Objective:Human mortality is affected by a lot of different factors.Geographic and demographic variations are two such criteria that play significant importance in establishing the variation in mortality rate.Methods:...Objective:Human mortality is affected by a lot of different factors.Geographic and demographic variations are two such criteria that play significant importance in establishing the variation in mortality rate.Methods:The current work uses data collected from the Centers for Disease Control and Prevention from 2018 to 2021 to study the dependence of mortality on several parameters such as gender,race,and age group.The analysis looks at all the different causes of death registered in the database and shows how they vary with not only the demographic variables mentioned above but also geographic variables such as states in the USA.The variation in trends pre-,during,and post-pandemic is also investigated.The study undertakes several multi-factorial relations such as location-age group,location-gender,age group-gender,and a blanket study across all the racesfor2018-2021.Results:Texas,California,and Florida were analyzed to be the states with the most number of deaths for the majority of causes.The study shows that before the pandemic two of the most critical causes of death identified were Atherosclerotic heart disease and Alzheimer's disease which was outnumbered by coronavirus disease 2019 in years 2020 and 2021 for the age groups of 35-84 years.Conclusion:The outcome of the study clearly shows the irrational availability of data among different ages,states,and races.In addition,it helps to provide interesting insights into how the mortality trends relate to demographic and geographic factors and point out the discrepancies among them.展开更多
AIM: To analyze the data from Tianjin Cancer Registry of mortality due to colon cancer from 1981 to 2000 in Tianjin, China. METHODS: Tumors diagnosed in this study were coded according to ICD-9. Mortality rates were c...AIM: To analyze the data from Tianjin Cancer Registry of mortality due to colon cancer from 1981 to 2000 in Tianjin, China. METHODS: Tumors diagnosed in this study were coded according to ICD-9. Mortality rates were calculated by sex and calendar year of diagnosis. RESULTS: Seventy point four percent of colon cancer deaths occurred in the age group of 55-79 years and the mortality rate reached its peak in the age group of 75-80 years. The average age at death was 64.10 years. An ascending trend was observed in the mean age of death due to colon cancer from 1981 through 2000. However, as for the sex ratio, there was no clear trend exhibited. During 1981-2000, the total number of deaths was 2147, 1041 males and 1106 females. The mean mortality rate of colon cancer was 3.04/100 000. The mortality caused by colon cancer ascended from 1981 to 2000. CONCLUSION: The epidemic trend of colon cancer in Tianjin and its risk factors and prevention should be studied further.展开更多
To determine the reason for the different mortality trends of ischemic heart disease （IHD） for China between Global Burden of Disease （GBD） 2010 and GBD2013, and to improve garbage code （GC） redistribution. All ...To determine the reason for the different mortality trends of ischemic heart disease （IHD） for China between Global Burden of Disease （GBD） 2010 and GBD2013, and to improve garbage code （GC） redistribution. All data were obtained from the disease surveillance points system, and two proportions for assigning chronic pulmonary heart disease （PHD） as GC to IHD were from GBD2010 and GBD2013,展开更多
Objective: To demonstrate the impact of inadequate standardization and population coverage on the ability to measure and improve maternal mortality in the United States. Data Sources: The CDC Wonder system for the yea...Objective: To demonstrate the impact of inadequate standardization and population coverage on the ability to measure and improve maternal mortality in the United States. Data Sources: The CDC Wonder system for the years 2000-2015 using the following definitions of maternal mortality and associated ICD-CM-10 codes: 1) Maternal deaths up to 42 days after delivery (A34, O00-O99, except O96-O97);2) Maternal deaths within one year after delivery (A34, O00-O99, except O97);3) All maternal deaths (A34, O00-O99). Study Design: For each year between 2000-2015, we provided maternal deaths, live births, and calculated maternal mortality ratios (MDR). For deaths within 42 days, we also calculated adjusted mortality ratios (ADR). Principal Findings: Maternal mortality comparisons which utilize inconsistent definitions and apply non-validated statistical adjustments produce specious results. Conclusions: Variation and inconsistency in definitions, coding, and other reporting anomalies render the current aggregated vital statistics on maternal mortality inadequate for accurate trending and service impact studies. The definition of maternal mortality must be expanded to all outcomes of pregnancy: births, induced abortions, and natural fetal losses.展开更多
文摘Objective:Human mortality is affected by a lot of different factors.Geographic and demographic variations are two such criteria that play significant importance in establishing the variation in mortality rate.Methods:The current work uses data collected from the Centers for Disease Control and Prevention from 2018 to 2021 to study the dependence of mortality on several parameters such as gender,race,and age group.The analysis looks at all the different causes of death registered in the database and shows how they vary with not only the demographic variables mentioned above but also geographic variables such as states in the USA.The variation in trends pre-,during,and post-pandemic is also investigated.The study undertakes several multi-factorial relations such as location-age group,location-gender,age group-gender,and a blanket study across all the racesfor2018-2021.Results:Texas,California,and Florida were analyzed to be the states with the most number of deaths for the majority of causes.The study shows that before the pandemic two of the most critical causes of death identified were Atherosclerotic heart disease and Alzheimer's disease which was outnumbered by coronavirus disease 2019 in years 2020 and 2021 for the age groups of 35-84 years.Conclusion:The outcome of the study clearly shows the irrational availability of data among different ages,states,and races.In addition,it helps to provide interesting insights into how the mortality trends relate to demographic and geographic factors and point out the discrepancies among them.
文摘AIM: To analyze the data from Tianjin Cancer Registry of mortality due to colon cancer from 1981 to 2000 in Tianjin, China. METHODS: Tumors diagnosed in this study were coded according to ICD-9. Mortality rates were calculated by sex and calendar year of diagnosis. RESULTS: Seventy point four percent of colon cancer deaths occurred in the age group of 55-79 years and the mortality rate reached its peak in the age group of 75-80 years. The average age at death was 64.10 years. An ascending trend was observed in the mean age of death due to colon cancer from 1981 through 2000. However, as for the sex ratio, there was no clear trend exhibited. During 1981-2000, the total number of deaths was 2147, 1041 males and 1106 females. The mean mortality rate of colon cancer was 3.04/100 000. The mortality caused by colon cancer ascended from 1981 to 2000. CONCLUSION: The epidemic trend of colon cancer in Tianjin and its risk factors and prevention should be studied further.
基金supported by the China Medical Board(grant No.12-107,15-208)China Medical Board Faculty Development Award(grant No.G16917561)China Scholarship Council(grant No.201408110083)
文摘To determine the reason for the different mortality trends of ischemic heart disease （IHD） for China between Global Burden of Disease （GBD） 2010 and GBD2013, and to improve garbage code （GC） redistribution. All data were obtained from the disease surveillance points system, and two proportions for assigning chronic pulmonary heart disease （PHD） as GC to IHD were from GBD2010 and GBD2013,
文摘Objective: To demonstrate the impact of inadequate standardization and population coverage on the ability to measure and improve maternal mortality in the United States. Data Sources: The CDC Wonder system for the years 2000-2015 using the following definitions of maternal mortality and associated ICD-CM-10 codes: 1) Maternal deaths up to 42 days after delivery (A34, O00-O99, except O96-O97);2) Maternal deaths within one year after delivery (A34, O00-O99, except O97);3) All maternal deaths (A34, O00-O99). Study Design: For each year between 2000-2015, we provided maternal deaths, live births, and calculated maternal mortality ratios (MDR). For deaths within 42 days, we also calculated adjusted mortality ratios (ADR). Principal Findings: Maternal mortality comparisons which utilize inconsistent definitions and apply non-validated statistical adjustments produce specious results. Conclusions: Variation and inconsistency in definitions, coding, and other reporting anomalies render the current aggregated vital statistics on maternal mortality inadequate for accurate trending and service impact studies. The definition of maternal mortality must be expanded to all outcomes of pregnancy: births, induced abortions, and natural fetal losses.
