0.899

0.997

(0.664 - 4.453)

(0.880 - 14.63)

(0.851 - 1.389)

(1.024 - 1.894)

(0.590 - 1.371)

(0.609 - 1.634)

Observations

3517

3531

22305

22305

4315

4315

Notes_Titles ciEform in parentheses; *** p<0.001, ** p<0.01, * p<0.05

From the Table above, the (unadjusted) Odds ratios reveal that acceptance of IPV as justified for any reason is a consistent factor exposing women that can be associated with its actual experience across countries. In each countries, women who justify IPV for any reason were also more likely to have experienced IPV. This relationship is significant at p. value <0.05 in all countries. However, there are three possible objections to reaching an hasty conclusions here. First this study does not claim causality. Second, women might begin to justify IPV only after several experience of IPV (see the normalization theory in Okenwa-Emegwa, L., Lawoko, S., & Jansson, B. (2016). Finally, the table is a product of single binary logistic regression. Other factors need to be controlled for to ascertain the consistency in statistics. This is done and result is presented in the table below.

Table 4.6: Reporting adjusted Odds ratios (aORs).

Regression analysis result: Reporting adjusted odds ratios (aORs) of factors exposing women to IPV across three African countries
DEPENDENT VAR.==>	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV
Attitude towards IPV	(aORs)	(aORs)	(aORs)	(aORs)	(aORs)	(aORs)
Never justified	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
IPVAW somewhar justified	1.868**	3.559***	1.501***	1.377**	0.825	1.409
	(1.255 - 2.781)	(1.900 - 6.664)	(1.286 - 1.753)	(1.127 - 1.682)	(0.526 - 1.294)	(0.894 - 2.221)
Yes IPVAW very justified	2.113**	3.556**	1.272**	1.461***	0.845	1.051
	(1.317 - 3.388)	(1.626 - 7.773)	(1.076 - 1.502)	(1.191 - 1.791)	(0.548 - 1.303)	(0.668 - 1.654)
DK/Missing	8.951***	4.256	0.817	1.188	0.539	0.695
	(2.909 - 27.54)	(0.433 - 41.82)	(0.543 - 1.230)	(0.752 - 1.874)	(0.288 - 1.008)	(0.276 - 1.750)
Constant	0.102***	0.0117***	0.0772***	0.0255***	0.219***	0.0817***
	(0.0686 - 0.151)	(0.00556 - 0.0244)	(0.0663 - 0.0899)	(0.0201 - 0.0324)	(0.145 - 0.331)	(0.0456 - 0.146)
Observations	1,752	1,755	13,758	13,758	1,528	1,528
	Notes_Titles ciEform in parentheses; *** p<0.001, ** p<0.01, * p<0.05

Table 4.6 further strengthens the relationship found between woman's justification of IPV and its actual experience, except in Sierra Leone where the relationship is not significant either in lifetime or in last 12 months prevalence.

Decision: Meanwhile acceptance of IPV as justified for any reason is positively associated with IPVAW and significant at 95% confidence interval in the Gambia and Nigeria, it is not consistently significant in Sierra Leone when other variables are controlled for only. Thus while I do not reject the hypothesis that women who accept that IPVAW could be justified for any reason are more likely to experience IPV, I do not accept that this relationship is consistent in all countries studied.

Hypothesis Two: Women whose father beat their mother will be more likely to experience IPV compared to their counterparts whose father did not beat their mother [Testing between Parental History of Violence and Woman's Actual IPV Experience]

violence women african protecting

Table 4.7: Association between parental violence history and IPV experience

Regression analysis result: Reporting logistic odds ratios of factors exposing women to IPV across three African countries
DEPENDENT VAR.==>	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV
	(ORs)	(ORs)	(ORs)	(ORs)	(ORs)	(ORs)
Parental violence (her father beat her mother)	GAMBIA	GAMBIA	NIGERIA	NIGERIA	SIERRA LEONE	SIERRA LEONE
No	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
Yes	2.139***	2.848***	4.362***	3.712***	2.134***	2.123***
	(1.483 - 3.085)	(1.824 - 4.447)	(3.828 - 4.971)	(3.180 - 4.334)	(1.753 - 2.597)	(1.719 - 2.621)
Don't know	1.235	1.790*	1.769***	1.481***	1.644***	1.458**
	(0.867 - 1.761)	(1.091 - 2.934)	(1.504 - 2.081)	(1.209 - 1.813)	(1.304 - 2.072)	(1.120 - 1.898)
Observations	3517	3531	22305	22305	4315	4315
Notes_Titles ciEform in parentheses; *** p<0.001, ** p<0.01, * p<0.05



Table 4.8: Reporting adjusted Odds Ratios

Regression analysis result: Reporting adjusted odds ratios (aORs) of factors exposing women to IPV across three African countries
DEPENDENT VAR.==>	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV
	(aORs)	(aORs)	(aORs)	(aORs)	(aORs)	(aORs)
Parental violence (her father beat her mother)
No	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
Yes	1.920*	2.506**	1.000***	2.249***	2.381***	2.266***
	(1.139 - 3.238)	(1.342 - 4.683)	(1.000 - 1.000)	(1.822 - 2.776)	(1.749 - 3.241)	(1.575 - 3.258)
Don't know	1.173	1.692	-----	1.241	2.435***	1.945**
	(0.650 - 2.119)	(0.853 - 3.359)	-----	(0.935 - 1.647)	(1.579 - 3.757)	(1.237 - 3.058)
Constant	0.102***	0.0117***	0.0772***	0.0255***	0.219***	0.0817***
	(0.0686 - 0.151)	(0.00556 - 0.0244)	(0.0663 - 0.0899)	(0.0201 - 0.0324)	(0.145 - 0.331)	(0.0456 - 0.146)
Observations	1,752	1,755	13,758	13,758	1,528	1,528
	Notes_Titles ciEform in parentheses; *** p<0.001, ** p<0.01, * p<0.05

In both tables, Tables 4.7 and 4.8, women who had a parental history of violence in which the father beats her mother were also more likely to have experienced IPV from their own husband or partner in adulthood. This is consistent in all countries.

Tables 4.9 and Table 4.10 below reports findings for the last three hypotheses and discussions of findings are provided hereunder.

Hypothesis Three: Women who earn income less than their husband's are more likely to experience IPV than their counterparts who earn about same as, or more than husband. [Testing Between Relative Income and IPV Experience

This is only significant in Nigeria where women who earn more income than husbands were also more likely to suffer from IPV compared to their counterparts who earn less than husbands or partners.

Hypothesis Four: Women whose husband/partner manifest any form of control over her will manifest higher likelihood of experiencing IPV compared to women whose husband/partner does not…. [Testing Between Husband controlling behavior and Woman's Actual IPV Experience]

This is indeed another novel finding in this study, using the scale of counts to reflect the number of controls a husband/partner manifest. In Table 4.9, likelihood of suffering from IPV from husband increases significantly as the number of controls increases. In all women whose husband controls in any way were more likely to have experience IPV from him in both lifetime and 12 months prevalence.

In Table 4.10, it is interesting to note that the same relationship is persistent despite controlling for other potential covariates. Likelihood of suffering from IPV from husband increases for a women as the number of his control (dominance) increases. This relational factor corroborates the second level factor or IPVAW proposed by Heise (1998) Social ecological model. It also extends our knowledge in the application of the Marital Power theory expounded by Jewkes (2002) and McKenry et. al (1995). The higher the dominance of husbands, the more likely he is to perpetrate IPV against the woman in all countries.

Hypothesis Five: Women whose husband/partner drink alcohol will manifest higher likelihood of experiencing IPV compared to women whose husband/partner does not. [Testing Between Woman's IPV Experience and Husband's Alcohol Consumption Behavior].

With the exception of the Gambian women in the last 12 months preceding the survey, women whose husband drink alcohol were more likely to report suffering from IPV from him compared to women whose husband or partner does not drink alcohol.

Controlling for other variables in Table 2, all relationship turns significant except for Sierra Leone where alcohol does not show any significant relationship with IPVAW either in the lifetime or in the last 12 months.

In conclusion, two variables were found to be consistent in their relationship with IPVAW against women and remains consistent irrespective of how the factors are modeled. These are parental history of violence (if her father beat her mother), husband control (strongly significant and likelihood increases with the number of controls), and alcohol consumption.

Table 4.9: Association between Husband alcohol consumption, Husband Control and Relative Income

Regression analysis result: Reporting logistic odds ratios of factors exposing women to IPV across three African countries
DEPENDENT VAR.==>	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV
Attitude towards IPV	(ORs)	(ORs)	(ORs)	(ORs)	(ORs)	(ORs)
Husband drinks alcohol	GAMNIA	GAMBIA	NIGERIA	NIGERIA	S. LEONE	S. LEONE
No	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
Yes	3.348**	1.922	4.170***	3.880***	1.855***	1.830***
	(1.552 - 7.223)	(0.822 - 4.490)	(3.722 - 4.671)	(3.403 - 4.423)	(1.379 - 2.495)	(1.463 - 2.289)
Husband controls (Nos.)
No	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
One control	3.917***	3.478***	1.898***	2.028***	2.334***	1.790**
	(2.916 - 5.263)	(2.184 - 5.538)	(1.658 - 2.173)	(1.635 - 2.516)	(1.639 - 3.324)	(1.171 - 2.736)
Two controls	4.532***	5.031***	3.036***	3.033***	4.166***	2.955***
	(3.149 - 6.522)	(2.819 - 8.979)	(2.619 - 3.520)	(2.463 - 3.734)	(3.144 - 5.520)	(2.137 - 4.086)
Three or more controls	8.562***	10.08***	11.75***	11.72***	6.367***	5.124***
	(5.892 - 12.44)	(6.019 - 16.88)	(10.15 - 13.59)	(9.609 - 14.28)	(4.993 - 8.119)	(3.764 - 6.975)
Missing/DK/No response	4.929	15.88*	3.833***	5.171***	5.104***	2.727*
	(0.926 - 26.24)	(1.875 - 134.5)	(2.968 - 4.951)	(3.742 - 7.147)	(2.187 - 11.91)	(1.035 - 7.186)
Relative income
Woman earns less	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
Woman earns about same	0.536	0.197**	0.961	0.843	0.676	0.6
	(0.198 - 1.454)	(0.0608 - 0.635)	(0.782 - 1.182)	(0.636 - 1.116)	(0.394 - 1.159)	(0.318 - 1.133)
Woman earns more	0.708	0.856	1.656***	1.761***	0.746	1.126
	(0.323 - 1.552)	(0.328 - 2.237)	(1.277 - 2.146)	(1.299 - 2.389)	(0.428 - 1.298)	(0.600 - 2.112)
Husband has no income	0.731	0.265	2.338**	1.857*	0.874	0.397
	(0.277 - 1.932)	(0.0330 - 2.131)	(1.397 - 3.913)	(1.132 - 3.048)	(0.277 - 2.759)	(0.141 - 1.117)
DK/Missing	1.009	0.573	1.397*	1.265	0.407*	0.386*
	(0.425 - 2.394)	(0.186 - 1.769)	(1.080 - 1.808)	(0.880 - 1.820)	(0.201 - 0.826)	(0.171 - 0.873)
Observations	3517	3531	22305	22305	4315	4315
Obs. (relative income)	1528	1528	13758	13758	1528	1528
	Notes_Titles ciEform in parentheses; *** p<0.001, ** p<0.01, * p<0.05

Table 4.10: Reporting Adjusted Odds Ratios

Regression analysis result: Reporting adjusted odds ratios (aORs) of factors exposing women to IPV across three African countries
DEPENDENT VAR.==>	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV
Attitude towards IPV	(aORs)	(aORs)	(aORs)	(aORs)	(aORs)	(aORs)
Husband drinks alcohol	GAMNIA	GAMBIA	NIGERIA	NIGERIA	S. LEONE	S. LEONE
No	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
Yes	4.406**	5.371**	3.819***	3.294***	1.581	1.067
	(1.659 - 11.70)	(1.645 - 17.54)	(3.337 - 4.372)	(2.780 - 3.903)	(0.962 - 2.598)	(0.677 - 1.681)
Husband controls (Nos.)
No	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
One control	2.886***	2.593**	2.343***	2.210***	2.916***	2.153*
	(1.972 - 4.222)	(1.434 - 4.688)	(1.990 - 2.757)	(1.717 - 2.844)	(1.717 - 4.953)	(1.105 - 4.197)
Two controls	3.601***	3.691**	3.606***	3.022***	5.039***	4.102***
	(2.202 - 5.889)	(1.625 - 8.385)	(3.050 - 4.264)	(2.358 - 3.874)	(3.191 - 7.957)	(2.328 - 7.225)
Three or more controls	6.996***	10.57***	11.05***	9.367***	8.257***	6.252***
	(4.177 - 11.72)	(5.743 - 19.46)	(9.159 - 13.32)	(7.333 - 11.97)	(5.251 - 12.98)	(3.625 - 10.78)
Missing/DK/No response	3.934	10.83**	3.691***	4.372***	1.122	1.572
	(0.677 - 22.85)	(1.848 - 63.51)	(2.554 - 5.334)	(2.825 - 6.765)	(0.211 - 5.965)	(0.251 - 9.829)
Relative income
Woman earns less	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
Woman earns about same	0.554	0.202*	0.908	0.747	0.78	0.649
	(0.201 - 1.531)	(0.0582 - 0.700)	(0.712 - 1.157)	(0.541 - 1.031)	(0.441 - 1.378)	(0.332 - 1.266)
Woman earns more	0.889	1.012	1.536**	1.455*	0.593	0.954
	(0.501 - 1.579)	(0.495 - 2.070)	(1.126 - 2.095)	(1.031 - 2.052)	(0.324 - 1.086)	(0.529 - 1.721)
Husband has no income	0.616	0.195	1.801*	1.097	1.491	0.516
	(0.220 - 1.722)	(0.0375 - 1.018)	(1.056 - 3.074)	(0.571 - 2.110)	(0.447 - 4.974)	(0.182 - 1.465)
DK/Missing	1.402	0.582	1.267	1.072	0.460*	0.485
	(0.477 - 4.114)	(0.124 - 2.742)	(0.948 - 1.692)	(0.720 - 1.598)	(0.212 - 0.997)	(0.213 - 1.106)
Constant	0.102***	0.0117***	0.0772***	0.0255***	0.219***	0.0817***
	(0.0686 - 0.151)	(0.00556 - 0.0244)	(0.0663 - 0.0899)	(0.0201 - 0.0324)	(0.145 - 0.331)	(0.0456 - 0.146)
Observations	1,752	1,755	13,758	13,758	1,528	1,528
	Notes_Titles ciEform in parentheses; *** p<0.001, ** p<0.01, * p<0.05



CHAPTER FIVE: CONCLUSION AND RECOMMENDATIONS

5.1 Summary and Discussion of Findings

This paper investigates the common and specific factors of IPV against women in there African countries with the aim of discovering factors that are consistent in their relationship to IPV against women beyond national and cultural boundaries. It employed the Social ecological model of Heise (1998), the Social learning theory of Bandura (1971), the Biopsychosocial model of McKenry et. al (1995). Five hypotheses were tested with the aid of binary logistic regression at 95% confidence interval. The study found that women with childhood exposure to domestic violence (in which her father beat her mother), who agree that it might be justifiable for a man to beat his wife for any reason, women with a husband or partner who drinks alcohol, and more importantly women whose husband exercise any form of control over were more likely to experience IPV compared to their counterparts without such characteristics. Women who earn income more than husband were more likely to report experiencing IPV in Nigeria compared to those women who earn less income than husband

Thus this paper extends our knowledge on consistent factors of IPVAW. It could therefore be predicted that men who manifest any of the five hypothetical husband controlling behaviors will be more likely to perpetrate IPV against their female partners in all the three countries. Likewise, women whose father beat her mother also stands a higher risk than their counterparts whose father did not beat her mother. This corroborates the individual intergenerational factor of Heise (1998) and the Social leaning theory of Bandura (1971).

The findings in this study also further corroborate a number of other studies such as Uthman, Moradi & Lawoko (2011) who investigated the relationship between attitude towards IPVAW and actual experiences in Nigeria using the penultimate 2008 NDHS. They found a strong correlation between women's acceptance of IPV as justified and its actual occurrence. However, beyond this, while the current study partly justifies this, it further reveals that the relationship does not hold true in every country - it was not statistically significant in Sierra Leone (see Table 4).

This paper also further agrees with the findings of Uthman, Moradi & Lawoko (2011) in Nigeria which reports early exposure to IPV in childhood is a strong correlate of actual experience of IPV in adulthood. A position equally justified by Abramsky, et. al (2011). By showing that this relationship is consistent beyond countries, this study extend further strengthen such position and add to this already existing body of literature

Antai, D. (2011) and Garcia-Moreno, Jansen,, Ellsberg, Heise, & Watts, (2006) ha ve reported that women whose husband manifests controls over were more likely to experience IPV. However, beyond these, the current study reveals that in all countries studied, the likelihood of a woman experiencing IPVAW tend to increase proportionately in tandem to the number of controls reported. Women whose husband or partner manifests one or two controls are statistically less likely to experiencing IV frim him compared to women whose husband exhibit three or more forms of control. This finding is novel and



Recommendation

Based on the findings in this paper, the paper proposes the following recommendations:

There is need for community mobilization towards which should include men. The situation in Sierra Leone reveals that the presence of laws and policies is not enough if they are not well managed and effectively implemented.

The role of community leaders in the mobilization and campaigns against IPV and all forms of violence against women at the community levels is very crucial.

The education of women and girls should continue to be pushed forward. There are tendencies that educated women are less likely to justify IPVAW and thus would be less likely to condone it.

Education also offers opportunities for better bargaining power in households. Hence, women are less likely to be perceived as “liabilities” by husbands.

Men need to be reeducated that wife who us more materially and financially richer is not a “curse” and that women are necessarily wanting to become the household “lords” over them - a perceptions which is known to have stirred rivalry and jealousy from husbands and thus episodes of IPVAW.

Alcohol consumption should be discouraged. Men who hold history of perpetrating IPV under guise of alcohol should be held accountable.

It is important that parents lay good legacies for their children as children might tend to replicate or condone what they have seen with parents.

Finally, onerous tasks lies on the head of the government, NGOs and other stakeholders in Africa to mitigate instances of intimate partner violence against women in all its shadows and manifestations in African societies.



Limitation of Study

The use of secondary quantitative data limits the extent to which issues of domestic violence can be interpreted. The use of mixed methods could have provided better results with explanatory power and testing or disproving of theories. Likewise, the study fitted one stage binary logistic regression model. This makes it difficult to decongest each variable and report the effect of difference in slopes of regression as a result of differences in intercept due to regional and residential variations. This could have been controlled for by multilevel logistic regression models. Notwithstanding, the paper provides useful information and extends our understating of the factors consistent in their relationship to IPVAW in the Gambia, Nigeria and Sierra Leone. There is need therefore for more in-depth studies employing qualitative ethnographic methods as well as longitudinal in approach in order to fully capture the possible causes of IPVAW in households. Further systematic studies are also needed to teste the statistically justifiability or refutability of Heise (1998) five levels across and being national and national boundaries.



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APPENDIX 1 - 4



Gender Empowerment Facts in Sierra Leone



Regression analysis result: Reporting logistic odds ratios of factors exposing women to IPV across three African countries

DEPENDENT VAR.==>	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV	EVER IPV	12 Months IPV
Attitude towards IPV	(ORs)	(ORs)	(ORs)	(ORs)	(ORs)	(ORs)
Never justified	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
IPVAW somewhat justified	1.630**	2.990***	1.684***	1.703***	1.439**	1.670***
	(1.220 - 2.179)	(1.854 - 4.824)	(1.483 - 1.912)	(1.462 - 1.983)	(1.126 - 1.839)	(1.288 - 2.166)
Yes IPVAW very justified	1.348	2.602**	1.688***	1.845***	1.103	1.315*
	(0.948 - 1.916)	(1.432 - 4.730)	(1.473 - 1.934)	(1.586 - 2.146)	(0.886 - 1.373)	(1.030 - 1.681)
DK/Missing	1.719	3.589	1.087	1.393*	0.899	0.997
	(0.664 - 4.453)	(0.880 - 14.63)	(0.851 - 1.389)	(1.024 - 1.894)	(0.590 - 1.371)	(0.609 - 1.634)
Parental violence (her father beat her mother)
No	1.000	1.000	1.000	1.000	1.000	1.000
	( - )	( - )	( - )	( - )	( - )	( - )
Yes	2.139***	2.848***	4.362***	3.712***	2.134***	2.123***
	(1.483 - 3.085)	(1.824 - 4.447)	(3.828 - 4.971)

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