Lateral epicondylosis tennis elbow is a degenerative noninflammatory condition of the common extensor origin at the lateral epicondyle of the elbow Tennis elbow has a prevalence of 1 3 peaking at age 35 50 years 1 It is associated with smoking and with a combination of repetitive and forceful manual activities 2
ntroduction: Growing evidence documents strong associations between volunteering and favorable health and well-being outcomes. However, epidemiological studies have not evaluated whether changes in volunteering are associated with subsequent health and well-being outcomes.
Methods: Data were from 12,998 participants in the Health and Retirement Study-a large, diverse, prospective, and nationally representative cohort of U.S. adults aged >50 years. Using multiple logistic, linear, and generalized linear regression models, this study evaluated if changes in volunteering (between t0, 2006/2008 and t1, 2010/2012) were associated with 34 indicators of physical health, health behaviors, and psychosocial well-being (in t2, 2014/2016). Models adjusted for sociodemographics, physical health, health behaviors, psychosocial factors, and personality, as well as volunteering and all outcomes in the prebaseline wave (t0, 2006/2008). Results accounted for multiple testing and data were analyzed in 2019.
Results: During the 4-year follow-up period, participants who volunteered ≥100 hours/year (versus 0 hours/year) had a reduced risk of mortality and physical functioning limitations, higher physical activity, and better psychosocial outcomes (higher: positive affect, optimism, and purpose in life; lower: depressive symptoms, hopelessness, loneliness, and infrequent contact with friends). Volunteering was not associated with other physical health outcomes (diabetes, hypertension, stroke, cancer, heart disease, lung disease, arthritis, overweight/obesity, cognitive impairment, and chronic pain), health behaviors (binge drinking, smoking, and sleep problems), or psychosocial outcomes (life satisfaction, mastery, health/financial mastery, depression, negative affect, perceived constraints, and contact with other family/children).
Conclusions: With further research, volunteering is an activity that physicians might suggest to their willing and able patients as a way of simultaneously enhancing health and society.
Abstract
Background
Mobile phone‐based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face‐to‐face support. In addition, mCessation can be automated and therefore provided affordably even in resource‐poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.
Objectives
To determine whether mobile phone‐based smoking cessation interventions increase smoking cessation rates in people who smoke.
Search methods
For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.
Selection criteria
Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone‐based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six‐month follow‐up.
Data collection and analysis
We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta‐analyses of the most stringent measures of abstinence at six months' follow‐up or longer, using a Mantel‐Haenszel random‐effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.
Main results
This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high‐income countries. There was moderate‐certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I2 = 71%; 13 studies, 14,133 participants). There was also moderate‐certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I2 = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high‐ and low‐intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I2 = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I2 = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower‐intensity smoking cessation support (either a lower‐intensity app or non‐app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I2 = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.
Authors' conclusions
There is moderate‐certainty evidence that automated text message‐based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate‐certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.
Plain Language Summary
Can programmes delivered by mobile phones help people to stop smoking?
Background
Tobacco smoking is a leading cause of preventable death. Mobile phones can be used to support people who want to quit smoking. In this review, we have focused on programmes that use text messages or smartphone apps to do so.
Search date
We searched for published and unpublished studies in October 2018.
Study characteristics
We included 26 randomised controlled studies (involving over 33,000 people) that compared smoking quit rates in people who received text messages or smartphone apps to help them quit, with people who did not receive these programmes. We were interested in studies that measured smoking for six months or longer.
Key results
We found that text messaging programmes may be effective in supporting people to quit, increasing quit rates by 50% to 60%. This was the case when they were compared to minimal support or were tested as an addition to other forms of stop‐smoking support. There was not enough evidence to determine the effect of smartphone apps.
Quality and completeness of the evidence
Most of the studies were of high quality, although three studies had high drop out rates. We are moderately confident in the results of the text messaging interventions, but there were some issues with unexplained differences between study findings and for some comparisons there was not much data. We have low confidence in the results concerning smartphone apps, and more studies are needed in this field.
AIMS:
The Hygia Chronotherapy Trial, conducted within the clinical primary care setting, was designed to test whether bedtime in comparison to usual upon awakening hypertension therapy exerts better cardiovascular disease (CVD) risk reduction.
METHODS AND RESULTS:
In this multicentre, controlled, prospective endpoint trial, 19 084 hypertensive patients (10 614 men/8470 women, 60.5 ± 13.7 years of age) were assigned (1:1) to ingest the entire daily dose of ≥1 hypertension medications at bedtime (n = 9552) or all of them upon awakening (n = 9532). At inclusion and at every scheduled clinic visit (at least annually) throughout follow-up, ambulatory blood pressure (ABP) monitoring was performed for 48 h. During the 6.3-year median patient follow-up, 1752 participants experienced the primary CVD outcome (CVD death, myocardial infarction, coronary revascularization, heart failure, or stroke). Patients of the bedtime, compared with the upon-waking, treatment-time regimen showed significantly lower hazard ratio-adjusted for significant influential characteristics of age, sex, type 2 diabetes, chronic kidney disease, smoking, HDL cholesterol, asleep systolic blood pressure (BP) mean, sleep-time relative systolic BP decline, and previous CVD event-of the primary CVD outcome [0.55 (95% CI 0.50-0.61), P < 0.001] and each of its single components (P < 0.001 in all cases), i.e. CVD death [0.44 (0.34-0.56)], myocardial infarction [0.66 (0.52-0.84)], coronary revascularization [0.60 (0.47-0.75)], heart failure [0.58 (0.49-0.70)], and stroke [0.51 (0.41-0.63)].
CONCLUSION:
Routine ingestion by hypertensive patients of ≥1 prescribed BP-lowering medications at bedtime, as opposed to upon waking, results in improved ABP control (significantly enhanced decrease in asleep BP and increased sleep-time relative BP decline, i.e. BP dipping) and, most importantly, markedly diminished occurrence of major CVD events.
TRIAL REGISTRATION:
ClinicalTrials.gov, number NCT00741585.
There are immediate and long-term health benefits of quitting for all smokers.
Beneficial health changes that take place:
BACKGROUND
E-cigarettes are commonly used in attempts to stop smoking, but evidence is limited regarding their effectiveness as compared with that of nicotine products approved as smoking-cessation treatments.
METHODS
We randomly assigned adults attending U.K. National Health Service stop-smoking services to either nicotine-replacement products of their choice, including product combinations, provided for up to 3 months, or an e-cigarette starter pack (a second-generation refillable e-cigarette with one bottle of nicotine e-liquid [18 mg per milliliter]), with a recommendation to purchase further e-liquids of the flavor and strength of their choice. Treatment included weekly behavioral support for at least 4 weeks. The primary outcome was sustained abstinence for 1 year, which was validated biochemically at the final visit. Participants who were lost to follow-up or did not provide biochemical validation were considered to not be abstinent. Secondary outcomes included participant-reported treatment usage and respiratory symptoms.
RESULTS
A total of 886 participants underwent randomization. The 1-year abstinence rate was 18.0% in the e-cigarette group, as compared with 9.9% in the nicotine-replacement group (relative risk, 1.83; 95% confidence interval [CI], 1.30 to 2.58; P<0.001). Among participants with 1-year abstinence, those in the e-cigarette group were more likely than those in the nicotine-replacement group to use their assigned product at 52 weeks (80% [63 of 79 participants] vs. 9% [4 of 44 participants]). Overall, throat or mouth irritation was reported more frequently in the e-cigarette group (65.3%, vs. 51.2% in the nicotine-replacement group) and nausea more frequently in the nicotine-replacement group (37.9%, vs. 31.3% in the e-cigarette group). The e-cigarette group reported greater declines in the incidence of cough and phlegm production from baseline to 52 weeks than did the nicotine-replacement group (relative risk for cough, 0.8; 95% CI, 0.6 to 0.9; relative risk for phlegm, 0.7; 95% CI, 0.6 to 0.9). There were no significant between-group differences in the incidence of wheezing or shortness of breath.
CONCLUSIONS
E-cigarettes were more effective for smoking cessation than nicotine-replacement therapy, when both products were accompanied by behavioral support. (Funded by the National Institute for Health Research and Cancer Research UK; Current Controlled Trials number, ISRCTN60477608.)
Choose a treatment plan that fits the patient.
A comprehensive approach to cessation is more successful than any one mode of therapy. For patients ready to commit to quitting, use both behavioral interventions and pharmacologic therapy. Good evidence suggests that each of the following pharmacotherapies can effectively support smoking cessation, unless contraindications are present:
• Nicotine replacement therapy (gum, lozenges, patches, inhalers, and nasal spray)
• Bupropion (a norepinephrine/dopamine reuptake inhibitor and nicotinic acetylcholine receptor antagonist)
• Varenicline (a partial agonist of the alpha-4/beta-2 nicotinic acetylcholine receptor)
