Pre-pregnancy weight, the rate of gestational weight gain, and the risk of early gestational diabetes mellitus among women registered in a tertiary care hospital in India.

BACKGROUND: The impact of pre-pregnancy weight and the rate of gestational weight gain (GWG) together on the risk of early GDM (< 24 weeks gestation; eGDM) has not been studied in the Indian context. We aimed to study the influence of (1) pre-pregnancy weight on the risk of eGDM diagnosed in two time intervals; and (2) in addition, the rate of GWG by 12 weeks on the risk of eGDM diagnosed in 19-24 weeks. METHOD: Our study utilized real-world clinical data on pregnant women routinely collected at an antenatal care clinic at a private tertiary hospital, in Pune, India. Women registering before 12 weeks of gestation (v1), with a singleton pregnancy, and having a follow-up visit between 19-24 weeks (v2) were included (n = 600). The oral glucose tolerance test was conducted universally as per Indian guidelines (DIPSI) at v1 and v2 for diagnosing eGDM. The data on the onset time of eGDM were interval censored; hence, we modeled the risk of eGDM using binomial regression to assess the influence of pre-pregnancy weight on the risk of eGDM in the two intervals. The rate of GWG by 12 weeks was added to assess its impact on the risk of eGDM diagnosed in v2. RESULT: Overall, 89 (14.8%) women (age 32 ± 4 years) were diagnosed with eGDM by 24 weeks, of which 59 (9.8%) were diagnosed before 12 weeks and 30 of 541 (5.5%) women were diagnosed between 19-24 weeks. Two-thirds (66%) of eGDM were diagnosed before 12 weeks of gestation. Women's pre-pregnancy weight was positively associated with the risk of GDM in both time intervals though the lower confidence limit was below zero in v1. The rate of GWG by 12 weeks was not observed to be associated with the risk of eGDM diagnosed between 19-24 weeks of gestation. These associations were independent of age, height, and parity. CONCLUSION: Health workers may focus on pre-pregnancy weight, a modifiable risk factor for eGDM. A larger community-based study measuring weight and GDM status more frequently may be warranted to deepen the understanding of the role of GWG as a risk factor for GDM.

Underreporting of SARS-CoV-2 infections during the first wave of the 2020 COVID-19 epidemic in Finland-Bayesian inference based on a series of serological surveys.

In Finland, the first wave of the COVID-19 epidemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took place from March to June 2020, with the majority of COVID-19 cases diagnosed in the Helsinki-Uusimaa region. The magnitude and trend in the incidence of COVID-19 is one way to monitor the course of the epidemic. The diagnosed COVID-19 cases are a subset of the infections and therefore the COVID-19 incidence underestimates the SARS-CoV-2 incidence. The likelihood that an individual with SARS-CoV-2 infection is diagnosed with COVID-19 depends on the clinical manifestation as well as the infection testing policy and capacity. These factors may fluctuate over time and the underreporting of infections changes accordingly. Quantifying the extent of underreporting allows the assessment of the true incidence of infection. To obtain information on the incidence of SARS-CoV-2 infection in Finland, a series of serological surveys was initiated in April 2020. We develop a Bayesian inference approach and apply it to data from the serological surveys, registered COVID-19 cases, and external data on antibody development, to estimate the time-dependent underreporting of SARS-Cov-2 infections during the first wave of the COVID-19 epidemic in Finland. During the entire first wave, there were 1 to 5 (95% probability) SARS-CoV-2 infections for every COVID-19 case. The underreporting was highest before April when there were 4 to 17 (95% probability) infections for every COVID-19 case. It is likely that between 0.5%-1.0% (50% probability) and no more than 1.5% (95% probability) of the adult population in the Helsinki-Uusimaa region were infected with SARS-CoV-2 by the beginning of July 2020.

Effects of technology-based interventions on dietary intake or anthropometrics among adolescents and adults in South Asia - A systematic review of intervention studies.

INTRODUCTION: Mobile technology has been increasingly used as part of dietary interventions, but the effects of such interventions have not been systematically evaluated in the South Asian context. The systematic review aimed to determine the effects of technology-based interventions on dietary intake or anthropometrics among adolescents and adults in South Asia. METHODS: Five electronic databases were searched (PubMed, Scopus, Web of Science, Global Health Library and Health Technology Assessment). Studies published in English between 1st January 2011 and 31st December 2021were included. Interventions that evaluated the effects of dietary interventions using technology on dietary outcomes and anthropometrics in adolescents or adults in the age group of 13-44 years (or a broader age group) from South Asia were eligible for inclusion. The risk of bias was assessed using the Cochrane Risk-of-bias 2 tool and ROBINS-I tool. A narrative synthesis was conducted. RESULTS: Twenty-one studies met the inclusion criteria (20,667 participants). Eleven of the 17 randomised controlled trials (RCTs) had a high overall risk of bias. The four non-randomised intervention studies had a serious or critical overall risk of bias. When including studies with low risk or some concern for bias, the interventions had a beneficial effect on at least one dietary outcome in four of the six RCTs that measured changes in diet, and no effect on the anthropometric outcomes in the six RCTs that measured changes in anthropometric outcomes. DISCUSSION: Technology-based dietary interventions have had some positive effects on dietary intake, but no effects on anthropometry in South Asia. More evidence is needed as the overall risk of bias was high in a majority of the studies.

Analysing Subgroups and Treatment Discontinuation in a Finnish Cohort of Patients with Neovascular AMD.

PURPOSE: We aimed to study the regional detailed visual outcome and treatment discontinuation of neovascular age-related macular degeneration (nAMD). METHODS: Clinical records of 110 patients treated for nAMD at the sole referral centre in the Helsinki region were analysed retrospectively. The follow-up was up to the fourth year. RESULTS: The mean visual acuity (VA) at baseline was 56.3 (SD 16.2) letters. The mean last VA at the first year was 59.7 (20.2), and the corresponding values for the second, third, and fourth years were 60.8 (20.6), 60.0 (19.0), and 59.7 (19.3). The mean difference from baseline was +3.39 (SD 14.6), +3.59 (17.6), +0.08 (18.9), and +3.08 (14.3). The number of patients declined each year, with only 51% of the patients being in treatment until the fourth year. The patients with shorter duration of follow-up tended to have a lower baseline VA, lesser gains, and an earlier decline in VA. The VA levels at the last visit were poorer in the shorter follow group. The initial VA response predicted later VA, whereas VA at baseline, age, or sex had no effect. However, the effect vanished with a longer time in treatment. CONCLUSIONS: Long-term VA stabilization was obtained in a regional material. Patients with neovascular AMD consist of cohorts with varying visual outcome and treatment time. Many of the patients benefit from the treatment for some time, however. When comparing real-world results, the outcome of the different follow-up time cohorts should be considered. This calls for new methods for analysing real-world nAMD treatment results.

Birth cohort differences in height, weight and BMI among Indian women aged 15-30 years: analyses based on three cross-sectional surveys.

OBJECTIVE: To explore long-term trends in height, weight and BMI across birth cohorts among Indian women aged 15-30 years. DESIGN: Nationally representative cross-sectional surveys. SETTING: Data from three National Family Health Surveys were conducted in 1998-1999, 2005-2006 and 2015-2016. Height and weight were modelled jointly, employing a multivariate regression model with age and birth cohorts as explanatory variables. The largest birth cohort (born 1988-1992) was the reference cohort. Stratified analyses by place of residence and by marital status and dichotomised parity were also performed. PARTICIPANTS: 437 753 non-pregnant women aged 15-30 years. RESULTS: The rate of increase in height, weight and BMI differed across birth cohorts. The rate of increase was much lower for height than weight, which was reflected in an increasing trend in BMI across all birth cohorts. In the stratified analyses, increase in height was found to be similar across urban and rural areas. Rural women born in the latest birth cohort (1998-2001) were lighter, whereas urban women were heavier compared to the reference cohort. A relatively larger increase in regression coefficients was observed among women born between 1978 and 1982 compared to women born between 1973 and 1977 when considering unmarried and nulliparous ever-married women and, one cohort later (1983-1987 v. 1978-1982), among parous ever-married women. CONCLUSION: As the rate of increase was much larger for weight than for height, increasing trends in BMI were observed across the birth cohorts. Thus, cohort effects show an important contributory role in explaining increasing trends in BMI among young Indian women.

Spotlight influenza: Estimation of influenza vaccine effectiveness in elderly people with assessment of residual confounding by negative control outcomes, Finland, 2012/13 to 2019/20.

BackgroundCohort studies on vaccine effectiveness are prone to confounding bias if the distribution of risk factors is unbalanced between vaccinated and unvaccinated study subjects.AimWe aimed to estimate influenza vaccine effectiveness in the elderly population in Finland by controlling for a sufficient set of confounders based on routinely available register data.MethodsFor each of the eight consecutive influenza seasons from 2012/13 through 2019/20, we conducted a cohort study comparing the hazards of laboratory-confirmed influenza in vaccinated and unvaccinated people aged 65-100 years using individual-level medical and demographic data. Vaccine effectiveness was estimated as 1 minus the hazard ratio adjusted for the confounders age, sex, vaccination history, nights hospitalised in the past and presence of underlying chronic conditions. To assess the adequacy of the selected set of confounders, we estimated hazard ratios of off-season hospitalisation for acute respiratory infection as a negative control outcome.ResultsEach analysed cohort comprised around 1 million subjects, of whom 37% to 49% were vaccinated. Vaccine effectiveness against laboratory-confirmed influenza ranged from 16% (95% confidence interval (CI): 12-19) to 48% (95% CI: 41-54). More than 80% of the laboratory-confirmed cases were hospitalised. The adjusted off-season hazard ratio estimates varied between 1.00 (95% CI: 0.94-1.05) and 1.08 (95% CI: 1.01-1.15), indicating that residual confounding was absent or negligible.ConclusionSeasonal influenza vaccination reduces the hazard of severe influenza disease in vaccinated elderly people. Data about age, sex, vaccination history and utilisation of hospital care proved sufficient to control confounding.

Exposure misclassification bias in the estimation of vaccine effectiveness.

In epidemiology, a typical measure of interest is the risk of disease conditional upon exposure. A common source of bias in the estimation of risks and risk ratios is misclassification. Exposure misclassification affects the measurement of exposure, i.e. the variable one conditions on. This article explains how to assess biases under non-differential exposure misclassification when estimating vaccine effectiveness, i.e. the vaccine-induced relative reduction in the risk of disease. The problem can be described in terms of three binary variables: the unobserved true exposure status, the observed but potentially misclassified exposure status, and the observed true disease status. The bias due to exposure misclassification is quantified by the difference between the naïve estimand defined as one minus the risk ratio comparing individuals observed as vaccinated with individuals observed as unvaccinated, and the vaccine effectiveness defined as one minus the risk ratio comparing truly vaccinated with truly unvaccinated. The magnitude of the bias depends on five factors: the risks of disease in the truly vaccinated and the truly unvaccinated, the sensitivity and specificity of exposure measurement, and vaccination coverage. Non-differential exposure misclassification bias is always negative. In practice, if the sensitivity and specificity are known or estimable from external sources, the true risks and the vaccination coverage can be estimated from the observed data and, thus, the estimation of vaccine effectiveness based on the observed risks can be corrected for exposure misclassification. When analysing risks under misclassification, careful consideration of conditional probabilities is crucial.

Mitigation of biases in estimating hazard ratios under non-sensitive and non-specific observation of outcomes-applications to influenza vaccine effectiveness.

BACKGROUND: Non-sensitive and non-specific observation of outcomes in time-to-event data affects event counts as well as the risk sets, thus, biasing the estimation of hazard ratios. We investigate how imperfect observation of incident events affects the estimation of vaccine effectiveness based on hazard ratios. METHODS: Imperfect time-to-event data contain two classes of events: a portion of the true events of interest; and false-positive events mistakenly recorded as events of interest. We develop an estimation method utilising a weighted partial likelihood and probabilistic deletion of false-positive events and assuming the sensitivity and the false-positive rate are known. The performance of the method is evaluated using simulated and Finnish register data. RESULTS: The novel method enables unbiased semiparametric estimation of hazard ratios from imperfect time-to-event data. False-positive rates that are small can be approximated to be zero without inducing bias. The method is robust to misspecification of the sensitivity as long as the ratio of the sensitivity in the vaccinated and the unvaccinated is specified correctly and the cumulative risk of the true event is small. CONCLUSIONS: The weighted partial likelihood can be used to adjust for outcome measurement errors in the estimation of hazard ratios and effectiveness but requires specifying the sensitivity and the false-positive rate. In absence of exact information about these parameters, the method works as a tool for assessing the potential magnitude of bias given a range of likely parameter values.

Effectiveness of 2 Influenza Vaccines in Nationwide Cohorts of Finnish 2-Year-Old Children in the Seasons 2015-2016 Through 2017-2018.

BACKGROUND: From 2015-2016 through 2017-2018, injectable, trivalent inactivated influenza vaccines (IIV3) and a nasal spray, tetravalent live-attenuated influenza vaccine (LAIV4) were used in parallel in Finland. To understand how well vaccination with each vaccine type protected children against influenza under real-life conditions, vaccine effectiveness in 2-year-olds was estimated for all 3 seasons. METHODS: Each season, a nationwide register-based cohort study was conducted. The study population comprised 60 088, 60 860, and 60 345 children in 2015-2016, 2016-2017, and 2017-2018, respectively. Laboratory-confirmed influenza was the study outcome. Seasonal influenza vaccination with either LAIV4 or IIV3 was the time-dependent exposure of interest. Vaccine effectiveness was defined as 1 minus the hazard ratio comparing vaccinated with unvaccinated children. RESULTS: From 2015-2016 through 2017-2018, the effectiveness of LAIV4 against influenza of any virus type was estimated at 54.2% (95% confidence interval, 32.2-69.0%), 20.3% (-12.7%, 43.6%), and 30.5% (10.9-45.9%); the corresponding effectiveness of IIV3 was 77.2% (48.9-89.8%), 24.5% (-29.8%, 56.1%), and -20.1% (-61.5%, 10.7%). Neither influenza vaccine clearly excelled in protecting children. The LAIV4 effectiveness against type B was greater than against type A and greater than the IIV3 effectiveness against type B. CONCLUSIONS: To understand how influenza vaccines could be improved, vaccine effectiveness must be analyzed by vaccine and virus type. Effectiveness estimates also expressing overall protection levels are needed to guide individual and programmatic decision-making processes. Supported by this analysis, the vaccination program in Finland now recommends LAIV4 and injectable, tetravalent inactivated influenza vaccines replacing IIV3.

Cohort study design for estimating the effectiveness of seasonal influenza vaccines in real time based on register data: The Finnish example.

This paper presents the principles of implementing register-based cohort studies as currently applied for real-time estimation of influenza vaccine effectiveness in Finland. All required information is retrieved from computerised national registers and deterministically linked via the unique personal identity code assigned to each Finnish resident. The study cohorts comprise large subpopulations eligible for a free seasonal influenza vaccination as part of the National Vaccination Programme. The primary outcome is laboratory-confirmed influenza. Each study subject is taken to be at risk of experiencing the outcome from the onset of the influenza season until the first of the following three events occurs: outcome, loss to follow up or end of season. Seasonal influenza vaccination is viewed as time-dependent exposure. Accordingly, each subject may contribute unvaccinated and vaccinated person-time during their time at risk. The vaccine effectiveness is estimated as one minus the influenza incidence rate ratio comparing the vaccinated with the unvaccinated within the study cohorts. Data collection in register-based research is an almost fully automated process. The effort, resources and the time spent in the field are relatively small compared to other observational study designs. This advantage is pivotal when vaccine effectiveness estimates are needed in real time. The paper outlines possible limitations of register-based cohort studies. It also addresses the need to explore how national and subnational registers available in the Nordic countries and elsewhere can be utilised in vaccine effectiveness research to guide decision making and to improve individual health as well as public health.

Mobile Helpline and Reversible Contraception: Lessons From a Controlled Before-and-After Study in Rural India.

BACKGROUND: Researchers and activists have expressed concerns over the lack of availability and nonuse of reversible, modern, contraceptive methods in India for decades. New attempts to increase access, availability, and acceptance of reversible contraceptives need to be developed, instead of relying solely on female sterilization. Mobile health (mHealth) initiatives may offer one way to serve underprivileged populations who face challenges in sexual and reproductive health (SRH) in countries such as India. OBJECTIVE: This study aimed to examine the outcome of an mHealth intervention for enhancing knowledge of, and practices related to, reversible contraceptives in rural Western India. METHODS: We implemented a nonrandomized controlled trial (before-and-after study in an intervention area and a control area) in the Indian state of Maharashtra. The intervention in this case was a mobile-based SRH helpline provided by a nongovernmental organization (NGO). Baseline and follow-up surveys were carried out in two government-run primary health center areas, one each in the intervention and control area, and 405 respondents were surveyed in the two rounds. An interview-based structured questionnaire suitable for a low-literacy environment was used to collect data. The effect of the intervention was estimated using logistic regression, adjusted for gender, by calculating robust standard errors to take into account the clustering of individuals by the area (intervention or control). In each regression model, the effect of intervention was estimated by including a term for interaction between the intervention area and the period before and after the intervention. The exponent of the regression coefficient of the interaction term corresponding to the period after the intervention, along with the 95% CI, is reported here. The odds ratio for the control village multiplied by this exponent gives the odds ratio for the intervention village. Calls received in the intervention were recorded and their topics analyzed. RESULTS: The current use of reversible contraception (18% increase in intervention area vs 2% increase in control area; 95% CI) has seen changes. The proportion of respondents who had heard of contraception methods from an NGO rose in the intervention area by 23% whereas it decreased in the control area by 1% (95% CI). However, the general level of awareness of reversible contraception, shown by the first contraceptive method that came to respondents' mind, did not improve. Demand for wider SRH information beyond contraception was high. Men and adolescents, in addition to married women, made use of the helpline. CONCLUSIONS: A mobile helpline that one can confidentially approach at a time most convenient to the client can help provide necessary information and support to those who need reversible contraception or other sexual health information. Services that integrate mHealth in a context-sensitive way to other face-to-face health care services add value to SRH services in rural India.

Determinants of plasma phospholipid arachidonic and docosahexaenoic acids among adolescent girls in central Mozambique - possible roles of iron and zinc.

We explored if linoleic acid (LA) and alpha-linolenic acid (ALA) will be efficiently converted to arachidonic acid (AA) and docosahexaenoic acid (DHA) in the adolescent girls (aged 15-18 years, n=145) in Mozambique consuming habitually low fat diet and if low iron and/or zinc status predicts the conversion. Total fat, LA and ALA intakes were 15-19%, 1.2-3.5% and 0.2-0.3% of energy, respectively in three areas. Iron and zinc intake varied between 9.6-12.3mg/day and 3.6-5.0mg/day. Significant negative association of plasma AA was found with plasma LA and ALA and significant positive association with serum ferritin. Plasma DHA associated, negatively with plasma LA and ALA. We showed that in a population with low intakes of LA and ALA, the proportions of phospholipid LA and ALA determines the relative proportions of AA and DHA and low iron status probably attenuates the conversion of LA to AA.

Mid-upper arm circumference is associated with biochemically determined nutritional status indicators among adolescent girls in Central Mozambique.

Biochemically determined nutritional status measurements in low-income countries are often too expensive. Therefore, we hypothesized that some anthropometrical or functional measurements (handgrip) could reflect nutritional status measured by specific biochemical indicators. We did a population-based study from 1 urban area and 2 rural districts in Zambézia Province of Mozambique. The participants (n=386) were non-pregnant adolescent girls between 15 and 18 years of age. 96% had a normal BMI-for-age score. Weight and mid-upper arm circumference (MUAC) were highly correlated (r>0.8) with each other and with total body muscle mass, body mass index (BMI), and with waist circumference, as well as with skinfolds (r>0.6). Upper and total arm lengths were correlated (r>0.7) with height and with each other, and right and left handgrip were correlated only with each other, as were triceps and subscapular skinfolds (r>0.7). Serum albumin correlated negatively with waist circumference (P<.001) and positively with MUAC (P=.007). Stepwise regressions showed that waist circumference, MUAC, weight, and handgrip were important nutritional status indicators in the models using hemoglobin, serum albumin, ferritin, zinc, and plasma retinol concentrations as dependent variables. MUAC could be a valuable anthropometric marker of the overall nutritional status of adolescent girls in low-income countries. When nutrition transition proceeds, waist circumference together with MUAC could form tools for the prediction of worsening of nutritional status.

Age at menarche and diet among adolescents in slums of Nashik, India.

BACKGROUND AND AIM: The role of dietary patterns in determining age at menarche is insufficiently understood in low-income countries. The relationship between dietary patterns, particularly the consumption of oil, and age at menarche in a slum-dwelling adolescent population in India is examined. METHODS: Data were derived from a cross-sectional baseline survey and anthropometric measurements among 10- to 19-year-old adolescents (n=545, female respondents 272, of whom 160 were post-menarcheal) and a household survey in two slums in the city of Nashik, Western India. By using mixed effects linear regression models, the association between age at menarche and household-wise use of sources of animal protein and oil and fat is examined. RESULTS: Age at menarche (mean 13.7 years) in the slums studied was relatively high according to Indian standards. Age at menarche and the consumption of dairy products, meat, fish and eggs were not associated. The household per capita consumption of vegetable oil had an inverse association with a girl's age at menarche, and there was an indication of a positive association between use of ghee (clarified butter) and age at menarche. These associations did not disappear when controlling for anthropometric status and socio-economic characteristics. CONCLUSION: Intake of fats and foods that are important sources of protein among underprivileged households in India is low and reflected in the relatively late age at menarche. The potential differences in the association between various types of fatty acids, energy intake and age at menarche in conditions of undernutrition requires further prospective study.

Optimal designs for epidemiologic longitudinal studies with binary outcomes.

Alternating presence and absence of a medical condition in human subjects is often modelled as an outcome of underlying process dynamics. Longitudinal studies provide important insights into research questions involving such dynamics. This article concerns optimal designs for studies in which the dynamics are modelled as a binary continuous-time Markov process. Either one or both the transition rate parameters in the model are to be estimated with maximum precision from a sequence of observations made at discrete times on a number of subjects. The design questions concern the choice of time interval between observations, the initial state of each subject and the choice between number of subjects versus repeated observations per subject. Sequential designs are considered due to dependence of the designs on the model parameters. The optimal time spacing can be approximated by the reciprocal of the sum of the two rates. The initial distribution of the study subjects should be taken into account when relatively few repeated samples per subject are to be collected. A study with a reasonably large size should be designed in more than one phase because there are then enough observations to be spent in the first phase to revise the time spacing for the subsequent phases.

FERTILITY INTENTIONS AND EARLY LIFE HEALTH STRESS AMONG WOMEN IN EIGHT INDIAN CITIES: TESTING THE REPRODUCTIVE ACCELERATION HYPOTHESIS.

In life history theory, early life adversity is associated with an accelerated reproductive tempo. In harsh and unpredictable conditions in developing societies fertility is generally higher and the reproductive tempo faster than in more secure environments. This paper examines whether differences in female anthropometry, particularly adult height, are associated with fertility intentions of women in urban environments in India. The study population consists of women aged 15-29 (N=4485) in slums and non-slums of eight Indian cities in the National Family Health Survey (NFHS) of 2005-2006. Adult height is taken as a proxy for early childhood health and nutritional condition. Fertility intentions are examined by using two variables: the desire to have a child or another child, and to have it relatively soon, as indicative of accelerated reproductive scheduling. Evidence supporting the acceleration hypothesis is found in two urban frames out of 26 examined in a two-staged multinomial logistic model. In three cases, the relationship between fertility intentions and height is the opposite than expected by the acceleration hypothesis: taller women have a higher predictive probability of desiring a(nother) child and/or narrower birth spacing. Potential explanations for the partly contradictory relationship between the childhood health indicator and fertility intentions are discussed.

Estimating haplotype frequencies by combining data from large DNA pools with database information.

We assume that allele frequency data have been extracted from several large DNA pools, each containing genetic material of up to hundreds of sampled individuals. Our goal is to estimate the haplotype frequencies among the sampled individuals by combining the pooled allele frequency data with prior knowledge about the set of possible haplotypes. Such prior information can be obtained, for example, from a database such as HapMap. We present a Bayesian haplotyping method for pooled DNA based on a continuous approximation of the multinomial distribution. The proposed method is applicable when the sizes of the DNA pools and/or the number of considered loci exceed the limits of several earlier methods. In the example analyses, the proposed model clearly outperforms a deterministic greedy algorithm on real data from the HapMap database. With a small number of loci, the performance of the proposed method is similar to that of an EM-algorithm, which uses a multinormal approximation for the pooled allele frequencies, but which does not utilize prior information about the haplotypes. The method has been implemented using Matlab and the code is available upon request from the authors.

Process evaluation of a tobacco prevention program in Indian schools--methods, results and lessons learnt.

In India, 57% of men between 15 and 54 years and 10.8% of women between 15 and 49 years use tobacco. A wide variety of tobacco gets used and the poor and the underprivileged are the dominant victims of tobacco and its adverse consequences. Project MYTRI (Mobilizing Youth for Tobacco-Related Initiatives in India) was a tobacco prevention intervention program, a cluster-randomized trial in 32 Indian schools which aimed to decrease susceptibility to tobacco use among sixth- to ninth-grade students in urban settings in India. This culture-specific intervention, which addressed both smokeless and smoked forms of tobacco, was Indian in content and communication. We qualitatively developed indicators which would help accurately measure the dose of the intervention given, received and reached. A multi-staged process evaluation was done through both subjective and objective measures. Training the teachers critically contributed toward a rigorous implementation and also correlated with the outcomes, as did a higher proportion of students participating in the classroom discussions and better peer-leader-student communication. A sizeable proportion of subjective responses were 'socially desirable', making objective assessment a preferred methodology even for 'dose received'. The peer-led health activism was successful. Teachers' manuals need to be concise.

Relative risks for stroke by age, sex, and population based on follow-up of 18 European populations in the MORGAM Project.

BACKGROUND AND PURPOSE: Within the framework of the MOnica Risk, Genetics, Archiving and Monograph (MORGAM) Project, the variations in impact of classical risk factors of stroke by population, sex, and age were analyzed. METHODS: Follow-up data were collected in 43 cohorts in 18 populations in 8 European countries surveyed for cardiovascular risk factors. In 93 695 persons aged 19 to 77 years and free of major cardiovascular disease at baseline, total observation years were 1 234 252 and the number of stroke events analyzed was 3142. Hazard ratios were calculated by Cox regression analyses. RESULTS: Each year of age increased the risk of stroke (fatal and nonfatal together) by 9% (95% CI, 9% to 10%) in men and by 10% (9% to 10%) in women. A 10-mm Hg increase in systolic blood pressure involved a similar increase in risk in men (28%; 24% to 32%) and women (25%; 20% to 29%). Smoking conferred a similar excess risk in women (104%; 78% to 133%) and in men (82%; 66% to 100%). The effect of increasing body mass index was very modest. Higher high-density lipoprotein cholesterol levels decreased the risk of stroke more in women (hazard ratio per mmol/L 0.58; 0.49 to 0.68) than in men (0.80; 0.69 to 0.92). The impact of the individual risk factors differed somewhat between countries/regions with high blood pressure being particularly important in central Europe (Poland and Lithuania). CONCLUSIONS: Age, sex, and region-specific estimates of relative risks for stroke conferred by classical risk factors in various regions of Europe are provided. From a public health perspective, an important lesson is that smoking confers a high risk for stroke across Europe.

Joint analysis of prevalence and incidence data using conditional likelihood.

Disease prevalence is the combined result of duration, disease incidence, case fatality, and other mortality. If information is available on all these factors, and on fixed covariates such as genotypes, prevalence information can be utilized in the estimation of the effects of the covariates on disease incidence. Study cohorts that are recruited as cross-sectional samples and subsequently followed up for disease events of interest produce both prevalence and incidence information. In this paper, we make use of both types of information using a likelihood, which is conditioned on survival until the cross section. In a simulation study making use of real cohort data, we compare the proposed conditional likelihood method to a standard analysis where prevalent cases are omitted and the likelihood expression is conditioned on healthy status at the cross section.