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Chapter 7: Problem 48

The mortality experience of 8146 male employees of a research, engineering, and metal-fabrication plant in Tonawanda, New York, was studied from 1946 to 1981 [2]. Potential workplace exposures included welding fumes, cutting oils, asbestos, organic solvents, and environmental ionizing radiation, as a result of waste disposal during the Manhattan Project of World War II. Comparisons were made for specific causes of death between mortality rates in workers and U.S. white-male mortality rates from 1950 to 1978 . Suppose that 17 deaths from cirrhosis of the liver were observed among workers who were hired prior to 1946 and who had worked in the plant for 10 or more years, whereas 6.3 were expected based on U.S. white-male mortality rates. What is the SMR for this group?

Short Answer

Expert verified
The SMR is approximately 2.70.

Step by step solution

01

Understand the Concept of SMR

The Standardized Mortality Ratio (SMR) is a measure that compares the observed number of deaths in a study population to the number of deaths that would be expected based on a larger reference population. It is calculated as the ratio of observed deaths to expected deaths.
02

Identify the Observed and Expected Deaths

From the problem, we know that there are 17 observed deaths from cirrhosis of the liver in the worker group. The expected number of deaths, based on U.S. white-male mortality rates, is 6.3.
03

Calculate the SMR

To find the SMR, divide the observed number of deaths by the expected number of deaths:\[SMR = \frac{\text{Observed Deaths}}{\text{Expected Deaths}} = \frac{17}{6.3}\]
04

Simplify the Calculation

Perform the division to get the SMR:\[SMR = \frac{17}{6.3} \approx 2.70\] This means the mortality rate in the studied group is 2.70 times higher than expected based on the reference population.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Mortality Rates
Mortality rates are a critical measure in healthcare and public health. They represent the frequency of deaths in a specific population over a certain period of time. These rates help us understand the health status and mortality pattern of a community. They are typically expressed as the number of deaths per 1,000 or 100,000 individuals per year.

In epidemiological studies, mortality rates allow researchers to compare different populations or subgroups. These comparisons can reveal factors that affect death rates. These factors might include lifestyle, healthcare access, or workplace conditions. Tracking mortality rates over time also indicates whether health interventions are effective. When we study specific causes of death, such as cancer or heart disease, mortality rates help highlight areas needing more attention and resources.
  • Key points: Mortality rates show how often deaths occur in a given population.
  • They are essential for assessing public health and guiding policy decisions.
  • Mortality rates can be specific to certain causes of death, like disease or accidents.
Observed vs Expected Deaths
The concept of observed versus expected deaths is fundamental in determining health patterns. Observed deaths are the actual number of deaths recorded in a specific population or group. In contrast, expected deaths are the number estimated based on data from a broader reference group, taking into account factors like age and gender.

In epidemiology, comparing observed to expected deaths helps assess whether a group faces higher health risks than the general population. The difference between these figures can indicate potential health hazards, such as environmental exposures or lifestyle factors affecting mortality. This comparison is crucial for identifying inequalities or excess mortality in specific groups.
  • Observed deaths: Actual recorded number of deaths in a group.
  • Expected deaths: Predicted number of deaths based on wider population data.
  • This comparison is central to identifying health disparities or excess risks.
Epidemiological Studies
Epidemiological studies are essential for understanding how diseases and health issues affect populations. They focus on the distribution, patterns, and determinants of health conditions in specific groups. Through these studies, researchers can identify risk factors for diseases and outcomes related to specific exposures, like workplace hazards mentioned in the exercise scenario.

These studies use various methods, including surveys, cohort studies, and case-control studies, to collect data. Epidemiologists analyze the data to find connections between health outcomes and possible causes. For instance, they might look at how exposure to certain chemicals affects mortality rates among workers, as with the Tonawanda plant workers.
  • Key objectives: Recognizing patterns and causes of diseases to guide interventions.
  • Types of data: Surveys, records, environmental exposure data.
  • Epidemiology helps inform public health strategies and disease prevention efforts.

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Most popular questions from this chapter

A clinical epidemiologic study was conducted to determine the long-term health effects of workplace exposure to the process of manufacturing the herbicide ( 2,4,5 trichlorophenoxy) acetic acid \((2,4,5-\mathrm{T}),\) which contains the contaminant dioxin [7]. This study was conducted among active and retired workers of a Nitro, West Virginia, plant who were exposed to the \(2,4,5-T\) process between 1948 and 1969 . It is well known that workers exposed to 2,4,5 -T have high rates of chloracne (a generalized acneiform eruption). Less well known are other potential effects of \(2,4,5-T\) exposure. One of the variables studied was pulmonary function. Suppose the researchers expect from general population estimates that \(5 \%\) of workers have an abnormal forced expiratory volume (FEV); defined as less than \(80 \%\) of predicted, based on their age and height. They found that 32 of 203 men who were exposed to \(2,4,5-T\) while working at the plant had an abnormal FEV. What hypothesis test can be used to test the hypothesis that the percentage of abnormal FEV values among exposed men differs from the general-population estimates?

Osteoporosis is an important cause of morbidity in middle-aged and elderly women. Several drugs are currently used to prevent fractures in postmenopausal women. Suppose the incidence rate of fractures over a 4 -year period is known to be \(5 \%\) among untreated postmenopausal women with no previous fractures. A pilot study conducted among 100 women without previous fractures aims to determine whether a new drug can prevent fractures. It is found that two of the women have developed fractures over a 4-year period. Suppose the new drug is hypothesized to yield a fracture rate of \(2.5 \%\) over a 4 -year period. How many subjects need to be studied to have an \(80 \%\) chance of detecting a significant difference between the incidence rate of fractures in treated women and the incidence rate of fractures in untreated women (assumed to be \(5 \%\) from Problem 7.105 )?

What will be the result if we conclude that the mean is greater than 45 when the actual mean is \(45 ?\) (i) We have made a type I error. (ii) We have made a type II error. (iii) We have made the correct decision.

Iron-deficiency anemia is an important nutritional health problem in the United States. A dietary assessment was performed on 51 boys 9 to 11 years of age whose families were below the poverty level. The mean daily iron intake among these boys was found to be 12.50 mg with standard deviation 4.75 mg. Suppose the mean daily iron intake among a large population of \(9-\) to 11 -year-old boys from all income strata is \(14.44 \mathrm{mg}\). We want to test whether the mean iron intake among the low-income group is different from that of the general population. State the hypotheses that we can use to consider this question.

The researchers decide to extend the study to a 5 -year period and find that 20 of the 200 people develop a cataract over a 5 -year period. Suppose the expected incidence of cataracts among \(65-\) to 69 -year-olds in the general population is \(5 \%\) over a 5 -year period. Test the hypothesis that the 5-year incidence rate of cataracts is different in the excessive-sunlight-exposure group compared with the general population, and report a \(p\) -value (two-sided).
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