Modelling of industrial ecological systems for evaluation of health services

Ecological Modelling, 31 (1986) 329-339

329

Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands

MODELLING OF INDUSTRIAL ECOLOGICAL SYSTEMS FOR EVALUATION OF HEALTH SERVICES

HISASHI O G A W A 1, KIICHIRO SATO 2, NOBUO JO 3, KAGEYU NORO i and KENZABURO TSUCHIYA a

i School of Medicine, University of Occupational and Environmental Health, Yahata, Nishi-ku, Kitakyushu 807 (Japan) 2 Department of Medical Administration and Statistics, Japan Medical Association, 2-5 Kanda Surugadai, Chiyoda-ku, Tokyo (Japan) 3Japan Institute of Synthetic Technology, Inc., Tokyo (Japan)

ABSTRACT Ogawa, H., Sato, K., Jo, N., Noro, K. and Tsuchiya, K., 1986. Modelling of industrial ecological systems for evaluation of health services. Ecol. Modelling, 31: 329-339. A macroscopic industrial ecological model has been developed to investigate the effects of changes in industrial structure on social well-being in general and health services in particular. The model is composed of various measures of industrial and employment structures, social and economic stocks, and environmental and pollution indicators as well as the health service sector. The model description is based on the system dynamics of these components. The simulation model was calibrated using available data of the past 60 years for the above setting in Japan. The simulation studies indicated that the gradual shift, in the industrial structure of Japan, from agriculture, light manufacture and heavy industry in the past to more emphasis on commercial and service industry in recent and coming years, would improve the level of living standards in Japan resulting in enhanced health service capability and lower death rate but with in.creasing adult disease rates and decreasing environmental capacity to absorb pollution in the year of 2000.

INTRODUCTION

Industrial ecological systems The study of industrial ecological systems at the University of Occupational and Environmental Health, Japan, originated in the idea that the structural and functional changes in an industrial society would have a strong influence on the development and maintenance of the health of its people. Although this idea had long been recognised, no serious effort has been made to analyze the relationship between the changes in an industrial 0304-3800/86/$03.50

© 1986 Elsevier Science Publishers B.V.

330

society and the state of health of the people from a system analytic point of view. The structure and inner-working of an industrial society resemble those of a natural ecosystem. The concepts in ecology such as habitat, succession, trophic level, limiting factors and community metabolism can also apply to the study of the ecology of an industrial society. For instance, an industry in a society may grow or decline as a consequence of dynamic changes in exogenous limiting resources and in the hierarchical and/or metabolic structure of that society. When studying the ecology of an industrial society (henceforth termed 'industrial ecology'), these concepts and methodologies employed in ecosystems analyses are useful. Industrial ecology has been a research subject also at the Japan Industrial Policy Research Institute since 1971. Their definition of industrial ecology is research for the prospect of dynamic harmonization between human activities and nature by a systems approach based upon ecology (JIPRI, 1983). The conceptual basis for this definition is the same as our definition of industrial ecology. However, the aim of the research on industrial ecological systems is different. While their study aims at the promotion of the development of industries which have dynamic harmonization with nature, our research has laid more emphasis on the promotion of the development and maintenance of health status in an industrial society. The health of individuals in a society is developed and maintained not only by physical and mental medical care services, but also through smooth interactions with their surroundings, including social, economic and natural environments. Therefore, to evaluate the health services for any society, the ecology of the society as a whole must be studied.

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Fig. 1. Relationship between industrial ecological system and health (after Tsuchiya, 1982).

331

The relationship between the industrial ecological system and health is presented in Fig. 1. Industries are roughly divided into three categories. They are interrelated and they have complex industrial structures consisting of the vertical system (parent companies, subsidiaries, etc.), the horizontal system (flow of materials and products, etc.), the geographical distribution, time distribution (from mining of mineral resources, manufacturing, consumption and recycling, etc.) and the population structure (age, sex, whitecollar and blue-collar workers, etc.). Workers' educational levels, sex, age, values, etc., are closely associated with the characteristics of the industry. In this connection, the workers' knowledge, skills, wealth and their physical and mental states of health, etc., act as social selections. This social selection, in turn, affects health conditions. Industry is affected by the economic and natural environments of society as a whole and this, in turn, will affect health directly or indirectly.

Modelling approach The analysis of the industrial ecological system for its health implications is a formidable task because: (a) the recognition of health is at the personal level whereas the industrial ecological system can hardly be studied at the individual level; and (b) the industrial ecological system encompasses a broad range of scientific disciplines. To alleviate the first problem mentioned above, a two-layer modelling approach was considered. The model structure is composed of an upper-layer and a lower-layer model. The upper-layer model has a macroscopic view of the industrial ecological system without detailed description and is divided into several sections. At the lower layer, each model corresponding to each section in the upper-layer model is more fully developed and described in detail. The resolution of the second problem requires a multidisciplinary team effort to attack the modelling research. The current team is composed of medical, social, economic, environmental and systems scientists and engineers. Having knowledge and experience in the lower-layer model section, each researcher contributes to the formulation of the upper-layer macroscopic model. This macroscopic model then becomes the common denominator or language of the team. MACROSCOPIC M O D E L

A diagrammatic representation of the macroscopic industrial ecological system model is depicted in Fig. 2. The model is composed of seven major sections: industry, population, labor force, living state, environment and

332 TABLE 1 Macroscopic industrial ecological system variables Variable Industry Agricultural production index Manufactural production index Net primary industrial product Net secondary industrial product Net tertiary industrial product Net national product Gross national product Per capita gross national product Population Total population Productive age population Birth rate Death rate Labor force Labor population Agricultural labor population Manufactural labor population Tertiary industrial labor population Agricultural employment fraction Manufactural employment fraction Tertiary industrial employment fraction Employment rate Living state Urban population ratio Engel coefficient Water supply coverage Female employment ratio Female college student ratio Period between the first and the last child births Environment and pollution Pollution control capitals Air pollution (sulfur dioxide) in major cities Pollution complaint cases Pollution induced patients General health National medical expense Per capita national medical expense Number of hospital beds Number of physicians Ratio of injury and disease Medical treatment recipients ratio Tuberculosis death rate Pneumonia gastrointestinal death rate Adult disease treatment recipients ratio

Unit

Symbol

-

XA

-

XM

109 yens 109 yens 109 yens 109 yens 109yens 104 yens

Y1 Y2 Y3 NP GP NI

103 persons 103 persons year- 1 year- 1

PT PP BR DR

103 103 103 103 (%) (%) (%) (%)

LP AL ML TL AR MR TR LR

persons persons persons persons

(%) (%) (%) (%) (%)

UP EG WA LF SF

year

PB

108 yen ppm number of cases number of persons

PC AP CP PP

109 yens 103 yens 105 beds per 105 persons per 103 persons persons per 105 persons persons per 105 persons persons per 105 persons persons per 105 persons

NE PE BD PN ID MT TB PG AD

333 TABLE 1

(continued)

Variable

Unit

Symbol

Occupational health Periodical health examination participants Occuputional injury and disease occurrence Occupational accident deaths

103 persons n u m b e r of cases n u m b e r of persons

HE OA OD

TABLE 2 Regression equations used in macroscopic industrial ecological system model Industry In Y1 = - 1 3 . 9 + 4 . 9 5 In X A In Y2 = 3.15 + 1.59 In X M In Y3 = 0.798 + 0.959 In Y2 In G P = 0.142+ 1.01 In N P Population BR = 33.5 - 0 . 0 4 7 0 NI (before 1955) BR 12.4+ 3.43 PB (after 1955) In D R = 0.0543 +0.443 l n ( T B + PG) (before 1960) In D R = 0.930 + 0.239 ln(TB + PG) (after 1960) Labor force A R = 15.8 + 3.51 ( X A / X M ) M R = 16.9 + 9.45 ( X M / X A ) LR = 8 5 . 5 - 2 . 1 1 l n ( - 1 8 . 6 + 1.66 NI) (before 1950) LR = 8 3 . 2 - 2.11 ln(37.3 + 5.11 NI) (after 1950) Living state In E G = 3.71 - 0 . 0 0 5 2 5 N I U P = - 72.5 + 5.78 M R In W A = 0.797 + 0.0473 U P LF 18.3 + 0.944 exp (3.28 + 0.160 In NI) In PB = 2 . 5 1 - 0 . 1 1 7 In L F SF = 0.935 + 0.479 In NI E n v i r o n m e n t and pollution In C P = 2.92 + 1.79 In X M In PP = - 5 9 . 6 - 1 . 8 8 In X M + 6.61 In G P In A P = - 2 . 2 2 - 0.290 In PC General health In ID = 1.46 + 0.731 in NI M T = 2220 + 48.1 ID In PG = 4 . 3 9 - 0 . 1 8 8 In PE in TB = 4 . 2 1 - 0 . 5 1 5 In PE P N = 180/(1.99 - 0.12 [ N E / G P ] ) In BD = 3.72 + 0.255 I n [ N E / G P ] + 0.682 In MT Occupational health In OA = 7.86 + 0.553 In X M (1966 to 1970) In O A = 14.3 - 0.866 In X M (after 1970) H E = - 3 1 2 0 0 + 0 . 8 1 1 LP In O D = - 1.42 + 0.436 In O A + 0.711 In H E - 0.336 In PE =

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pollution, general health, and occupational health. Each section has several variables, as shown in symbols in Fig. 2, which are listed in the full description in Table 1. The links between variables are shown as arrowheaded lines in Fig. 2, and the relationships between major variables are given in Table 2 as regression equations. The data necessary to determine the model coefficients were provided by various sources published in official documents from the Statistics Bureau of Prime Minster's Office, Statistics and Information Department of Ministry of Health and Welfare, Research and Statistics Department of Ministry of International Trade and Industry and others. All the data used are annual data, and where available, data of the past 60 years (from 1920 to 1980) were utilized. Our modelling exercise started in 1981 when only the conceptual model was established (Noro et al., 1981). In the following year, a numerical model was constructed as a pilot model (Sato et al., 1982) which was then incorporated into the current version. Although the current model as shown in Fig. 2 is an extremely simplified version of the real world, it is sophisticated enough to fully describe the industrial ecological system, but simple enough to keep track of and maintain its structure easily. All the variables included in the model are major ones in each of those

335 sections and also pertinent to the study of the industrial ecological system. The model has two level variables (i.e. the total population and pollution control capitals) which are integrated with time. The remaining variables are intermediate ones to complete feedback loops in the system. In a more detailed model these intermediate variables could be considered as level variables and have their own intermediate variables. However, in this macroscopic model the relationships between these intermediate variables cannot be defined clearly with theoretical equations, and therefore, regression equations have been developed. Although some relationships between the intermediate variables does not seem strongly correlated, the lowest coefficient of determination of the model regression equations is 0.65 and most are above 0.85. In addition to its macroscopic nature, the model has the following features: (1) The birth rates in recent years are considered to be strongly affected by the increasing role of women in an industrial society as shown by the increase in women workers and the decrease in the period between the births of the first and the last child. (2) The cause of death is expressed in the model not only by infectious diseases, such as tuberculosis, pneumonia and gastrointestinal disease, but also by adult diseases. (3) The numbers of physicians and hospital beds are considered as medical resources which are, in the current model, related to the demand-side variables such as ratio of recipients of medical treatment. (4) Although not sufficiently expressed, the environment and pollution section and the occupational health section are incorporated in the current model. SIMULATION RESULTS The simulation study of the model was conducted with the time span of 1920 through 2000, and several selected results are shown in Figs. 3 through 6. As can be seen in these figures, the simulation results are reasonably well fitted to the actual data of up to 1980, which may guarantee that at least the trends and orders of the simulation outputs are valid. This is sufficient for the purpose of the current macroscopic model. Figure 3 presents the simulation results for the numbers of births and deaths per 1000 persons. The sudden drops in the simulated results around 1955 are due to the functional changes necessary for the system description as shown in Table 2. As in many developed countries, Japan has experienced drops in both birth and death rates, and the model predicts that this tendency will continue in the future. This implies that the future society will

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have a top-heavy pyramid of age distribution, and will have to face the problems associated with the greying society and adjust to it. The industrial structure of Japan has shifted its center from agriculture, light manufacture, heavy industry in the past to commercial and service industries in recent years. The simulation results in Fig. 4 show that in

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338 coming years the productivities of the secondary and tertiary industries will increase steadily, and the difference in productivity between these and the primary industries will widen. The resulting gross national product in 2000 is predicted to be almost triple that in 1980. This predicted economic growth and the recent technological advancement can enable society to invest for better quality of life, such as improvements in water supply systems and air-quality control (Fig. 5) and for medical care services (Fig. 6). Although these favorable factors are expected to increase, the coming society in 2000 is predicted to face the problems of an increase in the adult disease rate nearly twice as high as that in 1980. All in all, the simulation study produced the generally expected results and some implication on the health service problems in the future. Thus, the effects of changes in industrial structure on health services can be evaluated through the linkages and loops built in the model. However, the macroscopic model cannot be used alone to answer all relevant questions. The lower-layer models are then necessary to look at more specific questions. SUMMARY A macroscopic industrial ecological system model (i.e. a macroscopic model for an ecological system in an industrial society) has been developed to investigate the effects of changes in industrial structure on health services. The modelling approach employed in this research was a two-layer structure modelling with a multidisciplinary team. The macroscopic model developed herein is the upper-layer model, of the two-layer modelling approach, having seven major sections: industry, population, labor force, living state, environment and pollution, general health, and occupational health. The lower-layer models, which are not yet developed in this paPer, are considered necessary for more specific problems at hand. The simulation model was calibrated using available data of the past 60 years for the industrial ecological system in Japan. The simulation study indicated mostly the expected results that the shift, in the industrial structure of Japan, from agriculture, light manufacture and heavy industry in the past to more emphasis on the tertiary industry in recent and coming years, would improve the level of living environments resulting in health servive enhancement. However, negative effects such as increased adult disease rates would also result, and the future industrial society would have to face the problems of a greying society. REFERENCES JIPRI, 1983. Industrial Ecology.Japan Industrial PolicyResearch Institute, Tokyo, 76 pp. (in Japanese).

339 Noro, K., Fujino, S., Sato, K., Jo, N., Tsuchiya, K. and Egawa, H., 1981. Industrial ecological model and medical informatics. In: M. Ohshima (Editor), Proc. 1st Joint Congr. Information in Medical and Biological Science, December 1981, Tokyo. Medical Information System Development Center, Tokyo, pp. 271-274 (in Japanese). Sato, K., Noro, K., Fujino, S., Jo, N., Tsuchiya, K., Yoshimura, T. and Iwao, S., 1982. Industrial ecological model. In: Y. Abe (Editor), Proc. 2nd Joint Congr. Medical Informatics in Japan, November 1982, Tokyo. Medical Information System Development Center, Tokyo, pp. 147-150 (in Japanese). Tsuchiya, K., 1983. Medical care in industrial society: development of medicoeconomics. In: Medicoeconomics Research Papers on Human Well-being and Economic Welfare. Japan Medical Association. Japan Times, Ltd., Tokyo, pp. 25-47.