"Income, Sanitation, Sharing, and the Weather: Infant Mortality in Turn of the Century Munich"

Abstract

The key to a continued decline in mortality in western Europe, GreatBritain, and the United States was a sustained decline in infantmortality. Most of this decline came about through a fall in mortalityfrom gastro-intestinal disease during the post neo-natal period. Theexperience of contemporary developing countries suggests the likelypaths by which transmission of diarrheal disease was reduced. Thispaper offers a micro-level analysis of the causes of infant mortality inMunich over the period 1890 to 1909. The analysis adopts ahousehold production approach to infant health as its framework. Theresults of the discrete hazard analysis suggests that weather conditionsand income were critical proximate influences on infant mortality. Acloser look at the decisions Munich households made about theimmediate environment suggests that housing conditions, particularlysharing toilet facilities and inhabiting apartments in more poorlyventilated sections of apartment blocks, exerted a powerful influenceon infant mortality.

John C. BrownDepartment ofEconomicsClark UniversityWorcester, MA 01610jbrown@clarku.edu

Note: Please do not quote or cite without the permission of the author.Clemens Wischermann of the University of Constance kindly provided muchof the data used in this study and the staff of the Munich City Archivesubstantially assisted collecting supplemental data. The German AcademicExchange Service and Clark University provided financial support. KavitaSethi and Irene Peters provided expert and careful research assistance. Seminar participants at the University of Munich, the University of Chicago,Northwestern University, the University of Connecticut, and HarvardUniversity provided many helpful comments on an earlier version of this paper.Young Sook Eom offered much helpful advice. All are absolved of any

1 See Woods, et. al.[1989: 114] for an example from the British doctor, Newsholme.

responsibility for the final product.Introduction

For most of the countries of western and central Europe, the key to the rapid decline in

mortality towards the end of the nineteenth century was the decline in infant mortality. Although

various conditions, including a series of hot and dry summers, may have masked the beginning of

the decline, by World War it was apparent that it was well underway in both England and

Germany. The decline in infant mortality was of key importance both for sustaining the decline

in general mortality that began in the last third of the nineteenth century. It was also critical for

the shift in the relative healthfulness of cities. Germany, in particular, experienced rates of infant

mortality that were far in excess of rates in much poorer countries such as Italy throughout the

period prior to World War I(Woods, et. al.[1988:349]). Indeed, at the turn of the century, no

other developed country of western Europe experienced such high infant mortality as Germany.

By the First World War, for example, Vögele[1994] has established that infant mortality in

middle- to large-sized German towns had fallen to such an extent that it was actually lower than

in small towns and rural areas. Figure 1 summarizes the decline for about forty-five larger

German cities with a population over 50,000 in the late 1880s. From an average of about 230 per

1,000 live births in the early 1890s, infant mortality remained relatively constant until the turn of

the century, when it began a rather precipitous decline. By 1912, it had fallen almost forty

percent.

Explaining Infant Mortality

Aside from offering a particularly example of dramatic mortality decline, the case of

Germany also highlights some of the key points at issue in explaining the decline in infant

mortality throughout Europe and the United States during this period. The excellent surveys by

Woods, et. al.[1989] and Vögele[1994] both offer the salient explanations that have appeared in

recent histories of public health and mortality. The answers to these questions typically stem

from catalogues of possible causes compiled by contemporary observers and later historians.1

2But note the argument of Fogel[1986, pp. 478-480], which links a potential decline in infantmortality strongly to a decline in neonatal mortality via an improvement in nutritional status.3See also the evidence in Koenig, et. al .[1990:260]. Very short birth intervals of less than twelvemonths, which are also very rare in historical populations, have also been found to have an influence(Pebley, et. al.[1994] and Curtis, et. al.[1993]).

The causal factors may be summarized as falling in three categories:

"� the frailty or initial endowment of health at birth

"� the potential exposure of the infant to infectious disease

"� the ability of the infant to resist disease or the ameliorative measures taken by parents to

cope with an ill infant.

A substantial literature has attempted to address all three of these issues, using both ecological

regression and individual-level data. Until recently, the general opinion based upon data on neo-

natal mortality from Britain, Germany, and Sweden was that post-neonatal mortality (essentially

after the first month of life) was primarily responsible for the decline in infant mortality after the

turn of the century (Woods, et. al. [1988], Spree [1995], and Lynch and Greenhouse [1994]).

Neonatal mortality would be most responsive to changes in the weight at birth and the incidence

of birth defects. Goldin and Margo [1989] and Ward and Ward [1984] found evidence for

relatively high birthweights among the infants of the very poor in Montreal and Philadelphia

during the mid- to late-nineteenth century2. In addition, some have argued that short intervals

between births would result in poorer health for the mother (maternal depletion) or reduce the

amount of resources available for the infant (sibling competition) (Knodel, et. al. [1991]). Once

appropriate controls are in place for birth order and family-level risks, Lynch and Greenhouse

[1994] find that this is not necessarily the case.3 More recently, Millward and Bell [2001] have

argued that the indirect influence of fertility and a proxy for maternal health (mortality from

tuberculosis) could have accounted for a substantial share of the decline in infant mortality over

the period 1870 to 1905, although the effect seems strongest on mortality from gastro-intestinal

disease. Given these results, efforts to explain the decline in infant mortality focus on the second

two influences.

Fundamentally, the attention paid to exposure and resistance stem from the knowledge

that the two chief causes of infant mortality (and contributors to its decline through the first few

decades of the twentieth century) were diarrheal diseases and respiratory diseases. Diarrheal

diseases appear to have been most important in urban Germany, parts of urban Britain, and many

cities in the United States. Overall, mortality rates from diarrheal diseases ca. 1910 ranged per

1,000 live births ranged from 62 per in German towns and 40 in Prussia, 10-20 in British towns

and in the countryside, and 26 in the cities the United States Registration area. Respiratory

diseases mortality rates were much more similar in cross-national comparisons: about 23 in

larger German cities and 19 in Prussia as a whole, about 20 in British towns, and about 15 in the

cities of the U.S. registration area. Clearly, cross-sectional (and much of the time series) variation

in infant mortality could be traced to differences in mortality from diarrheal disease (Rochester

[1919, pp. 59-63]).

Explaining the proximate causes of infant mortality differentials is of interest in its own

right. An explanation of what accounts for the differential also bears on an important debate in

the history of mortality decline initially ignited by McKeown [1976] with counter-arguments

presented by Szreter[1988 and 1997] and Johansson [1994]. At the risk of oversimplifying the

arguments, the role of public health interventions � their source and their

contribution � continues to play a central role in debates. The Szreter-Johannson view

emphasizes the importance of reduction in exposure to disease risk, including for infants. In the

strongest formulation presented by Szreter [1997], the knowledge available to governmental

decision-makers (in Britain) by the last third of the nineteenth century was a sufficient basis for

action. What was lacking was the appropriate alignment of political interests.

Although its thrust is distinct from McKeown �s, a new view that echoes the teachings of

the � New Public Health � movement of the early 1920s and later emphasizes the importance of

changes in private-decision-making (and perhaps the resources available to individual decision-

makers). Ewbank and Preston [1990], Mokyr and Stein [1997], [Mokyr[2000] present successive

refinements of this alternative view. Ewbank and Presont argued that the decline in infant

mortality was primarily the result of the diffusion of new methods of infant and child care

4See Newsholme[1910: 70-74]. See also the comments by the county health officer (Bezirksarzt)Schirmer [1911], who argued that � mothers have very little knowledge concerning the feedingand care of their children. �5These notes are from the � Berichten auf den Runderlaß vom 16. Juni 1908. �

consistent with the precepts of the germ theory of disease. Most of these new practices would

have reduced the exposure of infants to infectious disease, either by maintaining a cleaner home

environment (and swatting flies) or by ensuring that the infant received wholesome,

uncontaminated nutrition. These methods included the kinds of practices now taken for granted,

but apparently not practiced by many mothers and fathers under the scrutiny of local public

health officials, physicians and � lady � visitors to the homes of lower-income families. The most

general concern was overcoming what was labeled the � Ignorance and Fecklessness of

Mothers. � 4 Although mothers may have wished to � secure the welfare of their offspring � , as

Newsholme so succinctly puts it, their ignorance about the appropriate approach to infant care,

including their lack of understanding of the germ theory of disease, made it difficult for them to

make informed decisions. Concern was placed on were improving the quality of infant feeding,

either through encouraging breast feeding or providing for supplies of clean milk. Accounts

collected for an inquest into infant mortality conducted in 1908-1909 in Prussia offer a theme

that reappears in reports of local physicians in Bavaria. Even while still being nursed, infants

were fed food from the table (chewed up by adults for easier consumption!) and were given

cow �s milk from bottles with dirty nipples.5 Filthy pacifiers were also apparently widely used.

The proper care of milk was also a main concern, particularly keeping it cool during the summer

months. Keeping flies away from infants and keeping infants cool during hot months were also

changes in behavior that were recommended ( � Flugblatt zum Schutz der Säuglinge � ).

Efforts to assess these perspectives quantitatively have lagged behind the actual debate.

Two kinds of evidence are drawn upon to evaluate these proposed explanations, but there is still

not any overall consensus. Most of the methodological innovation has been focused upon

overcoming the limitations of the first approach, which simply looks at correlations taken at the

same time across geographic units of observation or social classes. The problem with this

approach to analysis is well known, since it fails to control for unobserved hetereogeneity in

cross-sectional units of observation. The direct impact of certain influences, such as income, may

explain much of the cross-sectional variation in infant mortality without being able to account for

the rapid decline over time. Multiple regression implementations of this approach have identified

candidate influences that may have been important at a particular point in time and that may have

changed rapidly over the period of the initial decline, such as the level of education of

women(Woods, et. al.[1989]). Individual case studies of cities (or countries) attempt to get

around this problem with their focus on the timing of changes in one of the commonly-accepted

potential explanations and then assessing whether it may or may not have occurred

simultaneously or prior to the decline in infant mortality.

The alternative approaches (Kinter[1982], Brown[2000] and Milward and Bell [2001])

employ both the cross-sectional and the time series data used in earlier studies, which allows for

some controls of unobserved hetereogeneity provided appopriate panel methods are used. These

studies of district- or town-level data also impose another constraint on results, since they focus

on the causation of mortality from two kinds of disease (diarrheal and � other � ) as well as

examining births to married mothers and extramarital births. As noted above, Kinter �s results

emphasize the importance of infant feeding practices and fertility behavior. Brown finds that

earnings of women were positively associated with the decline. Sanitary conditions (water closets

and piped ground water) negatively influenced infant mortality, but the impact of a full program

of reform implies only about one-third of the reduction. Efforts to influence the behavior of

mothers were also positively associated with mortality decline, but they would only account for

about one-quarter of the actual change. As noted above, Milward and Bell revive a nutrition- and

resource-based argument. The key to infant mortality decline in Britain was the improved health

of the mother (proxied by the decline in tuberculosis mortality), which in turned was prompted

by a reduction of fertility and improved nutrition arising from improvements in living standards.

Unfortunately, the aggregated data used in their study does not allow for an identification of

actual causal links.

Modeling Household Decision-Making

6Note that this simple formulation avoids any consideration of the allocation of time within the householdto health- or income-enhancing tasks. Nor does it allow for an examination of the question of householdallocation of X (which would include food). See Mokyr[1993] and Weir[1993]. Finally, the simpleversion of the first order conditions (1)-(3) imply that the goods purchased primarily as inputs into healthdo not offer additional direct consumption benefits to the household, which in many cases may not beeasy to demonstrate.

The perspective of Wolpin[1997], which informs his critique of statistical studies of the

determinants of infant and child mortality, is helpful here. The � new public health � view of

mortality decline emphasizes the importance of parental decision-making in causing both high

infant mortality at the onset of decline and in explaining subsequent mortality decline. The

proximate etiology of high infant mortality � high levels of diarrheal disease � is well-known, but it

is still uncertain how important household choices may have been in influencing mortality

outcomes. To think about household decisions, it is necessary to introduce a simple model of

choice that identifies both the potential tradeoffs households may have faced as well as some of

the (exogenous) influences on mortality. The model suggests an appropriate direction for

statistical estimation.

Suppose that the household has a utility function U(X,H), where X is a composite good

and H is the household's consumption of health(or low mortality). In turn, H=H(Z1, Z2,e), where

Zi is a purchased input to the household health production function and e is any exogenous

influence on mortality. In the case of infant mortality, e may include both the general level of

exposure in the environment as well as influences (high summer time temperatures, for example)

that influenced mortality.6 Zi may be any range of household goods, including soap, a clean

water supply, etc. Of course, HZ>0 and HE<0. If household income I=X+P1Z1+P2Z2, the first

order conditions for an optimum are as follows:

Together, they imply the indirect utility function, which is a function of Y, E, and the prices of

the inputs to the health production function:

Differentiating V(øP) with respect to the prices of the inputs to the health production function

yields the demands for inputs into health. Those inputs could be infant formula, soap, or renting

an apartment with adequate sanitary facilities. Actual health outcomes are thus

The literature on infant mortality suggests two important issues that arise from the household

production approach.

Mokyr[1997 and 2000] argues that an important component of the decline in infant

mortality was the gradual diffusion of the actual understanding of the � true � production

relationship H("�). It may be necessary to multiply H("�) by the function h(Kt), where Kt is the best

practice knowledge about mortality causation and h(Kt) approaches one. This suggests rewriting

equation (5) as

It is also possible that the impact of � fecklessness � may not be so straightforward. Low values of

K could actually distort the choice of Zi. The admonition against smothering the infant in

featherbeds during all seasons (including hot and dry periods of the summer months) that is

found in several accounts suggests that inadequate knowledge could lead to a striking

misallocation of household resources. As Wolpin [1997: 527-528] points out, what is of

importance is measuring the impact of the inputs, not necessarily the prices or the financial

resources (income) that allowed the purchase of the inputs.

Two other considerations introduce potential sources of error in recovering the actual

health production relationship (and understanding the actual causal factors leading to infant

mortality decline.). Rosenzweig and Schultz [1983] and Wolpin [1997] note that as soon as the

health of the is understood as the outcome of dynamic decision-making, two additional sources

of error are introduced. First, there will be unobserved hetereogeneity among families in their

ability to provide care for infants. To the extent that hetereogeneity influences behaviors that

affect health or mortality outcomes, the family could attempt to offset the risk. For example,

knowledge that the family has experienced high rates of infant deaths for specific to the family

but not a result of family behavior could prompt more attention to infant care or take measures to

ensure longer birth intervals. Of course, the measured impact of the observed behavior (the

longer birth interval, higher standard of housing) would be biased downwards because of the

correlation of the (unmeasured) risk and measure. The other potential source of bias will occur

during the early life of the child, as the family may update its choices in response to observed

potential risks. For example, it was well known in the United States, Britain, and Germany that

periods of hot and dry weather during the summer months significantly increased the risk of

infant death (most of the time because of diarrheal diseases)(Huck[1997] and Vögele [1994]).

Family behavioral responses to these (unmeasured) risks will affect also health outcomes and the

measurement of the efficacy of the choices of the Z-goods.

Finally, during the early period of infant mortality decline the question is still open about

the extent to which biological influences on infant health (the interval between births, the age at

birth of the mother, perhaps the birth order of the infant) reflect the outcome of conscious-

decision-making or stem instead from long-standing practices that were only giving way to

modern fertility control. This issue can not be definitively addressed here, but it suggests that a

more comprehensive perspective on the decline in infant mortality should take into account the

potential for interaction between fertility and infant mortality. For reasons already noted, these

biological influences would seem to be most important for the survival of the infant in the first

weeks of life (neonatal survival) rather than survival during the post-neonatal period.

Approaches to Estimation

Recognizing that some of the most important risks to an infant during his or her first year

7See the discussions in Vögele [1994] and in Rochester [1919].

of life varied over the course of the year, this study models the health outcome (H("�)) as a

discrete hazard function hi In discrete time (where i is an interval of one month),

hi =Pr(Death over interval i|Surviving to the beginning of i). Efron [1988] describes the a basic

approach to estimating discrete hazard functions of this kind using logistic regression. The

discrete hazard specification has two important advantages. First, it allows for the explicit

inclusion of the most important shocks to infant mortality during the late nineteenth and early

twentieth centuries: extremes of temperature or precipitation. As Figures1 and 2 suggest, these

shocks had differing impacts depending upon the time of year and the age of the infant. Figure 1

graphs the monthly infant mortality for Munich in 1911 and Baltimore in 1915 for the two most

causes: gastro-intestinal diseases and respiratory diseases. Despite the fact that infant mortality in

Munich for all births (both to married and unmarried women) was in excess of 200 per 1,000, or

about twice the rate in Baltimore, both cities showed the classic � summer peak � in infant

mortality common to most urbanized areas in Germany and the United States.7 This peak was

associated with particularly high temperatures and dry spells. Less pronounced was the

heightened risk of respiratory infections during the winter months. Wet weather would increase

the risk.

Another important feature of the discrete hazard specification is the ability to estimate the

functional form for the hazard in a flexible manner as a function of elapsed time. For example,

the hazard may vary with a cubic transformation of elapsed time. Efron [1988] derives a

straightforward Chi-Square test statistic that allows for a formal test of the functional form of the

hazard. This study used a two-step approach to estimating the hazard function. As Figure 2,

which compares the hazard rate for two main causes of death and overall, the hazard of an infant

death declined dramatically in both cities after the first month. In Baltimore, most of the decline

was the drop in the risk of gastro-intestinal diseases. In Munich, a major cause of death for neo-

nates was Lebenschwäche neugeborenen Kinder, which was eventually reclassified under gastro-

intestinal diseases. When this cause is included with the other gastro-intestinal diseases, the

profile of the hazard rates in Munich looks quite similar to the profile in Baltimore. In both cities,

hazard rates decline rapidly from the first to the second and third months and continue to decline

thereafter. Perhaps what is most striking is the fact that the hazard rate of dying from a gastro-

intestinal disease in Munich during the second and third month of life was eight times the rate in

Baltimore. Some of the differential was because of the particularly high rate of neo-natal

mortality among infants born to unmarried mothers. Almost one-third of births in Munich at the

turn of the century was to unmarried mothers. Whether the high mortality for all infants was

primarily a result of the low rates of breastfeeding or other factors is an issue that will be

examined further in the statistical analysis. Evidence from Groth and Hahn [1910] suggests that

by the end of the first month of life, about two-thirds of infants in Munich were not being breast-

fed. The statistical analysis essentially estimated two hazard functions: one for neo-natal deaths

(essentially a logistic analysis) and another for post neo-natal deaths. The estimation allowed for

a test of the appropriate functional form for the second subgroup.

Finally, the specification of the housing health production relationship focused on the

potential influence of housing conditions upon infant survival. Datasets providing detailed

information on consumption information (i.e., purchases of potential inputs to infant survival) are

extremely rare for the turn of the nineteenth century. One exception are data that provide

information on housing consumption, since there is a clear reason to believe in a link between

housing conditions and health.

Turn-of-the-century assessments of the contribution of housing conditions to mortality

focused on overcrowding as an important source of tuberculosis and poor ventilation as a

principal cause of summer diarrhoea(cholera infantum) of infants. But the age-old concerns with

the quality of sanitary facilities cropped up as well in studies carried out in Britain, the United

States, and Germany. Housing inspectors argued that the tenants continued to require instruction

about the rules of "healthy care of the home". In particular, attention needed to be paid to the

condition of toilets for both moral and health reasons(Frening[1911: 487]). Newsholme[1910:63-

68], a several-year study of infant mortality in Great Brtain based upon the reports of municipal

health officers, underscored the importance the introduction of � water carriage of waste � for

12

reductions in infant mortality. Hibbs[1916: 98-99] in his review of the conclusions of the

pioneering United States Children Bureau investigations of the influence of "social" conditions

on infant mortality reached similar conclusions. Housing conditions, which reflected in his view

primarily the resources available to the tenant, had noticeable influences on infant mortality rates.

Households without access to a water tap or without flush toilets experienced much higher rates

of infant mortality than others. Dempsey[1919:43] noted the relationship between families

sharing toilet facilities and higher infant mortality rates. The source of the problem lay in the

division of responsibility for keeping the toilet clean: � as one mother expressed it, �what is

everybody �s business is nobody �s business � �

The links between sanitation and health were key conclusions of the various housing

enquiries conducted in Germany conducted by the local insurance funds(Sachße and

Tennstedt[1982]). Typically written at the request of the administrative boards of the funds that

included substantial working class participation, the reports and the accompanying photos were

widely disseminated. The 1901 report of the Housing Enquete of the Berlin local insurance fund

for clerks noted, for example, that one-third of the sick individuals investigated by lived in

housing where they shared toilet facilities with fifteen or more people. It declared "this is an

immeasureable danger for the population"Kohn[1902: 23]; emphasis in the original). The

1902 report noted as well that

Common toilets for several households are rightly known as a source of severe problems.

They pose the danger of the transmission of disease, not to speak of the problem that a

large number of users reduces cleanliness(Kohn[1903: 25]).

These insights are consistent with what is now known about the role of sanitary

conditions in the tranmission of gastro-enteritis today. Until the early 1990s, gastro-enteritis was

still generally thought of as a water-born disease. A spate of research on the transmission of

diarrheal disease during the 1990s has established the importance of household sanitation

practices, particularly the disposal and treatment of human waste (VanDerslice [1995]). Curtis,

et. al.[2000] provide a nice summary of this literature.

8I am grateful to Dr. Paul Rufo of the University of Massachusetts Medical School for theseinsights.

13

Contamination with fecal matter provides a ready path for transmission, and the spread is

exacerbated by lack of adequate clean water. Figure 3, which is taken from Curtis, et. al. [2000]

illustrates the potential paths of transmission. Infant diarrhea arises from ingestion of a variety of

viruses and bacteria, which can be present in fecal matter. For the period and places under

consideration (19th and early 20th century urban Europe and the United States), the main paths of

transmission are highlighted by dark arrows. Transmission typically takes place either through

direct contact between the fingers or infected fluids (some practices in handling infant waste

promote this) or indirectly through foods, which can then be consumed by the infant. There are

two main strategies for preventing contamination. The first is isolation of fecal matter in an

enclosed privy or a flush toilet that is separated (indicated by strategy 1). The provision of sewers

(and flush toilets) has long been thought of as an essential part of this strategy, but it appears that

significant reductions in diarrhea can be achieved by isolating waste through the use of enclosed

privies. Successful isolation also requires that hands be washed to prevent the next step of

potential transmission. If hands are not washed, or waste is improperly disposed of (for example,

left in a yard), transmission into the environment is highly likely.

That leaves two additional potential points for intervention. If hands are not washed,

potential contamination via food is a substantial risk. Breast feeding (2) inadvertently also

prevented (or reduced) the risk of ingesting pathogens, even if the environment itself were

contaminated. Most studies conducted during the early 20th century and today have found

significantly lower rates of diarrhea among infants who are breastfed. The potential

contamination of the environment with pathogens also helps explain the summer peaks in

diarrheal disease.8 Warmer temperatures will in general promote growth of bacteria (and viruses).

Some bacteria (shigella) require a threshold concentration before they can actually cause harm. In

addition, bacteria present on stored food could multiply much more rapidly during warm

temperatures, although convincing evidence is still lacking over whether this potential source of

9Other diseases, such as trachoma (and perhaps polio) reflected the absence of hand-washing.

14

higher diarrhea is actually important (Curtis, et. al. [2002]). Any conditions of housing, including

poor ventilation in large apartment blocks, could lead to inadequate cooling during periods of hot

weather. The masonry construction used in most continental European cities (as opposed to the

United States and Scandinavia) also allowed for the gradual storing of heat. A stretch of warm

(and dry) weather would lead, with a lag, to increases in infant diarrhea.

Finally, the presence of plentiful soap and water is critical for the third intervention,

which is washing hands before preparing food and before handling the infant (3). Even in urban

areas, the availability of plentiful and inexpensive water in developing countries continues to be a

severe problem. By 1900, it was much less of a problem for urban areas in western Europe, the

United States, and Great Britain. Whether households also took advantage of the supplies of

water (and less expensive soap) to wash hands regularly is an open question.9

Table One provides evidence on the potential role of housing conditions in promoting

high rates of infant mortality in urban Germany ca. 1900. Most residents of larger German cities

had access to piped water on-site by the turn of century. However, as Table One suggests, the

ability to apply strategy 3 (hand-washing) may have been limited for a significant share of

residents of Augsburg and Nuremburg, where acceess to water supply was only in the courtyard

of the building. Apartment blocks could include ten or twenty apartments on three or four floors;

the trip to the water faucet in the courtyard could be significant. Other features of the home

environment were more suspect. Most homes in the small factory town of Lechausen (near

Augsburg) lacked access to flush toilets. Most households in much larger cities continued to rely

upon privies rather than flush toilets, despite the presence of sewer service. This anomaly

resulted from the initial unwillingness of authorities in many German states to allow untreated

sewage to be dumped into nearby lakes or rivers. Finally, another feature of housing that may

often be overlooked was the sharing of toilet facilities. As noted above, keeping toilets clean

(particularly privies) could have posed significant difficulties. Use by two or more families

multiplied the potential exposure to fecal matter and the transmission of pathogens. Exclusive

10Note that the family is defined here by the husband. Mortality of women in their child-bearingyears was high enough in Munich so that a second or third marriage following on the death of a

15

use of a (designated toilet) was still somewhat of a luxury, particularly in older buildings and

smaller towns such as Lechausen.

Data

This analysis of the impact of inputs to infant mortality draws upon two unique data

sources that are available in the Munich City Archive. By 1910, Munich had grown to be

Germany �s third largest city (after Hamburg and Berlin). Its infant mortality rate was fifth- or

sixth-highest among the 50 largest German cities as late as 1900. By 1912, the improvement to

be seen in Figure 4 had moved it toward the median of the distribution. The economic structure

of Munich was also quite diverse, with a large sector manufacturing woodworking products,

leather, and clothing, a large food-processing industry (including beer), and a large machine-

making industry. It was also the regional capital for the relatively well-off farming economy of

southern Bavaria (Upper Bavaria).

The first data source available in the Munich City Archive, the Polizeimeldebögen, or

PMB, is a collection of police registration records providing continuously updated information

on the demographic behavior and experience of most residents of Munich for the period 1867

through about 1909. Described in more detail in Lupprian [1994], the data source also includes

substantial detail about the background of both husband and wife, occupations, and taxes paid

(including income taxes). Brown, et. al.[1993] report the results of various tests for the accuracy

of reporting births and deaths. The PMB source shares a problem common to many historical

sources: stillbirths are under-reported. Otherwise, the reporting of high rates of neonatal mortality

suggests a pattern that is consistent with published information based upon actual birth and death

certificates. The median interval in this sample is about 21 months, which is consistent with

Knodel �s data from German villages during the last quarter of the nineteenth century (Knodel and

Wilson [1981, Table 9].

Table Two provides information on the distribution of infant deaths in the Munich

sample. The information is summarized by the family-specific infant mortality rate.10 As is the

spouse was not uncommon. In this sample, about ten percent of infants were born to the secondwife of a husband.11I am grateful to Dr. Clemens Wischermann of the University of Constance (Germany) whoprovided much of the manuscript material. The data were supplemented with additionalobservations. The data is found in the collection Wohnungsamt, Erhebungsbögen of the MunichCity Archive.

16

case in many other historical populations, the distribution of infant deaths in Munich was

profoundly unequal. Keeping in mind that fertility histories for many of these families were

incomplete, it is nonetheless striking that two-thirds of the families experienced no infant deaths

and 30 percent experienced rates of mortality in excess of 200 per 1,000. Certainly features that

were particular to certain families must have played an important role.

The other source of data used in this study is from the manuscript census forms of the

Munich Housing Census of 1904-1907. Undertaken in an effort to provide a comprehensive

appraisal of the state of Munich �s housing stock prior to a setting up a system of housing

inspection, the census took a detailed look at both the external structure of buildings, including

the kind of sanitary equipment, electricity, and gas service. The survey also measured all rooms

in apartments of five or fewer rooms, noted with particular thoroughness the details of sanitary

and sleeping arrangements, and provided copious comments on conditions note otherwise noted

on the census form. Wischermann[1985] provides an extended discussion of the source.11

The housing census forms also included the name and occupation of the current resident of the

apartment. Because of constraints on the time of archive personnel, the registration records for only

about 390 of the inhabitants of the original sample could be located. Of these households, about 237

included some births occurring in the period 1890 through 1909. Data for another 25 households was

identified for another study on job-to-job mobility in Munich. Housing census records were

found for these as well. The total number of births suitable for data analysis is about 760.

The sample was partitioned further into two groups: those for whom contemporaneous

information was available on housing was actually available (132 households with 212 births)

and the remainder. The inner-urban mobility of Munich residents made matching households

with housing data a challenging task. The median stay was 5.7 years for matched households, and

12The data are found at the German Wetterzentrale website:http://www.wetterzentrale.de/klima/index.html

17

one-quarter of the time of residence was under three years. For most families, the period in which

they inhabited the apartment for which data are available covered only a share of the fertility

history. It should be noted that even a stay of five years was unusual for younger couples. For all

apartments in Munich, the median length of tenancy was closer to two or three years.

The other variables used in the analysis include indicators of biological influences on

mortality risks, including the length of the previous birth interval, the birth order, and the age of

the mother at birth. It is usually expected the higher order births face higher risk of mortality than

lower order births. For reasons discussed earlier, a longer birth interval is indicative of a smaller

family size and allows the mother more time to recovery physically between births. Very young

and older mothers are more likely to bear children with low birthweights (and a higher risk of

mortality). The weight of the arguments in the literature suggests that these biological influences

should be most important for neo-natal deaths.

The literature also suggests that extremes of weather should constitute measurable shocks

to health production function. Candidate variables included the temperature and the amount of

rainfall. Experimentation suggested that variables measuring extremes of precipitation had the

most potential impact on infant mortality. The variable � Dry � took on a value of one when the

average monthly temperature exceeded 17 degrees Celsius. It was equal to zero for the first three

months of life. The variable wet took on a value of one when the average monthly rainfall

exceeded 200 cm. The data were collected at Munich-Riem (the site of the former Munich

airport).12

Finally, three variables measured either the resources available to the family (predicted

income) or the actual inputs into infant health found in the health production function (three

kinds of housing conditions.) Data on income taxes paid were available for about one-half of the

sample. The (median) income over the period for which fertility histories were available was

regressed on a vector of occupational dummy variables. The predicted income from this

13Exact calculation of the median income for Munich is not possible from the data on incometaxes paid, since a good number of potential taxpayers was exempt from income taxation becauseof ownership of a business.14The test is a �Ç 2 test with 8 degrees of freedom for the first subsample, and the test statistic for asignificant deviation from the actual hazard was 5.2 for both the linear and the quadraticspecifications. The �Ç 2 test statistic for the housing subsample was 17 with 11 degrees of freedomfor the linear specification and 7.9 for the quadratic specification. For both chosen specifications,the hypothesis of a significant difference between the actual and fitted values could be rejected atall conventional levels of significance.

18

regression was used for the remainder. Housing inputs that mattered to infant health would be

whether or not the family used a privy vault toilet, the number of households with which it

shared the toilet facilities, and whether or not it occupied a rear or side building in a larger

apartment block. All three of these variables would be expected to increase the hazard of dying

during the first year of life. Table 3 provides the definition, mean, and standard deviation of all of

the variables used in the analysis. Table Three provides a summary of the sample statistics for the

two subgroups of the data.

Results of the Statistical Analysis

The first step in the statistical analysis was estimating the appropriate specification of the

time dependence of the hazard. The results of alternative specifications are presented in Figure 5

for both subsamples. As is apparent from the graphs, the sample information replicates the

pattern of the hazard implied by the data available for the population as a whole, although the

hazard rates for the first few months of life are lower than for the population as a whole (in

1898), which are reproduced in Figure 2. Much of the differential is accounted for by the

inclusion of births to married and unmarried mothers in Figure 2. The other source of the

differential could be accounted for by the higher average income of the sample compared with

Munich as a whole. The median of 1,300 Marks in the sample is well above the actual median

income in Munich at the time, which was about 950 Marks ca. 1900.13 In any event, the graph

and the statistical tests suggested by Efron [1988] imply that the appropriate specification of the

hazard was linear in time for the first subsample and quadratic in time for the second

subsample.14

Tables Four and Five present the results of the statistical analysis. Consider first the

19

estimation of the causes of neo-natal mortality. Consistent across both samples, twins faced a

much higher probability dying during the first month of life compared with single births. The

birth order was the only other variable that consistently predicted a lower risk of mortality. The

subsample with information on housing (in which the median birth was also 1904) showed a

stronger influence of the mother �s age, birth order, and the log of predicted real income. The

Impact of the log of income was particularly strong on neo-natal mortality. The risk of dying in

the first month of life from the sample data was 0.06. An increase in income from 1,000 Marks to

2,000 Marks would have reduced the risk of dying substantially.

The results from Table 5 are even more instructive about the role of housing choices (the

choices of � inputs � to the health production function.) For both subsamples, the biological

variables (birth order, the length of the prior birth interval, and the age of the mother) jointly had

very little influence on mortality outcomes. Instead, the main focus of attention must be on the

role of whether-related shocks, income, and housing choices. Both abnormally dry periods and

abnormally wet periods increased the risk of infant death, although the impact was most

pronounced in the subsample without housing information. The average of the (monthly) hazard

in the fifth month of life with average conditions was about 0.008. Moving the household into a

crowded and poorly ventilated back or side building would have increased the hazard at the

fourth month from 0.008 to .04 or more (i.e., a more than tripled it). Increasing the number of

households using the toilet facilities from one to two would have increased the hazard of infant

death by 50 percent. These impacts mirror the impacts estimated for income. A reduction in

income from about 1,500 Marks (an income earned by a successful skilled worker) down to the

earnings of a day laborer (about 800 Marks) would triple the hazard of infant mortality during the

fifth month of life.

Conclusion and Extensions

The overall impact of the thrust of the statistical analysis is clear. The key proximate

determinants of variation in infant mortality during the period before the First World War were

unusual weather (the dry spell measures only the extreme upper five percent of the temperature

distribution, for example) and differences in income. The � biological � influences on mortality

20

played a secondary role. In reality, the proximate influences actually mask the importance

household decisions on where to live. The Munich housing market actually granted substantial

discounts to those willing to share toilet facilities with another household and those willing to

live in the more poorly ventilated back or side buildings of large apartment blocks. Those

discounts could average 10 or more Marks per month, or a savings of 120 Marks over the year.

For a family struggling to live on an income of only 800 Marks, that could represent substantial

savings in housing costs.

Understanding what influenced the demands for housing is the next step in an attempt to

appraise the importance of household decision-making for infant mortality decline. Three

changes between the early 1900s and the late 1920s, when the summer peak had disappeared will

complicate the analysis. Munich mothers decided to increase breast-feeding substantially, so that

by the late 1920s/early 1920s, a substantial share was relying upon � mother �s milk. � In addition,

Munich initiated a program of housing inspection to curb the worst violations of new housing use

codes, which included provisions on the maximum number of households permitted to share

toilet facilities. Older housing that had the worst sanitary conditions was also being torn down.

Finally, the efforts to disseminate � propaganda � and advice about the proper care of infants and

maintaining higher standards of hygiene in the home gained a strong impetus from declining

birthrates and concerns about saving infant lives (to serve at a later date in the army!). A

complete explanation of mortality decline will need to take account of these changes as well.

21

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Figure 1Infant Mortality by Month in Munich and Baltimore

Source: Munich [1899] from register data and Rochester [1919, Table 50].

Notes: The hazard is the probability of an infant death from the causes identified over the course

of the period (conditional upon having survived to the beginning of that period). The hazard

applies to all births. The � Gastro-Intestinal + Weakness � shows the effect of classifying deaths

from Eingeborene Lebenschwäche as gastro-intestinal disease. See Vögele [1994].

27

Figure 2The Hazard of an Infant Death by Four Periods

Source: Munich [1899] from register data and Rochester [1919, Table 50].

Notes: The hazard is the probability of an infant death from the causes identified over the course

of the period (conditional upon having survived to the beginning of that period). The hazard

applies to all births. The � Gastro-Intestinal + Weakness � shows the effect of classifying deaths

from Lebenschwäche as gastro-intestinal disease. See Vögele [1994].

28

Figure 3

The F-Diagram: Paths of Transmission of Infant Diarrhea

Source: Adapted from Curtis, et. al. [2000, p. 25].

Notes: The numbers refer to potential interventions. For an explanation, please see the text.

29

Figure 4

Infant Mortality in Munich, 1891-1912

Source: Statistisches Jahrbuch Deutscher Städte, various years.

30

For Subsample without Housing Data

For Subsample with Housing Data

Figure 5Actual and Predicted Hazard Functions for Alternative Specifications of the

Time Dependence of the Hazard

Source: Estimation of discrete hazard models with random effects logit.

31

Table 1

Housing and Sanitary Conditions in German Cities Ca. 1900

Sanitary feature Munich

1904-07

Augsburg

1904

Düsseldorf

1905

Leipzig

1910

Lechausen

1908

Nuremburg

1901-02

Water supply in

courtyard only

4 37 NA NA NA 20

Sewer

connection

90 85 NA NA 3 90

Privy 20 98 79 75 100 98

One household

per toilet

52 41 44 72 22 67

Three or more

households per

toilet

8 40 25 NA 54 14

Source:Rost[1906]; Buechel[1907]; Munich housing census sample; Grundstücks- und Wohungszählung[1907]; and Statistisches Amt

der Stadt Leipzig[1914].

32

Table 2

The Distribution of Infant Deaths in the Munich Sample

Infant mortality rate in

deaths per 1,000 live births

Percent of families

0 67.2

1-199 3.8

200-399 9.8

400-599 10.0

600-899 2.6

900-1000 6.0

Source: Munich sample.

Notes: The rates apply to families headed by the same husband. Children born to a second or

third wife are counted as belonging to the same family as children born to a first wife. There are a

total of about 260 families in the dataset who had births in the period 1890 through 1909.

33

Table 3

Variables and Descriptive Statistics

Variable Mean Standard Deviation

First in birth order 0.25 0.43

Interval for birthorder of 2

or higher (in years)

1.84 2.01

Birth order is 6 or higher 0.18 0.39

Twin 0.035 0.184

Mother � s age 30.5 6.45

Dry 0.03 0.17

Wet 0.03 0.16

Real median income (in

Marks of 1913)

1,514 1,036

Number of households

sharing toilet facilities

1.77 1.13

Privy vault toilet 0.20 0.39

Rear or side building 0.12 0.33

Source: Munich housing and demographic dataset. See the text for further description of the

variables.

34

Table 4The Causes of Neo-Natal Mortality in Munich: 1890-1909

Independent Variable Subsample without

housing information

Subsample with housing

information

First in birth order -1.317(0.71)

-1.76(1.61)

-1.60(1.60)

Interval for birth order 2 or higher -0.083(0.139)

0.026(0.26)

0.045(0.26)

Birth order is 6 or higher -0.510(0.70)

1.64(0.90)

1.55(0.91)

Twin 2.040(0.62)

3.75(1.13)

3.197(1.18)

Mother � s age 0.003(0.04)

-0.229(0.078)

-0.206(0.077)

Dry -0.399(1.05)

Wet 0.034(1.05)

1.087(1.11)

1.67(1.22)

Log of predicated real medianincome

0.035(0.97)

-2.447(1.96)

Number sharing toilet facilities 0.46(0.31)

Privy vault toilet 0.74(0.95)

Constant -5.12(6.98)

21.07(14.53)

�Ç 2 test for significance 18.7 (9 DF) 29.7 (8 DF) 29.5 (9 DF)

Number of births 512 190 169

Source: Results of logistic estimation.

Notes: Asymptotic standard errors are in parentheses. Observations in the subsample with

housing information were dropped because of perfect collinearity with the dependent variable.

35

Table 5The Causes of Post-Neonatal Mortality in Munich: 1890-1909

Independent Variable Subsample withouthousing information

Subsample with housinginformation

First in birth order -0.73(0.44)

-0.61(0.76)

-0.29(0.78)

Interval for birthorder 2 orhigher

-0.164(0.087)

-0.073(0.17)

-0.059(0.15)

Birth order is 6 or higher 0.085(0.32)

0.042(0.59)

0.135(0.65)

Mother � s age 0.068(0.189)

-0.042(0.05)

-0.055(0.55)

Dry 1.59(0.40)

0.99(1.07)

0.69(1.11)

Wet 1.059(0.43)

0.54(1.07)

1.210(1.10)

Log of predicated real medianincome

-1.667(0.64)

-2.09(1.05)

Privy vault toilet -0.001(0.69)

Number sharing toilet facilities 0.461(0.156)

Building in back or on side of lot 1.85(0.52)

Month (t) -0.165(0.044)

0.411(0.37)

0.54(0.38)

Month2 (t2) -0.051(0.03)

-0.056(0.034)

Constant 6.992(4.48)

11.41(7.83)

-5.046(1.95)

�Ç 2 test for significance 59.5 (9 DF) 12.8 (10 DF) 33.3 (12 DF)

Total periods of observation 4,914 1,827 1,827

Number of births 499 179 179

Average duration (in months) 9.8 10.2 10.2

Source: Results of estimation of the discrete hazard function using random-effects logit.

Notes: Asymptotic standard errors are in parentheses.