ABSTRACT
OBJECTIVE: Data regarding alcohol-caused health harms are required by policymakers for setting health priorities. However, these estimations are currently resource intensive, and estimates vary substantially by method. Thus, many countries, states, and regions do not track these harms. We address this limitation through creation of the International Model of Alcohol Harms and Policies (InterMAHP), an open-access alcohol harms estimator. InterMAHP consists of methodologies and program software designed to assist alcohol research teams in estimating alcohol-attributable mortality and morbidity, by region. It is available at www.intermahp.cisur.ca. Application is illustrated through updated estimates of alcohol-attributable mortality in Canada. METHOD: Mortality counts and per capita alcohol sales were obtained from Statistics Canada. Drinking and bingeing prevalences were obtained from the Canadian Substance Use Exposure Database. InterMAHP automated the calculations of alcohol-attributable fractions (AAF) using the modern AAF formulation and a gamma distribution to specify the continuous prevalence distribution of consumption. RESULTS: Alcohol is a leading driver of mortality in Canada. In 2016, more than 14,800 (95% CI [12,435, 17,127]) deaths were alcohol attributable, representing 5.5% of all deaths. This burden is borne disproportionately by men (79%). Among condition categories, cancer is the leading cause of alcohol-attributable mortality in both men and women. CONCLUSIONS: InterMAHP has the potential to assist public health researchers globally in estimating alcohol harms. This open-access software was used to estimate alcohol-attributable mortality in Canada, which was shown to be substantial. Policies proven to reduce alcohol consumption and related harms should be considered to reduce this burden.
Subject(s)
Alcohol Drinking/epidemiology , Alcohol Drinking/mortality , Alcohol-Related Disorders/epidemiology , Models, Statistical , Adolescent , Adult , Aged , Canada/epidemiology , Commerce/statistics & numerical data , Female , Humans , Male , Middle Aged , Morbidity , Prevalence , Public Policy , Software , Young AdultABSTRACT
This paper presents the empirical probability density of the power spectral density as a tool to assess the field performance of passive acoustic monitoring systems and the statistical distribution of underwater noise levels across the frequency spectrum. Using example datasets, it is shown that this method can reveal limitations such as persistent tonal components and insufficient dynamic range, which may be undetected by conventional techniques. The method is then combined with spectral averages and percentiles, which illustrates how the underlying noise level distributions influence these metrics. This combined approach is proposed as a standard, integrative presentation of ambient noise spectra.
Subject(s)
Environmental Monitoring/methods , Models, Theoretical , Noise , Signal Processing, Computer-Assisted , Ultrasonics , Environmental Monitoring/instrumentation , Fourier Analysis , Motion , Oceans and Seas , Pressure , Probability , Sound Spectrography , Time Factors , Transducers, Pressure , Ultrasonics/instrumentation , WaterABSTRACT
Rising underwater noise levels from shipping have raised concerns regarding chronic impacts to marine fauna. However, there is a lack of consensus over how to average local shipping noise levels for environmental impact assessment. This paper addresses this issue using 110 days of continuous data recorded in the Strait of Georgia, Canada. Probability densities of ~10(7) 1-s samples in selected 1/3 octave bands were approximately stationary across one-month subsamples. Median and mode levels varied with averaging time. Mean sound pressure levels averaged in linear space, though susceptible to strong bias from outliers, are most relevant to cumulative impact assessment metrics.
