Sentence examples for smoking expenditures from inspiring English sources

The results also indicate that coefficients of smoking expenditures on pipe tobacco, household size, income and region are statistically significant, but the variables for access to markets, jobs and transportation are not significant.

Although a previous study in India has shown a lack of a statistically significant difference in the association of smoking on expenditures for other goods across regions and income groups [ 34], research findings in Taiwan, China, and Bangladesh [ 12, 13, 20] suggest that lower-income households remain at risk for the crowding-out effect of household smoking on spending for other basic needs.

These countries bear almost 40% of the global US$1.4 trillionn cost of smoking from health expenditures and lost productivity.

All models control for age, sex, household income, and highest educational qualification, smoking status, physical activity energy expenditure, car ownership, and supermarket availability.

Smoking not only increases energy expenditure and suppresses appetite, but also is a risk factor for chronic diseases, which may lead to weight loss; 24 however, central weight gain as an effect of smoking may be more common and often associated with other adverse behaviors, such as overeating, irregular eating time, and lack of exercise.

In a multiple linear regression analysis, after adjusting for age, sex, ethnicity, height, smoking status, and daily energy expenditure, each 100-ng/g increase in plasma concentration of p,p´-DDE was associated with an 18.8-mL reduction in mean FVC (p = 0.002) and an 11.8-mL reduction in mean FEV1 (p = 0.013) (Table 3).

After adjusting for age, sex, ethnicity, height, smoking status, and daily energy expenditure, participants with detectable p,p´-DDT had a significantly lower mean FVC (difference = 311 mL; 95% CI: –492, –130; p = 0.003) and FEV1 (difference = 232 mL; 95% CI: –408, –55; p = 0.015) than those with nondetectable p,p´-DDT (Table 3).

Further analysis adjusted for potential mediators: energy intake, basal metabolic rate, obesity, hypertension, lipids, serum uric acid, smoking, energy expenditure, and glycohemoglobin.

Epidemiological and economic models will be used to estimate lifetime gains in QALYs from smoking cessation and savings in health care expenditures [ 33, 35].

A health-economical estimation claimed that 3.3% of total healthcare expenditures in Germany can be attributed to smoking [ 4].

Because the NHI claims database does not contain individuals' smoking statuses, it does not allow for distinguishing health expenditures for smokers from those for non-smokers.