Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Hemoglobin and adult height loss among Japanese workers: A retrospective study

  • Yuji Shimizu ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    shimizu@osaka-ganjun.jp

    Affiliation Department of Cardiovascular Disease Prevention, Osaka Center for Cancer and Cardiovascular Diseases Prevention, Osaka, Japan

  • Hidenobu Hayakawa,

    Roles Data curation, Formal analysis, Investigation, Methodology, Software, Validation

    Affiliation Department of Cardiovascular Disease Prevention, Osaka Center for Cancer and Cardiovascular Diseases Prevention, Osaka, Japan

  • Midori Takada,

    Roles Formal analysis, Investigation, Validation

    Affiliation Department of Cardiovascular Disease Prevention, Osaka Center for Cancer and Cardiovascular Diseases Prevention, Osaka, Japan

  • Takeo Okada,

    Roles Investigation, Validation

    Affiliation Department of Cardiovascular Disease Prevention, Osaka Center for Cancer and Cardiovascular Diseases Prevention, Osaka, Japan

  • Masahiko Kiyama

    Roles Conceptualization, Methodology, Project administration, Supervision

    Affiliation Department of Cardiovascular Disease Prevention, Osaka Center for Cancer and Cardiovascular Diseases Prevention, Osaka, Japan

Abstract

Height loss starting in middle age is reported to be associated with increased all-cause and cardiovascular mortality later in life. However, the mechanisms underlying this association are unclear. Hypoxia and oxidative stress, which are known causes of cardiovascular disease, could be reduced by hemoglobin. Therefore, hemoglobin could be inversely associated with height loss. However, high body mass index (BMI) is a known risk factor for intervertebral disc disorder, a known cause of height loss in adults. High BMI might confound the association between hemoglobin and height loss. Therefore, we performed analyses stratified by BMI status. To clarify the association between hemoglobin and height loss, we conducted a retrospective study of Japanese workers (6,471 men and 3,180 women) aged 40–74 years. Height loss was defined as being in the highest quintile of height decrease per year. In men overall and men with BMI <25 kg/m2, hemoglobin was significantly inversely associated with height loss; but no association was observed for men with high BMI (BMI ≥25 kg/m2) and for women. For men, after adjusting for known cardiovascular risk factors, adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for height loss with each 1 standard deviation (SD) increase in hemoglobin (1.0 g/dL for men and 0.8g/dL for women) were 0.89 (0.83, 0.95) for men overall, 0.82 (0.75, 0.89) for men who do not have high BMI, and 1.01 (0.92, 1.12) for men with high BMI. For women, the corresponding values were 0.97 (0.89, 1.06), 0.98 (0.89, 1.09), and 0.93 (0.75, 1.15) respectively. Hemoglobin is significantly inversely associated with height loss in men who do not have high BMI, but not in men with high BMI or women. These results help clarify the mechanisms underlying height loss, which has been reported to be associated with a higher risk of mortality in adults.

Introduction

Height loss starting in middle age is reported to be an independent risk factor for all-cause and cardiovascular mortality [1]. However, the mechanisms underlying the association between height loss and increased mortality are unclear. Understanding the mechanisms that cause height loss in middle age could help reduce mortality later in life.

Aging is a process that increases hypoxia and oxidative stress [2,3]. Hypoxia and oxidative stress, which are well known cardiovascular risk factors [4,5], have been reported to be associated with intervertebral disc disorder [6,7] and osteoporosis [810]. Since intervertebral disc disorder and vertebral fractures related to osteoporosis are well known causes of height loss in adults, hypoxia and oxidative stress might be associated with height loss.

Hypoxia causes oxidative stress [11]. The body produces erythropoietin, which activates hematopoiesis as an adaptation to hypoxia [12]. Erythropoietin increases hemoglobin concentrations [13]. Therefore, hemoglobin could act as an indicator of reduced hypoxia and oxidative stress. However, hematopoietic bone marrow activity declines with age [14,15]. Therefore, even though hemoglobin plays an important role in reducing hypoxia and oxidative stress, the process of aging lowers hemoglobin levels. In other words, hemoglobin could act as an indicator of variations in the aging process, such as height loss.

Previously, studies on the association between obesity (high body mass index [BMI]) and fracture have reported conflicting results [16]. However, another study reported participants with disc degeneration have higher BMI than participants without disc degeneration [17]. Another study reported that obesity is positively associated with intervertebral disc disorder [18]. Since obesity is reported to be positively associated with hemoglobin levels [19], high BMI could confound the association between hemoglobin and height loss by masking the beneficial effect of hemoglobin.

Therefore, we hypothesized that hemoglobin is inversely associated with height loss in participants with BMI <25 kg/m2. To clarify this association, we conducted a retrospective study of Japanese workers (6,471 men and 3,180 women) aged 40–74 years who participated in annual health check-ups between 2008 and 2018.

Materials and methods

Study population

The Ministry of Health, Labor and Welfare of Japan started specific medical examinations for cardiovascular disease prevention in 2008. In addition to physical examination and general laboratory tests of blood and urine samples, the medical examination contained a questionnaire about lifestyle and medical history.

Fig 1 shows the demographics of the study population. The present study population comprised 15,435 workers aged 40–74 years who participated in these specific medical examinations between 2008 and 2018 (baseline) at the Osaka Center for Cancer and Cardiovascular Diseases Prevention. Since the participants of this study were current workers who had the capacity to work, they might be relatively healthier than the general population. Furthermore, compared to the general population, the proportion of men might be higher because more men than women tend to become workers in Japanese society.

This study was approved by the ethics committee of the Osaka Center for Cancer and Cardiovascular Diseases Prevention (Project registration code: R2-Rinri-7). All procedures involving human participants were performed in accordance with the ethical standards of the ethics committee of the Osaka Center for Cancer and Cardiovascular Diseases Prevention and the 1964 Helsinki Declaration and its amendments. Consent for this study was obtained using the opt-out method with descriptions of the study on posters and the institutional website (www.osaka-ganjun.jp/effort/cvd/r-and-d/).

Subjects without data on drinking status (n = 57), total cholesterol (TC) (n = 1,179), or hemoglobin A1c (HbA1c) (n = 20) at baseline were excluded from the analysis. We also excluded subjects who had anemia (n = 991). Since the present study used data on height decrease per year, at least two height measurements (at baseline and end point) during observational period were necessary. Subjects without a height measurement during 2009–2019 (end point) were also excluded from the analysis (n = 3,537). The remaining 9,651 subjects with a mean age of 50.6 years (standard deviation [SD], 8.2 years; range, 40–74 years) were included in the study. The mean follow-up period of this study was 3.7 years (median, 3.0 [interquartile range, 1.9–5.6] years).

Data collection and laboratory measurements

Baseline data.

The baseline period of the present study was 2008–2018. Trained interviewers acquired medication history and habitual status data. Briefly, height in feet while wearing stockings and weight in while wearing light clothing were measured. BMI was calculated as weight divided by height squared (kg/m2). Resting blood pressure was measured twice. Mean blood pressure data was used in the analysis.

A fasting blood sample was collected. Hemoglobin (Hb), TC, triglycerides (TG), high-density lipoprotein cholesterol (HDLc), HbA1c, and serum creatinine were measured using standard procedures at the Osaka Center for Cancer and Cardiovascular Diseases Prevention. Low-density lipoprotein cholesterol (LDLc) was calculated using the Friedewald formula: LDLc = TC-(HDLc/5) mg/dL.

Between 2008 and 2012, HbA1c values were measured using the Japanese Diabetes Society (JDS) definition. Starting in 2013, HbA1c values were measured using the National Glycohemoglobin Standardization Program (NGSP) definition. The following equation, which was recently proposed by a JDS working group, was used to convert values: HbA1c(NGSP) = HbA1c(JDS) + 0.4% [20].

The World Health Organization (WHO) guidelines state that the international classification for high BMI among Asians is ≥ 25 kg/m2 [21]. We defined high BMI as BMI ≥ 25kg/m2.

Estimated glomerular filtration rate (eGFR) was calculated using an established method modified recently proposed by a working group of the Japanese Chronic Kidney Disease Initiative [22]. eGFR (mL/min/1.73 m2) was defined as 194 × (serum creatinine (enzyme method))-1.094× (age)-0.287 (×0.739 for women).

Chronic kidney disease was defined as eGFR < 60 mL/min/1.73 m2. Anemia was defined as Hb < 13 g/dL for men and Hb < 12 g/dL for women. Hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥ 90 mmHg, or use of anti-hypertensive medication. Dyslipidemia was defined as TG ≥ 150 mg/dL, LDLc ≥ 140 mg/dL, HDLc < 40 mg/dL, or use of lipid-lowering medication. Diabetes was defined as HbA1c (NGSP) ≥ 6.5% or glucose-lowering medication use.

Endpoint data.

To calculate height loss in the present study, at least 2 measurements during study period are required. Height was also measured during the endpoint period (2009–2019) using the same methods used during the baseline period (2008–2018). Briefly, height was measured while the participant was wearing stockings and light clothing.

Definition of height loss.

Height decrease per year (mm/year) was calculated as [(height at endpoint, mm)–(height at baseline, mm)]/(follow up duration, years). Sex-specific quintile values of height decrease per year (mm/year) were also calculated. A participant was considered to have height loss if he or she was in the highest quintile of height decrease per year. For sensitivity analysis, we used another definition of height loss based on sex-specific quartiles of height decrease per year. In this sensitivity analysis, we defined height loss as being in the highest quartile of height decrease per year.

Statistical analysis

Sex-specific characteristics of the study participants were summarized. Age, hemoglobin, and height were expressed as means ± SD. Daily drinking, current smoker status, hypertension, high BMI, dyslipidemia, diabetes, and chronic kidney disease were presented as percentages. Differences in those characteristics were calculated by sex.

Logistic regression was used to calculate odd ratios (ORs) and 95% confidence intervals (CIs) to determine associations between high BMI and height loss, high BMI and hemoglobin, and height loss and hemoglobin. For the association between height and hemoglobin, further analysis stratified by BMI status (high BMI absent versus present) was performed.

Two adjustment models were used. The first model adjusted only for age (age-adjusted model). The second model (multivariable model) also included other established confounding factors that included established cardiovascular risk factors such as drinking status (not daily drinker versus daily drinker), smoking status (no versus yes), hypertension, diabetes, dyslipidemia, and chronic kidney disease. High BMI was also included in the model used to investigate the association between height loss and hemoglobin.

To evaluate continuous values of height loss per year and hemoglobin levels by BMI status, we calculated simple correlation coefficients (r) using Spearman correlation analysis. We also calculated parameter estimates (Β) and standardized parameter estimates (β) using multiple linear regression.

All statistical analyses were performed with SAS for Windows (version 9.4; SAS Inc., Cary, NC, USA); p values of <0.05 were regarded as statistically significant.

Results

Characteristics of the study population by hemoglobin levels

Table 1 shows the characteristics of the study population by hemoglobin levels. For both men and women, current smoker, high BMI, and dyslipidemia were significantly positively associated with hemoglobin levels. In men, age was significantly inversely associated with hemoglobin and height was significantly positively associated with hemoglobin. In women, daily drinker status and hypertension were significantly positively associated with hemoglobin.

Associations between body mass index (BMI) and height loss

S1 Table shows sex-specific associations between high BMI and height loss. For both men and women, high BMI was significantly positively associated with the incidence of height loss. This association was unchanged even after adjusting for known cardiovascular risk factors.

Associations between high body mass index (BMI) and hemoglobin

S2 Table shows sex-specific associations between high BMI and hemoglobin. Independent of known cardiovascular risk factors, hemoglobin was significantly positively associated with high BMI for both men and women.

Associations between height loss and hemoglobin

Table 2 shows sex-specific associations between height loss and hemoglobin. Independent from known cardiovascular risk factors, hemoglobin was significantly inversely associated with height loss for men but not for women.

thumbnail
Table 2. Odds ratios (OR) and 95% confidence intervals (CI) for height loss in relation to hemoglobin levels.

https://doi.org/10.1371/journal.pone.0256281.t002

Associations between height loss and hemoglobin by body mass index (BMI) status

Table 3 shows sex-specific associations between height loss and hemoglobin by BMI status. For men who did not have high BMI, independent from known cardiovascular risk factors, hemoglobin was significantly inversely associated with height loss. This association was not observed for men with high BMI. For women, no significant associations were observed.

thumbnail
Table 3. Odds ratios (OR) and 95% confidence intervals (CI) for height loss in relation to hemoglobin by BMI status.

https://doi.org/10.1371/journal.pone.0256281.t003

Sensitivity analysis

To assess sensitivity, we performed the main analyses again with height loss defined as the highest quartile of height decrease per year. We obtained essentially the same results.

In the multivariable model, ORs for height loss with high BMI were 1.31 (1.15, 1.48) for men and 1.33 (1.06, 1.68) for women, respectively. In the multivariable model, ORs for high BMI and height loss for each 1 SD increase in hemoglobin were 1.46 (1.38, 1.55) and 0.91 (0.86, 0.97) for men and 1.30 (1.17, 1.44) and 1.00 (0.92, 1.08) for women. Among men stratified by BMI status, ORs for each 1 SD increase in hemoglobin and height loss were 0.84 (0.78, 0.91) for men without high BMI and 1.03 (0.94, 1.14) for men with high BMI. Among women, the corresponding values were 1.02 (0.93, 1.12) and 0.92 (0.75, 1.12), respectively.

Correlation between continuous values of height decrease per year and hemoglobin levels by BMI status

S3 Table shows correlations between continuous values of height decrease per year and hemoglobin levels by BMI status. The simple correlation analysis showed a slight but significant inverse correlation between continuous values of height loss per year and hemoglobin only in men with BMI <25 kg/m2. This correlation remained even after further adjusting for known cardiovascular risk factors.

Discussion

The major finding of the present study is that hemoglobin is significantly inversely associated with height loss in men, especially men who do not have high BMI. No significant associations were observed for men with high BMI or women.

Our previous cross-sectional study with 1,287 men aged 40–89 years revealed an inverse association between height and anemia in non-drinkers but not in drinkers [23]. Another cross-sectional study with 249 men aged 65–69 years showed a significant inverse association between height and reticulocyte count [24].

In the present study, we found further evidence that hemoglobin is significantly inversely associated with height loss among Japanese men aged 40–74 years, especially those with BMI <25 kg/m2. However, the mechanism underlying the present results has not yet been clarified. The potential mechanisms underlying the present results are shown in Fig 2.

thumbnail
Fig 2. Potential mechanism underlying the association between hemoglobin and height loss.

Associations shown in red (a–g) were observed in the present study. High BMI was defined as ≥25kg/m2. *1: Observed only among men.

https://doi.org/10.1371/journal.pone.0256281.g002

Aging is process that is strongly associated with increasing hypoxia and oxidative stress [2,3]. Increased hypoxia and oxidative stress have been reported to be associated with known causes of height loss such as intervertebral disc disorder [6,7] and osteoporosis [810]. Therefore, hemoglobin is necessary to prevent height loss. Iron deficiency, which causes anemia, is reported to accelerate intervertebral disc degeneration [25]. Older persons with osteosarcopenia were found to have low hemoglobin levels [26]. These studies partly support the argument that hemoglobin plays an important role in preventing height loss.

However, hematopoietic bone marrow activity declines with age [27,28]. Thus, hemoglobin production may be insufficient, especially in elderly individuals with increased hypoxia and oxidative stress. In this context, hemoglobin might act as an indicator of the capacity to prevent height loss. Hemoglobin found be to be inversely associated with height loss (Fig 2C).

However, this significant association was observed only in men. Differences in the influence of age on hemoglobin levels by sex might partly explain these sex-specific associations; an inverse association between hemoglobin and height loss was observed only in men. In the present study, we found a significant inverse association between age and hemoglobin; the simple correlation coefficient (r) of these two variables was -0.18 (p<0.001) (Fig 2A). For women, although menstruation might confound this association slightly, a significant positive association between these two variables was observed (r = 0.05, p = 0.008) (Fig 2E). Therefore, menstruation might act as a confounding factor on the results for women.

In the present study, for both men and women, high BMI was significantly positively associated with height loss (S1 Table, Fig 2D). The association between high BMI and fracture is inconsistent; some studies have reported positive associations while other studies have reported inverse associations [16]. A previous study reported that obesity might be associated with a lower risk of vertebral fracture [29]. However, BMI was significantly higher in subjects with disc degeneration than in subjects without disc degeneration [17]. Another study reported that obesity is associated with intervertebral disc disorder [18]. Therefore, intervertebral disk disorder might be underlying the positive association between high BMI and height loss. Both physical stress and chronic inflammation could be underlying the association between high BMI and height loss. High BMI is known to be associated with chronic inflammation [30]. A previous study reported that inflammation may play an important role in the etiology of fractures in men [31]. A strong association was observed between inflammation and intervertebral disc degeneration [32]. Further investigation with evaluation of inflammatory markers is necessary.

For both men and women, we found a significant positive association between high BMI and hemoglobin (S2 Table, Fig 2B). A previous study with 3,189 workers reported a significant positive association between hemoglobin and obesity [19], which partly supports our present results. Since chronic exposure to moderate hypoxia results in higher hemoglobin levels [33] and obesity is a state of hypoxia [34], high BMI might elevate hemoglobin levels. Obesity produces oxidative stress [35], partly via hypoxia [11]. Therefore, hemoglobin could be positively associated with high BMI, which acts as a partial indicator of oxidative stress levels.

Since high BMI was positively associated with hemoglobin (S2 Table, Fig 2B), a significant association between hemoglobin and height loss was observed in men who do not have high BMI (Table 3, Fig 2F and 2G). High BMI could act as a strong confounding factor in the association between hemoglobin and height loss.

In the present study, a significant inverse association between continuous values of height loss per year and hemoglobin levels was observed only among men without high BMI (S3 Table). However, the correlation was quite small. Diurnal height changes might act as a strong confounding factor of the influence hemoglobin has on continuous values of height loss per year [36].

One strength of the present study is that it is the first study to report that hemoglobin can prevent height loss in adult men. Based on multi-faceted analysis we could determine the potential mechanism underlying the present results because all of our present results can be explained by a simple mechanism. Declining age-related hematopoietic activity might play an important role in height loss during adulthood. Furthermore, this study showed that the concept of risk factor needs to change because among men, hemoglobin is inversely associated with height loss and positively associated with high BMI, while high BMI is significantly positively associated with height loss. Therefore, the same factor could be both beneficial and harmful and background status determines this characteristic, as in our previous studies [37,38]. Height loss starting in middle age is reported to be associated with higher total and cardiovascular mortality [1]. However, the mechanisms underlying this association are unclear. Since anemia is also reported to be associated with cardiovascular disease [39], the present study can help clarify the mechanisms underlying the association between height loss and cardiovascular disease.

The potential limitations of this study warrant consideration. In adults, height loss can be caused by vertebral fractures associated with osteoporosis and intervertebral disc degeneration, for which we did not have available data. Further investigation with data on those diseases is necessary. An efficient cutoff point to define height loss has not been established. In the present study, we used the highest quintile of height decrease per year. However, our sensitivity analysis based on quartile of height decrease per year showed essentially the same associations. Furthermore, we performed multi-faceted analysis and those results indicated a simple mechanism. Although hypoxia and oxidative stress might have a substantial effect on the study results, we had no data to evaluate oxidative stress. Further investigations with markers of hypoxia and oxidative stress such as hypoxia inducing factor (HIF), 8-hydroxydeoxyguanosine (8-OHdG), and superoxide dismutase (SOD) are necessary. Recent studies revealed a close connection between bone marrow activity and endothelial maintenance [40], including angiogenesis [41]. Since angiogenesis is also reportedly associated with intervertebral disc degeneration [42,43] and hemoglobin levels are strongly influenced by bone marrow activity [24], angiogenesis may also play an important role. However, we did not have data on angiogenesis.

Conclusion

In men, hemoglobin is significantly inversely associated with height loss, especially in men who do not have high BMI. This association was not observed in women. These results can help clarify the mechanisms underlying height loss in adults.

Supporting information

S1 Table. Odds ratios (OR) and 95% confidence intervals (CI) for height loss in relation to BMI status.

https://doi.org/10.1371/journal.pone.0256281.s001

(DOCX)

S2 Table. Odds ratios (OR) and 95% confidence intervals (CI) for high BMI (≥25kg/m2) in relation to hemoglobin levels.

https://doi.org/10.1371/journal.pone.0256281.s002

(DOCX)

S3 Table. Correlation between height decrease per year (mm/year) and hemoglobin by BMI status.

https://doi.org/10.1371/journal.pone.0256281.s003

(DOCX)

References

  1. 1. Masunari N, Fujiwara S, Kasagi F, Takahashi I, Yamada M, Nakamura T. Height loss starting in middle age predicts increased mortality in the elderly. J Bone Miner Res. 2012;27(1):138–145. pmid:21932348
  2. 2. Yeo EJ. Hypoxia and aging. Exp Mol Med. 2019;51(6):1–15. pmid:31221957
  3. 3. Liochev SI. Reflections on the theories of aging, of oxidative stress, and of science in general. Is it time to abandon the free radical (oxidative stress) theory of aging? Antioxid Redox Signal. 2015;23(3):187–207. pmid:24949668
  4. 4. Senoner T, Dichtl W. Oxidative stress in cardiovascular diseases: Still a therapeutic target? Nutrients. 2019;11(9):2090.
  5. 5. Abe H, Semba H, Takeda N. The roles of hypoxia signaling in the pathogenesis of cardiovascular diseases. J Atheroscler Thromb. 2017;24(9):884–894. pmid:28757538
  6. 6. Huang Y, Wang Y, Wu C, Tian W. Elevated expression of hypoxia-inducible factor-2alpha regulated catabolic factors during intervertebral disc degeneration. Life Sci. 2019;232:116565. pmid:31251999
  7. 7. Suzuki S, Fujita N, Hosogane N, Watanabe K, Ishii K, Toyama Y, et al. Excessive reactive oxygen species are therapeutic targets for intervertebral disc degeneration. Arthritis Res Ther. 2015;17:316. pmid:26542776
  8. 8. Tando T, Sato Y, Miyamoto K, Morita M, Kobayashi T, Funayama A, et al. Hif1alpha is required for osteoclast activation and bone loss in male osteoporosis. Biochem Biophys Res Commun. 2016;470(2):391–396. pmid:26792721
  9. 9. Miyauchi Y, Sato Y, Kobayashi T, Yoshida S, Mori T, Kanagawa H, et al. HIF1alpha is required for osteoclast activation by estrogen deficiency in postmenopausal osteoporosis. Proc Natl Acad Sci U S A. 2013;110(41):16568–16573. pmid:24023068
  10. 10. Domazetovic V, Marcucci G, Iantomasi T, Brandi ML, Vincenzini MT. Oxidative stress in bone remodeling: role of antioxidants. Clin Cases Miner Bone Metab. 2017;14(2):209–216. pmid:29263736
  11. 11. Pialoux V, Mounier R. Hypoxia-induced oxidative stress in health disorders. Oxid Med Cell Longev. 2012;2012:940121. pmid:23304260
  12. 12. Scholz H, Schurek HJ, Eckardt KU, Bauer C. Role of erythropoietin in adaptaion to hypoxia. Experientia. 1990;46(11–12):1197–11201. pmid:2253723
  13. 13. Lundby C, Thomsen JJ, Boushel R, Koskolou M, Warberg J, Calbet JA, et al. Erythropoietin treatment elevates haemoglobin concentration by increasing red cell volume and depressing plasma volume. J Physiol. 2007;578(Pt 1):309–314. pmid:17095558
  14. 14. Garvin K, Feschuk C, Sharp JG, Berger A. Does the number or quality of pluripotent bone marrow stem cells decrease with age? Clin Orthop Relat Res. 2007;465:202–207. pmid:17891036
  15. 15. Halawi R, Moukhadder H, Taher A. Anemia in the elderly: a consequence of aging? Expert Rev Hematol. 2017;10(4):327–335. pmid:28110585
  16. 16. Fassio A, Idolazzi L, Rossini M, Gatti D, Adami G, Giollo A, et al. The obesity paradox and osteoporosis. Eat Weight Disord. 2018;23(3):293–302. pmid:29637521
  17. 17. Samartzis D, Karppinen J, Chan D, Luk KD, Cheung KM. The association of lumbar intervertebral disc degeneration on magnetic resonance imaging with body mass index in overweight and obese adults: a population-based study. Arthritis Rheum. 2012;64(5):1488–1496. pmid:22287295
  18. 18. Sheng B, Feng C, Zhang D, Spitler H, Shi L. Associations between obesity and spinal diseases: A medical expenditure panel study analysis. Int J Environ Res Public Health. 2017;14(2):183. pmid:28208824
  19. 19. Yen Jean MC, Hsu CC, Hung WC, Lu YC, Wang CP, Tsai IT, et al. Association between lifestyle and hematological parameters: A study of Chinese male steelworkers. J Clin Lab Anal. 2019;33(7):e22946. pmid:31241225
  20. 20. Kashiwagi A, Kasuga M, Araki E, Oka Y, Hanafusa T, Ito H, et al. International clinical harmonization of glycated hemoglobin in Japan: From Japan Diabetes Society to National Glycohemoglobin Standardization Program values. J Diabetes Investig. 2012;3(1): 39–40. pmid:24843544
  21. 21. WHO expert consultation: Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004, 363(9403): 157–163. pmid:14726171
  22. 22. Imai E, Horio M, Watanabe T, Iseki K, Yamagata K, Hara S, et al. Prevalence of chronic kidney disease in the Japanese general population. Clin Exp Nephrol. 2009;13(6):621–630. pmid:19513802
  23. 23. Shimizu Y, Nakazato M, Sekita T, Kadota K, Miura Y, Arima K, et al. Height and drinking status in relation to risk of anemia in rural adult healthy Japanese men: the Nagasaki Islands study. Aging Male. 2015;18(2):100–105. pmid:25055346
  24. 24. Shimizu Y, Sato S, Koyamatsu J, Yamanashi H, Nagayoshi M, Kadota K, et al. Height indicates hematopoietic capacity in elderly Japanese men. Aging (Albany NY). 2016;8(10):2407–2413. pmid:27705902
  25. 25. Zhang C, Wang B, Zhao X, Li X, Lou Z, Chen X, et al. Iron deficiency accelerates intervertebral disc degeneration through affecting the stability of DNA polymerase epsilon complex. Am J Transl Res. 2018;10(11):3430–3442. pmid:30662597
  26. 26. Bani Hassan E, Vogrin S, Hernandez Viña I, Boersma D, Suriyaarachchi P, Duque G. Hemoglobin levels are low in sarcopenic and osteosarcopenic older persons. Calcif Tissue Int. 2020;107(2):135–142. pmid:32440760
  27. 27. Guralnik JM, Ershler WB, Schrier SL, Picozzi VJ. Anemia in the elderly: a public health crisis in hematology. Hematology Am Soc Hematol Educ Program. 2005:528–532. pmid:16304431
  28. 28. Cooper B. The origins of bone marrow as the seedbed of our blood: from antiquity to the time of Osler. Proc (Bayl Univ Med Cent). 2011;24(2):115–118. pmid:21566758
  29. 29. Walsh JS, Vilaca T. Obesity, type 2 diabetes and bone in adults. Calcif Tissue Int. 2017;100(5):528–535. pmid:28280846
  30. 30. Kawai T, Autieri MV, Scalia R. Adipose tissue inflammation and metabolic dysfunction in obesity. Am J Physiol Cell Physiol. 2021;320(3):C375–C391. pmid:33356944
  31. 31. Cauley JA, Barbour KE, Harrison SL, Cloonan YK, Danielson ME, Ensrud KE, et al. Inflammatory markers and the risk of hip and vertebral fractures in men: the osteoporotic fractures in men (MrOS). J Bone Miner Res. 2016;31(12):2129–2138. pmid:27371811
  32. 32. Molinos M, Almeida CR, Caldeira J, Cunha C, Gonçalves RM, Barbosa MA. Inflammation in intervertebral disc degeneration and regeneration. J R Soc Interface. 2015;12(104):20141191. pmid:25673296
  33. 33. Villafuerte FC, Cárdenas R, Monge-C C. Optimal hemoglobin concentration and high altitude: a theoretical approach for Andean men at rest. J Appl Physiol (1985). 2004;96(5):1581–1588. pmid:14672972
  34. 34. Hosogai N, Fukuhara A, Oshima K, Miyata Y, Tanaka S, Segawa K, et al. Adipose tissue hypoxia in obesity and its impact on adipocytokine dysregulation. Diabetes. 2007;56(4):901–911. pmid:17395738
  35. 35. Fernández-Sánchez A, Madrigal-Santillán E, Bautista M, Esquivel-Soto J, Morales-González A, Esquivel-Chirino C, et al. Inflammation, oxidative stress, and obesity. Int J Mol Sci. 2011;12(5):3117–3132. pmid:21686173
  36. 36. Saiklang P, Puntumetakul R, Swangnetr Neubert M, Boucaut R. Effect of time of day on height loss response variability in asymptomatic participants on two consecutive days. Ergonomics. 2019;62(12):1542–1550. pmid:31526175
  37. 37. Shimizu Y, Kawashiri SY, Yamanashi H, Koyamatsu J, Fukui S, Kondo H, et al. Reticulocyte levels have an ambivalent association with hypertension and atherosclerosis in the elderly: a cross-sectional study. Clin Interv Aging. 2019;14:849–857. pmid:31190771
  38. 38. Shimizu Y, Arima K, Noguchi Y, Kawashiri SY, Yamanashi H, Tamai M, et al. Potential mechanisms underlying the association between single nucleotide polymorphism (BRAP and ALDH2) and hypertension among elderly Japanese population. Sci Rep. 2020;10(1):14148. pmid:32843694
  39. 39. Kaiafa G, Kanellos I, Savopoulos C, Kakaletsis N, Giannakoulas G, Hatzitolios AI. Is anemia a new cardiovascular risk factor? Int J Cardiol 2015;186:117–124. pmid:25814357
  40. 40. Shi Q, Rafii S, Wu MH, Wijelath ES, Yu S, Ishida A, et al. Evidence for circulating bone marrow-derived endothelial cells. Blood. 1998;92(2):362–367. pmid:9657732
  41. 41. Siemerink MJ, Klaassen I, Vogels IM, Griffioen AW, Van Noorden CJ, Schlingemann RO. CD34 marks angiogenic tip cells in human vascular endothelial cell cultures. Angiogenesis. 2012;15(1):151–163. pmid:22249946
  42. 42. David G, Ciurea AV, Iencean SM, Mohan A. Angiogenesis in the degeneration of the lumbar intervertebral disc. J Med Life. 2010;3(2):154–161. pmid:20968201
  43. 43. Kwon WK, Moon HJ, Kwon TH, Park YK, Kim JH. The role of hypoxia in angiogenesis and extracellular matrix regulation of intervertebral disc cells during inflammatory reactions. Neurosurgery. 2017;81(5):867–875. pmid:28475716