Table 1.
Annual Morbidity-Related Productivity Losses (2018 $) Attributable to Cigarette Smoking, U.S.
| Cost category/cigarette smoking status | U.S. total (millions, $) | State total (millions, $) |
U.S. average ($)a | State average ($)a |
||||
|---|---|---|---|---|---|---|---|---|
| Median | Min | Max | Median | Min | Max | |||
|
| ||||||||
| Total morbidityb | ||||||||
| Currently or formerly smoked | 184,912 (125,625–244,254) |
2,697 AL |
291 WY |
16,946 CA |
1,938 (1,317–2,561) |
1,879 NC |
1,363 ID |
3,395 DC |
| Currently smoke | 105,870 (80,609–131,128) |
1,580 CO |
158 VT |
9,034 TX |
2,830 (2,155–3,506) |
2,707 CA |
1,996 ID |
4,974 DC |
| Formerly smoked | 79,042 (45,016–113,126) |
1,021 AL |
119 WY |
8,268 CA |
1,363 (776–1,951) |
1,317 TN |
959 ID |
2,342 DC |
| Absenteeismc | ||||||||
| Currently or formerly smoked | 9,354 (4,048–14,660) |
135 AL |
17 VT |
1,004 CA |
98 (42–154) |
98 LA, WA, NH, MO |
75 FL |
164 DC |
| Currently smoke | 6,661 (3,508–9,813) |
99 AL |
11 VT |
682 CA |
178 (94–262) |
179 NM, OR |
117 MS |
285 DC |
| Formerly smoked | 2,693 (540–4,847) |
37 CT |
6 AK |
322 CA |
46 (9–84) |
45 MA, IL, GA, AK, AZ |
30 ME, MI |
84 DC |
| Presenteeismd | ||||||||
| Currently or formerly smoked | 46,757 (46,477–47,033) |
653 AL |
86 WY |
4,878 CA |
490 (487–493) |
476 MO |
382 WV |
822 DC |
| Currently smoke | 30,510 (30,307–30,711) |
458 AL |
49 VT |
2,939 CA |
816 (810–821) |
785 OH, OR |
559 WV |
1,338 DC |
| Formerly smoked | 16,246 (16,170–16,323) |
227 OR |
29 WY |
1,938 CA |
280 (279–281) |
266 OH, OR |
197 MS |
478 DC |
| Home productivitye | ||||||||
| Currently or formerly smoked | 12,791 (7,163–18,420) |
188 OR |
24 VT |
1,354 CA |
134 (75–193) |
128 WY, AZ, WV |
105 SD |
239 DC |
| Currently smoke | 6,759 (4,438–9,079) |
106 CO |
10 VT |
594 CA |
181 (119–243) |
173 HI |
138 SD |
343 DC |
| Formerly smoked | 6,033 (2,725–9,340) |
82 CT |
11 WY |
760 CA |
104 (47–161) |
97 NV |
80 SD |
170 DC |
| Inability to workf | ||||||||
| Currently or formerly smoked | 116,010 (67,937–164,141) |
1,686 CO |
161 WY |
10,314 TX |
1,216 (712–1,721) |
1,189 IN |
766 ID |
2,170 DC |
| Currently smoke | 61,941 (42,356–81,525) |
863 AZ |
87 VT |
5,671 TX |
1,656 (1,132–2,180) |
1,573 IA, SD |
1,014 ID |
3,008 DC |
| Formerly smoked | 54,069 (25,581–82,616) |
708 AL |
73 WY |
5,248 CA |
932 (441–1,425) |
899 OK |
595 NM |
1,611 DC |
Note: Values in parentheses are 95% prediction intervals calculated on the basis of 95% CIs of regression-based estimates.
Per adult who smoked cigarettes.
Total morbidity costs attributable to cigarette smoking were computed as the sum of the absenteeism, presenteeism, household productivity, and inability to work costs. The total morbidity cost per adult who smoked cigarettes was computed by dividing the total morbidity cost by the number of adults who smoked cigarettes.
Absenteeism costs attributable to cigarette smoking were computed by multiplying the total missed workdays attributable to cigarette smoking by daily earnings. A standard negative binomial regression, which controlled for sociodemographic factors, was used with the 2014–2018 NHIS data to estimate the missed workdays attributable to cigarette smoking. Daily earnings were computed by dividing annual earnings, available from the CPS Table Creator, by 250 days. The total absenteeism cost per adult who smoked cigarettes was computed by dividing the total absenteeism cost by the number of adults who smoked cigarettes.
Presenteeism costs attributable to cigarette smoking were computed by multiplying the total presenteeism days (250 days minus missed workdays among adults who smoked cigarettes obtained from the 2014–2018 NHIS data) by daily earnings. To estimate presenteeism days per adult who smoked cigarettes, the authors assumed a 1.685% presenteeism rate for adults who currently smoke cigarettes and a 0.66% presenteeism rate for adults who formerly smoked cigarettes, per Bunn et al. (2006).4 The presenteeism cost per adult who smoked was computed by dividing the total presenteeism cost by the number of adults who smoked cigarettes.
Home productivity costs attributable to cigarette smoking were computed by multiplying the total number of bed days attributable to cigarette smoking by the dollar value of housework, available from the 2018 Expectancy Data. A standard negative binomial regression, which controlled for sociodemographic factors, was used with the 2014–2018 NHIS data to estimate the number of bed days attributable to cigarette smoking. The home productivity cost per adult who smoked a cigarette was computed by dividing the total home productivity cost by the number of adults who smoked cigarettes.
Inability to work costs attributable to cigarette smoking were computed by multiplying the total number of adults who smoked cigarettes and who were unable to work by annual earnings. A logistic regression model, which controlled for sociodemographic factors, was used with the 2014–2018 NHIS data to estimate the percentage of adults who smoked cigarettes and who were unable to work or the total number of adults who smoked a cigarette and were unable to work. The inability to work cost per adult who smoked cigarettes was computed by dividing the total inability to work cost by the number of adults who smoked cigarettes.
AK, Alaska; AL, Alabama; AZ, Arizona; CA, California; CO, Colorado; CPS, Current Population Survey; CT, Connecticut; DC, District of Columbia; FL, Florida; GA, Georgia; HI, Hawaii; IA, Iowa; ID, Idaho; IL, Illinois; IN, Indiana; LA, Louisiana; MA, Massachusetts; Max, maximum; ME, Maine; MI, Michigan; Min, minimum; MO, Missouri; MS, Mississippi; NC, North Carolina; NH, New Hampshire; NHIS, National Health Interview Survey; NM, New Mexico; NV, Nevada; OH, Ohio; OK, Oklahoma; OR, Oregon; SD, South Dakota; TN, Tennessee; TX, Texas; VT, Vermont; WA, Washington; WV, West Virginia.