research on factors affect booking at particular gestational age in shinyanga municipal council

8/3/2019 Research on Factors Affect Booking at Particular Gestational Age in Shinyanga Municipal Council

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2011

Group E as fulfillment of AMO course

Mar/2011

Research on Factors affect

booking at particular gestational

age in Shinyanga Municipal

Council

BUGANDO MEDICAL CENTRE ASSISTANT MEDICAL OFFICER’S COURSE

2009 – 2011

DEPARTMENT OF COMMUNITY MEDICINE

Researchers:

Julius Majula – Group Leader

Sally Sally

Chijo Matekere

Felix Ntimba

Yusuph Kitunguye

Principal Supervisor

Dr. S. Ngallaba MD, C, Epi, MPH

Co-Supervisor

Remmy Moshi - Administrator



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Table of content

Description Page number

1 Acronyms 3

2 Acknowledgement and dedication 4

3 Shinyanga Municipal Council map 5

4 Title 6

5 Abstract 6

6 Broad objective 6

7 Specific objectives 6

8 Introduction 6

9 Research question 7

10 Literature review 7

11 Study design 7

12 Ethical consideration 8

13 Sample size 8

14 Sampling method 8

15 Source of data 9

16 Software to be used in the study 10

17 Data collector 10

18 Analysis 11

19 Results 22

20 Discussion 23

21 Conclusion 24

22 Recommendation 24

23 Reference 24

24 Annex I 25

25 Annex II 26

26 Annex III 17



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Acronyms

AMO Assistant Medical Officer

ANC Antenatal Clinic

CO Clinical Officer

CO I/C Clinical Officer In-Charge

DMO District Medical Officer

DRCHC District Reproductive and Child Coordinator

Epi Info Is a public domain statistical software foe epidemiology developed by CDC

GA Gestational Age

MD Medical Doctor

MMO Municipal Medical Officer

MO I/C Medical Officer In-Charge

RCH Reproductive and Child Health

RCH4 Reproductive and Child Health Card 4

RMO Regional Medical Officer

RRCHC Regional Reproductive and Child Coordinator

SPSS Statistical Package for Social Science



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AKNOWLEDGEMENT AND DEDICATION

The research work involves a lot of work and time. We are among students of group E of

Bugando Medical Centre 2009/2011 intake, would haven’t successful achieved to our desire

goal, if not for good support from different authorities whom they were very much contributing

to our research.

First and foremost very special appreciations to Dr. Ngallaba and Dr. Mwichande for their

teaching materials and supervising us and guided as from proposal stage to the production of

these good achievements of this work is a results of their contribution, kindness and their love.

Acknowledge to AMO’s Principal, Dr. Mtani for their permission and mentality supporting us to

go at Shinyanga Municipal Council for conducting our research.

We thank RMO (Dr. C. Muniko) at Shinyanga Region Hospital for allowing us to conduct our

research in Shinyanga Municipal Council as part of their authority. We also thank RegionalReproductive and Child Health Coordinator (RRCHC) for her support during research period.

Other thanks to go for District Medical Officer (DMO) of Shinyanga Municipal Council, District

Reproductive and Child Health coordinator (DRCHC) and other DMO’s staff especially Eng.

Kassim Thadeo.

Acknowledge to Medical Officer in-charge at Shinyanga Regional Hospital Dr. Fredrick Mlekwa,

Dr. Dan Matekere (Head of Obstetrics & Gynecology Department) at Shinyanga Regional

Hospital, RCH clinic staff at Shinyanga Regional Hospital. We recognize the support we got from

staff of Kambarage Health Centre, Ngokolo RC dispensary and Old Shinyanga dispensary.

Without them we could not reached our target sample size.

We salute our field supervisor Mr. R. Moshi for his close and effective supervision during our

research. Other thanks to all pregnant women attending at Shinyanga Municipal RCH clinics

were the research have been carried out who kindly and adequately responded to our

questionnaires.

We recognize Mr. Julius Majula as group reader and his expertise in database construction, data

entry and data analysis using SPSS.

Lastly we pay special dedication to our family members, our employers, and our self for nice and

excellent cooperation done by group members which enable us to succeed our goals to this research

report.

Thank GOD



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Map

Shinyanga Municipal Council map showing location of four health facilities where study was

conducted.



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Title: Research on Factors affect booking at particular gestational age in Shinyanga Municipal

Council

Abstract: In order to achieve the aim of improving outcome of pregnancy for mother and

foetus, early booking (first antenatal visit), prior 16 weeks gestation is usually recommended by

Ministry of Health and Social Welfare. A survey of information on personal data, index

pregnancy, reason for booking at particular gestation age, past obstetric history and medical

history of 258 pregnant women attending the antenatal booking clinic at the Shinyanga

Municipal Council will be carried out using structured questioner.

Broad Objective: To determine factors which contribute booking at particular gestational age of

first antenatal attendance in Shinyanga Municipal Council by March 2011.

Specific Objectives:

• To identify age distribution among pregnant mother

• To identify level of education among booked mothers

• To list factors contributed for early and late booking

• To compare between early and late booking of pregnant women

• To identify spatial distribution among early and late booking

• To give recommendation to policy makers in Shinyanga Municipal Council on how to

improve the situation

Introduction:

Shinyanga Municipal Council is one of the eight Councils, which form Shinyanga region. It lies

between latitudes 30 30’’ and 3

045’.’ South of the equator and between longitude 33

020

’’and

330

35’’East of the Greenwich meridian. Shinyanga Municipal Council is comprised of 3 divisions,

17 wards, 19 villages, 25 streets and 95 hamlets.

Timely and adequate antenatal care is generally acknowledged to be effective method of

preventing adverse outcomes in pregnant women and their babies. Overtime, this form of care

for pregnant women has become an important pillar in the safe motherhood programme as it

aims to improve pregnancy outcome. Several studies have shown an association between late

gestation age at booking and adverse maternal and fetal outcome. Maternal factors related to



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this late start of antenatal care include young maternal age, low level of education,

unwanted/unplanned pregnancy. In order to improve the outcome of pregnancy for both

mother and fetus it is desirable for booking (first antenatal clinic) to take place in early

pregnancy prior to sixteen weeks.

The advantages include: -

1. Accurate determination of the gestational age especially when patient is unsure of her

last menstrual period.

2. Baseline investigations like urinalysis, full blood picture, Blood pressure and body mass

index can be performed, VDRL, PMTC.

The study therefore attempts to establish the factors influencing the patient’s decision to book

for antenatal care in respect to gestational age at booking.

Research questions:

1. What is a proportion of pregnant mothers who are attending before 16 weeks of

gestation age compared to late visit?

2. Is it education level contribute to early/late attendance?

3. Is it marriage contribute to early/late attendance?

Literature review:

1. Same study was conducted at Collage of Medicine; University of Lagos which showsmean gestation age at first antenatal visit was 19.1 years. Range 6 – 40 weeks of

gestation (www.ncbi.nlm.nih.gov/pubmed/20836323)

Study Design: A cross-sectional study of all pregnant women that booked at the antenatal clinic

at Shinyanga Municipal Council from 7th

March – 1st

April 2011 was undertaken to determine

the gestational age at booking. A structured questionnaire was administered by five AMO

students from Bugando AMO Training Collage whose was responsibility for this study as their

assignment for completion of their course. Other relevant information was retrieved from RCH4

card of the client. Inclusion criteria were those booked for antenatal care in ShinyangaMunicipal Council.

http://www.ncbi.nlm.nih.gov/pubmed/20836323






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Ethical consideration

The permit and clearance to conduct this research was obtained from principal of Assistant

Medical Officer (AMO) – Bugando – Mwanza, Regional Medical Officer (RMO) – Shinyanga,

District Medical Officer – Shinyanga Municipal Council, Dr I/C – Shinyanga Regional Hospital,

RCRCHC and I/C of RCH Shinyanga Hospital

Each respondent who participated was explained about the exercise and those who agreed to

participate are only who have interviewed. We appreciated the willingness of the respondent

who participated. Confidentiality during interview was adhered as during the whole procedure

each client was asked to take a seat at a point further from the public so that discussion should

not be noted or heard by somebody else. As with other medical procedures this was assumed

to reserve confidentiality between the respondent and interrogator. No names were written on

the questionnaire as part of confidentiality.

Sample size:

Shinyanga Municipal Council has a population of 210,609 by year 2011, with women in bearing age

35,588. Women giving birth is equal to 4% of total population, therefore 21,609 x 4% = 2424

8424/12months = 702

702 x 30% = 211

Therefore our sample size will be 211 clients.

Sampling Methods:

Sampling was done by random selection from 13 RCH clinics serving Shinyanga Municipal

Council by writing names of the clinics on piece of paper and tossing on the table. Randomly

we selected four clinics and come out with the following clinics, namely Shinyanga Regional

hospital, Ngokolo RC Dispensary, Kambarage Health Centre and Old Shinyanga dispensary.

Tools for data collection:

1. Structured questionnaire.

2. GPS

3. RCH card 4



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Source of data:

Data extracted from RCH Card 4 of all pregnant mothers attending at selected RCH clinics from 7th

March – 1st

April 2011 and other information asked directly from the mother. Four RCH clinics out of 13

which are rendering services in Shinyanga Municipal Council were selected by random sampling. The

selected RCH are Shinyanga Regional Hospital, Ngokolo RC Dispensary, Kambarage Health Centre andOld Shinyanga Dispensary.

Data collection:

Interviewer talking

with pregnant mothers

and collecting RCH

card 4



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Data handling and analysis: Data was organized, stored and manipulated using the following software: -

1. Microsoft access

2. SPSS

3. Epi Info

Data collectors: The second year AMO student for year 2011 as follow: -

1. Julius Majula

2. Felix Ntimba

3. Sally Sally

4. Chijo Matekere

5. Yusuph Kitunguye

Database design and data entry: Julius Majula (AMO II)

Map design: Julius Majula (AMO II)

Design of database

was done before

beginning of study,

and then data entry

was done every day to

minimize pile of

questionnaire and

make any correction if necessary.



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Analysis

Table 1: Statistical summary of age distribution.

Figure 1: Age distribution

0

5

10

15

20

25

30

35

40

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 42 45

Age Distribution

Age

Statistics

Age

Mean 25.08

Median 24.00

Mode 20

Std. Deviation 6.000

Variance 36.002

Range 30

Minimum 15

Maximum 45

Ages of pregnant mothers observed have a mean of 25.08

years.

Median 24 years

Mode 20 years

Range 30

Minimum age seen was 15 years and maximum of 45 years

The chart below shows pictorial age distribution, skewed to

right with extreme outlier – age 20.



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Figure 2: Age group distribution according to attendance up to 16 and above 16 weeks

It is recommended by Ministry of Health and Social Warfare a woman to become pregnant at

least at the age of 20 years. During our study period there were 44 pregnant mothers who have

aged below 20 (17%). Other risk age group was over 35 years, during our study period we

encountered 17 (7%) women. Unfortunately those women in old age they did not attend early

at RHC as you can see the above bar chart.

0

10

20

30

40

50

60

<16 16-20 21-25 26-30 31-35 36-40 41-45

Up to16 weeks

Over 16 weeks

Age Group

Age Group ditribution according to attendance

up to16 and above 16 weeks



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Table 2: Risk and non-risk age group

Age below 20 and over 35yrs 61 24%

Age between 20 - 35yrs 197 76%

Pie chart 1: Risk and non risk mothers according to age

Pie chart above shows risk age (age below 20 and above 35 years) combined which contributed

24% (61) of population study.

24%

76%

Age below 20 and over 35yrs

Age between 20 - 35yrs

Risk and non-risk mothers according to age



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Table 3: Level of education

Level of Education Up to 16 wks Over 16 wks Total % < 16 wks

None 8 21 29 28%

Primary School 57 109 166 34%

Secondary School 22 25 47 47%

Collage/University 8 8 16 50%

Figure 3: Effect of education on early pregnancy

Education has a big effect on early attendance. The above graph shows variation of attendance

according to level of education

8

57

22

8

21

109

25

8

0

20

40

60

80

100

120

Up to 16 wks

Over 16 wks

Effect of Education on Early Booking



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Table 4: Gestation Age

Statistics

Gestation age

N Valid 258

Missing 0

Mean 19.73

Std. Error of Mean .383

Median 20.00

Mode 20


Variance 37.840

Skewness .143

Std. Error of Skewness .152

Kurtosis -.363

Std. Error of Kurtosis .302

Range 34

Minimum 4

Maximum 38

Pie Chart 2: Early and late visit among pregnant mothers

HMIS data for year 2009 shows attendance before 20 weeks to be 45.99%. At projection of

6,871 pregnant women and attendance before 20 weeks were 3,160. Our study shows

attendance before 20 weeks to be 43%.

37%

63%

Gestation age up to 16wks

Gastataion age over 16wks

Early and Late visit

among pregnant

mothers in

Shinyanga Municipal

Council

Mother who attended at RCH

during study period has mean

gestation age of 19.73 weeks which

is a bit high for recommended

gestational age to make the first

visit which is below or at 16 weeks

Range is between 4 weeks up to 38

weeks. Out of 258 clients, mothers

who made their first visit at a

gestation age of 16 weeks or below

are 95 (36.8%)



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Table 6: Number of pregnancy in relation to booking before or after 16 weeks

ParityUp to 16

weeksAbove 16

weeksTotal % <16 wks GA

P135 52 87 40%

P227 36 63 43%

P311 25 36 31%

P49 17 26 35%

P57 13 20 35%

P65 6 11 45%

P71 7 8 13%

P80 3 3 0%

P90 2 2 0%

P110 2 2 0%

Figure 6:

The above graph shows number of pregnancy and behavior in first antenatal visit. It seems

women with few pregnancies tend to come early for first visit. As number of pregnancy

increases they become used and slow down gradually to zero visits before 16 weeks in 8th

pregnancy!

0

10

20

30

40

50

60

P1 P2 P3 P4 P5 P6 P7 P8 P9 P11

up 16 wks

Over 16 wks

Comparison between early and late booking

by number of pregnancy



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Table 7: Number of pregnancy among study population

Statistics

No of pregnancy

N Valid 258

Missing 0

Mean 2.76

Median 2.00

Mode 1


Range 10

Minimum 1

Maximum 11

Pie chart 3

Most of pregnant mothers seen at RCH clinic were primigravida, but the mean number of

pregnancies was 2.76 and median was 2 pregnancies. The range is 10 pregnancies which mean

the minimum was one pregnancy and maximum eleven.

82%

18%

Up to 4 pregnacies

Over 4 pregnacies



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Table 8: Factors contributing to early booking

Frequency Percent Valid Percent

Cumulative

Percent

Valid Knowledgeable 55 21.3 58.5 58.5

Counseled 18 7.0 19.1 77.7

Obstetric/Medical condition 21 8.1 22.3 100.0

Total 94 36.4 100.0

Missing System 164 63.6

Total 258 100.0

Pie Chart 4

The above pie chart shows reasons why they make their first visit before 16 weeks of gestation

age. Many responded to be knowledgeable followed by obstetrical or medical condition during

pregnancy. The least was cancelled either by parents or friends.

5518

21

Knowledgeble Councelled Obstetric/Medical condition

Factors which make Pregnanct mothers

to book before 16 weeks



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Table 9: Factors contributed to late booking over 16 weeks

Frequency PercentValid

PercentCumulative

Percent

Valid Client not informed 58 22.4 35.6 35.6

Ignorance 69 26.6 42.3 77.9

Poor infrastructure 3 1.2 1.8 79.8

Unwanted/Unplanned pregnancy 10 3.9 6.1 85.9

Others 20 7.7 12.3 98.2

Wait for pregnancy to grow 2 .8 1.2 99.4

Was on contraceptive 1 .4 .6 100.0

Total 163 62.9 100.0

Missing System 96 37.1

Total 259 100.0

Pie Chart 5

Factors which contributed to late booking (Over 16 weeks) was ignorance which contributed

26.6% followed by client not informed on the importance of coming early.

58

69

3

10 20

2 1Client not informed

Ignorancy

Poor infrastructure

Unwanted/Unplanned pregnancy

Others

Wait for pregnancy to grow

Was on contraceptive



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Table 10: No of pregnancy and first attendance in trimester

Trimester

Total1.00 2.00 3.00

NoOfPreg 1 16 61 10 87

2 14 41 8 63

3 6 20 10 36

4 5 14 7 26

5 4 13 3 20

6 2 8 1 11

7 1 3 4 8

8 0 3 0 3

9 0 1 1 2

11 0 1 1 2

Total 48 165 45 258

Mothers in their first pregnancy tend to come early in their first trimester than those who are

multi-gravida. This behavior decline as pregnancy increases.

0

10

20

30

40

50

60

70

P1 P2 P3 P4 P5 P6 P7 P8 P9 P11

1st Trimester

2nd Trimester

3rd Trimester

Number of pregnancy



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RESULTS

1. Pregnant mothers enrolled in our study had mean age of 25.08 while median is 20.

Mode is 20 and range of 30 with minimum of 15 and maximum of 45.

2. Pregnancy below 20 years contributed 44 (17%) and over 35 contributed 17 (7%), which

is not recommended by MOH&SW. Unfortunately those in old age they did not attendearl at RCH.

3. Mean gestational age are 19.73 weeks which is more than 3.73 week of recommended

gestational age to report at RCH. HMIS data of 2009 showed women who attended

below 20 weeks contributed 45.99%. The same gestational age group below 20 weeks)

in our study contributed 43%

4. Only 95 (36.8%) out of 258 pregnant mothers who managed to come before or at 16

weeks

5. It was observed that grand multiparity tend to book late. Some have made first visit at

38 weeks in 7th

pregnancy!

6. 18% of 258 mother have more than four pregnancies which is not recommended by

MOH&SW

7. There was early booking visit among observed population which contributed to 37%.

This was due to :

a. Knowledgeable of the clients - 21.3%

b. Counseled by relatives/friends - 7%

c. Obstetric/Medical conditions - 8.2%

8. Education has a big impact on early attendance. The more women become educated

the earlier she comes for first visit. The following is level of education and attendance

before 16 weeks: -

a. None - 29%

b. Primary school - 34%c. Secondary school - 48%

d. Collage/University - 50%

Therefore we thought that if secondary school for each ward will improve, we expect

pregnant mothers will increase the number of early visit attendance.

9. Factors contributing to late booking most of them are ignorance, client not informed

and unwanted pregnancy.

10. There is a good customer care because no any client blamed about health services or

health provider.



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LIMITATION

1. Time limited – The time allocated for research was four weeks, not enough for data

collection

2. Late supervision – Our supervisor came just two days before we wind up the research

period.3. No any financial support from the collage and even to other employers

4. There was poor communication between the collage and Shinyanga RMO’s office.

DISCUSION

Comparison between our study and the one done at University of Lagos.

Our study University of Lagos

Mean age 25.08 +/-6.00 30.5 +/-4.5Range 15 - 45 18 – 46

Mean gestation age at 1st

visit 19.73 +/- 6.151 19.1 +/- 7.8

Booking according to trimester

First trimester 48 (19%) 317 (27%)

Second trimester 165 (64%) 647 (55.2%)

Third trimester 43 (17%) 70 (6%)

Over 36 weeks 2 (1%) 3 (0.3%)

Education/Class Majority belong to

secondary school

and higher

Majority belong to

class 1

As statistics shows in comparison with other study, it shows women at Shinyanga

Municipal Council are becoming pregnant at early age (15years) compared with

those in Lagos who become pregnant at 18 years.

Also the mean age is low (25.08) with standard deviation of 6 compared with

30.5 and standard deviation of 4.5

Majority in our study population are coming in second trimester, and this looks

to have same picture as of Lagos. But in Shinyanga the number is a bit higher.

We use education level to categorize social status while in Lagos they use

classes. In our study we have seen that the more women become educated the

more they come earlier for the first time visit at RCH clinics.



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CONCLUSION

Extensive health education has benefit of antenatal care and the need for early

booking in 1st

trimester is advocated. Use of multimedia such as radio, TV, DVD

and CD to reach different cadre of society, meeting, drummer etc.Health education on delay sexual intercourse for girls to avoid early pregnancy as

shown in the study the minimum age was 15years.

Education to women will reduce early pregnancy and those who get pregnancy

in appropriate age will seek antenatal services earlier.

Advocate Family planning in the community in order to reduce early and grand

multiparity pregnancies. We encountered 2 (1%) pregnant mothers in their 11th

pregnancy!

RECOMMENDATION

1. Provision of health education on early booking

2. Use of impersonal methods of communication such as radio, TV and video,

village meetings, drummer, clinics etc.

3. Strengthen on continuous health education

4. Increase enrollments of children to join primary school.

REFFERECE

1. Study conducted at Collage of Medicine; University of Lagos

(www.ncbi.nlm.nih.gov/pubmed/20836323)

2. HMIS data 2009

3. RCH card 4 – From MOH&SW







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Annex I

Questionnaire on Factors affect booking at particular gestational age at RCH –

Shinyanga Regional Hospital – Group E

1. RCH card ID ____

2. RCH Clinic Name 1. Shinyanga RH

3. Sex Female

4. Age _____

5. Religion 1. Christian 2. Moslem 3. Pagan

6. Tribe 1. Msukuma 2. Mkerewe 3. Mjita 4. Mhaya 5. Mkurya 6. Jaluo 8. Others __________

7. Address (Street) ___________________________________________________

8. Ward 1. Ibadakuli 2. Chamakuha 3. Kitangili 4. Kizumbi 5. Ibinzamata 6. Ndala 7. Shy Urban

8. Ngokolo 9. Kambarage 10. Mwamashili

9. Occupation 1. Gov. Employee 2. Business 3.Farmer 4. Private employee 5. Others __________

10. Level of Education 1.None 2. Primary 3 Secondary. 4.Collage/University

11. Marital status 1. Single 2. Married 3. Cohabitant 4. Widowed

12. Distance in km from home to RCH clinic ________

13. No of pregnancies _______

14. No alive children ________

15. No of died children ________

16. Any abortion 1. Yes 2. No

17. If any abortion = Yes; How many? _______

18. Gestational age at 1st

attendance ___________ (Look at RCH4)

19. If gestation age booked at or before 16 weeks, what contributed for early booking

1. Knowledgeable 2. Counseled 3. Medical/obstetric condition

20. If gestation booked more than 16 weeks, what contributed for late booking

1.Pt not informed 2. Ignorance 3. Poor infrastructure 4. Poor customer care of H/provider 5.

Unwanted pregnancy 6. Others ___________________________



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ANNEX II

TIME TABLE FOR REASEARCH - GROUP E

DATE TIME ACTIVITYRESPONSIBLEPERSON

06-Mar-11 9am Travel to Shinyanga All researchers

07-Mar-11 8.00 am

Reporting to all authorities (RMO -

Shinyanga RMO + researchers

8.30 am Dr I/C Shinyanga Regional Hospital Dr I/C + researchers

9.00 am RRCHC RRCHC + researchers

9.30 am RCH Incharge Shinyanga hospital RCH I/C + researchers

10.00 am Start to work at Shinyanga RH - RCH

All researchers +

Clients

8 Mar-1 Apr 7.30 am Morning conference All researchers

8.30 am Break fast All researchers

9.00 am

Data collection in RCH clinics (Shinyanga

RH, Ngokolo Disp, Kambarage HC and

Old Shinyanga Dispensary

All researchers +

Clients

2pm Lunch time

4.00 pm Data entry All researchers

2 - Apr - 11 9.00 am Travel to Mwanza (BMC) All researchers

4 - 9- Apr-11 Data cleaning and analysis All researchers

11-Apr-11 Data presentation

All researchers +

Facilitators



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ANNEX III

BUDGET FOR RESEARCH - GROUP E

SN DESCRIPTION UNIT NO PRICE TOTAL

1 Per diem Each 5 45000 6,300,000.00

2 Traveling Mz-Shy_MZ Each 5 10000 50,000.00

3 Stationary Each 5 100000 500,000.00

GRAND TOTAL 6,850,000.00



Research team – Group E

research on factors affect booking at particular gestational age in shinyanga municipal council

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