Epidemiological patterns of extra-medical drug use in the United States: Evidence from the National Comorbidity Survey Replication, 2001–2003
Open accessAbstract
Background In 1994, epidemiological patterns of extra-medical drug use in the United States were estimated from the National Comorbidity Survey. This paper describes such patterns based upon more recent data from the National Comorbidity Survey Replication (NCS-R).Methods The NCS-R was a nationally representative face-to-face household survey of 9282 English-speaking respondents, aging 18 years and older, conducted in 2001-2003 using a fully structured diagnostic interview, the WHO Composite International Diagnostic Interview (CIDI) Version 3.0.Results The estimated cumulative incidence of alcohol use in the NCS-R was 92%; tobacco, 74%; extra-medical use of other psychoactive drugs, 45%; cannabis, 43% and cocaine, 16%. Statistically robust associations existed between all types of drug use and age, sex, income, employment, education, marital status, geography, religious affiliation and religiosity. Very robust birth cohort differences were observed for cocaine, cannabis, and other extra-medical drug use, but not for alcohol or tobacco. Trends in the estimated cumulative incidence of drug use among young people across time suggested clear periods of fluctuating risk.Conclusions These epidemiological patterns of alcohol, tobacco, and other extra-medical drug use in the United States in the early 21st century provide an update of NCS estimates from roughly 10 years ago, and are consistent with contemporaneous epidemiological studies. New findings on religion and religiosity, and exploratory data on time trends, represent progress in both concepts and methodology for such research. These estimates lead to no firm causal inferences, but contribute to a descriptive epidemiological foundation for future research on drug use and dependence across recent decades, birth cohorts, and population subgroups.
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TL;DR
Using the National Comorbidity Survey Replication (NCS-R, 2001–2003), this paper updates 1990–1992 NCS estimates of cumulative incidence of extra-medical drug use in the US, reporting 92% for alcohol, 74% for tobacco, 45% for any extra-medical drug use, 43% for cannabis, and 16% for cocaine. Strong birth-cohort differences appeared for cocaine, cannabis, and other extra-medical drugs but not for alcohol or tobacco, and drug use was robustly associated with age, sex, income, employment, education, marital status, geography, religion, and religiosity.
Key findings
- Cumulative incidence in the NCS-R Part II sample (n = 5,692): alcohol 92.0%, tobacco 73.6%, any extra-medical drug use excluding alcohol and tobacco 44.5%, cannabis 42.7%, cocaine 16.4%.
- Birth-cohort variation was pronounced for drugs other than alcohol and tobacco: any extra-medical drug use rose from 7.4% in the 1904–1942 cohort to 60.7% (1958–1972) and 54.9% (1973–1984); cannabis from 6.4% to 58.1% and 53.2%; cocaine peaked in the 1958–1972 cohort at 27.5% versus 16.3% in 1973–1984 and 1.1% in 1904–1942. Tobacco showed no cohort variation (χ² = 1.6, p = 0.653).
- Males were more likely than females to have used every drug type (e.g., female OR = 0.5 for alcohol, tobacco, any extra-medical drug, and cannabis; 0.4 for cocaine). Those with no religious affiliation were more likely than Mainline Protestants to have used cannabis, cocaine, and extra-medical drugs generally (OR = 1.4–2.0, p<0.05); low importance of religion was associated with higher odds of use across drug types.
- Exploratory time-trend analyses (1955–2001) showed the estimated cumulative incidence of extra-medical drug use among 16–21 year olds rising to about 41% by 1979, declining from the mid-1980s, and increasing again from 1995; tobacco among 13–19 year olds fell from 43% (1955) to 37% (1996), and alcohol among 14–19 year olds rose from 39% (1955) to about 60% in the mid-1980s before falling to roughly 50% by 1996.
Methods
- NCS-R: nationally representative face-to-face household survey of 9,282 English-speaking respondents ages 18+ in the coterminous US, conducted February 2001–April 2003 via computer-assisted personal interviews using the WHO Composite International Diagnostic Interview (CIDI) Version 3.0; participation level 71%. Drug-use items were administered to the Part II subsample (n = 5,692), selected by stratified enrichment and reweighted.
- Cumulative incidence proportions (lifetime history of ever-use) were estimated for alcohol, tobacco, any extra-medical drug use excluding alcohol and tobacco, cannabis, and cocaine, with Taylor series linearization standard errors in SUDAAN; bivariate and covariate-adjusted logistic regressions produced odds ratios with 95% CIs.
- Exploratory time-trend analyses used retrospectively recalled age of onset in discrete-time survival models (person-year unit, covariates for age, sex, race-ethnicity), with drug-specific age bands from the interquartile range of initiation (tobacco 13–19, alcohol 14–19, cannabis 16–21, cocaine 19–26, any extra-medical drug 16–21).
Limitations
- Stated: the 71% participation level, though non-response adjustment weights were applied because initial decliners reported higher drug use; cross-sectional samples are subject to selective attrition including drug-related excess mortality; age of first use is right-censored for younger cohorts; and retrospective recall of age of first use may be biased (though rank ordering of drugs appears stable).
- Stated: the authors note these biases are unlikely to fully explain the observed trends, citing consistency with other US and Australian studies, contrasting trends across drug types, and correspondence with drug-market data.
- Evident from the text: estimates are descriptive and the authors explicitly state they "lead to no firm causal inferences"; the time-trend analyses are labeled exploratory, and the paper notes uncertainty about whether increased use implies increased problems or dependence.
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- Findingown data
After covariate adjustment, inverse associations existed between completion of college and cocaine use (p<0.05).
“The picture changed with covariate adjustment, as shown in [Table 4](#T4), where inverse associations existed between completion of college and cocaine use (p<0.05).”
Quote in the paperNot a substantial claim - Findingown data
The estimated cumulative incidence of tobacco use in the NCS-R (US, 2001-2003) was 74%.
“The estimated cumulative incidence of alcohol use in the NCS-R was 92%; tobacco, 74%; extra-medical use of other psychoactive drugs, 45%; cannabis, 43%; and cocaine, 16%.”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, non-Hispanic Blacks were less likely than non-Hispanic Whites to have started smoking tobacco (OR = 0.7; p<0.05).
“c) persons of Hispanic origin, as well as non-Hispanic Blacks, were less likely than non-Hispanic Whites to have started smoking tobacco (OR = 0.6; p<0.05; OR = 0.7; p<0.05, respectively) ([Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
The estimated cumulative incidence of alcohol use in the NCS-R (US, 2001-2003) was 92%.
“The estimated cumulative incidence of alcohol use in the NCS-R was 92%; tobacco, 74%; extra-medical use of other psychoactive drugs, 45%; cannabis, 43%; and cocaine, 16%.”
Quote in the paperNot a substantial claim - Findingown data
In bivariate analyses, the OR for any extra-medical drug use was inverse for persons who did not attend college.
“Based upon estimates from the bivariate analyses, persons who did not attend college were more likely to have started tobacco smoking, whereas they were less likely to have consumed alcohol or cannabis; the OR for any extra-medical drug use was also inverse ([Table 3](#T3)).”
Quote in the paperNot a substantial claim
- Findingown data
In bivariate analyses, persons who did not attend college were more likely to have started tobacco smoking.
“Based upon estimates from the bivariate analyses, persons who did not attend college were more likely to have started tobacco smoking, whereas they were less likely to have consumed alcohol or cannabis; the OR for any extra-medical drug use was also inverse ([Table 3](#T3)).”
Quote in the paperNot a substantial claim - Findingown data
The estimated cumulative incidence of cannabis use in the NCS-R (US, 2001-2003) was 43%.
“The estimated cumulative incidence of alcohol use in the NCS-R was 92%; tobacco, 74%; extra-medical use of other psychoactive drugs, 45%; cannabis, 43%; and cocaine, 16%.”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, non-Hispanic Whites were most likely to have engaged in extra-medical use of other drugs compared to other race-ethnicity subgroups.
“The picture changed when covariate terms were added to the models ([Table 4](#T4)), namely: a) non-Hispanic Whites were most likely to have engaged in extra-medical use of other drugs compared to other race-ethnicity subgroups;”
Quote in the paperSubstantial claim - Findingown data
In the NCS-R, males were more likely than females to have become users of all drug types examined.
“males were more likely than females to have become users of all drug types”
Quote in the paperNot a substantial claim - Findingown data
The estimated cumulative incidence of cocaine use in the NCS-R (US, 2001-2003) was 16%.
“The estimated cumulative incidence of alcohol use in the NCS-R was 92%; tobacco, 74%; extra-medical use of other psychoactive drugs, 45%; cannabis, 43%; and cocaine, 16%.”
Quote in the paperNot a substantial claim - Findingown data
In bivariate logistic regression analyses of NCS-R data, non-Hispanic Black participants and those in the 'Other' race-ethnicity category (primarily Asian-Americans) were less likely than non-Hispanic Whites to have become users of alcohol or tobacco.
“On a bivariate level, participants identifying as non-Hispanic Blacks and those in the ‘Other’ category (primarily Asian-Americans) were less likely than non-Hispanic Whites to have become users of alcohol or tobacco, but few other differences were observed ([Table 3](#T3)).”
Quote in the paperNot a substantial claim - Findingown data
The estimated cumulative incidence of extra-medical use of psychoactive drugs other than alcohol and tobacco in the NCS-R (US, 2001-2003) was 45%.
“The estimated cumulative incidence of alcohol use in the NCS-R was 92%; tobacco, 74%; extra-medical use of other psychoactive drugs, 45%; cannabis, 43%; and cocaine, 16%.”
Quote in the paperNot a substantial claim - Findingown data
In the NCS-R, there was no birth-cohort-related variation in tobacco use.
“For tobacco, there was no such cohort-related variation”
Quote in the paperNot a substantial claim - Findingown data
In bivariate analyses, persons who did not attend college were less likely to have consumed alcohol or cannabis.
“Based upon estimates from the bivariate analyses, persons who did not attend college were more likely to have started tobacco smoking, whereas they were less likely to have consumed alcohol or cannabis; the OR for any extra-medical drug use was also inverse ([Table 3](#T3)).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, persons of Hispanic origin were less likely than non-Hispanic Whites to have started smoking tobacco (OR = 0.6; p<0.05).
“c) persons of Hispanic origin, as well as non-Hispanic Blacks, were less likely than non-Hispanic Whites to have started smoking tobacco (OR = 0.6; p<0.05; OR = 0.7; p<0.05, respectively) ([Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
In the NCS-R, statistically robust associations existed between all types of drug use and age, sex, income, employment, education, marital status, geography, religious affiliation and religiosity.
“Statistically robust associations existed between all types of drug use and age, sex, income, employment, education, marital status, geography, religious affiliation and religiosity.”
Quote in the paperSubstantial claim - Findingown data
After covariate adjustment, those who had never been married were less likely to have started engaging in drinking, tobacco smoking, or any extra-medical drug use.
“Those who had never been married as of the time of interview were *less* likely to have started engaging in drinking, tobacco smoking, or any extra-medical drug use, whereas those who had been separated or divorced generally were *more* likely to have become extra-medical drug users; the only exception was observed in relation to alcohol ([Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, those in the 'Other' race-ethnicity category had less experience with alcohol (adjusted OR = 0.4; p<0.05).
“b) those in the ‘Other’ category had less experience with alcohol (adjusted OR = 0.4; p<0.05),”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, marital status was more strongly associated with drug use than in bivariate analysis.
“Marital status was more strongly associated with drug use after covariate adjustment ([Table 4](#T4)), as compared to the bivariate OR estimate shown in [Table 3](#T3).”
Quote in the paperNot a substantial claim - Findingown data
By age 21, an estimated 1% of the 1904-1942 cohort had started cannabis use.
“In contrast, only an estimated 1% of the 1904–1942 cohort had started cannabis use by this age, and 68% had tried alcohol.”
Quote in the paperSubstantial claim - Findingown data
Exploratory analyses of time trends in the estimated cumulative incidence of use among young people passing through intervals of risk indicated robust increases in the likelihood of drug use initiation across the past half century.
“Exploratory analyses of time trends in the estimated cumulative incidence of use among young people passing through intervals of risk indicated robust increases in the likelihood of drug use initiation across the past half century.”
Quote in the paperSubstantial claim - Findingown data
Covariate-adjusted estimates showed an excess incidence of extra-medical drug use in the northeast region relative to the southern region (OR = 1.7 for cannabis, 1.4 for cocaine).
“Covariate-adjusted estimates also showed an excess incidence of extra-medical drug use in the northeast region relative to the southern region (e.g. [Table 4](#T4): OR = 1.7 for cannabis, 1.4 for cocaine).”
Quote in the paperSubstantial claim - Findingown data
By age 15, under 1% of the 1904-1942 cohort had used cannabis.
“More pronounced cohort-associated variations existed with respect to cumulative proportions estimated for starting drug use by age 15 years: in the 1973–1984 cohort, roughly one third had used alcohol (38%), and 14% had used cannabis; among the 1904–1942 cohort, under 1% had used cannabis, and 23% had used alcohol.”
Quote in the paperNot a substantial claim - Findingown data
Cumulative incidence of tobacco use by age 21 was similar across all birth cohorts.
“The cumulative incidence of tobacco use was similar across all birth cohorts by this age.”
Quote in the paperNot a substantial claim - Findingown data
For extra-medical use of drugs other than alcohol and tobacco, the interquartile range for age of initiation of use was 16-21 years.
“For extra-medical use of drugs other than alcohol and tobacco, the interquartile range for age of initiation of use was 16–21 years.”
Quote in the paperNot a substantial claim - Findingown data
For cocaine, cumulative incidence was 16% in both surveys.
“For other drugs, the corresponding pairs of estimates were as follows: tobacco smoking (74% vs. 76%); any extra-medical use of psychoactive drugs, 45% vs. 51%; cannabis, 43% vs. 46%; and cocaine, 16% (both surveys).”
Quote in the paperNot a substantial claim - Findingown data
In 1955, an estimated 43% of 13-19 year olds had become tobacco smokers.
“For tobacco, the interquartile range for initiation of smoking was 13–19 years, and in 1955, an estimated 43% of young people in this age range had become tobacco smokers.”
Quote in the paperNot a substantial claim - Findingown data
By age 21, 52% of the youngest cohort (1973-1984) had used cannabis.
“By the time they had turned 21 years, half of the youngest cohort (1973–1984) had used cannabis (52%), and 89% had used alcohol.”
Quote in the paperSubstantial claim - Findingown data
After covariate adjustment, cumulative incidence of tobacco smoking was inversely associated with the 'Other' religion category (OR = 0.5; p<0.05).
“Also shown in [Table 4](#T4), the cumulative incidence of tobacco smoking was inversely associated with being affiliated with Black Protestantism (aOR = 0.5; p<0.05) and with the ‘Other’ religion category (OR = 0.5; p<0.05).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, compared to those attending school or working for pay, homemakers were less likely to have started drinking alcohol (OR = 0.5; p<0.05).
“With covariate adjustment, compared to those attending school or working for pay, persons who classified themselves as homemakers were less likely to have started drinking alcohol (OR = 0.5; p<0.05; [Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
By age 15, 38% of the 1973-1984 cohort had used alcohol.
“More pronounced cohort-associated variations existed with respect to cumulative proportions estimated for starting drug use by age 15 years: in the 1973–1984 cohort, roughly one third had used alcohol (38%), and 14% had used cannabis; among the 1904–1942 cohort, under 1% had used cannabis, and 23% had used alcohol.”
Quote in the paperNot a substantial claim - Findingown data
Cumulative incidence of cocaine use tended to follow the rural-urban gradient, with residents of cities and suburbs being some 4-5 times more likely to have started using cocaine as compared to rural residents.
“Cumulative incidence of cocaine use tended to follow the rural-urban gradient, with residents of cities and suburbs being some 4–5 times more likely to have started using cocaine, as compared to rural residents.”
Quote in the paperNot a substantial claim - Findingown data
By age 21, 68% of the 1904-1942 cohort had tried alcohol.
“In contrast, only an estimated 1% of the 1904–1942 cohort had started cannabis use by this age, and 68% had tried alcohol.”
Quote in the paperNot a substantial claim - Findingown data
By age 15, 14% of the 1973-1984 cohort had used cannabis.
“More pronounced cohort-associated variations existed with respect to cumulative proportions estimated for starting drug use by age 15 years: in the 1973–1984 cohort, roughly one third had used alcohol (38%), and 14% had used cannabis; among the 1904–1942 cohort, under 1% had used cannabis, and 23% had used alcohol.”
Quote in the paperNot a substantial claim - Findingown data
This drug was typically cannabis.
“This drug was typically cannabis (which followed an extremely similar trend).”
Quote in the paperNot a substantial claim - Findingown data
By 1979, an estimated 41% of 16-21 year olds had become a user of one or more of the drugs in this category.
“In 1957, it was rare for individuals in that age range to have engaged in extra-medical use of these drugs, but the estimated cumulative incidence proportion grew substantially such that by 1979, an estimated 41% of 16–21 year olds in that year had become a user of one or more of the drugs in this category ([Figure 2](#F2)).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, those of 'Other' religions had reduced risk of starting to drink compared to Mainline Protestants (OR = 0.2; p<0.05).
“Covariate-adjusted excess risk of having used alcohol was found among Catholics (OR = 1.9; p<0.05) and a reduced risk of starting to drink was found among those of ‘Other’ religions (e.g., Islam; OR = 0.2; p<0.05; [Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, retirees were less likely to have started smoking cannabis (OR = 0.4; p<0.05).
“Retirees were less likely to have started smoking cannabis (OR = 0.4; p<0.05) or to have become extra-medical drug users (OR = 0.5; p<0.05).”
Quote in the paperNot a substantial claim - Findingown data
Alcohol use gradually increased to around 60% in the mid-1980s.
“For alcohol, a curvilinear trend was evident: in 1955, an estimated 39% of 14–19 year olds had begun alcohol use, gradually increasing to around 60% in the mid-1980s; this estimated proportion decreased such that among 14–19 year olds in 1996, roughly 50% had begun alcohol use.”
Quote in the paperNot a substantial claim - Findingown data
Those living in rural areas were just as likely to have started drinking alcohol or smoking tobacco as those living closer to, or in, 'central cities'.
“With respect to the rural-urban gradient, those living in rural areas were just as likely to have started drinking alcohol or smoking tobacco, as those living closer to, or in, ‘central cities’ ([Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
Those with the highest incomes were most likely to have engaged in extra-medical use of all drug types except cocaine.
“The association between income level and cumulative incidence of extra-medical drug use was positive, and although with covariate adjustment, the inverse associations became less statistically robust, the same general pattern was present: those with the highest incomes were most likely to have engaged in extra-medical use of all drug types but for cocaine (where the number of users was smallest ([”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, those with no current religious affiliation were more likely than Mainline Protestants to have started to use cannabis, cocaine, and extra-medical drug use generally (OR = 1.4-2.0, p<0.05).
“The only statistically robust variation with respect to extra-medical drug use concerned those who had no current religious affiliation: this group was more likely than Mainline Protestants to have started to use cannabis, cocaine, and extra-medical drug use generally (OR = 1.4–2,0, p<0.05; [Table 4](#T4)).”
Quote in the paperSubstantial claim - Findingown data
The association between income level and cumulative incidence of extra-medical drug use was positive.
“The association between income level and cumulative incidence of extra-medical drug use was positive, and although with covariate adjustment, the inverse associations became less statistically robust, the same general pattern was present: those with the highest incomes were most likely to have engaged in extra-medical use of all drug types but for cocaine (where the number of users was smallest ([”
Quote in the paperNot a substantial claim - Findingown data
For tobacco smoking, cumulative incidence was 74% in NCS and 76% in NCS-R.
“For other drugs, the corresponding pairs of estimates were as follows: tobacco smoking (74% vs. 76%); any extra-medical use of psychoactive drugs, 45% vs. 51%; cannabis, 43% vs. 46%; and cocaine, 16% (both surveys).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, Catholics had excess risk of having used alcohol compared to Mainline Protestants (OR = 1.9; p<0.05).
“Covariate-adjusted excess risk of having used alcohol was found among Catholics (OR = 1.9; p<0.05) and a reduced risk of starting to drink was found among those of ‘Other’ religions (e.g., Islam; OR = 0.2; p<0.05; [Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, retirees were less likely to have become extra-medical drug users (OR = 0.5; p<0.05).
“Retirees were less likely to have started smoking cannabis (OR = 0.4; p<0.05) or to have become extra-medical drug users (OR = 0.5; p<0.05).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, cumulative incidence of tobacco smoking was inversely associated with being affiliated with Black Protestantism (aOR = 0.5; p<0.05).
“Also shown in [Table 4](#T4), the cumulative incidence of tobacco smoking was inversely associated with being affiliated with Black Protestantism (aOR = 0.5; p<0.05) and with the ‘Other’ religion category (OR = 0.5; p<0.05).”
Quote in the paperNot a substantial claim - Findingown data
After covariate adjustment, individuals in 'Other' employment sub-categories were just as likely as the 'Working/student' subgroup to have started drinking alcohol.
“Individuals classifying themselves in ‘Other’ employment sub-categories (e.g., unemployed) were just as likely as the ‘Working/student’ subgroup to have started drinking alcohol, but were somewhat more likely to have started using the other drug types: this covariate-adjusted association was most robust with respect to cocaine (OR = 1.4; p<0.05; [Table 4](#T4)) and any extra-medical drug use (OR =”
Quote in the paperNot a substantial claim - Findingown data
This estimated proportion decreased such that among 14-19 year olds in 1996, roughly 50% had begun alcohol use.
“For alcohol, a curvilinear trend was evident: in 1955, an estimated 39% of 14–19 year olds had begun alcohol use, gradually increasing to around 60% in the mid-1980s; this estimated proportion decreased such that among 14–19 year olds in 1996, roughly 50% had begun alcohol use.”
Quote in the paperNot a substantial claim - Findingown data
Geographical location of current residence was related to drug use of all kinds.
“Geographical location of current residence was related to drug use of all kinds.”
Quote in the paperNot a substantial claim - Findingown data
For other drugs, cumulative incidence was lower for residents of rural areas than for residents of other areas.
“This was not the case for other drugs, where cumulative incidence was *lower* for residents of rural areas than it was for residents of other areas ([Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
Robust birth cohort-associated variations were observed in relation to initiation of alcohol consumption and extra-medical use of other drugs.
“Robust birth cohort-associated variations were not observed for cumulative incidence of tobacco smoking, but *were* observed in relation to initiation of alcohol consumption and extra-medical use of other drugs.”
Quote in the paperSubstantial claim - Findingown data
After covariate adjustment, those who had been separated or divorced were generally more likely to have become extra-medical drug users, except in relation to alcohol.
“Those who had never been married as of the time of interview were *less* likely to have started engaging in drinking, tobacco smoking, or any extra-medical drug use, whereas those who had been separated or divorced generally were *more* likely to have become extra-medical drug users; the only exception was observed in relation to alcohol ([Table 4](#T4)).”
Quote in the paperNot a substantial claim - Findingown data
For tobacco, the interquartile range for initiation of smoking was 13-19 years.
“For tobacco, the interquartile range for initiation of smoking was 13–19 years, and in 1955, an estimated 43% of young people in this age range had become tobacco smokers.”
Quote in the paperNot a substantial claim - Findingown data
The NCS-R disclosed statistically robust associations between extra-medical drug use and age, sex, income, employment, educational attainment, marital status, and geographical region.
“The NCS-R disclosed statistically robust associations between extra-medical drug use and age, sex, income, employment, educational attainment, marital status, and geographical region.”
Quote in the paperSubstantial claim - Findingown data
Robust birth cohort-associated variations were not observed for cumulative incidence of tobacco smoking.
“Robust birth cohort-associated variations were not observed for cumulative incidence of tobacco smoking, but *were* observed in relation to initiation of alcohol consumption and extra-medical use of other drugs.”
Quote in the paperNot a substantial claim - Findingown data
In 1957, it was rare for individuals aged 16-21 to have engaged in extra-medical use of these drugs.
“In 1957, it was rare for individuals in that age range to have engaged in extra-medical use of these drugs, but the estimated cumulative incidence proportion grew substantially such that by 1979, an estimated 41% of 16–21 year olds in that year had become a user of one or more of the drugs in this category ([Figure 2](#F2)).”
Quote in the paperNot a substantial claim - Findingown data
By age 15, 23% of the 1904-1942 cohort had used alcohol.
“More pronounced cohort-associated variations existed with respect to cumulative proportions estimated for starting drug use by age 15 years: in the 1973–1984 cohort, roughly one third had used alcohol (38%), and 14% had used cannabis; among the 1904–1942 cohort, under 1% had used cannabis, and 23% had used alcohol.”
Quote in the paperNot a substantial claim - Findingown data
Experience with tobacco smoking by age 15 was just as common for members of the oldest birth cohorts as it was among younger birth cohorts.
“Experience with tobacco smoking by age 15 was just as common for members of the oldest birth cohorts as it was among younger birth cohorts.”
Quote in the paperNot a substantial claim - Findingown data
By age 21, 89% of the youngest cohort (1973-1984) had used alcohol.
“By the time they had turned 21 years, half of the youngest cohort (1973–1984) had used cannabis (52%), and 89% had used alcohol.”
Quote in the paperNot a substantial claim - Findingown data
For alcohol, in 1955, an estimated 39% of 14-19 year olds had begun alcohol use.
“For alcohol, a curvilinear trend was evident: in 1955, an estimated 39% of 14–19 year olds had begun alcohol use, gradually increasing to around 60% in the mid-1980s; this estimated proportion decreased such that among 14–19 year olds in 1996, roughly 50% had begun alcohol use.”
Quote in the paperNot a substantial claim - Findingown data
The estimate for cumulative incidence of alcohol use was 92% in both NCS and NCS-R surveys.
“The estimate for cumulative incidence of alcohol use was 92% in both surveys.”
Quote in the paperNot a substantial claim - Findingown data
There are large differences in the cumulative incidence of use by age 15 years between adjacent cohorts.
“Furthermore, there are large differences in the cumulative incidence of use by age 15 years between adjacent cohorts (see, for example, the cocaine estimates for the three youngest birth cohorts).”
Quote in the paperSubstantial claim - Findingown data
By far the highest cumulative incidence of cocaine use was observed in a cohort of adults (1958-1972) who were entering the peak years of risk of initiating cocaine use when cocaine availability was growing to peak levels.
“By far the highest cumulative incidence of cocaine use was observed in a cohort of adults (1958–1972) who were entering the peak years of risk of initiating cocaine use when cocaine availability was growing to peak levels.”
Quote in the paperSubstantial claim - Findingown data
The observed association between religious affiliation and extra-medical drug use differed across drug types.
“Interestingly, this observed association differed across drug types”
Quote in the paperNot a substantial claim - Findingown data
The most recent cohort (1973-1984) has a lower cumulative incidence of cocaine use to date, despite a persisting widespread availability of cocaine in US communities.
“In contrast, the most recent cohort (1973–1984) has a lower cumulative incidence of cocaine use to date, despite a persisting widespread availability of cocaine in US communities, according to drug threat reports issued by the federal government.”
Quote in the paperSubstantial claim- Rests on an assumption: Drug threat reports issued by the federal government accurately indicate persisting widespread availability of cocaine in US communities.
- Findingown data
The epidemiological patterns of alcohol, tobacco, and other extra-medical drug use documented in the United States in the early 21st century provide an update of NCS estimates provided a decade ago.
“The epidemiological patterns of alcohol, tobacco, and other extra-medical drug use documented in the United States in the early 21st century provide an update of NCS estimates provided a decade ago.”
Quote in the paperSubstantial claim - Interpretationown data
Trends in the estimated cumulative incidence of drug use among young people across time suggested clear periods of fluctuating risk.
“Trends in the estimated cumulative incidence of drug use among young people across time suggested clear periods of fluctuating risk.”
Quote in the paperNot a substantial claim- Rests on an assumption: Retrospectively recalled age of onset data accurately reflect the timing of participants' initiation of extra-medical drug use.
- Premisereasoning
The cumulative incidence proportion, unlike all other known prevalence proportions, is not influenced by the duration of the experience under study.
“and this proportion is **not** influenced by the duration of the experience under study – in contrast to all other known prevalence proportions.”
Quote in the paperNot a substantial claim - Interpretationreasoning
This possibility [that cohort differences are due to higher mortality among early initiators] is unlikely to explain the rather large category-specific differences in cumulative incidence of extra-medical drug use across the birth cohorts.
“This possibility is unlikely, however, to explain the rather large category-specific differences in cumulative incidence of extra-medical drug use across the birth cohorts, for two reasons.”
Quote in the paperSubstantial claim - Interpretationown data
Similarities in cumulative incidence of drug use across NCS and NCS-R were noteworthy despite sampling frame differences.
“Comparing across the NCS and NCS-R surveys, conducted a decade apart, the similarities in cumulative incidence of drug use were noteworthy, despite sampling frame differences.”
Quote in the paperSubstantial claim- Rests on an assumption: The NCS and NCS-R surveys are comparable enough to compare cumulative incidence estimates despite sampling frame differences.
- Interpretationreasoning
Even if those who began use early had substantially increased mortality rates, this increased mortality would be unlikely to account for cumulative incidence proportions of cannabis use by age 15 years that were around 14% lower in the oldest cohort compared to the youngest cohort.
“Even if those who began use early had substantially increased mortality rates, this increased mortality would be unlikely to account for cumulative incidence proportions of cannabis use by age 15 years that were around 14% lower in the oldest cohort compared to the youngest cohort.”
Quote in the paperSubstantial claim - Study design and conductreasoning
The potential under-estimation bias due to non-response was adjusted for via a non-response adjustment weight that weighted up cases of participants with profiles found to be under-represented in the sample.
“Accordingly, the potential under-estimation bias was adjusted for, via a method that involved making a non-response adjustment weight, which weighted up the cases of participants with profiles found to be under-represented in the sample.”
Quote in the paperSubstantial claim - Premisecitation
The estimated levels of extra-medical drug use among people who initially declined to be interviewed in the NCS and the NCS-R were higher than those of people who initially agreed to be interviewed.
“The estimated levels of extra-medical drug use among people who initially declined to be interviewed in the NCS and the NCS-R were higher than those of people who initially agreed to be interviewed ([Kessler et al., 2004](#R20); [Kessler et al., 1995](#R21)).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Kessler et al., 2004
Not checked in the free run.
- cites Kessler et al., 1995 source
Not checked in the free run.
- Premisecitation
The age of first use of drugs is 'right censored' because younger birth cohorts have not yet reached older ages, so their reported drug use necessarily occurs at a younger age.
“Another limitation is a possible bias is that the age of first use of drugs is “right censored” ([Wu et al., 2003](#R35)): because younger birth cohorts have not yet reached older ages, their reported drug use necessarily occurs at a younger age.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Wu et al., 2003
Not checked in the free run.
- Premisecitation
This right-censoring bias is most relevant for the youngest birth cohort, whose youngest were still in the period of highest risk for initiation of illegal drug use.
“This is most relevant for the youngest birth cohort, the youngest of whom were still in the period of highest risk for initiation of illegal drug use ([Chen and Kandel, 1995](#R8); [Wagner and Anthony, 2002](#R34)).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Chen and Kandel, 1995
Not checked in the free run.
- cites Wagner and Anthony, 2002
Not checked in the free run.
- Interpretationreasoning
Such a bias is not relevant for estimates of the cumulative incidence proportion for ages through which all cohorts have passed, since comparisons may be made across cohorts for a given age in the lifespan.
“However, such a bias is not relevant for estimates of the cumulative incidence proportion for ages through which all cohorts have passed, since comparisons may be made across cohorts for a given age in the lifespan (e.g. age 15 years), where we still found cohort differences.”
Quote in the paperSubstantial claim - Interpretationreasoning
This potential source of underestimation bias is therefore minimised, if not corrected.
“This potential source of underestimation bias is therefore minimised, if not corrected.”
Quote in the paperSubstantial claim - Interpretationreasoning
Changes in the availability of drugs are not the sole explanation of changes in drug use.
“Changes in the availability of drugs are not the sole explanation of changes in use.”
Quote in the paperSubstantial claim - Interpretationown data
The pattern of the association between religious affiliation and extra-medical drug use across drug types was generally consistent with broad proscriptions of specific religious denominations.
“and the pattern was generally consistent with broad proscriptions of specific religious denominations”
Quote in the paperSubstantial claim - Premisecitation
Similar birth cohort trends in age of initiation of illegal drug use have been observed in other epidemiological studies in the United States and Australia, some of which used data collected across time.
“First, similar birth cohort trends in age of initiation of illegal drug use have been observed in other epidemiological studies in the United States ([Johnson and Gerstein, 1998](#R17); [Kerr et al., in press](#R19)), and Australia ([Degenhardt et al., 2000](#R10)), some of which used data collected across time (rather than relying solely on retrospective reports; e.g. see ([Kerr et al., in press]”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Johnson and Gerstein, 1998 source
Not checked in the free run.
- cites Kerr et al., in press
Not checked in the free run.
- cites Degenhardt et al., 2000
Not checked in the free run.
- Interpretationown data
This response bias cannot account for all of the differences in age of onset observed here, since the cumulative incidence of cocaine use was lower for the most recent cohort (1973-1984) than it was for the next older one (1958-1972).
“This cannot account for all of the differences in age of onset observed here, however, since the cumulative incidence of cocaine use was lower for the most recent cohort (1973–1984) than it was for the next older one (1958–1972).”
Quote in the paperSubstantial claim - Premisecitation
There is good evidence that drug availability and drug use co-vary in the general population.
“There is good evidence that drug availability and drug use co-vary in the general population ([Degenhardt et al., 2005](#R9); [Norstrom and Skog, 2003](#R28); [Room et al., 2005](#R29)).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Interpretationown data
Religious denomination and religiosity may also be important for illegal and other extra-medical drug use.
“The current study has suggested that religious denomination and religiosity may also be important for illegal and other extra-medical drug use.”
Quote in the paperSubstantial claim - Interpretationreasoning
It is unlikely that these biases completely account for the strong trends observed here.
“It is unlikely, however, that these biases completely account for the strong trends observed here.”
Quote in the paperSubstantial claim - Interpretationown data
Estimates from the current study were consistent with these patterns.
“Estimates from the current study were consistent with these patterns.”
Quote in the paperSubstantial claim - Interpretationreasoning
Associations linking drug use with religious affiliation may not be a simple reflection of the individual's perceived importance of religion, or religious beliefs per se.
“associations linking drug use with religious affiliation may not be a simple reflection of the individual’s perceived importance of religion, or religious beliefs per se.”
Quote in the paperSubstantial claim
- May combine two claims. 31
- Classified as probably not a substantial claim. 8
May combine two claims.
Findingown dataIn the NCS-R, alcohol use proportions were similar among younger birth cohorts (93-94%), slightly higher than the estimate for the oldest cohort (86%).
“Alcohol was used by the majority of participants: proportions using were similar among younger birth cohorts (93–94%), which were slightly higher than estimates observed for the oldest cohort (86%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the NCS-R, very robust birth cohort differences were observed for cocaine, cannabis, and other extra-medical drug use, but not for alcohol or tobacco.
“Very robust birth cohort differences were observed for cocaine, cannabis, and other extra-medical drug use, but not for alcohol or tobacco.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the NCS-R, younger adults were more likely than older adults to have become users of all drugs examined, with the exception of tobacco, for which there was no association with age at interview.
“younger adults were more likely than older adults to have become users of all drugs examined here (with the exception of tobacco, where there was no association with age at interview”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the NCS-R, cumulative incidence of cannabis use was largest for the two youngest cohorts, and was much larger for the 1943-1957 cohort (46%) than for those born 1904-1942 (6%).
“Similarly, the cumulative incidence proportions for cannabis use were largest for the two youngest cohorts; the proportion was also much larger for the 1943–1957 cohort (46%) than it was for those born between 1904–1942 (6%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the NCS-R, cumulative incidence of any extra-medical drug use excluding alcohol and tobacco was lowest for the oldest cohort (born 1904-1942, 7%), and the majority of the two youngest cohorts (55% and 61%) had become users of such drugs by the time of interview.
“Estimated cumulative incidence proportions for any extra-medical drug (excluding alcohol and tobacco) were lowest for the oldest cohort, born 1904–1942 (7%). Larger proportions were observed in more recent cohorts such that the majority of the two youngest cohorts (55% and 61%) had become users of such drugs by the time of interview”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the NCS-R, the highest cumulative incidence of cocaine use was in the 1958-1972 birth cohort (28%), while the 1973-1984 and 1943-1957 cohorts had similar and lower proportions (16% and 17%), and cocaine use was extremely uncommon in the oldest cohort (1%).
“The cohort with the highest cumulative incidence of use was the 1958–1972 birth cohort (28%), whereas the 1973–1984 and 1943–1957 cohorts had similar and lower proportions (16 and 17% respectively). Cocaine use was extremely uncommon among members of the oldest cohort (1%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAfter covariate adjustment, the inverse relationship largely remained, with those who held religion as 'very important' being less likely than others to have become drug users.
“This relationship largely remained after covariate adjustment, but the pattern was more akin to a threshold function, with those who held religion as “very important” to them being less likely than others to have become drug users.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThat proportion remained relatively stable across years, but a gradual decline was seen from the mid 1980s, such that the estimated proportion for young people who were 13-19 years old in 1996 was only 37%.
“That proportion remained relatively stable across years, but a gradual decline was seen from the mid 1980s, such that the estimated proportion for young people who were 13–19 years old in 1996 was only 37%.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe estimated cumulative incidence proportion for 16-21 year olds showed a decline from the mid 1980s, followed by an increase from 1995.
“The estimated cumulative incidence proportion for 16–21 year olds showed a decline from the mid 1980s, followed by an increase from 1995.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAfter covariate adjustment, individuals in 'Other' employment sub-categories were somewhat more likely to have started using other drug types, most robust for cocaine (OR = 1.4; p<0.05) and any extra-medical drug use (OR = 1.5; p<0.05).
“Individuals classifying themselves in ‘Other’ employment sub-categories (e.g., unemployed) were just as likely as the ‘Working/student’ subgroup to have started drinking alcohol, but were somewhat more likely to have started using the other drug types: this covariate-adjusted association was most robust with respect to cocaine (OR = 1.4; p<0.05; [Table 4](#T4)) and any extra-medical drug use (OR =”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataFor any extra-medical use of psychoactive drugs, cumulative incidence was 45% in NCS and 51% in NCS-R.
“For other drugs, the corresponding pairs of estimates were as follows: tobacco smoking (74% vs. 76%); any extra-medical use of psychoactive drugs, 45% vs. 51%; cannabis, 43% vs. 46%; and cocaine, 16% (both surveys).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn general, those living in the southern US region were less likely to have used all drugs examined, and those living in the West region were most likely to have done so.
“In general, those living in the southern US region were less likely to have used all drugs examined here, and those living in the West region were most likely to have done so ([Tables 3](#T3) and [4](#T4)).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataCompared to those in the southern states, those living in the Midwest were more likely to have started drinking alcohol (OR = 2.3; p<0.05) and were more likely to have started smoking cannabis (OR = 1.3; p<0.05).
“Compared to those in the southern states, those living in the Midwest were more likely to have started drinking alcohol (OR = 2.3; p<0.05; [Table 4](#T4)), and were more likely to have started smoking cannabis (OR = 1.3; p<0.05; [Table 4](#T4)).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataOn a bivariate level, self-reported importance of religion was inversely associated with drug use; those for whom religion was less important were more likely to have used all drug types.
“The self-reported importance of religion was inversely associated (on a bivariate level) with drug use: those for whom religion was less important were more likely to have used all drug types ([Table 3](#T3)).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataFor cannabis, cumulative incidence was 43% in NCS and 46% in NCS-R.
“For other drugs, the corresponding pairs of estimates were as follows: tobacco smoking (74% vs. 76%); any extra-medical use of psychoactive drugs, 45% vs. 51%; cannabis, 43% vs. 46%; and cocaine, 16% (both surveys).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThese trends were weaker for tobacco and alcohol, and were stronger for cannabis, cocaine and the other psychoactive drugs under study.
“These trends were weaker for tobacco and alcohol, and were stronger for cannabis, cocaine and the other psychoactive drugs under study.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the present study there was an association between religious affiliation and extra-medical drug use that remained statistically robust after covariate adjustment and was independent of the importance individuals placed upon their religious beliefs.
“The possible rôle of such norms was given support by the finding in the present study of an association between religious affiliation and extra-medical drug use, which remained statistically robust after covariate adjustment, and was independent of the importance that individuals placed upon their religious beliefs.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationIn the 1990-1992 National Comorbidity Survey, an estimated 92% of the population had used alcohol, 76% had engaged in tobacco smoking, 51% had any extra-medical use of psychoactive drugs, 46% cannabis, and 16% cocaine.
“In the NCS, it was estimated that the 92% of the population had used alcohol; 76% had engaged in tobacco smoking; 51%, any extra-medical use of psychoactive drugs; 46%, cannabis, and 16%, cocaine.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Anthony et al., 1994 source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.
Interpretationown dataNew findings on religion and religiosity, and exploratory data on time trends, represent progress in both concepts and methodology for research on extra-medical drug use.
“New findings on religion and religiosity, and exploratory data on time trends, represent progress in both concepts and methodology for such research.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductcitationThe NCS-R is a nationally representative household survey of English speakers ages 18 and older in the coterminous United States.
“the NCS-R is a nationally representative household survey of English speakers ages 18+ in the coterminous United States.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Kessler et al., 2004
Not checked in the free run.
- cites Kessler and Merikangas, 2004
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe NCS-R participation level was 71%.
“The participation level was 71%.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThe NCS-R epidemiological patterns of alcohol, tobacco, and other extra-medical drug use in the United States in the early 21st century provide an update of NCS estimates from roughly 10 years ago and are consistent with contemporaneous epidemiological studies.
“These epidemiological patterns of alcohol, tobacco, and other extra-medical drug use in the United States in the early 21st century provide an update of NCS estimates from roughly 10 years ago, and are consistent with contemporaneous epidemiological studies.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationConvincing evidence of significantly elevated mortality risk for cannabis use remains to be provided; existing cohort studies have been inconsistent, with very small and possibly negligible increases in mortality risk, even among regular cannabis users.
“In the case of cannabis use, convincing evidence of significantly elevated mortality risk remains to be provided; existing cohort studies have been inconsistent, with very small and possibly negligible increases in mortality risk, even among regular cannabis users ([Hall et al., 2001](#R15)).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Hall et al., 2001
Not checked in the free run.
May combine two claims.
Interpretationown dataClear cohort-associated variations existed in the age of initiation of alcohol use, but they were most marked for extra-medical use of drugs other than alcohol and tobacco.
“Clear cohort-associated variations existed in the age of initiation of alcohol use, but they were most marked for extra-medical use of drugs other than alcohol and tobacco ([Figure 1](#F1)).”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataParticularly for cannabis, cocaine, and other drugs, and less so for alcohol and tobacco, members of the more recently born cohorts have been much more likely to start such drug use in childhood and early-mid adolescence.
“Particularly for cannabis, cocaine, and other drugs, and less so for alcohol and tobacco, members of the more recently born cohorts have been much more likely to start such drug use in childhood and early-mid adolescence.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataContrasting birth cohort trends in cumulative incidence of drug use were observed across different drug types, suggesting that the pattern of responses was not being affected by a uniform response or selection bias.
“Second, contrasting birth cohort trends in cumulative incidence of drug use were observed across different drug types, suggesting that the pattern of responses was not being affected by a uniform response or selection bias.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThis phenomenon most likely involves complex feedback loops such that increasing numbers of drug users and demand move prices upward, drawing in new suppliers and supplies that make the drug more available, with persistence of relatively high levels of availability even after the peak incidence of use has occurred.
“This phenomenon most likely involves complex feedback loops such that increasing numbers of drug users and demand move prices upward, drawing in new suppliers and supplies that make the drug more available, with persistence of relatively high levels of availability even after the peak incidence of use has occurred.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationA proportion of those who begin using any drug will experience problems related to their use, and some will develop dependence.
“A proportion of those who begin using any drug will experience problems related to their use, and some will develop dependence ([Anthony et al., 1994](#R3); [Chen et al., 2005](#R7)).”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationLongitudinal studies of adolescents have found that estimates of the age of first use do tend to increase upon repeat assessment, but the rank ordering for the different drugs remains the same.
“Longitudinal studies of adolescents have found that estimates of the age of first use do tend to increase upon repeat assessment (i.e. as people age) ([Engels et al., 1997](#R11); [Henry et al., 1994](#R16); [Labouvie et al., 1997](#R23)), but the rank ordering for the different drugs remains the same ([Engels et al., 1997](#R11); [Henry et al., 1994](#R16); [Labouvie et al., 1997](#R23)).”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationReligious affiliation may have multiple paths of influence upon drug involvement, including the possibility that religious activities occupy leisure time and tend to surround an individual with non-using peers.
“Previous research suggested that religious affiliation may have multiple paths of influence upon drug involvement – including the possibility that religious activities occupy leisure time and”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Chen et al., 2004 source
Not checked in the free run.
Classified as probably not a substantial claim.
Study design and conductnone givenThese estimates lead to no firm causal inferences or interpretations.
“These estimates lead to no firm causal inferences or interpretations, but evidence of this type provides a foundation for more probing research on drug involvement across the decades and across birth cohorts”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationRecent work on alcohol has suggested that both religious denomination and religiosity were associated with alcohol use.
“These findings extend recent work estimating the effects of religion upon abstention from, and patterns of use of, alcohol ([Michalak et al., in press](#R24)), which has suggested that both religious denomination and religiosity were associated with alcohol use.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Michalak et al., in press
Not checked in the free run.
May combine two claims.
PremisecitationAlthough cocaine availability persisted in the late 1980s and early 1990s, the risk of starting cocaine use seems to have been declining over that period.
“Although cocaine availability persisted in the late 1980s and early 1990s, the risk of starting cocaine use seems to have been declining over that period ([Golub and Johnson, 1994](#R12), [1997](#R13); [Johnston et al., 2003](#R18); [Miech et al., 2005](#R25); [United States Substance Abuse and Mental Health Services Administration, 2005](#R33)).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Golub and Johnson, 1994
Not checked in the free run.
- cites Golub and Johnson, 1997
Not checked in the free run.
- cites Johnston et al., 2003
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationVery precocious or early initiation of drug use has been associated with a greater likelihood of later drug problems and with progression to the use of other drug types.
“Very precocious or early initiation of drug use has been associated with a greater likelihood of later drug problems, and with progression to the use of other drug types ([Anthony and Petronis, 1995](#R2); [Breslau et al., 1993](#R4); [Brook et al., 1999](#R5); [Grant et al., 2005](#R14); [Newcomb and Bentler, 1988](#R27); [Storr et al., 2004](#R32); [Wagner and Anthony, 2002](#R34)), but the”
Quote in the paperNot a substantial claim0 of 3 sources checked
The paper relies on this without support.
Retrospectively recalled age of onset data accurately reflect the timing of participants' initiation of extra-medical drug use.
“Exploratory analyses of time trends were conducted, making use of retrospectively recalled age of onset data from each participant’s interview.”
The paper relies on this without support.
The NCS and NCS-R surveys are comparable enough to compare cumulative incidence estimates despite sampling frame differences.
“Comparing across the NCS and NCS-R surveys, conducted a decade apart, the similarities in cumulative incidence of drug use were noteworthy, despite sampling frame differences.”
The paper relies on this without support.
Tobacco-associated mortality is especially large.
“Finally, tobacco-associated mortality is apt to be especially large, and yet this was the drug with the smallest cohort-associated variations.”
The paper relies on this without support.
Drug threat reports issued by the federal government accurately indicate persisting widespread availability of cocaine in US communities.
“In contrast, the most recent cohort (1973–1984) has a lower cumulative incidence of cocaine use to date, despite a persisting widespread availability of cocaine in US communities, according to drug threat reports issued by the federal government.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Of the 112 best drug use or abuse studies, 96 (86%) reported inverse relationships and only one study found a positive relationship.
“Of the 112 best studies, 96 (86%) reported inverse relationships [223–238] and only one study found a positive relationship [239].”
From Religion, Spirituality, and Health: The Research and Clinical Implications (2012) · cites this paper as [232]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Adjusted tobacco result for non-Hispanic Black respondents is misreported
MajorThe prose says non-Hispanic Black respondents were less likely to have started smoking, with OR=0.7 and p<0.05. Table 4 instead reports a tobacco OR of 0.9 with a 95% CI of 0.5-1.6 and no significance marker.
“persons of Hispanic origin, as well as non-Hispanic Blacks, were less likely than non-Hispanic Whites to have started smoking tobacco (OR = 0.6; p<0.05; OR = 0.7; p<0.05, respectively)”
“| Non-Hispanic Black | 1.7 | 0.6–4.7 | 0.9 | 0.5–1.6 | 1.1 | 0.6–2.1 | 1.0 | 0.5–1.9 | 0.6[\*](#TFN6) | 0.4–0.9 |”
Adjusted alcohol odds ratio for other religions is misstated
MinorThe prose reports an alcohol OR of 0.2 for the 'Other' religion category, whereas Table 4 reports 0.3.
“a reduced risk of starting to drink was found among those of ‘Other’ religions (e.g., Islam; OR = 0.2; p<0.05; [Table 4](#T4)).”
“| Others | 0.3[\*](#TFN6) | 0.2–0.6 | 0.5[\*](#TFN6) | 0.3–0.8 | 1.0 | 0.6–1.8 | 1.0 | 0.5–2.0 | 1.4 | 0.9–2.2 |”
Rural and central-city drinking odds are described as equal
MinorThe prose says rural residents were just as likely as central-city residents to have started drinking. Table 4 marks the alcohol OR of 1.6 for residents of central cities with fewer than 2 million people, relative to rural residents, as statistically significant.
“those living in rural areas were just as likely to have started drinking alcohol or smoking tobacco, as those living closer to, or in, ‘central cities’ ([Table 4](#T4)).”
“| Central city < 2 million | 1.6[\*](#TFN6) | 1.0–2.4 | 0.9 | 0.6–1.2 | 3.1[\*](#TFN6) | 2.4–4.0 | 2.8[\*](#TFN6) | 2.2–3.6 | 4.6[\*](#TFN6) | 3.3–6.2 |”
Claim of associations across every drug and covariate is too broad
MinorThe abstract claims statistically robust associations between all drug types and income, among other covariates. In the covariate-adjusted results, the income association for tobacco has p=0.990.
“Statistically robust associations existed between all types of drug use and age, sex, income, employment, education, marital status, geography, religious affiliation and religiosity.”
“| X23 [p] | 8.0 | [< 0.05] | 0.1 | [0.990] | 10.5 | [<0.05] | 9.7 | [<0.05] | 1.3 | [0.721] |”
White respondents do not have the highest adjusted estimate for every other-drug category
MinorThe prose says non-Hispanic White respondents were most likely to report extra-medical use of other drugs. In Table 4, the non-Hispanic Black point estimate for any extra-medical drug use is 1.1 relative to the White reference value of 1.0, although that difference is not statistically significant.
“non-Hispanic Whites were most likely to have engaged in extra-medical use of other drugs compared to other race-ethnicity subgroups”
“| Non-Hispanic Black | 1.7 | 0.6–4.7 | 0.9 | 0.5–1.6 | 1.1 | 0.6–2.1 | 1.0 | 0.5–1.9 | 0.6[\*](#TFN6) | 0.4–0.9 |”
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Advances in strategies for minimizing and adjusting for survey nonresponse
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Early smoking initiation and nicotine dependence in a cohort of young adults
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Psychological Medicine goes monthly
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Self-citation
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Religion, Spirituality, and Health: The Research and Clinical Implications
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“Of the 112 best studies, 96 (86%) reported inverse relationships [223–238] and only one study found a positive relationship [239].”
BackgroundCannabis use and educational achievement: Findings from three Australasian cohort studies
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An international contrast of rates of placental abruption: an age-period-cohort analysis
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Cannabis use and mental health-related quality of life among individuals with anxiety disorders
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- Authors
- Degenhardt, L., Chiu, W. T., Sampson, N., Kessler, R. C., & Anthony, J. C.
- Affiliations
- Michigan State University (US)
- Harvard University (US)
- Venue
- Drug and Alcohol Dependence
- Publisher
- Elsevier BV
- Published
- 2007-10
- Volume
- 90
- Issue
- 2-3
- Pages
- 210-223
- ISSN
- 0376-8716 (ISSN-L)
- PMC
- PMC2739901
- OpenAlex
- W2111124561
- Cited by
- 109
- References
- 37
- Citations by year
- 2025: 2 · 2024: 3 · 2023: 2 · 2022: 7 · 2021: 5 · 2020: 1 · 2019: 6 · 2018: 5 · 2017: 2 · 2016: 8 · 2015: 9 · 2014: 7 · 2013: 12 · 2012: 8
- FWCI
- 5.00
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Drug and Alcohol Dependence (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Eli Lilly and Company
- National Institutes of Health (5r13mh066849-04, 5r01mh052861-04, 5r01mh069864-04)
- National Institute of Mental Health (R13-MH-066849, R01 MH52861, R01MH046376, MH 46376, U01MH060220, R01‐MH069864, R01MH049098)
- National Institute on Drug Abuse (K05DA015799, R01DA016558)
- Topics
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Opioid Use Disorder Treatment
- Social Sciences › Demography › Youth, Drugs, and Violence
- Keywords
- alcohol consumption, tobacco use, cannabis use, cocaine use, drug use, cumulative incidence, birth cohort differences, religiosity, sociodemographic risk factors, National Comorbidity Survey Replication
- MeSH terms
- Adult, Aged, Aged, 80 and over, Alcoholism, Marijuana Abuse, Demography, Female, Humans, Male, Middle Aged, Surveys and Questionnaires, Tobacco Use Disorder, United States, Comorbidity, Prevalence, Cocaine-Related Disorders
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
Statistics and arithmetic are recomputed, not judged.
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