40% more likely to have DD (OR 1.40, CI 1.02-1.92) and were two times more likely to report poor GH (OR 2.09, CI 1.51-2.89) compared to those not exposed. Individuals exposed to secondary violence were 70% more likely to have DD (OR 1.70, CI 1.24-2.32) and were 48% more likely to report poor GH (OR 1.48, CO 1.06-2.05). This suggests that exposure to specific ACEs negatively impacts adult health, resulting in a higher likelihood of DD and poor GH.

No description available.