The characteristic large‐scale annual analysis by gender and age in heart failure patients: cohort for 10 years in Korea

Abstract

Aims

The prevalence and incidence rate of heart failure (HF) continues to increase along with the aging of the population and the increase of ischaemic heart disease. The morbidity and mortality of HF are also on the rise in the industrialized countries; it can be a great public health problem. A detailed and accurate analysis of the demographical incidence and prevalence of HF is an important first step in predicting the occurrence of the disease in the future and proper preparing for prevention. Here, we aimed to analyse the annual prevalence and incidence of HF by gender and age using long‐term national health insurance service data in the Republic of Korea.

Methods and results

A total of 47 243 patients newly diagnosed with HF between 2006 and 2015 among nationally representative random subjects of 1 000 000 were included. The data of age and gender were analysed by year, and the total population information of the Ministry of Land, Infrastructure, and Transport of Korea was referred to compare the data of HF patients with the total population (2008–15). Over the decade from 2006 to 2015, the prevalence of HF patients showed tendency of increase (P < 0.001). The overall incidence rate was also gradually increasing (P < 0.001), but in women, it tended to decrease gradually. Women significantly accounted higher than the male group in incidence of HF over the period (54.6% vs. 45.4%, P < 0.001). The mean age at the time of diagnosis gradually increased (P = 0.002 for total, P = 0.001 for each gender). Total incidence was highest in 70s (27.22%), but males were the most in their 60s and females were in their 70s. Analysis of annual trend by age and gender distribution of HF incidence in men presented highest in the 50s–70s with a similar pattern annually, and the incidence is increasing more recently. Different from that of men, in the case of women, the incidence gradually increased with age in a similar annual pattern, peaking in their 70s and gradually decreasing in recent years.

Conclusions

The prevalence and incidence of HF are gradually increasing. It increased rapidly in their 50s and older. It showed an increased incidence of HF especially in men between their 50s and 70s, and more observation and caution for the management of the risk factors may be needed to prevent HF in the male group.

Introduction

The prevalence and incidence rate of heart failure (HF) continues to increase along with the aging of the population and the increase of ischaemic heart disease.^1–4 The morbidity and mortality of HF are also on the rise in the industrialized countries,^5,6 which is emerging as a public health problem, and as a result, total costs of HF of care for people with HF are increasing and are expected to exceed $70 billion by 2030 as the population growth and aging in the United States.^2,7,8

As we have witnessed so far, the techniques and materials involved in diagnosing and treating heart disease have developed rapidly but have not been able to fully cure or prevent HF. This will eventually lead to a large increase in the HF patients group with the aging population. Therefore, a detailed and accurate analysis of the demographical incidence and prevalence of HF is an important first step in predicting the occurrence of the disease in the future and properly preparing for prevention. Here, we aimed to analyse the annual prevalence and incidence of HF by gender and age using long-term national health insurance service data in the Republic of Korea.

Methods

Statement of ethics

This study adhered to the tenets of the Declaration of Helsinki, and the National Health Insurance Service-National Sample Cohort (NHIS-NSC) 1.0 database 2002–15 project was approved by the Institutional Review Board of the Korean National Health Insurance Service (KNHIS). This study design was reviewed and approved by the Institutional Review Board of the National Health Insurance Service Ilsan Hospital, Gyeonggi-do, Korea. Written informed consent was waived.

Data sources

All nationals are obligated to enrol in the KNHIS in Republic of Korea. A total of 97% and 3% of the Korean population are covered by the Medical Assistance Program and the Medical Care (Medical Aid) for low-income groups or Patriots and Veterans Affairs Scheme, respectively. The NHI programme is a wage-based, contributory insurance programme covering ~97% of the population, while the Medical Aid programme is a government-subsidized public assistance programme for poor and medically indigent individuals.^9,10

So nearly all the data in the health system are centralized in large databases. In Korea, patients with KNHIS pay approximately 30% of their total medical expenses when using medical facilities, and medical providers are required to submit claims for the remaining 70% of the medical expenses. Claims are accompanied by data regarding diagnostic codes, procedures, prescription drugs, personal information about the patient, information about the hospital, the direct medical costs of both inpatient and outpatient care, and dental services. No health care records of the patients were duplicated or omitted because all Korean residents have received a unique identification number at birth. This number is used by the Korean government for purposes related to the health care system. Further, the KNHIS uses the Korean Classification of Diseases (KCD), which is a similar system to the International Classification of Diseases (ICD).¹¹

Study sample and definition of heart failure

This study used an NHIS-NSC 1.0 database 2002–15, which was released by the KNHIS in 2018. The data comprise 1 000 000 nationally representative random subjects, amounting to approximately 2.1% of the entire population in the KNHIS in 2006. The data were produced by the KNHIS using a systematic sampling method to generate a representative sample from all 48 222 537 Korean residents in 2006. This database includes all medical claims filed from January 2002 to December 2015.

This study was a non-interventional, retrospective registry study using data already available in electronic patient records from KNHIS for application of medical insurance.

The data were the sample cohort for diagnosis of ‘heart failure’ and were from all over the country from 2006 to 2015 with an approximate population of 47 243 inhabitants.

Patient population was based on those who have an ICD-10 diagnosis for HF (I50, I09.9, I11, I13, and I13.2) in their records for the first time between 2006 and 2015 (n = 47 243), and the epidemic and clinical analysis of HF prevalence according to gender and age was performed.

The HF group included all patients who received inpatient and outpatient care between 2006 and 2015 for an initial diagnosis of HF [KCD codes I50, I099, I110, I130, and I132, corresponding to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes I50, I09.9, I11, I13, and I13.2].

The HF patients were analysed according to age and gender, and the data were analysed by year. The total population information of the Ministry of Land, Infrastructure, and Transport of Korea was referred to compare with the data of HF patients (2008–15).

Statistical analysis

The prevalence and incidence of HF by year, age, and gender were analysed from various angles. Continuous variables were presented as a mean ± standard deviation, and categorical variables as a percentage of the group total. Student's t-test and the χ² test were used to compare continuous and categorical variables, respectively. To conduct the P for trend test, the number of cases of the disease in each category is calculated and the test statistic is calculated as the square of the correlation coefficient between the category numbers and the corresponding ranks of the categories. A significance level of 0.05 was selected. The statistical package SAS System for Windows, Version 9.4 (SAS Inc, Cary, NC, USA), was used to perform the analyses in this study.

Results

Prevalence

Over the decade from 2006 to 2015, the prevalence of HF patients showed tendency of increase (P for trend < 0.001, total, male, and female group) (Table 1 and Figure 1A). It was initially higher in women, but the prevalence of men and women became similar around 2015.

Table 1 Annual prevalence of heart failure for 10 years (2006–15)

Year	Total	Male	Female	P-value
N	% in 1 000 000	N	% in HF	N	% in HF
2006	4522	0.5	1798	39.8	2724	60.2	<0.001
2007	6655	0.77	2646	39.8	4009	60.2	<0.001
2008	7408	0.7	2956	39.9	4452	60.1	<0.001
2009	7861	0.8	3165	40.3	4696	59.7	<0.001
2010	8794	0.9	3580	40.7	5214	59.3	<0.001
2011	10 441	1.0	4498	43.1	5943	56.9	<0.001
2012	11 576	1.2	5143	44.4	6433	55.6	<0.001
2013	12 720	1.3	5840	45.9	6880	54.1	<0.001
2014	14 188	1.4	6700	47.2	7488	52.8	<0.001
2015	15 582	1.6	7561	48.5	8021	51.5	<0.001

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Incidence

The incidence of HF patients (n = 47 243) also showed tendency of increase in the total and male groups (P for trend < 0.001) but decrease in the female group from 2006 to 2015 (P for trend < 0.001) (Table 2 and Figure 1B). It was higher in women initially (P < 0.001) and became almost the same around 2013 and 2014 in both groups, and finally, it showed significant reverse in 2015 (P < 0.001). For reference, both male and female population of all age and over 40s in Korea are similarly increasing in 2008–15 (Figure 1C,D).

Table 2 Annual incidence of heart failure for 10 years (2006–15)

Year	Total	Male	Female	P-value
N	% in 47 243	N	% in HF	N	% in HF
2006	4522	9.5	1798	39.8	2724	60.2	<0.001
2007	4810	10.2	1949	40.5	2861	59.5	<0.001
2008	4330	9.2	1763	40.7	2567	59.3	<0.001
2009	3994	8.4	1661	41.6	2333	58.4	<0.001
2010	4211	8.9	1803	42.8	2408	57.2	<0.001
2011	5276	11.2	2460	46.6	2816	53.4	<0.001
2012	4854	10.3	2338	48.2	2516	51.8	0.003
2013	4979	10.5	2454	49.3	2525	50.7	0.154
2014	5126	10.9	2570	50.1	2556	49.9	0.782
2015	5141	10.9	2674	52.0	2467	48.0	<0.001
Total	47 243	100.0	21 470	45.5	25 773	54.5	<0.001

Gender distribution and mean age

HF incidence of women accounted for 54.6%, higher than that of male at 45.4% significantly (P < 0.001) (Table 3). The mean age at the incidence of HF increased significantly with age for 10 years (P for trend = 0.002 for total, P = 0.001 for each gender) (Table 4 and Figure 2).

Table 3 Gender distribution of incidence of heart failure for 10 years

	Incidence	Percentage	P-value
Male	21 470	45.4	<0.001
Female	25 773	54.6

Table 4 Annual pattern of mean age at the incidence of heart failure for 10 years

Year	Total	Male	Female
2006	63.1	60.1	65.2
2007	63.9	61.6	66.4
2008	64.7	61.5	66.9
2009	64.7	61.7	66.8
2010	64.1	61.6	65.9
2011	64.9	62.2	67.3
2012	64.5	62.6	66.3
2013	64.5	62.3	66.6
2014	64.1	62.0	66.3
2015	64.8	62.3	67.5
Mean	64.3	61.8	66.5

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Age-specific incidence

By age group, the incidence stayed low among patients under the age of 40 and has since increased rapidly with age in both men and women (P for trend < 0.001) (Table 5 and Figure 3-1). Patients in their 70s accounted for the largest portion (27.2%); however, the largest group in men was in their 60s (25.0%), whereas that in women was in their 70s (30.3%) (Table 5 and Figure 3-2). According to the gender ratio in adults, the ratio of both sides was similar in all age groups but the incidence rate of women increased more rapidly than men after the age of 70 (Table 5 and Figure 3-3A). And this pattern was similar to the age-specific gender distribution of the entire population in Korea (Figure 3-3B).

Table 5 Age-specific incidence of heart failure

Age group	Total	Male	Female
N	Percentage	N	% in age group	% in male	N	% in age group	% in female
0–9	206	0.4	112	54.4	0.5	94	45.6	0.4
10–19	252	0.5	137	54.4	0.6	115	45.6	0.4
20–29	629	1.3	311	49.4	1.5	318	50.6	1.2
30–39	1688	3.5	926	54.9	4.3	762	45.1	3.0
40–49	4624	9.7	2626	56.8	12.2	1998	43.2	7.8
50–59	8844	18.7	4729	53.5	22.0	4115	46.5	16.0
60–69	11 084	23.4	5365	48.4	25.0	5719	51.6	22.2
70–79	12 859	27.2	5062	39.4	23.6	7797	60.6	30.3
≥80	7057	14.9	2202	31.2	10.4	4855	68.8	18.7
Total	47 243	100	21 470	45.4	100	25 773	54.6	100

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Age- and gender-specific annual incidence

Annual incidence of HF by age and gender showed each specific trends (Table 6). Analysis of trend by year revealed a noticeable gradual increase in those over the age of 40 in men, but in contrast, women showed a similar or decreased trend in most age groups with a gradual increase only in the 80s (Figure 4).

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Table 6 Age- and gender-specific annual incidence of heart failure (2006–15)

Male
Year	Age
0–9	10–19	20–29	30–39	40–49	50–59	60–69	70–79	80+	Total
2006	20	8	40	75	279	364	480	390	142	1798
2007	7	9	33	83	264	405	521	450	177	1949
2008	10	6	25	97	205	383	452	417	168	1763
2009	7	16	31	75	193	365	406	392	176	1661
2010	9	16	30	71	236	393	460	395	193	1803
2011	9	14	29	105	290	582	600	556	275	2460
2012	10	19	21	77	269	504	600	600	238	2338
2013	9	12	27	105	284	572	575	631	239	2454
2014	10	15	29	126	287	618	622	590	273	2570
2015	21	22	46	112	317	541	649	641	325	2674
Sum	112	137	311	926	2624	4727	5365	5062	2206	21 470
% age	54.4	54.4	49.4	54.9	56.8	53.5	48.4	39.4	31.2	45.4
% male	0.5	0.6	1.4	4.3	12.2	22.0	25.0	23.6	10.3	100.0
Female
Year	Age
0–9	10–19	20–29	30–39	40–49	50–59	60–69	70–79	80+	Total
2006	12	10	54	85	226	406	689	849	393	2724
2007	8	10	37	73	230	427	685	923	468	2861
2008	10	5	32	74	198	375	573	838	462	2567
2009	9	10	28	59	172	357	531	753	414	2333
2010	11	18	29	88	178	415	525	676	468	2408
2011	2	12	24	64	206	471	643	847	547	2816
2012	13	12	31	86	190	398	545	760	481	2516
2013	7	10	29	66	207	472	482	738	514	2525
2014	13	15	35	80	207	433	521	711	541	2556
2015	9	13	19	87	184	361	525	702	567	2467
Sum	94	115	318	762	1998	4115	5719	7797	4855	25 773
% age	45.6	45.6	50.6	45.1	43.2	46.5	51.6	60.6	68.8	54.6
% female	0.4	0.4	1.2	3.0	7.8	16.0	22.2	30.3	18.8	100.0
Total	206	252	629	1688	4622	8842	11 084	12 859	7061	47 243

Analysis of trend by age distribution of HF incidence in men presented highest in the 50s–70s with a similar pattern annually, and the incidence is increasing more recently. Different from that of men, in the case of women, the incidence gradually increased with age in a similar annual pattern, peaking in their 70s and gradually decreasing in recent years (Figure 5A). For reference, the same analysis of trend by age distribution in total population in Korea over the past 8 years showed similar pattern for both men and women (Figure 5B).

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Discussion

This study is the first largest cohort study to show the characteristic annual incidence of HF by gender and age with simple graphic representation in both genders using the long-term data of sample cohort of KNHIS. The increase in HF in Korea and foreign countries also has been reported in previous studies.^12–15 Youn et al. presented several temporal trends of hospitalized patients with HF in Korea including mean age, aetiologies, comorbidities, and clinical outcomes.⁴ Lee et al. demonstrated increasing prevalence and distribution of comorbidities of HF in Korea. The prevalence of HF in females was also higher than in males among subjects aged 60 or older in that study.¹⁴ The number of patients with HF showed an average annual increase rate of 4.5% from 2009 to 2013. In those aged 80 years or above, the reported annual increase rate is 9%, which is about twice that of the adult population.¹⁶ Furthermore, with the rapid increasing trend of aging population, an increase in the prevalence of HF is also expected. Actually, the aging population rate in Korea is on a very steep rise, and the percentage of the population aged 60 years and above is predicted to increase from 13.7% in 2015 to 28.6% by 2050.¹⁷ In addition, HF is one of the leading causes of death in Korea.¹⁸

Analysing the difference in distribution by group and pattern over time and predicting outcomes in the event of a disease are very important. Because it is essential to identify and prepare for the vulnerable groups and to cope with the long-term path of the disease in the future, analyzing the difference in distribution by group and pattern over time and predicting outcomes in the event of a disease are very important. Especially, large numbers of patients with poor prognosis, such as HF, can be extended to social problems under the burden of medical costs and various systems.²

In this study, we showed that the prevalence of HF is gradually increasing over the decade from 2006 to 2015 and that a steeper increase in men was revealed. Interestingly, the incidence of heart failure also tended to increase in the overall and male groups, but decreased in the female group. Given that there is no gender difference in the age distribution of the total population, the gradual decline in the incidence of HF in women is unusual. Especially considering the population aging and the increasing trend of the total female population, it is difficult to explain the decrease in the incidence of HF in women.

However, it has been also mentioned in a previous study using the National Health Information Database (NHID) data from 2002 to 2018,¹⁹ and there have been some reports of a decrease in the incidence of HF overseas,^20–22 so it is necessary to pay attention to changes in Korea in the future. A large-scaled Norwegian population study of HF reported decreased incidence in 2016 compared with 2013 (age-standardized incidence rates were 4.43/1000 in 2013 and 4.23/1000 in 2016) with smaller incidence in female than male under the age of 80.²⁰ Ten-year age- and sex-specific temporal trends in incidence of HF in Västra Götaland, Sweden, revealed a decrease in overall incidence, but incidence of HF in the oldest age groups remains high.²¹ A population-based study of 4 million individuals in the United Kingdom showed decreased incidence of HF similarly for men and women, by 7% from 2002 to 2014.²² In the very elderly (>85 years), the standardized incidence appears to have increased, which is a conclusion similar to our study.

A review article on epidemiology of HF²³ introduced a data in Denmark from 1995 to 2012, based on a national sample of hospitalized patients, which showed similar trends of decline.²⁴ The decline was greater in women (43%) than in men (29%) in a data of the United States like our study.²⁵

Another unique pattern of our analysis was a noticeable difference of peak age between male and female. In women, the incidence is highest in those aged 70 or older, but in men, the highest incidence is seen between the ages of 50 and 70 in the graph. The similar pattern was observed in Australian epidemiologic data. Prevalence of HF in Australia between 2013 and 2018 showed more men in the age range from 55 to 84 years than women, and the total number of women with HF continued to increase with age, peaking only in the highest age bracket (≥85 years).²⁶

However, these studies did not provide a detailed analysis of HF incidence by sex, age, and year at a time. In our study, the incidence of HF by gender, age, and year is presented intuitively at a glance using simple graphs, and it can help to understand the changing pattern over time and the difference between both genders. Only with simultaneous analysis by year, gender, and age can make us know the vulnerable target group and analyse the cause, so it is the newest and most important point of our study to display these trends of age and sex by period so that we can see it at a glance.

From the graph of the rapidly increasing incidence of HF from 50s in women unlike men, we can only guess the possible correlation with hormonal changes after menopause and increased cardiovascular disease. It is difficult to explain exactly why the incidence of HF in women is gradually declining as opposed to men, even though both the total and the elderly population are increasing in both men and women. Of course, besides the fact that early detection and control of hypertension, diabetes, hyperlipidaemia, and cardiovascular diseases are becoming increasingly possible due to regular health check-up systems and easy accessibility to medical services, genetic and hormonal differences can also be considered, as well as differences of drug compliance, alcohol, and tobacco habits between both genders. However, there are no accurate data, and it seems necessary to analyse various epidemiological and clinical characteristics in both groups in the future. And this phenomenon can be different in each country due to differences in population distribution and trends, ethnicity, epidemiology, prevalence of other diseases affecting HF, smoking, drinking habits, sociocultural characteristics, and accessibility to medical services.

Therefore, further long-term data are warranted to elucidate the characteristic annual incidence of HF according to age, gender, and other epidemiologic factors in each country.

Study limitations

The most important limitation is that the diagnosis of HF was defined on the basis of KCD codes, which may be inaccurate compared with the diagnoses obtained from a medical chart, and underreporting or misclassification can be also possible. In South Korea, accurate diagnostic codes on medical records are essential for medical insurance claims; however, omission, underreporting, or misclassification of medical diagnosis can be possible, and it should be recognized in analysing the data. In addition, one of the major limitations is that there is no analysis of mortality rate or aetiology and comorbidities of HF. Moreover, if there was an analysis of the temporal trend of mortality rate, aetiology, and comorbidities, it would have been of great help in identifying the outcome or cause of HF by period.

Another limitation is that the individual laboratory results and the drug history of the patients could not be included in the data. So many indexes including ejection fraction in echocardiography or any laboratory data were not obtained, and more precise assessment could not be performed.

Conclusions

In conclusion, the prevalence and incidence of HF are gradually increasing. It increased rapidly in their 50s and older. It showed an increasing incidence of HF especially in men, and more observation and caution for the management of the risk factors may be needed to prevent HF in the male group.

Acknowledgements

We have special thanks to Haeyong Pak, MPH, for the assistance of statistical approach. This study used National Health Insurance Service-National Sample Cohort (NHIS-NSC) data (NHIS-2021-2-007), made by the NHIS.

Conflict of interest

The authors declare no conflict of interest.

Funding

This work was supported by the National Health Insurance Service Ilsan Hospital Grant (NHIMC 2018-07-037).

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