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.

No abstract

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.

The overarching framework for incorporating informatics into the Wesley College (Wesley) undergraduate curriculum was to teach emerging information technologies that prepared undergraduates for complex high-demand work environments. Federal and State support helped implement Wesley’s undergraduate Informatics Certificate and Minor programs. Both programs require project-based coursework in Applied Statistics, SAS Programming, and Geo-spatial Analysis (ArcGIS). In 2015, the State of Obesity listed the obesity ranges for all 50 US States to be between 21–36%. Yet, the Center for Disease Control and Prevention (CDC) mortality records show significantly lower obesity-related death-rates for states with very high obesity-rates. This study highlights the disparities in the reported obesity-related death-rates (specified by an ICD-10 E66 diagnosis code) and the obesity-rate percentages recorded for all 50 US States. Using CDC mortality-rate data, the available obesity-rate information, and ArcGIS, we created choropleth maps for all US States. Visual and statistical analysis shows considerable disparities in the obesity-related death-rate record-keeping amongst the 50 US States. For example, in 2015, Vermont with the sixth lowest obesity-rate had the highest reported obesity-related death-rate. In contrast, Alabama had the fifth highest adult obesity-rate in the nation, yet, it had a very low age-adjusted mortality-rate. Such disparities make comparative analysis difficult.