Achieving health equity in US suicides: a narrative review and commentary.

Suicide rates in the United States (US) reached a peak in 2018 and declined in 2019 and 2020, with substantial and often growing disparities by age, sex, race/ethnicity, geography, veteran status, sexual minority status, socioeconomic status, and method employed (means disparity). In this narrative review and commentary, we highlight these many disparities in US suicide deaths, then examine the possible causes and potential solutions, with the overarching goal of reducing suicide death disparities to achieve health equity.The data implicate untreated, undertreated, or unidentified depression or other mental illness, and access to firearms, as two modifiable risk factors for suicide across all groups. The data also reveal firearm suicides increasing sharply and linearly with increasing county rurality, while suicide rates by falls (e.g., from tall structures) decrease linearly by increasing rurality, and suicide rates by other means remain fairly constant regardless of relative county urbanization. In addition, for all geographies, gun suicides are significantly higher in males than females, and highest in ages 51-85 + years old for both sexes. Of all US suicides from 1999-2019, 55% of male suicides and 29% of female suicides were by gun in metropolitan (metro) areas, versus 65% (Male) and 42% (Female) suicides by gun in non-metro areas. Guns accounted for 89% of suicides in non-metro males aged 71-85 + years old. Guns (i.e., employment of more lethal means) are also thought to be a major reason why males have, on average, 2-4 times higher suicide rates than women, despite having only 1/4-1/2 as many suicide attempts as women. Overall the literature and data strongly implicate firearm access as a risk factor for suicide across all populations, and even more so for male, rural, and older populations.To achieve the most significant results in suicide prevention across all groups, we need 1) more emphasis on policies and universal programs to reduce suicidal behaviors, and 2) enhanced population-based strategies for ameliorating the two most prominent modifiable targets for suicide prevention: depression and firearms.

Effect of medical student debt on mental health, academic performance and specialty choice: a systematic review.

OBJECTIVES: With the high and rising total cost of medical school, medical student debt is an increasing concern for medical students and graduates, with significant potential to impact the well-being of physicians and their patients. We hypothesised that medical student debt levels would be negatively correlated with mental health and academic performance, and would influence career direction (ie, medical specialty choice). DESIGN: We performed a systematic literature review to identify articles that assessed associations between medical student mental health, academic performance, specialty choice and debt. The databases PubMed, Medline, Embase, Scopus and PsycINFO were searched on 12 April 2017, for combinations of the medical subject headings Medical Student and Debt as search terms. Updates were incorporated on 24 April 2019. RESULTS: 678 articles were identified, of which 52 met the inclusion criteria after being reviewed in full text. The majority of studies were conducted in the USA with some from Canada, New Zealand, Scotland and Australia. The most heavily researched aspect was the association between medical student debt and specialty choice, with the majority of studies finding that medical student debt was associated with pursuit of higher paying specialties. In addition, reported levels of financial stress were high among medical students, and correlated with debt. Finally, debt was also shown to be associated with poorer academic performance. CONCLUSIONS: Medical student debt levels are negatively associated with mental well-being and academic outcomes, and high debt is likely to drive students towards choosing higher paying specialties. Additional prospective studies may be warranted, to better understand how educational debt loads are affecting the well-being, career preparation and career choices of physicians-in-training, which may in turn impact the quality of care provided to their current and future patients.

Development of a PCR-based strategy for CYP2D6 genotyping including gene multiplication of worldwide potential use.

There is growing consensus on the potential use of pharmacogenetics in clinical practice, and hopes have been expressed for application to the improvement of global health. However, two major challenges may lead to widening the "biotechnological gap" between the developing and the industrial world; first the unaffordability of some current technologies for poorer countries, and second the necessity of analyzing all described alleles for every clinical case due to the inability to predict the ethnic group of a given patient. Because of its role in the metabolism of a number of drugs, cytochrome P450 2D6 (CYP2D6) is an excellent candidate for use in the optimization of drug therapy. CYP2D6 is a highly polymorphic gene locus with more than 50 variant alleles, and subjects can be classified as poor metabolizers (PM), extensive metabolizers (EM), or ultrarapid metabolizers (UM) of a given CYP2D6 substrate. Several strategies and methods for CYP2D6 genotyping exist. Some, however, are expensive and laborious. The aim of this study was to design a PCR-based genotyping methodology to allow rapid, straightforward, and inexpensive identification of 90%-95% of CYP2D6 PM or UM genotypes for routine clinical use, independent of the individual's ethnic group. CYP2D6 is amplified in initial extra long PCRs (XL-PCRs), which subsequently undergo fragment-length polymorphism analysis for the determination of carriers of CYP2D6 allelic variants. The same XL-PCRs are also used for the determination of CYP2D6 multiplication and 2D6*5 allele (abolished activity). The application of this new strategy for the detection of CYP2D6 mutated alleles and multiplications to routine clinical analysis will enable the PM and UM phenotypes to be predicted and identified at a reasonable cost in a large number of individuals at most locations.