Bronchial asthma is one of the most prevalent chronic respiratory diseases globally, affecting an estimated 262 million people and causing approximately 461,000 deaths annually. In India, the burden is substantial — the national prevalence ranges from 2.05% to 4.5% in adults, translating to approximately 30–35 million affected individuals, with significant urban-rural variation and emerging evidence of underdiagnosis. Despite remarkable advances in pharmacological therapy over the past three decades — from inhaled corticosteroids (ICS) to combination ICS/LABA therapy, biologics, and novel small molecules — a disturbingly large proportion of patients continue to experience uncontrolled or partially controlled disease. The Global Initiative for Asthma (GINA) stratifies asthma control into three levels — well-controlled, partly controlled, and uncontrolled — based on daytime and nocturnal symptoms, reliever use, activity limitation, and lung function. Real-world studies consistently demonstrate that asthma control remains suboptimal globally: the International AIRE (Asthma Insights and Reality in Europe) survey reported that only 5.3% of patients had well-controlled asthma, and data from INSPIRE and LIAISON studies confirm these patterns persist across diverse healthcare settings. Medication non-adherence is widely recognized as the single most important modifiable factor underlying poor asthma control. The World Health Organization estimates that 50% of patients with chronic conditions are non-adherent to their prescribed regimens, and asthma-specific adherence rates are frequently reported below 50% in clinical studies. In the context of inhaled therapy — the cornerstone of asthma treatment — non-adherence encompasses both intentional behavior (active decision to reduce or discontinue therapy) and unintentional factors (forgetting, poor inhaler technique, misunderstanding the prescribed regimen). The consequences of medication non-adherence in asthma are well-documented and clinically serious: increased frequency of acute exacerbations, emergency department visits, hospitalizations, accelerated lung function decline, and preventable mortality. From a health systems perspective, non-adherence generates substantial avoidable costs — estimated at USD 300 billion annually in the United States alone from disease consequences attributable to poor adherence across chronic diseases. In India, additional layers of complexity influence adherence: cost of inhalers and medications, deeply ingrained cultural misconceptions about inhaler use (fear of steroid dependence, stigma of device use in public), low health literacy, irregularity of follow-up in overburdened public health systems, and the perception that asthma is a disease to be managed only when symptomatic. These factors may create unique patterns of non-adherence distinct from those reported in Western populations. Despite the clinical importance of this topic, there is a paucity of studies from Indian tertiary care settings that simultaneously assess asthma control levels, quantify medication adherence using validated instruments, and rigorously examine the determinants and interrelationship between these two outcomes. This cross-sectional study was designed to address this gap.

2.1 Study Design and Setting This was a hospital-based cross-sectional observational study conducted at the Outpatient Department of Pulmonology and Respiratory Medicine, [Tertiary Care Teaching Hospital Name], [City], India, from January 2023 to June 2023 (6 months). The study was approved by the Institutional Ethics Committee (IEC Ref: XXXX/2022) and conducted in accordance with the Declaration of Helsinki. 2.2 Study Population Inclusion criteria: Adult patients aged 18 years and above; physician-confirmed diagnosis of bronchial asthma based on GINA 2022 criteria (characteristic symptom pattern and variable expiratory airflow limitation confirmed by spirometry); on prescribed asthma medications for at least 3 months prior to enrollment; attending regular OPD follow-up; able to provide written informed consent; able to communicate in Hindi, Telugu, or English. Exclusion criteria: Newly diagnosed asthma (duration <3 months); coexisting COPD, bronchiectasis, or active pulmonary tuberculosis; pregnancy; severe cognitive impairment or psychiatric illness precluding reliable interview; ICU or emergency department admission at time of interview; patients who had changed their medication regimen within the past 4 weeks. 2.3 Sample Size Assuming a prevalence of poor asthma control of 60% (as reported in prior Indian studies) with 95% confidence level and 5% precision, minimum sample size was 369. Accounting for potential non-response and incomplete records, 380 patients were approached, of whom 350 met eligibility criteria and consented to participate. 2.4 Data Collection Instruments Asthma Control Assessment Asthma control was assessed using the Asthma Control Test (ACT), a validated 5-item patient-reported outcome tool (scored 5-25). Scores were interpreted as: well-controlled (score 20-25), partly controlled (score 16-19), and uncontrolled (score 5-15), in accordance with GINA 2022 definitions. ACT has demonstrated strong correlation with specialist assessment of asthma control (r=0.72) and has been validated in Indian patient populations. Medication Adherence Assessment Medication adherence was assessed using the Morisky Medication Adherence Scale-8 (MMAS-8), a validated 8-item self-report questionnaire assessing adherence behavior over the preceding 30 days. The MMAS-8 yields a score of 0-8, classified as: high adherence (score 8), medium adherence (score 6 to <8), and low adherence (score <6). The MMAS-8 has demonstrated good reliability (Cronbach's alpha 0.61-0.83) and has been widely used in asthma adherence research. The questionnaire was translated into Hindi and Telugu using standard forward-back translation methodology and validated in a pilot sample of 30 patients. Determinants of Non-Adherence A structured interviewer-administered questionnaire was used to collect data on potential determinants of non-adherence, including: sociodemographic details (age, sex, education, occupation, socioeconomic status by modified Kuppuswamy scale); clinical characteristics (asthma severity, duration, comorbidities, inhaler device type); medication-related factors (polypharmacy, side-effect experience, cost burden); patient knowledge and beliefs (Beliefs about Medicines Questionnaire-Specific subscale); follow-up regularity; and inhaler technique assessment using a standardized checklist. 2.5 Statistical Analysis Data were entered in Microsoft Excel and analyzed using SPSS v26. Categorical variables are reported as frequency and percentage; continuous variables as mean +/- SD or median (IQR). Chi-square test was used for bivariate associations between adherence category and asthma control level, and between adherence and categorical determinants. Spearman correlation assessed the relationship between MMAS-8 and ACT scores as continuous variables. Multivariate logistic regression (dependent variable: low adherence vs. medium/high adherence) was performed to identify independent predictors of poor adherence, adjusting for age, sex, education, disease duration, and socioeconomic status. A p-value <0.05 was considered statistically significant.

3.1 Sociodemographic and Clinical Profile A total of 350 patients were enrolled (response rate 92.1%). Mean age was 41.8 +/- 13.6 years; 54.3% were female. Approximately 62% had education up to secondary level or below. By modified Kuppuswamy classification, 46.3% were from lower-middle or lower socioeconomic class. Mean disease duration was 8.4 +/- 5.9 years. ICS-containing regimens were prescribed in 84.6% of patients; 48.3% were on ICS/LABA combination inhalers. Full baseline characteristics are shown in Table 1. 3.2 Asthma Control Levels Based on ACT scoring, only 99 patients (28.3%) had well-controlled asthma (ACT 20-25); 135 (38.6%) were partly controlled (ACT 16-19); and 116 (33.1%) were uncontrolled (ACT 5-15). Mean ACT score was 16.4 +/- 4.8. The proportion with uncontrolled asthma was highest among patients aged 18-30 years (41.2%) and those from lower socioeconomic strata (44.4%). Uncontrolled asthma was significantly more common among patients with poor inhaler technique (58.4% vs. 14.2%, p<0.001) and those with irregular follow-up (52.3% vs. 15.6%, p<0.001). Table 2 summarizes asthma control distribution. 3.3 Medication Adherence Levels By MMAS-8 scoring, only 79 patients (22.6%) had high adherence (score 8); 145 (41.4%) had medium adherence (score 6 to <8); and 126 (36.0%) had low adherence (score <6). Mean MMAS-8 score was 5.8 +/- 1.9. Low adherence was most prevalent in the 18-30 age group (51.0%), among patients with primary education or below (52.8%), in those with low socioeconomic status (48.1%), and among patients prescribed more than 2 medications per day (44.8%). Only 40.3% of patients demonstrated correct inhaler technique on observation. Table 1: Sociodemographic and Clinical Characteristics of Study Participants (N=350) Characteristic n % / Mean +/- SD Age (years), Mean +/- SD 41.8 +/- 13.6 Age group 18-30 years 102 29.1% Age group 31-50 years 143 40.9% Age group >50 years 105 30.0% Female sex 190 54.3% Education: Primary or below 89 25.4% Education: Secondary 128 36.6% Education: Graduate and above 133 38.0% Socioeconomic class: Lower/Lower-middle 162 46.3% Disease duration < 5 years 124 35.4% Disease duration 5-10 years 128 36.6% Disease duration > 10 years 98 28.0% Inhaled corticosteroid (ICS) prescription 296 84.6% ICS/LABA combination inhaler 169 48.3% Oral theophylline in regimen 118 33.7% Comorbid allergic rhinitis 174 49.7% Comorbid GERD 64 18.3% Regular follow-up (>=3 monthly visits/year) 186 53.1% Correct inhaler technique demonstrated 141 40.3% LABA = Long-Acting Beta-Agonist; ICS = Inhaled Corticosteroid; GERD = Gastroesophageal Reflux Disease Table 2: Distribution of Asthma Control Levels (N=350) Asthma Control Level ACT Score Range n Percentage (%) Well-Controlled 20 - 25 99 28.3% Partly Controlled 16 - 19 135 38.6% Uncontrolled 5 - 15 116 33.1% Total 5 - 25 350 100.0% ACT = Asthma Control Test; GINA 2022 classification used for control categories Table 3: Distribution of Medication Adherence Levels (N=350) Adherence Level MMAS-8 Score n Percentage (%) High Adherence 8 79 22.6% Medium Adherence 6 to < 8 145 41.4% Low Adherence < 6 126 36.0% Total 0 - 8 350 100.0% MMAS-8 = Morisky Medication Adherence Scale-8 3.4 Association Between Adherence and Asthma Control There was a highly significant positive association between medication adherence level and asthma control category (chi-square = 184.6, df = 4, p<0.001). Among well-controlled patients, 87.3% had high adherence, 11.1% medium adherence, and only 1.0% low adherence. In contrast, among uncontrolled patients, only 8.5% had high adherence, 29.3% medium adherence, and 62.1% had low adherence. Spearman correlation between MMAS-8 score and ACT score was strongly positive (rs = 0.74, p<0.001). Full cross-tabulation is presented in Table 4. Table 4: Cross-Tabulation of Asthma Control Level by Medication Adherence Category (N=350) Asthma Control Level High Adherence n (%) Medium Adherence n (%) Low Adherence n (%) Total n Well-Controlled (ACT 20-25) 87 (87.3%) 11 (11.1%) 1 (1.0%)* 99 Partly Controlled (ACT 16-19) 27 (20.0%) 89 (65.9%) 19 (14.1%) 135 Uncontrolled (ACT 5-15) 10 (8.5%) 34 (29.3%) 72 (62.1%) 116 Total 79 (22.6%) 145 (41.4%) 126 (36.0%) 350 Chi-square = 184.6, df = 4, p<0.001. Spearman correlation between MMAS-8 score and ACT score: rs = 0.74, p<0.001. *Only 1 well-controlled patient had low adherence, suggesting symptom-based non-adherence may occur even with recent good control. 3.5 Reasons for Non-Adherence Among patients with medium or low adherence (n=271), the most commonly cited reasons for missing medications were: forgetting to take medications (58.3%), belief that medication is not needed when asymptomatic (52.4%), cost or affordability of inhalers (38.7%), fear of long-term steroid side effects from ICS (35.4%), inconvenience of inhaler use in public or at work (28.4%), and poor inhaler technique leading to perception of ineffectiveness (22.1%). These patterns were consistent across age groups, though cost-related non-adherence was more prevalent in lower socioeconomic strata (56.8%) and belief-related non-adherence more prevalent in younger patients (Table 5). Table 5: Self-Reported Reasons for Medication Non-Adherence Among Patients with Medium or Low Adherence (n=271) Reason for Non-Adherence n Percentage (%) Forgetting to take medication 158 58.3% No symptoms = no medication needed 142 52.4% Cost/affordability of inhalers or drugs 105 38.7% Fear of steroid side effects (ICS) 96 35.4% Inconvenience of inhaler use in public 77 28.4% Poor inhaler technique / perceived ineffectiveness 60 22.1% Dislike of taking medicines regularly 54 19.9% Irregular follow-up / forgot prescription 48 17.7% Belief that asthma can be cured permanently 43 15.9% Family/social pressure to reduce medications 31 11.4% Multiple responses permitted; percentages do not sum to 100. ICS = Inhaled Corticosteroids. 3.6 Determinants of Low Adherence — Multivariate Logistic Regression On multivariate logistic regression, five variables were independently associated with low medication adherence after adjusting for confounders (Table 6): perceived absence of symptoms when not taking medication (OR 4.17, 95% CI 2.48-7.01), belief that inhalers are harmful or cause dependence (OR 3.62, 95% CI 2.14-6.12), lower education (primary or below vs. graduate; OR 2.88, 95% CI 1.64-5.06), absence of regular follow-up (OR 2.74, 95% CI 1.62-4.63), and younger age (18-30 vs. >50 years; OR 2.41, 95% CI 1.36-4.28). Female sex, disease duration, and socioeconomic class did not remain significant in the multivariate model. Table 6: Multivariate Logistic Regression — Independent Predictors of Low Medication Adherence (MMAS-8 <6) Predictor Variable Crude OR Adjusted OR (95% CI) p-value Sig. No symptoms = no medication (belief) 5.22 4.17 (2.48-7.01) <0.001 *** Belief inhalers are harmful/cause dependence 4.18 3.62 (2.14-6.12) <0.001 *** Education: Primary or below (vs. Graduate) 3.44 2.88 (1.64-5.06) <0.001 *** Irregular follow-up (<3 visits/year) 3.06 2.74 (1.62-4.63) <0.001 *** Age 18-30 years (vs. >50 years) 2.84 2.41 (1.36-4.28) 0.003 ** Incorrect inhaler technique 2.14 1.86 (1.09-3.17) 0.023 * Polypharmacy (>2 medications/day) 1.96 1.58 (0.92-2.71) 0.098 NS Female sex 1.42 1.21 (0.74-1.98) 0.44 NS OR = Odds Ratio; CI = Confidence Interval; NS = Not Significant; *** p<0.001; ** p<0.01; * p<0.05. Reference categories: age >50 years; education = graduate and above; regular follow-up. Model adjusted for age, sex, education, disease duration, and socioeconomic class.

This cross-sectional study provides a comprehensive contemporary profile of asthma control levels and medication adherence in a tertiary care setting in India, and rigorously demonstrates the strong, quantitative association between these two critical outcomes. The finding that only 28.3% of patients achieved well-controlled asthma is alarming, though consistent with reports from other Indian and South Asian studies — a systematic review of Indian asthma studies reported well-controlled asthma in only 15-35% of patients across various settings. The rate of uncontrolled asthma (33.1%) is particularly concerning given that all enrolled patients were under specialist care, suggesting that even access to tertiary services does not guarantee adequate disease control. The prevalence of low medication adherence (36.0% by MMAS-8 criteria) is high and consistent with the global literature. A meta-analysis by Lam et al. (2015) reported non-adherence rates in asthma ranging from 30-70% depending on the measurement tool and population. The Indian context adds specific challenges: a 2017 survey found that 38% of Indian asthma patients had never been taught proper inhaler technique, and only 40% regularly refilled prescriptions. Our finding that only 40.3% of patients demonstrated correct inhaler technique is particularly troubling, as poor technique effectively renders even a fully adherent patient non-adherent in functional terms. The correlation between MMAS-8 score and ACT score (Spearman rs = 0.74, p<0.001) represents one of the strongest reported in the Indian literature, and the dose-response-like pattern visible in Table 4 — where 87.3% of well-controlled patients had high adherence compared to only 8.5% of uncontrolled patients — provides compelling evidence for the mechanistic link between adherence and control. This relationship is not merely associative: prospective studies have demonstrated temporal primacy of non-adherence in causing loss of asthma control and exacerbations. The most important finding from the determinants analysis is the outsized role of patient beliefs and health literacy over structural factors. The belief that asthma medication is not needed when asymptomatic (OR 4.17) and the belief that inhalers are harmful (OR 3.62) were the strongest independent predictors of low adherence, stronger than education level, follow-up regularity, or even age. This is consistent with the health belief model framework: perceived susceptibility (do I need the medication?) and perceived barriers (are there harms?) are the dominant cognitive determinants of preventive health behavior. This has direct clinical implications — adherence-focused counseling must prioritize correcting these misconceptions rather than merely emphasizing the importance of taking medications. The finding that younger patients (18-30 years) had 2.4-fold higher odds of low adherence than patients aged over 50 years deserves specific attention. Young adults with asthma face unique challenges: social stigma of inhaler use in peer settings, greater spontaneous symptom variation (leading to the perception that asthma is intermittent), competing life priorities, and lower perceived disease severity. Targeted adherence support for this demographic — including mHealth-based reminders, peer support groups, and age-appropriate educational materials — should be a priority. Irregular follow-up as an independent predictor of non-adherence (OR 2.74) highlights a critical systems-level gap. In overburdened public and tertiary facilities in India, extended intervals between clinic visits reduce the frequency of adherence assessment, counseling reinforcement, and inhaler technique correction. Innovative solutions — telephonic follow-up, pharmacist-led adherence programs, community health worker-facilitated home visits, and digital adherence monitoring devices — offer scalable approaches to bridge this gap. Cost-related non-adherence, reported by 38.7% of patients, points to the structural affordability barrier in asthma management. India lacks a comprehensive publicly funded inhaler supply system, unlike the provision of free oral medications under national disease control programs. The inclusion of ICS-containing fixed-dose combination inhalers in the National List of Essential Medicines and their provision through Jan Aushadhi Kendras at subsidized rates could substantially reduce this barrier. Limitations of this study include its cross-sectional design, which precludes causal inference regarding the adherence-control relationship; single-center data limiting generalizability; self-report bias in both MMAS-8 and ACT responses; and absence of objective adherence verification (e.g., pharmacy refill records, electronic inhaler monitoring). Future longitudinal studies measuring adherence and control simultaneously over time, incorporating objective adherence metrics, and evaluating adherence interventions are warranted.

This study demonstrates that poor asthma control and low medication adherence are both highly prevalent among asthma patients attending a tertiary care center, and the two are strongly and significantly correlated. Only 28.3% of patients had well-controlled asthma, and only 22.6% demonstrated high medication adherence. Patient misconceptions about the need for medication when asymptomatic and fears about inhaler harm are the most powerful modifiable predictors of non-adherence. These findings call for a paradigm shift in asthma outpatient care — from disease-focused prescription to patient-centered adherence support, incorporating structured education, misconception correction, regular inhaler technique assessment, and consistent follow-up.

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