68 research outputs found

    Divorce and Child Development

    Get PDF
    Divorce has become commonplace in the United States. Most Americans are likely to feel its effects directly either from the dissolution of their parents\u27 marriage, their own marriage, or the marriage of one of their offspring. Two recent studies using data from national surveys have estimated that close to half of all children borne in the late 1970s, when the divorce rate reached its peak, will witness the breakup of their family before they reach the age of 16 (Bumpass, 1984; Furstenberg et al., 1983). These startling figures have stimulated a tremendous amount of concern about the impact of divorce on the socialization process. The question of how divorce affects children has interested researchers for more than half a century, and hundreds of studies addressing this question have appeared in psychological and sociological journals. At first glance, it appears that the existing literature tells us very little, for it is rife with inconclusive and even contradictory results. Yet, if we go beyond the specific findings reported in any particular study and look at the larger pattern of results, the data assume a more consistent form, indicating some promising directions for future research

    Spatial Distance Between Parents and Adult Children in the United States

    Full text link
    ObjectiveThis brief report presents contemporary national estimates of the spatial distance between residences of parents and adult children in the United States, including distance to one’s nearest parent or adult child and whether one lives near all of their parents and adult children.BackgroundThe most recent national estimates of parent–child spatial proximity come from data for the early 1990s. Moreover, research has rarely assessed the spatial clustering of all parents and adult children.MethodData are from the 2013 Panel Study of Income Dynamics on residential locations of adults aged 25 years and older and each of their parents and adult children. The following two measures of spatial proximity were estimated: the share of adults who have their nearest parent or adult child at a given distance and the share of adults who have all parents and/or all adult children at a given distance. Sociodemographic and geographic differences were examined for both measures.ResultsAmong the adults with at least one living parent or adult child, a significant majority (74.8%) had their nearest parent or adult child within 30 miles, and about one third (35.5%) had all parents and adult children living that close. Spatial proximity differed substantially among sociodemographic groups, with those who were disadvantaged more likely to have their parents or adult children nearby. In most cases, sociodemographic disparities were much higher when spatial proximity was measured by proximity to all parents and all adult children instead of to the nearest parent or nearest adult child.ConclusionDisparities in having all parents and/or adult children nearby may be a result of family solidarity and also may affect family solidarity. This report sets the stage for new investigations of the spatial dimension of family cohesion.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154398/1/jomf12606_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154398/2/jomf12606.pd

    Disparities in Vulnerability to Severe Complications from COVID-19 in the United States

    Get PDF
    Preexisting health conditions increase vulnerability to severe complications from COVID-19. Among middle-aged and older Americans, vulnerability to severe COVID-19 complications based on preexisting conditions is 2-3 times greater for those with low versus high income. Vulnerability is about 40% higher for middle-aged and older adults with a high school degree or less than adults with a four-year college degree. In every age group, Blacks are more vulnerable than Whites, but Hispanics are at lower risk based on fewer preexisting health conditions

    The genetic architecture of the human cerebral cortex

    Get PDF
    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

    Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

    Get PDF
    Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

    Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

    Get PDF
    Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification
    corecore