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Transcript
EHS 655
Lecture 2:
Introduction and overview,
continued
Setting the stage

So, what exposure will we be focusing on this
semester?

Exposure selected based on…





Ubiquity of exposure (e.g., many sources)
Variability of exposure
Range of health effects
Availability of dataset
Over-emphasis on chemicals at SPH
2
Setting the stage

Will use dataset of noise exposures and two health
outcomes related to noise



Hearing loss
Hypertension
Concepts from this analysis can be readily
applied to


Any hazard
Workplace and community
exposures
3
Noise and associated health effects

Noise among most common occupational exposures

Noise-induced hearing loss (NIHL) among most
common, well-understood occupational diseases





100% preventable, but permanent, irreversible
Profound social and occupational effects
Linked to injuries and non-auditory effects
Time course of NIHL from variable noise unclear
Non-auditory effects of noise less well-understood

Hypertension, ischemic heart disease, etc
NIOSH, 1998; Berger, Royster, Royster, Driscoll, Layne, 2000
4
Noise and hearing loss
Henderson D et al, Ear Hear 2006
5
Noise and hearing loss
Henderson D et al, Ear Hear 2006
6
Noise and hearing loss
7
Noise and hearing loss
8
Noise and CVD
Van Kempen et al, Environ Health Persp, 2002
9
Environmental noise and CVD
Meta-analysis, 7-17% increase in CVD per 10 dB increase
Basner et al, Lancet, 2014
10
Environmental
noise and CVD
World Health Organization: >1
million healthy life years (i.e.,
Disability-Adjusted Life Years,
DALYs) lost annually due to
environmental noise
(Note: does not consider
occupational noise)
Basner et al, Lancet, 2014
11
Environmental noise and CVD
Estimated US
CVD savings
from 5 dB
reduction in
population
noise in 2014:
$3.9 billion
Swinburn et al, Am J Prev Med, 2015
12
Occup.
noise and
CVD
Retrospective cohort, 27,464 workers, mean 92 dBA, 24 years avg f/u
Davies et al, Epidemiol, 2005
13
One way to assess CVD: blood pressure


Measured using 2 numbers (e.g., 120 over 80 or 120/80)
First number = systolic blood pressure


Measures the pressure in blood vessels when heart beats
Second number = diastolic blood pressure

Measures pressure in blood vessels when heart rests between
beats
https://www.cdc.gov/bloodpressure/measure.htm
14
Okay, so noise is bad. Why do we
need another study?

Anyone know Hill’s Criteria for Causality?
http://nfs.unipv.it/nfs/minf/dispense/patgen/lectures/files/disease_causality.html
15
NIHL claims in one industry with highly
variable noise
7.5% 6000
workforce 1984-96, 21% accepted NIHL claims
Number of claims
5000
4000
1998 cost: $57 mil
All other
industries
All Industries
3000
Construction
2000
1000
0
84 85 86 87 88 89 90 91 92 93 94 95 96 97 98
Year claim was filed (1984-1998)
Daniell, Fulton-Kehoe, Cohen, Swan, Franklin, 2002
16
Overview of study (some of) our data
come from

Prospective study of early NIHL among construction
workers, 2000-2010

Why are studies like this rare?

Workers recruited at start of apprenticeship programs

Annual subject visit to University of Washington,
Seattle with:



Extensive battery of hearing tests
Survey of work experience, tasks, perceptions of exposure
Direct exposure measurements on cohort infeasible
17
Blood pressure data from study

Did not actually collect blood pressure data

I have simulated data and added it to dataset provided

Everything else in the dataset is real
18
Data needed to understand risk of
health effects of noise
Frequency
Protective
behaviors
Duration
Dose
Personal
risk factors
Intensity
Variability
Frequency x Duration x Intensity
= Exposure
19
Exposure assessment in construction
20
Exposure assessment

Full-shift dosimetry measurements



Dosimeters datalog exposure
parameters at 1-min intervals



Convenience sample of construction workers at sites around
Puget Sound
Shifts not all exactly 8 hours
Average level (LEQ)
Maximum level (LMAX)
Workers simultaneously record
tasks, hearing protector use, etc.
21
Task-based exposure assessment
100.0
Task A
Task B
Task A
Task C
Task A
Noise Level (dBA)
90.0
80.0
70.0
60.0
Measured
Exposure
50.0
40.0
0
50
100
150
200
250
Time (Minutes)
22
Subjective rating (SR) of noise
exposure

Workers assess own noise exposure via SR
What percent of time were
you exposed to each of the
following noise levels at
work?
_____% No louder than a normal speaking voice
_____% As loud as a vacuum
_____% As loud as a gas lawnmower
_____% As loud as a chainsaw
The total should add to
about 100 percent.
_____% As loud or louder than a siren
Total = about 100%

Simultaneously measure noise exposure

Combine for quantitative exposure estimate
Neitzel, Daniell, Sheppard, Davies, Seixas, 2009
23
Data needed to understand risk of
health effects of noise
Frequency
Protective
behaviors
Duration
Dose
Personal
risk factors
Intensity
Variability
24
Variability – alternative metrics

Different exposure parameters may help explain
health effects



Average
Maximum or peak
Can also compute ratios of these parameters

Maximum/average (peakiness of levels)
Seixas, Sheppard, Neitzel, 2005; Rappaport, 1991
25
Data needed to understand risk of
health effects of noise
Frequency
Protective
behaviors
Duration
Dose
Personal
risk factors
Intensity
Variability
26
Non-occupational sources of noise in
life
Others?
27
Data needed to understand risk of
health effects of noise
Frequency
Protective
behaviors
Duration
Dose
Personal
risk factors
Intensity
Variability
28
Factors to consider regarding use of
hearing protectors

Is it used and is it effective?
29
Other protective “behaviors”

Acoustic reflex

Biomarker of exposure
and susceptibility

Temporary Threshold
Shift at 2 mins postexposure, TTS2
30
Data needed to understand risk of
health effects of noise
Frequency
Protective
behaviors
Duration
Dose
Personal
risk factors
Intensity
Variability
31
From the reading
Kauppinen 1991, Appl Occup Environ Hyg
32
Introduction to the data files

Types of files


Dataset files
Variable description files

You’ll be using and referring to both regularly

How they’ll be introduced

New version of dataset most weeks, with additional variables
and (at least once) more measurements
33
Introduction to Stata

The program

The do-file

Why use a do-file?




Ease of manipulation of data
Documentation of manipulations and analyses
Preserve original data file
I’m forcing you to
34
Resources

Statistics Consulting Group, University of CaliforniaLos Angeles Institute for Digital Research and
Education


Which statistical analysis should I use?
http://www.ats.ucla.edu/stat/mult_pkg/whatstat/
Stata online help files

Frequently asked questions on using Stata
http://www.stata.com/support/faqs/
35