Several have claimed that the overreliance on benzodiazepines for many approved and off-label uses poses substantial human and social consequences comparable to those observed with the opioid epidemic. In light of these problems, alternatives are required to properly manage patients. Numerous states now permit the use of medical cannabis to treat conditions, such as chronic pain, that were traditionally treated with benzodiazepines, opioids, or both. As patients and physicians seek alternative treatments, little is known about whether the presence of cannabis laws helps to alleviate the burdens caused by these more traditional medications owing to the displacement of benzodiazepines and/or opioids toward cannabis.
Using data from multiple years of the National Survey on Drug Use and Health (2017, 2018, 2019), the effect of Medical Marijuana Laws (MMLs) on benzodiazepine and/or opioid use and misuse is examined while controlling for a variety of demographic characteristics. Supplemental analysis also is performed including the 2020 and 2021 survey years.
MMLs did not affect lone, legitimate benzodiazepine usage, but lower use of opioids and combinations of benzodiazepines and opioids was observed. MMLs appear to help attenuate benzodiazepine and/or opioid misuse to a substantial degree. Additional results suggest that the presence of an MML was related to annual, varying decreases in the use and misuse of benzodiazepines, opioids, and their combination across the years of data evaluated.
MMLs may serve to attenuate the consequences of benzodiazepine, opioid, and their combined use and/or misuse to varying degrees.
Citation: Jamie L. Flexon, Lisa Stolzenberg, Stewart J. D'Alessio. The impact of cannabis legislation on benzodiazepine and opioid use and misuse[J]. AIMS Medical Science, 2024, 11(1): 1-24. doi: 10.3934/medsci.2024001
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Several have claimed that the overreliance on benzodiazepines for many approved and off-label uses poses substantial human and social consequences comparable to those observed with the opioid epidemic. In light of these problems, alternatives are required to properly manage patients. Numerous states now permit the use of medical cannabis to treat conditions, such as chronic pain, that were traditionally treated with benzodiazepines, opioids, or both. As patients and physicians seek alternative treatments, little is known about whether the presence of cannabis laws helps to alleviate the burdens caused by these more traditional medications owing to the displacement of benzodiazepines and/or opioids toward cannabis.
Using data from multiple years of the National Survey on Drug Use and Health (2017, 2018, 2019), the effect of Medical Marijuana Laws (MMLs) on benzodiazepine and/or opioid use and misuse is examined while controlling for a variety of demographic characteristics. Supplemental analysis also is performed including the 2020 and 2021 survey years.
MMLs did not affect lone, legitimate benzodiazepine usage, but lower use of opioids and combinations of benzodiazepines and opioids was observed. MMLs appear to help attenuate benzodiazepine and/or opioid misuse to a substantial degree. Additional results suggest that the presence of an MML was related to annual, varying decreases in the use and misuse of benzodiazepines, opioids, and their combination across the years of data evaluated.
MMLs may serve to attenuate the consequences of benzodiazepine, opioid, and their combined use and/or misuse to varying degrees.
The idea of statistical convergence was given by Zygmund [1] in the first edition of his monograph published in Warsaw in 1935. The concept of statistical convergence was introduced by Steinhaus [2] and Fast [3] and then reintroduced independently by Schoenberg [4]. Over the years and under different names, statistical convergence has been discussed in the Theory of Fourier Analysis, Ergodic Theory, Number Theory, Measure Theory, Trigonometric Series, Turnpike Theory and Banach Spaces. Later on it was further investigated from the sequence spaces point of view and linked with summability theory by Bilalov and Nazarova [5], Braha et al. [6], Cinar et al. [7], Colak [8], Connor [9], Et et al. ([10,11,12,13,14]), Fridy [15], Isik et al. ([16,17,18]), Kayan et al. [19], Kucukaslan et al. ([20,21]), Mohiuddine et al. [22], Nuray [23], Nuray and Aydın [24], Salat [25], Sengul et al. ([26,27,28,29]), Srivastava et al. ([30,31]) and many others.
The idea of statistical convergence depends upon the density of subsets of the set N of natural numbers. The density of a subset E of N is defined by
δ(E)=limn→∞1nn∑k=1χE(k), |
provided that the limit exists, where χE is the characteristic function of the set E. It is clear that any finite subset of N has zero natural density and that
δ(Ec)=1−δ(E). |
A sequence x=(xk)k∈N is said to be statistically convergent to L if, for every ε>0, we have
δ({k∈N:|xk−L|≥ε})=0. |
In this case, we write \newline
xkstat⟶Lask→∞orS−limk→∞xk=L. |
In 1932, Agnew [32] introduced the concept of deferred Cesaro mean of real (or complex) valued sequences x=(xk) defined by
(Dp,qx)n=1qn−pnqn∑k=pn+1xk,n=1,2,3,… |
where p=(pn) and q=(qn) are the sequences of non-negative integers satisfying
pn<qnandlimn→∞qn=∞. | (1) |
Let K be a subset of N and denote the set {k:k∈(pn,qn],k∈K} by Kp,q(n).
Deferred density of K is defined by
δp,q(K)=limn→∞1(qn−pn)|Kp,q(n)|, provided the limit exists |
where, vertical bars indicate the cardinality of the enclosed set Kp,q(n). If qn=n, pn=0, then the deferred density coincides with natural density of K.
A real valued sequence x=(xk) is said to be deferred statistically convergent to L, if for each ε>0
limn→∞1(qn−pn)|{k∈(pn,qn]:|xk−L|≥ε}|=0. |
In this case we write Sp,q-limxk=L. If qn=n, pn=0, for all n∈N, then deferred statistical convergence coincides with usual statistical convergence [20].
In this section, we give some inclusion relations between statistical convergence of order α, deferred strong Cesàro summability of order α and deferred statistical convergence of order α in general metric spaces.
Definition 1. Let (X,d) be a metric space, (pn) and (qn) be two sequences as above and 0<α≤1. A metric valued sequence x=(xk) is said to be Sd,αp,q-convergent (or deferred d-statistically convergent of order α) to x0 if there is x0∈X such that
limn→∞1(qn−pn)α|{k∈(pn,qn]:xk∉Bε(x0)}|=0, |
where Bε(x0)={x∈X:d(x,x0)<ε} is the open ball of radius ε and center x0. In this case we write Sd,αp,q-limxk=x0 or xk→x0(Sd,αp,q). The set of all Sd,αp,q-statistically convergent sequences will be denoted by Sd,αp,q. If qn=n and pn=0, then deferred d-statistical convergence of order α coincides d -statistical convergence of order α denoted by Sd,α. In the special cases qn=n,pn=0 and α=1 then deferred d -statistical convergence of order α coincides d-statistical convergence denoted by Sd.
Definition 2. Let (X,d) be a metric space, (pn) and (qn) be two sequences as above and 0<α≤1. A metric valued sequence x=(xk) is said to be strongly wd,αp,q-summable (or deferred strongly d-Ces àro summable of order α) to x0 if there is x0∈X such that
limn→∞1(qn−pn)αqn∑k=pn+1d(xk,x0)=0. |
In this case we write wd,αp,q-limxk=x0 or xk→x0(wd,αp,q). The set of all strongly wd,αp,q-summable sequences will be denoted by wd,αp,q. If qn=n and pn=0, for all n∈N, then deferred strong d-Cesàro summability of order α coincides strong d-Cesàro summability of order α denoted by wd,α. In the special cases qn=n,pn=0 and α=1 then deferred strong d-Cesàro summability of order α coincides strong d-Ces àro summability denoted by wd.
Theorem 1. Let (pn) and (qn) be sequences of non-negative integers satisfying the condition (1), (X,d) be a linear metric space and x=(xk),y=(yk) be metric valued sequences, then
(i) If Sd,αp,q-limxk=x0 and Sd,αp,q-limyk=y0, then Sd,αp,q-lim(xk+yk)=x0+y0,
(ii)If Sd,αp,q-limxk=x0 and c∈C, then Sd,αp,q-lim(cxk)=cx0,
(iii) If Sd,αp,q-limxk=x0,Sd,αp,q-limyk=y0 and x,y∈ℓ∞(X), then Sd,αp,q-lim(xkyk)=x0y0.
Proof. Omitted.
Theorem 2. Let (pn) and (qn) be sequences of non-negative integers satisfying the condition (1) and α and β be two real numbers such that 0<α≤β≤1. If a sequence x=(xk) is deferred strongly d-Cesàro summable of order α to x0, then it is deferred d-statistically convergent of order β to x0, but the converse is not true.
Proof. First part of the proof is easy, so omitted. For the converse, take X=R and choose qn=n,pn=0 (for all n∈N),d(x,y)=|x−y| and define a sequence x=(xk) by
xk={3√n,k=n20,k≠n2. |
Then for every ε>0, we have
1(qn−pn)α|{k∈(pn,qn]:xk∉Bε(0)}|≤[√n]nα→0, as n→∞, |
where 12<α≤1, that is xk→0(Sd,αp,q). At the same time, we get
1(qn−pn)αqn∑k=pn+1d(xk,0)≤[√n][3√n]nα→1 |
for α=16 and
1(qn−pn)αqn∑k=pn+1d(xk,0)≤[√n][3√n]nα→∞ |
for 0<α<16, i.e., xk↛0(wd,αp,q) for 0<α≤16.
From Theorem 2 we have the following results.
Corollary 1. ⅰ) Let (pn) and (qn) be sequences of non-negative integers satisfying the condition (1) and α be a real number such that 0<α≤1. If a sequence x=(xk) is deferred strongly d-Cesàro summable of order α to x0, then it is deferred d-statistically convergent of order α to x0, but the converse is not true.
ⅱ) Let (pn) and (qn) be sequences of non-negative integers satisfying the condition (1) and α be a real number such that 0<α≤1. If a sequence x=(xk) is deferred strongly d-Cesàro summable of order α to x0, then it is deferred d-statistically convergent to x0, but the converse is not true.
ⅲ) Let (pn) and (qn) be sequences of non-negative integers satisfying the condition (1). If a sequence x=(xk) is deferred strongly d-Cesàro summable to x0, then it is deferred d-statistically convergent to x0, but the converse is not true.
Remark Even if x=(xk) is a bounded sequence in a metric space, the converse of Theorem 2 (So Corollary 1 i) and ii)) does not hold, in general. To show this we give the following example.
Example 1. Take X=R and choose qn=n,pn=0 (for all n∈N),d(x,y)=|x−y| and define a sequence x=(xk) by
xk={1√k,k≠n30,k=n3n=1,2,.... |
It is clear that x∈ℓ∞ and it can be shown that x∈Sd,α−wd,α for 13<α<12.
In the special case α=1, we can give the followig result.
Theorem 3. Let (pn) and (qn) be sequences of non-negative integers satisfying the condition (1) and x=(xk) is a bounded sequence in a metric space. If a sequence x=(xk) is deferred d-statistically convergent to x0, then it is deferred strongly d-Cesàro summable to x0.
Proof. Let x=(xk) be deferred d-statistically convergent to x0 and ε>0 be given. Then there exists x0∈X such that
limn→∞1(qn−pn)|{k∈(pn,qn]:xk∉Bε(x0)}|=0, |
Since x=(xk) is a bounded sequence in a metric space X, there exists x0∈X and a positive real number M such that d(xk,x0)<M for all k∈N. So we have
1(qn−pn)qn∑k=pn+1d(xk,x0)=1(qn−pn)qn∑k=pn+1d(xk,x0)≥εd(xk,x0)+1(qn−pn)qn∑k=pn+1d(xk,x0)<εd(xk,x0)≤M(qn−pn)|{k∈(pn,qn]:xk∉Bε(x0)}|+ε |
Takin limit n→∞, we get wdp,q-limxk=x0.
Theorem 4. Let (pn) and (qn) be sequences of non-negative integers satisfying the condition (1) and α be a real number such that 0<α≤1. If liminfnqnpn>1, then Sd,α⊆Sd,αp,q.
Proof. Suppose that liminfnqnpn>1; then there exists a ν>0 such that qnpn≥1+ν for sufficiently large n, which implies that
(qn−pnqn)α≥(ν1+ν)α⟹1qαn≥να(1+ν)α1(qn−pn)α. |
If xk→x0(Sd,α), then for every ε>0 and for sufficiently large n, we have
1qαn|{k≤qn:xk∉Bε(x0)}|≥1qαn|{k∈(pn,qn]:xk∉Bε(x0)}|≥να(1+ν)α1(qn−pn)α|{k∈(pn,qn]:xk∉Bε(x0)}|. |
This proves the proof.
Theorem 5. Let (pn) and (qn) be sequences of non-negative integers satisfying the condition (1) and α and β be two real numbers such that 0<α≤β≤1. If limn→∞(qn−pn)αqβn=s>0, then Sd,α⊆Sd,βp,q.
Proof. Let limn→∞(qn−pn)αqβn=s>0. Notice that for each ε>0 the inclusion
{k≤qn:xk∉Bε(x0)}⊃{k∈(pn,qn]:xk∉Bε(x0)} |
is satisfied and so we have the following inequality
1qαn|{k≤qn:xk∉Bε(x0)}|≥1qαn|{k∈(pn,qn]:xk∉Bε(x0)}|≥1qβn|{k∈(pn,qn]:xk∉Bε(x0)}|=(qn−pn)αqβn1(qn−pn)α|{k∈(pn,qn]:xk∉Bε(x0)}|≥(qn−pn)αqβn1(qn−pn)β|{k∈(pn,qn]:xk∉Bε(x0)}|. |
Therefore Sd,α⊆Sd,βp,q.
Theorem 6. Let (pn),(qn),(p′n) and (q′n) be four sequences of non-negative real numbers such that
p′n<pn<qn<q′n for all n∈N, | (2) |
and α,β be fixed real numbers such that 0<α≤β≤1, then
(i) If
limn→∞(qn−pn)α(q′n−p′n)β=a>0 | (3) |
then Sd,βp′,q′⊆Sd,αp,q,
(ii) If
limn→∞q′n−p′n(qn−pn)β=1 | (4) |
then Sd,αp,q⊆Sd,βp′,q′.
Proof. (i) Let (3) be satisfied. For given ε>0 we have
{k∈(p′n,q′n]:xk∉Bε(x0)}⊇{k∈(pn,qn]:xk∉Bε(x0)}, |
and so
1(q′n−p′n)β|{k∈(p′n,q′n]:xk∉Bε(x0)}|≥(qn−pn)α(q′n−p′n)β1(qn−pn)α|{k∈(pn,qn]:xk∉Bε(x0)}|. |
Therefore Sd,βp′,q′⊆Sd,αp,q.
(ii) Let (4) be satisfied and x=(xk) be a deferred d-statistically convergent sequence of order α to x0. Then for given ε>0, we have
1(q′n−p′n)β|{k∈(p′n,q′n]:xk∉Bε(x0)}|≤1(q′n−p′n)β|{k∈(p′n,pn]:xk∉Bε(x0)}|+1(q′n−p′n)β|{k∈(qn,q′n]:xk∉Bε(x0)}|+1(q′n−p′n)β|{k∈(pn,qn]:xk∉Bε(x0)}|≤pn−p′n+q′n−qn(q′n−p′n)β+1(q′n−p′n)β|{k∈(pn,qn]:xk∉Bε(x0)}|=(q′n−p′n)−(qn−pn)(q′n−p′n)β+1(q′n−p′n)β|{k∈(pn,qn]:xk∉Bε(x0)}|≤(q′n−p′n)−(qn−pn)β(qn−pn)β+1(qn−pn)β|{k∈(pn,qn]:xk∉Bε(x0)}|≤(q′n−p′n(qn−pn)β−1)+1(qn−pn)α|{k∈(pn,qn]:xk∉Bε(x0)}| |
Therefore Sd,αp,q⊆Sd,βp′,q′.
Theorem 7. Let (pn),(qn),(p′n) and (q′n) be four sequences of non-negative integers defined as in (2) and α,β be fixed real numbers such that 0<α≤β≤1.
(i) If (3) holds then wd,βp′,q′⊂wd,αp,q,
(ii) If (4) holds and x=(xk) be a bounded sequence, then wd,αp,q⊂wd,βp′,q′.
Proof.
i) Omitted.
ii) Suppose that wd,αp,q-limxk=x0 and (xk)∈ℓ∞(X). Then there exists some M>0 such that d(xk,x0)<M for all k, then
1(q′n−p′n)βq′n∑k=p′n+1d(xk,x0)=1(q′n−p′n)β[pn∑k=p′n+1+qn∑k=pn+1+q′n∑k=qn+1]d(xk,x0)≤pn−p′n+q′n−qn(q′n−p′n)βM+1(q′n−p′n)βqn∑k=pn+1d(xk,x0)≤(q′n−p′n)−(qn−pn)β(qn−pn)βM+1(qn−pn)αqn∑k=pn+1d(xk,x0)=(q′n−p′n(qn−pn)β−1)M+1(qn−pn)αqn∑k=pn+1d(xk,x0) |
Theorem 8. Let (pn),(qn),(p′n) and (q′n) be four sequences of non-negative integers defined as in (2) and α,β be fixed real numbers such that 0<α≤β≤1. Then
(i) Let (3) holds, if a sequence is strongly wd,βp′,q′-summable to x0, then it is Sd,αp,q-convergent to x0,
(ii) Let (4) holds and x=(xk) be a bounded sequence in (X,d), if a sequence is Sd,αp,q-convergent to x0 then it is strongly wd,βp′,q′-summable to x0.
Proof. (i) Omitted.
(ii) Suppose that Sd,αp,q-limxk=x0 and (xk)∈ℓ∞. Then there exists some M>0 such that d(xk,x0)<M for all k, then for every ε>0 we may write
1(q′n−p′n)βq′n∑k=p′n+1d(xk,x0)=1(q′n−p′n)βq′n−p′n∑k=qn−pn+1d(xk,x0)+1(q′n−p′n)βqn∑k=pn+1d(xk,x0)≤(q′n−p′n)−(qn−pn)(q′n−p′n)βM+1(q′n−p′n)βqn∑k=pn+1d(xk,x0)≤(q′n−p′n)−(qn−pn)β(q′n−p′n)βM+1(q′n−p′n)βqn∑k=pn+1d(xk,x0)≤(q′n−p′n(qn−pn)β−1)M+1(qn−pn)βqn∑k=pn+1d(xk,x0)≥εd(xk,x0)+1(qn−pn)βqn∑k=pn+1d(xk,x0)<εd(xk,x0)≤(q′n−p′n(qn−pn)β−1)M+M(qn−pn)α|{k∈(pn,qn]:d(xk,x0)≥ε}|+q′n−p′n(qn−pn)βε. |
This completes the proof.
The authors declare that they have no conflict of interests.
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