Moral injury and quality of life among military veterans.

INTRODUCTION: Moral injury concerns transgressive harms and the outcomes that such experiences may cause. A gap in the literature surrounding moral injury, and an outcome that may be important to include in the mounting evidence toward the need for the formal clinical acknowledgement of moral injury, has to do with the relationship between moral injury and quality of life. No studies have examined this relationship in US military veterans-a population that is disproportionately exposed to potentially morally injurious events. METHODS: A nationwide cross-sectional survey was conducted yielding 1495 military veterans. Participants were asked questions about moral injury and quality of life, among other things. Multivariable linear regression was used to characterise the adjusted relationship between moral injury and quality of life. RESULTS: Moral injury (mean=40.1 out of 98) and quality-of-life (mean=69.5 out of 100) scores were calculated for the sample. Moral injury was inversely associated with quality of life in an adjusted model, indicating that worsening moral injury was associated with decreased quality of life (adjusted unstandardised beta coefficient (b)=-0.3, p<0.001). Results showed that age moderated said relationship, such that ageing veterans experienced an increasingly worse quality of life with increasingly severe moral injury (b=-0.1, p=0.003). CONCLUSIONS: Results of the study showed that moral injury was inversely associated with quality of life and that this relationship rapidly worsens with age. More work is needed to more precisely understand this relationship and to determine the best strategies for intervention.

Illicit drug use and self-reported vision loss among military service members or veterans.

INTRODUCTION: Little is known about differences in vision loss prevalence among service members or veterans (SMVs) and civilians; further, no study has compared vision loss risk factors in these two populations. As such, we seek to fill this gap in the literature. METHODS: In this cross sectional study, we obtained data on 106 SMVs and 1572 civilians from the 2013-2018 National Health and Nutrition Examination Surveys. We compared the prevalence of or mean values of vision loss risk factors between SMVs and civilians using the Wald χ2 statistic or Kruskal-Wallis test. Further, we examined the relative strength of 17 vision loss risk factors in predicting self-reported vision loss via Firth's logistic regression. RESULTS: SMVs had a significantly higher prevalence of illicit drug use (20.75% vs 13.62%) and HIV (1.89% vs 0.41%), while civilians had a higher prevalence of poor dietary habits (7.61% vs 13.21%). SMVs also had higher mean values of systolic blood pressure (125.85 vs 122.53 mmHg), pack years of cigarette smoking (8.29 vs 4.25), and sedentary minutes per day (379.15 vs 337.07 min). More SMVs (8.49%) self-reported vision loss than civilians (4.48%). After adjustment for covariates, illicit drug use (adjusted ß coefficient=0.72, p=0.02) was associated with self-reported vision loss. CONCLUSIONS: This study indicates that self-reported vision loss among SMVs is more prevalent than among civilians, and vision loss in SMVs is associated with severe or prolonged illicit drug use.

Inequality as a Powerful Predictor of Infant and Maternal Mortality around the World.

BACKGROUND: Maternal and infant mortality are highly devastating, yet, in many cases, preventable events for a community. The human development of a country is a strong predictor of maternal and infant mortality, reflecting the importance of socioeconomic factors in determinants of health. Previous research has shown that the Human Development Index (HDI) predicts infant mortality rate (IMR) and the maternal mortality ratio (MMR). Inequality has also been shown to be associated with worse health in certain populations. The main purpose of the present study was to determine the correlation and predictive power of the Inequality Adjusted Human Development Index (IHDI) as a measure of inequality with the Infant Mortality Rate (IMR), Maternal Mortality Rate (MMR), Early Neonatal Mortality Rate (ENMR), Late Neonatal Mortality Rate (LNMR), and the Post Neonatal Mortality Rate (PNMR). METHODS AND FINDINGS: Data for the present study were downloaded from two sources: infant and maternal mortality data were downloaded from the Global Burden of Disease 2013 Cause of Death Database and the Human Development Index (HDI) and Inequality-Adjusted Human Development Index (IHDI) data were downloaded from the United Nations Development Program (UNDP). Pearson correlation coefficients were estimated, following logarithmic transformations to the data, to examine the relationship between HDI and IHDI with MMR, IMR, ENMR, LNMR, and PNMR. Steiger's Z test for the equality of two dependent correlations was utilized in order to determine whether the HDI or IHDI was more strongly associated with the outcome variables. Lastly, we constructed OLS regression models in order to determine the predictive power of the HDI and IHDI in terms of the MMR, IMR, ENMR, LNMR, and PNMR. Maternal and infant mortality were both strongly and negatively correlated with both HDI and IHDI; however, Steiger's Z test for the equality of two dependent correlations revealed that IHDI was more strongly correlated than HDI with MMR (Z = 4.897, p < 0.001), IMR (Z = 2.524, p = 0.012), ENMR (Z = 2.936, p = 0.003), LNMR (Z = 2.272, p = 0.023), and PNMR (Z = 2.277, p = 0.023). Furthermore, side-by-side OLS regression models revealed that, when IHDI was used as the predictor variable instead of HDI, the R2 value was 0.053 higher for MMR, 0.025 higher for IMR, 0.038 higher for ENMR, 0.029 higher for LNMR, and 0.026 higher for PNMR. CONCLUSIONS: Even when both the HDI and the IHDI correlate with the infant and maternal mortality rates, the IHDI is a better predictor for these two health indicators. Therefore, these results add more evidence that inequality is playing an important role in determining the health status of various populations in the world and more efforts should be put into programs to fight inequality.