Skip to main content
Download PDF

Preconception underweight impact on postnatal osteoporotic fracture: a retrospective cohort study using Japanese claims data

BMC Pregnancy and Childbirth volume 24, Article number: 315 (2024) Cite this article

Abstract

Background

Undernutrition and underweight are osteoporosis risk factors. Therefore, improving the health of underweight young women in Japan is an important medical issue. However, few studies have evaluated the association between being preconception underweight and postnatal osteoporotic fractures in young women.

Methods

This retrospective cohort study used a Japanese nationwide claims database (JMDC Inc.) to evaluate the effect of preconception underweight on the incidence of osteoporotic fracture within two years after delivery. Data from 16,684 mothers who delivered their first singleton babies between January 2006 and December 2020 were analysed. The combination of disease codes of fractures at sites associated with osteoporosis and medical procedures for fractures was defined as the incidence of osteoporotic fractures, whereas the body mass index (BMI) recorded 12–36 months before delivery was used as the exposure. We estimated the incidence of osteoporotic fractures by BMI category using a Kaplan–Meier curve and examined the fracture risk using Cox hazard regression analyses.

Results

Fifty-one women (0.31%) were affected by osteoporotic fractures within two years of delivery. More than 80% of these were rib fractures, and approximately 65% of fractures occurred after the first year postpartum. Preconception underweight (BMI < 18.5 kg/m2) was significantly associated with the incidence of postpartum osteoporotic fractures. There was no significant association between low BMI and postnatal fractures, as analysed via multiple categorical logistic regression analysis.

Conclusion

Appropriate control of preconception weight might be critical to improving the postpartum quality of life, subsequent bone health, and neonatal care environment.

Peer Review reports

Background

In recent years, being underweight has become a major issue in women’s healthcare in Japan. Japan is one of the developed countries with the most advanced trend of underweight females [1, 2]. Women with a body mass index (BMI), which is used as a criterion for estimating underweight and undernutrition, of less than 18.5 kg/m2 account for 11.5% of all Japanese women, reaching as high as 20.7% among young women in their 20s [3]. The high prevalence of low body weight among Japanese young women is suggested to be a result of more women embracing the Western appearance culture and thin-ideal standard propagated by the media. A shift to collectivist cultures, characterized by conformity to social norms, can more substantially affect food behaviours and increase eating disorders [4]. The mean age of Japanese primipara pregnant women is 30.7 years [5], which coincides with the age of women with a high prevalence of low body weight. According to multiple studies, severe underweight among middle-aged women aged 40 years or older not only increases the risk of noncommunicable diseases, such as type 2 diabetes mellitus and chronic kidney disease, but also causes osteoporosis and the associated locomotive syndrome [6, 7]. Thus, similar risks are assumed to be present for young women aged less than 40 years. However, many previous studies examining the association between osteoporosis and being underweight have focused on women aged 60 years or above, and few studies have examined the impact of being underweight in females at the reproductive age of 20–40 years on future bone health.

Pregnancy- and lactation-associated osteoporosis (PLO), a rare type of osteoporosis that develops in women of reproductive age, develops during late pregnancy or breastfeeding and is characterized by osteoporosis-related fractures, mainly vertebral body fractures, with severe back pain [8, 9]. Although the prevalence is low at 0.04–0.08% [10], PLO greatly impairs the mental state and quality of life of postpartum women, as it develops at a time when women are busy with breastfeeding and childcare and imposes a huge burden [11, 12]. The aetiology of PLO remains unclear, but its onset involves women’s physical characteristics before pregnancy, such as underweight and undernutrition, as with normal osteoporosis [13], in addition to physical or endocrinological changes in women from late pregnancy to after delivery, such as calcium loss from the body due to breastfeeding, a postpartum drop in blood oestrogen, and an increase in blood parathyroid hormone-related proteins [14, 15]. Therefore, to clarify the impact of being underweight in women of reproductive age on their future bone health, we focused on the association between preconception underweight and postpartum osteoporosis-related fragile fractures.

In addition, we used the real-world data (RWD) accumulated in the Japanese Medical Data Center (JMDC) Claims Database (JMDC Inc., Japan) in this study. Retrospective cohort studies using RWD target many cases with various backgrounds; therefore, they allow causal assumptions even for diseases with a low prevalence. Furthermore, in the JMDC Claims Database, claims and specific health check-up results have been anonymized, as entrusted by multiple health insurance associations. The JMDC Claims Database includes a wide variety of claims data, such as medical inpatient claims, medical outpatient claims, and dispensing claims, allowing follow-ups of outpatient visits and cases where consultation has been sought at multiple medical institutions. As many fracture treatments are provided as outpatient treatments, considering the reality of fracture treatment in Japan, the JMDC Claims Database was considered the most suitable RWD for this study.

Therefore, to explore the association between preconception underweight and postpartum fragility fractures in young Japanese women, we conducted a retrospective cohort study using the JMDC Claims Database.

Methods

We performed a retrospective observational analysis using the JMDC Claims Database (JMDC, Inc., Japan). The JMDC database is an epidemiological claims database that accumulates claims (inpatient, outpatient, and dispensing) and health check-up data received from multiple health insurance associations and mainly includes the data of employees and their families of relatively large companies in Japan. The JMDC Claims Database is used to understand the actual state of various diseases and medical treatments, and the details of the database have already been described in other papers [16,17,18]. The study was conducted in accordance with the tenets of the Declaration of Helsinki. In addition, we obtained approval from the Ethics Committee of the National Center for Child Health and Development before conducting this study (approval number 2021 − 157). We did not obtain informed consent because we used only an anonymized aggregate dataset. In this study, we used the JMDC Claims Database from January 2006 to December 2020 and extracted two datasets, namely, the Children and Women datasets. First, for the children’s dataset, out of the children born, we extracted data of children whose “birth date” matched the “insurance subscription date.” Next, for the women’s dataset, out of the women linked to babies by the family ID, we extracted data of women who were in an “own person” or “spouse” relationship with the subscriber. We combined these two datasets with household flags to create a mother-child dataset.

From the mother-child dataset, we excluded mother-child pairs with the child’s birth date after the mother’s insurance subscription period (n = 29,504), mother-child pairs with multiple gestations (n = 2,477), mother-child pairs with older siblings (n = 9,491), and mother-child pairs without regular maternal health check-up data 12–36 months before the child’s birth date (n = 204,459). Finally, 16,684 mother-child pairs were included in the analysis. We defined the child’s “birth date” as the delivery month for the women (Fig. 1).

Fig. 1
figure 1

Flowchart of the study. Osteoporotic fracture was defined as vertebral fractures, distal radius fractures, proximal humerus fractures, femoral proximal fractures, rib fractures, pelvic fractures, and lower leg fractures. JMDC, Japanese nationwide claims database

Full size image

Body mass index

To define preconception underweight, we used BMI values included in the women’s health check-up data 12–36 months before the child’s birth date and divided the subjects into three groups according to BMI: <18.5 kg/m2, 18.5–24.9 kg/m2, and ≥ 25.0 kg/m2. The BMI was calculated as follows: weight (kg)/[height (m)]2. In cases where multiple health check-ups were performed 12–36 months before the child’s birth date and there were multiple BMI values, we adopted the data for the time point closest to the birth date (Fig. 2).

Fig. 2
figure 2

Study design. The combination of disease codes of closed osteoporotic fractures and medical procedures for fractures 0–23 months after delivery were defined as “occurring of osteoporotic fractures.” The disease code and the health check-up data recorded 12–36 months before delivery were used as confounders, whereas the body mass index recorded 12–36 months before delivery was used as the exposure in this study. The data recorded at the latest health check before delivery were used. However, the data during pregnancy were not used. If the latest data differed depending on the item in the medical check-up data, we used the data from the medical check-up when the body mass index was recorded at the nearest time before delivery

Full size image

Outcome

We targeted eight types of fragility fractures as the outcomes, namely lumbar, thoracic spine, proximal femoral, proximal humeral, distal radius, pelvic, lower leg, and rib fractures [19, 20], because these sites are considered easy to fracture with low-level or low-energy trauma if the bone is osteoporotic.

The subjects labelled with both the disease name code of closed fragility fractures and the medical procedure code within two years after delivery were included (Additional file 1: Table S1).

Disease name codes for open fractures were excluded because open fractures are often caused by a significant injury unrelated to osteoporosis. Patients labelled with the disease name code for apparent primary or secondary osteoporosis before pregnancy were excluded.

The apparent osteoporosis diseases were as follows: postmenopausal osteoporosis, primary or idiopathic osteoporosis, post-oophorectomy osteoporosis, disuse osteoporosis, postoperative malabsorption osteoporosis, steroid-induced osteoporosis, drug-induced osteoporosis, juvenile or geriatric osteoporosis, secondary osteoporosis, spinal osteoporosis, and neoplastic pathological fractures (Additional file 1: Table S1). Owing to the nature of the database, the medical treatment of traffic injuries was not included in the JMDC claims database.

Measurements and definitions

We surveyed the mothers’ ages at delivery as well as the presence or absence of caesarean section (CS), diabetes mellitus, hyperlipidaemia, endocrine diseases, gynaecologic cancers, and anorexia nervosa, all of which may cause osteoporosis as a complication. These diseases were defined using injury/disease names or medical procedure codes (Additional file 1: Table S2). We extracted data on smoking, alcohol intake, and laboratory findings from the health check-up data. For the laboratory findings, we defined a haemoglobin concentration of less than 12 g/dL as anaemia, a total cholesterol level of less than 128 mg/dL as undernutrition, and an estimated glomerular filtration rate (eGFR) of less than 60 mL/min as an indicator of chronic kidney disease. The formulas were as follows: total cholesterol level = (serum low-density lipoprotein cholesterol) + (serum high-density lipoprotein cholesterol) + (serum total glycerides/5) and eGFR = 194 × (serum creatinine− 1.094) × (age− 0.287) × 0.739.

Statistical analysis

First, we described the incidence and timing of fractures within a period of up to two years after delivery and the types of fractures. Next, we classified the subjects according to age; preconception BMI; complications reported to be associated with osteoporotic fractures, such as alcohol intake, smoking, anaemia, undernutrition, chronic kidney diseases, diabetes mellitus, endocrine diseases, malignant tumours (gynaecologic cancers and breast cancer), and the use of proton pump inhibitors and compared the incidence of osteoporotic fractures in each group.

For the use of proton pump inhibitors, we used the disease name of reflux esophagitis, for which they were used as standard therapeutic drugs. In addition, to examine the impact of the delivery mode on fractures, we classified the subjects by the presence or absence of CS and compared the fracture rates. Subsequently, we showed the cumulative incidence of fractures within two clinical postpartum years in each group using Kaplan–Meier curves.

Then, as the incidence of fractures associated with the obesity group (≥ 25.0 kg/m2) was low, we classified the subjects into two groups of underweight (BMI < 18.5 kg/m2) and above standard (BMI ≥ 18.5 kg/m2) by their BMI. Finally, to explore the factors affecting the survival data of osteoporotic fractures, we calculated the crude hazard ratio and adjusted hazard ratio, as well as the 95% confidence interval, using the Cox proportional hazards model, with the presence or absence of osteoporotic fractures as the dependent variable. The age at delivery, BMI, alcohol intake, smoking, laboratory findings, and complications were the independent variables, selected from the database with subjects with three or more fractures in each category when the variable was classified by category and with an intergroup difference of 0.1% or above in the fracture rate. We set smoking as an independent variable because it is considered a clear osteoporosis-related factor [21], even though a difference of only 0.3% was observed in the fracture rate between the categories. We used SAS software (version 15.0; SAS Institute, Cary, NC, USA) for the analyses performed in this study and set the significance level as 5%.

Results

Characteristics of women with fragility fractures within 2 years after delivery

Of the 16,684 subjects analysed, 51 (0.31%) developed fragility fractures within two years of delivery. Table 1 shows the time and site of the fracture in the fracture cases. For the time of fracture, most fractures occurred 12–14 months after delivery (11 cases), followed by 21–23 months after delivery (10 cases) and 18–20 months after delivery (9 cases). Of all cases, 64.7% (33 cases) experienced fractures 1–2 years after delivery.

Table 1 Characteristic of women with osteoporotic fractures within 2 years after delivery
Full size table

For the site of fracture, rib fractures were the most common, accounting for 86.3% of all fracture cases. The other fractures involved the lumbar spine in 2 cases (3.9%), distal radius in 2 cases (3.9%), and lower leg in 3 cases (5.9%). While both cases of lumbar spine fractures occurred within two months after delivery, distal radius fractures and lower leg fractures occurred 15 months after delivery (lumbar spine fracture: 1–2 months after delivery: 2 cases; distal radius fracture: 15–17 months after delivery: 1 case, 18–20 months after delivery: 1 case; lower leg fracture: 18–20 months after delivery: 2 cases, 21–23 months after delivery: 1 case).

Incidence of osteoporotic fractures of the subjects between clinical categories

In Table 2, we compare the incidence of osteoporotic fractures in the subjects between the clinical categories assigned based on age, BMI, smoking and alcohol consumption, mode of delivery, complications, and several laboratory measurements recorded during the health checks. Women over 40 and aged 30–40 years showed a higher incidence of osteoporotic fractures than those aged 20–30 years (0.37% and 0.31%, respectively, vs. 0.18%). With regard to the BMI, the prevalence of fractures among women with a low BMI (< 18.5 kg/m2) was higher than that among normal (18.5–24.9 kg/m2) or heavy (> 25 kg/m2) BMI subjects (0.47% vs. 0.25% and 0.21%, respectively). Women who underwent CS and drank alcohol every day also seemed to have fractures more frequently than those who did not. The fracture incidence was similar between the groups when the assignation was based on smoking habits, laboratory data recorded during the health check, or complications.

Table 2 Incidence of osteoporotic fractures of the subjects between clinical categories
Full size table

Cumulative incidence of osteoporotic fracture within two years after delivery

Figure 3 shows the Kaplan–Meier estimates of the cumulative incidence of osteoporotic fractures among women with a low BMI and those with a normal or heavy BMI. The cumulative incidence of osteoporotic fractures was similar between the two groups up to one year after delivery; however, after one year, the fracture rate increased in the low BMI group, exceeding the cumulative incidence in the normal and heavy BMI groups.

Fig. 3
figure 3

Kaplan–Meier survival: cumulative incidence of osteoporotic fractures in women within 2 years post-delivery. Low body weight, the body mass index is less than 18.5 kg/m2 (solid line); more than normal body weight, the body mass index is over 18.5 kg/m2 (dotted line). Group — underweight (BMI < 18.5 kg/m2, solid line), -– normal/ heavy weight (BMI ≥18.5 kg/m2, dotted line)

Full size image

Factors associated with osteoporotic fractures occurring within two years after delivery

Women with a low BMI show significantly higher ratio of osteoporotic fractures within two years after delivery than those with a normal or heavy BMI (hazard ratio: 1.8, 95% confidence interval: 1.01–3.34) (Table 3). However, there was no significant association between a low BMI and postnatal osteoporotic fractures on multiple categorical logistic regression analysis using the age at delivery, daily alcohol intake, habitual smoking, and CS as adjusted variables. Other factors were not correlated with the incidence of osteoporotic fractures within two years of delivery, even in the crude analysis.

Table 3 Factors associated with osteoporotic fractures occurring within 2 years after delivery
Full size table

Discussion

Our retrospective cohort study using the JMDC database revealed the potential association between pre-conception underweight status and the incidence of osteoporotic fractures within two years after delivery. In total, 0.31% of all postpartum women developed osteoporotic fractures within two years after delivery, more than 80% of them were rib fractures, and approximately 65% developed fractures after one year after delivery. Preconception underweight (BMI < 18.5 kg/m2) was significantly associated with the incidence of postpartum fragility fractures. However, a significant association was not observed between a low preconception BMI and postnatal fractures in multiple categorical logistic regression analysis using the age at delivery, daily alcohol intake, habitual smoking, and delivery mode as adjusted variables.

The frequency, common site, and time of osteoporotic fractures shown in our study differ from the previously reported PLO characteristics. Although epidemiological information on PLO is limited, based on previous studies, the incidence of PLO is approximately 4–8 per 1 million people [9], the most common site is the vertebral body, and it most frequently occurs from the 3rd trimester of gestation to three months after delivery [10]. In contrast, in our study, the incidence of osteoporotic fractures within two years after delivery was 0.31%, which is approximately 1,000 times higher than that reported previously. In addition, spinal fractures accounted for approximately 4% of the total, and the fracture cases within three months after delivery only occurred in approximately one out of seven women. Such deviations could be because of the differences in research methods of our study compared with those of previous studies on PLO.

Most case reports or series and retrospective cohort studies on PLO have defined the disease based on clinical symptoms and the bone density [22]. On the other hand, we extracted data on osteoporotic fractures, a clinical outcome related to osteoporosis, by combining the disease name code of closed fractures in sites associated with osteoporosis and the medical procedures from the claims data of more than 10,000 women.

In a previous study that examined the fracture rate within two years of obstetric hospitalization using RWD, the incidence of osteoporotic fractures within two years after delivery was 0.045%, which was approximately 10% of the incidence calculated in our study [23]. This showed that there may have been cases other than the narrowly defined PLO among the extracted subjects. Because we conducted the study by further expanding the range to women without a history of obstetric hospitalization and women who underwent fracture treatment as outpatients, we may have had a broader spectrum of postnatal fragility fractures other than those related to PLO. However, fractures can negatively impact the postpartum quality of life, mental status, and work ability in women [11, 12]. As our study shows that more women suffer from osteoporotic fractures at a time imposed with postpartum burdens and require medical and social support than previously reported, we believe that our results could provide new important sights for the area of perinatal female bone healthcare.

Additionally, focusing on the sites of fracture, more than 80% of osteoporotic fractures within two years after delivery represented in this study were rib fractures. Although some rib fractures may be caused by trauma, the JMDC Claims Database does not include the medical procedure code for injuries caused by traffic accidents. Furthermore, we excluded subjects labelled with the disease code of open fracture, as women within two years after delivery are unlikely to perform high-intensity exercises that may induce fractures. Therefore, rib fractures are considered osteoporotic fractures that occur in the setting of low-level or low-energy trauma.

A history of fracture is a risk factor for future fractures [24] and is known to be significantly correlated with increased mortality risk in older adults, even if they are non-hip, non-vertebral fractures, including rib fractures [25]. The rib fracture, the major fracture among postpartum women in our study, has recently been reported as a predictor of future fractures in young and older postmenopausal women [26]. Therefore, viewing postpartum osteoporotic fractures as sentinel fractures may be necessary, which may increase the risk of future major fractures. For noncommunicable diseases such as hypertension and diabetes mellitus, pregnancy is known to be a window that allows a glimpse into future maternal health and a good opportunity for implementing appropriate preventive interventions [27]. For women who develop osteoporotic fractures after delivery, appropriate vitamin D supplementation and calcium intake, guidance of exercise habits, regular bone density measurement, and drug treatment may prevent future major fractures and extend their healthy life expectancy.

This study had several limitations. First, information regarding breastfeeding, physical activity, vitamin D insufficiency status, and family history, which are among the major causes of postpartum osteoporotic fractures, was not included in the analysis. However, to examine the incident risk of postpartum fracture, which is a rare disease, we believe that the advantage of being able to conduct the study using a database of many cases, such as the JMDC database, outweighs the disadvantage of not being able to examine detailed confounders. Second, as the incidence of fractures in the high BMI group was low, factors affecting the survival data of osteoporotic fractures could not be examined between the low BMI group (< 18.5 kg/m2) and the normal or high BMI group (≥ 18.5 kg/m2). In recent years, the increase in the number of young obese women has also become an issue in Japan. Thus, examining the risks for thin women with normal weight and obese women by conducting studies several years later after collecting sufficient data may be interesting. Third, we were unable to obtain information about the bone mineral density and bone metabolism markers from the database. These data are essential for the diagnosis of osteoporotic fractures. To overcome this limitation, we attempted to define osteoporotic fractures by combining medical procedures and disease name codes of closed fractures at eight osteoporosis-related bone sites based on expert opinion. Furthermore, we excluded the case of a major traffic injury and apparent primary or secondary osteoporosis before pregnancy. Finally, we used only one definition to obtain data on fragility fractures from the database. In the future, using other definitions would be worthy to examine the validity of the definition of postpartum fragility fracture.

Conclusions

We examined the correlation between preconception underweight (BMI < 18.5 kg/m2) and osteoporotic fractures within two years after delivery using an RWD in Japan. Although preconception underweight was significantly associated with the incidence of postpartum osteoporotic fractures, no significant association was shown using multiple categorical logistic regression analysis. Proper weight management for preconception women might be essential to improve the postpartum quality of life, prevent future fractures, and improve the bone health of the next generation.

Data availability

The data supporting the findings of this study are available from the corresponding author, Kayoko Kaneko, upon reasonable request.

Abbreviations

BMI:

Body mass index

CS:

Caesarean section

eGFR:

Estimated glomerular filtration rate

JMDC:

Japanese Medical Data Center

PLO:

Pregnancy- and lactation-associated osteoporosis

RWD:

Real-world data

References

  1. NCD Risk Factor Collaboration (NCD-RisC). Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants. Lancet. 2020;396(10261):1511–24.

    Article  Google Scholar 

  2. Otsuka H, Tabata H, Someya Y, Tamura Y. Trends in the prevalence of underweight in women across generations in Japan. J Bone Min Metab. 2021;39(4):719–20.

    Article  Google Scholar 

  3. Ministry of Health Labour and Welfare, Japan. 2020 Results of 2019 National Health and Nutrition Survey. https://www.mhlw.go.jp/stf/newpage_14156.html. Accessed 2 March, 2023.

  4. Kinoshita S, Kishimoto T. Anti-obesity drugs, eating disorders, and thinness among Japanese young women. Lancet Diabetes Endocrinol. 2024;12(2):90–2.

    Article  PubMed  Google Scholar 

  5. Results of. Annual Population and Social Security Surveys (The National Fertility Survey) [Internet]. 2021 [cited 2024/3/5]. https://www.mhlw.go.jp/toukei/saikin/hw/jinkou/tokusyu/syussyo07/index.html. Accessed 5 March 2024.

  6. Tatsumi Y, Ohno Y, Morimoto A, Nishigaki Y, Maejima F, Mizuno S, et al. U-shaped relationship between body mass index and incidence of diabetes. Diabetol Int. 2012;3(2):92–8.

    Article  Google Scholar 

  7. Tatsumi Y, Higashiyama A, Kubota Y, Sugiyama D, Nishida Y, Hirata T, et al. Underweight young women without later weight gain are at high risk for osteopenia after midlife: the KOBE Study. J Epidemiol. 2016;26(11):572–8.

    Article  PubMed  Google Scholar 

  8. Hardcastle SA, Yahya F, Bhalla AK. Pregnancy-associated osteoporosis: a UK case series and literature review. Osteoporos Int. 2019;30(5):939–48.

    Article  CAS  PubMed  Google Scholar 

  9. Smith R, Stevenson JC, Winearls CG, Woods CG, Wordsworth BP. Osteoporosis of pregnancy. Lancet. 1985;1(8439):1178–80.

    Article  CAS  PubMed  Google Scholar 

  10. Qian Y, Wang L, Yu L, Huang W. Pregnancy- and lactation-associated osteoporosis with vertebral fractures: a systematic review. BMC Musculoskelet Disord. 2021;22(1):926.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Gehlen M, Lazarescu AD, Hinz C, Schwarz-Eywill M, Pfeifer M, Balasingam S, et al. Long-term outcome of patients with pregnancy and lactation-associated osteoporosis (PLO) with a particular focus on quality of life. Clin Rheumatol. 2019;38(12):3575–83.

    Article  PubMed  Google Scholar 

  12. Ozcelik B, Ozcelik A, Debre M. Postpartum depression co-occurring with lactation-related osteoporosis. Psychosomatics. 2009;50(2):155–8.

    Article  CAS  PubMed  Google Scholar 

  13. Rizzoli R, Bonjour JP. Pregnancy-associated osteoporosis. Lancet. 1996;347(9011):1274–6.

    Article  CAS  PubMed  Google Scholar 

  14. Winter EM, Ireland A, Butterfield NC, Haffner-Luntzer M, Horcajada MN, Veldhuis-Vlug AG, et al. Pregnancy and lactation, a challenge for the skeleton. Endocr Connect. 2020;9(6):R143–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Kovacs CS. Calcium and phosphate metabolism and related disorders during pregnancy and lactation. In: Feingold KR, Anawalt B, Blackman MR, Boyce A, Chrousos G, Corpas E, et al. editors. Endotext. South Dartmouth (MA): MDText.com, Inc.　Copyright © 2000–2023. MDText.com, Inc.; 2000.

  16. Fujioka I, Ohtsu H, Yonemoto N, Sase K, Murashima A. Association between prenatal exposure to antidepressants and neonatal morbidity: an analysis of real-world data from a nationwide claims database in Japan. J Affect Disord. 2022;310:60–7.

    Article  CAS  PubMed  Google Scholar 

  17. Ogawa Y, Takeshima N, Furukawa TA. Maternal exposure to benzodiazepine and risk of preterm birth and low birth weight: a case-control study using a claims database in Japan. Asia Pac Psychiatry. 2018;10(3):e12309.

    Article  PubMed  Google Scholar 

  18. Kimura T, Snijder R, Nozaki K. Diagnosis patterns of CKD and Anemia in the Japanese Population. Kidney Int Rep. 2020;5(5):694–705.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Osteoporosis: assessing the risk of fragility fracture. London: National Institute for Health and Care Excellence (NICE). 2017. https://www.ncbi.nlm.nih.gov/books/NBK554920/. Accessed 2 March, 2023.

  20. Hernlund E, Svedbom A, Ivergård M, Compston J, Cooper C, Stenmark J, et al. Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos. 2013;8(1):136.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Lane NE. Epidemiology, etiology, and diagnosis of osteoporosis. Am J Obstet Gynecol. 2006;194(2 Suppl):S3–11.

    Article  CAS  PubMed  Google Scholar 

  22. Bishop N, Arundel P, Clark E, Dimitri P, Farr J, Jones G, et al. Fracture prediction and the definition of osteoporosis in children and adolescents: the ISCD 2013 Pediatric Official positions. J Clin Densitom. 2014;17(2):275–80.

    Article  PubMed  Google Scholar 

  23. Toba M, Terauchi M, Moriwaki M, Obayashi S, Miyasaka N, Fushimi K. Fractures within 2 years of an obstetric hospitalization: analysis of nationwide administrative data in Japan. J Bone Min Metab. 2022;40(5):748–54.

    Article  Google Scholar 

  24. Kanis JA, Johansson H, Harvey NC, Gudnason V, Sigurdsson G, Siggeirsdottir K, et al. The use of 2-, 5-, and 10-year probabilities to characterize fracture risk after a recent sentinel fracture. Osteoporos Int. 2021;32(1):47–54.

    Article  CAS  PubMed  Google Scholar 

  25. Alarkawi D, Bliuc D, Tran T, Ahmed LA, Emaus N, Bjørnerem A, et al. Impact of osteoporotic fracture type and subsequent fracture on mortality: the Tromsø Study. Osteoporos Int. 2020;31(1):119–30.

    Article  CAS  PubMed  Google Scholar 

  26. Sajjan SG, Barrett-Connor E, McHorney CA, Miller PD, Sen SS, Siris E. Rib fracture as a predictor of future fractures in young and older postmenopausal women: national osteoporosis risk Assessment (NORA). Osteoporos Int. 2012;23(3):821–8.

    Article  CAS  PubMed  Google Scholar 

  27. Sheiner E, Kapur A, Retnakaran R, Hadar E, Poon LC, McIntyre HD, et al. FIGO (International Federation of Gynecology and Obstetrics) Postpregnancy Initiative: long-term maternal implications of pregnancy complications-follow-up considerations. Int J Gynaecol Obstet. 2019;147(Suppl 1):1–31.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank Mariko Takagai and Noriko Hanai for their administrative support.

Funding

This work was supported by the Japanese Ministry of Health, Labour and Welfare (grant number: 22FB0201).

Author information

Authors and Affiliations

  1. Division of Maternal Medicine, Center for Maternal-Fetal, Neonatal and Reproductive Medicine, National Center for Child Health and Development, Tokyo, Japan

    Kayoko Kaneko, Eiko Miyagawa & Atsuko Murashima

  2. Department of Health Policy, National Center for Child Health and Development, Tokyo, Japan

    Maiko Suto & Kenji Takehara

  3. Division of Biostatistics, National Center for Child Health and Development, Tokyo, Japan

    Masashi Mikami

  4. Department of Orthopaedic Surgery, Shinshu University school of Medicine, Matsumoto, Japan

    Yukio Nakamura

Authors
  1. Kayoko Kaneko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maiko Suto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eiko Miyagawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Masashi Mikami
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yukio Nakamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Atsuko Murashima
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kenji Takehara
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

KK and KT designed the study and wrote the first draft of the manuscript. KK, MS, and EM designed the corset of variants used to extract data from the JMDC database. MM analysed the data. AM and YN provided professional advice. All authors contributed to the discussion and interpretation of the results, critically reviewed the manuscript, and approved the final version for submission.

Corresponding author

Correspondence to Kayoko Kaneko.

Ethics declarations

Ethics approval and consent to participate

The study was conducted in accordance with the tenets of the Declaration of Helsinki and was approved by the ethics committee of the National Center for Child Health and Development (approval no. 2021 − 157). The requirement for informed consent was waived due to the anonymous nature of the data, and this was approved by the Ethics Committee of the National Center for Child Health and Development (approval number: 1683).

Consent for publication

Not applicable.

Competing interests

A.M. received a research grant from Chugai Pharmaceutical Co. Ltd. and lecture fees from Astellas Pharma Inc. and Chugai Pharmaceutical Co. Ltd. The other authors have no conflicts of interest to declare.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

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 the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other 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 this licence, 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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kaneko, K., Suto, M., Miyagawa, E. et al. Preconception underweight impact on postnatal osteoporotic fracture: a retrospective cohort study using Japanese claims data. BMC Pregnancy Childbirth 24, 315 (2024). https://doi.org/10.1186/s12884-024-06514-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12884-024-06514-y

Keywords

BMC Pregnancy and Childbirth

ISSN: 1471-2393

Contact us