What this is
- This research investigates healthcare service non-use among in Shandong, China.
- are defined as those without children or whose children have left home.
- The study compares non-use rates of healthcare services between empty-nest and non-.
- It identifies financial difficulties as a significant barrier to healthcare access for empty-nest seniors.
Essence
- in Shandong, China, experience higher rates of compared to their non-empty-nest counterparts. Financial difficulties are the primary reason for this disparity.
Key takeaways
- have a non-visiting rate of 37.7%, higher than 32.7% for non-. This indicates a significant disparity in healthcare access between these groups.
- Financial difficulties are the leading cause of , affecting 46% of empty-nest seniors for non-visiting and 58% for non-hospitalization. This highlights the economic barriers faced by this population.
- Low-income households, lack of health insurance, and the presence of non-communicable chronic diseases are associated with higher non-use rates among empty-nest seniors. These factors underscore the need for targeted healthcare policies.
Caveats
- The study's cross-sectional design limits causal inferences about the relationship between identified factors and .
- Self-reported data may introduce bias, affecting the accuracy of reported healthcare use and reasons for non-use.
- Seasonal variations in health conditions were not accounted for, potentially influencing the non-use rates reported.
Definitions
- empty-nest elderly: Elderly individuals without children or whose children have left home, often living alone or with a spouse.
- non-use of healthcare services: Failure to visit healthcare providers when needed, including both outpatient visits and hospital admissions.
AI simplified
Background
China has the largest number of the older people in the world [1]. In 2013, 14.9 % of the Chinese population (202.4 million) were aged 60 and above [2]. Consistent with the global trend, China will step into a fastest aging period in its history [3, 4]. By 2050, the elderly is expected to represent 33 % of the total population [5, 6] . With the accelerating process of population aging trend, the absolute and relative numbers of empty-nest elderly families are both on the rise in China [7, 8]. Empty-nest elderly refers to those elderly with no children or whose children have already left home. These older people either live alone (empty-nest singles) or with a spouse (empty-nest couples) [9]. There were 100 million empty-nest older people in 2013, accounting for about 50 % of the total elderly population in China [10]. This proportion is projected to represent 90 % of the total aged population by 2030 [11].
To ensure equal access to health care according to needs, regardless of age, gender, ethnic background and capacity to pay, is an important goal for health service system worldwide [12, 13]. The aging process has raised concerns about equal access to health care for seniors, who are identified to have higher healthcare needs but often lack the financial capacity to pay [14]. Several studies have addressed this issue by examining associated factors with healthcare utilization among older people in China, including socio-demographic characteristics (e.g. age, gender), income, health insurance and healthcare needs [14β17]. Non-use of health care service (e.g. non-visiting, non-hospitalization) is another aspect of the health care access issue, which mainly results from limited availability or unavailability of health care services when they are needed, such as non-visiting and non-hospitalization [13]. It is one of the most important health care access issues we should address, as it may further result in more serious health problems and pose higher health burdens on individuals and households. Therefore, to assess non-use of health care service and its associated factors is of high priority. However, few studies have explored non-use of health care service and its associated factors among elderly in China.
The aging is accompanied by an increase in the prevalence of non-communicable chronic diseases (NCDs) and resultant disabilities [18, 19]. Some researchers indicate that empty-nest elderly are at higher risk of NCDs and other diseases than non-empty-nest ones. The empty-nesters also have less financial support from children [20, 21]. Thus, the empty-nest elderly may have higher prevalence of non-use of health care service (or poorer health care access) than non-empty-nest ones. To date, few studies have focused on the healthcare service use among empty-nest older people [21], no studies have identified the prevalence and profiles of non-use of health care services among empty-nest elderly. To remedy this situation, the present study aims to identify the non-use of healthcare among this special population. The overall goal of this study is to identify the prevalence of non-use of health care use and its associated factors among empty-nest older people. To do so, we have following specific objectives. First, we will compare the prevalence of non-use of health care services between empty-nest and non-empty-nest elderly. Second, we will identify the associated factors for non-use of health care services among the empty-nest elderly.
Methods
Study setting and study population
This study was conducted in Shandong province. It ranks the second in the number of total population in China. In 2012, the older people aged 60 and above accounted for 15 % of the total population (about 97 million) in Shandong. Among which, 50 % were empty-nesters [22].
Location of the study sites in Shandong province, China
Data collection
We collected the data from November 2011 to January 2012 by using a house-to house interview. All the elderly were interviewed face-to-face using a standard structured questionnaire by trained postgraduate students from Shandong University School of Public Health. To ensure quality, completed questionnaires were carefully checked by quality supervisors after the interview. The questionnaire included: household living arrangements, demographic information on individuals and households, self-rated health, health care needs, non-use of health care service and reasons.
Variables
Dependent variables
Two measures of the non-use of health care service are used as dependent variables: one) βNon-visitingβ, is defined as βnot visit physicians despite being ill within the last 2Β weeks; two) βNon-hospitalizationβ, is defined as βnot using inpatient services despite being referred by doctors for hospital admission during the previous year.β In addition, the respondents were also asked about the reasons for non-visiting and non-hospitalization.
Independent variables
Based on the Andersen model [23], we categorize the independent variables into three types: predisposing, enabling and need variables. a.) Predisposing variables. In the present paper, the variables include age (60β, 70β, 80+), gender (male, female), education (primary and below, junior, high and above), and marital stauts (married or others). b.) Enabling variables. We classify residence (urban, rural), empty-nester living arrangements (empty-nest single or living alone, empty-nest couple or living with a spouse), low-income households (In Chinese, we call it βDibaohuβ) which was identified by local governments and subsidized by local bureau of civil affairs, and health insurance (Medical insurance for urban employees scheme (MIUE), Medical insurance for urban residents scheme(MIUR),New cooperative medical scheme (NCMS), Others, such as commercial insurance). c.) Need variables. Self-rated health (good, moderate, bad), illness in the past 2 weeks and NCDs in the past 6 months are used as measures of needs.
Data analysis
The data was double entered and checked using EPI Data 6.04. The statistical package SPSS 13.0 was used to analyze the data. Chi-square test was used to compare non-use of health care between empty-nest and non-empty-nest elderly. Reasons for non-use of health care were presented as percentages. Preliminary analyses were performed firstly using univariate logistic regression to check which factors were associated with non-use of health care. Multivariate logistic regression was then employed to assess the explanatory variables for non-visiting and non-hospitalization. Statistical significance was set at the 5Β % level.
Ethical consideration
The Ethical Committee of Shandong University School of Public Health approved the study protocol. The investigation was conducted after the informed consents of all participants were obtained.
Results
| Characteristics | Total | Empty-nest | Non-empty-nest | P | |||
|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | ||
| Observations | 4469 | 100 | 2667 | 59.7 | 1802 | 40.3 | |
| Predisposing factors | |||||||
| Gender | 0 | ||||||
| Male | 2078 | 46.5 | 1286 | 48.2 | 792 | 44 | |
| Female | 2391 | 53.5 | 1381 | 51.8 | 1010 | 56 | |
| Age | 0 | ||||||
| 60β | 2629 | 58.8 | 1445 | 54.2 | 1184 | 65.7 | |
| 70β | 1429 | 32 | 968 | 36.3 | 461 | 25.6 | |
| 80+ | 411 | 9.2 | 254 | 9.5 | 157 | 8.7 | |
| Marriage status | 0 | ||||||
| Married | 3511 | 78.6 | 2210 | 82.9 | 1301 | 72.2 | |
| Others | 958 | 21.4 | 457 | 17.1 | 501 | 27.8 | |
| Education | 0.1 | ||||||
| Primary or below | 3145 | 70.4 | 1849 | 69.3 | 1296 | 71.9 | |
| Junior | 713 | 16 | 431 | 16.2 | 282 | 15.6 | |
| High or above | 611 | 13.7 | 387 | 14.5 | 224 | 12.4 | |
| Enabling factors | |||||||
| Residence | 0.083 | ||||||
| Urban | 2305 | 51.6 | 1404 | 52.6 | 901 | 50 | |
| Rural | 2164 | 48.4 | 1263 | 47.4 | 901 | 50 | |
| Living arrangements | NAb | ||||||
| Empty-nest single | 457 | 17.1 | |||||
| Empty-nest couple | 2210 | 82.9 | |||||
| Low income householda | 0.385 | ||||||
| Yes | 331 | 7.4 | 205 | 7.7 | 126 | 7 | |
| No | 4138 | 92.6 | 2462 | 92.3 | 1676 | 93 | |
| Insurancec | 0 | ||||||
| None | 193 | 4.3 | 117 | 4.4 | 76 | 4.2 | |
| MIUE | 1168 | 26.1 | 776 | 29.1 | 392 | 21.8 | |
| MIUR | 545 | 12.2 | 327 | 12.3 | 218 | 12.1 | |
| NCMS | 2518 | 56.3 | 1417 | 53.1 | 1101 | 61.1 | |
| Others | 45 | 1 | 30 | 1.1 | 15 | 0.8 | |
| Need factors | |||||||
| Self-rated health | 0 | ||||||
| Good | 2277 | 51 | 1278 | 47.9 | 999 | 55.4 | |
| Moderate | 1497 | 33.5 | 939 | 35.2 | 558 | 31 | |
| Bad | 695 | 15.6 | 450 | 16.9 | 245 | 13.6 | |
| Illness in the past 2Β week | 0 | ||||||
| Yes | 2896 | 64.8 | 1830 | 68.6 | 1066 | 59.2 | |
| No | 1573 | 35.2 | 837 | 31.4 | 736 | 40.8 | |
| NCD in the past 6Β monthsd | 0 | ||||||
| Yes | 2930 | 65.6 | 1809 | 67.8 | 1121 | 62.2 | |
| No | 1539 | 34.4 | 858 | 32.2 | 681 | 37.8 | |
| Non-use of health care | Total | Empty-nest (%) | Non-empty-nest(%) | -valueP |
|---|---|---|---|---|
| Outpatient service non- use | 0.008 | |||
| Physician visits | 1858(64.2) | 1141(62.3) | 717(67.3) | |
| Non-visiting | 1038(35.8) | 689(37.7) | 349(32.7) | |
| Inpatient service non-use | 0.166 | |||
| Admission | 618(65.5) | 391(63.9) | 227(68.4) | |
| Non-hospitalization | 326(34.5) | 221(36.1) | 105(31.6) |
| Reasons | Non-visiting | Non-hospitalization | ||||
|---|---|---|---|---|---|---|
| Total (%) | Empty-nesters (%) | Non-empty-Nesters (%) | Total (%) | Empty-nesters (%) | Non-empty-nesters (%) | |
| N | 1038 | 689 | 349 | 326 | 221 | 105 |
| Financial difficulties | 436(42.0) | 320(46.4) | 116(33.3) | 178(54.6) | 128(57.9) | 50(47.6) |
| Illness not serious | 366(35.3) | 215(31.3) | 151(43.3) | 76(23.3) | 47(21.3) | 29(27.6) |
| Without effective medical treatment | 59(5.7) | 44(6.4) | 15(4.3) | 29(8.9) | 18(8.1) | 11(10.5) |
| Poor transportation | 17(1.6) | 9(1.3) | 8(2.3) | -- | -- | |
| Inconvenient | 14(1.3) | 8(1.2) | 6(1.7) | -- | -- | |
| No enough time | -- | -- | -- | 8(2.5) | 4(1.8) | 4(3.8) |
| No beds | -- | -- | -- | 3(0.9) | 2(0.9) | 1(1.0) |
| Others | 145(14.0) | 92(13.4) | 53(15.2) | 32(9.8) | 22(10.0) | 10(9.5) |
| =23.41,=β0.000ΟP2 | =4.23,=β0.518ΟP2 | |||||
| Variable | Univariate model | Multivariate model | |||||
|---|---|---|---|---|---|---|---|
| Non-user (%) | P-value | ORca | OR95 % CIc | P-value | ORab | OR95 % CIa | |
| Predisposing factors | |||||||
| Gender | NAc | ||||||
| Male | 304(35.7) | 1 | |||||
| Female | 385(39.3) | 0.113 | 1.17 | 0.96β1.41 | |||
| Age | NA | ||||||
| 60β | 349(37.1) | 1 | |||||
| 70β | 272(39.0) | 0.438 | 1.08 | 0.89β1.33 | |||
| 80+ | 68(35.6) | 0.698 | 0.94 | 0.68β1.30 | |||
| Marriage status | |||||||
| Married | 540(36.5) | 1 | 1 | ||||
| Others | 149(42.5) | 0.039 | 1.28 | 1.01β1.63 | 0.217 | 1.17 | 0.91β1.49 |
| Education | |||||||
| Primary and below | 519(40.6) | 1 | 1 | ||||
| Junior | 99(35.0) | 0.082 | 0.79 | 0.60β1.03 | 0.469 | 0.9 | 0.68β1.20 |
| High or above | 71(26.5) | 0 | 0.53 | 0.39β0.71 | 0.007 | 0.64 | 0.46β0.88 |
| Enabling factors | |||||||
| Residence | |||||||
| Urban | 322(31.9) | 1 | 1 | ||||
| Rural | 367(44.7) | 0 | 1.73 | 1.43β2.09 | 0.002 | 1.69 | 1.21β2.35 |
| Living arrangements | |||||||
| Empty-nest singles | 149(42.5) | 1 | 1 | ||||
| Empty-nest couples | 540(36.5) | 0.039 | 0.78 | 0.62β0.99 | 0.217 | 1.17 | 0.91β1.49 |
| Low-income householdd | |||||||
| No | 613(36.4) | 1 | 1 | ||||
| Yes | 76(51.4) | 0 | 1.84 | 1.31β2.58 | 0.008 | 1.6 | 1.13β2.56 |
| Insurancee | |||||||
| None | 37(46.8) | 1 | |||||
| MIUE | 172(30.8) | 0.005 | 0.51 | 0.31β0.81 | 0.059 | 0.62 | 0.38β1.02 |
| MIUR | 81(32.8) | 0.025 | 0.55 | 0.33β0.93 | 0.056 | 0.6 | 0.35β1.01 |
| NCMS | 389(42.1) | 0.414 | 0.83 | 0.52β1.31 | 0.022 | 0.54 | 0.32β0.92 |
| Others | 10(47.6) | 0.949 | 1.03 | 0.39β2.71 | 0.842 | 1.11 | 0.41β2.96 |
| Need factors | |||||||
| Self-rated health | NA | ||||||
| Good | 241(36.5) | 1 | |||||
| Moderate | 280(36.8) | 0.899 | 1.01 | 0.82β1.26 | |||
| Bad | 168(41.0) | 0.145 | 1.21 | 0.94β1.55 | |||
| NCD in the past 6 monthsf | |||||||
| Yes | 651(36.9) | 1 | 1 | ||||
| No | 38(57.6) | 0.001 | 2.32 | 1.41β3.82 | 0.003 | 2.16 | 1.30β3.58 |
| Variable | Univariate model | Multivariate model | |||||
|---|---|---|---|---|---|---|---|
| Non-user (%) | P-value | ORca | OR95 % CIc | P-value | ORab | OR95 % CIa | |
| Predisposing factors | |||||||
| Gender | NAc | ||||||
| Male | 107(37.0) | 1 | |||||
| Female | 114(35.3) | 0.656 | 0.93 | 0.67β1.29 | |||
| Age | NA | ||||||
| 60β | 95(35.1) | 1 | |||||
| 70β | 94(36.7) | 0.691 | 1.08 | 0.75β1.54 | |||
| 80+ | 32(37.6) | 0.664 | 1.12 | 0.68β1.85 | |||
| Marriage status | NA | ||||||
| Married | 173(34.7) | 1 | |||||
| Others | 48(42.1) | 0.141 | 1.37 | 0.90β2.07 | |||
| Education | NA | ||||||
| Primary and below | 138(35.4) | 1 | |||||
| Junior | 37(38.5) | 0.564 | 1.15 | 0.72β1.82 | |||
| High or above | 46(36.5) | 0.819 | 1.05 | 0.69β1.60 | |||
| Enabling factors | |||||||
| Residence | NA | ||||||
| Urban | 142(35.9) | 1 | |||||
| Rural | 79(36.6) | 0.86 | 1.03 | 0.73β1.46 | |||
| Living arrangements | NA | ||||||
| Empty-nest singles | 48(42.1) | 1 | |||||
| Empty-nest couples | 173(34.7) | 0.141 | 0.73 | 0.48β1.11 | |||
| Low-income householdd | |||||||
| No | 190(33.8) | 1 | 1 | ||||
| Yes | 31(62.0) | 0 | 3.19 | 1.76β5.80 | 0.005 | 3.55 | 1.91β6.59 |
| Insurancee | |||||||
| None | 29(76.3) | 1 | 1 | ||||
| MIUE | 79(33.9) | 0 | 0.16 | 0.07β0.35 | 0 | 0.17 | 0.07β0.37 |
| MIUR | 29(34.5) | 0 | 0.16 | 0.07β0.39 | 0 | 0.16 | 0.07β0.39 |
| NCMS | 80(32.1) | 0 | 0.15 | 0.07β0.33 | 0 | 0.13 | 0.06β0.30 |
| Others | 4(50.0) | 0.145 | 0.31 | 0.06β1.50 | 0.161 | 0.32 | 0.07β1.57 |
| Need factors | |||||||
| Self-rated health | NA | ||||||
| Good | 55(31.8) | 1 | |||||
| Moderate | 97(38.6) | 0.149 | 1.35 | 0.90β2.03 | |||
| Bad | 69(36.7) | 0.327 | 1.24 | 0.80β1.92 | |||
| Illness in the past 2Β weeks | NA | ||||||
| Yes | 200(35.6) | 1 | |||||
| No | 21(42.0) | 0.367 | 1.31 | 0.73β2.36 | |||
| NCD in the past 6Β monthsf | |||||||
| Yes | 203(35.1) | 1 | 1 | ||||
| No | 18(52.9) | 0.039 | 2.08 | 1.04β4.16 | 0.027 | 2.24 | 1.10β4.59 |
Discussion
One of the main features of Chinaβs population aging is the transition of elderly household patterns. To live with children is a typical Chinese traditional family pattern for older people [21]. However, with the implementation of 1-child policy, the imbalance of economic development, and the acceleration of urbanization, the number of empty-nest families is on a rapid rise in the past decades. Our findings show that 59.7 % of the elderly in our sample are empty-nesters. This proportion is higher than the reported proportion of 49 % in 2012 in the same province [22]. According to this figure, we estimate there are about 10 million of elderly living without children in Shandong province. Among which, about 1.7 million are empty-nest singles.
Consistent with previous reports, our study finds that the empty-nest elderly have poorer self-rated health, higher prevalence of 2-week illness and NCDs, which indicates that the empty-nesters have poorer health status (or higher healthcare needs) than non-empty-nest elderly [20, 24]. The departure of the children, the most important source of the love feelings and social support for the elderly, will probably increase the loneliness and also negatively affect the quality of life of the empty-nest elderly. Such feelings of loneliness and poor quality of life will push many older people into a so-called empty-nest syndrome [7]. Many researchers have pointed out that the empty-nest syndrome could result in endocrine disorders, immune dysfunction, and further cause various diseases (e.g. cardiovascular disease, cancer) [7, 25]. As such, empty-nest elderly may have higher health care need than non-empty-nest ones. Organizing senior associations might help improve the empty-nestersβ mental health.
Ideally, health service system is established to ensure equal access to health care primarily based on health needs. If this is true, it could be that empty-nesters should experience at least as equal prevalence of non-use of health care as non-empty-nesters. However, our findings reveal that empty-nest older people receive statistically higher rate of non-visiting and slightly higher prevalence of non-hospitalization than non-empty-nest ones, which indicates an inequality of health service access between the two subgroups of the seniors. This finding suggests that it is very important to explore the reasons for the higher prevalence of non-use of health care among empty-nesters and develop targeting interventions to enhance accessibility for such vulnerable population.
Some previous studies indicated that financial difficulty is the key barrier to access of health care service [15, 20, 26]. In this study, the analysis of the self-reported reasons for non-use of health services among the elderly also shows that financial difficulty is the leading cause for giving up seeking out-patient and in-patient services when needed. When comparing with non-empty-nest seniors, we found that financial difficulty exerts a statistically larger negative effect on access to out-patient service and also a larger negative effect on access to in-patient health service (even though the difference is not statistically significant) among empty-nest ones, which may be associated with their lower income and less economic support from children than the non-empty-nest ones. Surprisingly, our findings show that over 46 % of the empty-nest seniors attribute their non-visiting to financial difficulty. One possible explanation for this phenomenon is that high prevalence of NCDs push the empty-nesters into a status of using health service repeatedly and pose a high economic burden on them. Another explanation might be the shortcomings of the health insurance policy design for the low reimbursement rate or ceiling of the out-patient services. Furthermore, we also observe that nearly 58 % of the empty-nesters report the reason of financial difficulty for non-hospitalization. These findings indicate a need for the government to redesign health insurance policies to improve the accessibility to healthcare by extending the out-patient benefit package and increasing reimbursement rate for in-patient service for empty-nest elderly.
An interesting finding in this study is that the empty-nesters with NCDs experience statistically lower non-use in both physician visits and hospitalization than those without NCDs, which is inconsistent with other studies conducted in general older people [14]. There are two possible explanations for such finding. First, as a population lacking of social support, empty-nesters will consider more about the serious consequences (e.g. disability) of non-use of NCDs-related healthcare service when needed. Second, NCDs are not easily curable and need more frequent physician visits. As a result, the empty-nesters being chronically ill will well understand the symptoms and severity of NCDs and know the importance of timely visit. This finding needs to be further studied to verify among the empty-nesters.
Similar with other studies, our findings reveal that empty-nesters from low-income family tend to experience non-visiting and non-hospitalization when adjusting for need factors and predisposing factors [14, 21]. We also find that health insurance schemes (e.g. NCMS) can significantly reduce the non-use of physician visits and hospitalization among the empty-nest seniors. The findings should therefore give an impetus to develop pro-poor and pro-empty-nested health insurance policies. A special insurance supplement to existing schemes (e.g. NCMS) or a combination of health insurance and medical assistance policy targeting poor empty-nesters may be effective to reduce non-use of healthcare when needed. It is also noted in the present study that empty-nesters with lower education and those from rural areas are more likely to have non-visiting, which indicates inequality of access to healthcare service among such subgroups.
The present study involves certain limitations. First, we use the period of 2Β weeks to control recall bias when measuring non-use of physician visits. However, the potential issue of seasonal variation, particularly for those acute diseases, is unavoidable. Second, information including perceived health status, healthcare use and reasons for non-use of healthcare were self-reported, leading to the possibility of subjective bias. Third, a cross-sectional design is employed in this study, therefore, the relationship between identified factors and non-use of healthcare use can not be interpreted as cause and effect.
Conclusion
This study shows that empty-nest seniors have higher healthcare needs than non-empty-nest ones. We observe an inequality of healthcare access between empty-nesters and non-empty-nesters. Financial difficulty is the leading cause for the non-use of healthcare service among the two sub-groups of seniors and such cause exerts a larger negative effect on access to healthcare among empty-nesters. The findings indicate some at-risk subgroups of empty-nesters for non-use of physician visiting and hospitalization, such as those from low-income family, the uninsured, and those without NCDs. A comprehensive pro-poor policy of a supplement to existing health insurance schemes or a combination of health insurance and medical assistance is necessary to increase healthcare use when needed among empty-nesters.