Gender Adjustment in Mortality Rates

Abstract

Age- and gender-related adjustment to measurements enable researchers to make more accurate comparisons between two groups of people (Hoyert & Anderson, 2001). By controlling specific variables, measurements become more meaningful (Naing, 2000). This is particularly important in epidemiology when comparing two populations with distinguishing characteristics when those characteristics have a direct effect on the issue measured (Anderson & Rosenberg, 1998). One commonly used example is comparing the death rates in Florida and Alaska (McKenzie, J., Pinger, R., & Kotecki, J., 2012). Florida’s population has a significantly higher number of older people. Older people tend to die more often than younger people. Therefore, comparing the basic, or crude, mortality rate for the entire population of each state is less useful than comparing mortality rates adjusted for age differences (Bhopal, 2002). Adjusting for age and gender in different populations will make comparisons more useful and more correct.

Age and Gender Adjustment in Two Managed Care Organizations

Age- and gender-related adjustments to measurements enable researchers to make more accurate comparisons between two groups of people (Hoyert & Anderson, 2001). By controlling for specific variables, measurements become more meaningful (Naing, 2000). This is particularly important in epidemiology when comparing two populations with distinguishing characteristics when those characteristics have a direct effect on the issue measured (Anderson & Rosenberg, 1998). One commonly used example is comparing the death rates in Florida and Alaska (McKenzie, J., Pinger, R., & Kotecki, J., 2012). Florida’s population has a significantly higher number of older people. Older people tend to die more often than younger people. So comparing the basic, or crude, mortality rate for the entire population of each state, or those with more air pollution, is less useful than comparing mortality rates adjusted for age differences (Bhopal, 2002).

Cardiovascular Mortality Rates

Using the statistics from the textbook (Fleming, 2008) alone, the Blue Grass East (BGE) Managed Care Organization (MCO) has a higher crude (or unadjusted) cardiovascular mortality rate, at 290 per 100,000. Blue Grass West (BGW) has a 160 (per 100,000) crude cardiovascular mortality rate. Using the information given, applying the cardiovascular rate to the actual population of BGW would mean that 192 people out of the 120,000 are affected by cardiovascular mortality.

Age-Adjusted Cardiovascular Mortality Rates

BGE 77% of the population less than 55 years old

BGW 90% of the population less than 55 years old

Using the direct age adjustment technique and the U.S. population as the standard along with the information in Table 6.7 (Fleming, 2008, p. ), the age-adjusted rates are:

BGE Age-Specific Mortality Rates

Less than 55: 22

55+: 1300

BGW:

Age-Specific Mortality Rates

Less than 55: 23

55%: 1315

The U.S. Mix in the population is 210,000,000 for the 1–54 age group and 70,000,000 for the 55+ age group. This gives a rate (which is essentially a percentage breakdown of the population) of .75 for the population under 55 and .25 for the population 55+.

Take the number of deaths in a population multiplied by the rate for that population. Then multiply by the weight to figure the total for that section of the population considered. Add both sections to get the total weighted rate.

For BGE: 46,200 (number of deaths expected for 1-54 age range) = 0.462 crude rate

100,000 (total population of BGE)

910

22 * .75 = 16.5

1,300 * .25 = 325

Total age-adjusted cardiovascular rate for BGE = 341.5

But if we use the breakdown of each MCO given, then we need to use .77 as a weight for the younger group and 0.23 as a weight for the older group. This gives us: 12.705 and 74.75, totaling 87.455. BGE’s total age-adjusted cardiovascular mortality rate is 87.455.

For BGW:

23*.75 = 17.5

1,315*.25 = 328.75

Total age-adjusted cardiovascular mortality rate = 346

But using the percentage breakdown of BGW, we use 0.90 as the weight for the younger group and 0.10 as the weight for the older group, giving us 15.75 and 32.875, totaling 48.625. BGW’s total age-adjusted cardiovascular mortality rate is 48.625. This means that BGE has a higher age-adjusted cardiovascular mortality rate.

Age- and Gender-Adjusted Cardiovascular Mortality Rates

Using Table 6.8 from the textbook (Fleming, 2008, p. ), we can adjust for both age and gender.

For BGE:40% men

BGW: 60% men

We must figure the rate for men and the rate for women separately, so we can use our weighting system to account for the gender divide in each MCO.

For BGE:

Men: 34,650 + 490,000 = 524,650 (Total for Men)

US stats: 105,000,000 + 35,000,000 = 140,000,000

524,650 / 140,000,000 = 0.0037475

374.75 per 100,000

When weighted: 374.75 * .40 = 149.9 (Men’s weighted part of the total rate)

Women: 13,000 + 480,000 = 493,000 (Total for Women)

US stats: 100,000,000 + 40,000,000 = 140,000,000

493,000 / 140,000,000 =

352.14 per 100,000

When weighted: 352.14 * .60 = 211.284 (Women’s weighted part of total)

Added together:

Men (Weighted) 149.9 + (Women weighted) 211.284 = 361.19 (Weighted Total)

For BGW:

Men: 542,150/140,000,000 =

387.25 per 100,000

387.25 * 0.60 = 232.35 (Men’s weighted part of total)

Women: 477,000/140,000 * 100,000 = 340.71

340.71 * -.40 = 136.85 (Women’s weighted part of total)

232.35 + 136.85 = 368.64 (Weighted Total)

With age and gender-adjusted rates, BGW has the higher mortality rates.

These separate examples have shown how adjusting for age and adjusting for gender can refine statistical information to make it easier to compare two different populations.

References

Anderson, R. N., & Rosenberg, H. M. (1998). Age standardization of death rates: Implementation of the year 2000 standard. National Vital Statistics Reports, 47(3), 1-20. Hyattsville, MD: National Center for Health Statistics. Retrieved from http://www.cdc.gov/nchs/data/nvsr/nvsr47/nvs47_03.pdf

Bhopal, R. (2002). Concepts of epidemiology: An integrated introduction to the ideas, theories, principles, and methods epidemiology. Oxford, UK: Oxford University Press. Retrieved from http://shdrc.skums.ac.ir/dorsapax/userfiles/file/Epidemiology_Concepts_2002.pdf

Fleming, S. T. (2008). Managerial epidemiology: Concepts and cases (2nd ed.). Chicago: Health Administration Press.

Hoyert, D. L., & Anderson R. N. (2001). Age-adjusted death rates: Trend data based on the year 2000 standard population. National Vital Statistics Reports, 49(9), 1-8. Hyattsville, MD: National Center for Health Statistics. http://www.cdc.gov/nchs/data/nvsr/nvsr49/nvsr49_09.pdf

McKenzie, J., Pinger, R., & Kotecki, J. (2012). An Introduction to Community and Public Health (7th Ed.). Sudbury, MA: Jones & Bartlett Learning. Retrieved from http://samples.jbpub.com/9780763790110/90110_CH01_McKenzie.pdf

Naing, N. N. (2000). Easy way to learn standardization: Direct and indirect methods. Malaysian Journal of Medical Sciences, 7(1), 10-15. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3406211/