Economics and Human Biology 17 (2015) 202–207

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Differences in height by education among 371,105 Dutch military conscripts Ying Huang a, Frans van Poppel b,c, L.H. Lumey a,d,* a

Epidemiology Department, Mailman School of Public Health, Columbia University, New York, USA Netherlands Interdisciplinary Demographic Institute (NIDI/KNAW)/University of Groningen, The Hague, The Netherlands c Department of Sociology, Utrecht University, The Netherlands d Department of Molecular Epidemiology, Leiden University Medical Center, The Netherlands b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 21 August 2014 Received in revised form 13 November 2014 Accepted 14 November 2014 Available online 22 November 2014

Adult height is associated with a variety of familial and socio-economic factors and large, well-defined populations are needed for a reliable assessment of their relative contributions. We therefore analyzed recorded heights from the military health examinations of 18-year conscripts in the Netherlands born between 1944 and 1947 and observed large differences by their attained education and by their father’s occupation. The 5.1 cm height gradient from lowest to highest education level was more than twice as large as the gradient between father’s occupation levels. The education gradient was not explained by common determinants of height including paternal occupation as a measure of familial background, region of birth, family size, or religion. ß 2014 Elsevier B.V. All rights reserved.

JEL classification: I12 I21 J17 Keywords: Height Socio-economic background Education Cognition Military conscripts

1. Introduction The association between body height and socioeconomic factors including parental occupation and a subject’s education is a well-recognized phenomenon (Peck and Lundberg, 1995; Meyer and Selmer, 1999; Silventoinen et al., 2001, 2003; Komlos and Kriwy, 2002; Gyenis and Joubert, 2004; Heineck, 2006; Krzyzanowska and Umlawska, 2010; Jordan et al., 2012). These same factors often underlie regional gradients and urban vs. rural gradients in height which have been observed in * Corresponding author at: Epidemiology Department, Mailman School of Public Health, Columbia University, 722 West 168 Street, Rm 1617a, New York, NY 10032, USA. Tel.: +1 212 305 9222; fax: +1 212 342 0168. E-mail address: [email protected] (L.H. Lumey). http://dx.doi.org/10.1016/j.ehb.2014.11.002 1570-677X/ß 2014 Elsevier B.V. All rights reserved.

several countries including the Netherlands (Fredriks et al., 2000; Hiermeyer, 2009; Schonbeck et al., 2012). Heights are now widely seen as a useful measure of human welfare (Steckel, 2009). Family studies suggest that most of the variation in height is under genetic control (McEvoy and Visscher, 2009) but environmental factors must also be important as suggested by the continuing secular increase in heights. In the Netherlands, this increase has been especially well documented. The increase began in the second half of the 19th century and accelerated in the second half of the 20th century (de Beer, 2004). By the end of the 20th century, the Dutch had become the tallest in the world (Fredriks et al., 2000; Komlos and Breitfelder, 2007; Schonbeck et al., 2012). Among Dutch military conscripts, the mean height

Y. Huang et al. / Economics and Human Biology 17 (2015) 202–207

increase since 1865 has been 21 cm (van Wieringen, 1986) and of this increase 9 cm was already achieved by 1940 (Brinkman et al., 1988). The most important environmental improvements are likely to be from better childhood living conditions in nutrition, health practices, and control of diseases, but these factors are hard to disentangle (Silventoinen, 2003). Family size is a factor (Fredriks et al., 2000), and psychosocial stress and adverse social conditions may also play a role (Batty et al., 2009). As familial conditions are closely related to occupation and education, well defined populations are needed to reliably assess the relative impact of both on adult height. In addition, regional differences in socio-economic conditions and education need to be taken into account (Vliegen et al., 1981). We therefore examined in a Dutch national conscript population the relation of conscript’s education and father’s socio-economic position to height at age 18 and the effects of region of birth, family size, and religion. 2. Methods

203

more than 6 years of formal education beyond primary school corresponding to 8–9, 10–11, 12, or 12+ years of education. Paternal occupation was ordered into five SES based categories ranging from laborers and miners, service employees (including shop assistants), farmers and farm workers, to clerical workers and self-employed individuals and managerial and professional occupations. Place of birth was classified by geographic region and urbanization to include selected cities in the North/East vs. remaining municipalities, selected cities in the West vs. remaining municipalities (including the province of Zeeland), and selected cities in the South vs. remaining municipalities. Religion was defined as Roman Catholic, Protestant (Dutch reformed or Calvinist), no religion, and other religions, including unknown. Family size was ranked by number. All remaining study subjects were included for analysis unless information was missing on height (1.8%), education (1.5%), or paternal occupation (6.8%). Because of partial overlaps of missing variables, 91.0% (n = 371,105) of the study population remained for analysis.

2.1. Study population 2.3. Statistical analysis We studied anonymized military records provided by the Dutch Ministry of Defense in 1969 for a study of the relation between early nutrition and mental performance at Columbia University (Stein et al., 1972). The records include all men of Dutch nationality born between January 1, 1944 and December 31, 1947 examined for military service in the Netherlands (n = 408,015). Military examinations were based on yearly listings of all Dutch male citizens in the national population registers. All men were called to the military service induction exam at age 18, except those living in psychiatric institutions or in nursing institutes for the blind or for the deaf–mute (0.6%). Foreign births (2.5%) were excluded. 2.2. Available measures Standing heights were measured for all men using the same military protocol with wall-mounted stadiometers. Measurements were taken without socks or shoes with the individuals’ head positioned in the Frankfort plane. From the military examination record we selected for further analysis subject’s education and paternal occupation as the variables of primary interest for this study. In addition, we selected other relevant variables for which associations with adult height have been reported (Fredriks et al., 2000), including place of birth in view of the North–South gradient in height in the Netherlands and religion and family size as closely related variables. In the Netherlands, the Catholic religion is predominant in the South and family size at the time was largest in this group (van Poppel, 1985). To evaluate the role of education, we defined six education categories, ordered by years of formal education in relation to primary school education from age 6 to 12. In the category ‘less than primary school’, we included individuals with special education for the handicapped. We then distinguished men who had received 2, 4, 6, or

We evaluated differences in height by education, paternal occupation, and other selected variables and carried out multiple linear regression models to evaluate the independent contribution of education, paternal occupation, and the other covariates to height at age 18. 3. Results Social and demographic characteristics of the study population are listed in Table 1 together with the range of heights of 18-year old conscripts within each of the variable categories not adjusting for other variables. There is a monotone height increase with a gradient of 5.1 cm comparing conscripts with the lowest and highest education level (range from 174.8 cm to 179.9 cm) and a 2.4 cm gradient comparing conscripts with fathers of the lowest and highest occupation status (range from 176.1 cm to 178.5 cm). In addition, there is a height difference by region of birth (range from 175.2 cm in the rural South to 178.7 cm in the urban North) and by religion (176.4 cm among Roman Catholics vs. 178.2 cm among Protestants). Starting at family size 2 (average height 178.2 cm), average heights tend to be lower among larger families (Table 1). The height increase with increasing conscript education is seen within all paternal occupation groups. It ranges from 4.3 cm comparing sons of miners and laborers to 5.4 cm comparing sons of fathers with professional or managerial positions. (Table 2 and Fig. 1) A monotone height increase by paternal occupation is seen within all conscript education levels (Table 2). These patterns are reflected in linear regression models with explanatory variable either subject’s education alone or paternal occupation alone (Table 3, Model A, upper and lower panels). With additional adjustment of subject’s education for paternal occupation (Model B, upper panel), the education gradient narrows from 5.1 cm to 4.4 cm, and

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Table 1 Height at age 18 by conscript education, paternal occupation, place of birth, family size and religion (univariate distributions).

Education 1. Less than primary school (%) 2. Primary school (%) 3. Primary + 2 years (%) 4. Primary + 4 years (%) 5. Primary + 6 years (%) 6. Primary + more than 6 years (%) Paternal occupation Miners and laborers (%) Service employees (%) Farm owners and workers (%) Clerical and self-employed (%) Professional and managerial (%) Place of birth North/East selected cities (%) North/East other (%) West selected cities (%) West other and Zeeland (%) South selected cities (%) South other (%) Number of brothers and/or sisters 0 (%) 1 (%) 2 (%) 3 (%) 4 (%) 5+ (%) Unknown (%) Religion Roman Catholic (%) Protestant (%) None (%) Other and unknown (%)

N

%

Height (SD), cm

18,586 53,589 147,111 103,299 36,531 11,989

5.0 14.4 39.6 27.8 9.8 3.2

174.8 175.8 177.2 178.2 179.1 179.9

(6.6) (6.4) (6.3) (6.3) (6.3) (6.3)

41,087 120,226 46,351 106,622 56,819

11.1 32.4 12.5 28.7 15.3

176.1 176.7 177.4 178.2 178.5

(6.5) (6.4) (6.4) (6.3) (6.4)

17,157 98,436 87,941 89,436 22,976 55,303

4.6 26.5 23.7 24.1 6.2 14.9

178.7 177.9 177.8 178.1 175.8 175.2

(6.5) (6.4) (6.5) (6.3) (6.4) (6.2)

17,607 63,433 73,244 62,557 46,601 107,565 98

4.7 17.1 19.7 16.9 12.6 29.0 0.0

178.0 178.2 178.0 177.6 177.3 176.5 176.2

(6.5) (6.5) (6.4) (6.4) (6.4) (6.4) (7.5)

152,940 152,875 63,279 2011

14.2 41.2 17.1 0.5

176.4 178.2 178.1 176.6

(6.4) (6.4) (6.4) (7.2)

with the further adjustment for covariates family size, religion, and place of birth (Model C, upper panel) the range narrows to 4.2 cm. The height difference comparing men with the lowest vs. the highest education level in adjusted Models B and C was therefore 14% resp. 18% smaller compared to the unadjusted Model A. The range in conscript heights comparing individuals whose fathers were in the lowest vs. the highest occupation level was 2.4 cm (Table 3, Model A, lower panel). This range narrows to 1.4 cm with additional adjustment for education (Model B, lower panel) and to 1.0 cm with the further adjustment for the other covariates (Model C, lower panel). The decrease in occupation height range in adjusted Models B and C is therefore 42% resp. 58% smaller compared to the unadjusted Model A.

4. Discussion In 18-year old conscripts in the Netherlands born between 1944 and 1947 we observe a height gradient of 5.1 cm comparing subjects across education categories. A gradient of this magnitude has previously been reported in studies among white American females (Komlos and Baur, 2004) and Norwegian males (Meyer and Selmer, 1999). A smaller height gradient was reported in Swedish conscripts born 1950–1975 (Magnusson et al., 2006) and German conscripts born 1975–1979 (Hiermeyer, 2009). The gradient is robust to adjustments for paternal occupation and other height correlates including region of birth and family size. In Sweden, adjustments were also made for parental education and socio-economic index and in Germany for region of birth. Our height differences across education levels are an order of magnitude larger than the 0.2 cm difference

Table 2 Height in cm at age 18 by conscript’s education and paternal occupation. Paternal occupation

Miners and laborers

Service employees

Farm owners and workers

Clerical and self-employed

Professional and managerial

Total

174.3

174.8

175.4

175.3

174.7

2. Primary school

4455 175.3

8284 175.6

2290 176.2

1973 176.6

1584 176.3

3.

10,566 176.5

23,911 176.8

5784 177.3

9236 177.8

4092 178.0

4. Primary school + 4 years

17,036 177.3

54,335 177.7

26,653 178.6

35,717 178.4

13,370 178.7

5. Primary school + 6 years

7593 177.3

28,036 178.2

8742 179.1

40,200 179.1

18,728 179.4

6. Primary school + more than 6 years

1189 178.6

4586 179.2

2085 180.0

14,808 179.8

13,863 180.1

248 176.1 (6.5) 41,087

1074 176.7 (6.4) 120,226

797 177.4 (6.4) 46,351

4688 178.2 (6.3) 106,622

5182 178.5 (6.4) 56,819

174.8 (6.6) 18,586 175.8 (6.4) 53,589 177.2 (6.3) 147,111 178.2 (6.3) 103,299 179.1 (6.3) 36,531 179.9 (6.3) 11,989 177.4 (6.4) 371,105

Height (SD) n Education level 1. Less than primary school

Total

Primary school + 2 years

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Fig. 1. Height in cm at age 18 by conscript education and paternal occupation.

Table 3 Relation of conscript education and paternal occupation to height in cm (95% confidence interval) at age 18.

Education Less than primary school Primary school +2 years +4 years +6 years +more than 6 years Paternal occupation Miners and laborers Service employees Farm owners and farmers Clerical and self-employed Professional and managerial

Model Aa

Model Bb

Model Cc

1.02 ( 1.12, 0.91) Reference 1.38 (1.32, 1.45) 2.39 (2.33, 2.46) 3.24 (3.16, 3.33) 4.07 (3.94, 4.19)

0.96 ( 1.07, 0.86) Reference 1.24 (1.17, 1.30) 2.07 (2.00, 2.14) 2.70 (2.61, 2.79) 3.48 (3.35, 3.60)

0.90 ( 1.00, 0.79) Reference 1.07 (1.01, 1.13) 1.83 (1.76, 1.89) 2.54 (2.46, 2.63) 3.25 (3.12, 3.37)

0.59 ( 0.66, 0.52) Reference 0.72 (0.65, 0.79) 1.45 (1.40, 1.50) 1.84 (1.77, 1.90)

0.37 ( 0.44, 0.30) Reference 0.59 (0.53, 0.66) 0.85 (0.80, 0.91) 1.02 (0.96, 1.09)

0.08 ( 0.15, -0.01) Reference 0.69 (0.62, 0.75) 0.78 (0.72, 0.83) 0.95 (0.88, 1.01)

a

Model A: Linear regression model with as explanatory variable either subject’s education alone or paternal occupation alone. Model B: Regression model with as explanatory variables paternal occupation and subject’s education. Model C: Regression model as in B with additional adjustment for family size, religion, and place of birth. Table entries represent height differences from the reference group. b c

reported for boys of ages 0–20 years in the Netherlands in 1997 (Fredriks et al., 2000). The height differences in the group 0–20 years in the 1997 study will underestimate the actual differences at age 18 however if they are agedependent. Cross-sectional height data for ages around puberty also ignore individual differences in maturation and growth tempo of same-age individuals. Based on the reported mean height and standard deviation scores of 18-year old boys in the 1997 study we would only expect a height difference of 1.4 cm comparing subjects in the lowest vs. highest education category. It has to be recognized however that our data were collected 30 years earlier and that the relations between occupation, education, and height may have changed over time. The height differences in our study are not directly comparable to those found among the Swedish conscripts

(Magnusson et al., 2006) because in Sweden the methodology differed and mean heights were not given by conscript education status. The Dutch conscript height differences by level of education appear to be larger than those found among German conscripts born 1975–1979 (Hiermeyer, 2009). The latter showed differences not exceeding 2 cm comparing the heights of men in the lowest tertile vs. the highest tertile of education. As the German conscripts represent births in a more recent time period compared to the Dutch the education height gradient could have diminished over time. The German data are also not quite comparable because of some differences in education categories and in the age of examination of the conscripts. Macro-economic and social conditions differed between the countries and these might have had an effect on

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the strength of the observed educational gradient in height. When from 1948 on the material damage caused by WWII had been repaired, the Dutch government choose an economic growth policy of which industrialization was the spearhead. After 1951, a period of uninterrupted economic growth and an explosive increase of prosperity started that lasted until the end of the 1960s. This resulted in full employment, a threefold increase of the national income and a doubling of per capita income. A strict income policy, price and rent controls and the creation of welfare state provisions guaranteed a more balanced income distribution and decent incomes for the population as a whole. In agriculture, technological developments led to the disappearance of traditional agricultural workers and small farmers and strongly increased production. The changes in the educational level of the young male population were enormous: whereas in 1950 for a substantial part of the younger generation had received little formal education beyond age 12, the democratization of the educational system in the 1950s and 1960s led to significant increases in the proportion of boys between ages 15 and 18 in full-time education (Schuyt and Taverne, 2000). In all these aspects the Netherlands improved its position in the international rankings. In our study population there was a weak relation between height and family size. This pattern had been noticed in the Netherlands and elsewhere (Fredriks et al., 2000; Carson, 2012). Additional adjustment for family size only had a marginal effect on the relation between height and education however. Height has been associated with long-standing illness and perceived ill health in an adult Finnish population (Silventoinen et al., 1999). Although there were small differences (1 cm) in height comparing military conscripts by medical examination outcome in Germany (Hiermeyer, 2009), the reported associations of height with education and paternal occupation in our study hold regardless of the results of the medical examination (fit for service; temporary unfit for service, unfit for service). Several explanations have been put forward to explain the relation between height and education. A common line of thought stresses the importance of parental socio-economic position and wealth as drivers of offspring height and education. These effects may in part be mediated by socio-economic differences in nutrition and health practices (Cavelaars et al., 2000; Komlos and Baur, 2004; Heineck, 2006). In this population, we found no relation between height and paternal occupation once conscript education was taken into account. As paternal occupation is only one aspect of family background, there may be other more important family characteristics that drive offspring heights. We have no additional information on any of these however. A second explanation stresses the impact of height on an individual’s self-esteem or on the esteem given by others (‘social esteem’). Both may foster psychological and social forces that encourage higher educational achievement (Magnusson et al., 2006; Szklarska et al., 2007). In this population, no psychological data were collected that might bear on these issues.

The third hypothesis raises the question if height might be related to education through cognitive ability (Case and Paxson, 2008). This question needs further exploration. Previous studies in Dutch conscripts show no relation between nutrition status in very early life and cognition at age 18 (Stein et al., 1972). Further studies are needed however to evaluate the relations between early life nutrition, cognitive ability, attained education and height. This could be an important area of further work, especially if long-run measures of social achievement and health become available in this population. According to a fourth line of reasoning, the relation between height and educational achievement could be driven by educational discrimination based on height. Support for this mechanism comes from a recent study of German pre-teen students showing that taller children were more likely to enroll in the most academic secondary school track based on primary school teachers’ recommendations favoring taller students, irrespective of student’s academic achievement and parent’s background (Cinnirella et al., 2011). But the net effect of height on education at any level of cognition could be small (Vagero and Modin, 2006). Our study has some limitations. As the study subjects were male, our results cannot directly be applied to females. Available studies suggest however that the relation between height and socioeconomic status is no different in men and women (Cavelaars et al., 2000; Silventoinen et al., 2001; Singh-Manoux et al., 2010). We have no information on mother’s occupation, education, or height. We think it is unlikely these unknown characteristics could have biased the study results because spouses tend to be much alike in these matters and show well established patterns of assortative mating by body height and socio-economic background (Illsley, 1955; Silventoinen et al., 2003). Nevertheless, it may have been possible to explain a larger part of the conscript height differences with missing information on paternal and maternal heights, education, and occupation. The overriding strength of our study is the inclusion of the entire Dutch male population at age 18, avoiding many issues related to selection bias. In addition, the study group was examined for military service with uniform methods and examined at the same age, avoiding many potential issues related to outcome assessment. This provides a population that is large enough for accurate effect estimates of the relative impact of key variables associated with height at this age. In summary, using height at age 18 as a proxy for early life exposures, we document a height gradient of over 5 cm between education groups in the Netherlands born at the end of World War II that cannot be explained by other traditional determinants including paternal socio-economic background, family size, or region of birth. Acknowledgements Supported in part by grant RO1-AG028593 from the National Institutes of Health, USA (PI: LHL). We thank the

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Differences in height by education among 371,105 Dutch military conscripts.

Adult height is associated with a variety of familial and socio-economic factors and large, well-defined populations are needed for a reliable assessm...
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