Research Article: Associations of Insulin and Insulin-Like Growth Factors with Physical Performance in Old Age in the Boyd Orr and Caerphilly Studies

Date Published: January 10, 2012

Publisher: Public Library of Science

Author(s): Kate Birnie, Yoav Ben-Shlomo, Jeff M. P. Holly, David Gunnell, Shah Ebrahim, Antony Bayer, John Gallacher, Richard M. Martin, Yiqing Song. http://doi.org/10.1371/journal.pone.0030096

Abstract

Insulin and the insulin-like growth factor (IGF) system regulate growth and are involved in determining muscle mass, strength and body composition. We hypothesised that IGF-I and IGF-II are associated with improved, and insulin with worse, physical performance in old age.

Physical performance was measured using the get-up and go timed walk and flamingo balance test at 63–86 years. We examined prospective associations of insulin, IGF-I, IGF-II and IGFBP-3 with physical performance in the UK-based Caerphilly Prospective Study (CaPS; n = 739 men); and cross-sectional insulin, IGF-I, IGF-II, IGFBP-2 and IGFBP-3 in the Boyd Orr cohort (n = 182 men, 223 women).

In confounder-adjusted models, there was some evidence in CaPS that a standard deviation (SD) increase in IGF-I was associated with 1.5% faster get-up and go test times (95% CI: −0.2%, 3.2%; p = 0.08), but little association with poor balance, 19 years later. Coefficients in Boyd Orr were in the same direction as CaPS, but consistent with chance. Higher levels of insulin were weakly associated with worse physical performance (CaPS and Boyd Orr combined: get-up and go time = 1.3% slower per SD log-transformed insulin; 95% CI: 0.0%, 2.7%; p = 0.07; OR poor balance 1.13; 95% CI; 0.98, 1.29; p = 0.08), although associations were attenuated after controlling for body mass index (BMI) and co-morbidities. In Boyd Orr, a one SD increase in IGFBP-2 was associated with 2.6% slower get-up and go times (95% CI: 0.4%, 4.8% slower; p = 0.02), but this was only seen when controlling for BMI and co-morbidities. There was no consistent evidence of associations of IGF-II, or IGFBP-3 with physical performance.

There was some evidence that high IGF-I and low insulin levels in middle-age were associated with improved physical performance in old age, but estimates were imprecise. Larger cohorts are required to confirm or refute the findings.

Partial Text

Increasing life expectancy in the UK has provoked public health concern about the prospects of a growing number of people experiencing functional limitations in old age. Understanding the causes of poor physical functioning and the identification of potential prevention strategies are critically important public health issues. One possible pathway contributing to poor physical functioning is the insulin-like growth factor (IGF) system. The IGF family contains two peptide hormones, or growth factors: IGF-I and IGF-II; and six binding proteins IGFBP-1 to -6 that modulate IGF activity [1]. Ageing is associated with a decline in levels of IGF-I, which may reflect decreases in growth hormone production with age [2]. The IGF system is involved in body composition, muscle maintenance and bone cell survival [3] and might influence measures of physical function in old age via a loss of muscle mass and strength [4]. A previous cross-sectional study indicates that high levels of IGF-I are weakly associated with faster walking speed [5] but results have not always been consistent [6], [7]. Other components of the IGF system may also be associated with functional ability with age: high IGF-I increases sensitivity to insulin [8] which may in turn be related to increased muscle strength [9]; circulating levels of IGFBP-2 are reduced in people with obesity [10] and insulin resistance [7], [11], [12] and may mediate associations of obesity and insulin resistance with poor physical functioning; higher circulating IGFBP-3 lowers the bioavailability of IGF-I, so may be associated with poorer physical performance, although, IGFBPs are thought to exert both positive and negative regulatory effects on IGF activity [13]. The role of IGF-II is less well known, although it has been suggested to play a critical role in muscle regeneration, and relatively higher IGF-II levels may prevent the age-related decline in muscle mass [14]. Understanding the role of the insulin-IGF system in physical performance has potential public health implications because it is nutritionally regulated, e.g. higher milk intake increases IGF-I [15], and IGFs are linked with other lifestyle factors, e.g. IGF-I and IGFBP-3 have been positively associated with increased physical activity and reduced cigarette smoking [16], so may be potentially modifiable.

Descriptive statistics for the outcomes, exposures and potential confounding variables are shown in Table 1. In Boyd Orr, the physical performance tests and IGF measurements were carried out when the participants were a mean age of 70.7 years (inter-quartile range [IQR] 67–74; range 63–83 years). CaPS men were older at the time of the physical performance tests (mean age 75.3; IQR 71–78; range 66–86 years) and their blood samples for the IGF measurements were taken approximately 19 years earlier (mean age 56.1; IQR 52–60; range 47–67 years).

This is the first study to suggest that higher IGF-I and lower insulin levels measured in mid-life are prospectively associated with improvements in objective assessments of physical performance measured decades later, although the effect estimates were imprecisely estimated (with wide confidence intervals) and so inferences from this study must be made with caution. The associations for insulin were explained by BMI and co-morbidities, though we cannot be certain whether BMI was the upstream determinant of raised insulin or vice versa. There were no associations with IGF-II in either cohort. An association between high IGFBP-2 and slower get-up and go speed was only observed when BMI and co-morbidities were controlled for, so should be interpreted with caution. In the cross-sectional analyses (Boyd Orr), higher levels of IGFBP-3 were associated with faster get-up and go times, but this was not seen in the prospective analyses (CaPS).

Source:

http://doi.org/10.1371/journal.pone.0030096