ORIGINAL RESEARCH article

Front. Public Health, 21 May 2024

Sec. Public Health Education and Promotion

Volume 12 - 2024 | https://doi.org/10.3389/fpubh.2024.1380710

Knowledge, attitudes, and practices among patients with anemia towards disease management

  • Department of Nursing, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, Zhejiang, China

Abstract

Objective:

This study aimed to assess the knowledge, attitudes and practices among anemia patients toward disease management.

Methods:

This web-based cross-sectional study was conducted between September and December 2023 at The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine). A self-designed questionnaire was developed to collect demographic information of anemia patients, and assess their knowledge, attitudes and practices (KAP) toward disease management.

Results:

A total of 396 valid questionnaires were collected. The mean age of the participants was 57.44 ± 16.80 years, and 52.02% were female. The mean knowledge, attitudes, and practices scores were 11.47 ± 1.73 (possible range: 0–14), 27.32 ± 2.96 (possible range: 7–35), and 40.49 ± 6.06 (possible range: 10–50), respectively. Multivariate analysis showed that bachelor’s degree or above was independently associated with sufficient knowledge (OR = 2.372, 95%CI: 1.160–4.853, p = 0.018). Knowledge (OR = 1.350, 95%CI: 1.166–1.563, p < 0.001) and hemoglobin within 60-90 g/L (OR = 1.782, 95%CI: 1.090–2.912, p = 0.021) were independently associated with positive attitudes. Moreover, attitudes (OR = 1.618, 95%CI: 1.454–1.799, p < 0.001) and diagnosis ≥1 year (OR = 1.949, 95%CI: 1.171–3.243, p = 0.010) were independently associated with proactive practices. The path analysis demonstrated that knowledge was directly and positively correlated with attitudes (β = 0.484, 95% CI: 0.363–0.647, p = 0.008), and attitudes was directly and positively correlated with practices (β = 1.195, 95% CI: 1.062–1.332, p = 0.007). Moreover, knowledge was indirectly and positively correlated with practice (β = 0.579, 95% CI: 0.434–0.805, p = 0.004).

Conclusion:

Anemia patients have sufficient knowledge, negative attitudes, but proactive practices toward the toward disease management Comprehensive training programs are needed to improve anemia patients practices in this area.

Introduction

Anemia is characterized by a deficiency in the quantity or quality of red blood cells or hemoglobin in the blood (1). The reduced oxygen-carrying capacity of the blood impairs tissue oxygenation, which leads to symptoms such as dizziness, palpitations, and chest pain (2). Consequently, individuals with anemia may experience declines in physical performance (3), decreased productivity (4), and increased susceptibility to falls or accidents (5). Besides, population-based studies indicated that anemia can act as risk factors of severe complications like heart diseases, developmental delays in children and neurological development (6, 7).

Globally, anemia prevalence is a significant concern, particularly impacting developing countries. Approximately 1.62 billion people worldwide, corresponding to 24.8% of the global population, were affected by anemia in 2016 (8). This prevalence varied widely across different regions and populations, with higher rates observed in low- and middle-income countries, particularly in South Asia, Central and West Africa, and parts of Southeast Asia (9). Notably, the prevalence of anemia in sub-Saharan African countries elevated to the alarming 39% during the same period (10). In China, the prevalence varies widely across different regions and populations. For instance, among Chinese adults with newly diagnosed HIV/AIDS, the prevalence was 51.9% (11). Besides, in central and eastern China, it was 13.4% (12). In rural areas, the prevalence was reported at 9.7% (13). Of note, the prevalence of anemia was alarmingly high at 41.98% among pregnant women (14). These figures highlight the significant public health challenge posed by anemia in China.

Effective management of anemia involves more than just medical treatment, it requires active patient engagement in self-management. This includes understanding the condition (15), adhering to treatment plans (12, 16), and making lifestyle adjustments (17). A Knowledge, Attitudes, and Practices (KAP) study is a research methodology used to assess the understanding, beliefs, and behaviors of individuals regarding a specific health issue (18). In the context of anemia management, a KAP study aims to investigate patients’ knowledge about anemia, their attitudes towards the condition, and their practices in managing it. A prior KAP study indicated that Indian adolescent girls exhibited satisfactory knowledge and a moderate level of attitude towards anemia (19). However, their practice scores regarding anemia were found to be low to moderate (20). To date, no KAP evidence has been available on the Chinese patients with anemia, which greatly retards the improvement in treating and managing the condition.

In response to these existing research gaps, this study aimed to investigate the KAP among patients with anemia towards disease management. By elucidating the factors influencing the KAP towards anemia management, this research can contribute valuable insights into the development of patient-centered interventions. We hypothesized that the positive inter-relationships are found between each dimension of KAP. Our findings have implications for advancement of evidence-based interventions to enhance the quality of care and support provided to individuals living with anemia.

Methods

Study design and participants

This web-based cross-sectional study was conducted between September and December 2023 at The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine). The study was ethically approved by the Ethics Committee of The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine) (Approval No. 2023-KLS-273- 01) and informed consent was obtained from the study participants.

This study employed a convenience sampling method to recruit participants diagnosed with anemia. The inclusion criteria were as follows: (1) Diagnosis of anemia, (2) Age of 18 years or older, (3) Ability to independently read and complete the required questionnaires, or to do so with the researchers’ assistance, and (4) Willingness to participate in the study, evidenced by the provision of signed informed consent. Exclusion criteria encompassed individuals with impaired consciousness, mental disorders, or those exhibiting non-cooperation.

Questionnaire

The questionnaire was developed with guidance from the relevant literature on anemia diagnosis and management (21–23). The initial draft was revised based on feedback from three experts in hematology and five experts in nursing of The First Affiliated Hospital of Zhejiang Chinese Medical University. Subsequently, a preliminary trial was conducted on a limited scale (n = 23), resulting in a Cronbach’s alpha coefficient value of 0.91, indicating good internal consistency.

The final questionnaire was in Chinese and consisted of four dimensions: demographic information, knowledge, attitudes and practices. The demographic information was consisted of 17 items, while the knowledge, attitude, and practice dimensions comprised 16, 7 and 10 items, respectively. Questions K11 and K13 were designed as trap questions, presenting exactly opposite meanings. They were used solely as a means to control the quality of the questionnaire and were not included in the subsequent statistical analysis. The study only provided a descriptive presentation of their correctness rates. Patients who selected “right” or “wrong” for both questions were deemed to have a logical conflict and were excluded from the survey. Consequently, the knowledge items were scored 1 point for a correct answer and 0 points for others, resulting in a possible score range of 0–14. The attitude items scored on a five-point Likert scale ranging from very positive (5 points) to very negative (1 point), with a possible score range of 7 to 35. The practice items also scored on a five-point Likert scale, ranging from very consistent (5 points) to very inconsistent (1 point), with a possible score range of 10 to 50.

Data collection was conducted via an online survey facilitated by the Sojump platform.1 The survey was disseminated to participants by QR codes linking to the questionnaire in various hospital settings, including wards, consultation rooms, and offices of medical staff. Prior to accessing the survey questions, participants were required to select the option “I agree to participate in this study.” This process ensured informed consent. All responses were gathered anonymously. To prevent duplicate submissions, an IP address restriction was implemented, allowing only one completed survey per unique IP address.

Statistical methods

STATA 17.0 (Stata Corporation, College Station, TX, United States) was used for statistical analysis. The continuous variables were expressed as mean ± SD, and the categorical variables was expressed as N (%). The continuous variables conformed to a normal distribution were tested by the t-test or ANOVA. Bloom’s cut-off of 80% was used to determine sufficient knowledge (≥11.2 points), positive attitude (≥28 points), and proactive practice (≥40) as the binary outcomes (24). Variables with p < 0.05 in the univariate logistic regression analysis are included in the multivariate logistic regression analysis (19). Pearson correlation analysis was used to analyze the correlation between KAP. The path analysis of KAP among anemia patients toward disease management was constructed with AMOS 24.0 (IBM, NY, United States). The hypotheses as following: (1) knowledge had direct effects on attitude, (2) knowledge had direct effects on practice, and (3) attitude had direct effects on practice.

Results

The initial survey generated a total of 500 responses. Among these, 104 of these questionnaires were subsequently excluded due to logical inconsistencies in the responses. As a result, the study successfully gathered 396 valid questionnaires, constituting an effective response rate of 79.20%.

The mean age of the participants was 57.44 ± 16.80 years. The majority were female (52.02%), and had BMI (kg/m2) within the range of 18.5–23.9 kg m−2 (56.06%). Furthermore, a significant proportion resided in rural areas (54.04%), possessed an educational background of junior high school or below (65.15%), and were covered by Urban Resident Basic Medical Insurance (URBMI). Additionally, 38.64% were retired, and 42.93% reported a monthly income ranging from 2,000 to 5,000 CNY. Health-related behaviors included the majority abstaining from both smoking (89.65%) and alcohol consumption (89.39%). Regarding hemoglobin levels, 39.14% exhibited levels within the 60-90 g/L range, while 38.13% recorded hemoglobin levels exceeding 90 g/L but below the normal threshold. Besides, a majority (55.81%) had undergone blood transfusions. Furthermore, 44.70% received an anemia diagnosis within the past year, while a slightly lower percentage (43.94%) received a diagnosis more than a year before (Table 1).

Table 1

N (%)Knowledge scoreAttitude scorePractice score
Mean ± SDpMean ± SDpMean ± SDP
Total39611.47 ± 1.7327.32 ± 2.9640.49 ± 6.06
Gender0.3160.2630.597
Male190 (47.98)11.56 ± 1.5827.49 ± 2.9440.66 ± 5.99
Female206 (52.02)11.39 ± 1.8627.16 ± 2.9840.34 ± 6.14
Age (years)57.44 ± 16.80
BMI (kg/m2)0.7380.1440.055
<18.557 (14.39)11.51 ± 1.9526.91 ± 3.2139.07 ± 6.50
18.5–23.9222 (56.06)11.52 ± 1.7027.19 ± 2.9540.39 ± 6.08
≥24.0117 (29.55)11.37 ± 1.6827.74 ± 2.8441.39 ± 5.70
Residence0.2200.0360.016
Rural214 (54.04)11.37 ± 1.8627.03 ± 3.0039.82 ± 6.21
Urban182 (45.96)11.59 ± 1.5627.65 ± 2.9041.29 ± 5.81
Marital status0.3890.8260.428
Single73 (18.43)11.63 ± 1.5927.25 ± 3.1839.99 ± 7.07
Married323 (81.57)11.44 ± 1.7627.33 ± 2.9240.61 ± 5.82
Highest education<0.001<0.0010.086
Junior high school or below258 (65.15)11.22 ± 1.8626.91 ± 3.0640.01 ± 5.74
High school or technical school46 (11.62)11.43 ± 1.8327.41 ± 2.6741.07 ± 6.29
College and above92 (23.23)12.18 ± 0.9528.40 ± 2.5641.57 ± 6.72
Occupation0.0050.0150.493
Formal employee/ part-time/ self-employed85 (21.46)12.06 ± 1.2228.20 ± 2.7641.38 ± 6.78
Unemployed38 (9.60)11.39 ± 1.9226.71 ± 2.7040.03 ± 5.66
Retired153 (38.64)11.27 ± 1.8227.09 ± 3.0440.37 ± 5.71
Other120 (30.30)11.33 ± 1.7927.17 ± 3.0040.18 ± 6.10
Monthly per capita income (CNY)0.0180.0340.399
<2,000125 (31.57)11.40 ± 1.8527.00 ± 2.8540.07 ± 6.15
2,000–5,000170 (42.93)11.25 ± 1.7727.14 ± 3.1540.28 ± 5.86
5,001-10,00066 (16.67)11.92 ± 1.3527.79 ± 2.5641.42 ± 6.34
>10,00035 (8.84)11.94 ± 1.5328.43 ± 2.8741.29 ± 6.19
Health insurance0.4660.4480.797
No health insurance3 (0.76)11.67 ± 1.5326.00 ± 2.6539.00 ± 9.17
New Rural Cooperative Medical Scheme (NRCMS)139 (35.10)11.27 ± 1.8727.11 ± 3.1440.19 ± 6.07
Urban Resident Basic Medical Insurance (URBMI)240 (60.61)11.59 ± 1.6527.42 ± 2.8840.61 ± 6.05
Commercial insurance5 (1.26)11.80 ± 1.1026.60 ± 1.6743.20 ± 1.48
Other9 (2.27)11.11 ± 1.9028.67 ± 2.9241.00 ± 7.45
Comorbidities (Multiple choices)
Malnutrition40 (10.10)11.70 ± 1.6026.83 ± 3.1039.25 ± 6.19
Chronic kidney disease52 (13.13)11.40 ± 1.6227.62 ± 3.0941.23 ± 5.87
Bleeding15 (3.79)10.93 ± 2.2527.40 ± 3.0039.80 ± 5.53
Aplastic anemia95 (23.99)11.52 ± 1.7927.87 ± 2.8242.67 ± 5.78
Hereditary anemia (e.g., thalassemia, sickle cell anemia)5 (1.26)11.00 ± 1.7328.20 ± 3.2740.40 ± 7.44
Autoimmune diseases11 (2.78)11.73 ± 0.7926.64 ± 2.2937.55 ± 9.52
Cancer and radiotherapy123 (31.06)11.33 ± 1.8226.68 ± 3.0439.65 ± 6.13
Anemia during pregnancy3 (0.76)12.33 ± 1.1530.33 ± 1.1549.00 ± 1.73
Myelodysplastic syndromes41 (10.35)11.44 ± 1.7027.90 ± 2.8141.59 ± 5.64
Other73 (18.43)11.62 ± 1.6026.79 ± 2.9239.38 ± 5.17
None of the above12 (3.03)12.58 ± 0.7927.00 ± 2.8938.75 ± 6.12
Smoking0.4840.7410.537
Yes41 (10.35)11.29 ± 1.8127.17 ± 2.9941.05 ± 5.04
No355 (89.65)11.49 ± 1.7227.33 ± 2.9640.43 ± 6.17
Alcohol consumption0.8630.9010.606
Yes42 (10.61)11.43 ± 1.8927.26 ± 3.5040.95 ± 5.04
No354 (89.39)11.48 ± 1.7127.32 ± 2.9040.44 ± 6.18
Habit of regular exercise0.8910.8970.103
Yes135 (34.09)11.49 ± 1.6727.29 ± 2.9141.19 ± 5.60
No261 (65.91)11.46 ± 1.7727.33 ± 3.0040.14 ± 6.27
Range of most recent hemoglobin test0.4600.0790.161
>90 g/L, but below normal151 (38.13)11.62 ± 1.7026.93 ± 3.0339.85 ± 6.31
60-90 g/L155 (39.14)11.37 ± 1.8527.61 ± 2.8640.63 ± 6.06
<60 g/L63 (15.91)11.29 ± 1.5927.13 ± 2.9640.79 ± 5.06
Normal (female>110 g/L male>120 g/L)27 (6.82)11.63 ± 1.5528.22 ± 2.9742.59 ± 6.57
History of blood transfusion0.8780.4280.023
Yes221 (55.81)11.48 ± 1.6927.42 ± 2.9041.11 ± 5.85
No175 (44.19)11.46 ± 1.7827.18 ± 3.0539.72 ± 6.25
Date of anemia diagnosis0.4990.1850.004
Less than 1 year177 (44.70)11.56 ± 1.7327.53 ± 2.9140.34 ± 6.15
1 year and more174 (43.94)11.36 ± 1.7227.28 ± 2.9741.30 ± 5.88
Uncertain45 (11.36)11.58 ± 1.7626.62 ± 3.1137.98 ± 5.77

Demographic characteristics.

In the items of health insurance, No Health Insurance refers to individuals who do not have any form of health insurance coverage. New Rural Cooperative Medical Scheme (NRCMS) is aimed at rural residents who are not formally employed. It is a voluntary program funded by individual premiums (subsidized by the government) and government contributions. The NRCMS primarily covers serious illnesses and provides a basic medical safety net, but coverage is limited, and out-of-pocket costs can still be significant. Urban Resident Basic Medical Insurance (URBMI) targets non-working urban residents, including children, the elderly, and others without formal employment. Similar to NRCMS, it is funded by personal contributions and government subsidies. The URBMI covers both inpatient and outpatient services, though the extent of coverage can vary by locality. Commercial Insurance is private health insurance purchased from commercial insurance companies. Individuals often buy commercial insurance to supplement the basic coverage provided by NRCMS or URBMI, as these programs can have substantial coverage gaps. Other insurance may include various other forms of insurance coverage which are not as commonly utilized or are specific to certain groups of people, such as employee health benefits provided by some companies, insurance schemes for government employees, or local health insurance programs that may exist in specific areas.

The mean knowledge, attitudes, and practices scores were 11.47 ± 1.73 (possible range: 0–14), 27.32 ± 2.96 (possible range: 7–35), and 40.49 ± 6.06 (possible range: 10–50), respectively. High knowledge scores were found among participants with a higher educational level (p < 0.001), those engaged in formal employment, part-time work, or self-employment (p = 0.005), and those with a monthly income exceeding 10,000 CNY (p = 0.018). Higher attitude scores were evident among participants residing in urban areas (p = 0.036), those with a higher educational level (p < 0.001), individuals engaged in formal employment, part-time work, or self-employment (p = 0.015), and those with a monthly income exceeding 10,000 CNY (p = 0.034). Besides, higher practice scores were observed among participants residing in urban areas (p = 0.016), those who had undergone a blood transfusion (p = 0.023), and individuals with anemia for 1 year or more (p = 0.004) (Table 1).

The highest correctness rates among the three knowledge items were observed for the statements: “Individuals with anemia typically exhibit pale skin” (K6) at 94.44%, “Treatment options for anemia may encompass iron supplements, blood transfusions, and hematopoietic growth factors” (K15) at 92.93%, and “Symptoms of anemia may include headaches, tinnitus, and cerebral hypoxia” (K7) at 92.17%. Conversely, the three items with the lowest correctness rates were: “Chemical substances such as benzene, herbicides, and pesticides can induce anemia” (K3) with a correctness rate of 38.13%, “While causes of anemia may vary, the treatment principles remain consistent” (K12) at 44.19%, and “Insufficient intake of iron, folic acid, and vitamin B12 leading to anemia can result from an imbalanced diet, poor cooking habits, and gastrointestinal diseases” (K2) at 82.07% (Supplementary Table S1).

A significant majority (96.47%) expressed a positive attitude, emphasizing the importance of adhering to medical advice, attending regular follow-up appointments, and following prescribed medication regimens (A4). In contrast, the lowest proportion (72.72%) indicated anxiety regarding the physical and mental discomfort associated with anemia and the potential for serious complications (A6). Likewise, 76.52% expressed full confidence in their ability to strictly adhere to self-management practices for anemia (A7) (Supplementary Table S2).

The highest proportion (92.93%) actively participated in the treatment of the underlying disease for improved disease management (P9). In contrast, only 58.84% recognized that the disease induces negative emotions like depression and anxiety, prompting them to actively seek psychological counseling or other forms of support (P8). Moreover, 60.10% actively sought information about anemia in the past year (P1) (Supplementary Table S3).

Pearson’s analysis was performed to assess the relationship between knowledge, attitudes, and practices. It was shown that the knowledge and the attitudes were positively correlated (r = 0.283, p < 0.001), and knowledge and practices were also positively correlated (r = 0.236, p < 0.001). Additionally, there was a positive correlation between attitude and practice scores (r = 0.604, p < 0.001) (Supplementary Table S4).

Multivariate analysis showed that bachelor’s degree or above was positively associated with knowledge (OR = 2.372, 95%CI: 1.160–4.853, p = 0.018) (Table 2). Besides, knowledge (OR = 1.350, 95%CI: 1.166–1.563, p < 0.001) and hemoglobin within 60-90 g/L (OR = 1.782, 95%CI: 1.090–2.912, p = 0.021) were positively associated with attitude. However, unemployment was negatively associated with attitude (OR = 0.416, 95%CI: 0.173–0.996, p = 0.049) (Table 3). Moreover, attitude (OR = 1.618, 95%CI: 1.454–1.799, p < 0.001) and diagnosis ≥1 year (OR = 1.949, 95%CI: 1.171–3.243, p = 0.010) were positively associated with practice (Table 4).

Table 2

Univariable analysisMultivariable analysis
OR(95%CI)pOR(95%CI)p
Gender
Maleref.
Female0.812(0.541 1.218)0.313
Age (years)0.981(0.969 0.993)0.0030.992(0.973 1.010)0.381
BMI (kg/m2)
<18.5ref.
18.5–23.90.733(0.397 1.353)0.321
≥24.00.800(0.411 1.555)0.511
Residence
Ruralref.
Urban1.282(0.853 1.926)0.232
Marital status
Singleref.
Married0.727(0.425 1.244)0.245
Highest education
Junior high school or belowref.ref.
High school or technical school1.797(0.926 3.488)0.0831.452(0.708 2.979)0.309
College and above3.341(1.907 5.584)<0.0012.372(1.160 4.853)0.018
Occupation
Formal employee/ part-time/ self-employedref.ref.
Unemployed0.451(0.201 1.015)0.0540.535(0.220 1.303)0.168
Retired0.469(0.260 0.845)0.0120.915(0.439 1.908)0.813
Other0.401(0.218 0.738)0.0030.650(0.316 1.337)0.242
Monthly per capita income (CNY)
<2,000ref.ref.
2,000–5,0000.963(0.605 1.535)0.8750.756(0.443 1.291)0.306
5,001-10,0002.192(1.138 4.222)0.0191.178(0.551 2.515)0.673
>10,0002.567(1.081 6.095)0.0331.087(0.399 2.966)0.870
Smoking
Yes0.794(0.413 1.524)0.487
Noref.
Alcohol consumption
Yes0.928(0.484 1.782)0.823
Noref.
Habit of regular exercise
Yes1.074(0.700 1.646)0.744
Noref.
Range of most recent hemoglobin test
>90 g/L, but below normalref.
60-90 g/L0.688(0.433 1.094)0.114
<60 g/L0.726(0.397 1.328)0.299
Normal (female>110 g/L male>120 g/L)0.742(0.321 1.716)0.485
History of blood transfusion
Yes1.042(0.694 1.564)0.845
Noref.
Date of anemia diagnosis
Less than 1 yearref.
1 year and more0.712(0.463 1.095)0.122
Uncertain0.888(0.451 0.748)0.731

Multivariable analysis of the knowledge.

The regression model for multivariate logistic regression analysis was: Knowledge ~ Age + Highest education + Occupation + Monthly per capita income.

Table 3

Univariable analysisMultivariable analysis
OR(95%CI)pOR(95%CI)p
Knowledge score1.364(1.186 1.568)<0.0011.350(1.166 1.563)<0.001
Gender
Maleref.
Female0.841(0.560 1.263)0.403
Age (years)0.989(0.977 1.001)0.067
BMI (kg/m2)
<18.5ref.
18.5–23.91.042(0.567 1.916)0.894
≥24.01.381(0.717 2.660)0.335
Residence
Ruralref.
Urban1.192(0.793 1.790)0.399
Marital status
Singleref.
Married1.212(0.712 2.065)0.479
Highest education
Junior high school or belowref.ref.
High school or technical school0.903(0.463 1.761)0.7650.796(0.384 1.649)0.539
College and above1.787(1.103 2.895)0.0181.312(0.749 2.298)0.343
Occupation
Formal employee/ part-time/ self-employedref.ref.
Unemployed0.366(0.158 0.845)0.0190.416(0.173 0.996)0.049
Retired0.543(0.316 0.931)0.0270.725(0.390 1.348)0.309
Other0.614(0.350 1.079)0.0900.779(0.409 1.482)0.447
Monthly per capita income (CNY)
<2,000ref.
2,000–5,0001.193(0.736 1.935)0.474
5,001-10,0001.368(0.739 2.531)0.318
>10,0001.866(0.873 3.990)0.107
Smoking
Yes1.056(0.544 2.049)0.873
Noref.
Alcohol consumption
Yes1.406(0.738 2.680)0.300
Noref.
Habit of regular exercise
Yes0.860(0.559 1.324)0.493
Noref.
Range of most recent hemoglobin test
>90 g/L, but below normalref.ref.
60-90 g/L1.550(0.970 2.475)0.0671.782(1.090 2.912)0.021
<60 g/L1.234(0.666 2.286)0.5041.407(0.740 2.676)0.297
Normal (female>110 g/L male>120 g/L)2.311(1.009 5.294)0.0482.237(0.928 5.391)0.073
History of blood transfusion
Yes1.058(0.702 1.593)0.788
Noref.
Date of anemia diagnosis
Less than 1 yearref.
1 year and more0.807(0.524 1.243)0.331
Uncertain0.805(0.408 1.588)0.531

Multivariable analysis of the attitudes.

The regression model for multivariate logistic regression analysis was: Attitude ~ Knowledge + Highest education + Occupation + Range of most recent hemoglobin test.

Table 4

Univariable analysisMultivariable analysis
OR(95%CI)pOR(95%CI)p
Knowledge score1.267(1.121 1.433)<0.0011.123(0.969 1.301)0.124
Attitude score1.612(1.457 1.784)<0.0011.618(1.454 1.799)<0.001
Gender
Maleref.
Female0.922(0.622 1.368)0.687
Age (years)0.989(0.978 1.001)0.076
BMI (kg/m2)
<18.5ref.
18.5–23.91.303(0.724 2.345)0.378
≥24.01.779(0.938 3.376)0.078
Residence
Ruralref.
Urban1.226(0.825 1.821)0.314
Marital status
Singleref.
Married1.106(0.665 1.839)0.698
Highest education
Junior high school or belowref.
High school or technical school1.143(0.610 2.141)0.677
College and above1.143(0.710 1.840)0.583
Occupation
Formal employee/ part-time/ self-employedref.
Unemployed0.932(0.434 2.003)0.856
Retired0.873(0.513 1.484)0.615
Other0.963(0.553 1.680)0.895
Monthly per capita income (CNY)
<2,000ref.
2,000–5,0001.040(0.656 1.651)0.867
5,001-10,0000.956(0.527 1.737)0.883
>10,0001.076(0.508 2.277)0.848
Smoking
Yes0.947(0.496 1.808)0.869
Noref.
Alcohol consumption
Yes1.000(0.527 1.896)1.000
Noref.
Habit of regular exercise
Yes1.340(0.883 2.034)0.169
Noref.
Range of most recent hemoglobin test
>90 g/L, but below normalref.
60-90 g/L1.336(0.852 2.094)0.207
<60 g/L1.343(0.745 2.420)0.327
Normal (female>110 g/L male>120 g/L)1.775(0.773 4.079)0.176
History of blood transfusion
Yes1.418(0.952 2.111)0.086
Noref.
Date of anemia diagnosis
Less than 1 yearref.ref.
1 year and more1.463(0.960 2.228)0.0771.949(1.171 3.243)0.010
Uncertain0.440(0.216 0.893)0.0230.451(0.195 1.045)0.063

Multivariable analysis of the practices.

The regression model for multivariate logistic regression analysis was: Practice ~ Knowledge + Attitude + Date of anemia diagnosis.

Path analysis was conducted to explore the direct and indirect relationships among KAP scores. The path analysis demonstrated that knowledge was directly and positively correlated with attitudes (β = 0.484, 95% CI: 0.363–0.647, p = 0.008), and attitudes was directly and positively correlated with practices (β = 1.195, 95% CI: 1.062–1.332, p = 0.007). Moreover, knowledge was indirectly and positively correlated with practice (β = 0.579, 95% CI: 0.434–0.805, p = 0.004) (Supplementary Table S5; Figure 1).

Figure 1

Discussion

The findings revealed that anemia patients have sufficient knowledge, negative attitudes, and proactive practices toward the disease management. Positive associations were observed among KAP scores. Comprehensive training programs are needed to improve anemia patients practices in this area.

Reportedly, Indian adolescent girls had similarly good knowledge and medium level of attitude towards anemia (20). Besides, low to moderate KAP scores towards anemia were observed among Indonesian adolescent girls (25). The shared negative attitudes in both published and our findings may stem from the chronicity of the condition, stigma or misconceptions associated with the anemia, and the perceived burden of long-term management. Therefore, patient-centered care models are recommended to address not only the physiological aspects of the condition, but also the psychosocial dimensions through open communication and shared decision-making. Of note, the high levels of knowledge and practice can lay strong foundations for psychosocial interventions.

As high as 94.44% correctly identified the pale skin as the symptom of anemia, which aligned with established medical knowledge (26). Moreover, the awareness of pale skin extends beyond mere knowledge, since the condition plays a pivotal role in early detection and timely intervention (27). However, only 38.13% exhibited the awareness regarding the potential environmental factors contributing to anemia. Environmental exposures to substances like benzene, herbicides, and pesticides have been documented to pose health risks, and their potential link to anemia has been explored in scientific literature (28–30). The underlying mechanisms include damaging the DNA in blood-forming cells, interfering with hormonal systems, disrupting endocrine function, or causing cellular damage (28–30). This finding has significant implications for public health education to address awareness gaps related to the etiological factors of anemia. Besides, a notable misconception was found among the participants regarding the uniformity of treatment principles for anemia (44.19%). In the anemia management, understanding the heterogeneity of causative factors and tailoring treatments accordingly is fundamental (31). The lack of awareness regarding the variation in treatment principles might stem from oversimplified health messaging or inadequate dissemination of comprehensive information to the public.

A majority of anemia patients (96.47%) had positive attitude toward adhering to medical advice, attending regular follow-up appointments, and following prescribed medication regimens. The positive attitude can be interpreted as a manifestation of patient engagement and a willingness to actively participate in their own healthcare. Such attitudes have been associated with improved treatment adherence, better management of chronic conditions, and overall positive health outcomes (32). Besides, 72.72% expressed anxiety about the physical and mental discomfort associated with anemia and the potential for serious complications. The anxiety reported by anemia patients may be attributed to various factors, including concerns about the impact of anemia on daily life, fear of complications, and uncertainty about the course of the condition. The finding underscored the importance of integrating both hematologists and mental health professionals into the overall care plan, as proposed by collaborative care models (33). Moreover, the high level of self-confidence reported by 76.52% in their ability to strictly adhere to self-management practices for anemia reflected their engagement in the healthcare. Encouraging and supporting this self-efficacy can contribute to better adherence to treatment plans, improved health outcomes, and enhanced overall well-being. Future research should continue to explore the dynamics of patient confidence and its impact on long-term anemia management.

As high as 92.93% actively participated in the treatment of the underlying disease for improved disease management. The current study’s higher engagement rate suggests advancements in healthcare provider-patient communication (34). Whereas, only 58.84% acknowledged that the psychosocial implications of anemia prompted the subsequent seeking of support. It highlighted that acknowledgment of psychosocial implications did not necessarily translate into active support-seeking behavior. This raised questions about potential barriers preventing individuals from seeking the necessary support. These barriers could include stigmas associated with mental health, lack of accessible support systems, or insufficient integration of psychosocial care into routine anemia management (35). Moreover, the observed rate of 60.10% actively seeking information in the past year reflected the prevalent engagement in understanding and addressing the anemia. Web-based health information seeking has been established to play important roles in the management of different disease (36). It can be recommended to promote online educational initiatives, empowering patients with the knowledge needed to make informed decisions, adhere to treatment plans, and actively participate in disease management.

Correlation analysis demonstrated the positive correlations among KAP scores, which aligned with the health belief model (37). In other words, anemia patients with greater knowledge are more likely to perceive the severity of their condition and engage in behaviors to address it. The influential factors of KAP scores were identified in the multivariate analysis. First, individuals with bachelor’s degree or above were more likely to possess knowledge about anemia. This aligned with the published literature indicating that education is a key determinant of health knowledge, as individuals with higher educational backgrounds tend to have better access to information and resources (38). Second, lower hemoglobin levels within the range of 60–90 g/L were positively associated with attitudes. Symptoms such as fatigue, weakness, and reduced quality of life may contribute to elevated attitudes, such as increased concerns about the condition, emotional distress, or altered perceptions of disease impact (39). Third, the negative association between unemployment and attitudes was observed. Unemployment can lead to financial strain, increased stress levels, and reduced access to healthcare resources, all of which may contribute to negative attitudes towards the management of anemia (40).

Limitations of the study

The study had several limitations. Initially, the cross-sectional design imposed challenges in establishing causal relationships in our findings. Secondly, the reliance on self-reported data introduces the risk of social desirability bias, which may lead to artificially elevated scores (41).

Areas for further research

Anemia patients have sufficient knowledge, negative attitudes, and proactive practices toward the disease management. Future research with larger sample size and multi-center design is needed to verify our findings. Besides, due to the cross-sectional design, longitudinal studies are warranted to infer causal relationships of KAP and possible interventional effects.

Conclusion

Despite its limitations, this study provides essential insights into the disease management dynamics of anemia patients. Utilizing path and Pearson correlation analyses, as well as univariate and multivariate statistical methods, it affirmed the relevance of the KAP of disease management among patients with anemia. Moreover, the examination of demographic and clinical factors further informs the development of these interventions. Such strategies are poised to amplify patient knowledge, which is pivotal in promoting positive attitudes and proactive behaviors, ultimately enhancing health outcomes.

Statements

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

The studies involving humans were approved by The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine) [No. 2023-KLS-273- 01]. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

BY: Writing – review & editing, Writing – original draft, Data curation. MX: Writing – review & editing, Writing – original draft, Formal analysis. FC: Writing – review & editing, Writing – original draft, Data curation. MP: Writing – review & editing, Writing – original draft, Data curation. XM: Writing – review & editing, Writing – original draft, Data curation.

Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article. The study was supported by Zhejiang Province Science and Technology Plan Project (No. 2023C03165) and Research Program of Zhejiang ChineseMedical University (No. 2022FSYYZZ06).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2024.1380710/full#supplementary-material

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Summary

Keywords

knowledge, attitudes, practices, anemia, cross-sectional study

Citation

Yao B, Xu M, Cheng F, Peng M and Mao X (2024) Knowledge, attitudes, and practices among patients with anemia towards disease management. Front. Public Health 12:1380710. doi: 10.3389/fpubh.2024.1380710

Received

02 February 2024

Accepted

06 May 2024

Published

21 May 2024

Volume

12 - 2024

Edited by

Gil Cunha De Santis, Hemocentro Foundation of Ribeirão Preto, Brazil

Reviewed by

Felipe Silva, Hemocentro Foundation of Ribeirão Preto, Brazil

Olutosin Ademola Otekunrin, University of Ibadan, Nigeria

Updates

Copyright

*Correspondence: Xiaopei Mao,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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