Estimation and Evaluation of Some Interdependencies of Environmental Conditions, Welfare Standards, Health Services, and Health Status

NOT FOR QUOTATION WITHOUT PERMISSION OF THE AUTHOR

ESTIMATION AND EVALUATION OF SOME INTER- DEPENDENCIES OF ENVIRONMENTAL CONDITIONS, WELFARE STANDARDS, HEALTH SERVICES, AND HEALTH STATUS

M. ~ojahczyk J. Krawczyk October 1981 CP-81-29

C o Z Z a b o r a t i v e P a p e r s report work which has not been performed solely at the International Institute for Applied Systems Analysis and which has received only limited review. Views or opinions expressed herein do not necessarily represent those of the Institute, its National Member Organizations, or other organi- zations supporting the work.

INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS A-2361 Laxenburg, Austria

FOREWORD

The principal aim of health care research at IIASA has been to develop a family of submodels of national health care systems for use by health service planners. The modeling work is pro- ceeding along the lines proposed in the Institute's current

Research Plan. It involves the construction of linked submodels dealing with population, disease prevalence, resource need,

resource allocation, and resource supply.

A national health care system is closely connected to the nationaleconomy and its environment. It is therefore necessary to consider the important links and interactions involved. This paper briefly summarizes research recently carried out in Poland thatanalyzessome of the interdependencies relating health status to welfare standards.

Recent publications in the Health Care Systems Task are listed at the end of this report.

Andrei Rogers Chairman

Human Settlements and Services Area

ABSTRACT

The building of complex models of socio-economic development especially on the regional level, requires the knowledge of

important relations and feedbacks between the health status of a population and the indices describing welfare standards such as environmental conditions, income level, and public services.

In developing a family of submodels of national health care systems for use by health service planners, it is important to consider the environmental impact on health status as well, since the environment forms one of the most significant external sub- systems influencing health care. Needless to say, more effort is needed in modeling the links between health care systems and the national economy.

In this paper, a set of basic health standard relationships are postulated. Through this the consequences of resource allo- cation policies can be determined, thus aiding the decision- making process. Proposed formulae are estimated on Polish

statistical data using cross-sectional analysis, and a critical evaluation of the significance of these relationships is given.

CONTENTS

1. INTRODUCTION

2. I N D I C E S D E S C R I B I N G WELFARE STANDARDS 3 . I N D I C E S O F HEALTH STATUS

4. V E R I F I C A T I O N O F THE S I G N I F I C A N C E O F THE HYPOTHESES 4.1 G e n e r a l R e m a r k s on t h e R e g r e s s i o n A n a l y s i s 4.2 V e r i f i c a t i o n R e s u l t s

5. CONCLUDING REMARKS

REFERENCES

RECENT PUBLICATIONS I N THE HEALTH CARE TASK

T h i s p a p e r was o r i g i n a l l y p r e p a r e d u n d e r t h e t i t l e " M o d e l l i n g f o r Management" f o r p r e s e n t a t i o n a t a N a t e r R e s e a r c h C e n t r e

(U.K. ) Conference on " R i v e r P o l l u t i o n C o n t r o l " , Oxford, 9 - 1 1 A s r i l , 1979.

ESTIMATION AND EVALUATION OF SOME INTER- DEPENDENCIES OF ENVIRONMENTAL CONDITIONS, WELFARE STANDARDS, HEALTH SERVICES, AND HEALTH STATUS

1. INTRODUCTION

Recent developments in industry, modifications in the welfare of populations, and changes of environmental conditions have

contributed to alterations in health status. Generally, it is rather difficult to define these transfomations, not to mention their quantification. The aim of this paper is to estimate some simple, econometric relationships that describe aspects of the health of a population as a function of the indices that charac- terize these changes. The authors believe that such an approach may contribute to a better evaluation of the present day situa- tion in the health care domain, may show the potential dangers in this sphere of activity, and finally, may induce some positive changes in trends. It is worth noting that some hypotheses about the significance of the relationships could have had more practical meaning if the statistical data had been more comprehensive at

the time of the study.

The major motivation of the study is simply to provide a regional development model (RDM) (e.g., Krug et al. 1980) with a tool that predicts the average health of the population as a function of production, consumption (including health care

s e r v i c e s ) , t h e e m i s s i o n o f p o l l u t a n t s , a n d o t h e r f a c t o r s t h a t c o r r e s p o n d t o a p a r t i c u l a r d e v e l o p m e n t s c e n a r i o . Thus t h e method i s b a s e d o n a model t h a t h a s as i n p u t v a r i a b l e s t h e q u a n t i t i e s g e n e r a t e d by t h e RDM t h a t i n some a g g r e g a t e s e n s e d e s c r i b e c o n d i t i o n s o f l i f e i n a r e g i o n . Development m o d e l s ( e . g . ,

Krug e t a l . 1980) u s u a l l y o p e r a t e w i t h some a g g r e g a t e v a r i a b l e s . However, i n t u i t i v e m o d e l s r e l a t i n g t h e h e a l t h s t a t u s t o t h e e n v i r o n m e n t a r e b a s e d o n d e t a i l e d m e a s u r e s o f t h e c o n c e n t r a t i o n o f p o l l u t a n t s ( e . g . , SO2

[q] ^,

t h e w e i g h t o f s u l p h u r d i o x i d e [SO2]

p e r cubic meter o f a i r ) t h a t d i r e c t l y a f f e c t t h e human o r g a n i s m . m

Thus t h e v a r i a b l e s d e s c r i b i n g t h e e n v i r o n m e n t e n v i s a g e d by WM a n d t h e i n t u i t i v e model d o n o t c o r r e s p o n d e x a c t l y w i t h o n e a n o t h e r . T h i s c a n b e overcome by

a ) b u i l d i n g a s i m p l e a n d e f f i c i e n t model d e s c r i b i n g t h e d i f f u s i o n o f p o l l u t a n t s

b ) b u i l d i n g a model t h a t e v a l u a t e s h e a l t h s t a t u s , b a s e d o n p o l l u t i o n c o n c e n t r a t i o n d a t a

U n f o r t u n a t e l y , n o n e o f t h e l i n k s i n t h e h y p o t h e t i c a l c h a i n shown i n F i g u r e 1 c a n b e made i n P o l a n d a t p r e s e n t . T h i s i s b e c a u s e t h e e x i s t i n g d i f f u s i o n m o d e l s a r e h i g h l y complex a n d s t i l l n e e d more d i s a g g r e g a t e d i n p u t d a t a t h a n t h e RDM c a n p r o v i d e ( P u d y k i e w i c z 1 9 8 0 ) . F u r t h e r m o r e , t h e d a t a a v a i l a b l e t o t h e a u t h o r s d e s c r i b i n g p o l l u t i o n c o n c e n t r a t i o n a r e c o l l e c t e d o n l y i n c e r t a i n g e o g r a p h i c a l l o c a t i o n s a n d n o t i n a l l areas

(see Borkowska 1979, a n d A t m o s p h e r i c P o l l u t i o n Yearbook 1 9 7 4 ) . T h e s e d a t a i n c l u d e two g r o u p s o f p o l l u t i o n : water ( b i o l o g i c a l oxygen demand a n d c o n t a m i n a t i o n by f e c e s ) a n d a i r (SO2 c o n c e n - t r a t i o n , d u s t c o n c e n t r a t i o n a n d d u s t f a l l ) . They c o u l d n o t b e u s e d i n o u r s t u d y , however, b e c a u s e t h e y were n o t c o m p r e h e n s i v e enough. Hence, t h e a s s i g n m e n t o f a v e r a g e h e a l t h i n d i c e s [ s e e Yearbook o f H e a l t h Care i n P o l a n d i n 1978 ( 1 9 7 9 ) l t o s u c h

e n v i r o n m e n t a l d a t a i s a l m o s t i m p o s s i b l e . T a k i n g t h e a b o v e i n t o a c c o u n t , t h e a u t h o r s d e c i d e d t o i n v e s t i g a t e t h e s i g n i f i c a n c e o f h y p o t h e s e s c o n c e r n i n g t h e i m p a c t o f e m i s s i o n a g g r e g a t e d a t a o n t h e h e a l t h o f a p o p u l a t i o n s i n c e t h e m o d e l s o b t a i n e d c a n be

used as tools only if the hypotheses have been tested.* The place of the proposed model and its connection with the RDM is shown in Figure 1.

However, it has to be emphasized that the structure proposed, which is based on emission data, obviously has drawbacks, because

it does not take into account the effects of pollutants imported from outside the region.** Thus the approach presented is a compromise between the availability of statistical data and what is ideally required. Its practical outputs should be viewed, therefore, as an examination of the broad impact of development scenarios on a population's health status and the relative degree of influence the various pollutants have on health.

Taking into account the above-mentioned compromise, Bojaiiczyk and Krawczyk (1 980) set forth a number of indices

describing standards of life by means of emission data (considered the explanatory variables) and indices of the health status

(explained variables). The hypotheses were then tested for their significance through a multiple regression analysis. The relationships were obtained, by a cross-sectional analysis, using statistical data provided by 49 Polish voivodships

(administrative areas) for the year 1978.

In this paper, only those groups of indices are presented for which the respective relations proved to be statistically significant in ~ojaiiczyk and Krawczyk (1980). The complete set of indices is broader, containing more measures of welfare

standards.

It should be borne in mind that according to the standard rules of regression analysis, the hypothesis concerning the significance of a relationship is accepted only when the null hypothesis is statistically rejected. The conclusions obtained by this method, which is based on a cross-sectional analysis,

*A similar approach was presented in North and Merkhofer (1975) and Buehring et al. (1976).

**Unfortunately in some regions, imported pollutants contribute to 30% of the total pollution (measured in terms of concentra- tion) (Juda 1980).

do not consider the dynamics of the processes under consideration.

Thus their use in prediction is restricted to systems that are not supposed to change very much--at least in the short run

(say, 2-4 years)

.

2. INDICES DESCRIBING WELFARE STANDARDS

According to the analysis carried out in Bojaficzyk and Krawczyk (1980), the description of welfare standards is given by a series of indices of natural units.*

The first are indices describing the natural environment quality

x

-

various gas emissions in tons per hectar 1

x2

-

water purification coefficient (amount of non- purified industrial wastes and municipal sewage related to water consumption in tons per ton)

+

x3

-

population density (number of inhabitants per kmL --a measure of social environment)

The choice of these indices assumes an obvious correlation between the emission and concentration of pollutants as well as the somewhat unreliable functioning of the water purification system.

The second is an index describing the welfare standard x 4

-

energy consumption in kilowatt hours per person This characterizes the level of wellbeing which is at present more important and significant in Poland, rather than the income

level.

**

*Some other methods of describing welfare standards are considered in the publications of Hellwig, 1968; e.g., a certain kind of multi-criteria1 approach aimed at comparisons of different regions or systems.

**Some measures of income have been considered in Bojaficzyk and Krawczyk (1980), but have been omitted in the further analysis due to the fairly weak explanatory features.

The t h i r d a r e i n d i c e s d e s c r i b i n g t h e h e a l t h c a r e s e r v i c e s l e v e l

x - number of p h y s i c i a n s p e r l o 4 p o p u l a t i o n 5

x 6 - number of b e d s i n g e n e r a l h o s p i t a l s p e r l o 4 p o p u l a t i o n The chosen i n d i c e s d e s c r i b e t h e a c c e s s i b i l i t y t o h e a l t h c a r e ser- v i c e s . Hence, t h e y a l s o d e s c r i b e t h e l e v e l s of t h e s e r v i c e s i n each a r e a .

The a u t h o r s a r e convinced t h a t t h e above s e r i e s of i n d i c e s do n o t e x h a u s t t h e s u b j e c t o f w e l f a r e s t a n d a r d s . I t i s p o s s i b l e t o make e a c h g r o u p r i c h e r o r t o add new o n e s . K o s t r z e w s k i e t a l . ( 1 9 7 3 ) , among o t h e r s , have worked on t h i s t o p i c . However, t h e a u t h o r s f e e l t h a t e s t i m a t i o n and e v a l u a t i o n o f t h e r e l a t i o n - s h i p s d e s c r i b i n g t h e i m p a c t o f t h e s e i n d i c e s on h e a l t h s t a t u s

may become a u s e f u l and i n t e r e s t i n g t o o l f o r p l a n n e r s and d e c i s i o n makers.

INDICES OF HEALTH STATUS

I n t h i s p a p e r , a s i n Bojaficzyk and Krawczyk ( 1 9 8 0 ) , t h e h e a l t h s t a t u s o f t h e s o c i e t y i s d e s c r i b e d by a s e t o f i n d i c e s

( i n n a t u r a l u n i t s ) t h a t c h a r a c t e r i z e t o some e x t e n t , t h e two s t a t e s of "bad h e a l t h " : d i s e a s e and d e a t h . Thus t h e two phenomena, m o r b i d i t y and m o r t a l i t y , have been c o n s i d e r e d . M o r b i d i t y and m o r t a l i t y f i g u r e s a r e t h o s e most o f t e n m e t i n World H e a l t h O r g a n i z a t i o n p u b l i c a t i o n s : e . g . , O f f i c i a l Record WHO (1973)

,

and o t h e r s s u c h a s Kostrzewski e t a l . ( 1 973) and S h i g a n ( 1 9 7 8 ) . These p a p e r s g i v e c o m p a r a t i v e s t u d i e s o f t h e h e a l t h s t a t u s f o r d i f f e r e n t c o u n t r i e s .

A n a t u r a l and b r o a d l y a p p l i e d method o f t a c k l i n g t h e h e a l t h s t a t u s problem i s by a n a l y z i n g t h e d a t a o f d i s e a s e f r e q u e n c y , d i s e a s e s t a g e ( e a r l i e r , advanced, o r t e r m i n a l ) and d e a t h r a t e s . U n f o r t u n a t e l y , i n f o r m a t i o n on m o r b i d i t y (new c a s e s o f d i s e a s e i n a t i m e u n i t a d o p t e d f o r a n a n a l y s i s ) and p r e v a l e n c e ( a l l c a s e s of d i s e a s e ) a r e q u i t e i n s u f f i c i e n t .

Basically, the routine statistical data in Poland consist of registered patient cases only, which is a rather typical situation for most countries. The data for latent patients (ill persons unaware of being ill) and unregistered patients (ill persons aware of being ill but staying away from health care services) are unavailable. However, it is possible to calculate morbidity, mortality, and prevalence rates using programs elaborated at the International Institute for Applied Systems Analysis in Laxenburg, Austria (see Shigan 1978;

Fujimasa et al. 1978; Kitsul 1980; Klementiev 1977). Unfortu- nately, some of these programs require, as a prerequisite, very expensive screening analyses for the representative subpopula- tions. This drawback cannot be overemphasized, since it limits the applicability of such modeling procedures.

Finally, the statistical data give the number of health services rather than the demand for health services, which would better characterize the health status of the society (Shigan

1978). (That is, they describe the realized demand, which is usually equal to the supply level.)

In this paper, three groups of indices have been proposed.

The data are taken from routine statistical yearbooks [Yearbook of Health Care in Poland in 1978 (1979) and Yearbook of Voivod- ships in 1978 (1979)1, which implies the acceptance of their well-known limitations:

a) indices describing the process of health care services delivery (treated as some measures of morbidity*)

y1

-

number of consultations with physicians (or dentists) per inhabitant

y2

-

number of patients in general hospitals per 10 ⁴ population**

*The indices of both a) and b) describe the approximate size of population afflicted with a disease.

**It would be more interesting to disaggregate this number according to disease group specification in c), but the data are not available.

b) morbidity indices

-

morbidity (new cases) in chosen disease groups per 1

o5

population* :

y j

-

^influenza

c) mortality indices

-

number of deaths per 10 population 5 caused by diseases from the following disease groups:**

y4

-

^cancer

y5

-

cardiovascular diseases y6

-

respiratory diseases

4. VERIFICATION OF THE SIGNIFICANCE OF THE HYPOTHESES 4.1 General Remarks on the Regression Analysis

The set of programs for multiple regression analysis developed in the Systems Research Institute (Identification Programs for Mathematical Models 1977) has been used to test the significance of postulated linear relationships (linear

type y = ax

+

e) between the welfare standards and health status indices. The indices describing welfare standards x = [xl.

...

^x61

may be grouped in three classes:

(1) x ~ ~ - xdescribes the quality of the environment ~ ~ x ~ ( 2 ) x4

-

denotes the level of welfare

( 3 ) X51X6

-

measures the supply of health services

The index describing the health status is y = [y 1...y6]

For a given type of regression model (linear or nonlinear), the above-mentioned package calculates and performs

-

regression coefficients (matrix)

-

regression model significance tests

-

regression coefficients significance tests

*Data for morbidity rates for disease groups given in c) is required.

**The postulated impact of the natural environment quality on morbidity was the main motivation of this choice.

The run begins with the full model (including all the input variables) and eliminates automatically non-significant

coefficients until the final version of the model is obtained.

This version has all the coefficients significant and/or minimal residual variance.

Note that once a regression model has been obtained, it must be analyzed carefully. A regression analysis is a useful

tool in the early stage of determining the probability (postulated) relationships between inputs and outputs. However, one should

not use it as a decisive criterion for the evaluation of cause- and-effect relationships.

4.2 Verification Results

The package of programs and procedures described in section 4.1 has been used to analyze the regression relationships between the index of health status (y) and indices of welfare standards

(x). In the sequence proposed in section 3, the final forms of linear regression models are now given.

The models obtained are characterized by three parameters that define the significance of the regression relationships

(F)

-

value of standard F-Snedecor test (at 0.05 signi- ficance level)

(a)

-

estimator of the square root of residual variance

( p )

-

multidimensional correlation coefficient

In Figure 2 and the remaining figures in this section, the average values of input and output variables have been denoted with broken lines. In several cases, the essentially multidimensional models have been obtained, i.e., more than one

input variable is significant. In such cases, it is necessary

to project the received regression hyperplane on the two-dimensional plane (parametrically dependent on average values of other

u 4J -4 E:

0 - 4

h k A an

a k

aJ rn

U S a J 0 0 4 J

E:

k W aJ a o r n

.n aJ

E a J k g m a , E: 3

4 m a J u E A a J 4

cra

-

LI ^tn '44 4

0 .d

cr) a

aJ aJ

u u a r

G -4 A a J a u

rn r:

c . 4 E:

aJ -4

a r:

a r o m

a .d 3 4J d 3 d

4 d 4 G d + ' 0 0 0 -4 a, cr

input variables). Therefore, these figures are for illustrative purposes only.*

The first regression model that will be presented here is the one referring to the number of consultations given by

physicians (and dentists) per inhabitant (see Figure 2):

where Fcrit has been calculated for N=49 with the number of degrees of freedom corresponding to the type of model.

Observe that the medical consultation rate (treated as a certain measure of morbidity, see section 3) depends on the environment quality, i.e., on gas emissions (x ) and on the

1 amount of non-purif ied water (x2)

.

The second regression model refers to the number of patients in general hospitals per l o 4 population (Figure 3) :

where the number of observations equals 49.

The results of the analysis show that the number of

patients is explained by the number of physicians per catchment population. They confirm the general opinion that the number

*In the figures, Warsaw is the biggest urbanized area with a relatively high welfare standard and health services level, and Katowice is the heavy industrialized region with probably the poorest environmental standard.

no.of hospitalized patients

10 pop. 4

I

I I I

I no.of physicians

I

! 10 pop.

I

Figure 3. Regressional dependence between the hospitalized patients and the number of physicians.

of physicians is far from the satisfactory saturation level*.

It seems that at present and in the near future, every increase in the number of physicians enables the admission of more

patients (and therefore decreases the number of patients on waiting lists). In the health care systems of centrally

planned economies such as Poland, there is usually a connection between the increase in the number of physicians and the increase in the number of beds, a phenomenon referred to as a standard

or norm ratio. The concept of standards (or norms) is fundamental in the planning practice of ministry and regional administrative bodies.

The third model gives the number of people suffering from influenza (y3) (new cases) per 1

o5

population (Figure 4) :

Thus the morbidity rate for influenza depends on:

--

population density with a positive coefficient (the higher the population density, the closer the inter- personal contacts that influence the morbidity rate of infectious diseases)

--

the number of physicians per catchment population also with a positive coefficient

The latter result can by no means by unexpected whereas at present, the number of physicians per

lo4

population is fairly low [15.0 in Poland, 19.4 in FRG, 23.1 in Hungary, see Yearbook of Health Care in Poland in 1978 (1979)l. An increase

in the number of physicians would, of course, result in better health diagnoses and better detection of illnesses. As soon

*The saturation level is itself a controversial concept (Shigan 1980; Silver 1972).

I

no.of influenza cases

7 * ,-

I

X

+

^Warsaw

no.of phys.

= 1 4 . 5 10 4 pop.

population density

Figure 4. Regressional dependence between the number of new influenza cases and the population density.

a s t h e demand l e v e l i s r e a c h e d , a f u r t h e r i n c r e a s e i n t h e number o f p h y s i c i a n s would improve t h e s t a n d a r d o f h e a l t h s e r v i c e s and l o w e r t h e m o r b i d i t y l e v e l .

The f o u r t h r e g r e s s i o n model m e a s u r e s t h e number o f d e a t h s c a u s e d by c a n c e r ( y 4 ) p e r 10 p o p u l a t i o n * ( F i g u r e 5 ) 5

From t h e f o u r t h r e g r e s s i o n model ( F i g u r e 5 1 , it c a n b e s e e n t h a t t h e d e a t h r a t e f o r c a n c e r d i s e a s e d e p e n d s on:

--

w a t e r p u r i f i c a t i o n e f f i c i e n c y , p o p u l a t i o n d e n s i t y , and e n e r g y c o n s u m p t i o n w i t h p o s i t i v e c o e f f i c i e n t s .

( T h e s e q u a n t i t i e s i n f l u e n c e t h e m o r b i d i t y l e v e l . )

--

number o f b e d s w i t h a n e g a t i v e c o e f f i c i e n t . ( I t i s n e c e s s a r y t o e n l a r g e f a c i l i t i e s o f i n - p a t i e n t h e a l t h s e r v i c e t o improve t h e c o n d i t i a n s o f t h e r a p y . )

The f i f t h model d e s c r i b e s t h e number o f d e a t h s c a u s e d b y c a r d i o v a s c u l a r d i s e a s e s ( y 5 ) p e r 1 0 p o p u l a t i o n ( F i g u r e 6 ) 5 :

*Here, it would b e m e t h o d o l o g i c a l l y more j u s t i f i e d t o t a k e t h e e m i s s i o n d a t a o f p o l l u k a n t s from t h e p a s t ( l e t u s s a y 5-8 y e a r s e a r l i e r ) b e c a u s e t h e d i s e a s e p r o c e s s h a s i t s own dynamics.

However, t h e s e d a t a w e r e n o t a t o u r d i s p o s a l , a n d t h e r e g i o n a l s h a r e s o f p o l l u t i o n i n t h e t o t a l p o l l u t a n t e m i s s i o n d o n o t v a r y much w i t h i n t h i s t i m e i n t e r v a l .

a

a, m c , U a , + E : m a

u a m

5 0 0

c m z a, -4

a 5 '4-4 a, 0

5 k

a h

d d c ,

a 3.4 E: U d 0 m - 4

-4 a Q m 3.4 m o m

a, -4 m k 5 a, D k U

a , a u t z u a

In this model as in the fourth model, the mortality rate for cardiovascular diseases depends on:

--

population density with a positive coefficient (impact on morbidity for "civilization disease")

--

number of beds with a negative coefficient (see explana- tion for the fourth model)

The sixth model gives the number of deaths caused by respiratory diseases per 10' population (Figure 7) :

The last model shows a regressional dependence of the mortality rate for respiratory diseases on the number of

available beds with a negative coefficient. It is very similar to the fourth and fifth models.

5. CONCLUDING REMARKS

The conclusions resulting from the above testing of the hypotheses is summarized here:

--

In three models, a relatively significant dependence

of outputs (indices y) to the number of beds in hospitals has been manifested, especially mortality indices

(from group c in section 3). This suggests that an improvement of hospital conditions could effectively contribute to the amelioration of the health status in Poland.

--

The water purification process may have been responsible for some mortality.

no-of deaths caused by respiratory diseases 10 5 POP*

X X

I

Figure 7. 'Regressional dependence between the number o f deaths caused by respira- tory diseases to the accessibility of hospitals.

--

An a p p a r e n t l y u n e x p e c t e d l a c k o f d e p e n d e n c e b e t w e e n t h e p r o p o s e d i n d i c e s d e s c r i b i n g t h e n a t u r a l e n v i r o n m e n t and some m o r b i d i t y m e a s u r e s h a s b e e n n o t i c e d (see more d e t a i l e d a n a l y s i s i n ~ o j a f i c z y k a n d Krawczyk ( 1 9 8 0 ) . A c c o r d i n g t o t h e a u t h o r s , t h i s i s b e c a u s e : a ) t h e

i n d i c e s p r o p o s e d d e s c r i b i n g t h e e m i s s i o n o f p o l l u t a n t s a r e i n f a c t a n i n s u f f i c i e n t m e a s u r e o f t h e d e t e r i o r a t i o n o f t h e e n v i r o n m e n t (see Lave and F r e e b u r g 1 9 7 3 , Werk

1977 a n d N o r t h a n d M e r k h o f e r 1 9 7 5 ) ; b ) a n a v e r a g e l e v e l o f t h e e n v i r o n m e n t p o l l u t i o n w i t h r e s p e c t t o t h e w h o l e c o u n t r y h a s n o t r e a c h e d t h e c r i t i c a l p o i n t .

--

An a p p a r e n t l y u n e x p e c t e d i n c r e a s e i n t h e g i v e n m o r b i d i t y m e a s u r e ( t h e number o f h o s p i t a l v i s i t s , e t c . ) ( g r o u p

a i n s e c t i o n 3 ) w i t h a n i n c r e a s e i n t h e number o f p h y s i c i a n s h a s p o i n t e d t o t h e n o n s a t u r a t i o n demand s i t u a t i o n f o r h e a l t h c a r e , w h i c h s u p p o r t s t h e w i d e l y a c c e p t e d o p i n i o n o f t h e demand f o r h e a l t h care s e e m i n g t o b e i n s a t i a b l e ( S h i g a n 1978; K o s t r z e w s k i 1 9 7 3 )

.

I t s h o u l d a l s o b e b o r n e i n mind t h a t t h i s s t u d y h a s b e e n r e t r o s p e c t i v e , i . e . , t h e i n f o r m a t i o n a b o u t t h e w e l f a r e s t a n d a r d s d e f i n e d i n s e c t i o n 2 w a s n o t e s p e c i a l l y a d a p t e d t o t h e h e a l t h s t a t u s i n d i c e s ( s e c t i o n 3 ) - - n o r w a s t h e r e v e r s e done.* Both g r o u p s of i n d i c e s h a v e b e e n r e c e i v e d from r o u t i n e s t a t i s t i c a l p u b l i c a t i o n s [Yearbook o f H e a l t h C a r e i n P o l a n d i n 1978 (1 9 7 9 )

,

a n d Yearbook o f V o i v o d s h i p s i n 1978 ( 1 9 7 9 ) J . I n t h e f u t u r e a p r o s p e c t i v e s t u d y s h o u l d b e made. Werk ( 1 9 7 7 ) a n d Lave and F r e e b u r g ( 1 9 7 3 ) p r e s e n t p o s s i b l e u s e o f some p r o s p e c t i v e m e t h o d s w h e r e t h e s e t s o f i n p u t a n d o u t p u t v a r i a b l e s a r e l e s s numerous, b u t t h e s t a t i s t i c a l d a t a a r e v e r y r i c h a n d e s p e c i a l l y c h o s e n . However, t h i s k i n d o f a p p r o a c h r e q u i r e s s u b s t a n t i a l l y l a r g e r e x p e n d i t u r e s .

*Some s u b p o p u l a t i o n s c o u l d b e c h o s e n a n d a n a l y z e d , e . g . , t h e g r o u p s e x p o s e d t o w e l l - d e f i n e d e n v i r o n m e n t a l h a z a r d s .

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