The Relationship between Body Mass Index and 10-Year Trajectories of Physical Functioning in Middle-Aged and Older Russians: Prospective Results of the Russian HAPIEE Study

Sex differences in physical functioning among older adults: cross-sectional results from the OUTDOOR ACTIVE study

BACKGROUND

Maintaining good functional ability is a key component of healthy ageing and a basic requirement for carrying out activities of daily living, staying independent, and delaying admission to a nursing home. Even though women have a higher life expectancy and slower age-related muscle mass loss than men, they often show a higher prevalence of limitations in physical functioning. However, the reasons behind these sex differences are still unclear. Therefore, the aims of this study were to investigate sex differences among older adults regarding physical functioning and to study which factors are explaining these sex differences.

METHODS

Cross-sectional data from participants of the OUTDOOR ACTIVE study residing in Bremen, Germany, aged 65 to 75 years, were included in the analyses. Physical functioning was assessed via a self-administered questionnaire using the SF-36 10-item Physical Functioning Scale. Social, lifestyle, and health-related factors were also assessed using the questionnaire. Physical activity was measured objectively using wrist-worn accelerometers over seven consecutive days. Descriptive analyses with absolute and relative frequencies, means and standard deviations, as well as T-tests and chi-square tests were carried out. To test for associations between sex, physical functioning, and several individual factors, linear regressions were performed.

RESULTS

Data of 2 141 participants (52.1% female) were included in the study. Women and men showed statistically significant differences in physical functioning, with men perceiving fewer limitations than women. On average, women had a physical functioning score of 81.4 ± 19.3 and men 86.7 ± 17.0. Linear regression showed a statistically significant negative association between physical functioning score and sex (β: -0.15, 95% CL: -0.19, -0.10). The association remained statistically significant when adding individual factors to the model. All factors together were only able to explain 51% of the physical functioning-sex association with health indicators and the presence of chronic diseases being the most influential factors.

CONCLUSIONS

We found sex differences in physical functioning, with older women having more limitations than older men. The results showed that health-related factors and chronic diseases played the biggest roles in the different physical functioning scores of women and men. These findings contribute to future longitudinal, more in-depth research.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00015117 (Date of registration 17-07-2018).

Physical activity positively impacts disability outcomes during transition from midlife to early older age irrespective of body mass index

We examined the effects of physical activity (PA) and body mass index (BMI) longitudinal patterns (trajectories) on subjective measures of mobility, function, and disability in adults and assessed whether effects of PA trajectories on function varied due to BMI. Group-based trajectory analyses were used to determine patterns of change in PA and BMI using data from the Health and Retirement Study 1931-1941 birth cohort (n = 10,507). Physical function was assessed by Mobility Limitations (0-5 scale) and Large Muscle Function (0-4 scale) Indexes, as well as with score for activities of daily living (ADLs) and instrumental activities of daily living (IADLs), with higher scores being worse. Our analyses estimated four distinct PA trajectories: decreasing, (2) fluctuating, (3) stable high, and (4) emergent (previously low/sedentary with increased PA over the study period). Worse mobility limitations, large muscle function, ADLs, and IADLs were associated with Decreasing and Fluctuating PA groups. Better outcomes were associated with Emergent and Stable High PA groups. The five BMI trajectories were stable normal/overweight, modest decreasing, fluctuating, steep decreasing, and increasing. No significant interaction existed between PA and BMI trajectories for Mobility Limitations (P= 0.577), Large Muscle Function (P= 0.511), ADLs (P= 0.600), and IADLs (P= 0.152). These findings may empower clinicians to promote messages to midlifers that meaningful changes in PA can improve function in older age.

Longitudinal trajectories of blood lipid levels in an ageing population sample of Russian Western-Siberian urban population

This study investigated 12-year blood lipid trajectories and whether these trajectories are modified by smoking and lipid lowering treatment in older Russians. To do so, we analysed data on 9,218 Russian West-Siberian Caucasians aged 45-69 years at baseline participating in the international HAPIEE cohort study. Mixed-effect multilevel models were used to estimate individual level lipid trajectories across the baseline and two follow-up examinations (16,445 separate measurements over 12 years). In all age groups, we observed a reduction in serum total cholesterol (TC), LDL-C and non-HDL-C over time even after adjusting for sex, statin treatment, hypertension, diabetes, social factors and mortality (P<0.01). In contrast, serum triglyceride (TG) values increased over time in younger age groups, reached a plateau and decreased in older age groups (> 60 years at baseline). In smokers, TC, LDL-C, non-HDL-C and TG decreased less markedly than in non-smokers, while HDL-C decreased more rapidly while the LDL-C/HDL-C ratio increased. In subjects treated with lipid-lowering drugs, TC, LDL-C and non-HDL-C decreased more markedly and HDL-C less markedly than in untreated subjects while TG and LDL-C/HDL-C remained stable or increased in treatment naïve subjects. We conclude, that in this ageing population we observed marked changes in blood lipids over a 12 year follow up, with decreasing trajectories of TC, LDL-C and non-HDL-C and mixed trajectories of TG. The findings suggest that monitoring of age-related trajectories in blood lipids may improve prediction of CVD risk beyond single measurements.

Weight change and risk of the foundation of National Institute of Health Sarcopenia-defined low lean mass: Data from the National Health and Nutrition examination surveys 1999-2004

BACKGROUND

Self-reported weight change may lead to adverse outcomes. We evaluated weight change with cutpoints of low lean mass (LLM) in older adults.

METHODS

Of 4984 subjects ≥60 years from NHANES 1999-2004, we applied LLM cutoffs of appendicular lean mass (ALM):body mass index (BMI) males<0.789, females<0.512. Self-reported weight was assessed at time of survey, and questions asked participants their weight one and 10 years earlier, and at age 25. Weight changes were categorized as greater/less/none than 5%. Logistic regression assessed weight change (gain, loss, no change) on LLM, after adjustment.

RESULTS

Of 4984 participants (56.5% female), mean age and BMI were 71.1 years and 28.2 kg/m2. Mean ALM was 19.7 kg. In those with LLM, 13.5% and 16.3% gained/lost weight in the past year, while 48.9% and 19.4% gained/lost weight in the past decade. Compared to weight at age 25, 85.2 and 6.1% of LLM participants gained and lost ≥5% of their weight, respectively. Weight gain over the past year was associated with a higher risk of LLM (OR 1.35 [0.99,1.87]) compared to weight loss ≥5% over the past year (0.89 [0.70,1.12]). Weight gain (≥5%) over 10-years was associated with a higher risk of LLM (OR 2.03 [1.66, 2.49]) while weight loss (≥5%) was associated with a lower risk (OR 0.98 [0.76,1.28]). Results were robust compared to weight at 25 years (gain OR 2.37 [1.76,3.20]; loss OR 0.95 [0.65,1.39]).

CONCLUSION

Self-reported weight gain suggests an increased risk of LLM. Future studies need to verify the relationship with physical function.