Factors Associated with Healthcare Avoidance among US Adults: Analyses of the 2019 Healthy Information National Trends Survey

Research Article

J Fam Med. 2021; 8(9): 1280.

Factors Associated with Healthcare Avoidance among US Adults: Analyses of the 2019 Healthy Information National Trends Survey

Bista S1, Yu R2, Shete S2,3,4#* and Shastri SS1#*

1Department of Health Disparities Research, University of Texas MD Anderson Cancer Center, USA

2Department of Biostatistics, University of Texas MD Anderson Cancer Center, USA

3Department of Epidemiology, University of Texas MD Anderson Cancer Center, USA

4Division of Cancer Prevention and Population Science, University of Texas MD Anderson Cancer Center, USA

#Co-Senior Authors and Co-Communicating Authors

*Corresponding author: Surendra Shastri, Department of Health Disparities Research, University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA

Sanjay Shete, 1400 Pressler Dr, Houston, TX 77030, USA

Received: October 20, 2021; Accepted: November 17, 2021; Published: November 24, 2021


Background: Healthcare avoidance represents a significant impediment to health and well-being of individuals and society. Avoidance undermines positive healthcare-seeking and carries significant health and economic consequences including increased morbidity and mortality as well as loss of job or economic productivity.

Objective: The current study analyzed factors associated with healthcare avoidance.

Methods: Using the 2019 Healthy Information National Trends Survey, we conducted multiple logistic regression to identify factors associated with avoiding doctor’s visit even when deemed necessary. Factors included sociodemographic, economic, access to health care, health care practices and trust to better understand medical care avoidance.

Results: Notably, 30.3% of Americans reported healthcare avoidance, and 29% reported “no/little/some trust” in medical information from the doctor. Greater likelihood of healthcare avoidance was observed among those who had less trust in medical information from their doctor, younger, and male. Significant health behavior predictors of healthcare avoidance included current smokers, those who had infrequent visits to health professionals, and those with better self-reported health.

Conclusions: By identifying multiple factors that may be associated with healthcare avoidance we can identify individuals at risk for avoidant behaviors and encourage positive health behavior.

Keywords: Healthcare avoidance; Trust in doctor; Health behaviors; Health promotion


Health behaviors are intentional or unintentional actions taken by individuals that can shape and directly impact health and general well-being [1,2]. Adoption of positive, health-promoting behaviors such as healthy diet, regular physical activity, avoiding risky behaviors (e.g. smoking), and timely utilization of health-care services (e.g. regular check-ups, cancer screening) are associated with reduced risk of cancer, diabetes, cardiovascular disease and other health problems [3-6]. In contrast, unhealthy lifestyle choices, health risky behavior and underutilization of health-care services are known to have adverse health consequences [7]. Medical care-seeking behavior in particular is an action taken by individuals that address healthrelated symptoms including seeking help from a range of medical channels to prevent, allay and treat health issues [8]. Not seeking needed or necessary medical care or avoiding visits to healthcare facilities represents a significant impediment to health promotion and overall well-being [9]. Such behavior is encapsulated in the concept of healthcare avoidance, which remains a prevalent issue among US adult populations [9].

The term avoidance is defined as the act of turning away from a perceived threat that evokes emotional or physiological distress, and often discussed as a coping strategy during stressful situations [9]. In the healthcare context, avoidance can manifest as treatment refusal (e.g. canceling appointments) or nonadherence, denial of symptoms and/or diagnosis [9-11], or delayed treatment seeking [9,12]. Thus, treatment avoidance undermines positive healthcare-seeking behaviors and carries significant health and economic consequences [10,13,14]. Healthcare avoidance makes a critical contribution to late stage disease diagnosis and poor survival rate [9,15,16]. Avoidance in the form of delaying screening and treatment have been associated with increased likelihood of late-stage breast cancer diagnosis, acute symptoms for heart disease, mortality from HIV [10,15,17,18], longer duration and cost of hospitalization, and loss of work productivity [17,19,20].

To better understand the phenomenon of healthcare avoidance, the Behavioral Model of Healthcare Service Use sheds insight into the social determinants of healthcare avoidance. Following this framework, healthcare avoidance is multifactorial, and a result of interplay of various individual and system-level factors [21]. Previous studies have related healthcare avoidance to sociodemographic factors (e.g. age, education, income), logistical barriers (e.g. lack of health insurance, scheduling issues), personal attitudes and beliefs (e.g. cancer worry, fatalistic attitude towards cancer) and provider-related factors (e.g. no usual source of care, provider distrust) [13,16,18,22- 24]. Studies examining predictors of treatment avoidance or delay have largely focused on patient populations such as those with breast cancer [10,25], rectal cancer [26], history of stroke [27], obesity [28], and diabetes and cardiovascular disease [29], or have narrowly focused on specific avoidant behaviors such as cancer screening and treatment [9,30].

Although healthcare avoidance is a common occurrence, existing studies are limited in its scope to provide a comprehensive account of this dynamic and complex phenomenon [9]. There is a need to advance more studies that emphasize systematic identification of various characteristics or factors that influence healthcare avoidance. The current study examines correlates of healthcare avoidance among US adults using a large, nationally representative dataset. We include several predisposing factors including socio-demographic, economic, access to health care, health care practices and trust to broaden our understanding of the notion of medical care avoidance.


Data and sample

In this study, we analyzed publicly available data from National Cancer Institute’s Health Information National Trends Survey 5 (HINTS 5) Cycle 3 (2019), which is a large-scale, household interview survey of noninstitutionalized US adults aged ≥18 years. The purpose of HINTS was to investigate trends in the publics’ attitudes, knowledge, and practices related to cancer-related healthcare access and use. Data collection was conducted from January 22 to April 30, 2019, and we used available sampling weights to derive population estimates. Additional information about the survey development, design, and methodology are described elsewhere [31].


Dependent variable: We used a one item measure to assess healthcare avoidance (i.e., ‘‘some people avoid visiting their doctor even when they suspect they should. Would you say this is true for you, or not true for you?”) That was rated as “True” or “Not True.”

Independent variables: Demographic factors included age (i.e., 18-34 years, 35-49 years, 50-64 years, 65+), sex (male or female), race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, or non-Hispanic Other), and place of residence (rural or urban). Respondents that identified as non-Hispanic White, 65+ years, female, and living in urban areas were considered as the reference group for their respective categories.

Socioeconomic factors included annual household income (<$35,000, $35,000-$49,999, $50,000-$74,999, or ≥$75,000) and education (≤ high school graduate, post high school or some college graduate, and college or postgraduate). College or postgraduate and earning <$35,000/year were the reference groups for their respective categories.

Lack of access to healthcare was measured with a single yes/ no question assessing health insurance status for a range of health insurance plans (i.e., “Are you currently covered by any of the following types of health insurance or health coverage plans?”). Listed insurance coverage included: “Insurance through a current or former employer or union”, “Insurance purchased directly from an insurance company,” “Medicare, for people 65 and older, people with certain disabilities,” “Medicaid, Medical Assistance, or any kind of government-assistance plan for those with low incomes or a disability,” “TRICARE or other military health care,” “ VA (including those who have ever used or enrolled for VA health care),” “Indian Health Service,” and “Any other type of health insurance or health coverage plan.” The “yes” response was used as reference.

Health-related practice was measured using two items related to frequency of healthcare visits and smoking status. Healthcare visit frequency was measured using a single frequency item (i.e., “In the past 12 months, not counting times you went to an emergency room, how many times did you go to a doctor, nurse, or other health professional to get care for yourself?”) rated on a 5-point scale (“None,” “1 or 2 times,” “3 or 4 times,” “5-9 times,”≥10 times”).

Smoking status was based on two questions related to cigarette smoking quantity (i.e., “Have you smoked at least 100 cigarettes in your entire life?”) and frequency (i.e., “How often do you now smoke cigarettes?”). Participants were asked to rate quantity with a yes/ no, and frequency with a 3-point scale (“not at all,” “some days,” or “everyday”). Participants were placed into one of three categories: (1) never smoker (“no” response to quantity question), (2) former smoker (“yes” response to the quantity, and “not at all” response to frequency question), or (3) current smoker (“yes” response to the quantity, and “every day” or “some days” response to the frequency question).

Health status was based on a single item of self-reported general health (i.e., “In general, would you say your health is…”) rated on a 5-point scale (1 = excellent, 2 = very good, 3 = good, 4 = fair/poor).

Trust in information from a doctor was assessed with a single item (i.e., “In general, how much would you trust information about health or medical topics from each of the following? A doctor”) rated on a 4-point scale (3 = a lot, 2 = some, 1 = a little, or 0 = not at all). The “some,” “a little,” and “not at all” responses were combined.

Statistical analyses

Statistical analyses were conducted using survey weights to account for the HINTS data collection strategies. The computation of weights involved calculating household-level base weights; adjusting for non-response; calculating person-level weights; and calibrating the person-level weights to population counts using the American Community Survey (HINTS 2019). Weighted prevalence of healthcare avoidance was calculated by demographic, socioeconomic, health access, psychosocial, behavioral, and overall health characteristics. We conducted survey-weighted logistic regression to evaluate factors associated with healthcare avoidance. Statistical significance was declared when a 2-sided p-value was ≤ 0.05. All analyses were conducted using SAS, version 9.4 and were weighted to be nationally representative.


Table 1 summarizes weighted percentages of demographic, socioeconomic, health access, psychosocial, behavioral, and overall health characteristics of study population stratified by whether respondents agreed that they avoid visiting their doctor even when they suspect they should. Overall, 30.5% endorsed healthcare avoidance with greater frequency among those between 18 and 34 years old (41%), males (35.4%), Hispanics (36.8%), those living in rural areas (34.6%), ≥ high school degree (36.4%), annual household income $35,000-49,999 (36.8%) and $50,000-75,999 (36.8%), current smokers (40.5%), those having some, little, or no trust in information coming doctors (41.7%), those having visited a health professional ≥10 in the past year (27.4%), those reporting fair/poor health (39.4%), and those without health insurance (52.9%).

Citation:Bista S, Yu R, Shete S and Shastri SS. Factors Associated with Healthcare Avoidance among US Adults: Analyses of the 2019 Healthy Information National Trends Survey. J Fam Med. 2021; 8(9): 1280.