Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States

Shiwani Mahajan; Javier Valero-Elizondo; Rohan Khera; Nihar R. Desai; Ron Blankstein; Michael J. Blaha; Salim S. Virani; Bita A. Kash; William A. Zoghbi; Harlan M. Krumholz; Khurram Nasir

doi:10.1001/jamanetworkopen.2019.17885

Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States

Mahajan, Shiwani; Valero-Elizondo, Javier; Khera, Rohan; Desai, Nihar R.; Blankstein, Ron; Blaha, Michael J.; Virani, Salim S.; Kash, Bita A.; Zoghbi, William A.; Krumholz, Harlan M.; Nasir, Khurram 2019-12-18 00:00:00 Key Points Question What are the prevalence and IMPORTANCE Prompt recognition of myocardial infarction symptoms is critical for timely access to characteristics of adults in the United lifesaving emergency cardiac care. However, patients with myocardial infarction continue to have a States who remain unaware of the delayed presentation to the hospital. symptoms of and the appropriate response to a myocardial infarction? OBJECTIVE To understand the variation and disparities in awareness of myocardial infarction Findings In this cross-sectional study of symptoms among adults in the United States. 25 271 US adults, 5.8% were not aware of any myocardial infarction symptoms, DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study used data from the 2017 and 4.5% chose a different response National Health Interview Survey among adult residents of the United States, assessing awareness of than calling emergency medical services the 5 following common myocardial infarction symptoms among different sociodemographic in response to these symptoms. These subgroups: (1) chest pain or discomfort, (2) shortness of breath, (3) pain or discomfort in arms or numbers were substantially higher in shoulders, (4) feeling weak, lightheaded, or faint, and (5) jaw, neck, or back pain. The response to a certain sociodemographic groups. perceived myocardial infarction (ie, calling emergency medical services vs other) was also assessed. Meaning Many individuals in the United MAIN OUTCOMES AND MEASURES Prevalence and characteristics of individuals who were States remain unaware of the symptoms unaware of myocardial infarction symptoms and/or chose not to call emergency medical services in of and appropriate response to a response to these symptoms. myocardial infarction. RESULTS Among 25 271 individuals (13 820 women [51.6%; 95% CI, 50.8%-52.4%]; 17 910 Supplemental content non-Hispanic white individuals [69.9%; 95% CI, 68.2%-71.6%]; and 21 826 individuals [82.7%; 95% CI, 81.5%-83.8%] born in the United States), 23 383 (91.8%; 95% CI, 91.0%-92.6%) considered chest Author affiliations and article information are listed at the end of this article. pain or discomfort a symptom of myocardial infarction; 22 158 (87.0%; 95% CI, 86.1%-87.8%) considered shortness of breath a symptom; 22 064 (85.7%; 95% CI, 84.8%-86.5%) considered pain or discomfort in arm a symptom; 19 760 (77.0%; 95% CI, 76.1%-77.9%) considered feeling weak, lightheaded, or faint a symptom; and 16 567 (62.6%; 95% CI, 61.6%-63.7%) considered jaw, neck, or back pain a symptom. Overall, 14 075 adults (53.0%; 95% CI, 51.9%-54.1%) were aware of all 5 symptoms, whereas 4698 (20.3%; 95% CI, 19.4%-21.3%) were not aware of the 3 most common symptoms and 1295 (5.8%; 95% CI, 5.2%-6.4%) were not aware of any symptoms. Not being aware of any symptoms was associated with male sex (odds ratio [OR], 1.23; 95% CI, 1.05-1.44; P = .01), Hispanic ethnicity (OR, 1.89; 95% CI, 1.47-2.43; P < .001), not having been born in the United States (OR, 1.85; 95% CI, 1.47-2.33; P < .001), and having a lower education level (OR, 1.31; 95% CI, 1.09-1.58; P = .004). Among 294 non-Hispanic black or Hispanic individuals who were not born in the United States, belonged to the low-income or lowest-income subgroup, were uninsured, and had a lower education level, 61 (17.9%; 95% CI, 13.3%-23.6%) were not aware of any symptoms. This group had 6-fold higher odds of not being aware of any symptoms (OR, 6.34; 95% CI, 3.92-10.26; P < .001) compared with individuals without these characteristics. Overall, 1130 individuals (4.5%; 95% CI, 4.0%-5.0%) chose a different response than calling emergency medical services in response to a myocardial infarction. (continued) Open Access. This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 1/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States Abstract (continued) CONCLUSIONS AND RELEVANCE Many adults in the United States remain unaware of the symptoms of and appropriate response to a myocardial infarction. In this study, several sociodemographic subgroups were associated with a higher risk of not being aware. They may benefit the most from targeted public health initiatives. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 Introduction Although mortality rates among patients hospitalized for myocardial infarction (MI) have seen a decreasing trend, patients with MI continue to have a delayed presentation to the hospital, and a 1,2 large number of them die before reaching the hospital. A critical aspect of lowering mortality associated with MI is ensuring timely access to lifesaving emergency cardiac care, for which prompt recognition of symptoms of a myocardial infarction (MI) and appropriate rapid emergency response are crucial. Previous studies from the United States have shown that, although awareness of MI symptoms has increased over the years, less than 50% of adults are aware of the 5 common symptoms (ie, chest pain or discomfort; shortness of breath; pain or discomfort in arms or shoulders; feeling weak, 4-8 lightheaded, or faint; and jaw, neck, or back pain). Although Healthy People 2020 set targets to improve awareness of these common symptoms, there is little information on the prevalence and characteristics of individuals who are not aware of any symptoms. Additionally, previous studies on MI symptom awareness have focused on disparities across limited demographic subgroups (eg, age, sex, and race/ethnicity); however, the association of sociocultural factors (eg, education level, socioeconomic status [SES], insurance status, and immigration status) and the cumulative 4,10 association of these potential risk factors with awareness remains largely unknown. Given that previous community interventions to improve awareness of symptoms and 11-14 emergency medical service (EMS) use in MI have largely been unsuccessful, this information can help identify subgroups that are most in need of and may benefit from targeted public health awareness initiatives, which can subsequently reduce mortality and morbidity attributable to MI. Accordingly, we used nationally representative data to estimate awareness of MI symptoms among adults in the United States, characterizing sociodemographic groups, both individually and in combination, that were particularly at risk of not being aware of any symptoms. Methods Study Design and Population We included 26 742 individuals aged 18 years and older, using data from the 2017 National Health Interview Survey (NHIS), which is an annual, cross-sectional, national, weighted survey that provides estimates on the noninstitutionalized US population using multistage sampling. Additional details of the NHIS survey are provided in the eMethods in the Supplement. We excluded 1471 participants because of missing information on awareness of MI symptoms (eFigure 1 in the Supplement). This study was exempt from review by the Yale University institutional review board committee because NHIS data are publicly available and deidentified. The study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Awareness of MI Symptoms Awareness was assessed by an individual’s responses to the question, “Which of the following would you say are the symptoms that someone may be having a heart attack?”: (1) chest pain or discomfort; (2) shortness of breath; (3) pain or discomfort in arms or shoulders; (4) feeling weak, lightheaded, JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 2/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States or faint; and (5) jaw, neck, or back pain. We studied responses individually, then divided them into 4 mutually exclusive subgroups based on the number of symptoms an individual was aware of, as follows: (1) none of the symptoms, (2) 1 to 2 symptoms, (3) 3 to 4 symptoms, and (4) all 5 symptoms. We also assessed the awareness of the 3 most common symptoms (ie, chest pain or discomfort; shortness of breath; and pain or discomfort in arms or shoulders) separately. Response to a Perceived MI We assessed the prevalence of adults who were aware of the need to access immediate emergency care by calling EMS in response to a perceived MI by their response to the question, “What is best thing to do when someone is having a heart attack?” Responses included call 9-1-1 or another emergency number, advise them to drive to the hospital, advise them to call their physician, call spouse or family member, and other. We studied all responses individually, then dichotomized the responses to calling 9-1-1 or another emergency number vs all other options. Independent Variables Other variables included in this study were age (ie, 18-39 years, 40-64 years, or65 years), sex (ie, male or female), race/ethnicity (ie, non-Hispanic white, non-Hispanic black, or Hispanic), SES (based on family income as a percentage of the federal poverty limit from the US Census Bureau and classified as high income [400%], middle income [200% to <400%], low income [125% to <200%], and lowest income [<125%]), education level (ie,some college orhigh school), insurance status (ie, public, private, or uninsured), geographic region (ie, Northeast, Midwest, South, or West), and immigration status (based on geographic place of birth and classified as US-born or non-US-born). For non-US-born individuals, we also collected information on their time in the United States (ie, <10 years vs10 years) and English proficiency (ie, speaks English well or very well vs does not speak English well or at all). English proficiency was measured directly, and in cases where the interviewee did not speak English well (<1.5%), a proxy was used to answer the survey questions. Statistical Analysis The NHIS uses complex sampling techniques to select the sample. After adjusting for nonresponse, age, sex, and race/ethnicity (based on the population estimates produced by the US Census Bureau), final person-level weights are created, which can then be used to provide national estimates. We described the survey-weighted proportions (with Rao-Scott χ ) of awareness for each of the 5 symptoms individually, the distribution of overall awareness (from 0 to 5), and the awareness of the 3 most common symptoms across different sociodemographic characteristics. Next, we assessed the association of these characteristics with not being aware of any MI symptoms using unadjusted and adjusted survey-specific logistic regression and multinomial regression models. Logistic regression was used to evaluate dichotomous outcome variables (eg, being aware of none vs any MI symptoms), while multinomial regression was used to study categorical outcome variables (eg, being aware of 0 vs 1 vs 2 vs 3 vs 4 vs all 5 MI symptoms). Explanatory variables included age, sex, race/ ethnicity, immigration status, education level, SES, insurance status, and region. We also created a composite score using race/ethnicity (non-Hispanic white vs non-Hispanic black and Hispanic), immigration status (US-born vs non-US-born), education level (some college vshigh school), SES (high or middle income vs low or lowest income), and insurance status (insured vs uninsured) to study the cumulative association of these factors with awareness of MI symptoms. We also assessed the proportion of individuals who chose a different response than calling EMS as a reaction to a perceived MI, both overall and by awareness of MI symptoms. We identified individual characteristics associated with not calling EMS in response to a MI, using unadjusted and adjusted survey-specific logistic regression models. We considered P < .05 statistically significant a priori for all analyses in our study, and all tests were 2-tailed. All analyses were performed using Stata version 13.0 (StataCorp) and accounted for JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 3/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States the survey design of the NHIS, including sampling weights, to ensure that our results were nationally representative. Results Population Characteristics Our study population included 25 271 individuals corresponding to more than 233.4 million adults in 2017; 13 820 (51.6%; 95% CI, 50.8%-52.4%) were women; 17 910 (69.9%; 95% CI, 68.2%-71.6%) were non-Hispanic white individuals; and 21 826 (82.7%; 95% CI, 81.5%-83.8%) were born in the United States (Table 1). A total of 7446 participants (28.3%; 95% CI, 27.0%-29.8%), representing an estimated 62.1 million individuals, were part of the low- or lowest-income subgroup, and 8683 participants (35.2%; 95% CI, 34.1%-36.3%), representing an estimated 81.8 million individuals, had an education level of high school or less. Most individuals had private insurance (12 745 [55.9%; 95% CI, 54.8%-57.0%]), followed by public insurance (10 274 [34.4%; 95% CI, 33.4%-35.4%]) and no insurance (2173 [9.7%; 95% CI, 9.1%-10.4%]). Table 1. Characteristics of Study Participants Estimated US Population, No. Characteristic No. (N = 25 271) Weighted % (95% CI) (N = 233 427 109) Age, y 18-39 8198 38.46 (37.51-39.41) 89 771 938 40-64 10 304 41.90 (41.03-42.78) 97 811 097 ≥65 6769 19.64 (19.01-20.29) 45 844 074 Sex Men 11 451 48.43 (47.65-49.22) 113 053 335 Women 13 820 51.57 (50.78-52.35) 120 373 774 Race/ethnicity Non-Hispanic white 17 910 69.93 (68.18-71.62) 151 775 038 Non-Hispanic black 2782 13.11 (12.04-14.25) 28 445 310 Hispanic 3010 16.97 (15.52-18.51) 36 822 570 Immigration status US-born 21 826 82.70 (81.51-83.83) 192 932 915 Non-US-born 3428 17.30 (16.17-18.49) 40 361 715 Education ≥Some college 16 517 64.84 (63.71-65.95) 150 806 910 ≤High school 8683 35.16 (34.05-36.29) 81 780 160 Family income subgroup High 9604 43.14 (41.85-44.44) 94 485 977 Middle 6737 28.48 (27.64-29.34) 62 370 753 Low 4218 16.72 (16.02-17.45) 36 621 219 Lowest 3228 11.65 (10.95-12.39) 25 522 093 Insurance Private 12 745 55.89 (54.83-56.95) 129 835 329 Public 10 274 34.38 (33.39-35.38) 79 855 830 Uninsured 2173 9.73 (9.09-10.40) 22 593 891 Region Northeast 4103 18.36 (16.80-20.03) 42 860 199 Midwest 6036 21.92 (20.71-23.17) 51 159 938 South 9366 36.42 (34.40-38.49) 85 010 955 West 5766 23.30 (21.59-25.10) 54 396 017 JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 4/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States Awareness of MI Symptoms In this nationally representative adult population, most individuals (23 383 [91.8%; 95% CI, 91.0%- 92.6%]) considered chest pain or discomfort a MI symptom, followed by shortness of breath (22 158 [87.0%; 95% CI, 86.1%-87.8%]), pain or discomfort in arms or shoulders (22 064 [85.7%; 95% CI, 84.8%-86.5%]), feeling weak, lightheaded, or faint (19 760 [77.0%; 95% CI, 76.1%-77.9%]), and jaw, neck, or back pain (16 567 [62.6%; 95% CI, 61.6%-63.7%]) (eTable 1 in the Supplement). Awareness of symptoms was significantly higher among individuals who were non-Hispanic white, born in the United States, had higher education levels, belonged to the high-income or middle-income subgroup, and had private insurance compared with individuals who were non-Hispanic black or Hispanic, were not born in the United States, had lower education levels, belonged to the low-income or lowest-income subgroup, and were uninsured (eTable 1 in the Supplement). For example, 16 959 of all non-Hispanic white participants (94.4%; 95% CI, 93.5%-95.1%) were aware that chest pain or discomfort is a symptom of MI, while 2529 of all Hispanic participants (84.8%; 95% CI, 83.0%-86.4%) were aware of this symptom; more individuals in the high-income subgroup than those in the lowest-income subgroup were aware that jaw, neck, or back pain is a symptom of MI (6694 [67.1%; 95% CI, 65.6%-68.5%] vs 1853 [55.3%; 95% CI, 52.7%-57.8%]) (eTable 1 in the Supplement). Overall, 14 075 individuals (53.0%; 95% CI, 51.9%-54.1%), representing 123.7 million adults, were aware of all 5 MI symptoms, whereas 4698 (20.3%; 95% CI, 19.4%-21.3%), representing 47.5 million adults, were not aware of the 3 most common symptoms and 1295 (5.8%; 95% CI, 5.2%-6.4%), representing 13.5 million adults, were not aware of any symptoms (eTable 2 and eTable 3 in the Supplement). Awareness of different numbers of MI symptoms (ranging from 0-5) varied substantially across sociodemographic subgroups (eFigure 2 in the Supplement). The proportion of individuals not aware of any of the symptoms was higher among non-Hispanic black and Hispanic individuals than non-Hispanic white individuals (164 [6.6%; 95% CI, 5.3%-8.2%] and 331 [10.5%; 95% CI, 9.1%-12.0%] vs 653 [4.0%; 95% CI, 3.4%-4.7%]; P < .001), among individuals not born in the United States than those born in the United States (418 [11.9%; 95% CI, 10.5%-13.4%] vs 877 [4.5%; 95% CI, 3.9%-5.2%]; P < .001), among individuals with lower education levels than those with higher education levels (623 [8.1%; 95% CI, 7.2%-9.0%] vs 667 [4.5%; 95% CI, 3.9%-5.3%]; P < .001), among individuals belonging to the low-income and lowest-income subgroups than those belonging to the high-income and middle-income subgroups (222 [8.1%; 95% CI, 6.8%-9.5%] and 285 [7.8%; 95% CI, 6.7%-9.0%] vs 339 [4.0%; 95% CI, 3.3%-4.8%] and 334 [5.8%; 95% CI, 4.9%-6.8%]; P < .001), among individuals with no insurance than those with public and private insurance (211 [9.9%; 95% CI, 8.4%-11.8%] vs 534 [6.0%; 95% CI, 5.3%-6.8%] and 547 [4.9%; 95% CI, 4.2%-5.8%]; P < .001), and among individuals living in the South than those living in the Midwest (588 [7.0%; 95% CI, 5.7%-8.5%] vs 245 [4.4%; 95% CI, 3.6%-5.5%]; P < .001) (eFigure 3 in the Supplement). The proportion of individuals who were not aware of the 3 most common symptoms was higher across similar subgroups (eg, Hispanic vs non-Hispanic white individuals, 936 [31.7%; 95% CI, 29.4%-34.0%] vs 2541 [14.8%; 95% CI, 13.9%-15.7%]; P < .001; non-US-born vs US-born individuals, 1227 [36.4%; 95% CI, 34.2%-38.7%] vs 3469 [17.0%; 95% CI, 16.1%-17.9%]; P < .001; lowest-income vs high-income subgroup, 879 [29.4%; 95% CI, 26.9%-32.1%] vs 1325 [15.3%; 95% CI, 14.2%-16.5%]; P < .001) (eTable 3 in the Supplement). In a subanalysis among individuals not born in the United States, we found that those who did not have good English proficiency were less likely to be aware of all 5 symptoms than those who had good English proficiency (298 [95% CI, 34.6%; 30.4%-39.1%] vs 1072 [40.2%; 95% CI, 37.6%-42.9%]; P < .001), and those who had been in the United States for less than 10 years were less likely to be aware of all 5 symptoms than those had been in the United States for 10 or more years (199 [29.4%; 95% CI, 25.1%-34.2%] vs 1137 [40.5%; 95% CI, 37.8%-43.2%]; P < .001). Similarly, those who did not have good English proficiency were more likely than those who had good English proficiency to be aware of none of the symptoms (185 [19.6%; 95% CI, 16.4%-23.2%] vs 233 [9.1%; 95% CI, 7.7%-10.7%]; P < .001), and those who had been in the United States for less than 10 years JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 5/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States were more likely than those who had been in the United States for 10 or more years to be aware of none of the symptoms (98 [14.8%; 95% CI, 11.5%-18.7%] vs 315 [11.2%; 95% CI, 9.8%-12.8%]; P < .001) (eFigure 4 in the Supplement). Sociodemographic Characteristics Associated With Lack of Awareness Overall, several individual characteristics were associated with not being aware of any MI symptoms (Figure 1). In an unadjusted model, we found that higher odds of not being aware of any symptoms were associated with black race (odds ratio [OR], 1.71; 95% CI, 1.30-2.24; P < .001) and Hispanic ethnicity (OR, 2.83; 95% CI, 2.28-3.50; P < .001) compared with non-Hispanic white race/ethnicity, Figure 1. Unadjusted and Risk-Adjusted Associations of Sociodemographic Characteristics With Not Being Aware of Any Symptoms of a Myocardial Infarction Favors Favors OR Characteristic (95% CI) Awareness No Awareness Aged 40-64 y vs ≥65 y Unadjusted 1.05 (0.90-1.23) Adjusted 0.91 (0.70-1.19) Aged 18-39 y vs ≥65 y Unadjusted 1.14 (0.96-1.36) Adjusted 0.98 (0.72-1.33) Men vs women Unadjusted 1.15 (0.99-1.33) Adjusted 1.23 (1.05-1.44) Non-Hispanic black vs non-Hispanic white Unadjusted 1.71 (1.30-2.24) Adjusted 1.36 (0.98-1.90) Hispanic vs non-Hispanic white Unadjusted 2.83 (2.28-3.50) Adjusted 1.89 (1.47-2.43) Non-US born vs US born Unadjusted 2.86 (2.39-3.41) Adjusted 1.85 (1.47-2.33) Education ≤ high school vs ≥ some college Unadjusted 1.84 (1.57-2.15) Adjusted 1.31 (1.09-1.58) Lowest-income subgroup vs high-income subgroup Unadjusted 2.12 (1.65-2.73) Adjusted 1.29 (0.96-1.74) Low-income subgroup vs high-income subgroup Unadjusted 2.03 (1.62-2.55) Adjusted 1.35 (1.02-1.77) Middle-income subgroup vs high-income subgroup Unadjusted 1.49 (1.20-1.83) Adjusted 1.19 (0.96-1.48) Uninsured vs private insurance Unadjusted 2.13 (1.67-2.71) Adjusted 1.26 (0.97-1.64) Public insurance vs private insurance Unadjusted 1.23 (1.03-1.47) Adjusted 1.09 (0.82-1.46) Northeast vs Midwest Unadjusted 1.23 (0.90-1.68) Adjusted 1.01 (0.72-1.42) South vs Midwest Unadjusted 1.62 (1.18-2.21) Adjusted 1.20 (0.85-1.69) West vs Midwest Unadjusted 1.23 (0.92-1.66) Adjusted 0.81 (0.58-1.13) Results show odds ratios (ORs) with 95% CI calculated 0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 using logistic regression. Adjusted model includes all Odds Ratio (95% CI) variables presented in the figure. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 6/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States not having been born in the United States (OR, 2.86; 95% CI, 2.39-3.41; P < .001) compared with being born in the United States, lower education levels (OR, 1.84; 95% CI, 1.57-2.15; P < .001) compared with higher education levels, the low-income (OR, 2.03; 95% CI, 1.62-2.55; P < .001) or lowest-income (OR, 2.12; 95% CI, 1.65-2.73; P < .001) subgroup compared with the highest-income subgroup, public (OR, 1.23; 95% CI, 1.03-1.47; P = .02) or no (OR, 2.13; 95% CI, 1.67-2.71; P < .001) insurance compared with private insurance, and living in the South (OR, 1.62; 95% CI, 1.18-2.21; P = .003) compared with living in the Midwest. When we adjusted for known confounders, we found that higher odds of not being aware of any symptoms were associated with male sex (OR, 1.23; 95% CI, 1.05-1.44; P = .01) compared with female sex, Hispanic ethnicity (OR, 1.89; 95% CI, 1.47-2.43; P < .001) compared with non-Hispanic white race/ethnicity, not being born in the United States (OR, 1.85; 95% CI, 1.47-2.33; P < .001) compared with being born in the United States, and lower education levels (OR, 1.31; 95% CI, 1.09-1.58; P = .004) compared with higher education levels (Figure 1). Using multinomial regression (adjusting for the statistically significant factors from the previous logistic regression), we found that there was a stepwise higher likelihood of not being aware as the aggregate number of symptoms grew. For example, compared with individuals born in the United States, those not born in the United States were 30% (relative risk ratio [RRR], 0.70; 95% CI, 0.53- 0.93; P = .01) less likely to be aware of 3 symptoms, 52% (RRR, 0.48; 95% CI, 0.37-0.62; P < .001) less likely to be aware of 4 symptoms, and 54% (RRR, 0.46; 95% CI, 0.36-0.58; P < .001) less likely to be aware of 5 symptoms of a MI compared with being aware of no symptoms. Similar trends in association were seen across other subgroups (eg, individuals with lower education levels had RRRs of 0.73 [95% CI, 0.61-0.89; P = .001] for being aware of 4 symptoms and 0.68 [95% CI, 0.56-0.82; P < .001] for being aware of 5 symptoms) (eTable 4 in the Supplement). Cumulative Association of Sociodemographic Factors With Awareness We evaluated 5 variables (ie, race/ethnicity, immigration status, education, income, and insurance status) associated with the greatest risk of not being aware of any MI symptoms and examined their combined association with awareness. Compared with the reference group with no high-risk characteristics (8793 white and US-born individuals who belonged to the middle-income or high- income subgroup, had insurance, and had a higher education level), those with 1, 2, 3, 4, and 5 high- risk characteristics had a stepwise decrease in awareness (Figure 2). Among 294 individuals with all 5 high-risk characteristics (representing 3.7 million adults in the United States), 88 (29.8%; 95% CI, 23.6%-36.8%) were aware of all 5 symptoms, compared with 5688 (62.9%; 95% CI, 61.5%-64.4%) in the reference group. Moreover, 61 individuals (17.9%; 95% CI, 13.3%-23.6%) with all 5 high-risk characteristics (representing approximately 664 143 adults) were not aware of a single MI symptom compared with 253 individuals (3.3%; 95% CI, 2.6%-4.0%) in the reference group (Figure 2). Using logistic regression analysis, we found that, compared with the reference group, those with all 5 high- risk characteristics had more than 6-fold higher odds of not being aware of any symptoms (OR, 6.34; 95% CI, 3.92-10.26; P < .001) (Table 2). Response to a Perceived MI Overall, 1130 individuals (4.5%; 95% CI, 4.0%-5.0%), representing 10.4 million adults, chose a different response than calling EMS in response to a perceived MI (eTable 5 in the Supplement). The proportion was significantly higher among individuals who were 65 years or older than among those who were aged 18 to 39 years (410 [5.8%] vs 285 [4.0%]; P = .001), men than women (540 [4.9%] vs 590 [4.1%]; P = .02), those who were not born in the United States than those who were born in the United States (197 [5.9%] vs 933 [4.2%]; P = .005), those who had a lower education level than those with a higher education level (455 [5.5%] vs 671 [3.9%]; P = .001), those belonging to the low-income and lowest-income subgroups than those belonging to the middle-income or highest- income subgroups (386 [11.3%] vs 653 [7.9%]; P < .001), and those with no insurance than those with private insurance (125 [6.8%] vs 436 [3.5%]; P < .001) (eTable 6 in the Supplement). In analysis JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 7/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States using logistic regression, being 65 years or older (OR, 1.63; 95% CI, 1.22-2.19; P = .001) and uninsured (OR, 1.59; 95% CI, 1.19-2.12; P = .001) had the strongest associations with not calling EMS in response to a perceived MI compared with being younger than 65 years and having private insurance, respectively (eTable 7 in the Supplement). In assessing response to a MI by awareness of MI symptoms, we found that 115 adults (9.8%; 95% CI, 7.7%-12.4%) among those who were not aware of any symptoms (representing 1.3 million individuals) chose a different response than calling EMS, compared with 538 adults (3.4%; 95% CI, 3.1%-3.9%) among those who were aware of all 5 symptoms of a MI (representing approximately 4.3 million adults) (eTable 8 in the Supplement). These differences were consistently seen across all sociodemographic subgroups. For example, among individuals with an education level of high school or less who were aware of none of the symptoms, 69 (12.0%; 95% CI, 8.9%-15.8%) chose a different response than calling EMS compared with 176 (3.6%; 95% CI, 3.0%-4.4%) individuals with an education level of high school or less who were aware of all 5 symptoms (P < .001). Among individuals who belonged to the low-income or lowest-income subgroup and were aware of none of Figure 2. Proportion of Individuals Aware of Different Number of Myocardial Infarction Symptoms by Number of High-Risk Characteristics A Aware of all 5 symptoms of myocardial infarction B Aware of 3 to 4 symptoms of myocardial infarction 80 80 60 60 40 40 20 20 0 0 0 1 2 3 4 5 0 1 2 3 4 5 High-risk Characteristics, No. High-risk Characteristics, No. C Aware of 1 to 2 symptoms of myocardial infarction D Aware of none of the symptoms of myocardial infarction 25 25 20 20 15 15 10 10 High-risk characteristics include non-Hispanic black or 5 5 Hispanic race/ethnicity, non-US-born immigrant status, low-income or lowest-income subgroup, 0 0 0 1 2 3 4 5 0 1 2 3 4 5 uninsured, and high school or lower education level. High-risk Characteristics, No. High-risk Characteristics, No. Error bars indicate 95% CIs. Table 2. Odds of Not Being Aware of Any Myocardial Infarction Symptoms Based on the Number of High-Risk Characteristics Unadjusted Model Adjusted Model High-Risk Characteristic, No. OR (95% CI) P Value OR (95% CI) P Value 0 1 [Reference] NA 1 [Reference] NA Abbreviations: NA, not applicable; OR, odds ratio. 1 1.34 (1.07-1.69) .01 1.33 (1.06-1.68) .01 High-risk characteristics include non-Hispanic black 2 1.79 (1.37-2.33) <.001 1.75 (1.33-2.31) <.001 or Hispanic race/ethnicity, non-US-born immigrant 3 2.76 (2.02-3.76) <.001 2.69 (1.96-3.70) <.001 status, low-income or lowest-income subgroup, 4 5.94 (4.31-8.19) <.001 5.89 (4.23-8.21) <.001 uninsured, and high school or lower education level. 5 6.46 (4.13-10.10) <.001 6.34 (3.92-10.26) <.001 Model adjusted for age, sex, and region. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 8/15 Proportion, % Proportion, % Proportion, % Proportion, % JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States the symptoms, 55 (12.5%; 95% CI, 9.2%-16.8%) chose a different response than calling EMS compared with 155 (4.2%; 95% CI, 3.4%-5.1%) who belonged to the low-income or lowest-income subgroups and were aware of all 5 symptoms (P < .001) (Figure 3). Discussion In this nationally representative cross-sectional study, we found that nearly 6% of individuals, or an estimated 13.5 million adults nationally, were not aware of a single symptom of a MI and nearly 1 in 12 individuals, or an estimated 19.1 million adults nationally, did not consider chest pain or discomfort a MI symptom. These numbers were substantially higher for individuals who were non-Hispanic black or Hispanic, were not born in the United States, had lower education levels, were uninsured, and belonged to the low-income and lowest-income subgroups. Among individuals having all these characteristics, 1 in 5 were not aware of any symptom of a MI. Moreover, nearly 4.5% of individuals, or an estimated 10.4 million adults nationally, chose a different response than immediately calling EMS on suspicion of a MI, and this proportion was more than double (9.8%) among adults who were not aware of any MI symptoms. Our study extends the previous literature on awareness of MI symptoms in several ways. First, most previous studies describing the awareness of MI symptoms have focused on individuals who 4,6,8,16,17 were aware of all 5 symptoms. However, we focused on individuals who were not aware of any or the most common symptoms and identified subgroups that were most in need of and may benefit the most from targeted public health awareness initiatives. Studies have reported a 10.1% Figure 3. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to a Perceived Myocardial Infarction, by Sociodemographic Characteristics and Awareness of Myocardial Infarction Symptoms Aware of none of the symptoms Aware of all 5 symptoms of myocardial infarction A Age B Sex C Race/ethnicity 25 25 25 20 20 20 15 15 15 10 10 10 5 5 5 0 0 0 18-39 40-64 ≥65 Men Women White Black Hispanic Age, y Sex Race/Ethnicity D Education level E Family income F Insurance 25 25 25 20 20 20 15 15 15 10 10 10 5 5 5 0 0 0 ≥Some College ≤High School High/Middle Low/Lowest Private Public Uninsured Education Level Income Level Insurance Type Error bars indicate 95% CIs. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 9/15 Proportion, % Proportion, % Proportion, % Proportion, % Proportion, % Proportion, % JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States increase in awareness of all 5 symptoms between 2008 and 2014, with 47.2% adults in the United States being aware of all 5 symptoms in 2014. Our results not only showed a small increase in awareness of all 5 symptoms since 2014 but also suggest that, even today, millions of individuals in the United States remain unaware of the most critical symptoms of a MI (eg, chest pain) and, therefore, are at a high risk of adverse outcomes after an MI. Second, to our knowledge, this study is the first to describe awareness rates across such diverse sociodemographic subgroups based on SES, insurance status, and immigration status. We found significant disparities across subgroups based on age, race/ethnicity, and education level, which were 4,10,16,18,19 consistent with previous reports on awareness and, additionally, identified non-US-born individuals, uninsured individuals, and individuals from the low-income and lowest-income subgroups as high-risk subgroups for not being aware of any symptoms. Third, to our knowledge, this is the first report studying the awareness of MI symptoms among immigrants and describing the association of acculturation factors (eg, English proficiency and duration of US residence) with awareness. We found that nearly 1 in 8 (12%) of the estimated 5 million non-US-born individuals were not aware of any symptoms and that acculturation factors had a significant association with awareness among immigrants. Given the increasing number of individuals in the United States who were born in other countries and the low symptom awareness rates among these individuals, public health professionals may need to tailor awareness campaigns according to these individuals’ linguistic and cultural needs. Fourth, to our knowledge, our study is the first to describe the cumulative association of the potential high-risk characteristics (ie, non-Hispanic black or Hispanic race/ethnicity, non-US-born, low income, uninsured, lower education level) with awareness. We reported a stepwise increase in the proportion of individuals who were not aware of any MI symptoms as the number of these high- risk characteristics increased. Among individuals with all 5 high-risk characteristics, nearly 1 in 5 individuals were not aware of any of the symptoms. As such, our findings underscore the importance of targeting public health initiatives toward these socioeconomically disadvantaged groups to improve awareness and subsequently reduce the mortality associated with MI. Finally, our assessment of the use of EMS in response to a perceived MI suggests that, although the use of EMS has increased from that previously reported in the literature (91.8% in 2008 and 93.4% in 2014), millions of individuals continued to choose a different response than immediately calling EMS. As expected, individuals who were unaware of the symptoms were also more likely to not call EMS; however, a significant number of adults with optimal symptom awareness also chose to not call EMS. Some possible explanations for this could be denial of symptoms, misattribution to symptoms to a noncardiac cause, perceived loss of control and ability to act, self-treatment 4,10,21-23 strategies, fear or embarrassment of being wrong, and concerns about cost. Given that early intervention in patients with MI is crucial to limit ischemic damage, prompt recognition of MI symptoms and rapid decision to seek care can reduce delays from symptom-onset to hospital presentation and improve survival. As such, it is critical to not only improve awareness of warning signs of a MI and the importance of early access to medical care but also to better understand and address the barriers that prevent individuals from accessing emergency medical care. The American Heart Association, the US Department of Health and Human Services, the National Heart, Lung, and Blood Institute, and the US Centers for Disease Control and Prevention have made substantial efforts to improve awareness of MI symptoms, such as the Go Red for Women and Go Red Por Tu Corazon (ie, Go Red for your Heart, which targets Spanish-speaking women), 24-28 Make the Call, Don’t Miss a Beat, The Heart Truth, and WISEWOMAN campaigns, respectively. While most of these initiatives are directed to women, our study found a nearly 10% higher awareness of all 5 MI symptoms and better use of EMS among women than men, which could be a reflection of the successful reach of these campaigns, although efforts to increase awareness of cardiovascular disease among women are still warranted. Disparities in awareness and response to MI symptoms found in our study corresponded closely 30-35 with the disparities seen in delays in hospital presentation and outcomes after MI. Racial and JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 10/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States ethnic minorities have been shown to have longer delay times than non-Hispanic white individuals. Similarly, individuals with lower SES and greater financial concerns have been shown to have a delayed presentation to the hospital, although this could be related to issues with access to care. It has been shown that focusing on the seriousness of the situation and increasing awareness among 4,36,37 specific population subgroups could be useful in reducing prehospital delays. As such, recognizing the subgroups that are at the highest risk of being unaware of MI symptoms is germane to the current debate regarding diminishing treatment delays for individuals experiencing a MI and can help better design health care policies and/or campaigns specifically tailored for them. Limitations This study has limitations. First, our assessment of awareness of MI symptoms was based on an arbitrary list, and while the most prevalent symptoms were listed, presentation of a MI may not be limited to these symptoms. Nevertheless, we showed that millions of individuals were unaware of even these most common symptoms of a MI. Second, not all MI symptoms included in this study should be weighted equally because some symptoms (eg, chest pain or discomfort) may be more easily identifiable than others. Therefore, although we provided the distribution of awareness of all MI symptoms and a composite score, we chose to focus our analyses on those who were not aware of any symptoms. Third, our assessment of MI symptom awareness was based on a set of closed- ended questions (ie, yes or no) that may bias responses, and offering of a set of symptoms could have led to an overestimation of the awareness rates. As such, the actual awareness rates may be even lower than those reported in our study. Fourth, although we studied and adjusted for the most important sociodemographic variables, MI awareness can inherently be driven by personal or familial exposure, which we were not able to assess because NHIS does not include this information. Fifth, because of the low sample size of Asian and other racial/ethnic groups, we could evaluate disparities only among the non-Hispanic white, non-Hispanic black, and Hispanic subgroups. Sixth, we could have overestimated the proportion of individuals choosing to call the EMS in response to a perceived MI because of a social desirability bias in responding; survey respondents may tend to answer questions in a manner that will be viewed favorably by the interviewer. Despite that, millions of individuals chose a different response than immediately calling EMS and could benefit from increasing awareness regarding the importance of early access to medical care. Conclusions Our study found that 53% of US adults in this study, representing 123.7 million adults in the United States, were aware of all 5 MI symptoms, and nearly 6% of individuals in our study, or an estimated 13.5 million adults nationally, were not aware of a single symptom of a MI. Additionally, significant sociodemographic disparities were seen in both the awareness of and appropriate response to MI symptoms. These findings highlight the need for targeted educational campaigns to not only improve awareness of MI symptoms but also emphasize the importance of early access to emergency medical care across all sociodemographic subgroups. ARTICLE INFORMATION Accepted for Publication: October 29, 2019. Published: December 18, 2019. doi:10.1001/jamanetworkopen.2019.17885 Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Mahajan S et al. JAMA Network Open. Corresponding Author: Khurram Nasir, MD, MPH, MSc, Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart and Vascular Center, 6550 Fannin St, Ste 1801, Houston, TX 77030 (knasir@ houstonmethodist.org). JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 11/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States Author Affiliations: Center for Outcomes Research and Evaluation, Yale New Haven Health, New Haven, Connecticut (Mahajan, Desai, Krumholz); Section of Cardiovascular Medicine, Department of Medicine, Yale School of Medicine, New Haven, Connecticut (Mahajan, Desai, Krumholz); Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart and Vascular Center, Houston, Texas (Valero-Elizondo, Zoghbi, Nasir); Center for Outcomes Research, Houston Methodist Research Institute, Houston, Texas (Valero-Elizondo, Kash, Nasir); Division of Cardiology, University of Texas Southwestern Medical Center, Dallas (Khera); Cardiovascular Imaging Program, Cardiovascular Division and Department of Radiology, Brigham and Women’s Hospital, Boston, Massachusetts (Blankstein); The Johns Hopkins Ciccarone Center for Prevention of Cardiovascular Disease, Baltimore, Maryland (Blaha); Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas (Virani); Section of Cardiology, Baylor College of Medicine, Houston, Texas (Virani); Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut (Krumholz). Author Contributions: Drs Mahajan and Nasir had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Mahajan, Valero-Elizondo, Khera, Desai, Virani, Kash, Nasir. Acquisition, analysis, or interpretation of data: Mahajan, Valero-Elizondo, Khera, Blankstein, Blaha, Kash, Zoghbi, Krumholz, Nasir. Drafting of the manuscript: Mahajan, Kash, Nasir. Critical revision of the manuscript for important intellectual content: Mahajan, Valero-Elizondo, Khera, Desai, Blankstein, Blaha, Virani, Zoghbi, Krumholz, Nasir. Statistical analysis: Mahajan, Khera. Administrative, technical, or material support: Mahajan, Khera, Desai, Blaha, Kash, Nasir. Supervision: Valero-Elizondo, Nasir. Conflict of Interest Disclosures: Dr Khera reported receiving grants from the National Heart, Lung, and Blood Institute and the National Center for Advancing Translational Sciences outside the submitted work. Dr Desai reported receiving grants and personal fees from Amgen, Boehringer Ingelheim, and Relypsa; receiving personal fees from Cytokinetics, Novartis, and scPharmaceuticals; having a contract with the Centers for Medicare & Medicaid Services; and receiving funding from Johnson and Johnson and Medtronic outside the submitted work. Dr Blankstein reported receiving grants from Astellas Pharma, Amgen, and Gilead Sciences; serving on the advisory board of Amgen; and consulting for EKOS outside the submitted work. Dr Blaha reported receiving grants from the American Heart Association, Aetna, Amgen, the National Institutes of Health, and the US Food and Drug Administration and serving on the advisory boards of Amgen, Sanofi, Regeneron Pharmaceuticals, Novartis, Novo Nordisk, Bayer, and Akcea Therapeutics outside the submitted work. Dr Virani reported receiving grants from the US Department of Veterans Affairs, Houston Veterans Affairs Health Services Research and Development, the American Heart Association, the American Diabetes Association, and the World Heart Federation and receiving honorarium from the American College of Cardiology for serving as associate editor outside the submitted work. Dr Krumholz reported working under contract with the Centers for Medicare & Medicaid Services to support quality measurement programs; being a recipient of a research grant, through Yale University, from Medtronic and the US Food and Drug Administration to develop methods for postmarket surveillance of medical devices; being a recipient of a research grant with Medtronic and being the recipient of a research grant from Johnson and Johnson, through Yale University, to support clinical trial data sharing; being a recipient of a research agreement, through Yale University, from the Shenzhen Center for Health Information for work to advance intelligent disease prevention and health promotion; collaborating with the National Center for Cardiovascular Diseases in Beijing; receiving payment from the Arnold and Porter Law Firm for work related to the Sanofi clopidogrel litigation, from the Ben C. Martin Law Firm for work related to the Cook Celect IVC filter litigation, and from the Siegfried and Jensen Law Firm for work related to Vioxx litigation; chairing a cardiac scientific advisory board for UnitedHealth; being a participant/participant representative of the IBM Watson Health Life Sciences Board; being a member of the advisory board for Element Science, the advisory board for Facebook, and the physician advisory board for Aetna; and being the cofounder of HugoHealth, a personal health information platform, and of Refactor Health, an enterprise healthcare artificial intelligence–augmented data management company outside the submitted work. No other disclosures were reported. REFERENCES 1. Benjamin EJ, Muntner P, Alonso A, et al; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics—2019 update: a report from the American Heart Association. 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Distribution of Awareness of Myocardial Infarction Symptoms and the Weighted Proportion of Non-US- Born Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms, by English Proficiency and Years in the United States eTable 1. Awareness of Individual Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics eTable 2. Awareness of Symptoms of a Myocardial Infarction (0 to 5), by Sociodemographic Characteristics eTable 3. Proportion of Individuals Who Were Not Aware of the 3 Most Common Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 14/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States eTable 4. Association Between Population Characteristics and Awareness of Myocardial Infarction Symptoms Using Multinomial Regression Analysis eTable 5. Distribution of Different Responses to Assessment of Emergency Response to Suspicion of Myocardial Infarction eTable 6. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics eTable 7. Association of Sociodemographic Characteristics With Choosing a Response Other Than Calling Emergency Medical Services on Suspicion of a Myocardial Infarction Using Logistic Regression eTable 8. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics and Awareness of Myocardial Infarction Symptoms JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 15/15 Supplementary Online Content Mahajan S, Valero-Elizondo J, Khera R, et al. Variation and disparities in awareness of myocardial infarction symptoms among adults in the United States. JAMA Netw Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 eMethods. Brief Description of the Survey Design for the National Health Interview Survey eFigure 1. Selection of Study Participants eFigure 2. Distribution of Awareness of Myocardial Infarction Symptoms by Sociodemographic Characteristics eFigure 3. Weighted Proportion of Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms by Sociodemographic Characteristics eFigure 4. Distribution of Awareness of Myocardial Infarction Symptoms and the Weighted Proportion of Non-US-Born Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms, by English Proficiency and Years in the United States eTable 1. Awareness of Individual Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics eTable 2. Awareness of Symptoms of a Myocardial Infarction (0 to 5), by Sociodemographic Characteristics eTable 3. Proportion of Individuals Who Were Not Aware of the 3 Most Common Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics eTable 4. Association Between Population Characteristics and Awareness of Myocardial Infarction Symptoms Using Multinomial Regression Analysis eTable 5. Distribution of Different Responses to Assessment of Emergency Response to Suspicion of Myocardial Infarction eTable 6. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics eTable 7. Association of Sociodemographic Characteristics With Choosing a Response Other Than Calling Emergency Medical Services on Suspicion of a Myocardial Infarction Using Logistic Regression © 2019 Mahajan S et al. JAMA Network Open. eTable 8. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics and Awareness of Myocardial Infarction Symptoms This supplementary material has been provided by the authors to give readers additional information about their work. © 2019 Mahajan S et al. JAMA Network Open. eMethods. Brief Description of the Survey Design for the National Health Interview Survey National Health Interview Survey (NHIS) is an annual, cross-sectional national weighted survey that provides estimates on the noninstitutionalized US population using multistage sampling. Response rates The participation rates for NHIS are actually very high. The conditional response rate for the Sample Adult component was 80.7%, which was calculated by dividing the number of completed Sample Adult interviews (n=26,742) by the total number of eligible sample adults (n=33,143). Weighting The final Sample Adult Weight includes design, ratio, nonresponse and post-stratification adjustments for sample adults. National estimates of all sample adult variables can be made using these weights. Use of Proxy In the NHIS, sample adults generally respond for themselves, although in a small number of cases, proxy responses are allowed if the selected adult had a physical or mental condition prohibiting him/her from responding. In the case of a proxy, the relationship to the sample adult is obtained. Of the 26,742 adults included in the NHIS in 2017, only in 423 cases or 1.58% cases, a knowledgeable proxy answered for the sample adult. Of these 423 cases, in 367 (87%) cases the proxy was a relative who lived in the same household. Source: National Center for Health Statistics. Survey Description, National Health Interview Survey, 2017. Hyattsville, Maryland. 2018. © 2019 Mahajan S et al. JAMA Network Open. eFigure 1. Selection of Study Participants © 2019 Mahajan S et al. JAMA Network Open. eFigure 2. Distribution of Awareness of Myocardial Infarction Symptoms by Sociodemographic Characteristics Abbreviations: US, United States © 2019 Mahajan S et al. JAMA Network Open. eFigure 3. Weighted Proportion of Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms by Sociodemographic Characteristics Abbreviations: US, United States © 2019 Mahajan S et al. JAMA Network Open. eFigure 4. Distribution of Awareness of Myocardial Infarction Symptoms and the Weighted Proportion of Non-US- Born Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms, by English Proficiency and Years in the United States A. Distribution of awareness of myocardial infarction symptoms among non-US-born individuals. © 2019 Mahajan S et al. JAMA Network Open. B. Weighted proportion of non-US-born individuals who were not aware of any myocardial infarction symptoms. © 2019 Mahajan S et al. JAMA Network Open. eTable 1. Awareness of Individual Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics Chest pain or Pain or discomfort in Feeling weak, Jaw, neck, or back Characteristics Shortness of breath discomfort arm lightheaded, or faint pain No. % Aware No. % Aware No. % Aware No. % Aware No. % Aware aware (95% CI) aware (95% CI) aware (95% CI) aware (95% CI) aware (95% CI) 91.8 (91.0- 87.0 (86.1- 85.7 (84.8- 77.0 (76.1- 62.6 (61.6- Overall 23,383 22,158 22,064 19,760 16,567 92.6) 87.8) 86.5) 77.9) 63.7) Age, y 91.5 (90.4- 86.8 (85.7- 81.1 (79.8- 76.9 (75.5- 53.3 (51.8- 18-39 7,576 7,186 6,780 6,390 4,521 92.5) 87.9) 82.4) 78.2) 54.9) 92.2 (91.3- 87.2 (86.1- 88.3 (87.3- 77.3 (76.1- 66.2 (64.9- 40-64 9,592 9,089 9,248 8,133 7,043 93.1) 88.1) 89.3) 78.5) 67.5) 91.4 (90.3- 86.9 (85.7- 88.9 (87.8- 76.6 (75.1- 73.1 (71.7- 65 6,215 5,883 6,036 5,237 5,003 92.5) 88.0) 90.0) 78.0) 74.6) Sex 91.4 (90.5- 86.1 (85.0- 83.9 (82.7- 75.8 (74.7- 57.6 (56.3- Men 10,562 9,939 9,788 8,799 6,870 92.3) 87.0) 85.0) 76.9) 58.9) 92.1 (91.1- 87.9 (86.9- 87.4 (86.3- 78.1 (77.0- 67.3 (66.1- Women 12,821 12,219 12,276 10,961 9,697 93.0) 88.8) 88.4) 79.2) 68.6) Race/Ethnicity Non-Hispanic 94.4 (93.5- 89.9 (89.0- 90.5 (89.7- 81.4 (80.5- 68.5 (67.4- 16,959 16,153 16,318 14,643 12,582 White 95.1) 90.7) 91.3) 82.3) 69.5) Non-Hispanic 90.5 (88.6- 85.1 (82.9- 79.1 (76.6- 72.0 (69.5- 55.7 (53.1- 2,525 2,364 2,267 1,995 1,591 Black 92.2) 87.0) 81.4) 74.3) 58.2) 84.8 (83.0- 79.5 (77.3- 76.9 (74.8- 66.3 (64.1- 46.8 (44.2- Hispanic 2,529 2,356 2,331 2,000 1,498 86.4) 81.5) 78.9) 68.5) 49.5) Immigration status 93.6 (92.8- 89.1 (88.2- 88.6 (87.8- 79.7 (78.8- 65.4 (64.3- US-born 20,523 19,514 19,573 17,531 14,820 94.4) 89.9) 89.4) 80.6) 66.4) 83.1 (81.4- 77.2 (75.1- 71.6 (69.4- 64.0 (61.7- 49.6 (47.1- Non-US-born 2,843 2,629 2,474 2,217 1,739 84.6) 79.1) 73.7) 66.2) 52.2) Education Some college 93.7 (92.9- 89.0 (88.1- 88.4 (87.5- 80.3 (79.3- 65.4 (64.2- 15,566 14,823 14,774 13,427 11,269 or higher 94.4) 89.8) 89.2) 81.3) 66.6) High school or 88.5 (87.2- 83.3 (82.1- 80.8 (79.3- 71.2 (69.8- 57.8 (56.3- 7,755 7,278 7,233 6,285 5,257 lower 89.6) 84.5) 82.1) 72.5) 59.2) © 2019 Mahajan S et al. JAMA Network Open. eTable 1. Continued. Family income 94.4 (93.4- 90.0 (88.9- 89.7 (88.7- 81.1 (79.8- 67.1 (65.6- High-income 9,124 8,728 8,726 7,905 6,694 95.2) 90.9) 90.6) 82.3) 68.5) Middle- 91.7 (90.6- 86.4 (85.1- 86.0 (84.6- 76.9 (75.4- 62.1 (60.4- 6,264 5,914 5,952 5,297 4,481 ) ) ) ) ) income 92.7 87.7 87.3 78.3 63.7 88.8 (87.4- 83.6 (82.0- 81.0 (79.3- 72.9 (71.2- 57.2 (55.2- Low-income 3,782 3,552 3,526 3,139 2,569 90.1) 85.0) 82.6) 74.6) 59.2) Lowest- 87.7 (85.7- 83.1 (81.2- 77.8 (75.2- 70.6 (68.3- 55.3 (52.7- 2,875 2,697 2,590 2,326 1,853 income 89.5) 84.8) 80.2) 72.8) 57.8) Insurance Private 93.2 (92.2- 88.3 (87.3- 87.1 (86.1- 79.0 (77.8- 62.5 (61.2- 12,002 11,409 11,282 10,254 8,266 insurance 94.1) 89.3) 88.1) 80.1) 63.8) Public 91.0 (90.0- 86.4 (85.4- 86.6 (85.6- 76.0 (74.8- 66.6 (65.4- 9,424 8,916 9,034 7,928 7,128 Insurance 91.9) 87.4) 87.6) 77.2) 67.8) 86.4 (84.3- 81.4 (79.1- 74.4 (71.6- 69.2 (66.6- 50.1 (47.3- Uninsured 1,884 1,766 1,687 1,520 1,136 88.2) 83.6) 77.1) 71.6) 52.9) Region 92.4 (91.0- 86.9 (85.2- 86.0 (84.1- 77.8 (75.6- 64.4 (62.1- Northeast 3,817 3,594 3,589 3,197 2,735 93.6) 88.5) 87.7) 79.8) 66.6) 93.9 (92.7- 89.1 (87.6- 88.3 (86.9- 79.2 (77.4- 64.8 (63.0- Midwest 5,687 5,415 5,391 4,843 4,045 94.9) 90.4) 89.6) 81.0) 66.5) 90.4 (88.6- 85.5 (83.7- 84.2 (82.2- 75.5 (73.9- 61.9 (60.0- South 8,520 8,070 8,054 7,147 6,048 91.9) 87.1) 86.0) 77.0) 63.8) 91.6 (89.8- 87.4 (86.0- 85.3 (83.7- 76.6 (74.6- 60.3 (58.1- West 5,359 5,079 5,030 4,573 3,739 93.0) 88.7) 86.8) 78.5) 62.5) Note: % aware represents the weighted proportion of adults who were aware of that symptom. Abbreviations: CI, Confidence Interval; US, United States © 2019 Mahajan S et al. JAMA Network Open. eTable 2. Awareness of Symptoms of a Myocardial Infarction (0 to 5), by Sociodemographic Characteristics Characteristics None of the 5 1 of the 5 2 of the 5 3 of the 5 4 of the 5 All 5 Weighted Weighted Weighted Weighted Weighted Weighted n n n n n n % % % % % % Overall 1295 5.77% 483 1.97% 990 4.32% 2618 11.32% 5810 23.61% 14,075 53.01% Age (years) 18-39 454 6.11% 150 1.76% 382 5.37% 1094 14.40% 2333 27.82% 3785 44.54% 40-64 499 5.64% 181 2.00% 342 3.52% 958 9.91% 2254 22.22% 6070 56.71% 65 342 5.39% 152 2.29% 266 4.00% 566 8.29% 1223 18.32% 4220 61.72% Sex Men 624 6.16% 223 1.97% 544 4.98% 1354 12.88% 2945 25.84% 5761 48.17% Women 671 5.41% 260 1.96% 446 3.71% 1264 9.85% 2865 21.51% 8314 57.57% Race/Ethnicity Non-Hispanic 653 3.97% 224 1.30% 515 3.01% 1549 8.84% 4091 23.60% 10,878 59.27% White Non-Hispanic 164 6.60% 77 2.41% 193 6.89% 395 15.37% 671 23.62% 1282 45.11% Black Hispanic 331 10.47% 126 3.73% 180 6.63% 450 16.82% 737 24.97% 1186 37.39% Immigration status US-born 877 4.50% 324 1.40% 735 3.60% 2091 10.26% 5101 24.22% 12,698 56.01% Non-US-born 418 11.87% 159 4.67% 254 7.77% 523 16.31% 704 20.66% 1370 38.73% Education Some college or 667 4.55% 215 1.36% 539 3.60% 1529 10.05% 3856 24.22% 9711 56.23% higher High school or 623 8.04% 263 2.97% 447 5.66% 1078 13.48% 1943 22.53% 4329 47.31% lower Family income High-income 339 3.98% 126 1.48% 273 3.21% 818 9.43% 2189 23.57% 5859 58.34% Middle-income 334 5.79% 96 1.75% 252 4.40% 695 11.55% 1577 24.65% 3783 51.86% Low-income 285 7.76% 117 2.64% 219 5.81% 495 12.92% 982 23.85% 2120 47.02% Lowest-income 222 8.06% 116 3.56% 183 5.81% 456 15.52% 764 22.53% 1487 44.52% Insurance Private insurance 547 4.93% 173 1.63% 446 3.99% 1290 10.83% 3167 25.08% 7122 53.54% Public Insurance 534 6.00% 223 1.99% 436 4.62% 992 10.23% 2086 21.06% 6003 56.10% Uninsured 211 9.94% 84 3.79% 103 5.19% 316 16.94% 540 24.13% 919 40.00% © 2019 Mahajan S et al. JAMA Network Open. eTable 2. Continued. Characteristics None of the 5 1 of the 5 2 of the 5 3 of the 5 4 of the 5 All 5 Weighted n n Weighted % n Weighted % n Weighted % n Weighted % n Weighted % Region Northeast 192 5.40% 95 2.38% 175 4.55% 408 10.12% 902 22.16% 2331 55.40% Midwest 245 4.44% 83 1.44% 189 3.34% 582 10.35% 1511 26.06% 3426 54.37% South 588 6.99% 204 2.11% 394 4.51% 1001 11.67% 2051 22.24% 5128 52.48% West 270 5.42% 101 1.92% 232 4.77% 627 12.61% 1346 24.59% 3190 50.70% Abbreviations: US, United States. © 2019 Mahajan S et al. JAMA Network Open. eTable 3. Proportion of Individuals Who Were not Aware of the 3 Most Common Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics 3 most common symptoms include: chest pain/discomfort; pain/discomfort in arms/shoulders; and shortness of breath Characteristics n Weighted % (95% CI) US population (n) Overall 4698 20.33 (19.38 - 21.32) 47,454,926 Age (years) 18-39 1859 24.70 (23.31 - 26.13) 22,168,989 40-64 1650 17.58 (16.50 - 18.72) 17,196,499 65 1189 17.65 (16.38 - 18.99) 8,089,438 Sex Men 2396 22.57 (21.35 - 23.83) 25,511,966 Women 2302 18.23 (17.10 - 19.41) 21,942,960 Race/Ethnicity Non-Hispanic White 2541 14.76 (13.87 - 15.69) 22,401,380 Non-Hispanic Black 716 27.53 (25.04 - 30.18) 7,831,386 Hispanic 936 31.65 (29.36 - 34.02) 11,652,343 Immigration status US-born 3469 16.97 (16.05 - 17.92) 32,732,662 Non-US-born 1227 36.42 (34.23 - 38.67) 14,698,828 Education Some college or higher 2610 17.11 (16.15 - 18.12) 25,801,663 High school or lower 2067 26.13 (24.68 - 27.63) 21,365,049 Family Income High-income 1325 15.28 (14.18 - 16.45) 14,437,408 Middle-income 1209 20.82 (19.30 - 22.43) 12,985,918 Low-income 989 25.74 (24.01 - 27.56) 9,427,720 Lowest-income 879 29.43 (26.88 - 32.11) 7,510,476 Insurance Private insurance 2119 18.38 (17.21 - 19.61) 23,865,065 Public Insurance 1935 20.14 (19.07 - 21.26) 16,081,776 Uninsured 619 31.34 (28.70 - 34.11) 7,081,116 Region Northeast 764 20.02 (18.04 - 22.16) 8,579,151 Midwest 956 17.05 (15.45 - 18.79) 8,724,961 South 1880 21.80 (19.92 - 23.81) 18,533,609 West 1098 21.36 (19.72 - 23.09) 11,617,205 Abbreviations: CI, confidence intervals; US, United States. © 2019 Mahajan S et al. JAMA Network Open. eTable 4. Association Between Population Characteristics and Awareness of Myocardial Infarction Symptoms Using Multinomial Regression Analysis Characteristics Aware of 1* Aware of 2* Aware of 3* Aware of 4* Aware of 5* RRR (95% CI) RRR (95% CI) RRR (95% CI) RRR (95% CI) RRR (95% CI) Sex Men (Reference: Women) 0.90 (0.67 - 1.21) 1.08 (0.85 - 1.36) 1.08 (0.90 - 1.30) 0.95 (0.80 - 1.13) 0.67 (0.57 - 0.79) Race/Ethnicity Non-Hispanic Blacks † † (Reference: Non-Hispanic 1.06 (0.68 - 1.65) 1.52 (1.04 - 2.24) 1.15 (0.79 - 1.68) 0.74 (0.52 - 1.05) 0.60 (0.43 - 0.84) Whites) Hispanics † † (Reference: Non-Hispanic 0.75 (0.47 - 1.18) 0.82 (0.54 - 1.24) 0.78 (0.58 - 1.04) 0.60 (0.46 - 0.79) 0.42 (0.33 - 0.54) Whites) Immigration status Non-US-born (Reference: † † † 1.29 (0.87 - 1.91) 0.91 (0.64 - 1.29) 0.70 (0.53 - 0.93) 0.48 (0.37 - 0.62) 0.46 (0.36 - 0.58) US-born) Education High school or lower † † † (Reference: Some college 1.42 (1.05 - 1.93) 1.08 (0.80 - 1.47) 0.94 (0.75 - 1.17) 0.73 (0.61 - 0.89) 0.68 (0.56 - 0.82) or higher) *All compared to aware of none of the symptoms P-value <0.05 Abbreviations CI, Confidence Interval; RRR, Relative Risk Ratio; US, United States © 2019 Mahajan S et al. JAMA Network Open. eTable 5. Distribution of Different Responses to Assessment of Emergency Response to Suspicion of Myocardial Infarction Responses n Weighted % (95% CI) Call 911 or another emergency medical services number 24,088 95.54% (95.05 - 95.99) Advise to drive to hospital 210 0.97% (0.76 - 1.23) Advise to call physician 155 0.61% (0.47 - 0.79) Call spouse or family member 99 0.39 (0.29 - 0.52) Other 666 2.49 (2.21 - 2.80) Abbreviations: CI, Confidence Interval. © 2019 Mahajan S et al. JAMA Network Open. eTable 6. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics Other responses include - advise to call physician, drive to hospital, call spouse or family member, and other. Characteristics n Weighted % US population, n p-value Overall 1130 4.46 10,381,192 Age (years) 0.001 18-39 285 3.95 3,542,792 40-64 435 4.27 4,168,065 65 410 5.84 2,670,335 Sex 0.02 Women 590 4.09 4,909,591 Men 540 4.85 5,471,601 Race/Ethnicity 0.075 Non-Hispanic White 771 4.09 6,202,974 Non-Hispanic Black 102 4.42 1,254,474 Hispanic 162 5.50 2,014,323 Immigration status 0.005 US-born 933 4.16 8,012,087 Non-US-born 197 5.90 2,369,105 Education 0.001 Some college or higher 671 3.91 5,888,368 High school or lower 455 5.47 4,457,629 Family income <0.001 High-income 360 3.59 3,394,545 Middle-income 293 4.36 2,711,562 Low-income 221 5.42 1,980,933 Lowest-income 165 5.87 1,490,372 Insurance <0.001 Private insurance 436 3.53 4,574,316 Public Insurance 565 5.27 4,198,735 Uninsured 125 6.82 1,536,767 Region 0.452 Northeast 185 3.99 1,705,125 Midwest 267 4.29 2,194,212 South 424 4.89 4,149,487 West 254 4.30 2,332,368 Abbreviations: US, United States. © 2019 Mahajan S et al. JAMA Network Open. eTable 7. Association of Sociodemographic Characteristics With Choosing a Response Other Than Calling Emergency Medical Services on Suspicion of a Myocardial Infarction Using Logistic Regression Other responses include - advise to call physician, drive to hospital, call spouse or family member, and other. Characteristics Unadjusted Model Adjusted Model* OR (95% CI) p-value OR (95% CI) p-value Age (years) 18-39 Reference Reference 40-64 1.08 (0.88 - 1.34) 0.453 1.08 (0.85 - 1.38) 0.515 65 1.51 (1.19 - 1.91) 0.001 1.63 (1.22 - 2.19) 0.001 Sex Women Reference Reference Men 1.20 (1.03 - 1.40) 0.023 1.23 (1.04 - 1.46) 0.016 Race/Ethnicity Non-Hispanic White Reference Reference Non-Hispanic Black 1.08 (0.76 - 1.53) 0.650 0.99 (0.72 - 1.38) 0.968 Hispanic 1.36 (1.07 - 1.73) 0.010 1.15 (0.77 - 1.71) 0.493 Immigration status US born Reference Reference Non-US born 1.45 (1.12 - 1.88) 0.005 1.20 (0.81 - 1.78) 0.369 Education Some college or higher Reference Reference High school or lower 1.42 (1.19 - 1.70) <0.001 1.22 (1.00 - 1.49) 0.046 Family income High-income Reference Reference Middle-income 1.22 (1.00 - 1.49) 0.046 1.05 (0.83 - 1.33) 0.049 Low-income 1.54 (1.21 - 1.95) <0.001 1.16 (0.86 - 1.56) 0.339 Lowest-income 1.67 (1.22 - 2.29) 0.001 1.37 (1.00 - 1.88) 0.679 Insurance Private insurance Reference Reference Public Insurance 1.52 (1.28 - 1.81) <0.001 1.11 (0.86 - 1.44) 0.434 Uninsured 2.00 (1.49 - 2.69) <0.001 1.59 (1.19 - 2.12) 0.001 Region Midwest Reference Reference Northeast 0.93 (0.68 - 1.25) 0.615 1.07 (0.77 - 1.48) 0.691 South 1.15 (0.85 - 1.54) 0.365 1.06 (0.79 - 1.42) 0.702 West 1.00 (0.77 - 1.30) 0.992 0.99 (0.74 - 1.34) 0.954 *Model adjusted for all population characteristics Abbreviations: OR, odds ratios; CI, confidence intervals; US, United States. © 2019 Mahajan S et al. JAMA Network Open. eTable 8. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics and Awareness of Myocardial Infarction Symptoms Aware of all 5 symptoms Characteristics Aware of none of the symptoms n Weighted % (95% CI) n Weighted % (95% CI) Overall 115 9.79 (7.69 - 12.40) 538 3.44 (3.07 - 3.85) Age (years) 18-39 43 11.15 (7.84 - 15.62) 89 2.30 (1.77 - 2.99) 40-64 34 7.86 (5.19 - 11.75) 218 3.35 (2.85 - 3.93) 65 38 11.03 (7.42 - 16.07) 231 5.24 (4.51 - 6.07) Sex Women 60 9.60 (6.20 - 14.56) 307 3.23 (2.80 - 3.72) Men 55 9.98 (7.46 - 13.23) 231 3.71 (3.16 - 4.36) Race/Ethnicity Non-Hispanic White 43 7.47 (4.69 - 11.70) 414 3.43 (3.03 - 3.88) Non-Hispanic Black 15 13.71 (7.50 - 23.74) 42 2.69 (1.84 - 3.93) Hispanic 40 10.42 (7.32 - 14.63) 43 3.83 (2.61 - 5.61) Immigration status US-born 66 8.94 (6.46 - 12.24) 490 3.48 (3.09 - 3.93) Non-US-born 49 11.39 (8.45 - 15.17) 48 3.16 (2.21 - 4.51) Education Some college or higher 45 7.64 (5.45 - 10.61) 360 3.34 (2.94 - 3.80) High school or lower 69 11.97 (8.94 - 15.84) 176 3.66 (3.01 - 4.44) Family income* High/middle-income 51 7.63 (5.27 - 10.93) 343 3.18 (2.77 - 3.65) Low/lowest-income 55 12.50 (9.19 - 16.79) 4.19 (3.44 - 5.11) Insurance Private insurance 50 8.21 (5.03 - 13.11) 311 2.48 (2.09 - 2.93) 192 4.93 (4.28 - 5.69) Public Insurance 39 10.43 (7.50 - 14.33) Uninsured 26 13.14 (8.44 - 19.89) 35 3.63 (2.34 - 5.59) Region 102 3.60 (2.73 - 4.73) Northeast 12 5.93 (2.70 - 12.51) 125 3.25 (2.61 - 4.04) Midwest 16 8.92 (4.93 - 15.62) 180 3.27 (2.72 - 3.92) South 61 11.07 (7.69 - 15.70) 131 3.79 (2.93 - 4.88) West 26 10.94 (7.19 - 16.29) Abbreviations: CI, confidence interval; US, United States *We combined high-income and middle-income groups into high/middle-income, and low-income and lowest-income groups into low/lowest-income due to small sample sizes. © 2019 Mahajan S et al. JAMA Network Open. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Network Open American Medical Association http://www.deepdyve.com/lp/american-medical-association/variation-and-disparities-in-awareness-of-myocardial-infarction-0G1hSj0Tzx

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Publisher: American Medical Association
Copyright: Copyright 2019 Mahajan S et al. JAMA Network Open.
eISSN: 2574-3805
DOI: 10.1001/jamanetworkopen.2019.17885
Publisher site: See Article on Publisher Site

Abstract

Key Points Question What are the prevalence and IMPORTANCE Prompt recognition of myocardial infarction symptoms is critical for timely access to characteristics of adults in the United lifesaving emergency cardiac care. However, patients with myocardial infarction continue to have a States who remain unaware of the delayed presentation to the hospital. symptoms of and the appropriate response to a myocardial infarction? OBJECTIVE To understand the variation and disparities in awareness of myocardial infarction Findings In this cross-sectional study of symptoms among adults in the United States. 25 271 US adults, 5.8% were not aware of any myocardial infarction symptoms, DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study used data from the 2017 and 4.5% chose a different response National Health Interview Survey among adult residents of the United States, assessing awareness of than calling emergency medical services the 5 following common myocardial infarction symptoms among different sociodemographic in response to these symptoms. These subgroups: (1) chest pain or discomfort, (2) shortness of breath, (3) pain or discomfort in arms or numbers were substantially higher in shoulders, (4) feeling weak, lightheaded, or faint, and (5) jaw, neck, or back pain. The response to a certain sociodemographic groups. perceived myocardial infarction (ie, calling emergency medical services vs other) was also assessed. Meaning Many individuals in the United MAIN OUTCOMES AND MEASURES Prevalence and characteristics of individuals who were States remain unaware of the symptoms unaware of myocardial infarction symptoms and/or chose not to call emergency medical services in of and appropriate response to a response to these symptoms. myocardial infarction. RESULTS Among 25 271 individuals (13 820 women [51.6%; 95% CI, 50.8%-52.4%]; 17 910 Supplemental content non-Hispanic white individuals [69.9%; 95% CI, 68.2%-71.6%]; and 21 826 individuals [82.7%; 95% CI, 81.5%-83.8%] born in the United States), 23 383 (91.8%; 95% CI, 91.0%-92.6%) considered chest Author affiliations and article information are listed at the end of this article. pain or discomfort a symptom of myocardial infarction; 22 158 (87.0%; 95% CI, 86.1%-87.8%) considered shortness of breath a symptom; 22 064 (85.7%; 95% CI, 84.8%-86.5%) considered pain or discomfort in arm a symptom; 19 760 (77.0%; 95% CI, 76.1%-77.9%) considered feeling weak, lightheaded, or faint a symptom; and 16 567 (62.6%; 95% CI, 61.6%-63.7%) considered jaw, neck, or back pain a symptom. Overall, 14 075 adults (53.0%; 95% CI, 51.9%-54.1%) were aware of all 5 symptoms, whereas 4698 (20.3%; 95% CI, 19.4%-21.3%) were not aware of the 3 most common symptoms and 1295 (5.8%; 95% CI, 5.2%-6.4%) were not aware of any symptoms. Not being aware of any symptoms was associated with male sex (odds ratio [OR], 1.23; 95% CI, 1.05-1.44; P = .01), Hispanic ethnicity (OR, 1.89; 95% CI, 1.47-2.43; P < .001), not having been born in the United States (OR, 1.85; 95% CI, 1.47-2.33; P < .001), and having a lower education level (OR, 1.31; 95% CI, 1.09-1.58; P = .004). Among 294 non-Hispanic black or Hispanic individuals who were not born in the United States, belonged to the low-income or lowest-income subgroup, were uninsured, and had a lower education level, 61 (17.9%; 95% CI, 13.3%-23.6%) were not aware of any symptoms. This group had 6-fold higher odds of not being aware of any symptoms (OR, 6.34; 95% CI, 3.92-10.26; P < .001) compared with individuals without these characteristics. Overall, 1130 individuals (4.5%; 95% CI, 4.0%-5.0%) chose a different response than calling emergency medical services in response to a myocardial infarction. (continued) Open Access. This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 1/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States Abstract (continued) CONCLUSIONS AND RELEVANCE Many adults in the United States remain unaware of the symptoms of and appropriate response to a myocardial infarction. In this study, several sociodemographic subgroups were associated with a higher risk of not being aware. They may benefit the most from targeted public health initiatives. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 Introduction Although mortality rates among patients hospitalized for myocardial infarction (MI) have seen a decreasing trend, patients with MI continue to have a delayed presentation to the hospital, and a 1,2 large number of them die before reaching the hospital. A critical aspect of lowering mortality associated with MI is ensuring timely access to lifesaving emergency cardiac care, for which prompt recognition of symptoms of a myocardial infarction (MI) and appropriate rapid emergency response are crucial. Previous studies from the United States have shown that, although awareness of MI symptoms has increased over the years, less than 50% of adults are aware of the 5 common symptoms (ie, chest pain or discomfort; shortness of breath; pain or discomfort in arms or shoulders; feeling weak, 4-8 lightheaded, or faint; and jaw, neck, or back pain). Although Healthy People 2020 set targets to improve awareness of these common symptoms, there is little information on the prevalence and characteristics of individuals who are not aware of any symptoms. Additionally, previous studies on MI symptom awareness have focused on disparities across limited demographic subgroups (eg, age, sex, and race/ethnicity); however, the association of sociocultural factors (eg, education level, socioeconomic status [SES], insurance status, and immigration status) and the cumulative 4,10 association of these potential risk factors with awareness remains largely unknown. Given that previous community interventions to improve awareness of symptoms and 11-14 emergency medical service (EMS) use in MI have largely been unsuccessful, this information can help identify subgroups that are most in need of and may benefit from targeted public health awareness initiatives, which can subsequently reduce mortality and morbidity attributable to MI. Accordingly, we used nationally representative data to estimate awareness of MI symptoms among adults in the United States, characterizing sociodemographic groups, both individually and in combination, that were particularly at risk of not being aware of any symptoms. Methods Study Design and Population We included 26 742 individuals aged 18 years and older, using data from the 2017 National Health Interview Survey (NHIS), which is an annual, cross-sectional, national, weighted survey that provides estimates on the noninstitutionalized US population using multistage sampling. Additional details of the NHIS survey are provided in the eMethods in the Supplement. We excluded 1471 participants because of missing information on awareness of MI symptoms (eFigure 1 in the Supplement). This study was exempt from review by the Yale University institutional review board committee because NHIS data are publicly available and deidentified. The study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Awareness of MI Symptoms Awareness was assessed by an individual’s responses to the question, “Which of the following would you say are the symptoms that someone may be having a heart attack?”: (1) chest pain or discomfort; (2) shortness of breath; (3) pain or discomfort in arms or shoulders; (4) feeling weak, lightheaded, JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 2/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States or faint; and (5) jaw, neck, or back pain. We studied responses individually, then divided them into 4 mutually exclusive subgroups based on the number of symptoms an individual was aware of, as follows: (1) none of the symptoms, (2) 1 to 2 symptoms, (3) 3 to 4 symptoms, and (4) all 5 symptoms. We also assessed the awareness of the 3 most common symptoms (ie, chest pain or discomfort; shortness of breath; and pain or discomfort in arms or shoulders) separately. Response to a Perceived MI We assessed the prevalence of adults who were aware of the need to access immediate emergency care by calling EMS in response to a perceived MI by their response to the question, “What is best thing to do when someone is having a heart attack?” Responses included call 9-1-1 or another emergency number, advise them to drive to the hospital, advise them to call their physician, call spouse or family member, and other. We studied all responses individually, then dichotomized the responses to calling 9-1-1 or another emergency number vs all other options. Independent Variables Other variables included in this study were age (ie, 18-39 years, 40-64 years, or65 years), sex (ie, male or female), race/ethnicity (ie, non-Hispanic white, non-Hispanic black, or Hispanic), SES (based on family income as a percentage of the federal poverty limit from the US Census Bureau and classified as high income [400%], middle income [200% to <400%], low income [125% to <200%], and lowest income [<125%]), education level (ie,some college orhigh school), insurance status (ie, public, private, or uninsured), geographic region (ie, Northeast, Midwest, South, or West), and immigration status (based on geographic place of birth and classified as US-born or non-US-born). For non-US-born individuals, we also collected information on their time in the United States (ie, <10 years vs10 years) and English proficiency (ie, speaks English well or very well vs does not speak English well or at all). English proficiency was measured directly, and in cases where the interviewee did not speak English well (<1.5%), a proxy was used to answer the survey questions. Statistical Analysis The NHIS uses complex sampling techniques to select the sample. After adjusting for nonresponse, age, sex, and race/ethnicity (based on the population estimates produced by the US Census Bureau), final person-level weights are created, which can then be used to provide national estimates. We described the survey-weighted proportions (with Rao-Scott χ ) of awareness for each of the 5 symptoms individually, the distribution of overall awareness (from 0 to 5), and the awareness of the 3 most common symptoms across different sociodemographic characteristics. Next, we assessed the association of these characteristics with not being aware of any MI symptoms using unadjusted and adjusted survey-specific logistic regression and multinomial regression models. Logistic regression was used to evaluate dichotomous outcome variables (eg, being aware of none vs any MI symptoms), while multinomial regression was used to study categorical outcome variables (eg, being aware of 0 vs 1 vs 2 vs 3 vs 4 vs all 5 MI symptoms). Explanatory variables included age, sex, race/ ethnicity, immigration status, education level, SES, insurance status, and region. We also created a composite score using race/ethnicity (non-Hispanic white vs non-Hispanic black and Hispanic), immigration status (US-born vs non-US-born), education level (some college vshigh school), SES (high or middle income vs low or lowest income), and insurance status (insured vs uninsured) to study the cumulative association of these factors with awareness of MI symptoms. We also assessed the proportion of individuals who chose a different response than calling EMS as a reaction to a perceived MI, both overall and by awareness of MI symptoms. We identified individual characteristics associated with not calling EMS in response to a MI, using unadjusted and adjusted survey-specific logistic regression models. We considered P < .05 statistically significant a priori for all analyses in our study, and all tests were 2-tailed. All analyses were performed using Stata version 13.0 (StataCorp) and accounted for JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 3/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States the survey design of the NHIS, including sampling weights, to ensure that our results were nationally representative. Results Population Characteristics Our study population included 25 271 individuals corresponding to more than 233.4 million adults in 2017; 13 820 (51.6%; 95% CI, 50.8%-52.4%) were women; 17 910 (69.9%; 95% CI, 68.2%-71.6%) were non-Hispanic white individuals; and 21 826 (82.7%; 95% CI, 81.5%-83.8%) were born in the United States (Table 1). A total of 7446 participants (28.3%; 95% CI, 27.0%-29.8%), representing an estimated 62.1 million individuals, were part of the low- or lowest-income subgroup, and 8683 participants (35.2%; 95% CI, 34.1%-36.3%), representing an estimated 81.8 million individuals, had an education level of high school or less. Most individuals had private insurance (12 745 [55.9%; 95% CI, 54.8%-57.0%]), followed by public insurance (10 274 [34.4%; 95% CI, 33.4%-35.4%]) and no insurance (2173 [9.7%; 95% CI, 9.1%-10.4%]). Table 1. Characteristics of Study Participants Estimated US Population, No. Characteristic No. (N = 25 271) Weighted % (95% CI) (N = 233 427 109) Age, y 18-39 8198 38.46 (37.51-39.41) 89 771 938 40-64 10 304 41.90 (41.03-42.78) 97 811 097 ≥65 6769 19.64 (19.01-20.29) 45 844 074 Sex Men 11 451 48.43 (47.65-49.22) 113 053 335 Women 13 820 51.57 (50.78-52.35) 120 373 774 Race/ethnicity Non-Hispanic white 17 910 69.93 (68.18-71.62) 151 775 038 Non-Hispanic black 2782 13.11 (12.04-14.25) 28 445 310 Hispanic 3010 16.97 (15.52-18.51) 36 822 570 Immigration status US-born 21 826 82.70 (81.51-83.83) 192 932 915 Non-US-born 3428 17.30 (16.17-18.49) 40 361 715 Education ≥Some college 16 517 64.84 (63.71-65.95) 150 806 910 ≤High school 8683 35.16 (34.05-36.29) 81 780 160 Family income subgroup High 9604 43.14 (41.85-44.44) 94 485 977 Middle 6737 28.48 (27.64-29.34) 62 370 753 Low 4218 16.72 (16.02-17.45) 36 621 219 Lowest 3228 11.65 (10.95-12.39) 25 522 093 Insurance Private 12 745 55.89 (54.83-56.95) 129 835 329 Public 10 274 34.38 (33.39-35.38) 79 855 830 Uninsured 2173 9.73 (9.09-10.40) 22 593 891 Region Northeast 4103 18.36 (16.80-20.03) 42 860 199 Midwest 6036 21.92 (20.71-23.17) 51 159 938 South 9366 36.42 (34.40-38.49) 85 010 955 West 5766 23.30 (21.59-25.10) 54 396 017 JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 4/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States Awareness of MI Symptoms In this nationally representative adult population, most individuals (23 383 [91.8%; 95% CI, 91.0%- 92.6%]) considered chest pain or discomfort a MI symptom, followed by shortness of breath (22 158 [87.0%; 95% CI, 86.1%-87.8%]), pain or discomfort in arms or shoulders (22 064 [85.7%; 95% CI, 84.8%-86.5%]), feeling weak, lightheaded, or faint (19 760 [77.0%; 95% CI, 76.1%-77.9%]), and jaw, neck, or back pain (16 567 [62.6%; 95% CI, 61.6%-63.7%]) (eTable 1 in the Supplement). Awareness of symptoms was significantly higher among individuals who were non-Hispanic white, born in the United States, had higher education levels, belonged to the high-income or middle-income subgroup, and had private insurance compared with individuals who were non-Hispanic black or Hispanic, were not born in the United States, had lower education levels, belonged to the low-income or lowest-income subgroup, and were uninsured (eTable 1 in the Supplement). For example, 16 959 of all non-Hispanic white participants (94.4%; 95% CI, 93.5%-95.1%) were aware that chest pain or discomfort is a symptom of MI, while 2529 of all Hispanic participants (84.8%; 95% CI, 83.0%-86.4%) were aware of this symptom; more individuals in the high-income subgroup than those in the lowest-income subgroup were aware that jaw, neck, or back pain is a symptom of MI (6694 [67.1%; 95% CI, 65.6%-68.5%] vs 1853 [55.3%; 95% CI, 52.7%-57.8%]) (eTable 1 in the Supplement). Overall, 14 075 individuals (53.0%; 95% CI, 51.9%-54.1%), representing 123.7 million adults, were aware of all 5 MI symptoms, whereas 4698 (20.3%; 95% CI, 19.4%-21.3%), representing 47.5 million adults, were not aware of the 3 most common symptoms and 1295 (5.8%; 95% CI, 5.2%-6.4%), representing 13.5 million adults, were not aware of any symptoms (eTable 2 and eTable 3 in the Supplement). Awareness of different numbers of MI symptoms (ranging from 0-5) varied substantially across sociodemographic subgroups (eFigure 2 in the Supplement). The proportion of individuals not aware of any of the symptoms was higher among non-Hispanic black and Hispanic individuals than non-Hispanic white individuals (164 [6.6%; 95% CI, 5.3%-8.2%] and 331 [10.5%; 95% CI, 9.1%-12.0%] vs 653 [4.0%; 95% CI, 3.4%-4.7%]; P < .001), among individuals not born in the United States than those born in the United States (418 [11.9%; 95% CI, 10.5%-13.4%] vs 877 [4.5%; 95% CI, 3.9%-5.2%]; P < .001), among individuals with lower education levels than those with higher education levels (623 [8.1%; 95% CI, 7.2%-9.0%] vs 667 [4.5%; 95% CI, 3.9%-5.3%]; P < .001), among individuals belonging to the low-income and lowest-income subgroups than those belonging to the high-income and middle-income subgroups (222 [8.1%; 95% CI, 6.8%-9.5%] and 285 [7.8%; 95% CI, 6.7%-9.0%] vs 339 [4.0%; 95% CI, 3.3%-4.8%] and 334 [5.8%; 95% CI, 4.9%-6.8%]; P < .001), among individuals with no insurance than those with public and private insurance (211 [9.9%; 95% CI, 8.4%-11.8%] vs 534 [6.0%; 95% CI, 5.3%-6.8%] and 547 [4.9%; 95% CI, 4.2%-5.8%]; P < .001), and among individuals living in the South than those living in the Midwest (588 [7.0%; 95% CI, 5.7%-8.5%] vs 245 [4.4%; 95% CI, 3.6%-5.5%]; P < .001) (eFigure 3 in the Supplement). The proportion of individuals who were not aware of the 3 most common symptoms was higher across similar subgroups (eg, Hispanic vs non-Hispanic white individuals, 936 [31.7%; 95% CI, 29.4%-34.0%] vs 2541 [14.8%; 95% CI, 13.9%-15.7%]; P < .001; non-US-born vs US-born individuals, 1227 [36.4%; 95% CI, 34.2%-38.7%] vs 3469 [17.0%; 95% CI, 16.1%-17.9%]; P < .001; lowest-income vs high-income subgroup, 879 [29.4%; 95% CI, 26.9%-32.1%] vs 1325 [15.3%; 95% CI, 14.2%-16.5%]; P < .001) (eTable 3 in the Supplement). In a subanalysis among individuals not born in the United States, we found that those who did not have good English proficiency were less likely to be aware of all 5 symptoms than those who had good English proficiency (298 [95% CI, 34.6%; 30.4%-39.1%] vs 1072 [40.2%; 95% CI, 37.6%-42.9%]; P < .001), and those who had been in the United States for less than 10 years were less likely to be aware of all 5 symptoms than those had been in the United States for 10 or more years (199 [29.4%; 95% CI, 25.1%-34.2%] vs 1137 [40.5%; 95% CI, 37.8%-43.2%]; P < .001). Similarly, those who did not have good English proficiency were more likely than those who had good English proficiency to be aware of none of the symptoms (185 [19.6%; 95% CI, 16.4%-23.2%] vs 233 [9.1%; 95% CI, 7.7%-10.7%]; P < .001), and those who had been in the United States for less than 10 years JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 5/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States were more likely than those who had been in the United States for 10 or more years to be aware of none of the symptoms (98 [14.8%; 95% CI, 11.5%-18.7%] vs 315 [11.2%; 95% CI, 9.8%-12.8%]; P < .001) (eFigure 4 in the Supplement). Sociodemographic Characteristics Associated With Lack of Awareness Overall, several individual characteristics were associated with not being aware of any MI symptoms (Figure 1). In an unadjusted model, we found that higher odds of not being aware of any symptoms were associated with black race (odds ratio [OR], 1.71; 95% CI, 1.30-2.24; P < .001) and Hispanic ethnicity (OR, 2.83; 95% CI, 2.28-3.50; P < .001) compared with non-Hispanic white race/ethnicity, Figure 1. Unadjusted and Risk-Adjusted Associations of Sociodemographic Characteristics With Not Being Aware of Any Symptoms of a Myocardial Infarction Favors Favors OR Characteristic (95% CI) Awareness No Awareness Aged 40-64 y vs ≥65 y Unadjusted 1.05 (0.90-1.23) Adjusted 0.91 (0.70-1.19) Aged 18-39 y vs ≥65 y Unadjusted 1.14 (0.96-1.36) Adjusted 0.98 (0.72-1.33) Men vs women Unadjusted 1.15 (0.99-1.33) Adjusted 1.23 (1.05-1.44) Non-Hispanic black vs non-Hispanic white Unadjusted 1.71 (1.30-2.24) Adjusted 1.36 (0.98-1.90) Hispanic vs non-Hispanic white Unadjusted 2.83 (2.28-3.50) Adjusted 1.89 (1.47-2.43) Non-US born vs US born Unadjusted 2.86 (2.39-3.41) Adjusted 1.85 (1.47-2.33) Education ≤ high school vs ≥ some college Unadjusted 1.84 (1.57-2.15) Adjusted 1.31 (1.09-1.58) Lowest-income subgroup vs high-income subgroup Unadjusted 2.12 (1.65-2.73) Adjusted 1.29 (0.96-1.74) Low-income subgroup vs high-income subgroup Unadjusted 2.03 (1.62-2.55) Adjusted 1.35 (1.02-1.77) Middle-income subgroup vs high-income subgroup Unadjusted 1.49 (1.20-1.83) Adjusted 1.19 (0.96-1.48) Uninsured vs private insurance Unadjusted 2.13 (1.67-2.71) Adjusted 1.26 (0.97-1.64) Public insurance vs private insurance Unadjusted 1.23 (1.03-1.47) Adjusted 1.09 (0.82-1.46) Northeast vs Midwest Unadjusted 1.23 (0.90-1.68) Adjusted 1.01 (0.72-1.42) South vs Midwest Unadjusted 1.62 (1.18-2.21) Adjusted 1.20 (0.85-1.69) West vs Midwest Unadjusted 1.23 (0.92-1.66) Adjusted 0.81 (0.58-1.13) Results show odds ratios (ORs) with 95% CI calculated 0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 using logistic regression. Adjusted model includes all Odds Ratio (95% CI) variables presented in the figure. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 6/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States not having been born in the United States (OR, 2.86; 95% CI, 2.39-3.41; P < .001) compared with being born in the United States, lower education levels (OR, 1.84; 95% CI, 1.57-2.15; P < .001) compared with higher education levels, the low-income (OR, 2.03; 95% CI, 1.62-2.55; P < .001) or lowest-income (OR, 2.12; 95% CI, 1.65-2.73; P < .001) subgroup compared with the highest-income subgroup, public (OR, 1.23; 95% CI, 1.03-1.47; P = .02) or no (OR, 2.13; 95% CI, 1.67-2.71; P < .001) insurance compared with private insurance, and living in the South (OR, 1.62; 95% CI, 1.18-2.21; P = .003) compared with living in the Midwest. When we adjusted for known confounders, we found that higher odds of not being aware of any symptoms were associated with male sex (OR, 1.23; 95% CI, 1.05-1.44; P = .01) compared with female sex, Hispanic ethnicity (OR, 1.89; 95% CI, 1.47-2.43; P < .001) compared with non-Hispanic white race/ethnicity, not being born in the United States (OR, 1.85; 95% CI, 1.47-2.33; P < .001) compared with being born in the United States, and lower education levels (OR, 1.31; 95% CI, 1.09-1.58; P = .004) compared with higher education levels (Figure 1). Using multinomial regression (adjusting for the statistically significant factors from the previous logistic regression), we found that there was a stepwise higher likelihood of not being aware as the aggregate number of symptoms grew. For example, compared with individuals born in the United States, those not born in the United States were 30% (relative risk ratio [RRR], 0.70; 95% CI, 0.53- 0.93; P = .01) less likely to be aware of 3 symptoms, 52% (RRR, 0.48; 95% CI, 0.37-0.62; P < .001) less likely to be aware of 4 symptoms, and 54% (RRR, 0.46; 95% CI, 0.36-0.58; P < .001) less likely to be aware of 5 symptoms of a MI compared with being aware of no symptoms. Similar trends in association were seen across other subgroups (eg, individuals with lower education levels had RRRs of 0.73 [95% CI, 0.61-0.89; P = .001] for being aware of 4 symptoms and 0.68 [95% CI, 0.56-0.82; P < .001] for being aware of 5 symptoms) (eTable 4 in the Supplement). Cumulative Association of Sociodemographic Factors With Awareness We evaluated 5 variables (ie, race/ethnicity, immigration status, education, income, and insurance status) associated with the greatest risk of not being aware of any MI symptoms and examined their combined association with awareness. Compared with the reference group with no high-risk characteristics (8793 white and US-born individuals who belonged to the middle-income or high- income subgroup, had insurance, and had a higher education level), those with 1, 2, 3, 4, and 5 high- risk characteristics had a stepwise decrease in awareness (Figure 2). Among 294 individuals with all 5 high-risk characteristics (representing 3.7 million adults in the United States), 88 (29.8%; 95% CI, 23.6%-36.8%) were aware of all 5 symptoms, compared with 5688 (62.9%; 95% CI, 61.5%-64.4%) in the reference group. Moreover, 61 individuals (17.9%; 95% CI, 13.3%-23.6%) with all 5 high-risk characteristics (representing approximately 664 143 adults) were not aware of a single MI symptom compared with 253 individuals (3.3%; 95% CI, 2.6%-4.0%) in the reference group (Figure 2). Using logistic regression analysis, we found that, compared with the reference group, those with all 5 high- risk characteristics had more than 6-fold higher odds of not being aware of any symptoms (OR, 6.34; 95% CI, 3.92-10.26; P < .001) (Table 2). Response to a Perceived MI Overall, 1130 individuals (4.5%; 95% CI, 4.0%-5.0%), representing 10.4 million adults, chose a different response than calling EMS in response to a perceived MI (eTable 5 in the Supplement). The proportion was significantly higher among individuals who were 65 years or older than among those who were aged 18 to 39 years (410 [5.8%] vs 285 [4.0%]; P = .001), men than women (540 [4.9%] vs 590 [4.1%]; P = .02), those who were not born in the United States than those who were born in the United States (197 [5.9%] vs 933 [4.2%]; P = .005), those who had a lower education level than those with a higher education level (455 [5.5%] vs 671 [3.9%]; P = .001), those belonging to the low-income and lowest-income subgroups than those belonging to the middle-income or highest- income subgroups (386 [11.3%] vs 653 [7.9%]; P < .001), and those with no insurance than those with private insurance (125 [6.8%] vs 436 [3.5%]; P < .001) (eTable 6 in the Supplement). In analysis JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 7/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States using logistic regression, being 65 years or older (OR, 1.63; 95% CI, 1.22-2.19; P = .001) and uninsured (OR, 1.59; 95% CI, 1.19-2.12; P = .001) had the strongest associations with not calling EMS in response to a perceived MI compared with being younger than 65 years and having private insurance, respectively (eTable 7 in the Supplement). In assessing response to a MI by awareness of MI symptoms, we found that 115 adults (9.8%; 95% CI, 7.7%-12.4%) among those who were not aware of any symptoms (representing 1.3 million individuals) chose a different response than calling EMS, compared with 538 adults (3.4%; 95% CI, 3.1%-3.9%) among those who were aware of all 5 symptoms of a MI (representing approximately 4.3 million adults) (eTable 8 in the Supplement). These differences were consistently seen across all sociodemographic subgroups. For example, among individuals with an education level of high school or less who were aware of none of the symptoms, 69 (12.0%; 95% CI, 8.9%-15.8%) chose a different response than calling EMS compared with 176 (3.6%; 95% CI, 3.0%-4.4%) individuals with an education level of high school or less who were aware of all 5 symptoms (P < .001). Among individuals who belonged to the low-income or lowest-income subgroup and were aware of none of Figure 2. Proportion of Individuals Aware of Different Number of Myocardial Infarction Symptoms by Number of High-Risk Characteristics A Aware of all 5 symptoms of myocardial infarction B Aware of 3 to 4 symptoms of myocardial infarction 80 80 60 60 40 40 20 20 0 0 0 1 2 3 4 5 0 1 2 3 4 5 High-risk Characteristics, No. High-risk Characteristics, No. C Aware of 1 to 2 symptoms of myocardial infarction D Aware of none of the symptoms of myocardial infarction 25 25 20 20 15 15 10 10 High-risk characteristics include non-Hispanic black or 5 5 Hispanic race/ethnicity, non-US-born immigrant status, low-income or lowest-income subgroup, 0 0 0 1 2 3 4 5 0 1 2 3 4 5 uninsured, and high school or lower education level. High-risk Characteristics, No. High-risk Characteristics, No. Error bars indicate 95% CIs. Table 2. Odds of Not Being Aware of Any Myocardial Infarction Symptoms Based on the Number of High-Risk Characteristics Unadjusted Model Adjusted Model High-Risk Characteristic, No. OR (95% CI) P Value OR (95% CI) P Value 0 1 [Reference] NA 1 [Reference] NA Abbreviations: NA, not applicable; OR, odds ratio. 1 1.34 (1.07-1.69) .01 1.33 (1.06-1.68) .01 High-risk characteristics include non-Hispanic black 2 1.79 (1.37-2.33) <.001 1.75 (1.33-2.31) <.001 or Hispanic race/ethnicity, non-US-born immigrant 3 2.76 (2.02-3.76) <.001 2.69 (1.96-3.70) <.001 status, low-income or lowest-income subgroup, 4 5.94 (4.31-8.19) <.001 5.89 (4.23-8.21) <.001 uninsured, and high school or lower education level. 5 6.46 (4.13-10.10) <.001 6.34 (3.92-10.26) <.001 Model adjusted for age, sex, and region. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 8/15 Proportion, % Proportion, % Proportion, % Proportion, % JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States the symptoms, 55 (12.5%; 95% CI, 9.2%-16.8%) chose a different response than calling EMS compared with 155 (4.2%; 95% CI, 3.4%-5.1%) who belonged to the low-income or lowest-income subgroups and were aware of all 5 symptoms (P < .001) (Figure 3). Discussion In this nationally representative cross-sectional study, we found that nearly 6% of individuals, or an estimated 13.5 million adults nationally, were not aware of a single symptom of a MI and nearly 1 in 12 individuals, or an estimated 19.1 million adults nationally, did not consider chest pain or discomfort a MI symptom. These numbers were substantially higher for individuals who were non-Hispanic black or Hispanic, were not born in the United States, had lower education levels, were uninsured, and belonged to the low-income and lowest-income subgroups. Among individuals having all these characteristics, 1 in 5 were not aware of any symptom of a MI. Moreover, nearly 4.5% of individuals, or an estimated 10.4 million adults nationally, chose a different response than immediately calling EMS on suspicion of a MI, and this proportion was more than double (9.8%) among adults who were not aware of any MI symptoms. Our study extends the previous literature on awareness of MI symptoms in several ways. First, most previous studies describing the awareness of MI symptoms have focused on individuals who 4,6,8,16,17 were aware of all 5 symptoms. However, we focused on individuals who were not aware of any or the most common symptoms and identified subgroups that were most in need of and may benefit the most from targeted public health awareness initiatives. Studies have reported a 10.1% Figure 3. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to a Perceived Myocardial Infarction, by Sociodemographic Characteristics and Awareness of Myocardial Infarction Symptoms Aware of none of the symptoms Aware of all 5 symptoms of myocardial infarction A Age B Sex C Race/ethnicity 25 25 25 20 20 20 15 15 15 10 10 10 5 5 5 0 0 0 18-39 40-64 ≥65 Men Women White Black Hispanic Age, y Sex Race/Ethnicity D Education level E Family income F Insurance 25 25 25 20 20 20 15 15 15 10 10 10 5 5 5 0 0 0 ≥Some College ≤High School High/Middle Low/Lowest Private Public Uninsured Education Level Income Level Insurance Type Error bars indicate 95% CIs. JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 9/15 Proportion, % Proportion, % Proportion, % Proportion, % Proportion, % Proportion, % JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States increase in awareness of all 5 symptoms between 2008 and 2014, with 47.2% adults in the United States being aware of all 5 symptoms in 2014. Our results not only showed a small increase in awareness of all 5 symptoms since 2014 but also suggest that, even today, millions of individuals in the United States remain unaware of the most critical symptoms of a MI (eg, chest pain) and, therefore, are at a high risk of adverse outcomes after an MI. Second, to our knowledge, this study is the first to describe awareness rates across such diverse sociodemographic subgroups based on SES, insurance status, and immigration status. We found significant disparities across subgroups based on age, race/ethnicity, and education level, which were 4,10,16,18,19 consistent with previous reports on awareness and, additionally, identified non-US-born individuals, uninsured individuals, and individuals from the low-income and lowest-income subgroups as high-risk subgroups for not being aware of any symptoms. Third, to our knowledge, this is the first report studying the awareness of MI symptoms among immigrants and describing the association of acculturation factors (eg, English proficiency and duration of US residence) with awareness. We found that nearly 1 in 8 (12%) of the estimated 5 million non-US-born individuals were not aware of any symptoms and that acculturation factors had a significant association with awareness among immigrants. Given the increasing number of individuals in the United States who were born in other countries and the low symptom awareness rates among these individuals, public health professionals may need to tailor awareness campaigns according to these individuals’ linguistic and cultural needs. Fourth, to our knowledge, our study is the first to describe the cumulative association of the potential high-risk characteristics (ie, non-Hispanic black or Hispanic race/ethnicity, non-US-born, low income, uninsured, lower education level) with awareness. We reported a stepwise increase in the proportion of individuals who were not aware of any MI symptoms as the number of these high- risk characteristics increased. Among individuals with all 5 high-risk characteristics, nearly 1 in 5 individuals were not aware of any of the symptoms. As such, our findings underscore the importance of targeting public health initiatives toward these socioeconomically disadvantaged groups to improve awareness and subsequently reduce the mortality associated with MI. Finally, our assessment of the use of EMS in response to a perceived MI suggests that, although the use of EMS has increased from that previously reported in the literature (91.8% in 2008 and 93.4% in 2014), millions of individuals continued to choose a different response than immediately calling EMS. As expected, individuals who were unaware of the symptoms were also more likely to not call EMS; however, a significant number of adults with optimal symptom awareness also chose to not call EMS. Some possible explanations for this could be denial of symptoms, misattribution to symptoms to a noncardiac cause, perceived loss of control and ability to act, self-treatment 4,10,21-23 strategies, fear or embarrassment of being wrong, and concerns about cost. Given that early intervention in patients with MI is crucial to limit ischemic damage, prompt recognition of MI symptoms and rapid decision to seek care can reduce delays from symptom-onset to hospital presentation and improve survival. As such, it is critical to not only improve awareness of warning signs of a MI and the importance of early access to medical care but also to better understand and address the barriers that prevent individuals from accessing emergency medical care. The American Heart Association, the US Department of Health and Human Services, the National Heart, Lung, and Blood Institute, and the US Centers for Disease Control and Prevention have made substantial efforts to improve awareness of MI symptoms, such as the Go Red for Women and Go Red Por Tu Corazon (ie, Go Red for your Heart, which targets Spanish-speaking women), 24-28 Make the Call, Don’t Miss a Beat, The Heart Truth, and WISEWOMAN campaigns, respectively. While most of these initiatives are directed to women, our study found a nearly 10% higher awareness of all 5 MI symptoms and better use of EMS among women than men, which could be a reflection of the successful reach of these campaigns, although efforts to increase awareness of cardiovascular disease among women are still warranted. Disparities in awareness and response to MI symptoms found in our study corresponded closely 30-35 with the disparities seen in delays in hospital presentation and outcomes after MI. Racial and JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 10/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States ethnic minorities have been shown to have longer delay times than non-Hispanic white individuals. Similarly, individuals with lower SES and greater financial concerns have been shown to have a delayed presentation to the hospital, although this could be related to issues with access to care. It has been shown that focusing on the seriousness of the situation and increasing awareness among 4,36,37 specific population subgroups could be useful in reducing prehospital delays. As such, recognizing the subgroups that are at the highest risk of being unaware of MI symptoms is germane to the current debate regarding diminishing treatment delays for individuals experiencing a MI and can help better design health care policies and/or campaigns specifically tailored for them. Limitations This study has limitations. First, our assessment of awareness of MI symptoms was based on an arbitrary list, and while the most prevalent symptoms were listed, presentation of a MI may not be limited to these symptoms. Nevertheless, we showed that millions of individuals were unaware of even these most common symptoms of a MI. Second, not all MI symptoms included in this study should be weighted equally because some symptoms (eg, chest pain or discomfort) may be more easily identifiable than others. Therefore, although we provided the distribution of awareness of all MI symptoms and a composite score, we chose to focus our analyses on those who were not aware of any symptoms. Third, our assessment of MI symptom awareness was based on a set of closed- ended questions (ie, yes or no) that may bias responses, and offering of a set of symptoms could have led to an overestimation of the awareness rates. As such, the actual awareness rates may be even lower than those reported in our study. Fourth, although we studied and adjusted for the most important sociodemographic variables, MI awareness can inherently be driven by personal or familial exposure, which we were not able to assess because NHIS does not include this information. Fifth, because of the low sample size of Asian and other racial/ethnic groups, we could evaluate disparities only among the non-Hispanic white, non-Hispanic black, and Hispanic subgroups. Sixth, we could have overestimated the proportion of individuals choosing to call the EMS in response to a perceived MI because of a social desirability bias in responding; survey respondents may tend to answer questions in a manner that will be viewed favorably by the interviewer. Despite that, millions of individuals chose a different response than immediately calling EMS and could benefit from increasing awareness regarding the importance of early access to medical care. Conclusions Our study found that 53% of US adults in this study, representing 123.7 million adults in the United States, were aware of all 5 MI symptoms, and nearly 6% of individuals in our study, or an estimated 13.5 million adults nationally, were not aware of a single symptom of a MI. Additionally, significant sociodemographic disparities were seen in both the awareness of and appropriate response to MI symptoms. These findings highlight the need for targeted educational campaigns to not only improve awareness of MI symptoms but also emphasize the importance of early access to emergency medical care across all sociodemographic subgroups. ARTICLE INFORMATION Accepted for Publication: October 29, 2019. Published: December 18, 2019. doi:10.1001/jamanetworkopen.2019.17885 Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Mahajan S et al. JAMA Network Open. Corresponding Author: Khurram Nasir, MD, MPH, MSc, Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart and Vascular Center, 6550 Fannin St, Ste 1801, Houston, TX 77030 (knasir@ houstonmethodist.org). JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 11/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States Author Affiliations: Center for Outcomes Research and Evaluation, Yale New Haven Health, New Haven, Connecticut (Mahajan, Desai, Krumholz); Section of Cardiovascular Medicine, Department of Medicine, Yale School of Medicine, New Haven, Connecticut (Mahajan, Desai, Krumholz); Division of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart and Vascular Center, Houston, Texas (Valero-Elizondo, Zoghbi, Nasir); Center for Outcomes Research, Houston Methodist Research Institute, Houston, Texas (Valero-Elizondo, Kash, Nasir); Division of Cardiology, University of Texas Southwestern Medical Center, Dallas (Khera); Cardiovascular Imaging Program, Cardiovascular Division and Department of Radiology, Brigham and Women’s Hospital, Boston, Massachusetts (Blankstein); The Johns Hopkins Ciccarone Center for Prevention of Cardiovascular Disease, Baltimore, Maryland (Blaha); Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas (Virani); Section of Cardiology, Baylor College of Medicine, Houston, Texas (Virani); Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut (Krumholz). Author Contributions: Drs Mahajan and Nasir had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Mahajan, Valero-Elizondo, Khera, Desai, Virani, Kash, Nasir. Acquisition, analysis, or interpretation of data: Mahajan, Valero-Elizondo, Khera, Blankstein, Blaha, Kash, Zoghbi, Krumholz, Nasir. Drafting of the manuscript: Mahajan, Kash, Nasir. Critical revision of the manuscript for important intellectual content: Mahajan, Valero-Elizondo, Khera, Desai, Blankstein, Blaha, Virani, Zoghbi, Krumholz, Nasir. Statistical analysis: Mahajan, Khera. Administrative, technical, or material support: Mahajan, Khera, Desai, Blaha, Kash, Nasir. Supervision: Valero-Elizondo, Nasir. Conflict of Interest Disclosures: Dr Khera reported receiving grants from the National Heart, Lung, and Blood Institute and the National Center for Advancing Translational Sciences outside the submitted work. Dr Desai reported receiving grants and personal fees from Amgen, Boehringer Ingelheim, and Relypsa; receiving personal fees from Cytokinetics, Novartis, and scPharmaceuticals; having a contract with the Centers for Medicare & Medicaid Services; and receiving funding from Johnson and Johnson and Medtronic outside the submitted work. Dr Blankstein reported receiving grants from Astellas Pharma, Amgen, and Gilead Sciences; serving on the advisory board of Amgen; and consulting for EKOS outside the submitted work. Dr Blaha reported receiving grants from the American Heart Association, Aetna, Amgen, the National Institutes of Health, and the US Food and Drug Administration and serving on the advisory boards of Amgen, Sanofi, Regeneron Pharmaceuticals, Novartis, Novo Nordisk, Bayer, and Akcea Therapeutics outside the submitted work. Dr Virani reported receiving grants from the US Department of Veterans Affairs, Houston Veterans Affairs Health Services Research and Development, the American Heart Association, the American Diabetes Association, and the World Heart Federation and receiving honorarium from the American College of Cardiology for serving as associate editor outside the submitted work. Dr Krumholz reported working under contract with the Centers for Medicare & Medicaid Services to support quality measurement programs; being a recipient of a research grant, through Yale University, from Medtronic and the US Food and Drug Administration to develop methods for postmarket surveillance of medical devices; being a recipient of a research grant with Medtronic and being the recipient of a research grant from Johnson and Johnson, through Yale University, to support clinical trial data sharing; being a recipient of a research agreement, through Yale University, from the Shenzhen Center for Health Information for work to advance intelligent disease prevention and health promotion; collaborating with the National Center for Cardiovascular Diseases in Beijing; receiving payment from the Arnold and Porter Law Firm for work related to the Sanofi clopidogrel litigation, from the Ben C. Martin Law Firm for work related to the Cook Celect IVC filter litigation, and from the Siegfried and Jensen Law Firm for work related to Vioxx litigation; chairing a cardiac scientific advisory board for UnitedHealth; being a participant/participant representative of the IBM Watson Health Life Sciences Board; being a member of the advisory board for Element Science, the advisory board for Facebook, and the physician advisory board for Aetna; and being the cofounder of HugoHealth, a personal health information platform, and of Refactor Health, an enterprise healthcare artificial intelligence–augmented data management company outside the submitted work. No other disclosures were reported. REFERENCES 1. Benjamin EJ, Muntner P, Alonso A, et al; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics—2019 update: a report from the American Heart Association. 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Reducing delay in patients with acute coronary syndrome and other time-critical conditions: a systematic review to identify the behaviour change techniques associated with effective interventions. Open Heart. 2019;6(1):e000975-e000975. doi:10.1136/openhrt-2018-000975 37. Mooney M, McKee G, Fealy G, O’ Brien F, O’Donnell S, Moser D. A randomized controlled trial to reduce prehospital delay time in patients with acute coronary syndrome (ACS). J Emerg Med. 2014;46(4):495-506. doi: 10.1016/j.jemermed.2013.08.114 SUPPLEMENT. eMethods. Brief Description of the Survey Design for the National Health Interview Survey eFigure 1. Selection of Study Participants eFigure 2. Distribution of Awareness of Myocardial Infarction Symptoms by Sociodemographic Characteristics eFigure 3. Weighted Proportion of Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms by Sociodemographic Characteristics eFigure 4. Distribution of Awareness of Myocardial Infarction Symptoms and the Weighted Proportion of Non-US- Born Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms, by English Proficiency and Years in the United States eTable 1. Awareness of Individual Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics eTable 2. Awareness of Symptoms of a Myocardial Infarction (0 to 5), by Sociodemographic Characteristics eTable 3. Proportion of Individuals Who Were Not Aware of the 3 Most Common Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 14/15 JAMA Network Open | Cardiology Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States eTable 4. Association Between Population Characteristics and Awareness of Myocardial Infarction Symptoms Using Multinomial Regression Analysis eTable 5. Distribution of Different Responses to Assessment of Emergency Response to Suspicion of Myocardial Infarction eTable 6. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics eTable 7. Association of Sociodemographic Characteristics With Choosing a Response Other Than Calling Emergency Medical Services on Suspicion of a Myocardial Infarction Using Logistic Regression eTable 8. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics and Awareness of Myocardial Infarction Symptoms JAMA Network Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 (Reprinted) December 18, 2019 15/15 Supplementary Online Content Mahajan S, Valero-Elizondo J, Khera R, et al. Variation and disparities in awareness of myocardial infarction symptoms among adults in the United States. JAMA Netw Open. 2019;2(12):e1917885. doi:10.1001/jamanetworkopen.2019.17885 eMethods. Brief Description of the Survey Design for the National Health Interview Survey eFigure 1. Selection of Study Participants eFigure 2. Distribution of Awareness of Myocardial Infarction Symptoms by Sociodemographic Characteristics eFigure 3. Weighted Proportion of Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms by Sociodemographic Characteristics eFigure 4. Distribution of Awareness of Myocardial Infarction Symptoms and the Weighted Proportion of Non-US-Born Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms, by English Proficiency and Years in the United States eTable 1. Awareness of Individual Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics eTable 2. Awareness of Symptoms of a Myocardial Infarction (0 to 5), by Sociodemographic Characteristics eTable 3. Proportion of Individuals Who Were Not Aware of the 3 Most Common Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics eTable 4. Association Between Population Characteristics and Awareness of Myocardial Infarction Symptoms Using Multinomial Regression Analysis eTable 5. Distribution of Different Responses to Assessment of Emergency Response to Suspicion of Myocardial Infarction eTable 6. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics eTable 7. Association of Sociodemographic Characteristics With Choosing a Response Other Than Calling Emergency Medical Services on Suspicion of a Myocardial Infarction Using Logistic Regression © 2019 Mahajan S et al. JAMA Network Open. eTable 8. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics and Awareness of Myocardial Infarction Symptoms This supplementary material has been provided by the authors to give readers additional information about their work. © 2019 Mahajan S et al. JAMA Network Open. eMethods. Brief Description of the Survey Design for the National Health Interview Survey National Health Interview Survey (NHIS) is an annual, cross-sectional national weighted survey that provides estimates on the noninstitutionalized US population using multistage sampling. Response rates The participation rates for NHIS are actually very high. The conditional response rate for the Sample Adult component was 80.7%, which was calculated by dividing the number of completed Sample Adult interviews (n=26,742) by the total number of eligible sample adults (n=33,143). Weighting The final Sample Adult Weight includes design, ratio, nonresponse and post-stratification adjustments for sample adults. National estimates of all sample adult variables can be made using these weights. Use of Proxy In the NHIS, sample adults generally respond for themselves, although in a small number of cases, proxy responses are allowed if the selected adult had a physical or mental condition prohibiting him/her from responding. In the case of a proxy, the relationship to the sample adult is obtained. Of the 26,742 adults included in the NHIS in 2017, only in 423 cases or 1.58% cases, a knowledgeable proxy answered for the sample adult. Of these 423 cases, in 367 (87%) cases the proxy was a relative who lived in the same household. Source: National Center for Health Statistics. Survey Description, National Health Interview Survey, 2017. Hyattsville, Maryland. 2018. © 2019 Mahajan S et al. JAMA Network Open. eFigure 1. Selection of Study Participants © 2019 Mahajan S et al. JAMA Network Open. eFigure 2. Distribution of Awareness of Myocardial Infarction Symptoms by Sociodemographic Characteristics Abbreviations: US, United States © 2019 Mahajan S et al. JAMA Network Open. eFigure 3. Weighted Proportion of Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms by Sociodemographic Characteristics Abbreviations: US, United States © 2019 Mahajan S et al. JAMA Network Open. eFigure 4. Distribution of Awareness of Myocardial Infarction Symptoms and the Weighted Proportion of Non-US- Born Individuals Who Were Not Aware of Any Myocardial Infarction Symptoms, by English Proficiency and Years in the United States A. Distribution of awareness of myocardial infarction symptoms among non-US-born individuals. © 2019 Mahajan S et al. JAMA Network Open. B. Weighted proportion of non-US-born individuals who were not aware of any myocardial infarction symptoms. © 2019 Mahajan S et al. JAMA Network Open. eTable 1. Awareness of Individual Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics Chest pain or Pain or discomfort in Feeling weak, Jaw, neck, or back Characteristics Shortness of breath discomfort arm lightheaded, or faint pain No. % Aware No. % Aware No. % Aware No. % Aware No. % Aware aware (95% CI) aware (95% CI) aware (95% CI) aware (95% CI) aware (95% CI) 91.8 (91.0- 87.0 (86.1- 85.7 (84.8- 77.0 (76.1- 62.6 (61.6- Overall 23,383 22,158 22,064 19,760 16,567 92.6) 87.8) 86.5) 77.9) 63.7) Age, y 91.5 (90.4- 86.8 (85.7- 81.1 (79.8- 76.9 (75.5- 53.3 (51.8- 18-39 7,576 7,186 6,780 6,390 4,521 92.5) 87.9) 82.4) 78.2) 54.9) 92.2 (91.3- 87.2 (86.1- 88.3 (87.3- 77.3 (76.1- 66.2 (64.9- 40-64 9,592 9,089 9,248 8,133 7,043 93.1) 88.1) 89.3) 78.5) 67.5) 91.4 (90.3- 86.9 (85.7- 88.9 (87.8- 76.6 (75.1- 73.1 (71.7- 65 6,215 5,883 6,036 5,237 5,003 92.5) 88.0) 90.0) 78.0) 74.6) Sex 91.4 (90.5- 86.1 (85.0- 83.9 (82.7- 75.8 (74.7- 57.6 (56.3- Men 10,562 9,939 9,788 8,799 6,870 92.3) 87.0) 85.0) 76.9) 58.9) 92.1 (91.1- 87.9 (86.9- 87.4 (86.3- 78.1 (77.0- 67.3 (66.1- Women 12,821 12,219 12,276 10,961 9,697 93.0) 88.8) 88.4) 79.2) 68.6) Race/Ethnicity Non-Hispanic 94.4 (93.5- 89.9 (89.0- 90.5 (89.7- 81.4 (80.5- 68.5 (67.4- 16,959 16,153 16,318 14,643 12,582 White 95.1) 90.7) 91.3) 82.3) 69.5) Non-Hispanic 90.5 (88.6- 85.1 (82.9- 79.1 (76.6- 72.0 (69.5- 55.7 (53.1- 2,525 2,364 2,267 1,995 1,591 Black 92.2) 87.0) 81.4) 74.3) 58.2) 84.8 (83.0- 79.5 (77.3- 76.9 (74.8- 66.3 (64.1- 46.8 (44.2- Hispanic 2,529 2,356 2,331 2,000 1,498 86.4) 81.5) 78.9) 68.5) 49.5) Immigration status 93.6 (92.8- 89.1 (88.2- 88.6 (87.8- 79.7 (78.8- 65.4 (64.3- US-born 20,523 19,514 19,573 17,531 14,820 94.4) 89.9) 89.4) 80.6) 66.4) 83.1 (81.4- 77.2 (75.1- 71.6 (69.4- 64.0 (61.7- 49.6 (47.1- Non-US-born 2,843 2,629 2,474 2,217 1,739 84.6) 79.1) 73.7) 66.2) 52.2) Education Some college 93.7 (92.9- 89.0 (88.1- 88.4 (87.5- 80.3 (79.3- 65.4 (64.2- 15,566 14,823 14,774 13,427 11,269 or higher 94.4) 89.8) 89.2) 81.3) 66.6) High school or 88.5 (87.2- 83.3 (82.1- 80.8 (79.3- 71.2 (69.8- 57.8 (56.3- 7,755 7,278 7,233 6,285 5,257 lower 89.6) 84.5) 82.1) 72.5) 59.2) © 2019 Mahajan S et al. JAMA Network Open. eTable 1. Continued. Family income 94.4 (93.4- 90.0 (88.9- 89.7 (88.7- 81.1 (79.8- 67.1 (65.6- High-income 9,124 8,728 8,726 7,905 6,694 95.2) 90.9) 90.6) 82.3) 68.5) Middle- 91.7 (90.6- 86.4 (85.1- 86.0 (84.6- 76.9 (75.4- 62.1 (60.4- 6,264 5,914 5,952 5,297 4,481 ) ) ) ) ) income 92.7 87.7 87.3 78.3 63.7 88.8 (87.4- 83.6 (82.0- 81.0 (79.3- 72.9 (71.2- 57.2 (55.2- Low-income 3,782 3,552 3,526 3,139 2,569 90.1) 85.0) 82.6) 74.6) 59.2) Lowest- 87.7 (85.7- 83.1 (81.2- 77.8 (75.2- 70.6 (68.3- 55.3 (52.7- 2,875 2,697 2,590 2,326 1,853 income 89.5) 84.8) 80.2) 72.8) 57.8) Insurance Private 93.2 (92.2- 88.3 (87.3- 87.1 (86.1- 79.0 (77.8- 62.5 (61.2- 12,002 11,409 11,282 10,254 8,266 insurance 94.1) 89.3) 88.1) 80.1) 63.8) Public 91.0 (90.0- 86.4 (85.4- 86.6 (85.6- 76.0 (74.8- 66.6 (65.4- 9,424 8,916 9,034 7,928 7,128 Insurance 91.9) 87.4) 87.6) 77.2) 67.8) 86.4 (84.3- 81.4 (79.1- 74.4 (71.6- 69.2 (66.6- 50.1 (47.3- Uninsured 1,884 1,766 1,687 1,520 1,136 88.2) 83.6) 77.1) 71.6) 52.9) Region 92.4 (91.0- 86.9 (85.2- 86.0 (84.1- 77.8 (75.6- 64.4 (62.1- Northeast 3,817 3,594 3,589 3,197 2,735 93.6) 88.5) 87.7) 79.8) 66.6) 93.9 (92.7- 89.1 (87.6- 88.3 (86.9- 79.2 (77.4- 64.8 (63.0- Midwest 5,687 5,415 5,391 4,843 4,045 94.9) 90.4) 89.6) 81.0) 66.5) 90.4 (88.6- 85.5 (83.7- 84.2 (82.2- 75.5 (73.9- 61.9 (60.0- South 8,520 8,070 8,054 7,147 6,048 91.9) 87.1) 86.0) 77.0) 63.8) 91.6 (89.8- 87.4 (86.0- 85.3 (83.7- 76.6 (74.6- 60.3 (58.1- West 5,359 5,079 5,030 4,573 3,739 93.0) 88.7) 86.8) 78.5) 62.5) Note: % aware represents the weighted proportion of adults who were aware of that symptom. Abbreviations: CI, Confidence Interval; US, United States © 2019 Mahajan S et al. JAMA Network Open. eTable 2. Awareness of Symptoms of a Myocardial Infarction (0 to 5), by Sociodemographic Characteristics Characteristics None of the 5 1 of the 5 2 of the 5 3 of the 5 4 of the 5 All 5 Weighted Weighted Weighted Weighted Weighted Weighted n n n n n n % % % % % % Overall 1295 5.77% 483 1.97% 990 4.32% 2618 11.32% 5810 23.61% 14,075 53.01% Age (years) 18-39 454 6.11% 150 1.76% 382 5.37% 1094 14.40% 2333 27.82% 3785 44.54% 40-64 499 5.64% 181 2.00% 342 3.52% 958 9.91% 2254 22.22% 6070 56.71% 65 342 5.39% 152 2.29% 266 4.00% 566 8.29% 1223 18.32% 4220 61.72% Sex Men 624 6.16% 223 1.97% 544 4.98% 1354 12.88% 2945 25.84% 5761 48.17% Women 671 5.41% 260 1.96% 446 3.71% 1264 9.85% 2865 21.51% 8314 57.57% Race/Ethnicity Non-Hispanic 653 3.97% 224 1.30% 515 3.01% 1549 8.84% 4091 23.60% 10,878 59.27% White Non-Hispanic 164 6.60% 77 2.41% 193 6.89% 395 15.37% 671 23.62% 1282 45.11% Black Hispanic 331 10.47% 126 3.73% 180 6.63% 450 16.82% 737 24.97% 1186 37.39% Immigration status US-born 877 4.50% 324 1.40% 735 3.60% 2091 10.26% 5101 24.22% 12,698 56.01% Non-US-born 418 11.87% 159 4.67% 254 7.77% 523 16.31% 704 20.66% 1370 38.73% Education Some college or 667 4.55% 215 1.36% 539 3.60% 1529 10.05% 3856 24.22% 9711 56.23% higher High school or 623 8.04% 263 2.97% 447 5.66% 1078 13.48% 1943 22.53% 4329 47.31% lower Family income High-income 339 3.98% 126 1.48% 273 3.21% 818 9.43% 2189 23.57% 5859 58.34% Middle-income 334 5.79% 96 1.75% 252 4.40% 695 11.55% 1577 24.65% 3783 51.86% Low-income 285 7.76% 117 2.64% 219 5.81% 495 12.92% 982 23.85% 2120 47.02% Lowest-income 222 8.06% 116 3.56% 183 5.81% 456 15.52% 764 22.53% 1487 44.52% Insurance Private insurance 547 4.93% 173 1.63% 446 3.99% 1290 10.83% 3167 25.08% 7122 53.54% Public Insurance 534 6.00% 223 1.99% 436 4.62% 992 10.23% 2086 21.06% 6003 56.10% Uninsured 211 9.94% 84 3.79% 103 5.19% 316 16.94% 540 24.13% 919 40.00% © 2019 Mahajan S et al. JAMA Network Open. eTable 2. Continued. Characteristics None of the 5 1 of the 5 2 of the 5 3 of the 5 4 of the 5 All 5 Weighted n n Weighted % n Weighted % n Weighted % n Weighted % n Weighted % Region Northeast 192 5.40% 95 2.38% 175 4.55% 408 10.12% 902 22.16% 2331 55.40% Midwest 245 4.44% 83 1.44% 189 3.34% 582 10.35% 1511 26.06% 3426 54.37% South 588 6.99% 204 2.11% 394 4.51% 1001 11.67% 2051 22.24% 5128 52.48% West 270 5.42% 101 1.92% 232 4.77% 627 12.61% 1346 24.59% 3190 50.70% Abbreviations: US, United States. © 2019 Mahajan S et al. JAMA Network Open. eTable 3. Proportion of Individuals Who Were not Aware of the 3 Most Common Symptoms of a Myocardial Infarction, by Sociodemographic Characteristics 3 most common symptoms include: chest pain/discomfort; pain/discomfort in arms/shoulders; and shortness of breath Characteristics n Weighted % (95% CI) US population (n) Overall 4698 20.33 (19.38 - 21.32) 47,454,926 Age (years) 18-39 1859 24.70 (23.31 - 26.13) 22,168,989 40-64 1650 17.58 (16.50 - 18.72) 17,196,499 65 1189 17.65 (16.38 - 18.99) 8,089,438 Sex Men 2396 22.57 (21.35 - 23.83) 25,511,966 Women 2302 18.23 (17.10 - 19.41) 21,942,960 Race/Ethnicity Non-Hispanic White 2541 14.76 (13.87 - 15.69) 22,401,380 Non-Hispanic Black 716 27.53 (25.04 - 30.18) 7,831,386 Hispanic 936 31.65 (29.36 - 34.02) 11,652,343 Immigration status US-born 3469 16.97 (16.05 - 17.92) 32,732,662 Non-US-born 1227 36.42 (34.23 - 38.67) 14,698,828 Education Some college or higher 2610 17.11 (16.15 - 18.12) 25,801,663 High school or lower 2067 26.13 (24.68 - 27.63) 21,365,049 Family Income High-income 1325 15.28 (14.18 - 16.45) 14,437,408 Middle-income 1209 20.82 (19.30 - 22.43) 12,985,918 Low-income 989 25.74 (24.01 - 27.56) 9,427,720 Lowest-income 879 29.43 (26.88 - 32.11) 7,510,476 Insurance Private insurance 2119 18.38 (17.21 - 19.61) 23,865,065 Public Insurance 1935 20.14 (19.07 - 21.26) 16,081,776 Uninsured 619 31.34 (28.70 - 34.11) 7,081,116 Region Northeast 764 20.02 (18.04 - 22.16) 8,579,151 Midwest 956 17.05 (15.45 - 18.79) 8,724,961 South 1880 21.80 (19.92 - 23.81) 18,533,609 West 1098 21.36 (19.72 - 23.09) 11,617,205 Abbreviations: CI, confidence intervals; US, United States. © 2019 Mahajan S et al. JAMA Network Open. eTable 4. Association Between Population Characteristics and Awareness of Myocardial Infarction Symptoms Using Multinomial Regression Analysis Characteristics Aware of 1* Aware of 2* Aware of 3* Aware of 4* Aware of 5* RRR (95% CI) RRR (95% CI) RRR (95% CI) RRR (95% CI) RRR (95% CI) Sex Men (Reference: Women) 0.90 (0.67 - 1.21) 1.08 (0.85 - 1.36) 1.08 (0.90 - 1.30) 0.95 (0.80 - 1.13) 0.67 (0.57 - 0.79) Race/Ethnicity Non-Hispanic Blacks † † (Reference: Non-Hispanic 1.06 (0.68 - 1.65) 1.52 (1.04 - 2.24) 1.15 (0.79 - 1.68) 0.74 (0.52 - 1.05) 0.60 (0.43 - 0.84) Whites) Hispanics † † (Reference: Non-Hispanic 0.75 (0.47 - 1.18) 0.82 (0.54 - 1.24) 0.78 (0.58 - 1.04) 0.60 (0.46 - 0.79) 0.42 (0.33 - 0.54) Whites) Immigration status Non-US-born (Reference: † † † 1.29 (0.87 - 1.91) 0.91 (0.64 - 1.29) 0.70 (0.53 - 0.93) 0.48 (0.37 - 0.62) 0.46 (0.36 - 0.58) US-born) Education High school or lower † † † (Reference: Some college 1.42 (1.05 - 1.93) 1.08 (0.80 - 1.47) 0.94 (0.75 - 1.17) 0.73 (0.61 - 0.89) 0.68 (0.56 - 0.82) or higher) *All compared to aware of none of the symptoms P-value <0.05 Abbreviations CI, Confidence Interval; RRR, Relative Risk Ratio; US, United States © 2019 Mahajan S et al. JAMA Network Open. eTable 5. Distribution of Different Responses to Assessment of Emergency Response to Suspicion of Myocardial Infarction Responses n Weighted % (95% CI) Call 911 or another emergency medical services number 24,088 95.54% (95.05 - 95.99) Advise to drive to hospital 210 0.97% (0.76 - 1.23) Advise to call physician 155 0.61% (0.47 - 0.79) Call spouse or family member 99 0.39 (0.29 - 0.52) Other 666 2.49 (2.21 - 2.80) Abbreviations: CI, Confidence Interval. © 2019 Mahajan S et al. JAMA Network Open. eTable 6. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics Other responses include - advise to call physician, drive to hospital, call spouse or family member, and other. Characteristics n Weighted % US population, n p-value Overall 1130 4.46 10,381,192 Age (years) 0.001 18-39 285 3.95 3,542,792 40-64 435 4.27 4,168,065 65 410 5.84 2,670,335 Sex 0.02 Women 590 4.09 4,909,591 Men 540 4.85 5,471,601 Race/Ethnicity 0.075 Non-Hispanic White 771 4.09 6,202,974 Non-Hispanic Black 102 4.42 1,254,474 Hispanic 162 5.50 2,014,323 Immigration status 0.005 US-born 933 4.16 8,012,087 Non-US-born 197 5.90 2,369,105 Education 0.001 Some college or higher 671 3.91 5,888,368 High school or lower 455 5.47 4,457,629 Family income <0.001 High-income 360 3.59 3,394,545 Middle-income 293 4.36 2,711,562 Low-income 221 5.42 1,980,933 Lowest-income 165 5.87 1,490,372 Insurance <0.001 Private insurance 436 3.53 4,574,316 Public Insurance 565 5.27 4,198,735 Uninsured 125 6.82 1,536,767 Region 0.452 Northeast 185 3.99 1,705,125 Midwest 267 4.29 2,194,212 South 424 4.89 4,149,487 West 254 4.30 2,332,368 Abbreviations: US, United States. © 2019 Mahajan S et al. JAMA Network Open. eTable 7. Association of Sociodemographic Characteristics With Choosing a Response Other Than Calling Emergency Medical Services on Suspicion of a Myocardial Infarction Using Logistic Regression Other responses include - advise to call physician, drive to hospital, call spouse or family member, and other. Characteristics Unadjusted Model Adjusted Model* OR (95% CI) p-value OR (95% CI) p-value Age (years) 18-39 Reference Reference 40-64 1.08 (0.88 - 1.34) 0.453 1.08 (0.85 - 1.38) 0.515 65 1.51 (1.19 - 1.91) 0.001 1.63 (1.22 - 2.19) 0.001 Sex Women Reference Reference Men 1.20 (1.03 - 1.40) 0.023 1.23 (1.04 - 1.46) 0.016 Race/Ethnicity Non-Hispanic White Reference Reference Non-Hispanic Black 1.08 (0.76 - 1.53) 0.650 0.99 (0.72 - 1.38) 0.968 Hispanic 1.36 (1.07 - 1.73) 0.010 1.15 (0.77 - 1.71) 0.493 Immigration status US born Reference Reference Non-US born 1.45 (1.12 - 1.88) 0.005 1.20 (0.81 - 1.78) 0.369 Education Some college or higher Reference Reference High school or lower 1.42 (1.19 - 1.70) <0.001 1.22 (1.00 - 1.49) 0.046 Family income High-income Reference Reference Middle-income 1.22 (1.00 - 1.49) 0.046 1.05 (0.83 - 1.33) 0.049 Low-income 1.54 (1.21 - 1.95) <0.001 1.16 (0.86 - 1.56) 0.339 Lowest-income 1.67 (1.22 - 2.29) 0.001 1.37 (1.00 - 1.88) 0.679 Insurance Private insurance Reference Reference Public Insurance 1.52 (1.28 - 1.81) <0.001 1.11 (0.86 - 1.44) 0.434 Uninsured 2.00 (1.49 - 2.69) <0.001 1.59 (1.19 - 2.12) 0.001 Region Midwest Reference Reference Northeast 0.93 (0.68 - 1.25) 0.615 1.07 (0.77 - 1.48) 0.691 South 1.15 (0.85 - 1.54) 0.365 1.06 (0.79 - 1.42) 0.702 West 1.00 (0.77 - 1.30) 0.992 0.99 (0.74 - 1.34) 0.954 *Model adjusted for all population characteristics Abbreviations: OR, odds ratios; CI, confidence intervals; US, United States. © 2019 Mahajan S et al. JAMA Network Open. eTable 8. Proportion of Individuals Who Chose a Response Other Than Calling Emergency Medical Services in Response to Suspicion of a Myocardial Infarction, by Sociodemographic Characteristics and Awareness of Myocardial Infarction Symptoms Aware of all 5 symptoms Characteristics Aware of none of the symptoms n Weighted % (95% CI) n Weighted % (95% CI) Overall 115 9.79 (7.69 - 12.40) 538 3.44 (3.07 - 3.85) Age (years) 18-39 43 11.15 (7.84 - 15.62) 89 2.30 (1.77 - 2.99) 40-64 34 7.86 (5.19 - 11.75) 218 3.35 (2.85 - 3.93) 65 38 11.03 (7.42 - 16.07) 231 5.24 (4.51 - 6.07) Sex Women 60 9.60 (6.20 - 14.56) 307 3.23 (2.80 - 3.72) Men 55 9.98 (7.46 - 13.23) 231 3.71 (3.16 - 4.36) Race/Ethnicity Non-Hispanic White 43 7.47 (4.69 - 11.70) 414 3.43 (3.03 - 3.88) Non-Hispanic Black 15 13.71 (7.50 - 23.74) 42 2.69 (1.84 - 3.93) Hispanic 40 10.42 (7.32 - 14.63) 43 3.83 (2.61 - 5.61) Immigration status US-born 66 8.94 (6.46 - 12.24) 490 3.48 (3.09 - 3.93) Non-US-born 49 11.39 (8.45 - 15.17) 48 3.16 (2.21 - 4.51) Education Some college or higher 45 7.64 (5.45 - 10.61) 360 3.34 (2.94 - 3.80) High school or lower 69 11.97 (8.94 - 15.84) 176 3.66 (3.01 - 4.44) Family income* High/middle-income 51 7.63 (5.27 - 10.93) 343 3.18 (2.77 - 3.65) Low/lowest-income 55 12.50 (9.19 - 16.79) 4.19 (3.44 - 5.11) Insurance Private insurance 50 8.21 (5.03 - 13.11) 311 2.48 (2.09 - 2.93) 192 4.93 (4.28 - 5.69) Public Insurance 39 10.43 (7.50 - 14.33) Uninsured 26 13.14 (8.44 - 19.89) 35 3.63 (2.34 - 5.59) Region 102 3.60 (2.73 - 4.73) Northeast 12 5.93 (2.70 - 12.51) 125 3.25 (2.61 - 4.04) Midwest 16 8.92 (4.93 - 15.62) 180 3.27 (2.72 - 3.92) South 61 11.07 (7.69 - 15.70) 131 3.79 (2.93 - 4.88) West 26 10.94 (7.19 - 16.29) Abbreviations: CI, confidence interval; US, United States *We combined high-income and middle-income groups into high/middle-income, and low-income and lowest-income groups into low/lowest-income due to small sample sizes. © 2019 Mahajan S et al. JAMA Network Open.

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JAMA Network Open – American Medical Association

Published: Dec 18, 2019

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Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States

Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States

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Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States

Variation and Disparities in Awareness of Myocardial Infarction Symptoms Among Adults in the United States

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