| Abstract|| |
Objectives : To study the association between women's exposure to marital physical violence with self-reported obstacles to use health facilities, and coverage by medical insurance. Material and Methods : This study was conducted on the 2005 Egypt Demographic Health Survey (EDHS) data. A subsample of 5249 currently-married women were investigated for both ever and the 12 months prior to survey exposure to physical violence by their current husbands, and its association with self-reported obstacles to use health facilities and coverage by medical insurance, adjusting for respondents' age, education, work, residence, wealth index, number of children ever borne, and empowerment in household decisions. Results: A total of 57% and 56% of women reported lack of healthcare provider and lack of drugs as obstacles to use medical care, respectively. Only 14% were covered by medical insurance. Around 29.4% of the studied women had been ever exposed to physical violence by their current husbands; of them 60% had been subjected to it in the 12 months prior to the survey. Logistic regression models showed that exposure to physical violence predicted reporting of the aforementioned two obstacles. Physically abused women were significantly less likely to be covered by medical insurance. Only a small proportion of women: those working, of higher education, higher wealth index or older age cohorts were medically insured. Conclusion: Extending the umbrella of medical insurance along with finding remedies to the existing obstacles of medical care in Egypt would play a significant role in both health sector reform and management of violence against women.
Keywords: Access, Egypt, medical insurance, risk factors, violence against women
|How to cite this article:|
Afifi M. Physical violence, obstacles to accessing healthcare, and insurance coverage of Egyptian currently-married women. Ann Trop Med Public Health 2010;3:2-7
|How to cite this URL:|
Afifi M. Physical violence, obstacles to accessing healthcare, and insurance coverage of Egyptian currently-married women. Ann Trop Med Public Health [serial online] 2010 [cited 2014 Jul 25];3:2-7. Available from: http://www.atmph.org/text.asp?2010/3/1/2/76176
| Introduction|| |
Violence against women (VAW) and exposure to physical abuse is common in Egypt as elsewhere around the Arab world. In a Sudanese study, from October 2001 to February 2002, abuse was reported by 41.6% of literate, married women attending the Arda Medical Center, Omdurman.  Regrettably, only 42.1% of the Sudanese doctors had a fair knowledge of the concept of domestic violence, and 27.4% viewed it as a worthwhile health problem.  Therefore, the barriers to screening cases, such as lack of knowledge and training, insufficient time at clinics and fear of problems with perpetrators should be overcome.  Similar studies had also showed the magnitude of the problem of domestic violence and its determinants in other Arab countries like Jordan and Lebanon. ,,
Health sector reform (HSR) in developing countries has stimulated many debates about the impact of such reform on the vulnerable groups, notably the poorest section and female gender.  Gender and poverty are highly linked to each other. Investing in women is an effective strategy to reduce the burden of poverty. Healthy women are increasingly being seen as the most effective conduit to household welfare.  Moreover, the gender approach to HSR also comprises the cultural factors that influence women's access and utilization of health services, as women have limited freedom to visit health facilities without the permission of their husbands or senior kin. 
Thirty-four percent of the currently-married women sample in the 1995 EDHS were ever beaten by their current husband while 16% were beaten in the year prior to the survey. Ever-beaten women were more likely to report health problems necessitating medical attention than others.  As part of the policy reform agenda of Egyptian Ministry of Public Health (MOPH), health insurance is being expanded to cover more beneficiaries and efforts are being focused on enhancing the quality of health services. Yet, ever-married women reported facing some obstacles to receive medical care in the 2005 EDHS and only 12% of them are covered by any type of health insurance. Insurance is clearly associated with employment; and coverage is concentrated among older women, urban residents, women with a secondary or higher education, and women in the fourth and highest wealth quintiles. 
To the best of our knowledge, no previous study in the Arab countries correlated VAW with their obstacles to use health facilities or their coverage by health insurance. The current study aimed, then, to investigate the relationship between women - ever and 12 months prior to the 2005 EDHS survey - exposed to husbands' physical violence with self-reported obstacles to medical care and coverage by medical insurance, controlling for other predictors such as the respondents' age, education, work, residence, wealth index, number of children ever borne, and empowerment in household decisions.
| Material and Methods|| |
Data of the 2005 EDHS  were downloaded for free from the Demographic and Health Surveys website.  Before downloading data, the author submitted a request to access the data from the site datasets and it was approved before access was granted. Access is only granted for legitimate research purposes. The 2005 EDHS is nationally representative household survey of 19,474 ever-married women's sample aged 15-49, and selected using a multistage sampling technique, to whom a face-to-face structured interview was administered and with a response rate of 99.5% of women completing the questionnaires. The sample design and detailed study methods and tools of the original survey was previously published in detail by El Zanaty and Way. 
The 2005 EDHS provides a wealth of health-related information on fertility, family planning, maternal and child health and nutrition, besides modules on female genital cutting, marital violence, and child maltreatment. Because only 5613 women were investigated for marital violence, of them 5249 were currently married, the current study was a secondary in-depth analysis conducted on the subsample of 5249 currently-married women interviewed for marital violence.
The main three outcome or dependent variables introduced in the different models of logistic regression analysis in the current study were: perception of lack of healthcare provider as an obstacle to receive medical care, perception of lack of drugs as an obstacle to receive medical care, and coverage by health insurance. The independent variables were the respondents' age, education, work, residence, number of children ever borne, empowerment in all household decisions, and wealth index. The relationship of ever and past year exposure to physical violence with the aforementioned outcome variables was investigated, controlling for other predictors, in logistic regression models in a sequential way.
Marital violence in the EDHS 2005 comprised both physical and sexual violence. Physical violence exposure, the variable used in the current study, was defined as pushing, throwing something, twisting arm, slapping, punching, kicking, dragging, trying to strangle or burn, or threatening or attacking with a knife or a weapon.
The empowerment variable was based on summing the women's responses on five questions about who in the household has the final say in decisions related to five specific areas: the women's own healthcare, large household purchases, everyday household purchases, visits to friends and relatives, and what food to cook each day. Woman or joint decision-making with her husband or others was coded "1", whereas husband or someone else alone was coded as "0." A score for empowerment in household decisions' scale was then constructed ranging from 0 to 5, where 5 constituted women empowered in the five areas aforementioned. Then, the score was dichotomized into "1" for those who scored 5 (highly empowered in all the decisions), and "0" which is the reference category representing women of low empowerment (i.e., only empowered in 4 or less household decisions).
The wealth index is a proxy for long-term standard of living of the household. It is based on the data collected in the 2005 EDHS households' ownership of consumer items such as a fan to a television and car; dwelling characteristics such as flooring material; type of drinking water source; toilet facilities; and other characteristics that are related to wealth status. Each household asset for which information is collected is assigned a weight or factor score generated through principal components analysis. The resulting asset scores are standardized in relation to a standard normal distribution with a mean of zero and a standard deviation of one. The wealth index has been compared against both poverty rates and gross domestic product per capita for India, and against expenditure data from household surveys in many countries. The evidence from those studies suggests that the assets' index is highly comparable to conventionally measured consumption expenditures. , Moreover, in a recent study "Poor women" are defined as those who belong to the bottom quintile of households arrayed according to the widely accepted asset-based wealth index. 
Data analysis were conducted using SPSS for Windows, Version 12.  Data are given as counts, percentages, and means. After doing the univariate and bivariate analysis for the study variables, different logistic regression models were run to get the most significant associated predictors adjusted for each other to the outcome variables aforementioned. The outcome dichotomous variables were coded 0 and 1. The odds ratio which shows the change in the odds of dependent variable(s) when the independent variable(s) changed from 0 to 1 in case of binary independent variables, or the next category or score in case of categorical or continuous variables, adjusted for other variables in the model. P value equal or below 0.05 was considered significant in all statistical tests.
| Results|| |
The sample of currently-married women, investigated for exposure to marital physical violence was 5249 women. Their mean age was 33.09 years (SD = 8.48). Those who had completed their secondary education or higher constituted 42.1% whereas 18% of the whole sample was working for cash. Urban residents constituted 44.8% of the sample. While 44.8% of the sample was empowered in all household decisions, 29.4% of the sample were ever exposed to physical violence by their current husbands, of them 60% were exposed to it in the 12 months prior to the survey. Around 57% and 56% of the currently-married women perceived lack of healthcare provider and lack of drugs as a significant obstacle for them to receive medical care, respectively. Only 13.6% of the sample was under the coverage of health insurance [Table 1].
Ever exposure to physical violence predicted the perception of two investigated obstacles of medical care. Similarly, it predicted being non-covered by health insurance till work status variable was entered in the model where exposure to violence stopped holding its significant relationship with the outcome variable. It denoted how significant employment in predicting health insurance coverage is (adjusted OR = 25.53). Empowered in all household decisions, richer wealth index and older age significantly and independently predicted insurance coverage. Conversely, empowered women and those with higher wealth index were less likely to report the lack of health providers or drugs as obstacles to receive medical care [Table 2]. Exposure to physical violence in the 12 months prior to the survey predicted the same aforementioned outcome variables in a similar pattern in [Table 3]. Other significant variables also showed a nearly similar pattern of relationship with the outcome variables.
|Table 2 :Relationship of ever exposure to physical violence (adjusted OR) with obstacles to access and insurance coverage outcomes in logistic regression models|
Click here to view
|Table 3 :Relationship of 12 months' prior to survey exposure to physical violence (adjusted OR) with obstacles to access and insurance coverage outcomes in logistic regression models|
Click here to view
| Discussion|| |
Despite the increasing recognition that domestic violence is a global public health concern, population-based studies of violence against women, its determinants and consequences remain scarce in developing countries.  The current study has examined and proved the association of ever and past year exposure to marital violence with self-reporting of some obstacles to access health services and coverage by medical insurance, adjusting for other covariates in multivariate logistic regression models. The study highlighted the importance of gender perspective in HSR. Extending the umbrella of medical insurance along with finding remedies to the existing obstacles of medical care in Egypt would play a significant mutual role in both HSR and management of VAW.
Relative to the majority of the countries of the Eastern Mediterranean, Egypt had an advanced order as regards health manpower rates per 100,000 population.  However, the majority (57%) of Egyptian women reported lack of health providers as a substantial problem to access healthcare services. Unfortunately, research on the perceptions of what constitutes quality of care from the viewpoint of male and female healthcare users is scarce.  Previous studies identified interpersonal relations and provider-client relations as a key component of quality of care. ,, While certain supply aspects of quality of care, such as condition of infrastructure and equipment, presence of adequate supplies of drugs, and organizational aspects of work flow and human resource utilization, can be improved and evaluated in a fairly objective manner, those aspects of quality that touch upon the demand aspects of the client-provider relationship are much more difficult to address.  Pittman and Hartigan  grouped existing research on the link between gender and quality of care according to the following four aspects: (1) differences in providers' attitudes toward female and male patients; (2) differences in behavior of providers in caring for female and male patients; (3) differences between male and female providers' attitudes and behavior toward patients; and (4) appropriateness of norms and protocols for women, given the biological and psycho-socially constructed differences between the sexes that determine specific health needs.  Male physicians tend to be more authoritative, less communicative, less interested in establishing dialogue, and engaging the client in a collaborative exploration for the amelioration of a health problem. ,, Therefore, women reporting lack of healthcare providers seem to imply lack of communication rather than its literal meaning. Moreover, gender issues are highly related to quality of care and hence, healthcare providers as well as policy-makers should have a gender perspective in HSR. Adopting qualitative methods to ensure gender equity in healthcare and improving provider-client interaction and humanity of health services are still needed as recommended by many researchers. ,,,
The current study showed that physically abused women were significantly less likely to be covered by medical insurance. Only a small proportion of women: those working, of higher education, higher wealth index or older age cohorts were medically insured. No urban-rural disparity in insurance coverage was seen after adjusting for other covariates. It seems that extending the umbrella of medical insurance along with finding remedies to the existing obstacles of medical care in Egypt would play a significant role in the identification and management of those exposed to physical violence.
Notwithstanding the importance of the study, it has its limitations. Potential biases in self-reported data and the difficulty to verify its accuracy other than through consistency of reporting is also another limitation. Also, some women may have been unwilling to report exposure to marital violence to the interviewer because they associated such experiences with shame, guilt, fear, or blame.  The most disturbing aspect of VAW is the extent to which it remains hidden. Another study under the peer review process by the author implied that an Egyptian woman would adopt the "culture of silence" till she was badly hurt by her husband. Women approached institutional help only when they could not endure anymore or the violence became life-threatening.  Finally, the study did not provide a clear picture of the nature of association between physical violence and the investigated outcome variables due to the complexity of the variables studied. The cross-sectional nature of the current study design precludes us from (dis)proving causality and temporality nature between the studied variables. Our data would not tell us whether physical abuse to women led to the increased likelihood of reporting access obstacles or abused women were subsequently more likely to express their perception on the quality of care.
The author would like to underscore some of the recommendations put forth in 2006 by the World Health Organization (WHO)  for the prevention and control of violence against women. These recommendations are: promote gender equality and women's rights, the need of multisectorial action plans to address the issue, enlist leaders in speaking out against VAW, establish information systems to monitor VAW, work on programs for primary prevention, develop a comprehensive health sector response to various impacts of VAW, use reproductive health services as an entry point for identification and management of VAW, sensitize legal systems for the needs of victims, and support research on the causes and consequences of VAW. 
Despite the study limitations, this study has its strengths. With its nationally representative large sample size, it contributes to the literature by estimating the prevalence of ever and 12 months' exposure to physical violence among Egyptian current-married women in 2005, and its correlates. It would also add to the existing knowledge on VAW, the later association with perception of obstacles to healthcare and poor coverage by medical insurance in Egypt. Bridging the gap of inequity in coverage, extending the umbrella of medical insurance coverage and developing a comprehensive gender-sensitive health sector response to various impacts of VAW should go in parallel to ensure HSR in Egypt. However, future research is still needed from other developing countries with similar obstacles to access care and limited medical insurance coverage to validate our results as well as to in-depth qualitative studies for further explanation of our findings.
| References|| |
|1.||Ahmed AM, Elmardi AE. A study of domestic violence among women attending a medical centre in Sudan. East Mediterr Health J 2005;11:164-74. |
|2.||Ahmed AM, Abdella ME, Yousif E, Elmardi AE. Response of Sudanese doctors to domestic violence. Saudi Med J 2003;24:1077-80. |
|3.||Shakhatreh FM, Maaitah RM, Gharaibeh MK. Psychosocial functioning and determinants of domestic violence among women. An epidemiological study. Saudi Med J 2005;26:343-5. |
|4.||Khawaja M. Domestic violence in refugee camps in Jordan. Int J Gynaecol Obstet 2004;86:67-9. |
|5.||Khawaja M, Tewtel-Salem M. Agreement between husband and wife reports of domestic violence: Evidence from poor refugee communities in Lebanon. Int J Epidemiol 2004;33:526-33. |
|6.||Standing H. Gender and equity in health sector reform programmes: A review. Health Policy Plan 1997;12:1-18. |
|7.||World Bank. A new agenda for women′s health and nutrition. Development in practice series. Washington DC: World Bank; 1994. |
|8.||Al Riyami AA, Afifi M, Mabry R. Women′s autonomy, education and employment in Oman and their influence on contraceptive use. Reproduct Health Matter. 2004;12:144-154. |
|9.||Diop-Sidibe N, Campbell JC, Becker S. Domestic violence against women in Egypt - Wife beating and health outcomes. Soc Sci Med 2006;62:1260-77. |
|10.||El-Zanaty F, Way A. Egypt Demographic and Health Survey 2005. Cairo, Egypt: Ministry of Health and Population, National Population Council, El-Zanaty and Associates, and ORC Macro; 2006. |
|11.||MEASURE DHS. Demographic and Health Surveys. Available from: http://www.measuredhs.com/login.cfm [last accessed on 2006 Oct 10]. |
|12.||Filmer D, Lant P. Estimating Wealth Effects without Expenditure Data-or Tears: An Application to Educational Enrollments in States of India. World Bank Policy Research Working Paper No. 1994. Washington, DC: Development Economics Research Group (DECRG), The World Bank; 1998. |
|13.||Rutstein S. Wealth versus Expenditure: Comparison Between the DHS Wealth Index and Household Expenditures in Four Departments of Guatemala, 1999. |
|14.||Kishor S, Johnson K. Reproductive health and domestic violence: Are the poorest women uniquely disadvantaged? Demography 2006;43:293-307. |
|15.||SPSS Inc. SPSS for Windows, Version 12.0 [Software]. Chicago, IL: SPSS Inc.; 2003. |
|16.||Koenig MA, Ahmed S, Hossain MB, Khorshed Alam Mozumder AB. Women′s status and domestic violence in rural Bangladesh: Individual and community level effects. Demography 2003;40:269-88. |
|17.||WHO. Demographic, social and health indicators for countries of the Eastern Mediterranean. WHO, Regional Office for the Eastern Mediterranean; 2006. |
|18.||Haddad S, Fournier P, Machouf N, Yatara F. What does quality mean to lay people? Community perceptions of primary health care in Guinea. Social Science and Medicine 1998;47:381-94. |
|19.||Huntington D, Schuler SR. The simulated client method. Evaluating client-provider interactions in family planning clinics. Stud Family Plan 1993;24:187-93. |
|20.||Mensch B, Fisher A, Askew I, Ajayi A. Using situation analysis data to assess the functioning of family planning clinics in Nigeria, Tanzania, and Zimbabwe. Stud Family Plan 1994;25:18-31. |
|21.||Peabody JW, Rahman O, Fox K, Gertler P. Quality of care in public and private primary health care facilities: Structural comparisons in Jamaica. Bull Pan Am Health Org 1994;28:122-41. |
|22.||Hartigan P. The importance of gender in defining and improving quality of care: Some conceptual issues. Health Policy Plan 2001;16:7-12. |
|23.||Pittman P, Hartigan P. Gender inequity: An issue for quality assessment researchers and managers. Health Care Women Intl 1996;17:469-86. |
|24.||Levy S, Dowling P, Boult L, Monroe A, McQuade W. The effects of physician and patient gender on preventive medicine practices in patients older than fifty. Family Med 1992;24:56-61. |
|25.||Delgado A, Lopez-Fernancez L, Luna J. Influence of the doctor′s gender in the satisfaction of the users. Med Care 1993;31:795-800. |
|26.||Franks P, Clancy C. Physician gender bias in clinical decision-making: Screening for cancer in primary care. Med Care 1993;31:213-8. |
|27.||Fonn S, Mtonga AS, Nkoloma HC, Bantebya Kyomuhendo G, daSilva L, Kazilimani E, et al. Health providers′ opinions on provider--Client relations: Results of a multi-country study to test Health Workers for Change. Health Policy Plan 2001;16:19-23. |
|28.||Fonn S, Xaba M. Health Workers for Change: Developing the initiative. Health Policy Plan 2001;16:13-18. |
|29.||Onyango-Ouma W, Laisser R, Mbilima M, Araoye M, Pittman P, Agyepong I, et al. An evaluation of Health Workers for Change in seven settings: A useful management and health system development tool. Health Policy Plan 2001;16:24-32. |
|30.||Pittman P, Blatt G, Rodriguez P. An assessment of Health Workers for Change, a quality of care intervention, in Allevaneda, Province of Buenos Aires, Argentina. Health Policy Plan 2001;16:40-6. |
|31.||Gage AJ. Women′s experience of intimate partner violence in Haiti. Soc Sci Med 2005;61:343-64. |
|32.||Naved RT, Azim S, Bhuiya A, Persson LA. Physical violence by husbands: Magnitude, disclosure and help-seeking behavior of women in Bangladesh. Soc Sci Med 2006;62:2917-29. |
|33.||WHO Multi-country Study on Women′s Health and Domestic Violence against Women. Available from: http://www.who.int/gender/violence/who_multicountry_study/en/ [last accessed on 2006 Dec 25]. |
Department of Non-Communicable Diseases Control, M.O.H (HQ), P.O. Box 393, P.C. 113, Muscat
[Table 1], [Table 2], [Table 3]