Discussion Papers In Economics
And BusinessA demographic and nutritional analysis of urban lower-class dwellers inmodern Japan revised version: the case of one Saimin-chiku in Tokyo, ca.1930
Kenichi Tomobe, Minori Oshidari, Keisuke Moriya, Yoshihiro Kawano

Discussion Paper 22-06-Rev.

February 2024

Graduate School of Economics
Osaka University, Toyonaka, Osaka 560-0043, JAPAN"A demographic and nutritional analysis of urban lower-class dwellers inmodern Japan revised version: the case of one Saimin-chiku in Tokyo, ca.1930"*
Kenichi Tomobe†, Minori Oshidari†† , Keisuke Moriya†††, Yoshihiro Kawano††††[Abstract]
This study aims at investigating a method to measure the standard of living, nutritional status, andphysical condition of the saimin (“the poor") who suddenly appeared in the modern age and settled there
despite their poverty. In the study of social science, the mainstream theories of poverty are Charles James
Booth's stratification theory based on income level and Benjamin Seebohm Rowntree's minimum cost ofliving theory based on the cost of living; both have their merits and demerits. This paper will measure thepoverty levels in terms of income and cost of living using data from a specified sub-district located inTokyo (the results of an on-site survey of approximately 180 households). Many households living in the
Saimin-chiku faced poverty both income levels and cost of living. In addition, observation of the healthstatus of the saimin households showed that roughly half of the community had a disease of some sort, or a
tuberculosis patient in the household. This provides a perspective which illuminates the difference insituation between the saimin households, who made a living based on an economy of mutual support, andthe small farmer households, who had a communal consumption lifestyle but had the capacity to be selfsupporting.
* This is a revised version of Discussion Papers in Economics and Business 22-06. Yoshihiro Kawano
contributed his political evaluation from the viewpoint of a national policy maker to this paper. This
research was financially supported by both a Grant-in-Aid for Scientific Research “Quantitative Analysis
of Household Economy by constructing the Database from Household Financial Diaries " (2023–2026,
Rissho University, Prof. Yukinobu Kitamura) and a Grant-in-Aid for Scientific Research " The effects ofurbanization and industrialization on child health in modern Japan: from infant and child mortality andheight growth of school children " (2020–2023, Hitotsubashi University, Prof. Kenichi Tomobe).
†: Corresponding author, Graduate School of Economics, Hitotsubashi University, 2-1 Naka, Kunitachi,
Tokyo, 186-8601, Japan. Email address: kenichi.tomobe@r.hit-u.ac.jp††: Bank of Yokohama, 3-1-1 Nishi-ku Minatomirai, Yokohama, Tokyo, 220-0012, Japan.
†††: Graduate School of Economics, Hitotsubashi University, 2-1 Naka, Kunitachi, Tokyo, 186-8601,
Japan.
††††: Member of House of Councilors, House of Council Building #720, 2-1-1 Nagatacho, Chiyodaku, Tokyo, 100-8962
JEL Classification:I14 N00 R00
Keywords: household, poverty, health, living standard, nutrition intake

Introduction: Households, Living Standards, and Nutrition
Regarding the lifestyle of peasants after the Ritsuryo era (mid-7th-10th century), it is safe to assume thatthe household, as a unit group of independent peasant, that is, was the unit of production and labor incultivation, a production activity that has continued since the Jomon (14,000–300 BCE) and Yayoi (300
B.C.–300 A.D.) eras.1 Conversely, what is unclear, is where the consumption and nutrition of household
members was supplied from. Historical studies have concluded that these peasants eventually became
independent as consumption units when they built houses (dependent on the main family) and ‘Kamado’,
installed cooking stoves (mainly in western Japan) and ‘Irori’, sunken hearths (mainly in eastern Japan).
While this criterion is clear, it is still yet to be confirmed whether it is correct. In the late Muromachi period(1333-1573), the situation of peasants who became independent usually consisted of a community ofhouses and lots.2 This is because it is natural to imagine that even if each house had its kitchen, the foodcooked at each kitchen would be shared among the houses. This characteristic is due to the fact thatmultiple independent houses were built within the grounds of a main house. Hence even if each house had akitchen, it was common to expect that any shortfalls would be accommodated between houses.
During the Edo period (1603-1867), each house emerged independently from the house community(yashiki); nevertheless, it is common to assume that the peasants living in these new houses in theneighborhood, including the initial house owners, continued to live together in a community of
consumption, and that the group became the basis for the formation of the so-called "Ie" (house), which has
also been a point of research to date.3 Moreover, this is the ground on which well-known rural sociologist
Kizaemon Ariga stated, "the household is the last redoubt of livelihood security."4 Up to this point in thehistory of Japanese society, the Ie and the household are distinct, and the distinction is to be made in theanalysis. In other words, the "standard of living as a household" and "standard of living as a house" differ
conceptually and interpretatively in the resultant analysis.
Consequently, what is the standard of living for the "saimin" (a term coined as an administrative term in
the late Meiji and Seed how can it be measured? Two theories on poverty have traditionally dominated thestudy of social sciences. The first is Charles Booth's hierarchy theory based on income level, and the otheris B.S.Rountree's minimum cost of living theory based on the cost of living5. Both have advantages anddisadvantages, but this paper will analyze the poverty level in terms of income level and cost of living(nutritional calories) using data from a specific small community in Tokyo in the early 1930s (results froma survey of roughly 180 households).

1．Income Level, Cost of Living, and Food of the Saimin Community
Firstly, the household income; the average monthly household income in the Saimin-chiku (lower-class
district) was 55.9 yen (93.7 yen for Tokyo city residents; same below in parentheses), 52% (7.1%) of allhouseholds earned less than 60 yen, and 96% (16%) earned less than 100 yen. In other words, almost allhouseholds in the Saimin community were in the bottom 20% of the households of Tokyo city residents atthat time. Thus, we consider them the least standard income earners of that time. According to thestratification of Booth's classification, we can assume a structure with "regular low-income earners" and"irregular standard earners" as the core, "occasional earners" as the very poor, and "temporary day laborers,
vagrants, etc." as the lowest stratum.
Next, the cost of living, i.e., nutritional intake (converted as the amount of energy needed for a male
1 See Masashi Oguchi, 1995, "Agricultural Management Unit in Ancient Japan", Toshiya Torao eds. Local

Rule under the Nation of Ritsuryo Codes, Yoshikawa Koubunkan Co., Ltd., pp. 248–260, and Kenichi
Tomobe, 2021, "A Brief History of Markets, Households & Infectious Diseases in Japan", Japan Spotlight,
237, May/June, pp.38-41.
2 See Kenichi Tomobe, 2007, Farm Household Economy in Pre-industrialized Japan, Yuhikaku PublishingCo., Ltd., Chapter 1. Here, the cooking stove installation is understood as a consumption unit.
3 See Tsuneichi Miyamoto, 2014, "City Culture and Rural Community Culture", Zenjiro Tamura eds.,
Selection of Tsuneichi Miyamoto's Lectures vol. 3, Rural Culture Association Japan.
4 See Kizaemon Aruga, 1978, Feudal Legacies and Modernization 2nd Ed., Takashi Nakano, Minoru
Yoneji, and Kyouichi Kakizaki eds., Works of Kizaemon Ariga vol. 4, Mirai-sha Publishers, pp. 187–277. In
this context, a village in the early modern period is understood as a cluster of houses.
5 See for example Charles Booth, 1892-1896, Life and labour of the people in London, and B.
Seebohm Rowntree, 1901, Poverty, A Study of Town Life.
1manual laborer = 3500 kcal/day, reflecting differences in age and gender) was examined; the average daily
calorie intake of "households" (reconstructed) lacked approximately 3096 kcal/day. Only 2% of households
could consume more than the required calories, which meant that 98% of the households were not getting
the minimum daily calorie. The detailed breakdown is as follows: 14% of all households were deficient inover 5000 kcal, 32% were deficient in 3000 to 5000 kcal, and 52% of all households were deficient in lessthan 3000 kcal.
Based on the theory of minimum cost of living, it is clear that the consumer life of the residents of theSaimin community was established based on a shared economy6 (an economy of mutual support). Perhaps
it is safe to conclude that "sharing" was assumed in almost every event pertaining to consumption.
Although some of the Saimin occupied two rooms, most lived in one room, so the kitchen was probably
shared. Recently, Noriko Yuzawa has offered an interesting perspective on the topic of sharing.7 As far as it
is known from the Saimin dietary menu, a simple "simmered dish" was served almost every evening as aside dish for dinner. Per Yuzawa's point, the importance of the presence of "simmered food" stalls in large
urban areas comes to the fore once again. Furthermore, the issue of consuming leftovers, which is often
pointed out in the study of the Saimin community, should not be understood simply as a phenomenon ofshared poverty but rather as a way of saving money and satisfying the pride of the poor by sharing "a warm
meal" called "leftovers." In addition, cooking over a fire may kill mold and bacteria, which, as will be seen,
has a hygienic effect.
2．What is "Poverty" in Economic History ?
How to understand the term "poverty" or "impoverishment" in the context of economic history? The term
"poverty" or "impoverishment" has been studied from various perspectives. In the field of economic history,
it is postulated by measuring the standard of living of workers during the Industrial Revolution.8 Moreover,in social welfare studies, the pros and cons of proposed measures have been determined by reference tomeasurements of "poverty" or "impoverishment."9 Alternatively, "poverty" as a contrast to "abundance" hasbeen the focus.
Poverty has also been measured through various methods. Real wages have been used as a measure ofliving standards. But, there has been criticism that while real wages can measure the standard of living ofwage earners, they cannot reflect the actual living conditions of non-wage earners, especially those living inrural areas. Additionally, the method of assessing living standards by body size, especially height, was also
assumed. In nineteenth-century England, people from rural areas were found to be taller than those fromurban areas. This is the consequence of exposure to poor urban living conditions, commonly referred to as
the urban penalty.10
It is argued that the standard of living is measured by calories expended and work intensity. Unlike real
wages, the measurement of calories earned can also measure the standard of living of non-wage workers
and calculate the number of calories obtained per working hour as long as the total working hours isdetermined. Notwithstanding, the number of calories obtained per hour of labor resulted in the hunters
being by far the richest, as they were able to obtain more calories (food) in fewer hours of labor.11
6 In the book, Tetsuo Najita, 2009, Ordinary economies in Japan : a historical perspective, 1750-1950,

ordinary economies are defined as economies of mutual assistance, which again implies the daily economyof the Saimin people.
7 See Noriko Yuzawa, 2022, History of Household Dish in the Modern Developed Town: Buy, Borrow, andShare the 'Fire' for Cooking", Gendai Shisou February 2022 Issue. For further details of the significance ofthe role played by "niuri-chaya (simmered dish restaurant)" in the Edo area in the Edo period, see Chapter
3 of Ryouichi Iino's book, Births of Izakaya, Chikumashobo Ltd.
8 See Takao Matsumura, 1989, "Revisiting the Discussion of Living Standard in the Period on British
Industrial Revolution: Fisrt Part", Mita Journal of Economics 82-2, July, pp. 353–372. Various other pieces
of research are available on the topic of living standards in the industrial revolution period.
9Kitahara, I. (1995), Toshi to hinkon no shakai-shi - Edo kara Tōkyō e -”, Yoshikawakōbunkan. [A Social
History of Cities and Poverty: From Edo to Tokyo, Yoshikawa Kobunkan.]
10 Mokyr, Joel and Cormac, O. Grada, 1996, "Height and Health in the United Kingdom 1815-1860:
Evidence from the East India Company Army", Explorations in Economic History 33-2, April, pp.141-168.
Moriya&Tomobe, 2023,”Gakuseki-bo karamiru Senzenki Noson niokeru Jido no Taikaku”[ A stature ofschool children in Pre-war rural Japan from the school register], pp.435-458.
11 See Gregory Clark, 2007, A farewell to Alms: A Brief Economic History of the World, Princeton,2

In consideration of the standard of living, "poverty," as most would perceive it, can be taken to mean abasic subsistence level, i.e., the minimum standard of living, or even lower. But, the demand to measure"poverty" arises on both levels. Thus, this paper will interpret "poverty" by observing the actual conditionsof those identified as "poor" in accordance with the results of a survey conducted by the Tokyo Municipal
Health Examination Center.

3．Lower-class dwellers and their household composition
There is an interesting document on “poverty” in “Nutrition Survey in a Saimin-chiku area in Tokyo”(hereafter referred to as “Hygienic Laboratory Survey”), which was published by the Tokyo Municipal
Hygienic Laboratory in 1931 as “Tokyo Municipal Hygienic Laboratory Report: Academic Report
No.7.”This document was a survey of the actual conditions of a Saimin-chiku community in the
Koishikawa district of Tokyo in 1930, in which the researcher in charge of approximately 200 households
visited each household every day to observe and record the survey items. The city of Tokyo prepared thisdocument for the purpose of conducting on-site surveys of various data on the lives of Saimin, and to use it
as basic data for formulating relief programs. The survey items were diverse, including the number offamily members by age, nutrient intake, disease status, occupation of the head of the household, householdincome and expenditure, type of housing, dentistry, number of pregnancies, number of births, number of
infant deaths, and so on. This data was more objective than other data, especially accuracy. Althoughsimilar surveys were conducted in Osaka, their primary survey methods were questionnaires and interviews.
In the Osaka City Infant Growth Survey conducted in 1937, the questionnaire collection rate was only
43.8%, and it is assumed that many of the mothers, especially those who had dropped out of elementary
school, had difficulty to fill out the “record sheets,” therefore, many of the households in the lowest
socioeconomic group of people could not be collected.12 In comparison, the survey of the Saimin-chiku area
was highly objective because the researcher visited and observed each household every day.
The hygienic laboratory survey in a Saimin-chiku area in Tokyo is an extremely important investigationthat can be used as the basis for administrative policy-making, and should be highly regarded as anadvanced case of the evidence-based policy-making methods generally adopted today.
Firstly, policy formulation is supported by research. According to the first report of the hygienic
laboratory survey, "There are some important social problems, and the poverty relief project is the mostimportant one." and "It is truly regrettable that there are few studies that should contribute to the basis ofrelief methods". This is a strong indication that policy planning is not based on ad hoc episodes, but rather
on a rational basis, with clearly defined policy objectives. This is considered to be an advanced example ofthe evidence-based policy-making method that modern administrative and legislative bodies are workingon.
Secondly, the data development, which is a prerequisite for planning social relief schemes, is supported
by careful surveys conducted through individual visits. The second report of the hygienic laboratory survey
states: 'Investigators visit each house and conduct a medical examination when the person is at home. The
thoroughness of the survey, "If the researcher is not at home, he or she will visit each house and conduct a
medical check-up on a public holiday", shows a strong enthusiasm for the formulation of a policy to help
the poor, and can be evaluated as a remarkably superior approach compared to the survey conducted in
Osaka City during the same period, and to contemporary survey methods using mail or online methods.
There the income situation of Saimin households was examined. As described in the previous section, theaverage monthly household income in the Koishikawa area was 55.9 yen, the severity of which was also
highlighted by the government’s response. During the time that this survey was conducted, the Osaka City
Medical Association provided free medical care for households with an annual household income of 800
yen or less, or a monthly income of 66.66 yen or less, and low-cost medical care was provided forhouseholds with an annual household income of 1,200 yen or less, or a monthly income of 100 yen or
less.13 Despite the differences between Tokyo and Osaka, there seem to have been no significant differencein wages between the two cities. By looking at eligibility for public assistance, the lower income
households in the Koishikawa area were not standard households. In addition, the “Survey of Persons with
Special Circumstances in Households Requiring Public Assistance in Tokyo,” prepared by the Social
Princeton University Press.
12Higami, Emiko, Infant Mortality and the Social Capital in Modern Osaka, Osaka University Press. Osaka.
2016: 213
13Ibid, 235-236.
3

Affairs Bureau of the City of Tokyo in 1934, included a table of “Living Standards for Households
Requiring Public Assistance,” as shown in Table 3-1.
Table 3-1 Living Standards for Households Requiring Public Assistance
Household income
Number of household
(yen)
1

25

2

35

3

45

4

55

5

60

(thereafter, increased by 5 yen for each additional person in the household)Source: Tokyo City Social Affairs Bureau, Survey of Persons with Special Circumstances in Households
Requiring Public Assistance, Tokyo City. 1934.

Although it is debatable whether the 1934 standard is applicable, as it was heavily influenced byseriously depression, this standard was adopted for comparison for this analysis. The average number ofhousehold members in the target area was 4.7, and living standard for households requiring public
assistance of 58.5 yen. Only 43 of the 183 households in Table 3-1 exceeded the standard, and even for
those that did, most were only slightly above the standard amount. The fact that the average monthly
household income in the target area was 55.9 yen confirmed that these households were not standard
income earners.
Next, turning to expenditures, food costs were 29 yen per household per month, and rent was 8.3 yen perhousehold per month. Since the average income was 55.9 yen, the surplus was 18.6 yen. However, sincesome of the households were engaged in such occupations as construction workers, laborers, and freelaborers, and their income was affected by weather conditions such as rain and snowfall, the actual surplus
was considered to be lower.14 It is interesting that children's allowance was included in the expenditures;
only 33 of the 183 households were known to have an allowance, but it amounts to 6 yen per household permonth and 2.5 yen per child per month. In some cases, households whose income minus rent and foodexpenses was in deficit also gave their children an allowance. Although the culture of giving an allowanceto children is not detailed here, it was not unique to the Koishikawa area, and it is thought that giving anallowance to children have been common practice in the Saimin-chiku area.
Regarding the occupation of the heads of households, while there was a segment of the population that
seems to have had a regular occupation, a certain number of them were found to have irregular or
temporary occupations that were closely related to poverty. In particular, household income was considered
to be very low when there was no unmarried male worker in the household. This is directly related to thenutritional status of the households, which will be discussed later.
Since information on the number of household members was available for both age groups and sexes,
this section divided the composition of households in the Saimin-chiku area as follows; households
consisting of (1) one man and one woman aged 21 or older and one man and one woman aged 20 oryounger (married couple and children); (2) one man and one woman aged 21 or older (married couple
only); (3) one man and one woman aged 21 or older and one man and one woman aged 20 or younger (asingle parent household); (4) single-person households; and (5) households with three or more persons aged
21 or older. In the case of (5), most of the households were considered to consist of a married couple andtheir adult children or a married couple and their parents living together.
Table 3-2 Classification of Household in Saimin-chiku area
14According to the report, it was found in an interview by the investigators. Tokyo Municipal Hygiene

Laboratory, Tokyo Municipal Hygiene Laboratory Report Academic Report 7 1931.
4

Household
Classification

Number ofHouseholds

Average Monthly
Income (yen)Married couple andchildren

113

54.8

Married couple only

19

38

Single parent
household7

61.3

Single personhousehold2―

Households with 3 ormore men and womenover 21 years old

42

67.6

Source: Tokyo Municipal Hygienic Laboratory, 1931, Tokyo Municipal Hygienic Laboratory Report
Academic Report No. 7.
The average monthly income of households was available for only 109 of the 183 households. This isbecause some households refused to be surveyed due to low income, irregular income, or other family
circumstances. Therefore, the average monthly income of single-person households was unknown.
The most striking feature of the survey was that there was a large difference in household incomes
between the households headed by a married couple plus children and those headed by a married couple
alone. Although the 1927 survey conducted by Tokyo City Hall found that households with lower incomes
were more fertile, Table 3-2 suggests that households made their own choices regarding reproduction inaccordance with their economic situation.
Next, by examining the housing conditions of the lower income households, of the 110 households
whose housing was known according to the hygienic laboratory survey, only 22 households lived in ahouse of two or more rooms, and 88 households lived in a one room house. The number of tatami mats perhousehold was 5.9 tatami mats, and 1.2 tatami mats per person, and with the most extreme case, being 4.5
tatami mats occupied by 8 persons (one tatami mat is about 0.9 meter by 1.8 meter). Not only were thehouses small and cramped, but they were also unsanitary. The Tokyo City Social Affairs Bureau’s “Surveyof Special Circumstances of Households Requiring Aid in Tokyo” pointed out that 57.6% of the housing in
the Saimin-chiku area was in poor condition, though this was the subjective opinion of the surveyor.
Although the environment referred to “extremely vague, including the state of sewage in the vicinity, thedensity of houses, and the degree of cleanliness,” the fact that more than half of the respondents lived in
housing that was even worse in the areas designated as “slum” cannot be overlooked. In addition, 71% of
the households live in low areas and 63.9% live in swamp areas, indicating that most of the households livein low areas. Although these results cannot be taken as a complete list of all households, it is clear thatmany of the households were located in low wetlands and were exposed to the risk of disease andepidemics.
4．Nutritional and physical conditions of lower-class households
As calorie intake has already been discussed in the previous section, this section examines household
intake of various nutrients. The average protein intake per household was 361 grams per day, or 51 grams
per person. The necessary dietary intake, taking into account differences in age and gender, only 23.5% of
the households had insufficient protein intake, which means that many of these households could obtainsufficient amounts of protein. However, 60% of the protein intake was covered by staple foods, and only
18% was made up of animal protein. They were not consuming a nutritionally well-balanced diet. In
contrast, daily household fat intake averaged at 31.7 grams and 8.3 grams per person, meaning that mosthouseholds were significantly deficient in fat intake. Their intake shows that animal fats accounted for only
32.6%, and most fat intake was obtained from staple foods and vegetable sources. Household intake of5

carbohydrates averaged at 1,500 grams per day or 350 grams per person. According to a nutritional survey
conducted by the Osaka Prefectural Health Department in 1920 in the Saimin-chiku area, the average daily
protein intake for an adult male was 81 grams, of which 15% was animal proteins, 9 grams of fat, and 580
grams of carbohydrates. Although the City of Tokyo estimated the intake per person with only a simple
calculation, it is assumed that the result would be similar to that of the survey conducted by the Osaka
Prefectural Health Department in 1920, considering the differences in gender and age.15
We examine the meals of lower-class households. Unfortunately, there was no survey conducted on themenus of all these households in that area; however, there were some survey results on the menus of somehouseholds and lower-class households with pulmonary tuberculosis patients. Both cases show that cooked
dishes such as miso soup and simmered dishes were served at least once a day. As mentioned above, it isevident that the sharing of "cooked dishes" was considered a creative way to save money and give a senseof pride to underprivileged people. Also, their meal menus indicate deficiencies in animal protein and fat.
At the same time, as shown in Table 4-1, among the 213 households that were available for the healthsurvey of all household members, 47.4% of males and 52.5% of females had some form of illness. Of these,
21.5% appeared to have eye diseases, suggesting that most of them were myopic, while roughly 30% of therest had some form of disease. Among those with diseases, gastrointestinal, neurological, and respiratory
disorders were the most common, accounting for 35.5%, 16.5%, and 13.7% of the illnesses, respectively.
Most of the neurological diseases occurred after 41 years, while digestive and respiratory diseases tended tooccur between 6 to 15 and 16 to 40 years.

Table 4-1 Health Survey Results
Under theage of 5

Age 6~15

Age 16~40

Age 41or
older

Total

Healthy（Male）

28

62

74

68

232

Healthy（Female）

32

45

67

50

194

Patients（Male）

23

66

47

73

209

Patients(Female)

26

68

51

69

214

（Unit: person）
Source: Tokyo City Hygienic Laboratory, 1931, “7th Scientific Report of Tokyo City Hygienic Laboratory,”
P.241-242
In the case of gastrointestinal diseases, malnutrition is thought to be the leading cause, while respiratory
diseases were mainly due to unhygienic living conditions. Of the 849 patients surveyed, 150 had
gastrointestinal disorders (17.7%), and 58 had respiratory diseases (6.8%). In the 183 households where thenutrition study was conducted, the incidence rate of gastrointestinal disorders was 9.4% (66 out of 700),
while for respiratory diseases it was 7% (49 out of 700). Although the incidence rate of gastrointestinal
illnesses varied, the incidence of gastrointestinal disorders was not as high as one would expect, given theunhygienic living conditions. As mentioned earlier, the low incidence level was probably the result of
cooked dishes, which killed some virus in the cooking process.
In addition, most households in the Saimin-chiku used to live in a single room with a shared kitchen andbathroom. Their houses were poorly lit and not well-ventilated, making them vulnerable to respiratory
diseases. This is also apparent because tonsillitis accounted for 17% of the diseases. The proportion of sickinfants under five years old was not as high as in other age groups. This was due to the minimal number of
those with eye diseases. Excluding eye diseases, the proportion of sick infants is higher than in other age
groups. Moreover, since infants with inferior physical strength and immunity tended to die from
15

Emiko HIgami(2016), 131.

6

gastrointestinal or respiratory diseases, they are not listed as patients.
Lastly, regarding the infant mortality rate, there were 636 childbirths and 179 infant deaths in all
households surveyed, resulting in an infant mortality rate of 275‰. Although a simple comparison cannot
be made because the infant mortality rate is unknown, an extremely high mortality rate is evident,
considering that its national average at that time was about 120‰. It is not surprising because the infantmortality rate in the Saimin-Chiku area in Osaka was 195‰.16 In a survey conducted by the Bureau ofSocial Affairs of Tokyo City between 1935 and1936, infant deaths and stillbirths were concentrated in theareas with households in need of social assistance, that is, the Saimin-chiku area. The total numbers ofchildbirths and infant deaths of the families in need of social assistance were 494 and 124, respectively,
resulting in an infant mortality rate of 251‰. Despite the difference in years, the infant mortality rate ofhouseholds in Saimin-Chiku area did not change significantly and remained high. Moreover, the highnumber of sick children between 6 and 15 years old and the high infant mortality rate indicates thatchildren were exposed to poverty before entering the workforce.

・５．Determinants of pregnancy and infant mortality
The previous section discussed child mortality. Here, multivariate regression analysis is undertaken so as
to identify possible factors affecting the incidence of pregnancy, gravidity and child mortality rate, which
could be directly associated with child death17.
・５．１ Factors affecting the presence of pregnancy experience
First, for the factors affecting the presence of pregnancy experience, a binomial logistic analysis was
performed using the experience of pregnancy (yes = 1, no = 0) as a response variable. The Model is statedas the following Formula.
1
⋯(1)

p=
1 + 𝑒𝑥𝑝[−(𝑏1𝑥1 + 𝑏2𝑥2 + ⋯+ 𝑏𝑖𝑥𝑖 + 𝑏0)](‘p’ represents the probability of the dependent variable to be 1. ‘𝑥𝑖’ is an explanatory variable and ‘𝑏𝑖’ apartial regression coefficient, calculated by the maximum likelihood estimation.)
Table 5-1 summarizes the factors examined as the explanatory variables and their descriptive statistics.
In addition to items from the Hygiene Laboratory Survey, it also includes other factors that this study
calculated based on them.
Table 5-1. Relations with the presence of pregnancy experience
Categories

Explanatory variables

Economicfactors

Household monthly income
Monthly income/ the number of family members
Monthly income/ the square root of the number of family
members
Monthly income – primary expenditures(Monthly income – primary expenditures)/ monthly income

Nutritional
factors

Calorie intake
Proportion of calorie intake from staple foods
Protein intake
Fat intake
Carbohydrate intake

The
numberofsamples
109
110

Min

Max

Mean

SD

15
5

125
35

56.4
13.5

19.5
6.1

109110
109

8.7

57.7

27.1

9.0

-20.3
-0.33
685
0.5
10.4
1.9
144.9

98.6
0.79
3165
0.96
108.9
86.2
1861

26.9
0.44
1681
0.85
51.1
8.3
347.7

18.9
0.21
349.3
0.06
13.4
7.7
132.3

182
182
182
182
182

16Emiko Higami, 2016, P.218

17 As a concept gravity means the number of pregnancy including miscarriage, stillbirth andlivebirth which is different from parity, number of livebirth as a demographic word but thereal scene wasn’t seen clearly.
7

Healthfactors
Familystructure
factors
Dwelling
factorfood cost per person
Proportion of sick persons
The number of dental caries per person
Presence of a female worker
Ratio of males
Proportion of workers
The number of tatami per person

182
167
143
110
182
110
110

0.03
0
0
0
0.2
0
0.29

0.31
1
32
1
1
1
7.75

0.16
0.44
7.6
0.35
0.52
0.38
1.51

0.04
0.31
5.7
―
0.16
0.21
0.98

The results of partial regression coefficients of logistic analysis are demonstrated in the following
Table 5-2. Using AIC (Akaike Information Criterion), Model (1) was obtained as the best fit model.
Also, in order to confirm that multicollinearity did not occur, Variance Inflation Factor (VIF) values
were calculated.
Table 5-2. Estimation of partial regression coefficientsMonthly
incomeexpendituresProtein intake–

primary

Fat intake
Ratio of maleThe number of tatami per person
Constant
The number of samples
Log-likelihood

Model(1)

VIF value

0.051(0.032)-0.137**(0.067)0.539*(0.291)
3.583(3.208)-2.057***(0.731)
6.146**(3.001)87-17.863

1.177
3.093
3.984
1.055
1.676

Note) ***, ** and * indicate a significance level at 1%, 5% and 10%. Values in parentheses show thestandard error.
Monthly income – primary expenditures indicated a positive partial regression coefficient, but the value
was not significant. It would be easy to imagine that a financially secure family is more likely to experience
pregnancy; however, no clear tendency was observed in the presence of pregnancy experience only.
Similarly, despite the positive correlation in the ratio of male family members, the finding was notstatistically significant. In contrast, regarding nutritional intake, a negative correlation was found in protein
intake, as well as a positive correlation in fat intake. Although further analysis would be required to
scrutinize the negative correlation of protein intake, it was presumably because protein was ingested largely
from staple foods as mentioned previously. As for fat intake, since it is the most effective energy sourcewith the function of storing surplus energy, a higher intake of fat seemingly led to better health andeventually to a higher chance of pregnancy. Moreover, while a negative correlation was detected in thenumber of tatami per person, it seemed to have been caused by the increased number of family members
after pregnancy and childbirth.
・５．２ Factors affecting gravidity
In 140 households with a wife having experience of pregnancy, a multiple regression analysis was
conducted using gravidity as the response variable. The Model is stated as the following Formula.

y = 𝛽0 + 𝛽1𝑥1 + 𝛽2𝑥2 + ⋯+ 𝛽𝑖𝑥𝑖 + 𝑢⋯(2)(‘𝑥𝑖’ is an explanatory variable, ‘𝑢’ an error term, and ‘𝛽𝑖’ a regression coefficient, obtained by theleast squares method.)
Here, regarding the explanatory variables in Table 5-1, the study explored correlation with gravidity. The
findings are depicted in Table 5-3.
Table 5-3. Relations with gravidity
8

Categories

Explanatory variables

Correlation
coefficient

Economicfactors

Household monthly income
Monthly income/ the numberof family members
Monthly income/ the squareroot of the number of family
members
Monthly income – primary
expenditures(Monthly income – primary
expenditures)/monthly
incomeCalorie intake
Proportion of calorie intake
from staple foods
Protein intake
Fat intake
Carbohydrate intake
Food cost per person
Proportion of sick persons
The number of dental caries
per person
Presence of a female worker
Ratio of males
Proportion of workers
The number of tatami perpersonNutritional
factors

Healthfactors
Familystructure
factors
Dwelling
factorUpper limit of
95% confidence
interval
0.421-0.291

P value

0.237**-0.468***Lower limit of
95% confidence
interval
0.034-0.614-0.082-0.244

0.084

0.331

0.017

-0.188

0.219

0.875

-0.269***-0.449-0.0680.01-0.11
0.312***

-0.27
0.156

0.056
0.454

0.194
0.0002-0.232***-0.291***-0.067-0.246***0.175**-0.079-0.383-0.435-0.229-0.3950.009-0.256-0.07-0.1330.099-0.085
0.331
0.102

0.005
0.0004
0.428
0.003
0.039
0.392

0.188***-0.057-0.214**-0.519***

0.024
-0.22
-0.4
-0.653

0.342
0.109
-0.01
-0.352

0.025
0.5
0.04
1.02E-0.7

0.023
2.59E-0.6Note) ***, ** and * indicate a significance level at 1%, 5% and 10% respectively.

The response variables with a significant correlation coefficient at 10% level or less were applied to theModel of Formula (2) so as to perform the multiple regression analysis. The results are illustrated in Model(2) of Table 5-4. Also, the best fit models, subsequently obtained using AIC, are shown in Model (3) of thesame Table.
Table 5-4. Relations with gravidity
Household monthly income
Monthly income/ the number offamily members(Monthly
income–primary
expenditures)/ monthly income
Proportion of calories intake from
staple foods
Protein intake
Fat intake
Food cost per person
Proportion of sick persons

Presence of a female worker
Proportion of workers
The number of tatami per person
Constant
The number of samples

Model(2)Model(3)0.091***(0.017)-0.176*(0.103)-5.181***(1.941)
2.071(5.300)0.036(0.039)-0.088(0.152)-10.401(10.093)-0.462(0.751)0.090***(0.013)-0.256***(0.050)-3.908***(1.507)0.747(0.597)-0.311(1.722)-0.279(0.590)2.906(5.063)0.716*(0.412)92

92

4.050***(0.716)9

Coefficient of determination
Adjusted coefficient of determination
F-statistic

0.559
0.498
9.206***(df=11.80)

0.535
0.514
25.050***(df=4.87)

Note) ***, ** and * indicate a significance level at 1%, 5% and 10% respectively. Values in parentheses show
the standard error.

In Model (3), standardized partial regression coefficients were calculated so as to investigate the degree ofeffect each explanatory variable had on the dependent variable. Then, in order to ensure thatmulticollinearity did not occur, Variance Inflation Factor (VIF) was evaluated, of which findings arepresented in Table 5-5.
Table 5-5. Standardized partial regression coefficients and VIF values of Model (3)Household monthly income
Monthly income/ the number offamily members
Presence of a female worker(Monthly
income–primary
expenditures)/ monthly income
Constant

Standardized
coefficient
0.6883-0.5543

partialregression

VIF value
1.737
1.983

0.1182-0.3260

1.050
2.783

-0.0252―

Despite the positive correlation in the household monthly income, Table 5-5 illustrated a negative
correlation in both monthly income/ the number of family members and (monthly income – primary
expenditures)/ monthly income. Among the economic factors categorized by income levels, the negative
explanatory variables especially reflected the standard of living. The higher the household monthly income
as a simple income level was, the more frequently the wife became pregnant. However, the examination ofliving standards demonstrated that the households with lower living standards had higher gravidity.
According to the standardized partial regression coefficients in Table 5-5, the household monthly income
was +0.69, monthly income/ the number of family members -0.55, and (monthly income – primary
expenditures)/ monthly income -0.33. That is, with respect to the scale of influence on the dependent
variable, the negative impact on living standards was more considerable than the positive impact of thehousehold monthly income. Given that the living standards of households were not fixed but fluctuateddepending on pregnancy and childbirth, the result of higher gravidity in the families with lower living
standards implies that pregnancy proved relatively more of a burden for the participating households than abenefit. It might explain that the standard of living dropped after the first pregnancy and childbirth andfurther deteriorated after another.
At the same time, the proportions of burdens and benefits of parenting differ according to the age ofchildren. When children are still small, the increased expenditures worsen the household’s living standards.
However, if they are old enough to work, the standard of living could improve due to the rise of household
monthly income. Gravidity of lower-class families had a positive correlation with the household monthly
income and a negative correlation with the variables reflecting the living standards. These findings
indicated that, whilst grown-up children could raise the household monthly income, many families were notable to recover the costs spent on child-rearing. Assuming that one of the purposes of having children in thelower-class households was to improve the future income and living standards, there seem to have been
unforeseen background circumstances (that the husband and wife did not want) that resulted in decreased
living standards after childbirth.
In addition, a positive correlation appeared between the presence of a female worker and gravidity. This
could be considered as evidence that, if they had unemployed children, parents needed to go to work for aliving even after childbirth.
・５．３ Factors affecting the child mortality rate
In the households having experience of pregnancy, a multiple regression analysis was performed with thechild mortality rate (the number of child deaths under five years/ the number of deliveries) as the response
variable. The Model is stated in Formula (3) as below.

y = 𝛽0 + 𝛽1𝑥1 + 𝛽2 𝑥2 + ⋯+ 𝛽𝑖 𝑥𝑖 + 𝑢

⋯(3)
10

(‘𝑥𝑖’ is an explanatory variable, ‘𝑢’ an error term, and ‘𝛽𝑖’ a regression coefficient, obtained by themethod of least squares.)First, as with the analysis of gravidity, correlation between the candidate explanatory variables and childmortality rate was explored. Table 5-6 presents the results.
Table 5-6. Relations between the child mortality rate and each explanatory variable
Categories

Explanatory variables

Correlation
coefficient

Economicfactors

Household monthly income
Monthly income/ the numberof family members
Monthly income/ the squareroot of the number of family
members
Monthly income – primary
expenditures(Monthly income – primary
expenditures)/monthly
incomeCalorie intake
Proportion of calorie intake
from staple foods
Protein intake
Fat intake
Carbohydrate intake
Food cost per person
Proportion of sick persons
The number of dental caries
per person
Presence of a female worker
Proportion of male family
members
Proportion of workers
The number of tatami perpersonNutritional
factors

Healthfactors
Familystructure
factors
Dwelling
factorUpper limit of
95% confidence
interval-0.105
0.297

P value-0.303***
0.099

Lower limit of
95% confidence
interval-0.479-0.107-0.141*-0.299

0.025

0.095

0.153
-0.093-0.346-0.293

0.052
0.114

0.143
0.376

0.319***-0.036

0.162
-0.2

0.459
0.129

0.0001
0.668

0.319***
0.298***
0.145*
0.232***
0.074
0.059

0.163
0.14
-0.02
0.07
-0.093-0.122

0.46
0.441
0.303
0.382
0.237
0.237

0.00010.0003
0.083
0.005
0.382
0.523

-0.046-0.0150.263***-0.209-0.170
0.063

0,119
0.15
0.443

0.584
0.862
0.011

0.181*-0.024

0.371

0.083

0.003
0.344

Note) ***, ** and * indicate a significance level at 1%, 5% and 10% respectively.

The multiple regression analysis was run by applying the dependent variables with a significant
correlation coefficient at 10% level or less to Formula (3). Model (4) of the following Table 5-7
demonstrates the results. Besides, the best fit models, calculated using AIC, are illustrated in Model(5) of the same Table. Furthermore, Table 5-8 presents the standardized partial regression coefficientsand VIF values of Model (5).
Table 5-7. Relations with the child mortality rate
Household monthly income
Monthly income/ the square root of the number offamily members
Calorie intake
Protein intake
Fat intake
Carbohydrate intake
Food cost per person
Proportion of workers

Model(4)-0.006(0.004)0.007(0.008)0.0001(0.0005)-0.001(0.007)-0.013(0.019)0.001(0.002)-0.289(1.487)0.234(0.179)11

Model(5)-0.004**(0.001)0.001(0.0005)
0.323**(0.150)

The number of tatami per person
Constant
The number of samples
Coefficient of determination
Adjusted coefficient of determination
F-statistic

0.013(0.073)0.175(0.238)
92
0.187
0.098
2.099**(df=9.82)

0.130(0.198)
92
0.168
0.140
5.942***(df=3.88)

Note) ***, ** and * indicate a significance level at 1%, 5% and 10% respectively. Values in parentheses show
the standard error.

Table 5-8. Standardized regression coefficients and VIF values of Model (5)Household monthly income
Carbohydrate intake
Proportion of workers
Constant

Standardized regression coefficient-0.2580.346
0.215-0.045

VIF value
1.062
1.100
1.037
―

A negative correlation was found between the household monthly income and child mortality rate. It was
not a surprising result because the higher the household income is, the more money should be spent onchildren. By contrast, the positive correlation with the proportion of workers, the child mortality rate seems
to have risen due to the absence of a caregiver at home. In the households without grandparents and older
children who could take care of younger ones, it was difficult for the parents to provide enough care forchildren all day long. Especially in the case of lower-class households, the husband worked outside frommorning to night without a day-off, while the wife was very busy with piecework and chores at home. The
result of the lower child mortality rate in the households with many family members seemingly reflects thefact that unemployed family members could look after children and that the parents already had someexperience of child-rearing. Obviously, leaving children at home alone while working was not child neglect
for the parents from the lower-class family. Their income was just enough to live from day to day, so
working outside of the house was directly related to their capacity to live, meaning the survival of children
at home. Children might die if the parents do not provide constant care; however, the end would be thesame if they do not work outside. Therefore, the determinant of the child mortality rate is depending onwhether the family has younger children or grandparents who can no longer work.
Moreover, Tables 5-6 and 5-7 depicted a positive correlation between the number of tatami per person
and child mortality rate. Although Model (4) could unfortunately not verify a significant result, this finding
was considered to support evidence that the households with a ‘babysitter’ have a lower rate of childmortality, as stated above.
Carbohydrate intake showed a positive correlation, but no observed significance. This was because thenumber of household members, utilized for calculating the amount of nutritional intake per person, and theinfant mortality rate possessed a negative correlation. Regression analysis using the total nutritional intakeof the household indicated a negative correlation, which was a convincing result. Regarding nutritional
status of households, further investigation would be necessary, for example, by employing indicators of theentire household, instead of per person.

Conclusion
We have examined the living standards and nutritional conditions of the households in the Saimin-chiku
area based on a survey conducted by the Hygiene Laboratory. Many of the households surveyed in Tokyo
City were considered poor, positioned in the bottom 20% of all households in the city, and 98% had
inadequate caloric intake. These findings can be confirmed by the menus of the households in the SaiminChiku area and households with pulmonary tuberculosis patients. While there were few households with asingle family member, most households comprised two or more adult men and women aged 21 or older.
Nearly half of the respondents suffered from some disease or health condition. Of those households inpoverty, the infant mortality rate tended to be lower for households with more family members. In contrast,
the infant mortality rate tended to be higher for households with a higher proportion of working family
12members. This suggests that childcare support mattered.
For couples in those households, pregnancy, childbirth, and parenting their children were a bet for life
with the hope of escaping poverty. When public assistance and social welfare for the poor were not yet inplace in Japan, all they could do was rely on the young labor force they had fostered on their own. Despite
the hope that children would grow up healthy enough to become part of the workforce, in many cases,
those couples often faced the loss of their children because they had to work hard and had little time orenergy left to take care of their children. The loss of children led them to a vicious circle in which they had
no choice but to give birth again. As a result, they must have sunk further into the swamp of poverty rather
than escaping from it.
Small farming households that emerged independently from the Yashiki residence communities in the
Edo period continued to live in separate houses while maintaining the commonality of consumer life. In
contrast, even among the lower-class households residing in the urban areas, we could see the reality thatthey lived based on the economy of mutual support. Unlike small farming households, which maintained
the commonality while having independent houses and the capacity to support themselves, lower-classhouseholds who shared the same kitchen with other households could not consume without an economy ofmutual support. It might also have been possible that sharing the kitchen kept the incidence ofgastrointestinal diseases at a lower level by sharing cooked dishes. The shared economy cannot be ignoredin considering poverty in the modern metropolis.
Despite numerous studies on lower-class people called Saimin, few studies have delved into the level ofnutritional conditions of their households. Whether in rural or urban areas, the primary living unit is the"family" or household; the household faces poverty. Like some researchers who emphasize the life-cycle
perspective in the household (or "family") in considering the farmer’s economy, it is essential to have ahousehold perspective in the analysis of urban areas.18 Of course, it is necessary to conduct research fromthe perspective of households while paying attention to the differences between rural areas.
Most recently Noriko Yuzawa reported that the eating space and daily life of workers at the Fukagawa
district in Tokyo c.1920s which was totally different from our case of Saimin district in this paper but there
are some issues related to gender division of labor and the difference of labor and living environment
between gender to consider in the next stage of research 19 . The case of laborers in Tokyo got theirautonomous system of food supply provided by their companies while the Saimin case had to secure theirfood supply by themselves.

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