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Extubation Quality Score

DISCUSSION

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As shown in Table II, seventy (19.5%) subjects were from families with high socio-economic status (SEC I and II), 160 (44.4%) were in the middle class (SEC III) and 130 (36.1%) were from low socio-economic background (SEC IV and V). Of the 70 subjects in the high socio-economic class, 64 lived in the urban area representing 22.2% of the urban study group while 6 resided in the rural area representing 8.3% of the rural study population. This difference in social class representation was statistically significant (χ2 = 7.094, df =1 p = 0.008).

Table II: Distribution of 360 Subjects according to social class

Social Class Frequency Percent

I 5 1.4

II 65 18.1

III 160 44.4

IV 107 29.7

V 23 6.4

Total 360 100.0

55 Weight

Between 10 and 14yrs of age, girls were significantly heavier than boys.

Subsequently, the difference narrowed to insignificant levels at 14 to 15.9 years. From 16 years on, boys were heavier than girls but the difference was not significant. There was a strong correlation between weight and age in both boys and girls r = 0.699 and 0.449 respectively. Analysis of variance (ANOVA) also confirmed this increase in weight with age in both boys and girls with p value < 0.0001 for both groups (F = 33.1827 for boys and 7.8464 for girls).

The mean weights for boys in the urban and rural areas were 46.5kg and 49.4kg respectively. The difference between these weights was not statistically significant (t

= -1.385, df = 178, p = 0.168). The mean weights for the urban girls (48.7kg) and the rural girls (49.2kg) were also similar (t = -0.297, df = 178, p=0.767). The variation of weight with age among various subsets of the study population is shown in Figure 1.

Table III: Mean weight (kg) of study subjects according to age and gender

Age(yrs) Boys(n) Mean ± SD Girls(n) Mean ± SD p-value df 10 – 11.9 14 30.1 ± 8.0 5 39.4 ± 3.8 0.025* 17 12 – 13.9 32 38.4 ± 8.5 29 44.3 ± 8.2 0.008** 59 14 – 15.9 46 46.3 ± 8.9 57 47.0 ± 6.9 0.620 101 16 – 17.9 53 52.8 ± 8.8 58 51.2 ± 9.6 0.358 109

≥18 35 54.4 ± 8.8 31 52.7 ± 6.8 0.387 64

All 180 47.1  11.3 180 48.7  8.6 0.142 358

* = Significant difference

** = Highly significant difference df = degree of freedom

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Table IV: Analysis of variance (ANOVA) of weight with age

Source of variation Sum of squares df Variance F-value p-value Boys

Between Groups 10084.5324 4 2521.1331 33.1827 0.0000 Within Groups 13296.0400 175 75.9774

Total 23380.5724 179

Girls

Between Groups 2017.0978 4 504.2744 7.8464 0.0000 Within Groups 11246.9600 175 64.2683

Total 13264.0578 179

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0 1 0 2 0 3 0 4 0 5 0 6 0

1 0 - 1 1 . 9 1 2 - 1 3 . 9 1 4 - 1 5 . 9 1 6 - 1 7 . 9 1 8 a n d a b o v e

A g e ( y e a r s )

Weight (kg)

u r b a n b o y s r u r a l b o y s u r b a n g i r l s r u r a l g i r l s

Figure 1: Weight variation with age according to gender and area of residence

58 Height

Below the age of 14years, there was no significant difference between the mean heights of boys and girls. Older boys however, were significantly taller than their female counterparts. Boys in urban and rural schools had similar mean heights, 160.4cm and 161.9 respectively (t = -0.689, df = 178, p =0.492). The mean height of girls in the urban area was 157.4cm and this was not significantly different from that of girls in the rural area, which was 157.0cm. The height pattern according to age, gender and area of residence is depicted in Figure 2.

Table V: Mean height (cm) of study subjects according to age and gender

Age(yrs) Boys (n) Mean ± SD Girls(n) Mean ± SD p-value df 10 – 11.9 14 140.5 ± 14.0 5 149.8 ± 1.8 0.162 17 12 – 13.9 32 152.1 ± 8.9 29 153.6 ± 8.4 0.515 59 14 – 15.9 46 160.0 ± 9.2 57 156.5 ± 6.2 0.024* 101 16 – 17.9 53 166.0 ± 7.9 58 159.3 ± 6.0 0.000** 109

≥18 35 169.5 ± 8.0 31 159.9 ± 4.7 0.000** 64

All 180 160.7  12.2 180 157.3  6.7 0.001** 358

* = Significant difference

** = Highly significant difference df = degree of freedom

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0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 0 1 8 0

1 0 - 1 1 . 9 1 2 - 1 3 . 9 1 4 - 1 5 . 9 1 6 - 1 7 . 9 1 8 a n d a b o v e

A g e ( y e a r s )

Height (cm)

u r b a n b o y s r u r a l b o y s u r b a n g i r l s r u r a l g i r l s

Figure 2: Height variation with age according to gender and area of residence

60 Body Mass Index

The mean BMI for the study population was 18.8±2.7 kg/m2 with females having a significantly higher mean than males (t = -6.006, df = 358, p =0.00001). At all ages, girls had higher BMI than boys with the difference being most marked in the 12 to 13.9yrs age group.

Table VI: Mean Body Mass Index (Kg/m2) of subjects according to age and gender

Age(yrs) Boys(n) Mean ± SD Girls(n) Mean±SD p-value df 10 – 11.9 14 15.1 ± 1.2 5 17.6 ± 1.8 0.002** 17 12 – 13.9 32 16.4 ± 2.0 29 18.7 ± 2.3 0.000** 59 14 – 15.9 46 17.9 ± 1.9 57 19.2 ± 2.5 0.005** 101 16 – 17.9 53 19.0 ± 2.5 58 20.1 ± 3.3 0.068 109

≥18 35 19.0 ± 2.0 31 20.5 ± 2.1 0.001** 64 All 180 17.9  2.4 180 19.6  2.8 0.000** 358

** = Highly significant difference df = degree of freedom

As shown in table VII, BMI correlated positively with age, weight, height, and diastolic BP in both boys and girls. In contrast to what obtained with boys, BMI showed no significant correlation with systolic blood pressure and serum cholesterol in girls.

Table VII: Correlation coefficients of Body mass index with other variables

Parameter Boys Girls All

Age 0.545** 0.331** 0.423**

Weight 0.875** 0.886** 0.841**

Height 0.561** 0.188* 0.311**

Systolic Blood Pressure 0.568** 0.142 0.351**

Diastolic blood pressure 0.351** 0.194** 0.268**

Serum Cholesterol 0.216** -0.31 0.102

** Correlation significant at p-value <0.01

*Correlation significant at p-value <0.05

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Table VIII shows the nutritional status of the study subjects according to gender and area of residence. Sixty-five students (18.1%) were underweight with BMI below the 5th centile. Forty percent of the underweight subjects were females. On the contrary, majority (81.8%) of the overweight subjects with BMI between the 90th and 95th centile were females. Similar proportions of the male and female study population, 77.2% and 78.3% respectively, were of normal weight.

Mean BMI for boys in the urban area (17.8 kg/m2) did not differ significantly from that for the boys in the rural area, 18.6kg/m2 (t = -1.751, df = 178, p=0.082). Girls in the urban area had a mean BMI of 19.5 kg/m2 and this was very similar to the mean of 19.9kg/m2 obtained for girls in the rural area. Trends in BMI with age among various sub-groups are shown in Figure 3.

Table VIII: Nutritional status of study subjects according to gender and area of residence

Centile Urban boys n=144(%)

Rural boys n=36(%)

Urban girls n=144(%)

Rural girls n=144(%)

Total n=360(%)

<5th 32 (22.2) 7 (19.4) 21 (14.6) 5 (13.9) 65 (18.1) 5th-25th 57 (39.6) 13 (36.1) 30 (20.8) 10 (27.8) 110 (30.6)

>25th – 50th 27 (18.8) 5 (13.9) 38 (26.4) 4 (11.1) 74 (20.6)

>50th-75th 19 (13.2) 7 (19.4) 37 (25.7) 13 (36.1) 76 (21.1)

>75th-90th 7 (4.9) 4 (11.1) 7 (4.9) 2 (5.6) 20 (5.5)

>90th-95th 2 (1.4) 0 (0) 7 (4.9) 2 (5.6) 11 (3.1)

>95th 0 (0) 0 (0) 4 (2.8) 0 (0) 4 (1.1)

Figures in parenthesis are percentages of the total number (n) of subjects in each subgroup

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0 5 1 0 1 5 2 0 2 5

1 0 - 1 1 .9 1 2 - 1 3 .9 1 4 - 1 5 .9 1 6 - 1 7 .9 1 8 a n d a b o ve

A g e (y e a r s)

Body Mass Index(Kg/m2)

u rb a n b o y s ru ra l b o y s u rb a n g irls ru ra l g irls

Figure 3: BMI variation with age according to gender and area of residence

64 Systolic Blood Pressure

As shown in Table IX, there was a consistent increase in systolic BP with age amongst the boys. Girls aged 10 to 13.9 years had significantly higher systolic blood pressure than boys (p  0.05). Subsequently, there was no gender related difference.

Table X shows the analysis of variance (ANOVA) of systolic BP with age for boys (F

= 12.5213, p = 0.00) and girls (F = 2.7608, p = 0.029)

In both boys and girls there were no significant urban-rural differences. The mean systolic blood pressures for boys in the urban and rural schools were 110.6mmHg and 110.4mmHg respectively. The corresponding values for the girls were 111.4mmHg and 114.2mmHg (t = -1.219, df = 178, p = 0.224). Trends in systolic blood pressure variation with age in various sub-groups is shown in Figure 4

As shown in Table XI, systolic blood pressure correlated positively with age, weight, height and diastolic blood pressure in both boys and girls. However in contrast to what obtained with the boys, systolic blood pressure did not correlate significantly with BMI and serum cholesterol amongst the girls.

Table IX: Mean systolic blood pressure (mmHg) of 360 subjects according to age and gender

Age(yrs) Boys(n) Mean±SD Girls(n) Mean±SD

p-value df 10 – 11.9 14 96.9 ± 11.3 5 110.8 ±12.2 0.032* 17 12 – 13.9 32 104.5 ± 13.1 29 110.8 ± 11.4 0.049* 59 14 – 15.9 46 107.8 ± 12.5 57 108.4 ± 11.2 0.778 101 16 – 17.9 53 115.4 ± 11.5 58 115.1 ± 12.9 0.900 109

≥18 35 117.9 ± 11.5 31 114.5 ± 11.0 0.214 64

All 180 110.6  13.5 180 112.1  12.0 0.264 358

* = Significant difference df = degree of freedom

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Table X: Analysis of variance (ANOVA) of systolic blood pressure with age Source of variation Sum of Squares df Variance F-value p-value Boys

Between Groups 7265.0966 4 1816.2742 12.5213 0.0000 Within Groups 25384.6300 175 145.0550

Total 32649.3266 179 Girls

Between Groups 1538.1006 4 384.5252 2.7608 0.0293 Within Groups 24374.2500 175 139.2814

Total 25912.3506 179

Table XI: Correlation coefficients of systolic blood pressure with other variables

Parameter Boys Girls All

Age 0.482** 0.196** 0.361**

Weight 0.617** 0.228** 0.463**

Height 0.528** 0.271** 0.418**

Body mass index 0.568** 0.142 0.351**

Diastolic Blood Pressure 0.559** 0.469** 0.525**

Serum Cholesterol 0.206** 0.097 0.053

** Correlation significant at p-value <0.01

*Correlation significant at p-value <0.05

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0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0

1 0 - 1 1 . 9 1 2 - 1 3 . 9 1 4 - 1 5 . 9 1 6 - 1 7 . 9 1 8 a n d a b o v e

A g e ( y e a r s )

Systolic BP (mmHg)

u r b a n b o y s r u r a l b o y s u r b a n g i r l s r u r a l g i r l s

Figure 4: Variation in systolic blood pressure with age according to gender and area of residence

67 Diastolic Blood Pressure

The mean diastolic blood pressure for the study population was 699.2 mmHg with a range of 48 to 96mmhg.There was no significant gender-related difference in diastolic BP at any age as shown in Table XII. Diastolic blood pressure correlated positively with age in boys but not in girls. Males and females in the urban areas had significantly higher mean diastolic blood pressures than their counterparts in the rural area. Urban males had a mean of 69.3mmHg compared with 64.7mmHg for the boys in the rural areas (t = 2.418, df = 178, p =0.017). The corresponding values for urban and rural females were 69.9mmHg and 66.9mmHg with a p value of 0.04 (t = 2.066, df = 178).

Table XII: Mean diastolic blood pressure (mmHg) of study subjects according to age and gender

Age(yrs) Boys(n) Mean ± SD Girls(n) Mean±SD

p-value df 10 – 11.9 14 65.1 ± 8.3 5 71.6 ± 9.1 0.164 17 12 – 13.9 32 65.6 ± 11.4 29 68.9 ± 7.5 0.191 59 14 – 15.9 46 65.8 ± 11.4 57 68.8 ± 8.1 0.127 101 16 – 17.9 53 72.5 ± 9.0 58 70.4 ± 8.5 0.213 109

≥18 35 69.3 ± 8.4 31 68.6 ± 7.1 0.741 64

All 180 68.4  10.3 180 69.3  7.9 0.296 358

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0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0

1 0 - 1 1 . 9 1 2 - 1 3 . 9 1 4 - 1 5 . 9 1 6 - 1 7 . 9 1 8 a n d a b o v e

A g e ( y e a r s )

Diastolic BP (mmHg)

u r b a n b o y s r u r a l b o y s u r b a n g i r l s r u r a l g i r l s

Figure 5: Variation in Diastolic blood pressure with age according to gender and area of residence

69 Total Serum Cholesterol

The mean total serum cholesterol was 148.1mg/dl with a range of 100 to 254mg/dl.

Except in the 12 to 13.9yrs age group, there was no significant gender-related difference in the mean serum cholesterol of the study population. In both boys and girls, there was no significant correlation between serum cholesterol and age (r = 0.088 for boys and –0.085 for females). p value obtained by two-way Analysis of variance (ANOVA) was 0.6418 (F = 0.6300) for the boys and 0.2500 (F = 1.3593) for the girls.

Comparing the mean value in the urban areas with those in the rural areas, no significant differences were found. Boys in the urban schools had mean serum cholesterol of 145.9mg/dl, which was comparable with 146.5mg/dl obtained for boys in the rural area (t = -1.36, df = 178, p = 0.892). The means for girls in the urban and rural areas were 148.9mg/dl and 156.6mg/dl respectively (t = -1.398, df = 178, p = 0.164).

Table XIII: Mean serum cholesterol (mg/dl) of study subjects according to age and gender

Age(yrs) Boys(n) Mean ± SD Girls(n) Mean ± SD p-value df

10 – 11.9 14 138.9 ± 16.7 5 147 ± 9.7 0.326 17

12 – 13.9 32 143.2 ± 15.7 29 154.7 ± 26.1 0.039 59 14 – 15.9 46 144.8 ± 25.6 57 155.6 ± 30.6 0.057 101 16 – 17.9 53 148.6 ± 32.2 58 143.8 ± 34.4 0.457 109

≥18 35 149.1 ± 26.9 31 148.0 ± 22.6 0.857 64

All 180 146.0  26.0 180 150.1  29.9 0.163 358

Table XIV: Analysis of variance (ANOVA) of total serum cholesterol with age Source of variation Sum of Squares df Variance F p-value Boys

Between Groups 1717.4655 4 429.3664 0.6300 0.6418 Within Groups 119276.3800 175 681.5793

Total 120993.8455 179

Girls

Between Groups 4805.3124 4 1201.3281 1.3593 0.2500

70

Within Groups 154660.7200 175 883.7755

Total 159466.0324 179

71 Obesity

Four subjects in the study population were obese with BMI above the 95th centile, giving a prevalence rate of 1.1%. All the 4 obese subjects were females living and schooling in the urban area. Three of the obese subjects belonged to families of high socio-economic status (social class II) while the 4th subject was from a low socio economic background (social class IV). This difference in social class was statistically significant

Table XV: Prevalence of obesity in various subgroups

Parameter n=4 Prevalence

Gender# Male 0 0%

Female 4 2.2%

School location Urban 4 1.4%

Rural 0 0%

Socio-economic class* High 3 4.3%

Middle/Low 1 0.3%

# - χ2 = 4.045, p =0.044, Fisher’s exact test p = 0.061 אַ- χ2 = 1.011, p =0.315, Fisher’s exact test p = 0.588

* - χ2 = 7.97, p = 0.005, Fisher’s exact test p = 0.024 χ2 = Chi-square

Table XVI: Distribution of obese subjects

Age (yrs) Gender Area of residence Body Mass Index (kg/m2)

1 12.0 Female Urban 24.33

2 14.3 Female Urban 28.31

3 17.5 Female Urban 26.69

4 17.8 Female Urban 27.02

72 Systolic Hypertension

The overall prevalence rate of systolic hypertension was 7.8%(28 subjects). Twenty of the 28 subjects with systolic hypertension were females and this gender difference in prevalence rates was statistically significant (χ2 = 5.57, p =0.018). There was no significant difference in the prevalence rate of systolic hypertension between the urban and rural subjects. Four of the 70 subjects from high socio-economic class had systolic hypertension, giving a prevalence rate of 5.7% amongst that group; this was not significantly different from 8.3% prevalence rate obtained for subjects in the middle and lower socio-economic classes (χ2 =0.516, p = 0.473).

Table XVII: Prevalence of systolic hypertension in various subgroups

Parameter n=28 Prevalence

Gender# Male 8 4.4%

Female 20 11.1%

School location Urban 22 7.6%

Rural 6 8.2%

Socio-economic class* High 4 5.7%

Middle/Low 24 8.3%

# - χ2 = 5.57, p =0.018, Fisher’s exact test p = 0.029 אַ- χ2 =0.039, p =0.844, Fisher’s exact test p = 0.808

* - χ2 =0.516, p = 0.473, Fisher’s exact test p =0.622 χ2 = Chi-square

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Table XVIII: Distribution of subjects with Systolic Hypertension (systolic BP above the 95th percentile for age & sex.45)

Age (yrs) Gender Area of residence Systolic BP (mmHg)

1 10.0 Male Urban 120

2 10.4 Female Urban 130

3 12.0 Male Urban 136

4 12.7 Female Urban 136

5 13.0 Female Urban 128

6 13.6 Male Urban 130

7 13.9 Female Urban 130

8 14.3 Female Urban 130

9 14.3 Female Urban 138

10 15.5 Female Urban 132

11 15.5 Female Urban 136

12 16.0 Female Rural 134

13 16.0 Female Urban 130

14 16.6 Female Urban 134

15 16.6 Female Urban 136

16 16.8 Female Urban 142

17 16.8 Female Urban 136

18 17.3 Male Rural 148

19 17.3 Male Urban 140

20 17.4 Female Urban 136

21 17.4 Female Urban 138

22 17.4 Female Urban 144

23 17.5 Male Urban 138

24 17.8 Male Rural 138

25 17.9 Female Rural 140

26 18.3 Male Urban 146

27 18.3 Female Rural 140

28 18.5 Female Rural 138

74 Diastolic Hypertension

Nineteen subjects had diastolic hypertension giving a prevalence rate of 5.3%. All identified hypertensive subjects resided in the urban area. The gender difference in prevalence rates of diastolic hypertension was not statistically significant, neither was the social class representation of these subjects.

Table XIX: Prevalence of diastolic hypertension in various subgroups

Parameter n=19 Prevalence

Gender# Male 12 6.7%

Female 7 3.9%

School location Urban 19 6.6%

Rural 0 0%

Socio-economic class* High 4 5.7%

Middle/Low 15 5.2%

# - χ2 =1.39, p =0.239, Fisher’s exact test p = 0.346 אַ- χ2 =5.015, p =0.025, Fisher’s exact test p = 0.018

* - χ2 =0.033, p = 0.856, Fisher’s exact test p = 0.772 χ2 = Chi-square

Table XX: Distribution of subjects with diastolic hypertension (diastolic BP above the 95th percentile for age & sex.45)

Age (yrs) Gender Area of residence Diastolic BP (mmHg)

1 10.4 Female Urban 80

2 10.8 Female Urban 80

3 11.8 Male Urban 80

4 12.0 Male Urban 96

5 12.7 Female Urban 84

6 13.3 Male Urban 86

7 13.5 Male Urban 86

8 13.6 Male Urban 88

9 14.3 Female Urban 88

10 14.6 Male Urban 90

11 15.3 Male Urban 90

12 15.7 Male Urban 88

13 15.8 Female Urban 84

14 16.0 Male Urban 90

15 16.0 Female Urban 88

16 16.3 Female Urban 90

17 17.0 Male Urban 88

18 17.3 Male Urban 88

19 17.5 Male Urban 90

75 Hypercholesterolaemia

Thirteen (3.6%) students had elevated serum total cholesterol of ≥200mg/dl. The difference between prevalence rates of hypercholesterolaemia amongst males and females was not statistically significant (χ2 =1.995, p = 0.158). The prevalence rate amongst the urban subjects was also not significantly different from that found amongst the rural study population. The difference between prevalence rates between subjects from high socio-economic background and those from lower social class also did not reach a level of statistical significance (χ2 =1.189, p = 0.275).

Forty-eight subjects (13.3%) had borderline levels of hypercholesterolaemia (170-199mg/dl). Of these 48 subjects, 37 resided in the urban area and 11 lived in the rural area; 25 were females while 23 were males.

Table XXI: Prevalence of hypercholesterolaemia in various subgroups

Parameter n=13 Prevalence

Gender# Male 4 2.2%

Female 9 5.0%

School location Urban 11 3.8%

Rural 2 2.8%

Socio-economic class* High 1 1.4%

Middle/Low 12 4.1%

# - χ2 =1.995, p =0.158, Fisher’s exact test p = 0.258 אַ- χ2 =0.180, p = 0.672, Fisher’s exact test p = 1.000

* - χ2 =1.189, p = 0.275, Fisher’s exact test p = 0.477

χ2 = Chi-square

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Table XXII: Distribution of subjects with hypercholesterolaemia (total serum cholesterol of 200mg/dl and above.88)

Age (yrs) Gender Area of residence Serum Total Cholesterol (mg/dl)

1 13.0 Female Urban 200

2 13.9 Female Urban 202

3 14.3 Female Rural 240

4 14.9 Male Urban 204

5 15.0 Female Urban 240

6 15.5 Female Urban 240

7 16.5 Female Urban 220

8 17.0 Male Urban 254

9 17.3 Male Urban 236

10 17.5 Female Rural 218

11 17.8 Female Urban 240

12 18.3 Female Urban 236

13 18.8 Male Urban 236

77

Interaction between identified cardiovascular risk factors

Forty five (12.5%) subjects had at least one cardiovascular risk factor; 28 (7.8%) had systolic hypertension, 4 (1.1%) were obese and 13 (3.6%) had hypercholesterolaemia.

Seven subjects had both systolic and diastolic hypertension. Three subjects had two co-existing risk factors– systolic hypertension and hypercholesterolaemia. None of the obese subjects had hypercholesterolaemia or hypertension. None of the youths had all three risk factors co-existing.

Of the 48 subjects with borderline hypercholesterolaemia, one was also overweight;

one had both systolic and diastolic hypertension while another two had systolic hypertension.

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