Background

Children exposed to secondhand smoke (SHS) have higher rates of behavioral and cognitive effects, including attention deficit hyperactivity disorder (ADHD), but the costs to the health care and education systems have not been estimated. We estimate these costs for school-aged children aged 5-15.

Methods

The relative risk (RR) of ADHD from SHS exposure was obtained from our previous work. SHS exposure was measured using 2 alternative approaches--reported exposure and serum cotinine-measured exposure. RRs and SHS exposure were used to determine the number of children with SHS-attributable ADHD, and mean costs of ADHD-related health care and education services were applied to obtain SHS-attributable health care and education costs.

Results

Annual health care costs of SHS-attributable ADHD ranged from $644 million (using reported SHS exposure) to $2.05 billion (using cotinine-measured exposure). SHS-attributable costs to the education system ranged from $2.90 to $9.23 billion.

Conclusions

The costs of SHS-attributable ADHD to the education system may total more than 4 times the costs for health care. The huge economic impact of SHS exposure on the education system has not been documented previously, and suggests that reducing childhood exposure to tobacco smoke will release substantial funds that could be used for general education of all children.

This study presents self-reported and serum cotinine measures of exposure to secondhand smoke (SHS) for nonsmoking children, adolescents, and adults. Estimates are disaggregated by time periods and sociodemographic characteristics based on analyses of the 1999-2006 National Health and Nutrition Examination Survey. Self-reported exposure rates are found to be highest for children, followed by adolescents and adults. Important differences in exposure are found by socioeconomic characteristics. Using serum cotinine to measure exposure yields much higher prevalence rates than self-reports. Rates of SHS exposure remain high, but cotinine levels are declining for most groups.

Objective

Healthcare and mortality costs of secondhand smoke (SHS) exposure at home among non-smokers in California were estimated for the year 2009.

Methods

Costs were estimated with an epidemiological model using California SHS home exposure rates and published relative risks. Healthcare costs included nine conditions, and mortality was estimated for four perinatal and three adult conditions. Three mortality-related measures were estimated: deaths, years of potential life lost (YPLL) and the value of lost productivity.

Results

SHS-attributable healthcare costs totalled over $241 million. The most costly conditions for children and adolescents were attention deficit hyperactivity disorder ($7.8 million) and middle ear disease ($5.6 million). For adults, the most costly conditions were ischaemic heart disease (IHD) ($130.0 million) and asthma ($67.4 million). Deaths of 821 Californians were attributable to SHS exposure in the home, including 27 infants whose mothers smoked while pregnant and 700 adults who died from IHD. These deaths represented a loss of over 13 000 YPLL and $119 million in lost productivity.

Conclusions

The economic impact of SHS exposure in the home totalled $360 million in California in 2009. Policies that reduce exposure to SHS at home have great potential for reducing healthcare and mortality costs.

Introduction

The economic impact of smoking, including healthcare costs and the value of lost productivity due to illness and mortality, was estimated for California for 2009.

Methods

Smoking-attributable healthcare costs were estimated using a series of econometric models that estimate expenditures for hospital care, ambulatory care, prescriptions, home health care, and nursing home care. Lost productivity due to illness was estimated using an econometric model predicting how smoking status affects the number of days lost from work or other activities. The value of lives lost from premature mortality due to smoking was estimated using an epidemiological approach.

Results

Almost 4 million Californians still smoke, including 146 000 adolescents. The cost of smoking in 2009 totaled $18.1 billion, including $9.8 billion in healthcare costs, $1.4 billion in lost productivity from illness, and $6.8 billion in lost productivity from premature mortality. This amounts to $487 per California resident and $4603 per smoker. Costs were greater for men than for women. Hospital costs comprised 44% of healthcare costs.

Conclusions

Despite extensive efforts at tobacco control in California, healthcare and lost productivity costs attributable to smoking remain high. Compared to costs for 1999, the total cost was 15% greater in 2009. However, after adjusting for inflation, real costs have fallen by 13% over the past decade, indicating that efforts have been successful in reducing the economic burden of smoking in the state.

Introduction

Baseline abstinence goal is a robust predictor of cigarette abstinence. However, important questions about goal remain unanswered. These include variables correlating with goal, changes in goal, relationship of goal and abstinence status over time, and predictors of change. The current study aimed to address these questions.

Method

Participants were treatment-seeking volunteers in two clinical trials. In Clinical Trial 1 (N=402), participants smoked ≥10 cigarettes per day (CPD) and were ≥50years of age. In Clinical Trial 2 (N=406), participants smoked ≥10 CPD, smoked within 30min of arising, and were ≥18years of age. The outcome variables were biochemically verified 7-day abstinence from cigarettes at weeks 12, 24, 52, and 104. Abstinence goal, demographic, psychological, and smoking related variables were assessed via standard instruments.

Results

At baseline, the greater the desire to quit and one's expectations of success, and the lesser the educational level, the more likely participants were to have a quit forever goal. Throughout the two-year study, abstinence from cigarettes and a lower educational level were correlated with a goal of quit forever; 37% of participants changed goal. There were no predictors of goal change. Abstinence goal was related to abstinence status across the study period. The goal predicted abstinence status at subsequent assessments, even when status was controlled.

Conclusion

Lesser educational levels were consistent predictors of a more stringent goal. Abstinence goal changes over time. These findings suggest that repeated counseling about goal is advisable and participants would benefit from such counseling, independent of demographic characteristics and smoking status.