Skip to main content
Download PDF

Gender differences in cost-related unmet healthcare needs: a national study in Turkiye

BMC Public Health volume 24, Article number: 2413 (2024) Cite this article

Abstract

Background

Unmet healthcare needs are a complex and multifaceted issue, influenced by individual, socioeconomic, and healthcare system factors. This study aimed to investigate the determinants influencing cost-related unmet healthcare needs within the Turkish population, emphasizing a comprehensive analysis of gender disparities in accessing healthcare services.

Methods

This secondary analysis scrutinizes the 2019 Turkiye Health Survey data of 16,976 individuals aged 15 and older. The dependent variables included cost-related unmet medical, dental, and prescribed medication, and mental services. The independent variables were considered under a three-domain approach for the determination of health service utilization, developed by Andersen. Logistic regression models with predisposing, enabling, and need factors were run for any self-perceived cost-related unmet need for each sex and overall population. Another six regression models for both sexes were run for each subgroup of indivuals with unmet healthcare needs.

Results

The study revealed that 15.4% of individuals cannot access healthcare due to financial constraints, with 16.8% for women and 13.5% for men. The highest level of unmet needs is associated with accessing dental care services for both sexes. According to multivariate analyses, the unmet need for both sexes decreases with older age and higher education level, and it is greater for those who have difficulties communicating in Turkish. By adding enabling and needs factors, the odds ratios of education decreased for men, while education became nonsignificant for women. Having chronic disease impacts unmet needs for both sexes. However, the inability to perform daily activities due to health problems was not a significant factor for men. Poorer household income increases overall unmet needs. Education is a determinant of both medical and mental care needs.

Conclusions

This pioneering study illuminates the multifaceted gender disparities in cost-related unmet healthcare needs across Turkiye, reflecting the intertwined issues of access influenced by a complex interplay of factors. Our findings underscore the significance of adopting an intersectional approach to address health inequalities.

Peer Review reports

Background

Unmet healthcare needs are situations where individuals perceive that they need medical care but do not receive it due to financial constraints, geographical, cultural, or transport barriers, waiting lists or delays, or personal beliefs. The perception of unmet healthcare needs is subjective and can vary based on personal circumstances, socioeconomic factors, and healthcare system characteristics [1,2,3,4,5]. Cost-related unmet healthcare needs are crucial because financial barriers directly impact access to necessary medical care, making them a more immediate and critical issue than other barriers such as geographical or cultural factors, and addressing these needs is essential for equitable healthcare access.

The prevalence and nature of cost-related unmet healthcare needs are intricately linked to both the structure of healthcare systems and individual socioeconomic determinants. Healthcare system structures encompass crucial aspects such as access, insurance coverage, financing, service quality, policies, resource allocation, and sociocultural influences, all of which significantly impact the presence of unmet healthcare needs [1, 3, 5,6,7,8,9,10]. Simultaneously, socioeconomic determinants of health—such as income, education, employment, and health insurance—have a profound influence on healthcare access [3, 5, 11,12,13,14,15,16,17,18]. Effectively addressing these dual elements is paramount to enhancing healthcare access and reducing disparities among diverse populations [2, 5, 6, 16, 19].

To analyse these unmet healthcare needs further, the behavioral model of health care utilization developed by Andersen and Newman provides an opportunity to understand the predictors of unmet healthcare needs at the individual level. In this model, access to healthcare services is framed by three pillars: demographic characteristics, which are related to individual life prior to the onset, are grouped as predisposing factors; socioeconomic conditions, which determine the utilization of health services and are classified as enabling factors; and need factors, which focus on health status [20,21,22].

Turkiye has a universal health coverage (UHC) system in financing of healthcare which is mostly employment based social insurance model. Despite of the growing private health insurance system, the finance of the healthcare is predominantly from the universal insurance system, driven by the government. The UHC requires all citizen pay a minimun premium and copayments. Although the individuals who can’t afford their premiums are protected by some regulations in the system, there is a significant number of people having difficulty in access to healthcare due to financial reasons.

The private sector’s role in healthcare has expanded significantly, with private hospitals increasing from 23.4% in 2002 to 37.4% in 2019. This shift has led to greater healthcare utilization but also a rise in out-of-pocket expenditures, reaching 16.7% of total health spending in 2019, highlighting ongoing challenges in achieving equitable access to healthcare in Turkey [23].

The literature highlights significant disparities in unmet healthcare needs between men and women, influenced by both biological sex and the societal construct of gender, particularly within patriarchal structures [3,4,14,24]. These gender norms impact health outcomes and access to services, with women often facing worse health status and a higher burden of nonfatal conditions despite men’s lower life expectancy [24]. Gender norms, societal structures, discrimination, and policies impact health disparities between men and women, particularly affecting women through unfavorable socioeconomic and psychosocial factors, thereby influencing their access to healthcare services [6, 16, 25]. Addressing the complex interactions between healthcare systems, socioeconomic determinants, and gender disparities is crucial for achieving equitable healthcare access. In Turkey, despite advancements in human development, gender equality lags, with significant income and labor force participation gaps between men and women—women’s income was only 47% of men’s in 2019, and their labor participation was 34% compared to men’s 72.6% [25]. While global research often overlooks Turkey’s unique context, there is a noticeable gap in understanding how these socioeconomic factors influence gender disparities in healthcare access. Although women generally have greater unmet healthcare needs, detailed studies on the differences between men and women in Turkey are limited [6, 16, 26]. This study investigates the socioeconomic determinants of cost-related unmet healthcare needs in Turkey, focusing on gender disparities. The findings are expected to inform healthcare policy in Turkey and offer insights for other countries facing similar challenges, ultimately guiding targeted interventions to improve equitable access to health services.

Methods

Study design and setting

This study is a secondary analysis of the 2019 Turkiye Health Survey (THS), which is a cross-sectional study conducted between September and December 2019 by the Turkish Statistical Institute (TurkStat). For national representation, the sampling of surveys utilizes a stratified, two-stage cluster sampling method based on the “Address-Based Registry System”. The THS 2019 included 17,084 adult individuals (aged 15 years and older) across Turkiye. The study methodology excluded individuals residing in dormitories, prisons, hospitals, nursing homes, small villages or hamlets [27].

The 2019 data, collected just before the COVID-19 pandemic, provides a baseline unaffected by the significant shifts in healthcare access and socioeconomic factors caused by the pandemic. The 2022 data was reviewed but found to have incomplete household income information, which is crucial for applying the Andersen model in our analysis. Given the importance of household income as a determinant in the model and the extraordinary changes in healthcare delivery during the pandemic, the 2019 dataset was chosen for a more accurate analysis.

The microdata set of the 2019 Health Survey was officially requested and obtained from TurkStat to develop gender-based analyses of unmet healthcare needs for this study [27]. After the data cleaning process, we included 16,976 individuals aged 15 years and older in our analyses.

Dependent variables

The dependent variables in this study center on identifying unmet healthcare needs related to costs across different areas, specifically focusing on medical care, dental care, prescribed medications, and mental health care. These variables were derived from responses to four specific survey questions posed to participants regarding their experiences within the past 12 months: 1) inability to afford necessary medical care; 2) inability to afford required dental care; 3) inability to afford prescribed medications; and 4) inability to afford mental health care, including treatment from psychologists or psychiatrists. A common variable for self-perceived cost-related unmet healthcare needs was created and defined as any positive response to the four questions in the questionnaire. Henceforth, the term ‘unmet need’ is used interchangeably with the phrase ‘cost-related unmet any healthcare need’ in the article.

Independent variables

The independent variables were considered under a three-domain approach for the determination of health service utilization, developed by Andersen and Newman [20]. All analyses were stratified by sex in addition to the overall group. In this framework, independent variables are classified into the following: (1) demographic variables, such as age, marital status, education, sex (in overall analysis), and difficulty communicating in Turkish people, as predisposing factors; (2) household income and employment status; universal health insurance; and taking care of someone other than spouses and children either in the household or not, as enabling factors in terms of resources for accessing health services; and (3) self-rated health status, chronic disease status/conditions, and limitations in daily activities, as need factors.

The variable ‘providing care to persons other than spouses and children’ refers to a positive response to the question: ‘Do you provide care or assistance to one or more persons suffering from an age-related issue, chronic health condition, or disability at least once a week? (Excluding spouses and children). Self-rated health (assessed with the question ‘How is your health in general?‘), chronic disease status (‘Do you have any longstanding illness or [longstanding] health problem?‘), and limitations in daily activities (‘For at least the past 6 months, to what extent have you been limited because of a health problem in activities people usually do?‘) were each evaluated using single-item questions in the survey. Detailed descriptions of each independent variable can be found on the metadata of the Turkiye Health Survey page of the Turkish Statistical Institute [28].

Statistical analyses

Pearson’s chi-square test was used to analyse the differences between the respondents with unmet needs overall and those stratified by sex. The data are presented as numbers and percentages.

Variables that were significant according to Pearson’s chi-square tests were considered independent variables in multivariate logistic regression models. For each sex and overall population, nine logistic regression models with predisposing, enabling, and need factors were run for unmet needs. Another six regression models for both sexes were run for each subgroup, such as the cost-related unmet need for medical care, dental care, prescribed medicine, and mental health care. In the analyses, forward logistic regression models were employed, and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. For Model 1, which included only predisposing factors, the Hosmer and Lemeshow test yielded a probe value less than 0.05 for the total group, whereas for Models 2 and 3, which included enabling and need factors, the probe value was greater than 0.05 for both sexes. For all analyses, the p value was considered < 0.05. The analysis was performed using the Statistical Package for Social Sciences (SPSS) version 26.

Ethical approval

The principles of the Declaration of Helsinki were followed, meaning that the survey results were published at an aggregate level and that the anonymity of the interviewed individuals and households was fully secured. Before interpreting the results, the researchers obtained the consent of the Ethical Board from the School of Medicine at Istanbul Okan University.

Results

The study group had an average age of 44.0 ± 17.7 years, which was similar for men and women (p > 0.05). As shown in Table 1, among the male subpopulation, a higher prevalence of active participation in the workforce (57.1% vs. 21.8% in women) and having a comparatively higher income (32.0%) were noted. Conversely, women had statistically significantly greater rates of low-level education (51.9% vs. 37.3% for men), being divorced or widowed (14.9% vs. 4.7%), having difficulty communicating in Turkish (3.7% vs. 2.4%), being homemakers (meaning housewives 59.4%), taking care of someone other than spouses and children (9.1% vs. 7.9%), having poor health (13.3% vs. 8.2% poor and very poor), having chronic illness (67.4% vs. 52.6%), and being severely limited in daily activities due to health-related issues (28.9% vs. 18.7%). Women reported a greater percentage of benefiting from universal health insurance than men did (93.0% vs. 90.5%). The associations between these independent variables and sex were statistically significant (p < 0.05) (Table 1).

Table 1 Descriptives of predisposing, enabling and need factors by gender (column%) (15 + years, Turkiye, 2019)
Full size table

Cost-related unmet needs

Table 2 shows that 15.4% of the individuals were unable to access any form of healthcare services due to financial constraints, 16.8% were women, and 13.5% were men. Among those of both sexes, the highest percentage of patients met dental care services (overall 12.0%), followed by medical care (9.1%), prescribed medicine (6.4%), and mental health care (3.1%). There was a 1.55-fold difference in cost-related unmet needs due to mental health care between men and women (95% CI: 1.26–1.91). The difference in unmet needs due to dental care was the lowest between the sexes, at 1.18 (95% CI = 1.07–1.31) (Table 2).

Table 2 Cost-related unmet needs in the past 12 months by sex (15 + years, Turkiye, 2019)
Full size table

A univariate investigation of the data revealed a noteworthy statistical distinction between men and women who met their healthcare needs and those whose needs were unmet (Table 3). It was found that female respondents more frequently reported unmet needs in all categories (predisposing, enabling, and needs). The results of univariate analysis, as presented in Table 3, indicate that, compared to men, women experience 1.28–1.34 times more of any type of unmet need until they are 55 years old. Women who are less educated have 1.20 (1.06–1.49) times more unmet needs. Additionally, women in all marital status groups, those with language barriers, individuals with poorer self-rated health, those with chronic illnesses, and those with limited daily activities due to health problems experienced higher levels of unmet needs (Table 3).

Table 3 Rate of cost-related unmet healthcare needs by sex (15 + years, Turkiye, 2019)
Full size table

Three multivariate models were developed to determine the impact of predisposing, enabling, and need factors on any perceived unmet needs for both men and women (Table 4). Moreover, incremental increases in Nagelkerke’s R-squared values were observed as the enabling and need factors were added stepwise into Models 1 and 2; these values are 0.126, 0.130, and 0.126 for men, women, and overall, respectively.

In Model 1, which includes predisposing factors, the unmet need for both sexes decreases with older age and higher education level, and it is greater for those who have difficulties communicating in Turkish. In addition, being divorced/widoved was statistically significant only for women in those three models (Table 4).

After adding the enabling factors, Model 2 showed that the effect of age decreased for men but not for women, while in Model 3, the needs factor appeared to increase the effect of age on unmet needs among both women and men. By adding enabling and needs factors to Model 1, the odds ratios of education decreased for men, while education became nonsignificant for women. According to all three models, the frequency of unmet needs was greater among divorced or widowed women than among unmarried women and men. All the models indicate that individuals with difficulty communicating in Turkish have greater unmet needs, even though the odds ratios are slightly lower in Model 3 (Table 4).

According to the overall analysis, gender is a statistically significant determinant in Models 1 and 2 but not in Model 3 after the need factors are added. Household income has the same effect in both Models 2 and 3 for men and women, presenting an increase in unmet needs parallel to decreasing income level. A lack of health insurance is also related to unmet needs for men and women. On the other hand, the findings suggest that, employment, unlike men, women do not play a statistically significant role in determining unmet needs.

Model 3, which also included needs factors, showed that chronic disease impacts unmet needs for men and women. However, the inability to perform daily activities due to health problems was not found to be a statistically significant factor related to unmet needs in men. Both men and women who reported their health as worse than good had greater unmet needs. These scores were 3.0 (95% CI: 2.3–3.9) and 2.0 (95% CI: 1.6–2.5) times greater for the participants reporting poor and very poor health, respectively, for men and women (Table 4).

Table 4 Multivariate analysis of any cost-related unmet healthcare needs by sex (15 + years, Turkiye, 2019)
Full size table

Given that the count of homemaker men was low, this group was excluded from the multiple analyses.

As shown in Table 5, to better explain the determinants of unmet needs among women and men, additional multivariate regression models were performed for each subcategory, which included medical care, dental care, prescribed medicines, and mental healthcare (Table 5). Younger age is a risk factor for both women and men in all types of unmet needs. For both men and women, education less than 5 years was related to 1.5 times more unmet medical care, while unmet prescribed medicine was related to education less than 8 years for both sexes. Education serves as a determinant of both unmet medical care and prescribed medicine needs among men and women according to multivariate regression models, but it does not explain the unmet need for dental and mental care among women. As shown in Table 5, being married increases the risk of unmet medical, dental, and healthcare services for both men and women, and the risk of unmet prescription drug needs for men only; however, it has no effect on the risk of unmet mental healthcare needs. However, divorce is not a determinant for men, but for women, it poses a greater risk factor than marriage (Table 5).

Age, having health insurance, being the poorest, caring for people other than spouses and children, having chronic disease, and having limitations due to health issues determine unmet mental healthcare needs in women; in contrast, in men, only employment, having health insurance, income, self-rated health status, and chronic disease are factors (Table 5). According to multivariate analyses, a limitation in daily activities due to health problems was not identified as a risk factor for men, in contrast to women, among the unmet mental healthcare needs.

Table 5 Multivariate analysis (predisposing, enabling and need factors) of cost-related unmet medical, dental, mental care and prescribed medicines by sex (15 + years, Turkiye, 2019)
Full size table

Discussion

This pioneering study is the first to analyze gender differences in cost-related unmet healthcare needs within a representative sample of the Turkish population. It reveals that socioeconomic determinants impact men and women differently, highlighting the need for an intersectional approach in public health.

Prevalence of cost-related unmet healthcare needs

We found that 15.4% of people aged 15 years or older reported unmet healthcare needs due to cost, exceeding the European Union’s average of 13.0% [29]. In comparison, earlier studies from 2016 using TURKSTAT data showed a prevalence of 13.6% [6, 16, 25]. The increase in unmet needs from 2016 to 2019 may be linked to Turkey’s economic instability, reflected in the decline of GDP per capita from $10,734.4 to $9,103 during this period [30]. Additionally, Turkey’s healthcare spending decreased from 6% of GDP in 2009 to 4.7% in 2019, according to the World Health Organization’s Global Health Expenditure database. This decline has intensified private healthcare expenses, particularly through out-of-pocket payments and private health insurance, increasing the financial burden on individuals [9]. The rise in unmet needs among women may be due to these heightened out-of-pocket healthcare expenses, with underprivileged groups disproportionately affected, perpetuating gender inequalities in Turkey and similar trends observed in Europe [24, 33].

Our findings revealed a greater prevalence of unmet needs among females (16.8%) than among males (13.5%), consistent with the findings of various reports and studies in this domain [1, 3, 4, 6, 25]. Notably, this finding aligns with Turkiye’s Global Gender Inequality Index, which, after increasing between 2000 and 2016, stagnated and declined in 2017 [25]. Gender inequality has been a substantial issue in Turkiye, especially in the labor market, where women face greater challenges than men in terms of informal work, unemployment, and lower wages [31]. Despite this disadvantage, universal health insurance covers both widowed and single women as beneficiaries of their husbands and fathers. An existing regulation allowing unmarried or widowed women lifelong utilization of their fathers’ health insurance still contributes to improved healthcare access in terms of financial support and necessary medical services [32]. However, it should be noted that this right applies only to women born before the law was accepted in 2008, meaning the number of female beneficiaries will steadily decrease over the years.

According to the study, accessing dental care services had the highest cost-related unmet needs for both genders. The significant unmet need for dental care could be attributed to the historically limited national health care system, the dominance of the private sector in Turkiye, regional disparities despite public sector growth, copayments for high-quality materials, and challenges in appointment scheduling. A higher cost of dental care exacerbates economic disparities between men and women [33,34,35].

Andersen and Newman’s model

In this study, we found that Andersen and Newman’s model [21] was an effective tool for understanding the socioeconomic determinants of unmet needs across all subgroups, consistent with previous findings [2, 26, 36, 37].

Predisposing factors

Predisposing factors such as younger age, lower education level, marital status, and difficulty with linguistic communication had differential impacts on access to healthcare between genders. Contrary to the findings of certain studies [16, 17], our findings align with those of other studies demonstrating a greater prevalence of unmet needs among younger age groups, with the highest occurrence occurring within the 35–44 age bracket [15,16,17,18,19]. This trend, where younger age serves as a risk factor for unmet needs across genders, except for men older than 55, can be attributed to multifaceted factors, including increased copayments and high youth unemployment rates in Turkiye, where the unemployment rate for those aged 15–24 was 22.5% for men and 30.6% for women [28,29,30,31,32,33,34,35,36,37,38,39,40].

The study revealed that lower education levels are a risk factor for unmet needs among both men and women when only predisposing factors are considered. This could be attributed to the fact that women with lower education levels may have greater perceived unmet needs due to a lack of health literacy. However, when enabling factors such as employment status and income are added to the model, the effect of lower education levels on perceived unmet needs for women disappears. This observation continues even after adding need factors such as chronic disease, health status, and limitations in daily activities. This finding suggests that education, therefore, may play a more determining role in employment, income, etc., among women in Turkiye. Similarly, a research study revealed that health insurance and income play crucial roles as primary mediators in connecting education levels with the utilization of healthcare services [12]. On the other hand, low education is related to unmet medical care and prescribed medicine needs among both men and women according to multivariate regression models. This finding aligns with previous research indicating that higher education levels are associated with better health literacy, leading to more effective utilization of healthcare services [14]. Unexpectedly, education is not related to the unmet need for dental or mental care among women. This could be due to various reasons, such as lower prioritization and postponement of dental and mental health due to mostly nonurgent conditions, a lack of awareness about the importance of these services, or other barriers to access.

Furthermore, while marriage elevated the risk of unmet medical, dental, and prescription drug needs for both genders, divorce or widowhood presented a heightened risk, specifically for women in terms of healthcare access. The literature encompasses studies reflecting diverse perspectives on the impact of marriage on healthcare utilization, suggesting either a positive, negative, or neutral influence [3, 40,41,42,43,44]. For women, especially housewives, divorce implies income loss, whereas for men, the risk is mitigated. Studies on low-income divorced women in Turkiye reveal that these women often struggle to improve their lives due to limited opportunities and legal challenges favoring men [45].

Consistent with the literature, having difficulty communicating with one’s mother tongue was one of the variables found to be a determinant of unmet needs in all three models for both genders [46,47,48]. Among the types of unmet needs, language barriers were important for unmet medical care among both men and women and unmet dental care for men only.

Enabling factors

In Andersen’s model of unmet needs, enabling factors are the conditions that make health service resources available to individuals and are grouped into family and community factors [21, 25]. In our study, enabling factors contributing to unmet healthcare demand for both genders included lower and middle household income, a lack of universal health insurance, and caregiving responsibility, while employment was statistically significant only for men. Lack of universal health insurance and low/lowest income are associated with all types of unmet needs. While unmet medical and dental care needs are significantly greater among employed and unemployed men, the unmet need for prescribed medicine is related only to unemployed men.

Family income directly influences the affordability of healthcare services, encompassing both the ability to purchase all services and covering copayments during healthcare utilization [7, 14, 49]. Emphasizing the significance of universal healthcare coverage as a strategy to foster health equity is noteworthy in this context [50, 51]. In addition, our analyses revealed a notable discrepancy in unmet needs, with men who are not covered by universal healthcare insurance experiencing higher rates of unmet needs than women. This divergence could be linked to the availability of facilities serving women’s health, such as nonprofit health centers operated by NGOs and local government initiatives.

However, a noticeable gender disparity is observed in the predictive role of employment, which is not statistically significant for women. A seemingly contradictory finding at first glance was that both employed and unemployed men reported greater unmet needs. Regular employment often correlates with having some form of health insurance, which facilitates access to healthcare [52, 53]. In this context, the association between unemployment and unmet healthcare needs is understandable, particularly in countries with limited social protection. On the other hand, a significant portion of employed men in Turkiye, estimated between 30.9% and 31.8% in 2019, are in unregistered employment, which typically does not offer health insurance through employers [54]. This lack of insurance could explain some of the unmet needs among employed men. Furthermore, within this age group, the higher prevalence of unmet needs among men may be attributed to the insufficient availability of occupational health services in workplaces, the limited scope of services, challenges in obtaining employer permission to seek healthcare, and wage deductions for obtaining health reports [55,56,57].

Many studies have shown that caregiving responsibilities may be related to postponing health care utilization, especially for women, due to gender differences [58,59,60,61]. Female caregivers, which are more prevalent in Turkiye, significantly impact women’s unmet needs and experience a greater burden [58, 62]. However, our study shows that caregiving also affects men, although differently. Male caregivers, despite being fewer in number, might experience significant stress balancing work and caregiving duties, compounded by societal perceptions of caregiving as a “feminine” role. This stigma can lead to a lack of support, social isolation, and increased stress for male caregivers [63,64,65]. Recognizing the diverse experiences of caregivers and providing adequate support for all, regardless of gender, is essential to mitigating the negative impacts of caregiving on healthcare access.

Needs factors

In our study, gender emerges as a statistically significant determinant in Models 1 and 2. However, its significance diminishes in Model 3 when we incorporate factors related to health needs. This shift in significance suggested that while gender might influence predisposition and access to resources (as seen in Models 1 and 2), it does not directly impact unmet healthcare needs when we account for actual health status and requirements (need factors) in the analysis (as in Model 3).

Consistent with the literature, women experience a greater frequency of poorer self-rated health status, chronic diseases, and limitations in daily activities due to health problems than men do [2, 42, 66,67,68,69]. In our study, both men and women who had any chronic illness reported a statistically significant influence on each type of unmet need. In contrast to the greater frequency among women, poor self-rated health had a more substantial impact on men’s cost-related unmet care needs. This could be due to differing perceptions of health severity and delayed healthcare-seeking behavior influenced by societal expectations of masculinity [70,71,72].

However, limitation in daily activities due to health problems primarily affected women’s access to medical care, highlighting a sex-specific factor. Cultural, social, and economic barriers, coupled with these health-related limitations, create additional challenges for women when seeking medical attention [3, 67]. Despite being proactive in seeking healthcare, women may prioritize their households’ needs over their own, leading to unmet medical care. Societal norms and expectations regarding gender roles may also cause women to downplay their health concerns or delay seeking care until their conditions worsen [73, 74]. These factors collectively pose significant barriers for women in accessing timely and adequate healthcare services.

In this study, need factors likely play a substantial role in mediating or explaining the relationship between gender and unmet healthcare needs. This change in the significance of sex from Models 1 and 2 to Model 3 underscores the importance of considering health status and requirements in understanding unmet healthcare needs.

Limitations

This study has several limitations. First, the cross-sectional nature of the study prevents us from exploring causal associations. The cross-sectional design may also cause selection bias because the temporal dynamics between predisposing, enabling, and need-related factors were not provided. Second, self-reported data are potentially based on perception and may also lead to recall bias. Additionally, the age grouping of < 35 years encompasses a wide and heterogeneous population, from adolescents to adults, which may influence the interpretation of age-related findings. The complexity of the determinants influencing unmet needs could extend beyond the variables analysed. Addressing these limitations through more comprehensive data collection, broader variables, and a deeper understanding of contextual influences would enhance the credibility and applicability of future studies.

Conclusion and policy implications

This pioneering study illuminates the multifaceted gender disparities in cost-related unmet needs across Turkiye, reflecting intricate access issues influenced by a complex interplay of predisposing, enabling, and need-related factors. Our findings underscore the significance of adopting an intersectional approach to address health inequalities.

The study highlights the significant rise in cost-related unmet needs in Turkiye people attributed to financial barriers, particularly affecting women, which coincides with gender inequality trends in employment and income, despite improved health care access through existing provisions. Private healthcare expenses intensified, particularly impacting underprivileged groups and perpetuating gender-based disparities. The predominant unmet need for dental care signifies systemic challenges, emphasizing the necessity of enhancing access to dental health services within the Turkish healthcare system.

Distinct sex-specific patterns emerged regarding predisposing factors such as age, marital status, and communication barriers. The influence of education on cost-related unmet needs among women has remained elusive. Factors contributing to unmet demand for both genders include lower household income, the absence of social health insurance, and caregiving responsibilities. Unemployment predicts healthcare access primarily for men, indicating that having health insurance has a significant influence on their employment status.

The caregiving burden impacts both women’s and men’s unmet needs in Turkiye, with men facing a considerable burden linked to higher employment rates and potential stress in balancing work and caregiving responsibilities. Addressing gender stereotypes related to caregiving and offering adequate support to all caregivers could mitigate the negative impacts of caregiving’s burden on both men’s and women’s well-being and healthcare access.

In essence, this study underscores the need for comprehensive interventions addressing the complex interaction of factors contributing to gender-based disparities in accessing healthcare services, emphasizing the urgency of mitigating these inequities for improved healthcare outcomes for all individuals in Turkiye.

Data availability

The data that support the findings of this study are available from the Turkish Statistical Institute, but restrictions apply to the availability of these data, which were used under licence for the current study and are not publicly available. However, the data are available from the authors upon reasonable request and with the permission of the Turkish Statistical Institute.Contact person for the data request: aslidavas@gmail.comThe web site where data can be purchased is: https://data.tuik.gov.tr/Kategori/GetKategori? p=Health-and-Social-Protection--101.

References

  1. Chaupain-Guillot S, Guillot O. Health system characteristics and unmet care needs in Europe: an analysis based on EU-SILC data. Eur J Health Econ. 2015;16:781–96. https://doi.org/10.1007/s10198-014-0629-x.

    Article  PubMed  Google Scholar 

  2. Popovic N, Terzic-Supic Z, Simic S, Mladenovic B. Predictors of unmet health care needs in Serbia; analysis based on EU-SILC data. PLoS ONE. 2017;12(11):e0187866. https://doi.org/10.1371/journal.pone.0187866.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Tadiri CP, Gisinger T, Kautzky-Willer A, et al. Determinants of perceived health and unmet healthcare needs in universal healthcare systems with high gender equality. BMC Public Health. 2021;21:1488. https://doi.org/10.1186/s12889-021-11531-z.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Cavalieri M. Geographical variation of unmet medical needs in Italy: a multivariate logistic regression analysis. Int J Health Geogr. 2013;12(27). https://doi.org/10.1186/1476-072X-12-27.

  5. Hoebel J, Rommel A, Schröder SL, Fuchs J, Nowossadeck E, Lampert T. Socioeconomic inequalities in Health and Perceived Unmet needs for Healthcare among the Elderly in Germany. Int J Environ Res Public Health. 2017;14(10):1127. https://doi.org/10.3390/ijerph14101127.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Yardim MS. Equity in access to care in the era of health system reforms in Turkiye. Health Policy (New York). 2018;122(6):645–5. https://doi.org/10.1016/j.healthpol.2018.03.016.

    Article  Google Scholar 

  7. Alemu F, Thornton JAS. Multimorbidity, low income and unmet need for healthcare: a national study of 41,135 older adults. Eur J Public Heal. 2022;32(3). https://doi.org/10.1093/eurpub/ckac129.503.

  8. Kruk ME, Gage AD, Arsenault C, Jordan K, Leslie HH, Roder-DeWan S, Adeyi O, Barker P, Daelmans B, Doubova SV, English M, García-Elorrio E, Guanais F, Gureje O, Hirschhorn LR, Jiang L, Kelley E, Lemango ET, Liljestrand J, Malata A, Marchant T, Matsoso MP. High-quality health systems in the Sustainable Development goals era: time for a revolution. Lancet Glob Health. 2018;6(11):e1196–252. https://doi.org/10.1016/S2214-109X(18)30386-3.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Polin K, Yıldırım H, Waitzberg R. Health Systems in Action Insight for Türkiye 2022. https://iris.who.int/bitstream/handle/10665/362347/9789289059213-eng.pdf?sequence=1 Accessed 20 December 2023.

  10. Yılmaz F. Measuring Quality of Preventive Health and Safety Services. J Eng Proj Prod Manag. 2022;12(2):101–7. https://doi.org/10.32738/JEPPM-2022-0009.

    Article  Google Scholar 

  11. Eurostat Statistics Explained. Unmet health care needs statistics. Ec.europa.eu. 2019. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Unmet_health_care_needs_statistics#Unmet_needs_for_health_care%0A Accessed 3 June 2023.

  12. Dang T. Do the more educated utilize more health care services? Evidence from Vietnam using a regression discontinuity design. Int J Health Econ Manag. 2018;18:277–99. https://doi.org/10.1007/s10754-018-9233-4.

    Article  PubMed  Google Scholar 

  13. Loef B, Meulman I, Herber GM, Kommer GJ, Koopmanschap MA, Kunst AE, Polder JJ, Wong A, Uiters E. Socioeconomic differences in healthcare expenditure and utilization in the Netherlands. BMC Health Serv Res. 2021;21(1):643. https://doi.org/10.1186/s12913-021-06694-9.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Wulifan JK, Brenner S, Jahn A, De Allegri M. A scoping review on determinants of unmet need for family planning among women of reproductive age in low and middle income countries. BMC Womens Health. 2016;16:2. https://doi.org/10.1186/s12905-015-0281-3. PMID: 26772591; PMCID: PMC4714507.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Fjær EL, Stornes P, Borisova LV, McNamara CL, Eikemo TA. Subjective p erceptions of unmet need for healthcare in Europe among social groups: findings from the European Social Survey (2014) special module on the social determinants of health. Eur J Public Health. 2017;27(Suppl 1):82–9.

    Article  PubMed  Google Scholar 

  16. Terzi M, Kurutkan MN, Şahin D, Kara O. Unmet medical care needs due to payment difficulty. Sağlık Akademisyenleri Dergisi. 2022;9(4):309–16. https://doi.org/10.52880/sagakaderg.1074505.

    Article  Google Scholar 

  17. WHO Commission on Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of health 2008. https://iris.who.int/bitstream/handle/10665/69832/WHO_IER_CSDH_08.1_eng.pdf?sequence=1 Accessed 03 June 2023.

  18. Braveman P, Gottlieb L. The social determinants of health: it’s time to consider the causes of the causes. Public Heal Rep. 2014;129:19–31. https://doi.org/10.1177/00333549141291S206.

    Article  Google Scholar 

  19. Pappa E, Kontodimopoulos N, Papadopoulos A, Tountas YND. Investigating unmet health needs in primary health care services in a representative sample of the Greek population. Int J Env Res Public Heal. 2013;10(5):2017–27. https://doi.org/10.3390/ijerph10052017.

    Article  Google Scholar 

  20. Anderson R. Revisiting the behavioural model and access to medical care: does it matter? J Heal Soc Behav. 1995;36:1–10. PMID: 7738325.

    Article  Google Scholar 

  21. Anderson R, Newman J. Societal and individual determinants of medical care utilization in the United States remove. Milbank Mem Fund Q Heal Soc. 2005;51(1):95–124. https://doi.org/10.1111/j.1468-0009.2005.00428.x.

    Article  Google Scholar 

  22. Babitsch B, Gohl DVLT. Rerevisiting Andersen’s behavioral model of Health services Use: a systematic review of studies from 1998–2011. GMS Psycho-Social-Medicine. 2012;9. https://doi.org/10.3205/psm000089.

  23. MoH, Ministry of Health of Turkey Health Statistics Yearbook. 2021. 2019. https://dosyasb.saglik.gov.tr/Eklenti/40566/0/health-statistics-yearbook-2019pdf.pdf Accessed 14 August 2024.

  24. Franklin P, Bambra C, Albani V. Gender equality and health in the EU. 2021. https://op.europa.eu/en/publication-detail/-/publication/5b59409f-56e4-11eb-b59f-01aa75ed71a1 Accessed 03 June 2023.

  25. Kızılırmak B, Memiş E, Toksöz G. Turkey’s Gender Equality Performance from 2000 to 2019: A Rights-Based Analysis via UNDP Human Development and Gender Development Indices. UNDP Turkey - CEID (Association for Montoring Gender Equiality) & UNDP Turkey. Ankara, 2022. https://dspace.ceid.org.tr/xmlui/handle/1/2035

  26. Başar D, Dikmen FH, Öztürk S. The prevalence and determinants of unmet health care needs in Turkey. Health Policy (New York). 2021;125(6):786–92. https://doi.org/10.1016/j.healthpol.2021.04.006.

    Article  Google Scholar 

  27. Turkey Health Survey TURKSTAT. 2019. https://data.tuik.gov.tr/Bulten/Index?p=Turkey-Health-Survey-2019-33661

  28. TURKSTAT. Metadata of Turkey Health Survey. 2019. https://data.tuik.gov.tr/Kategori/GetKategori?p=saglik-ve-sosyal-koruma-101&dil=2 Accessed 25 Nov 2023.

  29. Eurostat Statistics Explained. Unmet needs for health care. 2022. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Unmet_health_care_needs_statistics#Unmet_needs_for_health_care Accessed 25 Nov 2023.

  30. Worldbank. GDP per capita (current US$) - Turkiye. 2021 https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?end=2021&locations=TR&start=2016 Accessed 25 Nov 2023.

  31. World Economic Forum. Global Gender Gap Report. 2023. https://www.weforum.org/publications/global-gender-gap-report-2023/ Accessed 25 Nov 2023.

  32. Law No. 5510. Social Insurance and Universal Health Insurance Law. 2006. https://www.mevzuat.gov.tr/mevzuatmetin/1.5.5510.pdf Accessed 03 June 2023.

  33. Cinaroglu S. Poverty effects of public health reforms in Turkey: a focus on out-of‐pocket payments. J Eval Clin Pract. 2021;27(1):53–61.

    Article  PubMed  Google Scholar 

  34. İlgün G, Konca M, Yetim BŞB. Does Efficiency of Oral and Dental Health Centers Change by the Development Level of regions? Value Heal Reg Issues. 2022;31:61–6. https://doi.org/10.1016/j.vhri.2022.03.002.

    Article  Google Scholar 

  35. Ekici O, Tengilimoglu D, Işık O. Evaluating the current situation of oral and dental healthcare services in Turkey and recommending solutions. Heal Policy Technol. 2017;6(3):368–78. https://doi.org/10.1016/j.hlpt.2017.07.006.

    Article  Google Scholar 

  36. Hwang J. Understanding reasons for unmet health care needs in Korea: what are health policy implications? BMC Heal Serv Res. 2018;18:557. https://doi.org/10.1186/s12913-018-3369-2.

    Article  Google Scholar 

  37. Connolly, Sheelah M-AW. Unmet healthcare needs in Ireland: analysis using the EU-SILC survey. Health Policy (New York). 2017;1214:434–41. https://doi.org/10.1016/j.healthpol.2017.02.009.

    Article  Google Scholar 

  38. Şemsa Özar. Türkiye’de 1980 Sonrası Dönemde Kadın Emeği ve İstihdamı Politikaları: Kadın Hareketi, Sendikalar, Devlet ve İşveren Kuruluşları. Ahmet Makal ve Gülay Toksöz, editor. Geçmişten Günümüze Türkiye’de Kadın Emeği. Birinci. Istanbul; İmge; 2015. pp. 223–53.

  39. Yenilmez MI. Female employment and Care Economy in Turkey. Sosyol Araştırmaları Derg. 2019;22(1):69–95. https://doi.org/10.18490/sosars.559091.

    Article  Google Scholar 

  40. Ekiz Gökmen Ç. A new perspective on women’s care burden and employment in Turkey. New perspectives on Turkey. Camb Univ Press. 2022;66:11–34. https://doi.org/10.1017/npt.2021.21.

    Article  Google Scholar 

  41. Iwashyna TJ, Christakis NA. Marriage, widowhood, and health-care use. Soc Sci Med. 2003;57(11):2137-47. https://doi.org/10.1016/s0277-9536(02)00546-4. PMID: 14512244. https://doi.org/10.1016/S0277-9536(02)00546-4.

  42. Etiler N. Gender differences in self-rated health and their determinants in Turkey: a further analysis of Turkish health survey. Turkish J Public Heal. 2016;14(3):152–63. https://doi.org/10.20518/tjph.288395.

    Article  Google Scholar 

  43. Pandey KR, Yang F, Cagney KA, Smieliauskas F, Meltzer DO, Ruhnke GW. The impact of marital status on health care utilization among Medicare beneficiaries. Med (Baltim). 2019;98(12):e14871. https://doi.org/10.1097/MD.0000000000014871. PMID: 30896632; PMCID: PMC6709281.

    Article  Google Scholar 

  44. Colman E, Symoens S, Bracke P. Professional health care use and subjective unmet need for social or emotional problems: a cross-sectional survey of the married and divorced population of Flanders. BMC Health Serv Res. 2012;12:420. https://doi.org/10.1186/1472-6963-12-420.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Akpınar P. Turkish Divorcées and need for woman-friendly policies. In: Bonifacio GT, editor. Global currents in gender and feminisms. Leeds: Emerald Publishing Limited; 2012. pp. 93–105. https://doi.org/10.1108/978-1-78714-483-520171010.

    Chapter  Google Scholar 

  46. Hemberg J, Sved E. The significance of communication and care in one’s mother tongue: patients’ views. Nord J Nurs Res. 2021;41(1):42–53. https://doi.org/10.1177/2057158519877794.

    Article  Google Scholar 

  47. Samer E. Communication in Health Care: Impact of Language and Accent on Health Care Safety, Quality, and patient experience. Am J Med Qual. 2021;36(5):355–64. https://doi.org/10.1097/01.JMQ.0000735476.37189.90.

    Article  Google Scholar 

  48. Jang Y, Kim MT. Limited English proficiency and Health Service Use in Asian americans. J Immigr Minor Health. 2019;21(2):264–70. https://doi.org/10.1007/s10903-018-0763-0. PMID: 29797103; PMCID: PMC6252148.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Huang J, Birkenmaier J. Job loss and unmet health care needs in the economic recession: different associations by family income. Am J Public Health. 2014;10411:e178–83. https://doi.org/10.2105/AJPH.2014.301998.

    Article  Google Scholar 

  50. Stevens A, Neilson M, Rasanathan K, Syed SBKT. Quality and equity: a shared agenda for universal health coverage. BMJ Glob Heal. 2023;8(7):e012561. https://doi.org/10.1136/bmjgh-2023-012561.

    Article  Google Scholar 

  51. Wagstaff A, Neelsen S. A comprehensive assessment of universal health coverage in 111 countries: a retrospective observational study. Lancet Glob Health. 2020;8(1):e39–49. https://doi.org/10.1016/S2214-109X(19)30463-2.

    Article  PubMed  Google Scholar 

  52. Enthoven AC, Fuchs VR. Employment-based health insurance: past, present, and future. Health Aff (Millwood). 2006 Nov-Dec;25(6):1538-47. https://doi.org/10.1377/hlthaff.25.6.1538. PMID: 17102178.

  53. Yuan B, Li J, Wu L, Wang Z. Multi-level Social Health Insurance System in the age of frequent employment change: the Urban unemployment-Induced Insurance Transition and Healthcare utilization in China. Healthc (Basel). 2019;7(2):77. https://doi.org/10.3390/healthcare7020077.

    Article  Google Scholar 

  54. TÜİK. TÜİK Hanehalkı İşgücü Anketi Verileri. 2019. https://data.tuik.gov.tr/Bulten/Index?p=Isgucu-Istatistikleri-2019-33784#:~:text=%C4%B0%C5%9Fg%C3%BCc%C3%BC%202019%20y%C4%B1l%C4%B1nda%20bir%20%C3%B6nceki,%53%2C0%20olarak%20ger%C3%A7ekle%C5%9Fti.&text=15%2D64%20ya%C5%9F%20grubunda%20i%C5%9Fsizlik%20oran%C4%B1%20bir%20%C3%B6nceki%20y%C4%B1la%20g%C3%B6re,art%C4%B1%C5%9Fla%20%16%2C1%20oldu. Accessed 20 June 2023.

  55. Cimrin AH, Ozgur EA, Alıcı NS. Patient Referral as a quality outcome of Occupational Health Practice at the Workplace in Turkey. J Basic Clin Heal Sci. 2020;4(1):68. https://doi.org/10.30621/jbachs.2020.826.

    Article  Google Scholar 

  56. Artvinli F. The ethics of occupational health and safety in Turkey: responsibility and consent to risk. Acta Bioeth. 2016;22(1):111. https://doi.org/10.4067/S1726-569X2016000100012.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Hot I, Karlikaya E, Erdogan MS. Survey of the opinions on the occupational health system in Turkey expressed by patients of the Istanbul hospital of occupational diseases. Int J Occup Med Environ Health. 2011;24(2):192-8. https://doi.org/10.2478/s13382-011-0014-2. Epub 2011 Apr 27. PMID: 21526384. https://doi.org/10.2478/s13382-011-0014-2.

  58. Akpınar B, Küçükgüçlü O, Yener G. Effects of gender on burden among caregivers of Alzheimer’s patients. J Nurs Scholarsh. 2011;43(3):248–54. https://doi.org/10.1111/j.1547-5069.2011.01402.x. Epub 2011 Jul 18. PMID: 21884370.

    Article  PubMed  Google Scholar 

  59. Tingey JL, Lum J, Morean W, Franklin R, Bentley JA. Healthcare coverage and utilization among caregivers in the United States: findings from the 2015 behavioral risk factor Surveillance System. Rehabil Psychol. 2020;65(1):63–71. https://doi.org/10.1037/rep0000307. Epub 2020 Jan 23. PMID: 31971434.

    Article  PubMed  Google Scholar 

  60. Ngouakam H, Nekehforba E, Tientche B. Determinants of Delay in Healthcare Seeking for Common Childhood Illnesses among Caregivers with Under-Five Children in Touboro Health District, Near Cameroon’ s Northeastern Border with Chad. IJTDH. 2021 Apr. 14;42(5):1–14. https://journalijtdh.com/index.php/IJTDH/article/view/1098 Accessed 03 June 2023 https://doi.org/10.9734/ijtdh/2021/v42i530453

  61. Wolff JL, Spillman BC, Freedman VA, Kasper JD, A National Profile of Family and Unpaid Caregivers Who Assist Older Adults With Health Care Activities. JAMA Intern Med. 2016;176(3):372–9. https://doi.org/10.1001/jamainternmed.2015.7664. PMID: 26882031; PMCID: PMC4802361.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Yılmaz Kara B, Toprak D, Kara E, Özçelik N, Özyurt S, Karadoğan D, Gümüş A, Şahin Ü. Caregiver Burden in Pulmonary patients. J Gerontol Soc Work. 2023;66(3):400–12. Epub 2022 Jul 26. PMID: 35880439.

    Article  PubMed  Google Scholar 

  63. Baker KL, Robertson N, Connelly D. Men caring for wives or partners with dementia: masculinity, strain and gain. Aging Ment Health. 2010;14(3):319 – 27. doi: 10.1080/13607860903228788. PMID: 20425651.

  64. Mott J, Schmidt B, MacWilliams B. Male Caregivers: Shifting Roles Among Family Caregivers. Clin J Oncol Nurs. 2019;23(1):E17-E24. https://doi.org/10.1188/19.CJON.E17-E24. PMID: 30681996.

  65. Milligan C, Morbey H. Care, coping and identity: older men’s experiences of spousal care-giving. J Aging Stud. 2016;38:105–14. https://doi.org/10.1016/j.jaging.2016.05.002.

    Article  PubMed  Google Scholar 

  66. Ciambrone G, Kaski JC. Gender differences in the treatment of chronic ischemic heart disease: prognostic implications. Fundam Clin Pharmacol. 2010;24(6):707–10. https://doi.org/10.1111/j.1472-8206.2009.00774.x.

    Article  CAS  PubMed  Google Scholar 

  67. Bryant T, Leaver C, Dunn J. Unmet healthcare need, gender, and health inequalities in Canada. Health Policy. 2009;91(1):24–32. https://doi.org/10.1016/j.healthpol.2008.11.002.

    Article  PubMed  Google Scholar 

  68. Ronksley PE, Sanmartin C, Quan H, Ravani P, Tonelli M, Manns B, Hemmelgarn BR. Association between chronic conditions and perceived unmet health care needs. Open Med. 2012;6(2):e48–58. PMID: 23696769; PMCID: PMC3659214.

    PubMed  PubMed Central  Google Scholar 

  69. Boerma T, Hosseinpoor AR, Verdes E, et al. A global assessment of the gender gap in self-reported health with survey data from 59 countries./doi.org/. BMC Public Health. 2016;16:675. https://doi.org/10.1186/s12889-016-3352-y.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Anson O, Paran E, Neumann L, Chernichovsky D. Gender differences in health perceptions and their predictors. Soc Sci Med. 1993;36(4):419 – 27. https://doi.org/10.1016/0277-9536(93)90404-r. PMID: 8434267.

  71. Galdas PM, Cheater F, Marshall P. Men and health help-seeking behaviour: literature review. J Adv Nurs. 2005;49(6):616 – 23. https://doi.org/10.1111/j.1365-2648.2004.03331.x. PMID: 15737222.

  72. Abualhaija N. Men’s health disparities: causes and interventions. Nurs Forum. 2022;57(5):785–92. https://doi.org/10.1111/nuf.12764. Epub 2022 Jun 14. PMID: 35701992.

    Article  PubMed  Google Scholar 

  73. Bloomberg M, Dugravot A, Landré B, Britton A, Steptoe A, Singh-Manoux A, Sabia S. Sex differences in functional limitations and the role of socioeconomic factors: a multicohort analysis. Lancet Healthy Longev. 2021;2(12):e780–90. https://doi.org/10.1016/S2666-7568(21)00249-X. PMID: 34901907; PMCID: PMC8636280.

    Article  PubMed  PubMed Central  Google Scholar 

  74. EIGE. Women are more likely to have health limitations over their lifetime. Gender Equality Index 2021. 2021. https://eige.europa.eu/publications-resources/toolkits-guides/gender-equality-index-2021-report/women-are-more-likely-have-health-limitations-over-their-lifetime?language_content_entity=en Accessed: 10 December 2023.

Download references

Acknowledgements

Not applicable.

Funding

We did not utilize any financial resources.

Author information

Authors and Affiliations

  1. Faculty of Medicine, Department of Public Health, Ege University, Izmir, Turkey

    Aslı Davas

  2. School of Public Health, University of Nevada Reno (UNR), University of Nevada Reno (UNR), Reno, NV, USA

    Nilay Etiler

  3. School of Medicine, Istanbul Okan University, Istanbul, Turkey

    Nilay Etiler

Authors
  1. Aslı Davas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nilay Etiler
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AD played a key role in the data acquisition and performed the secondary analyses of the national sample. AD and NE contributed to the interpretation of the results and provided critical intellectual input throughout the research process. Both authors were actively involved in drafting and revising the manuscript, ensuring its intellectual content and accuracy. All the authors read and approved the final manuscript.

Corresponding author

Correspondence to Aslı Davas.

Ethics declarations

Ethics approval and consent to participate

The principles of the Declaration of Helsinki were followed, meaning that the survey results were published at an aggregate level and that the anonymity of the interviewed individuals and households was fully secured. Before interpreting the results, the researchers obtained the consent of the Ethical Board of the School of Medicine, Istanbul Okan University.

Consent for publication

NOT APPLICABLE.

Competing interests

The authors declare no competing interests.

This study is not an experimental study; it is a secondary analysis of the 2019 Turkey Health Survey (THS), a cross-sectional study conducted between September and December 2019 by the Turkish Statistical Institute (TurkStat). The consent of the participants was obtained by the Turkish Statistical Institute. The declaration of the Turkish Statistical Institute regarding metadata and publication as well as Instutional Quality Check Reports can be accessed on the bottom right side of the webpage: https://data.tuik.gov.tr/Bulten/Index?p=Turkey-Health-Survey-2019-33661.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Davas, A., Etiler, N. Gender differences in cost-related unmet healthcare needs: a national study in Turkiye. BMC Public Health 24, 2413 (2024). https://doi.org/10.1186/s12889-024-19878-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-024-19878-9

Keywords

BMC Public Health

ISSN: 1471-2458

Contact us