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Smoking Cessation Before Age 40 Years Brings Great Benefits
Chronic smoking remains a major cause of premature mortality on a global scale. Despite intensified efforts to combat this scourge, a quarter of deaths among middle-aged adults in Europe and North America are attributed to it. However, over the past decades, antismoking campaigns have borne fruit, and many smokers have quit before the age of 40 years, enabling some case-control studies.
Among those abstainers who made the right choice, the excess mortality attributable to smoking over a lifetime would be reduced by 90% compared with controls who continued smoking. The estimated benefit is clear, but the analysis lacks nuance. Is smoking cessation beneficial even at older ages? If so, is the effect measurable in terms of magnitude and speed of the effect? An article published online in The New England Journal of Medicine Evidence provided some answers to these questions.
Four-Cohort Meta-Analysis
The study was a meta-analysis of individual data collected within four national cohort studies that were linked to each country’s death registry. Two of these studies were nationally representative. The National Health Interview Survey involved a sample of US citizens living in the community, aged 20-79 years, who were included annually in the cohort between 1997 and 2018. The second, the Canadian Community Health Survey, included subjects in the same age group, with samples analyzed between 2000 and 2014.
In Norway, three cohort studies conducted between 1974 and 2003, in which participants aged 25-79 years were included, were combined to form the Norwegian Health Screening Survey. These were the Counties Study (1974-1988), the 40 Years Study (1985-1999), and the Cohort of Norway (1994-2003), respectively. The fourth cohort was established through recruitment via the UK Biobank, with adults aged 40-73 years invited to participate in the survey. The data analysis ultimately covered a relatively heterogeneous total population of 1.48 million adults, all from high-income countries and followed for 15 years. It relied on the Cox proportional hazards model applied to each study, considering smoker vs nonsmoker status, as well as the time elapsed since smoking cessation (less than 3 years, between 3 and 9 years, or at least 10 years). Statistical adjustments made in the context of multivariate Cox analysis considered age, education, alcohol consumption, and obesity.
Excess Mortality Confirmed
At the end of follow-up, 122,697 deaths were recorded. The comparison of smokers and nonsmokers confirmed smoking-related excess mortality, with adjusted hazard ratios (HRs) estimated at 2.80 for women and 2.70 for men. Smoking shortened life expectancy in the 40- to 79-year-age group by 12 years for women and 13 years for men, in terms of overall mortality. In terms of smoking-attributable specific mortality, the corresponding figures reached 24 and 26 years, respectively. Respiratory diseases ranked highest in both sexes (HR, 7.6 for women and 6.3 for men), followed by cardiovascular diseases (HR, 3.1 for women and 2.9 for men) and cancers (HR, 2.8 for women and 3.1 for men).
The Earlier, the Better
Smoking cessation halves overall excess mortality. Above all, quitting before age 40 years brings overall mortality back to the level of nonsmokers as early as the third year after quitting. The excess mortality decreases even more as the cessation period is prolonged, even after age 40 years. Thus, cessation ≥ 10 years in smokers aged 40-49 years almost cancels out overall excess mortality (-99% in women, -96% in men). The trend is almost as favorable in the older age group (50-59 years), with corresponding figures of -95% and -92%, respectively.
Long-term survival increases in the early years after cessation, especially if it occurs at a younger age, but the benefit remains tangible even in older smokers. Thus, cessation of less than 3 years, effective in patients aged 50-59 years, reduces overall excess mortality by 63% in women and 54% in men. In patients aged 60-79 years, the figures are -40% and -33%, respectively.
Naturally, the earlier the cessation, the greater the number of years gained. It is 12 years for cessation before age 40 years, reduced to 6 years for cessation between 40 and 49 years, and 2.5 years when it is even later (50-59 years). These quantitative results are approximate, given the methodology (a meta-analysis) and some heterogeneity in the studies, as well as the multitude of potential confounding factors that have not all been considered. Nevertheless, the results probably contain a kernel of truth, and their optimistic implications should be highlighted to encourage smokers to abstain, even older ones. Better late than never, even if the benefit of cessation is maximal when it occurs as early as possible, knowing that a minimum of 3 years of cessation would be sufficient to gain years of life.
This story was translated from JIM, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
Chronic smoking remains a major cause of premature mortality on a global scale. Despite intensified efforts to combat this scourge, a quarter of deaths among middle-aged adults in Europe and North America are attributed to it. However, over the past decades, antismoking campaigns have borne fruit, and many smokers have quit before the age of 40 years, enabling some case-control studies.
Among those abstainers who made the right choice, the excess mortality attributable to smoking over a lifetime would be reduced by 90% compared with controls who continued smoking. The estimated benefit is clear, but the analysis lacks nuance. Is smoking cessation beneficial even at older ages? If so, is the effect measurable in terms of magnitude and speed of the effect? An article published online in The New England Journal of Medicine Evidence provided some answers to these questions.
Four-Cohort Meta-Analysis
The study was a meta-analysis of individual data collected within four national cohort studies that were linked to each country’s death registry. Two of these studies were nationally representative. The National Health Interview Survey involved a sample of US citizens living in the community, aged 20-79 years, who were included annually in the cohort between 1997 and 2018. The second, the Canadian Community Health Survey, included subjects in the same age group, with samples analyzed between 2000 and 2014.
In Norway, three cohort studies conducted between 1974 and 2003, in which participants aged 25-79 years were included, were combined to form the Norwegian Health Screening Survey. These were the Counties Study (1974-1988), the 40 Years Study (1985-1999), and the Cohort of Norway (1994-2003), respectively. The fourth cohort was established through recruitment via the UK Biobank, with adults aged 40-73 years invited to participate in the survey. The data analysis ultimately covered a relatively heterogeneous total population of 1.48 million adults, all from high-income countries and followed for 15 years. It relied on the Cox proportional hazards model applied to each study, considering smoker vs nonsmoker status, as well as the time elapsed since smoking cessation (less than 3 years, between 3 and 9 years, or at least 10 years). Statistical adjustments made in the context of multivariate Cox analysis considered age, education, alcohol consumption, and obesity.
Excess Mortality Confirmed
At the end of follow-up, 122,697 deaths were recorded. The comparison of smokers and nonsmokers confirmed smoking-related excess mortality, with adjusted hazard ratios (HRs) estimated at 2.80 for women and 2.70 for men. Smoking shortened life expectancy in the 40- to 79-year-age group by 12 years for women and 13 years for men, in terms of overall mortality. In terms of smoking-attributable specific mortality, the corresponding figures reached 24 and 26 years, respectively. Respiratory diseases ranked highest in both sexes (HR, 7.6 for women and 6.3 for men), followed by cardiovascular diseases (HR, 3.1 for women and 2.9 for men) and cancers (HR, 2.8 for women and 3.1 for men).
The Earlier, the Better
Smoking cessation halves overall excess mortality. Above all, quitting before age 40 years brings overall mortality back to the level of nonsmokers as early as the third year after quitting. The excess mortality decreases even more as the cessation period is prolonged, even after age 40 years. Thus, cessation ≥ 10 years in smokers aged 40-49 years almost cancels out overall excess mortality (-99% in women, -96% in men). The trend is almost as favorable in the older age group (50-59 years), with corresponding figures of -95% and -92%, respectively.
Long-term survival increases in the early years after cessation, especially if it occurs at a younger age, but the benefit remains tangible even in older smokers. Thus, cessation of less than 3 years, effective in patients aged 50-59 years, reduces overall excess mortality by 63% in women and 54% in men. In patients aged 60-79 years, the figures are -40% and -33%, respectively.
Naturally, the earlier the cessation, the greater the number of years gained. It is 12 years for cessation before age 40 years, reduced to 6 years for cessation between 40 and 49 years, and 2.5 years when it is even later (50-59 years). These quantitative results are approximate, given the methodology (a meta-analysis) and some heterogeneity in the studies, as well as the multitude of potential confounding factors that have not all been considered. Nevertheless, the results probably contain a kernel of truth, and their optimistic implications should be highlighted to encourage smokers to abstain, even older ones. Better late than never, even if the benefit of cessation is maximal when it occurs as early as possible, knowing that a minimum of 3 years of cessation would be sufficient to gain years of life.
This story was translated from JIM, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
Chronic smoking remains a major cause of premature mortality on a global scale. Despite intensified efforts to combat this scourge, a quarter of deaths among middle-aged adults in Europe and North America are attributed to it. However, over the past decades, antismoking campaigns have borne fruit, and many smokers have quit before the age of 40 years, enabling some case-control studies.
Among those abstainers who made the right choice, the excess mortality attributable to smoking over a lifetime would be reduced by 90% compared with controls who continued smoking. The estimated benefit is clear, but the analysis lacks nuance. Is smoking cessation beneficial even at older ages? If so, is the effect measurable in terms of magnitude and speed of the effect? An article published online in The New England Journal of Medicine Evidence provided some answers to these questions.
Four-Cohort Meta-Analysis
The study was a meta-analysis of individual data collected within four national cohort studies that were linked to each country’s death registry. Two of these studies were nationally representative. The National Health Interview Survey involved a sample of US citizens living in the community, aged 20-79 years, who were included annually in the cohort between 1997 and 2018. The second, the Canadian Community Health Survey, included subjects in the same age group, with samples analyzed between 2000 and 2014.
In Norway, three cohort studies conducted between 1974 and 2003, in which participants aged 25-79 years were included, were combined to form the Norwegian Health Screening Survey. These were the Counties Study (1974-1988), the 40 Years Study (1985-1999), and the Cohort of Norway (1994-2003), respectively. The fourth cohort was established through recruitment via the UK Biobank, with adults aged 40-73 years invited to participate in the survey. The data analysis ultimately covered a relatively heterogeneous total population of 1.48 million adults, all from high-income countries and followed for 15 years. It relied on the Cox proportional hazards model applied to each study, considering smoker vs nonsmoker status, as well as the time elapsed since smoking cessation (less than 3 years, between 3 and 9 years, or at least 10 years). Statistical adjustments made in the context of multivariate Cox analysis considered age, education, alcohol consumption, and obesity.
Excess Mortality Confirmed
At the end of follow-up, 122,697 deaths were recorded. The comparison of smokers and nonsmokers confirmed smoking-related excess mortality, with adjusted hazard ratios (HRs) estimated at 2.80 for women and 2.70 for men. Smoking shortened life expectancy in the 40- to 79-year-age group by 12 years for women and 13 years for men, in terms of overall mortality. In terms of smoking-attributable specific mortality, the corresponding figures reached 24 and 26 years, respectively. Respiratory diseases ranked highest in both sexes (HR, 7.6 for women and 6.3 for men), followed by cardiovascular diseases (HR, 3.1 for women and 2.9 for men) and cancers (HR, 2.8 for women and 3.1 for men).
The Earlier, the Better
Smoking cessation halves overall excess mortality. Above all, quitting before age 40 years brings overall mortality back to the level of nonsmokers as early as the third year after quitting. The excess mortality decreases even more as the cessation period is prolonged, even after age 40 years. Thus, cessation ≥ 10 years in smokers aged 40-49 years almost cancels out overall excess mortality (-99% in women, -96% in men). The trend is almost as favorable in the older age group (50-59 years), with corresponding figures of -95% and -92%, respectively.
Long-term survival increases in the early years after cessation, especially if it occurs at a younger age, but the benefit remains tangible even in older smokers. Thus, cessation of less than 3 years, effective in patients aged 50-59 years, reduces overall excess mortality by 63% in women and 54% in men. In patients aged 60-79 years, the figures are -40% and -33%, respectively.
Naturally, the earlier the cessation, the greater the number of years gained. It is 12 years for cessation before age 40 years, reduced to 6 years for cessation between 40 and 49 years, and 2.5 years when it is even later (50-59 years). These quantitative results are approximate, given the methodology (a meta-analysis) and some heterogeneity in the studies, as well as the multitude of potential confounding factors that have not all been considered. Nevertheless, the results probably contain a kernel of truth, and their optimistic implications should be highlighted to encourage smokers to abstain, even older ones. Better late than never, even if the benefit of cessation is maximal when it occurs as early as possible, knowing that a minimum of 3 years of cessation would be sufficient to gain years of life.
This story was translated from JIM, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
Does the Internet Protect the Elderly From Cognitive Decline?
Several cross-sectional and longitudinal studies (though with relatively short follow-up periods) suggest that regular Internet use helps maintain cognitive reserve, although some observers have voiced skepticism. This hypothesis is particularly relevant for older patients facing the potentially detrimental effects of brain aging. According to some studies, memory, cognitive performance, and verbal reasoning tend to be better preserved among Internet users.
Several factors come into play, including socioeconomic disparities, socio-educational level, and generational differences, since Internet usage varies qualitatively and quantitatively with age. Older patients theoretically have more limited Internet usage. Under these conditions, the effect on cognitive functions would likely be modest compared with generations who were immersed in digital technology early on and tend to overuse it. After a certain age, accelerated brain aging would weigh much more heavily than any potential positive effects of the Internet. It is worth noting that the negative effects of Internet use have mainly been studied in young subjects, thus there is a lack of data concerning older patients.
Nearly 20,000 Participants
These considerations highlight the significance of a longitudinal cohort study that included 18,154 adults aged 50-64.9 years who were free from any dementia at baseline. These adults were participating in the Health and Retirement Study. The median follow-up period was 7.9 years, and follow-up extended to 17.1 years in some cases. Given that adults with better cognitive health are likely to self-select as regular users, the propensity score method was employed to control for this nonrandom factor using inverse probability weighting.
The risk for dementia based on initial Internet use was estimated using the Cox proportional hazards model, incorporating potentially late entry into the workforce and several covariables. Interactions with education level, gender, generation, and ethnic origin were also considered. Cumulative Internet exposure in terms of regular periodic use throughout life was included in the statistical analysis, as well as the hours spent on this activity each day. The analyses were conducted from September 2021 to November 2022.
Risk Nearly Halved
Regular Internet use was associated with a reduced risk for dementia, compared with irregular use. The hazard ratio (HR) for dementia was estimated at 0.57. After adjustment for the nonrandom factor of self-selection, this association persisted, and the HR decreased to 0.54. Accounting for baseline cognitive decline did not substantially change these results and yielded an HR of 0.62. The difference in risk between regular and irregular users was not altered by considering potential confounding factors such as education level, ethnic origin, gender, or generation. The longer the cumulative exposure over life, the lower the risk for dementia during follow-up.
The relationship between dementia risk and daily Internet usage hours seems to follow a U-shaped curve, with the lowest risk observed for durations between 0.1 and 2 hours. However, these estimates did not reach statistical significance because of the small sample size analyzed.
The risk for dementia appears to be approximately twice as low among regular Internet users compared with nonusers. This hypothesis deserves serious consideration because of the large sample size and long follow-up duration, as well as careful consideration of as many potential confounding factors as possible. Potential negative effects remain to be clarified as the study was not designed to detect them. The results of previous studies suggest that Internet usage should be moderate for optimal benefit, with approximately 2 hours per day being the most suitable duration, regardless of age, until proven otherwise.
This story was translated from JIM, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
Several cross-sectional and longitudinal studies (though with relatively short follow-up periods) suggest that regular Internet use helps maintain cognitive reserve, although some observers have voiced skepticism. This hypothesis is particularly relevant for older patients facing the potentially detrimental effects of brain aging. According to some studies, memory, cognitive performance, and verbal reasoning tend to be better preserved among Internet users.
Several factors come into play, including socioeconomic disparities, socio-educational level, and generational differences, since Internet usage varies qualitatively and quantitatively with age. Older patients theoretically have more limited Internet usage. Under these conditions, the effect on cognitive functions would likely be modest compared with generations who were immersed in digital technology early on and tend to overuse it. After a certain age, accelerated brain aging would weigh much more heavily than any potential positive effects of the Internet. It is worth noting that the negative effects of Internet use have mainly been studied in young subjects, thus there is a lack of data concerning older patients.
Nearly 20,000 Participants
These considerations highlight the significance of a longitudinal cohort study that included 18,154 adults aged 50-64.9 years who were free from any dementia at baseline. These adults were participating in the Health and Retirement Study. The median follow-up period was 7.9 years, and follow-up extended to 17.1 years in some cases. Given that adults with better cognitive health are likely to self-select as regular users, the propensity score method was employed to control for this nonrandom factor using inverse probability weighting.
The risk for dementia based on initial Internet use was estimated using the Cox proportional hazards model, incorporating potentially late entry into the workforce and several covariables. Interactions with education level, gender, generation, and ethnic origin were also considered. Cumulative Internet exposure in terms of regular periodic use throughout life was included in the statistical analysis, as well as the hours spent on this activity each day. The analyses were conducted from September 2021 to November 2022.
Risk Nearly Halved
Regular Internet use was associated with a reduced risk for dementia, compared with irregular use. The hazard ratio (HR) for dementia was estimated at 0.57. After adjustment for the nonrandom factor of self-selection, this association persisted, and the HR decreased to 0.54. Accounting for baseline cognitive decline did not substantially change these results and yielded an HR of 0.62. The difference in risk between regular and irregular users was not altered by considering potential confounding factors such as education level, ethnic origin, gender, or generation. The longer the cumulative exposure over life, the lower the risk for dementia during follow-up.
The relationship between dementia risk and daily Internet usage hours seems to follow a U-shaped curve, with the lowest risk observed for durations between 0.1 and 2 hours. However, these estimates did not reach statistical significance because of the small sample size analyzed.
The risk for dementia appears to be approximately twice as low among regular Internet users compared with nonusers. This hypothesis deserves serious consideration because of the large sample size and long follow-up duration, as well as careful consideration of as many potential confounding factors as possible. Potential negative effects remain to be clarified as the study was not designed to detect them. The results of previous studies suggest that Internet usage should be moderate for optimal benefit, with approximately 2 hours per day being the most suitable duration, regardless of age, until proven otherwise.
This story was translated from JIM, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
Several cross-sectional and longitudinal studies (though with relatively short follow-up periods) suggest that regular Internet use helps maintain cognitive reserve, although some observers have voiced skepticism. This hypothesis is particularly relevant for older patients facing the potentially detrimental effects of brain aging. According to some studies, memory, cognitive performance, and verbal reasoning tend to be better preserved among Internet users.
Several factors come into play, including socioeconomic disparities, socio-educational level, and generational differences, since Internet usage varies qualitatively and quantitatively with age. Older patients theoretically have more limited Internet usage. Under these conditions, the effect on cognitive functions would likely be modest compared with generations who were immersed in digital technology early on and tend to overuse it. After a certain age, accelerated brain aging would weigh much more heavily than any potential positive effects of the Internet. It is worth noting that the negative effects of Internet use have mainly been studied in young subjects, thus there is a lack of data concerning older patients.
Nearly 20,000 Participants
These considerations highlight the significance of a longitudinal cohort study that included 18,154 adults aged 50-64.9 years who were free from any dementia at baseline. These adults were participating in the Health and Retirement Study. The median follow-up period was 7.9 years, and follow-up extended to 17.1 years in some cases. Given that adults with better cognitive health are likely to self-select as regular users, the propensity score method was employed to control for this nonrandom factor using inverse probability weighting.
The risk for dementia based on initial Internet use was estimated using the Cox proportional hazards model, incorporating potentially late entry into the workforce and several covariables. Interactions with education level, gender, generation, and ethnic origin were also considered. Cumulative Internet exposure in terms of regular periodic use throughout life was included in the statistical analysis, as well as the hours spent on this activity each day. The analyses were conducted from September 2021 to November 2022.
Risk Nearly Halved
Regular Internet use was associated with a reduced risk for dementia, compared with irregular use. The hazard ratio (HR) for dementia was estimated at 0.57. After adjustment for the nonrandom factor of self-selection, this association persisted, and the HR decreased to 0.54. Accounting for baseline cognitive decline did not substantially change these results and yielded an HR of 0.62. The difference in risk between regular and irregular users was not altered by considering potential confounding factors such as education level, ethnic origin, gender, or generation. The longer the cumulative exposure over life, the lower the risk for dementia during follow-up.
The relationship between dementia risk and daily Internet usage hours seems to follow a U-shaped curve, with the lowest risk observed for durations between 0.1 and 2 hours. However, these estimates did not reach statistical significance because of the small sample size analyzed.
The risk for dementia appears to be approximately twice as low among regular Internet users compared with nonusers. This hypothesis deserves serious consideration because of the large sample size and long follow-up duration, as well as careful consideration of as many potential confounding factors as possible. Potential negative effects remain to be clarified as the study was not designed to detect them. The results of previous studies suggest that Internet usage should be moderate for optimal benefit, with approximately 2 hours per day being the most suitable duration, regardless of age, until proven otherwise.
This story was translated from JIM, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
What is the link between cellphones and male fertility?
Infertility affects approximately one in six couples worldwide. More than half the time, it is the man’s low sperm quality that is to blame. Over the last three decades, sperm quality seems to have declined for no clearly identifiable reason. Theories are running rampant without anyone having the proof to back them up.
Potential Causes
The environment, lifestyle, excess weight or obesity, smoking, alcohol consumption, and psychological stress have all been alternately offered up as potential causes, following low-quality epidemiological studies. Cellphones are not exempt from this list, due to their emission of high-frequency (800-2200 MHz) electromagnetic waves that can be absorbed by the body.
Clinical trials conducted in rats or mice suggest that these waves can affect sperm quality and lead to histological changes to the testicles, bearing in mind that the conditions met in these trials are very far from our day-to-day exposure to electromagnetic waves, mostly via our cellphones.
The same observation can be made about experiments conducted on human sperm in vitro, but changes to the latter caused by electromagnetic waves leave doubts. Observational studies are rare, carried out in small cohorts, and marred by largely conflicting results. Publication bias plays a major role, just as much as the abundance of potential confounding factors does.
Swiss Observational Study
An observational study carried out in Switzerland had the benefit of involving a large cohort of 2886 young men who were representative of the general population. The participants completed an online questionnaire describing their relationship with their cellphone in detail and in qualitative and quantitative terms.
The study was launched in 2005, before cellphone use became so widespread, and this timeline was considered when looking for a link between cellphone exposure and sperm quality. In addition, multiple adjustments were made in the multivariate analyses to account for as many potential confounding factors as possible.
The participants, aged between 18 and 22 years, were recruited during a 3-day period to assess their suitability for military service. Each year, this cohort makes up 97% of the male population in Switzerland in this age range, with the remaining 3% being excluded from the selection process due to disability or chronic illness.
Regardless of the review board’s decision, subjects wishing to take part in the study were given a detailed description of what it involved, a consent form, and two questionnaires. The first focused on the individual directly, asking questions about his health and lifestyle. The second, intended for his parents, dealt with the period before conception.
This recruitment, which took place between September 2005 and November 2018, involved the researchers contacting 106,924 men. Ultimately, only 5.3% of subjects contacted returned the completed documentation. In the end, the study involved 2886 participants (3.1%) who provided all the necessary information, especially the laboratory testing (including a sperm analysis) needed to meet the study objectives. The number of hours spent on a smartphone and how it was used were routinely considered, as was sperm quality (volume, concentration, and total sperm count, as well as sperm mobility and morphology).
Significant Associations
A data analysis using an adjusted linear model revealed a significant association between frequent phone use (> 20 times per day) and lower sperm concentration (in mL) (adjusted β: -0.152, 95% CI -0.316 to 0.011). The same was found for their total concentration in ejaculate (adjusted β: -0.271, 95% CI -0.515 to -0.027).
An adjusted logistic regression analysis estimated that the risk for subnormal male fertility levels, as determined by the World Health Organization (WHO), was increased by at most 30%, when referring to the concentration of sperm per mL (21% in terms of total concentration). This inverse link was shown to be more pronounced during the first phase of the study (2005-2007), compared with the other two phases (2008-2011 and 2012-2018). Yet no links involving sperm mobility or morphology were found, and carrying a cellphone in a trouser pocket had no impact on the results.
This study certainly involves a large cohort of nearly 3000 young men. It is, nonetheless, retrospective, and its methodology, despite being better than that of previous studies, is still open to criticism. Its results can only fuel hypotheses, nothing more. Only prospective cohort studies will allow conclusions to be drawn and, in the meantime,
This article was translated from JIM, which is part of the Medscape professional network. A version of this article appeared on Medscape.com.
Infertility affects approximately one in six couples worldwide. More than half the time, it is the man’s low sperm quality that is to blame. Over the last three decades, sperm quality seems to have declined for no clearly identifiable reason. Theories are running rampant without anyone having the proof to back them up.
Potential Causes
The environment, lifestyle, excess weight or obesity, smoking, alcohol consumption, and psychological stress have all been alternately offered up as potential causes, following low-quality epidemiological studies. Cellphones are not exempt from this list, due to their emission of high-frequency (800-2200 MHz) electromagnetic waves that can be absorbed by the body.
Clinical trials conducted in rats or mice suggest that these waves can affect sperm quality and lead to histological changes to the testicles, bearing in mind that the conditions met in these trials are very far from our day-to-day exposure to electromagnetic waves, mostly via our cellphones.
The same observation can be made about experiments conducted on human sperm in vitro, but changes to the latter caused by electromagnetic waves leave doubts. Observational studies are rare, carried out in small cohorts, and marred by largely conflicting results. Publication bias plays a major role, just as much as the abundance of potential confounding factors does.
Swiss Observational Study
An observational study carried out in Switzerland had the benefit of involving a large cohort of 2886 young men who were representative of the general population. The participants completed an online questionnaire describing their relationship with their cellphone in detail and in qualitative and quantitative terms.
The study was launched in 2005, before cellphone use became so widespread, and this timeline was considered when looking for a link between cellphone exposure and sperm quality. In addition, multiple adjustments were made in the multivariate analyses to account for as many potential confounding factors as possible.
The participants, aged between 18 and 22 years, were recruited during a 3-day period to assess their suitability for military service. Each year, this cohort makes up 97% of the male population in Switzerland in this age range, with the remaining 3% being excluded from the selection process due to disability or chronic illness.
Regardless of the review board’s decision, subjects wishing to take part in the study were given a detailed description of what it involved, a consent form, and two questionnaires. The first focused on the individual directly, asking questions about his health and lifestyle. The second, intended for his parents, dealt with the period before conception.
This recruitment, which took place between September 2005 and November 2018, involved the researchers contacting 106,924 men. Ultimately, only 5.3% of subjects contacted returned the completed documentation. In the end, the study involved 2886 participants (3.1%) who provided all the necessary information, especially the laboratory testing (including a sperm analysis) needed to meet the study objectives. The number of hours spent on a smartphone and how it was used were routinely considered, as was sperm quality (volume, concentration, and total sperm count, as well as sperm mobility and morphology).
Significant Associations
A data analysis using an adjusted linear model revealed a significant association between frequent phone use (> 20 times per day) and lower sperm concentration (in mL) (adjusted β: -0.152, 95% CI -0.316 to 0.011). The same was found for their total concentration in ejaculate (adjusted β: -0.271, 95% CI -0.515 to -0.027).
An adjusted logistic regression analysis estimated that the risk for subnormal male fertility levels, as determined by the World Health Organization (WHO), was increased by at most 30%, when referring to the concentration of sperm per mL (21% in terms of total concentration). This inverse link was shown to be more pronounced during the first phase of the study (2005-2007), compared with the other two phases (2008-2011 and 2012-2018). Yet no links involving sperm mobility or morphology were found, and carrying a cellphone in a trouser pocket had no impact on the results.
This study certainly involves a large cohort of nearly 3000 young men. It is, nonetheless, retrospective, and its methodology, despite being better than that of previous studies, is still open to criticism. Its results can only fuel hypotheses, nothing more. Only prospective cohort studies will allow conclusions to be drawn and, in the meantime,
This article was translated from JIM, which is part of the Medscape professional network. A version of this article appeared on Medscape.com.
Infertility affects approximately one in six couples worldwide. More than half the time, it is the man’s low sperm quality that is to blame. Over the last three decades, sperm quality seems to have declined for no clearly identifiable reason. Theories are running rampant without anyone having the proof to back them up.
Potential Causes
The environment, lifestyle, excess weight or obesity, smoking, alcohol consumption, and psychological stress have all been alternately offered up as potential causes, following low-quality epidemiological studies. Cellphones are not exempt from this list, due to their emission of high-frequency (800-2200 MHz) electromagnetic waves that can be absorbed by the body.
Clinical trials conducted in rats or mice suggest that these waves can affect sperm quality and lead to histological changes to the testicles, bearing in mind that the conditions met in these trials are very far from our day-to-day exposure to electromagnetic waves, mostly via our cellphones.
The same observation can be made about experiments conducted on human sperm in vitro, but changes to the latter caused by electromagnetic waves leave doubts. Observational studies are rare, carried out in small cohorts, and marred by largely conflicting results. Publication bias plays a major role, just as much as the abundance of potential confounding factors does.
Swiss Observational Study
An observational study carried out in Switzerland had the benefit of involving a large cohort of 2886 young men who were representative of the general population. The participants completed an online questionnaire describing their relationship with their cellphone in detail and in qualitative and quantitative terms.
The study was launched in 2005, before cellphone use became so widespread, and this timeline was considered when looking for a link between cellphone exposure and sperm quality. In addition, multiple adjustments were made in the multivariate analyses to account for as many potential confounding factors as possible.
The participants, aged between 18 and 22 years, were recruited during a 3-day period to assess their suitability for military service. Each year, this cohort makes up 97% of the male population in Switzerland in this age range, with the remaining 3% being excluded from the selection process due to disability or chronic illness.
Regardless of the review board’s decision, subjects wishing to take part in the study were given a detailed description of what it involved, a consent form, and two questionnaires. The first focused on the individual directly, asking questions about his health and lifestyle. The second, intended for his parents, dealt with the period before conception.
This recruitment, which took place between September 2005 and November 2018, involved the researchers contacting 106,924 men. Ultimately, only 5.3% of subjects contacted returned the completed documentation. In the end, the study involved 2886 participants (3.1%) who provided all the necessary information, especially the laboratory testing (including a sperm analysis) needed to meet the study objectives. The number of hours spent on a smartphone and how it was used were routinely considered, as was sperm quality (volume, concentration, and total sperm count, as well as sperm mobility and morphology).
Significant Associations
A data analysis using an adjusted linear model revealed a significant association between frequent phone use (> 20 times per day) and lower sperm concentration (in mL) (adjusted β: -0.152, 95% CI -0.316 to 0.011). The same was found for their total concentration in ejaculate (adjusted β: -0.271, 95% CI -0.515 to -0.027).
An adjusted logistic regression analysis estimated that the risk for subnormal male fertility levels, as determined by the World Health Organization (WHO), was increased by at most 30%, when referring to the concentration of sperm per mL (21% in terms of total concentration). This inverse link was shown to be more pronounced during the first phase of the study (2005-2007), compared with the other two phases (2008-2011 and 2012-2018). Yet no links involving sperm mobility or morphology were found, and carrying a cellphone in a trouser pocket had no impact on the results.
This study certainly involves a large cohort of nearly 3000 young men. It is, nonetheless, retrospective, and its methodology, despite being better than that of previous studies, is still open to criticism. Its results can only fuel hypotheses, nothing more. Only prospective cohort studies will allow conclusions to be drawn and, in the meantime,
This article was translated from JIM, which is part of the Medscape professional network. A version of this article appeared on Medscape.com.
T2D: Real benefits of new oral antidiabetic drugs
Cardiovascular disease is the most common cause of death in people living with type 2 diabetes (T2D). It is true that patient prognoses have improved with the use of metformin and by addressing cardiovascular risk factors. But the new oral antidiabetic drugs, SGLT2 (sodium glucose cotransporter-2) inhibitors (SGLT2i), and glucagon-like peptide-1 receptor agonists (GLP-1Ra) offer fresh therapeutic approaches.
A cohort of more than 2 million patients with T2D
What about in the real world, far away from the ideal conditions of randomized trials? Could combining SGLT2 inhibitors with GLP-1R agonists be even more effective?
These are the questions answered by a large retrospective cohort study in which 2.2 million patients with T2D receiving insulin were initially enrolled and monitored at 85 specialist centers spread throughout three countries (Denmark, the United Kingdom, and the United States).
Three groups were formed from this cohort according to whether they received monotherapy or combination treatments: SGLT2i (n = 143,600), GLP-1Ra (n = 186,841), and SGLT2i + GLP-1Ra (n = 108,5040). A control group received none of these treatments.
Propensity score matching took into account the following relevant variables: age, sex, ischemic heart disease, hypertension, chronic kidney disease, heart failure, and glycated hemoglobin. The data was analyzed using the Cox’s proportional hazards model, with follow-up at 5 years.
Real-world benefits – Even better when combined
The inter-group comparison suggests that oral antidiabetic agents are effective when taking into account three major events:
All-cause mortality: SGLT2i (hazard ratio, 0.49; confidence interval 95% 0.48-0.50); GLP-1Ra (HR, 0.47; CI 95% 0.46-0.48); SGLT2i + GLP-1Ra (HR, 0.25; CI 95% 0.24-0.26).
Admissions rate: respectively HR: 0.73 (0.72-0.74); 0.69 (0.68-0.69); 0.60 (0.59-0.61).
Myocardial infarction rate: respectively HR: 0.75 (0.72-0.78); 0.70 (0.68-0.73); 0.63 (0.60-0.66).
A complementary sub-analysis also revealed a more significant reduction in all-cause mortality in the event of exposure to the combination of two antidiabetic drugs versus SGLT2i alone (HR, 0.53 [0.50-0.55]) and GLP-1Ra as monotherapy (HR, 0.56 [0.54-0.59]).
This real-world retrospective cohort study involves a large sample size: more than 400,000 patients with T2D treated with new oral antidiabetic drugs and as many control patients. It suggests that SGLT2 inhibitors and GLP-1R agonists have a significant effect on overall mortality, as well as on the risk of myocardial infarction and the admissions rate. Yes, it is retrospective, but its findings are in line with those from the most recent and conclusive randomized trials that suggest a cardio- and nephroprotective effect, at least with regard to SGLT2 inhibitors.
This article was translated from JIM and a version appeared on Medscape.com.
Cardiovascular disease is the most common cause of death in people living with type 2 diabetes (T2D). It is true that patient prognoses have improved with the use of metformin and by addressing cardiovascular risk factors. But the new oral antidiabetic drugs, SGLT2 (sodium glucose cotransporter-2) inhibitors (SGLT2i), and glucagon-like peptide-1 receptor agonists (GLP-1Ra) offer fresh therapeutic approaches.
A cohort of more than 2 million patients with T2D
What about in the real world, far away from the ideal conditions of randomized trials? Could combining SGLT2 inhibitors with GLP-1R agonists be even more effective?
These are the questions answered by a large retrospective cohort study in which 2.2 million patients with T2D receiving insulin were initially enrolled and monitored at 85 specialist centers spread throughout three countries (Denmark, the United Kingdom, and the United States).
Three groups were formed from this cohort according to whether they received monotherapy or combination treatments: SGLT2i (n = 143,600), GLP-1Ra (n = 186,841), and SGLT2i + GLP-1Ra (n = 108,5040). A control group received none of these treatments.
Propensity score matching took into account the following relevant variables: age, sex, ischemic heart disease, hypertension, chronic kidney disease, heart failure, and glycated hemoglobin. The data was analyzed using the Cox’s proportional hazards model, with follow-up at 5 years.
Real-world benefits – Even better when combined
The inter-group comparison suggests that oral antidiabetic agents are effective when taking into account three major events:
All-cause mortality: SGLT2i (hazard ratio, 0.49; confidence interval 95% 0.48-0.50); GLP-1Ra (HR, 0.47; CI 95% 0.46-0.48); SGLT2i + GLP-1Ra (HR, 0.25; CI 95% 0.24-0.26).
Admissions rate: respectively HR: 0.73 (0.72-0.74); 0.69 (0.68-0.69); 0.60 (0.59-0.61).
Myocardial infarction rate: respectively HR: 0.75 (0.72-0.78); 0.70 (0.68-0.73); 0.63 (0.60-0.66).
A complementary sub-analysis also revealed a more significant reduction in all-cause mortality in the event of exposure to the combination of two antidiabetic drugs versus SGLT2i alone (HR, 0.53 [0.50-0.55]) and GLP-1Ra as monotherapy (HR, 0.56 [0.54-0.59]).
This real-world retrospective cohort study involves a large sample size: more than 400,000 patients with T2D treated with new oral antidiabetic drugs and as many control patients. It suggests that SGLT2 inhibitors and GLP-1R agonists have a significant effect on overall mortality, as well as on the risk of myocardial infarction and the admissions rate. Yes, it is retrospective, but its findings are in line with those from the most recent and conclusive randomized trials that suggest a cardio- and nephroprotective effect, at least with regard to SGLT2 inhibitors.
This article was translated from JIM and a version appeared on Medscape.com.
Cardiovascular disease is the most common cause of death in people living with type 2 diabetes (T2D). It is true that patient prognoses have improved with the use of metformin and by addressing cardiovascular risk factors. But the new oral antidiabetic drugs, SGLT2 (sodium glucose cotransporter-2) inhibitors (SGLT2i), and glucagon-like peptide-1 receptor agonists (GLP-1Ra) offer fresh therapeutic approaches.
A cohort of more than 2 million patients with T2D
What about in the real world, far away from the ideal conditions of randomized trials? Could combining SGLT2 inhibitors with GLP-1R agonists be even more effective?
These are the questions answered by a large retrospective cohort study in which 2.2 million patients with T2D receiving insulin were initially enrolled and monitored at 85 specialist centers spread throughout three countries (Denmark, the United Kingdom, and the United States).
Three groups were formed from this cohort according to whether they received monotherapy or combination treatments: SGLT2i (n = 143,600), GLP-1Ra (n = 186,841), and SGLT2i + GLP-1Ra (n = 108,5040). A control group received none of these treatments.
Propensity score matching took into account the following relevant variables: age, sex, ischemic heart disease, hypertension, chronic kidney disease, heart failure, and glycated hemoglobin. The data was analyzed using the Cox’s proportional hazards model, with follow-up at 5 years.
Real-world benefits – Even better when combined
The inter-group comparison suggests that oral antidiabetic agents are effective when taking into account three major events:
All-cause mortality: SGLT2i (hazard ratio, 0.49; confidence interval 95% 0.48-0.50); GLP-1Ra (HR, 0.47; CI 95% 0.46-0.48); SGLT2i + GLP-1Ra (HR, 0.25; CI 95% 0.24-0.26).
Admissions rate: respectively HR: 0.73 (0.72-0.74); 0.69 (0.68-0.69); 0.60 (0.59-0.61).
Myocardial infarction rate: respectively HR: 0.75 (0.72-0.78); 0.70 (0.68-0.73); 0.63 (0.60-0.66).
A complementary sub-analysis also revealed a more significant reduction in all-cause mortality in the event of exposure to the combination of two antidiabetic drugs versus SGLT2i alone (HR, 0.53 [0.50-0.55]) and GLP-1Ra as monotherapy (HR, 0.56 [0.54-0.59]).
This real-world retrospective cohort study involves a large sample size: more than 400,000 patients with T2D treated with new oral antidiabetic drugs and as many control patients. It suggests that SGLT2 inhibitors and GLP-1R agonists have a significant effect on overall mortality, as well as on the risk of myocardial infarction and the admissions rate. Yes, it is retrospective, but its findings are in line with those from the most recent and conclusive randomized trials that suggest a cardio- and nephroprotective effect, at least with regard to SGLT2 inhibitors.
This article was translated from JIM and a version appeared on Medscape.com.