Attributable Fraction Estimates Research Articles

Health Effects of Methylmercury in Coastal Areas of the Yatsushiro Sea, Far from Minamata.

Minamata disease, caused by ingesting seafood contaminated with methylmercury dumped by corporations, was discovered in 1956; however, there has been no continued investigation to determine the full extent of the damage. Since 2004, it has been discovered that affected patients can be found in areas further away from Minamata than previously known. In the present study, we investigated various symptoms and somatosensory disturbances in western Miyanokawachi District, northern Himedo District, southwestern Nagashima District, and the uncontaminated Amami district and calculated the proportion of patients with sensory disturbances as a percentage of the population in each area. Both touch and pain sensations, with a predominance of the peripheral extremities, were observed in 58.6% of patients in Miyanokawachi, 53.9% in Himedo, 37.8% in Nagashima, and 1.4% in Amami. The lowest estimates of attributable fractions of the exposed group for four-limb-predominant sensory disturbance in the population of the contaminated districts were 94.1% in Miyanokawachi, 94.6% in Himedo, and 91.4% in Nagashima, and general and perioral sensory disturbances were also high. This suggests that the presence or absence of these sensory disturbances is useful in the diagnosis of Minamata disease, even in more distant parts of the Yatsushiro Sea area.

Estimating and displaying population attributable fractions using the R package: graphPAF

Here we introduce graphPAF, a comprehensive R package designed for estimation, inference and display of population attributable fractions (PAF) and impact fractions. In addition to allowing inference for standard population attributable fractions and impact fractions, graphPAF facilitates display of attributable fractions over multiple risk factors using fan-plots and nomograms, calculations of attributable fractions for continuous exposures, inference for attributable fractions appropriate for specific risk factor →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rightarrow $$\\end{document} mediator →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rightarrow $$\\end{document} outcome pathways (pathway-specific attributable fractions) and Bayesian network-based calculations and inference for joint, sequential and average population attributable fractions in multi-risk factor scenarios. This article can be used as both a guide to the theory of attributable fraction estimation and a tutorial regarding how to use graphPAF in practical examples.

Impact of the use of small-area models on estimation of attributable mortality at a regional level.

The objective of this study is to assess the impact of applying prevalences derived from a small-area model at a regional level on smoking-attributable mortality (SAM). A prevalence-dependent method was used to estimate SAM. Prevalences of tobacco use were derived from a small-area model. SAM and population attributable fraction (PAF) estimates were compared against those calculated by pooling data from three national health surveys conducted in Spain (2011-2014-2017). We calculated the relative changes between the two estimates and assessed the width of the 95% CI of the PAF. Applying surveys-based prevalences, tobacco use was estimated to cause 53 825 (95% CI: 53 182-54 342) deaths in Spain in 2017, a figure 3.8% lower obtained with the small-area model prevalences. The lowest relative change was observed in the Castile-La Mancha region (1.1%) and the highest in Navarre (14.1%). The median relative change between regions was higher for women (26.1%), population aged ≥65 years (6.6%), and cardiometabolic diseases (9.0%). The differences between PAF by cause of death were never greater than 2%. Overall, the differences between estimates of SAM, PAF, and confidence interval width are small when using prevalences from both sources. Having these data available by region will allow decision-makers to implement smoking control measures based on more accurate data.

The contribution of metabolic risk factors to cardiovascular mortality in Golestan cohort study: Population attributable fraction estimation

BackgroundCardiovascular diseases (CVDs) are the leading causes of global mortality and disability. Several studies demonstrated that metabolic risk factors increase cardiovascular mortality. The aim of this study is to examine CVDs deaths and population attributable fractions (PAFs) of their metabolic risk factors in Iran. MethodsThis is a study on 8621 participants aged 45–75 years and older, recruited in the repeated measurement phase of the Golestan cohort study (GCS) in northeast of Iran. The Cox proportional hazards model was used to determine the adjusted hazard ratios (HRs). PAFs were calculated to enumerate CVDs mortality avoidable in the population if metabolic risk factors were eliminated. ResultsThe mortality of CVDs was attributable to metabolic factors, including high waist circumference (PAF, 28 %, [95 % CI: 16%–38 %]), high fasting blood sugar (FBS) (20 %, [15%–24 %]), overweight and obesity (19 %, [8%–28 %]), high blood pressure (16 %, [11%–21 %]), high low-density lipoprotein cholesterol (LDL-C) (8 %, [1%–15 %]), and high triglyceride (TG) (7 %, [3%–11 %]). Collectively, these metabolic risk factors accounted for 50 % of CVDs deaths. Females (67 %, [50%–78 %]) had a higher joint PAF of metabolic risk factors compared to males (43 %, [27%–55 %]). ConclusionsThe pattern of CVDs mortality attributable to metabolic risk factors in this study is not the same as similar studies in other parts of the world and previous studies in Iran. It is imperative that CVDs risk factors be specifically evaluated and addressed in various populations due to variety in geographical and temporal patterns in contribution of metabolic risk factors to CVD mortality.

The burden of overweight/obesity and weight-related behaviors attributable to food addiction in emerging adults

While food addiction has been positively associated with excess weight and disordered eating behaviors, this has not been examined in representative samples of emerging adults, who are at elevated risk for these outcomes. This study investigated relationships of food addiction with weight outcomes, weight perception, and weight-control behaviors in emerging adults and estimated the population attributable fraction to food addiction. Data from an observational cohort study were collected in seven annual waves from 2010 to 2016. A nationally representative sample of 2785 10th grade students was recruited from schools within each U.S. census region (73% participation) (mean ± SD baseline age = 16.3 ± 0.5years). Wave 7 retention was 81% (n = 2323, 60% female, mean ± SD = 22.6 ± 0.5 years). Outcomes included current BMI, BMI change from baseline – wave 7, increased weight status in wave 7 (increased weight status from baseline-wave 7), perceived overweight, dieting, any weight-control behavior, and extreme weight-control behaviors. Food addiction was measured in wave 7 using the modified Yale Food Addiction Scale. Relative risk of the outcomes associated with food addiction, and population attributable fraction, were estimated using adjusted log-binomial or robust Poisson regression analyses accounting for the complex survey design. Food addiction prevalence was 4.7%. Participants with food addiction were primarily females (91%); food addiction was uncorrelated with other sociodemographics. Food addiction was associated with 48%–167% increased RR for all outcomes, but these were attenuated after adjustment for confounders (31%–64%). The population attributable fraction for food addiction ranged from 2% (high wave 7 BMI) – 5% (extreme weight-control behaviors). Although the population attributable fraction estimates indicate that the public health burden of these outcomes attributable to food addiction may be relatively minor, food addiction may signal the presence of several adverse mental health symptoms.

Impact of Alcohol Consumption on Breast Cancer Incidence and Mortality: The Women's Health Study.

Background: Alcohol intake is associated with breast cancer (BC) risk, but estimates of greatest public health relevance have not been quantified in large studies with long duration. Materials and Methods: In this prospective cohort study of 39,811 women (median 25 years follow-up), we examined the association between alcohol consumption and BC incidence and mortality with adjusted hazard ratios (HRs), cubic splines, absolute risks, number needed to harm (NNH), and population-attributable fractions. Results: We documented 2,830 cases of BC, including 237 BC deaths. Each additional alcoholic drink/day was associated with a 10% higher rate (HR = 1.10, 95% confidence intervals [CIs]: 1.04-1.16) of total BC in a linear manner (p = 0.0004). The higher rate was apparent for estrogen receptor (ER)+ (HR = 1.12, 95% CI: 1.06-1.18) but not ER- tumors (HR = 0.95, 95% CI: 0.82-1.10), with a statistically significant difference between these associations (p = 0.03). We constructed models comparing BC incidence among 100,000 women followed for 10 years. Compared to a scenario where all women rarely or never consumed alcohol, we expect 63.79 (95% CI: 58.35-69.24) more cases (NNH = 1,567) had all women consumed alcohol at least monthly and 278.66 (95% CI: 268.70-288.62) more cases (NNH = 358) had all women consumed >1 drink/day. Approximately 4.1% of BC cases were attributable to consumption exceeding one drink/month. Conclusion: Alcohol consumption is associated with a linear dose-response increase in BC incidence even within recommended limits of up to one alcoholic drink/day, at least for ER+ tumors. Our estimates of risk differences, attributable fraction, and NNH quantify the burden that alcohol consumption imposes on women in the general population. ClinicalTrials.gov Identifier: NCT00000479.

Risk and attributable fraction estimation for the impact of exposure to compound drought and hot events on daily stroke admissions.

The projection indicates that compound drought and hot events (CDHEs) will intensify, posing risks to cardiovascular health by potentially increasing stroke incidents. However, epidemiological evidence on this topic remains scarce. This study investigates the association between exposure to CDHEs and the risk of daily stroke admissions, specifically examining the effects on various stroke categories such as Subarachnoid Hemorrhage (SAH), Intracerebral Hemorrhage (ICH), Ischemic Stroke (IS), Transient Ischemic Attack (TIA), and other types of stroke. Data on daily stroke admissions from 2010 to 2015 were obtained from the Urban Employee Basic Medical Insurance (UEBMI) and Urban Resident Basic Medical Insurance (URBMI) claims databases in Guangzhou, China. Hot events were identified as days when the daily mean temperature exceeded the 75th percentile during the warm season (May to October) over the study period. The Standardized Precipitation Evapotranspiration Index (SPEI) was utilized to identify drought conditions, with thresholds set at -1 and -1.5 for low-severity and high-severity drought events, respectively. Through a generalized additive model (GAM), we analyzed the cumulative effects of CDHE exposure on daily stroke admissions and calculated the Attributable Fraction (AF) related to CDHEs. The analysis included 179,963 stroke admission records. We observed a significant increase in stroke admission risks due to exposure to hot events coupled with high-severity drought conditions (RR = 1.18, 95%CI: 1.01-1.38), with IS being the most affected category (RR = 1.20, 95%CI: 1.03-1.40). The AF of total stroke admission attributed to hot events in conjunction with high-severity drought conditions was 24.40% (95%CI: 1.86%-50.20%). The combination of hot events with high-severity drought conditions is likely linked to an increased risk of stroke and IS admissions, which providing new insights into the impact of temperature and climate-related hazards on cardiovascular health.

Impact of Alcohol Consumption on Multiple Sclerosis Using Model-based Standardization and Misclassification Adjustment Via Probabilistic Bias Analysis.

The etiology of multiple sclerosis (MS) is still not well-demonstrated, and assessment of some risk factors like alcohol consumption has problems like confounding and measurement bias. To determine the causal effect of alcohol consumption on MS after adjusting for alcohol consumption misclassification bias and confounders. In a population-based incident case-control study, 547 patients with MS and 1057 healthy people were recruited. A minimally sufficient adjustment set of confounders was derived using the causal directed acyclic graph. The probabilistic bias analysis method (PBAM) using beta, logit-logistic, and triangular probability distributions for sensitivity/specificity to adjust for misclassification bias in self-reporting alcohol consumption and model-based standardization (MBS) to estimate the causal effect of alcohol consumption were used. Population attributable fraction (PAF) estimates with 95% Monte Carlo sensitivity analysis (MCSA) intervals were calculated using PBAM and MBS analysis. Bootstrap was used to deal with random errors. The adjusted risk ratio (95% MCSA interval) from the probabilistic bias analysis and MBS between alcohol consumption and MS using the three distribution was in the range of 1.93 (1.07 to 4.07) to 2.02 (1.15 to 4.69). The risk difference (RD) in all three scenarios was 0.0001 (0.0000 to 0.0005) and PAF was in the range of 0.15 (0.010 to 0.50) to 0.17 (0.001 to 0.47). After adjusting for measurement bias, confounding, and random error alcohol consumption had a positive causal effect on the incidence of MS.

Large sex differences in vulnerability to circulatory-system disease under current and future climate in Bucharest and its rural surroundings

Circulatory-system diseases (CSDs) are responsible for 50–60% of all deaths in Romania. Due to its continental climate, with cold winters and very warm summers, there is a strong temperature dependence of the CSD mortality. Additionally, within its capital Bucharest, the urban heat island (UHI) is expected to enhance (reduce) heat (cold)-related mortality. Using distributed lag non-linear models, we establish the relation between temperature and CSD mortality in Bucharest and its surroundings. A striking finding is the strong temperature-related response to high urban temperatures of women in comparison with men from the total CSDs mortality. In the present climate, estimates of the CSDs attributable fraction (AF) of mortality at high temperatures is about 66% higher in Bucharest than in its rural surroundings for men, while it is about 100% times higher for women. Additionally, the AF in urban areas is also significantly higher for elderly people, and for those with hypertensive and cerebrovascular diseases than in the rural surroundings. On the other hand, in rural areas, men but especially women are currently more vulnerable with respect to low temperatures than in the urban environment. In order to project future thermal-related mortality, we have used five bias-corrected climate projections from regional circulation models under two climate-change scenarios, RCP4.5 and RCP8.5. Analysis of the temperature-mortality associations for future climate reveals the strongest signal under the scenario RCP8.5 for women, elderly people as well as for groups with hypertensive and cerebrovascular diseases. The net AF increase is much larger in urban agglomeration for women (8.2 times higher than in rural surroundings) and elderly people (8.5 times higher than in rural surroundings). However, our estimates of thermal attributable mortality are most likely underestimated due to the poor representation of UHI and future demography.

Association of persistent pain with the incidence of chronic conditions following a disabling work-related injury.

In a cohort of workers disabled by a work-related injury or illness, this study aimed to: (i) compare pre-injury prevalence estimates for common chronic conditions to chronic condition prevalence in a representative sample of working adults; (ii) calculate the incidence of chronic conditions post-injury; and (iii) estimate the association between persistent pain symptoms and the incidence of common chronic conditions. Eighteen months post-injury, 1832 workers disabled by a work-related injury or illness in Ontario, Canada, completed an interviewer-administered survey. Participants reported pre- and post-injury prevalence of seven physician-diagnosed chronic conditions, and demographic, employment, and health characteristics. Pre-injury prevalence estimates were compared to estimates from a representative sample of workers. Multivariable logistic regression was used to examine the association of persistent pain with post-injury chronic condition incidence. Age-standardized pre-injury prevalence rates for diabetes, hypertension, arthritis, and back problems were similar to prevalence rates observed among working adults in Ontario, while prevalence rates for mood disorder, asthma and migraine were moderately elevated. Post-injury prevalence rates of mood disorder, migraine, hypertension, arthritis, and back problems were elevated substantially in this cohort. High persistent pain symptoms were strongly associated with the 18-month incidence of these conditions. The incidence of five chronic conditions over an 18-month follow-up period post injury was substantial. Persistent pain at 18 months was associated with this elevated incidence, with population attributable fraction estimates suggesting that 37-39% of incident conditions may be attributed to exposure to high levels of persistent pain.

Etiology of acute febrile illness in the peruvian amazon as determined by modular formatted quantitative PCR: a protocol for RIVERA, a health facility-based case-control study

BackgroundThe study of the etiology of acute febrile illness (AFI) has historically been designed as a prevalence of pathogens detected from a case series. This strategy has an inherent unrealistic assumption that all pathogen detection allows for causal attribution, despite known asymptomatic carriage of the principal causes of acute febrile illness in most low- and middle-income countries (LMICs). We designed a semi-quantitative PCR in a modular format to detect bloodborne agents of acute febrile illness that encompassed common etiologies of AFI in the region, etiologies of recent epidemics, etiologies that require an immediate public health response and additional pathogens of unknown endemicity. We then designed a study that would delineate background levels of transmission in the community in the absence of symptoms to provide corrected estimates of attribution for the principal determinants of AFI.MethodsA case-control study of acute febrile illness in patients ten years or older seeking health care in Iquitos, Loreto, Peru, was planned. Upon enrollment, we will obtain blood, saliva, and mid-turbinate nasal swabs at enrollment with a follow-up visit on day 21–28 following enrollment to attain vital status and convalescent saliva and blood samples, as well as a questionnaire including clinical, socio-demographic, occupational, travel, and animal contact information for each participant. Whole blood samples are to be simultaneously tested for 32 pathogens using TaqMan array cards. Mid-turbinate samples will be tested for SARS-CoV-2, Influenza A and Influenza B. Conditional logistic regression models will be fitted treating case/control status as the outcome and with pathogen-specific sample positivity as predictors to attain estimates of attributable pathogen fractions for AFI.DiscussionThe modular PCR platforms will allow for reporting of all primary results of respiratory samples within 72 h and blood samples within one week, allowing for results to influence local medical practice and enable timely public health responses. The inclusion of controls will allow for a more accurate estimate of the importance of specific prevalent pathogens as a cause of acute illness.Study RegistrationProject 1791, Registro de Proyectos de Investigación en Salud Pública (PRISA), Instituto Nacional de Salud, Perú.

A Health-Impact Assessment of an Ergonomic Measure to Reduce the Risk of Work-Related Lower Back Pain, Lumbosacral Radicular Syndrome and Knee Osteoarthritis among Floor Layers in The Netherlands

Sand-cement-bound screed floor layers are at risk of work-related lower back pain, lumbosacral radicular syndrome and knee osteoarthritis, given their working technique of levelling screed with their trunk bent while mainly supported by their hands and knees. To reduce the physical demands of bending of the trunk and kneeling, a manually movable screed-levelling machine was developed for floor layers in the Netherlands. The aim of this paper is to estimate the potential health gains of working with a manually movable screed-levelling machine on the risk of lower back pain (LBP), lumbosacral radicular syndrome (LRS) and knee osteoarthritis (KOA) compared to traditional working techniques. This potential health gain was assessed using the epidemiological population estimates of the Population Attributable Fraction (PAF) and the Potential Impact Fraction (PIF), combined with work-related risk estimates for these three disorders from systematic reviews. The percentage of workers exceeding these risk estimates was based on worksite observations among 28 floor layers. For LBP, 16/18 workers were at risk when using traditional working techniques, with a PAF = 38%, and for those using a manually movable screed-levelling machine, this was 6/10 with a PIF = 13%. For LRS, these data were 16/18 with a PAF = 55% and 14/18 with a PIF = 18%, and for KOA, 8/10 with a PAF = 35% and 2/10 with a PIF = 26%. A manually movable screed-levelling machine might have a significant impact on the prevention of LBP, LRS and KOA among floor layers in the Netherlands, and health-impact assessments are a feasible approach for assessing health gains in an efficient way.

Population attributable fraction estimates of cardiovascular diseases in different blood pressure levels in a large-scale cross-sectional study: a focus on prevention strategies and treatment coverage.

Hypertension is one of the major modifiable risk factors in developing cardiovascular diseases (CVD). Hence, we aimed to ascertain age- and sex-specific population attributable fraction (PAF) for CVD in different blood pressure levels to implement efficient preventive strategies at the population level. Participants' data were obtained from the Iranian stepwise approach for surveillance of noncommunicable disease risk factors (STEPs) survey to calculate PAF in four subsequent phases. In phase 0, PAF was measured, irrespective of the diagnosis status. In phase 1, the theoretical minimum range of 115 ≤SBP less than 130 mmHg was considered as the low-risk and measurements equal to or higher than 130 mmHg as the high-risk group. Across phase 2, patients were divided into normal and hypertensive groups based on the American College of Cardiology/American Heart Association guideline. In phase 3, patients were divided into two categories based on treatment coverage. A total number of 27 165 participants aged ≥25 years had valid blood pressure measurements and were enrolled. Phase 0: PAF generally had an upward trend with age advancing. Phase 1: participants with BP ≥130 mmHg comprised the largest PAF, extending from 0.31 (0.25-0.37) in older male individuals to 0.85 (0.79-0.91) in younger females. Phase 2: higher values were found in younger ages for hypertension. Phase 3 represented that attributable fractions among hypertensive patients who received treatment were much lower than drug-naïve hypertensive participants. Our study enlightens the necessity for implementing effective screening strategies for the younger generation and providing adequate access to antihypertensive medications for the low-risk population.

A nationwide study on sleep complaints and associated factors in older adults: ELSI-Brazil.

Sleep problems, such as difficulty falling asleep, staying asleep, early awakening with failure to continue sleep, and altered sleep-wake cycle, are common in the general population. This cross-sectional study with 6,929 older adults (≥ 60 years) aimed to estimate the prevalence of different types of sleep problems, their associated factors, and the population-attributable fraction of associated factors among older adults. The outcome variables consisted of self-reported sleep problems: insomnia (initial, intermediate, late, and any type of insomnia), poor sleep quality, and daytime sleepiness. The independent variables were sociodemographic and behavioral characteristics and health conditions. The prevalence proportions were initial insomnia (49.1%), intermediate insomnia (49.2%), late insomnia (45.9%), any type of insomnia (58.6%), poor sleep quality (15.6%), and daytime sleepiness (38.4%). Female sex, presence of two or more chronic diseases, not eating the recommended amount of fruits and vegetables, and regular and bad/very bad self-rated health were positively associated with the sleep problems investigated. Consuming alcohol once a month or more was inversely associated with initial insomnia. Population attributable fraction estimates ranged from 3% to 19% considering two or more chronic diseases, not eating the recommended amount of fruits and vegetables, and regular and bad/very bad self-rated health. High prevalence of self-reported sleep problems was evinced in older adults. These results can be useful to guide public health services in the creation of informational, evaluative, and screening strategies for sleep problems in older Brazilian adults.

Estimating the burden of disease attributable to high ambient temperature across climate zones: methodological framework with a case study.

With high temperature becoming an increasing health risk due to a changing climate, it is important to quantify the scale of the problem. However, estimating the burden of disease (BoD) attributable to high temperature can be challenging due to differences in risk patterns across geographical regions and data accessibility issues. We present a methodological framework that uses Köppen-Geiger climate zones to refine exposure levels and quantifies the difference between the burden observed due to high temperatures and what would have been observed if the population had been exposed to the theoretical minimum risk exposure distribution (TMRED). Our proposed method aligned with the Australian Burden of Disease Study and included two parts: (i) estimation of the population attributable fractions (PAF); and then (ii) estimation of the BoD attributable to high temperature. We use suicide and self-inflicted injuries in Australia as an example, with most frequent temperatures (MFTs) as the minimum risk exposure threshold (TMRED). Our proposed framework to estimate the attributable BoD accounts for the importance of geographical variations of risk estimates between climate zones, and can be modified and adapted to other diseases and contexts that may be affected by high temperatures. As the heat-related BoD may continue to increase in the future, this method is useful in estimating burdens across climate zones. This work may have important implications for preventive health measures, by enhancing the reproducibility and transparency of BoD research.

The social determinants of substance use associated with deaths of despair: Individual risks and population impacts

As the incidence of deaths from external causes including poisonings, suicide, and alcohol-related liver disease, increases in countries such as the United States and Canada, a better understanding of the fundamental social determinants of the substance use underlying these so-called “deaths of despair”, at the population level, is needed. Using data from the nationally representative data from the Canadian Community Health Survey (2003, 2015–2016, 2018 cycles) (N = 30,729), the independent associations between age, sex, marital status, immigrant status, race/ethnicity, education, income, rurality, affective health and the use of illicit substances, opioids (without distinction for prescription status), problematic levels of alcohol, and combined past-year use (≥2) of substances, were explored using multivariate logistic regression, marginal risk, and population attributable fraction estimation, with propensity score-adjusted sensitivity analyses. Males, those who were under 29 years, without a partner, born in Canada, White, or had an affective disorder reported both higher use of individual substances and multiple substances in the past year. Social determinants appear to explain a substantial proportion of substance use patterns overall. Between 10% and 45% of illicit substance, problematic alcohol, and polysubstance use prevalence was attributable to non-partnered marital status, non-immigrant status, and White race/ethnicity. Of opioid use prevalence, 25% was attributable to White race/ethnicity, 13% to affective disorder status and 4% to lower-income. Though not all substance use will result in substance-related morbidity or mortality, these findings highlight the role of social determinants in shaping the intermediary behavioural outcomes that shape population-level risk of “deaths of despair”.

Association between COVID-19 infection and work exposure assessed by the Mat-O-Covid job exposure matrix in the CONSTANCES cohort

ObjectivesThe COVID-19 pandemic has brought to light a new occupational health threat. We aimed to evaluate the association between COVID-19 infection and work exposure to SARS-CoV-2 assessed by a job-exposure...

Burden of cardiovascular diseases and depression attributable to psychosocial work exposures in 28 European countries.

BackgroundThis study aimed to estimate the annual burden of cardiovascular diseases and depression attributable to five psychosocial work exposures in 28 European Union countries (EU28) in 2015.MethodsBased on available attributable fraction estimates, the study covered five exposures, job strain, effort–reward imbalance, job insecurity, long working hours and workplace bullying; and five outcomes, coronary/ischemic heart diseases (CHD), stroke, atrial fibrillation, peripheral artery disease and depression. We estimated the burden attributable to each exposure separately and all exposures together. We calculated Disability-Adjusted Life Years (DALY) rate per 100 000 workers in each country for each outcome attributable to each exposure and tested the differences between countries and between genders using the Wald test.ResultsThe overall burden of CHD attributable to the five studied psychosocial work exposures together was estimated at 173 629 DALYs for men and 39 238 for women, 5092 deaths for men and 1098 for women in EU28 in 2015. The overall burden of depression was estimated at 528 549 DALYs for men and 344 151 for women (respectively 7862 and 1823 deaths). The three highest burdens in DALYs in EU28 in 2015 were found for depression attributable to job strain (546 502 DALYs), job insecurity (294 680 DALYs) and workplace bullying (276 337 DALYs). Significant differences between countries were observed for DALY rates per 100 000 workers.ConclusionsSuch results are necessary as decision tools for decision-makers (governments, employers and trade unions) when defining public health priorities and work stress preventive strategies in Europe.

A comparison of risk factors for cryptosporidiosis and non-cryptosporidiosis diarrhoea: A case-case-control study in Ethiopian children.

Cryptosporidiosis is a major cause of diarrhoea in young children in low-and-middle-income countries. New interventions should be informed by evidence pertaining to risk factors and their relative importance. Inconsistencies in the literature may to some extent be explained by choice of methodology, furthermore, most previous risk factor studies compared cryptosporidiosis cases to diarrhoea cases of other aetiologies rather than with controls without diarrhoea. We investigated a broad set of factors in under-2-year-olds presenting with diarrhoea to a hospital and a health center in southwestern Ethiopia. We applied quantitative cut-offs to distinguish between cryptosporidiosis and incidental Cryptosporidium infection or carriage, a hierarchical causal framework to minimize confounding and overadjustment, and a case-case-control design, to describe risk factors for both cryptosporidiosis and non-cryptosporidiosis diarrhoea. Moderate and severe acute malnutrition were strongly associated with both cryptosporidiosis and non-cryptosporidiosis diarrhoea. Previous healthcare attendance and low maternal education were only associated with cryptosporidiosis, whereas unsafe child stool disposal, prematurity and early cessation of exclusive breastfeeding were significantly associated with non-cryptosporidiosis diarrhoea only. By estimation of population attributable fractions, socioeconomic factors-specifically low maternal education-and public tap water use, were apparently more important risk factors for cryptosporidiosis than for non-cryptosporidiosis diarrhoea. Nutritional management of moderate acute malnutrition may be an effective intervention against cryptosporidiosis, particularly if combined with targeted therapy for cryptosporidiosis which, again, may mitigate nutritional insult. Focused caregiver education in healthcare settings and follow-up of children with acute malnutrition may prevent or improve outcomes of future episodes of cryptosporidiosis.

Modifiable risk factors and incidence of gout: Estimation of population attributable fraction in the US

ObjectiveThe burden of gout is substantial in the United States (US). Most gout cases can be attributed to modifiable risk factors, while systematic evidence-based assessment of gout cases and incidence attributable to the risk factors in the US is limited. MethodsThe estimated cases and incidence of gout in the US was obtained from global burden of disease (GBD) study 2019. We calculated the exposure rate of risk factors from National Health and Nutrition Examination Survey (NHANES) 2009–2010, since we estimated an average induction time of 10 years for risk factors and gout. We also conducted a meta-analysis to evaluate the associations of modifiable risk factors and gout in the US population. Furthermore, the population attributable fraction (PAF) was calculated using based on the prevalence of risk factors and relative risk (RR) from the meta-analysis. ResultsThe weighted prevalence of hypertension was 14.37%, and the average body mass index (BMI) and alcohol consumption was 28.50 kg/m2 and 7.14 g/d, respectively. Meta-analysis showed that individuals with hypertension had a higher risk of gout (2.12, 95% CI 1.88 to 2.40). For every five units of increase in BMI, the risk of gout increased by 1.48-fold (95% CI 1.26 to 1.75). The pooled RR was 1.21 (95% CI 1.13 to 1.29) for every 10 g/day increment of alcohol consumption. BMI, hypertension and alcohol consumption accounted for 53.58%, 13.85% and 12.66% of gout cases, respectively. Overall, 65.05% of gout incidence was attributable to the joint effects of these three risk factors. ConclusionHypertension, excess BMI and high alcohol consumption were responsible for approximately 65% of gout incidence in the US in 2019. Reducing the exposure to these factors can effectively reduce the incidence of gout.