Maternal Smoking & the 1998 Master Settlement Agreement Douglas E. Levy, Ph.D. Ellen R. Meara, Ph.D. Dept. Health Care Policy, Harvard Medical School Support Provided by AHRQ T32-HS00055 & NIA T32-AG00186

Price Responsiveness of Smoking Elasticity of smoking participation Elasticity of smoking participation General population  General population  Pregnant women Pregnant women -0.5 (Evans & Ringel; Natality Files ) -0.5 (Evans & Ringel; Natality Files ) -0.7 (Ringel & Evans; Natality Files ) -0.7 (Ringel & Evans; Natality Files ) -1.0 (Colman et al.; PRAMS data ) -1.0 (Colman et al.; PRAMS data ) The Master Settlement Agreement led to an immediate 22% (45 ¢ ) increase in cigarette prices The Master Settlement Agreement led to an immediate 22% (45 ¢ ) increase in cigarette prices Price increase from MSA could reduce Price increase from MSA could reduce Smoking among pregnant women 10-20% Smoking among pregnant women 10-20% Low birth weight 2-4% Low birth weight 2-4% DID IT? DID IT?

Study Design Examined four outcomes Examined four outcomes Maternal smoking participation and intensity Maternal smoking participation and intensity (# of cigarettes/day) LBW and birth weight in grams LBW and birth weight in grams Used interrupted time-series regressions to determine whether there were important changes in outcomes following the MSA Used interrupted time-series regressions to determine whether there were important changes in outcomes following the MSA Subgroup analyses by mothers’ age, race, education Subgroup analyses by mothers’ age, race, education

Study Data National Vital Statistics Natality Detail Files from 1996 to 2000 National Vital Statistics Natality Detail Files from 1996 to 2000 We exclude We exclude States not reporting maternal smoking (CA, IN, SD, upstate NY) States not reporting maternal smoking (CA, IN, SD, upstate NY) Non-singleton birth Non-singleton birth Mother 44 years old Mother 44 years old Incomplete data on outcomes and demographics Incomplete data on outcomes and demographics 4% had missing data given first three criteria 4% had missing data given first three criteria Control variables: Control variables: calendar month, state, excise taxes, maternal demographics, pregnancy characteristics, prenatal care, heavy alcohol consumption calendar month, state, excise taxes, maternal demographics, pregnancy characteristics, prenatal care, heavy alcohol consumption N = 9,638,863 N = 9,638,863

Study Period Infants conceived from January 1996 to February 2000 Infants conceived from January 1996 to February 2000 Adequately capture pre- and post-MSA trends without picking up later non-price effects of MSA Adequately capture pre- and post-MSA trends without picking up later non-price effects of MSA Exclude infants conceived from March 1998 through November 1998 Exclude infants conceived from March 1998 through November 1998 Avoid pregnancies only partially affected by MSA Avoid pregnancies only partially affected by MSA

Summary Statistics OutcomeAllSmokers Non- Smokers Smoking12.1%100%0% #Cigs/day (sd) 1.3 (4.4) 11.0 (7.4) 0 (0) LBW5.9%10.1%5.3% Birth weight, g (sd) 3352 (572) 3161 (575) 3378 (567)

Maternal Smokers Are… More likely to be white More likely to be white Less likely to have attended college Less likely to have attended college Younger Younger Less likely to be married Less likely to be married Likely to have fewer and later prenatal care visits More likely to have had a prior preterm birth More likely to drink heavily during pregnancy

Regression Analyses Y its =  0 +  time t +  MSA t +  time t *MSA t +  Month t +  Demographics i + u s + e ist Y its =  0 +  time t +  MSA t +  time t *MSA t +  Month t +  Demographics i + u s + e ist Time is monthly count; captures secular trend Time is monthly count; captures secular trend MSA captures immediate changes beginning Nov MSA captures immediate changes beginning Nov Time*MSA captures changes in trend following MSA Time*MSA captures changes in trend following MSA Month captures seasonal variation in outcome Month captures seasonal variation in outcome

Predicted Smoking Prevalence MSA, Nov. 1998

Predicted Smoking Prevalence 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All11.7%11.4%-2.2%p< Hispanic p= yo p<0.0001

Predicted LBW Prevalence 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All6.3%6.2%-1.8%p= Hispanic p= yo p=0.1077

Why So Little Effect? Perhaps remaining smokers are less likely to change habits in response to price hikes Perhaps remaining smokers are less likely to change habits in response to price hikes Perhaps earlier estimates based on changes in state excise taxes were confounded Perhaps earlier estimates based on changes in state excise taxes were confounded Simultaneous changes in attitude towards smoking Simultaneous changes in attitude towards smoking Simultaneous tobacco control legislation Simultaneous tobacco control legislation

Limitations No control group No control group Assumes trend is linear Assumes trend is linear Maternal smoking is self-reported Maternal smoking is self-reported Major states were excluded from the analysis Major states were excluded from the analysis 20% of births during this period 20% of births during this period

Implications Pros of price increases for tobacco control Pros of price increases for tobacco control Young women and their infants may benefit Young women and their infants may benefit Price changes affect most smokers Price changes affect most smokers Cons of price increases for tobacco control Cons of price increases for tobacco control Less effective than commonly believed Less effective than commonly believed Regressive taxation Regressive taxation Next steps Next steps Results in other populations? Results in other populations? Relate to new evidence re: long-run price-responsiveness Relate to new evidence re: long-run price-responsiveness

Predicted Smoking Prevalence 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All11.7%11.4%-2.2%p<  HS p< > HS p= yo p< yo p=0.0219

Predicted Cigarettes/Day 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All %p< White p< Black p= Hispanic p=0.5581

Predicted Cigarettes/Day 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All %p<  HS p< > HS p= yo p< yo p<0.0001

Predicted LBW Prevalence 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All6.3%6.2%-1.8%p= White p= Black p= Hispanic p=0.3726

Predicted LBW Prevalence 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All6.3%6.2%-1.8%p=  HS p= >HS p= yo p= yo p=0.1640

Predicted Birth Weight 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All %p< White p< Black p= Hispanic p=0.6212

Predicted Birth Weight 15mos Post-MSA Population w/o MSA w/MSARel. %  Pr(  MSA =  MSA*time = 0) All %p<  HS p= > HS p< yo p= yo p<0.0092

Cigarette Prices and Taxes