Publications

BACKGROUND

Globally and in the United States, smoking and obesity are leading causes of death and disability. Reliable estimates of prevalence for these risk factors are often missing variables in public health surveillance programs. This may limit the capacity of public health surveillance to target interventions or to assess associations between other environmental risk factors (e.g., air pollution) and health because smoking and obesity are often important confounders.

OBJECTIVES

To generate prevalence estimates of smoking and obesity rates over small areas for the United States (i.e., at the ZIP code and census tract levels).

METHODS

We predicted smoking and obesity prevalence using a combined approach first using a lasso-based variable selection procedure followed by a two-level random effects regression with a Poisson link clustered on state and county. We used data from the Behavioral Risk Factor Surveillance System (BRFSS) from 1991 to 2010 to estimate the model. We used 10-fold cross-validated mean squared errors and the variance of the residuals to test our model. To downscale the estimates we combined the prediction equations with 1990 and 2000 U.S. Census data for each of the four five-year time periods in this time range at the ZIP code and census tract levels. Several sensitivity analyses were conducted using models that included only basic terms, that accounted for spatial autocorrelation, and used Generalized Linear Models that did not include random effects.

RESULTS

The two-level random effects model produced improved estimates compared to the fixed effects-only models. Estimates were particularly improved for the two-thirds of the conterminous U.S. where BRFSS data were available to estimate the county level random effects. We downscaled the smoking and obesity rate predictions to derive ZIP code and census tract estimates.

CONCLUSIONS

To our knowledge these smoking and obesity predictions are the first to be developed for the entire conterminous U.S. for census tracts and ZIP codes. Our estimates could have significant utility for public health surveillance.

BACKGROUND

Graphic warning labels are a tobacco control best practice that is mandated in the US for cigarettes under the 2009 Family Smoking Prevention and Tobacco Control Act. However, smokeless tobacco products are not required to carry graphic warning labels, and as of September 2014, electronic cigarettes in the US carry no warning labels and are aggressively marketed, including with "reduced harm" or "FDA Approved" messages.

METHODS

In this online experiment, 483 US adult non-users of tobacco were randomized to view print advertisements for moist snuff, snus, and e-cigarettes with either warning labels (current warning label, graphic warning label) or "endorsements" (a "lower risk" label proposed by a tobacco company, an "FDA Approved" label) or control (tobacco advertisement with no label, advertisement for a non-tobacco consumer products). Main outcome measures included changes in perceived harm, positive attitudes towards, openness to using, and interest in a free sample of moist snuff, snus, and e-cigarettes.

RESULTS

The graphic warning label increased perceived harm of moist snuff and e-cigarettes. "Lower risk" and "FDA Approved" labels decreased perceived harm of moist snuff and snus respectively. Current warning label and graphic warning label significantly lowered positive attitudes towards e-cigarettes. In this sample of non-users of tobacco, 15% were interested in a free sample of alternative tobacco products (predominantly e-cigarettes). Proportion of participants interested in a free sample did not differ significantly across the conditions, but those interested in a free sample had significantly lower perceptions of harm of corresponding tobacco products.

CONCLUSIONS

Regulatory agencies should not allow "lower risk" warning labels, which have similar effects to the "FDA Approved" label, which is prohibited, and should consider implementing graphic warning labels for smokeless tobacco products and e-cigarettes.

UNLABELLED

The full-length isoform of matrixmetalloproteinase-2 (FL-MMP-2) plays a role in turnover of the cardiac extracellular matrix. FL-MMP-2 is also present intracellularly in association with sarcomeres and, in the setting of oxidative stress, cleaves myofilament proteins with resultant impaired contractility. Recently, a novel N-terminal truncated MMP-2 isoform (NTT-MMP-2) generated during oxidative stress was identified and shown to induce severe systolic failure; however, the injury mechanisms remained unclear. In this study, cardiac-specific NTT-MMP-2 transgenic mice were used to determine the physiological effects of NTT-MMP-2 on: force development of intact myocardium; the function of cardiac myofilaments in demembranated myocardium; and on intracellular Ca(2+) transients in isolated myocytes. We related the contractile defects arising from NTT-MMP-2 expression to the known intracellular locations of NTT-MMP-2 determined using immunohistochemistry. Comparison was made with the pathophysiology arising from cardiac-specific FL-MMP-2 transgenic mice. Consistent with previous studies, FL-MMP-2 was localized to myofilaments, while NTT-MMP-2 was concentrated within subsarcolemmal mitochondria and to sites in register with the Z-line. NTT-MMP-2 expression caused a 50% reduction of force development by intact myocardium. However, NTT-MMP-2 expression did not reduce myofilament force development, consistent with the lack of NTT-MMP-2 localization to myofilaments. NTT-MMP-2 expression caused a 50% reduction in the amplitude of Ca(2+) transients, indicating impaired activation.

CONCLUSIONS

Unlike FL-MMP-2, NTT-MMP-2 does not mediate myofilament damage. Instead, NTT-MMP-2 causes impaired myocyte activation, which may involve effects due to localization in mitochondria and/or to transverse tubules affecting Ca(2+) transients. Thus, FL-MMP-2 and NTT-MMP-2 have discrete intracellular locations and mediate different intracellular damage to cardiac myocytes.