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Health services accessibility among Spanish elderly
Social Science & Medicine 50 (2000) 17±26
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Health services accessibility among Spanish elderly Gloria FernaÂndez-Mayoralas*, Vicente RodrõÂ guez, Fermina Rojo Department of Geography, Institute of Economics and Geography, Spanish Council for Scienti®c Research (CSIC), C/ Pinar, 25, 28006 Madrid, Spain
Abstract The paper aims to identify the variables that best explain the use of health services by people aged 65 and over in Spain. The data comes from the 1993 Spanish National Health Survey (ENSE 93). The conceptual framework is the model proposed by Andersen, who suggests that utilisation is a function of predisposition to use the services, the ability to use them and of need. A bivariate and multivariate analysis (SPSS-X Discriminant Procedure) is conducted to de®ne the predictors that best discriminate users and non-users. The use of each health service is explained by a dierent set of variables. The need variables play a more important role in predicting the use of nondiscretionary services that are more closely related to healing processes (medical consultations, emergencies and hospitalisation). The predisposing and enabling variables are more relevant in explaining the use of dental services, indicating a certain degree of inequity of these discretionary services. # 1999 Elsevier Science Ltd. All rights reserved. Keywords: Elderly people; Health service utilisation; National Health Survey; Spain
Introduction Apart from dental services, considered as more discretionary (Andersen, 1995), it has been observed that the use of most health services increases with age (Anderson, 1973; Bowling et al., 1991; Hulka and Wheat, 1985; Newbold et al., 1995), is more widespread among females (Blazer et al., 1995; Bowling et al., 1991; Kleinman et al., 1981; Newbold et al., 1995), people who do not have a partner or who live alone (Bowling et al., 1991; Padgett et al., 1995), the inactive (Newbold et al., 1995) and also among people with a
* Corresponding author. Tel: +34-91-561-53-08; Fax: +3491-562-55-67. E-mail addresses: [email protected] (G. FernaÂndezMayoralas), [email protected] (V. RodrõÂ guez), f.rojo@ieg. csic.es (F. Rojo)
lower level of education (Wan and Odell, 1981) and a lower social status (Kleinman et al., 1981). The use of services also is associated with better access and availability, and this is seen mainly in urban environments (Anderson, 1973; Bowling et al., 1991) and among people who enjoy multiple health coverage (Kleinman et al., 1981; Miller, 1992; Padgett and Brodsky, 1992; RodrõÂ guez et al., 1994). Although factors in¯uencing supply and utilisation are very complicated and vary through time and space, most studies acknowledge that the predominant factor in the use of health services is need (Wan, 1989). This is an imprecise concept represented in the literature by a wealth of measurements of health status. Besides, ``need'' is related to the speci®c health system. The Spanish system provides universal coverage with limitations as regards mental, pharmacological and dental services. Access from primary to specialised (higher) health care
0277-9536/99/$ - see front matter # 1999 Elsevier Science Ltd. All rights reserved. PII: S 0 2 7 7 - 9 5 3 6 ( 9 9 ) 0 0 2 4 7 - 6
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levels is determined by ®rst level physician diagnosis. Medical (pharmacological) treatment is supported partially by the health care system, except for pensioners who obtain their medicines free upon prescription. Taking into account this type of health care system, it seems reasonable to assume that an individual's own view of his/her health aects their decision to visit a primary care provider. Health care providers will have more in¯uence on the use of specialised health services (Hulka and Wheat, 1985). One variable that may also act as a need factor is the range of medicines taken, partly because their use is determined by the physician. According to some studies, this variable depends on use of health services (HaÈkkinen, 1991; Linden et al., 1997). Another essential component of the state of elderly health relates to activities of daily living (personal care, housework and mobility) and, especially in the context of the situation, the limitations generated by health problems (reduction of the main activity or leisure activity, and being con®ned to bed) (Bowling et al., 1991). The eects on health and service use of smoking and drinking are also well known (HaÈkkinen, 1991). Therefore it seems clear that age is neither the only nor the fundamental variable for explaining the dierences in the levels of use of health services (FernaÂndez-Mayoralas et al., 1995). Thus, the main objective of this study is to identify the factors that distinguish between elderly health service users and non-users. The conceptual framework is the model proposed by Andersen that, in its 1968 version, suggested that people's use of health services is a function of their predisposition to use services, factors which enable or impede use, and their need for care (Andersen, 1995). This model has been criticised on three counts: (1) a lack of clear dierentiation between enabling and predisposing factors; (2) an emphasis on formal health care services to the neglect of informal care and social support; and (3) a conception of service use as a dichotomous event that ignores levels of care utilisation (Pescosolido, 1991). However, it is the analytical model most frequently applied in studies of the use of health services by elderly people (Wan, 1989). It is hypothesised that the model of each type of health contact will be de®ned by a dierent set of variables. The need variables will play a far more important role than the predisposing or enabling variables in predicting use, at least with regard to curative, non discretionary health services. The predisposing and enabling variables will be present in predicting the use of preventive discretionary health services, which happens to expose inequity of access (Andersen, 1995).
Material and methods Source The data have been taken from the 1993 Spanish National Health Survey (ENSE 93) with a sample of 21,058 non-institutionalised individuals aged 16 years or over. The 65+ population constituted 3475 individuals (16.5% of the respondents). Of this sub-sample, 9% were excluded from the analysis as a result of missing data in certain variables.
Health contacts selected: dependent variables The ENSE 93 asked the respondents if they had had any medical consultation as a result of any problem, discomfort or illness in the previous 15 days (excluding hospital out-patients and emergency visits); if they had been to a dentist, prosthetist or dental hygienist for a check-up, advice or treatment of oral problems over the last 3 months; and if, over the last year, they had been hospitalised for at least one night and/or had utilised any emergency service. Health coverage is universal in Spain, but there are considerable limitations on dental services, as most dental appointments are at private surgeries (RodrõÂ guez et al., 1994).
Independent variables Following Andersen's model, three types of variables were included (see categories and codes in Tables 1, 2 and 3): (a) Predisposition to use variables, referring to personal characteristics such as age, gender, marital status, form of cohabitation, job situation and level of education. (b) Use enabling variables, such as residing in urban or rural area and ownership of private health coverage. The ENSE 93 also provides information about social status, which is calculated on the basis of each individual's job category and level of education. However, in the end this variable was not selected for analysis because 30% of the cases were incompletely coded. (c) Need for services variables: perceived health, number of types of medicine taken; number of chronic illnesses diagnosed; restriction of the main activity; restriction of leisure activity; con®nement to bed due to health problems; functional ability in the Activities of Daily Living (personal care, instrumental activities, or housework, and those that require mobility); and smoking and drinking habits.
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Table 1 People age 65 or over, total and user of health services according to selected predisposing variables. %a Variables and categories codes
Total (n = 3154)
69.8 30.2
Emergency services (1 year) (n = 462)
69.3 30.7
Hospitalisation (1 year) (n = 330)
Dentist (3 months) (n = 270)
61.3 38.7
64.8 35.2
73.7 26.3
40.0 60.0
42.2 55.8
38.7 61.3
Gender Male 1. Female 2.
41.9 58.1
37.0 63.0
Marital status Married 0. Unmarried 1.
63.9 36.1 80.4 19.6 2.9 0.5 96.6
Level of education Higher studies 1. Secondary 2. Less than primary 3.
5.0 49.5 45.5
p < 0.0001;
62.3 37.7
63.3 36.7
78.9 21.1 1.2 0.2 98.6
80.7 19.3
81.2 18.8
86.3 13.7
3.3 0.4 96.3
3.3 0.6 96.1
4.1 3.3 92.6
4.3 46.1 49.6
6.7 46.5 46.8
7.0 57.9 35.1
Hospitalisation (1 year) (n = 330)
Dentist (3 months) (n = 270)
3.0 45.3 51.7
70.5 29.5
Job situation Working 1. Unemployment 2. Inactive 3.
62.1 37.9
Form of cohabitation Not living alone 0. Living alone 1.
p < 0.05;
Medical consultations (15 days) (n = 1042)
Age 65±74 years 1. 75+years 2.
a
Users
p < 0.00001.
Table 2 People age 65 or over, total and user of health services according to selected enabling variables. %a Variables and categories codes
Total (n = 3154)
Users Medical consultations (15 days) (n = 1042)
Emergency services (1 year) (n = 462)
Town size Rural (E10,000 inhabitants) 1. Urban (>10,000 inhabitants) 2.
28.0 72.0
27.4 72.6
21.6 78.4
21.8 78.2
21.1 78.9
Private health coverage No 0. Yes 1.
91.7 8.3
93.0 7.0
89.6 10.4
91.2 8.8
89.7 10.3
a
p < 0.05;
p < 0.005.
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Need variables related to dental health (i.e., toothache) are not provided by the ENSE 93 questionnaire.
Analysis The analysis was divided into two phases. The ®rst sought to establish the existence of bivariate associations for each health contact and exclude unrelated variables. A w 2 test with a minimum con®dence level of p < 0.05 was used. Only the cases with a complete set of responses were pre-selected (91% of respondents). During the second phase we employed SPSS-X to perform a discriminant analysis, a statistical technique for classifying and allocating individuals to groups given known characteristics (Norusis, 1990). The objective was to achieve linear combinations (discriminant functions) of independent variables (also called predictors) to serve as a basis for classifying the cases into two groups: users or non-users of health services. A stepwise variable selection method was used, using Wilks' Lambda coecients, with a minimum F to enter of 3.84 and a maximum F to remove of 2.71 and a minimum tolerance level of 0.001. An indicator of the eectiveness of the discriminant function is the percent of ``grouped'' cases correctly classi®ed, total and in each group (0=non-health service users, and 1=health service users). For the purposes of prediction, unstandardised coecients are useful for calculating the score achieved by a new case in the discriminant function and thus be able to assign it to one group or another. Nevertheless, since the magnitude and the signs of the coecients are aected by the correlation between variables, unstandardised coecients are not a good indicator of their relative importance, particularly if the variables use dierent units of measurement. Then, standardised coecients are displayed, including all the variables that were combined by discriminant functions and that comply with statistical signi®cance requirements. The signs of the coecients are arbitrary and indicate whether the variables aect the function by increasing or decreasing its resultant value. In this case, high values for the discriminant functions of medical consultation, hospitalisation and emergency are associated with the use of these health services, whereas small values are associated to nonuse. On the other hand, the discriminant function obtained for dental services is of the inverse sign. In this case, the centroids are of dierent signs: negative for group 1 ``users'' and positive for group 0 ``nonusers'', suggesting an inverse relationship with the variables. In other words, a lower discriminant function
value is associated with use, whereas a higher value is associated to non-use (Table 4). This must be regarded with caution when reaching conclusions about the sign of the eect of each variable.
Results Tables 1, 2 and 3 show the population aged 65 or over that uses each of the four health services in line with the selected variables, compared to the whole sample of the same age. Sample characteristics According to the 1991 Census (Instituto Nacional de EstadõÂ stica, 1994), 13.8% of the Spanish population was aged 65 or over. This group is slightly over-represented in the general ENSE 93 sample (14.3%), over those aged between 65 and 74 (9% vs 8.2%), while the proportion of elderly people aged 75 or over is slightly lower than the real proportion (5.2% vs 5.7%). Consequently the age and sex structure in this demographic subgroup in the ENSE 93 diers from the census structure, with a greater number of young elderly people and slightly fewer women. Almost 2/3 of the respondents were married, but one out of ®ve elderly people lived in single households. Nearly half said they had not completed primary education, whereas 5% had post-secondary education and 3% were unemployed. Most lived in urban places and approximately 8% had some form of private medical insurance, as well as public health coverage, which is universal (97%) in this age group. Over 40% claimed to be in good health and had not been diagnosed with any illness. Over 70% suered no functional limitation in their daily activities. Nearly three quarters of the sample were taking some form of medicine, a third smoked, or had done so in the past, and approximately 1% drank too much. Predisposition to use variables (Table 1) 1. Age is associated statistically only with the use of emergency services and hospitalisation: population aged 75 and over was more likely to use these health services. 2. In terms of gender, older women are more likely to seek medical care. 3. To be married was associated with the use of dental services. 4. Those living alone have a greater likelihood of visiting a physician than a dentist. 5. Retired, pensioners and housewives are most likely
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Table 3 People age 65 or over, total and user of health services according to selected need variables. %a Variables and categories codes
Total (n = 3154)
Perceived health status Good and very good 1. Fair 2. Bad and very bad 3.
40.4 43.7 15.9
No. Types of medicines taken None 0. 1 medicine 1. 2±3 medicines 2. 4+ medicines 3.
27.3 36.6 29.5 6.6
Emergency services (1 year) (n = 462)
Hospitalisation (1 year) (n = 330)
25.0 51.1 23.9 10.4 35.7 42.2 11.7
40.9 35.1 15.8 8.2
Restriction leisure activity Yes 1. No 2.
20.9 79.1
Restriction of main activity Yes 1. No 2.
17.4 82.6
28.6 39.0 20.2 12.2
33.7 66.3
29.8 70.2
Being con®ned to bed Yes 1. No 2.
12.7 87.3
Smoking habit Non smoker 1. Ex-smoker 2. Non habitual (E10 cigarettes/day) 3. Moderate (11±20 cigarettes/day) 4. Heavy smoker (>20 cigarettes/day) 5.
67.2 21.4 6.8 4.0 0.6
Personal care Without any limitation 0. Limitation in 1±2 activities 1. Limitation in 3+ activities 2.
Medical consultations (15 days) (n = 1042)
Chronic illnesses diagnosed None 0. 1 illness 1. 2 illnesses 2. 3+ illnesses 3.
Drinking habit Non drinker 0. E125 cc/day 1. >125 cc/day 2.
Users
21.7 78.3
17.1 43.7 39.2
17.3 33.2 37.4 12.1
32.5 34.6 19.3 13.6
39.3 60.7
35.5 64.5
14.2 46.7 39.1
Dentist (3 months) (n = 270) 40.6 43.5 15.9
19.1 35.8 32.4 12.7
31.4 33.6 28.4 6.6
36.0 29.7 18.8 15.5
44.1 31.5 15.6 8.8
33.9 66.1
21.4 78.6
28.3 71.7
18.5 81.5
25.1 74.9
24.2 75.8
11.5 88.5
67.8 22.9 6.7 1.3 1.3
65.8 26.1 4.5 3.0 0.6
70.5 19.2 4.4 4.8 1.1
70.9 21.8 4.2 2.7 0.4
69.4 29.5 1.1
73.7 25.8 0.5
75.2 17.4 7.4
65.2 23.2 11.6
73.6 25.5 0.9
61.6 22.1 16.3
78.4 21.3 0.3
62.4 21.5 16.1
66.1 32.4 1.5
81.9 12.2 5.9 continued overleaf
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22 Table 3 continued
Variables and categories codes
Housework activities Without any limitation 0. Limitation in 1±2 activities 1. Limitation in 3+ activities 2. Activities requiring mobility Without any limitation 0. Limitation in 1±2 activities 1. Limitation in 3+ activities 2. a
p < 0.05;
p < 0.005;
Total (n = 3154)
72.3 10.7 17.0
Users Medical consultations (15 days) (n = 1042)
Emergency services (1 year) (n = 462)
Hospitalisation (1 year) (n = 330)
62.1 13.8 24.1
74.7 15.2 10.1
p < 0.0001;
65.0 19.9 15.1
59.3 14.7 26.0
57.7 22.8 19.5
55.5 15.5 29.0
Dentist (3 months) (n = 270)
79.3 4.8 15.9
59.4 18.2 22.4
80.5 12.5 7.0
p < 0.00001.
to consult a doctor, but less likely to seek dental care than employed persons. 6. Medical and dental consultations are statistically associated with educational attainment. Less than primary education is associated with medical consultations, whereas those obtain dental care regularly are more likely to have a higher level of education.
functional limitation in performing at least one of their daily activities. With signi®cant dierences, doctor's appointments are more likely among people who do not smoke or drink. Non drinkers are also more likely to be admitted to hospital. However, of all the selected need variables, the only one associated with going to the dentist is having no limitations in personal care and housework-related activities.
Enabling variables (Table 2)
Multivariate analysis
People living in towns with more than 10,000 inhabitants are more likely to use an emergency service, be admitted to the hospital or go to the dentist. Town size had no statistical relationship with medical consultations. Although a larger proportion of emergency and dental services users have private medical coverage, possession of such insurance was not statistically associated with the use of health services. Need variables (Table 3) The need variables have more signi®cant associations with the utilisation of health services. Thus the population most likely to visit a doctor, use an emergency service, or be admitted to hospital has a poorer perceived state of health. Furthermore, this group takes 2 or more types of medicine, has been diagnosed with 2 or more illnesses (or only 1 or more, in the case of medical consultations), has had their main or leisure activity restricted in some way, has been con®ned to bed by health problems, and suers some form of
Having private health coverage was not included in the discriminant analysis because it revealed no statistical signi®cance in the bivariate analysis according to universal health coverage in Spain. Table 4 shows the standardised coecients of the variables that form the canonical discriminant function for each of the health contacts analysed. The functions are considered quite ecient because they correctly classify some 70% of the cases studied: medical consultations (67%), emergencies (71%) and hospitalisation (71%). In these three types of health services the function best ®ts the non-users group, for which a larger proportion of cases was classi®ed (69%, 73% and 72%, respectively). Medical consultations is functionally related to taking a variety of types of medicine (0.62), to having a poorer perceived state of health (0.28) and to having one's main activity restricted (ÿ0.25). With lower weights, the discriminant function includes two more need variables: suering some type of the functional limitation in housework and having been con®ned to bed by health problems in the last fortnight. A predis-
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Table 4 Discriminant functions for health services utilisation. Standardised canonical discriminant function coecients Variables Age Gender Marital status Form of cohabitation Job situation Level of education
Medical consultations
Emergency services
Hospitalisation
Dentist
0.16490 ÿ0.11726
ÿ0.21258
ÿ0.43761
ÿ0.19592
0.44917 0.37827 0.50383
0.18329
0.15790
ÿ0.41768
0.27568 0.61999
0.70132
0.77368
ÿ0.25309 ÿ0.14957
ÿ0.36527
0.14203
Town size Perceived health status No. of types of medicine taken No. of chronic illnesses diagnosed Restriction of the leisure activities Restriction of the main activity Con®ned to bed by health problems Personal care limitation Housework limitation Mobility limitation Smoking habit Drinking habit
0.15070
0.22288
ÿ0.20459
0.32561
0.30122 ÿ0.18234
Number and percent of correctly classi®ed cases Users (Group 1) Cases (%) Centroid Non-users (Group 0) Cases (%) Centroid Total %
647 62.1 0.55728
291 63.0 0.79990
204 61.8 0.82374
175 64.7 ÿ0.36427
1,464 69.3 ÿ0.27484
1,951 72.5 ÿ0.13712
2,042 72.3 ÿ0.09620
1,475 51.2 0.03420
66.9
71.1
71.2
52.3
posing variable is also involvedÐunemployed elderly are more likely to visit a doctor. 62% of the users of these services would be correctly classi®ed with this discriminant equation. As for emergency services, health status (0.70) and restricted main activity (ÿ0.36) variables best discriminate between users and non-users. Another need variable, limited mobility in daily activities, had a smaller coecient. The elderly and males were more predisposed to use emergency services. The discriminant function is completed with the size of residential area variable. Emergency services are more like to be used in urban places. Nearly two thirds of those who used an emergency service were correctly classi®ed by this function.
Hospital admission is predominantly associated with a poorer perceived state of health (0.77) and with suffering some form of limitation in daily mobility-related activities (0.30). The discriminant function also contains other variables that have less explanatory power (e.g., con®nement to bed in the last fortnight, drinking less alcohol, males, and more education are more likely to be admitted to the hospital). The use of hospital services is more frequent in urban settings. This discriminant function accounted for 62% of the hospitalised elderly. Moreover, the dental service discriminant function correctly classi®es only 52% of cases. Even so, it is the function that best ®ts the users group (group 1) because it correctly classi®es 65% of user individuals.
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The set of variables that form this function have coecients of similar weight and, since the user group 1 centroid is negative, it takes on a totally dierent meaning compared with other types of health contacts. With the exception of age and marital status, all the selected predisposing and enabling variables ®t the equation, and level of education has the largest coecient (0.50). However, the only need variable that entered the equation was the presence/absence of a functional limitation in personal care activities. Consequently, the use of dental services would be a function of having a higher level of education, living in an urban environment, not living alone, being a woman, being active and not suering any personal care limitations. Discussion and conclusions Among all adults, elderly people are the major consumers of health services in Spain. According to ENSE 93 data, more than one third of the population aged 65 years and over went to see a doctor during the fortnight before the interview and, over the last year, 14% used an emergency service while 11% were admitted to hospital. 19%, 13% and 7% of the population aged between 16 and 64 years old used these services, respectively (FernaÂndez-Mayoralas et al., 1995). However, it is dicult to discern between necessary and excessive use (Hulka and Wheat, 1985). People aged 65 years and over have a more pessimistic opinion of their health than other age groups (AbellaÂn et al., 1996). Sixteen percent said they were in poor health, as compared to 7% of the general adult population. Similarly, around 60% had been diagnosed with some type of illness and 73% were taking one or more types of medicine. Although most are capable of looking after themselves and do not live in homes for the elderly, more than 25% suered some type of limitation in their daily activities, such as personal care or housework (RodrõÂ guez and FernaÂndez-Mayoralas, 1994). Our results demonstrate that use of medical and dental health services is related to dierent sets of variables. Need variables best discriminate between users and non-users, referring to the non-discretionary and related curative services such as medical consultations, emergency and hospital services. Need variables selected appear only weakly in the function found for dental services, more discretionary and often based on preventive processes. In this case, predisposing and enabling variables play the most important role. However, certain interesting dierences are observed among non-discretionary health services. For example, the variable that best explains the use of medical consultations is the number of types of medicine taken.
The perceived state of health and limitations in housework activities have lower coecients, suggesting that, at the slightest symptom, individuals would routinely visit the doctor in order to obtain a prescription (HaÈkkinen, 1991). The other variables included in the function seem to con®rm this. These patients either have had activity restrictions or have been con®ned to bed by health problems over the last fortnight. Nevertheless, the presence of the number of types of medicine in the discriminant function may reduce the signi®cance of the number of diagnosed chronic illnesses, so the former may be an indirect predictor of ``objective'' morbidity. In fact, it has been found that much of the utilisation of physician services by the elderly is for regular check-ups and monitoring of chronic conditions and not for acute problems (Pol and Thomas, 1994). The only predisposing variable in the medical consultation discriminant function involves economic activity, which appears weak because over 95% of sample users are inactive. Neither urban nor rural residence entered into the equation, suggesting relative equality of access to these ``primary'' care services throughout the country. On the other hand, the functions that discriminate between users and non-users of hospitalisation and emergency services include size of residential area as an enabling variable for urban subjects. There are fewer specialised services available in rural areas (Blazer et al., 1995). Yet the most notable dierence with regard to primary health services is the importance of perceived health status and the presence of problems limiting mobility. These users, referred by physicians to hospitals or who required immediate care, felt that they were in poorer health than those who simply visited the doctor for consultation or to obtain a prescription (HaÈkkinen, 1991). This use of specialised health services is also explained by the inclusion of certain demographic variables which, despite having smaller coecients, point to certain associations. For example, the gender variable identi®es males as users, possibly those who more prone to illness. Age, however, only appears in the discriminant function for emergency services, indicating that the elderly are more likely to suer an emergency. Educational level appears to play a statistical role in hospitalisation. Taking into account that, on the one hand, admittance to hospital is the physician's decision in the Spanish system and, on the other, that only 8% of the elderly have private health insurance, educational level could help to determine access to higher levels of health care. It is already well known that increased education is associated with early awareness of symptoms of illness. As for the use of dental services, the greatest discriminant capacity is associated with a predisposing vari-
G. FernaÂndez-Mayoralas et al. / Social Science & Medicine 50 (2000) 17±26
able, the level of education. Because education is related to social status and level of income, it may also be considered an enabling variable for use of certain services subject to limitations in public coverage. We found that people with a higher level of education are more predisposed to (or more capable of) using dental care. Also, urban residents are statistically more likely to make use of dental services. Our analysis seems to support Andersen's observation that inequity of access exists with these private health services (Andersen, 1995). The discriminant function also includes predisposing variables (e.g., form of cohabitation, gender and activity relationship) and a need variable, the presence/ absence of a functional limitation in personal care-related daily activities. Thus, dental service users tend not to live alone, work, to be female, and be absent of functional limitations. This describes a population that enjoys better social and health conditions, and makes use of preventive dental care (Hulka and Wheat, 1985). However, an analysis of the need to use dental services should include variables that speci®cally refer to dental health status, information that is not provided by the ENSE 93. Since most people do not consider oral health as a priority, particularly less auent elderly, any analysis that takes on board such variables would probably not yield a model that included them with the same power than predisposing and enabling variables (Wan and Odell, 1981). Finally, two-thirds of the ENSE 93 elderly sample did not smoke or drink, thus we are unable to statistically demonstrate the health eects of these habits or their expected in¯uence on the utilisation of services. Acknowledgements This study was partially funded by the Health Planning and Assurance Oce (Spanish Health Ministry). An earlier version was presented at the 28th International Geographical Congress in The Hague (Holland), 1996. The authors are grateful to Mr. Jose Manuel Rojo and Mrs. Laura Barrios (both MSc, Computing Centre, CSIC) for their assistance in the statistical analysis; to Dr. Anthony M. Warnes (Centre for Ageing and Rehabilitation Studies, University of Sheeld, U.K.) for a helpful review of the paper; to Dr. Lorenzo Aguilar (SmithKline Beecham Pharmaceuticals) for his critical reading; and the helpful comments of two anonymous referees. References AbellaÂn, A., FernaÂndez-Mayoralas, G., Rodrõ guez, V., Rojo,
25
F., 1996. Envejecer en EspanÄa: Manual EstadõÂ stico sobre el Envejecimiento de la PoblacioÂn. FundacioÂn Caja de Madrid, Madrid. Andersen, R.M., 1995. Revisiting the behavioural model and access to medical care: Does it matter? Journal of Health and Social Behaviour 36, 1±10. Anderson, J.G., 1973. Demographic factors aecting health services utilization: A causal model. Medical Care XI, 104±120. Blazer, D.G., Landerman, L.R., Fillenbaum, G., Horner, R., 1995. Health Services Access and Use among Older Adults in North Carolina: Urban vs. Rural Residents. American Journal of Public Health 85, 1384±1390. Bowling, A., Farquhar, M., Browne, P., 1991. Use of services in old age: data from three surveys of elderly people. Social Science and Medicine 33, 689±700. FernaÂndez-Mayoralas, G., RodrõÂ guez, V., Rojo, F., Barrios, L., 1995. La utilizacioÂn de servicios sanitarios a partir de la Encuesta Nacional de Salud de 1.993. Ministerio de Sanidad y Consumo, Madrid. HaÈkkinen, U., 1991. The production of health and the demand for health care in Finland. Social Science and Medicine 33, 225±237. Hulka, B.S., Wheat, J.R., 1985. Patterns of utilization: the patient perspective. Medical Care 23, 438±460. Instituto Nacional de EstadõÂ stica, 1994. Censo de PoblacioÂn de 1.991. Tomo II. Resultados Nacionales. CaracterõÂ sticas Generales de la PoblacioÂn. Instituto Nacional de EstadõÂ stica, Madrid. Kleinman, J.C., Gold, M., Makuc, D., 1981. Use of ambulatory medical care by the poor: another look at equity. Medical Care 9, 1011. Linden, M., Horgas, A.L., Gilberg, R., Steinhagen-Thiessen, E., 1997. Predicting health care utilization in very old. The role of physical health, mental health, attitudinal and social factors. Journal of Aging and Health 9, 3±27. Miller, R.H., 1992. Access to ambulatory care among noninstitutionalized, activity-limited persons 65 and over. Social Science and Medicine 34, 1237±1247. Newbold, K.B., Eyles, J., Birch, S., 1995. Equity in health care: methodological contributions to the analysis of hospital utilization within Canada. Social Science and Medicine 40, 1181±1192. Norusis, M.J., 1990. SPSS Advanced Statistics User's Guide. SPSS, Chicago. Padgett, D.K., Brodsky, B., 1992. Psychosocial factors in¯uencing non-urgent use of the emergency room: a review of the literature and recommendations for research and improved service delivery. Social Science and Medicine 35, 1189±1197. Padgett, D.K., Struening, E.L., Andrews, H., Pittman, J., 1995. Predictors of emergency room use by homeless adults in New York city: the in¯uence of predisposing, enabling and need factors. Social Science and Medicine 41, 547±556. Pescosolido, B.A., 1991. Illness careers and network ties: A conceptual model of utilization and compliance. In: Albrecht, G., Levy, J. (Eds.), Advances in medical sociology. CO, JAI, Greenwich, pp. 161±184. Pol, L.G., Thomas, R.K., 1994. The Demography of Health and Health Care. Plenum Press, London.
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RodrõÂ guez, V., FernaÂndez-Mayoralas, G., 1994. Disability of elderly people in Spain. In: Rey, J.C., Tilquin, C. (Eds.), Dependency, the Challenge for the Year 2000. SYSTED 94. Swiss Institute for Public Health Press, Geneva, pp. 82±89. RodrõÂ guez, V., FernaÂndez-Mayoralas, G., Pumares, P., Barrios, L., 1994. AnaÂlisis de las modalidades de cobertura sanitaria de la poblacioÂn espanÄola seguÂn la Encuesta Nacional de Salud, 1993. Ministerio de Sanidad y Consumo, Madrid.
Wan, T.T.H., Odell, B., 1981. Factors aecting the use of social and health services among the elderly. Ageing and Society 1, 95±115. Wan, T.T.H., 1989. The behavioural model of health care utilization by older people. In: Ory, M.G., Bond, K. (Eds.), Aging and Health Care. Social science and policy perspectives. Routledge, London, pp. 52±77.
www.elsevier.com/locate/socscimed
Health services accessibility among Spanish elderly Gloria FernaÂndez-Mayoralas*, Vicente RodrõÂ guez, Fermina Rojo Department of Geography, Institute of Economics and Geography, Spanish Council for Scienti®c Research (CSIC), C/ Pinar, 25, 28006 Madrid, Spain
Abstract The paper aims to identify the variables that best explain the use of health services by people aged 65 and over in Spain. The data comes from the 1993 Spanish National Health Survey (ENSE 93). The conceptual framework is the model proposed by Andersen, who suggests that utilisation is a function of predisposition to use the services, the ability to use them and of need. A bivariate and multivariate analysis (SPSS-X Discriminant Procedure) is conducted to de®ne the predictors that best discriminate users and non-users. The use of each health service is explained by a dierent set of variables. The need variables play a more important role in predicting the use of nondiscretionary services that are more closely related to healing processes (medical consultations, emergencies and hospitalisation). The predisposing and enabling variables are more relevant in explaining the use of dental services, indicating a certain degree of inequity of these discretionary services. # 1999 Elsevier Science Ltd. All rights reserved. Keywords: Elderly people; Health service utilisation; National Health Survey; Spain
Introduction Apart from dental services, considered as more discretionary (Andersen, 1995), it has been observed that the use of most health services increases with age (Anderson, 1973; Bowling et al., 1991; Hulka and Wheat, 1985; Newbold et al., 1995), is more widespread among females (Blazer et al., 1995; Bowling et al., 1991; Kleinman et al., 1981; Newbold et al., 1995), people who do not have a partner or who live alone (Bowling et al., 1991; Padgett et al., 1995), the inactive (Newbold et al., 1995) and also among people with a
* Corresponding author. Tel: +34-91-561-53-08; Fax: +3491-562-55-67. E-mail addresses: [email protected] (G. FernaÂndezMayoralas), [email protected] (V. RodrõÂ guez), f.rojo@ieg. csic.es (F. Rojo)
lower level of education (Wan and Odell, 1981) and a lower social status (Kleinman et al., 1981). The use of services also is associated with better access and availability, and this is seen mainly in urban environments (Anderson, 1973; Bowling et al., 1991) and among people who enjoy multiple health coverage (Kleinman et al., 1981; Miller, 1992; Padgett and Brodsky, 1992; RodrõÂ guez et al., 1994). Although factors in¯uencing supply and utilisation are very complicated and vary through time and space, most studies acknowledge that the predominant factor in the use of health services is need (Wan, 1989). This is an imprecise concept represented in the literature by a wealth of measurements of health status. Besides, ``need'' is related to the speci®c health system. The Spanish system provides universal coverage with limitations as regards mental, pharmacological and dental services. Access from primary to specialised (higher) health care
0277-9536/99/$ - see front matter # 1999 Elsevier Science Ltd. All rights reserved. PII: S 0 2 7 7 - 9 5 3 6 ( 9 9 ) 0 0 2 4 7 - 6
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levels is determined by ®rst level physician diagnosis. Medical (pharmacological) treatment is supported partially by the health care system, except for pensioners who obtain their medicines free upon prescription. Taking into account this type of health care system, it seems reasonable to assume that an individual's own view of his/her health aects their decision to visit a primary care provider. Health care providers will have more in¯uence on the use of specialised health services (Hulka and Wheat, 1985). One variable that may also act as a need factor is the range of medicines taken, partly because their use is determined by the physician. According to some studies, this variable depends on use of health services (HaÈkkinen, 1991; Linden et al., 1997). Another essential component of the state of elderly health relates to activities of daily living (personal care, housework and mobility) and, especially in the context of the situation, the limitations generated by health problems (reduction of the main activity or leisure activity, and being con®ned to bed) (Bowling et al., 1991). The eects on health and service use of smoking and drinking are also well known (HaÈkkinen, 1991). Therefore it seems clear that age is neither the only nor the fundamental variable for explaining the dierences in the levels of use of health services (FernaÂndez-Mayoralas et al., 1995). Thus, the main objective of this study is to identify the factors that distinguish between elderly health service users and non-users. The conceptual framework is the model proposed by Andersen that, in its 1968 version, suggested that people's use of health services is a function of their predisposition to use services, factors which enable or impede use, and their need for care (Andersen, 1995). This model has been criticised on three counts: (1) a lack of clear dierentiation between enabling and predisposing factors; (2) an emphasis on formal health care services to the neglect of informal care and social support; and (3) a conception of service use as a dichotomous event that ignores levels of care utilisation (Pescosolido, 1991). However, it is the analytical model most frequently applied in studies of the use of health services by elderly people (Wan, 1989). It is hypothesised that the model of each type of health contact will be de®ned by a dierent set of variables. The need variables will play a far more important role than the predisposing or enabling variables in predicting use, at least with regard to curative, non discretionary health services. The predisposing and enabling variables will be present in predicting the use of preventive discretionary health services, which happens to expose inequity of access (Andersen, 1995).
Material and methods Source The data have been taken from the 1993 Spanish National Health Survey (ENSE 93) with a sample of 21,058 non-institutionalised individuals aged 16 years or over. The 65+ population constituted 3475 individuals (16.5% of the respondents). Of this sub-sample, 9% were excluded from the analysis as a result of missing data in certain variables.
Health contacts selected: dependent variables The ENSE 93 asked the respondents if they had had any medical consultation as a result of any problem, discomfort or illness in the previous 15 days (excluding hospital out-patients and emergency visits); if they had been to a dentist, prosthetist or dental hygienist for a check-up, advice or treatment of oral problems over the last 3 months; and if, over the last year, they had been hospitalised for at least one night and/or had utilised any emergency service. Health coverage is universal in Spain, but there are considerable limitations on dental services, as most dental appointments are at private surgeries (RodrõÂ guez et al., 1994).
Independent variables Following Andersen's model, three types of variables were included (see categories and codes in Tables 1, 2 and 3): (a) Predisposition to use variables, referring to personal characteristics such as age, gender, marital status, form of cohabitation, job situation and level of education. (b) Use enabling variables, such as residing in urban or rural area and ownership of private health coverage. The ENSE 93 also provides information about social status, which is calculated on the basis of each individual's job category and level of education. However, in the end this variable was not selected for analysis because 30% of the cases were incompletely coded. (c) Need for services variables: perceived health, number of types of medicine taken; number of chronic illnesses diagnosed; restriction of the main activity; restriction of leisure activity; con®nement to bed due to health problems; functional ability in the Activities of Daily Living (personal care, instrumental activities, or housework, and those that require mobility); and smoking and drinking habits.
G. FernaÂndez-Mayoralas et al. / Social Science & Medicine 50 (2000) 17±26
19
Table 1 People age 65 or over, total and user of health services according to selected predisposing variables. %a Variables and categories codes
Total (n = 3154)
69.8 30.2
Emergency services (1 year) (n = 462)
69.3 30.7
Hospitalisation (1 year) (n = 330)
Dentist (3 months) (n = 270)
61.3 38.7
64.8 35.2
73.7 26.3
40.0 60.0
42.2 55.8
38.7 61.3
Gender Male 1. Female 2.
41.9 58.1
37.0 63.0
Marital status Married 0. Unmarried 1.
63.9 36.1 80.4 19.6 2.9 0.5 96.6
Level of education Higher studies 1. Secondary 2. Less than primary 3.
5.0 49.5 45.5
p < 0.0001;
62.3 37.7
63.3 36.7
78.9 21.1 1.2 0.2 98.6
80.7 19.3
81.2 18.8
86.3 13.7
3.3 0.4 96.3
3.3 0.6 96.1
4.1 3.3 92.6
4.3 46.1 49.6
6.7 46.5 46.8
7.0 57.9 35.1
Hospitalisation (1 year) (n = 330)
Dentist (3 months) (n = 270)
3.0 45.3 51.7
70.5 29.5
Job situation Working 1. Unemployment 2. Inactive 3.
62.1 37.9
Form of cohabitation Not living alone 0. Living alone 1.
p < 0.05;
Medical consultations (15 days) (n = 1042)
Age 65±74 years 1. 75+years 2.
a
Users
p < 0.00001.
Table 2 People age 65 or over, total and user of health services according to selected enabling variables. %a Variables and categories codes
Total (n = 3154)
Users Medical consultations (15 days) (n = 1042)
Emergency services (1 year) (n = 462)
Town size Rural (E10,000 inhabitants) 1. Urban (>10,000 inhabitants) 2.
28.0 72.0
27.4 72.6
21.6 78.4
21.8 78.2
21.1 78.9
Private health coverage No 0. Yes 1.
91.7 8.3
93.0 7.0
89.6 10.4
91.2 8.8
89.7 10.3
a
p < 0.05;
p < 0.005.
G. FernaÂndez-Mayoralas et al. / Social Science & Medicine 50 (2000) 17±26
20
Need variables related to dental health (i.e., toothache) are not provided by the ENSE 93 questionnaire.
Analysis The analysis was divided into two phases. The ®rst sought to establish the existence of bivariate associations for each health contact and exclude unrelated variables. A w 2 test with a minimum con®dence level of p < 0.05 was used. Only the cases with a complete set of responses were pre-selected (91% of respondents). During the second phase we employed SPSS-X to perform a discriminant analysis, a statistical technique for classifying and allocating individuals to groups given known characteristics (Norusis, 1990). The objective was to achieve linear combinations (discriminant functions) of independent variables (also called predictors) to serve as a basis for classifying the cases into two groups: users or non-users of health services. A stepwise variable selection method was used, using Wilks' Lambda coecients, with a minimum F to enter of 3.84 and a maximum F to remove of 2.71 and a minimum tolerance level of 0.001. An indicator of the eectiveness of the discriminant function is the percent of ``grouped'' cases correctly classi®ed, total and in each group (0=non-health service users, and 1=health service users). For the purposes of prediction, unstandardised coecients are useful for calculating the score achieved by a new case in the discriminant function and thus be able to assign it to one group or another. Nevertheless, since the magnitude and the signs of the coecients are aected by the correlation between variables, unstandardised coecients are not a good indicator of their relative importance, particularly if the variables use dierent units of measurement. Then, standardised coecients are displayed, including all the variables that were combined by discriminant functions and that comply with statistical signi®cance requirements. The signs of the coecients are arbitrary and indicate whether the variables aect the function by increasing or decreasing its resultant value. In this case, high values for the discriminant functions of medical consultation, hospitalisation and emergency are associated with the use of these health services, whereas small values are associated to nonuse. On the other hand, the discriminant function obtained for dental services is of the inverse sign. In this case, the centroids are of dierent signs: negative for group 1 ``users'' and positive for group 0 ``nonusers'', suggesting an inverse relationship with the variables. In other words, a lower discriminant function
value is associated with use, whereas a higher value is associated to non-use (Table 4). This must be regarded with caution when reaching conclusions about the sign of the eect of each variable.
Results Tables 1, 2 and 3 show the population aged 65 or over that uses each of the four health services in line with the selected variables, compared to the whole sample of the same age. Sample characteristics According to the 1991 Census (Instituto Nacional de EstadõÂ stica, 1994), 13.8% of the Spanish population was aged 65 or over. This group is slightly over-represented in the general ENSE 93 sample (14.3%), over those aged between 65 and 74 (9% vs 8.2%), while the proportion of elderly people aged 75 or over is slightly lower than the real proportion (5.2% vs 5.7%). Consequently the age and sex structure in this demographic subgroup in the ENSE 93 diers from the census structure, with a greater number of young elderly people and slightly fewer women. Almost 2/3 of the respondents were married, but one out of ®ve elderly people lived in single households. Nearly half said they had not completed primary education, whereas 5% had post-secondary education and 3% were unemployed. Most lived in urban places and approximately 8% had some form of private medical insurance, as well as public health coverage, which is universal (97%) in this age group. Over 40% claimed to be in good health and had not been diagnosed with any illness. Over 70% suered no functional limitation in their daily activities. Nearly three quarters of the sample were taking some form of medicine, a third smoked, or had done so in the past, and approximately 1% drank too much. Predisposition to use variables (Table 1) 1. Age is associated statistically only with the use of emergency services and hospitalisation: population aged 75 and over was more likely to use these health services. 2. In terms of gender, older women are more likely to seek medical care. 3. To be married was associated with the use of dental services. 4. Those living alone have a greater likelihood of visiting a physician than a dentist. 5. Retired, pensioners and housewives are most likely
G. FernaÂndez-Mayoralas et al. / Social Science & Medicine 50 (2000) 17±26
21
Table 3 People age 65 or over, total and user of health services according to selected need variables. %a Variables and categories codes
Total (n = 3154)
Perceived health status Good and very good 1. Fair 2. Bad and very bad 3.
40.4 43.7 15.9
No. Types of medicines taken None 0. 1 medicine 1. 2±3 medicines 2. 4+ medicines 3.
27.3 36.6 29.5 6.6
Emergency services (1 year) (n = 462)
Hospitalisation (1 year) (n = 330)
25.0 51.1 23.9 10.4 35.7 42.2 11.7
40.9 35.1 15.8 8.2
Restriction leisure activity Yes 1. No 2.
20.9 79.1
Restriction of main activity Yes 1. No 2.
17.4 82.6
28.6 39.0 20.2 12.2
33.7 66.3
29.8 70.2
Being con®ned to bed Yes 1. No 2.
12.7 87.3
Smoking habit Non smoker 1. Ex-smoker 2. Non habitual (E10 cigarettes/day) 3. Moderate (11±20 cigarettes/day) 4. Heavy smoker (>20 cigarettes/day) 5.
67.2 21.4 6.8 4.0 0.6
Personal care Without any limitation 0. Limitation in 1±2 activities 1. Limitation in 3+ activities 2.
Medical consultations (15 days) (n = 1042)
Chronic illnesses diagnosed None 0. 1 illness 1. 2 illnesses 2. 3+ illnesses 3.
Drinking habit Non drinker 0. E125 cc/day 1. >125 cc/day 2.
Users
21.7 78.3
17.1 43.7 39.2
17.3 33.2 37.4 12.1
32.5 34.6 19.3 13.6
39.3 60.7
35.5 64.5
14.2 46.7 39.1
Dentist (3 months) (n = 270) 40.6 43.5 15.9
19.1 35.8 32.4 12.7
31.4 33.6 28.4 6.6
36.0 29.7 18.8 15.5
44.1 31.5 15.6 8.8
33.9 66.1
21.4 78.6
28.3 71.7
18.5 81.5
25.1 74.9
24.2 75.8
11.5 88.5
67.8 22.9 6.7 1.3 1.3
65.8 26.1 4.5 3.0 0.6
70.5 19.2 4.4 4.8 1.1
70.9 21.8 4.2 2.7 0.4
69.4 29.5 1.1
73.7 25.8 0.5
75.2 17.4 7.4
65.2 23.2 11.6
73.6 25.5 0.9
61.6 22.1 16.3
78.4 21.3 0.3
62.4 21.5 16.1
66.1 32.4 1.5
81.9 12.2 5.9 continued overleaf
G. FernaÂndez-Mayoralas et al. / Social Science & Medicine 50 (2000) 17±26
22 Table 3 continued
Variables and categories codes
Housework activities Without any limitation 0. Limitation in 1±2 activities 1. Limitation in 3+ activities 2. Activities requiring mobility Without any limitation 0. Limitation in 1±2 activities 1. Limitation in 3+ activities 2. a
p < 0.05;
p < 0.005;
Total (n = 3154)
72.3 10.7 17.0
Users Medical consultations (15 days) (n = 1042)
Emergency services (1 year) (n = 462)
Hospitalisation (1 year) (n = 330)
62.1 13.8 24.1
74.7 15.2 10.1
p < 0.0001;
65.0 19.9 15.1
59.3 14.7 26.0
57.7 22.8 19.5
55.5 15.5 29.0
Dentist (3 months) (n = 270)
79.3 4.8 15.9
59.4 18.2 22.4
80.5 12.5 7.0
p < 0.00001.
to consult a doctor, but less likely to seek dental care than employed persons. 6. Medical and dental consultations are statistically associated with educational attainment. Less than primary education is associated with medical consultations, whereas those obtain dental care regularly are more likely to have a higher level of education.
functional limitation in performing at least one of their daily activities. With signi®cant dierences, doctor's appointments are more likely among people who do not smoke or drink. Non drinkers are also more likely to be admitted to hospital. However, of all the selected need variables, the only one associated with going to the dentist is having no limitations in personal care and housework-related activities.
Enabling variables (Table 2)
Multivariate analysis
People living in towns with more than 10,000 inhabitants are more likely to use an emergency service, be admitted to the hospital or go to the dentist. Town size had no statistical relationship with medical consultations. Although a larger proportion of emergency and dental services users have private medical coverage, possession of such insurance was not statistically associated with the use of health services. Need variables (Table 3) The need variables have more signi®cant associations with the utilisation of health services. Thus the population most likely to visit a doctor, use an emergency service, or be admitted to hospital has a poorer perceived state of health. Furthermore, this group takes 2 or more types of medicine, has been diagnosed with 2 or more illnesses (or only 1 or more, in the case of medical consultations), has had their main or leisure activity restricted in some way, has been con®ned to bed by health problems, and suers some form of
Having private health coverage was not included in the discriminant analysis because it revealed no statistical signi®cance in the bivariate analysis according to universal health coverage in Spain. Table 4 shows the standardised coecients of the variables that form the canonical discriminant function for each of the health contacts analysed. The functions are considered quite ecient because they correctly classify some 70% of the cases studied: medical consultations (67%), emergencies (71%) and hospitalisation (71%). In these three types of health services the function best ®ts the non-users group, for which a larger proportion of cases was classi®ed (69%, 73% and 72%, respectively). Medical consultations is functionally related to taking a variety of types of medicine (0.62), to having a poorer perceived state of health (0.28) and to having one's main activity restricted (ÿ0.25). With lower weights, the discriminant function includes two more need variables: suering some type of the functional limitation in housework and having been con®ned to bed by health problems in the last fortnight. A predis-
G. FernaÂndez-Mayoralas et al. / Social Science & Medicine 50 (2000) 17±26
23
Table 4 Discriminant functions for health services utilisation. Standardised canonical discriminant function coecients Variables Age Gender Marital status Form of cohabitation Job situation Level of education
Medical consultations
Emergency services
Hospitalisation
Dentist
0.16490 ÿ0.11726
ÿ0.21258
ÿ0.43761
ÿ0.19592
0.44917 0.37827 0.50383
0.18329
0.15790
ÿ0.41768
0.27568 0.61999
0.70132
0.77368
ÿ0.25309 ÿ0.14957
ÿ0.36527
0.14203
Town size Perceived health status No. of types of medicine taken No. of chronic illnesses diagnosed Restriction of the leisure activities Restriction of the main activity Con®ned to bed by health problems Personal care limitation Housework limitation Mobility limitation Smoking habit Drinking habit
0.15070
0.22288
ÿ0.20459
0.32561
0.30122 ÿ0.18234
Number and percent of correctly classi®ed cases Users (Group 1) Cases (%) Centroid Non-users (Group 0) Cases (%) Centroid Total %
647 62.1 0.55728
291 63.0 0.79990
204 61.8 0.82374
175 64.7 ÿ0.36427
1,464 69.3 ÿ0.27484
1,951 72.5 ÿ0.13712
2,042 72.3 ÿ0.09620
1,475 51.2 0.03420
66.9
71.1
71.2
52.3
posing variable is also involvedÐunemployed elderly are more likely to visit a doctor. 62% of the users of these services would be correctly classi®ed with this discriminant equation. As for emergency services, health status (0.70) and restricted main activity (ÿ0.36) variables best discriminate between users and non-users. Another need variable, limited mobility in daily activities, had a smaller coecient. The elderly and males were more predisposed to use emergency services. The discriminant function is completed with the size of residential area variable. Emergency services are more like to be used in urban places. Nearly two thirds of those who used an emergency service were correctly classi®ed by this function.
Hospital admission is predominantly associated with a poorer perceived state of health (0.77) and with suffering some form of limitation in daily mobility-related activities (0.30). The discriminant function also contains other variables that have less explanatory power (e.g., con®nement to bed in the last fortnight, drinking less alcohol, males, and more education are more likely to be admitted to the hospital). The use of hospital services is more frequent in urban settings. This discriminant function accounted for 62% of the hospitalised elderly. Moreover, the dental service discriminant function correctly classi®es only 52% of cases. Even so, it is the function that best ®ts the users group (group 1) because it correctly classi®es 65% of user individuals.
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The set of variables that form this function have coecients of similar weight and, since the user group 1 centroid is negative, it takes on a totally dierent meaning compared with other types of health contacts. With the exception of age and marital status, all the selected predisposing and enabling variables ®t the equation, and level of education has the largest coecient (0.50). However, the only need variable that entered the equation was the presence/absence of a functional limitation in personal care activities. Consequently, the use of dental services would be a function of having a higher level of education, living in an urban environment, not living alone, being a woman, being active and not suering any personal care limitations. Discussion and conclusions Among all adults, elderly people are the major consumers of health services in Spain. According to ENSE 93 data, more than one third of the population aged 65 years and over went to see a doctor during the fortnight before the interview and, over the last year, 14% used an emergency service while 11% were admitted to hospital. 19%, 13% and 7% of the population aged between 16 and 64 years old used these services, respectively (FernaÂndez-Mayoralas et al., 1995). However, it is dicult to discern between necessary and excessive use (Hulka and Wheat, 1985). People aged 65 years and over have a more pessimistic opinion of their health than other age groups (AbellaÂn et al., 1996). Sixteen percent said they were in poor health, as compared to 7% of the general adult population. Similarly, around 60% had been diagnosed with some type of illness and 73% were taking one or more types of medicine. Although most are capable of looking after themselves and do not live in homes for the elderly, more than 25% suered some type of limitation in their daily activities, such as personal care or housework (RodrõÂ guez and FernaÂndez-Mayoralas, 1994). Our results demonstrate that use of medical and dental health services is related to dierent sets of variables. Need variables best discriminate between users and non-users, referring to the non-discretionary and related curative services such as medical consultations, emergency and hospital services. Need variables selected appear only weakly in the function found for dental services, more discretionary and often based on preventive processes. In this case, predisposing and enabling variables play the most important role. However, certain interesting dierences are observed among non-discretionary health services. For example, the variable that best explains the use of medical consultations is the number of types of medicine taken.
The perceived state of health and limitations in housework activities have lower coecients, suggesting that, at the slightest symptom, individuals would routinely visit the doctor in order to obtain a prescription (HaÈkkinen, 1991). The other variables included in the function seem to con®rm this. These patients either have had activity restrictions or have been con®ned to bed by health problems over the last fortnight. Nevertheless, the presence of the number of types of medicine in the discriminant function may reduce the signi®cance of the number of diagnosed chronic illnesses, so the former may be an indirect predictor of ``objective'' morbidity. In fact, it has been found that much of the utilisation of physician services by the elderly is for regular check-ups and monitoring of chronic conditions and not for acute problems (Pol and Thomas, 1994). The only predisposing variable in the medical consultation discriminant function involves economic activity, which appears weak because over 95% of sample users are inactive. Neither urban nor rural residence entered into the equation, suggesting relative equality of access to these ``primary'' care services throughout the country. On the other hand, the functions that discriminate between users and non-users of hospitalisation and emergency services include size of residential area as an enabling variable for urban subjects. There are fewer specialised services available in rural areas (Blazer et al., 1995). Yet the most notable dierence with regard to primary health services is the importance of perceived health status and the presence of problems limiting mobility. These users, referred by physicians to hospitals or who required immediate care, felt that they were in poorer health than those who simply visited the doctor for consultation or to obtain a prescription (HaÈkkinen, 1991). This use of specialised health services is also explained by the inclusion of certain demographic variables which, despite having smaller coecients, point to certain associations. For example, the gender variable identi®es males as users, possibly those who more prone to illness. Age, however, only appears in the discriminant function for emergency services, indicating that the elderly are more likely to suer an emergency. Educational level appears to play a statistical role in hospitalisation. Taking into account that, on the one hand, admittance to hospital is the physician's decision in the Spanish system and, on the other, that only 8% of the elderly have private health insurance, educational level could help to determine access to higher levels of health care. It is already well known that increased education is associated with early awareness of symptoms of illness. As for the use of dental services, the greatest discriminant capacity is associated with a predisposing vari-
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able, the level of education. Because education is related to social status and level of income, it may also be considered an enabling variable for use of certain services subject to limitations in public coverage. We found that people with a higher level of education are more predisposed to (or more capable of) using dental care. Also, urban residents are statistically more likely to make use of dental services. Our analysis seems to support Andersen's observation that inequity of access exists with these private health services (Andersen, 1995). The discriminant function also includes predisposing variables (e.g., form of cohabitation, gender and activity relationship) and a need variable, the presence/ absence of a functional limitation in personal care-related daily activities. Thus, dental service users tend not to live alone, work, to be female, and be absent of functional limitations. This describes a population that enjoys better social and health conditions, and makes use of preventive dental care (Hulka and Wheat, 1985). However, an analysis of the need to use dental services should include variables that speci®cally refer to dental health status, information that is not provided by the ENSE 93. Since most people do not consider oral health as a priority, particularly less auent elderly, any analysis that takes on board such variables would probably not yield a model that included them with the same power than predisposing and enabling variables (Wan and Odell, 1981). Finally, two-thirds of the ENSE 93 elderly sample did not smoke or drink, thus we are unable to statistically demonstrate the health eects of these habits or their expected in¯uence on the utilisation of services. Acknowledgements This study was partially funded by the Health Planning and Assurance Oce (Spanish Health Ministry). An earlier version was presented at the 28th International Geographical Congress in The Hague (Holland), 1996. The authors are grateful to Mr. Jose Manuel Rojo and Mrs. Laura Barrios (both MSc, Computing Centre, CSIC) for their assistance in the statistical analysis; to Dr. Anthony M. Warnes (Centre for Ageing and Rehabilitation Studies, University of Sheeld, U.K.) for a helpful review of the paper; to Dr. Lorenzo Aguilar (SmithKline Beecham Pharmaceuticals) for his critical reading; and the helpful comments of two anonymous referees. References AbellaÂn, A., FernaÂndez-Mayoralas, G., Rodrõ guez, V., Rojo,
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