Beverage consumption among adults in Newfoundland and Labrador, Canada prior to the implementation of a sugar-sweetened beverage tax

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Zaltz, Rachel Prowse, Yanqing Yi, Jessica O’Dea, Scott V. Harding This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4606952/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Mar, 2025 Read the published version in BMC Public Health → Version 1 posted 4 You are reading this latest preprint version Abstract Background Lawmakers in Newfoundland and Labrador (NL) recently passed Canada’s first sugar-sweetened beverage (SSB) tax. SSB tax evaluations rely on detailed understandings of beverage consumption patterns prior to policy implementation, but there is no recent literature about such patterns among NL residents during the pre-tax period. Methods We recruited a convenience sample of NL adults ages 19 and older and measured participant characteristics via online surveys and beverage intake via previously-validated, semi-quantitative beverage frequency questionnaires. We described the prevalence and mean intake of taxable SSBs, non-taxable SSBs, unsweetened beverages, and diet (non-nutritive sweetened) beverages. We explored bivariate associations between consumption of these beverages and sociodemographic characteristics identified as potential correlates of SSB intake. Results The sample (n = 1233) was 65% female, 57% between ages 30–59 years, and nearly all (94%) white. More than half (56.4%) consumed taxable SSBs weekly, and 63.3% consumed non-taxable SSBs weekly. The most-consumed taxable SSB was regular pop (mean (SD) 2092 (3120) mL/week); the most-consumed non-taxable SSB was coffee with added milk or sugar (mean (SD) 3859 (2895) mL/week). The prevalence of consuming taxable SSBs decreased with increasing age (18-30y 73%, 30-44y 65%, 45-59y 50%, 60y + 43%, p < 0.001), and was higher among males (60% vs. 54%, p = 0.04) and those reporting food insecurity (64% vs. 51%, p < 0.001). The prevalence of unsweetened beverage consumption was higher among those with more education (high school 81%, some post-secondary 88%, post-secondary or more 96%, p < 0.001), those working vs. not (92% vs. 87%, p = 0.006), and those above the poverty threshold (93% vs. 84%, p < 0.001). Weight status was only associated with diet beverage consumption (overweight/obese 54%, not overweight/obese 35%, p < 0.001). Conclusions Our findings align with prior studies of socioeconomic position and SSB consumption in Canada, which collectively demonstrate that, on average, those with lower knowledge and material resources consume more SSBs and fewer unsweetened beverages. This research provides necessary understanding of social patterning of beverage consumption in NL prior to tax implementation. Post-tax evaluations of this policy should investigate potential impacts of the tax on diet and health inequalities, as well as potential unintended consequences of beverage substitutions towards non-taxed SSBs. sugar-sweetened beverage tax health equity Canada Background Overconsumption of free or added sugars, defined as those added to any foods or beverages and those present in honey, syrup, and fruit juice, is associated with long term chronic health risks ( 1 ). Less than half of all Canadians meet the World Health Organization recommendation to consume fewer than 10% of total daily calories from free or added sugars, and only 5.4% meet the conditional recommendation for optimal nutrition to consume fewer than 5% of total daily calories from these sugars ( 2 ). Sugar-sweetened beverages (SSB) are the leading source of free or added sugars in the Canadian diet ( 3 ) and are thus a target for public health intervention. Health taxes are a leading method to reduce SSB consumption and improve diet quality ( 4 ). These taxes exist in more than 100 countries and are associated with decreases in purchasing and consumption, which, along with other policies focused on packaging, marketing, and availability, comprise a critical suite of public health interventions designed to reduce diet-related chronic diseases ( 4 ). There is no current national SSB tax in Canada, but in 2022, Newfoundland and Labrador (NL) became the first province to introduce its own excise-type SSB tax. While the taxation policy was introduced through the provincial government’s Department of Finance, the policy is promoted as an initiative to support health as the NL population has high incidences of both overweight and obesity ( 5 ), a large chronic disease burden ( 5 ), and highest per capita health care costs of all ten provinces in Canada. The NL SSB tax was introduced along with a public health messaging campaign titled “Rethink Your Drink” which aimed to promote water and other non-sugar-sweetened beverage options as the drink of choice ( 5 ). The NL policy is an excise tax of $ 0.20/litre imposed on SSB wholesalers based on their sales volume to retailers in the province; this tax is intended to be passed on fully from wholesalers to retailers, who receive no remittance with the expectation of passing the tax on to the consumer ( 5 ). The policy applies to all ready—to-drink sugar-sweetened soft drinks (i.e. soda/pop), bottled/canned or dispensed; and sugar-sweetened concentrated drink products (i.e. frozen concentrated fruit drinks, powders, and flavoured syrups). Beverages prepared at point-of-service with added sugar (e.g., blended coffee drinks) are not considered taxable; chocolate milk and 100% fruit juice are excluded from the policy ( 5 ). The NL SSB tax is the first of its kind in Canada and data collection to assess its impact is ongoing. Still, baseline research on the target population, including their pre-tax beverage consumption patterns, is needed. In a recent review on SSB reduction policies, Krieger and colleagues (2021) specifically highlight the need for an initial understanding of the target population and the characteristics associated with beverage consumption as a way to guide subsequent implementation and evaluation research ( 6 ). However, there is no data on SSB consumption in NL since the most recent Canadian Community Health Survey in 2015, and therefore no understanding of beverage consumption in the immediate period leading up to the new tax ( 7 ). Therefore, the purpose of this study was to measure beverage consumption among adults in NL, and to explore associations between social and demographic characteristics and beverage consumption patterns, prior to SSB tax implementation. Methods Overview This is a cross-sectional analysis of beverage consumption patterns and sociodemographic characteristics among adults ages 19 years and older residing in NL in August 2022, prior to the implementation of a SSB tax on September 1, 2022. Two recruitment approaches were used to recruit study participants and collect survey data. The research team recruited a convenience sample (e.g. social media advertising, direct email) and administered the survey from Memorial University using an online survey and data collection software (QualtricsXM, Seattle, WA, USA). The research team also used a commercial research company (MQO Research, St. John’s, Canada) to administer the same survey to an established consumer research panel on their survey software platform. All study participants provided informed consent prior to completing the online survey and upon completing the survey, each participant was offered either a $ 10 e-gift card or a similar honorarium from the commercial consumer research company. This study protocol was reviewed and approved by the Interdisciplinary Committee on Ethics in Human Research at Memorial University (ICEHR Number 20222081-SC). Demographic Questionnaire The demographic questionnaire captured information about participants’ age (years), sex at birth (male/female), gender (male, female, non-binary, prefer not to say), education (some/all high school, some post-secondary, Bachelor’s or more), occupation status (currently vs. not currently working), annual household income, children in home (children under 18 years in home, children 18 years and older in home, no children in home), race and ethnicity (White, Black, East/Southeast Asian, South Asian, Latino/a, Middle Eastern, Indigenous Canadian, other), food security status (secure, marginal, moderate, severe) using the 18-item Household Food Security Survey Module (HFSSM) in the Canadian Income Survey (CIS) and the Canadian Community Health Survey (CCHS) ( 8 , 9 ), height, and weight. We report sex assigned at birth because fewer than 1% of respondents indicated a gender identity different than their sex. We categorized age in four categories (< 30, 30–44, 45–59, 60 + years) and dichotomized race and ethnicity as White and non-White given extremely low (1–3%) proportions of responses for all non-White options. We categorized respondents’ poverty status as either above or below $ 50,000/year, which is the midpoint of the Statistics Canada 2022 Market Basket Measure thresholds for reference families in NL ( 10 ). We combined marginal, moderate, and sever food security statuses to represent food insecure. Finally, we used self-reported height and weight to calculate individual body mass index (BMI, kg/m 2 ) and categorized individuals as overweight or obese (BMI ≥ 25kg/m 2 ) versus not overweight or obese (BMI < 25kg/m 2 ). Beverage Consumption Study participants reported their beverage intake during the past seven days using a validated, semi-quantitative beverage frequency questionnaire ( 11 ). The beverage frequency questionnaire has been used extensively in survey-based research to evaluate food policies around the world through the International Food Policy Study ( 12 ). Participants reported how many times in the past week they consumed each of the following beverages, respectively: regular soda/pop, diet soda/pop, 100% fruit juice, sweetened fruit drinks, low/no-calorie fruit drinks, tap water, plain bottled water, flavoured/sweetened water, low/no-calorie flavoured water, regular sports drinks, low/no-calorie sports drinks, regular energy drinks, diet energy drinks, unflavoured milk or milk alternatives, flavoured/sweetened milk or milk alternatives, coffee, tea, specialty coffee drinks, sweetened smoothies/shakes, and unsweetened smoothies/shakes. Then, for each beverage respectively, participants selected the size of the cup, mug, can, bottle, or carton that corresponded to their usual intake amount, prompted by photographs of beverage containers and sizes in milliliters ( 11 ). We calculated beverage consumption, in milliliters, during the past seven days, multiplying the frequency and volume reported for each beverage ( 11 ). When participants reported less than the smallest size provided (i.e. less than 250 mL), we used a value of 50% of the volumes of the lowest serving size option presented to the participants ( 11 ). Similarly, when participants reported consuming more than the greatest size, we used a value of 125% of the volume of the largest serving size option presented to the participants ( 11 ). For interpretability, we created four beverage categories and summed total intakes within these categories: Unsweetened beverages (no added sugar or non-nutritive sweeteners): plain water, plain unflavoured milk, 100% fruit juice, coffee/tea black Taxable SSBs (subject to the NL SSB tax): regular soda/pop, juice drinks, regular sports drinks, regular energy drinks, flavoured/sweetened water Non-taxable (SSBs not subject to the NL SSB tax):coffee/tea with sugar, specialty coffee drinks, flavoured/sweetened milk, sweetened smoothies/shakes Diet beverages (sweetened with non-nutritive sweetener): diet soda/pop, diet flavoured water, diet juice drinks, diet sports drinks, diet energy drinks Statistical Analysis Data Cleaning A trained research assistant reviewed all new survey entries daily to identify and remove duplicitous attempts using strategies identified as the most effective by Storozuk et al. (2020) ( 13 ). Once the research team data and commercial research panel data were combined, we completed quality checks and reviewed the dataset for beverage intakes that would be considered improbable (e.g. excess of normal fluid intakes). We recoded all beverage frequency variables as missing when the frequency of beverage consumption per week equivalent to 0, greater than 100, or a non-number. Also, when the total beverage volume consumed per week exceeded 49 litres, and/or when the total volume of water exceeded 36 litres, all derived beverage frequency variables were recoded as missing ( 11 ). We summarized central tendencies, frequencies, and proportions of all demographic and beverage intake data. Then, we calculated the frequency and proportion of the study population who reported any consumption within each beverage category, and the weekly mean and standard deviation of consumption within each beverage category among those who reported any consumption. Finally, we explore bivariate associations between sociodemographic characteristics and beverage consumption in two parts: first, within each sociodemographic variable, we analyzed associations in the prevalence of weekly consumption (any versus none) for each beverage category using Pearson χ 2 tests; second, we analyzed differences in the average weekly consumption, in mililiters, of each beverage category, among those who reported any consumption, using Wilcoxon rank-sum tests for sociodemographic variables with two groups and Kruskal-Wallis tests for those with more than two groups. For all tests, we set an a priori α = 0.05 threshold for statistical significance. The results from these tests are unadjusted and should be interpreted cautiously and used for generating, rather than confirming, relevant hypotheses. We conducted all analyses using R statistical software 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria). Results Sample characteristics The study sample (n = 1233) was 65.2% female, over half (57.2%) were between 30–59 years old, and nearly all (93.8%) were white (Table 1 ). Most (84.2%) had some post-secondary or more education, and 58.7% were currently working. Two-thirds of the sample had annual household income above the poverty threshold, 61.3% were food secure, and most (71.7%) lived without children in the home. The majority (71.1%) of the study population were classified as overweight or obesity. Table 1 Demographic characteristics of study sample before implementation of a sugar-sweetened beverage tax in Newfoundland and Labrador (n = 1233) Characteristic Non-missing sample size, n (%) 1 n (%) Age group 19–29 years 1233 (100%) 237 (19.2%) 30–44 years 308 (25.0%) 45–59 years 397 (32.2%) 60 + years 291 (23.6%) Sex assigned at birth Female 1225 (99.3%) 799 (65.2%) Male 426 (34.8%) Education Some/all high school 1223 (100%) 193 (15.8%) Some post-secondary 541 (44.2%) Bachelor's or more 489 (40.0%) Occupation status Currently working 1217 (99.5%) 715 (58.7%) Not currently working 502 (41.3%) Poverty status 2 Below poverty threshold 1117 (91.3%) 370 (33.1%) Above poverty threshold 747 (66.9%) Food security status 3 Food secure 1187 (96.3%) 728 (61.3%) Not food secure 459 (38.7%) Children in home Children < 18y in home 1206 (98.6%) 341 (28.3%) No children in home 865 (71.7%) Race/Ethnicity 4 White 1215 (99.3%) 1140 (93.8%) Non-white 75 (6.2%) Overweight/obesity status 5 Overweight/obese 1064 (87.0%) 757 (71.1%) Not overweight/obese 307 (28.9%) 1 Total sample size within the specific measured characteristic without missing data; proportion of total study sample n = 1233 2 Based on self-reported annual income and Statistics Canada 2022 Market Basket Measure thresholds for reference families in Newfoundland and Labrador 3 Calculated using Statistics Canada Household Food Security Survey Module; food insecure includes marginal (9%), moderate (19%), and severe (12%) food insecurity 4 All self-reported non-white categories collapsed due to very small cell sizes; include 2.3% Indigenous, 1.5% East/Southeast Asian, 1% Black, and < 1% each South Asian, Latino/a, Middle Eastern, or those who reported “other” 5 Based on BMI calculated from self-reported height and weight; respondents with BMI ≥ 25 kg/m 2 considered to have overweight or obesity Beverage consumption, overall Study participants had the highest prevalence of weekly consumption of unsweetened beverages (89.9%), and the lowest prevalence of diet beverage consumption (49.1%) (Table 2 ). More than half (56.4%) consumed taxable SSBs weekly, and nearly two-thirds (63.3%) consumed non-taxable SSBs weekly. Participants consumed approximately 10,000 mL of unsweetened beverages per week, the majority of which came from plain water and black coffee or tea. The most-consumed taxable SSB was regular pop, at a mean (SD) 2092 (3120) mL/week; diet pop was the most-consumed diet beverage at a mean (SD) 2527 (3519) mL/week). The most-consumed non-taxable SSB was coffee with added milk or sugar at a mean (SD) 3859 (2895) mL/week. Table 2 Weekly beverage consumption among adults ages 19 years and older before implementation of a sugar-sweetened beverage tax in Newfoundland and Labrador Beverage Proportion of study sample who reported any weekly consumption, n (%) Weekly consumption, mL, among those who reported any consumption, mean (SD) Unsweetened beverages 1 1108 (89.9%) 10364 (8000) Plain water 1028 (83.4%) 8742 (7297) Plain, unflavoured milk (all fat types) 424 (34.4%) 1501 (1700) 100% Fruit Juice 473 (38.4%) 937 (1183) Coffee or tea, black 294 (23.8%) 4494 (3395) Sugar-sweetened beverages subject to tax 2 696 (56.4%) 2663 (3454) Regular soda/pop 547 (44.4%) 2092 (3120) Sugar-sweetened juice drinks 226 (18.3%) 996 (1262) Sugar-sweetened sports drink 148 (12.0%) 1417 (1382) Sugar-sweetened flavoured water 94 (7.6%) 1839 (2458) Sugar-sweetened energy drinks 67 (5.4%) 1500 (1986) Sugar-sweetened beverages not subject to tax 3 781 (63.3%) 3773 (3039) Coffee or tea, with milk or sugar 661 (53.6%) 3859 (2895) Blended, sugar-sweetened coffee drink 157 (12.7%) 1037 (948) Sugar-sweetened, flavoured milk 116 (9.4%) 1401 (2577) Sugar-sweetened smoothies 69 (5.6%) 1025 (1326) Diet beverages 4 606 (49.1%) 3108 (3880) Diet soda/pop 471 (38.2%) 2527 (3519) Diet, flavoured water 141 (11.4%) 2576 (3202) Diet juice drinks 100 (8.1%) 1059 (1131) Diet sports drink 83 (6.7%) 1814 (1915) Diet energy drinks 47 (3.8%) 1552 (1503) 1 Includes all beverages with no added sugars or sweeteners and 100% fruit juice which contains free but not added sugars 2 Includes ready-to-drink beverages and prepared dispensed beverages that contain added sugars (e.g. sugar, fructose, glucose, glucose-fructose, sucrose, honey, molasses, syrups etc.), including sugar-sweetened soda/pop, fountain drinks, juice drinks, sweetened waters, sports drinks, energy drinks, iced teas, and lemonades. Does not include beverages made at point-of-service. 3 Includes sweetened milks, coffee or tea with sugar added by consumer, and point-of-service smoothies and blended coffee drinks made on site. Beverage consumption and demographic characteristics The weekly prevalence of consuming unsweetened beverages was independently associated with education, occupation status, and income (Table 3 ). Nearly all (96.1%) individuals with a Bachelor’s degree or more consumed unsweetened beverages each week, compared to 87.8% among those with some post-secondary education and 81.3% among those with some or all high school (χ 2 ( 2 ) = 39.64, p < 0.001). Individuals currently working had a higher prevalence of consuming unsweetened beverages compared to those not working (92.0% vs. 87.3%, χ 2 ( 1 ) = 7.51, p = 0.006), as did those living above, versus below, the poverty threshold (93.4% vs. 83.5%, χ 2 ( 1 ) = 27.47, p < 0.001). There were no associations between age, sex, food security, or weight status and the prevalence of consuming unsweetened beverages. Table 3 Unadjusted associations between select demographic characteristics and prevalence weekly beverage consumption among adults ages 19 years and older before implementation of a sugar-sweetened beverage tax in Newfoundland and Labrador (n = 1233) Characteristic Unsweetened beverages, n (%) 1 SSBs targeted by legislation, n (%) 2 SSBs not targeted by legislation, n (%) 3 Diet beverages, n (%) 4 N (%) p 5 N (%) p 5 N (%) p 5 N (%) p 5 Age group 19–29 years 221 (93.2%) 0.18 172 (72.6%) < 0.001 153 (64.6%) 0.14 112 (47.3%) 0.34 30–44 years 278 (90.3%) 200 (64.9%) 208 (67.5%) 159 (51.6%) 45–59 years 354 (89.2%) 198 (49.9%) 235 (59.2%) 203 (51.1%) 60 + years 255 (87.6%) 126 (43.3%) 185 (63.6%) 132 (45.4%) Sex assigned at birth Female 728 (91.1%) 0.05 432 (54.1%) 0.04 533 (66.7%) < 0.001 423 (52.9%) < 0.001 Male 373 (87.6%) 256 (60.1%) 242 (56.8%) 180 (42.3%) Education Some/all high school 157 (81.3%) < 0.001 118 (61.1%) 0.20 114 (59.1%) 0.02 84 (43.5%) 0.14 Some post-secondary 475 (87.8%) 309 (57.1%) 328 (60.6%) 265 (49.0%) Bachelor's or more 470 (96.1%) 263 (53.8%) 333 (68.1%) 254 (51.9%) Occupation status Currently working 658 (92.0%) 0.006 423 (59.2%) 0.02 469 (65.6%) 0.06 376 (52.6%) 0.008 Not currently working 438 (87.3%) 263 (52.4%) 303 (60.4%) 225 (44.8%) Poverty status 6 Below poverty threshold 309 (83.5%) < 0.001 225 (60.8%) 0.06 225 (60.8%) 0.14 168 (45.4%) 0.06 Above poverty threshold 698 (93.4%) 411 (55.0%) 488 (65.3%) 384 (51.4%) Food security status 7 Food secure 661 (90.8%) 0.24 373 (51.2%) < 0.001 465 (63.9%) 0.69 367 (50.4%) 0.49 Not food secure 407 (88.7%) 295 (64.3%) 288 (62.7%) 222 (48.4%) Overweight/obesity status 8 Overweight/obese 679 (90.8%) 0.53 427 (56.3%) 0.7 477 (62.4%) 0.88 406 (53.6%) < 0.001 Not overweight/obese 278 (99.6%) 176 (57.5%) 191 (62.9%) 107 (35.0%) 1 Includes all tap and bottled plain water, 100% fruit juice, plain milk, black coffee/tea 2 Includes soda/pop, sugar-sweetened juice drinks, sugar-sweetened flavoured water, sports drinks, and energy drinks. Does not include coffee with added sugars, smoothies, sweetened milks, or other beverages prepared at point-of-service 3 Includes sweetened milks, coffee/tea with sugar, sweetened blended coffee drinks, sweetened smoothies 4 Includes all beverages with non-nutritive sweeteners 5 Unadjusted p-value from Pearson’s chi-squared test of group differences 6 Based on self-reported annual income and Statistics Canada 2022 Market Basket Measure thresholds for reference families in Newfoundland and Labrador 7 Calculated using Statistics Canada Household Food Security Survey Module; food insecure includes marginal (9%), moderate (19%), and severe (12%) food insecurity 8 Based on BMI calculated from self-reported height and weight; respondents with BMI ≥ 25 kg/m 2 considered to have overweight or obesity There were differences in the prevalence of consuming taxable SSBs each week by individual age, sex, occupation status, and food security status (Table 3 ). Individuals aged 19–29 years had a higher prevalence of taxable SSB consumption (72.6%) compared to all other age groups (χ 2 ( 3 ) = 61.53, p < 0.001). Males had a higher prevalence of taxable SSB consumption compared to females (60.1% vs. 54.1%, χ 2 ( 1 ) = 4.09, p = 0.04). Individuals currently working had a higher prevalence of taxable SSB consumption versus those not working (59.2% vs. 52.4%, χ 2 ( 1 ) = 5.49, p = 0.02), and those experiencing food security had a lower prevalence of taxable SSB consumption compared to those who were not (51.2% vs. 64.3%, χ 2 ( 1 ) = 19.43, p < 0.001). The prevalence of consuming taxable SSBs was not associated with education, poverty status, or weight status. Females had a higher prevalence of consuming non-taxable SSBs versus males (66.7% vs. 56.8%, χ 2 ( 1 ) = 11.72, p < 0.001), as did those with more, versus fewer years, of education (some/all high school 59.1%, some post-secondary 60.6%, Bachelor’s or more 68.1%, χ 2 ( 2 ) = 8.00, p = 0.02). There were no other associations between sociodemographic characteristics and the prevalence of non-taxable SSB consumption. The prevalence of consuming diet beverages was independently associated with sex, occupation status, and weight status. Females had a higher prevalence of consuming diet beverages versus males (52.9% vs. 42.3%, χ 2 ( 1 ) = 12.69, p < 0.001), and those currently working had a higher prevalence versus those not currently working (52.6% vs. 44.8%, χ 2 ( 1 ) = 7.11, p = 0.008). Finally, individuals with overweight or obesity had a higher prevalence of weekly diet beverage consumption versus those without overweight or obesity (53.6% vs. 35.0%, χ 2 ( 1 ) = 30.18, p < 0.001). There were several differences in the average volume of beverages consumed, among those who reported any consumption (Table 4 ). Notably, there were gradients of beverage intakes associated with education level. Study participants with a Bachelor’s degree or more consumed significantly more unsweetened beverages (mean [SD] = 11,117 [7,914] mL/week) than was consumed by those with some post-secondary education (10,356 [8,175]) and those with some/all high school (8,323 [7,461]) (p < 0.001). Conversely, participants with a Bachelor’s degree or more consumed significantly less taxable SSBs (1,868 [2,550]) than that consumed by those with some post-secondary education (2,947 [3,598]) and those with some or all high school (3,789 [4,373]) (p < 0.001). Individuals living below the poverty threshold consumed a mean (SD) 3,412 (4,422) mL/week of taxable SSBs, compared to 2,312 (2,860) mL/week among those living above the poverty threshold (p = 0.003). Similarly, those who reported having food security had a lesser mean (SD) intake of taxable SSBs (2,261 [2,913]) and lower intake of unsweetened beverages (9924 [8033]), compared to that consumed by those who reported any degree of food insecurity (taxable SSB: 3,159 [4,045], p < 0.001; unsweetened beverages: 10724 [7961], p = 0.03). Table 4 Unadjusted associations between select demographic characteristics and weekly beverage consumption among adults ages 19 years and older who reported any consumption before implementation of a sugar-sweetened beverage tax in Newfoundland and Labrador (n=?) Characteristic Unsweetened beverages (ml/week) 1 N = 1108 SSBs targeted by legislation (ml/week) 2 SSBs not targeted by legislation (ml/week) 3 Diet beverages (ml/week) 4 Mean (SD) p 5 Mean (SD) p 5 Mean (SD) p 5 Mean (SD) p 5 Age group <30 years (19–29 years) 10265 (7957) 0.97 2633 (2922) < 0.001 2398 (1835) < 0.001 3082 (4019) 0.02 30–44 years 10269 (8089) 3202 (4405) 3484 (2741) 3720 (4779) 45–59 years 10652 (8320) 2773 (3438) 4363 (3347) 3162 (3690) 60 + years 10154 (7509) 1673 (1916) 4486 (3324) 2309 (2489) Sex assigned at birth Female 10587 (8024) 0.19 2420 (3076) 0.01 3729 (3005) 0.67 3060 (3939) 0.38 Male 10022 (7986) 3053 (4002) 3902 (3133) 3256 (3769) Education Some/all high school 8323 (7461) < 0.001 3789 (4373) < 0.001 3826 (3504) 0.13 3501 (3834) 0.35 Some post-secondary 10356 (8175) 2947 (3598) 4079 (3218) 3047 (3698) Bachelor's or more 11117 (7914) 1868 (2550) 3493 (2648) 3073 (4095) Occupation status Currently working 10260 (7901) 0.71 2597 (3208) 0.54 3721 (2878) 0.98 3392 (3952) < 0.001 Not currently working 10485 (8126) 2718 (3808) 3856 (3263) 2635 (3752) Poverty status 6 Below poverty threshold 9373 (7782) 0.003 3412 (4422) 0.003 3516 (3051) 0.03 3143 (4145) 0.28 Above poverty threshold 10618 (7821) 2312 (2860) 3890 (2985) 3157 (3781) Food security status 7 Food secure 10724 (7961) 0.03 2261 (2911) < 0.001 3793 (2947) 0.64 2958 (3809) 0.28 Not food secure 9924 (8033) 3159 (4045) 3839 (3243) 3274 (3934) Overweight/obesity status 8 Overweight/obese 10303 (7932) 0.80 2757 (3753) 0.70 3910 (3067) 0.19 3262 (3991) 0.04 Not overweight/obese 10469 (8005) 2534 (2859) 3509 (2746) 2303 (2329) 1 Includes all tap and bottled plain water, 100% fruit juice, plain milk, black coffee/tea 2 Includes soda/pop, sugar-sweetened juice drinks, sugar-sweetened flavoured water, sports drinks, and energy drinks. Does not include coffee with added sugars, smoothies, sweetened milks, or other beverages prepared at point-of-service 3 Includes sweetened milks, coffee/tea with sugar, sweetened blended coffee drinks, sweetened smoothies 4 Includes all beverages with non-nutritive sweeteners 5 Unadjusted p-value from Wilcoxon rank-sum test (for variables with two groups) or Kruskal-Wallis tests (for those with > 2 groups) 6 Based on self-reported annual income and Statistics Canada 2022 Market Basket Measure thresholds for reference families in Newfoundland and Labrador 7 Calculated using Statistics Canada Household Food Security Survey Module; food insecure includes marginal (9%), moderate (19%), and severe (12%) food insecurity 8 Based on BMI calculated from self-reported height and weight; respondents with BMI ≥ 25 kg/m 2 considered to have overweight or obesity Discussion In this cross-sectional analysis, we described beverage consumption patterns among adults living in NL prior to the implementation of Canada’s first SSB tax. More than half of study participants regularly consumed taxable SSBs, with an average weekly intake of more than 2.5 liters. We found a variety of independent, unadjusted associations between sociodemographic characteristics and the prevalence and mean intake of taxable SSBs, non-taxable SSBs, unsweetened beverages, and diet beverages. Individuals with less education, those not working, and those living below the poverty threshold had a higher prevalence of regularly consuming SSB. These characteristics were also associated with decreased prevalence of consuming unsweetened beverages weekly. In general, our findings align with prior national studies of socioeconomic position (SEP) and SSB consumption in Canada, which collectively demonstrate that, on average, those with lower knowledge and material resources consume more SSBs and fewer unsweetened beverages ( 7 , 14 ). Researchers have previously observed this sociodemographic patterning of beverage intake, and more broadly, of overall diet quality, with consistent evidence that individuals and communities with lower SEP may have less healthy dietary intake with subsequent increases in chronic health outcomes ( 15 , 16 ). The mechanisms to explain this social patterning of diet quality include neighbourhood characteristics of the local food environment, like the availability (or lack thereof) of healthy foods and beverages ( 17 ), and the overall cost of healthier versus less healthy diets ( 18 ). High density of corner or convenience stores in NL and low access to full-service grocery stores or supermarkets, particularly in rural areas, may contributes to the increased consumption of SSBs among individuals with lower SEP ( 19 ). There is some evidence to suggest that healthier beverages are more expensive than less healthy beverages in NL ( 20 ), and this may additionally contribute to our observed social patterning of beverage consumption; of particular note, many areas of NL were under a boil water advisory during this baseline study and this may further contribute to a decrease in water consumption among those living in affected areas ( 21 ). At the time of this research, upwards of 130 communities in NL had current boil water advisories, affecting an estimated 83,350 people - approximately 15% of the province’s population. In future research, we intend to assess the contribution of living in these affected areas to the likelihood of consuming SSBs, and how the SSB tax may have differential impacts based on water quality issues. The prevalence of SSB consumption in Canada was estimated to be 56% by a national survey using the same validated beverage frequency questionnaire in 2017, which is consistent with our findings in NL. The total volume of SSBs among Canadian consumers was found to be slightly lower by Vanderlee and coauthors (2280mL) than our study in NL (2663 mL) which likely reflect the higher intakes of SSB in NL compared to Canada ( 7 , 22 ). Vanderlee and coauthors ( 22 ) reported that SSB consumption was significantly more prevalent and greater in Mexico than the other upper middle- and high-income countries, include Canada, the United States, and the United Kingdom. Positive outcomes have been found with SSB taxes in Mexico ( 23 ), UK ( 24 ), and American jurisdictions ( 25 , 26 ), which may suggest the baseline intakes of SSB in NL could be responsive to an SSB tax. We categorized SSBs in this study as either taxable or non-taxable, since the NL policy covers some but not all SSBs. For example, the World Health Organization defines any beverage with free or added sugars as an SSB, including 100% fruit juice and sweetened milks ( 1 ), but the NL policy does not tax these beverages. On average, study participants consumed over three liters per week of non-taxable SSBs including sweetened milks, 100% juice, blended coffee drinks, and blended smoothies, representing a likely high source of free or added sugars in the diet of NL residents ( 20 ). This baseline understanding of non-taxable SSB consumption is an important contribution to the literature as it may inform future changes to the SSB tax legislation that may capture a broader array of less healthy beverages. Globally, most SSB taxes do not apply to these beverages ( 4 ), and this may be for several reasons: first, evidence of the potential negative health impacts of 100% fruit juice consumption is mixed ( 27 – 29 ), though the most recent evidence suggests a moderate association between juice consumption and metabolic disorder, particularly among children ( 29 ); second, consumption of sweetened milks may have a modest association with increased adiposity and weight gain, but may also contribute to consumption of vitamin D and calcium (and other micronutrients depending on fortification policies in different jurisdictions), which are both public health nutrients of concern ( 30 ). SSBs prepared at point-of-purchase (e.g. smoothies, specialty coffees) may vary widely in their added sugar content, representing a potential challenge in applying taxes at points of purchase ( 4 ), and there is some experimental evidence to suggest that consumption of these beverages increase when they are not targeted by taxes ( 31 ). In this study, consumption of specialty coffees and smoothies was relatively low, compared to the SSBs targeted by the tax. Still, it is critical to monitor substitution effects that may occur when consumers shift their purchasing from taxed to non-taxed SSBs ( 32 , 33 ). One emerging area of SSB tax evaluation is the potential impact of consumers substituting taxed SSBs for beverages with non-nutritive sweeteners (“diet” drinks) ( 34 ). The negative health impacts of SSB consumption are in part mediated by increased caloric intake (overconsumption) and therefore this substitution may have short-term benefits for individuals at higher risk for metabolic disorder, including those with overweight and obesity or type 2 diabetes ( 35 ). In one recent randomized controlled trial, adults with overweight or obesity enrolled in a weight-loss program had similar weight loss when substituting SSBs for diet drinks or water ( 36 ), but there is evidence from prospective cohort studies that diet beverage consumption during childhood or adolescence increases risks of overall and central adiposity ( 37 , 38 ). Our study was limited to adults, and those with overweight or obesity had a higher weekly prevalence and consumption of diet beverages compared to those without overweight or obesity. Future research should focus on substitution effects, particularly within children and adolescents. Our findings are the first to describe beverage consumption in NL prior to the implementation of the SSB tax, and provide a necessary baseline understanding for future estimations of how the tax differentially impacts those living in the province. Collecting beverage consumption data prior to the implementation of the tax and examining social patterns of this consumption is a key step to elucidate potential unintended consequences of the policy and examine its potential to impact dietary health inequalities ( 39 ). For example, our findings collectively suggest an inverse relation between socioeconomic position and SSB consumption in NL, which may lead to a greater reduction of SSB consumption among individuals who are already disproportionately impacted by dietary health inequalities. We also measured non-taxable SSBs in the pre-implementation period to allow for an examination of post-tax substitution effects. However, our findings should be interpreted cautiously within the context of several limitations. First, our convenience sampling strategy may introduce self-selection bias: individuals with strong opinions about the forthcoming (at the time of the survey participation) SSB tax in NL or those with a greater interest in diet or health may have been more likely to choose to participate. Further, the online nature of the survey may have reduced participation from certain groups with poor access to the internet or data, or challenges accessing or using electronics. Second, we present unadjusted associations between sociodemographic characteristics and beverage consumption to generate hypotheses, and do not consider our findings confirmatory of any a priori hypothesis. Still, examining these unadjusted associations in the period immediately preceding tax implementation is critical to the design of post-tax evaluations, specifically when considering potential effect measure modifiers of the tax effect. Finally, the data we collected in this study does not assess the level of understanding or adherence of the participants to the Canada Food Guide (CFG-2019) recommendation for water as the drink of choice for Canadians or the Government of NL “Rethink Your Drink” education program. The CFG-2019 does not promote the consumption of any beverage other than water and these recommendations were in existence for 3 years prior to our study. The “Rethink Your Drink” education program was released at the same time the tax was implemented with very little awareness prior to its launch. Therefore, the impact of these positive nutrition education programs on beverage selection is also a contributing factor to individual beverage choice that is not discernible from the impact of the SSB tax as behavior modifying tool. Conclusions The prevalence of sugar-sweetened beverage consumption in NL prior to the implementation of Canada’s first SSB tax was high, with 56.4% of adults reporting weekly consumption of taxable beverages (soda/pop, juice drinks, sweetened waters, sports drinks, energy drinks) and 63.3% reporting weekly consumption of non-taxable (100% juice, flavoured milks, specialty coffee drinks, smoothies) beverages. There were sociodemographic differences in the prevalence and average consumption of these beverages, with a higher consumption of taxable beverages among young adults, males, individuals with high school education or less, and those living below the poverty threshold. Post-tax evaluations of this policy should consider the social patterning of beverage consumption prior to implementation when measuring potential impacts on health inequalities, as well as potential unintended consequences of beverage substitutions towards non-taxed SSBs. Abbreviations SSBs sugar-sweetened beverages NL Newfoundland and Labrador CFG Canada Food Guide WHO World Health Organization SEP socioeconomic position Declarations Ethics approval and consent to participate This study protocol was reviewed and approved by the Interdisciplinary Committee on Ethics in Human Research at Memorial University (ICEHR Number 20222081-SC). Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available due to data privacy concerns. Requests for access to data can be made directly to the corresponding authors and will be evaluated on a case-by-case basis until the final data set is archived in a repository. Competing interests The authors declare that they have no competing interests. Funding This study was funded by the Canadian Cancer Society (#707239) and Canadian Institutes of Health Research – Institute of Cancer Research (#181053) and Memorial University. DAZ is partially funded by the Canadian Institutes of Health Research and Banting and Best Diabetes Centre. Authors contributions Daniel A. Zaltz: Methodology, Formal analysis, Writing – Original draft preparation; Rachel Prowse: Conceptualization, Methodology, Funding acquisition, Supervision, Project administration, Writing – Review & Editing; Yanqing Yi: C onceptualization and Methodology, Writing – Review & Editing; Jessica O’Dea: Data collection, Preliminary analysis, Writing – Review & Editing Methodology ; Scott Harding: Conceptualization, Methodology, Funding acquisition, Supervision, Project administration, Writing – Review & Editing References Guideline. Sugars intake for adults and children. Geneva: World Health Organization; 2015. Liu S, Munasinghe LL, Ohinmaa A, Veugelers PJ. Added, free and total sugar content and consumption of foods and beverages in Canada. Health Rep. 2020;31(10):14–24. 10.25318/82-003-x202001000002-eng . Langlois K, Garriguet D, Gonzalez A, Sinclair S, Colapinto CK. Change in total sugars consumption among Canadian children and adults. Health Rep. 2019;30(1):10–9. PMID: 30649778. 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Government of Newfoundland and Labrador. 2024. https://www.gov.nl.ca/ecc/waterres/drinkingwater/advisories/ . Vanderlee L, White CM, Kirkpatrick SI, Rynard VL, Jáuregui A, Adams J, Sacks G, Hammond D. Nonalcoholic and Alcoholic Beverage Intakes by Adults across 5 Upper-Middle- and High-Income Countries. J Nutr. 2021;151(1):140–51. 10.1093/jn/nxaa324 . Colchero MA, Popkin BM, Rivera JA, Ng SW. Beverage purchases from stores in Mexico under the excise tax on sugar sweetened beverages: observational study. BMJ. 2016;352:h6704. 10.1136/bmj.h6704 . Scarborough P, Adhikari V, Harrington RA, Elhussein A, Briggs A, Rayner M, et al. Impact of the announcement and implementation of the UK Soft Drinks Industry Levy on sugar content, price, product size and number of available soft drinks in the UK, 2015-19: a controlled interrupted time series analysis. PLoS Med. 2020;17(2). doi.org/10.1371/journal.pmed.1003025 . Powell LM, Marinello S, Leider J, Andreyeva T. A Review and Metaanalysis of the Impact of Local U.S. Sugar-sweetened Beverage Taxes on Demand. Research Brief No. 121. Policy, Practice and Prevention Research Center, University of Illinois Chicago. Chicago, IL. August 2021. https://p3rc.uic.edu . Andreyeva T, Marple K, Marinello S, Moore TE, Powell LM. Outcomes Following Taxation of Sugar-Sweetened Beverages: A Systematic Review and Meta-analysis. JAMA Netw Open. 2022;5(6):e2215276. 10.1001/jamanetworkopen.2022.15276 . Auerbach BJ, Wolf FM, Hikida A, Vallila-Buchman P, Littman A, Thompson D, Louden D, Taber DR, Krieger J. Fruit Juice and Change in BMI: A Meta-analysis. Pediatrics. 2017;139(4):e20162454. 10.1542/peds.2016-2454 . D'Elia L, Dinu M, Sofi F, Volpe M, Strazzullo P, SINU Working Group. Endorsed by SIPREC. 100% Fruit juice intake and cardiovascular risk: a systematic review and meta-analysis of prospective and randomised controlled studies. Eur J Nutr. 2021;60(5):2449–67. 10.1007/s00394-020-02426-7 . Nguyen M, Jarvis SE, Chiavaroli L, Mejia SB, Zurbau A, Khan TA, Tobias DK, Willett WC, Hu FB, Hanley AJ, Birken CS, Sievenpiper JL, Malik VS. Consumption of 100% Fruit Juice and Body Weight in Children and Adults: A Systematic Review and Meta-Analysis. JAMA Pediatr. 2024;178(3):237–46. 10.1001/jamapediatrics.2023.6124 . Patel AI, Moghadam SD, Freedman M, Hazari A, Fang ML, Allen IE. The association of flavored milk consumption with milk and energy intake, and obesity: A systematic review. Prev Med. 2018;111:151–62. 10.1016/j.ypmed.2018.02.031 . Waterlander WE, Ni Mhurchu C, Steenhuis IH. Effects of a price increase on purchases of sugar sweetened beverages. Results from a randomized controlled trial. Appetite. 2014;78:32–9. 10.1016/j.appet.2014.03.012 . Andreyeva T, Marple K, Marinello S, Moore TE, Powell LM. Outcomes Following Taxation of Sugar-Sweetened Beverages: A Systematic Review and Meta-analysis. JAMA Netw Open. 2022;5(6):e2215276. 10.1001/jamanetworkopen.2022.15276 . Fletcher J, Frisvold D, Tefft N. Substitution patterns can limit the effects of sugar-sweetened beverage taxes on obesity. Prev Chronic Dis. 2013;10:E18. 10.5888/pcd10.120195 . Popkin BM, Ng SW. Sugar-sweetened beverage taxes: Lessons to date and the future of taxation. PLoS Med. 2021;18(1):e1003412. 10.1371/journal.pmed.1003412 . McGlynn ND, Khan TA, Wang L, Zhang R, Chiavaroli L, Au-Yeung F, Lee JJ, Noronha JC, Comelli EM, Blanco Mejia S, Ahmed A, Malik VS, Hill JO, Leiter LA, Agarwal A, Jeppesen PB, Rahelic D, Kahleová H, Salas-Salvadó J, Kendall CWC, Sievenpiper JL. Association of Low- and No-Calorie Sweetened Beverages as a Replacement for Sugar-Sweetened Beverages With Body Weight and Cardiometabolic Risk: A Systematic Review and Meta-analysis. JAMA Netw Open. 2022;5(3):e222092. 10.1001/jamanetworkopen.2022.2092 . Harrold JA, Hill S, Radu C, Thomas P, Thorp P, Hardman CA, Christiansen P, Halford JCG. Non-nutritive sweetened beverages versus water after a 52-week weight management programme: a randomised controlled trial. Int J Obes (Lond). 2024;48(1):83–93. 10.1038/s41366-023-01393-3 . Zhang J, Li Y, Li F, He M, Li J, Zhang S, Zhao W, Tang Y, Li Y, Xiong J, Yao P. Association between sugar-free beverage intake and childhood obesity among Chinese children and adolescents. Pediatr Obes. 2024;19(3):e13096. 10.1111/ijpo.13096 . Rios-Leyvraz M, Montez. Jason. (‎2022)‎. Health effects of the use of non-sugar sweeteners: a systematic review and meta-analysis. World Health Organization. https://iris.who.int/handle/10665/353064 . Alvarado M, Adams J, Penney T, Murphy MM, Abdool Karim S, Egan N, Rogers NT, Carters-White L, White M. A systematic scoping review evaluating sugar-sweetened beverage taxation from a systems perspective. Nat Food. 2023;4(11):986–95. 10.1038/s43016-023-00856-0 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 31 Mar, 2025 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 20 Jun, 2024 Editor assigned by journal 19 Jun, 2024 Submission checks completed at journal 19 Jun, 2024 First submitted to journal 19 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4606952","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":316752256,"identity":"1660fc24-0379-48cc-af03-0751c46a3435","order_by":0,"name":"Daniel A. Zaltz","email":"","orcid":"","institution":"University of Toronto","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"A.","lastName":"Zaltz","suffix":""},{"id":316752257,"identity":"ab6697ad-24d1-4408-9d1a-24ad4c88c5fb","order_by":1,"name":"Rachel Prowse","email":"","orcid":"","institution":"Memorial University of Newfoundland","correspondingAuthor":false,"prefix":"","firstName":"Rachel","middleName":"","lastName":"Prowse","suffix":""},{"id":316752258,"identity":"c3d74906-58d1-4536-b1cc-27ee170c3a3d","order_by":2,"name":"Yanqing Yi","email":"","orcid":"","institution":"Memorial University of Newfoundland","correspondingAuthor":false,"prefix":"","firstName":"Yanqing","middleName":"","lastName":"Yi","suffix":""},{"id":316752259,"identity":"3954a691-43a6-4622-bc3e-c22fd46e645c","order_by":3,"name":"Jessica O’Dea","email":"","orcid":"","institution":"Memorial University of Newfoundland","correspondingAuthor":false,"prefix":"","firstName":"Jessica","middleName":"","lastName":"O’Dea","suffix":""},{"id":316752260,"identity":"49b40dda-3461-460c-96a4-f2e1e236f6eb","order_by":4,"name":"Scott V. Harding","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtUlEQVRIiWNgGAWjYDACCSDmMWBg4Cddi2QDaVqA2OAAsTrkZzc/+/Cm4I7d5mtnzB4w1NgR1mJw55jxzDkGz5K33c4xN2A4lkyEFokEY2Yeg8PJZrdzzCQYG5iJcNiM9M9gLcazwVrqCWthuJEDtsXOQBqs5TARDruRU8w4x+BwgsTttDKJhGPHiXLYZoY3fw7b889O3ibxoaaaCIdBQWIDiEwgXgMDgz0pikfBKBgFo2CEAQB0ZzWI1L2vUgAAAABJRU5ErkJggg==","orcid":"","institution":"Memorial University of Newfoundland","correspondingAuthor":true,"prefix":"","firstName":"Scott","middleName":"V.","lastName":"Harding","suffix":""}],"badges":[],"createdAt":"2024-06-19 15:37:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4606952/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4606952/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-025-22432-w","type":"published","date":"2025-03-31T15:57:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80082017,"identity":"7f4ecf09-464b-4cf5-bd0e-00440500fbc9","added_by":"auto","created_at":"2025-04-07 16:05:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2115677,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4606952/v1/ae962f09-5fc6-46cb-b92e-989cb154a182.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Beverage consumption among adults in Newfoundland and Labrador, Canada prior to the implementation of a sugar-sweetened beverage tax","fulltext":[{"header":"Background","content":"\u003cp\u003eOverconsumption of free or added sugars, defined as those added to any foods or beverages and those present in honey, syrup, and fruit juice, is associated with long term chronic health risks (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Less than half of all Canadians meet the World Health Organization recommendation to consume fewer than 10% of total daily calories from free or added sugars, and only 5.4% meet the conditional recommendation for optimal nutrition to consume fewer than 5% of total daily calories from these sugars (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Sugar-sweetened beverages (SSB) are the leading source of free or added sugars in the Canadian diet (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) and are thus a target for public health intervention.\u003c/p\u003e \u003cp\u003eHealth taxes are a leading method to reduce SSB consumption and improve diet quality (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). These taxes exist in more than 100 countries and are associated with decreases in purchasing and consumption, which, along with other policies focused on packaging, marketing, and availability, comprise a critical suite of public health interventions designed to reduce diet-related chronic diseases (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). There is no current national SSB tax in Canada, but in 2022, Newfoundland and Labrador (NL) became the first province to introduce its own excise-type SSB tax. While the taxation policy was introduced through the provincial government\u0026rsquo;s Department of Finance, the policy is promoted as an initiative to support health as the NL population has high incidences of both overweight and obesity (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), a large chronic disease burden (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), and highest per capita health care costs of all ten provinces in Canada. The NL SSB tax was introduced along with a public health messaging campaign titled \u0026ldquo;Rethink Your Drink\u0026rdquo; which aimed to promote water and other non-sugar-sweetened beverage options as the drink of choice (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The NL policy is an excise tax of \u003cspan\u003e$\u003c/span\u003e0.20/litre imposed on SSB wholesalers based on their sales volume to retailers in the province; this tax is intended to be passed on fully from wholesalers to retailers, who receive no remittance with the expectation of passing the tax on to the consumer (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The policy applies to all ready\u0026mdash;to-drink sugar-sweetened soft drinks (i.e. soda/pop), bottled/canned or dispensed; and sugar-sweetened concentrated drink products (i.e. frozen concentrated fruit drinks, powders, and flavoured syrups). Beverages prepared at point-of-service with added sugar (e.g., blended coffee drinks) are not considered taxable; chocolate milk and 100% fruit juice are excluded from the policy (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe NL SSB tax is the first of its kind in Canada and data collection to assess its impact is ongoing. Still, baseline research on the target population, including their pre-tax beverage consumption patterns, is needed. In a recent review on SSB reduction policies, Krieger and colleagues (2021) specifically highlight the need for an initial understanding of the target population and the characteristics associated with beverage consumption as a way to guide subsequent implementation and evaluation research (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, there is no data on SSB consumption in NL since the most recent Canadian Community Health Survey in 2015, and therefore no understanding of beverage consumption in the immediate period leading up to the new tax (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Therefore, the purpose of this study was to measure beverage consumption among adults in NL, and to explore associations between social and demographic characteristics and beverage consumption patterns, prior to SSB tax implementation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eOverview\u003c/h2\u003e \u003cp\u003e This is a cross-sectional analysis of beverage consumption patterns and sociodemographic characteristics among adults ages 19 years and older residing in NL in August 2022, prior to the implementation of a SSB tax on September 1, 2022. Two recruitment approaches were used to recruit study participants and collect survey data. The research team recruited a convenience sample (e.g. social media advertising, direct email) and administered the survey from Memorial University using an online survey and data collection software (QualtricsXM, Seattle, WA, USA). The research team also used a commercial research company (MQO Research, St. John\u0026rsquo;s, Canada) to administer the same survey to an established consumer research panel on their survey software platform. All study participants provided informed consent prior to completing the online survey and upon completing the survey, each participant was offered either a \u003cspan\u003e$\u003c/span\u003e10 e-gift card or a similar honorarium from the commercial consumer research company. This study protocol was reviewed and approved by the Interdisciplinary Committee on Ethics in Human Research at Memorial University (ICEHR Number 20222081-SC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDemographic Questionnaire\u003c/h2\u003e \u003cp\u003eThe demographic questionnaire captured information about participants\u0026rsquo; age (years), sex at birth (male/female), gender (male, female, non-binary, prefer not to say), education (some/all high school, some post-secondary, Bachelor\u0026rsquo;s or more), occupation status (currently vs. not currently working), annual household income, children in home (children under 18 years in home, children 18 years and older in home, no children in home), race and ethnicity (White, Black, East/Southeast Asian, South Asian, Latino/a, Middle Eastern, Indigenous Canadian, other), food security status (secure, marginal, moderate, severe) using the 18-item Household Food Security Survey Module (HFSSM) in the Canadian Income Survey (CIS) and the Canadian Community Health Survey (CCHS) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), height, and weight.\u003c/p\u003e \u003cp\u003eWe report sex assigned at birth because fewer than 1% of respondents indicated a gender identity different than their sex. We categorized age in four categories (\u0026lt;\u0026thinsp;30, 30\u0026ndash;44, 45\u0026ndash;59, 60\u0026thinsp;+\u0026thinsp;years) and dichotomized race and ethnicity as White and non-White given extremely low (1\u0026ndash;3%) proportions of responses for all non-White options. We categorized respondents\u0026rsquo; poverty status as either above or below \u003cspan\u003e$\u003c/span\u003e50,000/year, which is the midpoint of the Statistics Canada 2022 Market Basket Measure thresholds for reference families in NL (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). We combined marginal, moderate, and sever food security statuses to represent food insecure. Finally, we used self-reported height and weight to calculate individual body mass index (BMI, kg/m\u003csup\u003e2\u003c/sup\u003e) and categorized individuals as overweight or obese (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25kg/m\u003csup\u003e2\u003c/sup\u003e) versus not overweight or obese (BMI\u0026thinsp;\u0026lt;\u0026thinsp;25kg/m\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBeverage Consumption\u003c/h3\u003e\n\u003cp\u003eStudy participants reported their beverage intake during the past seven days using a validated, semi-quantitative beverage frequency questionnaire (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The beverage frequency questionnaire has been used extensively in survey-based research to evaluate food policies around the world through the International Food Policy Study (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Participants reported how many times in the past week they consumed each of the following beverages, respectively: regular soda/pop, diet soda/pop, 100% fruit juice, sweetened fruit drinks, low/no-calorie fruit drinks, tap water, plain bottled water, flavoured/sweetened water, low/no-calorie flavoured water, regular sports drinks, low/no-calorie sports drinks, regular energy drinks, diet energy drinks, unflavoured milk or milk alternatives, flavoured/sweetened milk or milk alternatives, coffee, tea, specialty coffee drinks, sweetened smoothies/shakes, and unsweetened smoothies/shakes. Then, for each beverage respectively, participants selected the size of the cup, mug, can, bottle, or carton that corresponded to their usual intake amount, prompted by photographs of beverage containers and sizes in milliliters (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). We calculated beverage consumption, in milliliters, during the past seven days, multiplying the frequency and volume reported for each beverage (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). When participants reported less than the smallest size provided (i.e. less than 250 mL), we used a value of 50% of the volumes of the lowest serving size option presented to the participants (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Similarly, when participants reported consuming more than the greatest size, we used a value of 125% of the volume of the largest serving size option presented to the participants (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). For interpretability, we created four beverage categories and summed total intakes within these categories:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUnsweetened beverages (no added sugar or non-nutritive sweeteners): plain water, plain unflavoured milk, 100% fruit juice, coffee/tea black\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTaxable SSBs (subject to the NL SSB tax): regular soda/pop, juice drinks, regular sports drinks, regular energy drinks, flavoured/sweetened water\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNon-taxable (SSBs not subject to the NL SSB tax):coffee/tea with sugar, specialty coffee drinks, flavoured/sweetened milk, sweetened smoothies/shakes\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDiet beverages (sweetened with non-nutritive sweetener): diet soda/pop, diet flavoured water, diet juice drinks, diet sports drinks, diet energy drinks\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData Cleaning\u003c/p\u003e \u003cp\u003eA trained research assistant reviewed all new survey entries daily to identify and remove duplicitous attempts using strategies identified as the most effective by Storozuk et al. (2020) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Once the research team data and commercial research panel data were combined, we completed quality checks and reviewed the dataset for beverage intakes that would be considered improbable (e.g. excess of normal fluid intakes). We recoded all beverage frequency variables as missing when the frequency of beverage consumption per week equivalent to 0, greater than 100, or a non-number. Also, when the total beverage volume consumed per week exceeded 49 litres, and/or when the total volume of water exceeded 36 litres, all derived beverage frequency variables were recoded as missing (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe summarized central tendencies, frequencies, and proportions of all demographic and beverage intake data. Then, we calculated the frequency and proportion of the study population who reported any consumption within each beverage category, and the weekly mean and standard deviation of consumption within each beverage category among those who reported any consumption. Finally, we explore bivariate associations between sociodemographic characteristics and beverage consumption in two parts: first, within each sociodemographic variable, we analyzed associations in the prevalence of weekly consumption (any versus none) for each beverage category using Pearson χ\u003csup\u003e2\u003c/sup\u003e tests; second, we analyzed differences in the average weekly consumption, in mililiters, of each beverage category, among those who reported any consumption, using Wilcoxon rank-sum tests for sociodemographic variables with two groups and Kruskal-Wallis tests for those with more than two groups. For all tests, we set an \u003cem\u003ea priori\u003c/em\u003e α\u0026thinsp;=\u0026thinsp;0.05 threshold for statistical significance. The results from these tests are unadjusted and should be interpreted cautiously and used for generating, rather than confirming, relevant hypotheses. We conducted all analyses using R statistical software 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSample characteristics\u003c/h2\u003e \u003cp\u003eThe study sample (n\u0026thinsp;=\u0026thinsp;1233) was 65.2% female, over half (57.2%) were between 30\u0026ndash;59 years old, and nearly all (93.8%) were white (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Most (84.2%) had some post-secondary or more education, and 58.7% were currently working. Two-thirds of the sample had annual household income above the poverty threshold, 61.3% were food secure, and most (71.7%) lived without children in the home. The majority (71.1%) of the study population were classified as overweight or obesity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of study sample before implementation of a sugar-sweetened beverage tax in Newfoundland and Labrador (n\u0026thinsp;=\u0026thinsp;1233)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-missing sample size, n (%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u0026ndash;29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1233 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237 (19.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e308 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;59 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e397 (32.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e291 (23.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex assigned at birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1225 (99.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e799 (65.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e426 (34.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome/all high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1223 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e193 (15.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome post-secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e541 (44.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e489 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1217 (99.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e715 (58.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot currently working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e502 (41.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoverty status\u003c/b\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow poverty threshold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1117 (91.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e370 (33.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove poverty threshold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e747 (66.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFood security status\u003c/b\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1187 (96.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e728 (61.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot food secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e459 (38.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildren in home\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildren\u0026thinsp;\u0026lt;\u0026thinsp;18y in home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1206 (98.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e341 (28.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo children in home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e865 (71.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace/Ethnicity\u003c/b\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1215 (99.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1140 (93.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-white\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverweight/obesity status\u003c/b\u003e\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight/obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1064 (87.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e757 (71.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot overweight/obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e307 (28.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eTotal sample size within the specific measured characteristic without missing data; proportion of total study sample n\u0026thinsp;=\u0026thinsp;1233\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eBased on self-reported annual income and Statistics Canada 2022 Market Basket Measure thresholds for reference families in Newfoundland and Labrador\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003eCalculated using Statistics Canada Household Food Security Survey Module; food insecure includes marginal (9%), moderate (19%), and severe (12%) food insecurity\u003c/p\u003e \u003cp\u003e\u003csup\u003e4\u003c/sup\u003eAll self-reported non-white categories collapsed due to very small cell sizes; include 2.3% Indigenous, 1.5% East/Southeast Asian, 1% Black, and \u0026lt;\u0026thinsp;1% each South Asian, Latino/a, Middle Eastern, or those who reported \u0026ldquo;other\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u003csup\u003e5\u003c/sup\u003eBased on BMI calculated from self-reported height and weight; respondents with BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e considered to have overweight or obesity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBeverage consumption, overall\u003c/h2\u003e \u003cp\u003eStudy participants had the highest prevalence of weekly consumption of unsweetened beverages (89.9%), and the lowest prevalence of diet beverage consumption (49.1%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). More than half (56.4%) consumed taxable SSBs weekly, and nearly two-thirds (63.3%) consumed non-taxable SSBs weekly. Participants consumed approximately 10,000 mL of unsweetened beverages per week, the majority of which came from plain water and black coffee or tea. The most-consumed taxable SSB was regular pop, at a mean (SD) 2092 (3120) mL/week; diet pop was the most-consumed diet beverage at a mean (SD) 2527 (3519) mL/week). The most-consumed non-taxable SSB was coffee with added milk or sugar at a mean (SD) 3859 (2895) mL/week.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWeekly beverage consumption among adults ages 19 years and older before implementation of a sugar-sweetened beverage tax in Newfoundland and Labrador\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeverage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion of study sample who reported any weekly consumption, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeekly consumption, mL, among those who reported any consumption, mean (SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnsweetened beverages\u003c/b\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1108 (89.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e10364 (8000)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlain water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1028 (83.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8742 (7297)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlain, unflavoured milk (all fat types)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e424 (34.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1501 (1700)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100% Fruit Juice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e473 (38.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e937 (1183)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee or tea, black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e294 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4494 (3395)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSugar-sweetened beverages subject to tax\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e696 (56.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2663 (3454)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular soda/pop\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e547 (44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2092 (3120)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSugar-sweetened juice drinks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226 (18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996 (1262)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSugar-sweetened sports drink\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1417 (1382)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSugar-sweetened flavoured water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1839 (2458)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSugar-sweetened energy drinks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1500 (1986)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSugar-sweetened beverages not subject to tax\u003c/b\u003e\u003csup\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e781 (63.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3773 (3039)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee or tea, with milk or sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661 (53.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3859 (2895)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlended, sugar-sweetened coffee drink\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (12.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1037 (948)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSugar-sweetened, flavoured milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1401 (2577)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSugar-sweetened smoothies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1025 (1326)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiet beverages\u003c/b\u003e\u003csup\u003e\u003cb\u003e4\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e606 (49.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3108 (3880)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiet soda/pop\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e471 (38.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2527 (3519)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiet, flavoured water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2576 (3202)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiet juice drinks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1059 (1131)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiet sports drink\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1814 (1915)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiet energy drinks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1552 (1503)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eIncludes all beverages with no added sugars or sweeteners and 100% fruit juice which contains free but not added sugars\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eIncludes ready-to-drink beverages and prepared dispensed beverages that contain added sugars (e.g. sugar, fructose, glucose, glucose-fructose, sucrose, honey, molasses, syrups etc.), including sugar-sweetened soda/pop, fountain drinks, juice drinks, sweetened waters, sports drinks, energy drinks, iced teas, and lemonades. Does not include beverages made at point-of-service.\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003eIncludes sweetened milks, coffee or tea with sugar added by consumer, and point-of-service smoothies and blended coffee drinks made on site.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBeverage consumption and demographic characteristics\u003c/h3\u003e\n\u003cp\u003eThe weekly prevalence of consuming unsweetened beverages was independently associated with education, occupation status, and income (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Nearly all (96.1%) individuals with a Bachelor\u0026rsquo;s degree or more consumed unsweetened beverages each week, compared to 87.8% among those with some post-secondary education and 81.3% among those with some or all high school (χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;39.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Individuals currently working had a higher prevalence of consuming unsweetened beverages compared to those not working (92.0% vs. 87.3%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;7.51, p\u0026thinsp;=\u0026thinsp;0.006), as did those living above, versus below, the poverty threshold (93.4% vs. 83.5%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;27.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There were no associations between age, sex, food security, or weight status and the prevalence of consuming unsweetened beverages.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnadjusted associations between select demographic characteristics and prevalence weekly beverage consumption among adults ages 19 years and older before implementation of a sugar-sweetened beverage tax in Newfoundland and Labrador (n\u0026thinsp;=\u0026thinsp;1233)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnsweetened beverages,\u003c/p\u003e \u003cp\u003en (%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSSBs targeted by legislation,\u003c/p\u003e \u003cp\u003en (%)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eSSBs not targeted by legislation, n (%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eDiet beverages, n (%)\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u0026ndash;29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e221 (93.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e172 (72.6%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e153 (64.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e112 (47.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278 (90.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e200 (64.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e208 (67.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e159 (51.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;59 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e354 (89.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e198 (49.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e235 (59.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e203 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e255 (87.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e126 (43.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e185 (63.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e132 (45.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex assigned at birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e728 (91.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e432 (54.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e533 (66.7%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e423 (52.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e373 (87.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e256 (60.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e242 (56.8%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e180 (42.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome/all high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e157 (81.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e118 (61.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e114 (59.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e84 (43.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome post-secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e475 (87.8%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309 (57.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e328 (60.6%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e265 (49.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e470 (96.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e263 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e333 (68.1%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e254 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e658 (92.0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e423 (59.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e469 (65.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e376 (52.6%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot currently working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e438 (87.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e263 (52.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e303 (60.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e225 (44.8%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoverty status\u003c/b\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow poverty threshold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e309 (83.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e225 (60.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e225 (60.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e168 (45.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove poverty threshold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e698 (93.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e411 (55.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e488 (65.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e384 (51.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFood security status\u003c/b\u003e\u003csup\u003e\u003cb\u003e7\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661 (90.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e373 (51.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e465 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e367 (50.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot food secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e407 (88.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e295 (64.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e288 (62.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e222 (48.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverweight/obesity status\u003c/b\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight/obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e679 (90.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e427 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e477 (62.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e406 (53.6%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot overweight/obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278 (99.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176 (57.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e191 (62.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e107 (35.0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eIncludes all tap and bottled plain water, 100% fruit juice, plain milk, black coffee/tea\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eIncludes soda/pop, sugar-sweetened juice drinks, sugar-sweetened flavoured water, sports drinks, and energy drinks. Does not include coffee with added sugars, smoothies, sweetened milks, or other beverages prepared at point-of-service\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003eIncludes sweetened milks, coffee/tea with sugar, sweetened blended coffee drinks, sweetened smoothies\u003c/p\u003e \u003cp\u003e\u003csup\u003e4\u003c/sup\u003eIncludes all beverages with non-nutritive sweeteners\u003c/p\u003e \u003cp\u003e\u003csup\u003e5\u003c/sup\u003eUnadjusted p-value from Pearson\u0026rsquo;s chi-squared test of group differences\u003c/p\u003e \u003cp\u003e\u003csup\u003e6\u003c/sup\u003eBased on self-reported annual income and Statistics Canada 2022 Market Basket Measure thresholds for reference families in Newfoundland and Labrador\u003c/p\u003e \u003cp\u003e\u003csup\u003e7\u003c/sup\u003eCalculated using Statistics Canada Household Food Security Survey Module; food insecure includes marginal (9%), moderate (19%), and severe (12%) food insecurity\u003c/p\u003e \u003cp\u003e\u003csup\u003e8\u003c/sup\u003eBased on BMI calculated from self-reported height and weight; respondents with BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e considered to have overweight or obesity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere were differences in the prevalence of consuming taxable SSBs each week by individual age, sex, occupation status, and food security status (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Individuals aged 19\u0026ndash;29 years had a higher prevalence of taxable SSB consumption (72.6%) compared to all other age groups (χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;61.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Males had a higher prevalence of taxable SSB consumption compared to females (60.1% vs. 54.1%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;4.09, p\u0026thinsp;=\u0026thinsp;0.04). Individuals currently working had a higher prevalence of taxable SSB consumption versus those not working (59.2% vs. 52.4%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;5.49, p\u0026thinsp;=\u0026thinsp;0.02), and those experiencing food security had a lower prevalence of taxable SSB consumption compared to those who were not (51.2% vs. 64.3%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;19.43, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The prevalence of consuming taxable SSBs was not associated with education, poverty status, or weight status.\u003c/p\u003e \u003cp\u003eFemales had a higher prevalence of consuming non-taxable SSBs versus males (66.7% vs. 56.8%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;11.72, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as did those with more, versus fewer years, of education (some/all high school 59.1%, some post-secondary 60.6%, Bachelor\u0026rsquo;s or more 68.1%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;8.00, p\u0026thinsp;=\u0026thinsp;0.02). There were no other associations between sociodemographic characteristics and the prevalence of non-taxable SSB consumption.\u003c/p\u003e \u003cp\u003eThe prevalence of consuming diet beverages was independently associated with sex, occupation status, and weight status. Females had a higher prevalence of consuming diet beverages versus males (52.9% vs. 42.3%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;12.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and those currently working had a higher prevalence versus those not currently working (52.6% vs. 44.8%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;7.11, p\u0026thinsp;=\u0026thinsp;0.008). Finally, individuals with overweight or obesity had a higher prevalence of weekly diet beverage consumption versus those without overweight or obesity (53.6% vs. 35.0%, χ\u003csup\u003e2\u003c/sup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;30.18, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eThere were several differences in the average volume of beverages consumed, among those who reported any consumption (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Notably, there were gradients of beverage intakes associated with education level. Study participants with a Bachelor\u0026rsquo;s degree or more consumed significantly more unsweetened beverages (mean [SD]\u0026thinsp;=\u0026thinsp;11,117 [7,914] mL/week) than was consumed by those with some post-secondary education (10,356 [8,175]) and those with some/all high school (8,323 [7,461]) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, participants with a Bachelor\u0026rsquo;s degree or more consumed significantly less taxable SSBs (1,868 [2,550]) than that consumed by those with some post-secondary education (2,947 [3,598]) and those with some or all high school (3,789 [4,373]) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Individuals living below the poverty threshold consumed a mean (SD) 3,412 (4,422) mL/week of taxable SSBs, compared to 2,312 (2,860) mL/week among those living above the poverty threshold (p\u0026thinsp;=\u0026thinsp;0.003). Similarly, those who reported having food security had a lesser mean (SD) intake of taxable SSBs (2,261 [2,913]) and lower intake of unsweetened beverages (9924 [8033]), compared to that consumed by those who reported any degree of food insecurity (taxable SSB: 3,159 [4,045], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; unsweetened beverages: 10724 [7961], p\u0026thinsp;=\u0026thinsp;0.03).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnadjusted associations between select demographic characteristics and weekly beverage consumption among adults ages 19 years and older who reported any consumption before implementation of a sugar-sweetened beverage tax in Newfoundland and Labrador (n=?)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnsweetened beverages (ml/week)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1108\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSSBs targeted by legislation (ml/week)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eSSBs not targeted by legislation (ml/week)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eDiet beverages (ml/week)\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;30 years (19\u0026ndash;29 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10265 (7957)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2633 (2922)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2398 (1835)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3082 (4019)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10269 (8089)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3202 (4405)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3484 (2741)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3720 (4779)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;59 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10652 (8320)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2773 (3438)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4363 (3347)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3162 (3690)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10154 (7509)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1673 (1916)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4486 (3324)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2309 (2489)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex assigned at birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10587 (8024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2420 (3076)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3729 (3005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3060 (3939)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10022 (7986)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3053 (4002)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3902 (3133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3256 (3769)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome/all high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8323 (7461)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3789 (4373)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3826 (3504)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3501 (3834)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome post-secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10356 (8175)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2947 (3598)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4079 (3218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3047 (3698)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11117 (7914)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1868 (2550)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3493 (2648)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3073 (4095)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10260 (7901)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2597 (3208)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3721 (2878)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3392 (3952)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot currently working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10485 (8126)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2718 (3808)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3856 (3263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2635 (3752)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoverty status\u003c/b\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow poverty threshold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9373 (7782)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3412 (4422)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3516 (3051)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3143 (4145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove poverty threshold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10618 (7821)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2312 (2860)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3890 (2985)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3157 (3781)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFood security status\u003c/b\u003e\u003csup\u003e\u003cb\u003e7\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10724 (7961)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2261 (2911)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3793 (2947)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2958 (3809)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot food secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9924 (8033)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3159 (4045)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3839 (3243)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3274 (3934)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverweight/obesity status\u003c/b\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight/obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10303 (7932)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2757 (3753)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3910 (3067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3262 (3991)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot overweight/obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10469 (8005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2534 (2859)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3509 (2746)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2303 (2329)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eIncludes all tap and bottled plain water, 100% fruit juice, plain milk, black coffee/tea\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eIncludes soda/pop, sugar-sweetened juice drinks, sugar-sweetened flavoured water, sports drinks, and energy drinks. Does not include coffee with added sugars, smoothies, sweetened milks, or other beverages prepared at point-of-service\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003eIncludes sweetened milks, coffee/tea with sugar, sweetened blended coffee drinks, sweetened smoothies\u003c/p\u003e \u003cp\u003e\u003csup\u003e4\u003c/sup\u003eIncludes all beverages with non-nutritive sweeteners\u003c/p\u003e \u003cp\u003e\u003csup\u003e5\u003c/sup\u003eUnadjusted p-value from Wilcoxon rank-sum test (for variables with two groups) or Kruskal-Wallis tests (for those with \u0026gt;\u0026thinsp;2 groups)\u003c/p\u003e \u003cp\u003e\u003csup\u003e6\u003c/sup\u003eBased on self-reported annual income and Statistics Canada 2022 Market Basket Measure thresholds for reference families in Newfoundland and Labrador\u003c/p\u003e \u003cp\u003e\u003csup\u003e7\u003c/sup\u003eCalculated using Statistics Canada Household Food Security Survey Module; food insecure includes marginal (9%), moderate (19%), and severe (12%) food insecurity\u003c/p\u003e \u003cp\u003e\u003csup\u003e8\u003c/sup\u003eBased on BMI calculated from self-reported height and weight; respondents with BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e considered to have overweight or obesity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this cross-sectional analysis, we described beverage consumption patterns among adults living in NL prior to the implementation of Canada\u0026rsquo;s first SSB tax. More than half of study participants regularly consumed taxable SSBs, with an average weekly intake of more than 2.5 liters. We found a variety of independent, unadjusted associations between sociodemographic characteristics and the prevalence and mean intake of taxable SSBs, non-taxable SSBs, unsweetened beverages, and diet beverages.\u003c/p\u003e \u003cp\u003eIndividuals with less education, those not working, and those living below the poverty threshold had a higher prevalence of regularly consuming SSB. These characteristics were also associated with decreased prevalence of consuming unsweetened beverages weekly. In general, our findings align with prior national studies of socioeconomic position (SEP) and SSB consumption in Canada, which collectively demonstrate that, on average, those with lower knowledge and material resources consume more SSBs and fewer unsweetened beverages (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Researchers have previously observed this sociodemographic patterning of beverage intake, and more broadly, of overall diet quality, with consistent evidence that individuals and communities with lower SEP may have less healthy dietary intake with subsequent increases in chronic health outcomes (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The mechanisms to explain this social patterning of diet quality include neighbourhood characteristics of the local food environment, like the availability (or lack thereof) of healthy foods and beverages (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), and the overall cost of healthier versus less healthy diets (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). High density of corner or convenience stores in NL and low access to full-service grocery stores or supermarkets, particularly in rural areas, may contributes to the increased consumption of SSBs among individuals with lower SEP (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). There is some evidence to suggest that healthier beverages are more expensive than less healthy beverages in NL (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), and this may additionally contribute to our observed social patterning of beverage consumption; of particular note, many areas of NL were under a boil water advisory during this baseline study and this may further contribute to a decrease in water consumption among those living in affected areas (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). At the time of this research, upwards of 130 communities in NL had current boil water advisories, affecting an estimated 83,350 people - approximately 15% of the province\u0026rsquo;s population. In future research, we intend to assess the contribution of living in these affected areas to the likelihood of consuming SSBs, and how the SSB tax may have differential impacts based on water quality issues.\u003c/p\u003e \u003cp\u003eThe prevalence of SSB consumption in Canada was estimated to be 56% by a national survey using the same validated beverage frequency questionnaire in 2017, which is consistent with our findings in NL. The total volume of SSBs among Canadian consumers was found to be slightly lower by Vanderlee and coauthors (2280mL) than our study in NL (2663 mL) which likely reflect the higher intakes of SSB in NL compared to Canada (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Vanderlee and coauthors (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) reported that SSB consumption was significantly more prevalent and greater in Mexico than the other upper middle- and high-income countries, include Canada, the United States, and the United Kingdom. Positive outcomes have been found with SSB taxes in Mexico (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), UK (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), and American jurisdictions (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), which may suggest the baseline intakes of SSB in NL could be responsive to an SSB tax.\u003c/p\u003e \u003cp\u003eWe categorized SSBs in this study as either taxable or non-taxable, since the NL policy covers some but not all SSBs. For example, the World Health Organization defines any beverage with free or added sugars as an SSB, including 100% fruit juice and sweetened milks (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), but the NL policy does not tax these beverages. On average, study participants consumed over three liters per week of non-taxable SSBs including sweetened milks, 100% juice, blended coffee drinks, and blended smoothies, representing a likely high source of free or added sugars in the diet of NL residents (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). This baseline understanding of non-taxable SSB consumption is an important contribution to the literature as it may inform future changes to the SSB tax legislation that may capture a broader array of less healthy beverages. Globally, most SSB taxes do not apply to these beverages (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and this may be for several reasons: first, evidence of the potential negative health impacts of 100% fruit juice consumption is mixed (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), though the most recent evidence suggests a moderate association between juice consumption and metabolic disorder, particularly among children (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e); second, consumption of sweetened milks may have a modest association with increased adiposity and weight gain, but may also contribute to consumption of vitamin D and calcium (and other micronutrients depending on fortification policies in different jurisdictions), which are both public health nutrients of concern (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). SSBs prepared at point-of-purchase (e.g. smoothies, specialty coffees) may vary widely in their added sugar content, representing a potential challenge in applying taxes at points of purchase (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and there is some experimental evidence to suggest that consumption of these beverages increase when they are not targeted by taxes (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In this study, consumption of specialty coffees and smoothies was relatively low, compared to the SSBs targeted by the tax. Still, it is critical to monitor substitution effects that may occur when consumers shift their purchasing from taxed to non-taxed SSBs (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne emerging area of SSB tax evaluation is the potential impact of consumers substituting taxed SSBs for beverages with non-nutritive sweeteners (\u0026ldquo;diet\u0026rdquo; drinks) (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). The negative health impacts of SSB consumption are in part mediated by increased caloric intake (overconsumption) and therefore this substitution may have short-term benefits for individuals at higher risk for metabolic disorder, including those with overweight and obesity or type 2 diabetes (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). In one recent randomized controlled trial, adults with overweight or obesity enrolled in a weight-loss program had similar weight loss when substituting SSBs for diet drinks or water (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), but there is evidence from prospective cohort studies that diet beverage consumption during childhood or adolescence increases risks of overall and central adiposity (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Our study was limited to adults, and those with overweight or obesity had a higher weekly prevalence and consumption of diet beverages compared to those without overweight or obesity. Future research should focus on substitution effects, particularly within children and adolescents.\u003c/p\u003e \u003cp\u003eOur findings are the first to describe beverage consumption in NL prior to the implementation of the SSB tax, and provide a necessary baseline understanding for future estimations of how the tax differentially impacts those living in the province. Collecting beverage consumption data prior to the implementation of the tax and examining social patterns of this consumption is a key step to elucidate potential unintended consequences of the policy and examine its potential to impact dietary health inequalities (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). For example, our findings collectively suggest an inverse relation between socioeconomic position and SSB consumption in NL, which may lead to a greater reduction of SSB consumption among individuals who are already disproportionately impacted by dietary health inequalities. We also measured non-taxable SSBs in the pre-implementation period to allow for an examination of post-tax substitution effects. However, our findings should be interpreted cautiously within the context of several limitations. First, our convenience sampling strategy may introduce self-selection bias: individuals with strong opinions about the forthcoming (at the time of the survey participation) SSB tax in NL or those with a greater interest in diet or health may have been more likely to choose to participate. Further, the online nature of the survey may have reduced participation from certain groups with poor access to the internet or data, or challenges accessing or using electronics. Second, we present unadjusted associations between sociodemographic characteristics and beverage consumption to generate hypotheses, and do not consider our findings confirmatory of any \u003cem\u003ea priori\u003c/em\u003e hypothesis. Still, examining these unadjusted associations in the period immediately preceding tax implementation is critical to the design of post-tax evaluations, specifically when considering potential effect measure modifiers of the tax effect. Finally, the data we collected in this study does not assess the level of understanding or adherence of the participants to the Canada Food Guide (CFG-2019) recommendation for water as the drink of choice for Canadians or the Government of NL \u0026ldquo;Rethink Your Drink\u0026rdquo; education program. The CFG-2019 does not promote the consumption of any beverage other than water and these recommendations were in existence for 3 years prior to our study. The \u0026ldquo;Rethink Your Drink\u0026rdquo; education program was released at the same time the tax was implemented with very little awareness prior to its launch. Therefore, the impact of these positive nutrition education programs on beverage selection is also a contributing factor to individual beverage choice that is not discernible from the impact of the SSB tax as behavior modifying tool.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe prevalence of sugar-sweetened beverage consumption in NL prior to the implementation of Canada\u0026rsquo;s first SSB tax was high, with 56.4% of adults reporting weekly consumption of taxable beverages (soda/pop, juice drinks, sweetened waters, sports drinks, energy drinks) and 63.3% reporting weekly consumption of non-taxable (100% juice, flavoured milks, specialty coffee drinks, smoothies) beverages. There were sociodemographic differences in the prevalence and average consumption of these beverages, with a higher consumption of taxable beverages among young adults, males, individuals with high school education or less, and those living below the poverty threshold. Post-tax evaluations of this policy should consider the social patterning of beverage consumption prior to implementation when measuring potential impacts on health inequalities, as well as potential unintended consequences of beverage substitutions towards non-taxed SSBs.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSSBs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esugar-sweetened beverages\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNewfoundland and Labrador\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCFG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCanada Food Guide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSEP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esocioeconomic position\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study protocol was reviewed and approved by the Interdisciplinary Committee on Ethics in Human Research at Memorial University (ICEHR Number 20222081-SC).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to data privacy concerns. Requests for access to data can be made directly to the corresponding authors and will be evaluated on a case-by-case basis until the final data set is archived in a repository.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Canadian Cancer Society (#707239) and Canadian Institutes of Health Research \u0026ndash; Institute of Cancer Research (#181053) and Memorial University. DAZ is partially funded by the Canadian Institutes of Health Research and Banting and Best Diabetes Centre.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDaniel A. Zaltz:\u003c/strong\u003e Methodology, Formal analysis, Writing \u0026ndash; Original draft preparation; \u003cstrong\u003eRachel Prowse:\u003c/strong\u003e Conceptualization, Methodology, Funding acquisition, Supervision, Project administration, Writing \u0026ndash; Review \u0026amp; Editing; \u003cstrong\u003eYanqing Yi:\u003c/strong\u003e\u003cem\u003e\u0026nbsp;C\u003c/em\u003eonceptualization and Methodology, Writing \u0026ndash; Review \u0026amp; Editing; \u003cstrong\u003eJessica O\u0026rsquo;Dea:\u003c/strong\u003e Data collection, Preliminary analysis, Writing \u0026ndash; Review \u0026amp; Editing Methodology\u003cem\u003e;\u003c/em\u003e \u003cstrong\u003eScott Harding:\u003c/strong\u003e Conceptualization, Methodology, Funding acquisition, Supervision, Project administration, Writing \u0026ndash; Review \u0026amp; Editing\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGuideline. Sugars intake for adults and children. 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Health effects of the use of non-sugar sweeteners: a systematic review and meta-analysis. World Health Organization. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.who.int/handle/10665/353064\u003c/span\u003e\u003cspan address=\"https://iris.who.int/handle/10665/353064\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlvarado M, Adams J, Penney T, Murphy MM, Abdool Karim S, Egan N, Rogers NT, Carters-White L, White M. A systematic scoping review evaluating sugar-sweetened beverage taxation from a systems perspective. Nat Food. 2023;4(11):986\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s43016-023-00856-0\u003c/span\u003e\u003cspan address=\"10.1038/s43016-023-00856-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"sugar-sweetened beverage tax, health equity, Canada","lastPublishedDoi":"10.21203/rs.3.rs-4606952/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4606952/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLawmakers in Newfoundland and Labrador (NL) recently passed Canada\u0026rsquo;s first sugar-sweetened beverage (SSB) tax. SSB tax evaluations rely on detailed understandings of beverage consumption patterns prior to policy implementation, but there is no recent literature about such patterns among NL residents during the pre-tax period.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe recruited a convenience sample of NL adults ages 19 and older and measured participant characteristics via online surveys and beverage intake via previously-validated, semi-quantitative beverage frequency questionnaires. We described the prevalence and mean intake of taxable SSBs, non-taxable SSBs, unsweetened beverages, and diet (non-nutritive sweetened) beverages. We explored bivariate associations between consumption of these beverages and sociodemographic characteristics identified as potential correlates of SSB intake.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe sample (n\u0026thinsp;=\u0026thinsp;1233) was 65% female, 57% between ages 30\u0026ndash;59 years, and nearly all (94%) white. More than half (56.4%) consumed taxable SSBs weekly, and 63.3% consumed non-taxable SSBs weekly. The most-consumed taxable SSB was regular pop (mean (SD) 2092 (3120) mL/week); the most-consumed non-taxable SSB was coffee with added milk or sugar (mean (SD) 3859 (2895) mL/week). The prevalence of consuming taxable SSBs decreased with increasing age (18-30y 73%, 30-44y 65%, 45-59y 50%, 60y\u0026thinsp;+\u0026thinsp;43%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and was higher among males (60% vs. 54%, p\u0026thinsp;=\u0026thinsp;0.04) and those reporting food insecurity (64% vs. 51%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The prevalence of unsweetened beverage consumption was higher among those with more education (high school 81%, some post-secondary 88%, post-secondary or more 96%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), those working vs. not (92% vs. 87%, p\u0026thinsp;=\u0026thinsp;0.006), and those above the poverty threshold (93% vs. 84%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Weight status was only associated with diet beverage consumption (overweight/obese 54%, not overweight/obese 35%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur findings align with prior studies of socioeconomic position and SSB consumption in Canada, which collectively demonstrate that, on average, those with lower knowledge and material resources consume more SSBs and fewer unsweetened beverages. This research provides necessary understanding of social patterning of beverage consumption in NL prior to tax implementation. Post-tax evaluations of this policy should investigate potential impacts of the tax on diet and health inequalities, as well as potential unintended consequences of beverage substitutions towards non-taxed SSBs.\u003c/p\u003e","manuscriptTitle":"Beverage consumption among adults in Newfoundland and Labrador, Canada prior to the implementation of a sugar-sweetened beverage tax","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-09 06:18:58","doi":"10.21203/rs.3.rs-4606952/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-20T08:22:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-20T01:39:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-20T01:38:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-06-19T15:36:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bc036466-80a5-45c1-a18e-3ea2bda50eac","owner":[],"postedDate":"July 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-07T15:59:42+00:00","versionOfRecord":{"articleIdentity":"rs-4606952","link":"https://doi.org/10.1186/s12889-025-22432-w","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-03-31 15:57:10","publishedOnDateReadable":"March 31st, 2025"},"versionCreatedAt":"2024-07-09 06:18:58","video":"","vorDoi":"10.1186/s12889-025-22432-w","vorDoiUrl":"https://doi.org/10.1186/s12889-025-22432-w","workflowStages":[]},"version":"v1","identity":"rs-4606952","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4606952","identity":"rs-4606952","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}