18 research outputs found

    Large ethnic variations in recommended physical activity according to activity domains in amsterdam, the netherlands

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    <p>Abstract</p> <p>Purpose</p> <p>The level of recommended physical activity (PA) is met less frequently by people from some ethnic minorities than others. We explored whether these differences in recommended PA between ethnic minority groups and the general population varied by domain and type of culturally-specific activity.</p> <p>Methods</p> <p>Participants were sampled from the population based SUNSET study and were from ethnic Dutch (n = 567), Hindustani-Surinamese (n = 370) and African-Surinamese (n = 689) descent. The validated SQUASH-questionnaire measured PA for the following domains: commuting, occupation, household, leisure time. Culturally-specific activities were added as extra question within the leisure time domain. The effect of each domain on ethnic differences in recommended PA prevalence was examined by odds-ratio (OR) analysis through recalculating recommended PA, while, in turn, excluding the contribution of each domain.</p> <p>Results</p> <p>In the ethnic Dutch population, more vigorous PA in commuting and leisure time was reported compared to the Surinamese groups. The Hindustani-Surinamese and African-Surinamese reported more walking as commuting activity, while the Dutch group reported cycling more frequently. Ethnic differences in recommended PA became smaller in both Surinamese groups compared with the Dutch after removing commuting activity, for example, in Hindustani-Surinamese men (OR = 0.92, 95%CI: 0.62-1.37 vs. OR = 1.33, 0.89-2.00) and women (OR = 1.61, 1.12-2.32 vs. OR = 2.03, 1.41-2.92). Removing occupational activity resulted in larger ethnic differences in both groups compared with the Dutch. Smaller effects were found for yoga and dancing, leisure time and household activities.</p> <p>Conclusion</p> <p>This study shows that differences in PA between ethnic minority groups and the general population vary according to the activity domain. The results indicate that including all relevant domains and activities is essential for assessment of ethnic differences in recommended PA.</p

    Prevalence of diabetes mellitus and the performance of a risk score among Hindustani Surinamese, African Surinamese and ethnic Dutch: a cross-sectional population-based study

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    <p>Abstract</p> <p>Background</p> <p>While the prevalence of type 2 diabetes mellitus (DM) is high, tailored risk scores for screening among South Asian and African origin populations are lacking. The aim of this study was, first, to compare the prevalence of (known and newly detected) DM among Hindustani Surinamese, African Surinamese and ethnic Dutch (Dutch). Second, to develop a new risk score for DM. Third, to evaluate the performance of the risk score and to compare it to criteria derived from current guidelines.</p> <p>Methods</p> <p>We conducted a cross-sectional population based study among 336 Hindustani Surinamese, 593 African Surinamese and 486 Dutch, aged 35–60 years, in Amsterdam. Logistic regressing analyses were used to derive a risk score based on non-invasively determined characteristics. The diagnostic accuracy was assessed by the area under the Receiver-Operator Characteristic curve (AUC).</p> <p>Results</p> <p>Hindustani Surinamese had the highest prevalence of DM, followed by African Surinamese and Dutch: 16.7, 8.1, 4.2% (age 35–44) and 35.0, 19.0, 8.2% (age 45–60), respectively. The risk score included ethnicity, body mass index, waist circumference, resting heart rate, first-degree relative with DM, hypertension and history of cardiovascular disease. Selection based on age alone showed the lowest AUC: between 0.57–0.62. The AUC of our score (0.74–0.80) was higher than that of criteria from guidelines based solely on age and BMI and as high as criteria that required invasive specimen collection.</p> <p>Conclusion</p> <p>In Hindustani Surinamese and African Surinamese populations, screening for DM should not be limited to those over 45 years, as is advocated in several guidelines. If selective screening is indicated, our ethnicity based risk score performs well as a screening test for DM among these groups, particularly compared to the criteria based on age and/or body mass index derived from current guidelines.</p

    Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

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    Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

    Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

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    Background Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods We used data from 1990 to 2019 on people aged 30–79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings The number of people aged 30–79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306–359) million women and 317 (292–344) million men in 1990 to 626 (584–668) million women and 652 (604–698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55–62) of women and 49% (46–52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43–51) of women and 38% (35–41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20–27) for women and 18% (16–21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings

    Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)

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    From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions

    Prospective analysis of gender-related characteristics in relation to cardiovascular disease

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    OBJECTIVE: Differences in cardiovascular disease (CVD) incidence between men and women have been widely reported. Next to sex-related (biological) characteristics, gender-related (sociocultural) characteristics may partly explain how these differences arise. In this exploratory study, we examined the associations between selected gender-related characteristics and CVD incidence. METHODS: We linked baseline data of 18 058 participants without CVD from the population-based, multiethnic HEalthy LIfe in an Urban Setting study (Amsterdam, the Netherlands) to CVD incidence data, based on hospital admission and death records from Statistics Netherlands in 2013-2018. Using Cox regression analyses, we studied associations of time spent on household work, doing home repairs, primary earner status, type of employment, working in a male-dominated or female-dominated occupation and desire for emotional support with CVD incidence, stratified by sex. Analyses were adjusted for age, ethnicity and socioeconomic status. RESULTS: In men, gender-related characteristics were not associated with higher CVD incidence. In women, homemakers had a higher hazard for CVD compared with full-time workers (HR 2.34, 95% CI 1.35 to 4.04), whereas those spending a moderate amount of time on household work had a lower hazard for CVD than those spending little time (HR 0.56, 95% CI 0.34 to 0.95). CONCLUSION: Although we found no evidence for associations between gender-related characteristics and CVD incidence in men, being the homemaker and moderate time spent on household work appeared to be associated with CVD incidence in women. Thus, attention to gender-related characteristics might in future help to identify subgroups that may benefit from additional prevention strategies

    Are "functionally related polymorphisms" of renin-angiotensin-aldosterone system gene polymorphisms associated with hypertension?

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    <p>Abstract</p> <p>Background</p> <p>Genotype-phenotype association studies are typically based upon polymorphisms or haplotypes comprised of multiple polymorphisms within a single gene. It has been proposed that combinations of polymorphisms in distinct genes, which functionally impact the same phenotype, may have stronger phenotype associations than those within a single gene. We have tested this hypothesis using genes encoding components of the renin-angiotensin-aldosterone system and the high blood pressure phenotype.</p> <p>Methods</p> <p>Our analysis is based on 1379 participants of the cross-sectional SUNSET study randomly selected from the population register of Amsterdam. Each subject was genotyped for the angiotensinogen M235T, the angiotensin-converting enzyme insertion/deletion and the angiotensin II type 1 receptor A1166C polymorphism. The phenotype high blood pressure was defined either as a categorical variable comparing hypertension versus normotension as in most previous studies or as a continuous variable using systolic, diastolic and mean blood pressure in a multiple regression analysis with gender, ethnicity, age, body-mass-index and antihypertensive medication as covariates.</p> <p>Results</p> <p>Genotype-phenotype relationships were explored for each polymorphism in isolation and for double and triple polymorphism combinations. At the single polymorphism level, only the A allele of the angiotensin II type 1 receptor was associated with a high blood pressure phenotype. Using combinations of polymorphisms of two or all three genes did not yield stronger/more consistent associations.</p> <p>Conclusions</p> <p>We conclude that combinations of physiologically related polymorphisms of multiple genes, at least with regard to the renin-angiotensin-aldosterone system and the hypertensive phenotype, do not necessarily offer additional benefit in analyzing genotype/phenotype associations.</p

    Effects of a lifestyle intervention programme after 1 year of follow-up among South Asians at high risk of type 2 diabetes: a cluster randomised controlled trial

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    South Asians are at high risk of type 2 diabetes (T2D). We assessed whether intensive family-based lifestyle intervention leads to significant weight loss, improved glycaemia and blood pressure in adults at elevated risk for T2D.This cluster randomised controlled trial (iHealth-T2D) was conducted at 120 locations across India, Pakistan, Sri Lanka and the UK. We included 3684 South Asian men and women, aged 40-70 years, without T2D but with raised haemoglobin A1c (HbA1c) and/or waist circumference. Participants were randomly allocated either to the family-based lifestyle intervention or control group by location clusters. Participants in the intervention received 9 visits and 13 telephone contacts by community health workers over 1-year period, and the control group received usual care. Reductions in weight (aim >7% reduction), waist circumference (aim ≥5 cm reduction), blood pressure and HbA1C at 12 months of follow-up were assessed. Our linear mixed-effects regression analysis was based on intention-to-treat principle and adjusted for age, sex and baseline values.There were 1846 participants in the control and 1838 in the intervention group. Between baseline and 12 months, mean weight of participants in the intervention group reduced by 1.8 kg compared with 0.4 kg in the control group (adjusted mean difference -1.10 kg (95% CI -1.70 to -1.06), p<0.001). The adjusted mean difference for waist circumference was -1.9 cm (95% CI -2.5; to 1.3), p<0.001). No overall difference was observed for blood pressure or HbA1c. People who attended multiple intervention sessions had a dose-dependent effect on waist circumference, blood pressure and HbA1c, but not on weight.An intensive family-based lifestyle intervention adopting low-resource strategies led to effective reduction in weight and waist circumference at 12 months, which has potential long-term benefits for preventing T2D. A higher number of attended sessions increased the effect on waist circumference, blood pressure and HbA1c.EudraCT: 2016-001350-18; ClinicalTrials.gov: NCT02949739
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