Weight change and change of total cholesterol and high-density-lipoprotein cholesterol results of the MONICA Augsburg cohort study

Eberle, Ernst; Doering, Angela; Keil, Ulrich

doi:10.1016/1047-2797(91)90020-d

Cited by 15 publications

(8 citation statements)

References 14 publications

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“…On the other hand, in females at the age of 50-64 y where the cholesterol levels are already quite high, there is no statistically significant correlation between PHC and BMI, and among males is this PHC-BMI relation weak. The same relationship was observed by Eberle et al 42 Tanaka et al 43 reported that among malesFbut not among femalesFthere was a significant association between BMI and coronary stenosis, and this positive association was more pronounced among younger patients than older ones. Thus, this clinical finding is consistent with the result of our analysis indicating the presence of interaction effects of age and indirectly of gender on PHC-BMI relation.…”

Section: Resultssupporting

confidence: 70%

Analysis of the relationship between total cholesterol, age, body mass index among males and females in the WHO MONICA Project

et al. 2004

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OBJECTIVE: To explore the relationship between hypercholesterolaemia, age and BMI among females and males. DESIGN: Population-based cross-sectional survey. SUBJECTS: The data came from the initial surveys of the WHO MONICA Project. In all, 27 populations with 48 283 subjects (24 017 males and 24 266 females) aged 25-64 y were used for the analysis. MEASUREMENTS: Total cholesterol, weight, height, BMI, prevalence of hypercholesterolaemia (PHC) defined as cholesterol Z6.5 mmol/l, and the prevalence of obesity (POB) defined as BMI Z30 kg/m 2 . RESULTS: PHC increased with age, with PHC in males being significantly higher than in females at age range 25-49 y and significantly lower than in females at age range 50-64 y. Age-related increase in hypercholesterolaemia was steeper in females than in males. There was a statistically significant positive association between hypercholesterolaemia and BMI. Multiple logistic regression analysis revealed a negative statistically significant (Po0.001) effect modification involving age and BMI on the risk of having hypercholesterolaemia both in females and males. The relation between PHC and BMI became weaker in higher age groups, with no statistically significant association in females aged 50-64 y. CONCLUSION: Public health measures should be directed at the prevention of obesity in young adults since the strongest effect of obesity on the risk of hypercholesterolaemia has been found in subjects aged 25-39 y.

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Section: Resultssupporting

confidence: 70%

Analysis of the relationship between total cholesterol, age, body mass index among males and females in the WHO MONICA Project

et al. 2004

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“…22 When analyzing individual parameters or clusters taking the confounders into account, our results are in accordance with worldwide previous studies showing associations of blood pressure and lipid profile changes over time with changes in BMI for both sexes. 4,6,8,23,24 In addition, similarly to previous investigations, changes in GGT activity and uric acid concentrations 15 were significantly associated with BMI gain in both genders and no association was found with changes in fasting blood glucose levels. 4,7 Conversely, BMI changes were associated with changes in ALP and in inflammatory markers (hs-CRP, haptoglobin, orosomucoid and summary cluster inflammation) in women only.…”

Section: Discussionsupporting

confidence: 63%

“…3 To investigate the association between body fat mass and adiposity excess on cardiovascular diseases, several population-based studies evaluated the relationships of changes in anthropometric parameters with the metabolic syndrome (MS)-associated factors. Weight gain is accompanied by the early and more aggressive manifestations of well-recognized risk factors for atherosclerotic cardiovascular disease: blood pressure, [4][5][6][7] lipid profile, 4,5,[7][8][9] blood glucose and insulin resistance, 10 inflammatory biomarkers such as high-sensitivity C-reactive protein (hs-CRP), 11,12 liver enzymes such as g-glutamyl transferase (GGT) 13 and uric acid. 14,15 Conversely, weight loss improves cardiometabolic risk.…”

Section: Introductionmentioning

confidence: 99%

Five-year alterations in BMI are associated with clustering of changes in cardiovascular risk factors in a gender-dependant way: the Stanislas study

et al. 2008

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Objective: The purpose of the present longitudinal study was to describe the associations between the 5-year changes in body mass index (BMI) and alterations in the clusters of metabolic syndrome (MS)-related factors. Methods: The study population comprised 1099 middle-aged adults drawn from the Stanislas study. Individuals were stratified into four groups according to the 5-year changes in BMI (weight loss (o0 kg/m 2 ), and weight gain (0-1, 1-2 and 42 kg/m 2 )). Changes in various MS-related variables and clusters were compared between groups: anthropometric indices, blood pressure, lipid and inflammatory markers, liver enzymes, uric acid and the five summary factors extracted by using factor analysis ('risk lipids', 'liver enzymes', 'inflammation', 'protective lipids' and 'blood pressure').Results: There was a strong linear trend between increasing BMI and worsening of risk lipids and blood pressure factors for both men and women (Pp0.001). In men only, liver enzymes and protective lipids factors were significantly related to the 5-year gain of BMI (Pp0.001), whereas inflammation factor positively increased across the four BMI-change groups, in women only. Interaction terms for sex were statistically significant for inflammation and liver enzymes clusters. Conclusion: In our population, there was a strong linear trend between increasing BMI and worsening of various MS-related variables. More interestingly, the identification of five factors associated with BMI changes dependent to gender, support the hypothesis that weight gain, and probably obesity, trigger metabolic mechanisms that differ between men and women.

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“…[1][2][3][4][5][6][7][8][9][10][11][12][13][14] Adiposity is an important influence on adult lipid and lipoprotein profiles. [15][16][17][18][19][20][21] The body mass index (BMI) is often used as a proxy measure of adiposity and in adults BMI is positively related to LDL-C, TG and TC, and negatively related to HDL-C. 22 However, BMI is a composite of adipose and lean tissues, both of which can have distinct effects on lipid and lipoprotein levels. Unfortunately, the relative contributions of fat and lean tissue to variation in lipid and lipoprotein levels are indistinguishable when adjusting only for BMI or percent body fat.…”

Section: Introductionmentioning

confidence: 99%

Lipids, lipoproteins, lifestyle, adiposity and fat-free mass during middle age: the Fels Longitudinal Study

et al. 2005

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Introduction: Although lipid profiles tend to worsen with age, it is not fully known if such age-related changes are influenced primarily by body composition and lifestyle or by other aspects of aging. Objective: We investigated the extent to which the fat and fat-free components of body mass index (BMI) and lifestyle factors influence patterns of change in lipids independent of age. Design: Serial data were analyzed using sex-specific longitudinal models. These models use serial data from individuals to assume a general pattern of change over time, while allowing baseline age and the rate of change to vary among individuals. Subjects: Serial data were obtained from 940 examinations of 269 healthy white participants (126 men, 143 women), aged 40-60 years, in the Fels Longitudinal Study. Measurements: Measurements included age, the fat (FMI) and fat-free mass (FFMI) components of BMI, high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), triglycerides (TG), total cholesterol (TC), fasting glucose and insulin, physical activity, alcohol use and smoking, and women's menopausal status and estrogen use. Results: In both sexes, increased FMI was significantly associated with increased LDL-C, TG and TC, and decreased HDL-C. Increased FFMI was significantly related to decreased HDL-C and increased TG. Independent age effects remained significant only for LDL-C and TC in men and TC in women. Increased insulin was significantly related to increased TG in women. Moderate alcohol consumption was associated with higher HDL-C in men. Physical activity lowered male LDL-C and TC levels, and increased female HDL-C levels. Menopause was associated with increases in LDL-C. Premenopausal women not using estrogen had significantly lower HDL-C, TG, and TC than postmenopausal women taking estrogen. Conclusions: (1) Age is an important independent predictor for LDL-C and TC in men, and TC in women, but it is not as influential as body composition and lifestyle on HDL-C and TG in men and women, and LDL-C in women. (2) Increasing FMI is the major contributor to elevated TC, LDL-C and TG levels, and decreased HDL-C levels in men and women. (3) FFMI significantly influences HDL and TG levels in both sexes. (4) Maintaining a lower BMI via a reduced fat component may be more beneficial in lowering CVD risks than other factors.

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Weight change and change of total cholesterol and high-density-lipoprotein cholesterol results of the MONICA Augsburg cohort study

Cited by 15 publications

References 14 publications

Analysis of the relationship between total cholesterol, age, body mass index among males and females in the WHO MONICA Project

Analysis of the relationship between total cholesterol, age, body mass index among males and females in the WHO MONICA Project

Five-year alterations in BMI are associated with clustering of changes in cardiovascular risk factors in a gender-dependant way: the Stanislas study

Lipids, lipoproteins, lifestyle, adiposity and fat-free mass during middle age: the Fels Longitudinal Study

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