Skip to main content

Advertisement

  • Research
  • Open Access
  • Open Peer Review

Examining trends in cardiovascular disease mortality across Europe: how does the introduction of a new European Standard Population affect the description of the relative burden of cardiovascular disease?

Population Health Metrics201917:6

https://doi.org/10.1186/s12963-019-0187-7

  • Received: 28 March 2018
  • Accepted: 8 May 2019
  • Published:
Open Peer Review reports

Abstract

Background

Some mortality statistics are misleading when comparing between countries due to varying age distributions in their populations. In order to adjust for these differences, age-standardised mortality rates (ASMRs) are often produced. ASMRs allow for comparisons between countries as if both had the same standardised population. We examined whether the updating of the standard population for Europe affected the description of the relative burden between countries in cardiovascular disease (CVD) mortality across the continent.

Methods

Mortality and population data were obtained from the World Health Organization (WHO) mortality database. ASMRs were calculated using the direct method and two European Standard Populations (ESP): 1976 ESP and 2013 ESP. We investigated differences in ASMR76 (calculated using 1976 ESP) and ASMR13 (calculated using 2013 ESP), changes in rankings of countries between the two ASMRs and differences in trends in CVD mortality in each country for the two ASMRs.

Results

CVD rates calculated using the 1976 ESP were on average half the size of rates calculated using the 2013 ESP. Spearman’s rank coefficient showed that the ranks of countries by ASMRs calculated using the two ESPs were different for both sexes. Joinpoint analyses showed no difference in the direction of trend between ASMR76 and ASMR13 although differences in the magnitude of the change were found in some countries.

Conclusion

ASMRs are commonly used in studying the epidemiology of a disease. It is crucial that policy makers understand the effect of changes in standard populations on these rates. This includes how populations with different age distributions compare to each other. Similar effects may be seen in other diseases that are also more prevalent in older age groups, such as cancer and dementia.

Keywords

  • Cardiovascular disease
  • Epidemiology
  • European Standard Population
  • Mortality

Introduction

Despite large decreases in cardiovascular disease (CVD) mortality within Europe over the last four decades [13], CVD remains the leading cause of mortality in the continent [4]. More than 4 million deaths are attributed to CVD in Europe annually, accounting for 46% of all deaths, with the number of CVD deaths higher in women (2.2 million) than men (1.8 million) [2].

Despite decreasing trends in mortality from CVD found in most European countries, there is great variation in the extent of this decline between countries. For example, 10-year decreases in CVD age-standardised mortality rates (ASMRs) ranged from 1.3% and 6.3% for men and women respectively in Kyrgyzstan to 56.5% and 65.6% respectively in Kazakhstan [2]. It is no surprise that large inequalities remain across Europe in the relative and absolute burden of CVD [5, 6] with CVD-related mortality generally higher in Central and Eastern Europe [1, 2, 5, 7].

Comparing between countries and sexes can be problematic due to differences in population structure. Since CVD is more common in older age groups, countries or sexes with a greater proportion of older individuals may be expected to suffer a higher proportion of CVD deaths [8]. ASMRs are used to account for some differences in age and population structure and have been used to compare between European countries in the burden of many CVD outcomes, including mortality. ASMRs are calculated by applying age-specific mortality rates for different countries to the same standard population. Rates can differ depending on which standard population is used.

The European Standard Population (ESP) is recommended for the calculation of ASMRs in Europe. However, Eurostat, the statistical office of the European Union, updated the 1976 ESP in 2013 to reflect better the current European population structure that had changed from 1976 due to an increase in life expectancy [9]. The 2013 ESP has greater weighting on older age groups and has an upper limit disaggregated to include age groups of 90 years and older, compared to the 1976 ESP upper age limit of 85 and over [10].

The introduction of the 2013 ESP has been shown to lead to ASMRs in CVD about twice as large as those calculated using the 1976 ESP [2]. This increase may not be the same for all countries and sexes as there is a greater emphasis on older age groups in the 2013 ESP. Those with a greater proportion of older age groups liable to show relatively larger increases. This may change how we view inequalities in CVD mortality within Europe. We know that the change in standard population will change the ASMRs calculated; if this change is uniform across all countries, then the description and presentation of inequalities across Europe are unaffected. However, if this change in standard population leads to heterogeneous changes in ASMRs between countries, this may change the narrative around inequalities in CVD mortality across the continent.

In this study, we aimed to examine how updating the ESP changed the CVD ASMRs calculated for European countries and whether the extent of any relative difference varied by country. We calculated CVD ASMRs for each country and both sexes using both European Standard Populations, ESP13 and ESP76. We examined changes to ASMRs due to the change in ESP and examined changes in the trends in CVD mortality expressed through ASMRs calculated using the 1976 and 2013 ESPs. Joinpoint analysis was used to analyse trends in CVD ASMRs for both ESPs in each country over time and by sex.

Methods

Data on cause-specific numbers of deaths and population numbers, by sex and in 5-year age groups (up to 85 and over) for European countries were extracted from the WHO global mortality database. The WHO database collates data reported by national authorities based on their civil registration systems and contains data for 51 of 53 European countries. Data for each country were extracted and analysed for the years of 1965 to 2014, where available. Countries were excluded if both population and mortality data for that year were not available (Andorra and Monaco).

Cardiovascular disease as a cause of death was defined according to the following International Classification of Disease codes: ICD-10 (International Classification of Diseases, tenth revision) codes I00-I99; ICD-9 codes 390-459, ICD-8 codes A081-A088 and ICD-7 codes A080-A086. Age and sex-specific mortality rates were calculated and the direct method was used to calculate age-standardised mortality rates for both the ESP76 (ASMR76) and ESP13 (ASMR13). These rates are presented for the ‘most recent year’, which are related to the most recent data for which both mortality and population data were available.

Countries were ranked by CVD ASMRs with differences in rankings between ASMR76 and ASMR13 examined through Spearman’s rank test. All statistical analyses were performed using STATA (version 14.0).

Trends in ASMRs for both ESPs were calculated. Joinpoint Trend Analysis Software (version 4.3.1.0) was used to perform joinpoint regressions to identify periods with statistically distinct log-linear trends in death rates from CVD over time within each age group, by sex and country. We used joinpoint to calculate the average annual percentage change (AAPC) over the entire period of available data and the annual percentage change (APC) for individual trend segments. Segments are identified by inflexion points (‘joinpoints’) at which there is a significant change in trends, using a series of permutation tests, with Bonferroni adjustment for multiple comparisons. The changes in trend may include any change in intensity, but could include a change in direction. We used a two-sided significance level set at P < 0.05 for all tests. Significant joinponts for each country by sex (maximum of 5) were determined using a log-linear model, and the annual percentage change (APC) within each segment calculated. The use of a log-linear model enables the analysis of constant percentage (rather than absolute) change in prevalence over time. Plateauing of the most recent trend for a country was defined as the trend in the most recent segments showing either a less steep decline than the preceding segment, no significant difference to zero, or an increase. Joinpoint segments were compared between ASMRs from both ESPs to examine differences in trends.

Results

On average, 35 years of data were available for all countries. Complete data for all 49 years were only available for two countries, Malta and Austria, with 30 years or more of data available for 33 (64.7%) countries. Less than 10 years of data were available for three countries: Cyprus (9 years), San Marino (7 years) and Turkey (4 years). The number of total CVD deaths was greater in women than men in 42 out of 51 countries for the most recent available year. Furthermore, a higher percentage of total deaths that were from CVD were found in women in 48 out of 51 countries (Table 1).
Table 1

Overview of data availability and number of deaths, population by country and sex, most recent available year

Country

Data range (years)

Total years of data available (% of total years)*

Males

Females

Total population

Total no. CVD deaths (% of all deaths in that country that are from CVD)**

Total population

Total no. CVD deaths (% of all deaths in that country that are from CVD)**

Albania

1987–2004

37 (75)

1,558,376

4679 (47)

1,568,887

4212 (54)

Armenia

1981–2012

25 (51)

1,450,560

6494 (46)

1,573,567

6836 (51)

Austria

1965–2014

49 (100)

4,176,550

13,964 (37)

4,367,382

19,172 (47)

Azerbaijan

1981–2007

23 (47)

4,231,550

13,534 (51)

4,349,750

14,110 (59)

Belarus

1981–2011

26 (53)

4,403,227

35,509 (50)

5,069,945

34,678 (55)

Belgium

1965–2012

47 (96)

5,451,780

14,299 (27)

5,643,070

17,157 (31)

Bosnia and Herzegovina

1985–2011

41 (84)

1,875,931

8503 (47)

1,963,806

9887 (58)

Bulgaria

1965–2012

47 (96)

3,555,925

34,456 (61)

3,749,973

37,188 (70)

Croatia

1985–2013

29 (59)

2,053,788

10,445 (41)

2,201,901

13,787 (54)

Cyprus

2004–2012

9 (18)

420,010

1015 (35)

443,932

1004 (38)

Czech Republic

1986–2013

28 (57)

5,161,617

23,701 (24)

5,349,102

28,030 (52)

Denmark

1965–2012

49 (98)

2,771,208

6442 (25)

2,815,877

6654 (25)

Estonia

1981–2012

29 (59)

620,643

3491 (46)

708,668

4848 (62)

Finland

1965–2013

48 (98)

2,673,499

9575 (37)

2,765,485

10,079 (39)

France

1965–2011

46 (94)

30,630,778

64,659 (24)

32,593,667

74,025 (28)

Georgia

1981–2014

34 (69)

1,776,700

9664 (39)

1,950,300

10,933 (45)

Germany

1990–2013

24 (49)

39,469,105

153,309 (36)

41,176,500

201,184 (43)

Greece

1965–2012

47 (96)

5,431,556

23,438 (39)

5,661,227

26,290 (46)

Hungary

1965–2013

48 (98)

4,709,677

27,598 (45)

5,183,416

35,379 (55)

Iceland

1965–2009

45 (92)

161,548

381 (37)

157,698

348 (36)

Ireland

1965–2012

46 (94)

2,269,612

4779 (32)

2,315,795

4701 (33)

Israel

1975–2013

39 (80)

3,991,346

4819 (24)

4,068,110

5217 (25)

Italy

1965–2012

37 (76)

28,808,103

99,659 (34)

30,731,623

130,498 (41)

Kazakhstan

1981–2012

32 (65)

8,100,113

24,533 (31)

8,691,315

18,542 (29)

Kyrgyzstan

1981–2013

31 (63)

2,827,672

9017 (46)

2,892,180

8610 (57)

Latvia

1980–2012

43 (88)

930,696

6877 (50)

1,103,623

9436 (62)

Lithuania

1981–2012

32 (65)

1,376,201

9884 (48)

1,611,572

13,286 (66)

Luxembourg

1965–2013

48 (98)

271,765

523 (30)

271,595

650 (34)

Malta

1965–2014

49 (100)

213,607

577 (35)

213,814

654 (40)

Montenegro

2000–2009

10 (20)

311,262

1518 (50)

320,282

1700 (60)

Netherlands

1965–2013

48 (98)

8,320,868

18,026 (26)

8,483,577

20,437 (28)

Norway

1965–2013

48 (98)

2,551,676

5630 (28)

2,528,498

6455 (30)

Poland

1965–2013

48 (98)

18,411,126

82,518 (41)

19,620,506

94,910 (51)

Portugal

1965–2013

45 (92)

4,976,865

13,980 (26)

5,480,441

17,546 (33)

Republic of Moldova

1981–2013

31 (63)

1,711,931

9994 (50)

1,846,646

12,136 (67)

Romania

1969–2012

43 (88)

9,770,353

71,117 (53)

10,289,829

82,254 (67)

Russian Federation

1980–2011

32 (65)

66,113,269

484,763 (49)

76,847,639

589,956 (64)

San Marino

1995–2005

7 (14)

14,637

49 (42)

15,205

50 (49)

Serbia

1998–2013

11 (22)

3,488,466

24,499 (48)

3,675,666

28,859 (58)

Slovakia

1992–2010

18 (37)

2,639,896

12,856 (47)

2,791,128

15,682 (61)

Slovenia

1985–2010

26 (53)

1,014,709

3071 (33)

1,034,545

4260 (46)

Spain

1965–2013

48 (98)

22,900,000

53,487 (27)

23,700,000

63,997 (34)

Sweden

1965–2013

48 (98)

22,933,751

15,972 (37)

3,659,485

17,597 (38)

Switzerland

1965–2013

48 (98)

3,995,315

9719 (31)

4,094,044

11,793 (35)

TFYR Macedonia

1991–2010

20 (41)

1,029,724

5500 (54)

1,024,767

5566 (62)

Tajikistan

1981–2004

22 (45)

3,365,837

6691 (46)

3,344,334

6448 (53)

Turkey

2009–2013

4 (8)

38,164,870

70,476 (36)

37,889,747

71,750 (45)

Turkmenistan

1981–1998

28 (57)

2,337,600

6314 (38)

2,370,000

6847 (52)

The UK

1965–2013

48 (98)

31,532,873

79,935 (29)

32,572,781

79,860 (27)

Ukraine

1981–2012

32 (65)

20,969,728

186,857 (57)

24,443,259

249,569 (74)

Uzbekistan

1981–2005

25 (51)

13,069,360

39,235 (53)

13,097,660

39,877 (60)

*Years of available data expressed in relation to a total of 1965 to 2014

**CVD deaths expressed as a percentage of total deaths by sex, e.g. percentage of all deaths in males that were caused by CVD

CVD rates calculated using the 1976 ESP were on average half the size of rates calculated using the 2013 ESP (mean rate difference = 1.95; P < 0.001). The mean rate difference was 1.86 for men and 2.03 for women. ASMR13s were more than twice as large as ASMR76s in males for eight countries (Austria, Iceland, Italy, Kazakhstan, Netherlands, Norway, San Marino, Sweden, and Switzerland). In females, ASMR13s were more than twice as large as ASMR76s for more than three quarters of countries (Table 2).
Table 2

Rates (per 100,000) and rate difference for most recent year for all countries by ESP and sex

Country

Males

Females

1976 ESP rate

2013 ESP rate

Rate difference

1976 ESP rate

2013 ESP rate

Rate difference

Albania

490.7

950.7

1.94

354.8

724.5

2.04

Armenia

524.5

946.5

1.80

356.5

743.9

2.09

Austria

224.5

457.1

2.04

156.3

348.0

2.23

Azerbaijan

616.8

1078.1

1.75

488.9

944.7

1.93

Belarus

868.0

1448.0

1.67

394.0

726.9

1.84

Belgium

181.1

357.1

1.97

118.7

252.9

2.13

Bosnia and Herzegovina

474.7

918.6

1.93

385.4

805.2

2.09

Bulgaria

705.5

1299.5

1.84

469.1

959.6

2.05

Croatia

392.8

761.4

1.94

269.0

581.2

2.16

Cyprus

217.7

428.8

1.97

155.2

343.9

2.22

Czech Republic

384.7

747.6

1.94

251.0

538.2

2.14

Denmark

170.1

337.6

1.98

107.6

229.9

2.14

Estonia

501.0

920.2

1.84

269.3

572.4

2.13

Finland

250.0

480.7

1.92

136.3

295.5

2.17

France

141.0

275.2

1.95

81.0

174.1

2.15

Georgia

450.0

891.6

1.78

302.6

608.7

2.01

Germany

239.2

476.3

1.99

165.2

361.2

2.19

Greece

257.1

485.0

1.89

180.6

391.3

2.17

Hungary

494.1

921.3

1.86

310.7

646.3

2.08

Iceland

218.6

441.6

2.02

131.9

297.5

2.26

Ireland

214.0

420.5

1.97

134.9

290.2

2.15

Israel

130.0

255.0

1.98

90.3

194.9

2.16

Italy

193.7

393.8

2.03

131.5

289.6

2.20

Kazakhstan

517.0

779.9

1.51

262.9

437.5

1.66

Kyrgyzstan

806.1

1443.9

1.79

545.3

1087.4

1.99

Latvia

655.0

1156.8

1.77

353.4

718.6

2.03

Lithuania

616.0

1097.0

1.78

340.1

706.4

2.08

Luxembourg

167.1

332.7

1.99

118.6

254.9

2.15

Malta

206.0

407.7

1.98

147.8

317.0

2.15

Montenegro

510.1

922.3

1.81

415.4

829.4

2.00

Netherlands

161.3

322.0

2.00

109.1

233.5

2.14

Norway

165.8

334.3

2.02

107.1

235.1

2.20

Poland

410.4

756.0

1.84

241.9

505.6

2.09

Portugal

174.8

347.0

1.99

119.8

259.7

2.17

Republic of Moldova

750.7

1380.0

1.84

536.6

1071.5

2.00

Romania

603.5

1144.0

1.90

431.1

903.9

2.10

Russian Federation

836.1

1423.1

1.70

469.3

914.0

1.95

San Marino

242.2

516.6

2.13

155.5

322.0

2.07

Serbia

516.3

990.9

1.92

398.3

836.4

2.10

Slovakia

551.8

1048.1

1.90

360.2

758.5

2.11

Slovenia

269.2

532.9

1.98

178.0

390.6

2.19

Spain

151.0

292.4

1.94

97.3

211.5

2.17

Sweden

204.4

414.8

2.03

134.0

292.3

2.18

Switzerland

164.3

339.2

2.06

108.7

242.0

2.23

Tajikistan

710.3

1332.5

1.88

503.9

920.0

1.83

TFYR Macedonia

626.9

1228.8

1.96

490.6

1012.5

2.06

Turkey

306.7

582.7

1.90

224.8

458.2

2.04

Turkmenistan

966.4

1718.5

1.78

722.0

1335.3

1.85

The UK

176.1

334.3

1.90

110.2

227.9

2.07

Ukraine

873.3

1544.9

1.77

532.6

1065.8

2.00

Uzbekistan

858.0

1492.4

1.74

662.3

1225.1

1.85

Total mean (SD)

560.8 (231.6)

1031.5 (405.4)

1.86 (0.857)

375.3 (164.6)

751.3 (313.6)

2.03 (0.094)

Mean CVD rates calculated using both ESPs were significantly lower in females than males (mean rate males, ASMR76 = 560.8, ASMR13 = 1031.5; mean rate females, ASMR76 = 375.3, ASMR13 = 751.3, P < 0.001), but females had a significantly greater proportional difference in rates when comparing the ASMR76s and ASMR13s (mean rate difference; males = 1.86, females = 2.03, P < 0.001). Spearman’s rank coefficient showed that ranks of countries by ASMRs calculated using the two ESPs were different for both sexes (Spearman’s rho for men 0.995, P < 0.001; Spearman’s rho for women 0.97, P < 0.001).

The largest changes in ranking were found for males in Kazakhstan which was six places lower when the ranking was compared between ASMR13 and ASMR76. In women, Ukraine was four places lower. In both sexes, Central Asian and Eastern European countries moved the most number of ranked places. In men, Central Asian and Eastern European countries generally moved down the ranking, and for women, these countries generally moved up. For both sexes, the top two and bottom three countries remained the same for rates calculated using both ESP (Table 3).
Table 3

Ranking number for countries from lowest to highest cardiovascular disease mortality rates (per 100,000), by latest available year

Country

Males

Change in ranking

Females

Change in ranking

1976 ESP

2013 ESP

1976 ESP

2013 ESP

Albania

36

36

0

36

34

2

Armenia

35

34

1

34

36

− 2

Austria

18

18

0

18

20

− 2

Azerbaijan

40

38

2

38

44

− 6

Belarus

49

48

1

48

35

13

Belgium

11

11

0

11

9

2

Bosnia and Herzegovina

28

30

− 2

30

38

− 8

Bulgaria

43

43

0

43

45

− 2

Croatia

26

27

− 1

27

29

− 2

Cyprus

16

16

0

16

19

− 3

Czech Republic

25

25

0

25

27

− 2

Denmark

8

8

0

8

5

3

Estonia

31

31

0

31

28

3

Finland

21

20

1

20

15

5

France

2

2

0

2

1

1

Georgia

30

29

1

29

30

− 1

Germany

19

19

0

19

21

− 2

Greece

22

21

1

21

23

− 2

Hungary

29

32

− 3

32

31

1

Iceland

17

17

0

17

16

1

Ireland

15

15

0

15

13

2

Israel

1

1

0

1

2

− 1

Italy

12

12

0

12

12

0

Kazakhstan

34

28

6

28

24

4

Kyrgyzstan

46

47

− 1

47

49

− 2

Latvia

42

41

1

41

33

8

Lithuania

39

39

0

39

32

7

Luxembourg

7

5

2

5

10

− 5

Malta

14

13

1

13

17

− 4

Montenegro

32

33

− 1

33

39

− 6

Netherlands

4

4

0

4

6

− 2

Norway

6

6

0

6

7

− 1

Poland

27

26

1

26

26

0

Portugal

9

10

− 1

10

11

− 1

Republic of Moldova

45

45

0

45

48

− 3

Romania

38

40

− 2

40

41

− 1

Russia Federation

47

46

1

46

42

4

San Marino

20

22

− 2

22

18

4

Serbia

33

35

− 2

35

40

− 5

Slovakia

37

37

0

37

37

0

Slovenia

23

23

0

23

22

1

Spain

3

3

0

3

3

0

Sweden

13

14

− 1

14

14

0

Switzerland

5

9

− 4

9

8

1

Tajikistan

44

44

0

44

43

1

TFYR Macedonia

41

42

− 1

42

46

− 4

Turkey

24

24

0

24

25

− 1

Turkmenistan

51

51

0

51

51

0

The UK

10

7

3

7

4

3

Ukraine

50

50

0

50

47

3

Uzbekistan

48

49

− 1

49

50

− 1

*1 = lowest, 51 = highest

A majority of countries in both sexes showed a negative ASMR trend calculated using both ESPs. Joinpoint analyses showed no difference in the direction of trend between ASMRs. There were four countries (Albania, Slovenia, Tajikistan, and Turkey) in men and eight countries (Azerbaijan, Belarus, Montenegro, San Marino, Serbia, Slovakia, Slovenia, and Turkey) in women that have a continuous linear trend (no joinpoints identified).

In men, seven countries (San Marino, Austria, Belarus, Azerbaijan, Lithuania, Romania, and Hungary) had a greater decrease in the trend for ASMR13 than ASMR76. This was found in three countries for women (Belarus, Latvia, and Russia). A greater increase in trend in ASMR13 than ASMR76 was found in six countries for women (Albania, Bulgaria, Azerbaijan, Turkey, Kyrgyzstan, and Turkmenistan) and in one country for men (TFYR Macedonia). Four countries (Bulgaria, Russian Federation, Ukraine, and Uzbekistan) had a greater increase in trend for ASMR76 than ASMR13 in men and two in women (Kazakhstan and Uzbekistan) (Table 4).
Table 4

Average annual percentage changes and joinpoint analysis by country and sex by recent available year in males

 

Average annual percentage change (AAPC)

Joinpoint annual percentage change (APC) and end year for each segment in the best fitting model

Males

  

Segment 1

Segment 2

Segment 3

Segment 4

Segment 5

Country

 Albania

ESP 76

− 0.3 (− 1.3, 0.7)

          

ESP 13

− 0.1 (− 1.2, 0.9)

          

 Armenia

ESP 76

0 (− 0.7, 0.7)

1981

2.7^

1993

− 5.5^

2000

17.6^

2003

− 3.9^

  

ESP 13

0 (− 0.9, 0.8)

1981

2.5^

1993

− 6.4^

2000

22.6^

2003

− 4.4^

  

 Austria

ESP 76

− 2.8^ (− 3.4, − 2.3)

1965

18.1^

1971

− 3.6^

      

ESP 13

− 2.9 (− 3.5, − 2.3)

1965

21.2^

1971

− 3.7^

      

 Azerbaijan

ESP 76

− 0.4^ (− 0.8, − 0.1)

1981

0.7

1995

− 1.7^

      

ESP 13

− 0.5^ (− 0.8, − 0.1)

1981

− 0.2

2003

− 4.6^

      

 Belarus

ESP 76

− 0.5 (− 1, 0.1)

1981

3.9

1985

− 3.8^

1992

7.1

1996

− 2.1^

  

ESP 13

− 0.7 (− 1.2, − 0.2)

1981

4.7

1985

− 4.8^

1992

7.2

1996

− 2.2^

  

 Belgium

ESP 76

− 2.6^ (− 2.9, − 2.3)

1965

4.4

1971

− 2.9^

      

ESP 13

− 2.3 (− 2.6, − 2.1)

1965

4.5

1971

− 2.7^

      

 Bosnia and Herzegovina

ESP 76

− 0.7 (− 1.7, 0.3)

1985

8.5^

1988

− 1.1^

      

ESP 13

− 0.4 (− 1.4, 0.7)

1985

9.3

1988

− 0.9^

      

 Bulgaria

ESP 76

0.8^ (0.5, 1.2)

1965

24.1^

1969

1.5^

1998

− 1.8^

    

ESP 13

0.7^ (0.4, 1.1)

1965

23.7^

1969

1.4^

1998

− 1.8^

    

 Croatia

ESP 76

− 1.9^ (− 2.3, − 1.4)

1985

− 1.8^

1995

5.8

1998

− 4.0^

    

ESP 13

− 1.7^ (− 2.1, − 1.3)

1985

− 1.9^

1995

5.8

1998

− 3.7^

    

 Cyprus

ESP 76

− 3.8^ (− 4.7, − 2.8)

          

ESP 13

− 3.3^ (− 4.6, − 2.1)

          

 Czech Republic

ESP 76

− 3.0^ (− 3.2, − 2.9)

1986

− 0.5

1990

− 3.4^

2000

− 1.1

2003

− 5.1^

2013

− 2.5^

ESP 13

− 2.8^ (− 2.9, − 2.6)

1986

− 0.5

1990

− 3.1^

2000

− 0.2

2003

− 5.3^

2007

− 2.4^

 Denmark

ESP 76

− 2.2^ (− 2.6, − 1.9)

1965

2.3^

1973

− 1.5^

1991

− 3.7^

2003

− 6.0^

  

ESP 13

− 2.1^ (− 2.4, − 1.8)

1965

2.9^

1972

− 1.4^

1991

− 3.4^

2003

− 5.9^

  

 Estonia

ESP 76

− 2.0^ (− 2.3, − 1.7)

1981

− 0.9^

1991

3.2

1994

− 5.5

1997

− 2.2^

2012

− 5.2^

ESP 13

− 2.0^ (− 2.3, − 1.8)

1981

− 0.8^

1994

− 2.4^

2007

− 4.9^

    

 Finland

ESP 76

− 2.6^ (− 2.8, − 2.4)

1965

5.7^

1970

− 2.2^

1987

− 3.3^

    

ESP 13

− 2.3^ (− 2.5, − 2.1)

1965

5.9^

1970

− 2.1^

1990

− 3.1^

    

 France

ESP 76

− 2.4^ (− 2.7, − 2.1)

1965

13.7^

1969

− 2.0^

1986

− 6.8

1989

− 1.9^

2011

− 4.4^

ESP 13

− 2.3^ (− 2.6, − 2)

1965

14.2^

1969

− 1.9^

1986

− 6.7

1989

− 1.7^

2002

− 4.3^

 Georgia

ESP 76

− 1.7^ (− 2.5, − 0.9)

1981

− 0.2

2007

− 17.9

2011

9.5

    

ESP 13

− 1.8^ (− 2.6, − 0.9)

1981

− 0.1

2005

− 8.7^

      

 Germany

ESP 76

− 3.6^ (− 3.8, − 3.4)

1990

− 3.2^

2003

− 4.6^

2011

1.4

    

ESP 13

− 3.4^ (− 3.6, − 3.3)

1990

− 3.0^

2003

− 4.6^

2011

2

    

 Greece

ESP 76

− 0.4^ (− 0.8, − 0.1)

1965

23.2^

1968

1.3^

1987

− 1.0^

2002

− 4.1^

  

ESP 13

− 0.3 (− 0.7, 0.1)

1965

23.2^

1968

1.5^

1987

− 0.8^

2002

− 4.5^

  

 Hungary

ESP 76

− 0.6^ (− 0.9, − 0.3)

1965

10.9^

1970

0.2

1992

^2.3^

    

ESP 13

− 0.7^ (-1, -0.4)

1965

10.7^

1970

−0.2

1993

− 2.2^

    

 Iceland

ESP 76

− 2.6^ (− 2.8, − 2.4)

1965

5.7^

1970

− 2.2^

1987

− 3.3^

    

ESP 13

− 2.3^ (− 2.5, − 2.1)

1965

5.9^

1970

− 2.1^

1990

− 3.1^

    

 Ireland

ESP 76

− 2.3^ (− 2.7, − 1.9)

1965

7.7^

1969

− 0.4

1982

− 2.8^

1998

− 5.4^

  

ESP 13

− 2.2^ (− 2.5, − 1.8)

1965

7.8^

1969

− 0.4

1982

− 2.7^

1998

− 5.1^

  

 Israel

ESP 76

− 3.9^ (− 4.2, − 3.6)

1975

− 2.8^

1990

0.3

1994

− 10.2^

1997

− 4.7^

  

ESP 13

− 3.7^ (− 3.9, − 3.4)

1975

− 2.6^

1990

1

1994

− 10.2^

1997

− 4.5^

  

 Italy

ESP 76

− 2.4^ (− 2.7, − 2.1)

1965

11.0^

1969

− 1.4^

1983

− 3.2^

    

ESP 13

− 2.2^ (− 2.5, − 1.9)

1965

11.3^

1969

− 1.3^

1983

− 3.0^

    

 Kazakhstan

ESP 76

0.2 (− 0.6, 1.1)

1981

0.4

1991

7.7

1994

0.3

2007

− 11.3^

2012

− 25.3^

ESP 13

0.1 (− 0.8, 1)

1981

0.7

1991

6.3

1994

0.5

2007

− 11.9^

2010

− 29.7^

 Kyrgyzstan

ESP 76

0.9^ (0.7, 1.2)

1981

0.1

1991

5.7

1994

0.4^

    

ESP 13

0.9^ (0.7, 1.2)

          

 Latvia

ESP 76

− 0.9^ (− 1.2, − 0.5)

1980

− 0.8^

1991

9.3^

1994

− 9.2^

1997

− 0.3

2012

− 3.9^

ESP 13

− 1.0^ (− 1.3, − 0.8)

1980

− 1.0^

1991

6.8

1994

− 7.6

1997

− 0.3

2005

− 3.3^

 Lithuania

ESP 76

− 0.3^ (− 0.6, − 0.1)

1981

1.1^

1994

− 2.4^

2000

1.5

2006

− 3.0^

  

ESP 13

− 0.4^ (− 0.6, − 0.2)

1981

0.6

1994

− 0.9^

      

 Luxembourg

ESP 76

− 2.5^ (− 2.9, − 2.1)

1965

8.8^

1971

− 1.5^

1985

− 3.9^

    

ESP 13

− 2.2^ (− 2.6, − 1.8)

1965

9.7^

1971

− 1.2^

1985

− 3.7^

    

 Malta

ESP 76

−2.9^ (− 3.5, − 2.3)

1965

5.8^

1981

− 20.4

1984

− 3.5^

    

ESP 13

− 2.7^ (− 3.4, − 2.1)

1965

6.7^

1981

− 22.4

1984

− 3.2^

    

 Montenegro

ESP 76

− 0.7 (− 2.1, 0.7)

2000

−4.7

2002

3

2006

−5.8^

    

ESP 13

− 0.5 (− 2, 0.9)

2000

− 4.8

2002

3.5

2006

− 6.0^

    

 Netherlands

ESP 76

− 2.2^ (− 2.5, − 1.9)

1965

−  1.9

1967

12.6^

1970

− 1.3^

1985

− 2.4^

2013

− 5.1^

ESP 13

− 2.0^ (− 2.3, − 1.7)

1965

− 2.4

1967

13.1^

1970

− 1.3^

1985

− 2.1^

2000

− 4.8^

 Norway

ESP 76

− 2.1^ (− 2.5, −1.8)

1965

9.9^

1970

− 1.0^

1988

− 2.9^

1998

− 5.1^

  

ESP 13

− 1.9^ (− 2.2, − 1.5)

1965

11.3^

1970

− 1.2^

1995

− 4.6^

    

 Poland

ESP 76

− 0.7^ (− 1.2, − 0.3)

1965

5.6^

1971

1.4^

1991

− 3.6^

2002

− 2.4^

  

ESP 13

− 0.7^ (− 1.1, − 0.3)

1965

5.4^

1971

1.5^

1990

− 2.9^

    

 Portugal

ESP 76

− 2.2^ (− 2.8, − 1.6)

1965

0.2

1969

33.3^

1972

− 2.0^

1993

− 4.5^

  

ESP 13

− 2.0^ (− 2.6, − 1.4)

1965

0.1

1969

35.0^

1972

− 1.8^

1993

− 4.4^

  

 Republic of Moldova

ESP 76

0.1 (− 0.4, 0.7)

1981

− 0.3

1985

− 4.9^

1992

10.5^

1996

0.6

2013

− 2.8^

ESP 13

0.1 (− 0.5, 0.7)

1981

0.5

1985

− 6.3^

1992

11.7^

1996

1

2003

− 3.2^

 Romania

ESP 76

− 0.2 (− 0.5, 0.1)

1969

0.8^

1997

− 2.4^

      

ESP 13

− 0.3^ (− 0.5, 0)

1969

0.7^

1997

− 2.3^

      

 Russian Federation

ESP 76

0.3 (0, 0.7)

1980

− 1.1^

1991

10.2^

1994

− 6.7

1997

4.0^

2011

− 3.8^

ESP 13

0 (−0.3, 0.4)

1980

− 1.1^

1991

7.4

1994

− 5.7

1997

2.8^

2004

− 4.0^

 San Marino

ESP 76

− 3.7 (−12.7, 6.2)

          

ESP 13

− 4.6 (− 13.9, 5.7)

          

 Serbia

ESP 76

− 2.5^ (− 2.8, − 2.2)

          

ESP 13

− 2.4^ (− 2.7, − 2.1)

          

 Slovakia

ESP 76

− 1.2^ (− 1.5, − 0.8)

1992

2.6

1995

− 1.2^

2006

− 3.2^

    

ESP 13

− 0.8^ (− 1.2, − 0.4)

1992

3.6

1995

−  0.9^

2006

− 3.2^

    

 Slovenia

ESP 76

− 3.4^ (− 3.6, − 3.2)

          

ESP 13

− 3.2^ (− 3.4, − 3)

          

 Spain

ESP 76

− 2.6^ (− 3, − 2.3)

1965

− 30.8^

1968

16.0^

1973

− 3.0^

    

ESP 13

− 2.6^ (− 2.9, − 2.2)

1965

− 34.8^

1968

16.8^

1973

− 2.9^

    

 Sweden

ESP 76

− 2.1^ (− 2.4, − 1.8)

1965

4.5^

1971

− 0.3

1982

− 2.8^

1998

− 3.7^

  

ESP 13

− 1.9^ (− 2.2, − 1.6)

1965

4.6^

1971

− 0.4

1982

− 2.5^

1998

− 3.4^

  

 Switzerland

ESP 76

− 2.5^ (− 2.7, − 2.2)

1965

− 3.5

1967

7.8^

1970

− 0.8^

1980

− 2.8^

2013

− 3.7^

ESP 13

− 2.3^ (− 2.5, − 2.1)

1965

− 3.9

1967

8.7^

1970

− 0.8^

1980

− 2.7^

1997

− 3.5^

 Tajikistan

ESP 76

1.5^ (1, 2)

          

ESP 13

1.8^ (1.3, 2.3)

          

 TFYR Macedonia

ESP 76

0 (− 0.3, 0.4)

1991

0.9^

2003

− 1.7^

      

ESP 13

0.4^ (0, 0.8)

1991

1.4^

2003

− 1.5^

      

 Turkey

ESP 76

1.1 (− 1.5, 3.8)

          

ESP 13

1.1 (− 1.5, 3.8)

          

 Turkmenistan

ESP 76

1.4 (− 0.2, 3)

1981

0.5

1989

12.5

1992

− 5.3^

    

ESP 13

1.4 (0, 3)

1981

0.7

1989

11.5

1992

− 4.7^

    

 The UK

ESP 76

− 2.7^ (− 3, − 2.4)

1965

8.6^

1969

− 1.1^

1979

− 2.9^

1999

− 5.2^

  

ESP 13

− 2.6^ (− 2.9, − 2.3)

1965

9.1^

1969

− 1.2^

1979

− 2.7^

2001

− 5.5^

  

 Ukraine

ESP 76

0.7^ (0.3, 1.1)

1981

− 1.8^

1991

7.1^

1995

− 2.2

1998

2.3^

2012

− 3.1^

ESP 13

0.5^ (0.2, 0.9)

1981

0.7

1985

− 3.8^

1991

7.5

1994

1.1^

2006

− 3.1^

 Uzbekistan

ESP 76

0.7^ (0.3, 1.1)

1981

− 1.8^

1991

7.1^

1995

− 2.2

1998

2.3^

2012

− 3.1^

ESP 13

0.5^ (0.2, 0.9)

1981

0.7

1985

− 3.8^

1991

7.5

1994

1.1^

2006

− 3.1^

AAPC the average annual percentage change over the entire period of available data, APC annual percentage change over each identified joinpoint segment

^Values are significantly different to zero

Differences in the number of joinpoint segments between rates from both ESPs were found for five countries in men (Georgia, Lithuania, Norway, and Poland) and four countries (Albania, Estonia, Kyrgyzstan, and Lithuania) in women. A number of countries showed a plateau in recent trends, as defined by the most recent segment showing either a less steep decline than the preceding segment, no significant difference to zero, or an increase. These plateaus were identified at all times in trends of both ASMRs except for men in Georgia amongst whom a plateau found in the trend of ASMR76 was not found when using ASMR13 (Table 5).
Table 5

Average annual percentage changes and joinpoint analysis by country and sex by recent available year in females

Country

Average annual percentage change (AAPC)

Joinpoint annual percentage change (APC) and end year for each segment in the best fitting model

Females

 

Segment 1

Segment 2

Segment 3

Segment 4

Segment 5

Country

 Albania

ESP 76

0.1 (− 1.2, 1.4)

1987

− 4.9

1993

2.2^

      

ESP 13

0.2 (−1.1, 1.6)

          

 Armenia

ESP 76

− 0.3 (− 1, 0.3)

1981

2.2^

1993

− 4.4^

2000

12.9^

2003

− 4.3^

  

ESP 13

− 0.1 (− 0.8, 0.5)

1981

2.2^

1993

− 4.6^

2000

15.2^

2003

− 4.3^

  

 Austria

ESP 76

− 1.9^ (− 2.4, − 1.4)

1965

1.4

1983

− 3.2^

      

ESP 13

− 1.4^ (− 1.9, − 0.9)

1965

2.0^

1984

− 3.0^

      

 Azerbaijan

ESP 76

0.4^ (0.1, 0.7)

          

ESP 13

0.5^ (0.1, 0.9)

          

 Belarus

ESP 76

− 0.5 (− 1, 0.1)

1981

3.9

1985

− 3.8

1992

7.1

1996

− 2.1^

  

ESP 13

− 0.7^ (− 1.2, − 0.2)

1981

4.7

1985

− 4.8^

1992

7.2

1996

− 2.2^

  

 Belgium

ESP 76

− 2.5^ (− 2.7, − 2.3)

1965

7.8^

1969

− 2.6^

2004

− 4.3^

    

ESP 13

− 2.3^ (− 2.5, − 2.1)

1965

7.7^

1969

− 2.4^

2004

− 4.3^

    

 Bosnia and Herzegovina

ESP 76

− 0.8 (− 1.7, 0.1)

1985

4.6

1989

− 1.3^

      

ESP 13

− 0.4 (− 1.3, 0.5)

1985

5

1989

− 0.9^

      

 Bulgaria

ESP 76

0.1 (− 0.2, 0.4)

1965

22.6^

1969

0.5^

1998

− 2.1^

    

ESP 13

0.2 (− 0.1, 0.5)

1965

22.6^

1969

0.6^

1998

− 2.0^

    

 Croatia

ESP 76

− 2.0^ (− 2.4, − 1.6)

1985

− 2.0^

1995

5.7

1998

− 4.0^

    

ESP 13

− 1.7^ (− 2.1, − 1.3)

1985

− 1.9^

1995

6

1998

− 3.6^

    

 Cyprus

ESP 76

− 2.9^ (− 4.8, −  0.8)

          

ESP 13

− 2.2^ (− 4.4, 0)

          

 Czech Republic

ESP 76

− 2.8^ (− 2.9, − 2.6)

1986

− 2.3^

2003

− 3.8^

      

ESP 13

− 2.5^ (− 2.7, − 2.3)

1986

− 2.0^

2003

− 3.6^

      

 Denmark

ESP 76

− 2.3^ (− 2.6, − 2.1)

1965

3.2^

1970

− 1.7^

1993

− 3.4^

2003

− 5.6^

  

ESP 13

− 2.2^ (− 2.5, − 2)

1965

3.2^

1970

− 1.6^

1993

− 3.3^

2003

− 5.4^

  

 Estonia

ESP 76

− 2.7^ (− 3, − 2.4)

1981

1.1

1985

− 2.6^

1991

1.1

1994

− 3.8^

  

ESP 13

− 2.5^ (− 2.8, − 2.3)

1981

1.2

1985

− 2.3^

2002

− 3.9^

    

 Finland

ESP 76

− 2.9^ (− 3, − 2.7)

1965

− 3.1

1967

11.6^

1970

− 4.7^

1977

− 2.2^

2013

− 3.5^

ESP 13

− 2.9^ (− 3, − 2.7)

1965

− 3.3

1967

11.5^

1970

− 4.6^

1977

− 2.0^

2013

− 3.3^

 France

ESP 76

− 2.6^ (− 2.8, − 2.3)

1965

14.9^

1969

− 2.3^

1986

− 5.8

1990

− 2.0^

2011

− 4.7^

ESP 13

− 2.4^ (− 2.7, − 2.1)

1965

15.0^

1969

− 2.0^

1986

− 5.8

1990

− 1.9^

2011

− 4.8^

 Georgia

ESP 76

− 2.2^ (− 3, − 1.5)

1981

− 0.5

2004

− 7.9^

      

ESP 13

− 2.2^ (− 3, − 1.4)

1981

− 0.6

2004

− 7.8^

      

 Germany

ESP 76

− 3.0^ (− 3.2, − 2.9)

1990

− 3.0^

2000

− 0.7

2003

− 5.3^

2006

−  3.7^

2013

− 0.4

ESP 13

− 2.8^ (− 3, − 2.6)

1990

− 2.8^

2000

− 0.1

2003

− 5.3^

2006

− 3.5^

2013

− 0.3

 Greece

ESP 76

− 0.5^ (− 0.9, − 0.2)

1965

26.7^

1968

1.0^

1987

− 0.9^

2004

− 5.4^

  

ESP 13

− 0.2 (− 0.6, 0.1)

1965

26.1^

1968

1.4^

1986

− 0.5^

2004

− 5.5^

  

 Hungary

ESP 76

− 1.2^ (− 1.4, − 0.9)

1965

9.3^

1970

− 0.7^

1993

− 2.5^

    

ESP 13

− 1.1^ (− 1.3, − 0.9)

1965

9.1^

1970

− 0.8^

1996

− 2.4^

    

 Iceland

ESP 76

− 2.7^ (− 3, − 2.4)

1965

10.4^

1969

− 1.1

1978

− 3.0^

1998

− 5.0^

  

ESP 13

− 2.5^ (− 2.8, − 2.2)

1965

14.0^

1968

0

1976

− 2.7^

1998

− 4.7^

  

 Ireland

ESP 76

− 2.7^ (− 3, − 2.4)

1965

10.4^

1969

− 1.1

1978

− 3.0^

1998

− 5.0^

  

ESP 13

− 2.5^ (− 2.8, − 2.2)

1965

14.0^

1968

0

1976

− 2.7^

1998

− 4.7^

  

 Israel

ESP 76

− 4.5^ (− 4.7, − 4.2)

1975

− 3.2^

1999

− 13.6

2013

− 5.2

    

ESP 13

− 4.2^ (− 4.4, − 3.9)

1975

− 2.9^

1995

− 8.0^

1999

− 4.4^

    

 Italy

ESP 76

− 2.7^ (− 2.9, − 2.5)

1965

12.7^

1968

− 0.8

1976

− 3.1^

    

ESP 13

− 2.4^ (− 2.7, − 2.2)

1965

12.4^

1968

− 0.4

1976

− 2.9^

    

 Kazakhstan

ESP 76

0.2 (− 0.6, 1.1)

1981

0.4

1991

7.7

1994

0.3

2007

− 11.3^

2012

− 25.3^

ESP 13

0.1 (− 0.8, 1)

1981

0.7

1991

6.3

1994

0.5

2007

− 11.9^

2012

− 29.7^

 Kyrgyzstan

ESP 76

1.0^ (0.7, 1.2)

1981

0.1

1992

6.5

1995

− 4

1998

4.8

2013

− 0.5

ESP 13

1.2^ (0.9, 1.4)

          

 Latvia

ESP 76

− 1.6^ (− 1.9, − 1.4)

1980

− 1.2^

2003

− 3.7^

      

ESP 13

− 1.7^ (− 1.9, − 1.5)

1980

− 1.3^

2003

− 3.5^

      

 Lithuania

ESP 76

− 1.2^ (− 1.4, − 1)

1981

− 0.2

1995

− 1.8^

      

ESP 13

− 1.1 (− 1.3, − 0.9)

1981

1.6

1985

− 0.9^

2006

− 3.2^

    

 Luxembourg

ESP 76

− 2.7^ (− 3, − 2.3)

1965

7.4^

1971

− 1.2^

1984

− 4.4^

2000

3.2

2013

− 5.6^

ESP 13

− 2.4^ (− 2.8, − 2.1)

1965

18.4^

1968

0

1983

− 4.3^

2000

3.4

2013

− 5.3^

 Malta

ESP 76

− 3.4^ (− 3.9, − 2.8)

1965

5.3^

1981

− 21.9^

1984

− 3.7^

    

ESP 13

− 3.2^ (− 3.8, − 2.6)

1965

6.0^

1981

− 23.6^

1984

− 3.4^

    

 Montenegro

ESP 76

− 0.5 (− 1.9, 0.9)

          

ESP 13

− 0.2 (− 1.6, 1.2)

          

 Netherlands

ESP 76

− 2.3^ (− 2.5, − 2)

1965

− 5.6

1967

16.6^

1970

− 3.1^

1980

− 1.9^

2013

− 4.1^

ESP 13

− 2.2^ (− 2.4, − 1.9)

1965

− 5.8

1967

16.6^

1970

− 3.1^

1980

− 1.9^

2013

− 3.9^

 Norway

ESP 76

− 2.2^ (− 2.5, − 1.9)

1965

11.5^

1970

− 2.0^

1999

− 4.5^

    

ESP 13

− 2.0^ (− 2.3, − 1.7)

1965

− 1

1967

16.7^

1970

− 1.9^

1999

− 4.2^

  

 Poland

ESP 76

− 1.1^ (− 1.4, − 0.7)

1965

4.9^

1970

0.9^

1991

− 3.2^

    

ESP 13

− 0.9^ (− 1.2, − 0.5)

1965

5.2^

1970

1.0^

1991

− 2.9^

    

 Portugal

ESP 76

− 2.3^ (− 2.9, − 1.7)

1965

0.1

1969

33.6^

1972

− 2.2^

1996

− 4.9^

  

ESP 13

− 2.0^ (− 2.6, − 1.4)

1965

0.5

1969

34.1^

1972

− 1.7^

1995

− 4.6^

  

 Republic of Moldova

ESP 76

− 0.1 (− 0.7, 0.5)

1981

1

1985

− 6.4^

1992

9.9^

1996

1

2013

− 3.2^

ESP 13

− 0.1 (− 0.7, 0.5)

1981

1.6

1985

− 7.6^

1992

10.8^

1996

1.6

2013

− 3.1^

 Romania

ESP 76

− 0.9^ (− 1.1, − 0.6)

1969

0.7^

1985

− 1.0^

2003

− 3.7^

    

ESP 13

− 0.8^ (− 1, − 0.5)

1969

1.1^

1984

− 1.0^

2003

− 3.3^

    

 Russian Federation

ESP 76

− 0.2 (− 0.5, 0.1)

1980

− 1.0^

1991

5.8

1994

− 4.1

1997

2.4^

2011

− 4.0^

ESP 13

− 0.3^ (− 0.6, 0)

1980

− 0.5

1991

0.6^

2005

− 4.6^

    

 San Marino

ESP 76

0.9 (− 19.6,26.7)

          

ESP 13

0.9 (− 19.6, 26.7)

          

 Serbia

ESP 76

− 2.7^ (− 3, − 2.5)

          

ESP 13

− 2.5^ (− 2.7, − 2.2)

          

 Slovakia

ESP 76

− 2.7^ (− 3, − 2.5)

          

ESP 13

− 2.5^ (− 2.7, − 2.2)

          

 Slovenia

ESP 76

− 3.4^ (− 3.6, − 3.2)

          

ESP 13

− 3.2^ (− 3.4, − 2.9)

          

 Spain

ESP 76

− 3.0^ (− 3.3, −  2.7)

1965

24.2^

1969

− 2.7^

1990

− 3.9^

    

ESP 13

− 2.7^ (− 3.1, − 2.4)

1965

24.7^

1969

− 2.3^

1990

− 3.8^

    

 Sweden

ESP 76

− 2.2^ (− 2.4, − 2)

1965

5.3^

1970

− 1.7^

1985

− 2.8^

    

ESP 13

− 2.1^ (− 2.2, − 1.9)

1965

5.3^

1970

− 1.6^

1985

− 2.6^

    

 Switzerland

ESP 76

− 2.7^ (− 2.9, − 2.5)

1965

− 4.1

1967

10.6^

1970

− 3.0^

    

ESP 13

− 2.5^ (− 2.7, − 2.3)

1965

− 3.7

1967

11.0^

1970

− 2.8^

    

 Tajikistan

ESP 76

− 2.7^ (− 2.9, − 2.5)

1965

− 4.1

1967

10.6^

1970

− 3.0^

    

ESP 13

− 2.5^ (− 2.7, − 2.3)

1965

− 3.7

1967

11.0^

1970

− 2.8^

    

 TFYR Macedonia

ESP 76

− 2.7^ (− 2.9, − 2.5)

1965

− 4.1

1967

10.6^

1970

− 3.0^

    

ESP 13

− 2.5^ (− 2.7, − 2.3)

1965

− 3.7

1967

11.0^

1970

− 2.8^

    

 Turkey

ESP 76

0.1 (− 4.8, 5.2)

          

ESP 13

0.5 (− 4.6, 6)

          

 Turkmenistan

ESP 76

1.7 (− 0.2, 3.7)

1981

0.5

1989

15.3

1992

− 6.1^

    

ESP 13

1.8 (− 0.3, 3.8)

1981

0.5

1989

15.9

1992

− 6.4^

    

 The UK

ESP 76

– 2.7^ (− 3, − 2.4)

1965

13.2^

1969

− 2.6^

2001

− 5.5^

    

ESP 13

– 2.5^ (− 2.8, − 2.3)

1965

13.1^

1969

− 2.5^

2002

− 5.4^

    

 Ukraine

ESP 76

0.1 (− 0.2, 0.4)

1981

1.6

1985

− 4.3^

1991

8.1

1994

0.4

2012

− 2.7^

ESP 13

0.1 (− 0.2, 0.4)

1981

− 0.4

1988

− 8.1

1991

9.1^

1994

0.5

2012

− 2.4^

 Uzbekistan

ESP 76

1.5^

(0.9, 2)

1981

0.5

1990

7.4^

1994

− 0.7^

   

ESP 13

1.4^

(0.9, 2)

1981

0.6

1990

7.5^

1994

− 0.9^

   

AAPC refers to the average annual percentage change over the entire period of available data, APC refers to annual percentage change over each identified joinpoint segment

^Values are significantly different to zero

Discussion

The 2013 ESP changes the relative burden of CVD mortality rates for European countries by sex. The 1976 ESP rates are half as high as those calculated using 2013 ESP in countries for both sexes, and the ranking of countries by CVD ASMR changed when calculating ASMRs using the different standard populations. Despite largely similar trends between ASMR13 and ASMR76 for all countries by sex, there were some differences in trends in ASMRs calculated using different ESPs.

Joinpoint analyses allowed us to compare trends in the log of ASMRs calculated using the old and new ESPs. This demonstrated that for most countries the direction and intensity of the trend in the two ASMRs were similar, although some differences were apparent. In particular, a number of countries showed a difference in the intensity of the trend over the entire period, when comparing ESP76 to ESP13, although no country was found to have a change in the direction of the trend for either sex. Differences in intensity were more pronounced in countries when comparing the most recent trend, with one country demonstrating a change in the direction of the most recent segment.

Limitations of this research are that there is a variability of global coverage and data quality [11]. Developed countries use the vital record system whereas developing countries use verbal autopsy, which are generally weaker and not standardised [12, 13]. Furthermore, the results in this study may not be generalizable to countries outside of the WHO Europe Member States. However, findings are representable and internally valid because data were comparable between ESPs since the same data were used.

To our knowledge, this is the first paper to investigate trends in CVD mortality for all European countries. It is also the first to compare ASMRs calculated using ESP13 and ESP76 [2]. Our finding that ASMR76 were half as large as ASMR13s was similar to previous work investigating deaths from coronary heart disease (CHD) rather than CVD as done here [2]. We found no paper that had investigated the difference between trends in ASMRs calculated using ESP13 and ESP76 in total CVD or subtype, although trends in CVD agreed with previous analysis on trends in CHD ASMRs [11] in most countries. Differences in results between studies show a decrease in CHD ASMR in Bulgaria found in the previous [11] compared to an increase in CVD ASMR in the present study. These differences may be due to garbage codes, defined as incomplete registration of death and sex/age in the mortality data for CVD [14]. The WHO reported that Bulgaria had a large amount of garbage codes included for subgroups in CVD [15].

Such changes in standard populations can be confusing for policy makers and public alike, unless clarity is provided in the effect of such changes. We have demonstrated in this paper that the relative description of the burden of CVD mortality between countries occurs when changing the standard population used to calculate age-standardised rates. In addition, in some countries, the intensity and, in one country, the direction, of the most recent trend in CVD ASMRs was altered by the introduction of a new standard population, despite no change in the mortality and population data used to calculate them. Such changes can be misleading and care must be taken not to compare between analyses using different standard populations. ASMRs produce an estimate of mortality that relates to a standard population; this means it is only a useful measure when used comparatively between estimates using the same population. Rates calculated using the actual population are better when calculating an absolute mortality measure. This means that ASMRs can prove confusing, such that there is merit in adopting a standard population that is as representative of the actual population as possible. The most recent ESP (2013) was introduced to better reflect the contemporary population distribution of Europe, so this remains the most suitable ESP for the calculation of standardised rates; it must be noted, however, that this change may alter how we discuss the relative burden of CVD mortality across the continent and in some cases within countries.

Conclusion

Age-standardised rates are commonly used in studying the epidemiology of a disease. Although changing the standard population will change the rates, this paper also shows that it may change the relative burden of disease when countries or subgroups are compared to each other, despite using the same mortality data. It is crucial that policy makers understand the effect of changes in standard populations on these comparisons. Similar effects as those found in CVD in Europe, due to the change in the European Standard Population, may be seen in other diseases that are also more prevalent in older age groups, such as cancer and dementia.

Abbreviations

ASMR: 

Age-standardised mortality rates

ASMR13: 

Age-standardised mortality rates calculated using the 2013 European Standard Population

ASMR76: 

Age-standardised mortality rates calculated using the 1976 European Standard Population

CHD: 

Coronary heart disease

CVD: 

Cardiovascular disease

ESP: 

European Standard Population

ESP13: 

2013 European Standard Population

ESP76: 

1976 European Standard Population

ICD: 

International Classification of Disease

UK: 

United Kingdom

WHO: 

World Health Organization

Declarations

Acknowledgements

Not applicable

Funding

KW and NT were funded by the British Heart Foundation (grant URN: 006/P&C/CORE/2013/OXFSTATS). No other funding was received for this work.

Authors’ contributions

ST extracted the data, performed the data analysis and produced a first draft of the paper. NT and KW conceptualised and designed the project, and they also assisted on all aspects including data extraction, analysis and drafting the paper. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

Authors’ Affiliations

(1)
Centre on Population Approaches for Non-Communicable Disease Prevention, Nuffield Department of Population Health, University of Oxford, Oxford, UK
(2)
UCLA Comprehensive Vascular Neurology Program, Department of Neurology, University of California at Los Angeles, 710 Westwood Plaza, Los Angeles, CA 90095-17693, USA
(3)
World Health Organization European Office for Prevention and Control of Noncommunicable Diseases (NCD Office), Moscow, Russian Federation
(4)
Department for Health, University of Bath, Bath, BA2 7AY, UK

References

  1. Levi F, Lucchini F, Negri E, Vecchia CL. Trends in mortality from cardiovascular and cerebrovascular diseases in Europe and other areas of the world. Heart. 2003;88:119–24.View ArticleGoogle Scholar
  2. Townsend N, Nichols M, Scarborough P, Rayner M. Cardiovascular disease in Europe 2016: epidemiological update. Eur Heart J. 2016;0:1–14.Google Scholar
  3. Wilkins E, Wilson L, Wickramasinghe K, Bhatnagar P, Leal J, Luengo-Fernandez R, Burns R, Rayner M, Townsend N. European Cardiovascular Disease Statistics 2017. European Heart Network, Brussels; 2017.Google Scholar
  4. Evans J. Implementing the 2013 European Standard Population: the impact of selected upper age limits on mortality. London: Office for National Statistics; 2014. www.ons.gov.uk%2Fons%2Fguide-method%2Fuser-guidance%2Fhealth-and-life-events%2Frevised-european-standard-population-2013--2013-esp-%2Fimpact-of-varying-the-2013-esp-upper-age-limit-on-mortality-statistics.doc&usg=AOvVaw15m0tzEPMrg7CGAPz5vVZq. Accessed 15 July 2016Google Scholar
  5. Niederlaender E. Causes of death in the EU. In: Statistics in focus. European Communities. Luxembourg: Office for Official Publications of the European Communities; 2006. http://ec.europa.eu/eurostat/documents/3433488/5440941/KS-NK-06-010-EN.PDF/2a6372ce-2b38-4b2a-bdb1-0de9cd48fa5c. Accessed 15 July 2016.Google Scholar
  6. Vujcic IS, Sipetic SB, Dubljanin ES, Vlajinac HD. Trends in mortality rates from coronary heart disease in Belgrade (Serbia) during the period 1990-2010: a joinpoint regression analysis. BMC Cardiovasc Disord. 2013;13:112.View ArticleGoogle Scholar
  7. Sans S, Kestoloot H, Force DKBOTT. The burden of cardiovascular diseases mortality in Europe. Eur Heart J. 1997;18:1231–48.View ArticleGoogle Scholar
  8. Yazadanyar A, Newman AB. The burden of cardiovascular disease in the elderly: morbidity, mortality, and costs. Clin Geriatr Med. 2009;25(4):563–vii https://doi.org/10.1016/j.cger.2009.07.007.View ArticleGoogle Scholar
  9. Eurostat EC. Revision of the European Standard Population. Report of Eurostat’s task force. Luxembourg: Publications Office of the European Union; 2013. http://ec.europa.eu/eurostat/documents/3859598/5926869/KS-RA-13-028-EN.PDF/e713fa79-1add-44e8-b23d-5e8fa09b3f8f Accessed 17 JulyGoogle Scholar
  10. Olubenga O. The impact of calculating mortality rates using the 2013 European Standard Population on causes of death. London: Office for National Statistics; 2013.Google Scholar
  11. Nichols M, Townsend N, Scarborough P, Rayner M. Trends in age-specific coronary heart disease mortality in the European Union over three decades: 1980-2009. Eur Heart J. 2013;34:3017–27.View ArticleGoogle Scholar
  12. Pagidipati NJ, Gaziano TA. Estimating deaths from cardiovascular disease: a review of global methodologies of mortality measurement. Circulation. 2013;127:749–56.View ArticleGoogle Scholar
  13. Setal PW, Sankoh O, Roa C, Velkoff VA, Mathers C, Gonghuan Y, Hemed Y, Jha P, Lopez AD. Sample registration of vital events with verbal autopsy: a renewed commitment to measuring and monitoring vital statistics. Bull World Health Organ. 2005;83:611–7.Google Scholar
  14. WHO. WHO methods and data sources for global causes of death 2000–2011. Geneva: Department of Health Statistics and Information Systems, WHO; 2013. http://www.who.int/healthinfo/statistics/GHE_TR2013-3_COD_MethodsFinal.pdf. Accessed 25 June 2016Google Scholar
  15. WHO. European detailed mortality database. Copenhagen: World Health Organization Regional Office for Europe; 2015. https://gateway.euro.who.int/en/datasets/european-mortality-database/. Accessed 25 June 2016

Copyright

© The Author(s). 2019

Advertisement