Assessing the Readability of Online Patient Education Materials in Obstetrics and Gynecology Using Traditional Measures: Comparative Analysis and Limitations.

BACKGROUND: Patient education materials (PEMs) can be vital sources of information for the general population. However, despite American Medical Association (AMA) and National Institutes of Health (NIH) recommendations to make PEMs easier to read for patients with low health literacy, they often do not adhere to these recommendations. The readability of online PEMs in the obstetrics and gynecology (OB/GYN) field, in particular, has not been thoroughly investigated. OBJECTIVE: The study sampled online OB/GYN PEMs and aimed to examine (1) agreeability across traditional readability measures (TRMs), (2) adherence of online PEMs to AMA and NIH recommendations, and (3) whether the readability level of online PEMs varied by web-based source and medical topic. This study is not a scoping review, rather, it focused on scoring the readability of OB/GYN PEMs using the traditional measures to add empirical evidence to the literature. METHODS: A total of 1576 online OB/GYN PEMs were collected via 3 major search engines. In total 93 were excluded due to shorter content (less than 100 words), yielding 1483 PEMs for analysis. Each PEM was scored by 4 TRMs, including Flesch-Kincaid grade level, Gunning fog index, Simple Measure of Gobbledygook, and the Dale-Chall. The PEMs were categorized based on publication source and medical topic by 2 research team members. The readability scores of the categories were compared statistically. RESULTS: Results indicated that the 4 TRMs did not agree with each other, leading to the use of an averaged readability (composite) score for comparison. The composite scores across all online PEMs were not normally distributed and had a median at the 11th grade. Governmental PEMs were the easiest to read amongst source categorizations and PEMs about menstruation were the most difficult to read. However, the differences in the readability scores among the sources and the topics were small. CONCLUSIONS: This study found that online OB/GYN PEMs did not meet the AMA and NIH readability recommendations and would be difficult to read and comprehend for patients with low health literacy. Both findings connected well to the literature. This study highlights the need to improve the readability of OB/GYN PEMs to help patients make informed decisions. Research has been done to create more sophisticated readability measures for medical and health documents. Once validated, these tools need to be used by web-based content creators of health education materials.

Socioeconomic factors in the age-graded effect of incarceration on depressive symptoms in early adulthood.

Based on insights from the stress process and life-course paradigms, this study investigates the effect of incarceration on depressive symptoms during early adulthood (ages 18-40). We employed fixed-effects dynamic panel models that adjust for confounding effects due to unobserved time-invariant variables and reverse causality using data from the National Longitudinal Study of Adolescent to Adult Health (N = 11, 811). Our analysis shows that the effect of incarceration on depressive symptoms is greater when incarceration occurs after individuals have established a stable adult status (ages 32-40) as compared to incarceration that occurs at earlier stages of adulthood (ages 18-24 and ages 25-31). The age-graded effect of incarceration on depressive symptoms is partially attributable to time-varying effects of incarceration on socioeconomic factors, such as employment status and income. All these findings contribute to our understanding of the mental health consequences of incarceration.

Genetically Adjusted Propensity Score Matching: A Comparison to Discordant MZ Twin Models.

Discordant monozygotic (MZ) twin methodologies are considered one of the foremost statistical approaches for estimating the influence of environmental factors on phenotypic variance. Limitations associated with the discordant MZ twin approach generates an inability to estimate particular relationships and adjust estimates for the confounding influence of gene-nonshared environment interactions. Recent advancements in molecular genetics, however, can provide the opportunity to address these limitations. The current study reviews an alternative technique, genetically adjusted propensity scores (GAPS) matching, that integrates observed genetic and environmental information to adjust for the confounding of these factors in nonkin individuals. Simulations and a real data example were used to compare the GAPS matching approach to the discordant MZ twin method. Although the results of the simulated comparisons demonstrated that the discordant MZ twin approach remains the more robust statistical technique to adjust for shared environmental and genetic factors, GAPS matching - under certain conditions - could represent a viable alternative when MZ twin samples are unavailable. Overall, the findings suggest that GAPS matching can potentially provide an alternative to the discordant MZ twin approach when limited variation exists between identical twin pairs. Moreover, the ability to adjust for gene-nonshared environment interactions represents a potential advancement associated with the GAPS approach. The limitations of the approach, as well as polygenic risk scores, are also discussed.

Incarceration, polygenic risk, and depressive symptoms among males in late adulthood.

This study demonstrates how social and genetic factors jointly influence depression in late adulthood. We focus on the effect of incarceration, a major life event consistently found to be associated with mental health problems. Drawing on data from males in the Wisconsin Longitudinal Study and the Health and Retirement Study, we conduct a polygenic score analysis based on a genome-wide association study on depressive symptoms. Our analysis produces two important findings. First, incarceration experience mediates the association between the depression polygenic score and depressive symptoms in late adulthood (i.e., greater polygenic scores are associated with elevated incarceration risk, which increases depressive symptoms in late adulthood). Second, about one-fifth of the association between incarceration experience and late-adulthood depressive symptoms is accounted for by the depression polygenic score and childhood depression. These findings reveal complex biological and social mechanisms in the development of depression and, more broadly, provide important insights for causal inference in social science research.

The longitudinal associations between motivation, self-regulatory capacities, and future-oriented cognition and behavior among serious young offenders.

OBJECTIVES: The present study examined how changes in a set of motivational/self-regulatory factors were associated with subsequent change in future-oriented cognition and behavior. HYPOTHESES: We hypothesized that within-individual changes in aspirations, expectations, emotion regulation, resistance to peer influence, and impulse control would be positively associated with later change in future-oriented cognition and behavior. We also predicted that between-individual effects would be larger in magnitude than within-individual effects. METHOD: Serious young offenders (N = 1,318; M age = 16.04; 86% male) were followed over a 7-year period from adolescence to young adulthood during the Pathways to Desistance study. The analytical strategy incorporated both fixed and hybrid effects regression models to assess the time-ordered correlates of future-oriented cognition and behavior. RESULTS: Net of controls, within-individual changes in aspirations and expectations about the future, emotion regulation, and impulse control had statistically significant, positive associations with subsequent change in future-oriented cognition and behavior; however, between-person effects were much larger in magnitude than within-individual effects. CONCLUSIONS: Motivation and aspects of self-regulation are potentially important targets for correctional treatment and prevention efforts. Future orientation is an intermediate treatment mechanism worthy of further study. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Why are Women More Religious than Men? Do Risk Preferences and Genetic Risk Predispositions Explain the Gender Gap?

Risk preference theory argues that the gender gap in religiosity is caused by greater female risk aversion. Although widely debated, risk preference theory has been inadequately tested. Our study tests the theory directly with phenotypic and genetic risk preferences in three dimensions-general, impulsive, and sensation-seeking risk. Moreover, we examine whether the effect of different dimension of risk preference on the gender gap varies across different dimensions of religiosity. We find that general and impulsive risk preferences do not explain gender differences in religiosity, whereas sensation-seeking risk preference makes the gender gap in self-assessed religiousness and church attendance insignificant, but not belief in God, prayer, or importance of religion. Genetic risk preferences do not remove any of the gender gaps in religiosity, suggesting that the causal order is not from risk preference to religiosity. Evidence suggests that risk preferences are not a strong predictor for gender differences in religiosity.

Genetic architecture of socioeconomic outcomes: Educational attainment, occupational status, and wealth.

This study takes a socio-genomic approach to examine the complex relationships among three important socioeconomic outcomes: educational attainment, occupational status, and wealth. Using more than 8,000 genetic samples from the Health and Retirement study, it first estimates the collective influence of genetic variants across the whole human genome to each of the three socioeconomic outcomes. It then tests genetic correlations among three socioeconomic outcomes, and examines the extent to which genetic influences on occupational status and wealth are mediated by educational attainment. Analyses using the genomic-relatedness-matrix restricted maximum likelihood method show significant genetic correlations among the three outcomes, and provide evidence for both mediated and independent genetic influences. A polygenic score analysis demonstrates the utility of findings in socio-genomic studies to address genetic confounding in causal relationships among the three socioeconomic outcomes.

Opportunities and challenges of big data for the social sciences: The case of genomic data.

In this paper, we draw attention to one unique and valuable source of big data, genomic data, by demonstrating the opportunities they provide to social scientists. We discuss different types of large-scale genomic data and recent advances in statistical methods and computational infrastructure used to address challenges in managing and analyzing such data. We highlight how these data and methods can be used to benefit social science research.

Mixture SNPs effect on phenotype in genome-wide association studies.

BACKGROUND: Recently mixed linear models are used to address the issue of "missing" heritability in traditional Genome-wide association studies (GWAS). The models assume that all single-nucleotide polymorphisms (SNPs) are associated with the phenotypes of interest. However, it is more common that only a small proportion of SNPs have significant effects on the phenotypes, while most SNPs have no or very small effects. To incorporate this feature, we propose an efficient Hierarchical Bayesian Model (HBM) that extends the existing mixed models to enforce automatic selection of significant SNPs. The HBM models the SNP effects using a mixture distribution of a point mass at zero and a normal distribution, where the point mass corresponds to those non-associative SNPs. RESULTS: We estimate the HBM using Gibbs sampling. The estimation performance of our method is first demonstrated through two simulation studies. We make the simulation setups realistic by using parameters fitted on the Framingham Heart Study (FHS) data. The simulation studies show that our method can accurately estimate the proportion of SNPs associated with the simulated phenotype and identify these SNPs, as well as adapt to certain model mis-specification than the standard mixed models. In addition, we analyze data from the FHS and the Health and Retirement Study (HRS) to study the association between Body Mass Index (BMI) and SNPs on Chromosome 16, and replicate the identified genetic associations. The analysis of the FHS data identifies 0.3% SNPs on Chromosome 16 that affect BMI, including rs9939609 and rs9939973 on the FTO gene. These two SNPs are in strong linkage disequilibrium with rs1558902 (Rsq =0.901 for rs9939609 and Rsq =0.905 for rs9939973), which has been reported to be linked with obesity in previous GWAS. We then replicate the findings using the HRS data: the analysis finds 0.4% of SNPs associated with BMI on Chromosome 16. Furthermore, around 25% of the genes that are identified to be associated with BMI are common between the two studies. CONCLUSIONS: The results demonstrate that the HBM and the associated estimation algorithm offer a powerful tool for identifying significant genetic associations with phenotypes of interest, among a large number of SNPs that are common in modern genetics studies.

The Genome-Wide Influence on Human BMI Depends on Physical Activity, Life Course, and Historical Period.

In this analysis, guided by an evolutionary framework, we investigate how the human genome as a whole interacts with historical period, age, and physical activity to influence body mass index (BMI). The genomic influence is estimated by (1) heritability or the proportion of variance in BMI explained by genome-wide genotype data, and (2) the random effects or the best linear unbiased predictors (BLUPs) of genome-wide association studies (GWAS) data on BMI. Data were used from the Framingham Heart Study (FHS) in the United States. The study was initiated in 1948, and the obesity data were collected repeatedly over the subsequent decades. The analyses draw analysis samples from a pool of >8,000 individuals in the FHS. The hypothesis testing based on Pitman test, permutation Pitman test, F test, and permutation F test produces three sets of significant findings. First, the genomic influence on BMI is substantially larger after the mid-1980s than in the few decades before the mid-1980s within each age group of 21-40, 41-50, 51-60, and >60. Second, the genomic influence on BMI weakens as one ages across the life course, or the genomic influence on BMI tends to be more important during reproductive ages than after reproductive ages within each of the two historical periods. Third, within the age group of 21-50 and not in the age group of >50, the genomic influence on BMI among physically active individuals is substantially smaller than the influence on those who are not physically active. In summary, this study provides evidence that the influence of human genome as a whole on obesity depends on historical period, age, and level of physical activity.

Lifetime Socioeconomic Status, Historical Context, and Genetic Inheritance in Shaping Body Mass in Middle and Late Adulthood.

This study demonstrates body mass in middle and late adulthood as a consequence of the complex interplay among individuals' genes, lifetime socioeconomic experiences, and the historical context in which they live. Drawing on approximately 9,000 genetic samples from the Health and Retirement Study, we first investigate how socioeconomic status (SES) over the life course moderates the impact of 32 established obesity-related genetic variants on body mass index (BMI) in middle and late adulthood. Further, we consider differences across birth cohorts in the genetic influence on BMI and cohort variations in the moderating effects of life-course SES on the genetic influence. Our analyses suggest that persistently low SES over the life course or downward mobility (e.g., high SES in childhood but low SES in adulthood) amplified the genetic influence on BMI, while persistently high SES or upward mobility (e.g., low SES in childhood but high SES in adulthood) compensated for such influence. For more recent birth cohorts, while the genetic influence on BMI became stronger, the moderating effects of lifetime SES on the genetic influence were weaker compared to earlier cohorts. We discuss these findings in light of social changes during the obesity epidemic in the United States.

Is reproductive development adaptively calibrated to early experience? Evidence from a national sample of females.

Many developmental theories have not been sufficiently evaluated using designs that control for unobserved familial confounds. Our long-term goal is to determine the causal structure underlying associations between early environmental conditions and later psychosocial and health outcomes. Our overall objective in this study was to further evaluate predictions derived from applications of life history theory to female reproductive development, key among them that reproductive milestones translate early environmental risk into fertility, health, and behavioral outcomes. To this end, we used female data from the National Longitudinal Survey of Youth 1979 and structural equation modeling to conduct increasingly severe tests, beginning with covariate control and then progressing to sibling control and behavioral genetic designs. After adjusting for confounds varying between sets of siblings, we did not find evidence that age at menarche reflected components of early environment or that any focal outcomes reflected early fragmented family structure (birth to age nine). Although we detected no links between measured environment and individual differences in age at sexual debut, we did find that it reflected both shared and nonshared influences in our behavior genetic models. Interestingly, delayed sexual debut (into young adulthood) reflected identification of parents as the greatest influences and forecasted an array of fertility-related outcomes. Taken together, these findings challenge theories suggesting menarche timing is adaptively calibrated to early environment. They also highlight the need for more research using sibling control and related designs to examine the roles of environments in development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review.

BACKGROUND: Health literacy (HL) is the ability to make informed decisions using health information. As health data and information availability increase due to online clinic notes and patient portals, it is important to understand how HL relates to social determinants of health (SDoH) and the place of informatics in mitigating disparities. OBJECTIVE: This systematic literature review aims to examine the role of HL in interactions with SDoH and to identify feasible HL-based interventions that address low patient understanding of health information to improve clinic note-sharing efficacy. METHODS: The review examined 2 databases, Scopus and PubMed, for English-language articles relating to HL and SDoH. We conducted a quantitative analysis of study characteristics and qualitative synthesis to determine the roles of HL and interventions. RESULTS: The results (n=43) were analyzed quantitatively and qualitatively for study characteristics, the role of HL, and interventions. Most articles (n=23) noted that HL was a result of SDoH, but other articles noted that it could also be a mediator for SdoH (n=6) or a modifiable SdoH (n=14) itself. CONCLUSIONS: The multivariable nature of HL indicates that it could form the basis for many interventions to combat low patient understandability, including 4 interventions using informatics-based solutions. HL is a crucial, multidimensional skill in supporting patient understanding of health materials. Designing interventions aimed at improving HL or addressing poor HL in patients can help increase comprehension of health information, including the information contained in clinic notes shared with patients.

Educational Mobility, Pace of Aging, and Lifespan Among Participants in the Framingham Heart Study.

Importance: People who complete more education live longer lives with better health. New evidence suggests that these benefits operate through a slowed pace of biological aging. If so, measurements of the pace of biological aging could offer intermediate end points for studies of how interventions to promote education will affect healthy longevity. Objective: To test the hypothesis that upward educational mobility is associated with a slower pace of biological aging and increased longevity. Design, Setting, and Participants: This prospective cohort study analyzed data from 3 generations of participants in the Framingham Heart Study: (1) the original cohort, enrolled beginning in 1948; (2) the Offspring cohort, enrolled beginning in 1971; and (3) the Gen3 cohort, enrolled beginning in 2002. A 3-generation database was constructed to quantify intergenerational educational mobility. Mobility data were linked with blood DNA-methylation data collected from the Offspring cohort in 2005 to 2008 (n = 1652) and the Gen3 cohort in 2009 to 2011 (n = 1449). Follow-up is ongoing. Data analysis was conducted from June 2022 to November 2023 using data obtained from the National Institutes of Health database of Genotypes and Phenotypes (dbGaP). Exposure: Educational mobility was measured by comparing participants' educational outcomes with those of their parents. Main Outcomes and Measures: The pace of biological aging was measured from whole-blood DNA-methylation data using the DunedinPACE epigenetic clock. For comparison purposes, the analysis was repeated using 4 other epigenetic clocks. Survival follow-up was conducted through 2019. Results: This study analyzed data from 3101 participants from the Framingham Heart Study; 1652 were in the Offspring cohort (mean [SD] age, 65.57 [9.22] years; 764 [46.2%] male) and 1449 were in the Gen3 cohort (mean [SD] age, 45.38 [7.83] years; 691 [47.7%] male). Participants who were upwardly mobile in educational terms tended to have slower pace of aging in later life (r = -0.18 [95% CI, -0.23 to -0.13]; P < .001). This pattern of association was similar across generations and held in within-family sibling comparisons. There were 402 Offspring cohort participants who died over the follow-up period. Upward educational mobility was associated with lower mortality risk (hazard ratio, 0.89 [95% CI, 0.81 to 0.98]; P = .01). Slower pace of aging accounted for approximately half of this association. Conclusions and Relevance: This cohort study's findings support the hypothesis that interventions to promote educational attainment may slow the pace of biological aging and promote longevity. Epigenetic clocks have potential as near-term outcome measures of intervention effects on healthy aging. Experimental evidence is needed to confirm findings.

Gene-environment correlation: difficulties and a natural experiment-based strategy.

OBJECTIVES: We explored how gene-environment correlations can result in endogenous models, how natural experiments can protect against this threat, and if unbiased estimates from natural experiments are generalizable to other contexts. METHODS: We compared a natural experiment, the College Roommate Study, which measured genes and behaviors of college students and their randomly assigned roommates in a southern public university, with observational data from the National Longitudinal Study of Adolescent Health in 2008. We predicted exposure to exercising peers using genetic markers and estimated environmental effects on alcohol consumption. A mixed-linear model estimated an alcohol consumption variance that was attributable to genetic markers and across peer environments. RESULTS: Peer exercise environment was associated with respondent genotype in observational data, but not in the natural experiment. The effects of peer drinking and presence of a general gene-environment interaction were similar between data sets. CONCLUSIONS: Natural experiments, like random roommate assignment, could protect against potential bias introduced by gene-environment correlations. When combined with representative observational data, unbiased and generalizable causal effects could be estimated.

Testing Environmental Effects on Age at Menarche and Sexual Debut within a Genetically Informative Twin Design.

Life-history-derived models of female sexual development propose menarche timing as a key regulatory mechanism driving subsequent sexual behavior. The current research utilized a twin subsample of the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 514) to evaluate environmental effects on timings of menarche and sexual debut, as well as address potential confounding of these effects within a genetically informative design. Results show mixed support for each life history model and provide little evidence rearing environment is important in the etiology of individual differences in age at menarche. This research calls into question the underlying assumptions of life-history-derived models of sexual development and highlights the need for more behavior genetic research in this area.

Genetic associations with parental investment from conception to wealth inheritance in six cohorts.

Genetic inheritance is not the only way parents' genes may affect children. It is also possible that parents' genes are associated with investments into children's development. We examined evidence for links between parental genetics and parental investments, from the prenatal period through to adulthood, using data from six population-based cohorts in the UK, US and New Zealand, together totalling 36,566 parents. Our findings revealed associations between parental genetics-summarized in a genome-wide polygenic score-and parental behaviour across development, from smoking in pregnancy, breastfeeding in infancy, parenting in childhood and adolescence, to leaving a wealth inheritance to adult children. Effect sizes tended to be small at any given time point, ranging from RR = 1.12 (95% confidence interval (95%CI) 1.09, 1.15) to RR = 0.76 (95%CI 0.72, 0.80) during the prenatal period and infancy; ß = 0.07 (95%CI 0.04, 0.11) to ß = 0.29 (95%CI 0.27, 0.32) in childhood and adolescence, and RR = 1.04 (95%CI 1.01, 1.06) to RR = 1.11 (95%CI 1.07, 1.15) in adulthood. There was evidence for accumulating effects across development, ranging from ß = 0.15 (95%CI 0.11, 0.18) to ß = 0.23 (95%CI 0.16, 0.29) depending on cohort. Our findings are consistent with the interpretation that parents pass on advantages to offspring not only via direct genetic transmission or purely environmental paths, but also via genetic associations with parental investment from conception to wealth inheritance.

Every contact leaves a trace: contact with the criminal justice system, life outcomes, and the intersection with genetics.

Contact with the criminal justice (CJ) system is a relatively common occurrence in the United States. Criminologists and sociologists have long considered the impact of contact with the CJ system on later-in-life outcomes. This body of work has revealed a great deal of heterogeneity in life outcomes, suggesting individual differences are important to consider. At the same time, recent advances in the genomic sciences have allowed researchers to gather information from across the entire genome and to summarize that information into polygenic scores. In the present review, we consider how polygenic scores might be used to advance research into the impact of CJ system contact on life outcomes. In particular, we emphasize the importance of gene-environment interaction (G × E). We suggest that contact with the CJ system might represent a substantively important environmental moderator of polygenic risks. But we caution that studying the moderating role of contact with the CJ system will have its own complications-points that scholars must begin to consider and discuss now that the genomic era has reached the social sciences.

The Genome-Wide Study of Human Social Behavior and Its Application in Sociology.

Recent years have seen a push for the integration of modern genomic methodologies with sociological inquiry. The inclusion of genomic approaches promises to help address long-standing issues in sociology (e.g., selection effects), as well as open up new avenues for future research. This article reviews the substantive findings of behavior genetic/genomic research, both from the recent past (e.g., twin/adoption studies, candidate gene studies) and from contemporary genomic analyses. The article primarily focuses on modern genomic methods available to sociologists (e.g., polygenic score analysis) and their various applications for answering sociological questions. The article concludes by considering a number of areas to which genomic researchers and sociologists should pay close attention if a consilience between genomic methods and sociological research is to be fully realized.