Data Talks: Obesity-Related Influences on US Mortality Rates

Background: In the US, obesity is an epidemiologic challenge and the population fails to comprehend this complex public health issue. To evaluate underlying obesity-impact patterns on mortality rates, we data-mined the 1999-2016 Center for Disease Control WONDER database’s vital records.Methods: Adopting SAS programming, we scrutinized the mortality and population counts. Using ICD-10 diagnosis codes connected to overweight and obesity, we obtained the obesity-related crude and age-adjusted causes of death. To understand divergent and prevalence trends we compared and contrasted the tabulated obesity-influenced mortality rates with demographic information, gender, and age-related data.Key Results: From 1999 to 2016, the obesity-related age-adjusted mortality rates increased by 142%. The ICD-10 overweight and obesity-related death-certificate coding showed clear evidence that obesity factored in the male age-adjusted mortality rate increment to 173% and the corresponding female rate to 117%. It also disproportionately affected the nation-wide minority population death rates. Furthermore, excess weight distributions are coded as contributing features in the crude death rates for all decennial age-groups.Conclusions: The 1999-2016 data from ICD-10 death certificate coding for obesity-related conditions indicate that it is affecting all segments of the US population

Investigation Of Obesity-Related Mortality Rates In Delaware

As Delaware’s adult obesity crisis continues to be a leading public health concern, we evaluated Delaware’s 1999–2014 vital records to examine the association between obesity and mortality. We used the Delaware population death records from the Centers for Disease Control and Prevention (CDC) WONDER database and the Delaware Health Statistics Center (DHSC). Together with the vital records, we incorporated Microsoft Excel, SAS (Statistical Analysis System) and GIS (geographic information system) tools to analyze obesity influences from county residence, economic status, education, gender, and race. Using the 15-year (1999–2014) time span with the CDC WONDER database, we observed a statistically significant 28.7% increase in the age-adjusted Delaware obesity-related mortality rates (where obesity was a contributory factor). Furthermore, obesity influenced death counts in all three Delaware counties (New Castle, Kent, and Sussex). Kent County experienced the largest increase (66.0%), followed by New Castle County (47.4%), and Sussex County (25.2%). The DHSC mortality rates for all leading causes of death from 2000 to 2011 indicated relatively stable mortality rates for Delaware. However, using CDC WONDER data, the Delaware mortality rate for obesity as a single underlying cause in 2011 was 56.9% higher than mortality rate in 2000

Descriptive and Inferential Statistics in Undergraduate Data Science Research Projects

Undergraduate data science research projects form an integral component of the Wesley College science and mathematics curriculum. In this chapter, we provide examples for hypothesis testing, where statistical methods or strategies are coupled with methodologies using interpolating polynomials, probability and the expected value concept in statistics. These are areas where real-world critical thinking and decision analysis applications peak a student’s interest