Summary Demographic Table

Table 1 . summary Distribution of all variables ,Groupwise

Dependent: all all
age Mean (SD) 24.8 (3.6)
GA Mean (SD) 38.8 (1.3)
parity 0 252 (50.4)
1 199 (39.8)
2 39 (7.8)
3 10 (2.0)
Interval Mean (SD) 3.2 (3.0)
SFH.in.Cms Mean (SD) 33.8 (2.6)
Birth.wt Mean (SD) 3.0 (0.4)
eng 11 159 (31.8)
12 160 (32.0)
13 181 (36.2)
Johnson Mean (SD) 3.4 (0.4)
error Mean (SD) -0.3 (0.4)
absolute_error Mean (SD) 0.4 (0.3)
percentage_error Mean (SD) 15.2 (12.1)
category < 2 2 (0.4)
2 - 2.5 34 (6.8)
2.5 - 3.5 157 (31.4)
3 - 3.5 231 (46.2)
> 3.5 76 (15.2)
estimation overestimation 393 (78.6)
underestimation 107 (21.4)
Gravidity Multigravida 248 (49.6)
Primigravida 252 (50.4)
GA_Cat 32.3 5 (1.0)
[37.0,42.0) 486 (97.2)
[42.0,42.3] 9 (1.8)
SFH_Cat [26.5,30.0) 15 (3.0)
[30.0,38.0) 444 (88.8)
[38.0,41.0] 41 (8.2)
BW_Cat [1.84,2.50) 36 (7.2)
[2.50,4.00) 448 (89.6)
[4.00,4.50] 16 (3.2)
Station -3 59 (11.8)
-2 67 (13.4)
-1 55 (11.0)
0 160 (32.0)
1 46 (9.2)
2 48 (9.6)
3 65 (13.0)
Membrane_Status Intact 151 (30.2)
Ruptured 349 (69.8)
Age_Cat [18,20) 23 (4.6)
[20,25) 237 (47.4)
[25,30) 184 (36.8)
[30,35) 44 (8.8)
[35,40] 12 (2.4)
Sex_of_neonate Female 233 (46.6)
Male 267 (53.4)

Demographic Variables

Distribution of Demographic Variables in Our Population

Age Distribution

The plot above shows a flipped bar plot of Counts(X axis) and percentages(annotated within bar) of various categories. The top 2 age categories are as follows : 237/500(47.4%) patients are in group 20 - 25 . 184/500(36.8%) patients are in group 25 - 30 . The Full details of distribution is in table below.

age categories n percentage
< 20 23 4.6
20 - 25 237 47.4
25 - 30 184 36.8
30 - 35 44 8.8
>35 12 2.4

Gestational Age Distribution

The plot above shows a flipped bar plot of Counts(X axis) and percentages(annotated within bar) of various categories. The top 2 GA categories are as follows : 151/500(30.2%) patients are in group >40 . 140/500(28%) patients are in group 39 . The Full details of distribution is in table below.

GA categories n percentage
< 38 94 18.8
38 115 23.0
39 140 28.0
>40 151 30.2

Parity Distribution

The Flipped Bar- plot above shows Counts(X axis) and percentages(annotated within bar) of various categories. The top 2 sub-groups are as follows : 252/500(50.4 %) patients are in sub-group 0 199/500(39.8 %) patients are in sub-group 1 The Full details of distribution is in table below.

Group n total percentage Confidence_Interval
0 252 500 50.4 46.03% - 54.77%
1 199 500 39.8 35.58% - 44.14%
2 39 500 7.8 5.69% - 10.4%
3 10 500 2.0 1.03% - 3.52%

Gravidity Distribution

The Flipped Bar- plot above shows Counts(X axis) and percentages(annotated within bar) of various categories. The top 2 sub-groups are as follows : 252/500(50.4 %) patients are in sub-group Primigravida 248/500(49.6 %) patients are in sub-group Multigravida The Full details of distribution is in table below.

Group n total percentage Confidence_Interval
Primigravida 252 500 50.4 46.03% - 54.77%
Multigravida 248 500 49.6 45.23% - 53.97%

Actual Birth Weight Distribution

The Flipped Bar- plot above shows Counts(X axis) and percentages(annotated within bar) of various categories. The top 2 sub-groups are as follows : 231/500(46.2 %) patients are in sub-group [3.00,3.50) 157/500(31.4 %) patients are in sub-group [2.50,3.00) The Full details of distribution is in table below.

Group n total percentage Confidence_Interval
3 - 3.5 231 500 46.2 41.86% - 50.58%
2.5 - 3.5 157 500 31.4 27.45% - 35.57%
> 3.5 76 500 15.2 12.26% - 18.54%
2 - 2.5 34 500 6.8 4.84% - 9.26%
< 2 2 500 0.4 0.08% - 1.28%

Estimated Birth Weight Distribution

The Flipped Bar- plot above shows Counts(X axis) and percentages(annotated within bar) of various categories. The top 2 sub-groups are as follows : 212/500(42.4 %) patients are in sub-group [3.00,3.50) 189/500(37.8 %) patients are in sub-group [3.50,4.65] The Full details of distribution is in table below.

Group n total percentage Confidence_Interval
[3.00,3.50) 212 500 42.4 38.12% - 46.77%
[3.50,4.65] 189 500 37.8 33.63% - 42.11%
[2.50,3.00) 90 500 18.0 14.82% - 21.55%
[2.00,2.50) 9 500 1.8 0.89% - 3.26%

Symphysio-Fundal Height Distribution

The Flipped Bar- plot above shows Counts(X axis) and percentages(annotated within bar) of various categories. The top 2 sub-groups are as follows : 444/500(88.8 %) patients are in sub-group [30.0,38.0) 41/500(8.2 %) patients are in sub-group [38.0,41.0] The Full details of distribution is in table below.

Group n total percentage Confidence_Interval
[30.0,38.0) 444 500 88.8 85.81% - 91.34%
[38.0,41.0] 41 500 8.2 6.03% - 10.85%
[26.5,30.0) 15 500 3.0 1.76% - 4.78%

OUTCOMES Of INTEREST

Figure 8 Boxplot Of Distribution Of Actual and Predicted in our Population

In this Figure we see Box plot of Weight_Kg in 2 sub-groups of Type : Johnson and Actual Birth.wt respectively .The individual jittered data points of Weight_Kg are overlaid over transparent Boxplot for better visualisation. We see distribution of data in individual sub-groups of Type based on these box-plots. The lower edge of box plot represents -first quartile (Q1), Horizontal bar represents the median, Upper edge represnts third quartile (Q3), Two black lines (whiskers) emanating from box-plots signify range of non-outlier data for the particular sub-group. Lower whisker represents minimum(Q1- 1.5 interquartile range) non-outlier limit of Weight_Kg and upper whisker represnts maximum(Q1+1.5interquartile range) of Weight_Kg .Any data beyond whiskers of box-plots represents outliers in the sub-groups The big brown point in the box-plots represents mean Weight_Kg of 2 groups and it has been annotated in the figure itself. Summary Statistics of the groups is presented in table below

Table Summary Table Of Birth Weight within Groups

Group n Mean SD Median Minimum Maximum
Birth.wt 500 3.039 0.438 3.00 1.840 4.50
Johnson 500 3.378 0.426 3.41 2.092 4.65

The mean of Actual Birth Weight [ 3.04 ± 0.44 ] was significantly lower than predicted by Johnson’s Formula [ 3.38 ± 0.43 ] . The mean difference was -0.34 and 95 % confidence interval of the difference was ( -0.39 - -0.29 ) . The p value was <0.001 . The t statistic was -12.42 and degree of freedom of the Welch unpaired two-sample t test was 997.26 .In Formal statistical notation this result is expressed as : t(997.26) = -12.42, p= <0.001.

Correlation between Johnson and actual birth weight

The scatter plots above show relationship between Birth.wt on X axis and Johnson on Y axis. Graphically, we see that as Birth.wt increases, Johnson also increases . On a formal statistical linear regression analysis, we that line of best fit (blue line signifying line with least square difference) also has a positive slope implying a positive correlation. The gray shaded error around blue line signifies 95% confidence interval of linear regression line of best fit. The correlation between two variables is Significant . The Pearson’s correlation between Birth.wt and Johnson is 0.54 with 95% Confidence Interval of 0.48 to 0.6. the t statistic is 14.37 The p value is <0.001 .The degree of freedom is 498. In formal statistical notation this expressed as t(498)= 14.37, P= <0.001. r(Pearson) = 0.54 95% C.I. [0.48-0.6]. n= 500. The correlation is summmarised in table below

variable n Mean SD Median Minimum Maximum
Birth.wt 500 3.039 0.438 3.00 1.840 4.50
Johnson 500 3.378 0.426 3.41 2.092 4.65
Group 1 Group 2 Degree of Freedom T statistic Correlation 95 % C.I. P value
Birth.wt Johnson 498 14.37 0.54 0.48-0.6 <0.001
Group var1 var2 cor statistic conf.low conf.high parameter significance pvalue Confidence_Interval
2 - 2.5 Birth.wt Johnson 0.14 0.77 -0.22 0.47 30 Non-Significant 0.45 -0.22-0.47
2.5 - 3.5 Birth.wt Johnson 0.28 3.59 0.13 0.42 155 Significant <0.001 0.13-0.42
3 - 3.5 Birth.wt Johnson 0.18 2.83 0.06 0.31 229 Significant 0.01 0.06-0.31
> 3.5 Birth.wt Johnson 0.55 5.74 0.38 0.69 74 Significant <0.001 0.38-0.69

absolute error

The scatter plots above show relationship between Birth.wt on X axis and absolute_error on Y axis. Graphically, we see that as Birth.wt increases, absolute_error initially decreases and then increases (i.e. more at extremes) On a formal statistical linear regression analysis, we that line of best fit (blue line signifying line with least square difference) also has a negative slope implying a negative correlation. The gray shaded error around blue line signifies 95% confidence interval of linear regression line of best fit. The correlation between two variables is Significant . The Pearson’s correlation between Birth.wt and absolute_error is -0.39 with 95% Confidence Interval of -0.46 to -0.31. the t statistic is -9.36 The p value is <0.001 .The degree of freedom is 498. In formal statistical notation this expressed as t(498)= -9.36, P= <0.001. r(Pearson) = -0.39 95% C.I. [-0.46–0.31]. n= 500. The correlation is summmarised in table below

variable n Mean SD Median Minimum Maximum
absolute_error 500 0.436 0.310 0.375 0.00 1.45
Birth.wt 500 3.039 0.438 3.000 1.84 4.50

Box plot of Absolute error variation with categories of Birth weight

In this Figure we see Box plot of absolute_error in 5 sub-groups of category : 3 - 3.5,> 3.5,2 - 2.5,2.5 - 3.5 and < 2 respectively .The individual jittered data points of absolute_error are overlaid over transparent Boxplot for better visualisation. We see distribution of data in individual sub-groups of category based on these box-plots. The lower edge of box plot represents -first quartile (Q1), Horizontal bar represents the median, Upper edge represnts third quartile (Q3), Two black lines (whiskers) emanating from box-plots signify range of non-outlier data for the particular sub-group. Lower whisker represents minimum(Q1- 1.5 interquartile range) non-outlier limit of absolute_error and upper whisker represnts maximum(Q1+1.5interquartile range) of absolute_error .Any data beyond whiskers of box-plots represents outliers in the sub-groups The big brown point in the box-plots represents mean absolute_error of 5 groups and it has been annotated in the figure itself Summary Statistics of the groups is presented in table below

Group n Mean SD Median Minimum Maximum
< 2 2 0.872 0.329 0.872 0.640 1.105
2 - 2.5 34 0.746 0.300 0.800 0.075 1.315
2.5 - 3.5 157 0.536 0.333 0.500 0.020 1.435
3 - 3.5 231 0.370 0.274 0.310 0.000 1.450
> 3.5 76 0.278 0.168 0.245 0.025 0.710

We find that One-way ANOVA was significant for Group effect of category on absolute_error. In statistical notation it is expressed as F(4,495)=<0.01. The Effect size(Omega -Squared) of this One-way ANOVA test was 0.17 .

We find that One-way ANOVA was significant for Group effect of category on absolute_error. In statistical notation it is expressed as F(4,495)=<0.01. The  Effect size(Omega -Squared) of this One-way ANOVA  test was 0.17 .

Since Overall One-Way ANOVA was signifcant indicating an overall difference in groups, we undertook 10 unpaired t-test to look for inter-group differences The mean absolute_error in Group 2 was non-significantly lower than Group 2.5 . The difference was -0.13 and 95 % confidence interval was ( -0.69 - 0.44 ) . The adjusted p value was 0.97 . The mean absolute_error in Group 2.5 was non-significantly lower than Group 3.5 . The difference was -0.34 and 95 % confidence interval was ( -0.89 - 0.22 ) . The adjusted p value was 0.45 . The mean absolute_error in Group 3 was non-significantly lower than Group 3.5 . The difference was -0.5 and 95 % confidence interval was ( -1.05 - 0.05 ) . The adjusted p value was 0.09 . The mean absolute_error in Group > 3.5 was significantly lower than Group < 2 . The difference was -0.59 and 95 % confidence interval was ( -1.15 - -0.04 ) . The adjusted p value was 0.03 . The mean absolute_error in Group 2.5 was significantly lower than Group 3.5 . The difference was -0.21 and 95 % confidence interval was ( -0.36 - -0.06 ) . The adjusted p value was <0.001 . The mean absolute_error in Group 3 was significantly lower than Group 3.5 . The difference was -0.38 and 95 % confidence interval was ( -0.52 - -0.23 ) . The adjusted p value was <0.001 . The mean absolute_error in Group > 3.5 was significantly lower than Group 2 . The difference was -0.47 and 95 % confidence interval was ( -0.63 - -0.31 ) . The adjusted p value was <0.001 . The mean absolute_error in Group 3 was significantly lower than Group 3.5 . The difference was -0.17 and 95 % confidence interval was ( -0.25 - -0.09 ) . The adjusted p value was <0.001 . The mean absolute_error in Group > 3.5 was significantly lower than Group 2.5 . The difference was -0.26 and 95 % confidence interval was ( -0.37 - -0.15 ) . The adjusted p value was <0.001 . The mean absolute_error in Group > 3.5 was non-significantly lower than Group 3 . The difference was -0.09 and 95 % confidence interval was ( -0.19 - 0.01 ) . The adjusted p value was 0.1 . Table describing these tests with Tukey’s Post-Hoc correction is described below

Comparison Difference 95% Confidence Interval P value Significance
2 - 2.5 -0.13 -0.69 - 0.44 0.97 Non-significant
2.5 - 3.5 -0.34 -0.89 - 0.22 0.45 Non-significant
3 - 3.5 -0.50 -1.05 - 0.05 0.09 Non-significant
> 3.5 - < 2 -0.59 -1.15 - -0.04 0.03 Significant
2.5 - 3.5 -0.21 -0.36 - -0.06 <0.001 Significant
3 - 3.5 -0.38 -0.52 - -0.23 <0.001 Significant
> 3.5 - 2 -0.47 -0.63 - -0.31 <0.001 Significant
3 - 3.5 -0.17 -0.25 - -0.09 <0.001 Significant
> 3.5 - 2.5 -0.26 -0.37 - -0.15 <0.001 Significant
> 3.5 - 3 -0.09 -0.19 - 0.01 0.1 Non-significant

Percentage error

The scatter plots above show relationship between Birth.wt on X axis and percentage_error on Y axis. Graphically, we see that as Birth.wt increases, percentage_error initially decreases and then increases (i.e. more at extremes) On a formal statistical linear regression analysis, we that line of best fit (blue line signifying line with least square difference) also has a negative slope implying a negative correlation. The gray shaded error around blue line signifies 95% confidence interval of linear regression line of best fit. The correlation between two variables is Significant . The Pearson’s correlation between Birth.wt and percentage_error is -0.39 with 95% Confidence Interval of -0.46 to -0.31. the t statistic is -9.36 The p value is <0.001 .The degree of freedom is 498. In formal statistical notation this expressed as t(498)= -9.36, P= <0.001. r(Pearson) = -0.39 95% C.I. [-0.46–0.31]. n= 500. The correlation is summmarised in table below

variable n Mean SD Median Minimum Maximum
Birth.wt 500 3.039 0.438 3.00 1.84 4.50
percentage_error 500 15.245 12.090 12.73 0.00 60.05

Box plot of Absolute error variation with categories of Birth weight

In this Figure we see Box plot of percentage_error in 5 sub-groups of category : 3 - 3.5,> 3.5,2 - 2.5,2.5 - 3.5 and < 2 respectively .The individual jittered data points of percentage_error are overlaid over transparent Boxplot for better visualisation. We see distribution of data in individual sub-groups of category based on these box-plots. The lower edge of box plot represents -first quartile (Q1), Horizontal bar represents the median, Upper edge represnts third quartile (Q3), Two black lines (whiskers) emanating from box-plots signify range of non-outlier data for the particular sub-group. Lower whisker represents minimum(Q1- 1.5 interquartile range) non-outlier limit of percentage_error and upper whisker represnts maximum(Q1+1.5interquartile range) of percentage_error .Any data beyond whiskers of box-plots represents outliers in the sub-groups The big brown point in the box-plots represents mean percentage_error of 5 groups and it has been annotated in the figure itself Summary Statistics of the groups is presented in table below

Group n Mean SD Median Minimum Maximum
< 2 2 47.415 17.869 47.415 34.78 60.05
2 - 2.5 34 32.482 13.072 34.780 3.12 58.44
2.5 - 3.5 157 19.994 12.593 17.800 0.80 52.18
3 - 3.5 231 11.774 8.732 9.690 0.00 45.31
> 3.5 76 7.429 4.572 7.000 0.64 20.29

We find that One-way ANOVA was significant for Group effect of category on percentage_error. In statistical notation it is expressed as F(4,495)=<0.01. The Effect size(Omega -Squared) of this One-way ANOVA test was 0.317 .

We find that One-way ANOVA was significant for Group effect of category on percentage_error. In statistical notation it is expressed as F(4,495)=<0.01. The  Effect size(Omega -Squared) of this One-way ANOVA  test was 0.317 .

Since Overall One-Way ANOVA was signifcant indicating an overall difference in groups, we undertook 10 unpaired t-test to look for inter-group differences The mean percentage_error in Group 2 was non-significantly lower than Group 2.5 . The difference was -14.93 and 95 % confidence interval was ( -34.91 - 5.05 ) . The adjusted p value was 0.25 . The mean percentage_error in Group 2.5 was significantly lower than Group 3.5 . The difference was -27.42 and 95 % confidence interval was ( -46.96 - -7.88 ) . The adjusted p value was <0.001 . The mean percentage_error in Group 3 was significantly lower than Group 3.5 . The difference was -35.64 and 95 % confidence interval was ( -55.14 - -16.14 ) . The adjusted p value was <0.001 . The mean percentage_error in Group > 3.5 was significantly lower than Group < 2 . The difference was -39.99 and 95 % confidence interval was ( -59.66 - -20.31 ) . The adjusted p value was <0.001 . The mean percentage_error in Group 2.5 was significantly lower than Group 3.5 . The difference was -12.49 and 95 % confidence interval was ( -17.68 - -7.29 ) . The adjusted p value was <0.001 . The mean percentage_error in Group 3 was significantly lower than Group 3.5 . The difference was -20.71 and 95 % confidence interval was ( -25.75 - -15.66 ) . The adjusted p value was <0.001 . The mean percentage_error in Group > 3.5 was significantly lower than Group 2 . The difference was -25.05 and 95 % confidence interval was ( -30.72 - -19.39 ) . The adjusted p value was <0.001 . The mean percentage_error in Group 3 was significantly lower than Group 3.5 . The difference was -8.22 and 95 % confidence interval was ( -11.06 - -5.38 ) . The adjusted p value was <0.001 . The mean percentage_error in Group > 3.5 was significantly lower than Group 2.5 . The difference was -12.57 and 95 % confidence interval was ( -16.4 - -8.73 ) . The adjusted p value was <0.001 . The mean percentage_error in Group > 3.5 was significantly lower than Group 3 . The difference was -4.35 and 95 % confidence interval was ( -7.98 - -0.71 ) . The adjusted p value was 0.01 . Table describing these tests with Tukey’s Post-Hoc correction is described below

Comparison Difference 95% Confidence Interval P value Significance
2 - 2.5 -14.93 -34.91 - 5.05 0.25 Non-significant
2.5 - 3.5 -27.42 -46.96 - -7.88 <0.001 Significant
3 - 3.5 -35.64 -55.14 - -16.14 <0.001 Significant
> 3.5 - < 2 -39.99 -59.66 - -20.31 <0.001 Significant
2.5 - 3.5 -12.49 -17.68 - -7.29 <0.001 Significant
3 - 3.5 -20.71 -25.75 - -15.66 <0.001 Significant
> 3.5 - 2 -25.05 -30.72 - -19.39 <0.001 Significant
3 - 3.5 -8.22 -11.06 - -5.38 <0.001 Significant
> 3.5 - 2.5 -12.57 -16.4 - -8.73 <0.001 Significant
> 3.5 - 3 -4.35 -7.98 - -0.71 0.01 Significant

percentage_error categories n percentage
< 5 104 20.8
10 - 15 105 21.0
15 - 20 60 12.0
20 - 25 33 6.6
25 - 30 18 3.6
30 - 40 50 10.0
40 - 60 27 5.4
> 5 103 20.6

absolute_error categories n percentage
< 0.15 91 18.2
0.15 - 0.25 63 12.6
0.25 - 0.35 74 14.8
0.35 - 0.50 91 18.2
>0.50 181 36.2

Regression Equation

We fitted a linear model (estimated using OLS) to predict Birth.wt with age, GA, parity, Interval and SFH.in.Cms (formula = Birth.wt ~ age + GA + parity + Interval + SFH.in.Cms). Standardized parameters were obtained by fitting the model on a standardized version of the dataset. Effect sizes were labelled following Funder’s (2019) recommendations.

The model explains a significant and substantial proportion of variance (R2 = 0.33, F(5, 494) = 50.39, p < .001, adj. R2 = 0.33). he standard deviation of residual error was 0.36 implying Birth.wt was predicted with average accuracy of +- 0.36 by our model. The adjusted R - Square for our model is 0.33 implying our model predicts 33.11 percentage variation in Birth.wt .

The model’s intercept, corresponding to Birth.wt = 0, age = 0, GA = 0, parity = 0, Interval = 0 and SFH.in.Cms = 0, is at -1.30 (SE = 0.56, 95% CI [-2.40, -0.21[, std. intercept = 0.00, p < .05). Within this model: