4 Table 2: Association between single items of foods/beverages possi- bly inﬂuencing the acid load and distal forearm bone mineral den- sity, adjusted for possible confounding variables. Linear regression. Adjusted for all the other Adjusted for food items listed and the covariatesa,b covariatesa B (SE) P B (SE) P −0.003 −0.002 Colasc .012 .067 (0.001) (0.001) −0.004 −0.003 Non-cola soft drinksc .026 .128 (0.002) (0.002) 0.001 0.000 Fruit/berriesd .216 .812 (0.001) (0.001) 0.000 −0.001 Cooked vegetablesd .933 .670 (0.001) (0.001) 0.002 0.002 Raw vegetablesd .046 .174 (0.001) (0.001) 0.001 0.001 Fruit juiced .315 .386 (0.001) (0.001) a Gender, age, weight, height, years at school, smoking, frequency of alcohol intake, and leisure time physical activity. bPerformed with one by one of the items of food/beverages as main inde- pendent cFive intake frequency estimates (see Section 2) dSix intake frequency estimates (see Section 2). Unstandardized (B) regression coeﬃcients are shown. Table 3: Four diﬀerent linear regression models of the association between the Dietary Indexa and distal bone mineral density, as in- ﬂuenced by increasing number of possible confounding variables. B (SE) Model (1) (adjusted for −0.024 gender and age group) (0.007) Model (2) (+ weight + height) (−00. 0.00276) Model (3) (+ years at school) −0.024 (0.008) Model (4) (+ smokingb + alcoholc. leisure time physical −0.023 activity)d (0.008) β t −0.050 −3.238 −0.054 −3.490 −0.052 −3.210 −0.050 −3.003 P <.001 <.001 .001 .003 a The Dietary Index is the sum of intake frequency estimates of 2 diet items (colas and non-cola soft drinks) divided by the sum of intake estimates of 4 items (fruit/berries, cooked vegetables, raw vegetables/salads, and fruit juice). There were 5 response alternatives for beverages and 6 for the food items (see Section 2). bnever smoker versus current or previous. c1–7 times per week versus less frequent. dLeisure time physical activity 0, <1, 1-2, 3 or more hours per week. Unstandardized (B) and standardized (β) regression coeﬃcients are shown. number of possible covariates in models (2)–(4) (Table 3). The β coeﬃcient remained almost constant when adding variables such as body mass index, years at school, smoking, alcohol intake, and leisure time physical activity. Additional adjustment for milk consumption (5 response alternatives) did not change the result (β coeﬃcient = −0.050). An additional question asked the respondents whether their consumption of soft drinks were mainly with sugar or without. Of those answering this question, 35% mainly Journal of Osteoporosis Table 4: Association between various indexes assumed to partially reﬂect the acid load and distal forearm bone mineral density. The index was reduced by omitting one by one of its components: linear regression. Index type B (SE) β T P (1) The complete −0.023 −0.050 −3.003 .003 Dietary Indexa (0.008) −0.017 (2) Fruit juice −0.048 −2.869 .004 (0.006) −0.010 (3) Also raw vegetables −0.042 −2.452 .011 (0.004) (4) Also cooked −0.004 −0.044 −2.726 .006 vegetables (0.002) −0.003 (5) Also fruit/berries −0.048 −2.995 .003 (0.001) (6) Also non-cola −0.003 −0.040 −2.523 .012 soft drinks (0.001) a The Dietary Index is the sum of intake frequency estimates of 2 diet items (colas and non-cola soft drinks) divided by the sum of intake estimates of 4 items (fruit/berries, cooked vegetables, raw vegetables/salads, and fruit juice). There were 5 response alternatives for beverages and 6 for the food items (see Section 2). Covariates: those mentioned in Table 2. Unstandardized (B) and standardized (β) regression coeﬃcients are shown. used soft drinks without sugar. Taking this variable into the regression analyses did not change the results. The analyses in Table 3 were also done for BMD at ultra- distal site. The unstandardized (B) and standardized (β) regression coeﬃcients were slightly less negative, but the pat- tern was the same (results not shown). 3.4. Linear Regression Analyses in Each Gender. Model (4) in Table 3 was then used to analyze the association between BMD and the Dietary Index in women and men, separately. There was still a signiﬁcant association in men (P = .03) and women (P = .05), results not shown. 3.5. Reducing the Number of Variables in the Dietary Index. We ﬁnally studied the inﬂuence of reducing the number of components in the Dietary Index, by omitting one by one of its components, starting with fruit juice and ending with non-cola soft drinks, leaving cola solely in the formula (Table 4). Adjusting for the covariates mentioned in Table 2, the β values were gradually attenuated from −0.050 to −0.040 but the association remained signiﬁcant (Table 4). 4. Discussion The present ﬁndings would seem in keeping with the view that intake of fruits and vegetables acts positively and soft drinks negatively on bone mineral density. However, cross- sectional data are not suitable to clarify whether associations are causal. The Dietary Index probably reﬂects an unhealthy lifestyle in general, and mechanisms to explain the observed associations are not clariﬁed by the present results. Still, the consistency of our ﬁndings is noteworthy, and we will shortly discuss some possible mechanisms, based upon current li- terature.