The ideal conditions for healthy reproduction involves liberation from pain and diseases, the performance and enjoyment of safe sex activities, the ability to have children and a safe pregnancy and child birth and fertility regulation without compromising their health1. This is consistent with the purpose of marriage, which is to have a happy, healthy family with physical and mental support, protection and affection. Contrary to those expectations, the number of domestic violence cases has been increasing annually. From 2010-2012, the prevalence of violence against women was only 71 cases, but it increased to 92 cases in a period of 2013-20152. Pregnancy requires an extra attention and awareness from the husband, both physically and mentally. In fact, many expectant mothers experience violence. The data showed from 2010-2012, there were 11 cases of violence for expectant mothers, which in 2013-2015 increased to 27 cases3. Based on these data, the research problem can be formulated as "What are the consequences of violence against womens health reproduction? and What is the relationship between socio-demographic factors and health reproduction problems?"
Study by Salam et al.4 found that respondents with parity less than 4 times (>4) are likely to experience pregnancy complication rates of 73.81% compared to 26.2% for respondents with parity of 2-3 times. A higher frequency of parity is riskier than a lower frequency. Research revealed by Luke and Brown5 concluded that age factors and pregnancy complications can be described. Pregnancy complications tend to increase at a young age (<20), decrease at 20-30 years of age and increase again in old age (>30). This means that, younger and older pregnant women tend to be at risk for pregnancy complications.
The complication rate tends to be higher for women with a low education level because they probably do not understand the relationship between complications and other factors. They also have limited access and information about the complications of pregnancy and the ways of handling complications6. The result of this study supports the result of another study by Hutagalung et al.7 in which the authors discovered that 64.5% of respondents with <SLTP (Junior High School) education experienced complications compared to 33.5% of women with >SLTA (Senior High School) education. This pregnancy complication problem is related to the community mind set about education. They assume that education is not a major priority for women. As a result, less educated women generally do not know about pregnancy complications.
Unwanted pregnancy is a health reproduction problem related to the age of women. Expectant mothers over 35 years of age tend to experience more unwanted pregnancies than those under 35 years8. Women over 35 years old of age likely do not want more children because it is very risky. A study Indonesia Demographic and Health Survey9 showed that some older women desire the unwanted pregnancies. Educated women also desired the unwanted pregnancies. The level of a persons education is related to his or her knowledge as a result of rational in thinking, attitude and awareness, including of topics such as family planning8. Prihastuti8, stated that as a result of someone knowledge, people will have wide perspectives and experiences about everything, including their responsibility to have children. The significant rates of unwanted pregnancy categorized by education in women is 0.001%. This means that the education level affects the unwanted pregnancy rate. The data of Indonesian Demographic and Health Survey10 revealed that the birth of unwanted children increased with increasing ages and education. It can be observed by the fertility rate that this number decreases with higher education. Women with >SLTA education showed had desired fertility numbers of 2.1, whereas those with <SLTP education had values between 2.3-2.4.
According to Hartono, the difference in the social economic level for the health facility affected different health qualities of urban and rural communities11. Health Department of Central Sulawesi Province12 showed that the health facility in a city can improve the quality of pregnancy health care. Good pregnancy care is supported by an adequate health facility. Therefore, socio-demographic factors are related to several impacts of violence on womens reproductive health.
MATERIALS AND METHODS
Research method: Donggala Regency consists of 21 sub-districts and is geographically widespread over 10471.71 km2. The study sample was based on purposive sampling. The sample of the sub-district and village was chosen based on the number of violence cases. The data on violence to women obtained by police officer reports of Donggala from January, 2004-December, 2006 revealed that the Banawa district had 15 cases, which is higher than the 9 cases in Marawola. Of these two districts, Sunju and Tanjung Batu were purposively assigned.
Technique of respondent retrieval: A list of all married women of child bearing age between 15-49 years old was made to determine respondents in Sunju village and Tanjung Batu district; the criteria for inclusion were the following:
||Gave birth within 2 years
||Experienced violence in these periods based on information shared with the village midwife, headman and traditional village council
|Table 1:||Respondent distribution in Sunju village and Tanjung Batu based on the respondent characteristics
|Source: Data collection results of the community health center of Tinggede and Banawa|
|Table 2:||Pregnancy complications based on the ages affected by violence
The Community Health Center of Tinggede and Banawa in Sunju village had 70 respondents, whereas the Community Health Center of Banawa in Tanjung Batu District had 117 respondents. Meanwhile, the preview temporary data obtained by the headman and midwives showed that 14 women in Sunju village and 17 women in the Tanjung Batu district experienced violence. There were a total of 218 respondents in both villages/districts (Table 1).
The data were collected through a structured interview, FGD, observation and in-depth interview. Then, they were analyzed using a descriptive percentage analysis method.
RESULTS AND DISCUSSION
Violence affects the reproductive health of women. These impacts could be very dangerous, resulting in pregnancy complications, sexually transmitted diseases, unwanted pregnancy, unsafe abortion, premature birth, low birth weight and loss of sexual desire. The most dangerous impact is maternal and infant mortality. Analysis of the socio-demographics factors affecting reproductive health was performed to identify the socio-demographic characteristics of women who are vulnerable to violence. The analysis is very important for screening health reproduction problems caused by violence. There are some requirements for determining the health problems that are analyzed and counted using chi square testing. Based on the requirements, the analyzed health problem includes pregnancy complications and unwanted pregnancy.
Age: Table 2 shows clear differences in the groups of women who did and did not experience pregnancy complications according to age. Older women (>35 years old) had complication rates of 50.0%, which was followed by rates of 42.1% for younger women (<25 years old). As a result, older women tend to experience more complications than younger women. Most of the time, women who were 25-34 years old experienced violence, but only 10.9% experienced complications. This finding is consistent with the analysis of Felly and Senewe13 that the pregnancy complications tend to occur in older women (>35 years old). The low percentage of women who were 25-34 years old and experienced complications is closely related to the health reproduction maturity age. The age of 20-35 years is a healthy, safe reproduction age.
Wives who are <20 years old are less likely meet their nutritional needs during pregnancy, affecting their immune system. Meanwhile, women who are >35 years old can have deterioration and decreased endurance as well as many disease types, such as hypertension, kidney disease and elevated cholesterol. Both age groups are susceptible to pregnancy complications even if they are less likely to experience domestic violence.
The χ2 value was 14.3 with df = 2 at a significant level of 0.05 and 0.01%. The age factor showed that there is a significant difference among the age groups in terms of pregnancy complications. This conclusion strengthens the study of Salam et al.4 who stated that the age of the mother during pregnancy affects the pregnancy complication rate. Women who are under 20 years old or over 35 years old have a higher risk of pregnancy complications because these age groups have a low hemoglobin level. This study suggests that the frequency of placental abruption caused the increase in pregnancy complications according to the mothers age, particularly for women over 35 years of age. Placental abruption can occur because of prior abdominal impact or from domestic violence during pregnancy. Therefore, there is a meaningful relationship between expectant mothers and the frequency of placental abruption causing pregnancy complications. The results from Jahanfar et al.14 are not in agreement with this; the researchers found that there is no correlation between age and pregnancy complications for expectant women in Perak Malaysia who experienced violence. However, there is a correlation between the prevalence of violence and complications.
Education level: The education level of the expectant mother greatly influences the way they maintain their health and understand pregnancy complications. Women with low education levels tend to experience complications. This could happen because of the lack of understanding of pregnancy complications and other factors. Additionally, women with a low education level have low access to the information about complications. This study showed that the difference in the pregnancy complication status depends on the womans education level. The rate of women who experienced a complication with a low education level is 41.3%, with a secondary education level is 17.9% and with a high education level is 15.0%. This observation is reinforced by the groups of women who do not experience complications. The group of women who are least likely to experience a complication is the group with >SLTA 85.0%, whereas the rate was lowest for those with <SD 58.7%. These numbers showed that women with the highest level of education had the lowest chances of experiencing complications. This means that a low education level can contribute to pregnancy complications (Table 3).
The χ2 value is 7.0 with 2 df and a 0.05% of significant level. The wifes education level was significantly different between educated groups for the rate of pregnancy complications. This observation is in accordance with the research of that the education level affects pregnancy complications. Education can impact how mothers to think when assessing their bodies and reproductive health. Women with higher levels of education engage in more practical pregnancy care. Mothers with a low education level frequently underestimate symptoms or do not take symptoms like bleeding or signs of pregnancy complications seriously.
Total number of living children: Wives who experienced pregnancy complications tended to have >4 children (46.4%). By contrast, women with 2-3 children were more likely to experience violence and in this group, only 14.6% experienced complications. This observation is in accordance with the ideas stated by Chowdhary and Patel15 that the total number of children affects the pregnancy complication rate. Parity of >4 children has a 73.81% complication rate. Meanwhile, parity of 0-2 children has a 26.19% complication rate7 and also said that the use of contraceptives to reduce the number of pregnancies and births is considered to support efforts to prevent pregnancy complications (Table 4).
The result of this study, after testing for statistical significance, revealed that there is a difference in the distribution of the total children based on the pregnancy complication status and that the score is χ2 = 8.3 and df = 2 for a significance level of 0.05. This result is consistent with the analysis of the Indonesian Demographic and Health Survey10 that the parity of >4 increases the risk of experiencing pregnancy complications, which may be related to the mother not being sufficiently ready or physically and psychologically recovered to undergo pregnancy and give birth to the next child. Felly and Senewe13 presented a different idea in analyzing the factors related to the pregnancy complications and the parity based on the data in the Indonesian Demographic and Health Survey10. The researchers found that there is no relationship between pregnancy complications and parity.
Residence: The expectant mothers residence (village or city) is related to the pregnancy complications. Wives in Sunju village had a 47.2% pregnancy complication rate, whereas the rate was 17.2% for women who lived in Tanjung Batu.
|Table 3:||Pregnancy complication caused by violence based on education level
|Table 4:||Pregnancy complication caused by violence based on the total No. of living children
In the village, 80.6% of mothers had not experienced a pregnancy complication and 82.8% of mothers in the city had not experienced a complication. This means that most of the mothers who experienced pregnancy complications lived in the village (Table 5).
The χ2 obtained after significance testing was 9.7 with df 1 and significance levels of 0.05 and 0.01%. There was a significant difference between residence and the pregnancy complication rate. Pregnancy complications tend to occur in expectant mothers who work in intense jobs, such as sand mining in a river and raising sand into trucks. These jobs are draining and can cause pregnancy complications, such as fatigue, fever and headache. Pregnancy complications were more likely in Sunju village than in Tanjung Batu. This conclusion is consistent with Indonesian Demographic and Health Survey10 and Prihastuti8 that women who live in villages tend to experience complications because of their low socioeconomic status. The overall complication rate is low in Tanjung Batu village because recreational spots and entertainment facilities are available to expectant mothers. Expectant mothers who have experienced violence are at risk of experiencing pregnancy complications, such as headache or stress16. Therefore, the availability of relaxation facilities can reduce pregnancy complications.
Description of social demographics relative to pregnancy complications: In identifying the socio-demographic factors related to pregnancy complications caused by violence, age >35 is the most prominent with a violence rate of 50.0%.
|Table 5:||Pregnancy complication caused by violence based on residence
Although, violence is likely experienced by women who are 24-34 years old, the vulnerable age for pregnancy complications tend to occur around >35 years because it is related to maturity of the reproductive age12. By contrast, the age of 20-35 years is a healthy, safe reproductive age. Pregnancy at <20 years of age is biologically, psychologically and economically unstable, making women vulnerable to emotional shocks. Felly and Senewe13 stated that for ages >35 years, women are susceptible to deterioration and decreased body endurance and they have various diseases, such as hypertension, kidney disease and high cholesterol. Data presented in the Indonesian Demographic and Health Survey10 showed for ages >35 years or older, 90.1% of women attended their regular pregnancy checkups, whereas 94.2% of those who were 20-34 years of age attended their regular checkups. Pregnancy complications will not be detected in the early stage if the expectant mother does not frequently go to checkups. Curry et al.17 stated that the risky age groups participate in more intense checkup. The χ2 value supported these findings that although all socio-demographic variables showed differences between the pregnancy complication group and non-pregnancy complication group, the highest χ2 value was found for age, which was 14.7 at a significance level of 0.01 and 0.05 with a contingency coefficient (K) of 0.36. This means that the age variable is closely related to the pregnancy complication rate (Table 6). The relationship between the two variables is strong if the contingency coefficient18 is high, around values of 0 and 1.00.
Age: Age is an important variable influencing unwanted pregnancy because it can be used as a biological maturity indicator, particularly because it influences fertility. The fertility of women is at a level of 0 (zero) before menstruation. With first menstruation (menarche), women enter their reproductive period and the fertility level is no longer zero. Then, the fertility peaks at approximately age 25-29 before it slowly falls back.
|Table 6:||Socio-demographic factors of the respondents who experienced pregnancy complications based on the highest frequency and chi square test according to variables
Source: Processed from Table 2
, *Total respondents who experienced pregnancy complications because of violence, **Total respondents included 27 respondents who experienced pregnancy complications and 67 who did not
This means that the pattern of womens fertility according to their age forms an inverted U pattern. Fertility ends when women experience menopause. Fertility from menarche to menopause typically occurs in the age range of 15-49. But, it is currently assumed that women start their reproductive period earlier than 15 years of age and end at older than 49 years of age19, which could be from improvements in the nutrition level of individuals and the community. Table 7 shows that the rate of unwanted pregnancy is higher in older age (54.5%). Younger women (15-24) did not experience unwanted pregnancy because they were still in the early stages of marriage. Normally, in this stage, women desire children. By contrast, older women, who are in the middle of their marriage (<34 years old) and already have one or two children, want to postpone another pregnancy. Then, women who are >35 years old do not want any more children and this age range is also included in the high-risk pregnancy group.
The χ2 score is 17.4 after testing for significance with df 2 at significance levels of 0.05 and 0.01. There was a significant age factor difference in the rate of unwanted pregnancies. This finding is relevant to the analysis of SKDI 2007, which revealed that the unwanted pregnancy rate is often higher in older women. Prihastuti8 stated that the age of the wife greatly affects the percentage of unwanted pregnancies.
Mothers education level: Table 8 shows that the total of unwanted pregnancies is dominated by women at a higher education level (60.0%) compared to those with a lower education level (8.7%).
There were significant differences in the distribution of the wifes education, which means that the status of unwanted pregnancy scored as χ2 = 20.5 with a df = 2 at significant levels of 0.05 and 0.01. This is in accordance with statements by Nur2 that the unwanted pregnancy rate increases linearly with increased education. This means that women with a higher education level have a lower rate of desiring pregnancy. This symptom is easy to understand because high education enhances a persons knowledge, view and scope. Consequently, educated women can more easily receive new ideas, including negotiating with their husbands to use contraception. Additionally, education will improve womens awareness of the benefits of having fewer children. Therefore, women with a higher level of education tend to limit the number of children they have compared to women who have a lower level of education.
Total number of living children (amh): The distribution of children according to unwanted pregnancy showed that there is no difference in the distribution of the total children with a score of χ2 = 5.6, while the score is 6.87. Although, this relationship is not significant, women with many children women have the highest rate of unwanted pregnancy and then use the contraception. However, because their contraceptive needs are not being met, they continue to have unwanted pregnancies. This finding is relevant to the analysis in SDKI 2007 that 64.2% of married women did not want more children, which increased to 78.7% for women with 3 children. While, the unfulfilled need for KB increased from 9.9% according to SKDI 2003 to 10.0% according to SDKI 2007.
Table 9 shows that the more children women have, the higher the percentage of unwanted pregnancies. The percentage of women with >4 children is 39.3%, which is 17.1% for 2-3 children and 16% for less than 2. By contrast, the group of women desiring pregnancy was more likely to desire pregnancy when they had fewer children. This means that the factor of the total number of children can influence the unwanted pregnancy rate. Currently, women with low parity and women who are recently married do not desire early pregnancies.
Residence: There is a higher tendency toward unwanted pregnancy in Tanjung Batu (31.0%) compared to Sunju (11.1%).
|Table 7:||Unwanted pregnancy according to violence based on age group
|Table 8:||Unwanted pregnancy with violence based on the education level
|Table 9:||Unwanted pregnancy caused by violence based on the total No. of AMH
There are two reasons for this. First, women who live in the city work in the public sector. They are facing responsibilities to manage their work and family time; as a result, they do not desire many children and they tend to use contraception to avoid pregnancy. The choice of productive work is determined by a womans life cycle20. Women have the biological task of giving birth and breast feeding their children in addition to social tasks of parenting and managing the household. The life cycle of a woman is eventually passed. Getting married and having children belong to an important stage of womanhood and wifehood. A womans decision in engage in a productive activity is followed by a decision to balance productive work and reproduction. To achieve this balance and reduce unwanted pregnancies, many women who work outside the home use contraception. Second, women who live in the city clearly tend to experience more unwanted pregnancies because they are mobile and socialize more outside the house instead of having a limited experience as a housewife (Table 10).
Another factor by which residence influenced the unwanted pregnancy rate is the burden of living in a larger city. The high burden of life in the city affects the high burden of childcare, which can impact the unwanted pregnancy rate. There are differences in the residence distribution with a score of χ2 = 4.9 and df = 1 at a significance level of 0.05. This result is relevant to the studies conducted by Irawan21 and Chowdhary and Patel15 in which they stated that women who live in villages and cities have different pregnancy complications.
Description of socio-demographic factors for unwanted pregnancy: The identification of socio-demographic factors that are related to a reproductive health problem (unwanted pregnancy) demonstrated a high influence of the education level with >SLTA (60.0%).
|Table 10:||Unwanted pregnancy caused by violence based on residence
Women in the group of <SD experience the violence more frequently, but the impact of violence is higher in the group of women with >SLTA. Study from Salam et al.4 stated that the unwanted pregnancy rate is linearly increase with the increase in education level. This means that more educated women have a lower percentage of desired pregnancy. This phenomenon is easy to recognize because high education increases womens knowledge, view and scope of social interactions. Data in the Indonesian Demographic and Health Survey10 revealed a similar finding that the rate of undesired pregnancy increased with increasing age and education. The desired fertility number for women with an education level of >SLTA is 2.1, whereas that for >SLTP is between 2.3-2.4. The desired fertility number in the group with >SLTA is 2.5. The high gap in the actual fertility number and the desired fertility contributes to the high percentage of unwanted pregnancy. The nationally desired fertility number is 2.2, but the total fertility number is 2.6. As a result, the Indonesia Demographic and Health Survey10 confirmed that if an unwanted pregnancy can be prevented, the total number of fertility in Indonesia would be 2.2 instead of 2.6. This means that the unwanted pregnancy rate affects the fertility number in Indonesia.
The unwanted pregnancy rate was 23.4% for 94 respondents from two villages. If the sample is more than 94, the complication rate will be higher. The χ2 score showed that not all socio-demographic variables had differences between the groups of desired and unwanted pregnancies. The variable for total children did not show any differences22. The variable for the education level is clearly related to the unwanted pregnancy rate with an χ2 score of 20.5, significance levels of 0.01 and 0.05 and a contingency coefficient (K) of 0.42. This shows that the education level is related to the unwanted pregnancy rate because the K score is higher than that for all other variables. The higher K means that there is a closer relationship between the two variables17 (Table 11).
|Table 11:||Description of socio-demographic factors for respondents who experience violence based on the highest frequency and chi square test according to the variables
Source: Analyzed from Table 2
, *Total respondents who experience unwanted pregnancy because of violence, ** Total No. of respondents included 22 women who experienced unwanted pregnancy and 72 who did not, ***Significant
Reproductive health issues (pregnancy complications) are related to the socio-demographic factors of the women. There are differences in the pregnancy complication rates of women according to their age, education level, total number of living children and location of residence (village/city). Reproductive health issues (unwanted pregnancy) had differences according to the age, education level and residence. There was no difference between the number of living children and unwanted pregnancy rate. This finding complements the theory by Heise23 that pregnancy has a different impact on every woman and the differences are related to socio-demographic factors, such as age, education level, total number of living children and residence. Every woman has different types of socio-demographic factors; as a result, the level of suffering in response to violence is different in every individual.
Therefore, the impact of violence from the husband on the reproductive health of the wife is insufficiently explained by the theory of Heise. There is a need to consider other factors, such as the wifes socio-demographic background.