257 research outputs found
Saving Shortfalls and Delayed Retirement
Prior research has suggested that many older Americans have not saved enough to maintain consumption levels in old age. One way older persons might respond to inadequate savings would be to extend their worklives by delaying retirement. This paper examines evidence on this matter using the Health and Retirement Study, a nationally representative panel survey of people age 51-61 in 1992 followed for several years in a panel. We use the data to project household retirement assets and to determine how much more saving would be needed to preserve post-retirement consumption levels. Our research then examines the links between derived saving shortfall measures and delayed retirement patterns. Among nonmarried persons, there is evidence that larger shortfalls do produce delayed retirement, though the effect is not quantitatively large. For married couples, pre-retirement wealth shortfalls do not appear to be significantly associated with delayed retirement. Evidently couples have other means of handling saving shortfalls.
Modeling Lifetime Earnings Paths: Hypothetical versus Actual Workers
To assess the distributional effects of social security reform proposals, it is essential to have good information on real-world workersâ lifetime earnings trajectories. Until recently, however, policymakers have relied on hypothetical earnings profiles for policy analysis. We use actual lifetime earnings data from the Health and Retirement Study (HRS) to compare actual workersâ covered earnings profiles to these hypothetical profiles. We show that the hypothetical profiles do not track earnings patterns of current retirees; thus lifetime pay levels are much higher than for most HRS workers. Therefore, using hypothetical profiles could misrepresent benefits paid and taxes collected under such reforms.
Lifetime Earnings Variability and Retirement Wealth
This paper explores how earnings variability is related to retirement wealth. Past research has demonstrated that the average American household on the verge of retirement would need to save substantially more, in order to preserve consumption flows in old age. While several socioeconomic factors have been examined that might explain such problems, prior studies have not assessed the role of earnings variability over the lifetime as a potential explanation for poor retirement prospects. Thus two workers having identical levels of average lifetime earnings might have had very different patterns of earnings variability over their lifetimes. Such differences could translate into quite different retirement wealth outcomes. This paper evaluates the effect of earnings variability on retirement wealth using information supplied by respondents to the Health and Retirement Study (HRS). This is a rich and nationally representative dataset on Americans on the verge of retirement, with responses linked to administrative records from the Social Security Administration. Our research illuminates the key links between lifetime earnings variability and retirement wealth.
Retirement Wealth and Lifetime Earnings Variability
This paper explores understand how earnings variability influences peoplesâ retirement preparedness by influencing their accumulated wealth levels as of retirement age. Prior research has demonstrated that the US average household nearing retirement would need to save substantially more in order to preserve consumption in old age. While some socioeconomic factors have been suggested that might explain shortfalls, previous studies have not assessed the role of earnings variability over the lifetime as a potential explanation for poor retirement prospects. Thus two workers having identical levels of average lifetime earnings might have had very different patterns of earnings variability over their lifetimes. Such differences could translate into quite different retirement wealth outcomes. We evaluate the effect of earnings variability on retirement wealth using information supplied by respondents to the Health and Retirement Study (HRS). This is a rich and nationally representative dataset on Americans on the verge of retirement, with responses linked to administrative records from the Social Security Administration. Our research illuminates key links between lifetime earnings variability and retirement wealth
Breast MRI and tumour biology predict axillary lymph node response to neoadjuvant chemotherapy for breast cancer
Computational approaches identify a transcriptomic fingerprint of drug-induced structural cardiotoxicity
Structural cardiotoxicity (SCT) presents a high-impact risk that is poorly tolerated in drug discovery unless significant benefit is anticipated. Therefore, we aimed to improve the mechanistic understanding of SCT. First, we combined machine learning methods with a modified calcium transient assay in human-induced pluripotent stem cell-derived cardiomyocytes to identify nine parameters that could predict SCT. Next, we applied transcriptomic profiling to human cardiac microtissues exposed to structural and non-structural cardiotoxins. Fifty-two genes expressed across the three main cell types in the heart (cardiomyocytes, endothelial cells, and fibroblasts) were prioritised in differential expression and network clustering analyses and could be linked to known mechanisms of SCT. This transcriptomic fingerprint may prove useful for generating strategies to mitigate SCT risk in early drug discovery
Computational approaches identify a transcriptomic fingerprint of drug-induced structural cardiotoxicity
Structural cardiotoxicity (SCT) presents a high-impact risk that is poorly tolerated in drug discovery unless significant benefit is anticipated. Therefore, we aimed to improve the mechanistic understanding of SCT. First, we combined machine learning methods with a modified calcium transient assay in human-induced pluripotent stem cell-derived cardiomyocytes to identify nine parameters that could predict SCT. Next, we applied transcriptomic profiling to human cardiac microtissues exposed to structural and non-structural cardiotoxins. Fifty-two genes expressed across the three main cell types in the heart (cardiomyocytes, endothelial cells, and fibroblasts) were prioritised in differential expression and network clustering analyses and could be linked to known mechanisms of SCT. This transcriptomic fingerprint may prove useful for generating strategies to mitigate SCT risk in early drug discovery
Risk factors and knowledge associated with high unintended pregnancy rates and low family planning use among pregnant women in Papua New Guinea
Unintended pregnancy is a major driver of poor maternal and child health in resource-limited settings. Data on pregnancy intention and use of family planning (FP) is scarce in Papua New Guinea (PNG), but are needed to inform public health strategies to improve FP accessibility and uptake. Data from a facility-based cross-sectional sample of 699 pregnant women assessed prevalence and predictors of unintended pregnancy and modern FP use among pregnant women in East New Britain Province, PNG. More than half (55%) the women reported their pregnancy as unintended. Few (18%) reported ever having used a modern FP method, and knowledge of different methods was low. Being single, separated or divorced (AOR 9.66; 95% CI 3.27-28.54), educated to a tertiary or vocational level (AOR 1.78 CI 1.15-2.73), and gravidity>1 (AOR 1.43 for each additional pregnancy CI 1.29-1.59) were associated with unintended pregnancy; being accompanied by a male partner to ANC was associated with a reduced unintended pregnancy (0.46 CI 0.30-0.73). Factors associated with modern FP use included male partner involvement (AOR 2.26 CI 1.39-3.67) and gravidity>1 (AOR 1.54 for each additional pregnancy CI 1.36-1.74). FP use also varied by the facility women attended. Findings highlight an urgent need for targeted interventions to improve FP knowledge, uptake and access, and male partner involvement, to reduce unintended pregnancies and their complications
The Clinical Applications of a Systems Approach
In the second of a two part series, Ahn and colleagues provide a practical discussion of how a systems approach will affect clinical medicine, using diabetes as an example
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