Adult asthma and its relationship with smoking and obesity

What is asthma?

Several risk factors:

• Family history
• Viral respitory infections
• Allergies
• Occupational Exposures
• Smoking
• Air Pollution
• Obesity

• Asthma rates increasing accross globe
• 300 million people worlwide affected
• 24.6 million in the US diagnosed

• More likely to affect children
• Disproportionately affects low income populations
• non-Hispanics: 43% higher for blacks vs whites
• Disparities within mortality rates/seriousness

• Responsible for lost school and work days, early deaths
• $56 billion in total cost for the US (cdc.gov)

• Focused on Smoking and Obesity
• Using the CDC's “500 Cities: Local Data for Better Health” dataset
• Includes 2013-14 model-based estimates for 27 measures of chronic disease
• Tracks health info for adult (>18) population
• Includes city wide and individual census tract data

• Irritates airways in the lung
• Firsthand and secondhand smoke increase asthma risk
• Affects children whose mothers smoked during their pregnancy

• J.M. Vonk et. al: genetic evidence suggesting interaction with smoking
• Some adults more susceptible to develop asthma than others

• Jesse D. Thacher et al: found increased risk of asthma from exposure to cigarette smoke in infancy
• The risk of persistent asthma increases for highly exposed

• M. D. Eisner: relationship between adult asthma and secondhand smoke
• Less clear than childhood asthma and secondhand smoke
• Any expososure associated with higher rate of self-reported asthma
• Adult on-set asthma rates increased for children exposed to parental smoking

• Unclear relationship
• Extra weight causes some inflammation
• Obese individuals suffering from asthma use more medications and suffer worse symptoms
• American obesity rates are increasing

• Sveta Mohanan et. al: 2 phenotypes of asthma
• The first alters early onset allergic asthma
• The second unique form fully obesity caused

\[ y = \beta_0+ \beta_1x_1+ \beta_2x_2+ \beta_3x_1x_2+\epsilon \]

Where

\[ \beta_0 \ is \ the \ intercept \\ x_1 \ is \ the \ smoking \ rate \\ x_2 \ is \ the \ obesity \ rate \\ x_1x_2 \ is \ the \ interaction \ term y \ is \ the \ asthma \ rate \]

I assume \( \epsilon \sim N(0, \sigma^2) \)

The Residual standard error: \( \sigma \) = 1.107

*approximately 0

• Smoking plays biggest role in predicting Adult Asthma
• Obesity not a significant predictor
• Smoking and Obesity interaction significant
  

• Asthma, Smoking and Obesity rates represented by circle size and color
• Zoom in/out to focus on specific parts of the country
• Data displayed in scatterplot
• Adjustable circle size