Higher disease burden and lower utilization in Mongolian with breast cancer: a 9-year retrospective cohort study of 18.19 million adults in China

Abstract

Background:

Whether health inequalities of disease burden and medical utilization exist by ethnicity in Asian breast cancer (BC) patients remains unclear. The authors aim to measure ethnic disparities in disease burden and utilization among Mongolian and Han female BC patients in China.

Materials and methods:

Based on data extracted from Inner Mongolia Regional Health Information Platform, a retrospective cohort study was established during 2012–2021. Disease burden including incidence, 5-year prevalence, mortality, survival rate, and medical cost were analyzed and compared between Han and Mongolian patients.

Results:

A total of 34 878 female patients [mean (SD) age, 52.34 (10.93) years] were included among 18.19 million Chinese, and 4315 (12.03%) participants were Mongolian. Age-standardized rates of incidence are 32.68 (95% CI: 20.39–44.98) per 100 000. Higher age-specific incidence and 5-year prevalence were observed in Mongolian than in Han. The cost of BC annually per capita was significantly lower for Mongolian than Han [$1948.43 (590.11–4 776.42) vs. $2227.35 (686.65–5929.59), P<0.001]. Mongolian females showed higher all-cause mortality [30.92 (95% CI: 28.15–33.89) vs. 27.78 (95% CI: 26.77–28.83) per 1000, P=0.036] and BC-specific mortality [18.78 (95% CI: 16.64–21.13) vs. 15.22 (95% CI: 14.47–16.00) per 1000, P=0.002] than Han females. After adjusting covariates, Mongolian were associated with increased all-cause mortality [HR, 1.21, (95% CI: 1.09–1.34); P<0.001] and BC-specific mortality [HR, 1.31, (95% CI: 1.14–1.49); P<0.001].

Conclusion:

The findings of this cohort study highlight a higher level of disease burden with unmet medical demand in Mongolian patients, suggesting that more practical efforts should be made for the minority. Further research is needed to explore the concrete mechanisms of the disparities as well as eliminate health disproportion.

Introduction

Highlights

• This study first reported the disease burden and healthcare utilization of female breast cancer in Inner Mongolia based on large-scale population-based data including 18.19 million adults. The largest Mongolian population, accounting for over 50% worldwide, was observed, which addressed the research gap of ethnic disparities within Asia.

• Mongolian had higher ASR of incidence (P<0.001) and 5-year prevalence (P<0.001), all-cause mortality (P=0.036), and breast cancer-specific mortality (P=0.002).

• Mongolian patients had a worse medical utilization, with a lower cost of breast cancer annually per capita ($1948.43 vs. $2227.35, P<0.001).

• Mongolian patients had a worse prognosis than Han patients with significantly increased all-cause mortality (HR=1.21; P<0.001) and breast-specific mortality (HR=1.31; P<0.001).

Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among females worldwide¹. In China, BC was the first cause of cancer incidence among women¹, accounting for 18.4% of the global BC cases². The disease burden of BC is increasing both worldwide and in China^3,4. However, disparities exist in disease burden among different groups of people⁵, in which race/ethnicity plays a crucial part. African Americans have been focused on by most studies about race/ethnicity for female breast cancer (FBC), where the disparities in disease burden^6–9, inequalities in medical utilization^10–12, and the possible factors such as socioeconomic status^8,9,13, healthcare system^10,12, genomic biomarker^13–15, geographic region^16,17, comorbidity^11,18,19, and cultural background^8,9 were reported. In contrast, Asians were included in only a few studies and often classified into ‘Others’^20,21. Some studies reported the disease burden of FBC in Asian Americans and the disparities between them and other ethnic groups^16,22–24 but it is inappropriate to extrapolate the conclusions to Asians because of the evident differences between Asian Americans and Asians²⁵. Even in the group of Asian Americans, there is a call for further differentiation of the ethnicity due to the heterogeneity that has been reported²⁶. Moreover, significant disparities in the disease burden of FBC have been observed within Asian countries at the national level^27,28, indicating the necessity of further study within Asian ethnic groups.

In sum, few studies of ethnic disparities have been conducted in China, which contributed to the most BC patients (18.4% in 2020) in the world²⁹. Inner Mongolian is the third largest province in China, and it has a population of 4.25 million Mongolian, accounting for over 70% of the Mongolian population in China and 50% of the world. Mongolian are one of the largest ethnic minorities in East Asia with more than 10 million population worldwide, of which 6.3 million are Chinese residents³⁰. Therefore, exploring ethnic differences between Mongolian and Han helps people better understand the health equity status of the minority group not only in China but also worldwide. Inner Mongolia Regional Health Information Platform (IMRHIP) collects and administrates healthcare information of residents in Inner Mongolia to assist in addressing cancer health disparities across ethnicities³¹. This study was conducted to outline and analyze ethnic disparities of disease burden and medical utilization of BC based on IMRHIP.

Methods

Data sources

Data were obtained from IMRHIP, which integrated and collected data from National Basic Medical Insurance (NBMI), National Cancer Registry (NCR), and Cause-of-death Reporting System (CDRS) since 2012 with provincial coverage of 95% by 2020. The NBMI includes two databases, the Urban Employee Basic Medical Insurance database covering urban employees and the Urban Resident Basic Medical Insurance database covering unemployed urban and rural residents. It provides demographic characteristics of insured participants, records of inpatient and outpatient services, and cost information. The NCR collects, organizes, and analyzes tumor incidence, death, and survival data, which offers variables such as date of onset, age at diagnosis, disease diagnoses, tumor characteristics, etc. The CDRS collects data from national disease surveillance sites, National Health Commission, and some provinces and cities through an information management system. We obtained variables including the direct and underlying cause of death, International Classification of Disease code of the disease, date of death, etc. In sum, the advantages of IMRHIP include broad coverage, great interconnectivity between databases, accessibility to longitudinal and complete visit records, and rich variable information. More details can be checked elsewhere³¹.

The information about the Surveillance Cohort of All Cancers Species has been shared on the China Cohort Consortium (No. CCC2023050801). Patient information including demographics, disease diagnoses, tumor characteristics, cause of death, treatments, and expenses of inpatient and outpatient services were recorded and linked by encrypted ID numbers among databases. The patients were followed up until death or the end of the study, whichever came first. All records were deidentified to protect patient’s privacy and informed consent from participants was approved for exemption, approved by the Medical Ethics Committee of Inner Mongolia Autonomous Region Center for Disease Control and Prevention (NMCDCIRB2021001).

Study population

Patients diagnosed with BC between 1 January 2012, and 9 March 2021, in NBMI were identified based on diagnostic text and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) code of BC (C50). Natural language processing was applied to standardize the diagnostic text and codes, which were conducted independently by two researchers and reviewed by a third one. Patients without ID numbers (10, 0.03%) and male patients (630, 1.77%) were excluded. According to ethnicity, Han patients and Mongolian patients were analyzed and compared as two cohort groups.

Measurements

Age at diagnosis was categorized into seven groups: 18–30, 31–40, 41–50, 51–60, 61–70, 71–80, and ≥81^6,9,13 due to the nonlinear association between age and outcomes. The tumor stage was defined as ‘early’, ‘advanced’, and ‘unknown’ according to ‘5th ESO-ESMO international consensus guidelines for advanced breast cancer (ABC 5)’³². If the patient is operable, the tumor stage would be defined as ‘early’. If the patient is diagnosed with inoperable locally advanced breast cancer (LABC) or metastatic breast cancer (MBC), the stage would be ‘advanced’. Based on the comorbidities diagnosed before and after the diagnosis of BC, the Charlson Comorbidity Index (CCI) score was calculated and categorized as 0, 1, 2, and ≥3^33,34. For medical insurance, there were two types: employee basic medical insurance and resident basic medical insurance. Alcohol consumption and smoking rates were obtained from the 2018 Adult Chronic Disease and Nutrition Monitoring Survey in Inner Mongolia³¹. GDP level of residence was based on gross domestic product (GDP) per capita in 2020³⁵. Education level was based on the average years of schooling in 2020 obtained from the national population census³⁶. GDP level, education level, alcohol consumption rate, and smoking rate were stratified into two levels (high/low) by prefecture-level cities according to the median. Treatments for BC included surgery, chemotherapy, endocrine therapy, targeted therapy, and radiotherapy³⁷.

Statistical analysis

First, incidence and 5-year prevalence were calculated. We set a window of two years (2012 and 2013) to exclude prevalent cases when processing the data from the NBMI, which was one of the considerable data sources of new cases³⁸. Thus the incidence rates for each of the 7 years from 2014 to 2020 were calculated. The numerator of incidence was the number of new cases each year, and the numerator of 5-year prevalence was the number of BC patients alive during the past 5 years for each of the 5 years from 2017 to 2021³¹. The denominator for incidence and 5-year prevalence was the total number of residents each year in the NBMI. Subgroup analyses were conducted according to the GDP level of the residence, medical insurance, and education level.

Second, health utilization was measured by costs annually per capita and per-episode (US $1.00=6.47 RMB on 15 July 2020). Medical costs on overall services and specifically for BC were calculated, and inpatient and outpatient costs were differentiated. The number of inpatient and outpatient visits per capita overall and specifically for BC were also recorded.

Third, 5-year, 3-year, 2-year, and 1-year survival rates and mortality rates were calculated. The 5-year survival rate, for example, was defined as the proportion of patients who survive more than 5 years after diagnosis among patients diagnosed that year. For survival rates, subgroup analyses were conducted according to the GDP level of the residence, age at diagnosis, medical insurance, and education level. Both the all-cause mortality rate and BC-specific mortality rate were measured, and they were equal to the number of deaths divided by the total number of observations. A stratified Cox model was performed for all-cause mortality as the proportional hazard assumption was not satisfied by stage. The Fine and Gray competing risk model was performed for BC-specific mortality to estimate hazard ratios (HR) and 95% CI. Age and stage at diagnosis, GDP level of residence, alcohol consumption rate, smoking rate, CCI, medical insurance, education level, and all treatments were adjusted.

Mean±standard error (SD), median (interquartile range, IQR), and frequency (proportion) were presented for normal continuous variables, non-normal continuous variables, and categorical variables, respectively. Age-standardized rates (ASR) were determined using the WHO world standardized rates, 2000–2025³⁹. The average estimates in the subgroups were calculated by combining the estimates each year using a random effects meta-analysis based on the Clopper–Pearson method⁴⁰. The 95% CIs were estimated by the Poisson distribution⁴⁰. χ ² test, t test, and Kruskal–Wallis test were performed to compare the difference between variables of interest. All statistical analyses were performed using R version 4.1.2, and a two-sided P<0.05 was considered statistically significant. Data were analyzed and reported according to the Strengthening The Reporting of Observational Studies in Epidemiology (STROBE, Supplemental Digital Content 1, http://links.lww.com/JS9/C384) reporting guideline⁴¹ and the Strengthening The Reporting Of Cohort Studies in Surgery (STROCSS, Supplemental Digital Content 2, http://links.lww.com/JS9/C385) criteria⁴².

Results

Demographic characteristic

Within a total of 18.19 million participants in the cohort (eTable 1, Supplemental Digital Content 3, http://links.lww.com/JS9/C386), 35 508 BC patients were identified with a median follow-up of 3.16 years during 2012–2021, and 34 878 (98.23%) females were included in the study, contributing to 121 550.60 person-years. Four thousand three hundred fifteen (12.03%) females were Mongolian, who were more likely to be diagnosed 2 years younger compared with Han (50.20 vs. 52.67 years, P<0.001), had a higher proportion of resident basic medical insurance participants (30.52 vs. 14.93%, P<0.001), and more distributed in residences with lower GDP level (71.91 vs. 55.97%, P<0.001) and lower education level (67.72 vs. 43.89%, P<0.001) (Table 1).

Table 1.

Baseline characteristics of breast cancer patients during 2012–2021 in Inner Mongolia, grouped by ethnic groups^a.

	Overall	Han	Mongolian	P
Total: no. (%)	34 878 (98.23)	29 151 (81.27)	4 315 (12.03)	–
Age at diagnosis: x (s)	52.34±10.93	52.67±10.93	50.20±10.48	<0.001
Follow-up: median (IQR)	3.15 (1.54–5.09)	3.15 (1.54–5.08)	3.15 (1.46–4.98)	0.132
Stage
Early	13 852 (39.72)	11 574 (39.70)	1 723 (39.93)	0.149
Advanced	12 246 (35.11)	10 278 (35.26)	1 447 (33.53)
Unknown	8 780 (25.17)	72 99 (25.04)	1 145 (26.44)
Charlson comorbidity index scoreb
0	12 728 (40.81)	11 753 (40.32)	1 969 (45.63)	<0.001
1	1 610 (4.62)	13 11 (4.50)	218 (5.05)
2	2 491 (7.14)	19 66 (6.74)	406 (9.41)
≥3	16 544 (47.43)	14 121 (48.44)	1 722 (39.91)
GDP level of residencec
Low	20 349 (58.52)	16 315 (55.97)	3 103 (71.91)	<0.001
High	14 430 (41.48)	12 776 (43.83)	1 188 (27.53)
Medical insuranced
Employee	28 987 (83.11)	24 810 (85.11)	2 998 (69.48)	<0.001
Resident	5 891 (16.89)	4 351 (14.93)	1 317 (30.52)
Education levele
Low	16 217 (46.63)	12 770 (43.89)	2 905 (67.72)	<0.001
High	18 558 (53.37)	16 328 (56.11)	1 385 (32.28)

GDP, gross domestic product.

^aThere were missing data for GDP level of residence (99, 0.28%) and education level (103, 0.30%). For ethnic group, 10 patients (0.03%) were categorized into ‘others’.

^bCharlson comorbidity index score was calculated and categorized as 0, 1, 2, and ≥3.

^cGDP level of residence was stratified into two levels (high/low) by cities according to the median (66 377 RMB=$10 259.20).

^dThere were two types of medical insurance: employee basic medical insurance and resident basic medical insurance.

^eEducation level was stratified into two levels (high/low) by cities according to the average years of schooling in 2020.

Incidence and prevalence

The ASR of incidence for FBC during 2014–2020 was 32.68 (95% CI: 20.39–44.98) per 100 000. The ASR of 5-year prevalence was 167.48 (95% CI: 124.30–210.67) per 100 000. The age-specific incidence and prevalence showed unimodal distributions for both ethnic groups with the same age of peak (Fig. 1). The ASR of incidence in Mongolian patients was significantly higher than in Han [44.77 (95% CI: 17.77–71.77) vs. 34.28 (95% CI: 10.61–57.95) per 100 000, P<0.001], and the incidence in 2019 and 2020 were also significantly higher in Mongolian patients (P=0.049 and P<0.001, respectively) (eTable 2, Supplemental Digital Content 3, http://links.lww.com/JS9/C386). Additionally, Mongolian showed significantly higher 5-year prevalence rates in all age groups [173.00 (95% CI: 84.72–261.28) vs. 152.35 (95% CI: 86.38–218.32) per 100 000, P<0.001] (eTable 3, Supplemental Digital Content 3, http://links.lww.com/JS9/C386).

Figure 1.

Incidence rates and 5-year prevalence rates in Inner Mongolia among breast cancer patients, per 100 000, grouped by ethnic group and age group. All results are the rates of disease burden grouped by ethnic group and age group, and the error lines in each bar chart show 95% CI. (A) Incidence rates; (B) 5-year prevalence rates. Note: Incidence rate (per 100 000) was calculated as number of new cases of breast cancer each year among population at risk each year. 5-year prevalence rate (per 100 000) was calculated as the number of people alive who diagnosed during the past 5 years among the population each year.

Healthcare utilization

Only 66.04% of female patients recorded treatments for BC, with a lower proportion of Mongolian receiving treatments than Han (59.86 vs. 66.93%, P<0.001) (Table 2). The overall cost was $3333.29 (1388.73–7130.97) and the cost of BC was $2147.14 (660.51–5698.42) annually per capita.

Table 2.

Cost of breast cancer patients in Inner Mongolian during 2012–2021, grouped by ethnic groups, median (IQR).

Characteristics	Han	Mongolian	P
Patients with treatment of breast cancer (%)	66.93	59.86	<0.001
Annual per-capita cost (dollars)	3 404.00 (1 432.66–7 259.04)	3 023.61 (1 198.06–6 494.60)	<0.001
Annual per-capita cost on breast cancer (dollars)	2 227.35 (686.65–5 929.59)	1 948.43 (590.11–4 776.42)	<0.001
Inpatient
Annual per-capita cost (dollars)	2 797.87 (1 116.85–6 059.44)	2 561.00 (979.88–5 474.45)	0.162
Annual per-capita cost on breast cancer (dollars)	2 353.01 (778.00–6 000.94)	2 021.41 (672.78–4 736.29)	<0.001
Per-episode cost (dollars)	1 050.72 (581.64–1 932.21)	1 049.81 (576.59–1 891.22)	0.008
Per-episode cost on breast cancer (dollars)	1 057.80 (582.47–1 937.89)	1 057.66 (599.64–1 901.87)	<0.001
Visit	5.00 (2.00–10.00)	6.00 (2.00–10.00)	<0.001
Visit on breast cancer	4.00 (2.00–9.00)	4.00 (2.00–9.00)	0.796
Length of stay (d)	5.00 (3.00–11.00)	5.00 (3.00–10.00)	<0.001
Length of stay on breast cancer (d)	5.00 (3.00–11.00)	5.00 (3.00–9.00)	<0.001
Outpatient
Annual per-capita cost (dollars)	368.05 (146.50–991.89)	307.34 (138.24–841.78)	<0.001
Annual per-capita cost for breast cancer (dollars)	150.15 (40.82–537.74)	181.29 (51.68–482.05)	0.119
Per-episode cost (dollars)	14.84 (4.64 51.00)	12.36 (4.59–40.34)	<0.001
Per-episode cost for breast cancer (dollars)	84.40 (20.09–322.76)	106.57 (40.07–259.69)	<0.001
Visit	29.00 (8.00–67.00)	28.00 (8.00–65.75)	0.619
Visit for breast cancer	3.00 (1.00–7.00)	4.00 (2.00–9.00)	<0.001

The RMB-to-USD exchange rate is based on the 15 July 2020, exchange rate (1.00 USD=6.47 RMB).

The cost of BC annually per capita was significantly lower for Mongolian than Han in FBC [$1948.43 (590.11–4776.42) vs. $2227.35 (686.65–5929.59), P<0.001]. For inpatient cost, Mongolian patients recorded significantly lower annual per-capita cost for BC [$2021.41 (672.78–4736.29) vs. $2353.01 (778.00–6000.94), P<0.001]. For the outpatient cost, Mongolian recorded lower annual per-capita cost [$307.34 (138.24–841.78) vs. $368.05 (146.50–991.89), P<0.001] and per-episode cost [$12.36 (4.59–40.34) vs. $14.84 (4.64–51.00), P<0.001] but a higher per-episode cost for BC [$106.57 (40.07–259.69) vs. $84.40 (20.09–322.76), P<0.001] and more visits for BC [4.00 (2.00–9.00) vs. 3.00 (1.00–7.00) days, P<0.001] (Table 2).

Survival and prognosis

The all-cause mortality was 28.14 per 1000 person-years (95% CI: 27.21–29.10), while BC-specific mortality was 15.66 per 1000 person-years. Mongolian females showed higher all-cause mortality [30.92 (95% CI: 28.15–33.89) vs. 27.78 (95% CI: 26.77–28.83) per 1000, P=0.036] and BC-specific mortality [18.78 (95% CI: 16.64–21.13) vs. 15.22 (95% CI: 14.47–16.00) per 1000, P=0.002] than Han females (Table 3). No significant differences were observed in 5-year survival rates (Table 3 and eTable 4, Supplemental Digital Content 3, http://links.lww.com/JS9/C386) due to the small sample size (eTable 5, Supplemental Digital Content 3, http://links.lww.com/JS9/C386).

Table 3.

Prognosis and survival rates in Inner Mongolia during 2012–2021 among breast cancer patients, grouped by ethnic groups.

Characteristics	Han	Mongolian	P
No. of death
All-cause	2 822 (9.68)	456 (10.57)	0.071
Breast cancer-specific	1 546 (5.30)	277 (6.42)	0.003
Mortality, per 1 000 person-years
All-cause	27.78 (26.77–28.83)	30.92 (28.15–33.89)	0.036
Breast cancer-specific	15.22 (14.47–16.00)	18.78 (16.64–21.13)	0.002
5-year survival rate (2012–2015 combined), %	89.23 (87.10–91.37)	89.58 (87.22–91.95)	0.574
3-year survival rate (2012–2017 combined), %	92.66 (91.69–93.62)	93.37 (91.86–94.88)	0.800
2-year survival rate (2012–2018 combined), %	94.59 (93.78–95.39)	94.69 (93.5–95.88)	0.340
1-year survival rate (2012–2019 combined), %	96.68 (96.15–97.21)	97.03 (96.22–97.84)	0.315

Taking 5-year survival rate as an example, 5-year survival rate was defined as the proportion of patients alive more than 5 years after diagnosis among patients diagnosed that year.

After adjusting covariates, Mongolian were associated with increased all-cause mortality [HR, 1.21, (95% CI: 1.09–1.34); P<0.001] and BC-specific mortality [HR, 1.31, (95% CI: 1.14–1.49); P<0.001]. Older age at diagnosis and resident basic medical insurance purchasers were related to higher risks of mortality. Lower GDP level of residence was related to higher all-cause mortality [HR, 1.23, (95% CI: 1.08–1.41); P=0.002], and lower education level was associated with lower BC-specific mortality [HR, 0.83, (95% CI: 0.72–0.96); P=0.013] (Table 4).

Table 4.

Hazard ratios for risk of all-cause mortality and breast cancer-specific mortality in Inner Mongolia among breast cancer patients during 2012–2021.

	All-cause mortalitya				Breast cancer-specific mortalityb
Variable	Death	Person-year	HR (95% CI)a	P	Death	Person-year	HR (95% CI)	P
Age at diagnosis
18–30	36	84	1.00 [Reference]		25	53	1.00 [Reference]
31–40	227	587	1.09 (0.77–1.56)	0.617	154	392	1.06 (0.70–1.61)	0.790
41–50	878	2 084	1.32 (0.95–1.85)	0.102	533	1 165	1.15 (0.77–1.71)	0.500
51–60	1 075	2 349	1.82 (1.30–2.54)	<0.001	611	1 239	1.47 (0.98–2.19)	0.060
61–70	732	1 599	2.56 (1.83–3.59)	<0.001	361	682	1.76 (1.17–2.64)	0.006
71–80	367	751	4.96 (3.52–7.00)	<0.001	165	270	2.94 (1.93–4.49)	<0.001
>80	97	154	12.83 (8.74–18.84)	<0.001	50	71	7.87 (4.83–12.81)	<0.001
Ethnic
Han	2 819	6 305	1.00 [Reference]		1 546	3 140	1.00 [Reference]
Mongolian	455	962	1.21 (1.09–1.34)	<0.001	277	549	1.31 (1.14–1.49)	<0.001
Others	138	340	1.04 (0.88–1.24)	0.632	76	184	1.05 (0.83–1.32)	0.710
GDP level of residence
High	1 289	3 030	1.00 [Reference]		720	1 629	1.00 [Reference]
Low	2 123	4 577	1.23 (1.07–1.42)	0.004	1 179	2 244	1.22 (0.98–1.52)	0.076
Medical insurance
Employee	2 517	5 414	1.00 [Reference]		1 386	2 771	1.00 [Reference]
Resident	895	2 193	1.43 (1.32–1.55)	<0.001	513	1 102	1.39 (1.24–1.55)	<0.001
Education level
High	1 820	4 385	1.00 [Reference]		1 030	2 357	1.00 [Reference]
Low	1 592	3 222	1.00 (0.90–1.11)	0.961	869	1 516	0.83 (0.72–0.96)	0.013

GDP, gross domestic product.

^aStratified Cox model adjusted for age at diagnosis, ethnicity, GDP level of residence, medical insurance, education level, alcohol consumption rate level, smoking rate level, Charlson comorbidity index, surgery, chemotherapy, endocrine therapy, targeted therapy, radiotherapy, stage (strata) (n=34 775, excluded population=103).

^bFine and Gray competing risk model, adjusted for age at diagnosis, ethnicity, GDP level of residence, medical insurance, education level, alcohol consumption rate level, smoking rate level, Charlson comorbidity index, surgery, chemotherapy, endocrine therapy, targeted therapy, radiotherapy, stage (strata) (n=34 775, excluded population=103).

Discussion

We described the disease burden, medical utilization, and ethnic disparities in both aspects of BC based on IMRHIP data from 2012 to 2021. Mongolian showed higher incidence and prevalence with lower costs, and they were associated with increased all-cause and BC-specific mortality, which indicates health inequalities in the minority.

A moderate level of incidence of FBC was observed in Inner Mongolia compared to other countries and regions. The ASR of incidence of FBC (32.68 per 100 000) was close to the previous result in China²⁹ (39.1 per 100 000 in 2020) and other regions in Asia^3,43, and much lower than European and American countries^1,44, which was consistent with prior studies^4,5,29. There may be several explanations. First, the incidence might be under-reported due to the lower compliance of BC screening. It is reported that screening attendance is lower among Asian women regardless of nativity or acculturation^45–47, and the self-perception of low risk⁴⁵, use of alternative medicine⁴⁸, cultural custom⁴⁵ are possible reasons. Second, population-related genetic predispositions may cause disparities in incidence. With similar prevalence and genetically inherited susceptibility of BRCA1/2 mutations^49–51, BRCA1 was more common among western women while BRCA2 was more common among Asian women^49,52, with BRCA1 related to higher risk than the other^49,53. Also, Chinese women were reported to have a higher level of alpha-fetoprotein as a protective factor⁵⁴. Lastly, higher socioeconomic status, educational level, and the accompanying lifestyle (e.g. more alcohol consumption and late marriage) in western developed countries may contribute to a higher incidence rate^5,45,46,54.

Higher incidence and prevalence in Mongolian may be associated with the following factors: (1) Endocrine diseases such as obesity, and diabetes have been reported to increase the risk by increasing available estrogens⁵⁵. Higher proportions of obesity and overweight population, as well as diabetes patients, were observed in Mongolian than in Han^56,57. Furthermore, lifestyle (tobacco, alcohol, and diet) may increase the risk of obesity⁵⁸, and Mongolian tended to consume red meat, more alcohol, and tobacco^30,59. (2) Although no specific gene has been found, population genetic susceptibility may also play a part. Gene polymorphisms exist in BRCA1/2 between Mongolian and Han female patients with sporadic BC^60,61, which might provide a clue. (3) Allergy-related diseases such as allergic rhinitis were also found higher in Mongolian than in Han⁶². A review suggested a higher risk of BC among patients with a history of allergic rhinitis⁶³. In sum, Mongolian patients are faced with a higher disease burden of BC, appealing to more attention and inventions on these underserved minorities to eliminate ethnic disparities.

Another novel finding is the ethnic disparities in medical utilization. The cost of BC and the proportion of patients who received treatment were lower for Mongolian patients. Although few studies have described the ethnic disparities in cost in Asian areas, studies about African Americans showed that minorities were often disadvantaged in medical utilization¹⁰, which is consistent with our result. Potential reasons are as follows: for one thing, Mongolian showed a lower health literacy as fewer Mongolian females were willing to attend screening than Han females³⁰. Our results also showed that Mongolian had a lower education level, which might have influenced their awareness of the disease and treatment^12,18,64,65. For another, differences in medical insurance policies can lead to a gap in costs^18,65. Traditional Mongolian medicine accounts for a majority of treatment strategies among Mongolian patients, in parallel with Western medicine and traditional Chinese medicine³⁰, but it is normally uncovered by health insurance⁶⁶. Additionally, Mongolian had a higher proportion of participants covered by resident basic medical insurance, which generally offers a lower reimbursement ratio compared to other types of medical insurance in this study. These unfavorable situations may discourage Mongolian from seeking more medical care. Last but not least, our result displayed that Mongolian patients were more distributed in the residences of lower GDP levels, suggesting a disadvantaged economic position. These factors hindered healthcare-seeking behaviors and aggravated the inequalities of healthcare utilization. Although gaps remain in determining the cause of increased or decreased cost and higher or lower financial burden⁶⁵, the above discussion indicated Mongolian patients might be underserved with a higher burden.

Besides, the medical cost in this study was reported to be lower than that of western countries, which was consistent with prior studies^67–69. The cost of BC was $2147.14 annually per capita in Inner Mongolia, which was lower than that of the United States ($9567 for patients under 65, from 2008 to 2012)⁷⁰, Italy ($12 524, from 2007 to 2011)⁷¹, and Belgium ($2249, from 1997 to 2004)⁷². Taking the long span of the data into account, this probably resulted from the lower accessibility to newly expensive drugs and lower pricing in China. Take trastuzumab as an example. It was approved by the US Food and Drug Administration (FDA) in 1998 and the European Medicines Agency (EMA) in 2000⁷³. However, in China, trastuzumab was not included in the health insurance list until 2017⁷⁴. Observational studies^73,75 indicated that between 2000 and 2015 in patients with HER2þ metastatic BC, nearly 12% in America did not receive trastuzumab or other HER2-targeted agent in their treatment, while in China, 27.1% of those did not receive trastuzumab at any time after diagnosis and 49.2% did not receive trastuzumab in the first-line setting⁷⁶. As for the pricing, according to the 2022 Average Sale Price (ASP) and Chinese national drug prices, the cost of trastuzumab per mg in America ranged from $6.91–$10.37 but ranged from $1.55–$2.33 in China⁷⁷. In sum, the lower drug accessibility and pricing represented by trastuzumab⁷⁸ is an important factor in China’s lower medical expenses^68,79.

Furthermore, we first demonstrated that Mongolian patients had a worse prognosis than Han patients with significantly higher all-cause mortality and breast-specific mortality. One of the main reasons contributing to the worse outcome is the delay in diagnosis and treatment^9,47,48,64. Mongolian had a lower screening participation rate³⁰, which is not conducive to timely intervention of the disease. Second, considering important prognosis indicators of BC, Mongolian patients manifested higher TNM stage, larger tumor size, lower estrogen receptor (ER), and progesterone receptor (PR) positivity, and a higher rate of axillary nodal metastasis⁸⁰. Third, Mongolian were reported to have a 6–8 years younger average death age than Han^81,82, and have a shorter life expectancy since 1949^83,84. This could partly explain the higher mortality in Mongolian. Fourth, low economic status^9,14,85 and medical utilization¹² implied difficulties in accessing medical resources, leading to worse survival. Our results showed residences with lower economic levels where Mongolian were more distributed were associated with higher all-cause mortality, which was consistent with prior studies. Also, many drugs were not covered by insurance in China, causing a high burden and limiting access to first-line treatment for disadvantaged people⁵⁰. Last but not least, the aforementioned disadvantaged lifestyle accompanied by a higher prevalence of comorbidities³⁰ could generate a higher risk of cancer death^18,86.

In conclusion, our result reflected a potential unmet medical demand with a worse prognosis for Mongolian patients³¹, calling for stakeholders to take action to reduce the inequalities.

To our knowledge, this is the first study to reveal the ethnic disparities in the disease burden of BC based on 34 878 patients from 18.19 million general population in China. Several limitations should be taken into account when considering our findings. First, case ascertainment was restricted by the unavailability of laboratory data and imaging information obtained from medical insurance, but previous studies using NBMI to identify cancer cases have verified sensitivities and Positive predictive value (PPVs) above 90%^87,88. Second, larger sample sizes were required since the small sample size of patients with more than 5 years of follow-up resulted in the low powers of survival analyses. Moreover, the above disparities were only observed in Inner Mongolia, which means that external verification in other populations is needed. Nonetheless, it is important to note that the population of this study is currently the largest Mongolian patient population. Finally, variables of interest could be more comprehensive. BMI, tumor grade, and subtype were not available in our study, which may influence the further interpretation. However, the disparities in disease burden and medical utilization still hold substantial importance⁸⁹.

Conclusion

We revealed the ethnic disparities in the disease burden of BC based on large-scale population-based data in Inner Mongolia. Higher incidence and prevalence with worse prognosis and lower healthcare utilization were found in Mongolian than in Han. Mongolian BC patients with a higher level of disease burden might be faced with unmet medical demand, requiring more efforts on these minorities. To improve the health literacy of ethnic minorities, reform the health insurance system, and further implement the screening program among disadvantaged populations are feasible directions. Still, further research is needed to explore the concrete mechanisms of the disparities as well as eliminate health disproportion.

Ethical approval and consent to participate

Approved by the Medical Ethics Committee of the Inner Mongolia Center for Disease Control and Prevention (NMCDCIRB2021001), informed consent from participants was approved for exemption.

Consent

Approved by the Medical Ethics Committee of the Inner Mongolia Center for Disease Control and Prevention (NMCDCIRB2021001), informed consent from participants was approved for exemption.

Sources of funding

This work was supported by the Natural Science Foundation of China (No. 82173616 and No. 72342015).

Author contribution

J.C., L.Q., M.Q., Y.Z., Y.Y., Y.X., and S.W.: concept and design; J.C., L.Q., Y.X., Y.Z., H.Z., and S.W.: drafting the manuscript; J.C., L.Q., Y.Z., W.K., H.Z., Y.K., Y.J., Y.R., L.X., G.H., Y.Y., J.R., X.Y., S.D., X.Y., Y.S., Y.Y., Q.W., J.H., Y.W., G.L., M.W., X.Z., and S.W.: statistical analysis; Y.X. and S.W.: administrative, technical, or material support; Y.X. and S.W.: supervision. All authors contributed in acquisition, analysis, or interpretation of data and critical revision of manuscript for important intellectual content.

Conflicts of interest disclosure

Dr Shengfeng Wang reports grants from Natural Science Foundation of China (No. 82173616 and No. 72342015) during the conduct of the study. Dr. Shengfeng Wang confirmed that the funders did not play a role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication. No potential conflicts of interest were disclosed for the remaining authors.

Research registration unique identifying number (UIN)

ChiCTR1800018217.

Guarantor

Shengfeng Wang, PhD, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing, 100191, China (shengfeng1984@126.com, 86-010-82801525).

Availability of data and materials

Yunfeng Xi and Shengfeng Wang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. The datasets used and analyzed during the study are available from Yunfeng Xi on reasonable request.

Provenance and peer review

Not applicable.

Assistance with the study

Not applicable.

Presentation

Not applicable.

Supplementary Material

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