Early life risk factors for depression among young adults in the United States general population: Attributable risks and gender differences.

BACKGROUND: This study adopts individual and societal-level approaches to examine the contribution of childhood risk factors to major depressive episodes (MDE) in 2526 American young adults. METHODS: Nationally representative data from the 2017 U.S. Panel Study of Income Dynamics - Transition into Adulthood Supplement were analyzed using multivariate methods to assess the impact of parental mental illness, childhood adversities, childhood mental disorders, and childhood physical conditions. Adjusted odds ratios and population attributable risk proportions (PARPs) are calculated to estimate the proportion of MDE cases related to risk factors. RESULTS: The 12-month prevalence of positive screens for MDE was 25.4 %. Approximately 34 % of these were attributable to childhood mental disorders, 24 % to childhood physical conditions, 21 % to childhood adversities, and 16 % to parental mental illness. Childhood and parental depression were critical risk factors, both at the individual (odds ratio exceeding 2) and societal (PARP approximately 24 %) levels. Gender-specific risk factors were identified, with childhood physical abuse and childhood anxiety disorders constituting risk factors for females, and childhood externalizing disorders and childhood headaches as risk factors for males. Approximately 60 % of U.S. young adult MDE cases are attributable to risk factors before age 18. LIMITATIONS: Possible over reporting of MDE may have biased the associations between predictors and depression. CONCLUSIONS: Exposure to depression at a young age-one's own or parental depression-is a robust risk factor for both genders. Policies and interventions focused at alleviating the societal burden of depression should value its generational transmission.

Trends in population attributable fraction of modifiable risk factors for cardiovascular diseases across three decades.

AIM: To evaluate temporal trends, across three decades, in the population attributable fractions (PAFs) of modifiable risk factors for 5-year risk of cardiovascular diseases (CVDs). METHODS: Within population-based Rotterdam Study, we defined three time-groups of individuals without established CVD at 'baseline' with a mean age of 70 years, and followed for five years: Epoch 1990s (1989-1993, N=6195), Epoch 2000s (1997-2001, N=5572) and Epoch 2010s (2009-2014, N=5135). The prevalence of risk factors and related relative risks were combined to quantify PAFs. RESULTS: The PAF of the six risk factors combined for global CVD was 0.57 (95% confidence interval [CI] 0.47 to 0.65), 0.52 (0.39 to 0.62) and 0.39 (0.18 to 0.54) in three respective epochs. Hypertension contributed the highest PAF to global CVD in Epoch 1990s (0.37, 95% CI: 0.28 to 0.44) and 2000s (0.34, 95% CI: 0.22 to 0.43), while smoking was the largest contributor in Epoch 2010s (0.20, 95% CI: 0.06 to 0.32). Dyslipidemia changed population-level coronary heart disease risk over time. For stroke, hypertension became a less significant contributor over time, but smoking became a larger contributor. For heart failure, all risk factors showed non-significant PAFs in Epoch 2010s. PAFs related to individual risk factor varied among women and men. CONCLUSION: Six modifiable risk factors to population-level global CVD risk decreased over time, but still explained 39% of total CVD in the latest decade. PAFs changed considerably for hypertension, dyslipidemia, and smoking. Risk factors had different PAFs for different CVDs with pronounced sex differences.

The contribution of the individual cardiovascular risk factors to population CVD risk considerably changed over the past 3 decades, especially for hypertension, dyslipidemia, and smoking. Traditional modifiable risk factors exerted declining contributions to population burden of total CVD over the past three decades, suggesting good progress in CVD prevention. Nonetheless, in the latest decade, unfavorable risk factors accounted for 39% of total CVD burden. Sex differences in the contributions of abdominal obesity, diabetes and smoking to cardiovascular outcomes were observed.

What is the impact of job precariousness on depression? Risk assessment and attributable fraction in Spain.

OBJECTIVES: The prevalence of depression related to precarious employment (PE) has become a significant public health concern, given the declining trend of the standard employment relationship. Research has focused on the mental health detrimental effects of employment conditions, whereas there is scarce evidence concerning the burden of depression that could be prevented by targeting precariousness. This paper estimates the impact of PE on the risk of depression and the attributable fraction within the active and working salaried population in Spain. STUDY DESIGN: Observational cross-sectional on data drawn from the Spanish portion of European Health Survey 2020. METHODS: After applying selection criteria and descriptives, binary logistic regression models stratified by sex are used to examine the associations between a 9-categories combination of employment precariousness and occupational social class, and depressive symptoms. RESULTS: There is a higher risk of depression among individuals in PE and among those who are unemployed, with a notable gradient based on occupational social class for women. Adjusting by sex, age and foreign-born origin, we estimate that approximately 15.0% (95% confidence interval [CI]: 1.0%-26.2%) of depression cases among the working population and 33.3% (95% CI: 23.2%-43.2) among the active population can be attributed to PE. CONCLUSIONS: These findings highlight the public health impact of PE on mental health, provide evidence to estimate the economic burden linked to employment-related mental health, and underscore the need for policy changes and interventions at the level of labour markets and workplaces to mitigate the detrimental effects of PE.

Smoking-attributable mortality among Korean adults in 2019.

OBJECTIVES: Tobacco use ranks among the leading preventable causes of death worldwide. This study was conducted to calculate the mortality rate attributable to smoking in Korea for 2019 and to highlight the importance of tracking and monitoring smoking-related deaths for public health purposes. METHODS: Population attributable risk (PAR) was used to estimate the number of deaths related to smoking in 2019. PAR percentages were applied to the estimated mortality figures for various diseases, with PAR determined based on relative risk (RR). Levin's formula was used to calculate PAR, and RR was adjusted for age and alcohol consumption using Cox proportional hazards regression model to derive disease-specific regression coefficients. The analysis incorporated previously determined smoking rates from 1985, and use rates of novel tobacco products were not considered. RESULTS: The findings revealed a total of 67,982 smoking-attributable deaths in Korea in 2019, 56,993 of which occurred in men and 11,049 in women. The PAR of smoking for various causes of death in adult men was highest for lung cancer at 74.9%, followed by pneumonia (29.4%), ischemic heart disease (42.3%), and stroke (30.2%). For women, the PAR for smoking-related death was highest for lung cancer (19.9%), followed by stroke (7.6%), pneumonia (5.7%), and ischemic heart disease (9.1%). CONCLUSIONS: In countries experiencing rapid fluctuations in smoking rates, including Korea, regular studies on smoking-related mortality is imperative. Furthermore, it is necessary to investigate smoking-related deaths, including the prevalence of novel tobacco product use, to accurately gauge the risks associated with emerging tobacco products.

All-cause, premature, and cardiovascular death attributable to socioeconomic and ethnic disparities among New Zealanders with type 1 diabetes 1994-2019: a multi-linked population-based cohort study.

BACKGROUND: New Zealand (NZ) research into type 1 diabetes mellitus (T1DM) mortality can inform policy and future research. In this study we aimed to quantify the magnitude to which ethnicity and socioeconomic disparities influenced mortality at the population level among people with Type 1 diabetes (T1DM) in Auckland, New Zealand (NZ). METHODS: The cohort data were derived from the primary care diabetes audit program the Diabetes Care Support Service (DCSS), and linked with national primary care, pharmaceutical claims, hospitalisation, and death registration databases. People with T1DM enrolled in DCSS between 1994-2018 were included. All-cause, premature, and cardiovascular mortalities were estimated by Poisson regression models with adjustment for population-level confounders. The mortality rates ratio (MRR) was standardized against the DCSS type 2 diabetes population. Mortality rates were compared by ethnic group (NZ European (NZE) and non-NZE) and socioeconomic deprivation quintile. The population attributable fraction (PAF) was estimated for ethnic and socioeconomic disparities by Cox regression adjusting for demographic, lifestyle, and clinical covariates. The adjusted slope index inequality (SII) and relative index of inequality (RII) were used to measure the socioeconomic disparity in mortalities. RESULTS: Overall, 2395 people with T1DM (median age 34.6 years; 45% female; 69% NZE) were enrolled, among whom the all-cause, premature and CVD mortalities were 6.69 (95% confidence interval: 5.93-7.53), 3.30 (2.77-3.90) and 1.77 (1.39-2.23) per 1,000 person-years over 25 years. The overall MRR was 0.39 (0.34-0.45), 0.65 (0.52-0.80), and 0.31 (0.24-0.41) for all-cause, premature and CVD mortality, respectively. PAF attributable to ethnicity disparity was not significantly different for mortality. The adjusted PAF indicated that 25.74 (0.84-44.39)% of all-cause mortality, 25.88 (0.69-44.69)% of premature mortality, 55.89 (1.20-80.31)% of CVD mortality could be attributed to socioeconomic inequality. The SII was 8.04 (6.30-9.78), 4.81 (3.60-6.02), 2.70 (1.82-3.59) per 1,000 person-years and RII was 2.20 (1.94-2.46), 2.46 (2.09-2.82), and 2.53 (2.03-3.03) for all-cause, premature and CVD mortality, respectively. CONCLUSIONS: Our results suggest that socioeconomic disparities were responsible for a substantial proportion of all-cause, premature and CVD mortality in people with T1DM in Auckland, NZ. Reducing socioeconomic barriers to management and self-management would likely improve clinical outcomes.

Population Attributable Fraction of Nonvaccination of COVID-19 Due to Vaccine Hesitancy, United States, 2021.

Understanding the extent of coronavirus disease 2019 (COVID-19) nonvaccination attributable to vaccine hesitancy versus other barriers can help prioritize approaches for increasing vaccination uptake. Using data from the Centers for Disease Control and Prevention's Research and Development Survey, a nationally representative survey fielded from May 1 to June 30, 2021 (n = 5,458), we examined the adjusted population attribution fraction (PAF) of COVID-19 vaccine hesitancy attributed to nonvaccination according to sociodemographic characteristics and health-related variables. Overall, the adjusted PAF of nonvaccination attributed to vaccine hesitancy was 76.1%. The PAF was highest among adults who were ≥50 years of age (87.9%), were non-Hispanic White (83.7%), had a bachelor's degree or higher (82.7%), had an annual household income of at least $75,000 (85.5%), were insured (82.4%), and had a usual place for health care (80.7%). The PAF was lower for those who were current smokers (65.3%) compared with never smokers (77.9%), those who had anxiety or depression (65.2%) compared with those who did not (80.1%), and those who had a disability (64.5%) compared with those who did not (79.2%). Disparities in PAF suggest areas for prioritization of efforts for intervention and development of messaging campaigns that address all barriers to uptake, including hesitancy and access, to advance health equity and protect individuals from COVID-19.

Estimating cancers attributable to physical inactivity in Australia.

OBJECTIVES: It was previously estimated that 1814 (1.6 % of incident cancers) were attributable to physical inactivity in Australia in 2010, when only three sites were considered. We estimated the burden of cancer due to physical inactivity in Australia for 13 sites. DESIGN: The population attributable fraction estimated site-specific cancer cases attributable to physical inactivity for 13 cancers. The potential impact fraction was used to estimate cancers that could have been prevented in 2015 if Australian adults had increased their physical activity by a modest amount in 2004-05. METHODS: We used 2004-05 national physical activity prevalence data, 2015 national cancer incidence data, and contemporary relative-risk estimates for physical inactivity and cancer. We assumed a 10-year latency period. RESULTS: An estimated 6361 of the cancers observed in 2015 were attributable to physical inactivity, representing 4.8 % of all cancers diagnosed. If Australian adults had increased their physical activity by one category in 2004-05, 2564 cases (1.9 % of all cancers) could have been prevented in 2015. CONCLUSIONS: More than three times as many cancers are attributable to physical inactivity than previously reported. Physical activity promotion should be a central component of cancer prevention programmes in Australia.

Mediating effect of body fat percentage in the association between ambient particulate matter exposure and hypertension: a subset analysis of China hypertension survey.

BACKGROUND: Hypertension caused by air pollution exposure is a growing concern in China. The association between air pollutant exposure and hypertension has been found to be potentiated by obesity, however, little is known about the processes mediating this association. This study investigated the association between fine particulate matter (aerodynamic equivalent diameter ≤ 2.5 microns, PM2.5) exposure and the prevalence of hypertension in a representative population in southern China and tested whether obesity mediated this association. METHODS: A total of 14,308 adults from 48 communities/villages in southern China were selected from January 2015 to December 2015 using a stratified multistage random sampling method. Hourly PM2.5 measurements were collected from the China National Environmental Monitoring Centre. Restricted cubic splines were used to analyze the nonlinear dose-response relationship between PM2.5 exposure and hypertension risk. The mediating effect mechanism of obesity on PM2.5-associated hypertension was tested in a causal inference framework following the approach proposed by Imai and Keele. RESULTS: A total of 20.7% (2966/14,308) of participants in the present study were diagnosed with hypertension. Nonlinear exposure-response analysis revealed that exposure to an annual mean PM2.5 concentration above 41.8 µg/m3 was associated with increased hypertension risk at an incremental gradient. 9.1% of the hypertension burden could be attributed to exposure to elevated annual average concentrations of PM2.5. It is noteworthy that an increased body fat percentage positively mediated 59.3% of the association between PM2.5 exposure and hypertension risk, whereas body mass index mediated 34.3% of this association. CONCLUSIONS: This study suggests that a significant portion of the estimated effect of exposure to PM2.5 on the risk of hypertension appears to be attributed to its effect on alterations in body composition and the development of obesity. These findings could inform intersectoral actions in future studies to protect populations with excessive fine particle exposure from developing hypertension.

The EAT-Lancet Commission's Planetary Health Diet Compared With the Institute for Health Metrics and Evaluation Global Burden of Disease Ecological Data Analysis.

Background This article aimed to compare the EAT-Lancet Commission's "Planetary Health Diet" (PHD) with the Institute for Health Metrics and Evaluation (IHME) Global Burden of Disease Study 1990-2017 (GBD2017) dietary and other risk factor data. In the PHD/GBD comparison, we also intended to show the relevance of a new multiple regression analysis methodology with dietary and non-dietary risk factors (independent variables) for noncommunicable disease (NCD) deaths/100000/year in males and females 15-69 years old from 1990 to 2017 (NCDs, dependent variable). Methods We formatted worldwide GBD2017 dietary risk factors and NCD data on 1120 worldwide cohorts to obtain 7846 population-weighted cohorts. Each cohort represented about one million people, totaling about 7.8 billion people from 195 countries. With an empirically derived methodology, we compared the PHD animal- and plant-sourced food recommended ranges (kilocalories/day=KC/d) with optimal dietary ranges (KC/d) from GBD cohort data. Using GBD data subsets with low and high animal food consumption cohorts, our new GBD multiple regression formula derivation methodology equated risk factor formula coefficients to their population-attributable risk percents (PAR%s). Results We contrasted PHD recommendations for the available 14 dietary risk factors (KC/d means and ranges) with our GBD analysis methodology's optimal ranges for each dietary variable (KC/d mean and range): PHD beef, lamb, and pork mean: 30 KC/d (range: 0-60 KC/d)/GBD processed meat: 8.86 (1.69-16.03)+GBD red meat: 44.52 (20.37-68.68), PHD fish: 40 (0-143)/GBD: 19.68 (3.45-35.90), PHD whole milk or equivalents: 153 (0-306)/GBD: 40.00 (18.89-61.11), PHD poultry: 62 (0-124)/GBD: 56.10 (24.13-88.07), PHD eggs: 19 (0-37)/GBD: 19.42 (9.99-28.86), PHD: saturated oils 96 (0-96)/GBD added saturated fatty acids (SFA): 116.55 (104.04-129.07), PHD all added sugars: 120 (0-120)/GBD sugary beverages: 286.37 (256.99-315.76), PHD tubers or starchy vegetables: 39 (0-78)/GBD potatoes: 84.16 (75.75-92.58)+GBD sweet potatoes: 9.21 (4.05-14.37), PHD fruits: 126 (63-189)/GBD: 63.03 (21.61-113.71), PHD vegetables: 78.32 (9.48-196.14)/GBD: 85.05 (66.75-103.36), PHD nuts: 291 (0-437)/GBD nuts and seeds: 10.97 (5.95-15.98), PHD whole grains: 811 (811/811)/GBD: 56.14 (50.53-61.76), PHD legumes: 284 (0-379)/GBD: 59.93 (45.43-74.43), and total animal food PHD: (0/400)/GBD: 329.84 (212.49-447.19). Multiple regression low and high animal food subsets' (animal foods mean=147.09 KC/d versus animal foods mean=482.00 KC/d) formulas each with 28 dietary and non-dietary risk factors (independent variables) accounted for 52.53% and 28.83% of their respective total formula PAR%s with NCDs (dependent variable). Conclusions GBD data modeling supported many but not all the PHD dietary recommendations. GBD data suggested that the amount of consumption of animal foods was the dominant determinate of NCDs of countries globally. Adding to the univariate associations, multiple regression risk factor formulas with risk factor coefficients equated to their PAR%s further elucidated dietary influences on NCDs. This paper and the soon-to-be-released IHME GBD2021 (1990-2021) data should help inform the EAT-Lancet 2.0 Commission's work.

Strategies of Modelling Incident Outcomes Using Cox Regression to Estimate the Population Attributable Risk.

When the Cox model is applied, some recommendations about the choice of the time metric and the model's structure are often disregarded along with the proportionality of risk assumption. Moreover, most of the published studies fail to frame the real impact of a risk factor in the target population. Our aim was to show how modelling strategies affected Cox model assumptions. Furthermore, we showed how the Cox modelling strategies affected the population attributable risk (PAR). Our work is based on data collected in the North-West Province, one of the two PURE study centres in South Africa. The Cox model was used to estimate the hazard ratio (HR) of mortality for all causes in relation to smoking, alcohol use, physical inactivity, and hypertension. Firstly, we used a Cox model with time to event as the underlying time variable. Secondly, we used a Cox model with age to event as the underlying time variable. Finally, the second model was implemented with age classes and sex as strata variables. Mutually adjusted models were also investigated. A statistical test to the multiplicative interaction term the exposures and the log transformed time to event metric was used to assess the proportionality of risk assumption. The model's fitting was investigated by means of the Akaike Information Criteria (AIC). Models with age as the underlying time variable with age and sex as strata variables had enhanced validity of the risk proportionality assumption and better fitting. The PAR for a specific modifiable risk factor can be defined more accurately in mutually adjusted models allowing better public health decisions. This is not necessarily true when correlated modifiable risk factors are considered.

Influence of analytic methods, data sources, and repeated measurements on the population attributable fraction of lifestyle risk factors.

Population attributable risk (PAR%) reflects the preventable fraction of disease. However, PAR% estimates of cancer have shown large variation across populations, methods, data sources, and timing of measurements. Three statistical methods to estimate PAR% were identified from a systematic literature review: the Levin's formula, the comparative incidence rate method, and the comparative risk assessment method. We compared the variations in PAR% of postmenopausal breast cancer in the Nurses' Health Study to evaluate the influence by method choice, source of prevalence data, use of single vs repeated exposure measurements, and potential joint effects of obesity, alcohol, physical activity, fruit and vegetable intake. Across models of the three methods, the estimated PAR% using repeated measurements were higher than that using baseline measurement; overall PAR% for the baseline, simple update, and cumulative average models were 13.8%, 21.1%, 18.6% by Levin's formula; 13.7%, 28.0%, 31.2% by comparative risk assessment; and 17.4%, 25.2%, 29.3% by comparative incidence rate method. The estimated PAR% of the combination of multiple risk factors was higher than the product of the individual PAR%: 18.9% when assuming independence and 31.2% when considering the risk factors jointly. The three methods provided similar PAR% based on the same data source, timing of measurements, and target populations. However, sizable increases in the PAR% were observed for repeated measures over a single measure and for calculations based on achieving all recommendations jointly rather than individually.

Population attributable risk fraction of modifiable risk factors associated with poor self-rated health among children and adolescent; the CASPIAN-V study.

BACKGROUND: We aimed to determine the population attributable risk fraction (PARF) of the risk factors for poor SRH in Iranian children and adolescents. METHOD: This was a nationwide cross-sectional study conducted in 2015 among 14,400 students aged 6-18 years, living in 30 provinces of Iran. Data were collected using global school health survey questionnaire. Logistic regression was employed to determine the adjusted association of modifiable risk factors with SRH. We used average PARF to determine the preventable proportion of poor reported SRH. RESULTS: Of 14,400 recruited students, data on 13,983 subjects were analyzed in current study. The mean (SD) age of participants (n = 13,983) was 12.3 (3.16) years, and 49.3% were female. Poor SRH was reported in 19% of subjects. In total, 77% of poor reported SRH in Iranian children and adolescents could be attributed to insufficient daily sleep duration, physical injury, lack of close friend, dissatisfaction with family relationship, and the lack of a companion to share personal problems. We also found that physical pain had the largest PARF (32.4%) followed by anxiety (26.1%) and un-satisfaction with family relationship (5.2%). CONCLUSION: The established physical and social support factors of poor SRH were associated with a remarkable proportion of poor SRH in the Iranian pediatric population. Changing the children's risk factor profile to the lowest physical risk factor as well as reducing the anxiety level and preventing from physical painsmay significantly improve the SRH of children and adolescents.

Quantifying impact of obesity on cardiometabolic comorbidities and public health implications: Insights from South Africa.

INTRODUCTION: South Africa has the highest obesity and hypertension rates in the African region. In this cross-sectional study, we aimed to quantify the correlates and burden of obesity and their impacts on cardiometabolic conditions. METHODS: The study population was 80,270 men(41 %) and women(59 %) who participated in South African national surveys (2008-to-2017). Weighted-logistic regression models and the population attributable risk (PAR %) were used after accounting for the correlation structure of the risk factors in a multifactorial setting. RESULTS: Overall, 63 % of the women and 28 % of the men were either overweight or obese. Parity was identified as the most influential factor and exclusively associated with 62 % of the obesity in women; being married/cohabiting had the highest impact on obesity in men and associated with 37 % of the obesity. Overall, 69 % of them had comorbidities including hypertension, diabetes and heart disease. More than 40 % of the comorbidities were attributed to overweight/obesity. CONCLUSION: Developing culturally appropriate prevention programs are urgently needed to raise awareness of obesity, hypertension and their impacts on severe cardiometabolic diseases. This approach would also significantly reduce COVID-19 related poor health outcomes and premature deaths.

Population-level impact of beliefs and attitudes on vaccine decision-making in South Africa: results from the COVID-19 Vaccine Survey (2021/2022).

OBJECTIVES: In addition to being home to more than seven million HIV-infected individuals, South Africa also has a high burden of COVID-19 and related comorbidities worldwide. We aimed to identify the most influential "beliefs" and "attitudes" on vaccine decision-making behavior. STUDY DESIGN: This study used panel data from cross-sectional surveys. METHODS: We used the data from Black South Africans who participated in the "COVID-19 Vaccine Surveys" (November 2021 and February/March 2022) in South Africa. Besides standard risk factor analysis, such as multivariable logistic regression models, we also used the modified version of population attributable risk percent and estimated the population-level impacts of beliefs and attitudes on vaccine decision-making behavior using the methodology in multifactorial setting. RESULTS: A total of 1399 people (57% men and 43% women) who participated in both surveys were analyzed. Of these, 336 (24%) reported being vaccinated in survey 2. Overall low perceived risk, concerns around efficacy, and safety were identified as the most influential factors and associated with 52%-72% (<40 years) and 34%-55% (40+ years) of the unvaccinated individuals. CONCLUSION: Our findings highlighted the most influential beliefs and attitudes on vaccine decision-making and their population-level impacts, which are likely to have significant public health implications exclusively for this population.

The Projected Impact of Population-Wide Achievement of LDL Cholesterol <70 mg/dL on the Number of Recurrent Events Among US Adults with ASCVD.

PURPOSE: Adults with atherosclerotic cardiovascular disease (ASCVD) are recommended high-intensity statins, with those at very high risk for recurrent events recommended adding ezetimibe and/or a proprotein convertase subtilisin/kexin type 9 inhibitor if their low-density lipoprotein cholesterol (LDL-C) is ≥70 mg/dL. We estimated the number of recurrent ASCVD events potentially averted if all adults in the United States (US) ≥45 years of age with ASCVD achieved an LDL-C <70 mg/dL. METHODS: The number of US adults with ASCVD and LDL-C ≥70 mg/dL was estimated from the National Health and Nutrition Examination Survey 2009-2016 (n = 596). The 10-year cumulative incidence of recurrent ASCVD events was estimated from the REasons for Geographic And Racial Differences in Stroke study (n = 5390), weighted to the US population by age, race, and sex. The ASCVD risk reduction by achieving an LDL-C <70 mg/dL was estimated from meta-analyses of lipid-lowering treatment trials. RESULTS: Overall, 14.7 (95% CI, 13.7-15.8) million US adults had ASCVD, of whom 11.6 (95% CI, 10.6-12.5) million had LDL-C ≥70 mg/dL. The 10-year cumulative incidence of ASCVD events was 24.3% (95% CI, 23.2-25.6%). We projected that 2.823 (95% CI, 2.543-3.091) million ASCVD events would occur over 10 years among US adults with ASCVD and LDL-C ≥70 mg/dL. Overall, 0.634 (95% CI, 0.542-0.737) million ASCVD events could potentially be averted if all US adults with ASCVD achieved and maintained LDL-C <70 mg/dL. CONCLUSION: A substantial number of recurrent ASCVD events could be averted over 10 years if all US adults with ASCVD achieved, and maintained, an LDL-C <70 mg/dL.

Population-attributable risk of psychiatric disorders for suicide among adolescents and young adults in Taiwan.

BACKGROUND: Youth suicide rates have increased markedly in some countries. This study aimed to estimate the population-attributable risk of psychiatric disorders associated with suicide among Taiwanese youth aged 10-24 years. METHODS: Data were obtained from the National Death Registry and National Health Insurance (NHI) claims database between 2007 and 2019. Youth who died by suicide were included, and comparisons, 1:10 matched by age and sex, were randomly selected from the Registry for NHI beneficiaries. We used multivariable logistic regression to estimate suicide odds ratios for psychiatric disorders. The population-attributable fractions (PAF) were calculated for each psychiatric disorder. RESULTS: A total of 2345 youth suicide and 23 450 comparisons were included. Overall, 44.8% of suicides had a psychiatric disorder, while only 7.9% of the comparisons had a psychiatric disorder. The combined PAF for all psychiatric disorders was 55.9%. The top three psychiatric conditions of the largest PAFs were major depressive disorder, dysthymia, and sleep disorder. In the analysis stratified by sex, the combined PAF was 45.5% for males and 69.2% for females. The PAF among young adults aged 20-24 years (57.0%) was higher than among adolescents aged 10-19 years (48.0%). CONCLUSIONS: Our findings of high PAF from major depressive disorder, dysthymia, and sleep disorder to youth suicides suggest that youth suicide prevention that focuses on detecting and treating mental illness may usefully target these disorders.

Attributable risk of suicide for populations in Australia.

Objective: Each year approximately 3,000 Australians die by suicide. We estimated the population attributable risk for identified target populations to provide evidence on how much of the overall burden of suicide in the Australian population is experienced by each of them. Methods: We identified 17 demographic and clinical target populations at risk of suicide and calculated the population attributable fraction (PAF) using a single or pooled suicide risk and the proportional representation of each target population within Australia. Results: Large PAF estimates were found for men (52%, 95% confidence interval (CI) 51%-53%), people bereaved by suicide (35%, 95% CI 14%-64%), people with a mental health or behavioural condition (33%, 95%CI 17%-48%), people with a chronic physical condition (27%, 95%CI 18%-35%), adults aged 25-64 years (13%, 95%CI 12%-14%), LGB populations (9%, 95%CI 6%-13%), offenders (9%, 95%CI 8%-10%), and people employed in blue collar occupations (8%, 95%CI 4%-12%). Limitations: The PAF is limited by assumptions, namely, that risk factors are independent, and that the relationship between risk factors and outcomes are unidirectional and constant through time. Conclusions and implications for public health: Considerable reductions in the overall suicide rate in Australia may occur if risk factors are addressed in identified populations with large PAF estimates. These estimates should be considered as an adjunct to other important inputs into suicide prevention policy priorities.

Reducing Birth Defects by Decreasing the Prevalence of Maternal Chronic Diseases-Evaluated by Linked National Registration Dataset.

Birth defects (BDs) are an important cause of abortion, stillbirth, and infant mortality that may cause lifelong disability. The defects can be caused by genetics, environmental exposure, or maternal chronic diseases. We conducted a study to analyze the association between maternal chronic diseases and BDs and to evaluate the effect of decreasing the prevalence of maternal chronic diseases on reducing BDs. The data of newborns and their mothers were concatenated and analyzed from three national population databases: the National Health Insurance Research Database, the Birth Certificate Application, and the Birth Registration Database in Taiwan during the period of 2005 to 2014. Codes 740-759 of the International Classification of Diseases 9th Revision­Clinical Modification (ICD-9-CM) were used as the diagnosis of BDs. The prevalence of BDs was 2.72%. Mothers with cardiovascular diseases, hypertension, anemia, genitourinary tract infections, renal diseases, neurotic or psychotic disorders, gestational diabetes mellitus (DM), and pregestational type 1 or type 2 DM had a significantly higher prevalence of BDs. The population attributable risk percent (PAR%) of BDs was 1.63%, 0.55%, 0.18%, 1.06%, 0.45%, 0.22%, 0.48%, and 0.24% for maternal hypertension, cardiovascular disease, renal disease, genitourinary infection, anemia, neurotic and psychotic disorders, gestational DM, and pregestational type 1 or type 2 DM, respectively. The percentage change (−1%, −5%, and −10% of prevalence in 2034 compared with the prevalence in 2005−2014) of maternal disease and the predicted number of live births was used to estimate the decrease in the number of newly diagnosed BDs in 2034. By using the middle-estimated number of live births in 2034, we predicted that the number of BDs would decrease by 302, 102, 33, 196, 83, 41, 89, and 44 with a −5% prevalence of maternal hypertension, cardiovascular disease, renal disease, genitourinary infection, anemia, neurotic and psychotic disorders, gestational DM, and pregestational type 1 or type 2 DM, respectively. We conclude that mothers with chronic diseases, including cardiovascular diseases, hypertension, anemia, genitourinary tract infections, renal diseases, neurotic or psychotic disorders, gestational DM, and pregestational type 1 or type 2 DM, have a significantly higher (p < 0.01) prevalence of having offspring with BDs. Mothers with chronic diseases are associated with BDs. It is very important to set up a policy to decrease the prevalence of these maternal chronic diseases; then, we can reduce the incidence of BDs.

How many crashes does cellphone use contribute to? Population attributable risk of cellphone use while driving.

BACKGROUND: Cellphone distraction is a major contributing factor for traffic crashes, a leading cause of death worldwide. The novel naturalistic driving study (NDS) study with continuously collected in situ driving videos provides an opportunity to accurately estimate the safety impact of cellphone distraction. METHODS: We apply a case-cohort study design to the Second Strategic Highway Research Program NDS, the largest NDS up-to-date with more than 3400 participants. The data include with 842 level 1-3 crashes and 19,338 randomly selected control driving segments. We propose a partial Population Attributable Risk (PAR) estimator that provides consistent and stable estimation over time and across different driving behaviors. RESULTS: The US population-adjusted PAR show that 8% of crashes (PAR = 0.08, 95 %CI: [0.06, 0.19]) can be reduced if cellphone distraction were switched to sober, alert, and attentive driving behavior. Young adults (age 20-29 years) and middle-aged drivers (age 30-64 years) each contribute 39% of the population level PAR. Within each age group, the PARs vary substantially from 18% for young adult drivers to 5% for middle-aged drivers. The contribution of cellphone visual-manual tasks to crashes is more than 4 times larger than cellphone talking and accounts for 87.5% of cellphone-related crashes (PAR = 0.07). CONCLUSIONS: Cellphone distraction contributes to a considerable part of crashes. Young drivers are more susceptible to the influence of cellphone distraction and visual-manual distraction accounts for the majority of cellphone-related crashes.

Population Attributable Risks of Potential Modifiable Factors for Atrial Fibrillation in China: A National Survey.

Background: There is an association between atrial fibrillation (AF) and overall mortality as well as mobility. It is not known, however, what the preventable burden of AF in China is. This study aims to identify what proportion of the burden of AF may be avoided by modifiable risk factors. Methods: As part of the China National Stroke Screening and Prevention Project, 726,451 adults aged ≥40 years were enrolled in a representative cross-sectional study. The following seven factors have been categorized as modifiable risk factors for AF: body mass index, smoking, alcohol consumption, physical inactivity, hypertension, diabetes mellitus, and dyslipidemia. In order to calculate population-attributable risks (PARs), odds ratios (ORs) were calculated for selected risk factors. Results: The crude ORs increased with age (ORs ranged from 1.92 to 4.02). A total of 18,736 cases of prevalent AF have been identified. The overall prevalence of AF was 2.6%. The crude ORs increased with age (ORs range 1.92-4.03). The adjusted ORs and the corresponding confidence intervals (CIs) for these seven modifiable factors were 1.16 (95% confidence interval [CI]: 1.12-1.19), 1.56 (95% CI: 1.49-1.62), 2.15 (95% CI: 2.02-2.28), 2.07 (95% CI: 2.01-2.14), 2.71 (95% CI: 2.62-2.79), 2.10 (95% CI: 2.02-2.19), 2.52 (95% CI: 2.44-2.60), and 3.32 (95% CI: 3.18-3.48), respectively. Accordingly, 59.3% of all cases of AF could be explained by having these modifiable risk factors, among which hypertension accounted for the greatest share. Conclusion: In China, hypertension is the leading preventable cause of AF, and more than half of these cases can be prevented through improving those modifiable risk factors.