Application of a system dynamics model to inform investment in smoking cessation services in New Zealand.
OBJECTIVE
We estimated the long-term effects of smoking cessation interventions to inform government decision-making regarding investment in tobacco control.


METHODS
We extracted data from the 2006 New Zealand Tobacco Use Survey and other sources and developed a system dynamics model with the iThink computer simulation package. The model derived estimates of population cessation rates from smoking behaviors and applied these over a 50-year period, from 2001 to 2051, under business-as-usual and enhanced cessation intervention scenarios.


RESULTS
The model predicted larger effects by 2051 with the enhanced cessation than with the business-as-usual scenario, including: an 11% greater decline in adult current smoking prevalence (9 versus 10 per 100 people), 16% greater decline in per capita tobacco consumption (370 versus 440 cigarette equivalents per year), and 11% greater reduction in tobacco-attributable mortality (3000 versus 3300 deaths per year).


CONCLUSIONS
The model generated reliable estimates of the effects on health and on tobacco use of interventions designed to enhance smoking cessation. These results informed a decision announced in May 2007 to increase funding for smoking cessation by NZ $42 million over 4 years.
Tobias
Martin I
MI
Ministry of Health, Wellington, New Zealand. martin_tobias@moh.govt.nz
Cavana
Robert Y
RY
Bloomfield
Ashley
A
D000293:Adolescent; D000328:Adult; D003198:Computer Simulation; D006291:Health Policy / Q000191:economics*; D006293:Health Promotion / Q000191:economics; D006801:Humans; D008875:Middle Aged; D009520:New Zealand / Q000453:epidemiology; D015995:Prevalence; D012907:Smoking / Q000453:epidemiology; D016540:Smoking Cessation / Q000191:economics* / Q000379:methods* / Q000706:statistics & numerical data; D000074606:Smoking Prevention; D013598:Systems Theory; D055815:Young Adult
Aust N Z J Public Health. 2007 Jun;31(3):217-23
17679238
Int J Biomed Comput. 1982 Jan;13(1):69-86
7061170
Tob Control. 2007 Apr;16(2):91-5
17400945
Tob Control. 2000 Jun;9(2):228-36
10841861
Am J Public Health. 2008 Mar;98(3):556-9
17901429
Soc Sci Med. 2006 Apr;62(7):1819-30
16182422
Cochrane Database Syst Rev. 2004;(3):CD000146
15266423
Am J Public Health. 2000 Mar;90(3):401-3
10705858
Prev Med. 2005 Feb;40(2):170-80
15533526
Cochrane Database Syst Rev. 2005 Jan 25;(1):CD003999
15674921
Am J Epidemiol. 1998 Aug 1;148(3):249-58
9690361
Risk Anal. 2005 Aug;25(4):801-12
16268930
J Policy Anal Manage. 2004 Aug;23(4):857-72
15499707
Med Care. 2001 Oct;39(10):1131-41
11567175
Am J Public Health. 2006 Mar;96(3):452-8
16449591
Int J Epidemiol. 2005 Oct;34(5):1020-8
16030152
Prev Med. 2005 Jul;41(1):276-83
15917022
Am J Public Health. 2006 Mar;96(3):494-8
16449585
Oncogene. 2002 Oct 21;21(48):7326-40
12379876