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The health transition and biological living standards: Adult height andmortality in 20th-century Spain§,§§

Jeroen J.A. Spijker *, Antonio D. Camara, Amand Blanes

Centre d’Estudis Demografics and Department of Geography, Universitat Autonoma de Barcelona, Spain

1. Introduction

The health transition theory was elaborated with theaim of linking sanitary, socio-economic, cultural, andbehavioral changes to successive epidemiological transi-tions as societies evolve from a mortality pattern

dominated by infectious diseases and a low life expectancyto one dominated by degenerative diseases and a high lifeexpectancy (Caldwell et al., 1990; Vallin, 2007). Health anddisease are therefore determined in a multi-causalmanner, whereby health status is the outcome of thebalance between exposure to disease agents and individualsusceptibility resulting from a complex network of risks.

The transition from one epidemiological phase to thenext therefore not only signifies a change in mortalitystructure but also implies a change in the prevalence andtype of disease determinants (Olshansky and Ault, 1986).In the industrialized world, the mortality pattern isdominated by old-age mortality from chronic diseaseslinked, for the most part, to adult risk factors associatedwith adulthood, such as smoking.

However, research has also shown that adults’ diseaserisk is the result of exposure to a range of biological, social,and behavioral factors throughout their entire lifetime,

Economics and Human Biology 10 (2012) 276–288

A R T I C L E I N F O

Article history:

Received 16 July 2010

Received in revised form 2 August 2011

Accepted 2 August 2011

Available online 9 August 2011

JEL classification:

I10

J10

N00

O00

Keywords:

Cohort height

Infant mortality

Health surveys

Health transition

Spain

A B S T R A C T

This paper seeks new insights concerning the health transition in 20th century Spain by

analyzing both traditional (mortality-based) and alternative (anthropometric-based)

health indicators. Data were drawn from national censuses, vital and cause-of-death

statistics and seven National Health Surveys dating from 1987 to 2006 (almost 100,000

subjects aged 20–79 were used to compute cohort height averages). A multivariate

regression analysis was performed on infant mortality and economic/historical dummy

variables.

Our results agree with the general timing of the health transition process in Spain as has

been described to date insofar as we document that there was a rapid improvement of

sanitary and health care related factors during the second half of the 20th century reflected

by a steady decline in infant mortality and increase in adult height. However, the

association between adult height and infant mortality turned out to be not linear. In

addition, remarkable gender differences emerged: mean height increased continuously for

male cohorts born after 1940 but meaningful improvements in height among female

cohorts was not attained until the late 1950s.

� 2011 Elsevier B.V. All rights reserved.

§ This work is associated to the following research projects funded by

the Spanish Ministry of Science and Innovation: Crecimiento, Nutricion y

Bienestar en Espana. La influencia de los procesos socioeconomicos a largo

plazo en los niveles de vida biologicos y la salud (SEJ2007-67613);

Implicaciones sociodemograficas de las condiciones de salud en las edades

maduras (ref. CSO2009-09851-SOCI).§§ Contributors: All authors contributed equally to the article and have

approved the final version.* Corresponding author at: Centre d’Estudis Demografics, Edifici E2,

Campus de la UAB, 08193 Bellaterra, Barcelona, Spain.

Tel.: +34 93 581 30 60; fax: +34 93 581 30 61.

E-mail address: [email protected] (Jeroen J.A. Spijker).

Contents lists available at ScienceDirect

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jou r nal h o mep age: h t t p: / /w ww.els evier . co m/lo c ate /eh b

1570-677X/$ – see front matter � 2011 Elsevier B.V. All rights reserved.

doi:10.1016/j.ehb.2011.08.001


including certain early critical periods (Barker, 1995;Ben-Shlomo and Kuh, 2002), which may be exacerbatedby gender-related inequalities (Osmani and Sen, 2003).Known as ‘‘biological programming’’, such exposure haslong-lasting, even lifelong, effects on the structure orfunction of organs, tissues, and body systems, and theseeffects are not modified significantly by later experience.One example is under-nutrition during gestation whichincreases the risk of heart disease during adulthood (Panethand Susser, 1995). Another marker of early life conditionsand predictor of adult mortality in both Western (Marmotet al., 1984; Davey Smith et al., 1998) and non-Western(Song et al., 2003) populations is height as it is influenced byboth genes and childhood living conditions.

The extent to which one’s biological potential (i.e.,inherited stature) is attained depends on the net result ofthe body-energy equation until the physical-growth cycleis completed. Thus adult height is a ‘‘net nutritionalstatus’’ indicator, since it measures the balance betweeninputs (quantity and quality of food intake) and outputs(illness-related expenditure, physical effort, and energyexpended by the basal metabolism to maintain the body’svital functions) (Bogin, 1988). Its relevance to any study ofthe health transition derives from its capacity not only tocapture this health-related net effect but also to providean approximation of living conditions within any geneti-cally uniform population until adulthood is reached (Battyet al., 2009).

As for the interaction between epidemiological andsocio-economic factors, the final height averages ofpoorly nourished individuals who grow up in disease-ridden environments are, as a rule, inferior to those ofindividuals who are not so unfortunate, and their healthduring adulthood tends to be relatively poor, as well.However, this basic causation may be altered and evenreversed by selection effects (Bozzoli et al., 2009).Selection consists of the removal (i.e., through death)of the less healthy members of a cohort, who arepresumably shorter on average (Waaler, 1984; Alter,2004; Koch, 2011) with the result that the observedheight is biased to the right with respect to what theaverage cohort height would have been if everyone hadsurvived. Consequently, at very high levels of infant andchild mortality, the mean height of adult cohorts may behigher than that of cohorts exposed to lower mortalitylevels early in life.

A final point is that height trends should be analyzedalongside indicators that approximate the environmentalconditions until the age at which physical growth has beencompleted, or at least during the two periods of humangrowth that, according to auxology, are the most critical,infancy and adolescence (Tanner, 1986). This may there-fore tell us a great deal about the (changing) relativeimportance of the different early life phases on final adultstature.

1.1. Spain

Within a world context, Spain’s transition began early,the mortality rate there having already begun to decline bythe mid 1860s (Dopico and Reher, 1998; Nicolau, 2005).

However, this transition was late relative to that of the restof Western Europe, and particularly of France where suchan improvement had already begun generations earlier(Schofield et al., 1991; Livi-Bacci, 1992). In Spain, lifeexpectancy during the period 1863–70 was 29.4 years formen and 30.2 years for women, with the infant mortalityrate of approximately 250 deaths per 1000 live births(Dopico and Reher, 1998). By 1900, the latter rate haddeclined to 200 per 1000, but it was still one of the highestin Europe, together with those of Austria, Hungary,Germany, and Russia (Caselli et al., 1995; Robles andPozzi, 1997). Moreover, and significantly, child mortalityrates (ages 1–4), traditionally representative of socio-economic and sanitary developments, remained higherthan infant mortality rates until the turn of the century(Sanz-Gimeno and Ramiro-Farinas, 2002).

These adverse outcomes during the 19th century havealso been confirmed by a number of anthropometricstudies. During the second half of the 19th century theaverage height of Spanish men often stagnated or evendeclined (Martınez-Carrion and Perez-Castejon, 2002;Camara, 2009; Garcıa-Montero, 2009; Ramon-Munoz,2009; Hernandez and Moreno, 2009). The consensus ofthese studies is that during this period the overallimprovement in the mean stature of Spanish males (the1850–60 and 1890–1900 birth cohorts) was insignificant,from approximately 1.62 m to 1.63 m (Gomez-Mendozaand Perez Moreda, 1985; Camara and Garcıa-Roman,2010), making Spain’s men among the shortest in Europe(Komlos and Baur, 2004: p. 59).

The beginning of the 20th century marked a turningpoint for both indicators, as they began to increase slowlybut steadily as the country recovered from the previouscentury’s series of subsistence crises and epidemics.

The progress in life expectancy was interrupted only bythe Spanish flu (1918–20) and the Spanish Civil War(1936–39). Over the course of the 20th century, lifeexpectancy for men and women, respectively, rose fromapproximately 35 years in 19001 (33.8 and 35.7) to 59.8and 64.3 years in 1950 and to 75.6 and 82.5 years in 2000(Instituto Nacional de Estatistica, or INE, 1991, 2007), anabsolute gain of 41.8 and 46.8 years. FurthermoreSpaniards in the 1972–76 birth cohorts were on average9 cm (men) and 6 cm (women) taller than their 1911–15counterparts as our results will show.

Despite its late start, Spain’s health transition waslargely accomplished over a relatively short span as lifeexpectancy increased by almost 50 years over a period ofless than a century, whereas this improvement took almosttwo centuries in the early starter countries Sweden andFrance. It is the combination of the speed and degree ofthese improvements that makes Spain particularly worthyof study; and, on a more practical level, it is the fact thatthe Spanish National Health Surveys (SNHS) surveyeda large pool of individuals belonging to a wide range of

1 In 1900 life-expectancy elsewhere in Europe ranged from 32.4 years

in Russia, 42.8 years in Italy, 44.4 years in Germany, 47.4 years in France,

48.2 years in the UK, and 49.9 years in the Netherlands to 54.0 years in

Sweden (Livi-Bacci, 1992).

J.J.A. Spijker et al. / Economics and Human Biology 10 (2012) 276–288 277


20th-century birth cohorts with very different lifeexperiences that makes such a study feasible.

1.2. Study objectives

The main purpose of our study is to offer, on the basis ofboth traditional (mortality-based) and alternative (anthro-pometric-based) health indicators, insights into the healthtransition of Spain, an underdeveloped country forWestern European standards for much of the 20th century.We will focus our analysis on sex and cohort differentials.

We begin with an analysis of both total and cause-specific infant and child mortality trends by sex andchanges in life expectancy at birth decomposed by agegroups. We then turn our attention to the height of the1911–76 Spanish birth cohorts, thereby presenting thefirst continuous comparative height series for both malesand females. Finally, we perform a multivariate regressionanalysis of cohort height that will test the relativeimportance of early life environmental conditions, usinginfant mortality and time variables as proxies, during theaforementioned critical periods for the physical growth.Note that although previous studies (Marıa-Dolores andMartınez-Carrion, 2011) also considered mortality as apotential explanatory variable of height, we specificallylink mortality to the critical periods of physical growthacross birth cohorts.

Finally, we compare our results with those of otherstudies that directly or indirectly dealt with relateddimensions of the health transition in Spain, includingeconomic (Marıa-Dolores and Martınez-Carrion, 2011),educational (Nunez, 2003, 2005; Collantes, 2004), andsanitary changes (Robles et al., 1996). Whereas previousanthropometric studies of contemporary Spain empha-sized factors related to political policies (Costa-Font andGil, 2008), our discussion is primarily focused on theassociation between height and infant and adolescentenvironmental conditions in the context of the epidemio-logical transition in 20th-century Spain.

2. Data and method

2.1. Height

Height data used in this research are self-reported(without shoes on) and come from the SNHS, a cross-sectional interview-based survey conducted seven timesbetween 1987 and 2006. While the SNHS is not a panelsurvey, previous results demonstrated a high congruenceof anthropometric measurements among birth cohorts(Spijker et al., 2008; Camara and Spijker, 2010), althoughsome small sample biases did have to be addressed. As theelderly and the less populated regions were oversampledduring certain waves, samples were weighted with officialpopulation data from the National Statistics Institute (INE).This step warranted the aggregation of the microdatafrom the different waves into one large database contain-ing age, sex, height and birth cohort.2 Interviews were held

face-to-face, and indirect informants were not allowedexcept in 2003 (33%) and 2006 (3%); in these cases, meanadult cohort heights by sex did not differ substantiallyfrom those reported by the respondents originallysampled.

Data were also screened for errors and omissions withrespect to the variables age, sex, residence region, andheight. Finally, taking into account the availability ofcohort mortality data (infant death rates), we restrictedourselves to cohorts born in Spain between 1911 and 1976for the continuous cohort height series that we con-structed. Only adults between the ages of 20 and 79 wereanalyzed as these were considered to have attained theirmaximum height and less likely to be affected by selectioneffects. We thus arrived at a sample size of 99,409respondents (Table 1) that were utilized to computecohort height averages.

2.1.1. Data validation

It has been shown that self-reported data on stature areclosely correlated with measured data, often over 0.9(Gunnell et al., 2000), indicating that these data areadequate for a non-clinical study of cohort trends (Spenceret al., 2002). Nevertheless, several validation tests werecarried out.

We began by assessing the stability of cohort-heightmeans in order to confirm the reliability of anthropo-metric measurements. Despite the fact that these are self-reported heights from different surveys, the same single-year birth cohort observed similar average height atdifferent ages (e.g. 87% of the maximum differences in theaverage height of a single year birth cohort between 10-year age groups was less than 2 cm; results not shown).The comparison of the SNHS mean heights with those ofmilitary conscripts (Fig. 1) indicates that they follow thesame trend despite a consistently higher value (between1.4 and 1.9 cm) than the self-reported data. The latter islikely to be due to two reasons, a systematic over-reporting of height among the survey respondents and

Table 1

Number of cases used in the analysis by sex, 10-year age group and birth-

cohort.

Birth-cohort Age group

20–29 30–39 40–49 50–59 60–69 70–79

Males

1911–1919 210 818

1920–1929 275 2066 2194

1930–1939 270 2631 3099 1683

1940–1949 328 2680 3154 1752

1950–1959 419 3050 4083 1949

1960–1969 3989 4924 2921

1970–1976 3024 2481

Females

1911–1919 171 771

1920–1929 217 1846 2628

1930–1939 251 2282 3513 2456

1940–1949 328 2412 3594 2357

1950–1959 376 2736 4236 2604

1960–1969 3772 5264 3514

1970–1976 2895 3186

Source: Spanish National Health Surveys microdata, 1987–2006.

2 The wording and codification of these items have not changed across

surveys.

J.J.A. Spijker et al. / Economics and Human Biology 10 (2012) 276–288278


that conscripts in the military statistics had not yetcompleted their physical growth.3

Height data feature both a normal distribution and astable and small range in deviation from the mean acrosstime and between samples (Cole, 2000, 2003; A’Hearn,2004). The data (Fig. 2) approximate a normal distributionfor each of the three birth-cohort groups, with littlevariation in the respective standard deviations (averagingabout 7.0 cm and 6.4 cm among men and women,respectively). As expected, there was preference formultiples of 5 cm in the self-reported heights but thisrounding pattern is very similar both between males andfemales and across birth cohort groups.4

2.2. Mortality statistics

The principal source for Spanish vital-statistics data isthe Movimiento Natural de la Poblacion (MNP). Based onthe civil registry, basic information (mainly birth anddeath counts) is available for most years since 1858,and after 1900 its publication is annual and also includes

socio-demographic characteristics. Data after 1975 areavailable in electronic form from the website of theNational Statistics Institute (INE; www.ine.es), the yearwhen a series of modifications was made to certainconcepts and definitions used in the MNP statistics,including one of particular importance to our study: whatconstitutes a live birth. This was changed to conform tointernational standards, as until that moment the MNPdefined births in function of a legal criterion thatconsidered live births as infants surviving the first 24 h,and those that did not survive, as miscarriages. Theproblem with this definition is that it results in anunderestimation of the risk of dying in the first year oflife, a statistic that increases in significance as the infantmortality rate is reduced, and as an increasing proportionof infant deaths are confined to the first moments of life;during the first half of the 1970s, the infant mortality ratewas underestimated by as much as 30%. The reviseddefinition has been applied retroactively to correct thenumber of births and infant deaths prior to 1975,particularly relevant for the Civil War period (1936–39)as many (infant) deaths that occurred during andimmediately after the war were not recorded at all until1941 (Blanes, 2007).

Cause-specific mortality data prior to 1975 wereobtained from the annual edition of the MNP; for 1975and subsequent years, detailed death records in microdataform were requested from the INE. For the analysis of thechanges in the cause-specific pattern, we used theinternational classification of diseases (ICD), used by theWHO, as proposed by Murray and Lopez (1996). Prior tothe analysis, the relevant cause-of-death categories had tobe homogenized across seven successive ICDs, beginningwith the second one, in order to be able to construct a timeseries of cause-specific mortality. Population data, neededto estimate the population at risk in the calculation ofdeath rates, came from the Spanish censuses and frominter-census estimations produced by the authors.

2.3. Height and mortality

Three approaches are employed to test the linkbetween height and mortality using regression analysis.The first one considers the influence of environmentalconditions on the net nutritional status exclusivelyduring childhood. Those conditions are approached bythe infant mortality rate (m0) (Crimmins and Finch,2005).5 The expectation is that infant mortality iscorrelated negatively with height. The lower is m0 thehigher is living standards and heights will be greater.The second one attempts to account for the factors that

Fig. 1. Self-reported versus measured male heights. Spain, 1935–1974.

Source: Spanish National Health Surveys microdata, 1987–2006 and

Anuario Estadıstico de Espana (1954–90).

3 Regarding the first reason, Gil and Mora (2011) argue on the basis of

health data for the Spanish region of Catalonia that self-reported heights

are often exaggerated whereby over-reporting tends to increase with age.

They estimated mean differences between self-reported and measured

height to be 0.48, 0.40, 0.48, 0.73 and 1.42 cm among 15–24, 25–35, 36–

45, 46–55 and 56–65 year olds, respectively. Regarding the oldest age

group, these and our results are comparable to those obtained by Gunnell

et al. (2000) on 56–78 year-old British elderly who reported an average

over-estimation of 2.2 cm that also increased with age. Paradoxically, the

fact that elderly tend to overestimate their height (as they usually recall

what it was during early adulthood) actually serves our purposes. This is

because elderly are likely to report a height that approximates their

maximum height, reached at the end of the physical-growth process,

before the age-related shrinking process begins, which thus enables us to

compare it with the data provided by younger populations who are less

likely to overestimate their height (Borkan et al., 1983; de Groot et al.,

1996; Dey et al., 1999; Kuczmarski et al., 2001; Birrell et al., 2005; Gil and

Mora, 2011) and less likely to have shrunk. As to the second argument, not

all military conscript birth cohorts were measured at the same age; for

most of the century conscription took place at the age of 21, but during

the early 1970s and after 1986 it took place at age 18.4 On the whole this bias should not affect the analysis as heaping is

unlikely to change over time (i.e., across the seven health surveys) and

affects both tails of the distribution (heights ranged from 101 to 205 cm)

(Schneeweiß and Komlos, 2009).

5 Although cohort death rates were the preferred option as they

correspond to the experiences of real groups of individuals, the collecting

of annual age- and cohort-specific deaths did not begin until 1975. In fact,

cohort death rates published in the Human Mortality Database

(www.mortality.org) are estimates based on period data (Wilmoth

et al., 2007). Mortality rates at other ages related to critical physical

growth periods were also considered, but were discarded due to their

high correlation with m0 and their lower absolute value as individuals at

those ages are less vulnerable than newborns.



Fig. 2. Frequency distributions. Spanish heights (1987–2006) by birth cohort and sex (i) 1911–1936, (ii) 1937–1956, (iii) 1957–1976.

Source: Spanish National Health Surveys microdata (1987–2006).



affect adult height until the end of adolescence and,therefore, includes the important adolescent growthspurt which, together with the early infancy period, iswhen extrauterine human height experiences the fastestgrowth rates. However, adolescent mortality could notbe considered directly as a proxy for adolescentconditions, given that a high proportion comes fromexternal causes of death, making it a less appropriatepredictor of height. We therefore tested the effect ofadolescent conditions on average cohort height in twoways: (1) using the infant mortality rate as anapproximation of conditions during adolescence but attime t + 13 for girls and t + 15 for boys, i.e. the mainperiod of adolescent growth; and 2) regressing timedummy variables at adolescence on average cohortheight. This was also done for the first approach forcomparative purposes. Finally, a continuous time spe-cification was tested.

2.4. Historical time dummy variables

These variables refer to specific periods in Spain’spolitical and socio-economic history. These were linked tothe birth cohorts of the survey respondents during theearly infancy (ages 0–3) and the adolescent-growth-spurtyears (11–15 and 13–17 for females and males, respec-tively). The gender distinction was made as girls end theprocess of physical maturity earlier than males, while thebirth cohorts selected to represent each sex and timeperiod were those that spanned the largest portion of thehistorical period in order to avoid cohorts obtaining twodummy variables for the childhood or adolescent period.The historical periods that the dummy variables representare as follows6:

1911–22 Transition to industrial economy (modernization and

increase in agrarian productivity)

1923–30 Primo de Rivera dictatorship (a period of economic

growth, although its magnitude is a matter of debate;

see Carreras et al., 2005)

1931–35 Second Republic (a period of economic crisis and strong

public intervention in social-welfare areas such as health

and education)

1936–41 Spanish Civil War and immediate post-war period

1942–49 First decade of Franco’s regime (1939–75); severe

autarchy, economic stagnation, and widespread hardships

1950–59 Under an autarchic political system, a decade of rapid

economic growth

1960–76 Economic growth maintained by means of a national

policy of liberalization, industrialization, tourism, and

income from migrants in Western Europe; general

improvement in living standards7

Because there is a total of 6 categories (we use one asreference), we have created a set of 12 dummy variableswith dichotomous values 0–1: 6 for early infancy and 6 foradolescence (males and females differentiated) whoseassociation with cohort average height is also tested.

2.5. Modeling procedure

The regression analysis is performed using ordinaryleast squares. In the modeling procedure, when theinfluence of environmental conditions during early infancyis tested, either m0 or the infancy dummy is used, but notboth. The same policy applies to the influence of conditionsduring adolescence. Infancy and adolescence dummyvariables were not added simultaneously, as this wouldcomplicate the interpretation of the results. Instead, whenthe adolescent growth period was analyzed the m0

continuous variable, representing the living conditionsduring infancy, was included in order to capture theinteraction of environmental factors during the two criticalperiods of human growth.8

Finally, to control for any age-specific differences inaverage cohort height that may be observed within asingle-year birth cohort across the different surveys, therespondent’s age at the time of the interview was includedin all models as a control variable (i.e. age-specific cohortheight averages were modeled). Including age increased N

to 394. This corresponds to 66 birth cohorts observed atdifferent times (i.e. surveys), whereby for most cohortsseven observations could be obtained, although the oldestand youngest birth cohorts were not covered by allsurveys. As measurement bias is known to increase withage (see the Data and method sub-section) the log of agewas used.

3. Descriptive results

3.1. Mortality

The substantial gains in life expectancy that wereachieved in Spain during the 20th century were not evenlydistributed over time and across age groups (Table 2). Untilabout 1990, important improvements still came from thereduction of infant mortality (age 0),9 whereas since the1960s there has been little improvement in that of childmortality (ages 1–4). On the other hand, since the 1980s

6 A similar and useful summarized sequence of political and economic

milestones for this period can be found in Costa-Font and Gil (2008).7 Technically, the economic expansion ended in 1974, when the rate of

increase in GDP slowed (Carreras et al., 2005), but as our study extends to

the 1976 birth cohorts, we extend the time period to 1976 as well.

8 Several other specifications as well as diverse robustness checks were

carried out, including the addition of a time trend (Model 6 in Table 5) and

GDP in the models in order to control for secular changes in technology or

income, but the relationship between height and infant mortality

remained substantially unchanged. In addition, the association between

height and infant mortality was tested by means of a difference model, i.e.

in terms of annual variations whereby negative sign of the slope indicates

that annual decreases in mortality are associated with annual increases in

height and vice versa. Three-year moving averages were used to smooth

the randomness that is inherent in self-reported height data and the

occasional strong fluctuation in infant mortality. We ran these regres-

sions separately for both the time dummy variable and continuous time

approach and we controlled for age. Results showed that the estimated

coefficients were insignificant. This is partly explained by the fact that

despite the usually positive annual changes in height and negative annual

changes in infant mortality, there was no clear (for women) and no

significant (for men) pattern, whereby the introduction of the time

variable reduced any hint of a trend even further.9 The change in life expectancy between 1991 and 2001 was analyzed

as well, but it is not shown here because the interval is 10, not 20, years. In

any case, declines in infant mortality contributed only about 0.25 years to

the life expectancy increase that occurred during the 1990s, or about one-

third of the ten-year average of the previous two decades.



the elderly population accounts for most improvements inlife expectancy.10

Apart from the excess mortality caused by the Spanishflu (1918–20), infant and child mortality declined duringthe first decades of the 20th century.11 The fact, however,that there was little improvement in the cause-specificpattern, which remained dominated by communicablediseases, underlines the importance of environmentalcauses (particularly those that feature the interactionbetween nutrition and infection) during this initial stage ofthe decline in infant mortality in 20th-century Spain.12

Improvements continued during the 1920s and 1930s(between 1921 and 1935, infant and 1–4 year old mortalitydropped by 27% and almost 55%, respectively), translatinginto an acceleration of the structural decline of non-adultmortality which, as in previous decades, mostly benefited1–4 year olds rather than infants (that had resulted in thecorrection of the higher level of mortality among ages 1–4that characterized Spain and other Mediterranean coun-tries; Sanz-Gimeno and Ramiro-Farinas, 2002). Amonginfants, the sharp decline of communicable diseases after1941 must be highlighted (Fig. 3).

Finally, throughout the 20th century the infant mortalityrates of males and females converged (Table 3). The steadyimprovements in hygiene, sanitary, and education reducedthe biologically determined higher mortality rate amongboys, as prior living conditions were more hostile for boysthan for their biologically more resistant female counter-parts. Even though male infant mortality improved morethan female mortality did, in relative terms few sexdifferences can be discerned.

3.2. Height

The 20th century saw a dramatic increase in meanheight for both sexes. Nevertheless, during the early part ofthe century improvements (including the period ofeconomic growth during the 1920s), did not translate to

a stability of general nutritional status, as the fluctuationsin the height series and only marginal overall growthshowed. However, improvements were more pronouncedfor the cohorts born during the second half of the century(Fig. 4). Indeed, the average height of the Spanishpopulation (similar to other Southern European countries),

Table 3

Infant mortality rates by gender in Spain (per 1000 live births).

Birth cohort Rate Inter-period

decline (%)

Males Females Difference Males Females

1911–19 188.8 156.3 32.4 – –

1920–29 168.2 141.6 26.6 10.9 9.4

1930–39 141.2 117.9 23.3 16.0 16.7

1940–49 114.3 97.3 17.0 19.1 17.5

1950–59 65.8 54.0 11.8 42.4 44.5

1960–69 44.2 34.6 9.6 32.8 35.9

1970–79 22.7 17.7 5.0 48.7 48.8

1980–89 10.9 8.7 2.2 52.0 51.3

Source: Movimiento Natural de la Poblacion (Vital Statistics) and the

Spanish population censuses, 1910–1991.

Fig. 3. The combined communicable and perinatal mortality rates in Spain

for ages 0, 1–4, and 10–14. Birth cohorts 1911–76. Note: Communicative

diseases include infectious diseases, respiratory infectious diseases,

diarrhea, and enteritis. Perinatal mortality pertains to infants only.

Source: Movimiento Natural de la Poblacion (Vital Statistics) and the


Table 2

Age-specific changes in life expectancy at birth (in years) over time by gender in Spain (1911–1991).

Men Women

Change over 20 year period Change over 20 year period

1911–1931 1931–1951 1951–1971 1971–1991 1911–1931 1931–1951 1951–1971 1971–1991

Age

0 2.35 3.23 3.18 1.54 2.08 2.98 2.86 1.30

1–4 3.75 2.67 1.36 0.18 3.85 3.09 1.44 0.16

5–14 0.69 0.68 0.60 0.13 0.88 0.84 0.63 0.11

15–44 0.95 2.40 2.03 �0.28 1.57 2.92 2.24 0.33

45–64 0.20 1.21 1.40 1.00 0.72 1.22 1.42 1.20

65+ 0.08 0.31 0.85 2.00 0.27 0.40 1.71 2.96

Total 8.02 10.50 9.43 4.58 9.37 11.45 10.30 6.05

Source: Movimiento Natural de la Poblacion (Vital Statistics) and the Spanish population censuses, 1910–1991.

Note: Calculated using the decomposition method by Pollard (1988).

10 See Blanes (2007) and Spijker and Blanes (2009) for a detailed

analysis of life expectancy changes in Spain and the Spanish Autonomous

Region of Catalonia, respectively.11 Here we refer mainly to the national trend, because regional trends

differed substantially (Gomez-Redondo, 1992).12 This issue receives further attention in Section 4.



began to converge with those of Northern European ones(Hatton and Bray, 2010).

Gender differences during this process have been muchless studied in Spain and are therefore worth mentioning.Whereas male height began to increase steadily from theearly 1940s on, this did not occur among females until thelate 1950s (Table 4). In spite of the subsequent steadyincrease in average height among female birth cohorts, themale–female height gap remained stable at about 12.0–12.5 cm: a gap 2 cm wider than for early 20th-centurycohorts and more than 3 cm wider than for those bornduring the years 1936–41.

3.3. Mean heights and annual infant mortality rates by gender

If the mean adult height of a given birth cohort isplotted against the same cohort’s annual infant mortality

rate, the two variables are closely correlated, although in anon-linear fashion (Fig. 5). This non-linearity indicates thelack of association between infant mortality and adultheight for the earlier birth-cohort categories, while theassociation became clearly linear only after the infantmortality rate had declined to approximately 50 per 1000.On account of this non-linear association, m0 wastransformed into its natural logarithm for the multivariateregression analysis (Table 5).

In Model 1, we observe that cohort-specific infantmortality (used as an indicator of early-childhoodenvironmental conditions) is indeed negatively asso-ciated with adult height in the same cohort. In the

Table 4

Average height (cm) of the Spanish population by birth cohorts.

Birth

cohort

Men Women

Inter-cohort change Inter-cohort change

Average Total Annual

average

Average Total Annual

average

1911–17 166.81 157.28

1918–22 166.92 0.11 0.02 157.82 0.54 0.09

1923–30 167.76 0.85 0.13 158.29 0.47 0.07

1931–35 168.21 0.45 0.07 158.63 0.34 0.05

1936–38 168.42 0.21 0.05 159.04 0.42 0.10

1939–41 168.69 0.27 0.09 159.37 0.33 0.11

1942–49 169.85 1.16 0.21 159.61 0.25 0.04

1950–59 171.39 1.55 0.17 159.94 0.33 0.04

1960–65 173.38 1.99 0.25 161.12 1.18 0.15

1966–76 175.29 1.91 0.22 162.97 1.85 0.22

Source: Spanish National Health Surveys microdata, 1987–2006.

Note: Heights are self-reported. Inter-cohort change in average height

pertains to the difference in average height of one birth cohort and the

previous birth cohort. The annual averages are calculated by dividing this

inter-cohort change with the average number of years that the two

respective cohorts contain.

Fig. 4. Height of the 1911–76 Spanish birth cohorts.

Source: Spanish National Health Surveys microdata, 1987–2006. Three-year moving average.

Fig. 5. Scatterplot of infant mortality (m0) and height for Spanish birth

cohorts born 1911–76.

Source: Height: Spanish National Health Surveys microdata, 1987–2006.

Mortality: Movimiento Natural de la Poblacion (Vital Statistics) and the




case of men, an m0 value of 0.2 (occasionally observedduring the first two decades of the 20th century) wouldyield an estimated cohort height of 166.9 cm, an m0

value of 0.1 (typical for the 1942–49 cohorts) would

increase this height by 3.0 cm, while an m0 value of0.02 (as recorded for the latest available birth cohorts,1974–76) equals the predicted cohort height of176.7 cm, i.e., an additional increase of almost 7 cm. Inthe case of women, the modeled heights under the samem0 values were, respectively, 157.7 cm, 159.4 cm, and162.9 cm.13 The coefficient for m0 was statisticallysignificant in the models for both sexes, although thevalue of the coefficient was considerably higher in themale model.

Table 5

Regression analysis. Association between environmental conditions at infancy and adolescence and cohort average height.

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Coeff (SE) Coeff (SE) Coeff (SE) Coeff (SE) Coeff (SE) Coeff (SE)

Males

Constant 169.7 (1.8) 185.5 (1.0) 182.5 (1.2) 184.5 (1.2) 169.4 (1.9) 167.9 (1.7)Log of m0 �3.4 (0.2) �2.8 (0.3) �2.1 (0.2)Log of m0 at time t + 15 �2.7 (0.1)Time ((cohort – 1910)/10) 0.7 (0.1)1. Infancy (ages 0–3)

A. Cohorts 1911–22 �5.7 (0.4)B. Cohorts 1923–30 �5.0 (0.3)C. Cohorts 1931–35 �4.7 (0.3)D. Cohorts 1936–41 �4.5 (0.3)E. Cohorts 1942–49 �3.6 (0.3)F. Cohorts 1950–59 �2.1 (0.2)G. Cohorts 1960–76 Reference

2. Adolescence (ages 13–17)

B. Cohorts 1911–16 �5.3 (0.5) �2.5 (0.5)C. Cohorts 1917–21 �5.2 (0.4) �2.0 (0.5)D. Cohorts 1922–27 �4.6 (0.4) �2.1 (0.4)E. Cohorts 1928–35 �4.3 (0.3) �1.8 (0.4)F. Cohorts 1936–45 �4.0 (0.3) �1.3 (0.4)G. Cohorts 1946–62 �2.3 (0.2) �1.0 (0.2)H. Cohorts 1963–76 Reference Reference

Log of age �1.9 (0.3) �1.2 (0.4) �2.3 (0.4) �2.9 (0.2) �1.2 (0.3) �1.2 (0.3)R2 adjusted 0.889 0.891 0.881 0.870 0.897 0.901

N 394 394 394 394 394 394

Females

Constant 171.5 (1.8) 174.1 (1.0) 175.1 (1.2) 174.5 (1.1) 170.1 (1.9) 170.4 (1.7)Log of m0 �0.8 (0.2) �0.8 (0.3) �0.3 (0.3)

Log of m0 at time t + 13 �0.8 (0.1)Time ((cohort–1910)/10) 0.3 (0.1)1. Infancy (ages 0–3)

A. Cohorts 1911–22 �1.5 (0.4)B. Cohorts 1923–30 �1.1 (0.3)C. Cohorts 1931–35 �1.0 (0.3)D. Cohorts 1936–41 �0.8 (0.3)E. Cohorts 1942–49 �0.8 (0.2)F. Cohorts 1950–59 �1.1 (0.2)G. Cohorts 1960–76 Reference

3. Adolescence (ages 11–15)

B. Cohorts 1911–18 �2.2 (0.3) �1.2 (0.5)

C. Cohorts 1919–23 �1.2 (0.3) �0.2 (0.5)

D. Cohorts 1924–29 �1.5 (0.3) �0.7 (0.5)

E. Cohorts 1930–37 �1.3 (0.3) �0.5 (0.4)

F. Cohorts 1938–47 �1.0 (0.3) �0.2 (0.4)

G. Cohorts 1948–64 �1.1 (0.2) �0.7 (0.2)H. Cohorts 1965–76 Reference Reference

Log of age �3.5 (0.4) �2.9 (0.4) �3.7 (0.3) �3.5 (0.3) �3.0 (0.4) �3.1 (0.4)R2 adjusted 0.742 0.751 0.751 0.758 0.762 0.767

N 394 394 394 394 394 394

Source: Height: Spanish National Health Surveys microdata, 1987–2006. Mortality: Movimiento Natural de la Poblacion (Vital Statistics) and the Spanish

population censuses, 1910–1991 see Section 2.

Note: The dependent variable is cohort average height in cm. Historical periods during infancy (1) and adolescence (2 and 3): A – Transition to industrial

economy. B – Primo de Rivera dictatorship. C – Second Republic. D – Spanish Civil War and post-war. E – First decade of Franco regime. F – Economic growth

under autarchy. G – Economic development under liberal system. H – Transition to democracy. For the calculation of the statistical significance of the

regression model coefficients the data were not weighted. White’s test for heteroskedasticity was conducted for Model 5, but its presence could not be

confirmed (nR2 = 20.9 for males and 53.1 for females vs. x2 (393 d.f.) = 440.2 at p < 0.05). In bold, significant at 1%. In italics, significant at 5%.

13 The following average ages at survey interview were used in the

calculations of the above average heights: 74 years for the birth cohorts

1911–20, 52 years for the 1942–49 cohorts and 27 years for the 1974–76

cohorts (no distinction by sex was made).



If the m0 for birth cohort t + 13 years and t + 15 years isused in order to control for environmental conditions duringthe final stage of physical growth (Model 2), results are quitesimilar, although in the case of men the coefficient is slightlylower than according to the previous model. This result, inthe absence of any other control variable but age, suggeststhat, when it comes to physical-growth trends among theSpanish population, conditions during both infancy andadolescence are more important for males than for femalesand, in the case for males, the former period is moreimportant than the latter. The two m0 variables could not betested simultaneously because of their very high correlation.

Next we introduce time dummy variables into theregression equation. First, the variables related to the yearsof infancy and then of adolescence of the birth cohorts inquestion were tested and found to be statistically significant(Models 3 and 4). For any given dummy (i.e., time period) themodel coefficients were higher for males than for females.

We also find that the association between height andtime during the adolescent growth spurt is significant butsmaller than at the time of birth but only after controlling forliving conditions during infancy, as proxied by m0 (Model 5).The coefficients representing the earlier periods were farmore reduced than were the others, indicating that theeffect of the adolescent growth period on final heightdeclined.14 Moreover, the adolescent period becomeslargely insignificant for females, which is a noteworthydifference with respect to what was observed for males.

Finally, Model 6 tests for the potential effect of secularchanges (e.g. in technology and/or income) on changes inaverage population height after controlling for infant livingconditions by using continuous time variable instead of thedummy variables. Results showed that for both men andwomen the coefficient for time was significant, implyingthat factors other than conditions during infancy were alsoresponsible for the increases in height that were observedin Spain over the course of the 20th century.15

To sum up, our model results indicate that infancy is acritical period for physical growth in 20th-century Spain,although, especially for males, environmental conditionsduring the adolescent spurt should not be neglected.16

Indeed, our results (although not statistically significant)are in line with those of Martınez-Carrion and Perez-

Castejon (2002), who argued that the actual impact of theSpanish Civil War on the biological standard of living wasgreater among males born in the 1920s than it was amongthose who were born shortly before, during or just after thewar, on account of the fact that they still had a potential tocatch up during the 1950s.

4. Discussion and conclusions

During the course of the 20th century, Spain’s mortalitypattern evolved from onedominated byinfectiousdiseases ingeneral and high infant mortality in particular to onedominated by chronic adult diseases. This trend wasparalleled by the increase of cohort adult height, an indicatorof thebiologicalstandardofliving;butbecausethis transitionwas a complex, non-linear one, we also considered infantmortality and economical–historical time dummy variablesas an approximation of the environmental conditions duringthe two most critical periods of human growth, infancy andadolescence. This was done in order to measure the changingimpact of the early life phase on the health transition,focusing our attention on differences by sex and birth-yearcohort (1911–76). Our conclusion comprises three elements.

First, if infant mortality is chosen as one of the criteria toestablish a timing of the health transition then this processcannot be regarded as having been concluded in Spain untilabout 1980. It was only then when other age groups (i.e. 65and over) became the motor behind the observedimprovements in life expectancy at birth.

Second, the same can be said concerning height; in fact,the height increase never slowed down after averageheight for both sexes began its steady increase across birthcohorts since the end of the 1950s.

Third, variations in the relationship between infantmortality and height can be divided into three categories(Tables 3 and 4 and Fig. 5):

1. Significant improvements in the infant mortality ratewere found among males born during the years 1911–22 and 1931–35 and females born during the years1911–35 and 1942–59, but there was little progress intheir height patterns, which were marked by fluctua-tions and stagnation.

2. There was an increase in the infant mortality rate and astagnation in average height among the civil-war birthcohorts (1936–41), especially the male ones.

3. There was a significant improvement (somewhat later forfemales than for males) in both indicators among the birthcohorts born from the time the country had recoveredfrom the civil war, reflecting improvements in livingconditions. In this case, improvements in the infantmortality rate yielded proportional increases in height.17

14 If GDP was used as a proxy for infant living conditions rather than

infant mortality the impact of adolescence between cohorts also

diminished as compared to Model 4, although less so. Infant mortality

was, however, the preferred indicator as it is more directly related to

human height at the conceptual (especially biological) level.15 It should be noted that although the effect of including the continuous

time variable instead of the adolescence dummy variables on infant

mortality was only slight in the case of males, the coefficient for females

became insignificant. This suggests that improvements in infant

conditions was only significantly associated with increases in female

height during specific periods but not during the period as a whole.16 This was confirmed when elasticities were calculated for infant

mortality during childhood and adolescence (Models 1 and 2). Elasticity is

here a measurement of the relative change in height as a consequence of

the relative change in living conditions during childhood and adolescence

(as estimated by infant mortality during both periods). For males,

elasticity was greater during infancy than during adolescence (�0.09 and

�0.06, respectively), while for females elasticity was lower and equal for

both critical periods (�0.02).

17 A robustness test of the final regression model verified this association.

When the birth cohorts, male and female, were divided into those born until

and after 1948, the Model 5 coefficients for the log of infant mortality (the

proxy used for childhood living conditions) were virtually identical for each

group of cohorts (results not shown). Given its non-linear association, it

suggests that when childhood living conditions were poor, it required major

improvements in those conditions to achieve a small increase in average

population height, whereas when living conditions were good it required

only minor improvements to produce the same height increase.



In conclusion, the initial increase in survival that beganat the start of the 20th century was without similarimprovements in adult height. The factors that mayexplain this discrepancy deserve some discussion.

The first third of the 20th century in Spain was markedby mortality declines that led to substantial improvementsin life expectancy. These improvements were paralleledand explained by both economic and social factors. Theeconomic progress is illustrated by Prados’ (2003) esti-mates on GDP growth rates and studies on the notedincrease in agrarian productivity in Spain after efforts hadbeen made to overcome certain physical constraintscommon among Mediterranean countries which impededthem to follow the development of other WesternEuropean agrarian systems (Prados and Zamagni, 1992;Pujol et al., 2001; Barciela et al., 2005). Thus, despite thepersistence of an uneven wealth distribution and theinheritance of a poorly integrated domestic market(especially in regard to foods high in calories and protein,chiefly meat and dairy products), structural advancescontributed to improvements in the quality and avail-ability of foodstuffs and subsequent rise in energy inputs.

In addition, there is evidence of a progressive trans-formation, beginning in the 1920s, of some cultural andbehavioral health-related factors, such as changing atti-tudes towards nutrition and personal hygiene. For the firsttime, breast-feeding was encouraged (Balaguer et al.,1991), social and institutional public-health campaignswere organized, and women were offered both prenataland postnatal nutritional guidance (Reher, 2001; Nicolauand Pujol, 2008). These efforts are reflected in the fact thatsince the 1930s health-service consumption as a propor-tion of total consumption has increased significantly(Marıa-Dolores and Martınez-Carrion, 2011). This wasalso a period of progress in primary education, althoughthis was temporarily cut short by the civil war andimmediate post-war years (Nunez, 2003). While therewere certainly disparities nationwide, the overall literacyrate increased from 36% to 48% between 1900 and 1920(Collantes, 2004).

One result of all these efforts was a decrease in the non-adult mortality rate, which contributed to an increase inlife-expectancy. Sanitary conditions, however, in urban aswell as rural areas, remained underdeveloped. Forinstance, Criado (1925) reported that as late as the early1920s 90% of Spanish municipalities still lacked sewersystems and 80% also lacked potable-water systems(Balaguer et al., 1991). This concords with the few changesin the overall epidemiological pattern of these cohorts asthe infant and child mortality from communicative andperinatal diseases as a proportion of all-cause mortalityremained high despite a decrease in the latter.

We hypothesize that these diseases, which are highenergy consuming, partly offset the improvements innutritional inputs and health-related behavior thatimpeded the survivors to attain a higher stature (theaverage height of both sexes combined increased by only1.4 cm during this period). On the other hand, it may bethat the selection effect on the oldest cohorts was smallerthan expected. The survivors in the earliest cohorts, whichwere relatively small on account of the relatively high

infant mortality rate at the time, were not taller than thoseborn later, when that rate was decreasing. In other words,although selection became less rigorous over time, it didnot dominate scarring; if it had done so, then the survivorswould have been taller than the average of youngercohorts, a pattern found today among the world’s poorestregions (Bozzoli et al., 2009). Instead, during the first half ofthe 20th century, Spain appears to have achieved anequilibrium between selection and scarring effects thatwould explain short (and only slightly increasing) staturesin a context of declining mortality.

The health transition accelerated during the second halfof the 20th century thanks to rapid improvements inhygiene, and to other health-related factors associated witha high degree of socio-economic development (Robles andPozzi, 1997). Thus Spain recorded a decline in its infantmortality rate and an increase in cohort adult height,although it was not until about 1960 (when m0 dropped toabout 50 per thousand) when height also began to showsignificant improvements among Spanish women. Thesteady increase in adult height since then is a reflectionof the aforementioned combination of elements thatintervene in the body-energy equation. More and betternutritional inputs and less illness and infant work-relatedenergy expenditure contributed to both the decline in theinfant mortality rate and the dramatic increase in height. It isquite likely that these cohorts benefited from Spain’seconomic growth and thus from improvements in thestandard of living, and, more specifically, from health-careprograms, medicines, and medical technology that becameavailable toward the end of the autarchic regime. This is alsoargued by Marıa-Dolores and Martınez-Carrion (2011), whostate that economic growth alone could not account for thispositive trend in nutritional status, observing that improvedaccess to increasingly affordable consumer goods and healthservices were key aspects of this period of economicgrowth.18 These cohorts traversed the two critical periodsof physical growth, that is, infancy and adolescence, withoutencountering any significant setbacks.

Nonetheless, the progress made in cohort adult heightand infant mortality indicates that there was considerableroom for improvement. It is our belief that once sufficientcalorie and protein levels had been attained, in the mid-1950s (Cusso, 2005), other factors, such as the diseaseenvironment and the quality of hospital care, determinedthe progress of the biological indicators. For instance, in1950, more than 65% of Spanish households were notconnected to a water-supply system, and about half did nothave toilet facilities (Robles et al., 1996). As late as 1967 asmany as 300,000 urban households still lacked minimalbathroom facilities (a figure that excludes major suburbanareas that were usually even worse off).

Furthermore, it was not until the end of the 1960s that itbecame standard practice for a woman from a rural area togive birth in a hospital. Thus the increases in adult cohort

18 Recently, the role of public provisions and access to health services

has also been outlined in advanced stages of development to explain why

an outstanding economic performance does not always equals improve-

ments in net nutritional status (Komlos and Baur, 2004).



height reached their highest values in Spain over the 20thcentury just as the mean stature began to level off in someother European countries (Larnkjaer et al., 2006). The 1960scohorts were probably the first whose entire physical-growth process occurred within a context of food securityand diet diversification, together with a decrease of childlabor caused by rising school attendance. In addition,infectious diseases (as another output for the body-energybalance and particularly high in energy consumption) hadbeen substantially reduced, which also favored growth.

Finally, the birth cohorts of the 1940s and 1950s (bothmale and female) deserve special attention, as theyexperienced the most significant increase in life expec-tancy throughout the 20th century; in addition, the malecohorts born from the early 1940s experienced until, atleast, the end of our study period, a continual increase instature, whereas women did not until the late 1950s. Evenduring those decades of the 20th century marked bymalnutrition, one does not expect to find stunting to be asextensive as it had been during the previous century. Theaforementioned improvements in agricultural productiv-ity, in the educational system, in public and personalhygiene and medical advances (including antibiotics andvaccination programs): all of these elements prevented thesort of public-health catastrophe associated with postwarperiods. Those born during the war and postwar years andwho, as a result, suffered stunting during their infancy mayhave achieved greater catch-up growth during theiradolescence, since it coincided with Spain’s economicrecovery, than had previous birth cohorts. However, thistheory is not supported by the estimated coefficients of theadolescence time dummy variables for the 1946–62 maleand the 1948–64 female birth cohorts, their values beingstatistically comparable to those of the previous cohorts,after controlling for conditions during infancy.

Why did Spanish women not experience the samesustained trend until the 1960s? According to the dataprovided by Cavelaars et al. (2000), similar increases ofsexual dimorphism occurred in other European countries,although not for the same birth cohorts. Spain’s case seemsto be explained by the fact that males fared better thanfemales, as the convergence of their infant mortality rateswould indicate. Moreover, the model coefficient for infantmortality was about 70% higher for males: that is, maleheight benefited more from improving living conditionsduring infancy than female height. The fact that the modelcoefficients of the historical-period dummy variables forthe older birth cohorts representing conditions duringadolescence were higher for males indicates the highereco-sensibility of males during both critical periods forphysical growth, especially when living conditions aredifficult. Whether it is a social factor – specifically, genderpreference (or penalty), as suggested by Spijker et al., 2008;Costa-Font and Gil, 2008) – or a set of biological factors thatexplains the observed lag among female cohorts remainsan issue in need of further research.

Acknowledgements

The authors wish to thank Anna Cabre, Lucia Pozzi,Graziella Caselli, Julio Perez-Dıaz, John Komlos and the

anonymous reviewers for their helpful comments onpreliminary versions of this work, as well as Julie Smithfor her English correction of the manuscript.

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