WEBVTT 1 00:00:02.930 --> 00:00:08.209 Tony Lugemwa: I'd like to welcome you to the tobacco online policy. Seminar talks. 2 00:00:09.640 --> 00:00:29.490 Tony Lugemwa: Thank you for joining us today. My name is Tony Lucamore. Behavioral Health Research at Memphis Health Center, Topsy, organized by Michael Pesco at the University of Missouri, Tushan at the Ohio State University, Michael Darden at John Hopkins University, Jamie Hat Boyce 3 00:00:29.750 --> 00:00:36.540 Tony Lugemwa: at University of Massachusetts. I must, and just in white at Boston University 4 00:00:36.850 --> 00:00:45.269 Tony Lugemwa: the seminar will be 1 h with questions from the Moderator and discussant. The audience may pose questions and comments 5 00:00:45.770 --> 00:00:51.210 Tony Lugemwa: in the Q. And a panel, and the moderator will draw from these questions and comments 6 00:00:51.520 --> 00:01:03.310 Tony Lugemwa: in conversation with the presenter. Please review the guidelines on the tobaccopolicy.org website for acceptable questions. Now, that's tobaccopolicies. 1 1.org. 7 00:01:03.490 --> 00:01:11.330 Tony Lugemwa: and that's where you'll find all acceptable questions. Please keep the questions professional and related to research being discussed. 8 00:01:11.490 --> 00:01:21.200 Tony Lugemwa: Questions that meet the seminary guidelines will be shared with the presenter afterwards, even if they are not read aloud. Your questions are very much appreciated. 9 00:01:21.510 --> 00:01:30.620 Tony Lugemwa: This mission, this presentation is being video recorded and will be available along with presentation slides on the tops website 10 00:01:31.633 --> 00:01:35.650 Tony Lugemwa: that is tobaccopolicy.org. 11 00:01:36.020 --> 00:01:43.570 Tony Lugemwa: I will turn the presentation over today's moderator to Shang from Ohio State University to introduce our speaker. 12 00:01:44.040 --> 00:01:52.390 Ce Shang: Thank you. Today we continue our summer. 2025. Season with a grand rounds. Presentation by Doris Gammon. 13 00:01:52.390 --> 00:02:02.610 Ce Shang: entitled Measuring Changes in Tobacco product sales and availability. Following California's statewide flavored tobacco sales restriction. 14 00:02:02.610 --> 00:02:22.580 Ce Shang: a synthetic control method using retail scanner data. This presentation was selected with a competitive review process by submission through the Topps website. Ms. Gammon is a public health researcher and program manager in Rti Center for program and policy evaluation 15 00:02:22.850 --> 00:02:48.419 Ce Shang: to advance community health. She earned her Master's degree in economics from the University of North Carolina, Charlotte in 2010, and joined Rti that same year. Ms. Gammon has earned nearly 15 years of experience, leveraging scanner data to conduct time, series, analysis, and employ quasi-experimental designs to evaluate public health policy interventions 16 00:02:48.450 --> 00:03:13.409 Ce Shang: and their intended and unintended outcomes, with a focus on policies intended to reduce the harms associated with tobacco and alcohol, marketing and use. She has authored dozens of peer-reviewed manuscripts and conference presentations and her research has been cited in both proposed and final Federal rules by the Food and Drug Administration. 17 00:03:13.410 --> 00:03:35.610 Ce Shang: Ms. Gammon continues to advance the understanding of how policy, interventions, influence, population, health and inform regulatory decision-making. Dr. James Nannymaker, senior research scientist at Rti International and Morgan Whitney, a research public health analyst at Rti international are co-authors of the studies. 18 00:03:35.610 --> 00:03:41.780 Ce Shang: and we'll answer select questions in the Q. And A. Ms. Gannon. Thank you for presenting for us today. 19 00:03:44.160 --> 00:03:45.850 Doris Gammon: Thank you. See, for having me. 20 00:03:46.050 --> 00:03:50.410 Doris Gammon: Thank you. Everyone for joining. Kinda get my slides up now. 21 00:03:52.380 --> 00:03:53.290 Doris Gammon: Okay. 22 00:03:59.430 --> 00:04:00.240 Doris Gammon: okay. 23 00:04:00.400 --> 00:04:01.660 Doris Gammon: Think we're ready to go? 24 00:04:02.492 --> 00:04:13.670 Doris Gammon: So, as she said, my name is Dori Gammon, and I'm a public health researcher and program manager at Rti's Center for program and policy evaluation to advance community health. 25 00:04:14.640 --> 00:04:31.630 Doris Gammon: Today, I'm presenting the results from 2 studies, one that focuses on flavored non-cigarette tobacco product availability, and another that focuses both on the availability and sales of cigarettes before and after. Sb. 793, California's statewide flavored tobacco sales restriction. 26 00:04:31.730 --> 00:04:38.510 Doris Gammon: Both of these studies employed similar data and similar methods, but they cover different time periods, and they have different historical context. 27 00:04:38.840 --> 00:04:50.460 Doris Gammon: I'd also like to recognize my co-authors, Morgan, Whitney, James Nunnamaker, Lisa Henrikson, Nina Schleicher, Elizabeth Anderson, Rogers, Rafael Colonna, and Todd Rogers. 28 00:04:55.470 --> 00:05:07.149 Doris Gammon: The research was funded by the California Department of Public Health Tobacco Prevention program. I don't have any conflicts of interest to disclose, and the only tobacco related funding that I've received is from Federal and State governments. 29 00:05:07.500 --> 00:05:17.760 Doris Gammon: The findings and conclusions in this presentation are those of the authors, and they don't necessarily represent the views or opinions of the California Department of Public Health, or the California Health and Human Services Agency. 30 00:05:18.020 --> 00:05:29.120 Doris Gammon: and the author's own analyses and calculations are based in part on Nielsen, IQ. Retail services data. The conclusions drawn from these data are those of the authors, and don't reflect the views of Niq. 31 00:05:30.482 --> 00:05:35.160 Ce Shang: Sorry to interrupt. We can we still see the black box on your screen? 32 00:05:35.160 --> 00:05:35.930 Doris Gammon: No. 33 00:05:35.930 --> 00:05:37.210 Ce Shang: So, yeah. 34 00:05:38.360 --> 00:05:39.659 Doris Gammon: Alright! Let's try again. 35 00:05:39.660 --> 00:05:40.360 Ce Shang: Yep. 36 00:05:56.120 --> 00:05:57.070 Doris Gammon: Able to see it. 37 00:05:57.070 --> 00:06:02.710 Ce Shang: It's still there, the black box. So do you mind sharing slides rather than the screen? 38 00:06:05.020 --> 00:06:06.830 Ce Shang: Someone says they see the slides. 39 00:06:06.830 --> 00:06:07.570 Ce Shang: Okay? Oh. 40 00:06:07.570 --> 00:06:14.469 Doris Gammon: Okay, I'll try one more time through my app. Here 41 00:06:19.780 --> 00:06:21.399 Doris Gammon: is that showing up for you? 42 00:06:22.536 --> 00:06:29.313 Ce Shang: Yes, but unfortunately the black box is still there. I think we can continue with this. 43 00:06:29.860 --> 00:06:30.780 Ce Shang: yeah. 44 00:06:33.370 --> 00:06:35.250 Doris Gammon: I hate for it to be a distraction. 45 00:06:35.250 --> 00:06:40.740 Ce Shang: Yeah, it's it's likely the controls for zoom Serena said. So. 46 00:06:41.499 --> 00:06:47.279 Ce Shang: See if you can move it. It's probably just like on your zoom when your share screen is there? 47 00:06:50.550 --> 00:06:56.890 Ce Shang: Well, let's try one more time. But if it doesn't work, I think it's okay. I can still see like 90% of the east side. 48 00:06:56.890 --> 00:07:02.149 Doris Gammon: Oh, I see what you're seeing now. And I understand that we tested this. 49 00:07:02.350 --> 00:07:13.770 Doris Gammon: Okay, well, I'm gonna go on. Unfortunately, I don't know how to troubleshoot that right now. But the slides will be shared after apologies for the technical issue there. 50 00:07:14.250 --> 00:07:15.180 Doris Gammon: So 51 00:07:15.420 --> 00:07:25.560 Doris Gammon: just level setting here, we know that marketing of flavored tobacco targets, specific populations. We know that most youth who use tobacco start with flavored products and use them. 52 00:07:25.750 --> 00:07:38.409 Doris Gammon: And most non-hispanic black adults who smoke cigarettes use menthol cigarettes. It's approximately 80% compared to all adults who smoke cigarettes. Their menthol use is around 43.4%. 53 00:07:39.070 --> 00:07:52.320 Doris Gammon: So California statewide law. Sb. 7, 93 restricts most flavored tobacco product sales, and therefore could reduce tobacco use among priority populations. If the tobacco products are removed from the marketplace 54 00:07:56.610 --> 00:08:02.379 Doris Gammon: a little more background. So the policy went into effect on December 21, st 2022, 55 00:08:02.510 --> 00:08:08.220 Doris Gammon: and it prohibits the sales of tobacco products with characterizing flavors, including menthol cigarettes. 56 00:08:08.340 --> 00:08:14.739 Doris Gammon: It does have some exemptions for Shisha, and 21 and over stores, pipe, tobacco, and premium cigars. 57 00:08:15.280 --> 00:08:24.189 Doris Gammon: and it's also important to consider that almost half of California's population already had a flavored tobacco sales, restriction of some kind prior to the statewide policy. 58 00:08:26.880 --> 00:08:43.209 Doris Gammon: The California Department of Tax and Fee Administration and the California Department of Public Health began notifying tobacco retailers, distributors, and wholesalers. About Sb. 793. In December 2022, and January 2023, through online notices and direct mailers. 59 00:08:43.679 --> 00:08:56.330 Doris Gammon: Initially, there was a monetary fine of $250 per violation to the seller, and subsequent legislation has increased those fines and developed a different structure. 60 00:08:56.960 --> 00:09:12.260 Doris Gammon: There's also a rebuttable presumption and built into the policy such that products can be presumed flavored, based on marketing. But that's but it's not limited, including, but not limited to a product's name, packaging and advertising. 61 00:09:13.020 --> 00:09:22.029 Doris Gammon: We also saw, coincident with the implementation and effective date of Sb. 7, 93, the introduction of new non menthol cigarettes. 62 00:09:22.130 --> 00:09:26.750 Doris Gammon: many of which were chemically tested and had synthetic cooling agents in them. 63 00:09:27.640 --> 00:09:36.539 Doris Gammon: and noting here that postdating our study. But subsequent laws have been implemented to further strengthen. Sb. 793. 64 00:09:38.530 --> 00:09:51.599 Doris Gammon: Our research questions for the 1st study was from before to after Sb. 793. To what extent did non-cigarette tobacco product availability by flavor, category change in California compared to a control area? 65 00:09:51.940 --> 00:09:57.890 Doris Gammon: And we also looked at the extent to which cigarette sales and availability by flavor category changed 66 00:09:59.010 --> 00:10:07.399 Doris Gammon: before and after the policy to answer these questions we licensed data from Nilsen, IQ. For 24 Us. States, including California. 67 00:10:07.790 --> 00:10:17.019 Doris Gammon: Our pre-intervention period was approximately 23 months, and our post intervention period for the non-cigarette availability study was approximately 6 months. 68 00:10:17.210 --> 00:10:26.279 Doris Gammon: and for the cigarette availability in cells was approximately 12 months, and the time differences here are just when we were actually doing this study. This was the most recent data we could get. 69 00:10:27.880 --> 00:10:39.720 Doris Gammon: We analyze information on cigarettes, electronic nicotine delivery systems or ends, cigars, moist snuff, snooze, chew nicotine pouches, and roll your own tobacco. 70 00:10:40.070 --> 00:10:51.240 Doris Gammon: The store types covered by these data include convenience, grocery stores, drugstores, mass merchandisers, warehouse club stores, discount dollar stores and military retailers. 71 00:10:51.720 --> 00:11:00.020 Doris Gammon: Notably they don't cover what's happening online or in tobacco specialty stores and smaller format stores not tracked by the data collector 72 00:11:02.290 --> 00:11:16.640 Doris Gammon: for the non-cigarette availability study. We categorized flavors as either explicit concept or unflavored, based on the way that Nilsen has coded the flavor descriptor from external product packaging 73 00:11:17.020 --> 00:11:24.569 Doris Gammon: and for the cigarette study. We categorized flavors as either menthol, non-mental labeled or tobacco unflavored. 74 00:11:27.170 --> 00:11:30.299 Doris Gammon: Our outcomes were availability and sales 75 00:11:30.580 --> 00:11:44.879 Doris Gammon: for availability. We use the universal product code or upcs in the data for every product. Every product has a unique identifier, and it's based on its characteristics, such as brand sub brand flavor, nicotine strength and size. 76 00:11:45.610 --> 00:11:51.530 Doris Gammon: And we operationalized availability as the number of upcs with non-zero cells in each week. 77 00:11:52.070 --> 00:11:56.140 Doris Gammon: and availability informs the variety of products available on the market 78 00:11:57.300 --> 00:12:03.060 Doris Gammon: and for cells cigarette cells. We standardized units to a single pack of 20 sticks. 79 00:12:04.790 --> 00:12:12.659 Doris Gammon: To conduct this study, we use the synthetic control method. So this is a statistical technique to estimate the effect of an intervention. 80 00:12:12.900 --> 00:12:21.970 Doris Gammon: We, I broke this down into a 3 step process to share today. So first, st we create the synthetic California for each outcome which becomes our control group. 81 00:12:22.890 --> 00:12:34.320 Doris Gammon: So the way the synthetic control works is that it identifies the optimal combination of untreated States to produce a control group that matches the treatment group as closely as possible in the pre-intervention period. 82 00:12:34.560 --> 00:12:44.789 Doris Gammon: So the algorithm of this method is designed to minimize the root mean, squared, predicted error when comparing the outcome in the pre-intervention period between the treatment group and the synthetic control group. 83 00:12:45.980 --> 00:12:54.519 Doris Gammon: we ended up with 19 States in the donor tool pool because we excluded border States and States with flavored tobacco sales, restriction at the State level. 84 00:12:55.080 --> 00:13:03.590 Doris Gammon: The goal here was pre-intervention, comparability, so that we had a match comparison market and the predictors for our models were lagged values of the outcome. 85 00:13:04.120 --> 00:13:08.449 Doris Gammon: We also included population as a predictor in the model of cigarette pack sales. 86 00:13:10.630 --> 00:13:19.109 Doris Gammon: So once we had our synthetic controls identified, we were able to go to step 2, which is where we compared actual California to synthetic California. 87 00:13:19.230 --> 00:13:26.899 Doris Gammon: And here synthetic California is going to give us what would have happened in California had there not been a flavored tobacco sales restriction. 88 00:13:27.500 --> 00:13:31.020 Doris Gammon: And then finally, we moved to placebo models. 89 00:13:31.310 --> 00:13:45.400 Doris Gammon: This is a permutation test where the treatment is randomly assigned, and we estimated models where we iteratively replaced California with each State from the donor pool, and then we reestimated with California added to the donor pool. 90 00:13:45.880 --> 00:14:04.259 Doris Gammon: We then compare, we calculate, and we compare the ratio of the root, mean, squared, predicted error in the post and pre periods between the main model. California is the treatment and placebo models which we had 19 of, and then we can the larger the ratio in the California model, the stronger the support of a treatment effect. 91 00:14:10.960 --> 00:14:18.960 Doris Gammon: All right. So now I'm going to jump to the results. So for the 1st study, where we looked at non-cigarette tobacco product availability. 92 00:14:20.030 --> 00:14:23.090 Doris Gammon: Let me just see, here are we? Is there still a black box? 93 00:14:24.910 --> 00:14:30.680 Doris Gammon: There is okay, going to jump to these results now. 94 00:14:32.910 --> 00:14:49.669 Doris Gammon: so availability of non-cigarette tobacco products with explicit flavor names decreased in California, as you can see here at the time of Sb. 793 going into effect, and there was not a similar decrease in synthetic California. This supports and suggests a policy effect. 95 00:14:50.260 --> 00:15:04.909 Doris Gammon: and just to quantify some of this N's upc availability decreased by 65% from about 443 upcs in the pre-intervention period to 156 upcs in the post-intervention period. 96 00:15:05.020 --> 00:15:10.230 Doris Gammon: cigars decreased by about 40% smokeless tobacco by about 28% 97 00:15:10.330 --> 00:15:14.809 Doris Gammon: and nicotine pouches availability decreased by about 17%. 98 00:15:17.250 --> 00:15:27.840 Doris Gammon: The placebo results here show that the ratio for the main model was consistently larger than the ratio in the placebo models, and all of the placebo models. 99 00:15:28.000 --> 00:15:33.970 Doris Gammon: and the ratio was relatively large, especially for little cigars and cigaros and smokeless tobacco. 100 00:15:34.100 --> 00:15:38.230 Doris Gammon: This all supports that this was a policy effect that occurred. 101 00:15:41.350 --> 00:15:55.690 Doris Gammon: Availability of non-cigarette tobacco products that were unflavored in California diverged somewhat from synthetic California. After Sb. 793 went into effect, but not in a consistent direction and not very. There's not a very big gap there. 102 00:15:56.308 --> 00:15:59.520 Doris Gammon: When we look at the placebo results. 103 00:15:59.820 --> 00:16:06.440 Doris Gammon: we see that there's relatively small ratios in California compared to the placebo range 104 00:16:06.700 --> 00:16:20.610 Doris Gammon: for little cigars and cigarillos and smokeless tobacco. The ratio in California did exceed that of the placebo range, but they were still relatively small, so we might consider that weak support of a policy effect or a treatment effect. 105 00:16:20.830 --> 00:16:32.800 Doris Gammon: And then for ends, nicotine pouches, and roll your own tobacco we have. There's really not support here for a treatment effect and changes in unflavored versions of these products. 106 00:16:35.430 --> 00:16:42.989 Doris Gammon: Finally, we looked at availability of non-cigarette tobacco products with concept named flavors in California. And we see that 107 00:16:43.260 --> 00:16:52.030 Doris Gammon: in California it does diverge somewhat from synthetic California. After Sb. 793 goes into effect, but not again in a consistent direction. 108 00:16:52.300 --> 00:16:58.480 Doris Gammon: California availability decreased for ends and cigars, but it increased for smokeless tobacco. 109 00:17:02.040 --> 00:17:16.700 Doris Gammon: When we look at the ratio of the post to Pre Rmspe ratio for the main model. It's not consistently larger than the range of ratios in the placebo models for any of these products suggesting no treatment effect. 110 00:17:18.800 --> 00:17:20.780 Doris Gammon: So, in conclusion. 111 00:17:21.099 --> 00:17:28.979 Doris Gammon: for explicit flavor named products, the policy was associated with reduced availability. In the 1st 6 months following, Sb. 7, 93, 112 00:17:29.460 --> 00:17:33.849 Doris Gammon: there was a lower but notable level of products that remained available. 113 00:17:34.886 --> 00:17:46.860 Doris Gammon: For tobacco, unflavored non-cigarette tobacco products. There was no or weak evidence of a policy effect on availability and for concept flavored products. There was no evidence of a policy effect. 114 00:17:47.890 --> 00:18:00.780 Doris Gammon: and I call out here that average weekly availability of explicit named ends in California decreased by 65%. But in the post policy period there were still 156 upcs with explicit flavor names. 115 00:18:03.660 --> 00:18:07.149 Doris Gammon: All right, I'm going to move on to the results for our cigarette study. 116 00:18:10.250 --> 00:18:19.510 Doris Gammon: So for our analysis of menthol, cigarette cells and availability availability is on the top. Right panel, and cells are on the bottom right panel. 117 00:18:20.070 --> 00:18:29.640 Doris Gammon: Availability and sales of menthol cigarettes in California decreased at the point of intervention, and there was not a similar change observed in synthetic California 118 00:18:30.570 --> 00:18:38.519 Doris Gammon: availability decreased by about 44% in California and pack sales decreased by about 90% California 119 00:18:44.190 --> 00:18:57.300 Doris Gammon: for tobacco and unflavored availability and standard pack cells. In California cigarette pack sales in California we see a small gap in the post intervention period between California and synthetic California. 120 00:18:57.850 --> 00:19:00.879 Doris Gammon: the relative increase in sales in California. 121 00:19:01.240 --> 00:19:10.180 Doris Gammon: Compared to synthetic California. In the bottom panel there could be the result of some people who were previously using menthol cigarettes, switching to tobacco and flavored cigarettes. 122 00:19:10.580 --> 00:19:12.549 Doris Gammon: So that's something to keep in mind. 123 00:19:17.950 --> 00:19:22.089 Doris Gammon: Finally, we looked at non menthol labeled cigarette availability and sales. 124 00:19:22.710 --> 00:19:25.100 Doris Gammon: We see an immediate and 125 00:19:25.300 --> 00:19:34.320 Doris Gammon: large increase in the availability and pack sales of these products in California, and we don't see a similar change in synthetic California. 126 00:19:35.710 --> 00:19:43.420 Doris Gammon: the availability of these products increased 194%, while pack sales increased 708%. 127 00:19:44.290 --> 00:19:52.060 Doris Gammon: We also noticed that in late 2023 pack sales for these products in California started to go down pretty quickly. 128 00:19:52.845 --> 00:19:58.620 Doris Gammon: And this was driven by a decrease in camel crush oasis, non-mental oasis product sales. 129 00:19:58.940 --> 00:20:05.751 Doris Gammon: and was also, during the time that litigations were going on between the California oag and Reynolds tobacco 130 00:20:06.910 --> 00:20:10.410 Doris Gammon: about the determination that these products were presumptively flavored. 131 00:20:13.680 --> 00:20:22.350 Doris Gammon: We also see, like we did in the non-cigarette availability study. We see that there remains products on the market. They don't go to 0. 132 00:20:26.010 --> 00:20:28.950 Doris Gammon: The placebo results for these outcomes 133 00:20:29.330 --> 00:20:41.790 Doris Gammon: are here, and you can see that the Post Pre. Rms. PE in California was larger than any of the ratios in the placebo models for each outcome except the tobacco and unflavored cigarette pack cells. 134 00:20:42.500 --> 00:20:48.849 Doris Gammon: The ratio in California was also relatively low for the tobacco unflavored availability in pack cells. 135 00:20:50.410 --> 00:20:54.769 Doris Gammon: While the ratio in California was notably large for non-mental labeled pack cells. 136 00:20:55.340 --> 00:21:03.460 Doris Gammon: So again, these ones that are underlined are larger than all of the placebo bottles that were run, and it supports a policy effect. 137 00:21:06.960 --> 00:21:15.779 Doris Gammon: So, in conclusion, among menthol cigarettes, the policy was associated with reduced availability in pack cells. In the 1st year following, Sb. 793, 138 00:21:16.260 --> 00:21:21.079 Doris Gammon: and there was a lower but notable level of menthol cigarette availability in cells that remained 139 00:21:21.880 --> 00:21:29.120 Doris Gammon: for tobacco and unflavored cigarettes. There was weak evidence. The policy reduced availability and no change in pack cells. 140 00:21:30.240 --> 00:21:38.920 Doris Gammon: and for non-mental labeled cigarettes. We see the policy was associated with increased availability in pack cells. In the 1st year following, Sb. 7, 93. 141 00:21:39.050 --> 00:21:41.100 Doris Gammon: This could suggest substitution. 142 00:21:41.210 --> 00:21:47.240 Doris Gammon: We also saw a decrease in sales in late 2023 related to litigation around flavor, determination. 143 00:21:52.200 --> 00:21:54.330 Doris Gammon: The study has limitations. 144 00:21:55.320 --> 00:22:05.660 Doris Gammon: It excludes availability in sales and tobacco, specialty stores and online, and this could be particularly important when looking at end cells which often occur in those non-track channels. 145 00:22:06.640 --> 00:22:15.060 Doris Gammon: The availability and military commissaries and exchanges can't be parsed out. All of the cells are combined into one number across the store types. 146 00:22:15.320 --> 00:22:22.249 Doris Gammon: So it's important because military retailers are not required to comply with State law. They're under federal jurisdiction 147 00:22:22.510 --> 00:22:29.140 Doris Gammon: and compliance could be higher than we estimate. If the remaining availability is in military retailers. 148 00:22:30.826 --> 00:22:40.950 Doris Gammon: Our measure of availability is defined as any sales of a product over a specified period across the State. And it's unknown if continued availability is from a single store or multiple stores. 149 00:22:41.480 --> 00:22:45.719 Doris Gammon: but with a hundred percent compliance, availability would be 0 in state stores. 150 00:22:47.800 --> 00:22:50.179 Doris Gammon: The implications of this study are twofold 151 00:22:50.500 --> 00:22:59.609 Doris Gammon: statewide flavored tobacco sales, restrictions can be effective policies for substantially reducing the availability and sales of tobacco flavored tobacco products. 152 00:22:59.900 --> 00:23:07.970 Doris Gammon: However, enforcement and compliance agencies should be prepared to address avoidance. Tactics such as what we saw with the introduction of synthetic coolants 153 00:23:08.230 --> 00:23:21.990 Doris Gammon: and continued availability and sales of restricted tobacco products limits, the intended public health benefits of California's flavor ban law, and it suggests an opportunity for increased retailer education and enhanced enforcement. 154 00:23:25.580 --> 00:23:48.090 Doris Gammon: Finally, I wanted to go over some of the progress that's been made in the State of California to address, to strengthen the original flavored tobacco sales restriction. The 1st was Assembly Bill 935, which amended the California Steak Act. This became effective in January 2024, and it explicitly permits the local regulation and restrictions of Sb. 793. 155 00:23:48.830 --> 00:23:58.880 Doris Gammon: These local localities and jurisdictions were already allowed to regulate and or to enforce this policy, but this just explicitly put that on paper. 156 00:23:59.490 --> 00:24:05.400 Doris Gammon: It also expands the definition of a local retailer to include mobile units, such as vending machines and booths. 157 00:24:05.840 --> 00:24:20.180 Doris Gammon: It creates a tiered penalty system for violations, so that they increase with each subsequent violation, and it also clarified the roles of the California Department of Public Health and the Department of taxing the Administration in advancing and strengthening the State Labor law. 158 00:24:22.000 --> 00:24:35.880 Doris Gammon: and more recently, in September of last year 2 new bills were signed into Law Assembly Bill 32, 18, and Senate Bill 1230 together. These become effective by the way, January of 2025. So they just became effective. 159 00:24:36.210 --> 00:24:39.810 Doris Gammon: And they together create an unflavored tobacco list. 160 00:24:40.331 --> 00:24:53.290 Doris Gammon: Defining products allowed to be sold on the market. And this is to be administered by the State Attorney General's office in California, and it's supposed to go live on or before December 31st 2025 that's written in the law. 161 00:24:54.110 --> 00:24:58.949 Doris Gammon: These these laws also expand and clarify restrictions on delivery and online sales. 162 00:24:59.320 --> 00:25:05.999 Doris Gammon: They update the definition. This is important of characterizing flavor to include additives that create a cooling sensation. 163 00:25:06.420 --> 00:25:11.060 Doris Gammon: And subsequently, one month before this policy was to go into effect. 164 00:25:11.380 --> 00:25:18.799 Doris Gammon: Rj. Reynolds dropped their suit against the Ag. For the notices of determination that named their non-mental labeled cigarettes as flavored. 165 00:25:19.580 --> 00:25:30.290 Doris Gammon: It also updates the nicotine definition to include synthetic nicotine and nicotine analogs and it expands and increases fines and penalties and it expands the enforcement authority. 166 00:25:33.080 --> 00:25:42.980 Doris Gammon: So this was a lot. I have a couple takeaways. California's law prohibiting sales of flavored tobacco products did successfully reduce the availability and sales of flavored products. 167 00:25:43.520 --> 00:25:51.770 Doris Gammon: but remaining flavored product availability and sales in the 1st 6 months to one year. Post policy demonstrate an opportunity for further compliance. 168 00:25:52.240 --> 00:26:09.440 Doris Gammon: California, California is addressing enhanced compliance with the passage of the subsequent laws. We went over to strengthen the policy through increased fines, expanded location coverage, broader flavor and nicotine definitions and the explicit empowerment of multiple agencies to support enforcement. 169 00:26:09.880 --> 00:26:23.589 Doris Gammon: Our next steps are to study how change, how non-cigarette tobacco product sales changed in addition to the availability that we've done, and to assess the impact of these subsequent walls and to consider their applicability to current or future walls elsewhere. 170 00:26:25.770 --> 00:26:26.560 Doris Gammon: Thank you. 171 00:26:31.485 --> 00:26:34.398 Ce Shang: Thank you. So let's see 172 00:26:35.580 --> 00:26:51.330 Ce Shang: So I think it's time for our discussion to discuss the paper today. Our discussion is Dr. Zhongsun Duan, Assistant Professor from Department of Population Health Sciences at Georgia State University School of Public Health. 173 00:26:51.870 --> 00:26:56.799 Ce Shang: So Dr. Juan, take it from here and thank you. 174 00:26:57.373 --> 00:27:00.509 Zongshuan Duan: Yeah, thanks for inviting me here to be a discussant. 175 00:27:00.670 --> 00:27:19.849 Zongshuan Duan: And thank you, Doras, for introducing the background, methodology, and findings of those 2 very important studies. So the results are very meaningful. Given that the tobacco industry are really using flavor as a strategy to target youth, young adults and other priority populations. 176 00:27:20.405 --> 00:27:26.970 Zongshuan Duan: So I have a few questions today. Most of them are clarifying questions. 177 00:27:27.010 --> 00:27:50.899 Zongshuan Duan: So one thing I'm curious about is that nearly half of the California's population was already under some local flavored tobacco sales restriction before the Sb. 7. Before the statewide law. So can you elaborate like how the State law was functioning? Or was it more about scaling up 178 00:27:50.900 --> 00:28:04.300 Zongshuan Duan: or standardizing or closing any potential loopholes or gaps in the local policies? And how should we interpret some marginal and incremental effect of the State policy. 179 00:28:06.110 --> 00:28:10.040 Doris Gammon: Great questions. So the 180 00:28:10.750 --> 00:28:19.209 Doris Gammon: state policy doesn't preempt any local policies that were already in place. And so, if a jurisdiction already had 181 00:28:19.320 --> 00:28:27.070 Doris Gammon: a local flavored tobacco sales, restriction that was as strong or stronger than the statewide policy. Nothing changed for that jurisdiction. 182 00:28:27.597 --> 00:28:35.689 Doris Gammon: If if this locality had a weaker or no local policy, then the state policy would sort of preside over the law there 183 00:28:36.330 --> 00:28:45.200 Doris Gammon: and the we didn't study how we didn't study differential effects across different policy scenarios in this. 184 00:28:47.980 --> 00:29:01.450 Doris Gammon: But that's definitely an interesting question, and something to try to get at is how the state policy might have differentially impacted cells and availability in those local areas. 185 00:29:02.710 --> 00:29:18.120 Zongshuan Duan: Right? Yeah, so yeah, and also related to that. So so did you observe any regional differences in the impact of the state policy. So for areas with and without prior local flavor restrictions. 186 00:29:19.030 --> 00:29:19.570 Doris Gammon: Yeah. 187 00:29:19.570 --> 00:29:29.520 Doris Gammon: unfortunately, yeah, yeah, unfortunately, we we were using state level data. And so ourselves were one number for the state for every product. 188 00:29:29.933 --> 00:29:32.669 Doris Gammon: So we don't have that local variation in this study. 189 00:29:33.300 --> 00:29:34.410 Doris Gammon: In this data set. 190 00:29:35.440 --> 00:30:00.529 Zongshuan Duan: Okay, yeah. So yeah. And I also noticed that in the in the, in the measure session. So so in the published articles so the others mentioned that so they were using the flavor names from the packaging of the tobacco products to sort of clarify to classify the products as like concept, explicit 191 00:30:00.530 --> 00:30:28.749 Zongshuan Duan: and unflavored. So those 3 categories, so given that we know that the tobacco marketing tobacco companies, they are using different types of marketing strategies. So the language they are using in their packaging and labeling are really ambiguous and sometimes suggestive. So I just wonder how confident are you in the accuracy of the flavor categorization so based on the packaging only. 192 00:30:30.590 --> 00:30:32.509 Doris Gammon: Yeah, that's a great question, too. 193 00:30:33.720 --> 00:30:39.659 Doris Gammon: So I think the so the approach we took was that 194 00:30:40.590 --> 00:30:49.900 Doris Gammon: use the data? So the data say, what what was written on the product packaging. So the data vendor sort of they they code that from external product packaging 195 00:30:50.040 --> 00:30:50.720 Doris Gammon: and. 196 00:30:50.720 --> 00:30:51.090 Zongshuan Duan: Okay. 197 00:30:51.090 --> 00:31:04.480 Doris Gammon: So we used exactly what they coded to make our determination on. If the descriptor itself was explicit in terms of describing what would be defined as a characterizing flavor in the law. 198 00:31:05.235 --> 00:31:10.019 Doris Gammon: Or if it was not characterizing, then it would be concept. 199 00:31:10.260 --> 00:31:25.700 Doris Gammon: and the only reason it would be anything other for us is, if it says like only says tobacco, or general, or plain and then it can vary by whether or not the product has actual tobacco leaf in it. So our coding scheme is 200 00:31:25.820 --> 00:31:35.890 Doris Gammon: a little bit complicated, but I think to your point about they could name it whatever they they could name it tobacco and add flavors for sure, and so are you able to hear me. 201 00:31:36.420 --> 00:31:37.280 Zongshuan Duan: Yeah. 202 00:31:37.280 --> 00:31:43.829 Doris Gammon: Yeah, so they could name it tobacco on the pro product packaging. But they could add synthetic coolants in there, and we wouldn't know it 203 00:31:43.830 --> 00:31:44.880 Doris Gammon: right with this 204 00:31:44.880 --> 00:32:07.000 Doris Gammon: set. And so the office of the Attorney General's job is to say, Okay, flavor name is one way that we can maybe determine. A product is probably flavored, but they can also look at the way a product is advertised and marketed to help make that determination. But this study, of course, is limited to what's written on product packaging. And the assumption that 205 00:32:07.130 --> 00:32:15.029 Doris Gammon: if we say it's if if they say it's this and that descriptor is a characterizing descriptor that it has characterizing flavors. 206 00:32:15.160 --> 00:32:17.580 Doris Gammon: So there is a jump there that we have to make. 207 00:32:18.850 --> 00:32:29.159 Zongshuan Duan: Yeah, okay, yeah. So so yeah, so so it's basically coded based on like, the information provided by the scanner data set. 208 00:32:29.570 --> 00:32:50.270 Zongshuan Duan: Okay, got it? Okay, yeah. So yeah. So my next question is is about the results of those 2 studies. So so for the 1st study. So it's really great to see that the part, the flavor restriction policy really have a substantial impact 209 00:32:50.270 --> 00:33:02.939 Zongshuan Duan: on the explicit flavored products. As we can see that there's a large reduction of the upcs compared to before and after the policy went into impact. 210 00:33:02.950 --> 00:33:30.090 Zongshuan Duan: So I'm curious that so given that there are hundreds of flavored upcs, they are still available even after the State law went into effect. So what factors do you think are driving? This? Is this an issue like low, a slow enforcement, or some retailers, confusion or others. And what could be the potential implications for policies and practices. 211 00:33:31.610 --> 00:34:00.049 Doris Gammon: Yeah. So I think this might be related also to our relatively short post intervention period. So in the non-cigarette tobacco product availability study, we just had 6 months of data. That was all that was available at the time that we licensed the data. And so I think it's probably a lot of jurisdictions trying to get up to speed on. What does this mean? And retailers getting up to speed on? What does this mean? How do I operationalize. This. 212 00:34:01.550 --> 00:34:02.629 Doris Gammon: you know, is this. 213 00:34:02.750 --> 00:34:09.540 Doris Gammon: are they really enforcing this? And so I I think there's probably a learning curve there. And that 214 00:34:09.780 --> 00:34:24.900 Doris Gammon: I would hope, with the subsequent legislation and communication that we would, we would start to see that. And so that's, you know, an empirical question. But but for our study, I think. I think the short time period is 215 00:34:25.139 --> 00:34:27.449 Doris Gammon: probably working against us in terms of 216 00:34:28.080 --> 00:34:36.559 Doris Gammon: not working against us. But I I do think there's this time it takes time for the communication and the compliance to fully take hold. 217 00:34:37.164 --> 00:34:44.959 Doris Gammon: But from an industry perspective I don't know what's going on right. They're still just distributing those products to those stores to be sold. 218 00:34:45.710 --> 00:34:47.540 Doris Gammon: It seems like 219 00:34:47.969 --> 00:34:55.010 Doris Gammon: that's sort of blatantly happening as opposed to at the retailer level. I think there could. They probably just need more support and time. 220 00:34:55.889 --> 00:35:13.519 Zongshuan Duan: Yeah, okay? Yeah. And and also one minor question I'm curious about is that so is there any reason that for for the 1st study. So only the upc data are used instead of the sales data like the second study. Is there any particular reason for that? 221 00:35:14.450 --> 00:35:18.970 Doris Gammon: Yeah, I mean, I think we were focused on availability for that 1st study. And we, I think. 222 00:35:18.970 --> 00:35:19.450 Zongshuan Duan: Okay. 223 00:35:19.450 --> 00:35:21.700 Doris Gammon: Is to look at cells and. 224 00:35:21.700 --> 00:35:22.030 Zongshuan Duan: Okay. 225 00:35:22.030 --> 00:35:41.349 Doris Gammon: What availability can provide us, we think, is still really valuable in the sense that it gives us the array of all the products that are on the market, and how that's changing week to week. And we might, we might even think of that more as like an industry side component, whereas the sales might be more of a consumer side, the purchase and the amount of purchase. 226 00:35:41.480 --> 00:35:51.590 Doris Gammon: And so that availability measure kind of stands alone in that way. But we definitely want to take a next step and assess the changes in cells like we did in the cigarette study. 227 00:35:52.400 --> 00:36:14.229 Zongshuan Duan: Yeah, thank you. That's great. So yeah, I think now, we can sort of switch to the cigarette study. So yeah, so basically, I think the results of the second study is quite interesting and and striking to me, too. So we could see that how how responsive, how quickly the cigarette industry could respond 228 00:36:14.230 --> 00:36:32.700 Zongshuan Duan: to the policy change. As we can see, a sharp increase and a decrease of 2 types of products, mental and non-mental. So yeah, I just wonder is like, how should the policymakers address this type of product? Substitutions. 229 00:36:32.700 --> 00:36:36.760 Zongshuan Duan: like the nominal Cwise sharp increase like that. 230 00:36:38.970 --> 00:36:42.330 Doris Gammon: Yeah, it's hard to keep up with the industry. And 231 00:36:42.910 --> 00:36:53.059 Doris Gammon: so I think California is the model state in that they like. We showed at the end of the study is that they passed subsequent legislation to address that. 232 00:36:53.990 --> 00:36:58.260 Doris Gammon: Record time, you know, for that kind of process, so 233 00:36:58.680 --> 00:37:05.070 Doris Gammon: I don't know what else you could do except to just be ready to to be nimble. 234 00:37:06.560 --> 00:37:10.090 Doris Gammon: You know the loopholes, and and be ready to respond. 235 00:37:11.110 --> 00:37:16.210 Doris Gammon: You know, I think it's hard, though, like getting support for policy change can be an uphill battle. And 236 00:37:17.510 --> 00:37:32.449 Doris Gammon: so I I mean, I think there's a lot of possible solutions. But I think the most obvious one to me is what California did, which was to say, well, okay, we're gonna pass new laws. And on top of that we're gonna create this unflavored tobacco list. And 237 00:37:33.100 --> 00:37:34.620 Doris Gammon: right so. 238 00:37:34.620 --> 00:37:51.050 Zongshuan Duan: Yeah, yeah, I totally agree with that. Yeah. And also, I'm also curious about so so during the data analysis, so so did you observe any particular brands or products, drive the search in the non-mental labeled cigarette availability. 239 00:37:51.320 --> 00:37:57.930 Zongshuan Duan: So any particular brands or products, or from particular manufacturers, something like that. 240 00:37:59.080 --> 00:38:05.149 Doris Gammon: Yeah. So I mean definitely, there was the surge in the camel, non mineral products the Oas. 241 00:38:05.150 --> 00:38:05.820 Zongshuan Duan: Little hat. 242 00:38:05.820 --> 00:38:06.270 Doris Gammon: Those were. 243 00:38:06.750 --> 00:38:12.220 Doris Gammon: 1st to receive the notices of determination. In April of 2023. 244 00:38:12.410 --> 00:38:12.840 Zongshuan Duan: Okay. 245 00:38:13.020 --> 00:38:29.731 Doris Gammon: But there were many others, and the sales are a combination. I don't have the all the brands in front of me. That's a great question, though, and so we might be able to add some more information, either in the QA. If if we have that at our fingertips. I could also, 246 00:38:30.290 --> 00:38:33.220 Doris Gammon: email with you afterward about what that looks like. 247 00:38:33.900 --> 00:38:39.680 Zongshuan Duan: Yeah, sure. Thank you. Yeah. And yeah, yeah, I think, lastly, my last question, is that 248 00:38:39.680 --> 00:39:04.580 Zongshuan Duan: so? So it's like, Be so. So I saw the future studies you want to do in what to conduct in the next step session. So I also wonder beyond the product availability and sales. So do you see any plans for access like the consumer or the individual level impact of the California, Sb, 7, 9, 3. So, for example, using sir 249 00:39:04.580 --> 00:39:22.140 Zongshuan Duan: or consumer panel data. So to explore, like how consumer behaviors will change. So particularly among you know, youth, young adults and racial ethical minorities and other priority populations that are targeted by the tobacco flavors. 250 00:39:23.470 --> 00:39:30.869 Doris Gammon: Yeah, I mean, I definitely encourage everyone to look at across different data sources so that we can come up with 251 00:39:31.020 --> 00:39:40.490 Doris Gammon: so that we can challenge the independent. You know each study and compare it to others. Replicate this one. Yes, so I think in store. Retail observations are. 252 00:39:41.170 --> 00:39:56.190 Doris Gammon: To complement this work. Especially. Given the holes in, like the coverage of scanner data, we definitely need more data sources out there to explore and look at this population survey data. Yes, consumer panel data. Yes. So I think 253 00:39:56.810 --> 00:39:58.350 Doris Gammon: yes, there's a call for that. 254 00:39:58.830 --> 00:40:01.180 Zongshuan Duan: Yeah, yeah, okay. Thank you. 255 00:40:03.470 --> 00:40:28.049 Ce Shang: Thank you, Dr. Duan. So, audience, please keep your questions coming through the Q. And a panel. We look forward to hearing your questions, so I see there are some questions in the Q. And a panel. So one from Nobel shamed has there been any study done to evaluate the effect of unintended consequences from the affected population. 256 00:40:33.850 --> 00:40:38.280 Doris Gammon: So I'm not sure exactly how to answer that question. 257 00:40:39.393 --> 00:40:43.280 Doris Gammon: I accidentally pulled up the chat. There, let's pull that question back. 258 00:40:43.280 --> 00:40:46.530 Ce Shang: I I think you know. The 259 00:40:47.800 --> 00:40:59.769 Ce Shang: in your studies. Do you have plans, for example, to study unintended consequences? You're reviewing the literature. What's your takeaway about a possible unintended consequences? 260 00:41:00.890 --> 00:41:04.330 Doris Gammon: Sure. Yeah, I mean within our study 261 00:41:04.460 --> 00:41:15.420 Doris Gammon: that we've already done. We can see that the increase in availability and sales of these non menthol labeled products. It was an unintended consequence, I think, of the Paul of 262 00:41:16.960 --> 00:41:21.889 Doris Gammon: of the policy, and but in terms of the population level. 263 00:41:23.127 --> 00:41:29.889 Doris Gammon: With this a secret legislation. I think there's hope that there'll be, you know, less unintended consequences. 264 00:41:30.950 --> 00:41:36.560 Doris Gammon: So if if you have a follow up questions on that, I'm happy to answer. 265 00:41:36.560 --> 00:41:48.720 Ce Shang: Yeah, yeah, thank you. There's question from Cheryl Olsen. There has been an increase in smoke shops opening near me in Silicon Valley, in California in the past 2 years. 266 00:41:48.890 --> 00:42:01.820 Ce Shang: I don't know what mix of nicotine products are combustible or non-combustible, legal or illegal. They are selling, but demand has clearly not decreased. Have you looked at changes in the elicit tobacco market. 267 00:42:03.840 --> 00:42:05.519 Doris Gammon: Yeah, thanks for that question. Cheryl. 268 00:42:05.790 --> 00:42:11.859 Doris Gammon: with this data. No, we haven't looked at that. There are other ways to get at 269 00:42:13.650 --> 00:42:20.549 Doris Gammon: either illicit or illicit purchases, I guess, within the State 270 00:42:20.760 --> 00:42:47.209 Doris Gammon: which, through the in storytell observations, you can kind of get at whether or not those vape shops are selling these products. There was a recent paper by Arzoom that was just put out in tobacco control with the Stanford team that did survey vape shops around California, near and and farther from college campuses, and they found that in about half of stores they were selling flavored, disposable vapes. 271 00:42:48.159 --> 00:42:56.140 Doris Gammon: So definitely, I think, still room based on those studies and our findings, for in enhanced compliance. 272 00:42:56.780 --> 00:43:01.400 Doris Gammon: but so those would be considered illicit. Yeah. 273 00:43:03.240 --> 00:43:30.039 Ce Shang: Thank you. There's a question from Matthew Stone. You know that news, and IQ. Tracks 312 California commissaries, 261 of which is a very accurate like, they're very detailed numbers 261 of which reported tobacco sales. Yeah, these outlets are exempt from the statewide flavor ban, and may therefore inflate post-policy availability estimates. 274 00:43:30.120 --> 00:43:44.880 Ce Shang: Have you explored a sensitivity analysis that removes, commiserate upc altogether, or compares counties with versus without basis to gauge how much the exemption might be masking true retail compliance. 275 00:43:46.970 --> 00:44:10.470 Doris Gammon: yeah, so we reached out to Nelson about this, the data vendor who license the data to us, and we asked them. Hey, can we get this? The channel of data that we get is sort of like that group of stores I read in the beginning, in our methods or data section. It's a comp, it's it's the most comprehensive group of cells that we can get in the State. 276 00:44:10.660 --> 00:44:21.450 Doris Gammon: But the limitation is that it includes those commissary cells, and not just commissaries, but naval changes and other things. Any kind of military retail store and 277 00:44:21.863 --> 00:44:27.129 Doris Gammon: we asked them, could they parse it out? And they said, No, so what I did was, I actually 278 00:44:27.300 --> 00:44:35.709 Doris Gammon: started calling commissaries and talking to grocery managers and just trying to get a sense of what kind of tobacco products do you have? What are you selling? 279 00:44:36.010 --> 00:44:57.339 Doris Gammon: So I just called a small sample of them. One sold no tobacco, and then the others sold only limited lines of tobacco like some didn't sell e-cigarettes. Some didn't sell nicotine pouches, some didn't sell cigars, and so it was kind of all over the place. They some did sell cigars, and they sold wine, flavored cigars, for instance. So it was an interesting exercise. 280 00:44:57.510 --> 00:45:04.423 Doris Gammon: But what I came away with was that tobacco products are not ubiquitous in the military retailers. 281 00:45:05.690 --> 00:45:09.600 Doris Gammon: but also that you know, we need to look at other ways to 282 00:45:09.790 --> 00:45:18.399 Doris Gammon: ask this question where it's not, where that limitation, maybe is, is more limited or less influential in our study. Great question. 283 00:45:19.480 --> 00:45:37.339 Ce Shang: Thank you. Our Mike Pesco have 2 has 2 questions. The 1st one is, can you tell us anything? Which about the donor which donor states were selected to make up synthetic California. I know that it probably differs based on outcomes. 284 00:45:38.200 --> 00:45:49.859 Doris Gammon: Yeah, that's a good question. We didn't present that we. We could have presented a a nice graph on that. We didn't. I don't have that information in front of me, but I'm happy to share that after the call with anyone who's interested. 285 00:45:51.020 --> 00:45:54.059 Doris Gammon: Yeah. And it would differ. It does differ by outcome, for sure. 286 00:45:54.640 --> 00:46:08.940 Ce Shang: Thanks. The second question is, Topps has had a lot of presentations studying flavor restrictions. Does your study offer any surprising findings or novel insights within the context of the broader literature. 287 00:46:11.570 --> 00:46:13.984 Doris Gammon: Yeah, I mean, I don't think there's 288 00:46:15.530 --> 00:46:20.570 Doris Gammon: I mean, I think what this adds is a larger 289 00:46:20.700 --> 00:46:24.410 Doris Gammon: geographic look at what happened with. 290 00:46:25.210 --> 00:46:30.120 Doris Gammon: and sort of larger coverage of what happened with the non menthol labeled products in California. 291 00:46:31.226 --> 00:46:37.290 Doris Gammon: There have been some studies, but not any that have looked sort of statewide at what's going on. 292 00:46:37.470 --> 00:46:43.170 Doris Gammon: So I'm I'm glad that we're able to provide that to the literature. 293 00:46:43.570 --> 00:46:49.020 Doris Gammon: Yep, wasn't necessarily surprising, because we early on, saw what was happening in the market. 294 00:46:52.340 --> 00:46:54.659 Doris Gammon: I'll have to think about your question a little more. But yeah. 295 00:46:55.078 --> 00:46:55.914 Ce Shang: Thank you. 296 00:46:57.240 --> 00:47:06.059 Ce Shang: we have more audience questions. So Thomas Wilk is asking, do you know if the Nielsen data include vendors on tribal lands? 297 00:47:07.160 --> 00:47:09.960 Doris Gammon: That's a great question. And it can. 298 00:47:10.260 --> 00:47:28.869 Doris Gammon: So it depends. And that's something we're working with Nelson on right now. For other studies actually to understand more about, because if it does, the implication there is that it's another limitation. You know, there is a history of people going to reservations and Indian tribal lands to 299 00:47:29.360 --> 00:47:31.010 Doris Gammon: purchase 300 00:47:31.290 --> 00:47:44.950 Doris Gammon: cigarettes either for cheaper prices or now for getting the flavors that are no longer available in their their regular store. So I'm really glad you asked that question, and that's going to stay a priority for us to dig into. 301 00:47:46.450 --> 00:48:07.859 Ce Shang: There's another question from Nober Schmidt. What are vape shops in California supposed to exit on if they restrict themselves to legal products? Have you evaluated. How many shops have closed because of this legislation? I know this is a little beyond what you talked about. But is there any evidence or any data that can help answer the questions. 302 00:48:09.080 --> 00:48:14.250 Doris Gammon: I have a few thoughts, so there. 303 00:48:14.620 --> 00:48:22.800 Doris Gammon: the the ban doesn't restrict all in sales, so they can be tobacco or unflavored. And 304 00:48:24.070 --> 00:48:39.070 Doris Gammon: I, you know Justin White is who I'm thinking of about this question because you've done some work on sort of the impact on, you know, retailers of these policies, but I don't know if you've done this work for this particular policy and and specific to vape shops. 305 00:48:42.440 --> 00:48:46.839 Ce Shang: Okay? So no question from 306 00:48:47.170 --> 00:48:56.070 Ce Shang: Lubasi or Obedi. Have you explored the intersectionality of tobacco control and marginalized groups like gender? 307 00:48:57.227 --> 00:48:58.899 Ce Shang: I'm just wondering. 308 00:48:58.900 --> 00:49:15.759 Doris Gammon: Yes, we have done that. But we haven't done that in this study. So this data doesn't lend itself to really person level characteristics. And so we can't really get at that detailed level. It's a really important topic area. But unfortunately, we weren't able to get at that with this study. 309 00:49:16.810 --> 00:49:33.102 Ce Shang: Thank you. So I have a question regarding the measurement of availability. I'm just wondering, like, how comprehensive does retail scanner data provide in terms of the availability. Because, 310 00:49:34.210 --> 00:49:55.780 Ce Shang: if you think of the the market of tobacco, you know, there are vape shops. There are online stores. There are multiple sources where consumers can get their products. So I'm just wondering. And if even if that just looking at the data, sometimes they may not be able to pick up the emerging brands. So I'm just wondering, like. 311 00:49:56.080 --> 00:50:01.480 Ce Shang: how reliable availability measure is based on a retailer scanner data. 312 00:50:02.910 --> 00:50:21.960 Doris Gammon: Yeah, I mean, it's within the. It's within the confines of the store types. That it represents, I would say. And so there absolutely is a gap. We don't know what this means about availability and access online or in non tracked stores, but among the stores that are tracked, I mean, Nelson has. 313 00:50:22.723 --> 00:50:23.609 Doris Gammon: I think 314 00:50:23.800 --> 00:50:53.330 Doris Gammon: I want to say their actual data that they get. So they get data from a slice of stores across the nation, and then they have proprietary projection methods from which they then project what all of those stores are selling, and I think for a lot of them they can be fairly accurate projections in theory, because for some of their sample they might get like, let's say, half of the Bps but the rest they have to project to, but the distribution 315 00:50:53.480 --> 00:50:57.590 Doris Gammon: routes and channels. And I'm just speculating here. You know. Would 316 00:50:57.680 --> 00:51:23.869 Doris Gammon: the the inventory would probably be similar across the different franchises or chains now with independence, which they do also get information on independence. I think there's more manual from the Nelson IQ. Side. I think there's more manual in store audits happening. And we we know that they're still not capturing everything, even in those stores, but within what they do capture. This is what we see. 317 00:51:25.160 --> 00:51:25.830 Ce Shang: Thanks. 318 00:51:26.880 --> 00:51:34.220 Ce Shang: question from Caddy Corner. Would you feel comfortable? Utilizing this study design at a county level versus state. 319 00:51:35.810 --> 00:51:37.019 Doris Gammon: This design, and. 320 00:51:37.403 --> 00:51:40.466 Ce Shang: I could see inside control. It's my understanding. 321 00:51:42.480 --> 00:51:45.520 Doris Gammon: Yeah, I mean, I think as long as 322 00:51:46.100 --> 00:51:52.980 Doris Gammon: i mean, I think you do have to consider some of the assumptions of the synthetic control method. So that it's not like 323 00:51:53.790 --> 00:51:55.649 Doris Gammon: misused, I suppose. 324 00:51:55.940 --> 00:52:08.790 Doris Gammon: but I think with the right amount of information and data on the different units of analysis. You could absolutely employ the method at a more geographically granular level. 325 00:52:10.430 --> 00:52:33.119 Ce Shang: Yeah, I guess. That's a very interesting question. Because I I think that if you wanna do a deeper dive into the county level information that provides you can potentially select donor counties from outside California and do a county level analysis. Looking at each of the California county and see how the sales change. 326 00:52:33.931 --> 00:52:35.938 Ce Shang: Just that, I think. 327 00:52:36.690 --> 00:52:48.210 Ce Shang: from methodological perspective that can be done. I feel it's just, you know. I don't know there are any pros and cons to to go that route versus, you know, conducting analysis at the State level. 328 00:52:49.070 --> 00:52:58.150 Doris Gammon: Yeah. And I, I am remembering now there might be the synthetic control method, at least in the like version. One kind of thing that we're using is 329 00:52:58.610 --> 00:53:06.923 Doris Gammon: maybe only set up to have a single treatment group. So if you were at the county level and you had multiple treatment groups, 330 00:53:07.670 --> 00:53:13.660 Doris Gammon: You might reconsider that model or see if there's a different version of the synthetic control method that you could run 331 00:53:14.064 --> 00:53:17.720 Doris Gammon: but I haven't. I haven't done that. So Tbd. 332 00:53:18.295 --> 00:53:20.019 Ce Shang: Thanks. Another. 333 00:53:20.020 --> 00:53:26.960 Jim Nonnemaker: There are generalizations of the synthetic control method that have been developed for those types of situations. 334 00:53:28.840 --> 00:53:41.529 Ce Shang: Thanks, Jim. So a question from Mike Pasco. Again, did you use all pre-period time units or select pre-period time units for feeding Cincinte, California. 335 00:53:47.813 --> 00:53:58.819 Doris Gammon: So we used all of the data available in the model. So for the selection of the synthetic control, it was all the same time period for every 336 00:53:59.240 --> 00:54:03.200 Doris Gammon: observation or unit or state. 337 00:54:03.300 --> 00:54:09.009 Doris Gammon: So all pre-period time units, I think the answer is yes to your question. 338 00:54:11.010 --> 00:54:15.510 Doris Gammon: Yeah. So we didn't. We didn't select anything. No, I think it uses what you give it. So 339 00:54:15.908 --> 00:54:19.630 Doris Gammon: the model will use the time period that you give it to make that selection. 340 00:54:20.990 --> 00:54:21.455 Ce Shang: Okay. 341 00:54:21.920 --> 00:54:30.680 Jim Nonnemaker: You can actually choose that. But we I'm guessing. Morgan could probably speak to this better than I could. I'm assuming we did use all of them. 342 00:54:30.810 --> 00:54:31.900 Jim Nonnemaker: You could 343 00:54:32.330 --> 00:54:40.970 Jim Nonnemaker: use a smaller set, for example, if you thought that for some years prior there was a reason to 344 00:54:41.490 --> 00:54:48.510 Jim Nonnemaker: not include them, because that might introduce differences or something along those lines. Oh. 345 00:54:51.250 --> 00:55:00.023 Ce Shang: Yeah, sure there are a lot of consideration about the methods here. So it's very, very interesting. 346 00:55:00.630 --> 00:55:23.620 Ce Shang: I think I don't see any additional questions in the Q. And a panel. So thank you, everyone. So I'll ask our Mc. To take us out. And for audience who are interested in further discussion. We have top of the tops followed. So yeah, thank you. 347 00:55:24.030 --> 00:55:25.820 Ce Shang: Tony, please take it away. 348 00:55:26.170 --> 00:55:33.560 Tony Lugemwa: Well, we are unfortunately out of time. However, if you are still having any burning questions or thoughts 349 00:55:34.345 --> 00:55:41.919 Tony Lugemwa: for, miss, you can join us for top of the tops an interactive group discussion to join. 350 00:55:42.050 --> 00:55:54.727 Tony Lugemwa: Please copy the Zoom Meeting room, URL posted in the chat and switch rooms with us once. This is and concludes, we leave this webinar room open for an extra minute after the end of 351 00:55:55.230 --> 00:55:59.569 Tony Lugemwa: after the end, to give everyone a chance to copy the URL, which is 352 00:55:59.780 --> 00:56:06.860 Tony Lugemwa: bit.li that's bit.li stroke top tops meeting 353 00:56:08.194 --> 00:56:16.700 Tony Lugemwa: I'd like to thank you our presenter moderator and discussant. Finally, thank you. To the audience of 212 people 354 00:56:17.100 --> 00:56:20.940 Tony Lugemwa: for your participation have a top snots, weekend.