# Situation: The public health nurse of a Rural Health Unit (RHU) prepares the annual health statistics report of a municipality with a midyear population of 62,000. The report compares two years: Year before last — midyear population 60,000; total deaths 400; cardiovascular deaths 72 Last year — midyear population 62,000; total deaths 300; cardiovascular deaths 72 A council member points out that cardiovascular disease rose from 18% to 24% of all deaths. Which conclusion do these data BEST support?

> source: MyMerci (mymerci.kr)  
> url: https://mymerci.kr/pages/nclex_q.php?qn_id=627090  
> language: ko  
> subject: Nursing Practice I — Community Health Nursing

## 문제

Situation: The public health nurse of a Rural Health Unit (RHU) prepares the annual health statistics report of a municipality with a midyear population of 62,000.

The report compares two years:
Year before last — midyear population 60,000; total deaths 400; cardiovascular deaths 72
Last year — midyear population 62,000; total deaths 300; cardiovascular deaths 72
A council member points out that cardiovascular disease rose from 18% to 24% of all deaths. Which conclusion do these data BEST support?

## 보기

1. The share rose because other deaths fell, not because the risk rose **✔ 정답**
2. Residents faced a higher risk of dying from cardiovascular disease last year
3. Deaths from other causes rose, pushing up the cardiovascular share
4. The change in share cannot be judged without age-standardized rates

**정답: 1**

## 해설

The 18% and 24% figures are proportionate mortality ratios (72 ÷ 400 and 72 ÷ 300), which show the share of deaths, not the risk of dying. The cause-specific death rate, which measures risk, was 72 ÷ 60,000 × 100,000 = 120.0 per 100,000 and then 72 ÷ 62,000 × 100,000 = 116.1 per 100,000, a slight fall. The share rose because deaths from other causes fell from 328 to 228 while cardiovascular deaths stayed at 72.

## 심화 해설

Core concept: Proportionate mortality ratio versus cause-specific death rate

The figures cited by the council member—18% and 24%—are proportionate mortality ratios (PMR). A PMR answers only one question: among all people who died, what fraction died from a specific cause? It does not measure how likely a living person is to die from that cause. The actual risk of dying from cardiovascular disease is captured by the cause-specific death rate, which uses the total midyear population as the denominator.

Calculating the cause-specific death rate for cardiovascular disease shows a slight decline. In the year before last, the rate was 72 ÷ 60,000 × 100,000 = 120.0 per 100,000. Last year, it was 72 ÷ 62,000 × 100,000 = 116.1 per 100,000. The number of cardiovascular deaths stayed exactly the same at 72, while the population grew. Therefore, the risk of dying from cardiovascular disease did not rise—it fell modestly.

The PMR rose from 18% to 24% only because deaths from other causes dropped sharply, from 328 to 228, while cardiovascular deaths remained constant at 72. When the denominator of a proportion shrinks, the proportion itself can rise even if the numerator does not change. This is a classic pitfall in interpreting mortality statistics.

Watch out! A rising PMR is often misinterpreted as evidence of increasing disease risk. The PMR is a measure of relative cause composition among deaths, not a measure of mortality risk in the population.

Key point! To judge whether residents faced a higher risk of dying from cardiovascular disease, use the cause-specific death rate, not the PMR. The cause-specific death rate here fell from 120.0 to 116.1 per 100,000.

The provided reference on the proportionate mortality ratio reinforces this distinction. It notes that the PMR is a ratio of deaths from a cause of interest to deaths from other causes, and that interpreting it as a direct measure of risk requires specific conditions. The abstract highlights that an alternative—the mortality odds ratio—can be interpreted as an observed-to-expected ratio, but the PMR itself remains a measure of cause composition among decedents. In this municipality, the shift in composition reflects fewer competing deaths, not a worsening cardiovascular burden.

| Measure | Formula (last year) | Value | What it tells you |
| --- | --- | --- | --- |
| Proportionate mortality ratio (PMR) | Cardiovascular deaths ÷ total deaths × 100 | 72 ÷ 300 × 100 = 24% | Share of all deaths due to cardiovascular disease |
| Cause-specific death rate | Cardiovascular deaths ÷ midyear population × 100,000 | 72 ÷ 62,000 × 100,000 = 116.1 | Risk of dying from cardiovascular disease in the population |

The council member’s observation is arithmetically correct, but the conclusion drawn from it is not. The share rose because other deaths fell, not because the risk of cardiovascular death rose. Deaths from other causes declined from 328 to 228, which mechanically increased the cardiovascular share of a smaller total. This is the best-supported conclusion from the data.

## 임상 시나리오

Interpreting Mortality Statistics in Annual ReportsDistinguishing Share of Deaths from Risk of Dying
A rising proportionate mortality ratio (PMR) does not mean the risk of dying from that cause increased. In this case, the PMR for cardiovascular deaths rose from 18% to 24% only because total deaths from other causes fell from 328 to 228, while cardiovascular deaths stayed constant at 72.

To assess true risk, calculate the cause-specific death rate. The rate was 120.0 per 100,000 the year before last and 116.1 per 100,000 last year—a slight decline. The numerator stayed the same while the population denominator grew.

CautionNever interpret a change in PMR as a change in mortality risk without checking the cause-specific death rate. A shrinking denominator of total deaths can inflate a cause's share even when its risk is stable or falling.

## 핵심 개념

- **Proportionate Mortality Ratio (PMR)** — The proportion of all deaths in a population that are due to a specific cause. It reflects the share of deaths, not the risk of dying from that cause.
- **Cause-Specific Death Rate** — The number of deaths from a specific cause per population (e.g., per 100,000) during a given time. It is a measure of mortality risk from that cause.
- **Midyear Population** — An estimate of the population size at the midpoint of a year, used as the denominator in calculating annual rates.
- **Denominator Effect** — A change in a proportion or rate caused by a change in the denominator (e.g., total deaths) rather than the numerator (e.g., deaths from a specific cause).

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