Association of milk and dairy product consumption with the incidence of cardio-cerebrovascular disease incidence in middle-aged and older Korean adults: a 16-year follow-up of the Korean Genome and Epidemiology Study
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Abstract
BACKGROUND/OBJECTIVES
Unhealthy dietary behaviors constitute one of risk the factors for chronic and cardiovascular
diseases, which are prevalent in middle-aged and older populations. Milk and dairy
products are high-quality foods and important sources of calcium. Calcium protects
against osteoporosis and cardiovascular disease. Therefore, this study investigated
the association of milk and dairy product consumption with cardio-cerebrovascular
disease incidence in middle-aged and older Korean adults.
SUBJECTS/METHODS
Data were derived from the Ansan–Anseong cohort study, and a total of 8,009 individuals
aged 40–69 years were selected and followed up biennially. Cox proportional hazard
models were used to examine the association of milk and dairy product consumption
with cardio-cerebrovascular disease incidence.
RESULTS
During a mean follow-up period of 96.5 person-months, 552 new cases of cardio-cerebrovascular
disease were documented. Milk consumers (< 1 serving/day) exhibited a 23% lower risk
of cardio-cerebrovascular disease incidence than non-milk consumers (hazard ratio
[HR], 0.77; 95% confidence interval [CI], 0.61–0.97;
P for trend = 0.842). High yogurt consumption was associated with a 29% lower incidence
risk (≥ 0.5 servings/day vs. none: HR, 0.71; 95% CI, 0.53–0.96;
P for trend = 0.049), whereas high ice cream consumption was associated with a 70%
higher risk of cardio-cerebrovascular disease incidence (≥ 0.5 servings/day vs. none:
HR, 1.70; 95% CI, 1.01–2.88;
P for trend = 0.070).
CONCLUSIONS
This study indicates that less than one serving of milk and high yogurt consumption
are associated with a lower cardio-cerebrovascular disease risk in the middle-aged
and older populations.
Summary Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4–61·9) in 1980 to 71·8 years (71·5–72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7–17·4), to 62·6 years (56·5–70·2). Total deaths increased by 4·1% (2·6–5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8–18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6–16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9–14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1–44·6), malaria (43·1%, 34·7–51·8), neonatal preterm birth complications (29·8%, 24·8–34·9), and maternal disorders (29·1%, 19·3–37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000–183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000–532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation.
We provide an updated version of the Compendium of Physical Activities, a coding scheme that classifies specific physical activity (PA) by rate of energy expenditure. It was developed to enhance the comparability of results across studies using self-reports of PA. The Compendium coding scheme links a five-digit code that describes physical activities by major headings (e.g., occupation, transportation, etc.) and specific activities within each major heading with its intensity, defined as the ratio of work metabolic rate to a standard resting metabolic rate (MET). Energy expenditure in MET-minutes, MET-hours, kcal, or kcal per kilogram body weight can be estimated for specific activities by type or MET intensity. Additions to the Compendium were obtained from studies describing daily PA patterns of adults and studies measuring the energy cost of specific physical activities in field settings. The updated version includes two new major headings of volunteer and religious activities, extends the number of specific activities from 477 to 605, and provides updated MET intensity levels for selected activities.
To evaluate validity and reliability of the food-frequency questionnaire (FFQ) developed for the Korean Genome Epidemiologic Study (KoGES). FFQ was administered twice at 1-year interval (first FFQ (FFQ1) at the beginning and second FFQ (FFQ2) at the end of the study) and diet records (DRs) were collected for 3 days during each of the four seasons from December 2002 to May 2004 for those who attended the health examination center. At the end of the study period, we collected the 12-day DRs of 124 participants. The nutrient intakes from the DRs were compared with both FFQ1 and FFQ2. The intakes of energy and some nutrients estimated from FFQ1 and FFQ2 were different from those assessed by the DRs. Especially, the consumption of carbohydrates was higher in FFQ1 and FFQ2 than in the DRs. The de-attenuated, age, sex and energy intake adjusted correlation coefficients between the FFQ2 and the 12-day DRs in Korean population ranged between 0.23 (Vitamin A) and 0.64 (carbohydrate). The median for all nutrients was 0.39. The correlations were similar when we compared nutrient densities of both methods. Joint classification of calorie-adjusted nutrient intakes assessed by FFQ2 and 12-day DRs by quartile ranged from 25.8% (vitamin A) to 39.5% (carbohydrate, iron) for exact concordance. Except vitamin A, the proportion of subjects classified into distant quartile was less than 7% in all nutrients. The median of correlations between the two FFQs 1 year apart were 0.45 for all nutrient intakes and 0.39 for nutrient densities. We conclude that the FFQ we have developed appears to be an acceptable tool for assessing the nutrient intakes in this population. Further studies for calibration of the FFQ collected from multicenters participating in the KoGES are needed. This study was supported by the budget of the National Genome Research Institute, Korea National Institute of Health (2002-347-6111-221).
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