Increase in suicides the months after the death of Robin Williams in the US

Investigating suicides following the death of Robin Williams, a beloved actor and comedian, on August 11th, 2014, we used time-series analysis to estimate the expected number of suicides during the months following Williams’ death. Monthly suicide count data in the US (1999–2015) were from the Centers for Disease Control and Prevention Wide-ranging ONline Data for Epidemiologic Research (CDC WONDER). Expected suicides were calculated using a seasonal autoregressive integrated moving averages model to account for both the seasonal patterns and autoregression. Time-series models indicated that we would expect 16,849 suicides from August to December 2014; however, we observed 18,690 suicides in that period, suggesting an excess of 1,841 cases (9.85% increase). Although excess suicides were observed across gender and age groups, males and persons aged 30–44 had the greatest increase in excess suicide events. This study documents associations between Robin Williams’ death and suicide deaths in the population thereafter

Pre-eclampsia rates in the United States, 1980-2010: age-period-cohort analysis

Objective: To estimate the contributions of biological aging, historical trends, and birth cohort effects on trends in pre-eclampsia in the United States. Design: Population based retrospective study. Setting: National hospital discharge survey datasets, 1980-2010, United States. Participants: 120 million women admitted to hospital for delivery. Main outcome measures: Temporal changes in rates of mild and severe pre-eclampsia in relation to maternal age, year of delivery, and birth cohorts. Poisson regression as well as multilevel age-period-cohort models with adjustment for obesity and smoking were incorporated. Results: The rate of pre-eclampsia was 3.4%. The age-period-cohort analysis showed a strong age effect, with women at the extremes of maternal age having the greatest risk of pre-eclampsia. In comparison with women delivering in 1980, those delivering in 2003 were at 6.7-fold (95% confidence interval 5.6-fold to 8.0-fold) increased risk of severe pre-eclampsia. Period effects declined after 2003. Trends for severe pre-eclampsia also showed a modest birth cohort effect, with women born in the 1970s at increased risk. Compared with women born in 1955, the risk ratio for women born in 1970 was 1.2 (95% confidence interval 1.1 to 1.3). Similar patterns were also evident for mild pre-eclampsia, although attenuated. Changes in the population prevalence of obesity and smoking were associated with period and cohort trends in pre-eclampsia but did not explain the trends. Conclusions Rates of severe pre-eclampsia have been increasing in the United States and age-period-cohort effects all contribute to these trends. Although smoking and obesity have driven these trends, changes in the diagnostic criteria may have also contributed to the age-period-cohort effects. Health consequences of rising obesity rates in the United States underscore that efforts to reduce obesity may be beneficial to maternal and perinatal health

How healthy are survey respondents compared with the general population? Using survey-linked death records to compare mortality outcomes

Background: National surveys are used to capture US health trends and set clinical guidelines, yet the sampling frame often includes those in non-institutional households, potentially missing those most vulnerable for poor health. Declining response rates in national surveys also represent a challenge, and existing inputs to survey weights have limitations. We compared mortality rates between those who respond to surveys and the general population over time. Methods: Survey respondents from twenty waves of the National Health Interview Survey from 1990 through 2009 who have been linked to death records through 31 December 2011 were included. For each cohort in the survey, we estimated their mortality rates along with that cohort's mortality rate in the census population using vital statistics records and differences were examined using Poisson models. Results: In all years, survey respondents had lower mortality rates compared with the general population, when data were both weighted and unweighted. Among men, survey respondents in the weighted sample had 0.86 (95% C.I. 0.853-0.868) times the mortality rate of the general population (among women, RR=0.887; 95% C.I. 0.879-0.895). Differences in mortality are evident along all points of the life course. Differences have remained relatively stable over time. Conclusion: Survey respondents have lower death rates than the general US population, suggesting that they are a systematically healthier source population. Incorporating non-household samples and revised weighting strategies to account for sample frame exclusion and non-response may allow for more rigorous estimation of the US population's health

Work stress and alcohol consumption among adolescents: moderation by family and peer influences

Excessive alcohol use in adolescence can be detrimental to health and academic performance. Few studies consider the moderating effects of parental and peer influence within the context of adolescent work outside of the school environment. This study aims to examine work stress among adolescents and the association with alcohol use and drunkenness, in the context of parental and peer influences. Grade 12 students who participated in Monitoring the Future surveys between 2005 and 2009 (n = 12,341) were included in this study. Independent variables included work stress (job satisfaction, perceived safety, and perceived safety of possessions), self-reported perceptions towards academics and influence from parents and peers. Frequency of alcohol use and drunkenness were measured for lifetime, last 30 days and 12 months. The moderating effects of academic aspiration, parental, and peer influence were assessed on the relationship between work stress and alcohol use. Any work stress was positively associated with alcohol use over the past 12 months (odds ratio = 1.12, 95% confidence interval (CI) 1.02-1.23). Stratified analysis found that peer influence significantly moderated the relationship between work stress and alcohol use over the lifetime and past 12 months. Among adolescents with work stress, odds ratios of alcohol use over the lifetime was 0.83 (95% CI 0.71-0.97) for those with low negative peer influence and 1.09 (95% CI 0.97-1.22) for those with high negative peer influence. Problematic drinking patterns were more apparent among high school students who experienced stress at work. Positive peer influence, however, may buffer the adverse effect of work stress on alcohol use

Effects of minimum legal drinking age on alcohol and marijuana use: evidence from toxicological testing data for fatally injured drivers aged 16 to 25 years

Alcohol and marijuana are among the most commonly used drugs by adolescents and young adults. The question of whether these two drugs are substitutes or complements has important implications for public policy and prevention strategies, especially as laws regarding the use of marijuana are rapidly changing. Data were drawn from fatally injured drivers aged 16 to 25 who died within 1 h of the crash in nine states with high rates of toxicology testing based from 1999 to 2011 on the Fatality Analysis Reporting System (N = 7,191). Drug tests were performed using chromatography and radioimmunoassay techniques based on blood and/or urine specimens. Relative risk regression and Joinpoint permutation analysis were used. Overall, 50.5% of the drivers studied tested positive for alcohol or marijuana. Univariable relative risk modeling revealed that reaching the minimum legal drinking age was associated with a 14% increased risk of alcohol use (RR = 1.14, 95% CI: 1.02 to 1.28), a 24% decreased risk of marijuana use (RR = 0.76, 95% CI: 0.53 to 1.10), and a 22% increased risk of alcohol plus marijuana use (RR=1.22, 95% CI: 0.90 to 1.66). Joinpoint permutation analysis indicated that the prevalence of alcohol use by age is best described by two slopes, with a change at age 21. There was limited evidence for a change at age 21 for marijuana use. These results suggest that among adolescents and young adults, increases in alcohol availability after reaching the MLDA have marginal effect on marijuana use

Mortality from motorcycle crashes: the baby-boomer cohort effect

Background Motorcyclists are known to be at substantially higher risk per mile traveled of dying from crashes than car occupants. In 2014, motorcycling made up less than 1 % of person-miles traveled but 13 % of the total mortality from motor-vehicle crashes in the United States. We assessed the cohort effect of the baby-boomers (i.e., those born between 1946 and 1964) in motorcycle crash mortality from 1975 to 2014 in the United States. Methods Using mortality data for motorcycle occupants from the Fatality Analysis Reporting System, we performed an age-period-cohort analysis using the multiphase method and the intrinsic estimator method. Results Baby-boomers experienced the highest mortality rates from motorcycle crashes at age 20-24 years and continued to experience excess mortality after age 40 years. After removing the effects of age and period, the estimated mortality risk from motorcycle crashes for baby-boomers was 48 % higher than that of the referent cohort (those born between 1930 and 1934, rate ratio 1.48; 95 % CI: 1.01, 2.18). Results from the multiphase method and the intrinsic estimator method were consistent. Conclusions The baby-boomers have experienced significantly higher mortality from motorcycle crashes than other birth cohorts. To reduce motorcycle crash mortality, intervention programs specifically tailored for the baby-boomer generation are warranted

Age, period and cohort effects in frequent cannabis use among US students: 1991–2018

Background and AimsAs the legal status of cannabis changes across the United States and modes of administration expand, it is important to examine the potential impact on adolescent cannabis use. This study aimed to assess changes in prevalence of frequent cannabis use in adolescents in the United States and how far this varies by age and cohort.DesignAnalysis of Monitoring the Future, a nationally representative annual survey of 8th‐, 10th‐ and 12th‐grade students in the United States conducted from 1991 to 2018.SettingIn‐school surveys completed by US adolescents.ParticipantsA total of 1 236 159 8th‐, 10th‐ and 12th‐graders; 51.5% female, 59.6% non‐Hispanic white, 12.3% non‐Hispanic black, 13.4% Hispanic and 14.7% other race/ethnicity.MeasurementsFrequent cannabis use (FCU), defined as six or more occasions in the past 30 days, stratified by sex, race/ethnicity and parental education.FindingsFCU among US adolescents increased over the study period; the peak in 2010–18 was 11.4% among 18‐year‐old students. This increase was best explained by both period and cohort effects. Compared with respondents in 2005, adolescents surveyed in 2018 had period effects in FCU that were 1.6 times greater. Adolescents in younger birth cohorts (those born > 1988) had a lower increase in FCU than those born prior to 1988. Results were consistent across sex, parent education and race/ethnicity, with period effects indicating increasing FCU after 2005 and cohort effects indicating a lower magnitude of increase in more recent birth cohorts. Age and parental education disparities in FCU have increased over time, whereas race/ethnicity differences have converged over time; black students were 0.67 [95% confidence interval (CI) = 0.64–0.70] times as likely to use cannabis frequently as white students from 1991 to 2000, and 1.03 (95% CI = 0.98–1.09) times as likely from 2011 to 2018 (P‐value for time interaction < 0.001).ConclusionsThe prevalence of frequent cannabis use (FCU) increased from 1991 to 2018 among older adolescents in the United States. Racial/ethnic differences in FCU converged, whereas parental education differences have diverged.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151314/1/add14665_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151314/2/add14665.pd

Stigma as a fundamental hindrance to the United States opioid overdose crisis response.

Alexander Tsai and co-authors discuss the role of stigma in responses to the US opioid crisis

Cohort effects explain the increase in autism diagnosis among children born from 1992 to 2003 in California

The incidence and prevalence of autism have dramatically increased over the last 20 years. Decomposition of autism incidence rates into age, period and cohort effects disentangle underlying domains of causal factors linked to time trends. We estimate an age-period-cohort effect model for autism diagnostic incidence overall and by level of functioning

The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders

Although current classification systems have greatly contributed to the reliability of psychiatric diagnoses, they ignore the unique role of individual symptoms and, consequently, potentially important information is lost. The network approach, in contrast, assumes that psychopathology results from the causal interplay between psychiatric symptoms and focuses specifically on these symptoms and their complex associations. By using a sophisticated network analysis technique, this study constructed an empirically based network structure of 120 psychiatric symptoms of twelve major DSM-IV diagnoses using cross-sectional data of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, second wave; N = 34,653). The resulting network demonstrated that symptoms within the same diagnosis showed differential associations and indicated that the strategy of summing symptoms, as in current classification systems, leads to loss of information. In addition, some symptoms showed strong connections with symptoms of other diagnoses, and these specific symptom pairs, which both concerned overlapping and non-overlapping symptoms, may help to explain the comorbidity across diagnoses. Taken together, our findings indicated that psychopathology is very complex and can be more adequately captured by sophisticated network models than current classification systems. The network approach is, therefore, promising in improving our understanding of psychopathology and moving our field forward