871 resultados para SOCIAL STRUCTURE


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Conclusions about the effects of harsh parenting on children have been limited by research designs that cannot control for genetic or shared environmental confounds. The present study used a sample of children of twins and a hierarchical linear modeling statistical approach to analyze the consequences of varying levels of punishment while controlling for many confounding influences. The sample of 887 twin pairs and 2,554 children came from the Australian Twin Registry. Although corporal punishment per se did not have significant associations with negative childhood outcomes, harsher forms of physical punishment did appear to have specific and significant effects. The observed association between harsh physical punishment and negative outcomes in children survived a relatively rigorous test of its causal status, thereby increasing the authors' conviction that harsh physical punishment is a serious risk factor for children.

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Although cannabis is the most commonly used illicit drug, duration of cannabis use is typically short, with many of those who initiate cannabis use ceasing use by their late twenties. In this paper we analyze data from a volunteer Australian cohort of 6265 male and female twins to examine whether the duration of cannabis use is an informative phenotype for future genetic analyses. Genetic modeling indicated: (a) moderate genetic influences on duration of cannabis use in both males (41%; 95% CI = 31–51) and females (55%; 95% CI = 46–63); (b) strong genetic influences on cannabis dependence in both males (72%, 95% CI = 61–81) and females (62%, 95% CI = 48–74); (c) no evidence of shared environmental influences on duration of cannabis use or on cannabis dependence in either males or females. Importantly, this model fitting indicated that a substantial component of genetic influences (rg = .90, 95% CI = .77–.99 (males); .70, 95% CI = .57–.83 (females)) on duration of cannabis use was shared with those influencing liability to cannabis dependence. While there were high genetic correlations in both women and men, lifetime duration of cannabis may be uniquely informative in assessing components of liability to cannabis use.

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Categorical models dominate the eating disorder field, but the tandem use of categorical and dimensional models has been proposed. A transdiagnostic dimensional model, number of lifetime eating disorder behaviors (LEDB), was examined with respect to (1) its relationship to a variety of indicators of the individual's functioning, (2) the degree to which it was influenced by genetic and environmental risk factors, and (3) exposure to specific environmental risk factors. Data from self-report and interview from 1002 female twins (mean age = 34.91 years, SD = 2.09) were examined. While 15.4% women met criteria for a lifetime eating disorder, 29% had at least one LEDB. The dimensional measure provided an indicator of associated functioning, and was influenced primarily by the nonshared environment. The number of LEDB was associated with the degree of impaired functioning. This impairment was associated with conflict between parents and criticism from parents when growing up.

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Background: The objective was to determine whether the pattern of environmental and genetic influences on deviant personality scores differs from that observed for the normative range of personality, comparing results in adolescent and adult female twins. Methods: A sample of 2,796 female adolescent twins ascertained from birth records provided Junior Eysenck Personality Questionnaire data. The average age of the sample was 17.0 years ( S. D. 2.3). Genetic analyses of continuous and extreme personality scores were conducted. Results were compared for 3,178 adult female twins. Results: Genetic analysis of continuous traits in adolescent female twins were similar to findings in adult female twins, with genetic influences accounting for between 37% and 44% of the variance in Extraversion (Ex), Neuroticism (N), and Social Non-Conformity (SNC), with significant evidence of shared environmental influences (19%) found only for SNC in the adult female twins. Analyses of extreme personality characteristics, defined categorically, in the adolescent data and replicated in the adult female data, yielded estimates for high N and high SNC that deviated substantially (p < .05) from those obtained in the continuous trait analyses, and provided suggestive evidence that shared family environment may play a more important role in determining personality deviance than has been previously found when personality is viewed continuously. However, multiple-threshold models that assumed the same genetic and environmental determinants of both normative range variation and extreme scores gave acceptable fits for each personality dimension. Conclusions: The hypothesis of differences in genetic or environmental factors responsible for N and SNC among female twins with scores in the extreme versus normative ranges was partially supported, but not for Ex.

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This study uses a sample of young Australian twins to examine whether the findings reported in [Ashenfelter, Orley and Krueger, Alan, (1994). 'Estimates of the Economic Return to Schooling from a New Sample of Twins', American Economic Review, Vol. 84, No. 5, pp.1157-73] and [Miller, P.W., Mulvey, C and Martin, N., (1994). 'What Do Twins Studies Tell Us About the Economic Returns to Education?: A Comparison of Australian and US Findings', Western Australian Labour Market Research Centre Discussion Paper 94/4] are robust to choice of sample and dependent variable. The economic return to schooling in Australia is between 5 and 7 percent when account is taken of genetic and family effects using either fixed-effects models or the selection effects model of Ashenfelter and Krueger. Given the similarity of the findings in this and in related studies, it would appear that the models applied by [Ashenfelter, Orley and Krueger, Alan, (1994). 'Estimates of the Economic Return to Schooling from a New Sample of Twins', American Economic Review, Vol. 84, No. 5, pp. 1157-73] are robust. Moreover, viewing the OLS and IV estimators as lower and upper bounds in the manner of [Black, Dan A., Berger, Mark C., and Scott, Frank C., (2000). 'Bounding Parameter Estimates with Nonclassical Measurement Error', Journal of the American Statistical Association, Vol. 95, No.451, pp.739-748], it is shown that the bounds on the return to schooling in Australia are much tighter than in [Ashenfelter, Orley and Krueger, Alan, (1994). 'Estimates of the Economic Return to Schooling from a New Sample of Twins', American Economic Review, Vol. 84, No. 5, pp. 1157-73], and the return is bounded at a much lower level than in the US. (c) 2005 Elsevier B.V. All rights reserved.

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The heritability and stability over a 19 year period of long (23-item) and short (12-item) versions of Eysenck's Neuroticism scale were compared in a large Australian twin-family sample. Stability over 19 years of the 23-item Neuroticism scale was 0.62 and for the 12-item scale 0.59. Correlations between scores obtained by mailed questionnaire and telephone interview a few weeks apart were 0.87 for the long scale and 0.85 for the short scale; scores obtained by mail were slightly higher, particularly for females. The 12-item scale had slightly reduced power to discriminate both high and low scoring individuals on the full 23-item scale. Mean Neuroticism score for the 12-item scale was atypically low when compared to the distribution of the complete set of scores for all possible combinations (> 1 million) of 12-items drawn from the full 23-item EPQ-R. Mean heritabilities for the lowest and highest 300,000 of these combinations were 43.2% and 42.7%, respectively, somewhat higher than the 41.0% for the actual EPQ-R-S 12-item scale. Heritability for the 23-item scale was 46.5%. We conclude that there is little loss of either stability or heritability in using the short EPQ-R scale, but the choice of which 12-items could have been better. (c) 2005 Elsevier Ltd. All rights reserved.

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The aim of the study was to perform a genetic linkage analysis for eye color, for comparative data. Similarity in eye color of mono- and dizygotic twins was rated by the twins' mother, their father and/or the twins themselves. For 4748 twin pairs the similarity in eye color was available on a three point scale (not at all alike-somewhat alike-completely alike), absolute eye color on individuals was not assessed. The probability that twins were alike for eye color was calculated as a weighted average of the different responses of all respondents on several different time points. The mean probability of being alike for eye color was 0.98 for MZ twins (2167 pairs), whereas the mean probability for DZ twins was 0.46 (2537 pairs), suggesting very high heritability for eye color. For 294 DZ twin pairs genome-wide marker data were available. The probability of being alike for eye color was regressed on the average amount of IBD sharing. We found a peak LOD-score of 2.9 at chromosome 15q, overlapping with the region recently implicated for absolute ratings of eye color in Australian twins [Zhu, G., Evans, D. M., Duffy, D. L., Montgomery, G. W., Medland, S. E., Gillespie, N. A., Ewen, K. R., Jewell, M., Liew, Y. W., Hayward, N. K., Sturm, R. A., Trent, J. M., and Martin, N. G. (2004). Twin Res. 7:197-210] and containing the OCA2 gene, which is the major candidate gene for eye color [Sturm, R. A. Teasdale, R. D, and Box, N. F. (2001). Gene 277:49-62]. Our results demonstrate that comparative measures on relatives can be used in genetic linkage analysis.

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We examined early social influences across stages of smoking within the context of a twin study using an environmental exposure specific to smoking: whether twins started smoking at the same time (simultaneous smoking initiation: SSI). We expected that SSI would be a good index of shared social influences on smoking initiation. Rates of SSI were indeed significantly higher in MZ twins and in twins who shared peers and classes, as well as in male twins. With the exception of regular smoking in females, we found no significant difference in estimates of genetic and environmental parameters between SSI and non-SSI pairs for any of the smoking measures that we examined (DSM-IV and Fagerstrom HSI measures of nicotine dependence; DSM-IV nicotine withdrawal; heavy smoking; and in males, regular smoking). For regular smoking in females, allowing for additional shared environmental influences associated with SSI only modestly reduced our estimates of additive genetic variance (56% vs. 68%). These results indicate the important social influences that may occur for smoking initiation do not appear to seriously bias estimates of genetic effects on later stages of smoking.

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Diagnosis of a major depressive episode by the Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association requires 5 out of 9 symptoms to be present. Therefore, individuals may differ in the specific symptoms they experience and reach a diagnosis of depression via different pathways. It has been suggested that depressed women more often report symptoms of sleep disturbance, appetite or weight disturbance, fatigue, feelings of guilt/worthlessness and psychomotor retardation than depressed men. In the current study, we investigate whether depressed men and women differ in the symptoms they report. Two samples were selected from a sample of Dutch and Australian twins and siblings. First, Dutch and Australian unrelated depressed individuals were selected. Second, a matched epidemiological sample was created consisting of opposite-sex twin and sibling pairs in which both members were depressed. No sex differences in prevalence rates for symptoms were found, with the exception of decreased weight in women in the sample of unrelated individuals. In general, the similarities in symptoms seem to far outweigh the differences in symptoms between men and women. This signifies that men and women are alike in their symptom profiles for major depression and genes for depression are probably expressed in the same way in the two sexes.

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This article applies methods of latent class analysis (LCA) to data on lifetime illicit drug use in order to determine whether qualitatively distinct classes of illicit drug users can be identified. Self-report data on lifetime illicit drug use (cannabis, stimulants, hallucinogens, sedatives, inhalants, cocaine, opioids and solvents) collected from a sample of 6265 Australian twins (average age 30 years) were analyzed using LCA. Rates of childhood sexual and physical abuse, lifetime alcohol and tobacco dependence, symptoms of illicit drug abuse/dependence and psychiatric comorbidity were compared across classes using multinomial logistic regression. LCA identified a 5-class model: Class 1 (68.5%) had low risks of the use of all drugs except cannabis; Class 2 (17.8%) had moderate risks of the use of all drugs; Class 3 (6.6%) had high rates of cocaine, other stimulant and hallucinogen use but lower risks for the use of sedatives or opioids. Conversely, Class 4 (3.0%) had relatively low risks of cocaine, other stimulant or hallucinogen use but high rates of sedative and opioid use. Finally, Class 5 (4.2%) had uniformly high probabilities for the use of all drugs. Rates of psychiatric comorbidity were highest in the polydrug class although the sedative/opioid class had elevated rates of depression/suicidal behaviors and exposure to childhood abuse. Aggregation of population-level data may obscure important subgroup differences in patterns of illicit drug use and psychiatric comorbidity. Further exploration of a 'self-medicating' subgroup is needed.

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The relative length of the second and fourth fingers (the 2D:4D ratio) has been taken to be an indicator of prenatal exposure to testosterone, and hence possibly relevant to sexual orientation and other sex-differentiated behaviors. Studies have reported a difference in this ratio between Caucasian males in Britain and in the U.S.: higher average 2D:4D ratios were obtained in Britain. This raises the question of whether differences among different Caucasian gene pools were responsible or whether some environmental variable associated with latitude might be involved (e.g., exposure to sunlight or different day-length patterns). This question was explored by examining 2D:4D ratios for an Australian adolescent sample. The Australians were predominantly of British ancestry, but lived at distances from the equator more like those of the U.S. studies. The Australian 2D:4D ratios resembled those in Britain rather than those in the U.S., tending to exclude hypotheses related to latitude and making differences in gene pools a plausible explanation.

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Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation > 0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.