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SSM - Population Health 18 (2022) 101126
Available online 15 May 2022
2352-8273/© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).
Growing taller unequally? Adult height and socioeconomic status in Spain
(Cohorts 1940–1994)
Bego˜
na Candela-Martínez
a
,
*
, Antonio D. C´
amara
b
, Diana L´
opez-Falc´
on
c
,
Jos´
e M. Martínez-Carri´
on
a
a
Department of Applied Economics, Faculty of Economics and Business, CEIR Campus Mare Nostrum (CMN), Murcia University, 30100 Murcia, Spain
b
Departamento de Organizaci´
on de Empresas, Marketing y Sociología, Universidad de Ja´
en, Spain
c
Munich Center for the Economics of Aging, Max Planck Institute for Social Law and Social Policy, Germany
ARTICLE INFO
Keywords:
Living conditions
Inequality
Height
Socioeconomic status (SES)
Spain
Twentieth century
ABSTRACT
Socioeconomic inequalities and their evolution in different historical contexts have been widely studied. How-
ever, some of their dimensions remain relatively unexplored, such as the role played by socioeconomic status in
the trajectory of biological living standards, especially net nutritional status. The main objective of this article is
to analyze whether the power of socioeconomic status (SES) to explain differences in the biological dimensions of
human well-being (in this case, adult height, a reliable metric for health and nutritional status) has increased or
diminished over time. Educational attainment and occupational category have been used as two different proxies
for the SES of Spanish men and women born between 1940 and 1994, thus covering a historical period in Spain
characterized by remarkable socioeconomic development and a marked increase in mean adult height. Our data
is drawn from nine waves of the Spanish National Health Survey and the Spanish sample of two waves of the
European Health Interview Survey (ENSE) for the period 1987 to 2017 (N =73,699 citizens aged 23–47). A
multivariate regression analysis has been conducted, showing that, as a whole, height differentials by educa-
tional attainment have diminished over time, whereas differences by occupational category of household heads
have largely persisted. These results indicate the need for further qualication when describing the process of
convergence in biological well-being indicators across social groups. For instance, the progressive enrollment of a
greater proportion of the population into higher educational levels may lead us to underestimate the real dif-
ferences between socioeconomic groups, while other proxies of SES still point to the persistence of such
differences.
1. Introduction and objectives
In the study of the biological dimensions of well-being, anthropo-
metric parameters, particularly human stature, have gained unques-
tionable relevance in recent decades (Blum, 2013; Galofr´
e-Vil`
a, 2018;
Thompson et al., 2020). Since Tanner’s groundbreaking work in aux-
ology, human physical growth has come to be regarded as a ‘mirror of
health’ (Tanner, 1986) and, as a result, adult height is widely accepted
as a nal output indicator of several determinants of health related to
living conditions during pre-adult life. The height reached by an indi-
vidual in adulthood is considered a reasonable measure of the inuence
of environmental factors (i.e. physical, epidemiological and socioeco-
nomic (Bozzoli et al., 2009; Steckel, 2012; Akachi & Canning, 2015)) on
maximum genetic growth potential.
1
Basically, the interaction between
these factors determines the balance between energy intakes (e.g.
quantity and quality of food - Morgan, 2000; Puentes et al., 2016) and
energy expenditures (e.g. burden of exposure to illness and infectious
diseases and its interplay with malnutrition - Crimmins & Finch, 2006a,
b; Perkins et al., 2016).
A number of factors associated with the socioeconomic status of in-
dividuals may mediate this basic relationship between energy inputs and
outputs, giving rise to the possibility of using human height as an
* Corresponding author. Departamento de Economía Aplicada, Campus de Espinardo. Universidad de Murcia, Spain.
E-mail addresses: bcandela@um.es (B. Candela-Martínez), adcamara@ujaen.es (A.D. C´
amara), lopez-falcon@mea.mpisoc.mpg.de (D. L´
opez-Falc´
on), jcarrion@
um.es (J.M. Martínez-Carri´
on).
1
The effects of the environment on height and health susceptibility in adulthood can be traced right back to the gestational period (Roseboom et al., 2006) and the
predictive value of height in early childhood has been extensively demonstrated (Chen & Zhou, 2007).
Contents lists available at ScienceDirect
SSM - Population Health
journal homepage: www.elsevier.com/locate/ssmph
https://doi.org/10.1016/j.ssmph.2022.101126
Received 18 November 2021; Received in revised form 10 May 2022; Accepted 11 May 2022
SSM - Population Health 18 (2022) 101126
2
indicator of socioeconomic differentials and/or inequalities. On the
whole, it is expected that a higher socioeconomic position has a positive
inuence on the equation of energetic inputs and outputs that we have
dened based on auxology. On the inputs side, a higher SES would imply
a greater possibility of accessing a sufcient and varied diet; on the
outputs side, it would imply the possibility of living in healthier do-
mestic contexts and of overcoming infectious processes that negatively
affect growth (Cavelaars et al., 2000; Silventoinen et al., 2001; Sub-
ramanian et al., 2011). Furthermore, the socioeconomic status (SES)
clearly determines the need to work (and contribute to household in-
come) prior to adulthood, which is another potential factor of energy
expenditure.
2
The way SES and, consequently, SES-related differences are
approached in anthropometric studies strongly depends on the avail-
ability of information. However, information on income is hardly
available either due to the limitation of sources (e.g., for studies of past
populations) or the reluctance of informants to provide these data (e.g.,
for studies of current populations based on survey data). For this reason,
the most frequent and used proxies of SES are variables such as educa-
tional attainment and occupation. The two variables are related to one
another to a greater or lesser extent. We know that prior to the imple-
mentation of welfare state provisions in Western societies, the possi-
bility of following an educational path (i.e., the possibility of attending
school and nishing primary and subsequent levels) was very limited (to
only those from higher socioeconomic strata who could afford it).
Needless to say, the SES was and still is partly associated with the
occupational category of household heads. Therefore, the level of edu-
cation is often taken as a derivation of socioeconomic position and, in
consequence, as a valid proxy of SES. That said, we know that the syn-
ergies between education and the net nutritional status are actually
more complex, as education in itself may be one of the determinants of
the former in that it can prevent or enhance a good number of factors
that, according to auxology, inuence the physical growth process. For
example, education promotes knowledge of hygienic-sanitary measures,
leads to the adoption of lifestyles with less risky health behaviors and is
also a determinant of diet choice, where possible (Gao & Smyth, 2010;
Som et al., 2014; Viviani et al., 2020).
Over the course of the twentieth century, average adult height
increased dramatically in most populations around the world with few
exceptions, due to widespread improvements in living standards,
nutrition and health (Cole, 2000; Grasgruber et al., 2016; NCD Risk
Factor Collaboration, 2016). Western societies are a good illustration of
this process from the end of the nineteenth century onwards (Hatton &
Bray, 2010; Floud et al., 2011; Deaton, 2013). In light of the evidence, it
is assumed that among different birth cohorts, environmental conditions
will dictate the development of adult height and its trends within
genetically similar populations. In the long run, therefore, we may
expect increases in human height to mirror the general improvement in
living conditions, coinciding with the evolution of other health and
well-being indicators (Bogin et al., 2018; Fogel & Costa, 1997; Fogel,
2004; Grasgruber et al., 2014).
That said, progress in environmental conditions is not necessarily
linear and, moreover, their impact on the different population segments
varies considerably. There is extensive literature documenting drop
cycles as well as periods of stagnation of inter-generational growth,
correlating with diverse socioeconomic, political and epidemiological
scenarios (e.g. Baten & Wagner, 2003; Cox, 2019; Komlos & A’Hearn,
2019). Furthermore, it is widely accepted that environmental factors are
mediated by the socioeconomic status of individuals as both energy
intake and energy expenditure are often socially determined. This leads
us to consider height differentials across diverse social groups as po-
tential indicators of inequalities in the biological dimensions of
well-being (Blum, 2013; Carson, 2009; Gomula et al., 2021; Jaadla et al.,
2021; Lopuszanska-Dawida et al., 2020).
3
This paper seeks to examine the evolution of height differentials by
SES in Spain over a period when major improvements in living condi-
tions occurred: the second half of the twentieth century. To this end, we
analyze the role of individual and household-level factors. In practice,
this involves analyzing the variation in the level of impact on height of
these factors in different socioeconomic and political scenarios. Spain is
a particularly interesting case in this regard due to the accelerated pace
and intensity of its transition towards high levels of development and
standards of well-being (Prados de la Escosura, 2021; Carreras & Tafu-
nell, 2021), which resulted in sharp contrasts in living conditions over
the time span (i.e., among the birth cohorts) analyzed in this study. For
instance, life expectancy increased from 50 years (decade between 1930
and 1939) to 66 years (decade between 1950 and 1959) (Human Mor-
tality Database). Prior to the COVID-19 pandemic, this indicator in Spain
ranked among the highest in the world (82.7 years in the period
2010-18; Human Mortality Database). As for adult height, this country
recorded one of the highest rates of inter-generational growth over the
second half of the twentieth century (Hatton & Bray, 2010). The
involvement of various different factors in this trend has been broadly
discussed at the macro level, e.g., the positive evolution of economic
indicators (Prados de la Escosura, 2008; María-Dolores &
Martínez-Carri´
on, 2011), the nutrition transition (Ca˜
nabate &
Martínez-Carri´
on, 2017), the dramatic drop in the prevalence of infec-
tious diseases and infant mortality (Galofr´
e-Vil`
a & Harris, 2020; Quin-
tana-Domeque et al., 2011) and, nally, the implementation of social
provisions that reduced the inequality in terms of socioeconomic status
and enabled regional convergence (C´
amara et al., 2019;
Martínez-Carri´
on & María-Dolores, 2017). Nonetheless, relatively little
is known about the effect of these socioeconomic processes on specic
segments of the population, or in other words, about the ways in which
individual and household-level determinants operate on the trajectory
of biological well-being.
This paper addresses two specic research questions. The rst is
whether the rapid increase in the cohort average height observed during
the second half of the twentieth century was evenly spread across
different social groups in Spain. In this regard, we seek to determine the
degree of social convergence of biological living standards. The second
question is how SES and the manner in which it is operationalized
contribute to explaining height differentials in one socioeconomic
context or another. In other words, the extent to which SES more or less
inuences height differentials depending on historical periods and their
socioeconomic characterization and also the proxy that is used (for SES).
Men and women are addressed separately in the analysis of these two
questions, so as to establish (as a matter of additional interest) whether
the key determinants operate similarly on both sexes over time.
The main hypothesis driving our research is that historical contexts
of high environmental stress contributed to an increase in anthropo-
metric inequality in the absence of signicant institutionalized social
provisions. In such contexts, socioeconomic status would condition ac-
cess to an adequate diet in both quantitative and qualitative terms, as
2
Child labor is considered another major source of energy expenditure and
its deleterious effect on growth and development have been demonstrated in
some studies (Ambadekar et al., 1999). Its negative effects on health are also
well known. However, its impact on adult height is still a matter of some
controversy (Cortez et al., 2007). Work during childhood, particularly in the
case of females, increases the risk of illness, thus potentially interfering with the
abovementioned balance between energy intake and energy expenditure
(O’Donnell et al., 2005).
3
Spain serves to illustrate this. Since the mid-eighteenth century, height
differentials across socioeconomic groups (i.e. according to occupation,
educational attainment, etc.) have been clearly documented by elite groups
recording average heights of more than 1.70 m in the case of men C´
amara &
García-Rom´
an, 2010; Ca˜
nabate & Martínez-Carri´
on, 2018; Fuster, 2017; Gar-
cía-Montero, 2018).
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
3
would the burden of disease and physical labor in pre-adult ages. SES
would gradually lose its ability to explain height differentials over time
(i.e., across successive groups of cohorts) as welfare state provisions
began to be more effectively implemented. Thus, the effects of SES on
height would diminish for younger cohorts of Spaniards as a result of the
overall improvements in nutrition and sanitation, as well as increased
access to health services and a broader range of facilities. For older
cohorts, however, we would expect SES to determine biological well-
being to a greater extent due to the way it mediates access to basic re-
sources and a healthier domestic environment.
Accordingly, height trends by social group should show a converging
trend among younger cohorts of Spaniards who underwent their phys-
ical growth cycle in the context of both 1) the framework of a highly
developed society and 2) widespread welfare provisions. Conversely, we
would expect to observe higher social differentials and a greater inu-
ence of SES on height within historical contexts associated with high
environmental stress and/or a low level of social provisions.
Our study covers Spanish cohorts born from the 1940s to the 1990s.
We have grouped these cohorts into 10-year groups for analysis, except
for one ve-year group (1990-94). Clearly, the length of the growth
cycle of any given cohort will exceed the decade of their group. This is a
limitation of our study that we have opted to accept in the interests of
parsimony in both our analysis and the interpretation of the results. As a
rule, all cohort groups are made up of single cohorts who went through
their growth cycle in progressively improving environmental condi-
tions. By way of a brief overview, the socioeconomic and political
conditions in Spain in the decades analyzed were as follows. In the
1940s, Spain was characterized by the adverse effects of the Civil War.
Autarchy held back the economy until the end of the 1950s, although in
this decade an economic recovery and an acceleration of the urbaniza-
tion process took place (Prados de la Escosura & Ros´
es, 2012). During
the 1960s, all indicators of human well-being improved (Prados de la
Escosura & Ros´
es, 2021). The progress of the welfare state from 1975
onwards enabled inequalities to be reduced through the social redistri-
bution of income. In the 1980s, the welfare state was broadened and
strengthened thanks to a substantial growth in public spending on ed-
ucation and health. The new Historical Index of Human Development
reveals that after three decades of progress in living standards, Spain
closed the gap with Europe in around 1990 (Carreras & Tafunell, 2021;
Prados de la Escosura, 2021). Nevertheless, the episode of economic
recession in Europe in the early 1990s caused unemployment to rise to
20% in 1994 and slowed economic growth.
2. Data and methods
The study uses microdata from the adult samples of two health
interview surveys: Encuesta Nacional de Salud de Espa˜
na (Spanish Na-
tional Health Survey – ENSE) conducted in 1987, 1993, 1995, 1997,
2001, 2003, 2006, 2011 and 2017, and the Spanish sample from the
European Health Interview Survey (EHIS) conducted in 2009 and 2014.
Both are cross-sectional surveys (there is no follow-up of individuals)
and use multi-stage stratied sampling techniques with proportionality
criteria based on sex, age and place of residence. The interviews were
held face to face and all the information provided was self-reported. For
detailed information about criteria and general methodological aspects,
see (Ministerio de Sanidad Online) and (Instituto Nacional de Estadística
Online).
We proceeded by rst, harmonizing the variables included in the
analyses across the waves of these surveys and, second, by aggregating
these data, thus obtaining one large database. The harmonization and
aggregation of this large body of data allows us to construct long-term
series of cohort heights and also provides the statistical consistency
required to produce cross-tabulations of height as well as a number of
key explanatory variables. To homogenize the respondent type, only
direct informants were selected. Data provided by proxies were used in
the ENSE of 2003 and 2006 but these were discarded for the analysis.
Furthermore, only individuals with Spanish citizenship were selected.
4
Age and/or year of birth were used to sort individuals into the cohort
groups that formed the basis of our approach.
The age of the respondents selected for analysis was restricted ac-
cording to two criteria: they had to be over 20 years old in order to have
completed their physical growth process and they had to be under 50
years old in order to avoid distortion of the data due to age-related
shrinkage.
56
After the selection and grouping of birth cohorts, the age
range of the respondents included in our dataset was 23–47 at the time
of interview. The aggregation of the microdata from different waves of
ENSE enabled us to obtain a good representativeness of cohorts born
throughout the twentieth century. Furthermore, this allows us to
observe the evolution of the key variables of the study for each group of
cohorts in time. In this respect, it is important to note that previous
studies based on the ENSE show that the mean height of a group of
cohorts remains very stable once adulthood is reached (Spijker et al.,
2008). Table 1 shows the number of valid cases according to each var-
iable of analysis.
Height without shoes is self-reported in centimeters and the wording
of this item is uniform across surveys (“Approximately, what is your
height without shoes?”). It is well known that people tend to over-
estimate their height, which might be problematic for the use of this
indicator in clinical practice at the individual level. However, at a
population level, self-reported height has displayed very high correla-
tions with measured height (Rowland, 1990) and it has been used as a
valid measure in studies that investigate associations between anthro-
pometric parameters, health predictors and health outcomes (Lipsky
et al., 2019). In the case of Spain, the validity of self-reported height to
depict general trends over time and socioeconomic differentials has been
previously demonstrated (e.g. Spijker et al., 2008; C´
amara, 2015). For
the case at hand, it can be seen that the height distributions resulting
from our sample roughly follow a normal distribution curve. While
Table 1
Sample size of valid cases by variable of interest.
6
.
Information about Valid cases
Height 73,699
Educational attainment 72,905
Educational attainment (household head)
a
34,844
Social class (household head) 32,551
Region of residence 73,741
Age 73,741
Population size (municipality of residence) 73,741
Sex 73,738
Marital status 73,665
Source: Own calculations from the abovementioned sources.
a
Respondents who headed households amounted to 35,178 whereas those
who did not totaled 38,563.
4
Immigration ows and the immigrant stock in this country prior to the
decade of 2000–2010 were low. According to the 1991 population census, a
mere 0.9% of the population was foreign-born, increasing to 1.4% in 1996 and
1.5% in 1998 (INE, online a,b). ENSE 2003 asked for citizenship but not for
country of birth. For this reason, and given that the date (age) of arrival in
Spain was not provided in any survey, we opted to use the variable citizenship.
It should be noted that, within the age range of respondents used in this
research, the proportion of foreign-born Spanish citizens sampled in the surveys
was negligible in the cross-tabulations of cohort groups by the key variables of
analysis: 3.3% in 2009 and below 0.5% in the rest of the surveys.
5
Shrinkage may occur gradually from age 40 onwards, but especially after 50
(Birrell et al., 2005; de Groot et al., 1996; Dey et al., 1999).
6
Sex and age of the household head are not included in the analysis because
these variables only offer information for a limited number of observations.
Furthermore, 93% of household heads were male and only 7% female.
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
4
0 and 5-digit preference in self-reports generally results in heaping, this
occurs at the two tails of the distribution, which tends to remain sym-
metric for the most part. Moreover, the standard deviations are highly
constant across cohort groups and subgroups and are very close to those
found in normal distributions of measured heights (Cole, 2000, Fig. 1).
Missing height values (5% of the whole sample) were not randomly
distributed across the control variables used in our analyses. For
instance, missing heights are more frequent for older cohorts, less
educated individuals and women. For these reasons, we imputed any
missing values and contrasted the results of our analyses with and
without imputed heights (not shown; available upon request). As the
differences were negligible in terms of height trends and regression
coefcients, we opted to keep the imputed heights in order to achieve
statistical consistency for the diverse cross-tabulations implemented in
the descriptive analyses. Table 2 displays the valid cases in the nal
sample by cohort group and sex.
As we can observe in Fig. 1 and Table 2, the nal sample size differs
noticeably across the cohort groups. This is an expected effect of both a)
the available waves of the surveys used and b) the criteria for data se-
lection (i.e., age/cohort restrictions). For instance, individuals who are
included within the most recent birth cohort group (1990-94) may only
be drawn from the latest available survey which was conducted in 2017.
Coherently, this cohort group is made of individuals with a reduced
range of ages (24–27 years old). Consequently, there are fewer valid
cases for this cohort group (also because this is a 5-year cohort group). In
contrast, the individuals of the cohort group 1960-are taken from the
surveys carried out between 1987 and 2014 and their age range is
complete (23–47 following the restrictions applied).
Aside from the age range, other sources of heterogeneity in the
composition of these cohort groups exist. For instance, the cohort groups
differ in terms of their share of educational levels. This is an expected
result of the socioeconomic change in Spain (younger generations
attained higher levels of education as discussed below). Both the sample
size of cohort groups and the difference in their composition due to the
covariates involved in the analysis may potentially affect the results of
trends and differentials in height. For this reason, all the results that are
commented and discussed in this paper are based on multivariate
regression models that allow for the testing of the statistical signicance
of both inter-cohort changes in height and height differentials by SES-
related variables once the sample size of each cohort has been taken
into account and the effect of the remaining covariates has been
controlled for.
We will now describe the main variables that are included in the
analysis of this study.
Socioeconomic status: We have used educational attainment and
occupational category as proxies for socioeconomic status (SES).
7
To our
knowledge, previous anthropometric studies in Spain only test the effect
of SES as approximated by occupation and/or education level of the
respondents. Although we may assume that the respondent’s SES is
related to parental SES to a certain extent, both the respondent’s age and
the process of social mobility could distort the interpretation of height
differentials according to SES on the sole basis of the former. In other
words, it is important to relate height reached in adulthood to the pre-
vailing household socioeconomic conditions during the physical growth
cycle. This can only be estimated by using information on the SES of the
household head. In this study, we have included both educational
attainment and occupational category of the household head in order to
test their effect on height differentials across birth cohort groups.
Educational attainment had to be harmonized across surveys, as
sometimes the person interviewed was asked for the number of years of
education and other times for the highest level of education attained.
Furthermore, the educational levels are not uniform in the response set
due to changes made in the educational system over the last ve decades
in Spain. We have used the abridged International Standard Classica-
tion of Education (ISCED) to harmonize this variable into four categories
(the results are shown in Fig. 2):
1. Less than primary: individuals who did not complete the rst level at
school, which implies less than six years of schooling.
2. Primary: individuals who did complete the rst level at school, thus
receiving at least six years of schooling.
3. Secondary: individuals who completed the second level at school (old
system), secondary school (under the new system), or who obtained
a professional training qualication (under the new system; equiv-
alent to secondary school in total years of schooling).
4. University: individuals who obtained a university degree, PhD, or any
equivalent under the old system.
Primary studies have been taken as the reference category to analyze
height differentials. The share of this category over time, though vary-
ing, is systematically higher than 20%, which contributes to a higher
consistency of analysis among the younger cohorts analyzed.
Occupation has been harmonized into four ordinal categories
following the simplest codication used for the different ENSE waves.
The more recent waves of the ENSE provide much more detailed data on
occupation (through the four-digit codes of the National Classication of
Occupations: CNO79 in 2001, CNO94 in 2003 and 2006, and CNO11 in
2011, 2014 and 2017), whereas the early waves only include occupation
in broad categories (i.e., skilled workers, non-skilled workers, etc.).
Given that the more recent waves also include a variable referred to as
“CLASS”, obtained by classifying the occupations into seven broad cat-
egories that are roughly equivalent to the former response sets, we have
been able to harmonize this variable into the following four categories:
- Occupational category 1: Unskilled workers.
- Occupational category 2: Skilled workers.
-Occupational category 3: Intermediate positions in public adminis-
tration, freelancers and white-collar workers.
- Occupational category 4: High positions in public administration,
businessmen, CEOs and liberal professions.
For the survey that did not include the variable “class”, we were able
to infer it using occupation at time of interview (or most recent occu-
pation in the case of the unemployed or retired). Fig. 3 shows the
resulting distribution of occupation according to the four categories
described above.
Analyses: cohort series and regression model specications. Height series
are depicted for men and women separately using birth cohort as a time
scale. For this purpose, birth cohorts have all been grouped into decades
except for the youngest group, which covers a ve-year period. These
series according to the key variables of analysis can be found in the
appendix of this study (Figs. 9 and 10).
Height differentials by SES over time are examined through multi-
variate linear regression models. This technical approach is addressed so
as 1) to control for additional variables which might inuence the trends
and/or height differentials found and 2) to assess whether the trends and
differentials obtained are statistically signicant once the varying
7
Income was ruled out in this study due to the large proportion of missing
cases across surveys.
8
We have compared the result of this harmonization with the distribution
resulting from the 2011 Spanish census. Higher levels of education range very
similarly across cohort groups between the two sources whereas the percentage
of those with no studies is signicantly lower in the surveys with respect to the
census among the oldest cohorts. We tend to believe that this is due to the
differences in the codication of the original categories of education between
the two sources (surveys vs. census). Both the evolution of the distribution of
educational categories over time and gender-related differentials display a very
similar and coherent pattern between these two sources.
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
5
sample size and diverse source of heterogeneity across cohort groups are
controlled for.
As for the main explanatory variables used in this study (educational
attainment and occupational categories), we have tested their correla-
tion across cohort groups as well as potential interactions in order to
specify our regression models. The level of correlation was examined
through the Spearman correlation coefcient (
ρ
) which is considered the
most adequate statistic for ordinal variables. Regarding the association
between the educational attainment and the occupational category of
household heads,
ρ
=0.541 (sig =0.000; all cohorts),
ρ
=0.525 (sig =
0.000; cohorts 1940-49) and
ρ
=0.636 (sig =0.000; cohorts 1980-94).
Regarding the association between educational attainment (of those
who are not head of the household) and the occupational category of the
head of the household, the coefcient reported the following values:
ρ
=
0.349 (sig =0.000; all cohorts),
ρ
=0.366 (sig =0.000; cohorts 1940-
49) and
ρ
=0.330 (sig =0.000; cohorts 1980-94). These are all
expected and coherent results. A higher correlation is found when the
variables refer to the same individual (the household head). Also, the
correlation between educational attainment (of those who are not HH)
and the occupational category of HHs decreases, though slightly, be-
tween the two cut-off points of our analysis (1940-49 vs. 1980-94).
These levels of correlations can be considered as moderate (for the
rst relationship) and relatively low (for the second relationship)
9
.
Finally, a number of interactions between these variables were tested
with no signicant effects.
10
In light of the former tests and also considering that the models did
not exclude any of the SES-related variables of the household heads due
to collinearity effects, they were both included, together with the
Fig. 1. Height distributions by broad cohort groups (1940–1994)
Source: Own calculations based on the above-mentioned data sources.
Table 2
Valid cases (nal sample used in regression models) by cohort group and sex.
Cohort Men Women Total
1940-1949 2,214 2,376 4,590
1950-1959 4,869 5,156 10,025
1960-1969 11,131 13,170 24,301
1970-1979 11,786 13,293 25,079
1980-1989 4,153 4,506 8,659
1990-1994 498 547 1,045
Total 34,651 39,048 73,699
Source: Own calculations based on the above-mentioned data sources.
9
These results are also coherent with our research hypotheses. On the one
hand (rst relationship analyzed), and due to the change in the economic
structure of Spain and other European countries, the share of skilled and semi-
skilled jobs has increased over time. This is necessarily associated with an in-
crease in formal education in order to access the labor market. On the other
hand (second relationship analyzed), educational attainment becomes less and
less dependent on SES (as approached by the occupational category of the head
of the household) as welfare state provisions (democratization in access to
education in particular) rise in a given society.
10
The interaction between the educational attainment and the occupational
category of HHs (upper education*upper occupation) was tested and it was not
signicant in any of the cohort groups analyzed. No substantial change was
detected in the coefcients of the main explanatory variables applied to both
men and women. The interactions between each educational level of in-
dividuals and the two broad categories of education of HHs were also tested
with no signicant effects.
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
6
individuals’ educational attainment in the series of models that close the
results’ section of this study.
All the covariates listed below are also included in the models
following the usual norms and protocols. Categorical variables are
introduced by means of dummy variables whereby one category/vari-
able is excluded, thus serving as the reference category when inter-
preting the regression coefcients. The models include the following
control variables:
- Age (which technically produces the effect of including a time-trend,
thus helping to illustrate the improvement of environmental condi-
tions across single cohorts included in a given cohort group).
- Region of residence (in total, there are 18 regions, the 17 Spanish
Autonomous Communities and the two Northern African Autono-
mous Cities of Ceuta and Melilla that are considered as a single
region).
- Population size of place of residence (up to 10,000 inhabitants; from
10,001 to 50,000; from 50,001 to 100,000; more than 100,000).
- Marital status of the respondent. The latter, together with age, are
instrumental variables which serve to indirectly control for the
actual role of the respondent within the household. Ideally, the in-
uence of the household head’s SES on biological well-being should
be tested on the height of their descendants. In practice, however,
such an approach is not possible as kinship within households is not
provided in the surveys, but we can at least distinguish between the
head and non-heads of any given household.
Finally, for the models based on the household head’s SES, cohort
groups 1980-89 and 1990-94 were merged for the purpose of statistical
consistency. The results section presents several graphs summarizing the
main regression results. We only graphically represent those coefcients
that are statistically signicant. The complete regressions results can be
found in detail in the Appendix.
3. Results
Fig. 4 (Table 3 in the Appendix) displays the trend in mean cohort
height for individuals aged 23–47 (in this analysis we use all heights
available irrespective of whether the individual is the household head or
not). Control variables do not include the SES of the HHs. Average
stature shows a marked upward trend for birth cohorts born from the
1940s to the 1980s in the case of men. For women, this upward trend
started two decades later. In the case of men, there is evidence of a
considerable increase in mean height of about 5 cm among these birth
cohorts. Among women, the upward trend is less pronounced, repre-
senting an increase of around 2 cm over 40 years. For both sexes, the
upward trend stagnated and even descended in the 1990s.
Figs. 5 and 6 (Table 4 in Appendix) show height differentials ac-
cording to educational attainment, using primary studies as the refer-
ence category. As before, we used all valid heights, regardless of whether
an individual is a household head or not. The general picture obtained
points to a decrease in height differentials over time although the dif-
ference in favor of those with tertiary studies noticeably persists among
cohorts born between the 1960s and 1990s. That said, men born in the
1940’s cohort with a university degree were estimated to be around 4.5
cm taller than those with primary studies, whereas this difference is
about 3 cm among the youngest cohorts analyzed. Height differences
between other educational categories exhibit a clear decreasing trend
across birth cohorts or even disappear as indicated by the absence of
statistically signicant results.
The above analysis is replicated for women in Fig. 6. We found that
the height differentials between the educational categories follow the
same general pattern but are noticeably smaller than those among men
and, moreover, they remain more constant over time. For instance,
women with university studies are estimated to be 2 cm taller with
respect to those with primary studies for all birth cohorts analyzed
except for the oldest cohort group where no signicant difference is
found (probably due to the fact of the very low proportion of women
Fig. 2. ISCED-harmonized educational attainment in Spain among individuals aged 25+. Birth cohorts 1940-94
8
Source: own calculations based on the above-mentioned data.
Fig. 3. Distribution of occupation (%) by birth cohort
Source: own calculations based on the above-mentioned data.
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
7
who went to university within that generation). Women with secondary
studies born between the 1940s–1980s are around 1 cm taller than those
with primary education. And nally, women with less than primary
studies are estimated to be shorter than those with primary studies for
the cohorts from the 1940s to the 1970s. It is interesting to note that this
negative height difference almost tripled among these birth cohorts.
This is most likely due to the changing socioeconomic prole embodied
by these women with no studies. During a period of strong growth in
female schooling, the still signicant percentage of women who did not
nish primary studies would probably represent the most impoverished
sectors of Spanish society.
Figs. 7 and 8 (Table 5 in Appendix) show the signicant coefcients
when the educational attainment of the head of the household (HH) and
the occupation category of the HH are both introduced in the set of
models together with the individuals’ educational attainment. In these
models we only include individuals who are not household heads. In
order to maintain a good statistical consistency, the variables containing
the information on household heads (education and occupational cate-
gory) have been grouped into two categories: lower (no studies or pri-
mary; unskilled or skilled workers) and higher (secondary or university;
intermediate and high positions). As a rule, either one or another of the
SES variables for HHs is signicant but not both of them. This in itself is
an interesting nding, as are the differences observed between the ef-
fects on men and women.
Among men (Fig. 7), the only and strongly signicant effect for those
born in the 1940s was that represented by the educational attainment of
the household head (more than 6 cm taller than their counterparts from
the lower educational segment of households). During subsequent de-
cades, such a strong differential is not observed again, although we can
appreciate a diversication of signicant effects and its persistence over
time. For instance, since the 1960s, individuals from higher SES
households (as proxied by the occupational category of HHs) have
maintained a height difference of between 0.5 and 1 cm over those from
lower SES households. As expected, the differentials captured by the
Fig. 4. Average height (cm) by sex and birth cohort. Spain, 1940-1994
Source: own calculations based on the above-mentioned data.
Note: the women’s coefcient for the cohort group 1960-69 is not statistically signicant (Table 3 in Appendix).
Fig. 5. Average height difference (cm), by educational attainment (males). Reference: primary studies
Source: own calculations based on the above-mentioned data.
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
8
educational attainment of individuals are lower in this approach, but
they maintain the pattern observed in the former analysis (Fig. 5). For
instance, those individuals born in the 1980s and 1990s who attained
university studies are, on average, almost 2 cm taller than those with
primary studies, once the HH’s occupation has been controlled for.
Fig. 8 reports the results for women, showing that those belonging to
households where the HH had a higher occupational category and
educational attainment are estimated to be taller. This effect is highly
constant over time and systematically above 0.5 cm. In fact, it is the only
effect that persists among the younger women cohorts analyzed.
4. Discussion
The dynamics of inequalities in biological well-being during periods
of intense advances in living standards, particularly after the Second
World War, have already received attention in previous studies (e.g.
Bann et al., 2018; Cavelaars et al., 2000; Deaton, 2008; Silventoinen,
2001). In Spain, the life course of birth cohorts born between 1940 and
1994 have undergone profound economic, social, and political trans-
formations, yet little is known, so far, about how such changes have
shaped SES-related differentials in health and nutrition.
Our research hypothesis was that historical contexts of high envi-
ronmental stress would be more prone to SES-related anthropometric
differentials in the absence of signicant institutionalized social
Fig. 6. Average height difference (cm), by educational attainment (females). Reference: primary studies
Source: own calculations based on the above-mentioned data.
Fig. 7. Male height differentials (cm) by educational attainment and household head SES.
Source: own calculations based on the above-mentioned data.
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
9
provisions and that the SES would gradually lose its ability to explain
height differentials over time (i.e., across successive groups of cohorts)
as welfare provisions became more effectively implemented. The results
of this paper only partially conrm this hypothesis. For the most part,
our results conrm the convergence of trends in adult height by
educational attainment and occupational category in Spain over the
second half of the twentieth century. However, the overall reduction of
anthropometric differentials is mainly related to the overcoming of the
most negative effects of the Spanish civil war and the autarchic period.
From the 1960s, SES-related differentials were mostly stable.
11
At least
they did not decrease as had been expected within a context of major
improvements in terms of social provisions (it should be noted that
Spain has been a democracy since 1978).
As for educational attainment, the convergence may be partly related
to the spread of access to basic levels of education for the bulk of the
Spanish population. In other words, the SES-related effects that are
initially visible in educational levels relaxed or partly diluted when
access to higher levels of education became democratized. In short, the
gap in height between the higher and lower educated segments of the
Spanish population has indeed decreased but our results indicate
persistent differences in favor of those with university studies with
respect to those with primary education (2–3 cm among the male co-
horts born from the 1960s and 1.5–2 cm among the female cohorts born
from the 1950s).
Similarly, we can observe that the net effect of the occupational
category of the household head on individuals’ average heights has
remained stable and statistically signicant over the last decades
analyzed (around 1 cm among males and more than 0.5 cm among
women). In fact, previous studies conducted on male height in Spain
show that the gap between some occupational categories of individuals
(semi-skilled non-manual workers and manual workers) widened during
the central decades of the twentieth century. These authors suggest that
this is a reection of the general increase in inequality between socio-
economic groups (Ayuda & Puche, 2014).
Previous research on other European countries reveals a decrease in
height differentials between SES groups (e.g., Bann et al., 2018 by using
the father’s occupation as a proxy of SES). Other similar studies argue
that such a convergence in terms of net nutritional status is most likely
related to economic progress and the expansion of the welfare state in
the nal decades of the twentieth century (Bodzsar et al., 2015; Hauspie
et al., 1996). Nevertheless, considerable inequalities in nutritional status
are still present even in the most advanced industrialized societies, and
to a greater extent in developing countries (Bredenkamp et al., 2014;
Komlos & Baur, 2004). For instance, in Poland, although improvements
have been made in living conditions over a period of almost 50 years, as
reected in the secular trend in children’s height, there are still differ-
ences in height associated with social inequalities (Gomula et al., 2021,
by using four factors to approximate SES: level of urbanization, parents’
education and number of children). Furthermore, the evidence on the
convergence of height trends by educational attainment is not conclu-
sive either. Studies conducted of English children (Galobardes et al.,
2012, using the mother’s education as the key explanatory variable) nd
that differences in height, though probably smaller than in the past,
persisted. In France, height inequalities associated with education
remained virtually unchanged, and large, between 1970 and 2003:
around 4.5–5 cm among men and around 2.5–3 cm among women
(Singh-Manoux et al., 2011). This study shows that height differentials
as a function of income were much more moderate that when examined
in terms of education.
These and other evidence from previous research throws into ques-
tion whether general improvements in living standards in Western Eu-
ropean welfare economies always lead to convergence in terms of adult
stature (Silventoinen, 2003; Singh-Manoux et al., 2011). A paper that
analyzes the trends in physical stature of the Swiss population born
between 1955 and 1985 concludes that the quality of the health care
system and equal access to it seem to have a greater impact than other
redistributive aspects of the welfare state (Kues, 2010). Other research
papers question how state policies and practices may affect population
Fig. 8. Female height differentials (cm) by educational attainment and SES of household head
Source: own calculations based on the above-mentioned data.
11
Previous research on Spanish male cohorts born between 1840 and 1964
nds that height differentials by educational attainment increased during the
autarchic years (C´
amara et al., 2019).
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
10
health (Bhatta, 2021; Bird et al., 2019; McDonough et al., 2010) and
there are some examples of the critical effect that public policies that
promote income redistribution and universal access to education, health
and sanitation services may have on nutrition and living conditions
(Nú˜
nez & P´
erez, 2021, Monteiro et al., 2010).
At this point, it is also worth commenting on the differences found
between men and women. Height differentials by SES (regardless of the
approximation used) among men are larger and they vary more over
time with respect to women. These differences between the sexes could
be related to both a higher eco-sensitivity (i.e., susceptibility to envi-
ronmental conditions and changes in them over time) among men
(C´
amara et al., 2021, Zimina et al., 2019; Thurstans, et al., 2020a, b;
Spake et al., 2022) and to the fact that access to higher education for
older female cohorts was very limited in Spain (Ballarín Domingo, 2001;
Heath & Jayachandran, 2016; Pl¨
otz, 2017). We are inclined to believe
that the role of eco-sensitivity is more inuential in this regard, given
that the results of the analysis based on the educational attainment of
the household head (mostly men) paint the same picture.
Finally, the results also reveal that the upward trend in intergener-
ational growth shows clear signs of having come to an end, at least
temporarily, among Spanish cohorts born from the 1990s. This applies
to men and women, and it seems that this interesting result is not related
to any signicant variations in the height differential by SES. This
nding coincides with research from different European countries,
suggesting that growth has virtually stopped in northern Europe and
may have started to slow down in southern Europe. It is reasonable to
assume that there might be an upper limit to average heights, especially
in countries where living standards are already very high, such as Spain
and a number of other European societies. Some studies relate the
stagnation of cohort stature with the spread of obesity (Bann et al.,
2018). Early studies of populations in Finland and Sweden show a
slowdown in heights in the 1990s (Silventoinen et al., 2001). Using data
from military recruitments, previous research nds that some European
countries reached a height plateau in the 1990s, including Italy
(Larnkjær et al., 2006; Gohlke et al., 2009), but not Greece, where re-
cruits continued to grow (Papadimitriou et al., 2008). A study carried
out in the Netherlands, the tallest population in the world, found that the
long secular increasing trend in height has slowed down in recent de-
cades (Sch¨
onbeck et al., 2013). Similar results have also been found in
other European countries and in the United States (Komlos, 2007; Kues,
2010; Vinci et al., 2019).
After decades of intense growth, and similarly to the Dutch and other
European and North American populations, the Spanish population may
have reached a stable mean height in the 1990 cohorts, an issue that will
require further research in the near future.
5. Conclusions
Overall, the results obtained in this study lead us to conclude that
inequalities in the biological dimensions of well-being have tended to
diminish over time among Spaniards born since the 1940s. However,
this conclusion must be qualied in view of the evidence obtained from
both the pace of the reduction of height differentials over time and the
combination of the two approaches to SES (educational attainment and
occupational category). First, our study shows that height differentials
persisted during the decades of Spain’s modernization process and the
implementation of welfare provisions. Second, the results demonstrate
that the way SES is operationalized matters in itself, as they indicate that
height differentials according to educational attainment may be partly
explained by the association of this variable with the household head
occupation (i.e. SES-related occupation categories). Once this factor is
controlled for, height differentials by educational attainment diminish
or even disappear in the case of women.
Thus, the variety of approaches used to address this issue prompt us
to further qualify this apparent convergence. While differences in stat-
ure by educational level have mostly reduced over time, the differences
by occupational category (that of household heads) largely persist. In
general, height differentials decreased among the younger Spanish co-
horts when compared with those cohorts born during the 1940s and the
1950s, thus prior to the implementation of welfare state provisions. This
is particularly true in the case of men, for whom the education-related
height differentials were very large in the 1940s. These differentials
were smaller among women and remained more constant over time.
These results should be interpreted taking two facts into consideration:
the later access of women to education and the likely greater eco-
sensitivity of men.
In summary, we nd that the association between occupation and
height differentials is much weaker than that of educational attainment,
but it is persistent over time. This implies that education may play a
more complex and diverse role in determining biological well-being,
above and beyond acting as a sole proxy of SES. In addition, and most
importantly, it indicates that height differentials by educational attain-
ment may mask actual socioeconomic differences in biological well-
being among younger generations. This could be due to the extension
of education to lower classes in societies with high levels of welfare
provision. Alternative approaches and indicators should therefore be
contrasted with these results. In light of this evidence, the hypothesis
that social provisions have led to a reduction in inequality is not fully
conrmed. Instead, our results support the idea that, regardless of the
level of social provisions, the household environment still appears to be
a relatively signicant mediator in access to certain basic resources and
factors related to health and nutrition. Of course, the nature of this
mediation and the specic factors involved are yet to be determined,
given the limitations of the (mostly) contextual approximation we have
performed through cohort groups.
It is clear that our results add meaning to conclusions on the evolu-
tion of inequalities in biological well-being reached solely on the basis of
educational attainment. We have certainly been able to verify that in
Spain, the differentials in adult height according to education level have,
in general, reduced over time. However, in light of the contrasts
revealed with the approach based on occupational categories of house-
hold heads, we are inclined to believe that education is a better proxy of
SES in contexts where access to education is highly determined by
economic factors. Conversely, its usefulness in the analysis of height
differentials decreases as education becomes more democratized. This is
not surprising since, for the most part, the opening of access to the lower
classes of higher educational levels coincided, in Spain at least, with the
implementation of a number of social provisions including access to
health care and improved sanitation.
Authors contributions
Bego˜
na Candela-Martínez: Writing - Original Draft, Data curation,
Investigation, Formal analysis, Visualization. Antonio D. C´
amara:
Conceptualization, Writing- Original draft preparation, Methodology,
Software. Diana L´
opez-Falc´
on: Writing- Original draft preparation, Su-
pervision, Writing- Reviewing and Editing, Resources. Jos´
e M. Martínez-
Carri´
on: Supervision, Writing - review & editing.
Funding
This work was supported by the Ministry of Science, Innovation, and
Universities (Government of Spain), Projects HAR2016-76814-C2-2-P
(MCIN/AEI/10.13039/501100011033/FEDER/UE); PID2020-113793
GB-I00 (MCIN/AEI/10.13039/501100011033/FEDER/UE); Network
PHA-HIS. RED2018-102413-T (MICINNMICIU/AEI/UE).
Ethical Statement
We do not declare any potential ethical conict in relation to the data
and methods used in this research. No experimental procedure was
developed and the microdata used in the analyses was previously
B. Candela-Martínez et al.
SSM - Population Health 18 (2022) 101126
11
anonymized by the National Spanish Statistical Ofce (INE). These data
are managed, preserved and released by INE and they were free-
accessed online.
Declaration of competing interest
The authors declare that they have no conict of interest.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.ssmph.2022.101126.
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