Impact of adiposity on risk of female gout among those genetically predisposed: sex-specific prospective cohort study findings over &gt;32 years

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Abstract

Objectives

To evaluate the joint (combined) association of excess adiposity and genetic predisposition with the risk of incident female gout, and compare to their male counterparts; and determine the proportion attributable to body mass index (BMI) only, genetic risk score (GRS) only, and to their interaction.

Methods

We prospectively investigated potential gene-BMI interactions in 18 244 women from the Nurses’ Health Study and compared with 10 888 men from the Health Professionals Follow-Up Study. GRS for hyperuricaemia was derived from 114 common urate-associated single nucleotide polymorphisms.

Results

Multivariable relative risk (RR) for female gout was 1.49 (95% CI 1.42 to 1.56) per 5 kg/m ² increment of BMI and 1.43 (1.35 to 1.52) per SD increment in the GRS. For their joint association of BMI and GRS, RR was 2.18 (2.03 to 2.36), more than the sum of each individual factor, indicating significant interaction on an additive scale (p for interaction <0.001). The attributable proportions of joint effect for female gout were 42% (37% to 46%) to adiposity, 37% (32% to 42%) to genetic predisposition and 22% (16% to 28%) to their interaction. Additive interaction among men was smaller although still significant (p interaction 0.002, p for heterogeneity 0.04 between women and men), and attributable proportion of joint effect was 14% (6% to 22%).

Conclusions

While excess adiposity and genetic predisposition both are strongly associated with a higher risk of gout, the excess risk of both combined was higher than the sum of each, particularly among women.

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Most cited references 91

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Reproducibility and validity of a semiquantitative food frequency questionnaire.

WALTER WILLETT, LAURA SAMPSON, MEIR STAMPFER … (1985)

The aim of this study was to evaluate the reproducibility and validity of a 61-item semiquantitative food frequency questionnaire used in a large prospective study among women. This form was administered twice to 173 participants at an interval of approximately one year (1980-1981), and four one-week diet records for each subject were collected during that period. Intraclass correlation coefficients for nutrient intakes estimated by the one-week diet records (range = 0.41 for total vitamin A without supplements to 0.79 for vitamin B6 with supplements) were similar to those computed from the questionnaire (range = 0.49 for total vitamin A without supplements to 0.71 for sucrose), indicating that these methods were generally comparable with respect to reproducibility. With the exception of sucrose and total carbohydrate, nutrient intakes from the diet records tended to correlate more strongly with those computed from the questionnaire after adjustment for total caloric intake. Correlation coefficients between the mean calorie-adjusted intakes from the four one-week diet records and those from the questionnaire completed after the diet records ranged from 0.36 for vitamin A without supplements to 0.75 for vitamin C with supplements. Overall, 48% of subjects in the lowest quintile of calorie-adjusted intake computed from the diet records were also in the lowest questionnaire quintile, and 74% were in the lowest one of two questionnaire quintiles. Similarly, 49% of those in the highest diet record quintile were also in the highest questionnaire quintile, and 77% were in the highest one or two questionnaire quintiles. These data indicate that a simple self-administered dietary questionnaire can provide useful information about individual nutrient intakes over a one-year period.

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Recommendations for presenting analyses of effect modification and interaction.

Mirjam J Knol, Tyler J. VanderWeele (2012)

Authors often do not give sufficient information to draw conclusions about the size and statistical significance of interaction on the additive and multiplicative scales. To improve this, we provide four steps, template tables and examples. We distinguish two cases: when the causal effect of intervening on one exposure, across strata of another factor, is of interest ('effect modification'); and when the causal effect of intervening on two exposures is of interest ('interaction'). Assume we study whether X modifies the effect of A on D, where A, X and D are dichotomous. We propose presenting: (i) relative risks (RRs), odds ratios (ORs) or risk differences (RDs) for each (A, X) stratum with a single reference category taken as the stratum with the lowest risk of D; (ii) RRs, ORs or RDs for A within strata of X; (iii) interaction measures on additive and multiplicative scales; (iv) the A-D confounders adjusted for. Assume we study the interaction between A and B on D, where A, B and D are dichotomous. Steps (i) and (iii) are similar to presenting effect modification. (ii) Present RRs, ORs or RDs for A within strata of B and for B within strata of A. (iv) List the A-D and B-D confounders adjusted for. These four pieces of information will provide a reader the information needed to assess effect modification or interaction. The presentation can be further enriched when exposures have multiple categories. Our proposal hopefully encourages researchers to present effect modification and interaction analyses in as informative a manner as possible.