Exploring the Link between Altitude of Residence and Smoking Patterns in the United States.

INTRODUCTION: Smoking-related diseases affect 16 million Americans, causing approximately 480,000 deaths annually. The prevalence of cigarette smoking varies regionally across the United States, and previous research indicates that regional rates of smoking-related diseases demonstrate a negative association with altitude. The purpose of this study was to determine the relationship between altitude and the prevalence of cigarette smoking by county (N = 3106) in the United States. We hypothesized that smoking prevalence among adults would be negatively associated with mean county altitude. METHODS: A multivariate linear regression was performed to examine the relationship between county-level mean altitude and county smoking rate. Covariates were individually correlated with 2020 smoking data, and significant associations were included in the final model. RESULTS: The multivariate linear regression indicated that the county-level smoking rates are significantly reduced at high altitudes (p < 0.001). The model accounted for 89.5% of the variance in smoking prevalence, and for each 1000-foot increase in altitude above sea level, smoking rates decreased by 0.143%. Based on multivariate linear regression, the following variables remained independently and significantly associated: race, sex, educational attainment, socioeconomic status, unemployment, physical inactivity, drinking behavior, mental distress, and tobacco taxation. CONCLUSIONS: Our results indicate that smoking rates are negatively associated with altitude, which may suggest that altitude affects the pharmacokinetics, pharmacodynamics, and mechanistic pathways involved in cigarette use. Further research is needed to explore the relationship between altitude and smoking and how altitude may serve as a protective factor in the acquisition and maintenance of tobacco use disorders.

Detailed assessment of suicidal ideation in youth with bipolar disorder versus major depressive disorder.

OBJECTIVES: There is a critical need to better understand the factors underlying the increased suicide risk for youth with bipolar disorder (BD) in order to develop targeted prevention efforts. This study aimed to examine differences in characteristics of suicide ideation (SI) in youth with BD compared to youth with major depressive disorder (MDD) that may be associated with increased suicide risk. METHODS: One hundred and fifty-one participants (92 MDD and 59 BD), ages 13-21, completed a diagnostic interview and clinical assessments. Lifetime symptoms of SI and SA were assessed using the Columbia Suicide Severity Rating Scale. Ordinal logistic regression models were used to investigate whether the diagnostic group predicted the severity and intensity of the most severe or most common SI with the age of onset, age, and gender as covariates. RESULTS: Compared to MDD youth, BD youth were more likely to report experiencing more severe SI, p = 0.039, experiencing the most severe SI more frequently, p = 0.002, having less control of the most severe SI, p = 0.012, and that deterrents were less likely to stop them from acting on the most severe SI, p = 0.006. CONCLUSION: This study highlights differences in the severity and intensity of SI in youth with BD and suggests that youth with BD have greater difficulty inhibiting thoughts of SI which may lead to less resistance to suicide action. Findings underscore the need for a more detailed assessment of SI in youth with BD to better understand SI as a proximal risk factor for future SA and a potential target for intervention.

Effect of Altitude on Veteran Suicide Rates.

Aims: Suicide rates in the general population in the United States are correlated with altitude. To explore factors contributing to suicide among military veterans, we examined the relationship between veteran state-level suicide rates and altitude for 2014, including firearm-related and nonfirearm-related rates. Methods: Pearson's coefficients were calculated for altitude and each outcome. Mixed linear models were used to determine the association between suicide and altitude while adjusting for demographic confounds. Results: State mean altitude was significantly correlated with total veteran suicide rate (r = 0.678, p < 0.0001), veteran firearm-related suicide rate (r = 0.578, p < 0.0001), and veteran nonfirearm suicide rate (r = 0.609, p < 0.0001). In mixed models, altitude was significantly correlated with total veteran suicide rate (ß = 0.331, p < 0.05), veteran firearm suicides (ß = 0.282, p < 0.05), and veteran nonfirearm suicides (ß = 0.393, p < 0.05). Conclusion: This study adds to evidence linking altitude and suicide rates, arguing for additional research into the relationship between altitude and suicide among veterans.