Food insecurity impacts healthy lifestyle practices and medication adherence among persons with hypertension in Colombia and Jamaica: Findings from a cross-sectional study

Food insecurity impacts healthy lifestyle practices and medication adherence among persons with hypertension in Colombia and Jamaica: Findings from a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Food insecurity impacts healthy lifestyle practices and medication adherence among persons with hypertension in Colombia and Jamaica: Findings from a cross-sectional study Nadia R. Bennett, Jacqueline P. Duncan, Siyi Geng, Katherine T. Mills, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8135598/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 18 You are reading this latest preprint version Abstract Background Adherence to medications and healthy lifestyles are important health behaviours for hypertension control and may be influenced by food insecurity and socioeconomic status (SES). We examined associations between food insecurity and SES with medication adherence and healthy lifestyle practices among patients with hypertension in Colombia and Jamaica. Methods In a cross-sectional survey of hypertensive patients attending primary health centres in Colombia and Jamaica we collected self-reported demographic, education and employment information. Food insecurity was measured using two questions from the modified United States Department of Agriculture (USDA) food security instrument – was there sufficient money for 1) weekly food purchases and 2) healthy foods. Medication adherence was classified as high vs. low/medium using the IMPACTS-MAS questionnaire. Healthy lifestyle was scored using a 6-point scale as unfavourable (score ≤ 3) or favourable (score 4–6), 1 point each for eating less salt, exercising regularly, consuming ≥ 2 servings fruits and ≥ 3 servings vegetables daily, and reduced alcohol consumption or 2 points for abstinence. Multivariable logistic regression with medication adherence categories and lifestyle practice scores as dependent variables assessed associations with food insecurity and SES. Results Of 576 participants (Colombia 288; Jamaica 288), Colombians were older (66.5 years vs. 62.5 years, p < 0.001), had higher education attainment and were less likely to be employed/retired. Colombians had less food insecurity (64.6% vs. 89.0% p < 0.001), higher medication adherence (88.2% vs 50.7% p < 0.001) and more favourable lifestyle practices (86.2% vs. 47.2% p < 0.001). Food insecurity in both countries was inversely related to education, having private health insurance, high medication adherence and healthy lifestyle practices. In multivariable models, food insecurity was associated with increased odds of unfavourable lifestyle practice scores, (OR = 2.4; 95% CI: 1.1, 5.2 p = 0.028) and poor medication adherence (OR = 1.9; 95% CI: (1.0, 3.7) p = 0.072), after adjusting for age, sex, country, marital status, education and employment and having ≥ 2 chronic illnesses. No associations with the other SES examined. Conclusion Food insecure hypertensive patients had increased odds of unfavourable lifestyle practices and were twice as likely to have poor medication adherence. Strategies to address food insecurity may have a positive impact on hypertension control in low resource settings. socioeconomic status food insecurity hypertension medication adherence lifestyle Latin America and the Caribbean Background Cardiovascular diseases (CVDs) are the most common cause of non-communicable disease (NCD) deaths, accounting for 19 million deaths annually [ 1 ]. Hypertension, defined as an average systolic blood pressure ≥ 140 mm Hg, diastolic blood pressure ≥ 90 mm Hg, or taking antihypertensive medication, affects approximately 1.4 billion people worldwide and is the most important modifiable risk factor for CVD and disability-adjusted life years (DALYs) [ 2 , 3 ]. Healthy lifestyle practices – consuming less salt, eating more fruits and vegetables, decreased or no consumption of alcohol, and regular exercise – and use of antihypertensive medications has been shown to substantially reduce blood pressure, reduce major adverse cardiovascular events, cardiovascular mortality, healthcare costs, and improve quality of life [ 4 – 6 ]. The World Health Organisation’s (WHO) Global Hearts initiative and the American Heart Association’s (AHA) “Life’s Essential 8” program recognizes the importance of healthy lifestyle choices on cardiovascular health and promote them as an important means for primary and secondary prevention of cardiovascular disease [ 7 , 8 ]. Poor adherence with pharmacological treatment is an important reason for uncontrolled hypertension [ 9 , 10 ]. In one study, approximately 50% of patients discontinued prescribed antihypertensive medications within one year of initiating treatment [ 11 ]. The WHO describes non-adherence to pharmacological treatment as a problem of striking magnitude [ 12 ]. Factors such as socioeconomic status, the use of complex medication regimens, multimorbidity, and poor-quality of physician-patient relationships have been associated with poor adherence to pharmacological treatment, particularly in low and middle income countries (LMICs) with limited access to health resources [ 13 , 14 ]. Food insecurity, defined as the inability to access adequate and nutritious food for an active and healthy life due to factors such as financial constraints and food unavailability [ 15 ], has been associated with unhealthy lifestyle practices and poor medication adherence in North America and Europe [ 16 , 17 ]. In 2022, the Food and Agriculture Organisation (FAO) of the United Nations reported a 29.6% prevalence of moderate and severe food insecurity globally. However, higher levels of moderate and severe food insecurity were reported for Latin America (Mesoamerica 34.5%, South America 36.4%) and the Caribbean (60.6%) [ 18 ], compared to North America and Europe (7.9%) [ 19 ]. During the 2019 coronavirus disease (COVID-19) pandemic, secondary analysis of a survey of over 1 million adults in LAC estimated that the prevalence of food insecurity was approximately 76% [ 20 ]. Previous studies suggest that individuals with food insecurity take medications less frequently than prescribed, due to costs, and payments for medications are often deferred to save money to buy food [ 16 ]. This behaviour can be taken within the wider context of the social determinants of health (SDOH) and includes access to education, stable employment and financial resources. Low educational attainment and unemployment often exacerbate food insecurity and hinders adherence to antihypertensive medications and healthy lifestyle choices [ 21 , 22 ]. LAC countries with a high prevalence of uncontrolled hypertension combined with high levels of food insecurity and unemployment are especially vulnerable to increased CVD morbidity. Despite the compelling implications of these data, few studies have been conducted in the region to examine the association between food insecurity and adherence to antihypertensive medications and healthy lifestyle practices. The current study was conducted as part of a needs assessment investigation in preparation for the Caribbean and South America Team-based Strategy to Control Hypertension (CATCH) Study. The CATCH Study is a National Institutes of Health (NIH) supported cluster randomized trial to test the implementation and effectiveness outcomes of implementing and scaling up a team-based care strategy for blood pressure (BP) control in Colombia and Jamaica. In this paper we examine associations between socioeconomic status, food insecurity and adherence to healthy lifestyle behaviours and antihypertensive medications among patients with hypertension in both settings. Methods Participants and Study Procedures The design of this cross-sectional study has been previously described [ 23 ]. Between August 2021 and February 2022, 576 patients with hypertension were enrolled and completed an interviewer-administered questionnaire in Colombia and Jamaica (See Supplement 1 for the full questionnaire). In Colombia, patients with hypertension were randomly selected from four primary care clinics using an electronic medical records database. In Jamaica, consecutive patients with hypertension from 10 primary care clinics were selected on the days they visited the clinic. Due to the COVID-19 pandemic, all interviews were conducted by trained research assistants by phone. Measurements The survey gathered information on demographic characteristics (sex, age, education, employment, and marital status), geographic location (country of residence and urban/rural setting), and health status (comorbidities, use of antihypertensive medications, age at hypertension diagnosis). Data were also collected on health care financing, food insecurity, adherence to antihypertensive medications, lifestyle factors, and the impact of COVID-19 on their health and care. Multimorbidity was defined as the co-occurrence of ≥ 2 self-reported chronic conditions (diabetes, high cholesterol, depression, anxiety, kidney disease, stroke, heart attack/heart disease, overweight/obesity) [ 24 ]. Health care financing was categorized as follows: Insurance (Insurance by employer or private insurance purchased by participant or spouse), self-financed (out-of-pocket or family/friends), government (government subsidy or program) and charity. Socioeconomic status Socioeconomic status was measured using education attainment and employment status. To classify education participants were asked “What is your highest level of education” and patients classified as having less than high school, high school and more than high school education. For employment status participants were asked “Are you currently working including self-employment”. There were then classified into two categories – employed/retired vs. other (which included students, housewives, unemployed and disabled persons). Food insecurity Food insecurity was assessed by two questions from the USDA food security instrument: “The food that we bought just didn't last, and we didn't have money to get more” and “We couldn't afford to eat healthy meals with more fruits and vegetables” [ 25 ]. Persons were classified as food insecure if they responded “true most of the time” or “true some of the time” to either of these two questions. Lifestyle and Medication Adherence Lifestyle adherence was scored on a 6-point scale where 1 point was assigned for each of the following: currently eating less salt, exercising regularly, eating adequate amounts of fruit (at least 2 servings daily), vegetables (at least 3 servings daily). Points were assigned for alcohol moderation with reduction of intake receiving one point and complete abstinence from alcoholic beverages receiving 2 points. Lifestyle adherence was grouped as unfavourable (score ≤ 3) or favourable (score 4–6). Medication adherence was based on the Implementation of Multifaceted Patient-Centred Treatment Strategies for Intensive Blood Pressure Control medication adherence scoring system (IMPACTS-MAS) which used 2 questions: “ Over the last 7 days, on how many days did you not take any blood pressure pills? ” where points ranged between 0 (if no medications were taken for 7 days) and 4 (if all medications were taken for 7 days) and “ Over the last 7 days, on how many days did you cut back (or not take the full dose) of your blood pressure pills? ” where points ranged between 0 (if no medications were taken for 7 days) and 2 (if all medications were taken for 7 days). The sum of the responses to both questions were calculated and patients were classified as having high (6 points), medium (5 or 5.5 points) and low (< 5 points) medication adherence [ 26 ]. COVID-19 impact Given that the survey was conducted during the COVID-19 pandemic, we also sought to assess the impact of the pandemic restrictions on healthcare access. COVID-19 impact was determined based on responses to the question: “Were you not able to see a doctor or get prescription medications due to any of the following reasons – a) pharmacy, hospital or clinics closed; b) less time to see a doctor or get medications due to curfew restrictions; c) fear of contracting coronavirus if you leave the house” . After assigning “1” point to each “yes” response, a total score was used to categorize COVID-19 impact as minimal (score = 0), moderate (score = 1 to 2), and substantial COVID-19 impact (score = 3). Sample Size Using PASS 15 (NCSS, LLC) software based on assumption of stratification by sex and urban/rural status, a minimum sample of 288 participants per country was calculated to detect a 20% response proportion with a 95% confidence interval from 10%-30%. Statistical Analysis Analyses were done using SAS 9.4 (SAS Institute, Cary, NC). Frequency tables with percentages were generated and descriptive analyses used for the baseline population by food insecurity status. Mean and standard deviation were reported for continuous variables. Data were weighted based on distribution of age groups, sex, and residential areas within the respective target population of each country as assessed from clinic registers. In analyses that included participants from both countries, combined weights were applied. Sample sizes and frequency numbers are unweighted but means standard deviations (SDs) and percentages are weighted. Wald Chi-square test (or Fisher’s exact test for sparse data) was performed for differences between categorical variables, and Student’s t-test was used for differences between continuous variables, comparing Colombia and Jamaica. Bivariate analyses were done to explore associations between socioeconomic status and food insecurity with variables of interest including medication adherence and lifestyle practice score. The outcomes were dichotomized – medication adherence high vs. medium/low and lifestyle adherence – favourable vs. unfavourable. Using a p-value level of ≤ 0.2 from the bivariate models, logistic regression was used to build the final multivariable model. For medication adherence, we adjusted for age, sex (male vs. female), country, marital status (married/common law vs. not married/common law) and health care financing (having private health insurance vs not). For favourable lifestyle, we adjusted for age, sex (male vs. female), marital status (married/common law vs not married/common law), multimorbidity (having 2 or more vs. 0–1 chronic illnesses) and COVID-19 impact (minimal vs moderate and substantial). Results There were 576 participants (288 Colombia, 288 Jamaica) in this study, of which 31.5% were male. The Colombian participants were older than their counterparts from Jamaica (mean age 66.5 years vs. 62.5 years, p < 0.001) and were more likely to be in a married/common law relationship (58.9% vs. 40.6%, p < 0.001). Higher education levels were observed in Colombia, where more participants achieved “more than high school” education (30.3% vs. 17.2%, p = 0.01), while Jamaicans had higher employment/retiree levels (76.1% vs. 64.0%, p = 0.01) compared to Colombians (Supplement 2: Table 1 ). The Colombian participants had a shorter mean duration of hypertension compared to their counterparts in Jamaica (11.1 years vs. 16.5 years, p < 0.001) and had a lower percentage with multimorbidity though the difference was not statistically significant (39.2% vs. 49.5%, p = 0.05). In Colombia, private insurance was the main source of health care financing (88.3%) while government subsidy, meaning government, self, family friends and or charity was the primary source in Jamaica 92.4%), p < 0.001. Colombians had lower levels of food insecurity (64.6% vs. 89.0% p < 0.001) but greater proportion with higher medication adherence scores (88.2% vs 50.7% p < 0.001) and favourable lifestyle adherence 86.2% vs. 47.2% p < 0.001). (Supplement 2). Food Insecurity Table 1 describes the characteristics of participants of the study stratified by level of food insecurity. Overall, 440 (76.1%) of the participants were food insecure where the mean age and sex distribution of those who were food insecure compared to those who were food secure was similar. As education level increased food insecurity prevalence decreased (less than high school 42.2%, high school 39.4%, more than high school 18.3%, p < 0.001). Food insecure compared to food secure participants were also more likely to have no private insurance (58.5% vs. 21.3% P < 0.001), low/medium medication adherence scores (34.1% vs. 14.3% p < 0.001) and unfavourable adherence to favourable lifestyle practices (38.3% vs. 12.4% p < 0.001). Table 1 Characteristics of Study Participants by Food Insecurity Status* Characteristics Food Insecure N = 440 Food Secure N = 136 P-value for group difference Demographic Characteristics Age , Mean (SD) 64.8 (11.4) 64.5 (11.4) 0.845 Sex , n (%) 0.663 Male 198 (30.9) 76 (33.2) Female 242 (69.1) 60 (66.8) Country , n (%) < 0.001 Colombia 180 (45.1) 108 (78.4) Jamaica 260 (54.9) 28 (21.6) Location , n (%) 0.040 Urban 211 (65.6) 79 (76.0) Rural 229 (34.4) 57 (24.0) Education Level , n (%) < 0.001 Less than High school 185 (42.2) 30 (24.2) High School 182 (39.4) 45 (33.3) More than High school 73 (18.3) 61 (42.5) Employment status , n (%) 0.176 Employed/Retiree 298 (67.7) 113 (76.1) Other** 142 (32.3) 23 (23.9) Multimorbidity , n (%) 0.093 Yes (≥ 2 conditions) 211 (46.7) 58 (35.9) No 229 (53.3) 78 (64.1) Healthcare financing , n (%) < 0.001 Private Insurance 158 (41.5) 108 (78.7) No private insurance*** 282 (58.5) 28 (21.3) Medication adherence Score , n (%) < 0.001 Low/medium 156 (34.1) 23 (14.3) High 276 (65.9) 109 (85.7) Lifestyle Factors , n (%) Eat less salt 423 (96.5) 131 (97.8) 0.389 Exercising regularly 216 (44.3) 97 (68.5) 0.999† Eat ≥ 2 servings of fruits 177 (44.3) 87 (62.7) 0.006 Eat ≥ 3 servings of vegetables 151 (36.5) 93 (65.0) < 0.001 Lifestyle adherence , n (%) < 0.001 Unfavourable (≤ 3) 174 (38.3) 22 (12.4) Favourable (4–6) 266 (61.7) 114 (87.6) Covid − 19 Impact , n (%) < 0.001 Minimal 291 (65.2) 44 (28.5) Moderate/ Substantial 149 (34.8) 92 (71.5) * The sample sizes and actual frequency numbers are unweighted but means (SDs) or percentages are weighted. ** unemployed, housewife, students, disabled *** no private insurance- meaning government, self, family friends and charity † Fisher's exact test Socioeconomic Status Table 2 shows food insecurity, lifestyle practices and self-reported medication adherence stratified by educational attainment. We found that higher education was associated with less food insecurity. For example, 84.7% of those who had less than high school education was food insecure compared to 57.8% of those who had more than high school education (p < 0.001). However, medication adherence and lifestyle adherence scores were not significantly associated with education levels. We found that 28.5% participants with less that high school education compared to 27.7% with more than high school education had low/medium adherence (p = 0.817) and 34.8% participants with less that high school education compared to 22.7% with more than high school education had an unfavourable lifestyle adherence score (p = 0.067). (Supplement 2: Table 2 : Baseline Characteristics Stratified by Education Level) Table 2 Food insecurity, Medication and Lifestyle Adherence of Study Participants by Socioeconomic Status as measured by Educational Attainment* Characteristics Less than High School (N = 215) High School (N = 227) More than High School (N = 134) P-value for Group Difference Food Insecurity , n (%) < 0.001 Yes (Insecurity) 185 (84.7) 182 (79.0) 73 (57.8) No (Security) 30 (15.3) 45 (21.0) 61 (42.2) Medication Adherence Score , n (%) 0.817 Low/medium 62 (28.5) 78 (31.1) 39 (27.7) High 148 (71.5) 146 (68.9) 91 (72.3) Lifestyle Factors , n (%) Eat less salt 209 (96.1) 215 (96.6) 130 (98.1) 0.577† Exercising regularly 120 (49.5) 111 (44.7) 82 (59.3) 0.114 Decrease/don’t consume alcohol 212 (97.8) 225 (99.1) 132 (98.8) 0.533† Eat ≥ 2 servings of fruits 91 (44.4) 98 (48.8) 75 (55.5) 0.286 Eat at ≥ 3 servings of vegetables 80 (39.6) 91 (41.0) 73 (53.0) 0.125 Lifestyle adherence , n (%) 0.067 Unfavourable (≤ 3) 72 (34.8) 88 (35.5) 36 (22.7) Favourable (4–6) 143 (65.2) 139 (64.5) 98 (77.3) * The sample sizes and actual frequency numbers are unweighted but means (SDs) or percentages are weighted. † Fisher's exact test Table 3 shows the characteristics of participants of the study stratified by employment status. We found no significant associations between employment status and food insecurity, medication adherence and lifestyle adherence. (Supplement 2: Table 3 : Baseline Characteristics Stratified by Employment Status) Table 3 Food Insecurity, Medication and Lifestyle Adherence of Study Participants by Employment Status* Characteristics Employed/Retiree (N = 411) Other** (N = 165) P-value for Group Difference Food Insecurity , n (%) 0.176 Yes (Insecurity) 298 (73.9) 142 (81.1) No (Security) 113 (26.1) 23 (18.9) Medication Adherence Score , n (%) 0.088 Low/medium 138 (31.9) 41 (23.4) High 265 (68.1) 120 (76.6) Lifestyle Factors , n (%) Eat less salt 394 (96.6) 160 (97.2) 0.743 Exercising regularly 237 (52.6) 76 (44.2) 0.163 Decrease/don’t consume alcohol 406 (98.4) 163 (98.8) > 0.999† Eat ≥ 2 servings of fruits 191 (47.6) 73 (51.3) 0.545 Eat ≥ 3 servings of vegetables 166 (37.9) 78 (56.0) 0.003 Lifestyle adherence , n (%) 0.097 Unfavourable (≤ 3) 145 (34.7) 51 (26.2) Favourable (4–6) 266 (65.3) 114 (73.8) * The sample sizes and actual frequency numbers are unweighted but means (SDs) or percentages are weighted. ** unemployed, housewife, students, disabled † Fisher's exact test Table 4 shows the associations between education, employment and food insecurity and unfavourable lifestyle adherence. In unadjusted models, those with a high school education had almost two times the odds of unfavourable lifestyle scores compared to those with more than a high school education (OR: 1.9, 95%CI:1.0, 3.4, p = 0.041). Participants who were food insecure had 4 times the odds of having unfavourable lifestyle adherence (OR: 4.4, 95% CI: 2.2, 9.0, p < 0.001). This remained significant in the fully adjusted model that included age, sex, country, marital status, multi-morbidity and COVID-19 impact (OR: 2.4, 95% CI:1.1, 5.2, p = 0.028). Table 4 Crude and Adjusted odds Ratios exploring the Association between Education, Employment, Food Insecurity and Unfavorable Lifestyle*# Crude Odds Ratio (95% CI) P-value Adjusted Odds Ratio* (95% CI) P-value Education More than high school Reference Reference High school 1.9 (1.0, 3.4) 0.041 1.4 (0.8, 2.7) 0.258 Less than high school 1.8 (1.0, 3.3) 0.052 1.4 (0.7, 2.7) 0.366 Employment Employed/Retired Reference Reference Other ** 0.7 (0.4, 1.1) 0.097 0.8 (0.5, 1.3) 0.342 Food Insecurity Secure Reference Reference Insecure 4.4 (2.2, 9.0) < 0.001 2.4 (1.1, 5.2) 0.028 *Final model: age, sex, country, marital status, multimorbidity and covid impact # Favourable lifestyle was the outcome variable. ** unemployed, housewife, student, disabled Table 5 shows results for the associations between education, employment and food insecurity and antihypertensive medication adherence. In the unadjusted model, those who were food insecure had 3 times the odds of poor medication adherence compared to those that were food secure (OR: 3.1, 95% CI:1.7, 5.6, p < 0.001). This effect was attenuated after adjusting for age, sex, country, marital status, multimorbidity and COVID impact (Adjusted OR: 1.9, 95% CI: 1.0, 3.7, p = 0.072). There were no associations between education or employment and medication adherence in adjusted and unadjusted models. Table 5 Crude and Adjusted Odds Ratios exploring the Association Between Education, Employment, Food Insecurity and Antihypertensive Medication Adherence*# Crude Odds Ratio (95% CI) P-value Adjusted Odds Ratio (95% CI) P-value Education More than high school Reference Reference High school 1.2 (0.7, 2.1) 0.554 0.8 (0.4, 1.5) 0.529 Less than high school 1.0 (0.6, 1.9) 0.882 0.8 (0.4, 1.7) 0.519 Employment Employed/retired Reference Reference Other ** 0.7 (0.4, 1.1) 0.099 0.7 (0.4, 1.3) 0.248 Food Insecurity Secure Reference Reference Insecure 3.1 (1.7, 5.6) < 0.001 1.9 (1.0, 3.7) 0.072 *Final model: adjusted for age, sex, country, marital status and healthcare expenses #Favourable lifestyle was the outcome variable ** unemployed, housewife, student, disabled Discussion In this study of patients with hypertension who were being treated at primary care clinics in Colombia and Jamaica, high levels of food insecurity were recorded in both countries. Food insecurity but not socioeconomic status was associated with poor adherence to recommended lifestyle practices and poor medication adherence, although the association with medication adherence was attenuated and no longer significant after adjustment for potential confounding variables. This association between food insecurity and favourable lifestyle was not fully explained by other socioeconomic factors or the country in which participants lived. Latin America and the Caribbean has achieved the millennium development goal target of reducing the number of people suffering from hunger [ 27 ]. However, the COVID-19 pandemic, climate change and natural disasters, global political instability and increases in the cost of living have led to increasing food insecurity globally [ 27 ]. In 2022 FAO reported that the levels of food insecurity in LAC were 37.5% compared to the world estimate of 29.6%. The prevalence of moderate or severe food insecurity in South America was 37.5% and 60.6% in the Caribbean [ 18 ]. The prevalence of food insecurity in Colombia reported in this study (65%) was similar to the 66% noted in a previous national report [ 28 ]. However, in Jamaica we found a higher level of food insecurity (89%) than was previously reported (25–75%) [ 29 , 30 ]. These differences may be attributed to the study population (older persons with hypertension), the composite score used and the timing of the study. We did not identify studies that explored food insecurity in patients with hypertension from LAC. It is possible that the costs of managing blood pressure would pose an additional strain and contribute to the higher prevalence of food insecurity that we observed [ 31 ]. In addition, the study was conducted during the COVID-19 pandemic. Studies confirm that all four food insecurity dimensions (availability, accessibility, usability and sustainability) were compromised resulting in substantial price increases of healthy foods during the pandemic [ 32 ]. In our survey, food insecurity was based on 2 of the 6 items in the six-item short form of the USDA food security instrument: the ability to purchase sufficient food or purchase healthy foods in our study [ 25 ]. Other elements of food insecurity in the USDA food security instrument include cutting meal size and intake, feeling hungry but not being able to eat, and the frequency with which these disruptions occur. It is possible that variations in food security in surveys are due to variations in the data collection tools. Nevertheless, food insecurity is consistently high reinforcing the urgent need for effective strategies. We found a possible association between food insecurity and medication adherence, which is in keeping with the published literature [ 33 , 34 ]. The methods for recognizing medication adherence, and the instruments used to measure adherence in other studies have varied widely. We used the IMPACTS-MAS scoring system [ 26 ] which was not used in the previous studies conducted in Jamaica or Colombia. A 2021 meta-analysis showed that food insecurity decreased the odds of medication adherence by 44% [ 34 ]. Like our findings, other employment status (i.e. unemployed, housewife, student, disabled)and less education did not have a significant association with medication adherence. Cost-related underuse and medication restricting behaviours are some issues that have been identified in other studies examining the relationship between food insecurity and adherence [ 35 , 36 ] . Few studies report on lifestyle adherence in LAC, and the evaluation of lifestyle adherence is a complex construct. There are different combinations of measures when lifestyle adherence is reported in the literature. It is most frequently reported by a combination of dietary adherence (eating less salt), physical activity, medication adherence, weight management, smoking cessation and alcohol moderation. The lifestyle adherence score created for this study was comprehensive and took into account the individual components (eating less salt, exercising regularly, decreasing alcohol consumption or didn't drink, eating adequate (at least 2 servings daily) fruits and adequate (at least 3 servings daily) vegetables) of the score. We found that food insecurity decreased the odds of favourable lifestyle. Other studies have shown that food insecurity is inversely associated with favourable lifestyle factors including physical activity, diet, alcohol use and sleep quality[ 37 – 39 ]. For example, Kehoe et al showed that food insecurity affected the diet quality of young women in South Africa [ 40 ]. Alcohol abuse/dependence was associated with an increased odds of food insecurity among homeless men and women in the USA ((OR = 2.72, CI. 95 = 1.55, 4.77) [ 39 ]. For physical activity, authors hypothesize that external factors such as employment and long work hours of low-income food-insecure households may contribute to less physical activity [ 41 ]. Similarly, violence in communities may restrict physical activity for food insecure families. Of note, both Jamaica and Colombia have high homicide rates. Further studies in Jamaica and Colombia are needed to better understand the complex relationship between food insecurity and maintaining a healthy lifestyle. Strengths and Limitations This study adds to the body of literature on lifestyle practices and determinants of BP control in two different countries in LAC, which has a high burden of CVD. The recruitment of participants from two countries with different health systems and cultural practices provides information on the possible role of food insecurity in BP control and possible targets for programmes to reduce the burden of hypertension. One limitation is that other measures of SES and SDOH were not included in this study. Additionally, we relied on self-reported adherence to medication and healthy lifestyle, which may have resulted in reporting bias and misclassification of the outcomes. Information bias and misclassification could also have occurred due to the composite scores used for classification of lifestyle practices, medication adherence and food insecurity. The lifestyle adherence score was created for this study and, although validated in other populations, the instrument used to assess medication adherence (IMPACTS-MAS) [ 26 ] has not been previously used in Colombia or Jamaica. For food insecurity, only the first two (of six) questions of the modified USDA food security instrument were used. Structural and cultural factors such as policies and cultural practices are possible confounders or effect modifiers that were not captured in this study. Additionally, data collection occurred during the COVID-19 pandemic which had an impact on both food insecurity and lifestyle adherence with impacts differing between countries [ 20 , 42 ]. Therefore, these findings may not reflect the usual practices. Finally, it would have been useful to determine levels of food security (mild, moderate and severe) and their impact on medication adherence and favourable lifestyle. This may be explored in future studies. Conclusion Persons with hypertension who were food insecure had an increased odds of unfavourable lifestyle practices and were twice as likely to have poor medication adherence. This study provides valuable insight into the complex interplay between socioeconomic factors including food insecurity and hypertension control in Colombia and Jamaica. Consistently taking medications and making healthy lifestyle choices are necessary to maintain good health and slow progression of chronic diseases. Given the high prevalence of food insecurity and its role in lifestyle and medication adherence, our findings suggest that public health policies, programmes and multi-sectoral strategies are urgently needed if we are to effectively prevent and control hypertension in LAC. Abbreviations AHA American Heart Association ASS-15 Adaptive Significance Scale – 15 item version BP Blood pressure CATCH Caribbean and south America Team-Based Strategy to Control Hypertension COVID-19 Corona Virus Diseases 2019 CVDs Cardiovascular Diseases DALYs Disability-adjusted Life Years FAO Food and Agriculture Organisation of the United Nations FIES Food Insecurity Experience Scale IMPACTS-MAS Implementation of Multifaceted Patient-Centred Treatment Strategies for Intensive Blood Pressure Control medication adherence scoring system. LAC Latin America and the Caribbean LMICs Low- and Middle-Income Countries NCDs Non-communicable diseases PAHO Pan American Health Organisation SD Standard Deviations SDOH Social determinants of health USDA United States Department of Agriculture. WHO World Health Organization Declarations Ethics approval and consent to participate Ethical approval was granted by Institutional Review Board of Tulane University (12 August 2022; 2022-980, Institutional Bioethics Committee of Universidad de Santander in Colombia (16 July 2020; VII-050-BUC), the Mona Campus Research Ethics Committee of the University of the West Indies (30 June 2020; ECP 232 19/20), and the Ministry of Health and Wellness Advisory Panel on Ethics and Medico-Legal Affairs (26 April 2021; SRD/ETH/20). Conduct of this study adhered to the principles outlined in the Declaration of Helsinki and written informed consent was obtained from all participants included in this study. Consent for publication Not applicable Availability of data and materials The datasets generated during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no financial and non-financial competing interests Funding This study was funded by the National Institutes of Health (Ref# 1 UG3 HL152373-01). The views expressed are those of the authors and do not necessarily reflect those of the funding body Authors' contributions NB – Conception and design of the study, analysis and interpretation of data, drafted and revised the manuscript, and approved the submitted version. JD – Conception and design of the study, analysis and interpretation of data, drafted and revised the manuscript, and approved the submitted version. SG – Analysis and interpretation of the data, revised the manuscript, and approved the submitted version. MC – Reviewed the manuscript and approved the submitted version. KM – Conception and design, interpretation of data, revised the manuscript, and approved the submitted version. PW – Conception and design, interpretation of data, drafted and revised the manuscript, and approved the submitted version. AB – Conception and design, interpretation of data, revised the manuscript, and approved the submitted version. AA – Conception and design, revised the manuscript, and approved the submitted version. PL – Conception and design, interpretation of data, revised the manuscript, and approved the submitted version. PLJ – Conception and design, interpretation of data, revised the manuscript, and approved the submitted version. TF – Conception and design, interpretation of data, drafted and revised the manuscript, and approved the submitted version MTR – Conception and design, interpretation of data, drafted and revised the manuscript, and approved the submitted version Acknowledgements The authors thank Carene Lindsay, Zulma Urbina, Diego Ortega and Gustavo Aroca-Martinez for their assistance with participant recruitment and, data collection. Authors' information (optional) References Noncommunicable diseases. [ https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases] Mills KT, Bundy JD, Kelly TN, Reed JE, Kearney PM, Reynolds K, Chen J, He J. Global Disparities of Hypertension Prevalence and Control: A Systematic Analysis of Population-Based Studies From 90 Countries. Circulation. 2016;134(6):441–50. Roth GA, Mensah GA, Fuster V. The Global Burden of Cardiovascular Diseases and Risks: A Compass for Global Action. J Am Coll Cardiol. 2020;76(25):2980–1. Carey RM, Muntner P, Bosworth HB, Whelton PK. Prevention and Control of Hypertension: JACC Health Promotion Series. J Am Coll Cardiol. 2018;72(11):1278–93. Loef M, Walach H. The combined effects of healthy lifestyle behaviors on all cause mortality: a systematic review and meta-analysis. Prev Med. 2012;55(3):163–70. Lu Q, Zhang Y, Geng T, Yang K, Guo K, Min X, He M, Guo H, Zhang X, Yang H, et al. Association of Lifestyle Factors and Antihypertensive Medication Use With Risk of All-Cause and Cause-Specific Mortality Among Adults With Hypertension in China. JAMA Netw Open. 2022;5(2):e2146118–2146118. World Health Organization. Technical package for cardiovascular disease management in primary health care: healthy-lifestyle counselling. In. Geneva: World Health Organization; 2018. Lloyd-Jones DM, Allen NB, Anderson CA, Black T, Brewer LC, Foraker RE, Grandner MA, Lavretsky H, Perak AM, Sharma G. Life’s essential 8: updating and enhancing the American Heart Association’s construct of cardiovascular health: a presidential advisory from the American Heart Association. Circulation. 2022;146(5):e18–43. Abegaz TM, Shehab A, Gebreyohannes EA, Bhagavathula AS, Elnour AA. Nonadherence to antihypertensive drugs: A systematic review and meta-analysis. Medicine. 2017;96(4):e5641. Aguiar J, Ribeiro M, Pedro AR, Martins AP, da Costa FA. Awareness about barriers to medication adherence in cardiovascular patients and strategies used in clinical practice by Portuguese clinicians: a nationwide study. Int J Clin Pharm. 2021;43(3):629–36. Vrijens B, Vincze G, Kristanto P, Urquhart J, Burnier M. Adherence to prescribed antihypertensive drug treatments: longitudinal study of electronically compiled dosing histories. BMJ. 2008;336(7653):1114–7. Chaudri NAM. Adherence to long-term therapies evidence for action. In.; 2003. Choudhry NK, Kronish IM, Vongpatanasin W, Ferdinand KC, Pavlik VN, Egan BM, Schoenthaler A, Houston Miller N, Hyman DJ. Medication Adherence and Blood Pressure Control: A Scientific Statement From the American Heart Association. Hypertension. 2022;79(1):e1–14. Hamrahian SM, Maarouf OH, Fülöp T. A Critical Review of Medication Adherence in Hypertension: Barriers and Facilitators Clinicians Should Consider. Patient Prefer Adherence. 2022;16:2749–57. Hunger, Insecurity F. [ https://www.fao.org/hunger/en/] Wilder ME, Kulie P, Jensen C, Levett P, Blanchard J, Dominguez LW, Portela M, Srivastava A, Li Y, McCarthy ML. The Impact of Social Determinants of Health on Medication Adherence: a Systematic Review and Meta-analysis. J Gen Intern Med. 2021;36(5):1359–70. Maia I, Oliveira A, Santos AC. Food insecurity is associated with an unhealthy lifestyle score in middle- and older-aged adults: findings from the EPIPorto cohort. Food Secur. 2023;15(3):661–71. FAO. IFAD. PAHO.UNICEF and WFP: Latin America and the Caribbean-Regional Overview of Food Security and Nutrition 2023:Statistics and trends, vol. 2005. Santiago, Chile: FAO; IFAD ; UNICEF ; WFP ; PAHO ;; 2023. FAO I, UNICEF, WFP and WHO. The State of Food Security and Nutrition in the World 2020 Transforming food systems for affordable healthy diets. Rome, Italy: FAO, IFAD, UNICEF, WFP and WHO;; 2020. Benites-Zapata VA, Urrunaga-Pastor D, Solorzano-Vargas ML, Herrera-Añazco P, Uyen-Cateriano A, Bendezu-Quispe G, Toro-Huamanchumo CJ, Hernandez AV. Prevalence and factors associated with food insecurity in Latin America and the Caribbean during the first wave of the COVID-19 pandemic. Heliyon. 2021;7(10):e08091. Oladele CR, Khandpur N, Galusha D, Nair S, Hassan S, Wambugu V, Martinez-Brockman J, Nunez-Smith M, Perez-Escamilla R. Food insecurity and hypertension prevalence, awareness, and control in the Eastern Caribbean Health Outcomes Research Network Study. PLOS Glob Public Health. 2025;5(5):e0003296. Hernández-Vásquez A, Visconti-Lopez FJ, Vargas-Fernández R. Factors Associated with Food Insecurity in Latin America and the Caribbean Countries: A Cross-Sectional Analysis of 13 Countries. Nutrients 2022, 14(15). Duncan JP, Geng S, Lindsay C, Ferguson TS, Mills KT, Lopez-Lopez JP, He H, Lanza P, Marshall AN, Williams MJ et al. Differences in COVID-19 Vaccination and Experiences among Patients with Hypertension in Colombia and Jamaica during the COVID-19 Pandemic. Int J Environ Res Public Health 2024, 21(10). Navickas R, Petric VK, Feigl AB, Seychell M. Multimorbidity: What do we know? What should we do? J Comorb. 2016;6(1):4–11. Food Security in the U.S. - Survey Tools U.S. Household Food Security Survey Module. Six-Item Short Form Economic Research Service, USDA [ https://www.ers.usda.gov/sites/default/files/_laserfiche/DataFiles/50764/short2024.pdf] Allouch F, Peacock E, Mills KT, Whelton PK, Chen J, He J. A Novel Two-Question Antihypertensive Medication Adherence Scale Predicts Blood Pressure Control and Cardiovascular Disease Outcomes. In.: AHA Journals; 2023. Food Security in Latin America and the Caribbean, Factsheet. [ https://www.iadb.org/en/news/food-security-latin-america-and-caribbean] Colombia sees a. modest improvement in food security but half of the population remains exposed to climatic and economic risks [ https://www.wfp.org/news/colombia-sees-modest-improvement-food-security-half-population-remains-exposed-climatic-and?form=MG0AV3] GOAL 2 End hunger. achieve food security and improved nutrition and promote sustainable agriculture [ https://www.pioj.gov.jm/wp-content/uploads/2022/10/VNR_Goal_2.pdf?form=MG0AV3] Jamaica JM. Prevalence of Severe Food Insecurity in the Population: % of population [ https://www.ceicdata.com/en/jamaica/social-health-statistics/jm-prevalence-of-severe-food-insecurity-in-the-population--of-population?form=MG0AV3] Kostova D, Spencer G, Moran AE, Cobb LK, Husain MJ, Datta BK, Matsushita K, Nugent R. The cost-effectiveness of hypertension management in low-income and middle-income countries: a review. BMJ Glob Health 2020, 5(9). Gebeyehu DT, East L, Wark S, Islam MS. A systematic review of the direct and indirect COVID-19's impact on food security and its dimensions: pre-and post-comparative analysis. BMC Public Health. 2023;23(1):2298. Men F, Gundersen C, Urquia ML, Tarasuk V. Prescription medication nonadherence associated with food insecurity: a population-based cross-sectional study. CMAJ Open. 2019;7(3):E590–7. Wilder ME, Kulie P, Jensen C, Levett P, Blanchard J, Dominguez LW, Portela M, Srivastava A, Li Y, McCarthy ML. The Impact of Social Determinants of Health on Medication Adherence: a Systematic Review and Meta-analysis. J Gen Intern Med. 2021;36(5):1359–70. McClintock HF, Imel BE. Food insecurity and medication restricting behavior among persons with diabetes in the United States. Nutr Health. 2024;30(2):341–7. Herman D, Afulani P, Coleman-Jensen A, Harrison GG. Food Insecurity and Cost-Related Medication Underuse Among Nonelderly Adults in a Nationally Representative Sample. Am J Public Health. 2015;105(10):e48–59. Theodoridis X, Grammatikopoulou MG, Gkiouras K, Papadopoulou SE, Agorastou T, Gkika I, Maraki MI, Dardavessis T, Chourdakis M. Food insecurity and Mediterranean diet adherence among Greek university students. Nutr metabolism Cardiovasc diseases: NMCD. 2018;28(5):477–85. Witkowiak MM, Idris AN, Sato A, Sacre H, Haddad C, Rizk R, Malaeb D, Strahler J, Salameh P, Ierodiakonou D. Food insecurity and lifestyle behaviours in university students amidst the COVID-19 pandemic: a comparative survey across three countries. BMC Public Health. 2024;24(1):3571. Reitzel LR, Chinamuthevi S, Daundasekara SS, Hernandez DC, Chen TA, Harkara Y, Obasi EM, Kendzor DE, Businelle MS. Association of Problematic Alcohol Use and Food Insecurity among Homeless Men and Women. Int J Environ Res Public Health 2020, 17(10). Kehoe SH, Wrottesley SV, Ware L, Prioreschi A, Draper C, Ward K, Lye S, Norris SA. Food insecurity, diet quality and body composition: data from the Healthy Life Trajectories Initiative (HeLTI) pilot survey in urban Soweto, South Africa. Public Health Nutr. 2021;24(7):1629–37. To QG, Frongillo EA, Gallegos D, Moore JB. Household food insecurity is associated with less physical activity among children and adults in the U.S. population. J Nutr. 2014;144(11):1797–802. Beck J, Koebach A, Abreu L, Regassa MD, Hoeffler A, Stojetz W, Brück T. COVID-19 Pandemic and Food Insecurity Fuel the Mental Health Crisis in Africa. Int J public health 2024, 68. Additional Declarations No competing interests reported. Supplementary Files FIandHTNBMCPubhlthSupplementSurveySubmission.pdf FIandHTNBMCPubhlthSupplementSubmissionupdated.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Dec, 2025 Reviews received at journal 24 Dec, 2025 Reviews received at journal 21 Dec, 2025 Reviews received at journal 19 Dec, 2025 Reviews received at journal 16 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviews received at journal 14 Dec, 2025 Reviewers agreed at journal 13 Dec, 2025 Reviewers agreed at journal 11 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 08 Dec, 2025 Reviewers agreed at journal 08 Dec, 2025 Reviewers invited by journal 08 Dec, 2025 Editor assigned by journal 08 Dec, 2025 Editor invited by journal 28 Nov, 2025 Submission checks completed at journal 26 Nov, 2025 First submitted to journal 26 Nov, 2025 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. 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Hypertension, defined as an average systolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140 mm Hg, diastolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;90 mm Hg, or taking antihypertensive medication, affects approximately 1.4\u0026nbsp;billion people worldwide and is the most important modifiable risk factor for CVD and disability-adjusted life years (DALYs) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHealthy lifestyle practices \u0026ndash; consuming less salt, eating more fruits and vegetables, decreased or no consumption of alcohol, and regular exercise \u0026ndash; and use of antihypertensive medications has been shown to substantially reduce blood pressure, reduce major adverse cardiovascular events, cardiovascular mortality, healthcare costs, and improve quality of life [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The World Health Organisation\u0026rsquo;s (WHO) Global Hearts initiative and the American Heart Association\u0026rsquo;s (AHA) \u0026ldquo;Life\u0026rsquo;s Essential 8\u0026rdquo; program recognizes the importance of healthy lifestyle choices on cardiovascular health and promote them as an important means for primary and secondary prevention of cardiovascular disease [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePoor adherence with pharmacological treatment is an important reason for uncontrolled hypertension [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In one study, approximately 50% of patients discontinued prescribed antihypertensive medications within one year of initiating treatment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The WHO describes non-adherence to pharmacological treatment as a problem of striking magnitude [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Factors such as socioeconomic status, the use of complex medication regimens, multimorbidity, and poor-quality of physician-patient relationships have been associated with poor adherence to pharmacological treatment, particularly in low and middle income countries (LMICs) with limited access to health resources [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFood insecurity, defined as the inability to access adequate and nutritious food for an active and healthy life due to factors such as financial constraints and food unavailability [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], has been associated with unhealthy lifestyle practices and poor medication adherence in North America and Europe [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In 2022, the Food and Agriculture Organisation (FAO) of the United Nations reported a 29.6% prevalence of moderate and severe food insecurity globally. However, higher levels of moderate and severe food insecurity were reported for Latin America (Mesoamerica 34.5%, South America 36.4%) and the Caribbean (60.6%) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], compared to North America and Europe (7.9%) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. During the 2019 coronavirus disease (COVID-19) pandemic, secondary analysis of a survey of over 1\u0026nbsp;million adults in LAC estimated that the prevalence of food insecurity was approximately 76% [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePrevious studies suggest that individuals with food insecurity take medications less frequently than prescribed, due to costs, and payments for medications are often deferred to save money to buy food [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This behaviour can be taken within the wider context of the social determinants of health (SDOH) and includes access to education, stable employment and financial resources. Low educational attainment and unemployment often exacerbate food insecurity and hinders adherence to antihypertensive medications and healthy lifestyle choices [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. LAC countries with a high prevalence of uncontrolled hypertension combined with high levels of food insecurity and unemployment are especially vulnerable to increased CVD morbidity. Despite the compelling implications of these data, few studies have been conducted in the region to examine the association between food insecurity and adherence to antihypertensive medications and healthy lifestyle practices.\u003c/p\u003e\u003cp\u003eThe current study was conducted as part of a needs assessment investigation in preparation for the Caribbean and South America Team-based Strategy to Control Hypertension (CATCH) Study. The CATCH Study is a National Institutes of Health (NIH) supported cluster randomized trial to test the implementation and effectiveness outcomes of implementing and scaling up a team-based care strategy for blood pressure (BP) control in Colombia and Jamaica. In this paper we examine associations between socioeconomic status, food insecurity and adherence to healthy lifestyle behaviours and antihypertensive medications among patients with hypertension in both settings.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eParticipants and Study Procedures\u003c/h2\u003e\u003cp\u003eThe design of this cross-sectional study has been previously described [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Between August 2021 and February 2022, 576 patients with hypertension were enrolled and completed an interviewer-administered questionnaire in Colombia and Jamaica (See Supplement 1 for the full questionnaire). In Colombia, patients with hypertension were randomly selected from four primary care clinics using an electronic medical records database. In Jamaica, consecutive patients with hypertension from 10 primary care clinics were selected on the days they visited the clinic. Due to the COVID-19 pandemic, all interviews were conducted by trained research assistants by phone.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasurements\u003c/h3\u003e\n\u003cp\u003eThe survey gathered information on demographic characteristics (sex, age, education, employment, and marital status), geographic location (country of residence and urban/rural setting), and health status (comorbidities, use of antihypertensive medications, age at hypertension diagnosis). Data were also collected on health care financing, food insecurity, adherence to antihypertensive medications, lifestyle factors, and the impact of COVID-19 on their health and care. Multimorbidity was defined as the co-occurrence of \u0026ge;\u0026thinsp;2 self-reported chronic conditions (diabetes, high cholesterol, depression, anxiety, kidney disease, stroke, heart attack/heart disease, overweight/obesity) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Health care financing was categorized as follows: Insurance (Insurance by employer or private insurance purchased by participant or spouse), self-financed (out-of-pocket or family/friends), government (government subsidy or program) and charity.\u003c/p\u003e\n\u003ch3\u003eSocioeconomic status\u003c/h3\u003e\n\u003cp\u003eSocioeconomic status was measured using education attainment and employment status. To classify education participants were asked \u003cem\u003e\u0026ldquo;What is your highest level of education\u0026rdquo;\u003c/em\u003e and patients classified as having less than high school, high school and more than high school education. For employment status participants were asked \u0026ldquo;Are you currently working including self-employment\u0026rdquo;. There were then classified into two categories \u0026ndash; employed/retired vs. other (which included students, housewives, unemployed and disabled persons).\u003c/p\u003e\n\u003ch3\u003eFood insecurity\u003c/h3\u003e\n\u003cp\u003eFood insecurity was assessed by two questions from the USDA food security instrument: \u003cem\u003e\u0026ldquo;The food that we bought just didn't last, and we didn't have money to get more\u0026rdquo;\u003c/em\u003e and \u003cem\u003e\u0026ldquo;We couldn't afford to eat healthy meals with more fruits and vegetables\u0026rdquo;\u003c/em\u003e [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Persons were classified as food insecure if they responded \u0026ldquo;true most of the time\u0026rdquo; or \u0026ldquo;true some of the time\u0026rdquo; to either of these two questions.\u003c/p\u003e\n\u003ch3\u003eLifestyle and Medication Adherence\u003c/h3\u003e\n\u003cp\u003eLifestyle adherence was scored on a 6-point scale where 1 point was assigned for each of the following: currently eating less salt, exercising regularly, eating adequate amounts of fruit (at least 2 servings daily), vegetables (at least 3 servings daily). Points were assigned for alcohol moderation with reduction of intake receiving one point and complete abstinence from alcoholic beverages receiving 2 points. Lifestyle adherence was grouped as unfavourable (score\u0026thinsp;\u0026le;\u0026thinsp;3) or favourable (score 4\u0026ndash;6).\u003c/p\u003e\u003cp\u003eMedication adherence was based on the Implementation of Multifaceted Patient-Centred Treatment Strategies for Intensive Blood Pressure Control medication adherence scoring system (IMPACTS-MAS) which used 2 questions: \u0026ldquo;\u003cem\u003eOver the last 7 days, on how many days did you not take any blood pressure pills?\u003c/em\u003e\u0026rdquo; where points ranged between 0 (if no medications were taken for 7 days) and 4 (if all medications were taken for 7 days) and \u0026ldquo;\u003cem\u003eOver the last 7 days, on how many days did you cut back (or not take the full dose) of your blood pressure pills?\u003c/em\u003e\u0026rdquo; where points ranged between 0 (if no medications were taken for 7 days) and 2 (if all medications were taken for 7 days). The sum of the responses to both questions were calculated and patients were classified as having high (6 points), medium (5 or 5.5 points) and low (\u0026lt;\u0026thinsp;5 points) medication adherence [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eCOVID-19 impact\u003c/h2\u003e\u003cp\u003eGiven that the survey was conducted during the COVID-19 pandemic, we also sought to assess the impact of the pandemic restrictions on healthcare access. COVID-19 impact was determined based on responses to the question: \u003cem\u003e\u0026ldquo;Were you not able to see a doctor or get prescription medications due to any of the following reasons \u0026ndash; a) pharmacy, hospital or clinics closed; b) less time to see a doctor or get medications due to curfew restrictions; c) fear of contracting coronavirus if you leave the house\u0026rdquo;\u003c/em\u003e. After assigning \u0026ldquo;1\u0026rdquo; point to each \u0026ldquo;yes\u0026rdquo; response, a total score was used to categorize COVID-19 impact as minimal (score\u0026thinsp;=\u0026thinsp;0), moderate (score\u0026thinsp;=\u0026thinsp;1 to 2), and substantial COVID-19 impact (score\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample Size\u003c/h3\u003e\n\u003cp\u003eUsing PASS 15 (NCSS, LLC) software based on assumption of stratification by sex and urban/rural status, a minimum sample of 288 participants per country was calculated to detect a 20% response proportion with a 95% confidence interval from 10%-30%.\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAnalyses were done using SAS 9.4 (SAS Institute, Cary, NC). Frequency tables with percentages were generated and descriptive analyses used for the baseline population by food insecurity status. Mean and standard deviation were reported for continuous variables. Data were weighted based on distribution of age groups, sex, and residential areas within the respective target population of each country as assessed from clinic registers. In analyses that included participants from both countries, combined weights were applied. Sample sizes and frequency numbers are unweighted but means standard deviations (SDs) and percentages are weighted. Wald Chi-square test (or Fisher\u0026rsquo;s exact test for sparse data) was performed for differences between categorical variables, and Student\u0026rsquo;s t-test was used for differences between continuous variables, comparing Colombia and Jamaica.\u003c/p\u003e\u003cp\u003eBivariate analyses were done to explore associations between socioeconomic status and food insecurity with variables of interest including medication adherence and lifestyle practice score. The outcomes were dichotomized \u0026ndash; medication adherence high vs. medium/low and lifestyle adherence \u0026ndash; favourable vs. unfavourable. Using a p-value level of \u0026le;\u0026thinsp;0.2 from the bivariate models, logistic regression was used to build the final multivariable model. For medication adherence, we adjusted for age, sex (male vs. female), country, marital status (married/common law vs. not married/common law) and health care financing (having private health insurance vs not). For favourable lifestyle, we adjusted for age, sex (male vs. female), marital status (married/common law vs not married/common law), multimorbidity (having 2 or more vs. 0\u0026ndash;1 chronic illnesses) and COVID-19 impact (minimal vs moderate and substantial).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThere were 576 participants (288 Colombia, 288 Jamaica) in this study, of which 31.5% were male. The Colombian participants were older than their counterparts from Jamaica (mean age 66.5 years vs. 62.5 years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and were more likely to be in a married/common law relationship (58.9% vs. 40.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Higher education levels were observed in Colombia, where more participants achieved \u0026ldquo;more than high school\u0026rdquo; education (30.3% vs. 17.2%, p\u0026thinsp;=\u0026thinsp;0.01), while Jamaicans had higher employment/retiree levels (76.1% vs. 64.0%, p\u0026thinsp;=\u0026thinsp;0.01) compared to Colombians (Supplement 2: Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Colombian participants had a shorter mean duration of hypertension compared to their counterparts in Jamaica (11.1 years vs. 16.5 years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and had a lower percentage with multimorbidity though the difference was not statistically significant (39.2% vs. 49.5%, p\u0026thinsp;=\u0026thinsp;0.05). In Colombia, private insurance was the main source of health care financing (88.3%) while government subsidy, meaning government, self, family friends and or charity was the primary source in Jamaica 92.4%), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Colombians had lower levels of food insecurity (64.6% vs. 89.0% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but greater proportion with higher medication adherence scores (88.2% vs 50.7% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and favourable lifestyle adherence 86.2% vs. 47.2% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). (Supplement 2).\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eFood Insecurity\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e describes the characteristics of participants of the study stratified by level of food insecurity. Overall, 440 (76.1%) of the participants were food insecure where the mean age and sex distribution of those who were food insecure compared to those who were food secure was similar. As education level increased food insecurity prevalence decreased (less than high school 42.2%, high school 39.4%, more than high school 18.3%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Food insecure compared to food secure participants were also more likely to have no private insurance (58.5% vs. 21.3% P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), low/medium medication adherence scores (34.1% vs. 14.3% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and unfavourable adherence to favourable lifestyle practices (38.3% vs. 12.4% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eCharacteristics of Study Participants by Food Insecurity Status*\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFood Insecure\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;440\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFood Secure \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;136\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value for group difference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic Characteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e, \u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64.8\u0026nbsp;(11.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.5\u0026nbsp;(11.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.845\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.663\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\u003e198 (30.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76 (33.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003e242 (69.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (66.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCountry\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eColombia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e180 (45.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108 (78.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJamaica\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e260 (54.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLocation\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e211 (65.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79 (76.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229 (34.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57 (24.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation Level\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than High school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e185 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (24.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e182 (39.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than High school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73 (18.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61 (42.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.176\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployed/Retiree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e298 (67.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e113 (76.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e142 (32.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (23.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMultimorbidity\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.093\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes (\u0026ge;\u0026thinsp;2 conditions)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e211 (46.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (35.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229 (53.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78 (64.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealthcare financing\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrivate Insurance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e158 (41.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108 (78.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo private insurance***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e282 (58.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (21.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMedication adherence Score\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow/medium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e156 (34.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e276 (65.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e109 (85.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLifestyle Factors\u003c/b\u003e, \u003cb\u003en (%)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat less salt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e423 (96.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e131 (97.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.389\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExercising regularly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e216 (44.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e97 (68.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDecrease/don\u0026rsquo;t consume alcohol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e435 (98.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (98.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.999\u0026dagger;\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat\u0026thinsp;\u0026ge;\u0026thinsp;2 servings of fruits\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e177 (44.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87 (62.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat\u0026thinsp;\u0026ge;\u0026thinsp;3 servings of vegetables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e151 (36.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93 (65.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLifestyle adherence\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnfavourable (\u0026le;\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e174 (38.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (12.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFavourable (4\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e266 (61.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e114 (87.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCovid \u0026minus;\u0026thinsp;19 Impact\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMinimal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e291 (65.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 (28.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate/ Substantial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e149 (34.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92 (71.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e* The sample sizes and actual frequency numbers are unweighted but means (SDs) or percentages are weighted.\u003c/p\u003e\u003cp\u003e** unemployed, housewife, students, disabled\u003c/p\u003e\u003cp\u003e*** no private insurance- meaning government, self, family friends and charity\u003c/p\u003e\u003cp\u003e\u0026dagger; Fisher's exact test\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=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eSocioeconomic Status\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows food insecurity, lifestyle practices and self-reported medication adherence stratified by educational attainment. We found that higher education was associated with less food insecurity. For example, 84.7% of those who had less than high school education was food insecure compared to 57.8% of those who had more than high school education (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, medication adherence and lifestyle adherence scores were not significantly associated with education levels. We found that 28.5% participants with less that high school education compared to 27.7% with more than high school education had low/medium adherence (p\u0026thinsp;=\u0026thinsp;0.817) and 34.8% participants with less that high school education compared to 22.7% with more than high school education had an unfavourable lifestyle adherence score (p\u0026thinsp;=\u0026thinsp;0.067). (Supplement 2: Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e: Baseline Characteristics Stratified by Education Level)\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\u003eFood insecurity, Medication and Lifestyle Adherence of Study Participants by Socioeconomic Status as measured by Educational Attainment*\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLess than High School \u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;215)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh School \u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;227)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMore than High School\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;134)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value for Group Difference\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\u003eFood Insecurity\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes (Insecurity)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e185 (84.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e182 (79.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (57.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo (Security)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (15.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45 (21.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMedication Adherence Score\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.817\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow/medium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62 (28.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78 (31.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (27.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e148 (71.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e146 (68.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91 (72.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLifestyle Factors\u003c/b\u003e, \u003cb\u003en (%)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat less salt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e209 (96.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e215 (96.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e130 (98.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.577\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExercising regularly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e120 (49.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e111 (44.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82 (59.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDecrease/don\u0026rsquo;t consume alcohol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e212 (97.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e225 (99.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e132 (98.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.533\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat\u0026thinsp;\u0026ge;\u0026thinsp;2 servings of fruits\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e91 (44.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98 (48.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75 (55.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.286\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat at \u0026ge;\u0026thinsp;3 servings of vegetables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80 (39.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91 (41.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (53.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLifestyle adherence\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnfavourable (\u0026le;\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72 (34.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88 (35.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (22.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFavourable (4\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e143 (65.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e139 (64.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98 (77.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e* The sample sizes and actual frequency numbers are unweighted but means (SDs) or percentages are weighted.\u003c/p\u003e\u003cp\u003e\u0026dagger; Fisher's exact test\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the characteristics of participants of the study stratified by employment status. We found no significant associations between employment status and food insecurity, medication adherence and lifestyle adherence. (Supplement 2: Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e: Baseline Characteristics Stratified by Employment Status)\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\u003eFood Insecurity, Medication and Lifestyle Adherence of Study Participants by Employment Status*\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed/Retiree\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;411)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOther**\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;165)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value for Group Difference\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\u003eFood Insecurity\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.176\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes (Insecurity)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e298 (73.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e142 (81.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo (Security)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e113 (26.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (18.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMedication Adherence Score\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.088\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow/medium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e138 (31.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41 (23.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e265 (68.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120 (76.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLifestyle Factors\u003c/b\u003e, \u003cb\u003en (%)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat less salt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e394 (96.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160 (97.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.743\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExercising regularly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e237 (52.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76 (44.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.163\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDecrease/don\u0026rsquo;t consume alcohol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e406 (98.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e163 (98.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.999\u0026dagger;\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat\u0026thinsp;\u0026ge;\u0026thinsp;2 servings of fruits\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e191 (47.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73 (51.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.545\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEat\u0026thinsp;\u0026ge;\u0026thinsp;3 servings of vegetables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e166 (37.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78 (56.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLifestyle adherence\u003c/b\u003e, \u003cb\u003en (%)\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\u003cp\u003e0.097\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnfavourable (\u0026le;\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e145 (34.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51 (26.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFavourable (4\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e266 (65.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e114 (73.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e* The sample sizes and actual frequency numbers are unweighted but means (SDs) or percentages are weighted.\u003c/p\u003e\u003cp\u003e** unemployed, housewife, students, disabled\u003c/p\u003e\u003cp\u003e\u0026dagger; Fisher's exact test\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the associations between education, employment and food insecurity and unfavourable lifestyle adherence. In unadjusted models, those with a high school education had almost two times the odds of unfavourable lifestyle scores compared to those with more than a high school education (OR: 1.9, 95%CI:1.0, 3.4, p\u0026thinsp;=\u0026thinsp;0.041). Participants who were food insecure had 4 times the odds of having unfavourable lifestyle adherence (OR: 4.4, 95% CI: 2.2, 9.0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This remained significant in the fully adjusted model that included age, sex, country, marital status, multi-morbidity and COVID-19 impact (OR: 2.4, 95% CI:1.1, 5.2, p\u0026thinsp;=\u0026thinsp;0.028).\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\u003eCrude and Adjusted odds Ratios exploring the Association between Education, Employment, Food Insecurity and Unfavorable Lifestyle*#\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCrude Odds Ratio\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAdjusted Odds Ratio*\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.9 (1.0, 3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.4 (0.8, 2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.258\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.8 (1.0, 3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.4 (0.7, 2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.366\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployed/Retired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther **\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.7 (0.4, 1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.8 (0.5, 1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFood Insecurity\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsecure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.4 (2.2, 9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.4 (1.1, 5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.028\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e*Final model: age, sex, country, marital status, multimorbidity and covid impact\u003c/p\u003e\u003cp\u003e# Favourable lifestyle was the outcome variable.\u003c/p\u003e\u003cp\u003e** unemployed, housewife, student, disabled\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows results for the associations between education, employment and food insecurity and antihypertensive medication adherence. In the unadjusted model, those who were food insecure had 3 times the odds of poor medication adherence compared to those that were food secure (OR: 3.1, 95% CI:1.7, 5.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This effect was attenuated after adjusting for age, sex, country, marital status, multimorbidity and COVID impact (Adjusted OR: 1.9, 95% CI: 1.0, 3.7, p\u0026thinsp;=\u0026thinsp;0.072). There were no associations between education or employment and medication adherence in adjusted and unadjusted models.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCrude and Adjusted Odds Ratios exploring the Association Between Education, Employment, Food Insecurity and Antihypertensive Medication Adherence*#\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCrude Odds Ratio\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.2 (0.7, 2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.8 (0.4, 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.529\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.0 (0.6, 1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.882\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.8 (0.4, 1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.519\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployed/retired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther **\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.7 (0.4, 1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.7 (0.4, 1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.248\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFood Insecurity\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsecure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.1 (1.7, 5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.9 (1.0, 3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e*Final model: adjusted for age, sex, country, marital status and healthcare expenses\u003c/p\u003e\u003cp\u003e#Favourable lifestyle was the outcome variable\u003c/p\u003e\u003cp\u003e** unemployed, housewife, student, disabled\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"},{"header":"Discussion","content":"\u003cp\u003eIn this study of patients with hypertension who were being treated at primary care clinics in Colombia and Jamaica, high levels of food insecurity were recorded in both countries. Food insecurity but not socioeconomic status was associated with poor adherence to recommended lifestyle practices and poor medication adherence, although the association with medication adherence was attenuated and no longer significant after adjustment for potential confounding variables. This association between food insecurity and favourable lifestyle was not fully explained by other socioeconomic factors or the country in which participants lived.\u003c/p\u003e\u003cp\u003eLatin America and the Caribbean has achieved the millennium development goal target of reducing the number of people suffering from hunger [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, the COVID-19 pandemic, climate change and natural disasters, global political instability and increases in the cost of living have led to increasing food insecurity globally [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In 2022 FAO reported that the levels of food insecurity in LAC were 37.5% compared to the world estimate of 29.6%. The prevalence of moderate or severe food insecurity in South America was 37.5% and 60.6% in the Caribbean [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe prevalence of food insecurity in Colombia reported in this study (65%) was similar to the 66% noted in a previous national report [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, in Jamaica we found a higher level of food insecurity (89%) than was previously reported (25\u0026ndash;75%) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These differences may be attributed to the study population (older persons with hypertension), the composite score used and the timing of the study. We did not identify studies that explored food insecurity in patients with hypertension from LAC. It is possible that the costs of managing blood pressure would pose an additional strain and contribute to the higher prevalence of food insecurity that we observed [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In addition, the study was conducted during the COVID-19 pandemic. Studies confirm that all four food insecurity dimensions (availability, accessibility, usability and sustainability) were compromised resulting in substantial price increases of healthy foods during the pandemic [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn our survey, food insecurity was based on 2 of the 6 items in the six-item short form of the USDA food security instrument: the ability to purchase sufficient food or purchase healthy foods in our study [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Other elements of food insecurity in the USDA food security instrument include cutting meal size and intake, feeling hungry but not being able to eat, and the frequency with which these disruptions occur. It is possible that variations in food security in surveys are due to variations in the data collection tools. Nevertheless, food insecurity is consistently high reinforcing the urgent need for effective strategies.\u003c/p\u003e\u003cp\u003eWe found a possible association between food insecurity and medication adherence, which is in keeping with the published literature [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The methods for recognizing medication adherence, and the instruments used to measure adherence in other studies have varied widely. We used the IMPACTS-MAS scoring system [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] which was not used in the previous studies conducted in Jamaica or Colombia. A 2021 meta-analysis showed that food insecurity decreased the odds of medication adherence by 44% [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Like our findings, other employment status (i.e. unemployed, housewife, student, disabled)and less education did not have a significant association with medication adherence. Cost-related underuse and medication restricting behaviours are some issues that have been identified in other studies examining the relationship between food insecurity and adherence [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] .\u003c/p\u003e\u003cp\u003eFew studies report on lifestyle adherence in LAC, and the evaluation of lifestyle adherence is a complex construct. There are different combinations of measures when lifestyle adherence is reported in the literature. It is most frequently reported by a combination of dietary adherence (eating less salt), physical activity, medication adherence, weight management, smoking cessation and alcohol moderation. The lifestyle adherence score created for this study was comprehensive and took into account the individual components (eating less salt, exercising regularly, decreasing alcohol consumption or didn't drink, eating adequate (at least 2 servings daily) fruits and adequate (at least 3 servings daily) vegetables) of the score.\u003c/p\u003e\u003cp\u003eWe found that food insecurity decreased the odds of favourable lifestyle. Other studies have shown that food insecurity is inversely associated with favourable lifestyle factors including physical activity, diet, alcohol use and sleep quality[\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. For example, Kehoe et al showed that food insecurity affected the diet quality of young women in South Africa [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Alcohol abuse/dependence was associated with an increased odds of food insecurity among homeless men and women in the USA ((OR\u0026thinsp;=\u0026thinsp;2.72, CI.\u003csub\u003e95\u003c/sub\u003e = 1.55, 4.77) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. For physical activity, authors hypothesize that external factors such as employment and long work hours of low-income food-insecure households may contribute to less physical activity [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Similarly, violence in communities may restrict physical activity for food insecure families. Of note, both Jamaica and Colombia have high homicide rates. Further studies in Jamaica and Colombia are needed to better understand the complex relationship between food insecurity and maintaining a healthy lifestyle.\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and Limitations\u003c/h2\u003e\u003cp\u003eThis study adds to the body of literature on lifestyle practices and determinants of BP control in two different countries in LAC, which has a high burden of CVD. The recruitment of participants from two countries with different health systems and cultural practices provides information on the possible role of food insecurity in BP control and possible targets for programmes to reduce the burden of hypertension.\u003c/p\u003e\u003cp\u003eOne limitation is that other measures of SES and SDOH were not included in this study. Additionally, we relied on self-reported adherence to medication and healthy lifestyle, which may have resulted in reporting bias and misclassification of the outcomes. Information bias and misclassification could also have occurred due to the composite scores used for classification of lifestyle practices, medication adherence and food insecurity. The lifestyle adherence score was created for this study and, although validated in other populations, the instrument used to assess medication adherence (IMPACTS-MAS) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] has not been previously used in Colombia or Jamaica. For food insecurity, only the first two (of six) questions of the modified USDA food security instrument were used. Structural and cultural factors such as policies and cultural practices are possible confounders or effect modifiers that were not captured in this study. Additionally, data collection occurred during the COVID-19 pandemic which had an impact on both food insecurity and lifestyle adherence with impacts differing between countries [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Therefore, these findings may not reflect the usual practices.\u003c/p\u003e\u003cp\u003eFinally, it would have been useful to determine levels of food security (mild, moderate and severe) and their impact on medication adherence and favourable lifestyle. This may be explored in future studies.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePersons with hypertension who were food insecure had an increased odds of unfavourable lifestyle practices and were twice as likely to have poor medication adherence. This study provides valuable insight into the complex interplay between socioeconomic factors including food insecurity and hypertension control in Colombia and Jamaica. Consistently taking medications and making healthy lifestyle choices are necessary to maintain good health and slow progression of chronic diseases. Given the high prevalence of food insecurity and its role in lifestyle and medication adherence, our findings suggest that public health policies, programmes and multi-sectoral strategies are urgently needed if we are to effectively prevent and control hypertension in LAC.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAHA American Heart Association\u003c/p\u003e\n\u003cp\u003eASS-15 Adaptive Significance Scale \u0026ndash; 15 item version\u003c/p\u003e\n\u003cp\u003eBP Blood pressure\u003c/p\u003e\n\u003cp\u003eCATCH Caribbean and south America Team-Based Strategy to Control Hypertension\u003c/p\u003e\n\u003cp\u003eCOVID-19 Corona Virus Diseases 2019\u003c/p\u003e\n\u003cp\u003eCVDs Cardiovascular Diseases\u003c/p\u003e\n\u003cp\u003eDALYs Disability-adjusted Life Years \u003c/p\u003e\n\u003cp\u003eFAO Food and Agriculture Organisation of the United Nations\u003c/p\u003e\n\u003cp\u003eFIES Food Insecurity Experience Scale\u003c/p\u003e\n\u003cp\u003eIMPACTS-MAS Implementation of Multifaceted Patient-Centred Treatment Strategies for Intensive Blood Pressure Control medication adherence scoring system.\u003c/p\u003e\n\u003cp\u003eLAC Latin America and the Caribbean\u003c/p\u003e\n\u003cp\u003eLMICs Low- and Middle-Income Countries\u003c/p\u003e\n\u003cp\u003eNCDs Non-communicable diseases\u003c/p\u003e\n\u003cp\u003ePAHO Pan American Health Organisation\u003c/p\u003e\n\u003cp\u003eSD Standard Deviations\u003c/p\u003e\n\u003cp\u003eSDOH Social determinants of health\u003c/p\u003e\n\u003cp\u003eUSDA United States Department of Agriculture.\u003c/p\u003e\n\u003cp\u003eWHO World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eEthical approval was granted by Institutional Review Board of Tulane University (12 August 2022; 2022-980, Institutional Bioethics Committee of Universidad de Santander in Colombia (16 July 2020; VII-050-BUC), the Mona Campus Research Ethics Committee of the University of the West Indies (30\u003csup\u003e\u0026nbsp;\u003c/sup\u003eJune 2020; ECP 232 19/20), and the Ministry of Health and Wellness Advisory Panel on Ethics and Medico-Legal Affairs (26 April 2021; SRD/ETH/20).\u003c/p\u003e\n\u003cp\u003eConduct of this study adhered to the principles outlined in the Declaration of Helsinki and written informed consent was obtained from all participants included in this study.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no financial and non-financial competing interests\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study was funded by the National Institutes of Health (Ref# 1 UG3 HL152373-01). The views expressed are those of the authors and do not necessarily reflect those of the funding body\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNB\u003c/strong\u003e \u0026ndash; Conception and design of the study, analysis and interpretation of data, drafted and revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJD\u003c/strong\u003e \u0026ndash; \u0026nbsp; Conception and design of the study, analysis and interpretation of data, drafted and revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSG\u003c/strong\u003e \u0026ndash; Analysis and interpretation of the data, revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMC\u003c/strong\u003e \u0026ndash; Reviewed the manuscript and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKM\u003c/strong\u003e \u0026ndash; Conception and design, interpretation of data, revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePW\u003c/strong\u003e \u0026ndash; Conception and design, interpretation of data, drafted and revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAB\u003c/strong\u003e \u0026ndash; Conception and design, interpretation of data, revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAA\u003c/strong\u003e \u0026ndash; Conception and design, revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePL\u003c/strong\u003e \u0026ndash; Conception and design, interpretation of data, revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePLJ\u003c/strong\u003e \u0026ndash; Conception and design, interpretation of data, revised the manuscript, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTF\u003c/strong\u003e \u0026ndash; Conception and design, interpretation of data, drafted and revised the manuscript, and approved the submitted version\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMTR\u003c/strong\u003e \u0026ndash; Conception and design, interpretation of data, drafted and revised the manuscript, and approved the submitted version\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors thank Carene Lindsay, Zulma Urbina, Diego Ortega and Gustavo\u003csup\u003e\u0026nbsp;\u003c/sup\u003eAroca-Martinez for their assistance with participant recruitment and, data collection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; information (optional)\u003cbr\u003e \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNoncommunicable diseases. 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Six-Item Short Form Economic Research Service, USDA [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ers.usda.gov/sites/default/files/_laserfiche/DataFiles/50764/short2024.pdf]\u003c/span\u003e\u003cspan address=\"https://www.ers.usda.gov/sites/default/files/_laserfiche/DataFiles/50764/short2024.pdf]\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAllouch F, Peacock E, Mills KT, Whelton PK, Chen J, He J. A Novel Two-Question Antihypertensive Medication Adherence Scale Predicts Blood Pressure Control and Cardiovascular Disease Outcomes. In.: AHA Journals; 2023.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFood Security in Latin America and the Caribbean, Factsheet. [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.iadb.org/en/news/food-security-latin-america-and-caribbean]\u003c/span\u003e\u003cspan address=\"https://www.iadb.org/en/news/food-security-latin-america-and-caribbean]\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eColombia sees a. modest improvement in food security but half of the population remains exposed to climatic and economic risks [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.wfp.org/news/colombia-sees-modest-improvement-food-security-half-population-remains-exposed-climatic-and?form=MG0AV3]\u003c/span\u003e\u003cspan address=\"https://www.wfp.org/news/colombia-sees-modest-improvement-food-security-half-population-remains-exposed-climatic-and?form=MG0AV3]\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGOAL 2 End hunger. achieve food security and improved nutrition and promote sustainable agriculture [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.pioj.gov.jm/wp-content/uploads/2022/10/VNR_Goal_2.pdf?form=MG0AV3]\u003c/span\u003e\u003cspan address=\"https://www.pioj.gov.jm/wp-content/uploads/2022/10/VNR_Goal_2.pdf?form=MG0AV3]\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJamaica JM. Prevalence of Severe Food Insecurity in the Population: % of population [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ceicdata.com/en/jamaica/social-health-statistics/jm-prevalence-of-severe-food-insecurity-in-the-population--of-population?form=MG0AV3]\u003c/span\u003e\u003cspan address=\"https://www.ceicdata.com/en/jamaica/social-health-statistics/jm-prevalence-of-severe-food-insecurity-in-the-population--of-population?form=MG0AV3]\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKostova D, Spencer G, Moran AE, Cobb LK, Husain MJ, Datta BK, Matsushita K, Nugent R. The cost-effectiveness of hypertension management in low-income and middle-income countries: a review. BMJ Glob Health 2020, 5(9).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGebeyehu DT, East L, Wark S, Islam MS. A systematic review of the direct and indirect COVID-19's impact on food security and its dimensions: pre-and post-comparative analysis. BMC Public Health. 2023;23(1):2298.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMen F, Gundersen C, Urquia ML, Tarasuk V. Prescription medication nonadherence associated with food insecurity: a population-based cross-sectional study. CMAJ Open. 2019;7(3):E590\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilder ME, Kulie P, Jensen C, Levett P, Blanchard J, Dominguez LW, Portela M, Srivastava A, Li Y, McCarthy ML. The Impact of Social Determinants of Health on Medication Adherence: a Systematic Review and Meta-analysis. J Gen Intern Med. 2021;36(5):1359\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcClintock HF, Imel BE. Food insecurity and medication restricting behavior among persons with diabetes in the United States. Nutr Health. 2024;30(2):341\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHerman D, Afulani P, Coleman-Jensen A, Harrison GG. Food Insecurity and Cost-Related Medication Underuse Among Nonelderly Adults in a Nationally Representative Sample. Am J Public Health. 2015;105(10):e48\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTheodoridis X, Grammatikopoulou MG, Gkiouras K, Papadopoulou SE, Agorastou T, Gkika I, Maraki MI, Dardavessis T, Chourdakis M. Food insecurity and Mediterranean diet adherence among Greek university students. Nutr metabolism Cardiovasc diseases: NMCD. 2018;28(5):477\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWitkowiak MM, Idris AN, Sato A, Sacre H, Haddad C, Rizk R, Malaeb D, Strahler J, Salameh P, Ierodiakonou D. Food insecurity and lifestyle behaviours in university students amidst the COVID-19 pandemic: a comparative survey across three countries. BMC Public Health. 2024;24(1):3571.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReitzel LR, Chinamuthevi S, Daundasekara SS, Hernandez DC, Chen TA, Harkara Y, Obasi EM, Kendzor DE, Businelle MS. Association of Problematic Alcohol Use and Food Insecurity among Homeless Men and Women. Int J Environ Res Public Health 2020, 17(10).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKehoe SH, Wrottesley SV, Ware L, Prioreschi A, Draper C, Ward K, Lye S, Norris SA. Food insecurity, diet quality and body composition: data from the Healthy Life Trajectories Initiative (HeLTI) pilot survey in urban Soweto, South Africa. Public Health Nutr. 2021;24(7):1629\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTo QG, Frongillo EA, Gallegos D, Moore JB. Household food insecurity is associated with less physical activity among children and adults in the U.S. population. J Nutr. 2014;144(11):1797\u0026ndash;802.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeck J, Koebach A, Abreu L, Regassa MD, Hoeffler A, Stojetz W, Br\u0026uuml;ck T. COVID-19 Pandemic and Food Insecurity Fuel the Mental Health Crisis in Africa. Int J public health 2024, 68.\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":false,"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":"socioeconomic status, food insecurity, hypertension, medication adherence, lifestyle, Latin America and the Caribbean","lastPublishedDoi":"10.21203/rs.3.rs-8135598/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8135598/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAdherence to medications and healthy lifestyles are important health behaviours for hypertension control and may be influenced by food insecurity and socioeconomic status (SES). We examined associations between food insecurity and SES with medication adherence and healthy lifestyle practices among patients with hypertension in Colombia and Jamaica.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eIn a cross-sectional survey of hypertensive patients attending primary health centres in Colombia and Jamaica we collected self-reported demographic, education and employment information. Food insecurity was measured using two questions from the modified United States Department of Agriculture (USDA) food security instrument \u0026ndash; was there sufficient money for 1) weekly food purchases and 2) healthy foods. Medication adherence was classified as high vs. low/medium using the IMPACTS-MAS questionnaire. Healthy lifestyle was scored using a 6-point scale as unfavourable (score\u0026thinsp;\u0026le;\u0026thinsp;3) or favourable (score 4\u0026ndash;6), 1 point each for eating less salt, exercising regularly, consuming\u0026thinsp;\u0026ge;\u0026thinsp;2 servings fruits and \u0026ge;\u0026thinsp;3 servings vegetables daily, and reduced alcohol consumption or 2 points for abstinence. Multivariable logistic regression with medication adherence categories and lifestyle practice scores as dependent variables assessed associations with food insecurity and SES.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf 576 participants (Colombia 288; Jamaica 288), Colombians were older (66.5 years vs. 62.5 years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), had higher education attainment and were less likely to be employed/retired. Colombians had less food insecurity (64.6% vs. 89.0% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher medication adherence (88.2% vs 50.7% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and more favourable lifestyle practices (86.2% vs. 47.2% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Food insecurity in both countries was inversely related to education, having private health insurance, high medication adherence and healthy lifestyle practices. In multivariable models, food insecurity was associated with increased odds of unfavourable lifestyle practice scores, (OR\u0026thinsp;=\u0026thinsp;2.4; 95% CI: 1.1, 5.2 p\u0026thinsp;=\u0026thinsp;0.028) and poor medication adherence (OR\u0026thinsp;=\u0026thinsp;1.9; 95% CI: (1.0, 3.7) p\u0026thinsp;=\u0026thinsp;0.072), after adjusting for age, sex, country, marital status, education and employment and having\u0026thinsp;\u0026ge;\u0026thinsp;2 chronic illnesses. No associations with the other SES examined.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eFood insecure hypertensive patients had increased odds of unfavourable lifestyle practices and were twice as likely to have poor medication adherence. Strategies to address food insecurity may have a positive impact on hypertension control in low resource settings.\u003c/p\u003e","manuscriptTitle":"Food insecurity impacts healthy lifestyle practices and medication adherence among persons with hypertension in Colombia and Jamaica: Findings from a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-09 13:25:59","doi":"10.21203/rs.3.rs-8135598/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-26T15:08:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-24T17:46:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-21T22:13:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-19T13:16:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-16T23:52:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"131744584525081111793881862066039242548","date":"2025-12-16T01:00:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213279208741071109076892096011224069484","date":"2025-12-15T17:34:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-14T19:39:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120807513478185254092426375918395175202","date":"2025-12-13T20:17:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"130181764996278708401589429724816513023","date":"2025-12-11T22:33:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197892976341258787929113311369901921711","date":"2025-12-11T01:01:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298731138233605455968348589517481017705","date":"2025-12-08T14:05:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37335776814080026131518238087266809205","date":"2025-12-08T11:43:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-08T07:43:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-08T07:39:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-28T19:03:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-26T13:46:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-11-26T13:39:09+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":"7adfd203-5483-4591-b5fe-a014cd245d15","owner":[],"postedDate":"December 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T05:08:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-09 13:25:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8135598","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8135598","identity":"rs-8135598","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}