Knowledge, attitudes and practices towards blood donation among donors: a cross-sectional study in Shaoxing, Zhejiang, China

Abstract

Objective

To evaluate the knowledge, attitudes and practices (KAP) towards blood donation among blood donors.

Design

A cross-sectional study was conducted.

Setting

The study surveyed voluntary blood donors in Shaoxing, Zhejiang.

Participants

A total of 580 voluntary blood donors participated in the survey between May 2024 and June 2024.

Interventions

An investigator-designed questionnaire was administered to collect demographic data and assess participants’ KAP regarding blood donation.

Outcome measures

The outcome measures included the KAP scores of blood donors.

Results

Analysis revealed a mean knowledge score of 19.37±4.05 (possible range: 0–22), an attitude score of 46.28±4.45 (possible range: 10–50) and a practice score of 23.37±5.67 (possible range: 6–30). Knowledge scores correlated positively with attitude (r=0.580, p<0.001) and practice scores (r=0.494, p<0.001). Furthermore, attitude scores showed a strong correlation with practice scores (r=0.618, p<0.001). Structural equation modelling indicated that knowledge directly influenced attitudes (β=0.622, 95% CI 0.539 to 0.704, p=0.007) and had an indirect influence on practices (β=0.411, 95% CI 0.329 to 0.536, p=0.005). Attitudes directly influenced practices (β=0.661, 95% CI 0.554 to 0.761, p=0.006).

Conclusions

Blood donors exhibited good knowledge and positive attitudes, but their practices were suboptimal. These findings highlight the need for targeted interventions to enhance participation in blood donation.

Correspondence to Dr Lingling Jiang; [email protected]

STRENGTHS AND LIMITATIONS OF THIS STUDY

• The study involved 580 voluntary blood donors, providing a robust dataset that enhances the reliability and generalisability of the findings.

• The study’s cross-sectional design limits the ability to establish causality between knowledge, attitudes and practices regarding blood donation.

• Relying on self-reported questionnaires may introduce biases, affecting the accuracy of the knowledge, attitudes, and practices reported by participants.

Introduction

Blood donation is paramount in global healthcare, with over 100 million blood units contributed annually. The availability of blood units is crucial for patients undergoing surgery, coping with trauma, managing chronic illnesses and battling cancer. This essential procedure is a lifeline for many patients, sustaining and saving lives.¹ The two primary uses of blood units are for anaemia correction and acute blood loss.¹ Blood donation is essential for maintaining blood banks, and declining donation rates can compromise the proper management of patients with trauma, those undergoing major surgeries and patients with transfusion-dependent conditions (eg, transfusion-dependent thalassaemia).^{2 3} The WHO estimated that at least 1% of a nation’s population should voluntarily donate blood to meet the basic requirement for blood and its products.⁴ The high prevalence of chronic infections in some regions (eg, hepatitis B and C)^{5 6} and the use of certain medications can also limit blood donations.^{7 8} The donor must also meet fitness criteria (eg, minimum allowable haemoglobin level, a normal body temperature) and wait for the proper interval to replenish iron stores.^{9 10} Furthermore, offering incentives for blood donation appears economically inefficient.²

In addition to medical contraindications and regional incentives, individual knowledge and motivation play key roles in blood donation. Blood donation is a voluntary process, and while publicity campaigns can influence donation rates, a person’s knowledge of the importance of blood donation and their attitudes towards it are major factors influencing their practice of donating blood. Knowledge, attitudes and practice (KAP) surveys can be used to identify gaps, misunderstandings and misconceptions that can constitute barriers to the optimal performance of a specific set of actions in a specific population.^11–13 Previous KAP studies explored the domain of voluntary blood donation, including the reasons for donating blood or not, sources of knowledge, motivating and demotivating factors for voluntary blood donation and the impact of peer structure on potential donors, among others.^14–25 One previous study on college students in Wuhan (China) identified factors associated with their KAP towards blood donation.²⁶ Another study in Students in Sichuan showed that the KAP of donors was higher than that of non-donors.²⁷ Still, those factors can vary widely among different regions of the world, even within a country, due to differences in economic conditions, education, healthcare systems, culture and various socioeconomic factors. China is a large country with vast disparities in socioeconomic statuses among different provinces. Therefore, it is essential to perform KAP studies in specific areas to design interventions specific to those areas.

Therefore, the present study aimed to evaluate the KAP towards blood donation among blood donors in Zhejiang province, located in the economically developed southeastern region of China. The results could provide useful insights for blood donation management and education.

Methods

Study design and participants

This cross-sectional study enrolled voluntary blood donors at the Shaoxing Central Blood Station in Shaoxing, Zhejiang Province, China, between May 2024 and June 2024. The study was approved by the Ethics Committee of Shaoxing Central Blood Station (approval no. (2024) 1). Written informed consent was obtained from all participants.

The inclusion criteria were: (1) voluntary blood donors, (2) willingness to participate in the study and (3) age >18 years. Participants aged over 60 years were excluded.

Questionnaire design

The initial questionnaire draft was designed based on the literature.^14–23 The questionnaire was then revised based on feedback from two experts in the Zhejiang province blood donation system. The questionnaire underwent a preliminary survey and reliability testing, achieving a reliability score of 0.883. The participants were asked to indicate any question, word or item that was difficult to understand to ensure face validity.

The final questionnaire was in Chinese and consisted of four sections: demographic data, knowledge dimension, attitude dimension and practice dimension. Basic demographic information included gender, age, body mass index (BMI), local registered residence, place of residence, education, occupation, marital status, childbearing status, type of blood donation, number of times donated, main reasons for donating blood and information sources about blood donation. The knowledge dimension included 11 items, with responses scored as ‘very knowledgeable’ = 2 points, ‘heard of it’ = 1 point and ‘not clear’ = 0 points, resulting in a total score range of 0–22 points. The attitude dimension contained 10 questions scored using a 5-point Likert scale, with positive statements scored from ‘strongly agree’ = 5 points to ‘strongly disagree’ = 1 point, resulting in a total score range of 10–50 points. The practice dimension consisted of seven questions, with the first question analysed descriptively but not scored, and questions 2–7 scored from ‘never’ = 1 point to ‘always’ = 5 points, resulting in a total score range of 6–30 points. Scores in each dimension exceeding 80% of the total score were considered sufficient knowledge, favourable attitude and proactive practice.^{13 28}

Questionnaire distribution

The questionnaire was uploaded to the Questionnaire Star platform, and a QR code was generated. The QR code was distributed through the Shaoxing Central Blood Station, various blood donation centres (Lingchao Philanthropy Blood Donation Center, Shaoxing Love Blood Donation Center, Keqiao Love Blood Donation Center), WeChat groups (Shaoxing Central Blood Station ‘Board Friends Home’ group, Shaoxing College Platelet Alliance), the researcher’s WeChat Moments and mobile blood donation vehicles. Participants completed the questionnaire independently. To ensure data integrity, each IP address was limited to submitting one response, and all questions were mandatory for submission.

A trap question (‘10+10=30’) was included, and questionnaires with ‘true’ selected for this question were considered invalid. Questionnaires with obvious errors (eg, impossible age) or filled in an obvious pattern (eg, all first choices) were excluded. All questionnaires were filled out anonymously.

Sample size

A single population proportion formula, n=[(Z_α/2)²*P(1 P)]/d², was used to calculate the sample size. Since no prior KAP scores on blood donation among Chinese blood donors were available, the sample size for this study was calculated based on an expected proportion of 50%, with a confidence level of 95% and a margin of error of 5%, requiring a sample size of 384 individuals. Considering a 20% drop-out rate, a total of 480 individuals were required.

Statistical analysis

Statistical analysis was performed using SPSS 27.0 and AMOS 26.0 (IBM, Armonk, NY, USA). Continuous variables were expressed as means±SD and analysed using the Mann-Whitney U-test or Kruskal-Wallis H-test. Categorical variables were expressed as n (%). Spearman correlation analysis was used to assess the relationship between KAP dimensions. A structural equation modelling (SEM) analysis was conducted to test the following hypotheses: (H1) knowledge directly affects attitude, (H2) knowledge directly affects practice and (H3) knowledge indirectly affects practice through attitude. The model fit indices for SEM were evaluated against the following thresholds: minimum discrepancy function by df divided; root mean square error of approximation; standardised root mean square residual; Tucker–Lewis index; and comparative fit index. P values <0.05 were considered statistically significant.

Patient and public involvement

None.

Results

Characteristics of the participants

The study enrolled 580 participants with valid questionnaires. Genders were approximately equally represented, with 48.45% male and 51.55% female. The majority of participants were over 40 years old (34.83%), had a BMI <24 kg/m² (51.21%), were registered residents of Shaoxing City (62.41%), lived in urban areas (58.79%), had an associate degree education or above (70.34%), were not single (59.83%), had children (58.62%), were donating whole blood (84.31%) and had donated more than once (72.76%) (table 1). Online supplemental figure S1 shows that the main reasons for donating blood (at the time of the survey) were selfless contribution and helping others. Online supplemental figure S2 shows that the main source of information about blood donation was volunteer public welfare activities.

Table 1

Characteristics of the participants

Variables	N (%)	Knowledge	P	Attitudes	P	Practices	P
Total score	n=580	19.37±4.05		46.28±4.45		23.37±5.67
Gender			0.250		0.717		0.016
Male	281 (48.45)	19.02±4.49		46.05±4.84		23.92±5.66
Female	299 (51.55)	19.70±3.57		46.49±4.05		22.85±5.64
Age (years)			0.003		<0.001		<0.001
18–29	214 (36.9)	19.36±3.78		45.40±4.84		22.57±6.02
30–39	164 (28.28)	18.92±4.45		46.39±4.42		22.79±6.02
>40	202 (34.83)	19.75±3.97		47.13±3.86		24.68±4.69
Body mass index (kg/m2)			0.164		0.538		0.044
<24	297 (51.21)	19.51±3.75		46.21±4.42		23.00±5.63
24–27.9	171 (29.48)	19.18±4.44		46.28±4.62		23.64±5.23
28–34.5	61 (10.52)	19.54±4.53		46.90±4.21		25.10±5.32
≥35	51 (8.79)	19.02±3.80		45.96±4.45		22.51±7.19
Registered resident of Shaoxing City			<0.001		0.004		0.186
Yes	362 (62.41)	19.65±4.06		46.69±4.26		23.62±5.55
No	218 (37.59)	18.90±4.00		45.61±4.69		22.94±5.85
Place of residence			0.238		0.126		0.476
Rural	175 (30.17)	19.03±4.20		46.08±4.62		23.33±5.63
Urban	341 (58.79)	19.62±3.83		46.57±4.23		23.54±5.63
Suburban	64 (11.03)	18.94±4.67		45.30±5.03		22.55±5.99
Education level			0.007		0.009		0.023
Middle school and below	77 (13.28)	17.91±5.16		45.06±4.90		22.49±5.18
High school/technical secondary school	95 (16.38)	19.76±3.81		46.95±4.32		24.60±5.36
Associate degree and above	408 (70.34)	19.56±3.81		46.36±4.36		23.25±5.79
Occupation			<0.001		<0.001		<0.001
Government official	100 (17.24)	20.18±3.53		47.05±3.57		22.94±5.52
Professional technical personnel (eg, scientific research, engineering, agriculture, finance)	45 (7.76)	20.24±3.64		48.18±3.37		24.71±5.32
Higher education student	121 (20.86)	18.98±3.63		44.23±5.12		21.63±5.94
Office staff	99 (17.07)	19.11±4.50		46.90±4.01		22.92±5.72
Worker	51 (8.79)	18.82±4.18		45.88±4.14		24.47±4.67
Self-employed	70 (12.07)	18.74±4.75		46.49±4.65		24.11±5.47
Other	94 (16.21)	19.64±4.03		16.61±4.47		24.73±5.65
Marital status			0.046		<0.001		0.011
Single	233 (40.17)	19.29±3.83		45.43±4.79		22.62±5.91
Other	347 (59.83)	19.43±4.19		46.85±4.13		23.87±5.45
Children			0.017		<0.001		0.005
No children	240 (41.38)	19.15±4.09		45.31±4.98		22.52±6.00
Have children	340 (58.62)	19.53±4.02		46.96±3.91		23.96±5.35
Type of blood donation this time			<0.001		0.090		0.004
Whole blood	489 (84.31)	19.06±4.23		46.13±4.55		23.03±5.85
Blood component	91 (15.69)	21.04±2.23		47.09±3.81		25.15±4.15
Number of blood donations			<0.001		<0.001		<0.001
Once	158 (27.24)	18.16±4.61		45.27±4.96		22.13±6.16
Twice	98 (16.9)	18.57±4.41		45.39±4.74		22.62±6.02
3–4 times	93 (16.03)	19.34±3.81		46.40±4.06		23.43±5.44
5–10 times	76 (13.1)	19.53±3.73		46.97±3.82		23.03±5.57
>11 times	155 (26.72)	21.05±2.74		47.47±3.90		25.23±4.58

Knowledge

The mean knowledge score was 19.37±4.05 (possible range: 0–22) (table 1). The knowledge scores were significantly associated with age (p=0.003), city registration (p<0.001), education (p=0.007), occupation (p<0.001), marital status (p=0.046), children (p=0.017), type of blood donation (p<0.001) and the number of donations (p<0.001) (table 1). The two knowledge items with the lowest scores (yet still above 80%) were related to the target population for blood donation (K1) and the optimal interval between donations (K2) (table 2).

Table 2

Knowledge distribution

	N (%)
	Very familiar	Heard of it	Not clear
The country advocates that healthy citizens aged 18 to 55 voluntarily donate blood.	378 (65.17)	187 (32.24)	15 (2.59)
The interval between whole blood donations should be no less than 6 months. The interval for platelet donations should be no less than 2 weeks and no more than 24 times per year.	378 (65.17)	172 (29.66)	30 (5.17)
The usual amount of whole blood donated at one time is 200 millilitres, and it should not exceed 400 millilitres.	468 (80.69)	96 (16.55)	16 (2.76)
Vigorous exercise is not allowed after donating blood.	480 (82.76)	87 (15)	13 (2.24)
One should get adequate rest, eat light meals, and avoid fasting before donating blood.	489 (84.31)	78 (13.45)	13 (2.24)
A health check and blood test are required before donating blood.	489 (84.31)	81 (13.97)	10 (1.72)
Voluntary blood donation refers to the act of citizens donating their blood voluntarily without compensation.	506 (87.24)	61 (10.52)	13 (2.24)
A blood station is an institution that collects and provides blood for clinical use and is a non-profit organisation.	488 (84.14)	75 (12.93)	17 (2.93)
Voluntary blood donors and their relatives can enjoy blood use discounts.	427 (73.62)	141 (24.31)	12 (2.07)
In most cases, blood donation is safe, but occasionally, some individuals may experience reactions.	429 (73.97)	135 (23.28)	16 (2.76)
People with blood-borne infectious diseases are not allowed to donate blood.	489 (84.31)	80 (13.79)	11 (1.9)

Attitudes

The mean attitude score was 46.28±4.45 (possible range: 10–50) (table 1). The attitudes scores were significantly associated with age (p<0.001), BMI (p=0.044), education (p=0.023), occupation (p<0.001), marital status (p<0.001), children (p<0.001) and number of blood donations (p<0.001) (table 1). All attitude items showed high scores. The lowest score was observed regarding the expectation of receiving some form of return after blood donation (A4) (table 3).

Table 3

Attitude distribution

	N (%)
	Strongly agree	Agree	Neutral	Disagree	Strongly disagree
I believe that donating blood does not harm health and only requires a little courage.	362 (62.41)	195 (33.62)	7 (1.21)	14 (2.41)	2 (0.34)
I believe that donating blood can save lives and improve others’ health.	433 (74.66)	144 (24.83)	2 (0.34)		1 (0.17)
I believe that blood donations should be made when people are in good health.	447 (77.07)	128 (22.07)	5 (0.86)
I believe that blood donations should not be expected to be returned.	351 (60.52)	157 (27.07)	47 (8.1)	22 (3.79)	3 (0.52)
I believe blood stations should educate people about blood donation and promote it.	384 (66.21)	173 (29.83)	21 (3.62)	1 (0.17)	1 (0.17)
I am very satisfied with the blood donation services provided by the blood station.	421 (72.59)	151 (26.03)	6 (1.03)	2 (0.34)
I believe that improving the skills and attitudes of blood station staff will make me more willing to donate blood again.	403 (69.48)	160 (27.59)	14 (2.41)	1 (0.17)	2 (0.34)
I believe that the informatisation of voluntary blood donation (online appointment, online form filling, electronic blood donation certificate and online blood reimbursement function) makes blood donation more convenient.	426 (73.45)	143 (24.66)	9 (1.55)	1 (0.17)	1 (0.17)
I believe that convenient blood use discount measures would make me more willing to donate blood.	414 (71.38)	150 (25.86)	13 (2.24)	3 (0.52)
My family supports my blood donation.	343 (59.14)	173 (29.83)	34 (5.86)	25 (4.31)	5 (0.86)

Practice

The mean practice score was 23.37±5.67 (possible range: 6–30) (table 1). The practice scores were significantly associated with gender (p=0.016), age (p<0.001), BMI (p=0.044), education (p=0.023), occupation (p<0.001), marital status (p=0.011), children (p=0.005), type of blood donation (p=0.004) and the number of blood donations (p<0.001) (table 1). The lowest practice scores were observed regarding making an appointment online for blood donation (P4), encouraging others to donate blood (P3), propagating knowledge about the benefits and significance of blood donation (P2) and taking the initiative to learn more about blood donation (P5) (table 4).

Table 4

Practice distribution

	N (%)
	Always	Often	Sometimes	Rarely	Never
To ensure the quality of my blood donation, I will actively exercise.	243 (41.9)	196 (33.79)	80 (13.79)	56 (9.66)	5 (0.86)
I will educate my friends and family about the benefits and significance of blood donation.	233 (40.17)	151 (26.03)	112 (19.31)	70 (12.07)	14 (2.41)
I will encourage people around me to donate blood.	223 (38.45)	143 (24.66)	107 (18.45)	86 (14.83)	21 (3.62)
I will make an appointment online to donate blood.	222 (38.28)	111 (19.14)	95 (16.38)	90 (15.52)	62 (10.69)
I will take the initiative to learn about blood donation.	233 (40.17)	144 (24.83)	107 (18.45)	82 (14.14)	14 (2.41)
If there is a blood shortage at the blood station, I will donate blood proactively.	299 (51.55)	137 (23.62)	94 (16.21)	41 (7.07)	9 (1.55)

Correlations

As shown in table 5, knowledge scores were correlated to the attitude (r=0.580, p<0.001) and practice (r=0.494, p<0.001) scores. The attitude scores were correlated to the practice scores (r=0.618, p<0.001).

Table 5

Correlation analysis

	Knowledge	Attitudes	Practices
Knowledge	1
Attitudes	0.580 (p<0.001)	1
Practices	0.494 (p<0.001)	0.618 (p<0.001)	1

Structural equation modelling (SEM) analyses

Online Supplementary table S1 shows that the fit of the model was good. The mediation analysis showed that knowledge had a direct influence on attitudes (β=0.622, 95% CI 0.539 to 0.704, P=0.007) but only an indirect influence on practice (β=0.411, 95% CI 0.329 to 0.536, P=0.005). Attitudes had a direct influence on practice (β=0.661, 95% CI 0.554 to 0.761, P=0.006) (figure 1 and online supplementary table S2)

Figure 1. Structural equation modelling analysis.

Discussion

This study suggests that blood donors had good knowledge and positive attitudes but suboptimal practices towards blood donation. Such data could be used to design interventions to increase participation in blood donation in Zhejiang.

In the present study, the participants had good knowledge and positive attitudes. Such results are not surprising since the study was performed on blood donors, and the majority had donated blood more than once. A study in 16 Arabic countries showed that university students had poor knowledge and low donation rates but positive attitudes towards blood donation,²⁹ while studies in India³⁰ and Saudi Arabia³¹ showed higher knowledge levels. Knowledge of the societal benefits of blood donation and positive attitudes are essential for blood donors since blood donation is voluntary.² Even medical students were reported to have poor knowledge about blood donation yet maintain positive attitudes.^{15 16 18} It has been suggested that regular blood donation camps should be organised to spread the knowledge about blood donation and motivate eventual new donors.¹⁷

In the present study, the practice score was below (but near) the 80% threshold, indicating that some improvements might be necessary to optimise blood donation in Zhejiang. Although contraindications for blood donation are screened in the donation process, some knowledge of them can help promote the right knowledge in one’s surroundings. Again, since the study was performed on regular blood donors, those with contraindications were screened out in the past. The slightly suboptimal practice could also be related to time constraints associated with blood donation (eg, commuting to a donation centre, taking time for the whole blood donation process and waiting after blood donation to avoid side effects like dizziness and falls). Of course, it is expected that blood donors will have higher KAP scores than non-donors or the general population. Indeed, poor knowledge and practice of blood donation have been observed in the general population in several areas.^{24 25} Previous studies showed that the main reasons for not participating in blood donation were the fear of needles, the sight of blood, concerns about safety and adverse effects, disapproval from peers and never having been asked for.^{15 16 20} In 16 Arabic countries, the main barriers to blood donation were: not being asked (37%), ineligibility (33%), fear of pain or infection (18%), concerns about negative health effects (18%), difficulty accessing donation centres (15%) and medical mistrust (14%).²⁹ In the present study, the main motivation of blood donors for blood donation was selfless action that helps others. Future studies should be performed on the general population and should compare blood donors and non-donors. A better grasp of the factors associated with poor KAP towards blood donations and of the actual barriers to blood donation could be identified. Of note, many donors donate blood a single time without becoming regular donors.^31–33 That aspect should also be investigated to improve the regular donation rate.

In the present study, the majority of the participants were older, well-educated professionals, probably biasing the results towards a better KAP towards blood donation. In Wuhan (China), Ma et al²⁶ showed that blood donation among college and university students was associated with more favourable sociodemographic characteristics and health status, higher knowledge about blood donation and a more positive attitude towards blood donation. Eltewacy et al²⁹ reported that among university students in 16 Arabic countries, private and international university enrolment was associated with higher knowledge, while non-health science college students had lower knowledge, and participants > 20 years old were more likely to donate, while being female, having congenital or chronic diseases, and low knowledge of blood donation were associated with poor practice of blood donation. Socioeconomic status is associated with healthcare literacy.³⁴ Age was also reported to be associated with better blood donation practice.^{30 35} The female gender was associated with lower practice scores in the present study, as previously reported.²⁹ The lower practice in females could be related to cultural taboos about women donating blood.³⁶ Lower blood iron levels during menstruation³⁷ can also influence the eligibility for blood donation, complicating the donation process due to attention to donation timing. In addition, the weight eligibility criteria and side effects such as dizziness can be barriers to women donating blood despite higher altruism than in men.³⁸ Indeed, in the present study, a lower BMI was associated with lower practice scores. In the present study, since all participants were blood donors with a favourable socioeconomic status, it is possible that they were more willing to participate in blood donation. Again, a future study should include both blood donors and non-donors.

In the present study, knowledge influenced attitudes, which influenced practice. It is consistent with the KAP theory, stipulating that knowledge is the basis for knowledge while attitudes are the force driving practice.^{11 12} On the other hand, knowledge did not directly influence practice. Hence, those results could suggest that the key to improving practice would be to directly motivate individuals to participate in blood donation, facilitate the process and increase the opportunities for blood donation.

The present study had limitations. The participants were from a single area, limiting the generalisability of the results. The questionnaire was designed by the investigators based on local practices, culture and policies, limiting the generalisability of the results and the exportability of the questionnaire. The study was cross-sectional, preventing the analysis of causality. Still, a SEM analysis was performed as a surrogate of causality, but the results must be taken cautiously because causality is statistically inferred rather than observed.^39–41 The QR code was distributed publicly, and it was impossible to determine how many single people saw and scanned the code, preventing the calculation of a response rate. Finally, the social desirability bias can affect the results. Since the knowledge scores were high, there is a possibility that some participants might have answered what they knew they had to think or do instead of what they were really thinking or doing.^{42 43} Finally, this study enrolled blood donors, and the KAP status of the general population remains unknown.

In conclusion, blood donors had good knowledge and positive attitudes but suboptimal practices towards blood donation. These findings could inform the development of interventions aimed at increasing blood donation participation.

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. All data generated or analysed during this study are included in this article and supplementary information files.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

All procedures were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. The study was approved by the Ethics Committee of Shaoxing Central Blood Station (approval no. (2024) 1). Written informed consent was obtained from all participants. The study was carried out in accordance with the applicable guidelines and regulations.

Footnote

Contributors LJ, XZ and SZ carried out the studies, participated in collecting data, and drafted the manuscript. QM and FY performed the statistical analysis and participated in its design. NL and HL participated in the acquisition, analysis or interpretation of data and drafted the manuscript. All authors read and approved the final manuscript. The guarantor is LJ.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer-reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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