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The article of record as published may be found at https://doi.org/10.1080/10242694.2015.1005897 ; This study investigates the effect that US medical personnel deaths in combat have on other unit deaths and 'mili- tary success,' which we measure using commendation medals as a proxy. We use a difference-in-differences identi- fication strategy, measuring the changes over time in these outcomes following the combat loss of a medic or doctor and comparing it to the changes following the combat loss of a soldier who is not a medic or doctor. We find that overall unit deaths decrease in the five or ten days following the deaths of medical personnel in Vietnam, Korea, and the Pacific theater in World War II (WWII). In contrast, the WWII European and North African results indicate that overall unit deaths rise following medical personnel deaths. We find no relationship between medical personnel deaths and other unit deaths in Iraq and Afghanistan. For Korea and the Pacific theater of WWII, our estimates suggest unit commendation medals decrease following the deaths of medical personnel. This pattern of evidence is consistent with a model in which units often halted aggressive tactical maneuvers and reduced pursuit of their military objectives until deceased medical personnel were replaced. The results for the other conflicts are mixed and show little connection between medical personnel deaths and commendation medals.

AbstractThe conclusions about the association of maternal pregnancy environment, occupation, and benzene compounds with fetal CHD are not entirely consistent. Eight hundred seven CHD cases and 1008 controls were included in this study. All occupations were classified and coded against the Occupational Classification Dictionary of the People's Republic of China (2015 version). Logistic regressions were used to explore the correlation among environmental factors, occupation types, and CHDs in offspring. We found that living near public facilities and having exposure to chemical reagents and hazardous substances were significant risk factors for CHDs in offspring. We found that offspring of mothers who worked in agriculture and similar work during pregnancy suffered from CHD. The risk of all CHDs in the offspring of pregnant women working in production manufacturing and related work was significantly higher than that in unemployed pregnant women, the risk was also observed in 4 subtypes of CHDs. We compared the concentrations of the five metabolite (MA, mHA, HA, PGA, and SPMA) levels of benzene compounds in the urine of mothers in case and control groups and found no significant differences. Our study suggests that maternal exposure during pregnancy and certain environmental and occupational conditions are risk factors for CHD in offspring, but did not support an association between concentrations of metabolites of benzene compounds in the urine of pregnant women and CHDs in their offspring.

Smoking has a substantial impact on deaths from non-communicable chronic diseases (NCDs). Quantitatively measuring the impact of tobacco control on population health is of great theoretical and practical importance, for governments to make health policy decisions. Focusing on premature deaths, we predicted the deaths by 2030 from major NCDs caused by smoking among people aged 30–69 years in Sichuan Province, Southwest China. We extracted data for 1990–2015 from the Global Burden of Disease Study 2015 and calculated the population attributable fraction, to estimate the proportion of deaths caused by smoking. Four different tobacco control standards were used to estimate 2030 projections for the prevalence of smoking and premature mortality. If smoking prevalence were reduced by 30% from 2015 levels, premature mortality could be expected to decline by 24.4% in 2030, achieving 81.3% of the World Health Organization target for reducing premature mortality by 30%. Compared with the continuation of historical trends, the strongest tobacco control policy scenario would reduce premature mortality by 6.6%, prevent 23,600 deaths, reduce mortality by 7.8%, and increase life expectancy at birth by 0.3 years. Smoking bans represent an important action toward achieving national health goals.

Abstract
To investigate the correlation between maternal manganese and iron concentrations and the risk of CHD among their infant. A multi-center hospital-based case control study was conducted in China. There were 322 cases and 333 controls have been selected from pregnant women who received prenatal examinations. Correlations between CHDs and maternal manganese and iron concentrations were estimated by conditional logistic regression. Moreover, the interaction between manganese and iron on CHDs was analyzed. Compared with the controls, mothers whose hair manganese concentration was 3.01 μg/g or more were more likely to have a child with CHD than those with a lower concentration. The adjusted OR was 2.68 (95%CI = 1.44–4.99). The results suggested that mothers whose iron content was 52.95 μg/g or more had a significantly higher risk of having a child with CHD (aOR = 2.87, 95%CI = 1.54–5.37). No interaction between maternal manganese and iron concentrations was observed in the multiplicative or additive model. The concurrently existing high concentration of manganese and iron may bring higher risk of CHD (OR = 7.02). Women with excessive manganese concentrations have a significantly increased risk of having offspring with CHDs. The high maternal iron status also correlates with CHDs. The concurrently existing high concentration of manganese and iron may bring higher risk of CHD.

AbstractThe Poisson ridge estimator (PRE) is a commonly used parameter estimation method to address multicollinearity in Poisson regression (PR). However, PRE shrinks the parameters toward zero, contradicting the real association. In such cases, PRE tends to become an insufficient solution for multicollinearity. In this work, we proposed a new estimator called the Poisson average maximum likelihood‐centered penalized estimator (PAMLPE), which shrinks the parameters toward the weighted average of the maximum likelihood estimators. We conducted a simulation study and case study to compare PAMLPE with existing estimators in terms of mean squared error (MSE) and predictive mean squared error (PMSE). These results suggest that PAMLPE can obtain smaller MSE and PMSE (i.e., more accurate estimates) than the Poisson ridge estimator, Poisson Liu estimator, and Poisson K‐L estimator when the true s have the same sign and small variation. Therefore, we recommend using PAMLPE to address multicollinearity in PR when the signs of the true s are known to be identical in advance.