Associations between neighborhood characteristics: well-being and health vary over the life course

Background: Neighborhood characteristics are important determinants of individual health and well-being. For example, characteristics such as noise and pollution affect health directly, while other characteristics affect health and well-being by either providing resources (e.g. social capital in the neighborhood), which individuals can use to cope with health problems, or limiting the use thereof (e.g. crime). This also suggests that there might be age differentials in the impact of these characteristics, since individuals at different stages of life might need different resources. However, there is a lack of empirical evidence on age differentials in associations between well-being, health, and neighborhood characteristics. Objective: This paper studies associations between a wide range of neighborhood characteristics with the health and well-being of residents of the greater Berlin area. In particular, we focus on differences in the effects between younger (aged 20-35) and older (aged 60+) residents. Methods: We used data from the Berlin Aging Study II (312 younger and 993 older residents of the Berlin metropolitan area in Germany). We used survey data on health and well-being, combined these with subjective perceptions of the neighborhood, and geo-referenced indicators on the neighborhood, e.g. amenities (public transport, physicians, and hospitals). Results: The results show that access to public transportation is associated with better outcomes on all measures of health and well-being, and social support is associated with higher life satisfaction and better mental health. There are considerable differences between both age groups: while the associations between access to public transport and health and well-being are similar for both age groups, neighborhood social capital shows stronger associations for older residents. However, the difference is not always statistically significant. Conclusion: Having access to services is associated with better health and well-being regardless of age. Local policy makers should focus on lowering barriers to mobility in order to improve the health and well-being of the population. Since the social capital of a neighborhood is associated with better health and well-being among older residents, investments that increase social capital (e.g. community centers) might be warranted in neighborhoods with higher shares of older residents

Today’s older adults are cognitively fitter than older adults were 20 years ago, but when and how they decline is no different than in the past

History-graded increases in older adults' levels of cognitive performance are well documented, but little is known about historical shifts in within-person change: cognitive decline and onset of decline. We combined harmonized perceptual-motor speed data from independent samples recruited in 1990 and 2010 to obtain 2,008 age-matched longitudinal observations (M = 78 years, 50% women) from 228 participants in the Berlin Aging Study (BASE) and 583 participants in the Berlin Aging Study II (BASE-II). We used nonlinear growth models that orthogonalized within- and between-person age effects and controlled for retest effects. At age 78, the later-born BASE-II cohort substantially outperformed the earlier-born BASE cohort (d = 1.20; 25 years of age difference). Age trajectories, however, were parallel, and there was no evidence of cohort differences in the amount or rate of decline and the onset of decline. Cognitive functioning has shifted to higher levels, but cognitive decline in old age appears to proceed similarly as it did two decades ago

The challenge of antimicrobial resistance: What economics can contribute

BACKGROUND: Antimicrobial resistance (AMR) is increasing, driven by widespread antibiotic use. The wide availability of effective antibiotics is under threat, jeopardizing modern health care. Forecasts of the economic costs are similar to those of a 2°C rise in global average surface temperature, above preindustrial levels. AMR is becoming an urgent priority for policy-makers, and pressure is mounting to secure international commitments to tackle the problem. // ADVANCES: Estimating the value of interventions to reduce antibiotic use requires predictions of future levels of antibiotic resistance. However, modeling the trajectory of antibiotic resistance, and how marginal changes in antibiotic consumption contribute to resistance, is complex. The challenge of estimating the resulting impact on health and the economy is similarly daunting. As with the cost of climate change, estimates of total AMR costs are fraught with uncertainty and may be far too low. Much of the uncertainty arises from the complexity of estimating the cost of changes in overall resistance levels. This cost depends on various factors: which drug and pathogen are involved, the mechanism of antibiotic resistance, the prevalence of that pathogen, the types of infections it causes and their level of transmissibility, the health burden of those infections, and whether alternative treatments are available. Effective new antibiotics are urgently needed. However, without government intervention, R&D for antibiotics is rarely profitable, and most major pharmaceutical companies have left the field. New ways are needed to make antibiotic development profitable, decoupling profits from volumes sold. // OUTLOOK: Analogies can be drawn between climate change and AMR, both of which have been described as a global “tragedy of the commons.” There is some consensus that we should treat carbon emissions reduction as an insurance policy against the possibility of a catastrophic climate outcome—and avoid waiting for a definitive optimum-abatement policy. A similar paradigm shift is needed to incentivize both the introduction and valuation of interventions to reduce antibiotic use and R&D of new antibiotics. Rather than taxing the price and letting the market dictate the quantity of antibiotics supplied, an alternative may be to establish a regulatory body that issues prescribers tradable permits and to allow the market to determine the price. Such an approach could create a predictable revenue stream through more-foreseeable licensing fees for important antibiotics by decoupling the return on investment from the volume used. Approaches such as this could incentivize industry to develop new antibiotics for which there would otherwise be too small a market to provide a sufficient return on investment. Reducing inappropriate antibiotic use while expanding essential access is a difficult challenge, especially in low- and middle-income countries. However, policy-makers and philanthropists are alert to the importance of AMR and increasingly are making substantial research funds available, with much of these funds devoted to the social sciences. We need economists, across many different fields, to engage with this pressing global problem

Analyzing Regional Variation in Health Care Utilization Using (Rich) Household Microdata

This paper exploits rich SOEP microdata to analyze state-level variation in health care utilization in Germany. Unlike most studies in the field of the Small Area Variation (SAV) literature, our approach allows us to net out a large array of individual-level and state-level factors that may contribute to the geographic variation in health care utilization. The raw data suggest that state-level hospitalization rates vary from 65 percent to 165 percent of the national mean. Ambulatory doctor visits range from 90 percent to 120 percent of the national mean. Interestingly, in the former GDR states doctor visit rates are significantly below the national mean, while hospitalization rates lie above the national mean. The significant state-level differences vanish once we control for individual-level socio-economic characteristics, the respondents' health status, their health behavior as well as supply-side state-level factors

Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.</p

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits

Genetic variants linked to education predict longevity

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members’ polygenic profile score for education to predict their parents’ longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.</p