1
PULMONARY FUNCTION INDICES OF CHILDREN WITH SICKLE CELL ANAEMIA IN
ENUGU, SOUTH-EAST NIGERIA
Abstract
Background
The impact of sickle cell anaemia on the pulmonary function indices of children cannot be
downplayed. This is because the disorder causes obstruction of the …….and red blood cell
haemolysis which impairs lung function
Objectives: This is to determine the impact of sickle cell anaemia on the pulmonary function
indices of patients attending the paediatric sickle cell clinic at the University of Nigeria Teaching
Hospital (UNTH) Enugu, south-east Nigeria.
Methods: A cross sectional study of lung function of children with sickle cell anaemia aged 6-20
years in the city of Enugu. The study was compiled, analyzed and proofread between October 2014
and January 2015. Measurements of the peak expiratory flow rate, Forced Vital Capacity (FVC) and
the Forced Expiratory Volume in 1 second (FEV1) were taken using a single mini Wright peak flow
meter and an automated single breath vitalograph respectively.
Results: A total of 80 subjects were recruited into the study, comprising 40 HbSS patients and an
equal number of controls. Children with sickle cell anemia had lower values of FEV1(1.6±0.52),
FVC (1.76±0.95) and PEFR(309.00±82.64) when compared to those with normal Haemoglobin
genotype FEV1(12.01±0.53), FVC(2.12±0.54) and PEFR(364.10±87.85) and is statistically
significant. The mean FVC, FEV1/FVC and PEFR were also higher in the male controls compared
to the HbSS males but these differences were not statistically significant (p>0.05). Female controls
had significantly larger FEV1, FVC and PEFR compared to the SS females (p<0.05).
Conclusion: The lung function indices were significantly lower in children and adolescents with
sickle cell anaemia compared to matched controls with haemoglobin genotype HbAA.
2
Key words: Children; lung function; sickle cell anemia; Nigeria
Introduction
Sickle cell anaemia (SCA) is a genetic haematological disorder characterized by red blood cells that
assume an abnormal, rigid, sickle shape.1 This hereditary disorder contributes the equivalent of 3.4%
mortality in children aged under -5 worldwide or 6.4% in Africa.2
The prevalence of SCA in Nigeria ranges from 0.4% to 3%. 3 About 85% of sickle cell disorders and
over 70% of all affected births occur in Africa.
4
It is worth noting that at least 5.2% of the world
population carry a significant trait.
The clinical consequence of SCA, result from obstruction of the microvasculature by the sickled cells
and red blood cell haemolysis which causes multi-systemic manifestation. The lungs are affected in a
variety of ways by these pulmonary insults which if recurrent overtime, may leave the lungs with
chronic interstitial, parenchymal or vascular damage which may compromise pulmonary function.5,6
It has been documented that the prevalence of hypoxemia among SCA children is 13%.4 This
prevalence is attributable to the chronic anaemic state, micro vascular occlusion of the circulation by
sickled hemoglobin and constant pertubation of the endothelial membrane and consequent elaboration
of endothelial molecules which are commonly seen among SCA children especially those with
various types of vaso-occlusive episodes.7
Acute and chronic pulmonary complications occur frequently in patients with SCA, and contribute to
morbidity and mortality later in life. Although the pathogenesis of chronic pulmonary disease in SCD
has not been clearly defined, recurrent microvascular obstruction resulting in the development of
pulmonary hypertension, endothelial dysfunction, and parenchymal fibrosis are probably the primary
mechanisms.6
3
There is increasing evidence that repeated episodes of acute chest syndrome (ACS) may cause
permanent damage to the pulmonary parenchyma and vasculature. Repeated attacks of ACS are a
major risk factor for the development of sickle cell chronic lung disease. Studies of lung function in
SCD have also demonstrated a restrictive defect
8,9
while a reduction in total lung capacity (TLC) of
50% has been reported in advanced forms.
During steady-state sickle-cell disease, the major abnormality in pulmonary function is a restrictive
ventilatory impairment, characterized by a mild reduction in total lung capacity, and reduced
diffusion capacity for carbon monoxide
10
. These abnormalities worsen with age and are associated
with increases in pulmonary-artery pressures11
Whereas some studies have documented impaired lung function in sickle cell anaemia (HbSS)
patients.8-11 Other workers, however, reported what appears to be contrasting findings when they
compared lung function in children with sickle cell anaemia and those of healthy controls with normal
haemoglobin genotype.8-11 It is therefore necessary that ventilatory function studies be undertaken in
this part of the world to see if there is any difference with known values in other part of the world. In
this study we determine the impact of sickle cell anaemia on the pulmonary function indices of
patients attending the paediatric sickle cell clinic at the University of Nigeria Teaching Hospital
(UNTH) Enugu, south-east Nigeria and compare it with matched control and other findings
elsewhere.
Subjects and methods
Study area
This study was carried out in UNTH Ituku-Ozalla Enugu, south-east Nigeria. The hospital is a
referral centre for various health facilities in Enugu state and her environs. Enugu has a population
of 3.5 million people according to the National population census.12
Study population
4
These were patients with haemoglobin genotype HbSS attending the paediatric sickle cell clinic at
UNTH, who fulfilled the criteria for inclusion into the study. The controls comprised healthy
children with haemoglobin genotype HbAA matched for age, sex and height randomly selected
from primary and post primary schools within Enugu metropolis. All the controls also fulfilled the
criteria for inclusion into the study.
Ethical Consideration and Consent
Ethical clearance for the study was obtained from the Research and Ethical Committee of the
UNTH
and
the
Post
Primary Schools
Management
Board,
as
well
as
from
the
Headmasters/mistresses and principals of the selected primary and secondary schools whose
pupils/students were expected to participate in the study. Informed written consent was obtained
from the parents or guardians as appropriate prior to the recruitment of their children or wards into
the study. Verbal consent was also obtained from each of the study participants.
Study design
A cross sectional study of lung function was conducted in Enugu metropolis. The study was
compiled, analyzed and proofread between October 2014 and January 2015. Children with sickle
cell anaemia in steady state aged between 6-20 years who are willing to participate fully with a
consent obtained from the patient and parents/ guardian as applicable are included in the study
while children with presence of spinal deformity or any acute or chronic cardio-respiratory disease
which may affect the lung function indices sought were excluded from the study. For the controls,
the selection process was random, by multistage simple ballot. All the post-primary schools selected
were government institutions which have a fair representation of students from all social strata. All
the schools selected were visited by the researchers. In each of the schools, two streams of each
class were randomly selected by simple ballot. In each of the selected streams the students or pupils
as appropriate were first stratified according to age, sex, and height.
5
Pilot Study
A pilot investigation was undertaken in a group of 10 sickle cell (HbSS) patients, and an equal
number of healthy controls with genotype HbAA who were subsequently excluded from the main
study.
Pulmonary function tests
Measurements of the peak expiratory flow rate were taken using a single mini Wright peak flow
meter [Airmed, Clement Clarke International Limited Harlow, England W19516]. The instrument
was calibrated from the factory to a maximum PEFR of 800 litres per minute (l/min).
Measurements of the Forced Vital Capacity (FVC) and the Forced Expiratory Volume in 1 second
(FEV1) were taken using an automated single breath vitalograph [Spirovit-SP-1, SCHILLER-AG,
AH gasse 68, post fach, 6340 Barr, Switzerland].
Before the commencement of the study, the researchers were trained on the use of all equipment for
the present study by the Chief respiratory technician attached to the respiratory laboratory at
UNTH. On completion of the training, the researchers and the Chief respiratory technician
independently evaluated FVC, FEV1 and PEFR on seven subjects randomly selected from the
children’s’ outpatient clinic. The results obtained by the two observers were subjected to statistical
analysis using the student t-test. There was no statistically significant difference between the results
obtained by the two observers (p>0.05).
The procedure involved taking in as deep a breath as possible, and then applying their lips firmly
around the mouth piece to avoid any air leaks. Thereafter, the subject then breathed out as quickly
and as forcibly as possible into the peak flow meter. Recordings were made without nasal clips.
6
After each subject had become familiar with the technique the procedure was repeated three times,
and the best of these was recorded. For the spirometry, the same procedure was repeated. After a
rest period of about 5 minutes, the subjects after taking as deep a breath as possible applied their
lips tightly to the mouth piece of the spirometer to avoid any air leaks. They were instructed to blow
into the mouth piece as rapidly and completely as possible until they were told to stop.
Weight in kilograms scale [Deteco scales Inc. Brooklyn, New York, USA] sensitivity 0.5kg,
standing height in centimeters (cm) [stadiometer CMS weighing equipment of 17 Campdem Road,
London, NW1]. Were also taken
The social classes of subjects were determined using the mean of father’s occupation and mother’s
education. Socio-economic index scores were awarded to each child using the method
recommended by Oyedeji to assign family socio-economic class in their work done in a similar
setting.
Data Analysis
All data were coded, entered, and then analyzed using the Statistical Package for Social Sciences
program (SPSS), version 17. Results were presented in cross tabulation and tables. A value less than
0.05 were accepted as significant for each statistical test
Results
A total of 80 subjects were recruited into the study, comprising 40 HbSS patients and an equal
number of controls (healthy children of similar age, sex and height).
The distribution of the study population according to age and sex is illustrated in Table I.
The distribution of the HbSS patients and controls according to socio-economic groups is shown in
Table II.
7
Table III showed that children with sickle cell anemia had lower values of FEV1 (1.6±0.52), FVC
(1.76±0.95) and PEFR (309.00±82.64) when compared to those with normal Haemoglobin
genotype FEV1 (12.01±0.53), FVC(2.12±0.54) and PEFR (364.10±87.85) and is statistically
significant
The mean FVC, FEV1/FVC and PEFR were also higher in the male controls compared to the HbSS
males but these differences were not statistically significant (p>0.05). Female controls had
significantly larger FEV1, FVC and PEFR compared to the SS females (p<0.05). Table IV
The FEV1 increased consistently with age in both the HbSS patients and controls. The controls had
significantly higher FEV1 in all the age groups compared to the HbSS population (P<0.05). Table V
and figure 1
The FVC increased consistently with age in both the HbSS patients and controls. The controls had
higher values of FVC compared with the HbSS patients in all the age groups. These differences in
FVC values were only significant in the11-15years of age (P<0.05). (Table VI and figure 2)
The PEFR increased consistently with age in both the HbSS patients and controls. The controls had
comparable values of PEFR with the HbSS patients up to 10 years of age. The PEFR in the controls
was however, generally higher than PEFR in the HbSS patients at all ages but became significantly
higher from 11-20years of age (P<0.05). (Table VII and Figure 3)
Table VIII illustrates a comparison of the observed mean FEV1 of controls in the present study
with values predicted from previous studies at given heights in both males and females. There was
no statistically significant difference between FEVI observed in the present study and those
predicted by the two previous studies.
8
Discussion
The mean FEV1, FVC and PEFR were all significantly larger in the controls compared to the
HbSS patients, while comparable values of FEV1/FVC ratio were documented in the two
groups.
Sylvester et al [8] also noted similar findings in his study. The limitation of using FEVI/FVC
ratio in isolation to determine the severity of obstructive lung disorder has been reported. This
is because both FEV1 and FVC may decline with the progression of sickle cell disease
Koumbourlis [13] et al also noted decreased lung volume parameters in sickle cell anemia
children, he noted that in sickle cell disease (especially among patients with Hb SS),
abnormal lung function may be present. Airway reactivity had been implicated in the
pathogenesis
Some authors have attributed the lower values of lung function indices in HbSS patients to
the fact that they have a shorter thorax relative to body size as well as a narrower lateral chest
diameter compared to controls of same ethnicity.[14] These differences in thoracic and lung
volumes are believed to result in a reduction in the ratio of total lung capacity (TLC) to vital
capacity in the HbSS patients.
When lung volumes were analyzed according to age, the mean FEV1 was significantly larger
in the controls compared to the HbSS patients at all ages matched.
Mean FVC and mean PEFR were also generally higher in the controls compared to HbSS
patients at all ages. These differences however were not significant in all cases. Values of
mean FVC and mean PEFR were comparable in the younger HbSS patients and controls
(under 11 years of age). Significant differences appeared in mean PEFR with age, resulting in
significantly higher levels in controls compared to the HbSS patients from 11 years.
9
When lung function was analyzed according to sex, no significant difference was noticed
between both sexes in the HbSS patients. Similarly in the control group, no significant
differences were observed between the lung function test values in the males and females.
This finding of comparable lung function between the HbSS males and females is similar to
those of previous authors.[15] They concluded that gender may not be a very important
determinant of pulmonary function in the HbSS patients. Similar to findings in the present
study, other workers have also reported marginally but not significantly higher values of lung
function tests in healthy males compared to healthy females with HbAA genotype.
In the contrary, Oko –ose [16] and his colleagues in their own study found significantly
higher mean values of respiratory function tests in females compared to males. The larger
values of weight and body surface areas in females explained this gender variations..
Some workers have reported a plateau effect in lung function of normal males and females at
a certain age in life which is believed to be variable.[17] This plateau effect was noted at 23
years for males and 19 years for females.[17]
When PEFR in controls in the present study were compared to previously reported values in
healthy subjects, comparable values were observed in both sexes.[18] but significantly higher
than values predicted by Onadeko [18] et al at certain heights.
In the control females, the PEFR in the present study were comparable with values in a
previous study [18] and maintained consistently but marginally higher levels except between
135-147.9cm and 161-173.9cm where values were significantly higher than those predicted
by Onadeko et al [13]. One can therefore surmise that PEFR in the Caucasian population
approximated those in the present study in both sexes. However at higher heights in the
males, Caucasian values seemed to overtake those of the present study.
10
A reduction in lung volume of 1-2% in the sitting position compared to the standing position
has been reported by previous authors. This effect is noted to be greater in obese persons.
The observation of comparable PEFR values in the present study compared to Caucasian
values did not come entirely as a surprise despite previous reports of higher values of lung
function parameters in most Caucasian studies compared to studies in Africans.[1921].Reasons adduced for this previous higher values of lung function tests in Caucasians
compared to Africans include differences in environmental conditions like nutrition,
infections, as well as genetic differences in chest size, shape and possibly lung volumes.
Though some workers [22] have reported adverse effects of low socio-economic class on
lung function tests, in the present study the socio-economic spread of the SS patients and
matched controls were comparable. Any differences in lung function noticed are therefore
unlikely to result from differences in social class between the two groups.
Conclusions
The lung function indices were significantly lower in children and adolescents with sickle
cell anaemia compared to sex, age and height matched controls with haemoglobin genotype
HbAA. The lung function abnormality noted in HbSS patients appears to be restrictive rather
than obstructive in nature. Lung function indices correlate well with age and stature in south
eastern Nigeria as has been reported in other regions of the world.
Competing interests
The authors declare that we have no competing interests.
11
Authors’ contributions
Drs. KIA had primary responsibility for protocol development, patient screening, enrolment,
outcome assessment, preliminary data analysis, and writing of the manuscript. Dr. OOI and
JMC also supervised the design and execution of the study, and performed the final data
analyses. Drs. KIA, OOI and JMC AEO, IAN, EIJ, IBC participated in writing of the
manuscript.
Funding
There were no sponsors or grants given to us in this study. We bore all the expenses accrued
in this study
Acknowledgements
We thank the statistician who helped in data entering and analysis.
12
References
1. Yawn, BP; Buchanan, GR; Afenyi-Annan, AN; Ballas, SK; Hassell, KL; James, AH
et al. “Management of sickle cell disease: summary of the 2014 evidence- based
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2. Araba AB. A Survey of haematological variable in 600 healthy Nigerians. Niger Med
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3. Modell M, Dailison D. Bernadette M, Matthew D. Global epidemiology of
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4. Chinawa JM, Ubesie AC, Chukwu BF, Ikefuna AN, Emodi IJ. Prevalence of
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6. Vig R, Machado RF. Pulmonary complications of hemoglobinopathies. Chest 2010;
138 973-983.
7. Ataga KI, Moore CG, Hillery CA, Jones S, Whinna HC, Strayham A. Coagulation
activation and inflammation in sickle cell disease-associated pulmonary
hypertension. Haematologica 2008;93;20-6.
8. Sylvester KP, Patey RA, Milligan P, Dick M, Rafferty GF, Rees D, Thein SL,
Greenough A. Pulmonary function abnormalities in children with sickle cell disease.
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9. Arteta M, Campbell A, Nouraie M, Rana S, Onyekwere OC, Ensing G, Sable C,
Dham N, Darbari D, Luchtman Jones L, Kato GJ, Gladwin MT, Castro OL, Minniti
CP, Gordeuk VR. Abnormal pulmonary function and associated risk factors in
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36:185-9.
10. Powars DR, “Sickle cell anemia and major organ failure,” Hemoglobin.1990; 14:
573–598.
11. Anthi A, Machado RF, Jison ML “Hemodynamic and functional assessment of
patients with sickle cell disease and pulmonary hypertension,” The American Journal
of Respiratory and Critical Care Medicine, vol. 175, pp. 1272–1279, 2007.
12. National population commission 2006 provisional census figures. Census news
31:14.
13. Koumbourlis Ac, Hurlet- Jensen A, Bye MR. Lung function in infants with sickle
cell disease. . Pediatr Pulmonol. 1997; 24: 277-81.
13
14. .Pianosi P1, D'Souza SJ, Charge TD, Esseltine DE, Coates AL.Pulmonary function
abnormalities in childhood sickle cell disease. . J Pediatr. 1993; 122: 366-71.
15. VanderJagt , Trujillo MR, Jalo I, Bode-Thomas F, Glew HR, “Pulmonary function
correlates with body composition in Nigerian children and young adult with sickle
cell disease,” Journal of Tropical Pediatrics 2007;54: 87–93.
16. Oko-Ose JN., Iyawe 1V, Egbagbe E, Ebomoyi M .Lung Function Tests in SickleCell Patients in Benin City. ISRN Pulmonology 2012; 2012 :1-5.
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1983; 10: 45 – 55.
14
Table I: Age and Sex Distribution of HbSS and Controls
Age group
(Last
birthday)
HbSS
n (%)
6-10
4(20.0)
4(20.0)
3(15.0)
3(15.0)
7(17.5)
7(17.5)
11-15
11(55.0)
12(60.0)
12(60.0)
12(60.0)
23(57.5)
24(60.0)
16-20
5(25.0)
4(20.0)
5(25.0)
5(25.0)
10(25.0)
9(22.5)
Total
20(100.0)
20(100.0)
20(100.0)
20(100.0)
𝓧 = 0.155
Male
Control
n (%)
𝞉f= 2
Female
HbSS
Control
n (%)
n (%)
p- value = 0.05
Total
HbSS
n (%)
40(100.0)
Control
n (%)
40(100.0)
15
Table II: Distribution According to Socio-economic Classes of HbSS and Controls
Socioeconomic Class
HbSS
Control
n (%)
n(%)
I
1(2.5)
1(2.5)
II
4(10.0)
6(15.0)
Middle
III
11(27.5)
10(25.0)
Lower
IV
22(55.0)
18(45.0)
V
2(5.0)
5(12.5)
40(100.0)
40(100.0)
upper
Total
𝓧 = 2.133 𝞉f= 4 p- value = 0.7
16
Table III: Pearsons correlation coefficient for HbSS and Controls (Total study population )
Variables
FEV1.0
(Litres)
HbSS
FVC
(Litres)
PEFR
(Litres/min)
FEV1.0
(Litres)
Control
FVC
(Litres)
PEFR
(Litres/min)
Age (year)
0.81
0.71
0.75
0.80
0.79
0.86
Standing Height (cm)
0.87
0.78
0.79
0.89
0.85
0.90
Weight (Kg)
0.85
0.79
0.78
0.85
0.81
0.88
Chest Circumference(cm)
0.72
0.70
0.71
0.67
0.65
0.70
Body Surface Area (m2)
0.88
0.81
0.80
0.87
0.83
0.88
𝓧=
𝞉f= p- value = 0.01
17
Table IV: Relationship between FEV1, FVC, PEFR, Height, Body Surface Area (BSA) and Weight in Males (HbSS and Controls)
Correlation(s)
Intercept
Gradient
SD
Regression Equation
HbSS
FEV1 and Height
0.90
- 3.61
0.04
0.51
FEV1= -3.61+ 0.04 Ht
Controls
FEV1 and Height
0.88
- 3.59
0.04
0.55
FEV1 =-3.59 + 0.04 Ht
HbSS
FEV1 and BSA
0.93
-1.37
2.34
0.53
FEV1 = -1.37 + 2.34BSA
Controls
FEV1and BSA
0.89
- 0.84
2.19
0.56
FEV1 =- 0.84 + 2.2 BSA
HbSS
FEV1 and Wt
0.95
- 0.52
0.06
0.54
FEV1 = - 0.52 + 0.1 Wt
Controls
FEV1 and Wt
0.89
0.19
0.51
0.56
FEV1 = - 0.19 + 0.51 Wt
HbSS
FVC and Height.
0.75
- 3.36
0.03
0.50
FVC= -3.36 + 0.03Ht
Controls
FVC Height
0.86
- 3.61
0.04
0.56
FVC = - 3. 61 + 0.04Ht
HbSS
FVC and BSA
0.79
- 1. 21
2.35
0.57
FVC = - 1.21 + 2. 35 BSA
Controls
FVC and BSA
0.86
- 0.78
2.22
0.56
FVC = - 0.78 + 2.22 BSA
HbSS
FVC and Weight
0.81
- 0. 41
0.07
0.56
FVC = - 0.41 + 0.07 Wt
Controls
FVC and Weight
0.85
0.29
0.05
0.56
FVC = - 0.29 + 0. 05 Wt
HbSS
PEFR and Height
0.72
-301.96
4.22
59.68
PEFR=-301.9 + 4.22 Ht
18
Controls
PEFR and Height
0.90
-562.45
6.35
90.99
PEFR= -562.5 + 6.35 Ht
Table V. Relationship between FEV1, FVC, PEFR, Height, Body surface Area and Weight in Females (HbSS and Controls)
Correlation(s)
Intercept
Gradient
SD
Registration Equation
HbSS
FEV1 and Height
0.82
- 3.27
0.33
0.39
FEV1 =- 3. 27 + 0.33 Ht
Controls
FEV1 and Height
0.92
- 2.84
0.03
0.3 9
FEV1 -2.84 + 0.03 Ht
HbSS
FEV1 AND BSA
0.83
- 0.83
1.84
0.39
FEV1 = – 0.83 + 1.84 BSA
Controls
FEV1 AND BSA
0.87
-0.11
1.54
0.37
FEV1 = 0.11 + 1.54 BSA
HbSS
FEV1 and Wt
0.80
0.20
0.04
0.38
FEV1 = 0.19+0.04 Wt
Controls
FEV1 and Wt
0.84
0.62
0.03
0.36
FEV1 = 0. 62 + 0. 04 Wt
HbSS
FVC and Ht
0.85
- 3. 28
0.03
0.40
FVC = - 3.28 + 0. 03 Ht
Controls
FVC and Ht
0.85
-2.38
0.03
0.36
FVC = - 2.38 + 0.03 Ht
HbSS
FVC and BSA
0.86
- 0. 74
1.89
0.40
FVC = - 0.74 + 1.89 BSA
Controls
FVC and BSA
0.82
0.15
1.44
0.34
FVC = 0. 15 + 1. 44 BSA
HbSS
FVC and Wt.
0.83
0.31
0.04
0.39
FVC = 0.31 +0.04 Wt
Controls
FVC and Wt.
0.80
0.82
0.03
0.33
FVC = 0.82 + 0.03 Wt
19
HbSS
PEFR and Height
0.88
-614.95
6.31
73.68
PEFR= -614 + 6.31 Ht
Controls
PEFR and Height
0.89
-476.49
5.75
67.27
PEFR = -476.5 + 5.75 Ht
Table VI: Comparison of Observed PEFR values for Male Controls in Present Study and values Predicted from Previous Studies
Height(cm)
122-134.90
135-149.90
148-160.90
161 – 173.90
Observed PEFR
Predicted PEFR
(Present study)
(Previous Study)
Mean
SD
273.94
43.67
330.89
402.71
505.82
32.73
24.75
74.80
Mean
SD
P
++ 265.38
21.67
> 0.05
+ 262.71
26.86
> 0.05
** 240.74
21.11
> 0.05
+ 328 .62
20.46
> 0.05
++ 318 57
16.50
> 0.05
** 292.54
16.08
< 0.05
+ 409.20
24.18
> 0.05
++ 383 .60
19.52
> 0.05
** 355.88
19.01
> 0.05
+469 .05
19.01
> 0.05
20
Prediction equation (Previous Studies):
+Murray et al22 (Boston); **Onadeko et al18 (Nigeria); ++ Aderele et al23 (Nigeria)
++431.90
15.34
> 0.05
** 402. 92
14.94
> 0.05
21
Fig. 1: FEV1 in Relation to Age for HbSS and Controls
3.5
3.0
KEY
(Litres)
2.0
AGE (SS)
FEV1
2.5
1.5
FEV1 (control)
AGE (Control)
FEV1 (SS)
1.0
.5
6
8
10
12
14
16
18
20
22
Age (Years)
Figure 2: FVC in Relation to Age for HbSS and Controls
4.0
3.5
FVC (Litres)
3.0
KEY
2.5
2.0
FVC (SS)
1.5
AGE (SS)
FVC (Control)
1.0
AGE (Control)
.5
6
8
10
12
Age (Years)
14
16
18
20
22
22
Figure 3: PEFR in Relation to Age for SS and Controls
700
PEFR ( Litres Per min)
600
500
KEY
400
PEFR (SS)
AGE (SS)
300
PEFR (Control)
AGE (Control)
200
100
6
8
10
12
Age (Years)
Tables’ abbreviation
Ht = Height (cm)
Wt = Weight (kg)
BSA = Body Surface Area (m2)
SD =
Standard Deviation
14
16
18
20
22