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JSBCH 2022, 6(2): 874-884 |
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Ekonugraheni D H, Lydia E, Yusnaini Y, Yanti M. Factors Contributing to the Married Men’s Attitudes Towards Wife-beating in Indonesia. JSBCH 2022; 6 (2) :874-884
URL: http://sbrh.ssu.ac.ir/article-1-198-en.html
URL: http://sbrh.ssu.ac.ir/article-1-198-en.html
1- Department of Sociology, Sriwijaya University, Palembang, Indonesia , dyahhapsari@fisip.unsri.ac.id
2- Department of Sociology, Sriwijaya University, Palembang, Indonesia
2- Department of Sociology, Sriwijaya University, Palembang, Indonesia
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a Department of Sociology, Sriwijaya University, Palembang, Indonesia
Gender equality (Goal 5) is a component of the Sustainable Development Goals (SDGs) which has nine targets and must be achieved by 2030. Two of these nine targets are directly related to violence against women (VAW) (United Nations, 2015). In the private sphere, one form of VAW that often occurs is intimate partner violence (IPV) which involves various social relationships. According to KOMNAS Perempuan (2019), in 2018, there were 9,637 (71%) cases of VAW in the personal sphere, ranging from violence against wives (VAWi) (5,114 cases or 53%), violence in dating (2,073 cases or 21%), violence against girls (1,417 cases or 14%), and ex-husband violence, ex-boyfriend violence, and violence against domestic workers. This study will further elaborate on the phenomenon of violence against wives (VAWi) as a form of IPV in the private space, especially at the household level and focus on the phenomenon of wife-beating (WB) which is still common in Indonesia. In Indonesia, previous studies have indicated that VAWi is associated with the husband's demographic and personal characteristics, perspectives on masculinity (Eidhamar, 2018; Hayati et al., 2011, 2014), wife's actions expressing her agency as an autonomous woman (Aisyah & Parker, 2014); or when husbands are under financial pressure due to economic hardship or lose their status or prestige while their wives work (Nilan et al., 2014). However, previous studies have not explained further the factors that influence the husband's views or attitudes towards the WB phenomenon.
The husband's view/attitude towards WB is an individual attribute that cannot be separated from the identity, context, social situation in which a person is located (Flynn & Graham, 2010). The level of education, for example, tends to have no effect on the husband's views/attitudes towards WB (Nilan et al., 2014). This means that WB can be done by husbands with low or high education. In fact, from the women's side, the level of education is negatively associated with the risk of becoming a victim of WB (Amegbor & Rosenberg, 2019; Boyle et al., 2009; Costa et al., 2016; Fulu et al., 2013; Wang, 2016). It is predicted that the husband's education level is negatively associated with his views/attitudes towards WB (H1). Age also affects the husband's perception on WB (Chang et al., 2009; Mallory et al., 2016; Wang, 2016). Young husbands tend to be more potential to become perpetrators of WB compared to older husbands (Hayati et al., 2011; Shamu et al., 2013). It is predicted that the husband's age was negatively associated with his attitude/view of WB (H2).
Location of residence was also a predictor of IPV (Benson et al., 2003; Clark et al., 2008; Wang, 2016). However, whether the location of residence affects the husband's view of WB, still needs to be scientifically proven. It is estimated that the location of the residence is positively associated with the husband's attitude/view of WB (H3). Husband’s job also contributes to WB (Hayati et al., 2011; Weaver & Etzel, 2003). It is predicted that husbands who work in the agricultural sector are positively associated with their attitudes/views against WB (H4). The effect of the number of children on WB is still debatable. Several researchers have shown that the number of children living in the same house does not contribute to domestic violence (Purwoko et al., 2011; Shiyun et al., 2013). However, some researchers show the opposite finding (Adebowale, 2018; Kapadia et al., 2010). It is stimated that the number of children will be positively associated with the husband's attitude/views towards WB (H6). Previous studies have shown that smoking is positively associated with IPV (Weaver & Etzel, 2003; Yoshihama et al., 2010). However, researchers suspect that smoking habits among husbands will be positively associated with their attitudes/views towards WB (H7).
Prostitution is illegal for most religions in the world and can trigger a variety of sexually transmitted diseases and IPV (Abramsky et al., 2011; Aekplakorn & Kongsakon, 2007; Grisurapong, 2016; Jones & Ferguson, 2009; Kiss et al., 2012; Silverman et al., 2006; Tang & Lai, 2008). The researchers suspect that the practice of adultery among husbands is positively related to their views/attitudes towards WB (H8). Another factor contributing to IPV is the practice of polygamy (Abramsky et al., 2011; Aduloju et al., 2015; Gibbs et al., 2018; Tsiko, 2016; Vung et al., 2008; Vyas & Jansen, 2018). The contribution of polygamy is influenced by other factors, such as poverty level, old husband's age, husband's low education level (Vung et al., 2008), and economic dependence on husbands because their wives do not work, husbands who consume alcohol and smoke, which lead to aggressive actions (Aduloju et al., 2015; Vyas & Jansen, 2018). It is predicted that husbands who practice polygamy tend to agree with the practice of WB (H9). Finally, this study will include variables of household decision-making patterns. The results of previous research on the contribution of this variable to IPV are also controversial (Antai, 2011; Hindin & Adair, 2002). Moreover, the pattern of joint decision-making is negatively associated with the husband's views/attitudes towards WB (H10).
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Factors Contributing to the Married Men’s Attitudes Towards Wife-beating in Indonesia
Dyah Hapsari Ekonugraheni a*, Eva Lidya a, Yusnaini a, Mery Yanti a
a Department of Sociology, Sriwijaya University, Palembang, Indonesia
| A R T I C L E I N F O | A B S T R A C T | |
| ORIGINAL ARTICLE | Background: Domestic violence is a common problem in Indonesia, especially intimate partner violence (IPV). This study aims to analyze the predictors of attitudes of married men towards wife-beating (WB) for neglecting their children. Methods: The research data comes from the 7th Demography and Health Survey collected by the U.S. Agency for International Development in 2017. The respondents were 10,009 married male respondents aged 15-54 and responded to question 618 (Do you agree WB by husband for neglecting their children?). Results: The results showed that of the ten independent variables identified as predictors of married men’s attitude towards WB for neglecting their children, only six independent variables had a significant relationship, including adultery, age, smoking habit, location of residence, education level, and polygamy. Of these six independent variables, two independent variables (level of education and age) had a negative relationship, and four variables had a positive relationship with dependent variable significantly, p <0.01, with respective contributions of 82% (adultery), 121% (smoking habit), 125% (location of residence), and 233% (polygamy). The final logistic regression model can explain dependent variable of 2.06% significantly, X2 (6) = 170.43, p <0.01. Conclusion: This study suggests government institutions to make policy change in several sectors, such as education, social, information, tourism, health, economic, and regional development policy. Keywords: Domestic Violence, Spouse Abuse, Smoking, Polygamy, Sexual Behavior |
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Article History: Received: 08 Sep 2021 Revised: 02 Nov 2022 Accepted: 09 Nov 2022 |
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*Corresponding Author: Dyah Hapsari Ekonugraheni Email: dyahhapsari@fisip.unsri.ac.id Tel: +62 81367663351 |
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Citation:
Ekonugraheni DH, Lidya E, Yusnaini, Yanti M. Factors Contributing to the Married Men’s Attitudes Towards Wife-beating in Indonesia. Journal of Social Behavior and Community Health (JSBCH). 2022; 6(2): 874-884. |
Introduction
Gender equality (Goal 5) is a component of the Sustainable Development Goals (SDGs) which has nine targets and must be achieved by 2030. Two of these nine targets are directly related to violence against women (VAW) (United Nations, 2015). In the private sphere, one form of VAW that often occurs is intimate partner violence (IPV) which involves various social relationships. According to KOMNAS Perempuan (2019), in 2018, there were 9,637 (71%) cases of VAW in the personal sphere, ranging from violence against wives (VAWi) (5,114 cases or 53%), violence in dating (2,073 cases or 21%), violence against girls (1,417 cases or 14%), and ex-husband violence, ex-boyfriend violence, and violence against domestic workers. This study will further elaborate on the phenomenon of violence against wives (VAWi) as a form of IPV in the private space, especially at the household level and focus on the phenomenon of wife-beating (WB) which is still common in Indonesia. In Indonesia, previous studies have indicated that VAWi is associated with the husband's demographic and personal characteristics, perspectives on masculinity (Eidhamar, 2018; Hayati et al., 2011, 2014), wife's actions expressing her agency as an autonomous woman (Aisyah & Parker, 2014); or when husbands are under financial pressure due to economic hardship or lose their status or prestige while their wives work (Nilan et al., 2014). However, previous studies have not explained further the factors that influence the husband's views or attitudes towards the WB phenomenon.
The husband's view/attitude towards WB is an individual attribute that cannot be separated from the identity, context, social situation in which a person is located (Flynn & Graham, 2010). The level of education, for example, tends to have no effect on the husband's views/attitudes towards WB (Nilan et al., 2014). This means that WB can be done by husbands with low or high education. In fact, from the women's side, the level of education is negatively associated with the risk of becoming a victim of WB (Amegbor & Rosenberg, 2019; Boyle et al., 2009; Costa et al., 2016; Fulu et al., 2013; Wang, 2016). It is predicted that the husband's education level is negatively associated with his views/attitudes towards WB (H1). Age also affects the husband's perception on WB (Chang et al., 2009; Mallory et al., 2016; Wang, 2016). Young husbands tend to be more potential to become perpetrators of WB compared to older husbands (Hayati et al., 2011; Shamu et al., 2013). It is predicted that the husband's age was negatively associated with his attitude/view of WB (H2).
Location of residence was also a predictor of IPV (Benson et al., 2003; Clark et al., 2008; Wang, 2016). However, whether the location of residence affects the husband's view of WB, still needs to be scientifically proven. It is estimated that the location of the residence is positively associated with the husband's attitude/view of WB (H3). Husband’s job also contributes to WB (Hayati et al., 2011; Weaver & Etzel, 2003). It is predicted that husbands who work in the agricultural sector are positively associated with their attitudes/views against WB (H4). The effect of the number of children on WB is still debatable. Several researchers have shown that the number of children living in the same house does not contribute to domestic violence (Purwoko et al., 2011; Shiyun et al., 2013). However, some researchers show the opposite finding (Adebowale, 2018; Kapadia et al., 2010). It is stimated that the number of children will be positively associated with the husband's attitude/views towards WB (H6). Previous studies have shown that smoking is positively associated with IPV (Weaver & Etzel, 2003; Yoshihama et al., 2010). However, researchers suspect that smoking habits among husbands will be positively associated with their attitudes/views towards WB (H7).
Prostitution is illegal for most religions in the world and can trigger a variety of sexually transmitted diseases and IPV (Abramsky et al., 2011; Aekplakorn & Kongsakon, 2007; Grisurapong, 2016; Jones & Ferguson, 2009; Kiss et al., 2012; Silverman et al., 2006; Tang & Lai, 2008). The researchers suspect that the practice of adultery among husbands is positively related to their views/attitudes towards WB (H8). Another factor contributing to IPV is the practice of polygamy (Abramsky et al., 2011; Aduloju et al., 2015; Gibbs et al., 2018; Tsiko, 2016; Vung et al., 2008; Vyas & Jansen, 2018). The contribution of polygamy is influenced by other factors, such as poverty level, old husband's age, husband's low education level (Vung et al., 2008), and economic dependence on husbands because their wives do not work, husbands who consume alcohol and smoke, which lead to aggressive actions (Aduloju et al., 2015; Vyas & Jansen, 2018). It is predicted that husbands who practice polygamy tend to agree with the practice of WB (H9). Finally, this study will include variables of household decision-making patterns. The results of previous research on the contribution of this variable to IPV are also controversial (Antai, 2011; Hindin & Adair, 2002). Moreover, the pattern of joint decision-making is negatively associated with the husband's views/attitudes towards WB (H10).
Methods
This study uses an inferential quantitative approach that attempts to test the research hypothesis. The source of research data comes from the results of the 7th Demography and Health Survey (DHS) collected by the U.S. Agency for International Development, the National Family Planning Coordinating Board (BKKBN), the Central Bureau of Statistics, the Ministry of Health, and the ICF International, Inc., in 2017. The DHS VII sample covers 1,970 blocks involving 49,250 households spread across all provinces in Indonesia. The DHS VII interviewed 59,100 women aged 15-49 years and 24,625 men aged 15-24 years who had never been married and met the criteria for being interviewed. In each census block, the DHS VII selects 7 households to be interviewed using the Married Man's Questionnaire (MMQ). A total of 14,193 married men aged 15-54 years were interviewed using MMQ. The number of men who responded to question 618 (Do you agree WB wife-beating that by a husband spanking a wife for neglecting their children?) reached 10,009 respondents (BKKBN et al., 2018).
The research data will be processed and analyzed using logistic regression techniques and STATA 15™. Data analysis was carried out in two stages, including bivariate analysis and multivariate analysis. Bivariate analysis was carried out using cross-tabulation techniques and the aim was to select independent variables to be included in the multivariate analysis. According to Hosmer et al., (2013), only independent variables having p <0.25 can be included in the multivariate analysis. Multivariate analysis use logistic regression with the enter method (independent variables are entered into logistic regression one by one based on the X2 score at the time of bivariate analysis). The coefficient of logit was used to determine positive or negative relationship between independent and dependent variable. The odds ratio (OR) will interpret as the proportion of occurrent event. The goodness-of-fit of the final model was tested using the Hosmer-Lemeshow (Ĉ) method. The operation of the research variables is shown in Table 1.
This research was funded by the Dean of Faculty of Social and Political Science (FISIP), Sriwijaya University (UNSRI) based on the Decree of the Dean of FISIP UNSRI Number: 2269/UN9.FISIP/ TU.SK/2020, October 5, 2020. All respondents participate in the DHS VII research based on voluntary principle. DHS VII also create research protocol that respect the privacy of respondents. Interview are performed as privately as possible. Result of interview are strictly confidential.
The research data will be processed and analyzed using logistic regression techniques and STATA 15™. Data analysis was carried out in two stages, including bivariate analysis and multivariate analysis. Bivariate analysis was carried out using cross-tabulation techniques and the aim was to select independent variables to be included in the multivariate analysis. According to Hosmer et al., (2013), only independent variables having p <0.25 can be included in the multivariate analysis. Multivariate analysis use logistic regression with the enter method (independent variables are entered into logistic regression one by one based on the X2 score at the time of bivariate analysis). The coefficient of logit was used to determine positive or negative relationship between independent and dependent variable. The odds ratio (OR) will interpret as the proportion of occurrent event. The goodness-of-fit of the final model was tested using the Hosmer-Lemeshow (Ĉ) method. The operation of the research variables is shown in Table 1.
This research was funded by the Dean of Faculty of Social and Political Science (FISIP), Sriwijaya University (UNSRI) based on the Decree of the Dean of FISIP UNSRI Number: 2269/UN9.FISIP/ TU.SK/2020, October 5, 2020. All respondents participate in the DHS VII research based on voluntary principle. DHS VII also create research protocol that respect the privacy of respondents. Interview are performed as privately as possible. Result of interview are strictly confidential.
Results
Characteristic of respondent
Respondents of this study were married men aged 15-54 years who were interviewed using the MMQ. The total respondents who were successfully interviewed with the MMQ were 14,193 people. Of this target, the total number of men who responded to question 618 is 10,009 respondents (BKKBN et al., 2018). The mean age of the respondents was 39.54 years. The age of the respondents is quite varied as indicated by the value of standard deviation (8.55) and variance (73.17). The age data of the respondents are normally distributed because the data kurtosis rate was <3 or 2.10 points. The respondent's age data was still zero points, even though it had a negative slope (-0.14).
The origin of the respondents came from several provinces in Indonesia. However, the largest proportion came from three provinces in Java, including West Java (10.80%), Central Java (6.87%), and East Java (8.21%). This condition is very reasonable because Indonesia's population is concentrated on the Java Island. Several provinces outside Java Island contributed 4 percent of respondents: Aceh, North Sumatra, and East Nusa Tenggara. Meanwhile, other provinces contributed 1-3 percent of the respondents. More respondents lived in urban areas than in rural areas. Many respondents (52.71%) had graduated from junior high school/equivalent. The second position was occupied by respondents who had graduated from elementary school/equivalent (30.88%) and the third position was occupied by those who had graduated from high school/equivalent (14.37%). Respondents who did not attend school reached 2.04%. Most respondents were married. Only a handful of respondents lived in the same house as their partner without a legal marriage bond. In terms of occupation, many respondents worked in the agricultural sector (28.83%), industrial workers (23.69%), services (16.96%), and trade (13.63%).
The origin of the respondents came from several provinces in Indonesia. However, the largest proportion came from three provinces in Java, including West Java (10.80%), Central Java (6.87%), and East Java (8.21%). This condition is very reasonable because Indonesia's population is concentrated on the Java Island. Several provinces outside Java Island contributed 4 percent of respondents: Aceh, North Sumatra, and East Nusa Tenggara. Meanwhile, other provinces contributed 1-3 percent of the respondents. More respondents lived in urban areas than in rural areas. Many respondents (52.71%) had graduated from junior high school/equivalent. The second position was occupied by respondents who had graduated from elementary school/equivalent (30.88%) and the third position was occupied by those who had graduated from high school/equivalent (14.37%). Respondents who did not attend school reached 2.04%. Most respondents were married. Only a handful of respondents lived in the same house as their partner without a legal marriage bond. In terms of occupation, many respondents worked in the agricultural sector (28.83%), industrial workers (23.69%), services (16.96%), and trade (13.63%).
Bivariate analysis
Bivariate analysis was carried out to see whether statistically there is a relationship between each independent variable and the dependent variable. The results of the bivariate will determine whether an independent variable will be included in the multivariate analysis stage. In this context, according to Hosmer et al., (2013), the independent variable with p ≤ 0.25 can still be included in the multivariate analysis even though it is not statistically significant. The result of the bivariate analysis showed that of the ten variables identified by the researcher as effective dependent variable, two variables did not significantly affect dependent variable. However, only the variable of internet access could not be included in the multivariate analysis because the p was > 0.20. The variable of number of children, although not significant, was included in the multivariate analysis because of the p ≤ 0.20. Table 2 shows the summary of the bivariate analysis.
Multivariate analysis
The final model of logistic regression produced by this study contains six independent variables, including adultery, age, smoking habit, residence location, education level, and polygamy. Two independent variables have a negative relationship with dependent variable (age and education level). The contributions of age and education level are 63% and 82%, respectively, to explain dependent variable. The final model of logistic regression can estimate dependent variable by 2.06% significantly, X2 (6) = 170.43, p <0.01. The Hosmer-Lemeshow (Ĉ) test results confirm that there is no difference between the predictions produced by the model and the field data. This prediction is very convincing because it is statistically significant.
In terms of age, the respondents aged> 40 years had a 63% probability of not beating their wives due to neglecting the children. Thus, older men are less likely to beat their wives.. Meanwhile, in the context of education level, those with >high school/equivalent had an 82% probability of not beating their wives due to neglecting their children. In other words, the higher the educational level of the respondent, the lower the possibility of WB for neglecting children. However, the relationship between level of education and dependent variable was only significant at p <0.05, not at p <0.01. The other four variables had a positive relationship with dependent variable and were significant at p <0.01. Those who practice adultery, smoking habits, live in the rural area, and practice polygamy each have a probability of 82%, 121%, 125%, and 233%, to beat his wife for neglecting their children. The final logistic regression model is visualized in Table 3.
In terms of age, the respondents aged> 40 years had a 63% probability of not beating their wives due to neglecting the children. Thus, older men are less likely to beat their wives.. Meanwhile, in the context of education level, those with >high school/equivalent had an 82% probability of not beating their wives due to neglecting their children. In other words, the higher the educational level of the respondent, the lower the possibility of WB for neglecting children. However, the relationship between level of education and dependent variable was only significant at p <0.05, not at p <0.01. The other four variables had a positive relationship with dependent variable and were significant at p <0.01. Those who practice adultery, smoking habits, live in the rural area, and practice polygamy each have a probability of 82%, 121%, 125%, and 233%, to beat his wife for neglecting their children. The final logistic regression model is visualized in Table 3.
| Table 1. Operationalization of research variables | ||
| Type of variable | Conceptualization | Measurement |
| Dependent variable | ||
| Attitudes of men towards WB because of the factor of neglecting children | Attitudes or views, and not experience, of men aged 15 - 54 years towards the practice of WB. | This variable is measured by the question: “Do you agree that a husband hits a wife on the grounds of neglecting children? This variable is converted into a dummy variable (1 = agree and 0 = disagree). |
| Independent variable | ||
| Level of education | The level of formal education has been taken by the respondent | 1 = > High school; 0 = < High school |
| Age | Respondent age when interviewed by the DHS VII survey officers | 1 = Old (>40 years); 0 = Young (<40 years) |
| Location of residence | The administrative status of the area where the respondent lives | 1 = Rural; 0 = Urban |
| Type of occupation | Type of respondent’s job | 1 = Agriculture; 0 = Non agriculture |
| Internet access | Access respondent to internet facility | Measured by the question: "in the last 12 months, have you used the internet?" This variable is converted into a dummy variable: 1 = yes and 0 = no |
| Number of children | The number of children who still live with the respondent | 1 = >2 people; 0 = < 2 people |
| Smoking habit | Smoking habit among respondent | Measured by the question: “do you smoke every day, several days, or not at all? This variable is converted into a dummy variable: 1 = smoking; 0 = do not smoke |
| Adultery | Voluntary sexual intercourse between a married person and a person who is not his or her spouse. | Measured by a question: “in the last 12 months, have you paid someone in return to have sexual intercourse?” This variable is converted into a dummy variable (1 = yes and 0 = no) |
| Polygamy | The practice or custom of having more than one wife or husband at the same time. | Measured by the question: “how many wives do you currently have?” If the respondent's wife is more than 1 wife, then coded 1 (polygamy) and if only 1 wife is coded 0 |
| Household decision-making patterns | The involvement of husband/wife in making decisions related to purchasing household necessities | 1 = collective decision; 0 = only husband or wife decision |
| Table 2. Summary of the bivariate analysis between independent and dependent variable | |||||||
| Independent variable | Dependent variable (attitude of married man toward WB due to neglecting the children) | Total | X2 | df | p | V | |
| Disagree | Agree | ||||||
| Level of education | |||||||
| <High school | 7,058 (84.73%) | 1,299 (15.54%) | 8.357 (100%) | 10,06 | 1 | 0,00 | -0,03 |
| >High school | 1,230 (87.73%) | 172 (12.27%) | 1.402 (100%) | ||||
| Age | |||||||
| <40 years | 3,958 (81.93%) | 873 (18.07%) | 4,831 (100%) | 67,15 | 1 | 0,00 | -0,08 |
| >40 years | 4,330 (87.87%) | 598 (12.13%) | 4,928 (100%) | ||||
| Type of residence | |||||||
| Urban | 4,257 (86.58%) | 660 (13.42%) | 4,917 (100%) | 21,08 | 1 | 0,00 | 0,04 |
| Rural | 4,031 (83.25%) | 811 (16.75) | 4,842 (100%) | ||||
| Type of occupation | |||||||
| Agriculture | 5,922 (85.55%) | 1,000 (14.45%) | 6,922 (100%) | 7,29 | 1 | 0,00 | 0,02 |
| Non-agriculture | 2,361 (83.40%) | 470 (16.60%) | 2,831 (100%) | ||||
| Internet access | |||||||
| No | 5,016 (84.92%) | 891 (15.08%) | 5,907 (100%) | 0,00 | 1 | 0,98 | -0,00 |
| Yes | 3,270 (84.94%) | 580 (15.06% | 3,850 (100%) | ||||
| Number of children | |||||||
| <2 | 5,306 (84.58%) | 967 (15.42%) | 6,273 (100%) | 1,60 | 1 | 0,20 | -0,01 |
| >2 | 2,982 (85.54%) | 504 (14.46%) | 3,486 (100%) | ||||
| Smoking habits | |||||||
| No smoking | 2,438 (87.73%) | 341 (12.27%) | 2,779 (100%) | 23,91 | 1 | 0,00 | 0,04 |
| Smoking | 5,847 (83.80%) | 1,130 (16.20%) | 6,977 (100%) | ||||
| Adultery | |||||||
| No | 7,908 (85.66%) | 1,324 (14.34%) | 9,232 (100%) | 72,54 | 1 | 0,00 | 0,08 |
| Yes | 374 (71.92%) | 146 (28.08%) | 520 (100%) | ||||
| Polygamy | |||||||
| No | 8,245 (85.02%) | 1,453 (14.98%) | 9,698 (100%) | 9,99 | 1 | 0,00 | 0,03 |
| Yes | 43 (70.49%) | 18 (29.51%) | 61 (100%) | ||||
| Household decision-making | |||||||
| Alone | 4,768 (84.57%) | 870 (15.43%) | 5,638 (100%) | 4,17 | 1 | 0,04 | -0,02 |
| Joint | 3,078 (86.12%) | 496 (13.88%) | 3,574 (100%) | ||||
| X2 (Chi-square), df (degree of freedom), p (p-value), V (Cramer’s V) | |||||||
| Table 3. The final model of logistic regression | ||
| Independent variable | Dependent variable: attitude of married man toward WB due to neglecting the children |
OR |
| Adultery | 0.797*** | .829 |
| (0.103) | ||
| Age | -0.455*** | .634 |
| (0.0583) | ||
| Smoking habit | 0.197*** | 1.218 |
| (0.0682) | ||
| Location of residence | 0.230*** | 1.258 |
| (0.0580) | ||
| Level of education | -0.186** | .829 |
| (0.0896) | ||
| Polygamy | 0.847*** | 2.331 |
| (0.289) | ||
| Constant | -1.819*** | .162 |
| (0.0751) | ||
| Observations | 9,749 | |
| Standard errors in parentheses | ||
| *** p < 0.01, ** p < 0.05, * p < 0.1 | ||
Discussion
The research findings indicate a negative relationship between education level and WB. This finding is the basis for researchers to accept the first hypothesis (H1) (the husband's education level is negatively associated with his views/attitudes towards WB). In other words, when the husband is highly educated (> high school), he will disagree with WB. This finding corroborates the results of previous studies which show a negative association of education level with IPV (Amegbor & Rosenberg, 2019; Boyle et al., 2009; Costa et al., 2016; Fulu et al., 2013; Wang, 2016).
The results of this study also show a negative association between age and WB. This means that respondents aged > 40 years have a 63% chance not not beating their wives due to neglecting their children. This finding is the basis for the researchers to accept the second hypothesis (H2) (the husband's age is negatively associated with his attitude/views towards WB). This finding is consistent with the results of the previous studies which show that young husbands (≤ 35 years) tend to be more potential to become perpetrators of WB compared to older husbands (Hayati et al., 2011; Shamu et al., 2013). This may be due to the psychological maturity and level of economic stability of the husbands, which is believed by some that it may occur at the age of 40.
Furthermore, residence location is also positively associated with WB. This means that respondents in rural areas could commit acts of beating their wives due to the factor of neglecting their children by 125%. This finding is the basis for researchers to accept the third hypothesis (H3) (the location of the residence is positively associated with the husband's attitude/view of WB). The stronger the village characteristics in a residential location, the more likely husbands in that location agree with WB. The H3 is in line with the results of previous research which showed the location of residence as a predictor of IPV (Clark et al., 2008)
Meanwhile, type of occupation has a positive but insignificant relationship with WB, p > 0.10. This empirical finding is the basis for the researcher to reject the fourth hypothesis (H4) (husbands who work in the agricultural sector are positively associated with their attitudes/views towards WB). This finding contrasts with the results of research by Hayati et al. (Hayati et al., 2011) which showed a significant relationship between types of work in the agricultural sector and physical violence in households.
The number of children has a negative relationship and can explain WB by 106%. This means that the greater the number of children, the greater the chance of WB due neglecting the children. However, this relationship is not significant, p >0.10. This finding is the basis for researchers to reject the fifth hypothesis (H5) (the number of children will be positively associated with the husband's attitude/view of WB). These findings corroborate some previous studies showing that the number of children living in the same house does not contribute to domestic violence (Purwoko et al., 2011; Shiyun et al., 2013). However, the results of this study undermine some research results that show that the number of children living together is a significant predictor of WB (Adebowale, 2018; Kapadia et al., 2010).
The smoking habit has a significant positive relationship and contributes 121% to explain WB. The smokers have the probability of 121% to beat their wives due to neglecting their children. This probability was statistically significant, p <0.001. This finding is the basis for researchers to accept the sixth hypothesis (H6) (smoking habit among husbands will be positively associated with their attitudes/views towards WB). This finding is consistent with the previous research showing a positive association of smoking with IPV (Weaver & Etzel, 2003; Yoshihama et al., 2010). Respondents who have committed adultery have an 82% probability of WB. This relationship is positive and significant, p <0.01. This finding is the basis for researchers to accept the seventh hypothesis (H7) (the practice of adultery among husbands is positively related to their views/attitudes towards WB). This finding is in line with the results of the previous studies showing that men who commit adultery are more likely to commit WB (Abramsky et al., 2011; Grisurapong, 2016; Jones & Ferguson, 2009; Kiss et al., 2012; Silverman et al., 2006; Tang & Lai, 2008).
The relationship between polygamy and WB is positive and significant, p <0.01. This means that those who are polygamous have a 233% probability of engaging in WB due to neglecting their children. This finding is the basis for researchers to accept the eighth hypothesis (H8) (husbands who practice polygamy tend to agree with WB). This finding corroborates the results of previous studies that showed a positive relationship between polygamy and WB (Abramsky et al., 2011; Aduloju et al., 2015; Gibbs et al., 2018; Tsiko, 2016; Vung et al., 2008; Vyas & Jansen, 2018). The variable of household decision-making patterns has a negative but not significant relationship with WB, p >0.10. These results are the basis for researchers to reject the ninth hypothesis (H9) (joint decision-making patterns are negatively associated with husbands' views/attitudes towards WB). This finding contradicts previous studies that showed a significant relationship between the variable household decision-making patterns and WB (Antai, 2011; Hindin & Adair, 2002).
The results of this study also show a negative association between age and WB. This means that respondents aged > 40 years have a 63% chance not not beating their wives due to neglecting their children. This finding is the basis for the researchers to accept the second hypothesis (H2) (the husband's age is negatively associated with his attitude/views towards WB). This finding is consistent with the results of the previous studies which show that young husbands (≤ 35 years) tend to be more potential to become perpetrators of WB compared to older husbands (Hayati et al., 2011; Shamu et al., 2013). This may be due to the psychological maturity and level of economic stability of the husbands, which is believed by some that it may occur at the age of 40.
Furthermore, residence location is also positively associated with WB. This means that respondents in rural areas could commit acts of beating their wives due to the factor of neglecting their children by 125%. This finding is the basis for researchers to accept the third hypothesis (H3) (the location of the residence is positively associated with the husband's attitude/view of WB). The stronger the village characteristics in a residential location, the more likely husbands in that location agree with WB. The H3 is in line with the results of previous research which showed the location of residence as a predictor of IPV (Clark et al., 2008)
Meanwhile, type of occupation has a positive but insignificant relationship with WB, p > 0.10. This empirical finding is the basis for the researcher to reject the fourth hypothesis (H4) (husbands who work in the agricultural sector are positively associated with their attitudes/views towards WB). This finding contrasts with the results of research by Hayati et al. (Hayati et al., 2011) which showed a significant relationship between types of work in the agricultural sector and physical violence in households.
The number of children has a negative relationship and can explain WB by 106%. This means that the greater the number of children, the greater the chance of WB due neglecting the children. However, this relationship is not significant, p >0.10. This finding is the basis for researchers to reject the fifth hypothesis (H5) (the number of children will be positively associated with the husband's attitude/view of WB). These findings corroborate some previous studies showing that the number of children living in the same house does not contribute to domestic violence (Purwoko et al., 2011; Shiyun et al., 2013). However, the results of this study undermine some research results that show that the number of children living together is a significant predictor of WB (Adebowale, 2018; Kapadia et al., 2010).
The smoking habit has a significant positive relationship and contributes 121% to explain WB. The smokers have the probability of 121% to beat their wives due to neglecting their children. This probability was statistically significant, p <0.001. This finding is the basis for researchers to accept the sixth hypothesis (H6) (smoking habit among husbands will be positively associated with their attitudes/views towards WB). This finding is consistent with the previous research showing a positive association of smoking with IPV (Weaver & Etzel, 2003; Yoshihama et al., 2010). Respondents who have committed adultery have an 82% probability of WB. This relationship is positive and significant, p <0.01. This finding is the basis for researchers to accept the seventh hypothesis (H7) (the practice of adultery among husbands is positively related to their views/attitudes towards WB). This finding is in line with the results of the previous studies showing that men who commit adultery are more likely to commit WB (Abramsky et al., 2011; Grisurapong, 2016; Jones & Ferguson, 2009; Kiss et al., 2012; Silverman et al., 2006; Tang & Lai, 2008).
The relationship between polygamy and WB is positive and significant, p <0.01. This means that those who are polygamous have a 233% probability of engaging in WB due to neglecting their children. This finding is the basis for researchers to accept the eighth hypothesis (H8) (husbands who practice polygamy tend to agree with WB). This finding corroborates the results of previous studies that showed a positive relationship between polygamy and WB (Abramsky et al., 2011; Aduloju et al., 2015; Gibbs et al., 2018; Tsiko, 2016; Vung et al., 2008; Vyas & Jansen, 2018). The variable of household decision-making patterns has a negative but not significant relationship with WB, p >0.10. These results are the basis for researchers to reject the ninth hypothesis (H9) (joint decision-making patterns are negatively associated with husbands' views/attitudes towards WB). This finding contradicts previous studies that showed a significant relationship between the variable household decision-making patterns and WB (Antai, 2011; Hindin & Adair, 2002).
Conclusion
This study aims to analyze the predictors of attitudes of married men towards WB. The study results indicate that two independent variables have a negative relationship (age and education level) and the other four independent variables have a positive relationship (adultery, smoking habits, location of residence, and polygamy). This study recommends the government to reform public policy in several sectors, such as education (revise compulsory education program, sex education), social (close and banning localization, unregistered marriage), information (increasing media literacy), tourism (sharia tourism), health (smoke-free zone policy), economic (cigarette tax), and regional development (utilizing village fund to promote gender equality). Finally, the researchers suggest that qualitative research methods can be used to generate unique, in-depth, and detailed knowledge about WB at the household level.
Conflict of interest
The authors declare that there is no conflict interest.
Acknowledgement
Thank you for the USAID who give access to DHS data and for the journal reviewer who provide significant advice for the article improvement.
Author’s contribution
The authors confirm contribution to the paper as follows: study conception and design, D.H.E.; interpretation of results, E.L.; Draft manuscript preparation, Y.; Creating dataset and data analysis, M.Y.; All authors reviewed the results and approved the final version of the manuscript.
References
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Nilan, P., Demartoto, A., Broom, A., & Germov, J. (2014). Indonesian Men’s Perceptions of Violence Against Women. Violence Against Women, 20(7), 869–888. https://doi.org/10.1177/ 1077801214543383
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Vyas, S., & Jansen, H. A. F. M. (2018). Unequal power relations and partner violence against women in Tanzania: A cross-sectional analysis. BMC Women’s Health, 18(1), 185. https://doi.org/10.1186/s12905-018-0675-0
Wang, L. (2016). Factors influencing attitude toward intimate partner violence. Aggression and Violent Behavior, 29, 72–78. https://doi.org/ 10.1016/j.avb.2016.06.005
Weaver, T. L., & Etzel, J. C. (2003). Smoking patterns, symptoms of PTSD and depression: Preliminary findings from a sample of severely battered women. Addictive Behaviors, 28(9), 1665–1679. https://doi.org/10.1016/j.addbeh.2003.08.041
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Adebowale, A. S. (2018). Spousal age difference and associated predictors of intimate partner violence in Nigeria. BMC Public Health, 18(1), 212. https://doi.org/10.1186/s12889-018-5118-1
Aduloju, P. O., Olagbuji, N. B., Olofinbiyi, A. B., & Awoleke, J. O. (2015). Prevalence and predictors of intimate partner violence among women attending infertility clinic in south-western Nigeria. European Journal of Obstetrics & Gynecology and Reproductive Biology, 188, 66–69. https://doi.org/10.1016/j.ejogrb.2015.02.027
Aekplakorn, W., & Kongsakon, R. (2007). Intimate partner violence among women in slum communities in Bangkok, Thailand. Singapore Medical Journal, 48(8), 763–768.
Aisyah, S., & Parker, L. (2014). Problematic Conjugations: Women’s Agency, Marriage, and Domestic Violence in Indonesia. Asian Studies Review, 38(2), 205–223. https://doi.org/10.1080/ 10357823.2014.899312
Amegbor, P. M., & Rosenberg, M. W. (2019). What geography can tell us? Effect of higher education on intimate partner violence against women in Uganda. Applied Geography, 106(March), 71–81. https://doi.org/10.1016/ j.apgeog.2019.03.009
Antai, D. (2011). Controlling behavior, power relations within intimate relationships and intimate partner physical and sexual violence against women in Nigeria. BMC Public Health, 11. https://doi.org/10.1186/1471-2458-11-511
Benson, M. L., Fox, G. L., DeMaris, A., & Van Wyk, J. (2003). Neighborhood Disadvantage, Individual Economic Distress and Violence Against Women in Intimate Relationship. Journal of Quantitative Criminology, 19(3), 207–235. https://doi.org/10.1023/A:1024930208331
Boyle, M. H., Georgiades, K., Cullen, J., & Racine, Y. (2009). Community influences on intimate partner violence in India: Women’s education, attitudes towards mistreatment and standards of living. Social Science and Medicine, 69(5), 691–697. https://doi.org/10.1016/j. socscimed.2009.06.039
Chang, D. F., Shen, B. J., & Takeuchi, D. T. (2009). Prevalence and demographic correlates of intimate partner violence in Asian Americans. International Journal of Law and Psychiatry, 32(3), 167–175. https://doi.org/10.1016/j.ijlp. 2009.02.004
Clark, C. J., Silverman, J., Khalaf, I. A., Ra’ad, B. A., et al. (2008). Intimate Women’s Partner Efforts Violence to Avoid and Interference with Pregnancy in Jordan. Studies in Family Planning, 39(2), 123–132.
Costa, D., Hatzidimitriadou, E., Ioannidi-Kapolou, E., Lindert, J., Soares, J. J. F., et al. (2016). Male and female physical intimate partner violence and socio-economic position: A cross-sectional international multicenter study in Europe. Public Health, 139, 44–52. https://doi.org/ 10.1016/j.puhe.2016.05.001
Eidhamar, L. G. (2018). ‘My Husband is My Key to Paradise.’ Attitudes of Muslims in Indonesia and Norway to Spousal Roles and Wife-Beating. Islam and Christian-Muslim Relations, 29(2), 241–264. https://doi.org/10.1080/09596410.2017.1405636
Flynn, A., & Graham, K. (2010). “Why did it happen?” A review and conceptual framework for research on perpetrators and victims’ explanations for intimate partner violence. Aggression and Violent Behavior, 15(3), 239–251. https://doi.org/10.1016/j.avb.2010.01.002
Fulu, E., Jewkes, R., Roselli, T., & Garcia-Moreno, C. (2013). Prevalence of and factors associated with male perpetration of intimate partner violence: Findings from the UN Multi-country Cross-sectional Study on Men and Violence in Asia and the Pacific. The Lancet Global Health, 1(4), e187–e207. https://doi.org/10.1016/S2214-109X(13)70074-3
Gibbs, A., Corboz, J., & Jewkes, R. (2018). Factors associated with recent intimate partner violence experience amongst currently married women in Afghanistan and health impacts of IPV: a cross sectional study. BMC Public Health, 18(1), 593. https://doi.org/10.1186/s12889-018-5507-5
Grisurapong, S. (2016). 391 Risk factors of Intimate Partner Violence (IPV) of Thai Women. Injury Prevention, 22(Suppl 2), A143.2-A143. https://doi.org/10.1136/injuryprev-2016-042156.391
Hayati, E. N., Emmelin, M., & Eriksson, M. (2014). “We no longer live in the old days”: A qualitative study on the role of masculinity and religion for men’s views on violence within marriage in rural Java, Indonesia. BMC Women’s Health, 14(1), 1–13. https://doi.org/10.1186/ 1472-6874-14-58
Hayati, E. N., Högberg, U., Hakimi, M., Ellsberg, M. C., & Emmelin, M. (2011). Behind the silence of harmony: Risk factors for physical and sexual violence among women in rural Indonesia. BMC Women’s Health, 11, 52. https://doi.org/10.1002/app.10449
Hindin, M. J., & Adair, L. S. (2002). Who’s at risk? Factors associated with intimate partner violence in the Philippines. Social Science and Medicine, 55(8), 1385–1399. https://doi.org/10. 1016/S0277-9536(01)00273-8
Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied Logistic Regression. John Wiley & Sons, Inc.
Jones, J. H., & Ferguson, B. (2009). Demographic and social predictors of intimate partner violence in Colombia: A dyadic power perspective. Human Nature, 20(2), 184–203. https://doi.org/ 10.1007/s12110-009-9064-6
Kapadia, M. Z., Saleem, S., & Karim, M. S. (2010). The hidden figure: Sexual intimate partner violence among Pakistani women. European Journal of Public Health, 20(2), 164–168. https://doi.org/10.1093/eurpub/ckp110
Kiss, L., Schraiber, L. B., Heise, L., Zimmerman, C., Gouveia, N., et al. (2012). Gender-based violence and socioeconomic inequalities: Does living in more deprived neighborhoods increase women’s risk of intimate partner violence? Social Science & Medicine, 74(8), 1172–1179. https://doi.org/10.1016/j.socscimed.2011.11.033
KOMNAS Perempuan. (2019). Korban Bersuara, Data Bicara Sahkan RUU Penghapusan Kekerasan Seksual sebagai Wujud Komitmen Negara: Catatan Kekerasan terhadap Perempuan. Catatan Tahunan Tentang Kekerasan Terhadap Perempuan, 123.
Mallory, A. B., Dharnidharka, P., Deitz, S. L., Barros-Gomes, P., Cafferky, B., et al. (2016). A meta-analysis of cross-cultural risk markers for intimate partner violence. Aggression and Violent Behavior, 31, 116–126. https://doi.org/10.1016/j.avb.2016.08.004
National Population and Family Planning Board (BKKBN), Statistics Indonesia (BPS), The Ministry of Health (KEMENKES), & ICF International (ICF). (2018). Indonesia Demographic and Health Survey 2017. National Population and Family Planning Board (BKKBN), Statistics Indonesia (BPS), The Ministry of Health (KEMENKES), and ICF International (ICF).
Nilan, P., Demartoto, A., Broom, A., & Germov, J. (2014). Indonesian Men’s Perceptions of Violence Against Women. Violence Against Women, 20(7), 869–888. https://doi.org/10.1177/ 1077801214543383
Purwoko, A., Sukiyono, K., & Sigit Priyono, B. (2011). Probabilitasi Terjadinya Tindak Kekerasan Terhadap Wanita dalam Rumah Tangga: Studi pada Masyarakat Berbasis Pertanian di Kabupaten Bengkulu Utara. Sosiohumaniora, 13(1), 58. https://doi.org/ 10.24198/sosiohumaniora.v13i1.5462
Shamu, S., Abrahams, N., Zarowsky, C., Shefer, T., & Temmerman, M. (2013). Intimate partner violence during pregnancy in Zimbabwe: A cross-sectional study of prevalence, predictors, and associations with HIV. Tropical Medicine & International Health, 18(6), 696–711. https://doi.org/10.1111/tmi.12078
Shiyun, S. C., Hazizan, A., Meng, L. X., Wee, L. Y., Hung, S. et al. (2013). Age, Low Education and Unemployment are Associated with Intimate Partner Violence among Women. Indonesian Journal of Obstetrics and Gynecology, 37(2), 63–70. https://doi.org/ 10.32771/inajog.v37i2.339
Silverman, J. G., Decker, M. R., Kapur, N. A., Gupta, J., & Raj, A. (2006). Violence against wives, sexual risk and sexually transmitted infection among Bangladeshi men. Sexually Transmitted Infections, 83(3), 211–215. https:// doi.org/10.1136/sti.2006.023366
Tang, C. S. K., & Lai, B. P. Y. (2008). A review of empirical literature on the prevalence and risk markers of male-on-female intimate partner violence in contemporary China, 1987-2006. Aggression and Violent Behavior, 13(1), 10–28. https://doi.org/10.1016/j.avb.2007.06.001
Tsiko, R. G. (2016). A Spatial Latent Gaussian Model for Intimate Partner Violence Against Men in Africa. Journal of Family Violence, 31(4), 443–459. https://doi.org/10.1007/s10896-015-9784-9
United Nations. (2015). Transforming our world: The 2030 Agenda for Sustainable Development. United Nations.
Vung, N. D., Ostergren, P.-O., & Krantz, G. (2008). Intimate partner violence against women in rural Vietnam—Different socio-demographic factors are associated with different forms of violence: Need for new intervention guidelines? BMC Public Health, 8(1), 55. https://doi.org/ 10.1186/1471-2458-8-55
Vyas, S., & Jansen, H. A. F. M. (2018). Unequal power relations and partner violence against women in Tanzania: A cross-sectional analysis. BMC Women’s Health, 18(1), 185. https://doi.org/10.1186/s12905-018-0675-0
Wang, L. (2016). Factors influencing attitude toward intimate partner violence. Aggression and Violent Behavior, 29, 72–78. https://doi.org/ 10.1016/j.avb.2016.06.005
Weaver, T. L., & Etzel, J. C. (2003). Smoking patterns, symptoms of PTSD and depression: Preliminary findings from a sample of severely battered women. Addictive Behaviors, 28(9), 1665–1679. https://doi.org/10.1016/j.addbeh.2003.08.041
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Type of Study: Original Article |
Subject:
Social Behavior
Received: 2022/09/8 | Accepted: 2022/11/9 | Published: 2022/11/15
Received: 2022/09/8 | Accepted: 2022/11/9 | Published: 2022/11/15
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