Search

OBJECTIVE: Recent research found that inmates experience undesirable and rapid weight gain during incarceration in Canadian federal penitentiaries. However, little is known about what factors and daily movement behaviours (e.g., physical activity, screen time, and sleep) influence weight gain during incarceration. This study examines how these 24-h movement/non-movement behaviours contribute to weight gain during incarceration. METHODS: This retrospective cohort study explored how weight change outcomes during incarceration (weight change, body mass index (BMI) change, and yearly weight gain) were influenced by physical activity, screen time, and sleep in a convenience sample of 754 inmates. The outcome measures were taken twice, once from participants’ medical chart at admission and again during a face-to-face follow-up interview (conducted in 2016–2017; mean follow-up time of 5.0 ± 8.3 years). Physical activity, screen time, and sleep were self-reported. The statistical analysis was chi-square testing, non-parametric median comparison testing, and regression analysis to control for confounders. RESULTS: Inmates who engaged in at least 60 min of daily physical activities gained less weight (4.5 kg) compared to inmates who reported not exercising (8.3 kg). Different types of exercise (cardiovascular exercises, weight lifting, and team sports) were helpful at limiting weight gain, but playing sports was the most effective. Screen time and sleep were not associated with weight gain outcomes. CONCLUSION: Among the behaviours examined, physical inactivity was significantly associated with higher weight gain during incarceration. However, even high levels of physical activity (> 60 min/day) were not sufficient to eliminate weight gain during incarceration in Canada. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.17269/s41997-018-0165-z) contains supplementary material, which is available to authorized users.

Background The coronavirus disease 2019 (COVID-19) pandemic began with a detected cluster of pneumonia cases in Wuhan, China in December 2019. Endemic transmission was recognized in Canada in early February 2020, making it urgent for public health stakeholders to have access to robust and reliable tools to support decision-making for epidemic management. The objectives of this paper are to present one of these tools-an aged-stratified dynamic compartmental model developed by the Public Health Agency of Canada in collaboration with Statistics Canada-and to model the impact of non-pharmaceutical interventions on the attack rate of COVID-19 infection in Canada. Methods This model simulates the impact of different levels of non-pharmaceutical interventions, including case detection/isolation, contact tracing/quarantine and changes in the level of physical distancing in Canada, as restrictive closures began to be lifted in May 2020. Results This model allows us to highlight the importance of a relatively high level of detection and isolation of cases, as well as tracing and quarantine of individuals in contact with those cases, in order to avoid a resurgence of the epidemic in Canada as restrictive closures are lifted. Some level of physical distancing by the public will also likely need to be maintained. Conclusion This study underlines the importance of a cautious approach to lifting restrictive closures in this second phase of the epidemic. This approach includes efforts by public health to identify cases and trace contacts, and to encourage Canadians to get tested if they are at risk of having been infected and to maintain physical distancing in public areas.

Background Very little is known about how incarceration influences a person's weight in Canada. We sought to determine how inmates' weights change during their incarceration in Canadian federal penitentiaries. Methods We performed a retrospective, longitudinal cohort study to examine weight change in Canadian federal penitentiaries. To participate, inmates had to have been incarcerated for at least 6 months at the time of the study. Current anthropometric data were measured or taken from medical records, then compared with anthropometric data from the beginning of incarceration (mean follow-up of 5.0 ± 8.3 yr). We examined 3 outcomes: change in weight (kg), change in body mass index (BMI) and rate of weight change (kg/yr) during incarceration. Results A total of 1420 inmates participated in this study. Almost three-quarters (73.0%, n = 1037)) of participants gained weight during incarceration. Inmates gained a median of 6.2 (95% confidence interval [CI] 5.6-6.9) kg, and BMI increased by 2.0 (95% CI 1.8-2.2). Obesity rates increased by 71%, from 26.6% of participants (n = 378) on admission to 45.4% of participants at follow-up (n = 645). The proportion of inmates with a BMI in the normal range (18.5-24.9) decreased by 52%. Weight gain was found to be associated with older age, region (Ontario v. Atlantic), ethnicity (Aboriginal inmates showed the highest weight gain), longer incarceration, and longer total sentence. However, weight gain was not associated with sex, feeding system or spoken language. Interpretation The Canadian correctional environment can be considered obesogenic, with most inmates experiencing undesirable and rapid weight gain during their incarceration. Rates of obesity increased dramatically during incarceration, and could put inmates at increased risk of obesity-related health problems.

ObjectiveThis study aimed to determine how inmates’ body weight changed during incarceration in Canadian federal penitentiaries, based on their history of tobacco use. Since tobacco was banned from all Canadian federal penitentiaries in 2008, little is known about the unintended health consequences of this ban, especially on inmates’ body weight.DesignCohort study.SettingParticipants were male and female inmates incarcerated for at least 6 months in Canadian federal penitentiaries. We collected data from 10 institutions in two Canadian regions (Ontario and Atlantic).ParticipantsWe collected data from 754 inmates who volunteered to participate in the study.InterventionThis study examined weight change in relation to a history of tobacco use. In 2016–2017, anthropometric data were collected and compared with recorded anthropometric data at the beginning of incarceration (mean follow-up of 5.0±8.3 years). Self-reported data on tobacco and substance use were collected. Weight change was compared between inmates with and without a history of tobacco use.OutcomesThe main outcome measures were body weight change (kg), body mass index (BMI) change (kg/m2), annual weight change (kg/year), and BMI and waist circumference (cm) at the time of the interview.ResultsDuring incarceration, ex-smokers gained more than twice the amount of weight compared with non-smokers (7.5 kg weight gain for smokers vs 3.7 kg weight gain for non-smokers). Once adjusted for covariates in a regression analysis, for inmates who gained the most weight (75th and 90th percentiles), non-smokers had, respectively, 1.64 and 2.3 lower BMI points than ex-smokers.ConclusionsDuring incarceration in Canadian federal penitentiaries, inmates with a history of tobacco use gained significantly more weight than non-smokers. This put them at increased risk of developing obesity-related health problems. This information is important for the prison setting when planning related programmes and regulation.

Our study compares adequacy of nutritional intakes among pregnant women with different prepregnancy BMI and explores associations between nutritional intakes during pregnancy and both prepregnancy BMI and gestational weight gain (GWG). We collected dietary information from a large cohort of pregnant Canadian women (n861) using a 3-d food record. We estimated usual dietary intakes of energy (E), macronutrients and micronutrients using the National Cancer Institute method. We also performed Pearson’s correlations between nutritional intakes and both prepregnancy BMI and GWG. In all BMI categories, intakes considered suboptimal (by comparison with estimated average requirements) were noted for Fe, vitamin D, folate, vitamin B6, Mg, Zn, Ca and vitamin A. Total fat intakes were above the acceptable macronutrient distribution range (AMDR) for 36 % of the women. A higher proportion of obese women had carbohydrate intakes (as %E) below the AMDR (v.normal-weight and overweight women; 19v.9 %) and Na intakes above the tolerable upper intake level (v.other BMI categories; 90v.77–78 %). In all BMI categories, median intakes of K and fibre were below adequate intake. Intakes of several nutrients (adjusted for energy) were correlated with BMI. Correlations were detected between energy-adjusted nutrient intakes and total GWG and were, for the most part, specific to certain BMI categories. Overweight and obese pregnant women appear to be the most nutritionally vulnerable. Nutrition interventions are needed to guide pregnant women toward their optimal GWG while also meeting their nutritional requirements.

Background: Assessments of the dietary intakes in various populations suggest that pregnant women have difficulty meeting all their nutritional requirements through diet alone. Few large-scale studies have considered both food sources and supplements in assessing the adequacy of nutritional intakes during pregnancy.Objective: Our study aimed to assess nutritional intakes during pregnancy by examining dietary sources and supplements. It then compared these findings with Dietary Reference Intakes.Design: We conducted a nutrition study in a large pregnancy cohort using a 3-d food record during the second trimester of pregnancy. Detailed information about supplement consumption was obtained by interview at each prenatal visit. We estimated the distribution of total usual intakes for energy, macronutrients, and micronutrients for 1533 pregnant women.Results: A third of the participants had total fat intakes that exceeded the Acceptable Micronutrient Distribution Range. A majority of women (85%) had sodium intakes above the Tolerable Upper Intake Level (UL). Median intakes for fiber and potassium were lower than Adequate Intakes. Dietary intakes of vitamin B-6, magnesium, and zinc were below the Estimated Average Requirements (EARs) for 10-15% of the women. A majority of the women had dietary intakes below the EARs for iron (97%), vitamin D (96%), and folate (70%). When we considered micronutrient intakes from both food and supplements, we found that the prevalence of inadequate intake was

There is a lack of evidence pointing to specific dietary elements related to weight gain and obesity prevention in childhood and adulthood. Dietary intake and obesity are both inherited and culturally transmitted, but most prospective studies on the association between diet and weight status do not take genetics into consideration. The objective of this study was to document the association between dietary intake at 9 years and subsequent Body Mass Index (BMI) in adolescent monozygotic boy and girl twin pairs. This research used data from 152 twin pairs. Dietary data were collected from two 24-hour-recall interviews with a parent and the child aged 9 years. Height and weight were obtained when the twins were aged 9, 12, 13, and 14 years. Intrapair variability analysis was performed to identify dietary elements related to BMI changes in subsequent years. BMI-discordant monozygotic twin pairs were also identified to analyze the dietary constituents that may have generated the discordance. After eliminating potential confounding genetic factors, pre-adolescent boys who ate fewer grain products and fruit and consumed more high-fat meat and milk had higher BMIs during adolescence; pre-adolescent girls who consumed more grain products and high-fat meat and milk had higher BMIs during adolescence. Energy intake (EI) at 9 years was not related to BMI in subsequent years. Our study suggests that messages and interventions directed at obesity prevention could take advantage of sex-specific designs and‚ eventually‚ genetic information.

We consider a discrete-time risk process driven by proportional reinsurance and an interest rate process. We assume that the interest rate process behaves as a Markov chain. To reduce the risk of ruin, we may reinsure a part or even all of the reserve. Recursive and integral equations for ruin probabilities are given. Generalized Lundberg inequalities for the ruin probabilities are derived given a stationary policy. To illustrate these results, a numerical example is included.

Background Few twin studies have examined nutrition-related phenotypes among children, and none has investigated energy and macronutrient intakes. Objective The objective was to quantify genetic and environmental influences on variations in energy and macronutrient intakes among children aged 9 years. Design We conducted a nutrition study among children participating in the Quebec Newborn Twin Study, a population-based birth cohort of twins. We derived dietary data from two multiple-pass 24-hour dietary recalls with a parent and his or her child. The analysis employed a classic twin study design and used data from 379 twin pairs. Results Univariate analyses indicate that heritability for mean daily energy (kcal) and macronutrient (g) intakes was moderate, ranging from 0.34 (95% CI: 0.22, 0.46) to 0.42 (0.31, 0.53). Genetic effects also accounted for 0.28 (0.16, 0.40) of the variance in percent of energy from lipids, while only environmental (shared and unique) effects accounted for the variance in percent of energy from proteins and carbohydrates. The shared environment did not contribute to variations in daily intakes for most of the nutritional variables under study. Multivariate analyses suggest the presence of macronutrient-specific genetic influences for lipids and carbohydrates, estimated at 0.12 (0.04, 0.19) and 0.20 (0.11, 0.29) respectively. Conclusions The unique environment (i.e., not shared by family members) has the largest influence on variances in daily energy and macronutrient intakes in 9-year-old children. This finding underscores the need to take obesogenic environments into account when planning dietary interventions for younger populations.

Ruin probabilities in a controlled discrete-time risk process with a Markov chain interest are studied. To reduce the risk of ruin there is a possibility to reinsure a part or the whole reserve. Recursive and integral equations for ruin probabilities are given. Generalized Lundberg inequalities for the ruin probabilities are derived given a constant stationary policy. The relationships between these inequalities are discussed. To illustrate these results some numerical examples are included.

The problem of finding a minimum energy state (or density matrix) can be restated as a linear programming problem. This problem can be solved sequentially applying the maximum entropy principle, using the energy as a control parameter. The method thus described falls within the class of interior point methods for linear programs. In the classical (non quantum) setup, things go pretty much as expected, whereas in the quantum setup the approach depends on whether we use a basis in which the density matrix is diagonal or not. Here we present a novel maxentropic way of solving this problem.

Background Eating behaviors during childhood are related both to children’s diet quality and to their weight status. A better understanding of the determinants of eating behavior during childhood is essential for carrying out effective dietary interventions. Methods We assessed the contribution of genetic and environmental factors to variations in selected eating behaviors in early and late childhood. Information on eating behaviors came from questionnaires administered to parents of children participating in the Quebec Newborn Twin Study when the twins were 2.5 and 9 years old (n = 692 children). Dichotomous variables were derived and analyzed using structural equation modeling, as part of a classic twin study design. We performed univariate and bivariate longitudinal analyses to quantify sources of variation and covariation across ages, for several eating behavior traits. Results We found moderate to strong heritability for traits related to appetite such as eating too much, not eating enough and eating too fast. Univariate analysis estimates varied from 0.71 (95% CI: 0.49, 0.87) to 0.89 (0.75, 0.96) in younger children and from 0.44 (0.18, 0.66) to 0.56 (0.28, 0.78) in older children. Bivariate longitudinal analyses indicated modest to moderate genetic correlations across ages (rA varying from 0.34 to 0.58). Common genetic influences explained 17% to 43% of the phenotypic correlation between 2.5 and 9 years for these appetite-related behaviors. In 9-year-old children, food acceptance traits, such as refusing to eat and being fussy about food, had high heritability estimates, 0.84 (0.63, 0.94) and 0.85 (0.59, 0.96) respectively, while in younger children, the shared environment (i.e., common to both twins) contributed most to phenotypic variance. Variances in meal-pattern-related behaviors were mostly explained by shared environmental influences. Conclusions Genetic predispositions explain a large part of the variations in traits related to appetite during childhood, though our results suggest that as children get older, appetite-related behaviors become more sensitive to environmental influences outside the home. Still, for several traits environmental influences shared by twins appear to have the largest relative importance. This finding supports the notion that familial context has considerable potential to influence the development of healthy eating habits throughout childhood.