AMHSR
*Corresponding Author:
Onoh RC
Department of Obstetrics and Gynaecology Federal Medical Centre, Abakaliki, Ebonyi State, Nigeria
E-mail:
[email protected]

Dear Aji Gopakumar,

Thanks for painstakingly going through the article titled "Pattern and determinants of antenatal booking at Abakaliki Southeast Nigeria." I wish to acknowledge that your review will make the work more informative and help reduce the error margin to the barest minimum. In line 8–12, the total respondent number in Table 1 for “religion” and “parity” was given as 343 and 402, respectively, instead of 344. In “religion,” the values for Jehovah witness should be changed from 2 (0.99), 0 (0), and 3 (100) to 3 (0.99), 0 (0), and 3 (100) for total, early, and late booking, respectively. This will correct the total from 343 to 344. It was a typographical error of putting 2 as total instead of 3. In "parity," the total parity of 402 will be 344, if para ³5 is corrected from 78 (5.8), 2 (15.2), and 17 (85) to the actual values of 20 (5.8), 3 (15), and 17 (85) for the total, early, and late booking, respectively. In page no. 171, the correct value for marital status is 91.9% (316/344) which should replace 92.9 (13/14). In line 13–15, Chi-square could still be used for such conclusions if the value taken is the likelihood-ratio Chi-square with Yate’s correction using Williams’ criterion when any of the cell values is less than 5. This was done in this study. In line 16–22, Table 2, which showed, "Events of previous pregnancy and its influences on the booking pattern" which was done for 233 respondents? Chronic illness should be for 233, but was wrongly generated by the Epi-info during analysis. So, 327 (95.1%), 54 (16.5), and 273 (83.5%) should be replaced by 216 (92.7), 35 (16.2), and 181 (83.8) for total, early, and late booking, respectively. Also, the total for those who had previous chronic illness should be 17 (7.3%) instead of 17 (4.9). The Chi-square and P-value should read as 0.195 and 0.659, respectively, instead of 0.567 (0.451). The P-value for influence on counseling in previous pregnancy on booking should be 0.601 instead of −0.601. It was a typographical error. In line 23–27, with reference to Chi-square testing in cell values less than 5, Chisquare could still be used for such conclusions if the value taken is the likelihood-ratio Chi-square with Yate’s correction using Williams’ criterion when any of the cell values is less than 5.[1-4] This was done in this study.

Variables n=344 %=(100) Early Late χ2 P value
Age (years)          
<19 14 (4.1) 1(7.1) 13 (92.9) 5.88(0.317)
20 – 24 60 (17.4) 15(25.0) 45 (75.0)  
25 – 29 140 (40.7) 19(13.6) 121 (86.4)  
30 – 34 94 (27.3) 18(19.2) 76 (80.8)  
35 – 39 33 (9.6) 5 (33.3) 28 (84.8)  
> 40 3 (0.9) 0 (66.7) 3 (100)  
Marital status          
Engaged 13 (3.8) 5 (38.5) 8 (61.5)  
Not married 12 (3.59) 2 (16.7) 10 (83.3)  
Widowed 2 (0.6) 0 (0) 2 (100) 5.053 (0.282)
Separated 1 (0.3) 0 (0) 1 (100)  
Married 316 (91.9) 51(16.1) 265 (83.9)  
Family setting          
Monogamy 311 (90.4) 51(16.4) 260 (83.6)  
Polygamy 18 (5.2) 2 (11.1) 16 (88.9) 0.352 (0.553)
N/A 15 (4.4) 5 (33.3) 10 (66.7)  
Religion          
Moslem 4 (1.2) 2 (50) 2 (50)  
Pentecostal 130 (37.5) 20(15.4) 110 (84.6)  
Protestants 41 (11.9) 4(9.8) 37 (90.2) 6.649 (0.355)
Roman catholic 164 (47.7) 32(19.5) 132 (80.5)  
Traditional 1 (0.3) 0 (0) 1 (80.5)  
Pagans 1 (0.3) 0 (0) 1 (100)  
Jehovah witness 3 (0.99) 0 (0) 3 (100)  
Educational status          
No. formal education 5 (1.5) 0 (0) 5 (100)  
Primary 29 (8.4) 7 (24.1) 22 (75.9)  
Secondary 148 (43.0) 24(16.2) 124 (83.8) 2.158
Tertiary 162 (47.1) 27(16.7) 135 (83.3) (0.540)
Socio-economic status of women          
House wife 38 (11.1) 4 (12.5) 34 (87.5)  
Farmer 10 (2.9) 1 (10) 9 90)  
Petty trader 30 (8.8) 6 (20) 24 (80)  
Seamstress 12 (8.5) 0 (0) 12 (100)  
Artisan/fashion/ design 10 (2.9) 3 (30) 7 (70) 10.500
Civil servant 112 (32.7) 24 (21.4) 88 (78.6) (0.486)
Professional 8 (2.3) 1 (12.5) 7 (87.5)  
Business woman 49 (14.3) 9 (18.4) 40 (81.6)  
Pastor 2 (2.6) 1 (50) 1 (50)  
Student 67 (19.6) 9 (13.4) 58 (86.6)  
Corpers 4 (1.2) 0 (0) 4 (100)  
Politicians 2 (0.6) 0 (0) 2 (100)  
Parity          
0 111 (32.3) 19(17.1) 92 (82.9)  
1 79 (23.0) 19(24.1) 60 (75.9) 5.197
2 60 (17.4) 09(15.0) 51 (85) (0.392)
3 41 (11.9) 05(12.2) 36 (87.8)  
4 33 (9.6) 03 (9.1) 30 (90.9)  
≥5 20 (5.8) 03(15.0) 17 (85.0)  

Table 1: Socio demographic characteristic and booking pattern

Variables Total Early Late χ2 (P value)
Complication in previous pregnancy        
Yes 60 (25.9) 12 (20) 4.8 (80) 0.617
No 173(74.1) 27 (15.6) 14.6 (84.4) (0.432)
Complication in Previous was reason for booking now        
Yes 33 (55) 7 (21.2) 26 (78.8) 0.067
No 27 (45) 5 (18.5) 22 (81.5) (0.795)
Counseling on early booking in previous pregnancy        
Yes 159(68.2) 28 (17.6) 131 (82.4) 0.273
No 74 (31.8) 11 (14.9) 63 (85.1) (0.601)
Booking status in previous pregnancy        
Booked 228(62.3) 38 (16.7) 190 (83.3) 0.996
Un-booked 5 (1.5) 0 (0) 5 (100) (0.318)
Chronic illness diagnosed in previous pregnancy        
Yes 17(7.3) 4 (23.5) 13 (76.5) 0.195
No 216(92.7) 35 (16.2) 181 (83.8) (0.659)

Table 2: Events of previous pregnancy and its influences on booking pattern

The conclusion about misconception was derived from Tables 3 to 5. In table 3 the respondents suggested that the ideal gestational date for antenatal booking was in second trimester [128 (37.2%)] and third trimester [33 (9.6%)]. Table 4 also shows misconception in the row for ideal period for booking, where 29 (85.3) respondents felt that the ideal period is not in the first trimester. This is also shown in Table 5. The reasons given for not supporting early antenatal booking were that nothing is done by the doctor, pregnancy is still too early, makes one reveal her pregnancy too early, and makes one visit too frequently. These are all misconceptions. Regarding the financial constraints, it was statistically significant in the analysis, and Chi-square could still be used for such conclusions if the value taken is the likelihood-ratio Chi-square with Yate’s correction using Williams’ criterion when any of the cell values is less than 5. Finally, even though Fischer’s exact test could be used in place of Chi-square when any cell value is less than 5, the use of likelihood Chi-square with Yate’s correction using Williams’ criterion takes care of the error margin.

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