The current study explored the impact of genetic relatedness differences (ΔH) and sample size on the performance of nonclassical ACE models, with a focus on same-sex and opposite-sex twin groups. The ACE model is a statistical model that posits that additive genetic factors (A), common environmental factors (C), and specific (or nonshared) environmental factors plus measurement error (E) account for individual differences in a phenotype. By extending Visscher’s (2004) least squares paradigm and conducting simulations, we illustrated how genetic relatedness of same-sex twins (HSS) influences the statistical power of additive genetic estimates (A), AIC-based model performance, and the frequency of negative estimates. We found that larger HSS and increased sample sizes were positively associated with increased power to detect additive genetic components and improved model performance, and reduction of negative estimates. We also found that the common solution of fixing the common environment correlation for sex-limited effects to .95 caused slightly worse model performance under most circumstances. Further, negative estimates were shown to be possible and were not always indicative of a failed model, but rather, they sometimes pointed to low power or model misspecification. Researchers using kin pairs with ΔH less than .5 should carefully consider performance implications and conduct comprehensive power analyses. Our findings provide valuable insights and practical guidelines for those working with nontwin kin pairs or situations where zygosity is unavailable, as well as areas for future research.

This study aimed to quantify a latent variable for body size (BS) in pigs by using five linear body measurements including body length (BL), body height (BH), chest width (CW), chest girth (CG) and tube girth (TG), and also to identify the most associated single nucleotide polymorphisms (SNP) and related genes with BS by using the genomic best linear unbiased prediction (GBLUP) based genome-wide association study (GWAS) or GBLUP-GWAS methodology. To perform a GWAS on the BS latent trait, we used a mixed linear model and identified a total of 53 significant SNPs. Additionally, we found that nine genes, including Rho GTPase activating protein 12 (ARHGAP12), transmembrane protein 108 (TMEM108), T-cell lymphoma invasion and metastasis inducing factor 1 (TIAM1), ras homologue gene family member B (RHOB), POU class 4 homeobox 1 (POU4F1), follistatin-related protein 4 (FSTL4), cellular communication network factor 2 (CCN2), beaded filament structural protein 2 (BFSP2) and attractin-like protein 1 (ATRNL1) were associated with the BS trait in pigs. These genes are involved in several biological processes, including the regulation of anatomical structure, morphogenesis, the regulation of cell size and growth. The results suggest that the identified SNP and related genes may play important roles in regulating the growth and development of pigs. The results imply that these genes could be promising candidates for further exploration of the underlying mechanisms of body size variation. Furthermore, the findings have significant practical implications for enhancing the efficiency and profitability of pig farming through genetic selection.

It is crucial to understand the genetic mechanisms and biological pathways underlying the relationship between obesity and serum lipid levels. Structural equation models (SEMs) were constructed to calculate heritability for body mass index (BMI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the genetic connections between BMI and the four classes of lipids using 1197 pairs of twins from the Chinese National Twin Registry (CNTR). Bivariate genomewide association studies (GWAS) were performed to identify genetic variants associated with BMI and lipids using the records of 457 individuals, and the results were further validated in 289 individuals. The genetic background affecting BMI may differ by gender, and the heritability of males and females was 71% (95% CI [.66, .75]) and 39% (95% CI [.15, .71]) respectively. BMI was positively correlated with TC, TG and LDL-C in phenotypic and genetic correlation, while negatively correlated with HDL-C. There were gender differences in the correlation between BMI and lipids. Bivariate GWAS analysis and validation stage found 7 genes (LOC105378740, LINC02506, CSMD1, MELK, FAM81A, ERAL1 and MIR144) that were possibly related to BMI and lipid levels. The significant biological pathways were the regulation of cholesterol reverse transport and the regulation of high-density lipoprotein particle clearance (p < .001). BMI and blood lipid levels were affected by genetic factors, and they were genetically correlated. There might be gender differences in their genetic correlation. Bivariate GWAS analysis found MIR144 gene and its related biological pathways may influence obesity and lipid levels.

We aim to determine the correlation between parental rearing, personality traits, and obsessive–compulsive disorder (OCD) in different quantiles. In particular, we created an intermediary effect model in which parental rearing affects OCD through personality traits. All predictors were measured at the time of the survey, comprising parental rearing (paternal rearing and maternal rearing), demographics (grade and gender), and personality traits (neuroticism, extroversion, and psychoticism). These results suggest that (a) paternal emotional warmth was negatively correlated with OCD at the 0.40–0.80 quantile, while maternal emotional warmth was positively correlated with the OCD at the 0.45–0.69 quantile. (b) The correlation between negative parental rearing and OCD ranged from the 0.67 to 0.95 quantile for paternal punishment, 0.14–0.82 quantile for paternal overprotection, 0.05–0.36 and >0.50 quantile for maternal over-intervention and overprotection, and 0.08–0.88 quantile for maternal rejection. (c) Extroversion, neuroticism, and psychoticism were not only associated with OCD in a particular quantile but also mediated between parental rearing (namely parental emotional warmth, paternal punishment, paternal overprotection, maternal rejection, maternal over-intervention, and overprotection) and OCD. These findings provide targets for early interventions of OCD to improve the form of family education and personality traits and warrant validation.

Data of 2780 Markhoz kids originated from 1216 dams and 211 sires during 1993–2016 in Markhoz Goat Breeding Station, located in Sanandaj, Iran, were used. Traits investigated were body weights at birth, weaning, six-month age [six months weight (6MW)], nine-month age and yearling age [yearling weight (YW)]. Two considered multivariate models including standard multivariate model (SMM) and fully recursive multivariate model (FRM) were compared using deviance information criterion (DIC) and predictive ability measures including mean square of error (MSE) and Pearson's correlation coefficient between the observed and predicted values $(r(y,\hat{y}))$ of records. Spearman's rank correlation coefficients between posterior means of direct genetic effects of the studied traits of kids under SMM and FRM were also calculated across all, 50, 10 and 1% top-ranked animals. In general, FRM performed better than SMM in terms of lower DIC and MSE and also higher $r\lpar y\comma \;\hat{y}\rpar$. For all traits, the lowest MSE and the highest $r\lpar y\comma \;\hat{y}\rpar$ were obtained under FRM. All structural coefficients estimated under FRM were statistically significant except for that of 6MW on YW. Comparisons of Spearman's rank correlations between posterior means of direct genetic effects of kids for growth traits under SMM and FRM revealed that taking the causal relationships among the studied growth traits of Markhoz goat into account may cause considerable re-ranking for the animals in terms of estimated breeding values, especially for the top-ranked animals. It may be concluded that FRM had more plausibility over SMM for genetic evaluation of the studied growth traits in Markhoz goat.

Creating and assessing relatively broad conservation education curricula is important when trying to reach a variety of students. We used a curriculum centred around a storybook in 12 schools in four separate areas of Indonesia, reaching 529 students. We visited each school twice, and taught the ecology and importance of the target taxa, Indonesia’s seven threatened slow loris species (Nycticebus spp.). Through cultural consensus analyses and structural equation modelling, we found that students from all regions showed improvements in knowledge, and that the distance from the forest to where children lived, teachers’ use of given education materials, and students’ use of the storybook all affected student performance in drawing and essay accuracy. Here we make suggestions for creating and evaluating multi-site environmental education programmes. We recommend creating curricula that are not inclusive of any particular community; providing teachers with materials to supplement a conservation intervention; giving each child their own copy of any visual materials used in the lessons; following up with students and teachers about the use of such materials; and interviewing teachers and students regarding their experience with and attitudes towards the study subject. Furthermore we suggest practitioners share their materials and have confidence in adapting them for other species and locations.

Optimization of production factors plays a central role in efficient milk production operations. Causal relationships between production parameters (health, fertility, feeding, performance and farm size) on the one hand and efficiency parameters on the other have been identified in several studies. In recent years, structural equation modelling (SEM) has not only gained importance in agriculture but also in milk production, providing the opportunity to investigate multilateral relationships. Additionally, SEM enables an estimation of parameters which are not themselves measurable, the so-called latent variables. The current study was based on the data of 943 branch settlements (including the years 2012 and 2013) of dairy farms keeping German Holstein cows in Schleswig-Holstein (Northern Germany) which provided a combination of the structural parameters, economic parameters and biological performance of the farms. An SEM using this combined data was applied to investigate the complexity of influences on efficiency parameters in milk production. Efficiency was sub-divided into and evaluated by two effect variables (economic efficiency and biological efficiency). Economic efficiency was defined as a conventional efficiency assessment criterion from full-cost accounting, whereas biological efficiency was used to evaluate the quality of herd management. Performance was identified as the key parameter for independent evaluation of efficiency by assessing biological (γ41 = 0.644) or economic efficiency (γ42 = 0.266). The SEM explained more than three times higher proportion of the variance in biological efficiency than in economic efficiency. The investigation proved the eligibility of partial least squares SEM for the evaluation of efficiency in milk production.

The present study aimed to estimate heritability of Hwabyung (HB) symptoms in adolescent and young adult twins in South Korea. The sample included 1,601 twins consisting of 143 pairs of monozygotic male (MZM), 67 pairs of dizygotic male (DZM), 295 pairs of monozygotic female (MZF), 114 pairs of dizygotic female (DZF), and 117 pairs of opposite-sex dizygotic (OSDZ) twins and 129 twins with non-participating co-twins (mean age = 19.1 ± 3.1 years; range: 12–29 years). An HB symptom questionnaire was given to twins via a telephone interview. Consistent with the literature of HB, the mean level of HB was significantly higher in females than in males. Maximum likelihood twin correlations for HB were 0.31 (95% CI [0.16, 0.45]) for MZM, 0.19 (95% CI [-0.05, 0.41]) for DZM, 0.50 (95% CI [0.41, 0.58]) for MZF, 0.28 (95% CI [0.11, 0.44]) for DZF, and 0.23 (95% CI [0.05, 0.40]) for OSDZ twins. These patterns of twin correlations suggested the presence of additive genetic influences on HB. Model-fitting analysis showed that additive genetic and individual-specific environmental influences on HB were 44% (95% CI [37, 51]) and 56% (95% CI [49, 63]), respectively. Shared environmental influences were not significant. These parameter estimates were not significantly different between two sexes, and did not change significantly with age in the present sample, suggesting that genetic and environmental influences on HB in both sexes are stable across adolescence and young adulthood.

The objectives of this study were to infer phenotypic causal networks involving gestation length (GL) and calving difficulty (CD) for the primiparity of 1850 Japanese Black heifers, and the birth weight (BWT), withers height (WH) and chest girth (CHG) of their full blood calves, and to compare the causal effects among them. The inductive causation (IC) algorithm was employed to search for causal links among these traits; it was applied to the posterior distribution of the residual (co)variance matrix of a multiple-trait sire-maternal grand sire (MGS) model. The IC algorithm implemented with 95% and 90% highest posterior density intervals detected only one structure with links between GL and BWT (WH or CHG) and between BWT (WH or CHG) and CD, although their directions were not resolved. Therefore, a possible causal structure based on the networks obtained from the IC algorithm [GL→BWT (WH or CHG)→CD] was fitted using a structural equation model to infer causal structure coefficients between the traits. The structural coefficients of GL on BWT and of BWT on GL on the observable scale showed that an extra day of GL led to a 270-g gain in BWT, and a 1-kg increase in BWT increased the risk for dystocia by 1.1%, in the causal structure. Similarly, an increase in GL by 1 day resulted in a 2.1 (2.0)-mm growth in WH (CHG), and a 1-cm increase in WH (CHG) increased the risk of dystocia by 1.2% (0.9%). The structural equation model was also fitted to alternative causal structures, which involved the addition of a directed link from GL to CD, or GL→CD to the structures described above. The inferred structural coefficients with the alternative structures were almost the same as the corresponding ones that had GL→BWT (WH or CHG)→CD. However, the direct causal effect of the extra link from GL on CD was similar to the indirect causal effect of GL through the mediating effect of BWT (WH or CHG) on CD and significant (P<0.05). This suggest that maternal genetic effects might not be removed completely from the residual variance components in the sire-MGS model, and the application of the IC algorithm to the variances from the model could detect an incorrect structure. Nonetheless, fitting the structural equation model to the causal structure provided useful information such as the magnitude of the causal effects between the traits.

Utilizing a newly released cognitive Polygenic Score (PGS) from Wave IV of Add Health (n = 1,886), structural equation models (SEMs) examining the relationship between PGS and fertility (which is approximately 50% complete in the present sample), employing measures of verbal IQ and educational attainment as potential mediators, were estimated. The results of indirect pathway models revealed that verbal IQ mediates the positive relationship between PGS and educational attainment, and educational attainment in turn mediates the negative relationship between verbal IQ and a latent fertility measure. The direct path from PGS to fertility was non-significant. The model was robust to controlling for age, sex, and race; furthermore, the results of a multigroup SEM revealed no significant differences in the estimated path coeficients across sex. These results indicate that those predisposed towards higher verbal IQ by virtue of higher PGS values are also predisposed towards trading fertility against time spent in education, which contributes to those with higher PGS values producing fewer offspring at this stage in their life course.

Anaemia in children is a public health concern in Mexico; Federal food assistance programmes are being implemented to prevent it. We undertook this research to investigate the indirect association between food assistance programmes (FAP) and anaemia through dietary and socio-economic conditions of beneficiary children. A structural equation model (SEM) was constructed to assess associations among FAP, dietary and socio-economic conditions, as well as anaemia. A cross-sectional comparative study was conducted based on a sample of 1214 households with children <5 years old, beneficiaries of two FAP: Prospera and rescue from malnutrition with amaranth (RMA) and a comparison group in San Luis Potosí, Mexico. The SEM and a decomposition effect analysis revealed the existence of a significant indirect association of FAP on the prevalence of anaemia via dietary and socio-economic conditions in children under 5 years old. The Prospera assistance programme showed a significant indirect positive association with the prevalence of anaemia (standard coefficient=0·027, P<0·031), and the RMA programme showed a significant indirect negative association with the prevalence of anaemia (standard coefficient=−0·029, P=0·047). There was a direct association between FAP and dietary and socio-economic conditions. FAP could indirectly modify the prevalence of anaemia in young children with a direct improvement on dietary and socio-economic conditions. The unexpected finding of the association between RMA, dietary and socio-economic conditions and the prevalence of anaemia reflects differences in the focus of the programmes.

The association between dietary patterns and metabolic cardiovascular risk factors has long been addressed but there is a lack of evidence towards the effects of the overall diet on the complex net of biological inter-relationships between risk factors. This study aimed to derive dietary patterns and examine their associations with metabolic cardiovascular risk factors following a theoretic model for the relationship between them. Participants included 417 adults of both sexes, enrolled to the cross-sectional population-based study performed in Brazil. Body weight, waist circumference, high-sensitivity C-reactive protein, blood pressure, total cholesterol:HDL-cholesterol ratio, TAG:HDL-cholesterol ratio, fasting plasma glucose and serum leptin were evaluated. Food consumption was assessed by two non-consecutive 24-h dietary recalls adjusted for the within-person variation of intake. A total of three dietary patterns were derived by exploratory structural equation modelling: ‘Traditional’, ‘Prudent’ and ‘Modern’. The ‘Traditional’ pattern had a negative and direct effect on obesity indicators (serum LEP, body weight and waist circumference) and negative indirect effects on total cholesterol:HDL-cholesterol ratio, TAG:HDL-cholesterol ratio and fasting plasma glucose. The ‘Prudent’ pattern had a negative and direct effect on systolic blood pressure. No association was observed for the ‘Modern’ pattern and metabolic risk factors. In conclusion, the ‘Traditional’ and ‘Prudent’ dietary patterns were negatively associated with metabolic cardiovascular risk factors among Brazilian adults. Their apparent protective effects against obesity and high blood pressure may be important non-pharmacological strategies for the prevention and control of obesity-related metabolic disorders and CVD.

Retirement is an inherently complex process due to the multitude of variables that influence it. The present article proposes that by combining our understanding of retirement phases (a conceptual framework) with a theory that specifies a general mechanism for retirement adaptation (a theoretical framework), we can improve how we research retirement. Accordingly, this study proposes and tests a model exploring the antecedents and consequences of the retirement process across three stages: Pre-retirement, Transition and Adaptation, using data collected from 550 Australian retirees. Multiple outcomes are explored, including adjustment, wellbeing and life satisfaction, as well as variables including planning, perception of wealth, resources and mastery. The model showed a significant influence of resources on both phases and outcomes, with mastery showing the strongest relationships of all the resources. Results suggest that outcomes in retirement may be improved by promoting retirement planning, improving exit conditions and building key resources, in particular, mastery. Overall, the model demonstrates the value of combining theory and conceptual frameworks to inform the specification of statistical models to research retirement. Research implications and alternative models are discussed.

Shared values, public trust in an agency, and attitudes can influence support for successful conservation initiatives. To understand these relationships, this paper examines the role of social trust as a partial mediator between salient values similarity and attitudes toward wolves in south-western Alberta, Canada. Rural residents in this area face increasing wolf depredation on livestock. Data were obtained from a mail questionnaire (n = 566 respondents, response rate = 70%) sent to rural residents in three municipal districts in south-western Alberta. Attitudes were predicted to directly influence behavioural intention to support or oppose wolf management. Most respondents held slightly similar values as the management agency and minimally trusted the agency to effectively manage wolves. As predicted, social trust in the agency served as a partial mediator between salient value similarity and attitudes toward wolves. Salient value similarity was also a strong predictor of attitudes toward wolves. Attitudes toward wolves predicted behavioural support. Thus, social trust of the management agency can influence attitudes and management preferences concerning a species. When dealing with human-wildlife conflict, social trust should be examined to understand the context of the problem.

Background: Disaster recovery is a complex phenomenon. Too often, recovery is measured in singular fashion, such as quantifying rebuilt infrastructure or lifelines, without taking in to account the affected population's individual and community recovery. A comprehensive framework is needed that encompasses a much broader and far-reaching construct with multiple underlying dimensions and numerous causal pathways; without the consideration of a comprehensive framework that investigates relationships between these factors, an accurate measurement of recovery may not be valid. This study proposes a model that encapsulates these ideas into a single framework, the Socio-Ecological Model of Recovery.

Methods: Using confirmatory factor analysis, an operational measure of recovery was developed and validated using the five measures of housing stability, economic stability, physical health, mental health, and social role adaptation. The data were drawn from a sample of displaced households following Hurricane Katrina. Measures of psychological strength, risk, disaster exposure, neighborhood contextual effects, and formal and informal help were modeled to examine their direct and indirect effects on recovery using a structural equation model.

Findings: All five elements of the recovery measure were positively correlated with a latent measure of recovery, although mental health and social role adaptation displayed the strongest associations. An individual's psychological strength had the greatest association with positive recovery, followed by having a household income greater than $20 000 and having informal social support. Those factors most strongly associated with an absence of recovery included the time displaced since the hurricane, being disabled, and living in a community with substantial social disorder.

Discussion: The socio-ecological framework provides a robust means for measuring recovery, and for testing those factors associated with the presence or absence of recovery.

(Disaster Med Public Health Preparedness. 2010;4:S46-S54)