Mental health problems are a considerable public health issue and spending time in nature has been promoted as a way to access a range of psychological benefits leading to the development of nature‐based interventions for people with severe and enduring mental health problems. Less, however, is understood about the potential benefits and efficacy of day‐to‐day routine access to outdoor green and blue spaces for mental health service users.N = 11) using qualitative interviews and an online general population survey (N = 1791). Qualitative evidence highlighted the restorative benefits of nature and identified a number of barriers associated with fears around personal safety, social anxiety, fatigue and lack of motivation. COVID‐19 had also restricted access to green and blue spaces. Having social contact and support encouraged people to spend time outdoors. In the quantitative survey, self‐report and standardised measures  were used to assess past and current mental wellbeing.Using a mixed‐methods design between April and October 2021, we explored the benefits and barriers to spending time outdoors with a purposive sample of mental health service users  and they were involved in the development of the research idea, funding application, design, data collection, analysis, writing up and dissemination activities. Natural environments provide interest and offer opportunities to escape from daily hassles or worriesBeing outdoors creates opportunities to establish social networks and increase social capital that can contribute to wellbeing,Although the evidence base is limited,perceptions of one's healthEven ,p.376 can lead people to reflect on their life, and ‘one's priorities and possibilities, on one's actions and one's goals’,p.197. Spending time in nature can compound feelings of isolation or be a reminder of how disconnected everyday life can be from the physical world.While the many benefits of green and blue spaces have been explored, it is also possible for individuals to experience negative associations with green and blue spaces. Nature can evoke overwhelming, existential anxieties: climate change, the ruthlessness of survival within nature and the ‘perspective‐making power of nature,N = 11) and a general population survey accessed online (N = 1791) (April–October 2021).We know less about the benefits and effectiveness of routine access to green and blue spaces for mental health users. To explore these issues further, we used a mixed‐methods design to identify potential barriers to spending time outdoors with a purposive sample of mental health service users  was no longer possible due to working‐from‐home restrictions to ameliorate this, we distributed paper questionnaires within Praxis Care's supported living settings.2.2Participants for the qualitative interviews were in receipt of a range of different services  and were invited to participate by the Head of Research in Praxis Care based in Northern Ireland.Participants for the quantitative online survey were recruited through a number of different sources in the United Kingdom and the United States including a targeted sample of people interested in mental health issues accessed through Praxis Care's internal communication network and via the Mental Health Foundation and Praxis Care social media platforms (Twitter and Facebook), and a general population sample using Amazon MTurk's survey tool.2.3A semistructured interview framework was developed to explore a range of themes with a purposive sample of mental health service users recruited through Praxis Care services. The qualitative interviews explored: exposure, frequency and dose of accessing green and blue spaces—time of day, social connections; facilitators and barriers to accessing green and blue spaces; benefits; negative effects and past experiences and future hopes.data familiarisation and writing familiarisation notes; (2) systematic data coding; (3) generating initial themes from coded and collated data; (4) developing and reviewing themes; (5) refining, defining and naming themes; (6) writing the report.Telephone interviews were conducted with 11 participants between February and April 2021. Three members of the research team, including two experts by experience, carried out one‐to‐one interviews lasting approximately 45 min each. Qualitative interviews were digitally recorded and transcribed for analysis by P. W. Thematic analysis2.4Findings from the qualitative interviews and the research literature were used to develop a quantitative online survey using the Qualtrics™ platform. The short online survey was advertised online and included the following measures.2.5Demographic information: year of birth; gender identity; sexual identity; disability status; relationship status; dependents and carer status; employment status; household financial coping; ethnicity; current or previous mental health diagnosis; current medication; city/country location.2.6Experience of mental health problems was assessed using a self‐report measure, endorsement of any of the following statements was coded as a dichotomous variable ‘Yes’  or ‘No’: ‘I have no mental health problems’.2.7α = .82–.85).The PHQ‐8 is a well‐validated self‐report measure for assessing depressive symptom severity2.8α = .89–.93).The short version of the Warwick–Edinburgh Mental Wellbeing Scale (SWEMWBS)2.9Participants were asked ‘over the past month, on average, how often have you spent time outdoors?’ and could choose one selection from seven items: ‘more than once a day’, ‘once a day’, ‘several times a week’, ‘once a week’, ‘once every 2 weeks’, ‘once’, ‘none’. This applied to any free or leisure time not spent working, job hunting, studying or doing household chores. They were then asked ‘Is there a time of day you prefer?’ A range of options was available from early morning to night time, participants could endorse multiple items.2.10Questions about facilitators and barriers were generated from the research literature. Participants were asked to indicate ‘what encourages you to spend time outdoors? ‘the weather’; ‘my mood’; ‘my friends/family’; ‘the right clothing/shoes’; ‘conservation/environmental reasons’; ‘to get a break from other people’; ‘my pets’ and a free text option of ‘other’. Respondents were asked ‘Not everyone enjoys spending time outdoors, are there times when you don't like going outside?’ and could endorse as many items that applied to them from: ‘no free time/other commitments’; ‘feeling unsafe’; ‘it's difficult to get to/access’; ‘the weather’; ‘how I look/feel about myself’ and ‘makes me feel anxious’.33.13.1.1M = 53, SD = 12.61). The use of Praxis Care services was a proxy measure of an existing mental health problem that could range from mild‐moderate to severe and enduring.Eleven service users (six women and five men) participated in the telephone semistructured interviews; each interview lasted around 45 min. They ranged in age from 34 to 84 years old . For others who viewed leaving the house for everyday tasks as a source of anxiety, ‘I do like to go out but it's just that I get butterflies…you panic a bit and then you want to go back to the house…’ .3.1.3Interviewees made a clear association between spending time outdoors and mental wellbeing. The word ‘lift’ was used to describe the effects of spending time in green and blue spaces, ‘lift your spirits’ , ‘lifts your mind’  and ‘the psychological benefits are it keeps my mood lifted’ . Nature provided a contrast to the built environment, where ‘concrete almost wears you out…nature… it's uplifting you’ .Enjoying wildlife, specifically birds and birdsong, was mentioned by half of those interviewed, and functioned as a way of connecting with nature.3.1.4Nature was described as calming, soothing, and peaceful and expressed as pure and cleansing, ‘I think it clears you and you are sharper, yes, that's the purification thing, it just gives; it's so inspiring’ . Negative elements of the outdoors were also referred to as a source of anxiety including litter, dog fouling, rats and chewing gum on the pavements.3.1.5Fear and safety issues were raised in a number of different contexts. Practical safety issues were a concern for some. Personal safety, traffic, lack of footpaths or fear of falling and injury was also a concern, ‘I get anxious over my physical issues because I'm scared of falling’ . Antisocial behaviour, such as alcohol and drug use in public spaces, was also considered a barrier.Fear relating to social anxiety and experiencing panic attacks was expressed by a number of respondents trying to manage their negative feelings.3.1.6The opportunity that public spaces provide to promote social cohesion also resonated with half of the respondents talking about the social aspect of spending time outdoors, whether this was ‘talking and walking’  or having the opportunity to ‘get to meet people’  and ‘say hello, there is a kind of little community, social thing’ .3.1.7Many of those interviewed were vulnerable and became increasingly isolated during the lockdown. Some people relied on others to spend time outdoors, whether this was a family member or friend or the support services that Praxis Care offered. When these services were withdrawn, this impacted considerably their capacity to leave their home. ‘Now, we can't meet people. People are important to other people. They help each other’ .3.1.8A number of barriers to spending time in green and blue spaces were discussed. Lack of transport was an issue, especially for those living in rural areas. Physical health and tiredness could be a limiting factor, but problems associated with social isolation impacted being outdoors, ‘It's just not a place I would go to on my own, you know, I wouldn't ever think of going to a park’ because you would need company to go there . Mental health difficulties also could restrict attempts to socialise or leave the home, ‘I went and nobody talked to me and then I got really down so that's why I don't go out much’ .3.1.9All of the interviewers were connected to Praxis Care, either as service users or employees, and reference was made to the support the organisation offered people, from providing social contact over the telephone, ‘you know when you get the phone call, it makes you feel better, makes you think that someone is thinking about you “cause you get lonely on your own”’  to calling to the house and encouraging them to get some exercise and fresh air, ‘Praxis Care, the wee girls came with me for a walk and it makes me feel good…we go for a walk round the park and we talk, and then come back to the house, it makes me feel out of breath’ . Other factors that contributed to spending time outdoors were associated with promoting mental wellbeing, undertaking functional household‐related activities  and the opportunity for social contact.3.23.2.1N = 1791 people participated in the online survey. The demographics of the sample are summarised in Table Between September and November 2021, a total of 3.2.2χ2 = 23.57, p = .001) or current wellbeing using the PHQ‐8 cutoff score of 10 or more  = 61.25, p < .000). Respondents scoring ‘high’ on the SWEMWBS scale were also more likely than those rated ‘low’ or ‘medium’ to spend time outdoors at least once or more than once a day.The majority of participants had access to green (90.8%) and blue spaces (69.6%) Table . People Asked to consider their activity over the past month, respondents endorsed the different reasons why they had spent time outdoors Table . Again, χ2 = 5.36, p = .021) or night time χ2 = 14.06, p < .000). Night‐time preference was also observed in the PHQ‐8 > 10 samples  = 4.18, p = .041). A significant relationship was observed between respondents scoring ‘high’ levels of wellbeing on the SWEMWBS and spending time outdoors in the early morning  = 18.98, p < .000).Participants were also asked if there was a particular time of day that they preferred to go outdoors, multiple items could be endorsed Table . Again s3.2.3χ2 = 5.85, p = .016)  = 18.91, p < .000). N = 125 respondents provided an answer to the ‘other’ open‐ended question and exercise (n = 33) was the most popular reason for spending time outdoors, spending time in nature (n = 16) and gardening (n = 11).What encourages you to spend time outdoors?: Facilitators for those with experience of any mental health problems included ‘my mood’, ‘the right clothing/shoes’ and ‘to get a break from other people’. For those without self‐reported mental health problems were more likely to be encouraged by the weather to go outdoors than those with experience of problems , and insects/bugs (n = 10).Not everyone enjoys spending time outdoors, are there times when you don't like going outside?: Participants with experience of past or current problems were statistically significantly more likely to identify barriers such as ‘feeling unsafe’, ‘how I look/feel about myself’ and ‘makes me feel anxious’ than those without mental health problems Table . They we4Spending time outdoors, in green and/or blue spaces was recognised as contributing to people's wellbeing, and offered mental health service users opportunities to feel restored, enjoy nature, be active and have social contact. It was mostly structured around errands or specific tasks and was considered to be an important part of a regular routine to help tackle negative aspects of their day. Spending time outdoors had the potential to elevate mood, ‘lift your spirits, lifts your mind’, helped to reduce unhelpful behaviours—whether these related to challenging feelings of fear, social anxiety or avoiding unhealthy eating habits. A clear link between exercise and wellbeing was understood and the concept that nature was restorative, soothing and clean and required protection and preservation was depicted by those interviewed. However, a range of practical and psychological barriers prevented access was evident. Lack of transport, physical health problems and feeling tired restricted some people's activities but having some social support  to encourage them to leave the house was a valuable resource. Reflecting on the quantitative results, people without experience of mental health problems were more likely to have a higher frequency and dose of green and blue spaces compared to those with mental health problems. Unpicking why these differences were found is complicated however some light may be shed on the variation in motivations to spend time outdoors between the two groups. There were clear differences in how and why people accessed green and blue spaces, with the general sample more likely to endorse positively framed reasons such as getting exercise, enjoy the weather or gardening. Those without mental health problems endorsed items that focused on self‐improvement such as increasing physical activity and physical health, enjoying nature and the fresh air and investing time in themselves. Green and blue spaces were considered a way to improve both physical and mental wellbeing. Those with experience of mental health problems portrayed a more negative personal perspective of the barriers they faced. These included issues around self‐image, managing anxiety, feeling guilt or dealing with stress. Relying on external motivators was more likely to be endorsed such as walking a pet and having someone to encourage them to get outdoors. There were no differences between the two groups in a number of aspects including taking part in planned outdoor activities such as walking groups and outdoor gyms. Spending time outdoors to improve concentration, and motivation or to work through a problem was also similar. Meeting up with friends and family was equally important to both groups.Going out at night was preferred by those with mental health problems by either measure. Further research could help explore the reasons why this might be the case and hypotheses could include the role of social anxiety, personal safety and disrupted circadian rhythms. Feeling safe at night is a particular issue for many women, creating safer spaces and greater awareness of the vulnerabilities women experience on a regular basis, better lighting and more effective outdoor security measures may help increase feelings of safety for everyone.Like the participants in our study, the general public value the importance and benefits of green and blue spaces for wellbeing.Messaging about the benefits of green and blue spaces is equally important for people with mental health problems and must tackle the anxieties and concerns people raised, people should feel safe, secure and supported to access outdoors and be aware of the mental health benefits that may be available. Although our data did not highlight demographic differences in people's experiences of feeling unsafe, it is important to acknowledge, explore and consider that people may feel unsafe for a wide range of intersecting reasons, for example, in relation to gender, age, sexual orientation, physical appearance and being from visible minorities. Improving access to green and blue spaces has the potential to help address these inequities and the wider social determinants of health, but these complexities need to be considered in the development and promotion of safe, open and accessible places for everyone. How to create and promote accessible spaces for all should be a priority for planners and policymakers, and involving service users and carers in these processes will help to ensure all the relevant and complex issues are considered.4.1It is clear that there are different barriers and facilitators for people who are experiencing mental health problems. The emerging evidence on the contribution that green and social prescribing can make to reduce mental health inequalities is encouraging. Mental health providers, GPs, social workers, education and workplace settings should be encouraged to respond to and incorporate the research learning to establish opportunities and experiences to engage with nature in recognition of its therapeutic benefits. The development of policy guidance would be a welcome starting point and would acknowledge the need to adopt and embed sustainable practices. Inequalities extend to access to green and blue spaces and planning policies already address the need for improving access but this does not tackle existing estate and the fact that social housing stock is often located in areas of social deprivation. Interventions that promote feelings of safety, and reduce anxiety via buddy systems/could promote the social gateway to green and blue spaces. Promoting the benefits of being outdoors should use appropriate and relevant language and identify goals for those experiencing mental health problems such as improving self‐image, reducing anxiety, increasing social contact and enhancing mood. Improving access to green and blue spaces is a joint responsibility across government departments and policy needs to reflect this. The longer‐term impact of COVID‐19 on mental health is also an area of developing concern and we need to understand whether the impact of isolation has reinforced anxieties about being in now less familiar, crowded public spaces.4.2We were unable to access an SMI sample because of Covid restrictions. To account for this deficit, we contacted service users living in supported living settings despite our directed efforts to recruit an SMI population, analyses found that almost half of the online participants reported mental health problems, including SMI. The majority of participants in the qualitative study were older adults therefore we cannot generalise these findings to younger people. Using MTurk to access a general population that included a large number of US participants and people were paid a small amount to participate, it is unlikely that participants were a random sample and therefore we are unable to generalise any findings to the United Kingdom.5Promoting green and blue spaces as a mental health prevention, early intervention or treatment option could be a valuable public mental health approach, but it is important that access to safe spaces is improved through public planning and policy. Ways of providing access, on whatever scale, within the existing estate of supported housing for people with mental health problems should be considered. The importance of appropriate messaging could help promote the appeal of green and blue spaces to different users. More research is required into the routine use of green and blue spaces and the potential positive impact on wellbeing.Claire McCartan and Gavin Davidson led all aspects of the project. Lee Knifton, Paul Webb and Chris White contributed to the study design and, with Liam Bradley and Katherine Greer, contributed to writing the research proposal and applying for and securing project funding. Liam Bradley, Katherine Greer and Paul Webb developed the qualitative interview schedule and Paul Webb facilitated data collection. Katherine Greer and Aodán Mulholland conducted the qualitative interviews. All authors contributed to the analysis and study write‐up. Each author certifies that they have made a direct and substantial contribution to the conception, design and delivery of the study. We are grateful to the service users who participated in the interviews and thanks to Emily Peckham, Piran White, Simon Gilbody and the Closing the Gap team for their support and guidance delivering the project.Gavin Davidson's post at Queen's University Belfast is partly funded by Praxis Care which was one of the partners in this project. The remaining authors declare no conflict of interest.Ethical approval for the qualitative stage was granted by the Research Ethics Committee of the School of Social Sciences, Education and Social Work at Queen's University Belfast in April 2019. The quantitative stage was approved by the NHS West Midlands—Coventry and Warwickshire Research Ethics Committee in July 2020 (REC reference 20/WM/0172). All participants provided written informed consent before taking part.


Prior studies suggested that antidepressant use is associated with an increased risk of dementia compared to no use, which is subject to confounding by indication. We aimed to compare the dementia risk among older adults with depression receiving first-line antidepressants  versus psychotherapy, which is also considered the first-line therapy for depression.This retrospective cohort study was conducted using the US Medical Expenditure Panel Survey from 2010 to 2019. We included adults aged ≥ 50 years diagnosed with depression who initiated SSRI/SNRI or psychotherapy. We excluded patients with a dementia diagnosis before the first record of SSRI/SNRI use or psychotherapy. The exposure was the patient’s receipt of SSRI/SNRI (identified from self-report questionnaires) or psychotherapy . The outcome was a new diagnosis of dementia within 2 years  identified using ICD-9/ICD-10 codes from the Medical Conditions file. Using a multivariable logistic regression model, we reported adjusted odds ratios (aORs) with 95% confidence intervals (CIs). We also conducted subgroup analyses by patient sex, age group, race/ethnicity, severity of depression, combined use of other non-SSRI/SNRI antidepressants, and presence of underlying cognitive impairment.Among 2,710 eligible patients , 89% used SSRIs/SNRIs, and 11% received psychotherapy. The SSRI/SNRI users had a higher crude incidence of dementia than the psychotherapy group (16.4% vs. 11.8%), with an aOR of 1.36 (95% CI = 1.06–1.74). Subgroup analyses yielded similar findings as the main analyses, except no significant association for patients who were aged < 65 years , male , Black , had a higher PHQ-2 , and had underlying cognitive impairment .Our findings suggested that older adults with depression receiving SSRIs/SNRIs were associated with an increased dementia risk compared to those receiving psychotherapy.The online version contains supplementary material available at 10.1186/s12877-023-04475-z. • Our findings suggested that SSRI/SNRI use was associated with an increased dementia risk compared to psychotherapy among older adults with depression.• Subgroup analyses yielded similar findings as the main analyses, except no significant association for patients who were aged < 65 years, male, Black, had a higher PHQ-2 score, and had underlying cognitive impairment.Why does this matter?Clinicians should be aware of SSRI/SNRI-associated dementia risk when considering the first-line treatment for older adults with depression. Patient characteristics may also play a critical role in such an association.The online version contains supplementary material available at 10.1186/s12877-023-04475-z. We certify that this work is novel. This work is the first to compare first-line antidepressants  to an active comparator  to reduce confounding by indication instead of comparing antidepressant use to no use in prior studies.One out of ten older adults aged ≥ 65 years suffers from dementia in the United States (US), and the prevalence dramatically increases with age . The ecoPsychotherapy and antidepressants are considered the mainstay treatments for depression . PsychotAlthough antidepressants are beneficial for managing depressive symptoms, some studies reported the association between antidepressants and risk of dementia. For example, a meta-analysis found an increased long-term risk (follow-up > 1 year) of dementia associated with antidepressant use compared to no use among older adults . Kodesh Prior studies are limited by only comparing antidepressant exposure with no exposure, which may be subject to confounding by indication and severity . That isThis study used the 2010–2019 US Medical Expenditure Panel Survey (MEPS) data, a longitudinal, large-scale survey of noninstitutionalized adults in the US . Each pahttps://meps.ahrq.gov/mepsweb/ ). Due to the nature of de-identification and public availability of the MEPS data, the University of Florida IRB determined the study exempt and did not require informed consent to participate.MEPS data is reviewed and approved by the Westat Institutional Review Board (IRB) annually and is established under a multi-project assurance (MPA M-1531) granted by the Office for Protection from Research Risks. After carefully removing individual’s identifiable information, an annual series of Public Use Files of de-identified MEPS data are made publicly available to researchers  codes  . We furtOur exposure of interest was the patient’s receipt of SSRIs/SNRIs versus psychotherapy. We identified SSRI/SNRI use from the questionnaires in the prescribed medicines files using therapeutic classification variables from Cerner Multum, Inc.  and ICD-10 codes  from the Medical Conditions file  . Given tTo evaluate the heterogeneity in the drug effect among different patient subgroups, we grouped patients by sex , age group , race/ethnicity , severity of depression , concomitant use of non-SSRI/SNRI antidepressants , and underlying cognitive impairment . Then, we repeated all the steps in the main analysis in each subgroup.To test the robustness of our findings, we performed two sensitivity analyses. First, we used a 1:1 greedy nearest neighbor PS matching approach to match patients using SSRI/SNRI to those receiving psychotherapy. Similar to the main analysis, PS matching with the PROC SURVEYLOGISTIC procedure allows us to estimate the population ATT. Second, we used a subset of covariates  to estimate the PS and repeated the sIPTW approach.As shown in Fig. In Table Most subgroup analyses reported consistent results with the main analysis, except for patients who were aged < 65 years, male, Black, had a PHQ-2 score of 3–6, and had underlying cognitive impairment, for whom the adjusted ORs (95% CI) were 1.23 (0.93–1.62), 1.34 (0.95–1.90), 0.76 (0.48–1.19), 1.39 (0.90–2.15), and 1.06 (0.80–1.42), respectively. The sensitivity analyses yielded similar findings as the main analysis. The adjusted ORs (95% CI) were 1.27 (1.18–1.37) using the 1:1 PS matching and 1.12 (1.05–1.20) when removing comedications from the PS calculation.In this retrospective cohort study using nationally representative survey data in the US, we found that older adults with depression receiving SSRIs/SNRIs were associated with a 31% increased risk of dementia within two years compared to those receiving psychotherapy after adjusting for patient characteristics such as age, sex, race/ethnicity, depression severity, underlying cognitive impairment, comorbidities, and concomitant drugs. Most subgroup analyses yielded similar results, except for patients who were aged < 65 years, male, Black, had a PHQ-2 score of 3–6, and had underlying cognitive impairment, which did not show significant differences in the risk of dementia between SSRI/SNRI use and psychotherapy.Unlike previous studies largely comparing antidepressant users with nonusers, our study adopted the active comparison group approach to reduce confounding by indication and severity in older adults with depression. Our findings were consistent with some of the prior studies. For example, a meta-analysis including observational studies with at least a 1-year follow-up period showed that SSRI use was associated with an increased risk of dementia compared to no SSRI use, with a pooled risk ratio (RR) of 1.75 (95% CI: 1.03–2.96). However, the heterogeneity in the meta-analysis was extremely high, and one out of five included studies suggested that SSRI use was associated with a lower risk of dementia  . AnotherIn the subgroup analyses, we found that the association between SSRI/SNRI use and dementia risk did not exist in patients with a higher PHQ-2 score. Patients with a higher PHQ-2 score might reflect those with more severe depression or uncontrolled depression, which may confound the drug effect . That isThere are some limitations in our study. First, we used MEPS data, which only follow a patient for at most 2 years, which may not be long enough for dementia to occur and underestimate the risk of dementia . HoweverOur findings provide valuable insight into the complex association among depression, antidepressants, and risk of dementia, providing additional evidence for clinicians while prescribing antidepressants for patients with depression. Future longitudinal studies are warranted to allow the identification of new users of antidepressants and the evaluation of long-term dementia risk.Additional file 1: Appendix Figure 1. Directed acyclic graph illustrating the relationships among exposure, outcome, and confounders. Appendix Figure 2. Detailed steps of the statistical analysis. Appendix Table 1. Variables included in our study.


Actinobacillus pleuropneumoniae (apxIVA) and Pasteurella multocida (kmt1). The methods showed good linearity, precision, and accuracy. In both healthy and diseased pigs, a significant correlation was observed between LC/MS and the microbiological assay  and between LC/MS and the enzyme-linked immunosorbent assay (ELISA) . A strong correlation was observed between the microbiological assay and the ELISA in both healthy and diseased pigs . A Bland-Altman analysis revealed good agreement between the methods, i.e., 95% of the differences were within the limits of agreement. Therefore, the microbiological assay and the ELISA, which demonstrated sufficient precision and accuracy, can be viable alternatives to LC/MS when it is unavailable.Employing affordable and uncomplicated sample preparation techniques to recommend the most efficient antibacterial therapy could help reduce antibiotic-resistant bacteria. This study evaluated the suitability of immunoassays and microbiological assays as alternatives for liquid chromatography/mass spectrometry (LC/MS) in determining plasma tylosin concentrations after intramuscular administration at a dose of 20 mg/kg to both healthy and diseased pigs in clinical veterinary practice. The diseased pigs were confirmed using the target genes  Staphylococcus, Streptococcus, and Corynebacterium [Actinobacillus pleuropneumoniae and Pasteurella multocida in pigs [Tylosin is an antibiotic commonly used in veterinary medicine for the treatment of respiratory infections in pigs . Tylosinacterium . Tylosin in pigs ,5.The prevention and treatment of pathogenic respiratory bacterial infections in pigs can be enhanced by directly measuring plasma antibiotic concentration and conducting antibiotic susceptibility testing, and thereby increasing the effectiveness of antimicrobial therapy . In addiMethods such as liquid chromatography/mass spectrometry (LC/MS), microbiological assay, and enzyme-linked immunosorbent assay (ELISA) can determine plasma concentration ,9. TheseIf we can establish a strong correlation between LC/MS and field-applicable microbiological methods or ELISA in healthy and infected swine plasma following the administration of tylosin to pigs, it will be possible to prescribe optimal antibacterial therapies in the field using simple and low-cost sample preparation technology. This could help reduce the emergence of resistant bacteria. Thus, this study aimed to evaluate the correlation of LC/MS with a microbiological assay and an ELISA when determining the plasma concentration of tylosin in healthy and infected pigs.apxIVA and kmt1 polymerase chain reaction (PCR) target genes for A. pleuropneumoniae and P. multocida with respective fragment sizes of 377 bp , out of which 5 infected pigs exhibited clinical signs such as reduced activity, labored breathing, and coughing. Similarly, the rest of the infected pigs were lethargic and less engaged with their surroundings compared with their healthy counterparts. The diseased pig samples had the f 377 bp a and 460f 377 bp b, confirThe concentration–time profiles of tylosin in the plasma after intramuscular injection in healthy and infected pigs were determined using three methods, namely LC/MS, microbiological assay, and ELISA, and the results are presented in 2), slope, and y-intercept were 0.98, 1.00, and 0.16, respectively. The limit of detection (LOD) was 0.014 µg/mL and the limit of quantification (LOQ) was 0.042 µg/mL. Both the intra-assay precision and the inter-assay precision were determined to be <20%, and the accuracy of the assays were 101.34–113.62% and 97.38–108.36% for the intra- and inter-assays, respectively  values from the assays on three different days, and these values ranged from 4.08% to 7.64%. The intra- and inter-assay accuracy rates were 85.95–116.04% and 84.20–102.02%, respectively  and the slope of 0.806 indicate a dose-dependent relationship. Likewise, a correlation was observed in the diseased pigs, with a Pearson correlation coefficient of 0.950 (p < 0.001) and a slope of 1.330  and a slope of 0.694 (p < 0.001) (of 0.694 b. A sign< 0.001) e.To assess the agreement between LC/MS and the ELISA, a Bland–Altman plot was produced, and this displayed the differences between the LC/MS and ELISA datasets versus the mean tylosin concentrations obtained using these two methods. The mean difference in the concentrations obtained using the two methods was −0.17 in the healthy pigs, with limits of agreement of −2.10 and 1.77 b, whereap < 0.001) and a slope of 0.782 were observed, whereas for the diseased pigs, a Pearson correlation coefficient of 0.910 (p < 0.001) and a slope of 0.881 were observed, indicating a dose-dependent relationship  and LC/MS are the most widely accepted methods of assessing drug plasma concentrations, and they are both highly accurate and capable of analyzing multiple compounds in a single sample . HoweverIn this study, we aimed to develop a low-cost method for determining plasma tylosin concentrations that can be used in laboratories where LC/MS is inaccessible. Alternative methods for measuring drug concentrations, such as immunoassays and microbiological assays, are available ,19. AlthComparing microbiological and instrumental methods with other biological methods is a common practice used to investigate potential variations in the pharmacological activity of drugs and determine drug concentrations in the plasma. It has been found that microbiological assays may have limited sensitivity compared with other analytical methods. The detection limit of the assay may not be sufficient to accurately measure low drug concentrations in plasma samples. This can be a limitation when analyzing drugs that exhibit low plasma concentrations, or when studying drug pharmacokinetics in the body . A previIn this study, we analyzed plasma tylosin concentrations over time in healthy and diseased pigs and found similar concentration changes over time using all three methods. Each method demonstrated satisfactory performance with inter- and intra-assay coefficients of variation within ±20.0% for the RSD (%). These results suggest that the microbiological and ELISA methods may be used in place of LC/MS for measuring tylosin, and that they have potential for rapid and on-site application. To confirm this possibility, we statistically analyzed the data to compare the three methods.p < 0.001), between LC/MS and the ELISA , and between the microbiological assay and the ELISA  in the healthy pigs, and by those between LC/MS and the microbiological assay , between LC/MS and the ELISA  and between the microbiological assay and the ELISA  in the diseased group.Bland and Altman developed the Bland–Altman plot to evaluate similarities between two sets of numerical measurements. In this study, the Bland–Altman plot indicated a high level of agreement between the measurement methods, with 95% of the differences between the two methods falling within the appropriate limits. However, the suitability of these limits should be determined based on clinical and biological considerations . To use Although the ELISA is a valuable tool, there are certain limitations and obstacles that may affect the precision and consistency of its results . Its speThis study found good correlation between different analytical methods used to measure tylosin levels in plasma. ELISAs and microbiological assays have several advantages, including simplicity, cost-effectiveness, and the ability to provide important insights into a drug’s effectiveness and potency. However, it is important to acknowledge that these assays may not be suitable for all types of drugs, and their limitations should be taken into account. Certain drugs may not be accurately detected or quantified by these assays due to factors such as interference from other substances, complex drug formulations, or the absence of specific microbial targets. Therefore, while microbiological assays can be valuable in drug testing, it is crucial to supplement them with other analytical methods to ensure a thorough and precise evaluation of a drug’s properties.A. pleuropneumoniae and P. multocida displayed various symptoms, including anorexia, high body temperature, labored breathing, and coughing, all of which are symptoms that are typically observed in diseased pigs [This study involved creating a diseased porcine model through intranasal inoculation. The pigs infected with sed pigs . After tsed pigs . Therefosed pigs . Hence, Standard tylosin (>96%) was purchased from Sigma . The injectable tylosin was obtained from Samyang Anipharm . Nicotinamide adenine dinucleotide (NAD) was obtained from Sigma. All chemicals and reagents used in this study were of HPLC grade.A. pleuropneumoniae (BA2000013) and P. multocida (BA1700127) were provided by the Animal and Plant Quarantine Agency . Before use, the bacterial isolates were streaked on brain heart infusion agar  supplemented with 0.02% NAD and incubated at 37 °C in 5% CO2. For the microbiological assay, M. luteus KCCM 11236 was obtained from the Korean Culture Center of Microorganisms (KCCM) and cultured on tryptic soy broth  at 37 °C for 18 h.9 cfu/mL of A. pleuropneumoniae and P. multocida to establish a disease model. During the experiment, clinical respiratory disease score, intestinal function score, appearance/abnormal signs, and clinical signs were recorded [A. pleuropneumoniae and P. multocida infections were monitored by culturing nasal swabs, and infections were confirmed by the presence of the apxIVA gene [kmt1 gene [A. pleuropneumoniae and P. multocida, respectively.The study was carried out on 14 pigs (Duroc × Landrace × Yorkshire) aged 5–6 weeks with an average weight of 9.5 ± 1.1 kg. The animals were acclimatized for 1 week with free access to the water and feed. The animal study was approved by the Animal Ethics Committee of the Petobio Clinical Institute (PTB-2022-IACUC-013-A). After proper adaptation, the pigs were divided into a healthy group and an infected group, with each group consisting of seven animals. The bacterial challenge was performed according to a previously described method, but with some modifications . The 40 recorded ,35. A. pIVA gene  and the mt1 gene , used fog for 10 min at approximately 5 °C. The plasma from each Vacutainer was divided into aliquots of about 0.6 mL which were deep frozen at approximately −75 °C until analysis.The healthy and diseased pigs received intramuscular tylosin injections at a dose of 20 mg/kg. The selection of a 20 mg/kg drug dose was based on previous studies  that hadg for 10 min at 4 °C. The 2 mL of supernatant was collected to dryness in a water bath using nitrogen at 50 °C. The residue was then dissolved in 200 μL of methanol, agitated for 1 min, and centrifuged at 12,000 rpm for 10 min at 4 °C. The final 70 μL of supernatant was analyzed using LC/MS.Preparation for the LC/MS analysis was as follows. The 250 μL plasma samples were thawed at room temperature and then deproteinized with methanol (2 mL) via vortexing for 15 min and centrifuged at 3300× M. luteus KCCM 11236 as the test organism [M. luteus KCCM 11236 bacterial suspension was added to tempered nutrient agar from Becton, Dickinson and Company, Franklin Lakes, NJ, USA, at a concentration of 106 cfu/mL. The agar mixture was immediately poured onto assay plates in 2.2 mm layers. After allowing the samples to solidify for 45 min, wells with 0.5 cm diameters were created and filled with 60 μL plasma samples or tylosin standards covering a range of concentrations from 1 μg/mL to 16 μg/mL. The agar plates were then incubated for 18 h at 37 °C. The zones of bacterial inhibition were measured using a digital caliper from Mitutoyo, Japan. This method was chosen for its high sensitivity, simplicity, and strong correlation with HPLC measurements [Plasma tylosin concentrations were determined via a microbiological assay using organism . The bacurements . The meturements .0) × 100%. Here, A = average absorbance of standard or sample and A0 = Average absorbance of 0 ppb standard. For the standard curve, the absorbance percentage of each standard was plotted on the y-axis, and the logarithmic concentration was plotted on the x-axis, resulting in a semi-log plot. The precision of the assays was evaluated by assessing repeatability, which was expressed as the relative standard deviation (RSD). To determine accuracy, a control sample was introduced at the beginning of the procedure, and the measured value was calculated by dividing it by the nominal value and multiplying the result by 100.Plasma tylosin concentrations were assessed using an ELISA kit (E-FS-E058) obtained from Amsbio . A 1 mL serum sample was transferred to a 2 mL e-tube and centrifuged for 5 min at 4000 rpm at room temperature. Following centrifugation, 0.1 mL of the supernatant was collected and mixed with 0.9 mL of the reconstitution buffer provided by the ELISA kit. The mixture was then oscillated for 30 s. Finally, a 50 μL sample was extracted for detection, following the manufacturer’s instructions. The optical density was determined at 450 nm using an Epoch microplate reader . The percentage of absorbance was determined using the following formula: . The flow rate was 0.4 mL/min and the sample injection volume was 3 μL. The column temperature was maintained at 40 °C. The monitored precursor ion for tylosin was 916.3 m/z. The validation of the assay was performed according to a procedure described elsewhere [The LC/MS analysis was performed using a 1200 HPLC system from Agilent Technologies  that was connected to a 6140 single mass spectrometer (Agilent Technologies). The mass spectrometer was set up with an electrospray positive ionization mode using a capillary voltage of 3500 V, and it had optimal ESI-MS parameters, such as a drying gas temperature of 350 °C, a drying gas flow of 5 L/min, and a nebulizing gas pressure of 45 psi. The separations were accomplished using an Eclipse Plus C18 column  from Agilent Technologies. The mobile phase consisted of a mixture of 0.1% formic acid in water (Eluent A) and 0.1% formic acid in acetonitrile solution (Eluent B), with a ratio of 30:70 . The agreement of the three analytical methods was evaluated using the Pearson correlation coefficient method and the Bland-Altman method ,43.In this study, the results of comparing three different methods for measuring tylosin plasma concentrations were significant, considering the importance of monitoring antibiotic concentrations in animals to prevent the emergence of antibiotic-resistant bacteria, which can be caused by the overuse of antibiotics in farming practices. Thus, the microbiological assay and the ELISA, both of which are cost effective and accessible, could replace LC/MS. Nevertheless, these simpler methods still require improvements in their precision and consistency before they can be extensively used in clinical applications for antibacterial therapy.