Abstract
Abstract
Objectives
To describe the prevalence and characteristics of traditional, complementary and integrative medicine (TCIM) practice and product use by the population of the UK providing up-to-date data on the landscape of TCIM use in the UK.
Design, setting and participants
A cross-sectional online survey, administered using the Qualtrics platform, among adults (aged 18 years and over) residing in the UK (England, Wales, Scotland or Northern Ireland). Data were collected between May and October 2024. The 40-item instrument covered four domains: demographics, health status, use of health products and practices, and use of health services. Descriptive statistics were used to summarise survey responses, and χ² tests were applied to assess associations between participant characteristics and TCIM use. Backwards stepwise logistic regression was conducted to identify predictors of TCIM use across four outcome categories (p≤0.05).
Results
The sample (n=1559) was broadly representative of the UK population. Prevalence of any TCIM use over a 12-month period was 65.9% with 19.1% consulting a TCIM practitioner and 63.3% using any TCIM product or practice. Bodywork therapists (massage therapists 9.4%, chiropractors 7.9%, yoga teachers 5.0%) and homeopaths (4.1%) were the most commonly consulted TCIM practitioners and Anthroposophic doctors were the least commonly consulted (2.1%). Among TCIM products, vitamin and mineral supplements were the most commonly used (37.3%) and relaxation or meditation practices were reported by 19.4% of respondents. TCIM users were more likely to be female, identify as Asian or Black, have a chronic disease diagnosis, report good health, possess private health insurance, have a higher education level, be employed (or seeking employment) and sometimes experience financial management difficulties.
Conclusions
There is substantial use of TCIM across the UK adult population and there is a need for more research on integrating TCIM into mainstream healthcare and the National Health Service. Clear strategies are necessary to enhance communication between TCIM and conventional healthcare providers, ensure patient safety and promote person-centred, coordinated models of care.
Keywords: COMPLEMENTARY MEDICINE, Surveys and Questionnaires, Cross-Sectional Studies
STRENGTHS AND LIMITATIONS OF THIS STUDY.
The study uses a nationally representative dataset, enhancing the generalisability of the findings.
The comprehensive analysis of traditional, complementary and integrative medicine (TCIM) use across multiple categories—including practitioner consultations, product use and practices—provides a detailed understanding of TCIM engagement in the UK.
The study does not assess the health outcomes of TCIM use, limiting insights into its effectiveness.
Introduction
Traditional, complementary and integrative medicine (TCIM)—healthcare practices and products outside of mainstream medicine—is recognised by the WHO as an important yet underestimated resource, especially in the prevention and management of chronic conditions and meeting the health needs of ageing populations.1 2 These diverse practices and interventions may include (but are not limited to) chiropractic, herbal medicine, homeopathy, massage therapy, mind-body medicine, naturopathic medicine, nutritional medicine, osteopathy, traditional Chinese medicine and yoga. 88% of WHO member states acknowledge their population’s use of TCIM and have formally developed policies, laws, regulations, programmes and offices for TCIM to govern these practices. According to WHO, TCIM plays an important role in supporting population health needs and addressing many of the unique global health challenges of the 21st century.1
The global prevalence of TCIM utilisation shows considerable variation across studies and geographical areas, highlighting differences in cultural practices and healthcare demands. A systematic review examining national surveys from 14 countries found the 12-month prevalence of TCIM use ranged between 24% and 71.3%.3 This discrepancy can be attributed, in part, to variations in the definition of TCIM and the research methods used in these studies. Despite such variations between settings, TCIM use has demonstrated consistently meaningful prevalence at a global level over time.3 In the UK, surveys focused on practitioner-led TCIM over a 12-month period reported use by 10% of the general population in 2001 (UK),4 12% in 2005 (England)5 and 16% in 2015 (England).6
The increasing prevalence of TCIM use up to 2015 calls for greater attention and updated data on the UK general population’s engagement with, and experience of, TCIM. As the landscape of health and healthcare evolves over time, it is essential to understand individuals’ needs and behaviours surrounding TCIM use. This includes not only identifying a more contemporary prevalence of TCIM use, but also examining relationships between TCIM use, user characteristics and health status; patient-provider information-sharing; and patient experiences of care. This study captures the latest data on these key factors, providing the insights needed to inform responsive healthcare and policy development regarding TCIM, within the broader health field in the UK.
Moreover, the WHO’s Global Traditional Medicine Strategy 2025–20347 offers a contemporary framework for understanding TCIM within modern health systems. The strategy emphasises evidence generation, regulatory strengthening and the people-centred integration of safe and effective TCIM practices into national healthcare, highlighting their relevance to universal health coverage and population health needs. Positioning this study within that framework underscores the importance of updated UK data to inform policy and the responsible integration of TCIM in line with global health priorities.
Methods
Study design and setting
This online, cross-sectional survey aimed to describe the prevalence of TCIM use and the sociodemographic and health characteristics of TCIM users among the UK population. We used the Strengthening the Reporting of Observational Studies in Epidemiology cross-sectional checklist when writing our manuscript.8
Participants
The study included adults (aged 18 years and over) residing in the UK (England, Wales, Scotland and Northern Ireland) who could read and understand English sufficiently to provide full, informed consent and complete the survey (or have access to someone to assist them).
Recruitment and sampling strategy
The study employed purposive convenience sampling to recruit a nationally representative sample of the UK adult population as reported in population estimates based on 2021 national census data.9 The online survey was administered using the Qualtrics platform (Qualtrics, Provo, Utah, USA). Participants were recruited via the Qualtrics survey panel database, which comprises individuals who have previously consented to be contacted for research participation. Database members were emailed a link to the participant information sheet, from which point they chose to consent and continue the survey. Participants were stratified to ensure representativeness with the UK population. Data were collected between 26 May and 14 October 2024.
Sample size
The sample size of 1500 was calculated based on previous data reporting 12-month use of any TCIM or product in the UK,5 6 precision of 0.02 and 95% confidence level within the current population of UK adults aged 18 years and older. Previous studies on the prevalence of TCIM use5 suggest that approximately 26% of UK adults (~67 000 000 total population) have been reported to use TCIM in 2010, and approximately 16% have consulted a TCIM practitioner in 2018.6 To achieve a 95% CI and 5% margin of error, this requires a minimum of 296 survey respondents who use any TCIM, and a minimum of 207 who access TCIM via a TCIM practitioner. However, there are numerous types of TCIM that may be used by individuals, including consulting with different kinds of TCIM practitioners and the use of various TCIM products and practices. To ensure there is sufficient data to enable specific subgroup analyses of the most common TCIMs reported in previous research, at least 1500 study participants have been recruited. This sample size aligns with previous survey research examining TCIM use in the Australian population.10 11
Instrument
In 2017 and 2023, a survey was conducted to examine complementary medicine (CM) use, health and communication behaviours in a representative sample of the Australian general population.11 This Australian survey was modified to suit the current context in the UK and employed the term ‘CM’ in alignment with prevailing terminology at that time. To address the complexity and diversity in the field—and variations in TCIM definitions—this manuscript uses the term TCIM to better capture the nuanced overlap between TCIM professions and practices. The current 40-item instrument covered four domains: demographics, health status, health products and practices, and health services. All items were used in this analysis. Where applicable, items used fixed-response options, including five-point Likert-type scales (eg,‘never’ to ‘very often’ or ‘strongly disagree’ to ‘strongly agree’) for questions on frequency, attitudes or experiences. Other items used categorical response options (eg, age ranges, gender categories or yes/no responses). As the instrument was based on a survey previously used in large, nationally representative samples (Australia) and demonstrated content validity in those studies, no formal psychometric validation of the UK-adapted instrument was undertaken. Only minor (wording) modifications to ensure clarity and cultural suitability for the UK population were conducted before deployment. The full instrument is provided in online supplemental file 1.
Demographics
Nine items covered participant demographics, including age (by range), gender, location, ethnicity, financial status (as financial manageability), highest educational qualification, current employment status, current relationship status and health insurance coverage (private and government-subsidised).
Health status
Participants were asked to provide information about various health status factors, including the incidence of diagnosis or treatment for a range of different health conditions, covering 35 chronic conditions (eg, diabetes, cancer, fibromyalgia, osteoarthritis, anxiety disorder, irritable bowel syndrome) as well as COVID-19. They were also presented with the Short Form-20 instrument to measure quality of life.12
Health products and practice use
14 items explored respondents’ use of health products and practices over the previous 12 months, including pharmaceuticals, homeopathic remedies, herbal medicines (Chinese or Western), vitamin or mineral supplements, and practices like yoga, tai chi and mindfulness.
Health service use
Two survey items captured participants’ frequency of visits to various health professionals over the past 12 months. Health professions covered by this item included medical doctors (eg, general practitioners, hospital doctors, specialist doctors), allied health professionals (eg, pharmacists, nurses, physician associates, physiotherapists), and TCIM health professionals (eg, acupuncturists, chiropractors, homeopaths, massage therapists).
Analysis
Statistical analyses were conducted using StataSE V.18 statistical analysis software.13 Data were cleaned before analysis by removing non-genuine responses, identified as such through examination of Qualtrics bot-detection captcha and duplicate response scores, as well as standard data integrity checks (eg, excessive straight-lining, inconsistent or nonsensical open-text responses). Descriptive data were reported as frequencies and percentages for all data arising from survey items relevant to the research aim. Some demographic and health status items were recoded from continuous to categorical variables (age, chronic condition multimorbidities) or had categories with smaller cell values combined where appropriate (gender, ethnicity, relationship status, financial) to facilitate reporting and inferential analyses. Health status variables pertaining to diagnosed chronic conditions were broadly grouped into categories consistent with previous studies11 14 (ie, mental health condition, cardiovascular condition, gastrointestinal condition, musculoskeletal condition, respiratory condition) to support inferential analyses. New variables were also generated to report binary incidence of any chronic condition diagnosis or treatment, and to present the number of comorbid chronic conditions (none to five or more). A list of variables included in each category is available in online supplemental file 2.
The national representativeness of the sample was measured against national census data using χ² tests. The effect size of any statistically significant differences was defined using Cramer’s V analysis and categorised according to Rea and Parker15 using a 6-point scale ranging from ‘negligible effect’ (0.00 to <0.10) to ‘very strong effect’ (0.80 to <1.00). Associations between participant characteristics and their use of any CM were measured using χ² tests. Alpha values were set at ≤0.05.
Backwards stepwise logistic regression analysis was performed to identify the characteristics of CM users based on four outcome categories: any CM use, any CM practitioner consulted, any CM product use and any CM practice. Variables were included in each individual baseline model if they were found to have a statistical association with the respective outcome category, determined by a χ² test, with an alpha value of ≤0.2. The variable with the highest alpha value was removed stepwise from each baseline model, and its removal was checked using a likelihood ratio test. The remaining variables formed a model with the most parsimonious combination of characteristics to predict the outcome. All retained variables were reported from the model if they had an alpha value of ≤0.05.
Results
The survey was accessed by 3824 individuals (excluding 384 responses removed as non-genuine responses) of whom 2054 consented to participate in the survey, and 1580 completed the survey (defined as providing a response to the last survey item they were shown). After removal of problematic observations with inconsistent responses (n=21), surveys from 1559 participants were included in the final analysis. A response rate of 41% was calculated based on the final sample size divided by the number of respondents who accessed the survey information page (excluding observations removed for suspected fraud and data integrity issues). Participants were found to be representative of UK demographics by geographical location (p=0.811) and gender (p=0.643), but statistically different by age category (p<0.001) due to a lesser proportion of participants aged 60 years and over compared with the general population. Cramer’s V analysis found the effect size of this difference was negligible (V=0.001) (online supplemental file 3).
Sociodemographic and health characteristics
There was a slightly higher proportion of females (53.8%) than males (45.9%) among the sample, and participants ‘aged 60 years and over’ represented the highest proportion age category (26.4%) (table 1). More participants were based in mid-England (26.2%) compared with other locations. Most participants reported a white ethnicity (83.5%), with much lower representation from other groups (0.8%–6.9%). Participants were most commonly married to an opposite sexed person (42.1%) or never married (33.5%), in full-time (42.5%) or part-time (19.4%) work and having a secondary education qualification (33.8%) as their highest level of study. They reported financial manageability most commonly as ‘difficult some of the time’ (32.8%) or ‘not too bad’ (30.7%). Most participants did not have private health insurance (83.7%). Differences in participant characteristics based on CM use were identified for age (p<0.001), location (p=0.003), ethnicity (p<0.001), as well as employment (p<0.001), education (p<0.001) and private health insurance (p<0.001) status.
Table 1. Sociodemographic and health characteristics of survey respondents.
| Characteristics | All participants | Any CM use | No CM use | χ2 |
|---|---|---|---|---|
| n=1559 (100%) | n=1028 (65.9%) | n=531 (34.1%) | P value | |
| Gender | ||||
| Female | 839 (53.8) | 566 (55.1) | 273 (51.4) | 0.164 |
| Male | 716 (45.9) | 459 (44.7) | 257 (48.4) | |
| Non-binary and other* | 4 (0.3) | 3 (0.3) | 1 (0.2) | |
| Age | ||||
| 18–29 | 288 (18.5) | 226 (22.0) | 62 (11.7) | <0.001 |
| 30–39 | 299 (19.2) | 197 (19.2) | 102 (19.3) | |
| 40–49 | 289 (18.6) | 201 (19.6) | 88 (16.6) | |
| 50–59 | 270 (17.3) | 161 (15.7) | 109 (20.6) | |
| 60 and over | 411 (26.4) | 242 (23.6) | 169 (31.9) | |
| Location | ||||
| Northern England | 354 (22.7) | 219 (21.3) | 135 (25.4) | 0.003 |
| Mid England | 409 (26.2) | 257 (25.0) | 152 (28.6) | |
| Southern England | 345 (22.1) | 226 (22.0) | 119 (22.4) | |
| Greater London | 206 (13.2) | 162 (15.8) | 44 (8.3) | |
| Wales | 81 (5.2) | 52 (5.1) | 29 (5.5) | |
| Scotland | 129 (8.3) | 88 (8.6) | 41 (7.7) | |
| Northern Ireland | 35 (2.3) | 24 (2.3) | 11 (2.1) | |
| Ethnicity | ||||
| White | 1301 (83.5) | 822 (80.0) | 479 (90.2) | <0.001 |
| Black, Black British, Caribbean or African | 108 (6.9) | 91 (8.9) | 17 (3.2) | |
| Asian or Asian British | 104 (6.7) | 87 (8.5) | 17 (3.2) | |
| Mixed or multethnic groups | 33 (2.1) | 19 (1.9) | 14 (2.6) | |
| Other ethnic group(s)/prefer not to state | 13 (0.8) | 9 (0.9) | 4 (0.8) | |
| Relationship status | ||||
| Never married | 522 (33.5) | 341 (33.2) | 181 (34.1) | 0.331 |
| Married (opposite sex) | 657 (42.1) | 451 (43.9) | 206 (38.8) | |
| Married (same sex) | 30 (1.9) | 20 (2.0) | 10 (1.9) | |
| Civil partnership (opposite sex) | 111 (7.1) | 72 (7.0) | 39 (7.3) | |
| Civil partnership (same sex) | 12 (0.8) | 7 (0.7) | 5 (0.9) | |
| Separated/divorced/widowed | 227 (14.6) | 137 (13.3) | 90 (17.0) | |
| Employment status | ||||
| Full-time work (≥35 hours per week) | 663 (42.5) | 460 (44.8) | 203 (38.2) | <0.001 |
| Part-time work (<35 hours per week) | 302 (19.4) | 210 (20.4) | 92 (17.3) | |
| Casual temp work (irregular hours) | 35 (2.3) | 29 (2.8) | 6 (1.1) | |
| Looking for work | 97 (6.2) | 73 (7.1) | 24 (4.5) | |
| Not in the paid workforce nor looking | 462 (29.6) | 256 (24.9) | 206 (38.8) | |
| Educational status | ||||
| No formal qualifications | 45 (2.9) | 24 (2.3) | 21 (4.0) | <0.001 |
| Primary education | 15 (1.0) | 9 (0.9) | 6 (1.1) | |
| Secondary education | 527 (33.8) | 306 (29.8) | 221 (41.6) | |
| Vocational education | 373 (23.9) | 235 (22.9) | 138 (26.0) | |
| Bachelor’s education | 386 (24.8) | 283 (27.5) | 103 (19.4) | |
| Master’s degree | 180 (11.6) | 144 (14.0) | 36 (6.8) | |
| Doctorate | 33 (2.1) | 27 (2.6) | 6 (1.1) | |
| Financial status | ||||
| It is impossible | 82 (5.3) | 52 (5.1) | 30 (5.7) | 0.289 |
| It is difficult all of the time | 285 (18.3) | 180 (17.5) | 105 (19.8) | |
| It is difficult some of the time | 511 (32.8) | 356 (34.6) | 155 (29.2) | |
| It is not too bad | 479 (30.7) | 311 (30.3) | 168 (31.6) | |
| It is easy | 202 (13.0) | 129 (12.6) | 73 (13.8) | |
| Private health insurance | ||||
| Yes | 254 (16.3) | 209 (20.3) | 45 (8.5) | <0.001 |
| No | 1305 (83.7) | 819 (79.7) | 486 (91.5) | |
| Self-reported general health | ||||
| Excellent | 144 (9.2) | 107 (10.4) | 37 (7.0) | 0.002 |
| Very good | 438 (28.1) | 302 (29.4) | 136 (25.6) | |
| Good | 521 (33.4) | 345 (33.6) | 176 (33.2) | |
| Fair | 350 (22.5) | 219 (21.3) | 131 (24.7) | |
| Poor | 106 (6.8) | 55 (5.4) | 51 (9.6) | |
| Diagnosed or treated for chronic condition (previous 12 months) | ||||
| Yes | 898 (57.6) | 609 (59.2) | 289 (54.5) | 0.068 |
| No | 661 (42.4) | 419 (40.8) | 242 (45.6) | |
| Multimorbidities (no. chronic conditions diagnosed or treated, n=898) | ||||
| One condition | 322 (35.9) | 222 (36.5) | 100 (34.6) | 0.868 |
| Two conditions | 233 (26.0) | 156 (25.6) | 77 (26.6) | |
| Three conditions | 139 (15.5) | 93 (15.3) | 46 (15.9) | |
| Four conditions | 84 (9.4) | 60 (9.9) | 24 (8.3) | |
| Five or more conditions | 120 (13.4) | 78 (12.8) | 42 (14.5) | |
| Chronic condition diagnosed or treated | ||||
| Mental health condition | 376 (24.1) | 262 (25.5) | 114 (21.5) | 0.079 |
| Cardiovascular condition | 270 (17.3) | 160 (15.6) | 110 (20.7) | 0.011 |
| Gastrointestinal condition | 227 (14.6) | 159 (15.5) | 68 (12.8) | 0.158 |
| Musculoskeletal condition | 186 (11.9) | 117 (11.4) | 69 (13.0) | 0.352 |
| Respiratory condition | 171 (11.0) | 112 (10.9) | 59 (11.1) | 0.897 |
| Diabetes (type 1 or type 2) | 144 (9.2) | 102 (9.9) | 42 (7.9) | 0.193 |
| Migraine | 141 (9.0) | 99 (9.6) | 42 (7.9) | 0.262 |
| Sleep disorder | 109 (7.0) | 85 (8.3) | 24 (4.5) | 0.006 |
| Female reproductive condition | 84 (5.4) | 65 (6.3) | 19 (3.6) | 0.023 |
| Fibromyalgia/myalgic encephalomyelitis | 62 (4.0) | 42 (4.1) | 20 (3.8) | 0.76 |
| Cancer | 57 (3.7) | 42 (4.1) | 15 (2.8) | 0.209 |
| Male reproductive condition | 48 (3.1) | 34 (3.3) | 14 (2.6) | 0.467 |
| Autoimmune condition | 37 (2.4) | 27 (2.6) | 10 (1.9) | 0.361 |
| COVID-19 diagnosed or treated | 280 (18.0) | 201 (19.6) | 79 (15.0) | 0.023 |
Excluded from Chi2 due to small cell size.
CM, complementary medicine.
Over half of the participants (57.6%) reported being diagnosed with or treated for a chronic health condition in the previous 12 months, with most of those reporting only one condition (35.9%). The most common type of health condition reported by participants with a chronic condition was mental health (24.1%), followed by cardiovascular conditions (17.3%). No differences in the incidence or number of chronic conditions were found when comparing any CM use with no CM use; however, a comparatively lower rate of cardiovascular conditions (20.7% vs 15.6%; p=0.011), and a higher rate of sleep disorders (8.3% vs 4.5%; p=0.006), female reproductive conditions (6.3% vs 3.6%; p=0.023) was reported by CM users.
Health services and treatment use
Overall, participants reported similar rates of visiting a medical doctor (74.2%) or an allied health provider (72.0%) and much lower rates of consulting a CM practitioner (19.1%). Prevalence of any CM use over a 12-month period was 65.9%. Participants visited general practitioners (65.6%) and pharmacists (58.2%) more commonly than any other type of health professional (table 2). Consultations with hospital doctors (31.7%) and community nurses (29.1%) were also common. The most frequently reported CM practitioners visited by participants were massage therapists (9.4%), yoga teachers (7.9%), chiropractors (5.0%) and homeopaths (4.1%). Osteopaths (3.4%), naturopaths (2.4%) and anthroposophic doctors (2.3%) were least reported. Pharmaceuticals were the most common treatment, reported by 76.0% of participants, whereas 63.6% reported using a CM product (45.5%) or practice (38.9%). Over-the-counter pharmaceuticals were the treatments reported by the highest proportion of participants (57.8%) followed by prescription-only pharmaceuticals (49.9%). Among the CM products, vitamin and mineral supplements were used most commonly (37.3%) while relaxation or meditation was the most common CM practice reported (19.4%).
Table 2. Prevalence of conventional and CM health service and treatment utilisation.
| CM use | (n) | (%) | CM use | (n) | (%) |
|---|---|---|---|---|---|
| Any medical doctor | 1156 | 74.2 | Any CM use | 1028 | 65.9 |
| General practitioner | 1022 | 65.6 | Any CM practitioner | 298 | 19.1 |
| Hospital doctor | 494 | 31.7 | Massage therapist | 146 | 9.4 |
| Specialist doctor | 407 | 26.1 | Yoga teacher | 123 | 7.9 |
| Any allied health provider | 1122 | 72.0 | Chiropractor | 78 | 5.0 |
| Pharmacist | 907 | 58.2 | Homeopath | 64 | 4.1 |
| Community nurse | 453 | 29.1 | Western herbalist | 64 | 4.1 |
| Counsellor/psychologist | 204 | 13.1 | Acupuncturist | 57 | 3.7 |
| Physiotherapist | 188 | 12.1 | TCM practitioner | 55 | 3.5 |
| Healthcare assistant | 179 | 11.5 | Osteopath | 53 | 3.4 |
| Paramedic | 103 | 6.6 | Naturopath | 37 | 2.4 |
| Physician assistant | 93 | 6.0 | Anthroposophic doctor | 36 | 2.3 |
| Care coordinator | 74 | 4.8 | Any CM product | 710 | 45.5 |
| Dietician | 90 | 5.8 | Vitamin/mineral supplements | 581 | 37.3 |
| Any pharmaceutical product | 1184 | 76.0 | Aromatherapy oils | 100 | 6.4 |
| Prescription-only | 778 | 49.9 | Western or Chinese herbal medicines | 99 | 6.4 |
| Over the counter | 901 | 57.8 | Homeopathy | 77 | 4.9 |
| Flower essences | 53 | 3.4 | |||
| Any CM Practice | 620 | 39.8 | |||
| Relaxation or meditation | 303 | 19.4 | |||
| Yoga | 138 | 8.9 | |||
| Tai Chi or Qigong | 29 | 1.9 | |||
| Nature prescription | 416 | 26.7 | |||
| Any CM Product or Practice | 991 | 63.6 |
CM, complementary medicine; TCM, traditional Chinese medicine.
Characteristics of CM users
Online supplemental table 3 presents the characteristics predicting CM use, as determined through backwards stepwise logistic regression. Males had lower odds (aOR 0.75, 95% CI (0.59 to 0.95)) of any CM use than females, and individuals aged 30–39 years had lower odds (aOR 0.68, 95% (CI 0.50 to 0.91)) than those aged 18–29 years. Participants with a bachelor’s (aOR 1.60, 95% CI (1.21 to 2.12)) or Master’s degree (aOR 2.03, 95% (CI 1.34 to 3.04)) had higher odds of using any CM product compared with those with no formal qualifications. Those reporting financial manageability as ‘difficult some of the time’ (aOR 1.35, 95% CI (1.06 to 1.72)) had increased odds compared with those who found it ‘impossible’ or ‘difficult all of the time’. Participants identifying as Asian or Asian British (aOR 2.26, 95% CI (1.29 to 3.96)), Black, Black British, Caribbean or African (aOR 2.01, 95% CI (1.14 to 3.55)) also showed greater odds of using CM than whites. Furthermore, participants with private health insurance had a higher likelihood of using CM. Those self-rating their health as ‘good’ (aOR 1.76, 95% CI (1.10 to 2.83)), ‘very good’ (aOR 1.91, 95% CI (1.15 to 3.15)) or ‘excellent’ (aOR 2.14, 95% CI (1.15 to 3.98)) had greater odds of using CM compared with those with ‘poor’ health. However, individuals with a chronic condition diagnosis or treatment (aOR 1.52, 95% CI (1.14 to 2.02)) or a sleep disorder (aOR 1.96, 95% CI (1.17 to 3.29)) had a higher likelihood of using any CM, while those with cardiovascular disease were less likely to use any CM (aOR 0.69, 95% CI (0.50 to 0.95)).
Any CM practitioner
Participants of all ages were less likely to consult any CM practitioner (aOR 0.28–0.48) than those aged 18–29. Individuals of Asian or Asian British (aOR 1.74, 95% CI (1.06 to 2.85)), or Black, Black British, Caribbean or African (aOR 1.83, 95% CI (1.13 to 2.98)) ethnicity were more likely to visit a CM practitioner compared with those identifying as white. Participants with a bachelor’s (aOR 1.65, 95% CI (1.18 to 2.30)) or master’s (aOR 1.82, 95% CI (1.20 to 2.78)) degree, and those with private health insurance (aOR 2.89, 95% CI (2.05 to 4.05)), were more likely to consult a CM practitioner than those with no formal qualification or health insurance. People with ‘excellent’ self-rated health (aOR 1.68, 95% CI (1.02 to 2.76)) had greater odds of visiting a CM practitioner compared with those with ‘poor’ self-rated health, yet people with any chronic disease diagnosis (aOR 1.55, 95% CI (1.08 to 2.22)) or with diabetes mellitus (type 1 or 2) (aOR 1.61, 95% CI (1.01 to 2.57)) were also more likely to consult a CM practitioner compared with those without those diagnoses.
Any CM product
Predictors for using CM products included gender, location, education, employment and health status. Specifically, males were found to be less likely than females to use any CM products (aOR 0.64, 95% CI (0.51 to 0.80)) and those living in northern, mid or southern England were less likely (aOR 0.58–0.71) than residents of Greater London to use such products. Individuals with a bachelor’s (aOR 1.50, 95% CI (1.14 to 1.99)) or Master’s (aOR 1.62, 95% CI (1.13 to 2.34)) degree were more likely than participants with no formal education to use any CM product, as is the case for those with private health insurance (aOR 1.79, 95% CI (1.32 to 2.41)) compared with uninsured individuals. Participants using any CM product were more likely to report having a chronic condition (aOR 1.86, 95% CI (1.45 to 2.38)), a sleep disorder (aOR 1.61, 95% CI (1.04 to 2.49)) or a COVID-19 diagnosis or treatment (aOR 1.34, 95% CI (1.02 to 1.78)) in the previous 12 months.
Any CM practice
Participants’ education, employment, financial management and health were predictors of using any CM practice. Individuals not in the paid workforce or seeking work were less likely to use any CM practice (aOR 0.73, 95% CI (0.56 to 0.95)) than those in full-time work. Additionally, those managing their finances as ‘not too bad’ (aOR 0.74, 95% CI (0.58 to 0.95)) or ‘easy’ (aOR 0.64, 95% CI (0.44 to 0.91)) were also less likely to use any CM practice than those who found it ‘impossible’ or ‘difficult all of the time’. In contrast, participants with private health insurance had greater odds of using any CM practice (aOR 1.37, 95% CI (1.01 to 1.85)) than those without insurance, and similarly, individuals with bachelor’s (aOR 1.86, 95% CI (1.44 to 2.40)) or master’s (aOR 1.87, 95% CI (1.31 to 2.65)) degrees also had a higher likelihood of using any CM practice compared with people with no formal qualifications. In terms of health status, participants with a sleep disorder (aOR 2.05, 95% CI (1.27 to 3.31)) had higher odds of using any CM practice than other participants, and individuals with ‘good’ (aOR 1.45, 95% CI (1.09 to 1.94)), ‘very good’ (aOR 1.42, 95% CI (1.03 to 1.95)) or ‘excellent’ (aOR 1.65, 95% CI (1.06 to 2.57)) health were more likely to use any CM practice than those with ‘poor’ self-rated health.
Discussion
Our study is the first thorough analysis of TCIM use among the UK population since 2015, based on a nationally representative survey. The findings of this study suggest that two out of three individuals in the UK population use some form of TCIM. More specifically, one in five participants reported consulting a TCIM practitioner, nearly half of the participants used TCIM products, and over a third practised TCIM in the previous year. These figures align with earlier studies showing that high levels of TCIM use have become a well-established part of the healthcare landscape in the UK.6 16 The substantial use demonstrates the growing public interest in TCIM compared with 25 years ago, emphasising the need for further research on how to better integrate TCIM into mainstream healthcare and the National Health Service (NHS). Our findings offer an updated perspective to support appropriate integration and coordination of the various healthcare types used by community members, which is not only crucial to ensure safety and effectiveness but may also promote more person-centred approaches. At the same time, we alert the reader to remain mindful of the distinction between TCIM practitioners, products and practices, as this is important for interpreting the integrated patterns described in the discussion.
The UK is comparable to other Western countries in terms of significant public engagement in TCIM and self-care. Our 12-month TCIM use prevalence (66%) exceeds earlier UK estimates of 41%–50%.5 10 It aligns with Australian data, where 63%–68% of adults use TCIM,11 while Germany (51%)17 and France (42%) 18report slightly lower rates. Previous research indicates that patients’ experiences with the conventional health system are influential, as both the unsatisfactory results from conventional therapy and the desire to further reduce side effects are widely reported as key drivers of CM use.19 20 In subpopulations with chronic health conditions, the use of CM is reported to be associated with reducing side effects from conventional medicine, addressing dissatisfaction with standard care and assisting in disease management.20 The NHS is currently facing significant challenges, including an overburdened healthcare system,21 increased prevalence of chronic diseases, patient dissatisfaction with conventional treatments and financial constraints.22 In recent years, these financial constraints have led to longer waiting times, decreased service availability and increased pressure on general practitioners and hospital services,23 which might have encouraged patients to consider TCIM as an alternative. At this critical juncture for the NHS, the potential benefits of integrating evidence-based TCIM must be explored and exploited to address rising rates of chronic disease, enhance patient satisfaction and reduce healthcare costs. Given the growing public demand, it seems the time has now come for the NHS to develop regulatory frameworks and evidence-based strategies for integrating TCIM.
Demographic and socioeconomic factors and TCIM use
This study provides important insights into the demographic and socioeconomic determinants of TCIM use in the UK. Our findings show that women, younger people and those with higher education levels are more likely to use TCIM. Increased health awareness and information access, along with a focus on holistic and preventative health, particularly for women, may account for the greater interest and utilisation of TCIM among these specific demographics.5 24 Our research also indicates that individuals identifying as Asian and Black were more inclined to use TCIM compared with those who indicated they were White, suggesting a possible cultural emphasis on non-biomedical healthcare.10 This finding highlights the importance of cultural considerations in healthcare planning and policy development as the minoritised ethnic population in the UK is growing substantially through immigration, a youthful age structure and, in some cases, relatively high fertility.25
Our analyses also show that socioeconomic factors, such as employment status and financial health, are associated with TCIM use. Interestingly, in our study, individuals experiencing financial difficulties were more likely to use any TCIM, which contrasts with earlier studies suggesting that TCIM is predominantly used by wealthier individuals.18 26 However, this mainly resulted from using self-care practices and products, which are typically low-cost, rather than consultations with TCIM practitioners. When analysed separately, those with private health insurance were more likely to see a practitioner, which suggests greater financial security. This indicates that TCIM use among financially constrained individuals relies on accessible self-care rather than paid services. Despite its increasing popularity, TCIM is still rarely offered in NHS services and largely resides in the private sector. The lack of NHS integration means that patients must pay out-of-pocket for many TCIM treatments, making them less accessible to lower-income individuals. Consequently, the advantages of TCIM might mainly benefit individuals who can pay for private healthcare or private insurance, thereby increasing health inequalities. For individuals with lower income, financial constraints may hinder their ability to access TCIM services, even if they are perceived as beneficial, which may mean they are self-prescribing TCIM products and not receiving advice from a qualified practitioner to ensure they are accessing the safest and most effective treatments for their unique needs.
A critical interpretation indicates that higher TCIM use among women, younger adults, highly educated groups and minoritised ethnic communities may reflect deeper structural and cultural factors rather than mere differences in health awareness. Collectively, these patterns show that TCIM use is not solely a matter of preference but may also be a response to structural inequalities, unmet needs and cultural mismatches within the UK healthcare system.
Health status and TCIM use
Individuals in our study with a chronic disease diagnosis were more likely to use TCIM than the general population—a finding that was consistent across all categories of TCIM use examined and aligned with earlier studies from the UK and Australia.11 27 While this may be reflective of higher healthcare use in general, the high prevalence of both TCIM and conventional medicine use supports the evidence that individuals with chronic health conditions have a strong desire for holistic, patient-centred approaches in the management of their condition,28 29 which is often accessed through different TCIM.14 Another finding shared between this study and previous international research is that TCIM is often used by individuals with sleep disorders and diabetes. Research suggests that TCIM interventions such as acupuncture and Chinese herbal medicine30 31 and mindfulness-based interventions32 may offer benefits for sleep disorders. Similarly, naturopathic medicine and certain herbal supplements show potential in diabetes management,33 though further research is needed to confirm efficacy.
In contrast to the high TCIM use by individuals with a chronic condition, self-reported health was also positively correlated with TCIM use; those rating their health as good to excellent were more likely to engage in TCIM practices than those with poor health. This suggests that TCIM might be used proactively for well-being maintenance rather than only as a response to illness. Previous studies show that healthier individuals often adopt TCIM practices like yoga, meditation and dietary supplements to maintain their health.10 Moreover, psychological factors such as self-efficacy and a holistic health perspective among TCIM users may also contribute to higher self-perceived health, even among those managing chronic conditions. Alternatively, this finding may suggest participants using TCIM are experiencing health benefits from their use, which is resulting in greater self-rated health status. Ultimately, the cross-sectional nature of this study precludes drawing definitive conclusions about the direction of this relationship; thus, further research is needed to evaluate the health effects of specific TCIM and conditions.
Study strengths and limitations
A key strength of this study is its use of a nationally representative dataset, enhancing the generalisability of the findings. The comprehensive analysis of TCIM use across multiple categories—including practitioner consultations, product use and practices—provides a detailed understanding of TCIM engagement in the UK. Additionally, the study considers various influencing factors such as gender, ethnicity, education, employment, financial status and health, offering a holistic perspective on TCIM use. Nevertheless, certain limitations must be acknowledged. The reliance on self-reported data introduces the possibility of recall and responder bias. However, previous studies indicate that recall bias is minimal when reporting health behaviours within a 12-month period. In general, online panel recruitment may introduce selection bias, as participants often have higher digital literacy, health awareness or interest in TCIM, which can affect reported prevalence. The comparatively high representation of some sociodemographic groups—such as those of white ethnicity, or those living in England—may introduce some bias to the study findings. Mediation of any potential bias arising from the sample demographics has been applied through the selection of appropriate statistical tests and employment of a nationally representative sample. Nevertheless, care should be taken when generalising the study findings to specific sociodemographic contexts. Additionally, the study does not assess the health outcomes of TCIM use, limiting insights into its effectiveness, and unmeasured confounders (eg, health beliefs, cultural affiliation) may have influenced the results. Therefore, future research should investigate the effectiveness of various TCIM interventions and examine the motivations and barriers to TCIM use among socially disadvantaged or underrepresented communities.
Practice implication
Given that individuals with chronic conditions and those reporting good to excellent health both frequently engage with TCIM, integrative models of care that include evidence-based TCIM practices may support both preventive health and chronic disease management. There is a need for improved training among healthcare professionals regarding TCIM, clear communication pathways between conventional and TCIM practitioners, and the development of regulatory and referral frameworks within the NHS to support safe, equitable access.
Conclusions and future directions
This nationally representative study provides the first updated evidence since 2015 on TCIM use in the UK, showing that two-thirds of adults engage with TCIM. TCIM use was high among both people with chronic conditions and those reporting good health, indicating use for treatment and well-being. These findings underscore the need for future research and for the safe, evidence-informed integration of TCIM within UK healthcare by strengthening regulatory oversight and practitioner accreditation, developing evidence-based referral pathways, integrating TCIM practitioners into multidisciplinary teams and improving public access to reliable TCIM information. As the UK healthcare system evolves, integrating TCIM into a sustainable, patient-centred model could help meet the diverse health needs of the population.
Supplementary material
Acknowledgements
Footnotes
Funding: This work was supported by grants from The Blackie Foundation Trust and Ann Hill Trust, plus public donations to the Homeopathy Research Institute. The funders had no involvement in the study design;in the collection, analysis and interpretation of the data; in the writing of the report; and in the decision to submit the paper for publication.
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2025-104334).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Ethics approval: This study involves human participants and has been approved in line with the University of Technology Sydney Human Research Ethics Committee guidelines (UTS HREC REF NO. ETH24-9154) and with the University of Bristol Human Research Ethics Committee (Ref: 17676). Participants gave informed consent to participate in the study before taking part.
Data availability free text: The authors welcome collaboration or proposals for additional research questions to be analysed using the dataset. Interested researchers are encouraged to contact the corresponding author to discuss access and potential partnership.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Data availability statement
Data are available on reasonable request.
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