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Cardiovascular diseases (CVDs) are the most common cause of non-communicable disease mortality in sub-Saharan African (SSA) countries. Gaps in knowledge of CVD conditions and their risk factors are important barriers in effective prevention and treatment. Yet, evidence on the awareness and knowledge level of CVD and associated risk factors among populations of SSA is scarce. This review aimed to synthesize available evidence of the level of knowledge of and perceptions towards CVDs and risk factors in the SSA region. Five databases were searched for publications up to December 2016. Narrative synthesis was conducted for knowledge level of CVDs, knowledge of risk factors and clinical signs, factors influencing knowledge of CVDs and source of health information on CVDs. The review was registered with Prospero (CRD42016049165). Of 2212 titles and abstracts screened, 45 full-text papers were retrieved and reviewed and 20 were included: eighteen quantitative and two qualitative studies. Levels of knowledge and awareness for CVD and risk factors were generally low, coupled with poor perception. Most studies reported less than half of their study participants having good knowledge of CVDs and/or risk factors. Proportion of participants who were unable to identify a single risk factor and clinical symptom for CVDs ranged from 1.8% in a study among hospital staff in Nigeria to a high of 73% in a population-based survey in Uganda and 7% among University staff in Nigeria to 75.1% in a general population in Uganda respectively. High educational attainment and place of residence had a significant influence on the levels of knowledge for CVDs among SSA populations. Low knowledge of CVDs, risk factors and clinical symptoms is strongly associated with the low levels of educational attainment and rural residency in the region. These findings provide useful information for implementers of interventions targeted at the prevention and control of CVDs, and encourages them to incorporate health promotion and awareness campaigns in order to enhance knowledge and awareness of CVDs in the region.

The role of air pollution exposure in the development of asthma, allergies, and related symptoms remains unclear, due in part to the limited number of prospective cohort studies with sufficiently long follow-ups addressing this problem. We studied the association between traffic-related air pollution and the development of asthma, allergy, and related symptoms in a prospective birth cohort study with a unique 8-year follow-up. Annual questionnaire reports of asthma, hay fever, and related symptoms during the first 8 years of life were analyzed for 3,863 children. At age 8, measurements of allergic sensitization and bronchial hyperresponsiveness were performed for subpopulations (n = 1,700 and 936, respectively). Individual exposures to nitrogen dioxide (NO(2)), particulate matter (PM(2.5)), and soot at the birth address were estimated by land-use regression models. Associations between exposure to traffic-related air pollution and repeated measures of health outcomes were assessed by repeated-measures logistic regression analysis. Effects are presented for an interquartile range increase in exposure after adjusting for covariates. Annual prevalence was 3 to 6% for asthma and 12 to 23% for asthma symptoms. Annual incidence of asthma was 6% at age 1, and 1 to 2% at later ages. PM(2.5) levels were associated with a significant increase in incidence of asthma (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.10-1.49), prevalence of asthma (OR, 1.26; 95% CI, 1.04-1.51), and prevalence of asthma symptoms (OR, 1.15; 95% CI, 1.02-1.28). Findings were similar for NO(2) and soot. Associations were stronger for children who had not moved since birth. Positive associations with hay fever were found in nonmovers only. No associations were found with atopic eczema, allergic sensitization, and bronchial hyperresponsiveness. Exposure to traffic-related air pollution may cause asthma in children.

Gastrointestinal and respiratory diseases are major causes of morbidity for young children, particularly for those children attending child day care centers (DCCs). Although both diseases are presumed to cause considerable societal costs for care and treatment of illness, the extent of these costs, and the difference of these costs between children that do and do not attend such centers, is largely unknown. Estimate the societal costs for care and treatment of episodes of gastroenteritis (GE) and influenza-like illness (ILI) experienced by Dutch children that attend a DCC, compared to children that do not attend a DCC. A web-based monthly survey was conducted among households with children aged 0-48 months from October 2012 to October 2013. Households filled-in a questionnaire on the incidence of GE and ILI episodes experienced by their child during the past 4 weeks, on the costs related to care and treatment of these episodes, and on DCC arrangements. Costs and incidence were adjusted for socioeconomic characteristics including education level, nationality and monthly income of parents, number of children in the household, gender and age of the child and month of survey conduct. Children attending a DCC experienced higher rates of GE (aIRR 1.4 [95%CI: 1.2-1.9]) and ILI (aIRR: 1.4 [95%CI: 1.2-1.6]) compared to children not attending a DCC. The societal costs for care and treatment of an episode of GE and ILI experienced by a DCC-attending child were estimated at €215.45 [€115.69-€315.02] and €196.32 [€161.58-€232.74] respectively, twice as high as for a non-DCC-attending child. The DCC-attributable economic burden of GE and ILI for the Netherlands was estimated at €25 million and €72 million per year. Although children attending a DCC experience only slightly higher rates of GE and ILI compared to children not attending a DCC, the costs involved per episode are substantially higher.

Maternal diet during pregnancy has the potential to affect airway development and to promote T-helper-2-cell responses during fetal life. This might increase the risk of developing childhood asthma or allergy. We investigated the influence of maternal food consumption during pregnancy on childhood asthma outcomes from 1 to 8 years of age. A birth cohort study consisting of a baseline of 4,146 pregnant women (1,327 atopic and 2,819 nonatopic). These women were asked about their frequency of consumption of fruit, vegetables, fish, egg, milk, milk products, nuts, and nut products during the last month. Their children were followed until 8 years of age. Longitudinal analyses were conducted to assess associations between maternal diet during pregnancy and childhood asthma outcomes over 8 years. Complete data were obtained for 2,832 children. There were no associations between maternal vegetable, fish, egg, milk or milk products, and nut consumption and longitudinal childhood outcomes. Daily consumption of nut products increased the risk of childhood wheeze (odds ratio [OR] daily versus rare consumption, 1.42; 95% confidence interval [95% CI], 1.06-1.89), dyspnea (OR, 1.58; 95% CI, 1.16-2.15), steroid use (OR, 1.62; 95% CI, 1.06-2.46), and asthma symptoms (OR, 1.47; 95% CI, 1.08-1.99). Results of this study indicate an increased risk of daily versus rare consumption of nut products during pregnancy on childhood asthma outcomes. These findings need to be replicated by other studies before dietary advice can be given to pregnant women.

Risk factors often develop at young age and are maintained over time, but it is not fully understood how risk factors develop over time preceding cardiovascular disease (CVD). Our objective was to examine how levels and trajectories of metabolic risk factors and biochemical markers prior to diagnosis differ between people with and without CVD over a period of up to 15-20 years. A total of 449 incident non-fatal and fatal CVD cases and 1,347 age- and sex-matched controls were identified in a prospective cohort between 1993 and 2011. Metabolic risk factors and biochemical markers were measured at five-year intervals prior to diagnosis. Trajectories of metabolic risk factors and biochemical markers were analysed using random coefficient analyses. Although not always statistically significant, participants with CVD had slightly more unfavourable levels for most metabolic risk factors and biochemical markers 15-20 years before diagnosis than controls. Subsequent trajectories until diagnosis were similar in participants with incident CVD and controls for body mass index, diastolic blood pressure, total cholesterol, HDL cholesterol, random glucose, triglycerides, gamma glutamyltransferase, C-reactive protein and uric acid. Trajectories were more unfavourable in participants with CVD than controls for systolic blood pressure, waist circumference and estimated glomerular filtration rate (p≤0.05). For example, among participants with CVD, systolic blood pressure increased on average by 9 mmHg over the 18-year period preceding diagnosis, whereas the increase among controls was 4 mmHg. In conclusion, unfavourable levels of metabolic risk factors and biochemical markers are present long before CVD, which indicates that the risk of CVD is already partly determined in young adulthood. This underscores the need for early prevention to reduce the burden of CVD.

Currently, no standard tool is publicly available that allows researchers or policy-makers to quantify the impact of policies using epidemiological evidence within the causal framework of Health Impact Assessment (HIA). A standard tool should comply with three technical criteria (real-life population, dynamic projection, explicit risk-factor states) and three usability criteria (modest data requirements, rich model output, generally accessible) to be useful in the applied setting of HIA. With DYNAMO-HIA (Dynamic Modeling for Health Impact Assessment), we introduce such a generic software tool specifically designed to facilitate quantification in the assessment of the health impacts of policies. DYNAMO-HIA quantifies the impact of user-specified risk-factor changes on multiple diseases and in turn on overall population health, comparing one reference scenario with one or more intervention scenarios. The Markov-based modeling approach allows for explicit risk-factor states and simulation of a real-life population. A built-in parameter estimation module ensures that only standard population-level epidemiological evidence is required, i.e. data on incidence, prevalence, relative risks, and mortality. DYNAMO-HIA provides a rich output of summary measures--e.g. life expectancy and disease-free life expectancy--and detailed data--e.g. prevalences and mortality/survival rates--by age, sex, and risk-factor status over time. DYNAMO-HIA is controlled via a graphical user interface and is publicly available from the internet, ensuring general accessibility. We illustrate the use of DYNAMO-HIA with two example applications: a policy causing an overall increase in alcohol consumption and quantifying the disease-burden of smoking. By combining modest data needs with general accessibility and user friendliness within the causal framework of HIA, DYNAMO-HIA is a potential standard tool for health impact assessment based on epidemiologic evidence.

Background Influencing the life-style risk-factors alcohol, body mass index (BMI), and smoking is an European Union (EU) wide objective of public health policy. The population-level health effects of these risk-factors depend on population specific characteristics and are difficult to quantify without dynamic population health models. Methods For eleven countries—approx. 80 % of the EU-27 population—we used evidence from the publicly available DYNAMO-HIA data-set. For each country the age- and sex-specific risk-factor prevalence and the incidence, prevalence, and excess mortality of nine chronic diseases are utilized; including the corresponding relative risks linking risk-factor exposure causally to disease incidence and all-cause mortality. Applying the DYNAMO-HIA tool, we dynamically project the country-wise potential health gains and losses using feasible, i.e. observed elsewhere, risk-factor prevalence rates as benchmarks. The effects of the “worst practice”, “best practice”, and the currently observed risk-factor prevalence on population health are quantified and expected changes in life expectancy, morbidity-free life years, disease cases, and cumulative mortality are reported. Results Applying the best practice smoking prevalence yields the largest gains in life expectancy with 0.4 years for males and 0.3 year for females (approx. 332,950 and 274,200 deaths postponed, respectively) while the worst practice smoking prevalence also leads to the largest losses with 0.7 years for males and 0.9 year for females (approx. 609,400 and 710,550 lives lost, respectively). Comparing morbidity-free life years, the best practice smoking prevalence shows the highest gains for males with 0.4 years (342,800 less disease cases), whereas for females the best practice BMI prevalence yields the largest gains with 0.7 years (1,075,200 less disease cases). Conclusion Smoking is still the risk-factor with the largest potential health gains. BMI, however, has comparatively large effects on morbidity. Future research should aim to improve knowledge of how policies can influence and shape individual and aggregated life-style-related risk-factor behavior.

Background It is well known that maternal smoking during pregnancy and maternal pre-pregnancy overweight have opposite effects on the infants’ birth weight. We report on the association of the combination between both risk factors and the infants’ birth weight. Methods We studied 3241 infants born at term in the PIAMA birth cohort. Maternal smoking during pregnancy and pre-pregnancy height and weight were self-reported. Multivariable regression analysis was performed to assess the associations between infants of mothers who only smoked during pregnancy, who only had pre-pregnancy overweight and who had both risk factors simultaneously, on term birth weight and the risk of being SGA or LGA. Results Of 3241 infants, 421 infants (13%) were born to smoking, non-overweight mothers, 514 (15.8%) to non-smoking, overweight mothers, 129 (4%) to smoking and overweight mothers and 2177 (67%) to non-smoking, non-overweight mothers (reference group). Infants of mothers who smoked and also had pre-pregnancy overweight had similar term birth weight (− 26.6 g, 95%CI: − 113.0, 59.8), SGA risk (OR = 1.06, 95%CI: 0.56, 2.04), and LGA risk (OR = 1.09, 95%CI: 0.61, 1.96) as the reference group. Conclusions Our findings suggested that the effects of maternal smoking during pregnancy and maternal pre-pregnancy overweight on infants’ birth weight cancel each other out. Therefore, birth weight may not be a good indicator of an infant’s health status in perinatal practice because it may mask potential health risks due to these maternal risk factors when both present together.

Background People with higher socio-economic status (SES) are generally in better health. Less is known about when these socio-economic health differences set in during childhood and how they develop over time. The goal of this study was to prospectively study the development of socio-economic health differences in the Netherlands, and to investigate possible explanations for socio-economic variation in childhood health. Methods Data from the Dutch Prevention and Incidence of Asthma and Mite Allergy (PIAMA) birth cohort study were used for the analyses. The PIAMA study followed 3,963 Dutch children during their first eight years of life. Common childhood health problems (i.e. eczema, asthma symptoms, general health, frequent respiratory infections, overweight, and obesity) were assessed annually using questionnaires. Maternal educational level was used to indicate SES. Possible explanatory lifestyle determinants (breastfeeding, smoking during pregnancy, smoking during the first three months, and day-care centre attendance) and biological determinants (maternal age at birth, birthweight, and older siblings) were analysed using generalized estimating equations. Results This study shows that socio-economic differences in a broad range of health problems are already present early in life, and persist during childhood. Children from families with low socio-economic backgrounds experience more asthma symptoms (odds ratio (OR) 1.27; 95% Confidence Interval (CI) 1.08-1.49), poorer general health (OR 1.36; 95% CI 1.16-1.60), more frequent respiratory infections (OR 1.57; 95% CI 1.35-1.83), more overweight (OR 1.42; 95% CI 1.16-1.73), and more obesity (OR 2.82; 95% CI 1.80-4.41). The most important contributors to the observed childhood socio-economic health disparities are socio-economic differences in maternal age at birth, breastfeeding, and day-care centre attendance. Conclusions Socio-economic health disparities already occur very early in life. Socio-economic disadvantage takes its toll on child health before birth, and continues to do so during childhood. Therefore, action to reduce health disparities needs to start very early in life, and should also address socio-economic differences in maternal age at birth, breastfeeding habits, and day-care centre attendance.

Background There is ample evidence that childhood overweight is associated with increased risk of chronic disease in adulthood. The aim of this study was to investigate associations between childhood overweight and common childhood health problems. Methods Data were used from a general population sample of 3960 8-year-old children, participating in the Dutch PIAMA birth cohort study. Weight and height, measured by the investigators, were used to define BMI status (thinness, normal weight, moderate overweight, obesity). BMI status was studied cross-sectionally in relation to the following parental reported outcomes: a general health index, GP visits, school absenteeism due to illness, health-related functional limitations, doctor diagnosed respiratory infections and use of antibiotics. Results Obesity was significantly associated with a lower general health score, more GP visits, more school absenteeism and more health-related limitations, (adjusted odds ratios around 2.0 for most outcomes). Obesity was also significantly associated with bronchitis (adjusted odds ratio (aOR) and 95% confidence intervals (95%CI): 5.29 (2.58;10.85) and with the use of antibiotics (aOR (95%CI): 1.79 (1.09;2.93)). Associations with flu/serious cold, ear infection and throat infection were positive, but not statistically significant. Moderate overweight was not significantly associated with the health outcomes studied. Conclusion Childhood obesity is not merely a risk factor for disease in adulthood, but obese children may experience more illness and health related problems already in childhood. The high prevalence of the outcomes studied implies a high burden of disease in terms of absolute numbers of sick children.