The Social Determinants of Healthcare Access for Rural Elderly Women - A Systematic Review of Quantitative Studies

2.1. Search Strategy

Literature search was undertaken (PROSPERO: CRD42016046605) across major electronic databases including MEDLINE and MEDLINE In-Process, PsycINFO, PubMed, ProQuest, Web of Science, CINAHL and ERIC. A combination of several key words along with their synonyms was used in the search including ‘healthcare access’, ‘healthcare utilization’, ‘healthcare resources’, ‘access barriers’, ‘socioeconomic factors’, ‘healthcare’, ‘health seeking behavior’, ‘elderly’, ‘older women’, ‘rural women’, ‘rural health’, and ‘remote areas’. This search was conducted from April 2016 to August 2016. A manual search was also conducted of the relevant references of retrieved articles, citations by authors, hand searched articles and experts’ opinions. The search and selection strategy was developed by the principal author and reviewed and checked by the other authors and one librarian [9].

2.2. Data Selection Strategy

Only peer reviewed empirical quantitative studies published from January 2000 to August 2016 in English were considered. To be included in this review, a study had to have REW as research participants. Additionally, studies were included if they investigated determinants of healthcare access in relation to preventive measures, communicable and non-communicable diseases, and reported at least one of the MHS access related outcomes. Studies on interventions targeted at the identification of the determinants and its association with healthcare utilization for REW were included. Studies that were excluded included literature reviews, secondary analyses of data and if the data were not specific to determinants of REW’s healthcare access. Studies were also excluded if they reported healthcare access from non-relevant aspects or specialized care such as the use of complementary and alternative medication, exercise, pre-natal care and pregnancy, reproductive healthcare, childbirth and post-natal care, dental care, cancer care, HIV and palliative care. No country or follow-up study restrictions were applied.

2.3. Data Extraction Process

The initial literature search identified 6899 citations. There were 473 articles of potential interest and, after examination of the full texts, 38 quantitative studies met all inclusion criteria apart from the provision of explicit healthcare outcomes for REW (See Fig. 1). A checklist was used based on the guidelines from the Centre for Reviews and Dissemination (CRD) for assessing the quality of each study [10]. The data synthesis and analysis processes followed the CRD guidelines. Each article was assessed for methodological quality following several criteria namely: relevance to this systematic review; validity and appropriateness of methodology and instruments used; quality of research evidence such as generalizability of the findings; reporting quality in terms of data analysis process; and stated limitations in the study and how these limitations were adjusted [10].

Information was extracted from each study about authors, years, settings, participants, research methods and findings on the stated determinants in relation to healthcare access and healthcare seeking (See Table 1). Most of the studies included different population groups in their investigation and only one study identified that solely investigated REW’s healthcare access in USA. Thus, the authors selected the studies that included at least 10% REW of the total study population and reported the determinants of the REW’s healthcare access differently. These determinants were related to: (i) the REW such as literacy; (ii) the economic condition such as poverty; (iii) the medical treatments including health seeking beliefs and behaviors; (iv) the healthcare system including accessibility and adequacy of healthcare facilities; and (v) sociocultural status including mobility and social relationships.

2.4. Data Analysis Process

Meta-analysis of the data was inappropriate because of the heterogeneity in the studies including socioeconomic and cultural differences in low, middle and high income countries, the collected data, designs and settings. Extracted information from the selected studies was tabulated and significant SDoH were included. Multifaceted relationships between the SDoH were identified and grouped into themes using a combination of thematic and content analysis. The model developed by Braveman, Egerter & Williams in 2010 was employed because of its categorization of the SDoH that can provide structure to the identified evidence in the discussion chapter. Two broad categories in the SDoH were identified focusing on healthcare inequalities and disadvantages, including downstream and upstream SDoH [11]. Downstream SDoH mean the factors that impact on healthcare at macro level, and they include health knowledge, perceived healthcare seeking behaviors and healthcare support [11]. Upstream SDoH mean the inequalities in socioeconomic and cultural circumstances, which are fundamental causes of low healthcare access [11]. Applying this model distinguished the determinants, often intertwined in personal, healthcare, socioeconomic and cultural factors.

3.1. Health Literacy and Education

The association of the health literacy of REW and their healthcare access was significant, which was closely related to a lack of general education and lack of knowledge about health and healthcare among REW [12, 13]. Nineteen studies found that schooling was a statistically significant determinant in REW’s access to MHS. The REW with formal education were more likely to visit MHS early and regularly than women with no formal education in low/middle and high income countries [14-18]. In contrast, education attainment showed a weak positive relationship with the utilization of MHS among Filipino elderly women (r = 0.152), while 66.78% had at least a high school level of education [19]. Differences in the level of education among the REW living in South Africa [six and more years of education had a twofold increased odds of using healthcare compared to those with no formal education: p < 0.05 (p = 0.001) (OR: 2.49; CI: 1.27 - 4.86)] and Israel [3% in the variability among the age groups] were identified as significant in using MHS [12, 18]. As such, education levels of REW was a strong indicator in access and utilisation of MHS.

Three studies indicated that the utilization of MHS by REW increased with the knowledge about health and healthcare services [12, 20]. Knowledge about health conditions and availability of MHS was a determinant for REW [0.6%] in MHS use in low/middle income countries like South Africa [12]. Less than one-third (28.7%) of the REW were aware of their health needs in Nigeria [14]. Pullen, Fiandt, & Walker (2001) also highlighted that there was a lack of information about the existing availability of MHS among REW, where healthcare practiners’ recommendations made significant contribution to regression equation [Beta weight - 69] in a high income country like USA, which impacted on visits to the healthcare centres and also influenced healthcare seeking behaviours.

3.2. Passive Healthcare Seeking Behavior

A significant relationship between passive healthcare seeking behavior of REW and healthcare access was identified in several studies, and these behaviors included: a feeling of not being ill enough, self-treatment tendencies, mistrust of modern healthcare services, depression and perceived stigma.

Six studies found that the reason women did not seek assistance from MHS for ailments was because the women did not consider their ailment sufficiently serious until they appeared as physical symptoms. In their view, they were not feeling unwell enough [12, 21-24]. Cheng et al. (2005) identified that 25% of REW living in China did not know whether their health problems were serious enough to visit a hospital. In Nigeria, 57% of REW indicated the non-seriousness of the ailment was a reason to not use a MHS [24]. Additionally, REW who did receive healthcare were less likely to use medication in a timely manner as prescribed [21, 22]. Studies by Onwubiko et al. (2014) and Nipun et al. (2015) established that the feeling of not being ill enough substantially increased the chances of REW’s reluctance to visit healthcare centers and use medications in two low income countries (i.e., Nigeria and India).

Three studies identified a significant relationship between self-treatment tendency and the utilization of MHS [25-27]. Jordan, Wilson, & Dobson (2011) indicated, in Australia, that only 48% REW received advice about diet, 20% about exercise and 10% having been advised to weigh them daily. This resulted in an interest in home remedies, traditional healers and over-the-counter medications for self-treatment rather than visiting hospitals, especially in low income country like Bangladesh [26]. The tendency of self-care was also statistically evident in USA [p < 0.05], however, not as significant as in low income countries like Nigeria [P < 0.05; OR: 1.7 (95% CI= 0.38-0.67] [14, 27]. This healthcare seeking behavior in combination with a mistrust of MHS had a negative impact on REW’s access to MHS.

Several studies demonstrated that mistrust was directly related with a decrease in the use of MHS [19, 24, 28-31]. Rural elderly women living in Australia who visited healthcare centers stated a lower satisfaction with GP, specialist or allied health professional than urban women and this was significantly associated [p < 0.01] with their access to MHS [28]. In India, REW most often visited healthcare professionals who were well-known to them and were perceived as having a simple approach and being culturally competent [6.0% reported as a barrier] [30]. Additionally, there was a positive belief among REW women about the use of spiritual healing in low/middle income countries such as Nigeria [20.2% reported as a barrier], South Africa [p < 0.001], and India [15.8% reported as a barrier] [24, 29, 30]. This lack of faith in doctors and nurses and the positive beliefs about spiritual healing led REW to visit traditional healers rather than MHS.

The mental health of REW also had an influence on healthcare access with those suffering from depression less likely to use MHS [32-36]. In Pakistan, depression of elderly women was also evident which contributed to not using MHS [p < 0.001], but this depression was related to natural calamity [32]. Living with depression increased a sense of helplessness for REW in seeking MHS even in high income countries such as Switzerland [p = 0.008 (OR 6.4, 95% CI 1.6 - 24.8] and Australia [P value is not reported] and in USA [p < .001] [33-35]. This state of depression resulted in REW not seeking MHS.

Three studies identified that perceived stigma was involved in access to MHS and this stigma is associated with having any illness impacted on the REW healthcare access to MHS in Nigeria [20.2% reported as a barrier] and India [49.6% reported as a barrier] [24, 30]. Discrimination of REW in the form of dominance and disempowerment contributed to perceive stigma in these low income countries. The REW who attributed stigma as a factor in not seeking healthcare at a MHS significantly related this stigma as being the reason for a lack of healthcare support.

3.3. Lack of Healthcare Support

The prevailing healthcare system played a statistically significant role in restricting REW’s use of MHS. Determinants identified in relation to MHS included limited care services, inadequate healthcare professionals, a scarcity of medical equipment and medications, long waiting times, poor attitudes of care workers and lack of health insurance coverage. Each of the determinants had an association with limited access for REW.

Studies showed that healthcare access was associated with the availability of services for REW and acknowledged the limitation of healthcare centres and services for REW [27, 31, 37, 38]. In contrast, only one quantitative study conducted in Nigeria reported that most REW [89.4%] received treatment with the availability of MHS for themselves [14]. Whilst two seperate studies conducted in a USA [p < 0.01] and Germany [p < 0.05 (p = 0.023)] reported a lack of pharmacies and outpatient non-physician services, studies conducted in low income countries confirmed that there were a small number of hospitals or clinics in rural areas of Nigeria [2.8% reported as a barrier] and Ghana [47.8% reported as a barrier] [14, 15, 31, 37]. Rural elderly women who lived near a rural care centre were more likely to access and receive adequate healthcare than the women without a close healthcare centre in both low/middle and high income countries [15, 32]. Healthcare services not being close by and a shortage of doctors and nurses in healthcare centres were identified in the studies as impacting negatively on healthcare access for REW.

Inadequate numbers of doctors and nurses in rural healthcare centers were attributed to the use of MHS [12, 21, 32, 38]. A shortage of healthcare professionals identified impacted on REW’s access to MHS in Nigeria [2.8% reported as barrier], Ghana [54.2% reported as a barrier] [14, 15]. Moreover, there was a reported significant shortage of specialist doctors and nurses in rural healthcare centers in the USA [p < 0.001 ] and they were rarely available in low income countries like Ghana [61.7% reported it as a barrier] and South Africa [3.4% reported as a barrier] [12, 15, 39]. As such, a shortage of healthcare professionals impacted on healthcare access for REW and this access was further hindered by the supply of medical equipment and medications.

A number of the studies identified an association between the lack of supply of medical equipment and medications and the use of MHS. Rural elderly women living in low income countries like Ghana [54.2% reported as a barrier] and South Africa [7.3% reported as a barrier] were less likely to use local healthcare services due to a lack of medical equipment and medications [12, 15]. Healthcare utilization was also impacted on by a poor supply of medications in rural healthcare centers in Germany [p < 0.05 (p = 0.019)] [15]. Living in rural areas of low income countries was positively affected by an inadequate supply of equipment and medications that in turn resulted in a poor utilization of MHS.

Association of waiting a long time to be seen and treated in care centers also affected the use of MHS. The experience of long waiting times impacted negatively on REW’s visits to local public healthcare centers in Nigeria [3% reported as a barrier], India [16% reported as a barrier], USA [p < 0.05] and China [24% empty nesters reported as a barrier] [14, 23, 39, 40]. No study found in both low income and high income countries that reported the the avarage waiting times in seeking care [23, 38, 39, 41].

The attitude of healthcare professionals had a negative and statistically significant effect on MHS use [12, 40]. Ameh et al. (2014) highlighted that the attitudes of doctors and nurses at first visit [6.7% empty nesters reported as a barrier] were significantly associated with the use of healthcare services in subsequent visits in South Africa. Rural elderly women expressed their dissatisfaction with the way they were treated by doctors and nurses in a number of low income countries including South Africa, China and India [29, 30, 40]. Experience of mistreatment included receiving no or little attention, as well as a perception of receiving incorrect medical treatment [30, 40]. This experience of mistreatment by REW was a negative factor impacting on subsequent access to healthcare centres.

Lack of healthcare insurance coverage was another important barrier in the use of MHS. Rural elderly women who had healthcare insurance were more likely to use healthcare than non-policy holders in low income countries such as Brazil [(outpatient: 2.42 (2.11–2.77); (any hospitalization: 1.18 (1.03-1.36) and more than one hospitalization: 1.18 (0.91-1.52)] and Ghana [75% of health insurance policy holders said they utilize care facilities as against 56.2% of non-policy holders] [15, 17]. Healthcare insurance also had a positive affect on improving access for REW living in the USA [p < 0.05 (p = 0.0001)] [31, 42]. However, Ameh et al. (2014) identified that a small number of REW, who received free consultations and medications under government schemes in South Africa, better utilised MHS. Only three studies assessed the effect of health insurance on REW’s MHS use in low income countries [12, 15, 22]. Those REW with healthcare insurance were more likely to access MHS and access was also influenced by free healthcare and the financial resources available to them.

3.4. Financial Constraints

Most studies indicated a statistically significant association between financial constraints and REW’s healthcare access. The economic factors identified included levels of poverty, the cost of treatments and a lack of finances whether personal, from the family or the government. The impact of each of these determinants negatively affected healthcare access for REW.

The association between poverty and access to MHS was identified as one of the most important SDoH in the non-use of MHS and included individual poverty and household poverty [14, 16, 17, 21]. Elderly women who had no or low incomes and personal savings were less likely to use healthcare from MHS in rural Bangladesh [p < 0.05 (OR 0.75; CI 0.60 - 0.95)] and in India [p < 0.05 (OR 2.00, 95% CI 0.84-4.80)] [26]. There was no difference identified between low/middle and high income countries in relation to the impact of personal income on healthcare use, which was also determined by the household’s economic status [12, 16, 21, 23]. The higher the household economic status meant the more positive and statistically significant impact on the adequate use of MHS in Nigeria [OR: 0.46 (0.38 - 0.67)] and India [p < 0.05 (p = 0.0409)] [14, 23, 26]. Poverty was also statistically significant in meeting the costs of medical treatments and this led to less health seeking and a low use of MHS.

Some studies indicated an association of the costs of seeking treatments (i.e. transportation, fees for physicians, laboratory tests and medications) with MHS use. For example, REW who sought healthcare were restricted in using MHS regularly because of the high cost of treatments [24, 28, 43]. In contrast, free and/or subsidized healthcare support enhanced the utilization of MHS in Nepal, which more men received free care than women [(56% of men, 35% of women, P= 0.073)] [43]. This subsidized healthcare support was also evident in Australia that contributed to the increase of the rate of MHS utilization among REW [38, 44]. A low economic capacity influenced REW seeking healthcare and was identified as due to a lack of financial support from family members and the governments.

Three studies found that REW who perceived they had adequate support from family members and the government were more likely to use MHS [22, 30, 32]. Disinterest of younger family members in spending money on elderly women in the family also resulted in REW reduced use of MHS in India [p < 0.05 (OR 2.04, 95% CI 1.09-3.83)] and Pakistan [p < 0.001] [22, 32]. Furthermore, REW who did not receive financial support from the government in India were less likely to use MHS than elderly women who had such support [p < 0.05 (OR 2.13, 95% CI 1.11-4.07)] [22]. Living in a low income country was statistically associated with a lack of financial support from both the family and the government, and this significantly impacted on their access.

3.5. Transportation Difficulties

Access to MHS was affected by geographical accessibility factors including distances, travelling and transportation [18, 21, 23, 32, 44, 45]. A long distance to healthcare centers reduced the number of regular visits for REW in both low/middle and high income countries [14, 15, 44, 46]. Long distances caused increased travel time and led REW to fewer visits to healthcare centers in Ghana [p < 0.05 (p = 0.021)], India [28.4% reported as a barrier] and Vietnam [p < 0.05] [15, 22, 47]. Several studies reported an association of inconvenient transportation with the non-use of MHS and this inconvenience was related to the unavailability in low/middle income countries like South Africa [1.1% reported it as a barrier] and Ghana [p < 0.05 (p = 0.001)] and also discomfort in using transportation in USA [p < 0.05 (p = 0.02)] [12, 15, 42]. Consequently, the distance and travel time in combination with an inadequate transportation system were significant barriers [32, 40]. Thus, living in rural areas was positively associated with the problems of transportation that impacted on visits to healthcare centers. Being reliant on family members for transportation and access to MHS made family relationships another important factor for REW accessing healthcare.

3.6. Relationship Matters

A reliance on social and family relationships had a statistically significant impact on REW’s access to MHS with poor quality relationships negatively influencing the access [30, 33, 48]. Chan & Griffths (2009) and Onwubiko et al. (2014) found that REW who had a feeling of social loneliness were less likely to use MHS in Pakistan [p < 0.01] and Nigeria [p = 0.01 (OR 2.26; CI 1.41-3.63)]. Isolation from intimate relationships increased the chances of vulnerability and an unwillingness to utilize medical treatments as REW often needed someone to help them in travelling and seeking healthcare [24]. Three studies also indicated a relationship between healthcare access and social networks [30, 32, 40]. Liu et al. (2007) reported that decreasing social networks also led REW to use medical treatments in an inappropriate way in China [p < .05]. Dependency of REW on their friends, family and neighbors in seeking healthcare was compounded when they were more likely to lose their friends as they aged that then resulted in less access.

3.7. Culture of Restriction

The cultural determinants included family restrictions on mobility and or a dependency on male family members. Being an aged woman, resulted in limited autonomy to travel alone to healthcare centers in both Switzerland [p < 0.05 (p = 0.003)] and Vietnam [p < 0.005 ] [33, 47]. Though the causes were not clear, this restriction in movement impacted on the use of MHS, and in some countries was also influenced by being dependent on male family members. Three studies indicated that REW were dependent on family members, male family members in particular, in relation to receiving in-home help, accompaniment in travelling to the healthcare centers and in managing healthcare [33, 37, 49]. Rural elderly women who were mostly dependent on family members were less likely to use MHS in Switzerland [p < 0.05 (p = 0.031)] and in Germany [p < 0.05 (p = 0.008)] [33, 37]. Additionally, refusal from family members to help the REW was an important factor for the non-utilization [49]. Such dependent circumstances for REW did not improve their healthcare access in these communities both in developing and developed countries.

In summarizing the findings, the review suggested a number of determinants in relation to REW’s access to MHS. It was evident that REW were disadvantaged by individual, institutional, economic, social and cultural determinants under seven categories described above. This review confirmed that not only did healthcare systems impact on outcomes, but also individual, socioeconomic and cultural barriers influenced REW’s access. These constraints in healthcare and social environments shaped REW’s personal healthcare seeking behaviors. Thus, individual circumstances in combination with healthcare, cultural and social environments and reliance on others were significant determinants in the utilization of MHS for REW.