Anthropometric data indicate that the human phenotype is changing. Today's adult is greater in stature, body mass and fat mass. Accurate measurement of body composition is necessary to maintain surveillance of obesity within the population and to evaluate associated interventions. The aim of the present study was to construct and validate generalised equations for percentage body fat (%BF) prediction from anthropometry in 1136 adult men and women. Reference values for %BF were obtained using dual-energy X-ray absorptiometry. Skinfold thickness (SF) at ten sites and girth (G) at seven sites were measured on 736 men and women aged 18–81 years (%BF 5·1–56·8 %). Quantile regression was employed to construct prediction equations from age and log-transformed SF and G measures. These equations were then cross-validated on a cohort of 400 subjects of similar age and fatness. The following generalised equations were found to most accurately predict %BF: $Men:\,(age\times 0\cdot 1) + (logtricepsSF\times 7\cdot 6) + (logmidaxillaSF\times 8\cdot 8) + (logsuprspinaleSF\times 11\cdot 9) - 11\cdot 3$ (standard error of the estimate: 2·5 %, 95 % limits of agreement: − 4·8, +4·9) $Women:\,(age\times 0\cdot 1) + (logabdominalG\times 39\cdot 4) + (logmidaxillaSF\times 4\cdot 9) + (logbicepsSF\times 11\cdot 0) + (logmedialcalfSF\times 9\cdot 1) - 73\cdot 5$ (standard error of the estimate: 3·0 %, 95 % limits of agreement: − 5·7, + 5·9) These generalised anthropometric equations accurately predict %BF and are suitable for the measurement of %BF in adult men and women of varying levels of fatness across the lifespan.