The Standardized Mortality Ratio and Life Expectancy

1992 ◽  
Vol 135 (7) ◽  
pp. 824-831 ◽  
Author(s):  
Shan P. Tsai ◽  
Robert J. Hardy ◽  
C. P. Wen
Keyword(s):  
Life Expectancy ◽  
Standardized Mortality Ratio ◽  
Mortality Ratio

scholarly journals Comparison of three small-area mortality metrics according to urbanity in Korea: the standardized mortality ratio, comparative mortality figure, and life expectancy

2020 ◽  
Author(s):  
Ikhan Kim ◽  
Hwa-Kyung Lim ◽  
Hee-Yeon Kang ◽  
Young-Ho Khang
Keyword(s):  
Population Structure ◽  
Life Expectancy ◽  
Rural Areas ◽  
Small Area ◽  
Standardized Mortality Ratio ◽  
Small Areas ◽  
Mortality Figure ◽  
Specific Mortality ◽  
Small Area Level ◽  
Mortality Ratio

Abstract Background: This study aimed to compare three small-area level mortality metrics according to urbanity in Korea: the standardized mortality ratio (SMR), comparative mortality figure (CMF), and life expectancy (LE) by urbanity.Methods: We utilized the National Health Information Database to obtain annual small-area level age-specific numbers of population and deaths in Korea between 2013 and 2017. First, differences in the SMR by urbanity were examined, assuming the same age-specific mortality rates in all small-areas. Second, we explored the differences in ranking obtained using the three metrics (SMR, CMF, and LE). Third, the ratio of CMF to SMR by population was analyzed according to urbanity.Results: We found that the age-specific population distributions in urbanized areas were similar, but rural areas had a relatively old population structure. The age-specific mortality ratio also differed by urbanity. Assuming the same rate of age-specific mortality across all small-areas, we found that comparable median values in all areas. However, areas with a high SMR showed a strong predominance of metropolitan areas. The ranking by SMR differed markedly from the rankings by CMF and LE, especially in areas of high mortality, while the latter two metrics did not differ notably. The ratio of CMF to SMR showed larger variations in small-areas in rural areas, particularly in those with small populations, than in metropolitan and urban areas.Conclusions: In a comparison of multiple SMRs, bias could exist if the study areas have large differences in population structure. The use of CMF or LE should be considered for comparisons if it is possible to acquire age-specific mortality data for each small-area.

scholarly journals Comparison of three small-area mortality metrics according to urbanity in Korea: the standardized mortality ratio, comparative mortality figure, and life expectancy

2019 ◽  
Author(s):  
Ikhan Kim ◽  
Hwa-Kyung Lim ◽  
Hee-Yeon Kang ◽  
Young-Ho Khang
Keyword(s):  
Population Structure ◽  
Life Expectancy ◽  
Rural Areas ◽  
Urban Areas ◽  
Small Area ◽  
Mortality Data ◽  
Standardized Mortality Ratio ◽  
Mortality Figure ◽  
Specific Mortality ◽  
Mortality Ratio

Abstract Background: This study aimed to compare three small-area level mortality metrics according to urbanity in Korea: the standardized mortality ratio (SMR), comparative mortality figure (CMF), and life expectancy (LE) by urbanity.Methods: We utilized the National Health Information Database to obtain annual age-specific numbers of population and deaths for all neighborhood-level areas in Korea between 2013 and 2017. First, differences in the SMR by urbanity were examined, assuming the same age-specific mortality rates in all neighborhoods. Second, we explored the differences in ranking obtained using the three metrics (SMR, CMF, and LE). Third, the ratio of CMF to SMR by population was analyzed according to urbanity.Results: We found that the age-specific population distributions in urbanized areas were similar, but rural areas had a relatively old population structure. The age-specific mortality ratio also differed by urbanity. Assuming the same rate of age-specific mortality across all neighborhoods, we found that comparable median values in all areas. However, areas with a high SMR showed a strong predominance of metropolitan areas. The ranking by SMR differed markedly from the rankings by CMF and LE, especially in areas of high mortality, while the latter two metrics did not differ notably. The ratio of CMF to SMR showed larger variations in neighborhoods in rural areas, particularly in those with small populations, than in metropolitan and urban areas.Conclusions: In a comparison of multiple SMRs, bias could exist if the study areas have large differences in population structure. The use of CMF or LE should be considered for comparisons if it is possible to acquire age-specific mortality data for each neighborhood.

Loss of life expectancy derived from a standardized mortality ratio in Denmark, Finland, Norway and Sweden

2018 ◽  
Vol 46 (7) ◽  
pp. 767-773 ◽  
Author(s):  
Mette Vinther Skriver ◽  
Michael Væth ◽  
Henrik Støvring
Keyword(s):  
Life Expectancy ◽  
Mortality Data ◽  
Standardized Mortality Ratio ◽  
Loss Of Life ◽  
Theoretical Relationship ◽  
Life Expectancy At Birth ◽  
Linear Association ◽  
Approximate Relationship ◽  
Mortality Ratio ◽  
The Relationship

Aims: The standardized mortality ratio (SMR) is a widely used measure. A recent methodological study provided an accurate approximate relationship between an SMR and difference in lifetime expectancies. This study examines the usefulness of the theoretical relationship, when comparing historic mortality data in four Scandinavian populations. Methods: For Denmark, Finland, Norway and Sweden, data on mortality every fifth year in the period 1950 to 2010 were obtained. Using 1980 as the reference year, SMRs and difference in life expectancy were calculated. The assumptions behind the theoretical relationship were examined graphically. The theoretical relationship predicts a linear association with a slope, [Formula: see text], between log(SMR) and difference in life expectancies, and the theoretical prediction and calculated differences in lifetime expectancies were compared. We examined the linear association both for life expectancy at birth and at age 30. All analyses were done for females, males and the total population. Results: The approximate relationship provided accurate predictions of actual differences in lifetime expectancies. The accuracy of the predictions was better when age was restricted to above 30, and improved if the changes in mortality rate were close to a proportional change. Slopes of the linear relationship were generally around 9 for females and 10 for males. Conclusions: The theoretically derived relationship between SMR and difference in life expectancies provides an accurate prediction for comparing populations with approximately proportional differences in mortality, and was relatively robust. The relationship may provide a useful prediction of differences in lifetime expectancies, which can be more readily communicated and understood.

scholarly journals Could different treatment approaches in acromegaly influence life expectancy? A comparative study between Bulgaria and Campania (Italy)

2014 ◽  
Vol 171 (2) ◽  
pp. 263-273 ◽  
Author(s):  
Annamaria Colao ◽  
Silvia Vandeva ◽  
Rosario Pivonello ◽  
Ludovica Francesca Stella Grasso ◽  
Emil Nachev ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Disease Control ◽  
Treatment Options ◽  
Somatostatin Analogs ◽  
Survival Rates ◽  
Treatment Modalities ◽  
Standardized Mortality Ratio ◽  
Biochemical Control ◽  
Mortality Ratio ◽  
The Impact

BackgroundMortality in acromegaly strictly depends on optimal control of GH and IGF1 levels. Modern medical therapy with somatostatin analogs (SSAs) and GH receptor antagonists (GHRAs) is not available in many countries due to funding restrictions. This retrospective, comparative, cohort study investigated the impact of different treatment modalities on disease control (GH and IGF1) and mortality in acromegaly patients.MethodsTwo cohorts of patients with acromegaly from Bulgaria (n=407) and Campania, Italy (n=220), were compared, and mortality rates were evaluated during a 10-year period (1999–2008).ResultsThe major difference in treatment approach between cohorts was the higher utilization of SSAs and GHRAs in Italy, leading to a decreased requirement for radiotherapy. Significantly more Italian than Bulgarian patients had achieved disease control (50.1 vs 39.1%, P=0.005) at the last follow-up. Compared with the general population, the Bulgarian cohort had a decreased life expectancy with a standardized mortality ratio (SMR) of 2.0 (95% CI 1.54–2.47) that was restored to normal in patients with disease control – SMR 1.25 (95% CI 0.68–1.81). Irradiated patients had a higher cerebrovascular mortality – SMR 7.15 (95% CI 2.92–11.37). Internal analysis revealed an independent role of age at diagnosis and last GH value on all-cause mortality and radiotherapy on cerebrovascular mortality. Normal survival rates were observed in the Italian cohort: SMR 0.66 (95% CI 0.27–1.36).ConclusionsSuboptimal biochemical control was associated with a higher mortality in the Bulgarian cohort. Modern treatment options that induce a strict biochemical control and reduce the necessity of radiotherapy might influence the life expectancy. Other factors, possibly management of comorbidities, could contribute to survival rates.

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