Artigos

INTRODUCTION

Since the Alma-Ata Declaration in 1978 (1), the World Health Organization (WHO) has promoted the rational and integrated use of Traditional, Complementary and Integrative Medicines (TCIM) in national health systems, especially in primary care. Traditional Medicines, such as Traditional Chinese Medicine, Ayurveda, and Unani, are based on cultural knowledge and practices and have been used in health maintenance and disease treatment (2). Complementary Medicine, including Homeopathy and Naturopathy, and Integrative Medicine, which combines conventional and complementary practices in a coordinated manner, have also gained global recognition and usage (3).
In Brazil, TCIM practices, referred to as Integrative and Complementary Medicine (ICM), are formally recognized and regulated by the National Policy of Integrative and Complementary Practices (PNPIC), instituted in 2006. ICM includes various therapies such as acupuncture, herbal medicine, homeopathy, and meditation, and is viewed as a comprehensive approach to health, focusing on disease prevention and the promotion of self-care (4). The PNPIC aims to integrate these practices into the Unified Health System (SUS), providing users with the option to choose therapies that best meet their needs (5).
The implementation of the PNPIC in the SUS involved the creation of guidelines for the provision and regulation of these practices, as well as the inclusion of variables about ICM in the National Health Survey (PNS). Data from 2019 show that 17,350 services in the Health Care Network offered some type of ICM, covering 4,297 Brazilian municipalities and all capitals (6). Additionally, the Program for Improvement of Access and Quality of Primary Care (PMAQ) and the creation of the Family Health Support Nucleus (NASF) contributed to the dissemination and implementation of ICM in Brazil (7).
Non-communicable diseases (NCDs), such as arterial hypertension (AH) and diabetes mellitus (DM), represent a major challenge to global public health. These diseases are responsible for the highest burden of morbidity and mortality, with significant consequences for the quality of life and economy of countries. The control of NCDs requires multifaceted interventions, including both conventional treatments and complementary approaches, such as ICM (8).
In Brazil, it is estimated that 52% of the adult population reports at least one NCD, with prevalences of AH and DM of 23.9% (9) and 7.7% (10), respectively. Recommendations for healthy behaviors, such as maintaining a balanced diet and regular physical activity, are widely recognized as essential for managing these conditions. Data indicate that, globally, the prevalence of these recommendations is high: in Italy, 85.6% (11) of diabetics and hypertensives receive guidance on hypertension control, while in Brazil, 87.7% of hypertensives and 95.8% of diabetics received advice on healthy eating (12).
Studies such as the PREMIER clinical trial demonstrate that lifestyle interventions, including weight loss, sodium reduction, increased physical activity, and the DASH diet, are effective in reducing blood pressure and controlling hypertension. The results showed significant reductions in blood pressure and improvement in hypertensive status, highlighting the importance of lifestyle changes as effective strategies for managing hypertension and diabetes (13). However, one study showed that only about 57% of people with type 2 diabetes and 31% of people with hypertension received lifestyle advice to increase physical activity, improve diet, and lose weight (14), demonstrating a gap in the implementation of these recommendations. Although evidence from systematic reviews and clinical trials shows that provider recommendations for lifestyle changes are effective and expected in primary care (15), population-based studies are still needed to describe the prevalence of these lifestyle-based recommendations.
Given the high prevalence of diabetes and hypertension, it is also essential to understand how ICM is being recommended and used in managing these pathologies. Previous studies suggest that sociodemographic characteristics, such as gender, age, race, socioeconomic and educational levels, may influence the use and recommendation of ICM (16–18).
This study seeks to fill gaps in the literature, as there is a scarcity of population-based studies that specifically investigate the recommendation of ICM by health care professionals in the management of hypertension and diabetes in Brazil. Investigating how ICM is recommended in relation to conventional lifestyle management practices is essential for understanding treatment dynamics and providing valuable insights for public policy. This population-based research aims to analyze the frequency and sociodemographic factors associated with the recommendation of ICM and compare it with the frequency of other recommendations by health care professionals for Brazilians with AH and DM.

METHODOLOGY

This is a cross-sectional study with national representativeness. We used data from the PNS-2019, was conducted between August 2019 and March 2020, aiming to provide detailed information on the health determinants and needs of the Brazilian population.
The PNS-2019 employed a multi-stage clustered sampling approach. First, primary sampling units (PSUs) were randomly selected from the 2010 Demographic Census, excluding small and special samples such as military quarters and long-term care institutions. Next, random selection of households (secondary sampling units) was conducted, followed by the random selection of an individual aged 15 years or older living in the selected households (tertiary sampling units). The expected sample was 108,255 households, considering a 20% non-response rate, ensuring an 80% statistical power for precise health indicator estimates. For the analysis of the described outcomes, participants aged between 15 and 107 years who responded to the Resident Questionnaire were selected, totaling 90,846 individuals interviewed.
The data collection questionnaire is divided into three parts: household characteristics, socioeconomic and health information of all household residents, and information about lifestyle, chronic diseases, the use of Integrative and Complementary Medicine, treatment recommendations, among other aspects of the selected resident. Data collection was conducted by trained interviewers using a digital questionnaire.
The PNS-2019 questions used to assess the primary outcomes were: “During any consultations for hypertension, did a doctor or another health professional give you any of these recommendations?” and “During any consultations for diabetes, did a doctor or another health professional give you any of these recommendations?”. The possible responses to these questions were "yes" or "no". For hypertension, the recommendations included maintaining a healthy diet, maintaining an adequate weight, reducing salt intake, engaging in regular physical activity, not smoking, avoiding excessive alcohol consumption, attending regular follow-ups with a health care professional, and using acupuncture, medicinal plants and herbal medicine, homeopathy, meditation, yoga, tai chi chuan, liang gong, or other integrative and complementary practices. Similarly, for diabetes, the recommendations included maintaining a healthy diet, maintaining an adequate weight, engaging in regular physical activity, not smoking, avoiding excessive alcohol consumption, reducing the consumption of pasta and bread, avoiding sugar, sugary drinks, and sweets, monitoring blood glucose at home, regularly examining the feet, attending regular follow-ups with a health care professional, and using acupuncture, medicinal plants and herbal medicine, homeopathy, meditation, yoga, tai chi chuan, liang gong, or other integrative and complementary practices.
The following sociodemographic factors were assessed: sex (male or female), age of participants (15-34, 35-49, 50-62, and 63 or older), self-reported skin color (white, black, mixed race, Asian, Indigenous), living with a partner (whether the spouse or partner lives in the household), area of residence (urban or rural), education level (primary, secondary, higher), regions of the country (North, Northeast, Southeast, South, Midwest), presence of private health insurance (yes or no), and monthly per capita family income based on the Brazilian minimum wage (1 minimum wage = R$ 998.00), categorized as up to ½, >½ to 1, 1 to 2, and > 2 minimum wages. The monthly per capita family income was estimated by dividing the household income by the number of people living in the household.
The statistical analysis included descriptive analysis of all sociodemographic, health, and outcome variables. Logistic regression models were used to obtain crude and adjusted Odds Ratios (ORs) and 95% confidence intervals (95% CI) for the association between explanatory variables (sociodemographic) and the outcome (recommendation of ICM) controlling for covariates. Initially, a bivariate analysis was conducted for each independent variable concerning the outcome, calculating the crude ORs and p-values. Variables with p-values < 0.20 in the bivariate analysis were selected for inclusion in the adjusted multivariate model. Subsequently, all selected variables were simultaneously included in the adjusted model, where adjusted ORs and p-values were calculated. Only variables with a p value p ? 0,05 were kept in the final model. Statistical analysis was performed using STATA 16 software and the Survey Data (svy) command. All estimates were weighted to account for the complex survey design of the PNS-2019 and to make the estimates nationally representative. Additionally, the frequencies of ICM recommendations were compared with other health recommendations provided by health care professionals.
The PNS-2019 was approved by the National Health Ethics Committee (CONEP) (process no. 3.529.376) in August 2019. Participation was voluntary, and participants signed a consent form. The questionnaire could be completed in full or in part. The PNS-2019 dataset is publicly available on the website of the Brazilian Institute of Geography and Statistics (IBGE), without information that could identify individuals.

RESULTS

Data from 90,846 participants with complete information on the recommendation of ICM were analysed. The sample showed a predominance of female participants (52.9%), with the majority aged between 15 and 34 years (35.7%), and individuals of mixed race (44.1%). Most participants had primary education (43.1%), 73.4% did not have private health insurance, and 85.9% lived in urban areas. The highest concentration of participants was in the Northeast region (34.7%), and 58.3% lived with a partner (TABLE 1).
Of the 90,846 participants, 2,110 were excluded for not having their blood pressure measured. Of the remaining 88,736, 64,885 did not have a diagnosis of AH. Among the 23,851 diagnosed with AH, 4,723 were excluded due to lack of information or outdated blood pressure measurements. Thus, 19,128 participants were included in the analysis, of which 1,591 received ICM guidance and 17,537 did not receive such guidance.
The results show that the highest proportion of ICM recommendations for AH was observed among women (8.9%), participants of Asian (13.7%) and Indigenous (13.4%) descent, those with higher education (9.8%), and residents in urban areas (8.2%). The highest prevalence of recommendations was observed in the North region (12.2%) and the lowest in the Northeast (6.5%). The bivariate analysis showed that female sex (OR = 1.39; 95% CI 1.09 – 1.79), Indigenous (OR = 2.19; 95% CI 1.06 - 4.52) and mixed race (OR = 1.27; 95% CI 1.02 – 1.58), higher education (OR = 1.40; 95% CI 1.04 – 1.87), and urban residency (OR = 1.41; 95% CI 1.08 – 1.87) were associated with a higher likelihood of receiving ICM recommendations. Living in the Northeast (OR = 0.50; 95% CI 0.37 – 0.67), Southeast (OR = 0.58; 95% CI 0.41 – 0.80), and South (OR = 0.64; 95% CI 0.46 – 0.88) regions presented lower odds of ICM recommendations. In the multivariate analysis, adjusting for confounding factors, the associations between female sex (adjusted OR = 1.41; 95% CI 1.11 – 1.79), Indigenous race (adjusted OR = 2.39; 95% CI 1.15 – 4.94), mixed race (adjusted OR = 1.35; 95% CI 1.06 – 1.72), and living in the Northeast (adjusted OR = 0.50; 95% CI 0.37 – 0.68) and Southeast (adjusted OR = 0.60; 95% CI 0.42 – 0.85) regions remained significant, indicating that these socioeconomic and demographic factors influence the recommendation of ICM for patients with AH (TABLE 2).
Graph 1 illustrates the health care professionals’ recommendations to participants with AH. The most common recommendation was to reduce salt intake (88.4%), followed by maintaining a healthy diet (87.7%), while ICM was recommended to only 7.9% of the participants.
Of the 90,846 participants, 6,773 were excluded for never having their blood glucose measured. Of the remaining 84,073, 76,699 were not diagnosed with DM. Among the 7,374 diagnosed with DM, 1,048 were excluded due to lack of information or outdated measurements. Thus, 6,326 participants were included in the analysis, of which 736 received ICM guidance and 5,590 did not receive such guidance.
The results demonstrate that participants aged 35 to 49 years had the highest frequency of ICM recommendations (15.7%), followed by those with higher education (15.5%) and secondary education (15.1%), residents in the Midwest region (17.3%) and those living with a partner had an occurrence of 12.8%. In the bivariate analysis, age between 35 to 49 years (OR = 2.25; 95% CI 1.45 – 3.48) and 50 to 62 years (OR = 1.58; 95% CI 1.10 – 2.28) were significantly associated with ICM recommendations, as well as higher education (OR = 1.83; 95% CI 1.29 – 2.60) and secondary education (OR = 1.78; 95% CI 1.23 – 2.56), living with a partner (OR = 1.36; 95% CI 1.02 – 1.82), while the Northeast region had a lower likelihood of ICM recommendations (OR = 0.66; 95% CI 0.45 – 0.95). In the multivariate analysis, age between 35 to 49 years (adjusted OR = 2.57; 95% CI 1.65 – 4.01) and 50 to 62 years (adjusted OR =1.95; IC 95% 1,24 – 3,06), higher education (adjusted OR = 1.91; 95% CI 1.22 – 2.90) and secondary education (adjusted OR = 1.91; 95% CI 1.08 – 3.39), living with a partner (adjusted OR = 1.34; 95% CI 1.01 – 1.79) showed significant associations with ICM recommendations. The Northeast region (adjusted OR = 0.67; 95% CI 0.44 – 0.95) and a per capita income between 1 and 2 minimum wages (adjusted OR = 0.51; 95% CI 0.30 – 0.87) presented lower recommendations for ICM (TABLE 3).
Graph 2 presents the health care professionals recommendations to participants with DM, highlighting a significant emphasis on maintaining a healthy diet (95.8%) and avoiding sugar consumption (93.7%). The lowest frequencies of recommendations were for the use of ICM (11.8%) and maintaining an adequate weight (9.25%).

DISCUSSION
The results of this study provide an overview of the recommendations regarding ICM in the health care of Brazilians reporting AH and DM. This is an original study as no national publications were found that addressed this topic. Additionally, we identified sociodemographic factors associated with ICM recommendations for these pathologies, which may be useful for public policy planning. In the case of AH, women and individuals of mixed race and Indigenous descent were more likely to receive ICM recommendations, while individuals living in the Northeast and Southeast regions had lower chances of receiving these recommendations. Similarly, for DM, ICM recommendations were higher among those aged 35 to 49 and 50 to 62 years, those with higher educational levels, and individuals living with a partner, while the recommendation was lower in the Northeast region. Overall, ICM recommendations were low compared to other health management guidelines and care recommendations typically provided by health care professionals. For AH, the main recommendations included reducing salt intake and maintaining a healthy diet, while for DM, there was an emphasis on maintaining a healthy diet and avoiding sugar consumption.
The results of this study reveal a lower frequency of ICM recommendations compared to other management guidelines for AH and DM. These findings indicate that ICM is not yet fully integrated into health recommendations, despite scientific evidence supporting its efficacy and safety. Robust evidence from systematic reviews and meta-analyses shows that auricular therapy can reduce blood pressure (19); meditation lowers blood pressure, cortisol, and triglycerides (20); and garlic has antihypertensive effects (21). Yoga also significantly reduces blood pressure (22). In the treatment of DM, yoga improves glycaemic outcomes (23); meditation reduces glycated hemoglobin (24); and acupuncture controls blood glucose and HbA1c (25). Traditional Chinese Medicine practices, such as Tai Chi Chuan and Qi Gong, aid in glycaemic control (26–28).
The findings suggest that factors such as sex, race, education level, age, and region of the country are associated with (and may influence) the recommendation of ICM. Women, individuals of Indigenous and mixed race, those with higher education, older individuals, and those living with a partner showed a higher likelihood of receiving ICM recommendations. These results are consistent with previous studies pointing to a higher acceptance and use of ICM in these specific groups (29–32). Unlike our findings, one study revealed that 63% of hypertensive patients used ICM to improve their health condition (33). Another study found that 39.1% of diabetic patients reported using ICM as part of their disease control strategies (34). Additionally, another study found a greater association between ICM use in individuals with AH and DM (35).
When compared to international literature, the prevalence of ICM use varies widely across countries. Studies show that the use of ICM in the past 12 months can range from less than 10% in some European countries to more than 50% in South Korea and China. Our findings remain below the international average (26.4%), as reported in a systematic review conducted with information from 32 countries (36). In Brazil, the prevalence was estimated at 5.3% in 2019, with higher use among women, individuals with higher education, residents of the North region, and older adults (17), results similar to our study. This same study found an association between white race, higher socioeconomic level, having private health insurance, and living in rural areas, which differs from our results (17). Previous studies in Brazil have also documented barriers to the recommendation and implementation of ICM in primary care, including insufficient knowledge about its effectiveness, lack of standardized clinical protocols, limited professional training, and organizational challenges within the health system (37,38). These structural and institutional factors may help to explain the low levels of ICM recommendation found in our study, despite the official recognition of these practices within the SUS. It is worth noting, however, that while these studies report the use of ICM, our outcome refers to the recommendation of these practices by health professionals. These are distinct but related constructs, and given the scarcity of studies addressing recommendation specifically, we used ICM use as an approximate (proxy) measure for discussion purposes.
In this study, recommendations for healthy eating, physical activity, and regular monitoring, health care practices that are already well-established and accepted by health care professionals and patients, had the highest frequency of recommendation by health care professionals. However, these recommendations vary between studies. For example, in the study by Williams et al. (2021) (39) on the care of hypertensive patients, the recommendations for reducing salt intake, healthy eating, and regular physical activity were 44.9%, 46.2%, and 57.7%, respectively. In the present study, these same recommendations were 88.4%, 87.7%, and 84%, respectively. Regarding DM, 93.7% of our participants were advised to avoid sugar consumption, compared to 66.4% in the Williams study.
These differences highlight the importance of public health strategies tailored to the cultural and economic context of each population, as well as the need to improve adherence and implementation of lifestyle recommendations by health care professionals (40,41). Personalizing these lifestyle recommendations to the patient's perspective can increase their effectiveness. Patient-centered approaches, which assess readiness for change, determine available resources, and establish goals, are effective ways to achieve this personalization (42,43).
This study has strengths, such as the use of a nationally representative sample, which allows the generalization of the results to the Brazilian population. The analysis of sociodemographic and economic factors associated with ICM recommendations enables a better understanding of potential inequalities in access to these practices. Additionally, the study provides an overview of the various health practices adopted by Brazilian health care professionals in the treatment of two important public health issues. However, the study also has limitations. The cross-sectional nature of the data prevents causal inference. The reliance on self-reports may introduce recall bias and under or overestimation of the recommendations received. Furthermore, the lack of qualitative data limits the understanding of the motivations and perceptions of health care professionals regarding the recommendation of ICM. It is important to note that, regarding self-reported skin color, the number of Asian and Indigenous participants who received ICM recommendations was small. Thus, the estimates of association for these groups should be interpreted with caution due to the reduced sample size and the resulting lower precision of confidence intervals



FINAL CONSIDERATIONS

The results of this study reveal a lower frequency of ICM recommendations compared to other management guidelines for arterial hypertension and diabetes mellitus by health care professionals. Still, a significant portion of the Brazilian population, 7.9% of hypertensive patients and 9.2% of diabetic patients, receive recommendations for ICM as part of their health care. The identification of sociodemographic characteristics associated with ICM recommendations can help in the implementation and/or dissemination of these practices within the public health system. Despite scientific evidence supporting the efficacy and safety of ICM, it is still not fully integrated into health care recommendations, due to barriers such as a lack of knowledge and training among health care professionals, as well as resistance from some managers and professionals. Therefore, it is important to tailor public health strategies to the specific context of each population, while also valuing patients' lifestyles. Patient-centered approaches, which consider readiness for change and available resources, can improve adherence and effectiveness of these recommendations. Policies and training programs are needed to increase the integration of ICM into health care practices. Longitudinal and qualitative studies are essential to better understand the barriers and facilitators for recommending and using ICM, promoting greater equity in access to these practices within the context of SUS.

FUNDING

The authors express their gratitude to the Coordination for the Improvement of Higher Education Personnel (CAPES) for granting the master's scholarship.

REFERENCES

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