Individual characteristics associated with utilization of nursing care in very old population: cross-sectional study

doi:10.21203/rs.3.rs-1410858/v1

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Research Article

Individual characteristics associated with utilization of nursing care in very old population: cross-sectional study

https://doi.org/10.21203/rs.3.rs-1410858/v1

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Background: Older adults aged 80 or older belong to the most frequent recipient of nursing care. Since this age group remains often underrepresented in previous research, little is known about the characteristics associated with utilization of nursing care services. Therefore, the aim of this study was to examine individual (predisposing, enabling, and need) predictors of nursing care utilization in very old population of North Rhine-Westphalia (NRW).

Methods: Using data from a representative cross-sectional study, 1,531 community-dwelling and institutionalized individuals aged ≥80 years were included. The use of outpatient care services, day care, private and inpatient nursing care was considered. Multinomial regression was applied to investigate the factors explaining nursing care use in very old adults.

Results: Overall, 69.9% of participants used no nursing care services, 21.9% were using outpatient/day and/or private care, and 8.2% were institutionalized. Compared to very old adults who did not use any nursing care services, users of outpatient/day and/or private care had higher likelihood of being older, having no partner, and experiencing higher functional and cognitive disability. Comparing non-users with those using inpatient nursing care, institutionalized individuals were more likely older, had lower socioeconomic status, were childless and not in partnership, socially isolated, felt more likely lonely, were more functional and cognitive impaired, but they experienced less likely five or more chronic conditions, and were less likely physically pre-frail and frail.

Conclusions: Individual need factors (referring to health status) dominated in explaining utilization of outpatient/day and/or private care, suggesting that very old population in NRW may have equitable access to these services. Since social structure, region, and social resources explained who have received inpatient nursing care, this kind of care might be inequitable accessible to very old adults in NRW. Nevertheless, the results indicate that nursing homes could substitute the role of missing closest relatives as potential caregivers, prevent frailty and multimorbidity, but fail to ensure social inclusion of the oldest-old within facilities.

community-dwelling

nursing home

frailty

social factor

advanced age

In Germany, like in many European countries, an increasing trend in the proportion of the population aged 80 and over can be observed (1). Despite a majority of older adults aged 80 or older live at home, the proportion of individuals in need of nursing care has been continually rising in this age group over last years (2). In 2019, 40.0% of persons aged 80 and older needed care according to German nursing insurance system, of which 74.2% received home care (formal or informal) and 25.8% were institutionalized (2). To overcome these challenges of healthcare system, it is important to understand what individual characteristics explain nursing care utilization (NCU), especially in the oldest age group with the most nursing care users (2). However, there are to date only few studies in Germany including younger age groups (3–5). Therefore, the aim of the present study was to explore individual characteristics associated with NCU of the very old population in North Rhein-Westphalia (NRW), the most populated state of Germany.

To identify relevant predictors, behavioral model of health services use developed by Andersen (6) was adapted which differentiates three types of determinants:

First, predisposing factors involve characteristics increasing the likelihood of NCU, such as demographics or social background. In most studies, older age (4, 7–13) and belonging to ethnic majority (12, 14) was consistently reported as predisposing risk factors for use of home care or nursing home utilization. There are inconclusive findings regarding sex and social background. On the one hand, higher education level (3, 7), and female sex (3, 12, 13) was associated with NCU. However, other studies failed to identify any association in this regard (4, 9, 11, 14). An US study found that older adults living in rural areas had higher risk of nursing home admission (12).

Second, enabling determinants include resources needed to use care services, such as social relationships which may impede or facilitate NCU. There is overwhelming consensus about the increased likelihood of use of formal caregiving services for older adults who experience a lack of social support and loneliness (8, 11, 13, 15). Cegri et al. (9) found social vulnerability (assessed, e.g., on the basis of family situation or social relations) significantly predicting admission to home care and institutionalization during the 8-year follow-up. Having children or regular contact with them (10, 12, 14), being married (12, 13), and living together with at least one other person in the same household (3, 4, 8–11) were identified as resources protecting from NCU. Size of social network was not associated with NCU (16).

Third, the need for care represents the most important determinant as it relates to person's health status. Not surprisingly, functional ability has been found to be a key aspect. The majority of studies reported higher need for assistance in performing basic activities of daily living (ADL) and/or and instrumental activities of daily living (IADL) being associated with the NCU (3, 4, 7, 9–12). Similarly, decreased cognitive function rose the risk for NCU (4, 8, 9, 11, 14). Using different assessment tools, previous studies (15, 17–19) consistently showed that physical frailty was associated with increased use of home care services. Based on Tilburg Frailty Indicator, Verver et al. (18) observed that besides physical frailty, also the combination of physical, social (e.g., living alone, low social support), and psychological frailty (e.g., problems with memory) contributed to higher use of informal and home care. Cegri et al. (9) found that individuals rating their health status as poor at the study baseline had higher risk of admission into home care or nursing home over the next eight years. Kehusmaa et al. (11) demonstrated that frequent utilization of care services can contribute to an improvement in perceived health status over time. Other studies could not confirm the association between subjective health and NCU (4, 12, 14). Similar inconclusive effects were found regarding the association between multimorbidity and NCU (3, 9, 13).

Following Anderson (6), this paper examined which predisposing, enabling, and need factors, contribute to the explanation of nursing care utilization among the very old population in NRW.

Study design

Data from the representative study “Quality of Life and Well-Being of the Very Old in North Rhine-Westphalia” (NRW80+) were used, collected between 2017 and 2018. In the study sample, community-dwelling and institutionalized individuals aged 80 years or older were included. Proxy interviews were conducted when target persons could not participate themselves due to health impairment. To correct for oversampling in older age groups (85–89 years, 90 years or older) and men, data weights were applied, which allows a generalization of the results for the very old population in NRW. In total, 1,863 persons participated in computer-assisted personal interviews including 176 interviews with proxies. For further details about the study design, see Hansen et al. (20).

Measures

Dependent variable

To define the utilization of nursing care among the participants, data from two different sources were used. First, respondents provided information on the type of nursing care they were currently receiving. Initially, participants specified whether they were receiving full inpatient nursing care or not. If this was not the case, they were further asked whether they were using outpatient care services, day care and/or private care. Second, the interviewer’s assessment of living arrangements was additionally considered, since we found several indicators that self-reported type of received care could not be plausible for few respondents. These cases are described in more details below.

No nursing care use (noNCU) was attributed to persons, who according to interviewer’s assessment lived in a private, multigenerational or assisted living apartment/house, or whose residential form was unknown, and at the same time they did not use any of the care services (full inpatient, outpatient, day or private care). Given that there are different hybrid forms of care and housing options for older adults in Germany (21), noNCU was possible also for persons who were recognized as residents of nursing homes, residential care groups, retirement homes or seniors’ residences by interviewers. These participants reported not to use any of the care services and had predominantly no need for care collected as self-reported care degree determining the need of long-term care according on the German Long-term Care Insurance.

Regardless of residential form, participants who stated using outpatient, day and/or private care were assigned to outpatient/day/private nursing care use (odpNCU) group. Additionally, 8 respondents were included in odpNCU as well, although they reported to receive full inpatient care. According to interviewers, these persons lived in typical private house or apartment. Since a full inpatient care is only possible in an institution in Germany (which can be clearly distinguished from private housing during an on-site interview), and most of them reported themselves to be in need of care, we proposed these participants received more likely some kind of outpatient or day nursing care.

Finally, inpatient nursing care use (inpNCU) was given, when respondents lived in nursing homes, residential care groups, retirement homes or seniors’ residences according to interviewer’s assessment and they reported to receive full inpatient care.

Independent variables

Based on previous findings, age (in years), migration background (no/yes), sex, and socioeconomic status (SES) were included as predisposing factors. Using the lnternational Standard Classification of Occupations 2008 defined by Ganzeboom (22) SES referred to the last occupational position of the respondent before she or he retired. The scale ranged from 16 (e.g., cleaners, helpers) to 90 (judges) (23). In additition, community size considering four region types was included; the operationalization was described in detail elsewhere (24).

Enabling factors referred to presence of children (no/yes), partnership status (in partnership vs. no partnership), time spent with others (never or rarely/ sometimes/often or very often), loneliness (never or sometimes/most of the time or always), and social isolation. Following Huxbold and Engstler (25), individuals were defined as socially isolated if they could not name more than one person in their social network to whom they had contact with at least once a week. Moreover, household members were counted as part of the social network.

Finally, functional and cognitive impairment, multimorbidity, physical frailty as well as subjective health status were considered as need factors. Functional abilities were assessed using seven items referring to IADL and seven items related to ADL (26). For IADL and ADL, the mean score was calculated ranging from zero (not possible without help) to two (no help needed). Based on SF-8 (27), self-rated health status was measured with one item (very good/rather good/rather poor/very poor). Multimorbidity was operationalized as experiencing five or more chronic conditions using self-reported medically treated diseases. For more information on the assessment of multimorbidity in NRW80 + see Brijoux et al. (28). To determine cognitive impairment, the Demtect screening tool (29) was applied, defining the cut-off of eight and fewer points as dementia, and nine to 12 points as mild cognitive impairement (28). The definition of physical frailty was based on Fried et al. (30) using four frailty criteria: exhaustion, unintentional weight loss, weakness, and low physical activity. Respondents meeting four or three criteria were defined as frail, those who met two or one criteria were classified as pre-frail, and persons meeting non of the criterion were categorized as robust. Details on operationalization of physical frailty within the NRW80 + were published elsewhere (24).

Statistical analyses

Participants whose handgrip strength was not measured because the interviews were conducted with proxies (N = 176), and who refused to perform the handgrip strength test (N = 110), were excluded from the analyses. The score of the handgrip strength test was needed for the operationalization of weakness (criterion of physical frailty). Similarly, respondents were excluded, when they denied the cognition test Demtect (N = 46). Final analysis sample included 1,531 very old adults. Multiple imputation was applied to replace missing values. The majority of missing values occurred in the cognition score (15.2%) and SES (2.9%). In total of 20 imputed datasets were generated. The results of the original (non-imputed) dataset are only reported when they significantly differed from the imputed dataset. Multinomial regression was applied to analyze the (predisposing, enabling, need) factors of utilization of nursing care services in very old adults. Statistical significance was set at p < 0.05. The variance inflation factors did not exceed the threshold of two by any of the included variables. For all analyses, IBM SPSS Statistics (Version 26) was used.

In our study sample, 69.9% very old adults did not use any of the nursing care services. 21,9% used outpatient, day care services and/or private care. Inpatient nursing care was provided to 8.2% of very old persons. For the further details about sample description see in Table 1.

Table 1

Description of study population differenciated by utilization of nursing care (N = 1,549)
Variable		Total	NoNCU	OdpNCU	InpNCU
		% or mean (SD)	% or mean (SD)	% or mean (SD)	% or mean (SD)
Total		100	69.9	21.9	8.2
Age (in years)		84.8 (4.0)	84.0 (3.4)	86.0 (4.1)	88.3 (5.0)
Sex
	male	37.1	41.6	31.5	13.5
	female	62.9	58.4	68.5	86.5
Socioeconomic status^a		41.5 (20.7)	43.8 (20.9)	37.1 (20.0)	33.6 (16.7)
Migration background
	no	76.7	76.8	77.4	74.6
	yes	23.3	23.2	22.6	25.4
Community type
	5,000 to 49,999	13.4	12.8	17.1	7.9
	50,000 to 99,999	13.4	12.7	12.9	20.5
	100,000 to 499,999	34.0	33.5	37.1	30.1
	≥ 500,000	39.2	40.9	32.9	41.5
Children
	no	11.5	11.7	8.0	19.0
	yes	88.5	88.3	92.0	81.0
Partnership status
	no partnership	58.2	51.0	70.8	85.7
	in partnership	41.8	49.0	29.2	14.3
Social isolation
	no	78.4	79.9	83.4	51.8
	yes	21.6	20.1	16.6	48.2
Loneliness
	never/rarely	95.0	97.0	90.9	88.1
	mostly/always	5.0	3.0	9.1	11.9
Time spent with others
	never/rarely	14.5	13.9	18.0	11.3
	sometimes	25.3	23.7	28.9	29.6
	often/very often	60.1	62.4	53.1	59.1
Self-rated health status
	very good	11.0	12.8	4.7	12.6
	rather good	50.2	53.5	39.8	49.6
	rather poor	31.8	28.4	43.1	29.9
	very poor	7.0	5.3	12.4	7.9
Basic activities of daily living (0 = not possible without help; 2 = no help needed)		1.7 (0.4)	1.9 (0.2)	1.3 (0.5)	1.2 (0.6)
Instrumental activities of daily living (0 = not possible without help; 2 = no help needed)		1.5 (0.6)	1.8 (0.3)	1.0 (0.5)	0.7 (0.6)
≥ 5 chronical conditions
	no	71.7	76.5	54.7	75.6
	yes	28.3	23.5	45.3	24.4
Physical frailty
	robust	24.8	32.1	5.3	14.2
	pre-frail	57.0	57.6	57.7	51.2
	frail	18.1	10.3	37.0	34.6
Dementia (Demtect)
	no cognitive impairment (13–18)	72.5	81.5	58.6	32.8
	mild cognitive impairment (9–12)	17.0	14.5	21.1	27.2
	Dementia (< 9)	10.5	4.0	20.3	40.0
Note. Weighted data. NoNCU: no nursing care use. OdpNCU: outpatient, day, and/or private nursing care use. InpNCU: inpatient nursing care use. SD: Standard Deviation. In case the values differed among the imputed datasets, average values are reported. p < 0.05; p < 0.01; **p < 0.001.
^aBased on Ganzeboom and Treiman (23), the value of 42 refers to professions such as firefighters or aircraft engine mechanics. The value 44 represents general managers of restaurants and hotels (small enterprises). 37 stands e.g. for market salespersons or bookbinders. 34 represents e.g. heavy truck drivers or waiters/waitresses.

As shown in Table 2, an increase in age (in years) was significantly associated with enhanced odds of odpNCU by 5.6% and of inpNCU by 14.3% (relative to noNCU). Increase of SES by one unit (e.g., from senior officials to production department managers) was associated with a 1.7% decrease in odds of inpNCU. Very old adults who lived in communities with 5,000 to 49,999 (compared to 500,000 or more) inhabitants had 78.4% lower likelihood of inpNCU. Not having children was associated with 3.827 times higher odds of inpNCU. Having partner decreased the likelihood of odpNCU by 42.3% and inpNCU by 56.7%. Social isolation was linked with 3.939 times higher odds of inpNCU. Similarly, experiencing loneliness most of the time or always increased the likelihood of inpNCU 2.942 times. One-unit-increase in ADL (e.g., from not possible without help to possible with little help) was associated with decreased odds of odpNCU by 98.5% and of inpNCU by 99.0%. Increase in IADL declined the likelihood of odpNCU by 81.9% and of inpNCU by 95.6%. Experiencing five or more chronical conditions was linked to a 57.7% decrease of inpNCU. Pre-frailty (compared to robust) was associated with a 75.8% decline of inpNCU and being frail decreased the odds of inpNCU by 91.5%. One-unit-increase of cognitive capacity (e.g., from dementia to mild cognitive impairment) reduced the likelihood of odpNCU by 37.5% as well as of inpNCU by 52.3%. The model estimates are shown in Table 2.

Table 2

Multinomial regression model of the associations between home environment and frailty level (N = 1,549)
		OdpNCU relative to noNCU			InpNCU relative to noNCU
		Odds ratio	95% CI		Odds ratio	95% CI
Predisposing factors
Age		1.056*	1.005	1.109	1.143***	1.069	1.224
Sex (Ref: female)		1.132	0.721	1.776	0.509	0.235	1.104
Socioeconomic Status		0.995	0.985	1.006	0.983*	0.967	1.000
Migration background (Ref: no)		0.665	0.422	1.050	0.928	0.477	1.808
Community type (Ref: ≥500,000)
	100,000 to 499,999^a	1.498	0.959	2.340	0.563	0.282	1.124
	50,000 to 99,999	1.178	0.647	2.146	1.253	0.548	2.867
	5,000 to 49,999	1.355	0.765	2.399	0.216**	0.079	0.592
Enabling factors
Children (Ref: yes)^a		0.713	0.390	1.302	3.827**	1.710	8.564
Partnership status (Ref: no partnership)^a		0.577*	0.367	0.908	0.433*	0.195	0.962
Social isolation (Ref: no)		0.761	0.466	1.243	3.939***	2.056	7.546
Loneliness (Ref: never/rarely)^a		2.004	0.950	4.227	2.942*	1.581	7.892
Time spent with others (Ref: often/very often)
never/rarely		0.867	0.507	1.481	0.434	0.178	1.061
sometimes		0.939	0.600	1.471	0.800	0.405	1.581
Need factors
Self-rated health status		1.045	0.799	1.366	1.469	0.973	2.218
Basic activities of daily living		0.015***	0.006	0.036	0.010***	0.004	0.029
Instrumental activities of daily living		0.181***	0.111	0.295	0.044***	0.020	0.094
≥ 5 chronical conditions (Ref: no)		1.203	0.789	1.833	0.423*	0.204	0.878
Physical frailty (Ref: robust)
pre-frail^a		1.436	0.779	2.648	0.242**	0.101	0.577
frail		1.136	0.528	2.445	0.085***	0.026	0.272
Dementia (Demtect)		0.625**	0.439	0.890	0.477**	0.309	0.738
Pseudo R-squared (Nagelkerke)^b		0.695***
Note. Weighted data. NoNCU: no nursing care use. OdpNCU: outpatient, day, and/or private nursing care use. InpNCU: inpatient nursing care use. Ref: Reference Category.
^aThe findings differed between the original and full imputed dataset. For more details see result section. ^bCalculated as the mean value of from all imputed datasets.
p < 0.05; p < 0.01; **p < 0.001.

Following differences in the results of the original (non-imputed) dataset were found: not having children was significantly associated with decreased odds of odpNCU by 60.7% (OR = 0.393, [95% CI: 0.185, 0.835]); relationship status was not linked to odpNCU; living in communities with 100,000 to 499,999 (compared to 500,000 or more) inhabitants significantly decreased inpNCU by 70.6% (OR = 0.294, [95% CI: 0.125, 0.693]), physical pre-frailty and loneliness were not associated with inpNCU.

The current study showed that predisposing (age), enabling (partnership status), and need factors (functional and cognitive impairment) predicted the use of outpatient, day and/or private nursing care of very old adults in NRW. Several predisposing (age, SES, community size), enabling (presence of children, partnership status, social isolation, loneliness) as well as need factors (functional and cognitive impairment, physical frailty, multimorbidity) were significantly associated with inpNCU.

Consistent with previous literature, the predisposing factor increasing age was associated with both odpNCU (cf. 7, 9, 13) and inpNCU (cf. 4, 8, 9, 12). This result underlines that nursing care needs increase with age. In the present study, very old adults with higher SES had lower likelihood of inpNCU, opposite to finding of Yu et al. (7) and Steinbeisser et al. (3). Since the majority of previous studies considering education level as indicator of social class found no relationship with inpNCU (3, 4, 7), this finding may indicate that use of the last occupation before retirement (22) could be more appropriate indicator of social status than educational level. Other explanation of these inconsistencies might be related to the higher age of the study participants, suggesting increase of socioeconomic gradient in health over time (cf. 31, 32). There is evidence that persons with higher SES experience better health status over the lifespan (31–33), which might result in lower likelihood of NCU (cf. 34). Furthermore, inconsistent with a study conducted in the US (12), there was lower likelihood of inpNCU among very old adults living in communities of NRW with less than 50,000 inhabitants. Taking the findings of Kuppler and Wagner (35) into account, lower inpNCU in smaller communities might be attributed to lower inpatient nursing care supply in these areas of NRW. Other perspective provides the study of Zimmermann et al. (24) reporting lower likelihood of physical frailty among very old adults who lived in small communities of NRW, which could lead to lower demand for inpNCU.

Looking at enabling factors, similar to previous findings, having children (cf. 12, 14) decreased the likelihood of inpNCU. Likewise, being in partnership reduced the demand of odpNCU (cf. 7, 9, 13) and of inpNCU (cf. 4, 8, 12). Moreover, social isolation and feeling lonely increased the likelihood of inpNCU, which is also in accordance with research literature (3, 4, 8, 9). On the one hand, these findings may indicate that the lack of close social connections (such as absence of children or partner) and loneliness may facilitate the use of inpatient nursing care services. On the other hand, admission to long-term care facilities might lead to the loss of existing social networks and consequently to loneliness (cf. 36).

The majority of individual need characteristics played an important role in explaining of NCU of very old population. In line with previous research, participants with higher impairment in ADL and IADL had increased likelihood of odpNCU (cf. 9–11) and of inpNCU (cf. 3, 4, 9, 12). Similarly, lower cognitive function was associated with increased demand for both odpNCU and inpNCU (4, 8, 9, 11). In contrast to previous studies (3, 5, 9, 37), experiencing physical pre-frailty and frailty as well as multimorbidity was lower in inpNCU than in noNCU. Protective effect of inpNCU on multimorbidity and physical frailty might be explained according to Andersen (6) in terms of effective access to inpatient nursing care services in NRW, when the use of the services contributes to an improvement of physical health status. However, this effect could be also related to a bias of the analysis sample, since proxy interviews were excluded.

The present study investigated for the first time the relationship between individual characteristics and the different types of NCU using representative data for the very old population in NRW. For the definition of NCU, self-reported information as well as information from interviewers were considered to identify NCU status as accurately as possible. Furthermore, besides sociodemographic and health characteristics included in previous German studies (3–5), social predictors of NCU (such as isolation or loneliness) were included. However, the study has also some limitations. First, for the definition of physical frailty, four instead of five criteria recommended by Fried et al. (30) were used, because walking speed was not assessed in NRW80+. The exclusion of this criterion was previously found to have the smallest impact on predicting adverse health outcomes (38). Second, the proxy interviews had to be excluded from the analyses because of the absent measurement of handgrip strength of the target person. Multiple imputation was performed to replace the missing values in order to minimize possible bias. Third, since cross-sectional data were used for the analysis, no conclusions about causal relationships can be derived.

Conclusion

Applying Andersen's behavioral model (6), the dominance of individual need factors in explaining of odpNCU suggests that very old adults in NRW have an equitable access to this kind of nursing services based on actual care demands. Instead, the access to inpNCU could be characterized as inequitable because social structure, region, and enabling resources determine who receives the care (cf. 6). However, the findings suggest that inpNCU of very old adults might serve as a compensation of missing social resources (i.e., closest relatives as potential informal caregivers). Additionally, the results indicate that prevention of social isolation and loneliness, recognized as indicators of social frailty (15, 18), has not been sufficiently established in residential care facilities in NRW. Since the evidence show that social frailty predict physical frailty, disability, and mortality (39–42), appropriate interventions to enhance social inclusion of very old adults living in inpatient nursing care settings are needed. Finally, there might be an indication of inequitable supply of institutional care services in smaller communities of NRW. Further research is needed to investigate this aspect in more detail.

ADL

basic activities of daily living

IADL

instrumental activities of daily living

inpNCU

inpatient nursing care use

NCU

nursing care utilization

noNCU

no nursing care use

NRW

North Rhein-Westphalia

NRW80+

representative study “Quality of Life and Well-Being of the Very Old in North Rhine-Westphalia”

odpNCU

outpatient, day, and/or private nursing care use

SES

socioeconomic status.

Acknowledgement

The project is part of the Key Research Area “Aging and Demographic Change” at the Cologne Center for Ethics, Rights, Economics, and Social Sciences of Health at the University of Cologne in Germany. Members of the project board are Michael Wagner and Susanne Zank.

Authors’ contribution

JZ framed the study design, performed the analyses, and was the only contributor in writing the manuscript.

Funding

NRW80+ was funded by the Ministry of Innovation, Science and Research of North Rhine-Westphalia, Germany [23-8.03-125240]. The funding agency played no role in the design, collection, analysis and interpretation of data, or writing of the manuscript.

Availability of data and materials

The dataset of NRW80+ is available as a scientific use file at the GESIS – Leibniz Institute for the Social Sciences data repository under https://doi.org/10.4232/1.13527.

Ethics approval and consent to participate

The protocol of NRW80+ was approved by the ethics committee of the Medical Faculty of the University of Cologne (No. 17-169). Informed consent was obtained from all participants. All procedures were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not applicable.

Conflicts of interest

The author declares no competing interest.

Author details

¹Cologne Center of Ethics, Rights, Economy, and Social Science of Health, University of Cologne, Albertus-Magnus-Platz, Cologne 50923, Germany

Eurostat. Population by age group; 2021. Available from: URL: https://ec.europa.eu/eurostat/databrowser/view/tps00010/default/table?lang=en.
Statistisches Bundesamt. Pflegestatistik 2019: Pflege im Rahmen der Pflegeversicherung; Deutschlandergebnisse; 2020. Available from: URL: https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Gesundheit/Pflege/Publikationen/Downloads-Pflege/pflege-deutschlandergebnisse-5224001199004.pdf?__blob=publicationFile.
Steinbeisser K, Grill E, Holle R, Peters A, Seidl H. Determinants for utilization and transitions of long-term care in adults 65 + in Germany: results from the longitudinal KORA-Age study. BMC Geriatr 2018; 18(1):172.
Luppa M, Luck T, Matschinger H, König H-H, Riedel-Heller SG. Predictors of nursing home admission of individuals without a dementia diagnosis before admission - results from the Leipzig Longitudinal Study of the Aged (LEILA 75+). BMC Health Serv Res 2010; 10:186.
Dapp U, Minder CE, Anders J, Golgert S, Renteln-Kruse W von. Long-term prediction of changes in health status, frailty, nursing care and mortality in community-dwelling senior citizens - results from the longitudinal urban cohort ageing study (LUCAS). BMC Geriatr 2012; 14.
Andersen RM. National Health Surveys and the Behavioral Model of Health Services Use. Med Care 2008; 46(7):647–53.
Yu H-W, Tu Y-K, Chen Y-M. Sociodemographic characteristics, disability trajectory, and health care and long-term care utilization among middle-old and older adults in Taiwan. Arch Gerontol Geriatr 2019; 82:161–6.
Braunseis F, Deutsch T, Frese T, Sandholzer H. The risk for nursing home admission (NHA) did not change in ten years–a prospective cohort study with five-year follow-up. Arch Gerontol Geriatr 2012; 54(2):e63-7.
Cegri F, Orfila F, Abellana RM, Pastor-Valero M. The Impact of Frailty on Admission to Home Care Services and Nursing Homes: Eight-Year Follow-Up of a Community-Dwelling, Older Adult, Spanish Cohort. BMC Geriatr 2020; 20(1).
Kjær AA, Siren A. Formal and informal care: trajectories of home care use among Danish older adults. Ageing Soc 2020; 40(11):2495–518.
Kehusmaa S, Autti-Rämö I, Helenius H, Hinkka K, Valaste M, Rissanen P. Factors associated with the utilization and costs of health and social services in frail elderly patients. BMC Health Serv Res 2012; 12(1):1–9.
Cohen A, Bulanda JR. Social Supports as Enabling Factors in Nursing Home Admissions: Rural, Suburban, and Urban Differences. J Appl Gerontol 2016; 35(7):721–43.
Gobbens RJJ, van Assen MALM. Frailty and its prediction of disability and health care utilization: the added value of interviews and physical measures following a self-report questionnaire. Arch Gerontol Geriatr 2012 [cited 2020 Jan 16]; 55(2):369–79.
Noël-Miller C. Spousal loss, children, and the risk of nursing home admission. J Gerontol B Psychol Sci Soc Sci 2010; 65B(3):370–80.
Lambotte D, Donder L de, van Regenmortel S, Fret B, Dury S, Smetcoren A-S et al. Frailty differences in older adults' use of informal and formal care. Arch Gerontol Geriatr 2018; 79:69–77.
Dupraz J, Henchoz Y, Santos-Eggimann B. Formal home care use by older adults: trajectories and determinants in the Lc65 + cohort. BMC Health Serv Res 2020; 20(1):22.
Sicsic J, Ravesteijn B, Rapp T. Are frail elderly people in Europe high-need subjects? First evidence from the SPRINTT data. Health Policy 2020; 124(8):865–72.
Verver D, Merten H, Blok C de, Wagner C. A cross sectional study on the different domains of frailty for independent living older adults. BMC Geriatr 2019 [cited 2020 Mar 4]; 19(1):61.
Hoeck S, François G, Geerts J, van der Heyden J, Vandewoude M, van Hal G. Health-care and home-care utilization among frail elderly persons in Belgium. Eur J Public Health 2012 [cited 2020 Jan 16]; 22(5):671–7.
Hansen S, Kaspar R, Wagner M, Woopen C, Zank S. The NRW80 + Study: Conceptual Background and Design Decisions. Z Gerontol Geriatr 2021; 54:76–84.
Crößmann G, Börner K. Neue Wohn- und Betreuungsformen im heimrechtlichen Kontext. Berlin; 2005 [cited 2022 Feb 22]. Available from: URL: https://www.bmfsfj.de/resource/blob/78970/38ef7ee9cbe1fe05547e46c9e7109d29/croessmann-data.pdf.
Ganzeboom H. A new international socio-economic index [ISEI] of occupational status for the international standard classification of occupation 2008 [ISCO-08] constructed with data from ISSP 2002–2007: With an analysis of quality of occupational measurement in ISSP. Lisbon; 2010. (Annual Conference of International Social Survey Programme).
Ganzeboom H, Treiman DJ. Internationally Comparable Measures of Occupational Status for the 1988 International Standard Classification of Occupations. Soc Sci Res 1996; 25:201–39.
Zimmermann J, Hansen S, Wagner M. Home environment and frailty in very old adults. Z Gerontol Geriatr 2021; 54:114–9.
Huxbold O, Engstler H. Soziale Isolation und Einsamkeit bei Frauen und Männern im Verlauf der zweiten Lebensphase. In: Vogel C, Wettstein M, Tesch-Römer C, editors. Frauen und Männer in der zweiten Lebenshälfte: Älterwerden im sozialen Wandel. Wiesbaden: Springer VS; 2019. p. 71–89.
Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist 1969; 9(3):179–86.
Ellert U, Lampert T, Ravens-Sieberer U. Messung der gesundheitsbezogenen Lebensqualität mit dem SF-8. Eine Normstichprobe für Deutschland. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2005; 48(12):1330–7.
Brijoux T, Woopen C, Zank S. Multimorbidity in old age and its impact on life results. Z Gerontol Geriatr 2021; 54:108–13.
Kalbe E, Kessler J, Calabrese P, Smith R, Passmore AP, Brand M et al. DemTect: a new, sensitive cognitive screening test to support the diagnosis of mild cognitive impairment and early dementia. Int J Geriatr Psychiatry 2004; 19(2):136–43.
Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56A(3):M146-M156.
House JS, Lantz PM, Herd P. Continuity and Change in the Social Stratification of Aging and Health Over the Life Course: Evidence From a Nationally Representative Longitudinal Study From 1986 to 2001/2002 (Americans' Changing Lives Study). J Gerontol B-Psychol 2005; 60(SPI/2):15–26.
Stolz E, Mayerl H, Waxenegger A, Rásky É, Freidl W. Impact of socioeconomic position on frailty trajectories in 10 European countries: evidence from the Survey of Health, Ageing and Retirement in Europe (2004–2013). J Epidemiol Community Health 2017; 71(1):73–80.
Uphoff EP, Pickett KE, Cabieses B, Small N, Wright J. A systematic review of the relationships between social capital and socioeconomic inequalities in health: a contribution to understanding the psychosocial pathway of health inequalities. Int J Equity Health 2013; 12:54.
van der Heyden J, Demarest S, Tafforeau J, van Oyen H. Socio-economic differences in the utilisation of health services in Belgium. Health Policy 2003; 65(2):153–65.
Kuppler M, Wagner M. Effect of Regional Long-Term Care Service Supply on Choice of Care Arrangement in Old Age. Population Ageing 2020.
Zamanzadeh V, Rahmani A, Pakpour V, Chenoweth LL, Mohammadi E. Psychosocial changes following transition to an aged care home: qualitative findings from Iran. Int J Older People Nurs 2017; 12(2).
Kim Y-P, Choe Y-R, Park J-H, Kim S, Won C-W, Hwang H-S. Frailty index associated with all-cause mortality, long-term institutionalization, and hip fracture. Eur Geriatr Med 2019; 10(3):403–11.
Theou O, Cann L, Blodgett J, Wallace LMK, Brothers TD, Rockwood K. Modifications to the frailty phenotype criteria: Systematic review of the current literature and investigation of 262 frailty phenotypes in the Survey of Health, Ageing, and Retirement in Europe. Ageing Res Rev 2015; 21:78–94.
Ma L, Sun F, Tang Z. Social Frailty Is Associated with Physical Functioning, Cognition, and Depression, and Predicts Mortality. J Nutr Health Aging 2018; 22(8):989–95.
Yamada M, Arai H. Social Frailty Predicts Incident Disability and Mortality Among Community-Dwelling Japanese Older Adults. J Am Med Dir Assoc 2018; 19(12):1099–103.
Tsutsumimoto K, Doi T, Makizako H, Hotta R, Nakakubo S, Kim M et al. Social Frailty Has a Stronger Impact on the Onset of Depressive Symptoms than Physical Frailty or Cognitive Impairment: A 4-Year Follow-up Longitudinal Cohort Study. J Am Med Dir Assoc 2018; 19(6):504–10.
Makizako H, Shimada H, Tsutsumimoto K, Lee S, Doi T, Nakakubo S et al. Social Frailty in Community-Dwelling Older Adults as a Risk Factor for Disability. J Am Med Dir Assoc 2015; 16(11):1003.e7-11.

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Individual characteristics associated with utilization of nursing care in very old population: cross-sectional study

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