Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Smoking-attributable morbidity: acute care hospital diagnoses and days of treatment in Canada, 2002

  • Dolly Baliunas1, 2Email author,
  • Jayadeep Patra2,
  • Jürgen Rehm1, 2, 3,
  • Svetlana Popova2 and
  • Benjamin Taylor1, 2
BMC Public Health20077:247

DOI: 10.1186/1471-2458-7-247

Received: 25 January 2007

Accepted: 18 September 2007

Published: 18 September 2007

Abstract

Background

Smoking is one of the most important risk factors for burden of disease. Our objective was to estimate the number of hospital diagnoses and days of treatment attributable to smoking for Canada, 2002.

Methods

Distribution of exposure was taken from a major national survey of Canada, the Canadian Community Health Survey. For chronic diseases, risk relations were taken from the published literature and combined with exposure to calculate age- and sex-specific smoking-attributable fractions (SAFs). For fire deaths, SAFs were taken directly from available statistics. Information on morbidity, with cause of illness coded according to the International Classification of Diseases version 10, was obtained from the Canadian Institute for Health Information.

Results

For Canada in 2002, 339,179 of all hospital diagnoses were estimated to be attributable to smoking and 2,210,155 acute care hospital days. Ischaemic heart disease was the largest single category in terms of hospital days accounting for 21 percent, followed by lung cancer at 9 percent. Smoking-attributable acute care hospital days cost over $2.5 billion in Canada in 2002.

Conclusion

Since the last major project produced estimates of this type, the rate of hospital days per 100,000 population has decreased by 33.8 percent. Several possible factors may have contributed to the decline in the rate of smoking-attributable hospital days: a drop in smoking prevalence, a decline in overall hospital days, and a shift in distribution of disease categories. Smoking remains a significant health, social, and economic burden in Canada.

Background

Smoking is responsible for high levels of morbidity and mortality. Smoking causes substantially increased risk of lung cancer, upper aerodigestive cancer, several other cancers, heart disease, stroke, chronic respiratory disease and a range of other medical conditions[1]. In 1996, a major study estimating the economic costs attributable to substance abuse in Canada (1992 data), was published[2]. As part of the analysis, the numbers of hospital separations and days of hospital treatment that could be attributed to smoking tobacco were estimated to be 208,095 and 3,024,265 respectively. This paper updates the estimates for the year 2002, using age- and sex-specific relative risks from recent meta-analyses and morbidity classified according to the International Classification of Disease version 10 (ICD-10).

Methods

The aim of the present study was to estimate the proportion of acute care hospital diagnoses and hospital days attributable to smoking in Canada for the year 2002.

Identification of diseases and meta-analyses on smoking risk relations

To identify the malignant and non-malignant health conditions for inclusion in the estimate, this analysis was guided by the 2004 Health Consequences of Smoking: A Report from the Surgeon General[1] which considers the following criteria in judgments of causality: consistency, strength of association, specificity, temporality, coherence, dose-response, and experimental evidence. The 2004 Surgeon General's report implemented a standardized, hierarchical language to summarize conclusions about causality, the highest of which is, "evidence is sufficient to infer causality". Only health outcomes for which the previous conclusion was reached for active smoking were included in the present analysis. Additionally, two conditions for which the causal role of passive smoking is conclusive were included.

Once identified, conditions were translated into corresponding ICD-10 codes. Finally, a comprehensive search strategy of current meta-analyses was performed for each disease category and its risk relationship with smoking.

Meta-analyses were identified using the Pubmed and OVID (1966 – January week 3, 2005) databases. Search criteria were: smoking or tobacco, meta-analysis, and each disease category described in this paper.

Meta-analyses that included measures of smoking dose were preferred over those that only used current/former/never categories. However, if relative risks (RRs) for dose-response specific exposures were not found among the meta-analyses, current/former/never or ever/never categories were used. In 16 out of 20 disease categories included for active smokers, dose-response specific RRs were available. In two categories, plus one for smokers aged 65 or older, only current/former/never RRs were available. In two categories, only ever/never RRs were available. Similarly, analyses that included age- and sex-stratified estimates of relative risk were preferred over more crude estimates. Age-specific estimates were available for ischaemic heart disease (IHD), cardiac arrhythmias, heart failure, and cerebrovascular disease. In cases where a more recently published meta-analysis did not exist, the relative risk from English et al [3] was used. When a meta-analysis was published later than 1995, there was usually only one that presented data on smoking dose, so it was used as the source of relative risk. If there was more than one, all were examined, and that of highest quality and the most comprehensive based on age and smoking dose categories was chosen.

The ICD-10 codes of all disease categories related to smoking included in the present analysis are presented in Table 1.
Table 1

Smoking related disease categories and sources of risk relations

Condition

ICD-10 code

Source from meta-analysis or SAF

Mental and behavioural disorders due to use of tobacco [tobacco abuse]

F17

100% SAF per definition

Toxic effect of tobacco and nicotine

T65.2

100% SAF per definition

Oropharyngeal cancer

C00-C14, D00.0

English et al., 1995 [3]

Oesophageal cancer

C15, D00.1

English et al., 1995 [3]

Stomach cancer

C16, D00.2

Tredaniel et al., 1997 [15]

Pancreatic cancer

C25, D01.9

English et al., 1995 [3]

Laryngeal cancer

C32, D02.0

English et al., 1995 [3]

Trachea, bronchus and lung cancers

C33-C34

Simonato et al., 2001 [16]

Cervical cancer

C53, D06

Plummer et al., 2003 [17]

Urinary tract cancer

C64-C68

Zeegers et al., 2000 [18]

Renal cell carcinoma

C64

Hunt, 2005 [19]

Bladder cancer

C67, D09.0

Brennan et al., 2000; 2001 [20,21]

Acute myeloid leukaemia

C92.0

Brownson et al., 1993 [22]

Ischaemic heart disease

I20-I25

Law, 1997 & Law, 2003 [23,24]

Pulmonary circulatory disease

I26-I28

English et al., 1995 [3]

Cardiac arrhythmias

I47-I49

Follow IHD

Heart failure; complications and ill-defined descriptions disease

I50-I51

Follow IHD

Cerebrovascular diseases

I60-I69

English et al., 1995 [3]

Atherosclerosis

I70-I79

English et al., 1995 [3]

Pneumonia & influenza

J10-J18

English et al, 1995 [3]

Chronic obstructive pulmonary disease

J40-J44

Single et al., 1996 [2]

Ulcers

K25-K28

English et al., 1995 [3]

Low birth weight and short gestation

P05-P07

English et al., 1995 [3]

Sudden infant death syndrome

R95

English et al., 1995 [3]

Fires

X00-X09

Council of Canadian Fire Marshals and Fire Commissioners. Annual Report 2000, 2003 [9]

Passive smoking-attributable morbidity was derived by applying sex-specific RRs and rates of morbidity from lung cancer and age- and sex-specific RRs and rates of morbidity from IHD to the population of Canadians who have never smoked but are exposed to environmental tobacco smoke (ETS) in the home from spouses and other sources. RR estimates were obtained from the most comprehensive meta-analyses applicable to Canada. This procedure did not include the effect of ETS exposure on current smokers and thus the total burden of smoking was underestimated.

All RRs used may be obtained from the comprehensive report of this cost study [4].

Prevalence of smoking in Canada

Smoking prevalence for different levels of smoking consumption for Canada as a whole were obtained from the Canadian Community Health Survey 2003 (CCHS cycle 2.1) [5], a population based representative survey conducted by Statistics Canada. All prevalence estimates were sex- and age group-specific. The categorizations of smoking status, however, varied by disease based on the RRs available in the meta-analyses; for example, for COPD, RRs risks were available for current, former and never smokers, thus the prevalence of current, former and never smokers was used. For each disease for which the identified meta-analysis included dose-response-specific RRs, prevalence estimates also were dose-specific (e.g., never, former, current, 1–14, 15–24, 25+ cigarettes per day). Current smokers, those who reported occasional smoking or daily smoking, were further categorized by number of cigarettes per day when sufficient information existed to do so.

The prevalence of non-smokers living inside a home where another person smokes was also available from the CCHS data set and was used to calculate 2002 passive smoking hospital diagnoses and days.

The sample weights provided by Statistics Canada to ensure comparability between the CCHS sample and the Canadian population were used to calculate prevalence based on sex and age groups. The age groups used were 15–29, 30–44, 45–59, 60–69, 70–79, and 80+.

Morbidity data

Acute care hospital diagnoses and days data in Canada for 2002 were obtained from the Canadian Institute for Health Information (CIHI) on national and provincial levels according to ICD-10. For the national level, data were provided for each disease condition as well as for each sex and five-year age group from 0 to 80. However, the national level data were actually composed of only seven provinces and two territories (Alberta, British Columbia, Newfoundland, Northwest Territories, Nova Scotia, Ontario, Prince Edward Island, Saskatchewan, Yukon Territory). Based on these, data for Canada as a whole were estimated using the total population: the disease-specific rate of occurrence observed in the data provided was applied to the total population of Canada to obtain the estimated number of disease-specific occurrences.

The Hospital Morbidity Database (HMDB) held by CIHI captures information on patients separated (through discharge or death) from acute care facilities in Canada. As such, it provides national data on acute care hospitalizations by diagnoses and procedures. Day procedures (e.g., day surgeries), outpatient, and emergency department visits are not captured in this database. Stillborns and cadaveric donor "discharges" are excluded, whereas newborns are included in the HMBD database. Figures are based on facility geography, that is, where the hospital is located (i.e., it may include non-Canadians). Additionally, the statistics reflect the number of hospitalizations, which is somewhat higher than the number of individuals diagnosed since individuals with multiple admissions during a single year would be counted more than once.

Hospital days (Length of Stay) is associated with the condition coded as Most Responsible Diagnosis (MRD) on the patient's hospital record. In other words, the MRD accounts for the majority of a patient's days in hospital. MRD is the one diagnosis that describes the most significant condition of the patient that is responsible for his/her stay in hospital. In a case where multiple diagnoses may be classified as most responsible, coders are instructed to code the diagnosis responsible for the longest length of stay[6]. However, there is still overlap in the database, i.e. more than one diagnosis listed per hospital stay. Thus, to calculate hospital days attributable to tobacco smoking without overlap, the disease-specific hospital days were scaled down by the factor of overall hospital days in Canada divided by the total of the disease-specific hospital days.

Computing smoking-attributable fractions

The smoking-attributable fraction (SAF) is defined as the fraction of the disease in the population that would not have occurred if the effect associated with smoking was absent [7, 8]. SAFs were assessed for different specific causes of illnesses by two methods:

  • chronic disease SAFs were calculated by combining exposure from CCHS and RR estimates from meta-analyses,

  • fire injury was calculated using direct estimates of smoking involvement from the Council of Canadian Fire Marshals and Fire Commissioners[9].

We used the most comprehensive meta-analysis for each condition, as described above (see also Table 1). The RR for each condition was combined with different levels of smoking consumption for each sex and age group and an attributable fraction was obtained using the following formula (see Walter, 1976, 1980).
S A F = i = 1 k P i ( R R i 1 ) i = 0 k P i ( R R i 1 ) + 1 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacqWGtbWucqWGbbqqcqWGgbGrcqGH9aqpdaWcaaqaamaaqahabaGaemiuaa1aaSbaaSqaaiabdMgaPbqabaGcdaqadaqaaiabdkfasjabdkfasnaaBaaaleaacqWGPbqAaeqaaOGaeyOeI0IaeGymaedacaGLOaGaayzkaaaaleaacqWGPbqAcqGH9aqpcqaIXaqmaeaacqWGRbWAa0GaeyyeIuoaaOqaamaaqahabaGaemiuaa1aaSbaaSqaaiabdMgaPbqabaGcdaqadaqaaiabdkfasjabdkfasnaaBaaaleaacqWGPbqAaeqaaOGaeyOeI0IaeGymaedacaGLOaGaayzkaaGaey4kaSIaeGymaedaleaacqWGPbqAcqGH9aqpcqaIWaamaeaacqWGRbWAa0GaeyyeIuoaaaaaaa@54E5@

i: exposure category with baseline exposure or no smoking i = 0.

RRi: relative risk at exposure level i compared to no consumption.

Pi: prevalence of the ith category of exposure.

The SAFs were then applied to the hospital diagnosis and length of stay information to estimate the smoking-attributable morbidity by age and sex. To illustrate this procedure, a simple example follows. For chronic obstructive pulmonary disorder (COPD) the all-age and all-sex RRs for current smokers, and former smokers, relative to never smokers are 9.80, 6.70. The prevalence, with rounding error, of current, former, and never smokers among men aged 45–59 were 26.0, 53.0, and 21.1. Simple algebra produces a SAF of 0.84, which is applied to the 978 hospital diagnoses of COPD among all Canadian men of this age group to determine that 823 of the diagnoses were attributable to smoking (355 and 468 among the current and former smokers respectively). It is notable that although the RR among current smokers is greater than that among former smokers, the greater prevalence of former smokers among men aged 45–59 resulted in a larger smoking-attributable burden of COPD among the former smokers.

Estimating costs of acute care hospital days

Daily average per-capita cost for acute care hospital separations for each available province and territory was obtained from CIHI [10]. For Nunavut, average per-capita cost was not available; therefore, average per-capita cost for Northwest Territories was substituted. To obtain the total costs for each province and territory, daily average per-capita cost was applied to the total number of smoking-attributable acute care hospital days. These numbers were summed to obtain the total for Canada. A similar procedure was followed for those acute care hospital days attributable to alcohol and illegal drugs for comparison purposes.

Results

Table 2 gives an overview of the estimated smoking exposure in Canada by sex and age group. As expected, men smoked more than women on average, and smoking prevalence decreased with age.
Table 2

Smoking status by sex and age group in Canada, 2002

Smoking categories

15–29 years

30–44 years

45–59 years

60–69 years

70–79 years

80+ years

Overall (All ages)

Current

Female

26.3

24.7

23.0

15.1

10.3

5.9

21.8

 

Male

31.0

30.7

26.0

17.2

9.8

7.5

26.3

Former

Female

26.2

38.3

43.5

45.2

42.7

38.9

37.8

 

Male

25.8

38.9

53.0

64.2

70.4

73.5

44.6

Never

Female

47.5

36.9

33.4

39.8

47.1

55.2

40.4

 

Male

43.1

30.4

21.1

18.7

19.7

19.0

29.1

Total per sex

100

100

100

100

100

100

100

Source: CCHS cycle 2.1 (2003)

Table 3 provides the estimates of smoking-attributable hospital diagnoses. Overall, in Canada in 2002, 339,179 hospital diagnoses from acute care facilities were smoking-attributable, accounting for 218,791 hospital diagnoses among men and 120,389 among women. Please note: these numbers were derived by multiplying SAFs with the number of diagnoses for each category, thereby producing numbers with decimals. As a result, there may be rounding errors after collapsing numbers over different categories. Among hospital diagnoses caused by smoking, the three biggest contributors were cardiovascular disease, malignant neoplasms and respiratory disease. Indeed, the single disease category of ischaemic heart disease accounted for 30.3 percent of the smoking-attributable hospital diagnoses (102,704 diagnoses; males: 75,814; females: 26,890). The next largest single categories were cardiac arrythmias (29,623 hospital diagnoses, males: 19,222, females: 10,401), and lung cancer (28,929 hospital diagnoses, males: 18,488, females: 10,441). With respect to age, the overall average age for a smoking-attributable hospital diagnosis was 61.9 years for men and 62.8 years for women. There were notable differences between disease categories. For fire injuries, the average age for a smoking-attributable hospital diagnosis was 44.9 years for men and 53.9 years for women. Smoking-attributable hospital diagnoses due to the toxic effects of tobacco and nicotine occurred at the age of 29.5 years for men and 37.0 years for women.
Table 3

SAFs*, hospital diagnoses and acute care hospital days attributable to smoking for major disease categories in Canada, 2002

Disease condition (for definition by ICD 10 see Table 1)

Number of diagnoses

Hospital days

 

SAF in % (all ages)

mean age at diagnosis

Smoking-attributable diagnoses

SAF in % (all ages)

Smoking-attributable hospital days

 

M

F

M

F

M

F

Overall

M

F

M

F

Overall

ACTIVE SMOKERS

Malignant neoplasms

   Oropharyngeal cancer

58.7

51.3

59.6

60.1

2,128

1,116

3,244

34.8

30.2

13,302

6,125

19,427

   Oesophageal cancer

48.8

40.0

66.4

68.8

1,338

387

1,725

29.4

23.6

9,453

3,140

12,593

   Stomach Cancer

16.4

12.5

67.0

66.1

546

233

780

9.8

7.4

4,308

2,068

6,376

   Pancreatic cancer

17.7

13.4

65.6

67.5

623

478

1,101

10.4

8.0

4,189

3,831

8,021

   Laryngeal cancer

67.7

60.8

65.8

64.2

950

236

1,187

40.4

35.6

7,637

1,815

9,452

   Lung cancer

88.6

63.8

68.6

66.2

18,488

10,441

28,929

53.4

37.9

124,082

75,280

199,362

   Cervical cancer

--

36.4

--

48.5

--

1,381

1,381

--

21.4

--

4,807

4,807

   Urinary tract

55.6

38.3

68.7

68.2

8,336

2,392

10,728

33.2

22.6

38,017

13,149

51,165

   Renal cell carcinoma

26.0

7.5

63.7

62.0

993

176

1,169

15.7

4.2

5,996

1,116

7,112

   Bladder cancer

67.7

52.4

72.5

72.6

7,336

1,832

9,169

40.9

31.3

29,288

8,604

37,892

   Acute myeloid leukemia

21.9

17.7

59.2

56.4

465

310

775

12.8

10.7

4,461

3,316

7,777

   Total malignant neoplasms

    

32,875

16,974

49,849

  

205,449

113,530

318,979

Tobacco abuse

   Tobacco abuse

100.0

100.0

55.6

52.9

4,042

3,481

7,522

100.0

100.0

18,204

15,776

33,979

   Toxic effect of tobacco and nicotine

100.0

100.0

29.5

37.0

7

7

14

100.0

100.0

9

30

39

   Total tobacco abuse

    

4,049

3,488

7,536

  

18,213

15,805

34,018

Cardiovascular diseases

   Ischaemic heart disease

            

   Age < 45 yrs

51.4

44.3

36.6

36.3

6,534

1,758

8,293

30.4

26.5

20,044

6,548

26,593

   45–59 yrs

42.2

37.3

52.0

52.0

32,360

8,979

41,339

25.2

22.3

119,120

36,466

155,586

   60–69 yrs

29.1

23.4

64.5

64.5

22,681

8,294

30,975

17.4

14.0

103,449

42,245

145,694

   70–79 yrs

10.0

7.3

74.5

74.5

9,346

4,518

13,865

6.0

4.3

52,164

26,986

79,150

   80+ yrs

8.9

5.1

87.0

87.0

4,891

3,340

8,232

5.3

3.1

32,243

24,358

56,601

   Pulmonary circulatory disease

81.0

76.4

65.2

65.8

9,251

10,601

19,852

47.9

44.9

81,952

90,735

172,687

   Cardiac arrythmias

            

   Age < 45 yrs

43.6

37.5

33.6

32.9

2,025

1,323

3,348

24.7

20.5

9,158

5,577

14,735

   45–59 yrs

42.2

37.3

52.0

52.0

5,483

2,348

7,832

25.2

22.2

29,911

12,656

42,568

   60–69 yrs

29.1

23.4

64.5

64.5

5,782

2,650

8,432

17.3

13.9

35,626

16,305

51,931

   70–79 yrs

10.0

7.3

74.5

74.5

3,493

2,069

5,562

6.0

4.3

24,437

14,648

39,084

   80+ yrs

8.9

5.1

87.0

87.0

2,439

2,011

4,450

5.3

3.1

19,254

16,975

36,228

   Heart failure

            

   Age < 45 yrs

41.0

31.7

34.1

34.2

1,005

631

1,635

23.5

18.0

6,764

4,771

11,535

   45–59 yrs

42.2

37.3

52.0

52.0

3,841

1,904

5,745

25.2

22.3

24,850

13,435

38,285

   60–69 yrs

29.1

23.4

64.5

64.5

4,553

2,517

7,070

17.4

14.0

31,466

18,134

49,600

   70–79 yrs

10.0

7.3

74.5

74.5

3,008

1,911

4,918

6.0

4.3

22,437

15,173

37,610

   80+ yrs

8.9

5.1

87.0

87.0

2,748

2,319

5,066

5.3

3.1

22,183

20,520

42,703

   Cerebrovascular diseases

            

   Age < 65 yrs

39.1

35.4

52.8

50.5

5,033

3,449

8,482

23.5

21.3

45,470

32,326

77,796

   > = 65 yrs

14.7

10.5

76.9

78.4

5,535

4,113

9,647

8.8

6.2

58,485

48,105

106,589

   Atherosclerosis

33.5

36.9

68.9

69.4

14,036

9,896

23,933

19.8

21.7

109,603

80,842

190,445

   Total cardiovascular diseases

  

62.2

65.2

144,044

74,631

218,675

  

848,617

526,806

1,375,423

Respiratory diseases

   Pneumonia & Influenza

17.3

12.8

69.4

68.3

13,246

8,648

21,894

11.5

8.3

118,770

74,914

193,684

   Chronic obstructive pulmonary disease

82.6

76.9

67.0

66.8

5,268

4,463

9,731

49.3

45.5

32,022

27,608

59,630

   Total respiratory diseases

  

68.7

67.8

18,514

13,111

31,625

  

150,793

102,522

253,315

Intestinal diseases

   Ulcer

47.7

38.4

65.4

68.3

6,237

4,026

10,263

28.8

22.6

45,416

31,551

76,967

Perinatal period

   Low birthweight and short gestation

24.7

20.6

0.0

0.0

6,770

5,057

11,827

14.8

12.3

59,906

42,580

102,485

   Sudden infant death syndrome

31.2

26.5

0.0

0.0

2

1

3

19.6

16.7

2

0

2

   Total perinatal diseases

  

0.0

0.0

6,772

5,059

11,832

  

59,907

42,580

102,487

Injury

   Fire injury

24.6

23.4

44.9

53.9

244

101

346

24.6

24.6

1,529

737

2,266

Total active smokers

  

61.6

62.3

212,735

117,390

330,126

  

1,329,923

833,531

2,163,455

PASSIVE SMOKERS

   Lung cancer

1.6

1.4

66.5

65.2

330

231

561

0.9

0.8

2,163

1,643

3,806

   Ischaemic heart disease

1.8

1.5

64.7

70.5

5,725

2,768

8,493

1.0

0.8

27,073

15,821

42,894

   Total passive smokers

  

64.8

70.1

6,056

2,999

9,054

  

29,235

17,465

46,700

TOTAL SMOKING-ATTRIBUTABLE

  

61.9

62.8

218,791

120,389

339,179

  

1,359,159

850,996

2,210,155

* The SAF (smoking attributable fraction) is the fraction of the disease in the population that would not have occurred if the effect associated with smoking was absent. It is calculated by means of a formula that combines prevalence of smoking and relative risk of a particular disease. The SAF is then applied to the total number of occurrences of disease to estimate the number of occurrences that are attributable to smoking.

Table 3 also provides the estimates of smoking-attributable acute care hospital days. Overall, in Canada in 2002, 2,210,155 hospital days were estimated to be attributable to smoking (males: 1,359,159; females: 850,996). This accounts for 10.3 percent of all acute care hospital days in Canada in 2002. The vast majority (97.9 percent) of these hospital days were due to active, as opposed to passive, smoking. However, only two categories of disease were considered to have sufficient evidence to conclude a causal relationship with passive smoke exposure. As further research is generated, additional disease categories may be broadly recognized, and hence affect future estimates of smoking-attributable morbidity.

Among the acute care hospital days attributable to smoking, the three biggest contributors were cardiovascular disease, malignant neoplasms and respiratory disease. The single disease category that accounted for the most smoking-attributable hospital days was ischaemic heart disease (21.0%; 463,625 hospital days; males: 327,021; females: 136,604). The next largest single categories were lung cancer (9.0%; 199,362 hospital days, males: 124,082; females: 75,280), and pneumonia and influenza (8.8%; 193,684 hospital days; males: 118,770, females: 74,914).

Acute care hospital costs are shown in table 4.
Table 4

Costs of acute care hospital days attributable to smoking, alcohol consumption and illegal drug use in Canada, 2002

 

Acute care hospital days costs (in millions dollars)

Smoking

2551.2

Alcohol consumption

1458.6

Illegal drug use

426.4

Source: Rehm J, Baliunas D, Brochu S, Fischer F, Gnam W, Patra J, Popova S, Sarnocinska-Hart A, Taylor B. The costs of substance abuse in Canada 2002. Canadian Centre on Substance Abuse. Ottawa, 2006. ISBN 1-896323-92-8

Conclusion

Overall, there were 2,210,155 acute care hospital days attributable to smoking, accounting for 10.3 percent of all those in Canada in 2002. At the time of the last cost study (data for 1992) for which similar estimates were produced, the number of acute care hospital days attributed to smoking was higher at 3,024,265, which accounted for 7.3 percent of all acute care hospital days. In considering these numbers, it must be noted that the total number of hospital days due to overall morbidity has decreased due to changes in the Canadian health care system meant to reduce health care expenditures such as progress in treatment associated with a shorter length of stay, and a shift from inpatient to outpatient treatment; the total acute care hospital days decreased from approximately 41.5 million in 1992 to 21.5 million in 2002 [2]. In addition, the size of the population has increased from 28,366,737 in 1992 to 31,372,587 in 2002 [11]. Therefore, in order to get the best sense of the cost of smoking on hospital days, it is most appropriate to consider the rate of hospital days per 100,000 population which has decreased from 10,635 in 1992 to 7,045 in 2002, a decrease of 33.8 percent. Thus, there have been gains made in the health of Canadians with respect to the morbidity due to smoking since the last Canadian cost study.

There are several possible factors that have contributed to the decline of the rate of smoking-attributable hospital days. The proportion of Canadians who are current smokers has decreased. The prevalence of current smoking decreased from 31.1 percent in 1991 to 23.0 percent in 2003 [5, 12]. It may be premature to conclude that the observed decreases in smoking-attributable hospital days have been caused by the decreases in smoking prevalence. Most diseases caused by smoking have a long latent period. Thus, declines in smoking in the last few years would not be expected to produce substantial improvements in the burden of smoking related diseases on the Canadian population for some time.

In addition to the decrease in smoking levels, there have been important shifts in the overall distribution of causes of death in Canada during this period. Mortality due to heart disease has been decreasing for several decades. From 1992 to 1999, the age-standardized mortality rate (standardized by the 1991 Canadian population) decreased from 272.2 to 232.9 per 100,000 population [13]. Ischaemic heart disease was the single greatest cause of smoking-attributable morbidity in both 1992 and 2002, but overall deaths due to ischaemic heart disease, not just those attributable to smoking, have decreased, accounting for 22.1 percent of all deaths in 1992 and 18.2 percent of all deaths in 2002. Morbidity data is not collected in the same manner as mortality data, however according to the Public Health Agency of Canada, among males, the age-standardized hospital separation rate for ischaemic heart disease (standardized by the 1991 Canadian population) decreased from 622.6 to 564.9 per 100,000 in 1999[13]. Further, it should be acknowledged that the decline in heart disease in Canada began prior to recently observed decreases in prevalence of smoking. Similarly, the proportion of smoking-attributable lung cancer hospital days has declined from 14.1 percent to 9.2 percent of the total smoking attributable hospital days. The overall incidence of lung cancer has decreased over recent years. In 1992 the age-standardized incidence rate of lung cancer among males was 90.2 per 100,000 population. By 2002, this had declined to 73.3 per 100,000 population. Among females, the incidence, though lower, has increased from 39.7 to 45.2 per 100,000 population.

Although the same approach was utilized in calculating the smoking-attributable fractions in both 1992 and 2002, different inputs were used. That is, the relative risks that were used to estimate the relationships between smoking and specific health outcomes were updated to reflect recently available literature. Also, this analysis, in determining which health outcomes to include in these estimates, was guided by the report of the Surgeon General and thus included acute myeloid leukaemia but did not include chemotherapy under a separate heading. This may be suspected of causing significant differences in the estimates for the two years, however in one of a number of sensitivity analyses published in a recent article, when 2002 data were analyzed using the 1992 approach in addition to our present approach the estimates were very similar (2,316,166 versus 2,210,155)[14].

The smoking-attributable hospital diagnoses estimates produced in this analysis cannot be compared with the first Canadian cost study, as that work measured hospital separations and not diagnoses.

The burden of smoking-attributable morbidity as measured by hospital diagnoses has decreased substantially since the last Canadian cost study, which estimated the burden of morbidity attributable to smoking in Canada. While this is reason for optimism, smoking continues to present a serious health concern in Canada; smoking causes substantial morbidity in this country, and carries huge humanitarian and financial costs. In 2002, smoking-attributable acute care hospital days alone cost Canadian taxpayers in excess of 2.5 billion dollars[4], far more than alcohol and illegal drug use consumption combined. Given concerns about the increasing cost of the Canadian health care system and the pressures to preserve this same system, here is a viable target for cost savings. Smoking-attributable morbidity is avoidable. Thus, it is vital that policy and policy-makers address this substantial health, social, and economic burden in Canada.

Declarations

Acknowledgements

This contribution was in part enabled by funding for the Second Canadian Study on Social Costs of Substance Abuse from various sources, under the umbrella of the Canadian Centre on Substance Abuse. The lead author, during this work, was supported by an Ontario Tobacco Research Unit Ashley Studentship in Tobacco Control, an Ontario Graduate Scholarship in Science and Technology, and a Canadian Institutes of Health Research Canada Graduate Scholarship Doctoral Award.

Authors’ Affiliations

(1)
Public Health Sciences Department, University of Toronto
(2)
Centre for Addiction and Mental Health
(3)
Research Institute for Public Health and Addiction

References

  1. U.S.Department of Health and Human Services: The health consequences of smoking: a report of the Surgeon General. 2004, Atlanta, GA., Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office of Smoking and Health.Google Scholar
  2. Single E, Robson L, Xie X, Rehm J: The costs of substance abuse in Canada. 1996, Ottawa, Canadian Centre on Substance AbuseGoogle Scholar
  3. English DR, Holman CDJ, Milne E, Winter MJ, Hulse GK, Codde G, Bower CI, Corti B, de Klerk N, Knuiman MW, Kurinczukn JJ, Lewin GF, Ryan GA: The quantification of drug caused morbidity and mortality in Australia 1995. 1995, Canberra, Australia, Commonwealth Department of Human Services and Health.Google Scholar
  4. Rehm J, Baliunas D, Brochu S, Fischer B, Gnam W, Patra J, Popova S, Sarnocinska-Hart A, Taylor B: The costs of substance abuse in Canada 2002. 2006, Ottawa, Canadian Centre on Substance AbuseGoogle Scholar
  5. Canada S: Canadian Community Health Survey, Cycle 2.1 [Catalogue 82M0013XCB]. 2003, Ottawa, Statistics CanadaGoogle Scholar
  6. CIHI - Canadian Institute for Health Information: Data quality documentation: discharge abstract database 2002-2003. 2004, Ottawa, CIHIGoogle Scholar
  7. Walter SD: The estimation of interpretation of attributable risk in health research. Biometrics. 1976, 32: 829-849. 10.2307/2529268.View ArticlePubMedGoogle Scholar
  8. Walter SD: Prevention of multifactorial disease. American Journal of Epidemiology. 1980, 112: 409-416.PubMedGoogle Scholar
  9. Council of Canadian Fire Marshalls and Fire Commissioners: Fire Losses in Canada Annual Report, 2000. 2003, Council of Canadian Fire Marshals and Fire Commissioners.Google Scholar
  10. CIHI - Canadian Institute for Health Information: Canadian MIS database: hospital finance performance indicators 1999-2000 to 2001-2002. 2004, Ottawa, CIHIGoogle Scholar
  11. Canada S: Estimates of population by age and sex for Canada, Provinces and Territories. 2006, Ottawa, Statistics CanadaGoogle Scholar
  12. Canada S: General Social Survey, Cycle 6 (1991)[catalogue 89F0115XIE]. 1992, Ottawa, Statistics CanadaGoogle Scholar
  13. Canada PHA: Cardiovascular disease surveillance on-line. 2006, [http://dsol-smed.phac-aspc.gc.ca/dsol-smed/cvd/index_e.html]Google Scholar
  14. Patra J, Taylor B, Rehm J, Popova S, Baliunas D: Substance-attributable morbidity and mortality changes to Canada's epidemiological profile: measurable differences over a ten-year period. Canadian Journal of Public Health. 2007, 98: 228-234.PubMedGoogle Scholar
  15. Tredaniel J, Boffetta P, Buiatti E, Saracci R, Hirsch A: Tobacco smoking and gastric cancer: review and meta-analysis. International Journal of Cancer. 1997, 72: 573-10.1002/(SICI)1097-0215(19970807)72:4<565::AID-IJC3>3.0.CO;2-O.View ArticleGoogle Scholar
  16. Simonato L, Agudo A, Ahrens W, Benhamou E, Benhamou S, Boffetta P, Brennan P, Darby SC, Forastiere F, Fortes C, Gaborieau V, Gerken M, Gonzales CA, Jockel KH, Kreuzer M, Merletti F, Nyberg F, Pershagen G, Pohlabeln H, Rosch F, Whitley E, Wichmann HE, Zambon P: Lung cancer and cigarette smoking in Europe: an update of risk estimates and an assessment of inter-country heterogeneity. International Journal of Cancer. 2001, 91: 876-887. 10.1002/1097-0215(200102)9999:9999<::AID-IJC1139>3.0.CO;2-7.View ArticlePubMedGoogle Scholar
  17. Plummer M, Herrero R, Franceschi S, Meijer CJ, Snijders P, Bosch FX, de Sanjose S, Munoz N: Smoking and cervical cancer: pooled analysis of the IARC multi-centric case-control study. Cancer Causes & Control. 2003, 14: 805-814. 10.1023/B:CACO.0000003811.98261.3e.View ArticleGoogle Scholar
  18. Zeegers MP, Tan FE, Dorant E, van Den Brandt PA: The impact of characteristics of cigarette smoking on urinary tract cancer risk: a meta-analysis of epidemiologic studies. [Review] [87 refs]. Cancer. 2000, 89: 630-639. 10.1002/1097-0142(20000801)89:3<630::AID-CNCR19>3.0.CO;2-Q.View ArticlePubMedGoogle Scholar
  19. Hunt JD, van der Hel OL, McMillan GP, Boffetta P, Brennan P: Renal cell carcinoma in relation to cigarette smoking: meta-analysis of 24 studies. International Journal of Cancer. 2005, 114: 101-108. 10.1002/ijc.20618.View ArticlePubMedGoogle Scholar
  20. Brennan P, Bogillot O, Cordier S, Greiser E, Schill W, Vineis P, Lopez-Abente G, Tzonou A, Chang-Claude J, Bolm-Audorff U, Jockel KH, Donato F, Serra C, Wahrendorf J, Hours M, t'Mannetje A, Kogevinas M, Boffetta P: Cigarette smoking and bladder cancer in men: a pooled analysis of 11 case-control studies. International Journal of Cancer. 2000, 86: 289-294. 10.1002/(SICI)1097-0215(20000415)86:2<289::AID-IJC21>3.0.CO;2-M.View ArticlePubMedGoogle Scholar
  21. Brennan P, Bogillot O, Greiser E, Chang-Claude J, Wahrendorf J, Cordier S, Jockel KH, Lopez-Abente G, Tzonou A, Vineis P, Donato F, Hours M, Serra C, Bolm-Audorff U, Schill W, Kogevinas M, Boffetta P: The contribution of cigarette smoking to bladder cancer in women (pooled European data). Cancer Causes & Control. 2001, 12: 411-417. 10.1023/A:1011214222810.View ArticleGoogle Scholar
  22. Brownson RC, Novotny TE, Perry MC: Cigarette smoking and adult leukemia: a meta-analysis. Archives of Internal Medicine. 1993, 153: 469-475. 10.1001/archinte.153.4.469.View ArticlePubMedGoogle Scholar
  23. Law MR, Morris JK, Wald NJ: Environmental tobacco smoke exposure and ischaemic heart disease: an evaluation of the evidence.[see comment]. British Medical Journal. 1997, 315: 973-980.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Law MR, Wald NJ: Environmental tobacco smoke and ischemic heart disease. Progress in Cardiovascular Diseases. 2003, 46: 31-38. 10.1016/S0033-0620(03)00078-1.View ArticlePubMedGoogle Scholar
  25. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/7/247/prepub

Copyright

© Baliunas et al; licensee BioMed Central Ltd. 2007

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement