Abstract
Introduction
Sickle cell disease (SCD), a chronic hematologic disorder, is linked to higher morbidity and mortality rates. SCD is thought to impact 0.8% to 30% of Sudanese, making it one of the most common genetic diseases in the country. Patients with sickle cell disease may experience negative effects from the disease. In this study, children with SCD were evaluated at the selected hospitals in Khartoum state to assess their health-related quality of life (HRQOL).
Materials and methods
A cross-sectional facility-based study was conducted at five governmental pediatric hospitals in Khartoum state and their referral clinics. A four-section questionnaire (sociodemographic information, clinical characteristics, barriers to accessing health care, and the standardized PedQL™ Generic Core Scale) was employed. Total coverage was used. The statistical software for social sciences (SPSS) was used to analyze the data and determine the correlation between the variables.
Results
We included 336 children with sickle cell disease, 191 (56.8%) males. Most participants were from Gaafar Ibnauf Specialized Hospital (n = 286, 85.1%). The majority were outpatients (77.4%), and 52.7% had a family history of the disease. Blood transfusions were required for 59.5% of patients, while 83.0% never needed exchange transfusions. The most common initial manifestation was painful crises (55.7%), while arthritis (49.4%) became a frequent symptom. The median total HRQOL score was 73.75 [57.50, 87.50]. The highest median HRQOL scores were in East Darfur, River Nile, and Central Darfur, while the lowest were in White Nile and Blue Nile. Factors significantly influencing HRQOL included hospital setting, number of affected siblings, rural residence, and father’s employment. Linear regression showed that having more affected siblings was associated with higher HRQOL, while rural residence lowered HRQOL in older children. Father’s employment improved HRQOL in younger children, while consanguinity had a negative impact.
Conclusions
Children with SCD had poor HRQOL, with low scores across multiple HRQOL domains. Factors such as consanguinity and father’s unemployment negatively affected patients’ HRQOL. Interventions are required to address such factors, and to alleviate the impact of barriers to healthcare access.
Keywords: Sickle cell disease (SCD), Health-related quality of life (HRQOL), Pediatrics, Sudan, Cross-Sectional study
Introduction
Sickle cell disease (SCD) is the world’s most common genetic hemoglobin (Hb) condition [1], caused by a point mutation resulting in the substitution of glutamic acid with valine at the sixth amino acid position of the beta-globin [2]. The affected red blood cells become sticky in the deoxygenated state, eventually leading to the classic disease features [3]. SCD is an autosomal recessive disorder; the homozygous hemoglobin S (HbSS) mutation is the most prevalent and severe form. The most common heterozygous genotypes are SC or S/-thalassemia. Individuals with a single HbS gene (HbAS) are asymptomatic carriers and exhibit the sickle cell trait.
SCD is a chronic systemic disease with variable clinical manifestations, including acute and chronic complications. Acute complications include acute hemolytic crisis, splenic sequestration, aplastic crisis, and vaso-occlusive crises (VOCs; such as acute pain crisis, acute chest syndrome, priapism, stroke, and dactylitis). Chronic complications such as avascular bone necrosis, pulmonary hypertension, heart failure, kidney disease, retinopathy, and leg ulcers may occur. SCD patients are also at an increased risk for infections [3].
Several preventive and therapeutic measures [2, 4, 5] are used to tackle these complications. Neonatal screening can aid early diagnosis, while hydroxyurea and pneumococcal vaccination are used to prevent complications. The management of VOCs includes a range of supportive measures to exchange blood transfusions. A potential cure may lie in allogeneic hematopoietic stem cell transplantation for patients with severe disease, although identical HLA donors are required [3].
In 2021, about 7.74 million individuals were living with SCD [6]. An estimated 400,000 babies are born with SCD annually [4], two-thirds of whom are in Africa [7]. In this region, around 50%−90% of infants born with SCD die before the age of five, which accounts for 20% of neonatal deaths and 5% of under-5 child mortality. The economic burden of SCD on both the families and nations is also enormous [2]. As a chronic genetic condition, SCD affects different age groups and, therefore, requires attention at various stages of life. Besides its genetic basis, sociodemographic characteristics play a significant role in predicting the disease trajectory, and its burden might be influenced by behavioural modifications [2]. Understanding the patient-reported impact of SCD on well-being and patients’ views on how their disease is managed is critical to identifying unmet needs, addressing barriers to care, challenging misconceptions, and improving quality of life (QoL) [4].
The impact of SCD on physical and mental health, social life, academic performance, and work can negatively affect QoL to a significant degree [4]. Focus group discussions with children and adolescents with SCD revealed that the disease undermines QoL in important ways [8], and SCD patients fare poorly on health-related quality of life (HRQOL) surveys compared to controls [9]. The famous Pain in Sickle Cell Epidemiology Study (PiSCES Project) showed that poorer physical and mental QoL in SCD patients was associated with high levels of depression and anxiety, as well as the frequency of pain episodes; these factors accounted for most of the variance in all domains of QoL amongst participants [10]. A study from Nigeria [11] on HRQOL of SCD adolescents showed that HRQOL was significantly lower in patients compared to their healthy peers in important dimensions (physical and social functioning, physical and emotional roles limitation, bodily pain, vitality and general health perception); hospitalisation, SCD complications and SCD stigma were significantly associated with lower HRQOL.
In Sudan, sickle cell disease is a significant health problem, particularly in the western region, where the HbS allele frequency among the Misseriya tribe is reported to range from 18.2% in Kordofan state to 30.4% in Darfur state [7]. The high prevalence of the disease in the region could be attributed to the fact that Sudan shows one of the world’s highest rates of consanguinity, with first-cousin marriages accounting for 40–45% of all marriages, and the disease being of autosomal recessive inheritance [5, 7].
While many efforts have been made to control infectious diseases in Africa, the burden of non-communicable diseases has generally gained less attention [7]. Although quite prevalent, SCD in Sudan remains underinvestigated, especially when it comes to its impact on HRQOL. This study aims to fill the gap in understanding the clinical features and the socio-economic factors affecting HRQOL among SCD children in Khartoum State, providing insights that could guide targeted interventions to improve healthcare access and overall quality of life.
Materials and methods
A descriptive, facility-based cross-sectional study was conducted in Khartoum state, one of the eighteen Sudanese states with an estimated area of 22,142 square kilometers. It contains the largest population in Sudan (7,687,547) and different multicultural ethnic groups. The study was conducted in five large governmental pediatric hospitals in Khartoum where most SCD patients are referred for follow-up, namely: Gaafar Ibnauf Specialised Hospital for Children (the largest pediatric hospital in Sudan), Ahmed Qassim Specialized Hospital, Albuluk Hospital, Omdurman Teaching Hospital, and Abu Seid Hospital.
This study totally covered all SCD patients aged 2–18 years who were seen in the outpatient clinics or admitted to the hematology department (inpatients) in the selected hospitals during the study period (November 2022 to mid-February 2023). Critically ill patients were excluded from the study so as to not burden them with answering the questionnaire. Children whose guardians refused to participate or were unavailable during the data collection period were also excluded from the study.
A Google Forms-based questionnaire was developed by the authors and used for data collection. The form was filled out by the data collectors in the facility during the study period to ensure standardized and complete data collection, thereby minimizing the risk of missing data. Additionally, all data collectors had reliable internet access, ensuring a smooth and uninterrupted data entry process. This approach also streamlined data management by allowing real-time monitoring and reducing potential errors associated with manual data entry. The questionnaire consisted of four sections: sociodemographic data, clinical characteristics, barriers to access health care, and the Parent Proxy-Report of the Pediatric Quality of Life Inventory (PedsQL). PedsQL is a standardized questionnaire that can be completed by parents to measure the health-related quality of life (HRQOL) in four dimensions: physical, emotional, social, and school functioning for children aged 5–18 years or nursery/daycare functioning for those aged 2–4 years. Each item contains five options of “Never,” “Almost Never,” “Sometimes,” “Often,” and “Almost Always” in the form of a five-point Likert scale ranging from 0 to 4. Items are then scored (100 for “Never”, 75 for “Almost Never”, 50 for “Sometimes”, 25 for “Often”, and 0 for “Almost Always”) and the total scale score is the mean of all items [12]. Two different versions of the PedsQL scale were used. The first version, namely the PedsQL PARENT report for toddlers for patients aged 2–4 years old, consists of 21 items. The second version, PARENT report for Young Children (ages 5–7), Children (ages 8–12) and Teens (ages 13–18) consists of 23 items. The PedsQL scale is known for consistently demonstrating good internal consistency and reliability, with Cronbach’s alpha values typically exceeding 0.70 [13, 14]. All questionnaire items were translated into Arabic and two independent experts reviewed the validity and appropriateness of the questionnaire translation carried out by the authors.
Participants’ parents were administered the questionnaire by trained medical data collectors. The data collectors were 4th year medical students who received comprehensive training, including interactive role-play exercises and mock interviews. Additionally, techniques of using neutral language and standardized questions and avoiding unconscious biases were reinforced. A small pilot study was used to test the questionnaire and the data collection process for any issues.
Data was cleaned and managed carefully; completeness was checked in advance. Data were coded and entered after cleaning using the Statistical Package for Social Science (SPSS) version 29. Descriptive statistics such as frequencies and percentages were used for categorical data and median with its quartiles for continuous data. For inferential statistics, the Kruskal-Wallis and Mann-Whitney U tests were used to compare the median of the different independent groups. In addition, Linear regression analysis was used to assess factors influencing the quality of life in children with sickle cell disease. Statistical significance was set at a level of p < 0.05.
Ethical approval was obtained from the Ethical Committee at the Department of Community Medicine, Faculty of Medicine, University of Khartoum (ethical approval number: COMMED 2022-94-43). Permission was taken from the Khartoum State Ministry of Health and the administrations of the study hospitals. Informed consent was taken from the participants’ guardians. Furthermore, the questionnaire was totally anonymous. The researchers declare no conflict of interest.
Results
The study included the data of 336 children diagnosed with sickle cell disease, out of a total of 358 children approached (response rate: 93.9%). 191 (56.8%) of the participants were males. Their median age was 8 (4.5, 12) years, while their median age at diagnosis was 1 (0.6, 4) years. Participants were from five major pediatric hospitals in Khartoum state, with most from Gaafar Ibnauf Specialized Hospital (n = 286, 85.1%). The majority of patients were outpatients (n = 260, 77.4%). Regarding family history, 177 (52.7%) had a family history of sickle cell disease. Among the patients, 160 (47.6%) had no siblings with sickle cell disease, 68 (20.2%) had one affected sibling, and 63 (18.8%) had two or more affected siblings (Table 1).
Table 1.
Participants’ Sociodemographics, clinical Characteristics, and healthcare facilities accessibility
| Variable | Category | 2–4 years | 5–18 Years | Total (n, %) |
|---|---|---|---|---|
| Age (in years)* | 2.5 (2, 3) | 9 (6, 13) | 8 (4.5, 12) | |
| Age at diagnosis (in years)* | 0.7 (0.5, 1.5) | 1 (0.6, 4) | 1 (0.6, 4) | |
| Hospital Name | Gaafar Ibnauf Specialized Hospital | 53 (15.8%) | 233 (69.3%) | 286 (85.1%) |
| Ahmed Gassim | 2 (0.6%) | 17 (5.1%) | 19 (5.7%) | |
| Albuluk Hospital | 2 (0.6%) | 12 (3.6%) | 14 (4.2%) | |
| Omdurman Hospital for Children | 0 (0.0%) | 14 (4.2%) | 14 (4.2%) | |
| Abu Seid Hospital for Children | 0 (0.0%) | 3 (0.9%) | 3 (0.9%) | |
| Patient Category | Admitted to the ward | 11 (3.3%) | 65 (19.3%) | 76 (22.6%) |
| Outpatient clinic | 46 (13.7%) | 214 (63.7%) | 260 (77.4%) | |
| Gender | Male | 40 (11.9%) | 151 (44.9%) | 191 (56.8%) |
| Female | 17 (5.1%) | 128 (38.1%) | 145 (43.2%) | |
| Family History of Sickle Cell Disease | No | 28 (8.3%) | 131 (39.0%) | 159 (47.3%) |
| Yes | 29 (8.6%) | 148 (44.0%) | 177 (52.7%) | |
| Siblings with SC | No siblings with SC | 35 (10.4%) | 125 (37.2%) | 160 (47.6%) |
| One sibling with SC | 6 (1.8%) | 62 (18.5%) | 68 (20.2%) | |
| Two or more siblings with SC | 7 (2.1%) | 56 (16.7%) | 63 (18.8%) | |
| Educational Level of the Mother | Illiterate | 8 (2.4%) | 32 (9.5%) | 40 (11.9%) |
| Basic religious education | 2 (0.6%) | 41 (12.2%) | 43 (12.8%) | |
| Basic schooling (primary level) | 14 (4.2%) | 97 (28.9%) | 111 (33.0%) | |
| Secondary schooling | 19 (5.7%) | 61 (18.2%) | 80 (23.8%) | |
| Higher education | 14 (4.2%) | 48 (14.3%) | 62 (18.5%) | |
| Educational Level of the Father | Illiterate | 3 (0.9%) | 15 (4.5%) | 18 (5.4%) |
| Basic religious education | 10 (3.0%) | 53 (15.8%) | 63 (18.8%) | |
| Basic schooling (primary level) | 12 (3.6%) | 89 (26.5%) | 101 (30.1%) | |
| Secondary schooling | 16 (4.8%) | 69 (20.5%) | 85 (25.3%) | |
| Higher education | 16 (4.8%) | 53 (15.8%) | 69 (20.5%) | |
| Employment Status of the Mother | Employed | 4 (1.2%) | 36 (10.7%) | 40 (11.9%) |
| Unemployed | 53 (15.8%) | 243 (72.3%) | 296 (88.1%) | |
| Employment Status of the Father | Employed | 54 (16.1%) | 229 (68.2%) | 283 (84.2%) |
| Unemployed | 3 (0.9%) | 50 (14.9%) | 53 (15.8%) | |
| Family Monthly Income | Less than 100 USD | 17 (5.1%) | 75 (22.3%) | 92 (27.4%) |
| 100–200 USD | 20 (6.0%) | 103 (30.7%) | 123 (36.6%) | |
| More than 200 USD | 20 (6.0%) | 101 (30.1%) | 121 (36.0%) | |
| Consanguinity | First-degree cousin | 24 (7.1%) | 136 (40.5%) | 160 (47.6%) |
| Relative | 17 (5.1%) | 55 (16.4%) | 72 (21.4%) | |
| Not related | 16 (4.8%) | 88 (26.2%) | 104 (31.0%) | |
| Area of Residency | Khartoum State | 39 (11.6%) | 183 (54.5%) | 222 (66.1%) |
| Outside Khartoum State | 18 (5.4%) | 95 (28.3%) | 113 (33.6%) | |
| Hospitalizations | < 5 | 36 (10.7%) | 128 (38.1%) | 164 (48.8%) |
| 24 − 5 | 19 (5.7%) | 77 (22.9%) | 96 (28.6%) | |
| 25–49 | 2 (0.6%) | 38 (11.3%) | 40 (11.9%) | |
| 50 and above | 0 (0.0%) | 36 (10.7%) | 36 (10.7%) | |
| Transfusions | Never | 25 (7.4%) | 111 (33.0%) | 136 (40.5%) |
| Once | 19 (5.7%) | 62 (18.5%) | 81 (24.1%) | |
| Multiple | 13 (3.9%) | 106 (31.5%) | 119 (35.4%) | |
| Exchange Transfusions | Never | 56 (16.7%) | 223 (66.4%) | 279 (83.0%) |
| Once | 0 (0.0%) | 29 (8.6%) | 29 (8.6%) | |
| Multiple | 1 (0.3%) | 27 (8.0%) | 28 (8.3%) | |
| Type of Nearest Healthcare Facility | Primary healthcare center | 19 (5.9%) | 89 (27.5%) | 108 (33.3%) |
| Secondary hospital | 18 (5.6%) | 95 (29.3%) | 113 (34.9%) | |
| Tertiary hospital | 7 (2.2%) | 65 (20.1%) | 72 (22.2%) | |
| Private center | 9 (2.8%) | 22 (6.8%) | 31 (9.6%) | |
|
Distance from Residence to Healthcare Facility |
Less than 30 min | 43 (12.8%) | 164 (48.8%) | 207 (61.6%) |
| 30 min to 1 h | 9 (2.7%) | 64 (19.0%) | 73 (21.7%) | |
| 1 h to 2 h | 3 (0.9%) | 37 (11.0%) | 40 (11.9%) | |
| More than 2 h | 2 (0.6%) | 14 (4.2%) | 16 (4.8%) |
*Median and quartiles
In terms of parental education, 111 (33.0%) of mothers and 101 (30.1%) of fathers had completed primary education. Only 11.9% (n = 40%) of mothers were employed, whereas most fathers were employed (n = 283, 84.2%). The majority of families (n = 222, 66.1%) resided in Khartoum State. Regarding monthly income, 27.4% (n = 92) earned less than 100 USD. In terms of consanguinity, 160 (47.6%) of the couples were first-degree cousins (Table 1).
Regarding hospitalizations, 36 (10.7%) had 50 or more admissions. Blood transfusions were required for 200 (59.5%) of the patients, with 119 (35.4%) having multiple transfusions. Exchange transfusions were never required for 279 (83.0%) of the patients (Table 1).
The nearest healthcare facilities to participants were secondary hospitals (n = 113, 33.6%), primary healthcare centers (n = 108, 32.1%), tertiary hospitals (n = 72, 21.4%), and private centers (n = 31, 9.2%). Only 4.8% of participants (n = 16) had to travel more than 2 h (Table 1).
Of the participants, the highest number of cases originated from North Kordofan (n = 45), Western Darfur (n = 40), Sennar (n = 41), and Al Jazirah (n = 37). Other states with notable case numbers included West Kordofan (n = 27), Al Qadarif (n = 25), and South Darfur (n = 23) (Fig. 1).
Fig. 1.
Distribution of Participants by State of Origin
Regarding the HRQOL scores, the highest median scores were observed in East Darfur (85.31 [75.31, 92.19]), River Nile (86.88 [86.88, 86.88]), and Central Darfur (87.19 [61.72, 89.38]). Participants from Western Darfur (76.48 [59.22, 90.63]) and South Kordofan (74.69 [61.25, 82.19]) also had relatively high scores. In contrast, the lowest median scores were reported in White Nile State (64.84 [55.31, 85.94]) and Blue Nile (68.59 [56.95, 83.20]) (Fig. 1).
The most common manifestations at first presentation were a painful sickling crisis (n = 187, 55.7%) and anemia (n = 105, 31.3%). Arthritis was the least common initial presentation (n = 20, 6.0%). However, arthritis became one of the most frequently experienced clinical symptoms of SCD (n = 166, 49.4%), along with anemia (n = 124, 36.9%) and painful crises (n = 140, 41.7%) (Fig. 2).
Fig. 2.
Frequency of Symptoms at First Presentation and Most Experienced Clinical Symptoms Among Participants with Sickle Cell Disease
Two different versions of the PedsQL scale were used to assess the participants’ HRQOL in four domains: physical, emotional, social, and School or nursery/day care functioning. The scores range from 0 to 100, with higher scores indicating better health-related quality of life. The total HRQOL score had a median of 73.75 [57.50, 87.50]. Participants aged 2–4 years had a median total HRQOL score of 79.06 [52.19, 91.41], while those aged 5–18 years had a median score of 73.44 [58.91, 86.41] (Table 2).
Table 2.
Median quality of life scores across four domains (Physical, Emotional, Social, and school or nursery/day care functioning) and total Health-related quality of life (HRQOL)
| Measure | 2–4 years | 5–18 Years | Total |
|---|---|---|---|
| Physical Total | 71.88 (37.50, 90.63) | 68.75 (43.75, 87.50) | 68.75 (43.75, 87.50) |
| Emotional Total | 65.00 (40.00, 85.00) | 75.00 (60.00, 90.00) | 75.00 (55.00, 90.00) |
| Social Total | 100.00 (40.00, 100.00) | 90.00 (65.00, 100.00) | 90.00 (65.00, 100.00) |
| School or Nursery/day care Total* | 100.00 (70.00, 100.00) | 70.00 (55.00, 90.00) | 75.00 (55.00, 100.00) |
| HRQOL Total Scale | 79.06 (52.19, 91.41) | 73.44 (58.91, 86.41) | 73.75 (57.50, 87.50) |
*The school functioning domain was assessed for children aged 5–18 years, whereas the nursery/daycare functioning domain was assessed for those aged 2–4 years
In specific domains, the physical health scores were 68.75 [43.75, 87.50] overall, with 71.88 [37.50, 90.63] for those aged 2–4 years and 68.75 [43.75, 87.50] for those aged 5–18 years. Emotional health had a median score of 75.00 [55.00, 90.00] overall, with 65.00 [40.00, 85.00] for those aged 2–4 years and 75.00 [60.00, 90.00] for those aged 5–18 years. The social health scores were 90.00 [65.00, 100.00] overall, with 100.00 [40.00, 100.00] for those aged 2–4 years and 90.00 [65.00, 100.00] for those aged 5–18 years. School or nursery/day care functioning had a median score of 75.00 [55.00, 100.00] overall, with 100.00 [70.00, 100.00] for those aged 2–4 years and 70.00 [55.00, 90.00] for those aged 5–18 years (Table 2).
Several factors influenced participants’ HRQOL in our study. Using the Kruskal-Wallis and Mann-Whitney U tests, significant differences in HRQOL scores were found across hospital settings (p = 0.017), with patients at Abu Seid Hospital having the highest median HRQOL score of 89.84 [52.81, 95.47], while those at Albuluk Hospital had the lowest (48.05 [34.06, 64.38]). However, age category (p = 0.583), outpatient status (p = 0.116), gender (p = 0.994), and family history of sickle cell disease (p = 0.888) were not significantly associated with total HRQOL scores. Although father’s employment status showed a trend toward significance (p = 0.086), it did not reach statistical significance. Other variables, including parental education level, family monthly income, consanguinity, number of hospitalizations, blood transfusions, and exchange transfusions, did not show statistically significant differences in HRQOL scores (p > 0.05) (Table 3).
Table 3.
Factors associated with total Health-related quality of life (HRQOL)
| Category | Median (Q1, Q3) | Test | p value |
|---|---|---|---|
| Age Category | |||
| 2–4 Years | 79.06 (52.19, 91.41) | 7585* | 0.583 |
| 5–18 Years | 73.44 (58.91, 86.41) | ||
| Hospital Name | |||
| Gaafar Ibnauf Specialised Hospital | 73.91 (59.38, 87.50) | 12.111† | 0.017 |
| Ahmed Gassim | 77.34 (52.81, 92.19) | ||
| Albuluk Hospital | 48.05 (34.06, 64.38) | ||
| Omdurman Hospital | 66.95 (47.50, 90.00) | ||
| Abu Seid Hospital | 89.84 (52.81, 95.47) | ||
| Patient Category | |||
| Admitted to the Ward | 69.30 (48.52, 88.13) | 11050.5* | 0.116 |
| Outpatient Clinic | 74.22 (60.00, 87.50) | ||
| Gender | |||
| Male | 73.91 (57.97, 88.75) | 13840.5* | 0.994 |
| Female | 72.97 (57.03, 87.19) | ||
| Family History of Sickle Cell | |||
| No | 75.00 (57.34, 86.41) | 14,197* | 0.888 |
| Yes | 72.97 (57.97, 89.22) | ||
| Number of Siblings with SC | |||
| No siblings with SC | 70.31 (53.28, 86.25) | 9.93† | 0.128 |
| One sibling with SC | 71.64 (57.97, 84.84) | ||
| Two or more siblings with SC | 75.31 (57.97, 91.88) | ||
| Mother’s Educational Level | |||
| Illiterate | 64.53 (53.52, 87.50) | 4.821† | 0.306 |
| Basic Religious Education | 73.44 (60.94, 85.16) | ||
| Primary Schooling | 72.50 (56.88, 85.16) | ||
| Secondary Schooling | 75.63 (56.17, 89.53) | ||
| Higher Education | 77.19 (63.75, 91.09) | ||
| Father’s Educational Level | |||
| Illiterate | 66.64 (53.75, 83.44) | 5.945† | 0.203 |
| Basic Religious Education | 73.44 (60.00, 87.50) | ||
| Primary Schooling | 72.81 (58.75, 86.88) | ||
| Secondary Schooling | 73.91 (54.06, 85.00) | ||
| Higher Education | 77.03 (63.13, 91.41) | ||
| Mother’s Employment Status | |||
| Employed | 72.81 (57.34, 86.09) | 6058* | 0.811 |
| Unemployed | 73.75 (57.50, 87.58) | ||
| Father’s Employment Status | |||
| Employed | 75.31 (57.19, 89.22) | 6386* | 0.086 |
| Unemployed | 65.78 (58.75, 82.50) | ||
| Family Monthly Income | |||
| < 100 USD | 72.50 (58.44, 83.75) | 3.252† | 0.197 |
| 100–200 USD | 79.22 (57.19, 89.38) | ||
| > 200 USD | 71.25 (57.34, 89.69) | ||
| Consanguinity | |||
| First-degree Cousin | 74.53 (57.66, 87.50) | 1.271† | 0.53 |
| Relative | 76.09 (60.94, 90.23) | ||
| Not Related | 72.66 (54.30, 87.89) | ||
| Number of Hospitalizations | |||
| < 5 | 73.59 (55.08, 89.61) | 2.166† | 0.539 |
| 24 − 5 | 76.25 (60.23, 86.33) | ||
| 25–49 | 71.72 (57.42, 85.94) | ||
| 50 and above | 69.38 (59.22, 82.19) | ||
| Number of Blood Transfusions | |||
| Never | 73.91 (57.97, 87.34) | 0.981† | 0.612 |
| Once | 77.03 (59.06, 89.38) | ||
| Multiple | 72.81 (57.19, 84.69) | ||
| Exchange Transfusions | |||
| Never | 73.44 (57.34, 88.75) | 2.258† | 0.23 |
| Once | 80.63 (61.25, 89.22) | ||
| Multiple | 74.92 (46.17, 83.20) | ||
*Mann Whitney U test, † Kruskal test
Linear regression analysis was used to assess factors influencing the HRQOL in children with sickle cell disease. In the overall model, a higher number of siblings with sickle cell disease was significantly associated with increased HRQOL scores (B = 3.060, 95% CI: 0.487, 5.633, p = 0.020). However, no other predictors in the overall model reached statistical significance. Among participants aged 2–4 years, having an employed father was significantly associated with higher HRQOL scores (B = 47.251, 95% CI: 5.988, 88.513, p = 0.026), while consanguinity showed a negative impact on HRQOL (B = −14.941, 95% CI: −28.363, −1.518, p = 0.030). For participants aged 5–18 years, residing in rural areas was associated with significantly lower HRQOL scores (B = −5.914, 95% CI: −11.651, −0.176, p = 0.043). Other variables, including hospital name, patient category, gender, family history of sickle cell disease, parental education, employment status, family income, hospitalizations, and transfusions, did not show statistically significant associations with HRQOL scores (p > 0.05) (Table 4).
Table 4.
Multiple linear regression analysis of factors associated with Health-related quality of life (HRQOL) scores among participants
| Overall | 2–4 Years | 5–18 Years | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Predictor | B (95% CI) | Beta | p value | B (95% CI) | Beta | p value | B (95% CI) | Beta | p value |
| (Constant) | 62.095 (26.888, 97.302) | — | 0.001 | 9.186 (−132.066, 150.438) | — | 0.895 | 86.385 (51.371, 121.399) | — | < 0.001 |
| Hospital name | −3.227 (−7.380, 0.926) | −0.12 | 0.127 | −19.205 (−47.160, 8.750) | −0.29 | 0.171 | −3.254 (−7.307, 0.799) | −0.139 | 0.115 |
| Patient category | 0.818 (−7.084, 8.719) | 0.016 | 0.839 | 1.388 (−26.617, 29.392) | 0.02 | 0.92 | 0.201 (−8.004, 8.407) | 0.004 | 0.961 |
| Gender | 0.924 (−4.464, 6.311) | 0.021 | 0.736 | 8.317 (−12.745, 29.380) | 0.127 | 0.427 | −0.458 (−5.871, 4.955) | −0.011 | 0.868 |
| Family history of SCD | −3.356 (−9.221, 2.509) | −0.075 | 0.261 | 3.776 (−20.446, 27.999) | 0.065 | 0.753 | −2.074 (−8.031, 3.882) | −0.051 | 0.493 |
| Number of siblings | 3.060 (0.487, 5.633) | 0.163 | 0.020* | 2.778 (−9.151, 14.708) | 0.101 | 0.638 | 2.110 (−0.466, 4.685) | 0.124 | 0.108 |
| Mother’s education | −0.156 (−2.795, 2.483) | −0.009 | 0.908 | 0.110 (−10.492, 10.713) | 0.005 | 0.983 | −0.122 (−2.782, 2.538) | −0.007 | 0.928 |
| Father’s education | 1.381 (−1.427, 4.190) | 0.073 | 0.334 | 6.519 (−4.146, 17.185) | 0.278 | 0.222 | 0.224 (−2.664, 3.112) | 0.013 | 0.879 |
| Mother’s employment | −0.893 (−9.454, 7.669) | −0.013 | 0.837 | 7.501 (−38.078, 53.079) | 0.062 | 0.739 | −1.585 (−10.044, 6.874) | −0.026 | 0.712 |
| Father’s employment | 0.407 (−7.053, 7.867) | 0.007 | 0.915 | 47.251 (5.988, 88.513) | 0.393 | 0.026* | −3.484 (−10.704, 3.735) | −0.066 | 0.343 |
| Family income | 1.414 (−2.100, 4.928) | 0.051 | 0.429 | −6.199 (−20.197, 7.799) | −0.176 | 0.373 | 2.558 (−1.052, 6.168) | 0.099 | 0.164 |
| Consanguinity | −1.932 (−4.966, 1.101) | −0.076 | 0.211 | −14.941 (−28.363, −1.518) | −0.44 | 0.030* | −0.999 (−4.050, 2.052) | −0.043 | 0.519 |
| Area of residency | −5.268 (−10.855, 0.319) | −0.113 | 0.064 | −13.427 (−36.760, 9.906) | −0.221 | 0.249 | −5.914 (−11.651, −0.176) | −0.138 | 0.043* |
| Origin | 0.246 (−0.286, 0.777) | 0.055 | 0.364 | 0.748 (−1.047, 2.543) | 0.13 | 0.402 | 0.093 (−0.455, 0.641) | 0.023 | 0.738 |
| Hospitalizations | −0.258 (−3.121, 2.605) | −0.012 | 0.859 | 14.313 (−2.358, 30.983) | 0.283 | 0.09 | −1.434 (−4.235, 1.367) | −0.076 | 0.314 |
| Transfusions | −0.495 (−3.780, 2.790) | −0.019 | 0.767 | 3.099 (−8.298, 14.495) | 0.085 | 0.583 | 0.166 (−3.256, 3.587) | 0.007 | 0.924 |
| Exchange transfusions | −0.160 (−4.976, 4.657) | −0.004 | 0.948 | 1.940 (−30.570, 34.449) | 0.019 | 0.904 | −0.421 (−5.055, 4.212) | −0.012 | 0.858 |
Discussion
Despite the high prevalence of SCD in Sudan, reaching up to 30.4% in Western Sudan [5], and the evidence of worse HRQOL among SCD children [15], there is a lack of national studies investigating the effect of SCD on HRQOL. The median age of the participants was 8.0 years while the median age at diagnosis was 1.0 years (7.2 months − 4.0 years). In other studies from Nigeria, the median age at SCD diagnosis was 2.0 years (2.5 months − 14.0 years) and 1.5 years (3.0 months − 12.0 years) [16, 17]. Due to financial and logistical barriers, the unavailability of routine screening programs in Sudan and Nigeria may have led to delayed diagnosis and, possibly, more complications. Implementation of screening programs has been shown to effectively reduce SCD burden in other populations, such as in Bahrain [18].
Gaafar Ibnauf Children Hospital is the second oldest pediatric hospital in Africa and the largest in Sudan where the majority of Sudan SCD patients follow up [19]. Patients from other hospitals are referred to its weekly SCD clinic. Therefore, 85.1% of our participants were from Gaafar Ibnauf Hospital.
Most participants were from the western states (Kurdufan and Darfur) while no patients were from the Northern and Kassala states. SCD and sickle cell trait are well known to be endemic in western Sudan and prevalent among western tribes due to factors such as high consanguinity and malaria endemicity, which are strong factors related to the recessive SCD gene. This is further exacerbated by the lack of premarital and antenatal screening [5]. Sickle cell trait confers partial protection against Plasmodium falciparum malaria, for which several mechanisms are suggested [20].
SCD is inherited in an autosomal recessive pattern. Due to social and cultural factors, levels of consanguineous marriage are high in Sudan. A recent study reported a 42.8% level of consanguinity and highlighted that the highest levels were found in the western states, where SCD is also prevalent [21]. In our study, 70% of the participants were children born to consanguineous parents, and 51.9% of the participants had a positive family history of sickle cell disease. Health education, awareness-raising interventions, and premarital screening programs should be implemented to tackle the disease from this aspect.
The first presentations of SCD in our study cases were sickle crises and anemia. Arthritis was the most frequent manifestation although it was uncommon as a first presentation of the disease. This may reflect an important aspect of health-seeking behavior in these families, where only life-threatening or troublesome conditions lead the families to seek health care for their children more than a chronic slow disease process such as arthritis. This behavior may be, at least in part, attributable to the financial hardship and high cost of care for SCD patients. Future studies in Sudan should focus on studying the cost of illness in these patients as it may have a direct effect on the quality of life.
SCD patients, along with their families, face many barriers and challenges, including healthcare access, social stigma, chronic pain, disabilities, and others [22]. In Sudan, the healthcare system is inequitable; therefore, barriers to healthcare access can represent a real struggle. According to our study, primary healthcare centers were not the first station of care for most participants. The nearest healthcare facilities to most patients were secondary hospitals. The unavailability of healthcare facilities, along with a lack of money and transportation, were common healthcare access barriers. Less commonly, there was a lack of knowledge regarding where to seek medical attention or health insurance coverage details.
It is evident that sickle cell disease significantly impairs the quality of life of adolescents. A study from the US confirmed that adolescents with SCD had impaired quality of life when compared to a normative sample [23]. In Africa, the mean global HRQOL score in SCD patients was 60 in Kenya [24] and 62 in Malawi [25], similar to other low-income countries like Brazil 60.7 [26]. In our study, the median global HRQOL score was 73.75 (57.50–87.50), comparable to the previous studies.
Our participants scored the lowest in the physical domain and the highest in the social one. This pattern agrees with a study carried out in Grenada [27], a developing country, although it is worth noting that higher scores were reported there across all domains than in our study. Although age distribution did not significantly affect HRQOL, another study demonstrated better quality of life among older patients [28]. However, in contrast, a meta-analysis reported significantly lower HRQOL among older patients [29].
Although not shown, outpatients could be expected to have better HQQOL scores than inpatients. The severe complications necessitating hospital admission experienced by the inpatients negatively affect their quality of life, especially if multiple or recurrent events occur. In addition, the hospital conditions, the strange environment, and the social withdrawal from school and friends are all contributing factors. Across the different hospitals, a statistically significant difference in the HRQOL scores was observed (p = 0.017). The highest scores were reported from Abu Sied hospital while the lowest were from Albuluk. Several hospital-related as well as patient distribution factors could be contributing.
Acute chest syndrome and painful crises, two of the most serious SCD emergencies, were not significantly associated with lower quality of life scores. The severe pain experienced in these complications affects not only the current quality of life of these patients but may also lead to long-term psychological sequelae in these children. In contrast, pain and low hemoglobin levels were associated with lower HRQOL scores in the Malawi study. Moreover, a meta-analysis of the HRQOL of SCD patients confirmed the negative impact of pain on HRQOL. In both our study and the meta-analysis, no significant association was found between parents’ educational level and HRQOL [29]. However, a similar survey from Albaha, Saudi Arabia found that higher education levels may improve the quality of life of sickle children [30]. Alternatively, father employment rather than education was found to significantly affect HRQOL among children less than four years old (p = 0.026). Of note, this significant impact was not noted with the monthly income.
Limitations
The study’s findings could be further strengthened by stratifying the study participants based on the disease-causing hemoglobin variant, and assessing for differences in HRQOL between the SCD subtypes. The unavailability of genotype testing limited this aspect of our study, and in this regard, participants were considered to be a single group. Another limitation of the study is related to the nature of the questionnaire chosen for the study - the PedsQL questionnaire, although standardized, was originally validated in the United States. The Sudanese population of sickle cell patients likely face different perceived difficulties in healthcare, and hold different expectations of the healthcare system, when compared to Western communities. An additional limitation regarding the data collection is the recall bias which might have been introduced due to the fact that the questionnaire was completed by participants’ caregivers. The caregiver’s answers may have also not fully represented the child’s experiences.
Recommendations
An important recommendation for researchers in the field is to design a questionnaire that is better suited for African communities in general, and local (e.g. Sudanese) communities in particular. Future longitudinal studies should investigate the causal relationships between HRQOL and disease severity in Sudanese SCD patients. The HRQOL assessment of SCD children may be enhanced using a genotype-specific instrument instead of a generic one. Improvements in HRQOL should be prioritized when planning SCD interventions. Larger studies at national level involving more hospitals and states would yield a better and more generalizable view of this relatively common disease and its burden, particularly on the quality of life of the sufferers. In addition, implementing newborn screening programs in Sudan will improve early detection and management of the disease.
Conclusion
Sickle cell patients in Sudan are diagnosed relatively late, usually not before they complete their first year of life. The most common initial presentations of the disease are sickle crises and anemia. The disease is most common in communities of western Sudanese origin, where rates of consanguinity and malaria endemicity are high. SCD has a negative impact on the patients’ HRQOL, with a median global HRQOL score of 73.75, and the lowest scores in the physical domain. HRQOL was found to be significantly associated with consanguinity and fathers’ employment status. Common barriers to healthcare access include financial hardship and difficulty of transportation to healthcare facilities, which further exacerbate the disease burden.
Acknowledgements
The authors wish to express their sincere gratitude to Dr. Rofida Asmally and Dr. Mohamed Almahal for their generous guidance and support. We also extend our appreciation to Ethar Annan, Gismat Ansari, Samwaal Hashash, and Wadaha Alhaj, from the University of Khartoum, Faculty of Medicine for their valuable contributions to the data collection process.
Declaration of AI use: The authors declare that they did not use any AI tool.
Registration details: Not Applicable.
Authors’ contributions
Conceptualization: Gaffar Alemam A. ManhalMethodology: Gaffar Alemam A. Manhal, Abdullatif Yasir H. Eissa, Ahmed Zaki W. Mohamed Elhassan, Mohamed H. FadulFormal analysis: Mohamed H. Fadul, Ammar Elgadi, Gaffar Alemam A. ManhalInvestigation: Suodad Elhassan, Mohamed Awad, Tina Magzoub, Gaffar Alemam A. ManhalResources: Gaffar Alemam A. Manhal, Duha Bushra Ahmed MohammedData Curation: Gaffar Alemam A. Manhal, Abdullatif Yasir H. Eissa, Ahmed Zaki W. Mohamed Elhassan, Writing - Original Draft: Gaffar Alemam A. Manhal, Abdullatif Yasir H. Eissa, Ahmed Zaki W. Mohamed Elhassan, Mohamed H. Fadul, Ammar ElgadiWriting - Review & Editing: Gaffar Alemam A. Manhal, Abdullatif Yasir H. Eissa, Ahmed Zaki W. Mohamed Elhassan, Mohamed H. Fadul, Ammar Elgadi, Suodad Elhassan, Mohamed Awad, Tina Magzoub, Duha Bushra Ahmed MohammedVisualization: Mohamed H. Fadul, Ammar ElgadiSupervision: Gaffar Alemam A. ManhalProject administration: Gaffar Alemam A. ManhalFunding acquisition: Not Applicable.
Funding
The research presented in this paper was solely funded by the authors.
Data availability
Data supporting the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the Declaration of Helsinki. Ethical approval to conduct and publish this research was obtained from the Department of Community Medicine, Faculty of Medicine, University of Khartoum, and the approval number “COMMED 2022-94-43” was assigned to the study.
All participants in this study were required to provide informed consent and express their willingness to participate in the study.
Consent for publication
All participants in this study provided informed consent expressing their agreement to publish this study.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Cesar P, Dhyani A, Augusto Schwade L, Acordi P, Xerez Albuquerque C, Nina R, et al. Epidemiological, clinical, and severity characterization of sickle cell disease in a population from the Brazilian Amazon. Hematology/ Oncol Stem Cell Therapy. 2019;12(4):204–10. [DOI] [PubMed] [Google Scholar]
- 2.Nwabuko OC, Onwuchekwa U, Iheji O. An overview of sickle cell disease from the socio-demographic triangle-a Nigerian single-institution retrospective study. Pan Afr Med J. 2022;41. [DOI] [PMC free article] [PubMed]
- 3.Leleu H, Arlet JB, Habibi A, Etienne-Julan M, Khellaf M, Adjibi Y et al. Epidemiology and disease burden of sickle cell disease in france: A descriptive study based on a French nationwide claim database. PLoS ONE. 2021;16(7 July). [DOI] [PMC free article] [PubMed]
- 4.Osunkwo I, James J, El-Rassi F, Nero A, Minniti CP, Trimnell C, et al. Burden of disease, treatment utilization, and the impact on education and employment in patients with sickle cell disease: A comparative analysis of high- and low- to middle-income countries for the international sickle cell world assessment survey. Am J Hematol. 2022;97(8):1055–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Mohammed Sabahelzain M, Hamamy H. The ethnic distribution of sickle cell disease in Sudan. Pan Afr Med J. 2014;18. [DOI] [PMC free article] [PubMed]
- 6.Thomson AM, McHugh TA, Oron AP, Teply C, Lonberg N, Tella VV et al. Global, regional, and national prevalence and mortality burden of sickle cell disease, 2000–2021: a systematic analysis from the Global Burden of Disease Study 2021. The Lancet Haematology. 2023;10(8):e585–99. Available from: 10.1016/s2352-3026(23)00118-7 [DOI] [PMC free article] [PubMed]
- 7.Daak AA, Elsamani E, Ali EH, Mohamed FA, Abdel-Rahman ME, Elderdery AY, et al. Sickle cell disease in Western sudan: genetic epidemiology and predictors of knowledge, attitude and practices. Trop Med Int Health. 2016;21(5):642–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Thomas VJ, Taylor LM. The psychosocial experience of people with sickle cell disease and its impact on quality of life: qualitative findings from focus groups. Br J Health Psychol. 2002;7(3):345–63. [DOI] [PubMed] [Google Scholar]
- 9.Fuggle P, Shand PA, Gill LJ, Davies SC. Pain, quality of life, and coping in sickle cell disease. Arch Dis Child. 1996;75(3):199–203. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Levenson JL, McClish DK, Dahman BA, et al. Depression and anxiety in adults with sickle cell disease: the pisces project. Psychosom Med. 2008;70(2):192–6. 10.1097/PSY.0b013e31815ff5c5. [DOI] [PubMed] [Google Scholar]
- 11.Adeyemo TA, Ojewunmi OO, Diaku-Akinwumi IN, Ayinde OC, Akanmu AS. Health related quality of life and perception of stigmatisation in adolescents living with sickle cell disease in nigeria: A cross sectional study. Pediatr Blood Cancer. 2015;62(7):1245–51. 10.1002/pbc.25503. [DOI] [PubMed] [Google Scholar]
- 12.PedsQL TM. (Pediatric Quality of Life Inventory TM). (n.d.). https://www.pedsql.org/
- 13.Hayes A, Raghunandan R, Killedar A, et al. Reliability, acceptability, validity and responsiveness of the CHU9D and PedsQL in the measurement of quality of life in children and adolescents with overweight and obesity. Int J Obes. 2023;47:622–9. 10.1038/s41366-023-01305-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Lim Y, Lee S, Hong I, et al. Preliminary reliability and validity of the PedsQL™ family impact module in parents of children with congenital muscular dystrophy. J Rare Dis. 2024;3:33. 10.1007/s44162-024-00057-8. [Google Scholar]
- 15.Stokoe M, Zwicker HM, Forbes C, Abu-Saris NELH, Fay-McClymont TB, Désiré N, et al. Health related quality of life in children with sickle cell disease: A systematic review and meta-analysis. Blood Rev. 2022;56:100982. [DOI] [PubMed] [Google Scholar]
- 16.Brown BJ, Akinkunmi BF, Fatunde OJ. Age at diagnosis of sickle cell disease in a developing country. 39, J Med Med Sci. 2010. [PubMed]
- 17.Akodu SO, Diaku-Akinwumi IN, Njokanma OF. Age at diagnosis of sickle cell anaemia in lagos, Nigeria. Mediterr J Hematol Infect Dis. 2013;5(1). [DOI] [PMC free article] [PubMed]
- 18.Al Arrayed S. Campaign to control genetic blood diseases in Bahrain. In: Community Genetics. 2005. pp. 52–5. [DOI] [PubMed]
- 19.Osman Swar M, Cardio D. Historical Perspectives Building Gaafar Ibnauf Children’s Hospital: Unprecedented story [Internet]. Vol. 15, S. 2015. Available from: http://www.sudanjp.orghttp://www.sudanjp.org101 [PMC free article] [PubMed]
- 20.Archer NM, Petersen N, Clark MA, Buckee CO, Childs LM, Duraisingh MT. Resistance to plasmodium falciparum in sickle cell trait erythrocytes is driven by oxygen-dependent growth Inhibition. Proc Natl Acad Sci U S A. 2018;115(28):7350–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Elhadi YAM, Alrawa SS, Alfadul ESA, Mahgoub EAA, El-Osta A, Belal SA et al. Consanguinity and willingness to perform premarital genetic screening in Sudan. Eur J Hum Genet. 2023. [DOI] [PMC free article] [PubMed]
- 22.Brennan-Cook J, Bonnabeau E, Aponte R, Augustin C, Tanabe P. Barriers to care for persons with sickle cell disease: the case manager’s opportunity to improve patient outcomes. Prof Case Manag. 2018;23(4):213–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Rock K, Ho S, Gray VL, et al. Muscle Properties, gross motor Performance, and quality of life in children with sickle cell disease. Pediatr Phys Ther. 2023;35(4):450–6. 10.1097/PEP.0000000000001037. [DOI] [PubMed] [Google Scholar]
- 24.Auma CP, Owino EJ. Influence of gender on quality of life of paediatric patients with sickle cell disease attending a referral hospital in Western Kenya; a preliminary analysis. East Afr Med J. 2021;98(3):3608–15. [Google Scholar]
- 25.Wachepa S, Bvalani R, Namubiru T, Namugerwa S, Kaudha G, Mpasa A, Munube D, Rujumba J, Ozuah N, Kiguli S. Health-related quality of life of patients with sickle cell disease aged 8–17 years at Kamuzu central Hospital, Malawi. Pediatr Blood Cancer. 2022;69(10):e29876. 10.1002/pbc.29876. Epub 2022 Jul 20. PMID: 35856744. [DOI] [PubMed] [Google Scholar]
- 26.Oliveira CDL, Kelly S, de Almeida-Neto C, et al. Quality of life in pre-adolescent children with sickle cell disease in Brazil. Pediatr Hematol Oncol. 2019;36(8):457–67. 10.1080/08880018.2019.1660743. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Grygiel A, Ikolo F, Stephen R, Bleasdille D, Robbins-Furman P, Nelson B et al. Sickle cell disease in grenada: quality of life and barriers to care. Mol Genet Genomic Med. 2021;9(1). [DOI] [PMC free article] [PubMed]
- 28.Allen TM, Anderson LM, Rothman JA, Bonner MJ. Executive functioning and health-related quality of life in pediatric sickle cell disease. Child Neuropsychol. 2017;23(8):889–906. [DOI] [PubMed] [Google Scholar]
- 29.Pandarakutty S, Murali K, Arulappan J, Al Sabei SD. Health-related quality of life of children and adolescents with sickle cell disease in the middle East and North Africa region a systematic review. Sultan Qaboos Univ Med J. 2020;20(4):e280–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Alzahrani T, Alzahrani R, Alzahrani A, Alzahrani A, Adawi A, Alqthami A, Alshehri A. Health related quality of life of children with sickle cell anemia and their Parents; quantitative study in Albaha; Saudi Arabia. J Pharm Res Int. 2021;33(27A):9–17. 10.9734/jpri/2021/v33i27A31487. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data supporting the findings of this study are available from the corresponding author upon reasonable request.