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. 2017 Mar 3;12(3):e0173117. doi: 10.1371/journal.pone.0173117

The association between adult attained height and sitting height with mortality in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Norie Sawada 1,2, Petra A Wark 1, Melissa A Merritt 1, Shoichiro Tsugane 2, Heather A Ward 1, Sabina Rinaldi 3, Elisabete Weiderpass 4,5,6,7, Laureen Dartois 8, Mathilde His 8, Marie-Christine Boutron-Ruault 8, Renée Turzanski-Fortner 9, Rudolf Kaaks 9, Kim Overvad 10,11, María-Luisa Redondo 12, Noemie Travier 13, Elena Molina-Portillo 14,15, Miren Dorronsoro 16, Lluis Cirera 17, Eva Ardanaz 15,18,19, Aurora Perez-Cornago 20, Antonia Trichopoulou 21,22, Pagona Lagiou 21,22,23, Elissavet Valanou 21, Giovanna Masala 24, Valeria Pala 25, Petra HM Peeters 26, Yvonne T van der Schouw 26, Olle Melander 27, Jonas Manjer 28, Marisa da Silva 4, Guri Skeie 4, Anne Tjønneland 29, Anja Olsen 29, Marc J Gunter 3, Elio Riboli 1, Amanda J Cross 1,*
Editor: Stefan Kiechl30
PMCID: PMC5336260  PMID: 28257491

Abstract

Adult height and sitting height may reflect genetic and environmental factors, including early life nutrition, physical and social environments. Previous studies have reported divergent associations for height and chronic disease mortality, with positive associations observed for cancer mortality but inverse associations for circulatory disease mortality. Sitting height might be more strongly associated with insulin resistance; however, data on sitting height and mortality is sparse. Using the European Prospective Investigation into Cancer and Nutrition study, a prospective cohort of 409,748 individuals, we examined adult height and sitting height in relation to all-cause and cause-specific mortality. Height was measured in the majority of participants; sitting height was measured in ~253,000 participants. During an average of 12.5 years of follow-up, 29,810 deaths (11,931 from cancer and 7,346 from circulatory disease) were identified. Hazard ratios (HR) with 95% confidence intervals (CI) for death were calculated using multivariable Cox regression within quintiles of height. Height was positively associated with cancer mortality (men: HRQ5 vs. Q1 = 1.11, 95%CI = 1.00–1.24; women: HRQ5 vs. Q1 = 1.17, 95%CI = 1.07–1.28). In contrast, height was inversely associated with circulatory disease mortality (men: HRQ5 vs. Q1 = 0.63, 95%CI = 0.56–0.71; women: HRQ5 vs. Q1 = 0.81, 95%CI = 0.70–0.93). Although sitting height was not associated with cancer mortality, it was inversely associated with circulatory disease (men: HRQ5 vs. Q1 = 0.64, 95%CI = 0.55–0.75; women: HRQ5 vs. Q1 = 0.60, 95%CI = 0.49–0.74) and respiratory disease mortality (men: HRQ5 vs. Q1 = 0.45, 95%CI = 0.28–0.71; women: HRQ5 vs. Q1 = 0.60, 95%CI = 0.40–0.89). We observed opposing effects of height on cancer and circulatory disease mortality. Sitting height was inversely associated with circulatory disease and respiratory disease mortality.

Introduction

Poor nutrition, illness and early life exposures may contribute to ill health in later life [1–3]; however, there is a paucity of data to explore such associations in prospective cohorts with extended follow-up of children. Adult height is an easily measured variable, and is thought to reflect both genetic and environmental factors including nutrition, physical and social environments in early life [4, 5].

The association between height and mortality has been investigated in previous studies. A meta-analysis of 121 cohort studies comprising over 1 million participants reported that height was inversely associated with risk of death from circulatory diseases such as coronary disease, stroke and heart failure [6]. In contrast, height was positively associated with risk of death from melanoma and cancers of the pancreas, endocrine and nervous systems, ovary, breast, prostate, colorectum, blood and lung [6]. Despite many studies investigating overall height and mortality, there have been few studies examining the association between sitting height and mortality. Higher sitting height is of interest because compared with adult height, sitting height may be more strongly positively associated with insulin resistance [7], and is positively associated with lung function, independently of height [8]; therefore, the effects of sitting height on mortality might be different from those of overall height. One cohort study reported that sitting height was positively associated with cancer mortality and inversely associated with death from circulatory disease [9], but others showed no association [7, 10–12].

To further knowledge on the association of height and health outcomes among adults, we examined whether adult height and sitting height were associated with overall and cause-specific mortality in a large prospective cohort of approximately half a million men and women from 10 European countries.

Methods

Study cohort

The European Prospective Investigation into Cancer and Nutrition (EPIC) study includes 23 centres within 10 European countries (Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom (UK)). Most centres recruited from the general population living in defined towns and provinces. In Florence (Italy) and Utrecht (the Netherlands), however, participants undergoing breast cancer screening were recruited; parts of the Italian and Spanish cohorts were recruited among blood donors and their spouses; most of the Oxford cohort (UK) consisted of vegetarian and health-conscious volunteers; and female members of the health insurance scheme for state school employees were recruited in France. Between 1992 and 2000, 521,457 individuals (approximately 70% women, mostly 20–70 years old) were enrolled after providing written informed consent. Ethical approval for the EPIC study was obtained from the review boards of the International Agency for Research on Cancer (IARC) and local participating centres. The cohort characteristics have been described in detail elsewhere [13, 14].

Exposure assessment

At recruitment, standardized questionnaires on lifestyle, demographic information and personal history were collected [13, 14]. Height was measured in participating centres to the nearest 0.1, 0.5, or 1.0 cm in participants without shoes on [15]. Norway was the only centre in which height was all self-reported; furthermore, height was only measured in 29% of the French and 13% of the Oxford cohort with the remainder of the participants self-reporting their height. Self-reported data on height tends to be overestimated, with the degree of overestimation being larger for shorter individuals and this also depends on age [15]. The self-reported data from the Oxford cohort were adjusted using earlier described sex-specific regression equations that incorporated age [15]; this was not done for the French cohort because the interval between the self-reported data and measurement was considered to be too long to do so reliably, thus only those participants with measured data were included. Sitting height was measured (the minimum unit was 0.1cm) in over 90% of participants in six countries (Italy, Spain, the Netherlands, Germany, Greece, Denmark) and in 29% of French participants.

Follow-up and endpoint assessment

Vital status, causes and dates of death were ascertained from population registries in Denmark, Italy (except Naples), the Netherlands, Norway, Spain, Sweden, and the UK. In Germany, Greece and Naples, this information was obtained by follow-up mailings or inquiries to municipal registries, regional health departments, physicians, and hospitals, and also by directly contacting their next-of-kin. In France, the causes and dates of death were obtained from the French Epidemiological Center for the Medical Causes of Death (CépiDc, Inserm).

Mortality data were coded according to the 10th revision of the International Classification of Diseases (ICD-10). All-cause mortality included deaths from external causes. The codes for the underlying cause of death were classified as follows: circulatory (ICD-10: I00-I99), cancer (C00-C97), respiratory (J00-J99), other or not reported (all other codes). Additionally, cancers were classified as smoking-related cancers [16] (oral cavity (C00-06), pharynx (C10), nasopharynx (C11-13), oesophagus (C15), stomach (C16), colorectal (C18-20), liver (C22), bile duct (C24), pancreas (C25), larynx and lung (C32-34), uterine cervix (C53), ovarian (C56), kidney and renal pelvis, ureter and bladder (C64-68), and myeloid leukaemia (C92) [16]) and non-smoking-related cancers (all other cancers). Furthermore, circulatory disease was subdivided into ischaemic heart disease (I20-I25), myocardial infarction (I21), cerebrovascular disease (I60-I69), haemorrhagic stroke (I60-I62) and ischemic stroke (I63).

Statistical analysis

From the 521,457 participants recruited, those in a subsample in France (n = 52,809) and in the whole cohort in Norway (n = 37,185) were excluded because measured height was unavailable. Additionally, participants with missing questionnaire data (n = 1,286), missing dietary data (n = 6,627), missing all potential confounders (n = 3,127), without dates of death or follow-up information (n = 542) and those within the lowest and highest 1% of the cohort distribution of the ratio of reported total energy intake to energy requirements (n = 10,133) were excluded [17]. The final analytic cohort consisted of 409,748 individuals. For the analysis of sitting height, participants whose sitting height was not assessed were also excluded, leaving an analytic cohort for sitting height of 253,427 individuals.

Cox proportional hazard regression models with age as the underlying time scale were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association between height, sitting height and mortality risk. Height and sitting height were analysed as categorical variables defined by quintiles, and rounded off to the nearest 1 cm, and as continuous variables. Time at risk was estimated from the date of recruitment to the date of death, emigration, loss to follow-up, or the end of follow-up (a maximum through 2010, depending on centre), whichever occurred first. To control for differences in questionnaire design and follow-up procedures, all models were stratified by study centre. Models were further stratified by age at recruitment (continuous) to allow the form of the baseline hazard functions to vary across ages. All models were fitted for men and women separately, and adjusted for weight (kg, quintiles), combined recreational and household physical activity (inactive, moderately inactive, moderately active, active, unknown), alcohol consumption (0, >0–4, 5–14, 15–29, 30–59, ≥ 60 g/day), smoking status (never, former smokers (who quit <10 or ≥10 years ago), current smokers (1–14, 15–24 or ≥25 cigarettes per day), current smoker but amount missing (unknown smoking status), education level (none/primary school, technical or professional school, secondary school, university degree, not specified/missing) and energy intake (kcals/day, continuous). Moreover, the Cox models for women were further adjusted for menopausal status (pre, post-, peri-menopausal or unknown) and menopausal hormone use (yes, no, unknown). Potential non-linearity of the dose-response relationship was investigated using restricted cubic spline regression with knots placed at the 5th, 25th, 75th and 95th percentiles of height and corresponding likelihood ratio tests to compare the goodness-of-fit of the models with and without the spline terms [18, 19]. Because linearity could indeed be assumed, we computed a test for trend based on models with height and sitting height as a continuous variable.

Finally, we conducted interaction analyses to examine the relation between sitting height and overall height in relation to mortality; for these analyses we categorized height and sitting height into tertiles (low, middle and high) and examined risks within each combined strata and calculated a P-value for the interaction term. In addition, we examined interaction terms for height (as a continuous variable, per 5cm increment) and all-cause and cause-specific mortality according to country, age at recruitment, body mass index (BMI), smoking status and alcohol intake.

All reported P-values were two-sided and were regarded as statistically significant if P<0.05. The potential for multiple comparisons was addressed by examining Bonferroni correction; p = 0.004 (0.05/13 variables). All analyses were performed using Statistical Analysis Software (SAS version 9.1, SAS Institute, Cary, NC).

Results

After an average follow-up of 12.5 years (range 0.01–17.8), 29,810 participants (15,320 men and 14,490 women) had died from any cause among all 409,748 participants. Out of all deaths with a reported cause (n = 25,526), major causes were cancer (n = 11,931), diseases of the circulatory system (n = 7,346) and the respiratory tract (n = 1,266). Among participants with data on sitting height, there were 15,630 all-cause deaths, 6,909 deaths from cancer, and 3,656 deaths from circulatory diseases. Participants who were taller, compared with those who were shorter, were younger, heavier, had higher energy intakes and were more physically active. The proportion of current smokers was lower in taller men but there was a higher proportion of current smokers in taller women; furthermore, taller women were more likely to have a higher education level, consume higher levels of alcohol, to be premenopausal, and among post-menopausal women, were more likely to use menopausal hormones (Table 1). After excluding individuals without data for sitting height, the characteristics were similar to those with measured height (data not shown).

Table 1. Baseline characteristics according to height.

Characteristic Height
<168cm (n = 24,624) 168-172cm (n = 32,317) 173-175cm (n = 23,126) 176-180cm (n = 35,141) ≧181cm (n = 29,754)
% Median (10–90%) % Median (10–90%) % Median (10–90%) % Median (10–90%) % Median (10–90%)
MEN
  Age at recruitment (years) 55.8 (42.9–67.5) 54.0 (41.1–64.9) 53.3 (40.1–64.2) 52.3 (39.1–63.3) 50.7 (32.7–61.6)
  Weight (g) 73.0 (61.4–87.0) 77.0 (65.5–91.2) 79.4 (67.9–94.3) 81.8 (70.0–97.2) 86.5 (73.6–103.5)
  Education
    None 13 5 2 1 0.3
    Primary school completed 43 35 31 25 18
    Technical/professional school completed 18 23 25 27 26
    Secondary school completed 9 12 13 14 17
    University 14 22 26 31 37
    Missing 3 3 3 3 2
  Smoking status
    Never smokers 30 31 32 34 37
    Former smokers 37 38 38 37 34
      Time since stopped smoking (years) 13.0 (2.5–31.0) 14.5 (3.0–31.0) 14.5 (2.5–31.0) 15.0 (2.5–30.5) 14.0 (2.5–29.0)
      Duration of smoking (years) 23 (8–40) 21 (7–38) 20 (6–37) 20 (6–36) 18 (5–34)
    Current smokers 32 30 30 28 28
      No. of cifarettes/day 18 (4–31) 18 (4–30) 17 (5–30) 17 (4–30) 15 (4–30)
      Duration of smoking (years) 34.5 (22.5–48) 34.5 (21–46) 34 (20.5–45.5) 33.5 (19.5–45) 32 (14.5–43.5)
    Missing 2 2 1 1 1
  Alcohol consumption (g/day) 12.3 (0–5.19) 12.6 (0.4–51.0) 12.6 (0.6–50.9) 12.5 (0.8–48.6) 12.3 (0.9–48.1)
    Non-consumers 11 7 6 5 4
  Physical activity
    Active 21 24 25 25 26
  Total energy intake (kcal/day) 2,262 (1,543–3,201) 2,315 (1,599–3,248) 2,337 (1,612–3,262) 2,351 (1,627–3,298) 2,439 (1,687–3,394)
<156cm (n = 48,547) 156-159cm (n = 51,049) 160-162cm (n = 47,088) 163-167cm (n = 66,397) ≧168cm (n = 51,705)
% Median (10–90%) % Median (10–90%) % Median (10–90%) % Median (10–90%) % Median (10–90%)
WOMEN
  Age at recruitment (years) 54.6 (40.8–66.8) 52.7 (38.6–64.6) 51.7 (37.5–63.8) 51.3 (36.4–63.1) 50.0 (30.4–60.9)
  Weight (g) 61.7 (50.1–78.1) 62.5 (51.6–79.8) 63.8 (53.1–81.0) 65.5 (55.0–82.8) 68.7 (58.2–86.0)
  Education
    None 18 7 3 2 0.4
    Primary school completed 40 32 27 22 15
    Technical/professional school completed 13 21 25 28 30
    Secondary school completed 13 16 18 19 21
    University 11 18 22 24 31
    Missing 4 6 5 5 3.6
  Smoking status
    Never smokers 67 59 55 52 50
    Former smokers 16 21 24 25 27
      Time since stopped smoking (years) 14.0 (2.5–31.0) 14.0 (2.5–30.0) 14.0 (2.5–29.5) 14.0 (2.5–29.0) 13.0 (2.0–27.5)
      Duration of smoking (years) 17.0 (4.0–34.0) 16.0 (4.0–33.0) 16.0 (4.0–32.0) 15.0 (4.0–32.0) 14.0 (4.0–31.0)
    Current smokers 16 19 20 21 23
      No. of cifarettes/day 11.0 (3.0–21.0) 11.0 (3.0–21.0) 11.0 (3.0–21.0) 12.0 (3.0–21.0) 12.0 (3.0–21.0)
      Duration of smoking (years) 27.0 (10.5–42.0) 28.5 (15.5–42.5) 29.5 (16.0–42.5) 30.0 (15.5–42.0) 29.0 (12.5–40.5)
    Missing 1 1 1 1 1
  Alcohol consumption (g/day) 1.3 (0–17.7) 2.8 (0–20.7) 3.8 (0–22.7) 4.5 (0–23.8) 5.6 (0.2–25.6)
    Non-consumers 20 19 14 11 8
  Physical activity
    Active 9 14 17 19 23
  Total energy intake (kcal/day) 1,808 (1,231–2,586) 1,852 (1,282–2,618) 1,873 (1,303–2,637) 1,886 (1,317–2,642) 1,923 (1,349–2,678)
  Menopausal status
    Premenopausal 28 33 35 36 44
    Postmenopausal 55 49 46 44 37
    Perimenopausal 12 14 15 17 17
    Surgical postmenopausal 5 4 4 3 2
  Use of menopausal hormone
    yes 18 22 24 25 23
    Missing 5 8 9 11 11
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Tables 2 and 3 shows the HRs for height and all-cause and cause-specific mortality in men and women, respectively. There was a statistically significant linear inverse association between height and all-cause mortality in men (HRQ5 vs. Q1 = 0.85, 95%CI = 0.80–0.91, p for trend<0.01), but no association was observed in women (HRQ5 vs. Q1 = 1.01, 95%CI = 0.95–1.08, p for trend = 0.66). We observed a positive association between height and death from cancer in both sexes (HRQ5 vs. Q1 = 1.11, 95%CI = 1.00–1.24, p for trend = 0.08 in men; HRQ5 vs. Q1 = 1.17, 95%CI = 1.07–1.28, p for trend<0.01 in women). HRs for smoking-related cancers and non-smoking-related cancers were not substantially different (Table 3). In contrast, height was inversely associated with the risk of death from circulatory disease in both sexes (HRQ5 vs. Q1 = 0.63, 95%CI = 0.56–0.71, p for trend<0.01 in men; HRQ5 vs. Q1 = 0.81, 95%CI = 0.70–0.93, p for trend<0.01 in women). Furthermore, height was inversely associated with ischaemic heart disease and myocardial infarction in both men and women, as well as cerebrovascular disease mortality in men only. There was no association between height and death from stroke or respiratory diseases in men or women. Excluding subjects with a past history of cancer, cardiovascular disease or diabetes (n = 38,760) yielded similar results (data not shown).

Table 2. Hazard ratios* and 95% confidence intervals for all cause and cause-specific mortality according to height in men.

Height
Cause of death <168 cm 168-<173 cm 173-<176 cm 176-<181 cm ≧181cm P for linear trend† HR (95% CI) per 5 cm increase in height
All-cause mortality Person-years 293,986 390,290 280,389 431,003 369,328
Deaths 3,416 3,753 2,464 3,311 2,376
HR (95% CI) 1 0.93 (0.89–0.98) 0.91 (0.86–0.96) 0.86 (0.81–0.91) 0.85 (0.80–0.91) <0.01 0.96 (0.94–0.97)
Cause-specific mortality Person-years 277,037 363,393 260,139 399,967 344,047
Cancer Deaths 1,112 1,338 905 1,249 916
HR (95% CI) 1 1.05 (0.97–1.15) 1.07 (0.97–1.17) 1.06 (0.96–1.17) 1.11 (1.00–1.24) 0.08 1.03 (1.00–1.05)
Smoking-related cancer Deaths 453 574 373 519 389
HR (95% CI) 1 1.26 (1.05–1.52) 1.21 (0.98–1.50) 1.30 (1.06–1.59) 1.04 (0.83–1.31) 0.93 0.99 (0.95–1.04)
Non smoking-related cancer Deaths 659 764 532 730 527
HR (95% CI) 1 0.95 (0.82–1.09) 0.94 (0.80–1.10) 1.07 (0.91–1.25) 0.86 (0.72–1.03) 0.36 0.98 (0.95–1.02)
Circulatory disease Deaths 1,166 1,065 715 845 608
HR (95% CI) 1 0.79 (0.73–0.87) 0.78 (0.71–0.87) 0.64 (0.58–0.72) 0.63 (0.56–0.71) <0.01 0.88 (0.86–0.90)
Ischaemic heart disease Deaths 632 594 412 483 323
HR (95% CI) 1 0.75 (0.66–0.84) 0.75 (0.65–0.86) 0.59 (0.52–0.68) 0.54 (0.46–0.63) <0.01 0.86 (0.83–0.89)
Myocardial infarction Deaths 319 311 207 267 172
HR (95% CI) 1 0.78 (0.66–0.92) 0.75 (0.62–0.91) 0.64 (0.53–0.77) 0.54 (0.43–0.67) <0.01 0.86 (0.82–0.90)
Cerebrovascular disease Deaths 238 182 112 124 95
HR (95% CI) 1 0.81 (0.66–1.00) 0.80 (0.62–1.03) 0.65 (0.50–0.84) 0.73 (0.54–0.99) <0.01 0.91 (0.86–0.97)
Haemorrhagic stroke Deaths 61 59 34 45 44
HR (95% CI) 1 0.80 (0.54–1.18) 0.65 (0.41–1.04) 0.61 (0.38–0.96) 0.73 (0.44–1.20) 0.13 0.89 (0.79–0.99)
Ischemic stroke Deaths 33 21 12 26 17
HR (95% CI) 1 0.47 (0.26–0.85) 0.36 (0.18–0.74) 0.60 (0.33–1.11) 0.55 (0.27–1.14) 0.20 0.85 (0.72–1.01)
Respiratory disease Deaths 191 165 98 118 66
HR (95% CI) 1 0.96 (0.77–1.21) 1.01 (0.77–1.32) 0.95 (0.72–1.24) 0.87 (0.62–1.23) 0.49 0.97 (0.90–1.04)
Other cause of death Deaths 595 624 389 567 431
HR (95% CI) 1 0.86 (0.76–0.97) 0.77 (0.67–0.88) 0.76 (0.67–0.88) 0.74 (0.64–0.87) <0.01 0.92 (0.89–0.95)
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* Hazard ratios (HR) and 95% confidence intervals (95% CI) estimated in a Cox regression model stratified by centre, 1-year age and 5-year birth cohort categories, adjusted for education level (none,/primary school completed, technical/professional school, secondary school, university degree, not specified), smoking status (never smoker, former smoker who quit <10 years ago, former smoker who quit >10 years ago, former smoker, unknown when quit, current smoker of 1–14 cigarettes a day, current smoker of 15–24 cigarettes a day, current smoker of > = 25 cigarettes a day, current smoker but amount missing, smoking status unknown), physical activity (inactive, moderately inactive, moderately active, active), alcohol consumption (0, 0-<5, 5-<15, 15-<30, 30-<60, > = 60 g/day), weight (quintiles), intake of energy (kcals/day, continuous).

† Median values of each category as continuous variable (cm).

Table 3. Hazard ratios* and 95% confidence intervals for all cause and cause-specific mortality according to height in women.

Height
Cause of death <156 cm 156-<160 cm 160-<163 cm 163-<168 cm ≧168cm P for linear trend† HR (95% CI) per 5 cm increase in height
All-cause mortality Person-years 590,468 628,657 581,655 680,731 791,060
Deaths 3,167 2,884 2,695 2,879 2,865
HR (95% CI) 1 0.97 (0.92–1.02) 1.04 (0.99–1.10) 0.98 (0.93–1.04) 1.01 (0.95–1.08) 0.66 1.00 (0.99–1.02)
Cause-specific mortality Person-years 554,304 587,926 543,440 635,688 745,828
Cancer Deaths 1,138 1,254 1,201 1,335 1,483
HR (95% CI) 1 1.07 (0.98–1.16) 1.14 (1.04–1.24) 1.09 (0.99–1.19) 1.17 (1.07–1.28) <0.01 1.05 (1.02–1.07)
Smoking-related cancer Deaths 503 512 542 540 551
HR (95% CI) 1 0.97 (0.81–1.17) 1.08 (0.89–1.31) 0.98 (0.81–1.19) 0.98 (0.80–1.20) 0.79 1.00 (0.95–1.04)
Non smoking-related cancer Deaths 635 742 659 795 932
HR (95% CI) 1 1.12 (0.96–1.30) 1.11 (0.95–1.30) 1.00 (0.86–1.17) 1.10 (0.94–1.28) 0.62 1.01 (0.97–1.05)
Circulatory disease Deaths 842 638 506 521 440
HR (95% CI) 1 0.95 (0.85–1.06) 0.92 (0.82–1.04) 0.86 (0.76–0.98) 0.81 (0.70–0.93) <0.01 0.94 (0.91–0.97)
Ischaemic heart disease Deaths 303 233 179 188 135
HR (95% CI) 1 0.89 (0.75–1.07) 0.83 (0.68–1.01) 0.78 (0.64–0.96) 0.61 (0.48–0.78) <0.01 0.88 (0.83–0.93)
Myocardial infarction Deaths 147 113 109 110 84
HR (95% CI) 1 0.86 (0.66–1.12) 0.96 (0.73–1.26) 0.84 (0.63–1.12) 0.67 (0.49–0.92) 0.02 0.89 (0.82–0.96)
Cerebrovascular disease Deaths 274 197 180 158 134
HR (95% CI) 1 0.94 (0.77–1.14) 1.07 (0.87–1.32) 0.88 (0.70–1.10) 0.84 (0.65–1.07) 0.15 0.96 (0.90–1.02)
Haemorrhagic stroke Deaths 73 73 64 66 67
HR (95% CI) 1 0.98 (0.70–1.37) 0.99 (0.69–1.43) 0.88 (0.61–1.28) 0.89 (0.60–1.33) 0.48 0.97 (0.88–1.07)
Ischemic stroke Deaths 21 25 27 22 16
HR (95% CI) 1 0.99 (0.54–1.80) 1.10 (0.60–2.03) 0.77 (0.40–1.48) 0.59 (0.28–1.22) 0.10 0.86 (0.72–1.01)
Respiratory disease Deaths 179 108 118 134 89
HR (95% CI) 1 0.72 (0.56–0.93) 0.95 (0.73–1.23) 0.98 (0.75–1.26) 0.75 (0.56–1.01) 0.31 0.96 (0.89–1.03)
Other cause of death Deaths 568 470 442 436 461
HR (95% CI) 1 0.91 (0.80–1.04) 1.01 (0.88–1.16) 0.88 (0.76–1.01) 0.95 (0.82–1.11) 0.44 0.97 (0.94–1.01)
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* Hazard ratios (HR) and 95% confidence intervals (95% CI) estimated in a Cox regression model stratified by centre, 1-year age and 5-year birth cohort categories, adjusted for education level (none,/primary school completed, technical/professional school, secondary school, university degree, not specified), smoking status (never smoker, former smoker who quit <10 years ago, former smoker who quit >10 years ago, former smoker, unknown when quit, current smoker of 1–14 cigarettes a day, current smoker of 15–24 cigarettes a day, current smoker of > = 25 cigarettes a day, current smoker but amount missing, smoking status unknown), physical activity (inactive, moderately inactive, moderately active, active), alcohol consumption (0, 0-<5, 5-<15, 15-<30, 30-<60, > = 60 g/day), weight (quintiles), intake of energy (kcals/day, continuous), menopausal status (pre, post-, peri-, unknown) and menopausal hormone use (yes, no, unknown).

† Median values of each category as continuous variable (cm).

Tables 4 and 5 shows the HRs for sitting height and all-cause and cause-specific mortality in men and women, respectively. We observed inverse associations for sitting height and all-cause mortality in both men and women (HRQ5 vs. Q1 = 0.81, 95%CI = 0.74–0.88, p for trend<0.01 in men; HRQ5 vs. Q1 = 0.86, 95%CI = 0.79–0.94, p for trend<0.01 in women). In contrast to the findings for overall height, we did not observe an association between sitting height and cancer mortality in either men or women. The associations between sitting height and circulatory disease mortality were similar to the inverse findings for overall height. In addition, we observed an inverse association between sitting height and death from haemorrhagic stroke in men only (HRQ5 vs. Q1 = 0.44, 95%CI = 0.23–0.84, p for trend<0.01) and from respiratory disease in men and women (HRQ5 vs. Q1 = 0.45, 95%CI = 0.28–0.71, p for trend <0.01; HRQ5 vs. Q1 = 0.60, 95%CI = 0.40–0.89, p for trend<0.01, respectively). When we analysed the association between sitting height and mortality, additional adjustment for overall height did not substantially change our results.

Table 4. Hazard ratios* and 95% confidence intervals for all cause and cause-specific mortality according to sitting height in men.

Sitting height
Cause of death <87 cm 87-<89 cm 89-<91 cm 91-<93 cm ≧93cm P for linear trend† HR (95% CI) per 1 cm increase in height
MEN
All-cause mortality Person-years 190,524 155,166 193,151 192,945 271,451
Deaths 1,894 1,273 1,531 1,412 1,839
HR (95% CI) 1 0.87 (0.81–0.94) 0.89 (0.83–0.96) 0.84 (0.78–0.91) 0.81 (0.74–0.88) <0.01 0.98 (0.97–0.99)
Cause-specific mortality Person-years 183,369 148,567 184,265 183,540 255,934
Cancer Deaths 710 497 635 597 808
HR (95% CI) 1 0.91 (0.80–1.02) 1.01 (0.90–1.14) 1.01 (0.89–1.14) 1.07 (0.94–1.22) 0.29 1.01 (0.995–1.02)
Smoking-related cancer Deaths 303 229 294 236 352
HR (95% CI) 1 1.28 (0.97–1.69) 1.21 (0.93–1.58) 1.32 (0.99–1.76) 1.30 (0.98–1.73) 0.66 1.01 (0.98–1.03)
Non smoking-related cancer Deaths 407 268 341 361 456
HR (95% CI) 1 0.82 (0.66–1.02) 0.83 (0.67–1.02) 0.90 (0.73–1.12) 0.78 (0.63–0.97) 0.09 0.98 (0.96–1.00)
Circulatory disease Deaths 615 367 425 353 443
HR (95% CI) 1 0.81 (0.70–0.93) 0.81 (0.70–0.93) 0.69 (0.60–0.81) 0.64 (0.55–0.75) <0.01 0.96 (0.94–0.97)
Ischaemic heart disease Deaths 291 192 219 176 221
HR (95% CI) 1 0.84 (0.69–1.02) 0.81 (0.67–0.99) 0.67 (0.54–0.83) 0.62 (0.50–0.78) <0.01 0.95 (0.93–0.97)
Myocardial infarction Deaths 159 101 119 100 113
HR (95% CI) 1 0.86 (0.66–1.12) 0.88 (0.67–1.15) 0.77 (0.57–1.03) 0.63 (0.47–0.86) <0.01 0.95 (0.93–0.98)
Cerebrovascular disease Deaths 139 61 80 53 63
HR (95% CI) 1 0.72 (0.52–0.98) 0.87 (0.64–1.19) 0.62 (0.43–0.89) 0.56 (0.38–0.82) <0.01 0.96 (0.93–0.99)
Haemorrhagic stroke Deaths 36 22 29 20 26
HR (95% CI) 1 0.75 (0.43–1.32) 0.80 (0.46–1.39) 0.53 (0.28–0.99) 0.44 (0.23–0.84) <0.01 0.93 (0.88–0.98)
Ischemic stroke Deaths 18 3 10 6 12
HR (95% CI) 1 0.24 (0.07–0.85) 0.71 (0.29–1.72) 0.46 (0.16–1.35) 0.72 (0.26–1.97) 0.85 0.99 (0.91–1.09)
Respiratory disease Deaths 110 60 41 46 39
HR (95% CI) 1 0.85 (0.60–1.19) 0.52 (0.35–0.78) 0.67 (0.45–1.01) 0.45 (0.28–0.71) <0.01 0.93 (0.90–0.96)
Other cause of death Deaths 375 265 308 297 345
HR (95% CI) 1 0.87 (0.74–1.03) 0.82 (0.69–0.97) 0.79 (0.66–0.94) 0.64 (0.53–0.77) <0.01 0.96 (0.94–0.97)
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* Hazard ratios (HR) and 95% confidence intervals (95% CI) estimated in a Cox regression model stratified by centre, 1-year age and 5-year birth cohort categories, adjusted for education level (none,/primary school completed, technical/professional school, secondary school, university degree, not specified), smoking status (never smoker, former smoker who quit <10 years ago, former smoker who quit >10 years ago, former smoker, unknown when quit, current smoker of 1–14 cigarettes a day, current smoker of 15–24 cigarettes a day, current smoker of > = 25 cigarettes a day, current smoker but amount missing, smoking status unknown), physical activity (inactive, moderately inactive, moderately active, active), alcohol consumption (0, 0-<5, 5-<15, 15-<30, 30-<60, > = 60 g/day), weight (quintiles), intake of energy (kcals/day, continuous).

† Median values of each category as continuous variable (cm).

Table 5. Hazard ratios* and 95% confidence intervals for all-cause and cause-specific mortality according to sitting height in women.

Sitting height    
Cause of death   <82 cm 82-<84 cm 84-<86 cm 86-<88 cm ≧88cm P for linear trend† HR (95% CI) per 1 cm increase in height
All-cause mortality Person-years 336,999 329,496 426,977 404,731 484,850    
    Deaths 1,582 1,332 1,674 1,467 1,626    
    HR (95% CI) 1 0.95 (0.88–1.03) 0.94 (0.87–1.02) 0.90 (0.83–0.97) 0.86 (0.79–0.94) <0.01 0.99 (0.98–0.99)
                   
Cause-specific mortality Person-years 320,489 311,699 402,879 381,913 459,258    
Cancer Deaths 614 606 822 730 890    
    HR (95% CI) 1 1.08 (0.96–1.21) 1.13 (1.01–1.27) 1.07 (0.94–1.20) 1.08 (0.95–1.22) 0.26 1.01 (0.995–1.02)
  Smoking-related cancer Deaths 292 242 352 292 344    
    HR (95% CI) 1 0.78 (0.59–1.03) 0.78 (0.59–1.03) 0.86 (0.64–1.14) 0.71 (0.53–0.95) 0.12 0.98 (0.96–1.01)
  Non-smoking-related cancer Deaths 322 364 470 438 546    
    HR (95% CI) 1 1.09 (0.87–1.37) 1.04 (0.83–1.30) 0.96 (0.77–1.21) 1.15 (0.91–1.44) 0.15 1.01 (0.995–1.03)
Circulatory disease Deaths 442 264 294 230 223    
    HR (95% CI) 1 0.80 (0.68–0.94) 0.77 (0.65–0.91) 0.69 (0.57–0.83) 0.60 (0.49–0.74) <0.01 0.95 (0.94–0.97)
  Ischaemic heart disease Deaths 136 79 86 63 57    
    HR (95% CI) 1 0.77 (0.57–1.03) 0.69 (0.51–0.94) 0.59 (0.42–0.83) 0.47 (0.33–0.69) <0.01 0.94 (0.91–0.97)
  Myocardial infarction Deaths 69 46 61 44 40    
    HR (95% CI) 1 0.85 (0.57–1.26) 0.87 (0.59–1.29) 0.71 (0.46–1.10) 0.54 (0.34–0.87) <0.01 0.94 (0.90–0.98)
  Cerebrovascular disease Deaths 131 90 92 68 67    
    HR (95% CI) 1 0.96 (0.72–1.28) 0.86 (0.64–1.16) 0.73 (0.52–1.02) 0.64 (0.44–0.92) 0.02 0.96 (0.94–0.99)
  Haemorrhagic stroke Deaths 38 36 35 34 43    
    HR (95% CI) 1 0.93 (0.57–1.50) 0.73 (0.44–1.20) 0.75 (0.45–1.27) 0.79 (0.46–1.35) 0.28 0.97 (0.93–1.02)
  Ischemic stroke Deaths 10 10 13 9 6    
    HR (95% CI) 1 0.91 (0.36–2.28) 0.86 (0.35–2.12) 0.64 (0.24–1.75) 0.40 (0.13–1.24) 0.10 0.92 (0.84–1.01)
Respiratory disease Deaths 89 47 69 55 61    
    HR (95% CI) 1 0.58 (0.40–0.84) 0.66 (0.46–0.93) 0.59 (0.40–0.86) 0.60 (0.40–0.89) <0.01 0.95 (0.92–0.98)
Other cause of death Deaths 296 281 298 275 287    
    HR (95% CI) 1 1.06 (0.89–1.26) 0.88 (0.74–1.06) 0.90 (0.75–1.09) 0.81 (0.66–0.98) <0.01 0.98 (0.96–0.995)
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* Hazard ratios (HR) and 95% confidence intervals (95% CI) estimated in a Cox regression model stratified by centre, 1-year age and 5-year birth cohort categories, adjusted for education level (none,/primary school completed, technical/professional school, secondary school, university degree, not specified), smoking status (never smoker, former smoker who quit <10 years ago, former smoker who quit >10 years ago, former smoker, unknown when quit, current smoker of 1–14 cigarettes a day, current smoker of 15–24 cigarettes a day, current smoker of > = 25 cigarettes a day, current smoker but amount missing, smoking status unknown), physical activity (inactive, moderately inactive, moderately active, active), alcohol consumption (0, 0-<5, 5-<15, 15-<30, 30-<60, > = 60 g/day), weight (quintiles), energy intake (kcals/day, continuous), menopausal status (pre, post-, peri-, unknown) and menopausal hormone use (yes, no, unknown).

† Median values of each category as continuous variable (cm).

We also investigated interactions between sitting height and overall height in relation to mortality (Table 6). Taller overall height and taller sitting height was strongly inversely associated with death from respiratory disease in men (Pinteraction = 0.03) but not women. However, there were no significant interactions between sitting height and overall height in relation to all-cause, cancer or circulatory disease mortality. Interaction terms for overall height and mortality by age, smoking status (smoker/non-smoker), and alcohol intake (high/low) did not reveal meaningful differences; however, for BMI, we observed an increased risk per 5cm increment in height for all-cause mortality only among women with a BMI <25 kg/m2 (data not shown).

Table 6. Hazard ratios* and 95% confidence intervals for all-cause and cause-specific mortality according to sitting height and overall height in men and women.

Overall height (tertiles)
Lowest (<170 cm) Middle (170-<176 cm) Highest (≧92 cm) Pinteraction
MEN
All-cause mortality Lowest (<89 cm) 1 0.89 (0.82–0.97) 1.04 (0.87–1.24)
Middle (89-<92 cm) 0.99 (0.90–1.08) 0.88 (0.82–0.96) 0.81 (0.73–0.90) 0.58
Highest (≧92 cm) 0.99 (0.79–1.25) 0.91 (0.83–1.00) 0.83 (0.76–0.90)
All cancer Lowest (<89 cm) 1 0.93 (0.81–1.07) 1.18 (0.89–1.56)
Middle (89-<92 cm) 1.08 (0.93–1.26) 1.03 (0.91–1.16) 0.98 (0.83–1.15) 0.77
Highest (≧92 cm) 1.03 (0.71–1.48) 1.18 (1.02–1.36) 1.08 (0.95–1.23)
Circulatory disease Lowest (<89 cm) 1 0.75 (0.64–0.89) 0.74 (0.50–1.08)
Middle (89-<92 cm) 0.95 (0.80–1.12) 0.75 (0.65–0.87) 0.58 (0.47–0.72) 0.53
Highest (≧92 cm) 0.91 (0.60–1.39) 0.70 (0.58–0.84) 0.62 (0.53–0.73)
Respiratory disease Lowest (<89 cm) 1 1.27 (0.87–1.84) 1.22 (0.48–3.09)
Middle (89-<92 cm) 0.79 (0.49–1.28) 0.69 (0.45–1.04) 0.36 (0.17–0.75) 0.03
Highest (≧92 cm) 0.71 (0.17–2.92) 0.84 (0.51–1.38) 0.50 (0.32–0.80)
Sitting height (tertiles) Lowest (<158cm) Middle (158-<163 cm) Highest (≧163 cm) Pinteraction
WOMEN
All-cause mortality Lowest (<84 cm) 1 1.07 (0.98–1.16) 1.15 (0.95–1.39)
Middle (84-<87 cm) 0.91 (0.82–1.00) 1.00 (0.93–1.08) 1.02 (0.93–1.12) 0.29
Highest (≧87 cm) 1.04 (0.83–1.30) 0.91 (0.82–1.01) 0.93 (0.86–1.01)
All cancer Lowest (<84 cm) 1 1.07 (0.94–1.23) 1.19 (0.91–1.55)
Middle (84-<87 cm) 1.04 (0.89–1.20) 1.14 (1.02–1.27) 1.08 (0.94–1.25) 0.66
Highest (≧87 cm) 1.24 (0.91–1.68) 0.99 (0.85–1.15) 1.09 (0.97–1.23)
Circulatory disease Lowest (<84 cm) 1 1.19 (0.99–1.44) 1.30 (0.85–1.98)
Middle (84-<87 cm) 0.84 (0.67–1.06) 0.89 (0.74–1.07) 0.88 (0.70–1.12) 0.05
Highest (≧87 cm) 0.97 (0.59–1.60) 0.86 (0.67–1.09) 0.75 (0.62–0.91)
Respiratory disease Lowest (<84 cm) 1 0.67 (0.43–1.10) 1.43 (0.64–3.16)
Middle (84-<87 cm) 0.46 (0.25–0.84) 0.85 (0.59–1.22) 1.07 (0.70–1.62) 0.11
Highest (≧87 cm) 0.31 (0.04–2.25) 0.72 (0.43–1.19) 0.71 (0.48–1.05)
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* Hazard ratios (HR) and 95% confidence intervals (95% CI) estimated in a Cox regression model stratified by centre, 1-year age and 5-year birth cohort categories, adjusted for education level (none,/primary school completed, technical/professional school, secondary school, university degree, not specified), smoking status (never smoker, former smoker who quit <10 years ago, former smoker who quit >10 years ago, former smoker, unknown when quit, current smoker of 1–14 cigarettes a day, current smoker of 15–24 cigarettes a day, current smoker of > = 25 cigarettes a day, current smoker but amount missing, smoking status unknown), physical activity (inactive, moderately inactive, moderately active, active), alcohol consumption (0, 0-<5, 5-<15, 15-<30, 30-<60, > = 60 g/day), weight (quintiles), energy intake (kcals/day, continuous). Models in women were further adjusted by menopausal status (pre, post-, peri-, unknown) and menopausal hormone use (yes, no, unknown).

After Bonferroni correction, the significance of our results was not substantially changed.

Discussion

In this large prospective study, overall height was positively associated with deaths from cancer, but inversely associated with deaths from circulatory disease. These results are supported by a previous meta-analysis of 1 million people from 121 prospective studies [6]. In the present study, sitting height was not associated with cancer mortality but was inversely associated with all-cause mortality, circulatory deaths, and death from respiratory disease. To our knowledge, this is the first study to report an inverse association between sitting height and death from respiratory disease. The World Cancer Research Fund/ American Institute for Cancer Research (WCRF/AICR) reported that there is convincing data that height increases the risk of individuals being diagnosed with cancers of the colorectum, breast (postmenopausal) and ovary [20, 21]; furthermore, height ‘probably’ increases the risk of cancers of the pancreas and breast (premenopausal). To complement this previous data on incidence, our data suggests a role for height and risk of cancer mortality.

Short stature is a well-documented risk factor for mortality from circulatory diseases [6, 9, 22], ischemic heart disease [23], ischemic stroke [22, 24, 25] and haemorrhagic stroke [24, 25] in previous studies. The results of this current analysis corroborate these prior studies but we also observed strong inverse associations between height and subtypes of circulatory disease death despite their different pathologies.

Whether a relationship between sitting height and mortality also exists is largely unknown. Wang et al. reported height and sitting height were positively associated with cancer death, but were inversely associated with death from cardiovascular disease in a cohort of 135,000 Chinese men and women [9]. Four other studies reported no association between sitting height and mortality [7, 10–12]. Our study in a large European population generally supports the reports from the Chinese, although we did not find a positive association between sitting height specifically and cancer mortality.

There are several potential underlying mechanisms to explain the opposing association of adult height with circulatory disease and cancer mortality. The positive association between adult height and mortality from cancer may be a result of taller people having larger organs, and a greater number of cells at risk of malignant transformation and/or proliferation [26]. Furthermore, attained adult height is known to be related to early nutrition in childhood or adolescence [3, 5]. In contrast, the inverse association between height and cardiovascular disease mortality has been proposed to be due to taller people and people with higher sitting height having larger coronary vessel diameters and a slower heart rate and/or greater lung capacity [8, 27–30]. Height may also be a marker of early exposure to components of the insulin/growth hormone axis. Height is correlated with circulating levels of insulin-like growth factor (IGF)-I, the main mediator of growth hormone activity and a hormone that has been positively associated with cancers at a number of anatomic sites [31–35], but IGF-1 levels are generally inversely related with circulatory disease risk [36–40]. Crowe et al. reported that each 10cm increase in height corresponded to a 4% increase in circulating IGF-1 levels [41]; therefore, increasing IGF-1 levels might mediate the opposing effect of height on cancer and circulatory disease mortality. To clarify the underlying mechanisms, further studies are needed to investigate IGF-1 levels in relation to cause-specific mortality risk while accounting for adult height. Furthermore, several genetic factors are related with height, cancer and cardiovascular disease [42, 43]. Identifying such genetic variants might shed light on potential mechanisms underlying the associations between height and mortality.

Davey Smith et al. reported that sitting height was strongly positively associated with insulin resistance [7]; thus, we expected a clearer association between sitting height and cancer mortality than overall height. Despite finding a positive association between overall height and cancer mortality in our data, there was no association for sitting height. These null findings for sitting height and cancer mortality may be plausible because despite the association with insulin resistance, sitting height has been associated with improved prognosis in cancer survivors due to better lung function in those with greater sitting height [8, 44]. Our finding that sitting height was inversely associated with death from respiratory disease is of note as this may be due to the aforementioned association between sitting height and lung function [8, 44].

Height is positively associated with education level among women in this study. Previous studies reported that lower educational levels have been associated with increased mortality, and incidence of coronary heart disease and stroke in Europe and the United States [45–47]. In an attempt to control for this potential confounder, we adjusted our models for educational level, although our results did not change from the unadjusted models.

A major strength of the EPIC study is the large study population representing findings from multiple countries and its long follow-up, resulting in a large number of deaths allowing us to analyse and distinguish between different causes of death. This study enabled us to examine measured height on the majority of participants, to adjust the self-reported height variable in the others, and to examine measured sitting height in a large subset of the cohort. In contrast, this study had some limitations. With a large body of information on lifestyle variables, we could adjust for many potential confounding factors, although the possibility of residual confounding cannot be excluded. Additionally, we divided cardiovascular disease into subgroups, which may result in some degree of misclassification.

In conclusion, this study revealed opposing findings for the relationship between height on cancer and circulatory disease mortality. Specifically, we showed that height was positively associated with death from cancer, but inversely associated with death from circulatory disease. Furthermore, this is the first study to show the inverse association between sitting height and death from respiratory disease. These findings could be used to contribute to risk prediction models to target individuals for specific screening programmes.

Abbreviations

BMI

body mass index

CI

confidence interval

EPIC

European Prospective Investigation into Cancer and Nutrition

HR

hazard ratio

IARC

International Agency for Research on Cancer

ICD

International Classification of Diseases

IGF

insulin-like growth factor

WCRF/AICR

World Cancer Research Fund/American Institute of Cancer Research

Data Availability

For information on how to submit an application for gaining access to EPIC data and/or biospecimens, please follow the instructions at http://epic.iarc.fr/access/index.php.

Funding Statement

The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF), Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC-2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020), AGAUR, Generalitat de Catalunya (exp. 2014 SGR 726), Health Research Funds RD12/0036/0018, European Regional Development Fund (ERDF) “A way to build Europe” (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Associated Data

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Data Availability Statement

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