Introduction

The report is based on the overall objective of investigating the timely utilisation of antenatal care services by the women of reproductive age group across the socio demographic variables and husband/partner characteristics. The health of the future generations is greatly dependent on the growth and development of the baby in the mother’s womb. The success of the foetal life determines the health of the newborn and also majorly impacts the health and disease risk of the adult (EBCOG Scientific Committee, 2015). The antenatal healthcare is defined as the care from the health professions during pregnancy and is thereby also known as pregnancy and maternity care. It involves appointments with the midwife or sometimes a doctor who is specialised in pregnancy and childbirth, that is obstetrician. The antenatal care potentially links the pregnant women and their family with the formal health system and thereby increases the accessibility to skilled attendants and also reduces the chance of mortality and other health consequences associated with pregnancy and delivery. It also plays a vital role in promoting good health of the women throughout their life. The lack of proper care utilisation breaks this link and affects both the pregnant women and the babies and this thereby depicts its public health importance (World Health Organization, 2016). The current antenatal care focuses on medical risks and needs to be evolved for including non medical factors and for reaching out to all parts of the community. There are large disparities that exist in countries as well as within nations, cities and population groups in this form of care. Thus, it is needed to enhance the awareness among the professionals to address both the medical and social issues such as social deprivation and domestic violence to enhance the utilisation of antenatal care services (EBCOG Scientific Committee, 2015). The socio demographic variables potentially influence the utilisation of antenatal care. The financial status of the households potentially determines the early initiation of antenatal care. The utilisation of antenatal care also depends on rural and urban living. The early initiation of utilisation of antenatal care depends on age, educational level and wealth index. The women with higher wealth and educational level are more likely to access the care (Ng’ambi et al., 2022). The husband/partner characteristics such as husband’s education and marital status determines their involvement and thereby impacts the utilisation of antenatal care. Both the variables that are socio demographic and husband/partner’s characteristics are potentially linked to each other. The educational level of the husband/partner potentially determines the income level which further demonstrates their involvement and determines the utilisation of antenatal care by the women. Moreover, the marital status of the women also determines the partner’s involvement and accessibility of antenatal care by the pregnant women (Mohammed et al., 2020). All these thereby demonstrate the relationship of the variables of interest that are the socio demographic and husband/partner’s characteristics. This particular analysis in this report will help in investigating the timely utilisation of antenatal care by the women who are at their reproductive age by relating it to their socio demographic characteristics and husband’s/partner’s characteristics. This will thereby help in understanding the impact of these different variables on the proper utilisation of care and health status of women in their reproductive age.

According to Nababan et al. (2018), the inequity in the utilisation of maternal healthcare services varies on the basis of education, urban rural location, region and religion. The trend depends on the difference between the financial status such as rich and poor. The women who are rich are 5.45 times more likely to access the antenatal care services. The urban women are also more likely to use these services by about 3 times more than the rural women (Nababan et al., 2018). Sakeah et al. (2017) conducted the cross sectional study and stated that having a partner with a high educational level is positively associated with the utilisation of antenatal care. Marital status is also associated with the attendance in antenatal care. It was further stated that the youngest, poorest and least educated women and the women with the uneducated partners are less likely to attend the antenatal services (Sakeah et al., 2017). Afaya et al. (2020) stated that the awareness and further education of the reproductive age women potentially enhances their knowledge regarding the importance of antenatal care and this further plays a significant role in enhancing their attendance in the antenatal care (Afaya et al., 2020). According to Tello Torres et al. (2021), the women in the age groups of 20 to 34 years and 35 to 49 years and having higher education and belonging to wealthy quintiles show increased compliance with antenatal care (Tello Torres et al., 2021). The study of Yaya et al. (2019) stated that the intersecting areas of gender status and socioeconomic status potentially determines the access to proper care. It was further mentioned that the economic marginalisation and financial dependency of the women on their partner for the pregnancy healthcare costs potentially determines the utilisation of care. The financial status of men and the workload during pregnancy also determines the barrier to access antenatal care (Yaya et al., 2019). As per the findings of Sarfraz et al. (2016), the social barriers, financial constraints and non acceptability of the community midwives potentially affects the utilisation of the antenatal care (Sarfraz et al., 2016). From the survey conducted by Andriani et al. (2021), it can be stated that the continuity of the utilisation of services is potentially associated with age, reproductive status, family influence and accessibility related factors. It is also important to enhance the reproductive health education of both men and women for enhancing the utilisation (Andriani et al., 2021). Kabir et al. (2021) potentially presented a different aspect that stated the impact of intimate partner violence on the accessibility and timely utilisation of antenatal care services. The study also stated that the advanced education of women potentially increases the attendance of antenatal care whereas the women residing with alcoholic partners are more likely to experience partner abuse which further negatively impacts the utilisation of antenatal care (Kabir et al., 2021).

Methods

Research Philosophy

The research philosophy depicts the belief of the researcher regarding the way through which the data is gathered, analysed and used. It deals with the source and nature of data of the research (Kumar, 2018). In this meta analysis study that uses the statistical process, the researcher is going to use the positivism philosophy as the study adhered to only factual data that are gained from proper authenticated sources. This particular philosophy is potentially associated with quantitative methods that are used in this research report. The interpretivism philosophy is not used as the research is not going to involve qualitative data, that is, it is not associated with subjectivist views. The pragmatism philosophy applied to research that uses both qualitative and quantitative data, that is, mixed methodology and thus it is also not chosen by the researcher. Realism is not selected as the research is not independent from the reality of human minds (Alharahsheh and Pius, 2020). 

Research Approach

The research approach is defined as the procedure that is selected by the researcher for collecting and analysing data to interpret the results. For this particular research, the researcher opted for the deductive approach that involves application of theory to the data for testing the same. It thereby involves making inferences from general to specific conclusions. The inductive research approach is not opted by the researcher as it focuses on searching patterns from observations to develop theories and this particular research does not focus on doing this. The abductive research approach is also not suitable as the research does not focus on making observations and seeking any hypothesis that would fit those observations (Bairagi and Munot, 2019).

Research Design

The research design is defined as the framework of the research methods and techniques that the researcher’s choose to conduct the research study. This particular research implements exploratory design as it enables the researcher to investigate the problem related to the utilisation of antenatal care in accordance with the sociodemographic variables and partner’s/ husband’s characteristics that have not been clearly defined before. It thereby helps in providing a better understanding of the problem. The explanatory research design is not chosen as the research method as it focuses on exploring the reason behind the problem where limited information is available. The descriptive research design is also not chosen as it focuses on obtaining information for systematically describing the phenomenon or the situation which is not the case for this research (Sileyew, 2019).

Data Collection

Data collection is defined as the process of gathering accurate data from various sources to accomplish and address the research objective. Among the two types of data collection, primary and secondary, the researcher has chosen secondary data collection that involves collecting data from already existing sources (Rinjit, 2020). In this research, the researcher collects secondary quantitative data as the dataset from SADHS Women Data. The primary data collection is not chosen by the researcher as the research has not involved any human participants and has not collected data in a first hand manner.

Data Analysis

Secondary quantitative data has been gathered from “SADHS Women Data” from DHS Program website. It was extracted from extracted from South Africa Demographic and Health Survey (SADHS) 2016. The survey was conducted as a collaboration between Statistics South Africa (Stats SA) and the South African Medical Research Council (SAMRC) with technical support from ICF through The DHS Program of the United States Agency for International Development (USAID). It provides different quantitative data presentation about the characteristics of men and their wife who need the antenatal care service at their reproductive age. The utilisation of secondary quantitative data has helped in the overall growth and development of the research process by showing significant understanding of the research. Important data related to “antenatal care”, husband/ partner characteristics of the wives who are aiming to gain antenatal care services has collected from SADHS Women Data. These data have bee collected to conduct statistical analysis with the us of MS excel. Regression, correlation test have been done to text the hypothesis and related to the use of drugs, alcohols and the rate of education significantly affect the traits of domestic violence among husband or partners of women who are in higher need of antenatal care at their reproductive age.

Ethical Considerations

In order to retain the reliability and authenticity of the research has been maintained along with the privacy and security of the collected information. The information has been collected with the maintenance of data protection act regulation which is helpful to maintain the authenticity and reliability of the gathered data considering its impact on the society.

Results

Descriptive Analysis

Doctor

 

Nurse/Midwife

 

Community health worker

 

Traditional birth attendant

 

Other

 

Percentage of receiving antenatal care

 

Number of women

 

                           

Mean

16.65

Mean

77.145

Mean

0.6

Mean

0

Mean

0.01

Mean

93.79

Mean

758.95

Standard Error

2.711122316

Standard Error

2.72318

Standard Error

0.12161198

Standard Error

0

Standard Error

0.01

Standard Error

0.357984

Standard Error

139.9367

Median

15.05

Median

79.55

Median

0.6

Median

0

Median

0

Median

93.6

Median

603.5

Mode

#N/A

Mode

#N/A

Mode

0.6

Mode

0

Mode

0

Mode

93.5

Mode

#N/A

Standard Deviation

12.12450759

Standard Deviation

12.17843

Standard Deviation

0.543865308

Standard Deviation

0

Standard Deviation

0.044721

Standard Deviation

1.600954

Standard Deviation

625.8161

Sample Variance

147.0036842

Sample Variance

148.3142

Sample Variance

0.295789474

Sample Variance

0

Sample Variance

0.002

Sample Variance

2.563053

Sample Variance

391645.8

Kurtosis

3.424135885

Kurtosis

2.903534

Kurtosis

7.650819553

Kurtosis

#DIV/0!

Kurtosis

20

Kurtosis

0.47467

Kurtosis

0.200482

Skewness

1.768362424

Skewness

1.54192

Skewness

2.240018018

Skewness

#DIV/0!

Skewness

4.472136

Skewness

0.119386

Skewness

1.000937

Range

50.1

Range

51.5

Range

2.5

Range

0

Range

0.2

Range

6.9

Range

2158

Minimum

1.2

Minimum

44.6

Minimum

0

Minimum

0

Minimum

0

Minimum

90.4

Minimum

42

Maximum

51.3

Maximum

96.1

Maximum

2.5

Maximum

0

Maximum

0.2

Maximum

97.3

Maximum

2200

Sum

333

Sum

1542.9

Sum

12

Sum

0

Sum

0.2

Sum

1875.8

Sum

15179

Count

20

Count

20

Count

20

Count

20

Count

20

Count

20

Count

20

Confidence Level(95.0%)

5.674444221

Confidence Level(95.0%)

5.699681

Confidence Level(95.0%)

0.254536799

Confidence Level(95.0%)

0

Confidence Level(95.0%)

0.02093

Confidence Level(95.0%)

0.749269

Confidence Level(95.0%)

292.891

 

Table 1: Descriptive Statistics

The above table suggested that the antenatal care provider’s demographic characteristics. Women in their antenatal care gains the required car facilities from Doctor, nurse or Midwife, community health worker, traditional birth attendant and others. Highest mean value is found to be 77.145 which suggest that the results are relevant in terms of showing the relationship between antenatal care provider’s statistics.

T test Drug users and no drug users’ husband/partners

 

     

t Test: Paired Two Sample for Means

   
     

 

Drug not used

Often uses drugs

Mean

10.31428571

47.98571429

Variance

51.3247619

647.5280952

Observations

7

7

Pearson Correlation

0.981538052

 

Hypothesized Mean Difference

0

 

df

6

 

t Stat

5.39755732

 

P(T<=t) one tail

0.000833865

 

t Critical one tail

1.943180281

 

P(T<=t) two tail

0.00166773

 

t Critical two tail

2.446911851

 

 

Table 2: T test Drug users and no drug users’ husband/partners

The above table showcases the t test between “drug taker husbands/partners” and those who does take drugs. The hypothesized mean difference shows the value of 0. It shows that the husband’s /partners of wives are more drug users than less drug users are tending to become more emotional, physical and sexual violator over their partners wives which increases their necessity towards antenatal care.

T test Less education and higher educated husband/partners

     

t Test: Paired Two Sample for Means

   
     

 

Variable 1

Variable 2

Mean

10.38571429

3.842857143

Variance

57.84142857

15.32952381

Observations

7

7

Pearson Correlation

0.977785542

 

Hypothesized Mean Difference

0

 

df

6

 

t Stat

4.478659862

 

P(T<=t) one tail

0.0020992

 

t Critical one tail

1.943180281

 

P(T<=t) two tail

0.0041984

 

t Critical two tail

2.446911851

 

 

Table 3: T test Less education and higher educated husband/partners

The above table showcases the t test between “no education” and “more than secondary education” have shown the corelated relationship. The hypothesized mean difference shows the value of 0. It shows that the husband’s /partners of wives’ who does not have required education are tends to become more emotional, physical and sexual violator over their partners wives which increases their necessity towards antenatal care.

T test Alcoholic and non alcoholic husband/partners

     

t Test: Paired Two Sample for Means

   
     

 

Variable 1

Variable 2

Mean

274.85

78.1125

Variance

576541.9457

12824.76696

Observations

8

8

Pearson Correlation

0.985324046

 

Hypothesized Mean Difference

0

 

df

7

 

t Stat

0.858721063

 

P(T<=t) one tail

0.209462702

 

t Critical one tail

1.894578605

 

P(T<=t) two tail

0.418925404

 

t Critical two tail

2.364624252

 

 

Table 4: T test Alcoholic and non alcoholic husband/partners

The above table showcases the t test between “non alcoholic husband/partners” and “alcoholic husband/partners” have shown the corelated relationship. The hypothesized mean difference shows the value of 0. It shows that the husband’s /partners of wives’ who are alcoholic are tends to become more emotional, physical and sexual violator over their partners wives which increases their necessity towards antenatal care.

Regression

SUMMARY OUTPUT

               
                 

Regression Statistics

             

Multiple R

0.349731128

             

R Square

0.122311862

             

Adjusted R Square

0.097110172

             

Standard Error

0.882994694

             

Observations

6

             
                 

ANOVA

               

 

df

SS

MS

F

Significance F

     

Regression

1

0.434614817

0.434614817

0.557427

0.496791

     

Residual

4

3.118718516

0.779679629

         

Total

5

3.553333333

 

 

 

     
                 

 

Coefficients

Standard Error

t Stat

P value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

93.23105345

1.007333172

92.55235117

8.17E 08

90.43425

96.02786

90.43425

96.02786

physical violence

0.058442154

0.078276616

0.746610633

0.496791

0.15889

0.275773

0.15889

0.275773

 

 

Literacy

Physical violation

Emotional Violence

Percentage receiving antenatal care

Literacy

1

     

Physical violation

0.442322548

1

   

Emotional Violence

0.580399794

0.349731128

1

 

Percentage receiving antenatal care

0.503085502

0.519908187

0.891888793

1

         

Table 5: Regression

From the above table the dependent value is “Literacy” of husband/partners and the intendent value is “physical violence”. The r square value of 0.122 suggested that less education of partners leads to increasing violation of women which increases their requirement for antenatal services.

Discussion

It has been found from the data analysis that in the antenatal care process for women who are required antenatal care there are different antenatal care providers such as Doctor community health workers, traditional birth attendant, nurse or mid wife, and others. These service provisions are highly important in terms of developing their reproductive care facility at the time of pregnancy. Sarfraz et al. (2016) stated that the trend depends on the difference between the financial status such as rich and poor. It was further stated that the youngest, poorest and least educated women and the women with the uneducated partners are less likely to attend the antenatal services. Similarly, the economic marginalisation and financial dependency of the women on their partner for the pregnancy healthcare costs potentially determines the utilisation of care. The continuity of the utilisation of services is potentially associated with age, reproductive status, family influence and accessibility related factors. Thus, it shows that the antenatal care potentially links the pregnant women and their family with the formal health system and thereby increases the accessibility to skilled attendants and also reduces the chance of mortality and other health consequences associated with pregnancy and delivery.

It is also important to enhance the reproductive health education of both men and women for enhancing the utilisation. Kabir et al. (2021) suggested that the impact of intimate partner violence on the accessibility and timely utilisation of antenatal care services. The study also stated that the advanced education of women potentially increases the attendance of antenatal care whereas the women residing with alcoholic partners are more likely to experience partner abuse which further negatively impacts the utilisation of antenatal care. It has been understood that on the promotion of antenatal care the traits associated to literacy rate of husbands or partners pf the women involved in the antenatal care services provided an effect on the traits of emotional and physical violence on women. It suggests that the women who suffered from domestic violence are in higher need of antenatal care.

The strength of this research is that the present research successfully shows significant utilisation of antenatal care services for women reproductive age group with the evaluation of their socio demographic variables and by their husband or partner characteristics. These are highly necessary through which interrelation between these variables have been accomplished. On the other hand, the weakness of this research is that it does not address current challenges of antenatal care services provided for women. In addition, the roles of antenatal care providers have also not been analysed in this research.

References

Afaya, A., Azongo, T.B., Dzomeku, V.M., Afaya, R.A., Salia, S.M., Adatara, P., Kaba Alhassan, R., Amponsah, A.K., Atakro, C.A., Adadem, D. and Asiedu, E.O., (2020). Women’s knowledge and its associated factors regarding optimum utilisation of antenatal care in rural Ghana: A cross sectional study. Plos one, 15(7), p.e0234575.

Alharahsheh, H.H. and Pius, A., (2020). A review of key paradigms: Positivism VS interpretivism. Global Academic Journal of Humanities and Social Sciences, 2(3), pp.39 43.

Andriani, H., Rachmadani, S.D., Natasha, V. and Saptari, A., (2021). Continuity of maternal healthcare services utilisation in Indonesia: analysis of determinants from the Indonesia Demographic and Health Survey. Family Medicine and Community Health, 9(4).

Bairagi, V. and Munot, M.V. eds., (2019). Research methodology: A practical and scientific approach. CRC Press.

EBCOG Scientific Committee, (2015). The public health importance of antenatal care. Facts, views & vision in ObGyn, 7(1), p.5.

Kabir, R., Chakraborty, R., Vinnakota, D. and Siddika, N., (2021). Intimate partner violence constrains timely utilisation of antenatal care services among Armenian women: Results from a nationally representative sample. International journal of critical illness and injury science, 11(4), p.209.

Kumar, R., (2018). Research methodology: A step by step guide for beginners. Sage.

Mohammed, S., Yakubu, I. and Awal, I., (2020). Sociodemographic factors associated with women’s perspectives on male involvement in antenatal care, labour, and childbirth. Journal of pregnancy, 2020.

Nababan, H.Y., Hasan, M., Marthias, T., Dhital, R., Rahman, A. and Anwar, I., (2018). Trends and inequities in use of maternal health care services in Indonesia, 1986–2012. International journal of womens health, 10, p.11.

Ng’ambi, W.F., Collins, J.H., Colbourn, T., Mangal, T., Phillips, A., Kachale, F., Mfutso Bengo, J., Revill, P. and Hallett, T.B., (2022). Socio demographic factors associated with early antenatal care visits among pregnant women in Malawi: 2004–2016. PloS one, 17(2), p.e0263650.

Rinjit, K., (2020). Research methodology.

Sakeah, E., Okawa, S., Rexford Oduro, A., Shibanuma, A., Ansah, E., Kikuchi, K., Gyapong, M., Owusu Agyei, S., Williams, J., Debpuur, C. and Yeji, F., (2017). Determinants of attending antenatal care at least four times in rural Ghana: analysis of a cross sectional survey. Global health action, 10(1), p.1291879.

Sarfraz, M., Tariq, S., Hamid, S. and Iqbal, N., (2016). Social and societal barriers in utilization of maternal health care services in rural Punjab, Pakistan. Journal of Ayub Medical College Abbottabad, 27(4), pp.843 849.

Sileyew, K.J., (2019). Research design and methodology (pp. 1 12). Rijeka: IntechOpen.

Tello Torres, C., Hernández Vásquez, A., Dongo, K.F., Vargas Fernández, R. and Bendezu Quispe, G., (2021). Prevalence and Determinants of Adequate Compliance with Antenatal Care in Peru. Revista Brasileira de Ginecologia e Obstetrícia, 43, pp.442 451.

World Health Organization, (2016). WHO recommendations on antenatal care for a positive pregnancy experience. World Health Organization.

Yaya, S., Okonofua, F., Ntoimo, L., Udenige, O. and Bishwajit, G., (2019). Gender inequity as a barrier to women’s access to skilled pregnancy care in rural Nigeria: a qualitative study. International health, 11(6), pp.551 560.

Appendices

Women demographic characteristics

Age

Doctor

Nurse_or_Mid_wife

Community_health_worker

Traditional_Birth _attendant

Other

Percentage_receiving_antenatal_care_from_skilled_provider

Number_of_women

<20

7

87.7

0.7

0

0

94.7

432

20 34

18

75.5

0.6

0

0

93.5

2200

35 49

22.5

70.9

0.5

0

0.2

93.4

404

Birth Order

             

1

16

79

0.5

0

0

95

1040

2 to 3

18.7

74.1

0.7

0

0

92.8

1586

4 to 5

14.1

80.1

0

0

0

94.2

326

6+

10.6

80.9

2.5

0

0

91.5

84

Residence

             

Urban

20.1

72.4

0.8

0

0

92.4

1942

Non urban

11.8

84.1

0.2

0

0

95.9

1094

Education

             

No education

1.2

96.1

0

0

0

97.3

42

Primary incomplete

8

85.7

0

0

0

93.7

141

Primary complete

8.1

82.3

1

0

0

90.4

108

Secondary incomplete

9.8

83.6

0.8

0

0

93.4

1486

Secondary complete

18.9

74.6

0.5

0

0

93.5

908

More than secondary

51.3

44.6

0.2

0

0

95.8

351

Wealth

             

Lowest

6.9

86.7

0.2

0

0

93.7

650

Second

7.8

85.1

1

0

0

92.8

739

Middle

16.2

77.9

0.6

0

0

94.1

671

Fourth

22.2

73.1

0.6

0

0

95.3

557

Highest

43.8

48.5

0.6

0

0

92.4

418

Husband characteristics

age

Literacy

Number of men

Internet use

Employment status

Married

HIV test

20 24

94.1

588

981

588

7.2

38.5

25 29

95.6

506

312

506

25

28.7

30 34

94.7

450

225

450

48.6

49.3

35 39

95

395

184

395

53.6

52.8

40 44

91.9

348

100

345

62.4

48

45 49

93.8

271

91

271

63.6

45.3

 

Background characteristic

 

 

 

 

Physical and sexual and emotional

 

Physical or sexual or emotional

Number of ever in union women

Emotional violence

Physical violence

Sexual violence

Physical and sexual

Physical or sexual

Husband’s/partner’s education

 

 

 

 

 

 

 

 

No education

17.3

13.5

3

2.5

2.3

14

20.1

244

Primary incomplete

16.9

16.4

2.3

2.3

2.1

16.4

22.7

276

Primary complete

8.8

10.3

0.9

0.5

0.5

10.8

14.8

107

Secondary incomplete

16.9

18.1

6.1

4.7

3.8

19.5

25

866

Secondary complete

10.2

9.5

2.5

0.8

0.8

11.3

15.7

622

More than secondary

7.9

4.3

0.3

0.1

0.1

4.5

9.7

395

Don’t know

13.3

19.6

5.2

4.5

4

20.3

24.7

72

Husband’s/partner’s alcohol consumption

               

Does not drink alcohol

               
 

9.1

8.3

2.2

1.5

1.4

9.1

13.2

2,154

Drinks alcohol but is never drunk

               

13.9

3.1

0

0

0

3.1

13.9

37

Is sometimes drunk

16.7

16.5

4.4

2.9

2.6

17.9

24.7

1,072

Is often drunk

45.9

53.8

20

17.3

12.4

56.6

64.9

354

Don’t know

0

0

0

0

0

0

0

5

Husband’s/partner’s drug usage

               

Does not use drugs

13.9

13.9

4

2.8

2.3

15

20.3

 

Sometimes uses drugs

21.1

23.9

9.3

9.3

3.7

23.9

29.8

3,502

Often uses drugs

58.5

68.1

23.9

23.2

17.2

68.9

76.1

42

Don’t know

77

66.3

44.1

40.1

40.1

70.3

82

53

Spousal education difference

             

24

Husband better educated

12.7

12.6

2.9

2.1

1.9

13.5

18.1

 
                               

Wife better educated

14.7

16.2

4.3

3.4

2.5

17.1

22

783

Both equally educated

12.1

9.1

2.6

1.3

1.2

10.5

16.5

858

Neither educated

19

13.6

3.9

3.6

3.6

13.8

22.6

755

Don’t know

13.3

19.6

5.2

4.5

4

20.3

24.7

116

Spousal age difference

             

72

Wife older

12

16.5

3.4

3.1

3.1

16.7

19.2

 

Wife is same age

14

18.2

3.3

1.6

0.2

19.8

24.1

 

294

 

Wife 1 4 years younger

13

12.5

3.7

2.7

2.1

13.6

19

 

168

 

Wife 5 9 years younger

12

10

3

1.4

1.3

11.6

16.9

 

934

 

Wife 10 or more years

               

729

 

younger

17

14.8

3.6

3.3

3.2

15.1

22

     

Number of marital control behaviours displayed by husband/ partner

               

456

 

0

3.8

4.4

1.1

0.5

0.3

5

6.8

     

1 to 2

16

17.8

2.4

1.6

1.4

18.7

25.5

 

2,001

 

3 to 4

44

39

14.9

11

8.6

42.9

58.1

 

993

 

5

67

64.9

32.7

31.4

26.4

66.2

77.9

 

477

 

Number of decisions in which women participate

               

151

 

0

7.1

7.4

0

0

0

7.4

8.4

     

1 to 2

21

20.4

7.3

6.5

3.2

21.2

29.4

 

46

 

3

12

12.9

3.2

1.9

1.8

14.2

19.3

 

174

 
                               

1,589

 

 

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