I quit, and it feels so good! Not tobacco- a job. For the past 7 months, I’ve been humbled and also mortified by working the front lines of what is sometimes glorified as “primary data collection for health behavior research.” This is only phone peddling of an unexpected sort: rather than sales, donations, or debt collection, the desired outcome is completed surveys. But instead of collecting data, telephone interviewers spend most of their shifts getting yelled at or hung up on. And who could blame the world at large for reacting this way to calls from strangers with stilted and over-eager introductions?
I’ve worked in data collection before, measuring things like traffic volume, pavement cracks, salt marsh redox potential, and all the species of bugs and grubs scraped from riverbed rocks. But this is the first time I’ve had to interface (intervoice?) with fellow humans, and it’s painful. A lot of data these days is collected by pained people like me in call centers like this, where teams of 100+ interviewers cold-call random households and sometimes businesses for research studies commissioned by all sorts of clients (ex: universities, government health departments,) about topics like tobacco use, physical activity, nutrition, and smoking policies in apartment buildings. One of the surveys the office does each year is New York State Adult Tobacco Survey (ATS). When I discovered that this project’s data is published online, I jumped at the opportunity to examine the finished product of all those hours of tedious dialing. Below, I analyze the 2009 and 2010 data.
The purpose of ATS is to help the New York State Tobacco Control Program monitor how attitudes about smoking change over time. The program uses this information to better target their activities (smoking cessation services, media campaigns, and policy work promoting tobacco control), and also to brag that desired behavior/attitude changes reported through ATS are an indicator of their effective programming (FALLACY!). In any case, this is important to understand because tobacco use is currently the leading cause of preventable deaths in the U.S.
The Centers for Disease Control and Prevention conducted a 2010 study of 33 Adult Tobacco Surveys conducted in 19 states from 2003-2007. The sample size (or number of survey respondents) for each ATS ranged from 1,300 to 12,000 (NY’s was just over 4,000 in 2009 and 2010). However, all analysis is done after the data is weighted by each respondent’s probability of selection within the state, according to race, ethnicity, sex, and household size. Bottom line: the numbers presented here are in terms of projected state population rather than simply the number of survey respondents.
The prevalence of current smokers within New York State is somewhere around 17.0% percent (16.3% in 2009, 17.7% in 2010) – which is fairly low nationally, as the CDC study showed a median prevalence of 19.2%, with states ranging from 13.3% (Hawaii in 2006) to 25.4% (West Virginia in 2005). Tobacco use prevalence for cigarettes, cigars (including cigarillos and little filtered cigars), and smokeless tobacco (chew, dip, snuff) is graphed below, comparing the lowest, highest, and median rates from the CDC review to New York’s 2009/2010 ATS results.
But how does cigarette smoking prevalence vary across the state?
It’s a tricky question to answer through the ATS. The most precise geographic information in the 2010 data-set is the postal/zip code of each respondent. However, only about half of New York State’s (over-4,000) zip codes are represented in the data, as shown below:
To avoid bias, I merged the zip code data for county-level analysis, comparing the projected prevalence of current smokers (shown below). Keep in mind that this map is imprecise: estimates from a sample comprising only 0.03% of the state’s adult population, inhabiting only half of its zip codes. It’s unlikely, for example, that over half of adults in Yates county (population of 19,000 over-18) are smokers. However, the map does illustrate some broader trends, such as a cluster of counties radiating South and West from Albany, but North of NYC, with prevalence rates above the state average (17%). Though looking at the map above reveals these counties also happen to have a large proportion of their geographic area unrepresented in the data.
The cost of addiction- to the addicted, but also to the rest of the population- is a subject that I find particularly interesting.
Making cigarettes more expensive is meant to discourage smoking, and New York has the highest cigarette excise tax in the nation: bumped up to $4.35 per pack in July 2010. But it’s important to keep in mind that this tax revenue comes disproportionally from the pockets of lower-income residents.
That’s because people with annual household incomes under $30,000 are more than twice as likely to be current smokers (42%), compared to the general population (20%) as shown above, and among smokers, those with lower incomes are also 20% more likely to be at least moderately concerned about the cost of cigarettes. But the rising costs are here to stay, as the link between increased cigarette prices and lower smoking prevalence has been vigorously proven (vigorous = meta-analysis of over 500 studies!) across low, middle, and high income groups.
Some health economists argue that the regressive nature of the excise tax (burdening the poor more than anyone else) is addressed by directing that tax revenue into cessation services that target low-income smokers. Indeed, NY’s ATS data shows that among smokers, those with lower incomes are most likely to be aware of and have used the state’s quit-line (which offers free counseling and Nicotine Replacement Therapy). So low-income smokers may be making most use of cessation services, but they are also paying for it big-time, and it’s not helping much: the disparity in smoking status between income-groups remains.
Health disparity by social class is nothing new. But when it comes to addiction, nutrition, and other lifestyle factors, discussion tends to gravitate strongly toward the responsibility of the individual. And I agree, individual responsibility is an important factor. But it’s also important to remember what we are collectively responsible for: the barriers to employment, childcare, transportation, and other societal circumstances beyond an individual’s control that may fuel chronic stress and drive them toward certain health behaviors.