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Substance use continues to contribute to significant morbidity and mortality in the United States, for both women and men, more so than any other preventable health condition. To reduce the public health burden attributable to substances, the National Institute on Drug Abuse and the National Institute on Alcohol Abuse and Alcoholism have identified that medication development for substance use disorder is a high priority research area. Furthermore, both Institutes have stated that research on sex and gender differences in substance use medication development is a critical area. The purpose of the current narrative review is to highlight how sex and gender have been considered (or not) in medication trials for substance use disorders to clarify and summarize what is known regarding sex and gender differences in efficacy and to provide direction to the field to advance medication development that is consistent with current NIH ‘sex as a biological variable’ (SABV) policy. To that end, we reviewed major classes of abused substances (nicotine, alcohol, cocaine, cannabis, opioids) demonstrating that, sex and gender have not been well-considered in addiction medication development research. However, when adequate data on sex and gender differences have been evaluated (i.e., in tobacco cessation), clinically significant differences in response have been identified between women and men. Across the other drugs of abuse reviewed, data also suggest sex and gender may be predictive of outcome for some agents, although the relatively low representation of women in clinical research samples limits making definitive conclusions. We recommend the incorporation of sex and gender into clinical care guidelines and improved access to publicly available sex-stratified data from medication development investigations. Highlights Substance use continues to contribute to significant morbidity and mortality in the United States. To reduce the public health burden attributable to substances, the National Institute on Drug Abuse and the National Institute on Alcohol Abuse and Alcoholism have identified that medication development for substance use disorder is a high priority research area. We reviewed major classes of abused substances (nicotine, alcohol, cocaine, cannabis, opioids) demonstrating that, sex and gender have not been well-considered in addiction medication development research. When adequate data on sex and gender differences have been evaluated (i.e., in tobacco cessation), clinically significant differences in response have been identified between women and men. However, these data are not at all considered in clinical care guidelines. We recommend improved access to publicly available sex-stratified data from medication development investigations, to inform clinical practice and to improve treatment provided to women with substance use disorders.

Purpose of Review We review recent research (2018–2023) on gender differences in suicidal behaviors (i.e., suicidal ideations and attempts, death by suicide). We examine research studies in the following areas: developmental period, substance use, and special populations (Veterans, sexual and gender minorities). Recent Findings Novel results were found in these different areas. For example, suicide rates for female youth are increasing at a faster rate relative to male youth. Further, some evidence suggests that heavy alcohol use/binge drinking is a significant and growing risk factor for suicidal behaviors in women. Military service may be a more significant risk factor for suicidal behaviors among male Veterans compared to female Veterans. Additionally, suicide rates are rising for gender minority youth/young adults. Summary Recent research on gender differences in suicide outcomes demonstrates findings that align with previous research, as well as new insights on this important topic.

While exposure to nicotine during developmental periods can significantly affect brain development, studies examining the association between maternal smoking and autism spectrum disorder (ASD) in offspring have produced conflicting findings, and prior meta-analyses have found no significant association. Our meta-analysis used a novel approach of investigating population-level smoking metrics as moderators. The main meta-analysis, with 22 observational studies comprising 795,632 cases and 1,829,256 control participants, used a random-effects model to find no significant association between maternal smoking during pregnancy and ASD in offspring (pooled odds ratio (OR) = 1.16, 95% CI: 0.97–1.40). However, meta-regression analyses with moderators were significant when we matched pooled ORs with adult male smoking prevalence ( z  = 2.55, p  = 0.01) in each country, using World Health Organization data. Our study shows that using population-level smoking metrics uncovers significant relationships between maternal smoking and ASD risk. Correlational analyses show that male smoking prevalence approximates secondhand smoke exposure. While we cannot exclude the possibility that our findings reflect the role of paternal or postnatal nicotine exposure, as opposed to maternal or in utero nicotine exposure, this study underlines the importance of investigating paternal and secondhand smoking in addition to maternal smoking in ASD.

The correlates of legally significant outcomes that have been identified in people with mental disorders are of limited value in understanding the mechanisms by which these outcomes occur. To describe the relationships between mental disorder, impaired psychosocial function, and three legally significant outcomes in a representative sample of the US population. We used a population survey, the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III, sample size 36,309), to identify people who self-reported serious trouble with the police or the law over the past 12 months and two lifetime outcomes, being incarcerated and engaging in violence to others. DSM-5 categories were generated using the Alcohol Use Disorder and Associated Disabilities Interview Schedule-5. Psychosocial function was assessed using social and role-emotional function scores of the 12-Item Short-Form Health Survey Version 2. Participants with mental disorder, but not people with no diagnosis, who reported serious trouble with the police or with the law during the previous 12 months reported significantly worse psychosocial function than those who did not report such trouble. The size of the statistical effect varied by diagnosis, moderate for some forms of mental illness and for alcohol abuse and nonsignificant for drug abuse and the personality disorders. Effect sizes were largest for diagnoses where legally significant outcomes were least common. The effect of impaired psychosocial function, for instance in disrupting family and social networks that would otherwise protect against these legally significant outcomes, warrants further investigation in studies with longitudinal designs.

Although the use of nondrug rewards (e.g., money) to facilitate smoking cessation is widespread, recent research has found that such rewards may be least effective when people who smoke cigarettes are tempted to do so. Specifically, among people who smoke, the neural response to nondrug rewards appears blunted when access to cigarettes is anticipated, and this blunting is linked to a decrease in willingness to refrain from smoking to earn a monetary incentive. Accordingly, methods to enhance the value of nondrug rewards may be theoretically and clinically important. The current proof-of-concept study tested if real-time fMRI neurofeedback training augments the ability to upregulate responses in reward-related brain areas relative to a no-feedback control condition in people who smoke. Adults ( n = 44, age range = 20-44) who reported smoking >5 cigarettes per day completed the study. Those in the intervention group ( n = 22, 5 females) were trained to upregulate brain responses using feedback of ongoing striatal activity (i.e., a dynamic “thermometer” that reflected ongoing changes of fMRI signal intensity in the striatum) in a single neurofeedback session with three training runs. The control group ( n = 22, 5 females) underwent a nearly identical procedure but received no neurofeedback. Those who received neurofeedback training demonstrated significantly greater increases in striatal BOLD activation while attempting to think about something rewarding compared to controls, but this effect was present only during the first training run. Future neurofeedback research with those who smoke should explore how to make neurofeedback training more effective for the self-regulation of reward-related brain activities.

The correct version of the table is below. Description of sample: diagnosis and outcomes variables (n = 36,293) Diagnosis Serious legal trouble past 12 m Lifetime incarceration Lifetime violence to others n 12m n life n (%) OR (95% CI) c n (%) OR (95% CI) c n (%) OR (95% CI) c No diagnosis 22618 17775 154 (0.7%) Ref 809 (4.6%) Ref 1660 (9.4%) Ref Any SU, MI or PD 13675 18518 502 (3.7%) 6.1*** (5.1; 7.4) 3321 (18.0%) 4.7*** (4.2; 5.2) 6547 (35.4%) 4.9*** (4.5; 5.3) Any SU or MI 12126 17755 467 (3.9%) 6.4*** (5.3; 7.7) 3181 (18%) 4.7*** (4.2; 5.2) 6117 (34.5%) 4.7*** (4.3; 5.1) Any MI or PD 10797 13843 394 (3.6%) 6.2*** (5.2; 7.5) 2402 (17.4%) 4.5*** (4.0; 5.1) 5419 (39.2%) 5.8*** (5.3; 6.2) Any SU or PD 9514 13219 462 (4.9%) 8.3*** (6.9; 10.0) 3034 (23.1%) 6.3*** (5.6; 7.1) 5681 (43.1%) 6.6*** (6.1; 7.2) Comorbid SU and MI 2214 5470 171 (7.7%) 14.0*** (11.3; 17.4) 1428 (26.2%) 7.4*** (6.6; 8.4) 2743 (50.2%) 8.8*** (8.1; 9.7) Comorbid SU and PD 2039 3455 205 (10.1%) 19.5*** (15.7; 24.2) 1287 (37.4%) 13.2*** (11.5; 15.2) 2522 (73.0%) 24.3*** (21.5; 27.5) Comorbid MI and PD 3480 4198 207 (5.9%) 10.6*** (8.5; 13.3) 1186 (28.3%) 8.9*** (7.8; 10.3) 1665 (20.6%) 17.3*** (15.4; 19.4) Comorbid SU and PD and MI 1323 2671 132 (10.0%) 19.0*** (14.6; 24.6) 963 (36.1%) 12.4*** (10.7; 14.5) 1944 (72.8%) 23.7*** (20.8; 26.9) Any MI 8532 12296 286 (3.4%) 5.6*** (4.6; 6.9) 1938 (15.8%) 4.0*** (3.6; 4.5) 4411 (35.9%) 5.0*** (4.6; 5.4) Schizophrenia/Psychosis 337 902 28 (8.3%) 17.5*** (10.6; 28.9) 218 (24.2%) 6.5*** (4.9; 8.6) 381 (42.2%) 6.9*** (5.3; 9.0) Any Mood Disorder 4894 8639 198 (4.0%) 7.1*** (5.7; 8.9) 1382 (16.1%) 4.1*** (3.6; 4.6) 3252 (37.7%) 5.4*** (4.9; 5.8) Major Depression 3961 7430 149 (3.8%) 6.6*** (5.1; 8.4) 1061 (14.4%) 3.5*** (3.1; 4.0) 2584 (34.8%) 4.7*** (4.3; 5.2) Persistent Depressive 1185 2017 52 (4.4%) 7.6*** (5.4; 10.8) 371 (18.5%) 5.0*** (4.2; 5.9) 849 (42.3%) 6.7*** (5.8; 7.7) Bipolar 1 565 752 37 (6.5%) 12.7*** (8.0; 20.1) 235 (31.5%) 9.8*** (7.6; 12.5) 491 (65.5%) 17.0*** (14.0; 20.7) Any Anxiety Disorder 4700 5989 155 (3.3%) 5.5*** (4.3; 7.0) 1108 (16.9%) 4.3*** (3.8; 4.9) 2313 (38.7%) 5.6*** (5.1; 6.2) Specific Phobia 2035 2279 51 (2.5%) 4.3*** (3.0; 6.2) 353 (15.5%) 3.9*** (3.2; 4.6) 853 (37.5%) 5.4*** (4.7; 6.2) Social Anxiety 980 1255 37 (3.8%) 5.9*** (3.9; 8.9) 274 (22.0%) 5.9*** (4.9; 7.2) 552 (44.1%) 7.0*** (6.0; 8.3) Panic 1103 1811 52 (4.7%) 7.0*** (4.7; 10.3) 353 (19.6%) 5.2*** (4.2; 6.3) 797 (44.1%) 6.9*** (6.1; 7.9) Agoraphobia 549 690 22 (4.0%) 6.1*** (3.5; 10.6) 158 (23.1%) 6.3*** (4.8; 8.3) 342 (49.7%) 8.4*** (7.0; 10.1) Generalized Anxiety 1908 2708 82 (4.3%) 7.2*** (5.2; 10.0) 505 (18.7%) 4.8*** (4.1; 5.6) 1170 (43.2%) 6.7*** (6.0; 7.6) Posttraumatic Stress 1778 2337 87 (4.9%) 7.7*** (5.6; 10.6) 531 (22.8%) 6.3*** (5.4; 7.4) 1248 (53.4%) 9.8*** (8.7; 11.1) Eating Disordera 385 615 6 (1.6%) 2.3 (1.0; 5.6) 89 (14.5%) 3.8*** (2.7; 5.2) 251 (40.8%) 6.2*** (5.1; 7.5) Any Substance Use Disorder 5808 10929 352 (6.1%) 10.5*** (8.6; 12.7) 2671 (24.6%) 6.7*** (6.0; 7.6) 4449 (40.8%) 6.1*** (5.5; 6.7) Alcohol Abuse 5133 10000 306 (6.0%) 10.2*** (8.3; 12.5) 2388 (24.0%) 6.6*** (5.8; 7.4) 4032 (40.4%) 6.0*** (5.4; 6.6) Drug Abuse 1487 3548 154 (10.4%) 19.9*** (15.5; 25.5) 1342 (38.1%) 13.1*** (11.3; 15.1) 1960 (55.4%) 11.2*** (9.9; 12.5) Any personality disorderb NA 5745 315 (5.5%) 10.6*** (8.3; 13.5) 1650 (28.8%) 9.1*** (8.0; 10.4) 3754 (65.3%) 17.3*** (15.6; 19.1) Borderlineb NA 4300 250 (5.8%) 11.3*** (8.9; 14.3) 1240 (28.9%) 9.4*** (8.2; 10.7) 2911 (67.7%) 19.4*** (17.4; 21.7) Antisocialb NA 1600 132 (8.3%) 16.6*** (12.2; 22.6) 714 (44.8%) 18.5*** (15.7; 21.8) 1356 (84.8%) 49.8*** (41.8; 59.4) Schizotypalb NA 2438 148 (6.1%) 12.7*** (9.7; 16.6) 685 (28.2%) 8.8*** (7.4; 10.5) 1522 (62.4%) 15.0*** (13.1; 17.1) Sample is limited to people with data on functional impairment. Lower scores indicate poorer perceived functioning. *p<.05, **p<.01, ***p<.001. a Includes bulimia, anorexia nervosa. b Only lifetime personality disorder diagnoses are available. c Data weighted to adjust for non-response.

Background Social determinants of health (SDOH) and clinical severity factors are known to shape substance use disorder (SUD) treatment outcomes, yet limited research has explored how these influences differ by sex. Understanding these differences is important to improving treatment equity and outcomes in publicly funded treatment systems. Methods This study analyzed data from the 2018–2022 Treatment Episode Data Set-Discharges (TEDS-D), a national dataset of adults discharged from publicly funded SUD treatment programs. Sex-stratified binary logistic regressions were used to examine predictors of two outcomes: treatment non-completion and substance use at discharge. Predictors included SDOH (i.e., employment, education level, housing status, criminal justice involvement, prior treatment history, marital status, health insurance coverage and treatment duration) and indicators of SUD severity (e.g., age at first use, polysubstance use, and co-occurring psychiatric disorders). Results Both SDOH and clinical severity indicators were significantly associated with poorer treatment outcomes, with distinct patterns by sex. Women showed more consistent risk for poor treatment outcomes across predictors, including unemployment, psychiatric comorbidities, and polysubstance use, while lack of prior treatment history was the strongest predictor of substance use at discharge and dropout for men. Other predictors, such as housing instability, criminal justice involvement, and later-onset substance use, were also associated with increased risk of non-abstinence and dropout, with notable sex differences. Health insurance coverage was associated with better outcomes for both sexes, with the protective effect more consistent in women. Conclusions These findings emphasize the need for sex-informed treatment approaches that address both social determinants of health and clinical complexity. Tailoring care to the unique risks and contexts of men and women may improve retention and reduce substance use at discharge, particularly in publicly funded systems. Highlights We examined social determinants of health (SDOH), and substance use disorder (SUD) severity-related predictors of substance use and treatment completion in a national sample of approximately 7 million adults. Women demonstrated more consistent vulnerability across predictors, including unemployment, co-occurring psychiatric disorders, and polysubstance use. For men, lack of prior treatment for SUD was the most consistent predictor for substance use at discharge and treatment dropout. Housing instability, access to healthcare, and financial barriers showed sex-specific effects, with women generally experiencing great risk of unsuccessful treatment. Findings highlight the importance of improving SUD care to address sex-specific risks and structural barriers, especially in publicly funded systems. Plain English Summary Substance use treatment is not a one-size-fits-all process. Recovery is shaped by both structural challenges, such as housing instability or limited access to care, and the clinical severity of substance use. These factors influence whether someone completes treatment and stays abstinent, and they often affect men and women in different ways. In this study, we analyzed data from approximately 7 million publicly funded substance use treatment episodes across the United States. We looked at how social determinants of health (e.g. employment status, education, housing, access to treatment) and clinical factors (e.g. age of substance use onset, psychiatric comorbidities and polysubstance use), were associated with two key outcomes: whether a person completed treatment and whether they reported use of their primary substance at the end of care. We found that women often faced greater challenges, especially regarding unemployment, co-occurring mental health conditions and using more than one type of substance. For men, being new to treatment was a strong predictor of poorer treatment success. These findings demonstrate the need for treatment programs to offer support that meets men and women where they are, considering the different barriers and challenges each group may face along the path to sustained recovery.

Introduction: Sex differences exist in tobacco smoking. Women have greater difficulty quitting smoking than men. Tobacco smoking is driven by the reinforcing effects of nicotine, the primary addictive component in cigarettes. Nicotine binds to nicotinic acetylcholine receptors facilitating dopamine release in striatal and cortical brain regions. Dysregulated dopamine D2/3 receptor signaling in dorsolateral prefrontal cortex (dlPFC) is associated with cognitive deficits such as impairments in attention, learning, and inhibitory control that impede quit attempts. Sex steroid hormones such as estradiol and progesterone, influence drug-taking behaviors, through dopaminergic actions, suggesting that their influence may explain sex differences in tobacco smoking. The goal of this study was to relate dlPFC dopamine metrics to sex steroid hormone levels in people who smoke and healthy controls. Methods: Twenty-four (12 women) people who smoke cigarettes and 25 sex- and age-matched controls participated in two same-day [11C]FLB457 positron emission tomography scans, one before and one after amphetamine administration. D2R availability (BPND) at baseline and after amphetamine administration were calculated. On the same day, plasma samples were collected for analysis of sex steroid hormone levels: estradiol, progesterone, and free testosterone. Results: Women who smoke had trending lower levels of estradiol than sex-matched counterparts. Men who smoke had higher levels of estradiol and trending higher levels of free testosterone than sex-matched counterparts. In women only, lower estradiol was significantly associated with lower pre-amphetamine dlPFC BPND. Discussion/Conclusions: This study demonstrated that lower estradiol is associated with lower dlPFC D2R availability in women which may underlie difficulty resisting smoking.