Cognition in Context: Pathways and Compound Risk in a Sample of US Non-Hispanic Whites

The population of individuals with cognitive impairment and dementia is growing rapidly, necessitating etiological investigation. It is clear that individual differences in cognition later in life have both genetic and multi-level environmental correlates. Despite significant recent progress in cellular and molecular research, the exact mechanisms linking genes, brains, and cognition remain elusive. In relation to cognition, it is unlikely that genetic and environmental risk factors function in a vacuum, but rather interact and cluster together. The purpose of the present study was to examine whether aspects of individual socioeconomic status (SES) explain the cognitive genotype-phenotype association, and whether neighborhood SES modifies the effects of genes and individual SES on cognitive ability. Using data from non-Hispanic White participants in the 2016 wave of the Health and Retirement Study, a national sample of United States adults, we examined links between a polygenic score for general cognition and performance-based cognitive functioning. In a series of weighted linear regressions and formal tests of mediation, we observed a significant genotype-phenotype association that was partially attenuated after including individual education to the baseline model, although little reductions were observed for household wealth or census tract-level percent poverty. These findings suggest that genetic risk for poor cognition is partially explained by education, and this pathway is not modified by poverty-level of the neighborhood

Exploring Rural-Urban Differences in Polygenic Associations for Health among Older Adults in the United States

A complex combination of genes and environment influence health and, as a result, both genes and environment can play a role in shaping health disparities. We consider distinctions in these influences across rural and urban settings, expanding upon work that shows lower genetic associations in rural compared to urban places by studying an older age group and examining more than the typical outcomes of alcohol/substance abuse. Using a sample of 14,994 adults from the 1992 through 2016 waves of the Health andRetirement Study, our results suggest genetic associations for BMI and heart conditions are significantly lower in rural compared to urban settings. We do not find evidence in support of this association for depression and smoking. In sum, the results suggest the gene-environment interaction may play a role in the well-documented disparities across rural and urban places within the United States, further highlighting the importance of the social, economic, and built environments for individual health

The Sequencing of a College Degree during the Transition to Adulthood: Implications for Obesity

In this study we consider the health implications of the sequencing of a college degree vis-à-vis familial roles during the transition to adulthood. We hypothesize that people who earned a college degree before assuming familial roles will have better health than people who earned a college degree afterwards. To test this hypothesis, we focus on obesity and use data from the National Longitudinal Study of Adolescent Health. Results show that marriage before completion of college was associated with a 50% higher probability of becoming obese when compared with marriage after completion of college. Parenthood before college completion was associated with a greater-than two-fold increase in the probability of becoming obese when compared to parenthood afterwards for Black men. These findings suggest that the well-established association of education with health depends on its place in a sequence of roles

Local Crime and Substance Use Disorders: A Comparison of Midlife Adults in the 1990s and 2000s

This study investigated how sociopolitical changes in the United States between the 1990s and 2000s may explain the increase in substance use disorders and reduced longevity in more recent cohorts of US midlife adults. The 2008 recession which drastically increased unemployment rates across the country may have had negative implications for downstream contextual and individual processes, including both local crime rates and substance use disorders. The Midlife in the United States Survey cohort (1995; n = 6148; 20–75 years) and the MIDUS Refresher cohort (2011; n = 3543; 23–76 years) reported on substance use disorders. These data were linked to Uniform Crime Reporting violent crime rates to determine whether associations between local crime and substance use disorders changed among two separate cohorts of US midlife adults assessed before or after the 2008 recession. In 1995, despite higher local crime rates, substance use disorders were not associated with local crime. The comparatively lower crime rates of 2011, however, associated with greater prevalence of substance use disorders. Considering unemployment rates from the Decennial Census and American Community Survey, which were substantially higher in 2011 relative to 1995, completely diminished the local crime rate-substance use disorder association. The increased prevalence of substance use disorders observed in the more recent cohort of midlife adults assessed in the current study may represent maladaptive coping to local crime after the 2008 recession

Using smart energy meter data to design better policy: Prepayment meter customers, fuel poverty and policy targeting in Great Britain

During winter 2022–23, residential energy prices were exceptionally high in Europe. Governments provided unprecedented energy support payments, but millions of households still suffered from inadequate access to energy. This paper uses gas and electricity smart meter data from 2019 to 20 to 2022–23 for 11,500 prepayment meter (PPM) customers in Great Britain to characterise energy use over time, by dwelling and household characteristics, examine the effects of high prices and cold weather, evaluate current policy and propose improvements. Households with PPMs are a group where fuel poverty is highly concentrated. This sample use less energy than the general population and 63 % self-disconnected at least once a year, with an annual average 28 h of disconnection. Using smart meter data has enabled identification of groups in extreme need: 7 % of households use scarcely any energy, and no gas, for heating; 4 % self-disconnect for at least 240 h per year. More homes self-disconnected from gas during cold periods than at other times, despite the greater need for heating. The paper proposes replacing the current ‘Cold Weather Payment’ policy that has proven ineffective with advance, daily payments directly to energy accounts that are triggered by forecasts of minimum temperatures of −4 °C. High prices in 2022–23 had a very significant effect: annual gas use per household fell by 20 %, while electricity use fell by 3 %, compared with 2019–20. A new Energy Cost Support Scheme is proposed to provide financial support for households in fuel poverty, worth about £1000 per household. For the longer term, smart meter data could enable better targeting of support for vulnerable households and the fuel poor

Finding the fuel poor and framing better policy

The UK Government needs to make urgent decisions about whether and how to support more vulnerable energy users in the winter of 2023-24. The additional support provided in 2022-23 has been withdrawn, but prices continue to be very high, and in the absence of help, millions of households will struggle without adequate energy for heating, hot water, cooking and other vital services. This report uses data from smart-enabled prepayment meter customers to explore how the Government can best target support to those in greatest need, i.e. those in fuel poverty, and to describe the minimum level of support needed to prevent serious suffering this coming winter. This report is based on household energy consumption and other data for 11,519 households with dual-fuel gas and electricity supplies, provided by the energy company Utilita. Using data from four years, 2019-20 to 2022-23, analysis has looked at how energy use, rates and duration of self-disconnection have varied with external temperature, price, dwelling and household characteristics, and how policies and targeted payments affected energy use and self-disconnection

Using smart energy meter data to design better policy: prepayment meter customers, fuel poverty and policy targeting in Great Britain

During winter 2022–23, residential energy prices were exceptionally high in Europe. Governments provided unprecedented energy support payments, but millions of households still suffered from inadequate access to energy. This paper uses gas and electricity smart meter data from 2019 to 20 to 2022–23 for 11,500 prepayment meter (PPM) customers in Great Britain to characterise energy use over time, by dwelling and household characteristics, examine the effects of high prices and cold weather, evaluate current policy and propose improvements. Households with PPMs are a group where fuel poverty is highly concentrated. This sample use less energy than the general population and 63 % self-disconnected at least once a year, with an annual average 28 h of disconnection. Using smart meter data has enabled identification of groups in extreme need: 7 % of households use scarcely any energy, and no gas, for heating; 4 % self-disconnect for at least 240 h per year. More homes self-disconnected from gas during cold periods than at other times, despite the greater need for heating. The paper proposes replacing the current ‘Cold Weather Payment’ policy that has proven ineffective with advance, daily payments directly to energy accounts that are triggered by forecasts of minimum temperatures of −4 °C. High prices in 2022–23 had a very significant effect: annual gas use per household fell by 20 %, while electricity use fell by 3 %, compared with 2019–20. A new Energy Cost Support Scheme is proposed to provide financial support for households in fuel poverty, worth about £1000 per household. For the longer term, smart meter data could enable better targeting of support for vulnerable households and the fuel poor

The Association Between the MAOA 2R Genotype and Delinquency Over Time Among Men: The Interactive Role of Parental Closeness and Parental Incarceration

Using a panel of 6,001 males from the National Longitudinal Study of Adolescent and Adult Health, we examine potential moderation by paternal incarceration and parent-child closeness altering the relationship between the rare 2R MAOA genotype and delinquency. By jointly examining moderation patterns for both the mother and father with the transmission of the MAOA genotype from mother to son, we are able to make inferences about the specific genetic model that best explains these outcomes. In line with prior research, we find a direct relationship between the MAOA 2R genotype and delinquency, independent of parental incarceration and closeness. Examining moderation patterns, we find that delinquency risk for the 2R allele is buffered for males close to their biological or social father, but not their biological mother. We conclude that the 2R delinquency association is not due to passive gene-environment correlation but is best characterized as a social control gene-environment interaction

Does Crime Trigger Genetic Risk for Type 2 Diabetes in Young Adults? A G x E Interaction Study Using National Data

Background Living in neighborhoods perceived as disordered exacerbates genetic risk for type 2 diabetes (T2D) among older adults. It is unknown whether this gene-neighborhood interaction extends to younger adults. The present study aims to investigate whether crime, an objectively measured indicator of neighborhood disorder, triggers genetic risk for T2D among younger adults, and whether this hypothesized triggering occurs through exposure to obesity. Methods Data were from the Wave I (2008) National Longitudinal Study of Adolescent to Adult Health. A standardized T2D polygenic score was created using 2014 GWAS meta-analysis results. Weighted mediation analyses using generalized structural equation models were conducted in a final sample of 7606 adults (age range: 25–34) to test the overall association of T2D polygenic scores with T2D, and the mediating path through obesity exposure in low, moderate, and high county crime-rate groups. Age, sex, ancestry, educational degree, household income, five genetic principal components, and county-level concentrated advantage and population density were adjusted. Results The overall association between T2D polygenic score and T2D was not significant in low-crime areas (p = 0.453), marginally significant in moderate-crime areas (p = 0.064), and statistically significant in high-crime areas (p = 0.007). The mediating path through obesity was not significant in low or moderate crime areas (ps = 0.560 and 0.261, respectively), but was statistically significant in high-crime areas (p = 0.023). The indirect path through obesity accounted for 12% of the overall association in high-crime area. Conclusion A gene-crime interaction in T2D was observed among younger adults, and this association was partially explained by exposure to obesity

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures