Truly global standards and definitions will likely never exist for tobacco control surveillance. One difference across definitions of smoking status is whether or not a lifetime consumption of 100 cigarettes is a necessary criterion for ever and current smoking. Frequently asked questions about this measure demonstrate a need for information on its development and appropriateness in different settings. This commentary attempts to assemble information on the origin and adoption of this measure and provide some critical commentary on its usefulness.The question has been traced to Canadian and American mortality cohort studies from the mid-1950s. From there it has spread to inconsistent use in many settings. To our knowledge, it was not originally (or since) empirically defined as a threshold of exposure related to health consequences or future smoking risk when used in youth.Anecdotal evidence over several decades, however, shows the question has pragmatic utility in self-report data collection. It is a useful, if somewhat arbitrary, screener for “never regular” tobacco use among adults, where never smoking needs to be defined in data collection. Use of the criterion may lower prevalence estimates somewhat. Definitions must always be considered when creating time-trends or international comparisons.There are also circumstances where it is inappropriate to exclude individuals who do not meet this criterion from further data collection, or reports. For research in youth, the criterion typically should be used only with more detailed information about experimentation, but it may be a useful additional indicator of established smoking.

Intimate partner violence (IPV) is a significant public health problem. There is a lack of data on IPV risk factors from longitudinal studies and from low and middle income countries. Identifying risk factors is needed to inform the design of appropriate IPV interventions. Data were from the Rakai Community Cohort Study annual surveys between 2000 and 2009. Female participants who had at least one sexual partner during this period and had data on IPV over the study period were included in analyses (N = 15081). Factors from childhood and early adulthood as well as contemporary factors were considered in separate models. Logistic regression was used to assess early risk factors for IPV during the study period. Longitudinal data analysis was used to assess contemporary risk factors in the past year for IPV in the current year, using a population-averaged multivariable logistic regression model. Risk factors for IPV from childhood and early adulthood included sexual abuse in childhood or adolescence, earlier age at first sex, lower levels of education, and forced first sex. Contemporary risk factors included younger age, being married, relationships of shorter duration, having a partner who is the same age or younger, alcohol use before sex by women and by their partners, and thinking that violence is acceptable. HIV infection and pregnancy were not associated with an increased odds of IPV. Using longitudinal data, this study identified a number of risk factors for IPV. These findings are useful for the development of prevention strategies to prevent and mitigate IPV in women.

Diagnosis of influenza in older adults may be complicated by atypical presentations or when patients present with complications of an underlying illness. We aimed to identify clinical characteristics and epidemiological factors associated with influenza among community-dwelling adults aged ≥60 years presenting to emergency departments. We identified patients with influenza-compatible chief complaints presenting to emergency departments of six acute care hospitals in Ontario, Canada during the 2011/12 and 2012/13 influenza seasons. Clinical characteristics, medical history and demographics were collected by patient interview, chart review and by contacting vaccine providers. Nasopharyngeal swabs were tested for influenza using polymerase chain reaction. We modeled predictors of influenza using multivariable logistic regression models that compared individuals with and without influenza. Of 1318 participants, 151 (11 %) had influenza (98 A/H3N2, 12 A/H1N1, 4 A [not sub-typed], 37 B). In the multivariable model, clinical symptoms associated with influenza were cough (OR 6.4, 95 % CI 3.2, 13.0), feverishness and/or triage temperature ≥37.2 °C (OR 3.0, 95 % CI 2.0, 4.7), 2–5 days from symptom onset to the emergency department visit (OR 2.2, 95 % CI 1.5, 3.2), and wheezing (OR 2.1, 95 % CI 1.3, 3.3). The effect of cough on influenza increased with older age. Epidemiological factors associated with increased odds for influenza included weeks when ≥10 % influenza tests from provincial laboratories were positive (OR 5.1, 95 % CI 1.2, 21.7) and exposure to a person with influenza-like illness (OR 1.9, 95 % CI 1.3, 2.8). Among participants with influenza, only 47 (31 %) met the U.S. Centers for Disease Control and Prevention criteria for influenza-like illness (temperature ≥37.8 °C and cough and/or sore throat). As in younger adults, cough and feverishness are the two symptoms most predictive of influenza in the elderly. Current influenza-like illness definitions did not adequately capture influenza in older adults.

Background: The prison setting and health status of people who experience imprisonment increase the risks of COVID-19 infection and sequelae, and other health impacts of the COVID-19 pandemic. Objectives: To conduct a mixed methods systematic review on the impacts of the COVID-19 pandemic on the health of people who experience imprisonment. Data sources: We searched Medline, PsycINFO, Embase, the Cochrane Library, Social Sciences Abstracts, CINAHL, Applied Social Sciences Index and Abstracts, Sociological Abstracts, Sociology Database, Coronavirus Research Database, ERIC, Proquest Dissertations and Theses, Web of Science, and Scopus in October 2021. We reviewed reference lists for included studies. Study eligibility criteria: Original research conducted in or after December 2019 on health impacts of the COVID-19 pandemic on adults in prisons or within three months of release. Study appraisal and synthesis methods: We used the Joanna Briggs Institute’s Critical Appraisal Checklist for Qualitative Research for qualitative studies and the Joanna Briggs Institute’s Critical Appraisal Checklist for Studies Reporting Prevalence Data for quantitative studies. We qualitized quantitative data and extracted qualitative data, coded data, and collated similar data into categories. Results: We identified 62 studies. People in prisons had disproportionately high rates of COVID-19 infection and COVID-19 mortality. During the pandemic, all-cause mortality worsened, access to health care and other services worsened, and there were major impacts on mental wellbeing and on relationships with family and staff. There was limited evidence regarding key primary and secondary prevention strategies. Limitations: Our search was limited to databases. As the COVID-19 pandemic is ongoing, more evidence will emerge. Conclusions: Prisons and people who experience imprisonment should be prioritized for COVID-19 response and recovery efforts, and an explicit focus on prisons is needed for ongoing public health work including emergency preparedness. Prospero registration number: 239324.

Background: Community quarantine is controversial, and the decision to use and prepare for it should be informed by specific quantitative evidence of benefit. Case-study reports on 2002-2004 SARS outbreaks have discussed the role of quarantine in the community in transmission. However, this literature has not yielded quantitative estimates of the reduction in secondary cases attributable to quarantine as would be seen in other areas of health policy and cost-effectiveness analysis.Methods: Using data from the 2003 Ontario, Canada, SARS outbreak, two novel expressions for the impact of quarantine are presented. Secondary Case Count Difference (SCCD) reflects reduction in the average number of transmissions arising from a SARS case in quarantine, relative to not in quarantine, at onset of symptoms. SCCD was estimated using Poisson and negative binomial regression models (with identity link function) comparing the number of secondary cases to each index case for quarantine relative to non-quarantined index cases. The inverse of this statistic is proposed as the number needed to quarantine (NNQ) to prevent one additional secondary transmission.Results: Our estimated SCCD was 0.133 fewer secondary cases per quarantined versus non-quarantined index case; and a NNQ of 7.5 exposed individuals to be placed in community quarantine to prevent one additional case of transmission in the community. This analysis suggests quarantine can be an effective preventive measure, although these estimates lack statistical precision.Conclusions: Relative to other health policy areas, literature on quarantine tends to lack in quantitative expressions of effectiveness, or agreement on how best to report differences in outcomes attributable to control measure. We hope to further this discussion through presentation of means to calculate and express the impact of population control measures. The study of quarantine effectiveness presents several methodological and statistical challenges. Further research and discussion are needed to understand the costs and benefits of enacting quarantine, and this includes a discussion of how quantitative benefit should be communicated to decision-makers and the public, and evaluated.