Shimizu et al.
Journal of Physiological Anthropology(2024) 43:15
https://doi.org/10.1186/s40101-024-00362-7

ORIGINAL ARTICLE

Journal of
Physiological Anthropology

Open Access

Association between underweight, serum
albumin levels, and height loss in the Japanesemale population: a retrospective study
Yuji Shimizu1* , Eiko Honda1, Nagisa Sasaki1, Midori Takada1, Tomokatsu Yoshida1 and Kazushi Motomura1

Abstract
Background Previous study has shown that height loss (defined as the highest quartile of height loss per year)
was inversely associated with serum albumin levels. Furthermore, comparatively healthy hyponutrition has been
linked with being underweight; as such, underweight might be inversely associated with serum albumin levels
and positively associated with height loss.
Methods To clarify the associations between serum albumin level, underweight status, and height loss, we conducted a retrospective study of 8,096 men over 4.0 years (median).
Results Serum albumin level at baseline was inversely associated with being underweight (body mass index[BMI]: < 18.5 kg/m2) at baseline and height loss. The known cardiovascular risk factor adjusted odds ratio (OR) and 95%
confidence interval (CI) of underweight at baseline and of height loss for 1 standard deviation increment of serum
albumin (0.28 g/dL) was 0.79 (0.70, 0.90) and 0.84 (0.80, 0.88). Underweight was also shown to be positively associatedwith height loss: with the reference of normal-low weight (BMI: 18.5–22.9 kg/m2), the adjusted OR (95% CI) was 1.60
(1.21, 2.10).
Conclusion Comparative healthy hyponutrition, which is related to low serum albumin levels and being underweight, is a significant risk factor for height loss among Japanese men. These results help to clarify the mechanisms
underlying height loss.
Keywords Albumin, Hyponutrition, BMI, Height loss
Introduction
A previous study on Japanese general workers identified
a significant inverse association between serum albumin
level and height loss, which was defined as the highest
quartile of height loss per year [1]. However, the mechanism underlying this inverse association has not yet beenclarified.

*Correspondence:
Yuji Shimizu
simizu@iph.osaka.jp
1
Epidemiology Section, Division of Public Health, Osaka Instituteof Public Health, Osaka, Japan

Another study of Japanese general workers showed asignificant positive association between eating speed andheight loss, defined as being in the highest quintile ofheight decrease per year among non-overweight individuals (body mass index [BMI] below 25.0 kg/m2). In thisstudy, high BMI (≥ 25.0 kg/m2) was found to be positively
associated with eating speed and height loss [2].
Since being underweight, which is related to hyponutrition, has been linked to reduced serum concentrationsof albumin, these studies evoke and contradict thesefindings.
Hyponutrition, which is associated with low serum
albumin levels, is a risk factor for height loss [1], whereas© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Shimizu et al. Journal of Physiological Anthropology(2024) 43:15

hypernutrition, which is related to high BMI, is also positively associated with height loss [2].
Height loss starting in middle age may be associatedwith all-cause and cardiovascular disease-related mortality [3]. Endothelial repair activity evaluated by the
number of circulating endothelial progenitor cell (CD34positive cell) has also been reported to be inversely
associated with height loss [4]. Low levels of circulating
CD34-positive cell are associated with an increased riskof cardiovascular disease [5, 6].
Therefore, clarifying the associations between serum
albumin, underweight, and height loss could aid in developing a novel strategy for cardiovascular prevention
as the target population for preventing cardiovasculardisease.

Materials and methods
Study population

The study population comprised 14,494 residents of
Yao city, an urban community in western Japan, aged
40–73 years, who underwent an annual medical checkup from 2014 to 2021. The first checkup was considered
the baseline. Participants without a drinking habits data(n = 14), or without serum data (n = 2,554), were excluded.
We further excluded 3,049 participants who did notundergo an annual health checkup during the follow-up
period (2015–2022). Participants who were followed up
for less than 1 year (n = 781) were also excluded frompresent study. The remaining participant, 8,096 men aged
63.0 years ± 9.0 years (range, 40–73 years), were enrolled
in the study. The mean follow-up period (standard deviation [SD]) was 3.4 (1.2) years.
This study was approved by the ethics committee of
Osaka Institute of Public Health (project registration
code: 2311–02). All procedures involving human participants were performed in accordance with the ethicalstandards of the Ethics Committee of Osaka Institute of
Public Health and the 1964 Declaration of Helsinki andits amendments. Informed consent for this study was
obtained from all participants for study population using
the opt-out method, with descriptions of the study presented on the institution’s website (https://​www.​iph.​osaka.​jp/​s004/​099/​2311-​02.​pdf ) (accessed on 12th January 2024). All analyses for this study were conductedusing deidentified data, and the authors completing theanalysis did not have access to data with identifiers. For
research purposes data were extracted 26th December
2023.
Data collection and laboratory measurements

The data used in this study were statutory reporting
data of annual health checkups performed in Yao City.
Because these annual health check-ups are supported

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by the Japanese government, the methods used for datacollection and laboratory measurements are nationallystandardized.
Baseline data

The baseline period of this study was from 2014 to 2021.
BMI was calculated as weight divided by height in meterssquared (kg/m2). The resting blood pressure was measured twice. Fasting blood samples were collected fromall patients. Albumin, triglyceride (TG), high-density
lipoprotein cholesterol (HDLc), low-density lipoproteincholesterol (LDLc), and Hemoglobin A1c (HbA1c) levels
were also measured.
BMI categories were defined as follows: underweight,
BMI < 18.5 kg/m2; normal-low weight, BMI: 18.5–22.9
kg/m2; normal-high weight, BMI:23.0–24.9 kg/m2;
overweight, BMI: 25.0–29.9 kg/m2 and obesity, BMI≥ 30 kg/m 2 . Hypertension was defined as systolicblood pressure ≥ 140 mmHg and diastolic blood pressure≥ 90 mmHg. Dyslipidemia was defined as TG ≥ 150 mg/dL,
LDLc ≥ 140 mg/dL, HDLc < 40 mg/dL. Higher HbA1c
was defined as HbA1c (5.6–6.4%) and high HbA1c as
HbA1c (≥ 6.5%).
Endpoint data

The endpoint of this study was from 2015 to 2022. Duringbaseline evaluations, the height (cm) was measured.
Decreases in height per year (cm/year) were calculatedusing height measurements at baseline and at the endpoint. Height loss was defined as being in the highest
quartile of annual height decrease (decreased by 0.23 cm/year), as in previous studies [1, 4].
Statistical analysis

The characteristics of the study population were calculated according to serum albumin levels and BMI
categories. Age was expressed as means ± SD. Obesity,
overweight, normal-high weight, normal-low weight,
underweight, hypertension, daily drinker, non-drinker,
smoker, higher HbA1c, high HbA1c, and dyslipidemia
are also shown as percentages. Significant differenceswere evaluated using the Jonckheere-Terpstra trend test
for continuous variables and the Cochran-Armitage
trend test for proportions.
Logistic regression was applied to calculate the odds
ratios (ORs) and 95% confidence intervals (CIs) of being
underweight and incidence of height loss for serum albumin. The ORs and 95% CIs of height loss for the BMI categories were calculated using a logistic regression model.
Height loss is reportedly associated with cardiovascular mortality [3], and may also be influenced by endothelial repair [4]. Therefore, the cardiovascular risk factors
may have acted as confounders in this study. High BMI

Shimizu et al. Journal of Physiological Anthropology(2024) 43:15

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Table 1 Characteristics of the study population in relation to serum albumin levels
Serum albumin
Quartile 1 (low)P for trend
Quartile 2

Quartile 3

Quartile 4 (high)No. of participants

1,642

2,216

2,259

1,979

Age, year

65.5 ± 6.9

64.0 ± 8.0

62.5 ± 9.1

60.2 ± 10.3

< 0.001

Obesity, %

3.8

3.7

4.1

5.4

0.163

Overweight, %

23.7

28.5

30.4

31.7

0.005

Normal high weight, %

24.9

26.1

26.6

27.3

0.081

Normal low weight, %

42.0

38.3

36.6

33.5

0.003

Underweight, %

5.6

3.3

2.3

2.2

0.538

Hypertension, %

26.9

28.9

28.2

32.7

< 0.001

Daily drinker, %

53.8

48.4

46.5

40.8

< 0.001

Non-drinker, %

29.2

33.8

33.8

36.2

0.690

Smoker, %

31.7

27.7

27.0

25.3

0.002

Higher HbA1c, %

43.6

46.5

45.6

46.4

<0.001High HbA1c, %

11.9

11.0

12.0

14.1

0.0032

40.7

48.6

51.3

Dyslipidemia, %
2

55.8
2

< 0.001
2

Obesity: BMI(≥30.0 kg/m ). Overweight: BMI (25.0–29.9 kg/m2). Normal high weight: BMI (23.0–24.9 kg/m ). Normal low weight: BMI (18.5–22.9 kg/m ). Underweight:
BMI (<18.5 kg/m2 ). Hypertension: systolic blood pressure≥140 mmHg and/or diastolic blood pressure≥90 mmHg. Higher HbA1c: 5.6–6.4%. High HbA1c: ≥6.5%.
Serum albumin levels: < 4.2 g/dL for quartile 1 (low), 4.2–4.3 g/dL for quartile 2, 4.4–4.5 g/dL for quartile 3, and ≥ 4.6 g/dL for quartile 4 (high)BMI body mass index(≥ 25.0 kg/m2) [2], hypertension [7], higher HbA1c (5.6–
6.5%) [8] were reported to be positively associated withheight loss. Diabetes, which is related to high HbA1c(≥ 6.5%), is an established risk factor for intervertebral disk
degeneration [9]. Two different approaches were used toadjust for the confounding factors. First, we adjusted forage (age-adjusted model). In the multivariate model, theadjustment factors were dependent on the analysis. For the
analysis between serum albumin and underweight status,
we included several other potential confounding factors,
namely age, obesity (yes, no), overweight (yes, no), hypertension (yes, no), daily drinker (yes, no), non-drinkers (yes,no), smoker (yes, no), higher HbA1c (yes, no), high HbA1c(yes, no), and dyslipidemia (yes, no). For the analysis ofserum albumin levels and height loss, we adjusted for age,
obesity (yes, no), overweight (yes, no), underweight (yes,no), hypertension (yes, no), daily drinker (yes, no), nondrinker (yes, no), smoker (yes, no), higher HbA1c (yes, no),high HbA1c (yes, no), and dyslipidemia (yes, no). To assess
the association between BMI categories (underweight,
normal-low weight, normal-high weight, overweight, andobesity) and height loss, age, hypertension (yes or no),daily drinker (yes or no), non-drinker (yes or no), smoker(yes or no), higher HbA1c (yes or no), high HbA1c (yes orno), and dyslipidemia (yes or no) were adjusted for.
Statistical significance was set at p < 0.05. All statisticalanalyses were performed using SAS for Windows (version
9.4; SAS Inc., Cary, NC, USA).

Results
Characteristics of the study population in relation to serum
albumin levels

Table 1 shows the characteristics of the study population according to serum albumin levels. Overweight,
hypertension, higher HbA1c, high HbA1c, and dyslipidemia were significantly positively associated withserum albumin levels, while age, normal-low weight,
daily drinker, and smoker were significantly inversely
associated with serum albumin levels.
Characteristics of the study population in relation to BMI
categories

The characteristics of the study population according
to the BMI categories are presented in Table 2. Hypertension, higher HbA1c, high HbA1c, and dyslipidemia
were significantly positively associated with BMI categories, whereas non-drinkers, and smokers showed asignificant inverse association with BMI categories. An
inverse U-shaped association was observed between
daily drinker and the BMI categories.
Association between serum albumin and underweight

Independent of known potential confounders, a significant inverse association between serum albumin levels and underweight status was also observed(Table 3).

Shimizu et al. Journal of Physiological Anthropology(2024) 43:15

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Table 2 Characteristics of the study population in relation to BMI categories
BMI categories
Underweight

P for trend
Normal low

Normal high

Overweight

ObesityNo. of participants

262

3027

2129

2334

344

Age, year

63.5 ± 9.0

63.5 ± 8.9

63.8 ± 8.3

62.4 ± 9.1

57.1 ± 10.5

Hypertension, %

14.9

25.3

28.3

34.1

47.1

< 0.001

Daily drinker, %

43.1

48.4

49.0

45.2

39.5

<0.0010.9901

Non-drinker, %

43.1

32.3

32.0

35.2

33.7

<0.001

Smoker, %

39.3

29.9

26.2

25.2

26.5

0.037

Higher HbA1c, %

33.2

41.7

46.6

50.8

49.1

< 0.001

High HbA1c, %

8.0

9.4

11.6

14.9

25.3

< 0.001

Dyslipidemia, %

19.8

40.8

51.5

59.9

65.1

< 0.001

Hypertension: systolic blood pressure≥140 mmHg and/or diastolic blood pressure≥90 mmHg. Higher HbA1c: 5.6–6.4%. High HbA1c: ≥6.5%. BMI categories: < 18.5 kg/
m2 for underweight, 18.5–22.9 kg/m2 for normal low, 23.0–24.9 kg/m2 for normal high, 25.0–29.9 kg/m2 for overweight, and ≥ 30.0 kg/m2 for obesity

Table 3 Association between serum albumin and underweight status
Serum albumin

P for trend

1 SD incrementof serumalbumin

Quartile 1 (low)Quartile 2

Quartile 3

Quartile 4 (high)No. of participants

1,642

2,216

2,259

1,979

No. of underweight, n (%)

92 (5.6)

74 (3.3)

52 (2.3)

44 (2.2)

Age-adjusted model

Reference

0.58(0.42, 0.79)

0.39(0.28, 0.56)

0.39(0.26, 0.55)< 0.0010.69 (0.61, 0.78)

Multivariable model

Reference

0.70(0.50, 0.96)

0.50(0.35, 0.71)

0.55(0.37, 0.81)< 0.001

0.79 (0.70, 0.90)

Multivariable model: Adjusted for age, obesity, overweight, hypertension, daily drinker, non-drinker, smoker, higher HbA1c, high HbA1c. SD standard deviation. 1 SD is
0.28 g/dL. Serum albumin levels: < 4.2 g/dL for quartile 1 (low), 4.2–4.3 g/dL for quartile 2, 4.4–4.5 g/dL for quartile 3, and ≥ 4.6 g/dL for quartile 4 (high)Table 4 Association between serum albumin and height loss
Serum albumin
Quartile 1 (low)Quartile 2

Quartile 3

P for trend

1 SD incrementof serumalbumin

Quartile 4 (high)No. of participants

1,642

2,216

2,259

1,979

No. of height loss, n (%)

520 (31.7)

590 (26.6)

522 (23.1)

392 (19.8)

Age-adjusted model

Reference

0.82(0.71, 0.94)

0.70(0.61, 0.81)

0.62(0.53, 0.72)< 0.001

0.83(0.79, 0.88)

Multivariable model

Reference

0.83(0.72, 0.96)

0.72(0.62, 0.83)

0.63(0.54, 0.74)< 0.001

0.84(0.80, 0.88)

Multivariable model: Adjusted for age, underweight, overweight, obesity, hypertension, daily drinker, non-drinker, smoker, higher HbA1c, high HbA1c, dyslipidemia.
SD standard deviation. 1 SD is 0.28 g/dL. Serum albumin levels: < 4.2 g/dL for quartile 1 (low), 4.2–4.3 g/dL for quartile 2, 4.4–4.5 g/dL for quartile 3, and ≥ 4.6 g/dL forquartile 4 (high)

Association between serum albumin and height loss

Independent of known potential confounders, a significant inverse association was observed between serum
albumin level and height loss (Table 4).
Association between BMI categories and height loss

Independent of known potential confounders, in thenormal-low weight reference group, underweightpatients showed significantly higher ORs for heightloss. In the reference group with a normal-low weight,
obesity showed significantly higher ORs for height loss.
This association remained significant even after adjusting for known confounders (Table 5).
Associations between height loss, defined as being
in the highest quintile of annual height decrease

In addition, we performed the same analyses with height
loss, defined as being in the highest quintile of the annual

Shimizu et al. Journal of Physiological Anthropology(2024) 43:15

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Table 5 Association between categories of body mass index (BMI) and height loss
BMI categories
Underweight

Normal low

Normal highp

Overweightp

Obesitypp

No. of participants

262

3,027

2,129

2,334

344

No. of height loss, n (%)

91 (34.7)

747 (24.7)

522 (24.5)

574 (24.6)

90 (26.2)

Age-adjusted model

1.64(1.26, 2.14)< 0.001

Reference

0.98(0.86, 1.12)

0.777

1.04
(0.96, 1.18)

0.587

1.36
(1.05, 1.77)

0.021

Multivariable model

1.60(1.21 2.10)< 0.001

Reference

1.00(0.88, 1.14)

0.972

1.06
(0.93, 1.21)

0.389

1.37
(1.05, 1.79)

0.019

Multivariable model: Adjusted for age, hypertension, daily drinker, non-drinker, smoker, higher HbA1c, high HbA1c, dyslipidemia. BMI categories: < 18.5 kg/m2 forunderweight, 18.5–22.9 kg/m2 for normal low, 23.0–24.9 kg/m2 for normal high, 25.0–29.9 kg/m2 for overweight, and ≥ 30.0 kg/m2 for obesity

height decrease. The association between serum albumin
levels and height loss, and the association between BMI
categories and height loss were also calculated. Overall, the age-adjusted and multivariable ORs (95% CIs) ofheight loss for a 1 SD increment of serum albumin were0.83 (0.79, 0.88) and 0.84 (0.80, 0.89). In the normal-low
weight reference group, the age-adjusted and multivariable ORs (95% CIs) of height loss for underweight status
were 1.88 (1.43, 2.49) and 1.85 (1.40, 2.46), respectively.
The reference group was normal-low weight. the age
adjusted ORs (95% CIs) of height loss for normal-highweight, overweight and obesity were 0.96 (0.83, 1.01),
1.07 (0.93, 1.22), and 1.36 (1.02, 1.80). The corresponding
values in the multivariable model were 1.00 (0.88, 1.14),
1.06 (0.93, 1.21) and 1.37 (1.05, 1.79), respectively.

Discussion
In this study, being underweight, which is inversely associated with serum albumin levels, was found to be positively associated with height loss among Japanese men.
A previous study of 8,982 Japanese worker aged 40 to
74 years showed significant positive association between
high BMI (≥ 25.0 kg/m2) and height loss (defined as being
in the highest quintile of height decrease per year) [2].
This finding is partly consistent with the present results.
In the present study, even overweight (25.0–29.9 kg/m2)
status did not show any significant associated with therisk of height loss.
The present study found further evidence that being
underweight (< 18.5 kg/m2) is a significant risk factor forheight loss among Japanese men. However, the mechanisms underlying the association between underweightand height loss remain unknown. Figure 1 shows thepotential mechanisms underlying these results.
Compression fractures of the spine and narrowed
intervertebral space are two major causes of height loss
among adults. Furthermore, osteoporosis causes compression fractures and vertebral disc degeneration causes
narrowing of the intervertebral space.

Disruption of the microcirculation has been reported
as being associated with osteoporosis [10]. Disturbanceof blood flow to the intervertebral discs may also play a
crucial role in the development of lumbar disc degeneration [11].
CD34-positive cells, which play an important role inendothelial repair [12] contribute to the maintenanceof microcirculation by promoting angiogenesis [13]and neovascularization [14]. The number of circulating
CD34-postive cells can be used as a marker of endothelial repair activity [15]. As circulating CD34-positive
cells have been reported to be inversely associated withheight loss [4], blood flow disturbance, which is related toa shortage of endothelial repair, may cause height loss in
the general population.
Because serum albumin influences the migration of
CXCR4-expressing primary CD34 + hematopoietic progenitor cells [16], low levels of serum albumin may be
associated with height loss [1], indicating the disadvantage of activating endothelial repair. In the present study,
serum albumin was found to be inversely associatedwith height loss (Table 4) (Fig. 1h) and underweight status (Table 3) (Fig. 1f ). This may be because underweightparticipants might have a disadvantage in activating
endothelial repair, which might cause height loss. Therefore, underweight status was positively associated withheight loss (Table 5) (Fig. 1g), partly because of thepresence of lower levels of albumin.
In addition to endothelial repair activity, serum albumin contributes to extracellular antioxidant defenses[17]. as such, higher serum albumin levels may havehigher antioxidant activity than lower serum albumin
levels. Smoker, hypertension, dyslipidemia higher HbA1c
and high HbA1c showed essentially the same association with serum albumin levels and BMI categories in
the present study. Smoker showed a significant inverse
association with serum albumin levels (Table 1) and BMI
categories (Table 2) (Fig. 1c). Hypertension, dyslipidemia,
higher HbA1c, and high HbA1c levels were significantly

Shimizu et al. Journal of Physiological Anthropology(2024) 43:15

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Fig. 1 Possible mechanism underlying height loss. Alb albumin. Relations in red (a ~ h) were observed in this study

positively associated with serum albumin levels (Table 1)and BMI categories (Table 2) (Fig. 1a, d, e). These associations may be explained by nutritional status.
Conversely, in daily drinkers, serum albumin levels
showed a linear inverse association (Table 1) (Fig. 1b),whereas BMI categories showed an inverse U-shaped
association (Table 2). Similarly, in the present study,
serum albumin levels showed a linear inverse association with height loss (Table 4), whereas the BMI categories showed an inverse U-shaped association with heightloss (Table 5). Platelets contribute to endothelial repair in
conjunction with circulating CD34-positive cell [18]. Ethanol directly attenuates platelet activation [19] and influences on endothelial health [20]. Therefore, differences inthe distribution of daily drinkers may partly explain the
difference between serum albumin and BMI categories
as risk factors for height loss. Further investigations onplatelet activity are necessary.
Postural changes during the observation period may
also have played an important role in the present associations. There are bidirectional relationships between
postural changes and a compression fracture of the spine,and between postural change and a narrowed intervertebral space due to intervertebral disc degeneration. Compression fractures of the spine and intervertebral discdegeneration, which can cause postural changes, canalso be induced by decreased thoracic extensor muscle
strength, which is related to postural changes [21, 22].
Therefore, postural changes might act as a mediator of

the association between the serum albumin level andheight loss, and the association between BMI categories
and height loss.
The primary clinically relevant finding of the present study is that both obesity and underweight statusincrease the risk of height loss among Japanese men.
Serum albumin partly acts as a marker of height loss,
which is related to underweight status.
The limitations of this study warrant further consideration. Firstly, we only investigated associations in men.
Although essentially the same associations were observed
for women, the goodness of fit test evaluated by the Hosmer–Lemeshow test was not validated for the analyses
among women. As menopausal status may influence
height loss, a more detailed study including information on menopausal status may be necessary for women.
Although the highest quartile of height decrease per
year was defined as height loss in the present study, an
efficient cut-off point to define height loss has not been
established. However, additional analyses that definedheight loss using the highest quintile of height decrease
per year showed essentially the same associations.

Conclusion
In conclusion, the present study showed that being
underweight, which is inversely associated with serum
albumin levels, was positively associated with height loss
among Japanese men. These findings could help to clarify
the mechanisms underlying height loss in Japanese men.

Shimizu et al. Journal of Physiological Anthropology(2024) 43:15

Abbreviations
BMI	Body mass index
OR	Odds ratio
CI	Confidence interval
SD	Standard deviation
TG	Triglycerides
HDLc	High-density lipoprotein cholesterol
LDLc	Low-density lipoprotein cholesterol
HbA1c	Hemoglobin A1c
Acknowledgements
None.

Page 7 of 8

3.

4.

5.

Authors’ contributions
The authors contributed to study in the following manner: study design (YS);
analysis (YS, EH, NS, MT, TY, KM); drafting manuscript (YS); interpretation (YS,
EH, NS) statistical review (YS, NS); revision to manuscript (all authors).
Funding
This study was supported by The Japan Agency for Medical Research andDevelopment [22rea522104h0001]. This study was also supported by Grantsin-Aids for Scientific Research from Japan Society for the Promotion of Science(No.22K06421). The funders had no role in study design, data collection andanalysis, decision to publish, or preparation of the manuscript.
Availability of data and materials
The datasets generated and/or analyzed during the current study are not publicly available due to ethical considerations. Qualified researchers may apply
for access a minimal dataset by contacting data management staff at epiana@
iph.osaka.jp. Information regarding data requests is also available at https://​www.​iph.​osaka.​jp/​s016/​000/​index.​html (accessed on 12the January 2024).

6.

7.
8.

9.

Declarations

10.

Ethics approval and consent to participate
This study was approved by the ethics committee of Osaka Institute of Public
Health (project registration code: 2311–02). All procedures involving humanparticipants were performed in accordance with the ethical standards of the
Ethics Committee of Osaka Institute of Public Health and the 1964 Declaration of Helsinki and its amendments. Informed consent for this study was
obtained from all participants for study population using the opt-out method,with descriptions of the study presented on the institution’s website (https://​www.​iph.​osaka.​jp/​s004/​099/​2311-​02.​pdf ) (accessed on 12th January 2024).
All analyses for this study were conducted using deidentified data, and theauthors completing the analysis did not have access to data with identifiers.
For research purposes data were extracted 26th December 2023.

11.

12.
13.
14.

Consent for publication
Not applicable.
Competing interests
The authors declare no conflict of interest.
Received: 5 March 2024 Accepted: 15 May 2024

15.

16.
17.

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