Association between physical activity and healthcare costs by weight status in middle age: Evidence from the Northern Finland Birth Cohort 1966

Association between physical activity and healthcare costs by weight status in middle age: Evidence from the Northern Finland Birth Cohort 1966 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Association between physical activity and healthcare costs by weight status in middle age: Evidence from the Northern Finland Birth Cohort 1966 Hanna Junttila, Mikko Vaaramo, Iiro Nerg, Sanna Huikari, Jaana Kari, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3373605/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives To study the association of physical activity (PA) with individual-level outpatient primary healthcare (PHC) costs in midlife according to body mass index (BMI) categories. Methods The study population comprised 4 076 participants from the Northern Finland Birth Cohort 1966. The probability of having PHC costs and the previous year PHC cost levels at age 46 according to BMI and self-reported PA and their joint interactions were estimated using a two-part model. The BMI categories were healthy weight, overweight, and obesity at ages 31 and 46, and weight gain between such ages. The PA categories were inactive and active at ages 31 and 46, and turning inactive and turning active between such ages. The adjusted predicted annual individual-level PHC costs (€) for the combined BMI and PA categories were estimated. Results The participants with obesity had a significantly higher probability of having PHC costs (OR = 3.15, 95%CI 1.23–8.02 for females; OR = 3.77, 95%CI 1.31–10.85 for males) than the participants with healthy weight. The participants with obesity (OR = 1.33, 95%CI 1.01–1.75), and those with weight gain (OR = 1.22, 95%CI 1.03–1.44) had significantly higher PHC costs than the participants with healthy weight among females, but not among males. Joint associations of any of the BMI and PA categories with the probability of having PHC costs or cost levels were not found. Among females, the inactive participants with weight gain had 25% higher predicted costs than the inactive participants with healthy weight; and among the participants who turned active, those with weight gain had 65% higher predicted costs than those with healthy weight. Among males with healthy weight, the inactive ones had 38% higher predicted costs than the active participants. Conclusions Reaching the current PA recommendations does not mitigate the impact of obesity and weight gain on outpatient PHC costs in midlife. Health sciences/Health care/Health policy Health sciences/Medical research/Epidemiology Health sciences/Health care/Public health/Epidemiology Health sciences/Health care/Weight management Health sciences/Health care/Diagnosis/Body mass index Figures Figure 1 INTRODUCTION Obesity-related healthcare costs have been rising over the past decades ( 1 – 4 ) and have been predicted to further rise ( 5 ). National spending on direct medical costs related to overweight and obesity has been estimated to be around 4.9–10% of the total healthcare expenditures ( 3 , 6 ), and that related to obesity alone around 0.7–2.8% ( 7 , 8 ). Individuals with obesity have been estimated to have approximately 30–100% higher medical costs than those with healthy weight ( 1 , 6 , 9 , 10 ). Previous research has shown that the health-related risks of obesity can be considerably reduced by physical activity (PA) ( 11 – 16 ). Increasing PA to meet the current recommendations (≥ 150 min/week moderate-to-vigorous PA [MVPA]) ( 17 ) has been reported to eliminate much of the increased mortality risk associated with obesity ( 11 ). PA and cardiorespiratory fitness have been suggested to be more important than weight loss in preventing mortality ( 11 , 13 – 15 ). Better cardiorespiratory fitness was reported to be associated with lower healthcare costs in a 6-year follow-up study, particularly among individuals with obesity ( 18 ). In cross-sectional settings, mean annual unadjusted ( 19 ) and adjusted healthcare costs ( 20 , 21 ) were reported to be lower for those with at least low physical activity compared to sedentary ones among manufacturing employees with obesity ( 21 ) and among randomly sampled middle-aged females ( 19 ) and retirees ( 20 ) with as well healthy weight, overweight, as obesity. Among 18–65 years old university and tertiary care medical center employees, increasing frequency of at least 30 minutes lasting aerobic PA up to four to five weekly exercises were associated with lower healthcare costs across all weight categories ( 22 ). There is no longitudinal birth cohort based large-scale evidence of the impact of PA on obesity-related healthcare costs. Thus, in the present study, we addressed the aforementioned research gap by employing a two-part model that has been shown to fit healthcare expenditures very well ( 23 ). The two-part model allowed us to separately estimate the probability of incurring any outpatient primary healthcare (PHC) costs and, among those who used PHC services, the level of PHC costs, and to compare the results according to the changes in the participants’ PA and body mass index (BMI). The use of individual-level data obtained from a large, unselected, population-based birth cohort and linked to the well-validated national register data gave the present study an advantage over selected populations. Our hypothesis was that reaching the current PA recommendations is associated with lower obesity-related PHC costs. METHODS Study population The study sample consisted of 4 076 (2 324 females and 1 752 males) participants from the population-based Northern Finland Birth Cohort 1966 (NFBC1966) ( 24 , 25 )31- (in 1997) and 46-year (in 2012) follow-ups ( 24 , 25 ). Figure 1 presents construction of the study sample. Detailed information about the follow-ups, attrition analyses, and representativeness of NFBC1966 have been reported previously ( 24 ). Pregnant females at 31-year follow-up were excluded from the study. The participants gave written informed consent before participating in the NFBC1966 study. The Ethical Committee of the Northern Ostrobothnia Hospital District in Oulu, Finland approved the Northern Finland Birth Cohort study (§ 94/2011), which was performed according to the Declaration of Helsinki 1983. Overweight and obesity BMI at ages 31 and 46 was calculated by dividing the measured weight (kg) by the measured height in meters squared (m 2 ) ( 26 , 27 ). If measured parameters were not available, self-reported weight and height were used for the calculations at ages 31 and 46 (see Supplementary Digital Content 1( 28 )). The participants were categorized as follows, according to their BMI ( 26 , 27 , 29 ): ( 1 ) stable obesity (BMI ≥ 30 kg/m 2 at ages 31 and 46); ( 2 ) weight gain (any change to a higher BMI category; that is, change from healthy weight to overweight or obesity, or from overweight to obesity from age 31 to 46); ( 3 ) stable overweight (BMI 25–29.9 kg/m 2 at ages 31 and 46); and ( 4 ) stable healthy weight (BMI 18.5–24.9 kg/m 2 at ages 31 and 46). Physical activity Self-reported leisure-time PA was assessed through the same questionnaire at ages 31 and 46. The participants were asked about the frequency and duration of their engagement in brisk PA (at least some sweating and getting out of breath, corresponding MVPA, ≥ 3 metabolic equivalent of tasks [MET]) (see Supplementary Digital Content 2). The answers were transformed into total weekly minutes of MVPA by multiplying the frequency by the duration. For the analyses, the participants were categorized as follows: ( 1 ) turned inactive (MVPA ≥ 150 min/week at age 31, but < 150 min/week at age 46); ( 2 ) stable inactive (MVPA < 150 min/week at ages 31 and 46); ( 3 ) stable active (MVPA ≥ 150 min/week at ages 31 and 46); and ( 4 ) turned active (MVPA < 150 min/week at age 31, but ≥ 150 min/week at age 46). Healthcare costs Individual-level outpatient PHC costs at age 46 (in 2012) were calculated utilizing the self-reported use of both public and private sector outpatient PHC services in the previous year. The numbers of visits to public sector PHC and occupational healthcare centers to avail of nurse, physiotherapist, physician, and psychology services; to private healthcare to avail of physiotherapist and physician services; and to mental health and substance abuse centers; and the number of physician home visits were asked. The outpatient PHC costs were calculated by multiplying the number of visits to each previously mentioned PHC services and physician home visits with the standard unit costs of those services reported by the Finnish Institute for Health and Welfare ( 30 ), and summing up the costs. All monetary values were converted into 2011 euros, utilizing the monetary value multiplier from Statistics Finland ( 31 ). Covariates Information on the participants’ marital status, employment status, and the highest educational achievement at age 46 was obtained from Statistics Finland ( 31 ). Marital status was dichotomized as “married” (married or in a registered relationship at age 46) and “not married” (others). Employment status was dichotomized as “unemployed” (≥ 6 months unemployment) and “employed” at age 46. Education level was dichotomized according to the International Standard Classification of Education 2011 ( 32 ); those with at least a bachelor’s degree were included in the high education group. Based on to the participants’ self-reported PA at age 14, they were classified as “physically active” or “physically inactive”( 33 ). The information on smoking (never smoked/ex-smoker/current smoker), risk-level alcohol use (≥ 23.5 doses/week for males, ≥ 14 doses/week for females; one dose = 12 g alcohol ( 34 )), daily consumption of fresh vegetables, and weekly consumption of fast food (pizzas and hamburgers) was self-reported at age 46. Statistical analyses A high proportion of the participants had no outpatient PHC costs at all, and among those who had such costs, the expenditures were highly skewed; that is, a small number of participants had very high PHC costs. This shape of medical expenditures is common ( 35 , 36 ), and to account for the shape of the healthcare cost distribution, we used a two-part healthcare cost model ( 23 ). The first part of the model is a logit model that estimates the probability of incurring healthcare costs. The second part estimates the level of healthcare costs conditional on having such costs and is specified as a generalized linear model (GLM) with a gamma variance structure and log link. Both parts of the two-part model included PA categories, BMI categories, and their joint interactions. The analyses were adjusted for covariates listed above and were conducted separately for females and males (for the detailed model specifications, see Supplementary Digital Content 3). Finally, the adjusted predicted levels of individual annual outpatient PHC costs of a person with average characteristics were calculated for the combined BMI and PA categories. All analyses were conducted using Stata version 16.0 (StataCorp LLC, College Station, Texas 77845, USA). RESULTS Descriptive statistics Table 1 shows the descriptive characteristics of all the participants of the NFBC1966 31-year and 46-year follow-ups and the study sample. Table 1 Characteristics of all the participants of the Northern Finland Birth Cohort 1966 (NFBC1966) 31-year (1997) and 46-year (2012) follow-ups and the study sample. All the participants of NFBC1966, Study sample, N = 4 076 still alive in 2012, N = 9 284 (39.45% of those who were alive and living (77.0% of total NFBC1966 cohort population) in Finland with known address in 2012) Females Males Females Males N = 4 809 (51.8%) a N = 4 475 (48.2%) a N = 2 324 (57.02) a %) N = 1 752 (42.98) a %) Married at age 46, N (%) 2 777 (57.25) b 2 477 (55.35) b 1 436 (61.79) b 1 098 (62.67) b High education at age 46, N (%) 2 448 (50.90) b 1 631 (36.45) b 1 381 (59.42) b,c 824 (47.03) b,c Unemployed at age 46, N (%) 309 (6.75) b 442 (10.28) b 128 (5.51) b,d 142 (8.11) b,d Health behavior Non-smoker, N (%) 2 111 (58.3) 1 381 (45.47) 1 414 (60.84) 872 (49.77) Ex-smoker, N (%) 808 (22.31) 860 (28.32) 515 (22.16) 515 (29.39) Current smoker at age 46, N (%) 702 (19.39) 796 (26.21) b 395 (17) c 365 (20.83) b,c Risk-level alcohol use at age 46, N (%) 133 (3.56) 206 (6.57) 80 (3.44) 97 (5.54) Daily use of fresh vegetables at age 46, N (%) 1 540 (41.61) 736 (23.74) 946 (40.71) c 460 (26.26) c Weekly fast-food consumption at age 46, N (%) 508 (13.69) 907 (29.19) 307 (13.21) c 494 (28.2) c Physically active at age 14, N (%) 3 186 (69.7) 3 435 (82.63) 1652 (71.08) c 1 476 (84.25) c Mean primary healthcare costs at age 46, € (SD) 399.53 (689.75) 289.50 (443.02) 374.75 c (575.43) 284.44 c (443.71) MVPA at age 31, mean min/w (SD) 86.40 (101.65) 102.33 (123.31) 89.66 c (103.18) 105.58 c (121.77) MVPA at age 46, mean min/w (SD) 117.22 (120.87) 109.92 (121.69) 118.80 (119.71) 113.10 (118.47) Mean change in MVPA from age 31 to 46, min/w (SD) 30.24 (132.00) 7.05 (138.44) 29.14 c (130.40) 7.52 c (135.45) Mean weight change from age 31 to 46, kg (SD) 7.11 (8.63) a 6.50 (8.25) 7.60 a,c (8.08) 6.8 c (7.44) PA change from 31 to 46 year , N (%) 3 238 (67.33) 2 592 (57.92) 2 324 (100) 1 752 (100) Turned inactive, N (%) 368 (11.37) 363 (14) 272 (11.7) 249 (14.21) Stable inactive, N (%) 1 915 (59.14) 1 471 (56.75) 1 354 (58.26) 974 (55.59) Stable active, N (%) 324 (10.01) 352 (13.58) 243 (10.46) 254 (14.5) Turned active, N (%) 631 (19.49) 406 (15.66) 455 (19.58) 275 (15.7) BMI change from 31 to 46 year , N (%) 3 238 (66.85) 2 592 (59.87) 2 324 (100) 1 752 (100) Stable obesity, N (%) 243 (7.56) 181 (6.76) 167 (7.13) 101 (5.76) Weight gain, N (%) 1 258 (39.13) 1 030 (38.45) 913 (38.9) 669 (38.18) Stable overweight, N (%) 289 (8.99) 686 (25.61) 205 (8.82) 455 (25.97) Stable healthy weight, N (%) 1 425 (44.32) 782 (29.19) 1 039 (45.15) 527 (30.08) High education = bachelor’s degree or higher education; risk-level alcohol use: ≥23.5 doses/week for males, ≥ 14 doses/week for females; MVPA = moderate-to-vigorous physical activity (≥ 3MET); PA = physical activity; min/w = minutes/week; kg = kilogram; turned inactive = MVPA ≥ 150 min/week at age 31, but < 150 min/week at age 46; stable inactive = MVPA < 150 min/week at ages 31 and 46; stable active = MVPA ≥ 150 min/week at ages 31 and 46; turned active = MVPA < 150 min/week at age 31, but ≥ 150 min/week at age 46; BMI = body mass index; stable obesity = BMI ≥ 30 kg/m 2 at ages 31 and 46; weight gain = any change to a higher BMI category (i.e. change from healthy weight to overweight or obesity or from overweight to obesity) from age 31 to 46; stable overweight = BMI 25–29.9 kg/m 2 at ages 31 and 46; stable healthy weight = BMI 18.5–24.9 kg/m 2 at ages 31 and 46. a Difference between the study sample and those who participated in the 31- or 46-year follow-up and were still alive in 2012 at 5% significance level, t-test b Difference between the study sample and those who participated in the 31- or 46-year follow-up and were still alive in 2012 at 5% significance level, Pearson Chi-squared test c The level of statistical significance for the difference between females and males p < 0.001 d The level of statistical significance for the difference between females and males p < 0.01 The study participants were more often married, highly educated, and employed; males of the study sample were more often non-smokers, and females with higher mean weight change from age 31 to 46 than the all NFBC1966 members attended to 31-year and 46-year follow-ups. There were no differences in MVPA, or frequency of different PA and BMI change categories from age 31 to 46. Among the study participants, females had higher average individual-level outpatient PHC costs in the previous year than males at age 46 (mean €375/year vs. €284/year, p < 0.001). Females had lower MVPA than males at age 31 (mean 89.66 min/week, SD 103.18 vs. 105.58 min/week, SD 121.77, p < 0.001), but there was no difference at age 46 (mean 118.80 min/week, SD 119.71 vs. 113.10 min/week SD 118.47, p = 0.065). The MVPA volume increased by 29 min/week (SD = 130.4) on average in females and 8 min/week (SD = 135.45) in males, and weight increased by 7.6 kg (SD = 8.08) on average in females and 6.8 kg (SD = 7.44) in males between ages 31 and 46 ( p < 0.001 and p < 0.001, respectively). Table 2 reports the results of the multivariate logistic regression analyses conducted concerning the associations of the BMI and PA categories at ages 31 and 46, along with their joint associations, with the probability of having any outpatient PHC costs. Table 2 The associations of physical activity and BMI at ages 31 and 46 with the probability of having outpatient primary healthcare costs according to multivariate logistic regressions analysis. OR (95%CI) unadjusted adjusted Females Males Females Males BMI change from 31 to 46 yr Stable obesity 3.53 ** (1.39–8.92) 3.47 * (1.34–8.96) 3.15 * (1.23–8.02) 3.77 * (1.31–10.85) Weight gain 1.19 (0.83–1.71) 1.31 (0.91–1.90) 1.19 (0.78–1.67) 1.27 (0.86–1.87) Stable overweight 0.83 (0.48–1.44) 1.33 (0.87–2.02) 0.83 (0.46–1.49) 1.26 (0.81–1.95) PA change from 31 to 46 yr Turned inactive 2.12 (0.99–4.52) 1.14 (0.59–2.22) 1.80 (0.84–3.89) 1.32 (0.64–2.70) Stable active 0.87 (0.52–1.47) 1.38 (0.77–2.47) 0.73 (0.43–1.26) 1.51 (0.81–2.83) Turned active 1.05 (0.66–1.67) 0.77 (0.45–1.32) 0.97 (0.60–1.59) 0.85 (0.48–1.50) Interaction terms between BMI and PA at ages 31 & 46 Stable obesity * Turned inactive 0.31 (0.03–3.20) 1.11 (0.11–11.22) 0.32 (0.03–3.36) 0.81 (0.07–8.83) Stable obesity * Stable active 1 0.23 (0.04–1.22) 1 0.20 (0.04–1.17) Stable obesity * Turned active 1 0.38 (0.07–1.99) 1 0.43 (0.06–2.97) Weight gain * Turned inactive 0.37 (0.14–0.96) 1.08 (0.44–2.63) 0.41 (0.15–1.08) 0.91 (0.36–2.34) Weight gain * Stable active 1.24 (0.47–3.29) 0.60 (0.26–1.36) 1.37 (0.51–3.69) 0.52 (0.22–1.24) Weight gain * Turned active 1.12 (0.53–2.37) 2.23 (0.96–5.18) 1.14 (0.53–2.45) 1.97 (0.82–4.70) Stable overweight * Turned inactive 0.66 (0.12–3.67) 0.83 (0.33–2.11) 0.71 (0.12–4.06) 0.84 (0.31–2.28) Stable overweight * Stable active 3.19 (0.38–27.11) 0.97 (0.37–2.56) 3.51 (0.41–30.29) 0.90 (0.33–2.45) Stable overweight * Turned active 1.83 (0.54–6.23) 2.13 (0.84–5.42) 1.67 (0.48–5.85) 2.18 (0.81–5.89) Married 0.96 (0.72–1.27) 1.21 (0.93–1.58) High education 1.09 (0.82–1.45) 0.94 (0.72–1.22) Unemployed 0.61 (0.36–1.01) 0.58 * (0.39–0.88) Health behavior Ex-smoker 0.98 (0.70–1.37) 1.28 (0.94–1.73) Current smoker 1.19 (0.80–1.79) 1.02 (0.73–1.43) Risk-level alcohol use 1.01 (0.49–2.10) 1.36 (0.73–1.43) Daily consumption of fresh vegetables 1.27 (0.95–1.69) 1.09 (0.80–1.47) Weekly consumption of fast food 0.89 (0.60–1.31) 1.12 (0.85–1.50) Physically active at age 14 0.80 (0.59–1.09) 0.90 (0.63–1.28) Constant 7.31 *** (5.70–9.39) 3.63 *** (2.78–4.75) 8.42 *** (5.36–13.22) 3.28 *** (2.02–5.35) N 2 453 1 905 2 298 1 752 Log likelihood -817.51 -865.98 -758.58 -793.15 LR chi2 19.21 24.33 25.54 36.73 Prob > chi2 0.117 0.060 0.272 0.047 Pseudo R2 0.012 0.014 0.017 0.023 Robust standard errors are in parentheses. The level of statistical significance: ***p < 0.001, **p < 0.01, *p < 0.05. Base category: Stable healthy weight (BMI 18.5–24.9 kg/m 2 at ages 31 and 46) - Stable inactive (MVPA < 150 min/week at ages 31 and 46). BMI = body mass index; PA = physical activity; stable obesity = BMI ≥ 30 kg/m 2 at ages 31 and 46; weight gain = any change to a higher BMI category (i.e. change from healthy weight to overweight or obesity or from overweight to obesity) from age 31 to 46; stable overweight = BMI 25–29.9 kg/m 2 at ages 31 and 46; turned inactive = MVPA ≥ 150 min/week at age 31, but < 150 min/week at age; stable active = MVPA ≥ 150 min/week at ages 31 and 46; turned active = MVPA < 150 min/week at age 31, but ≥ 150 min/week at age 46; high education = bachelor’s degree or higher education; risk-level alcohol use: ≥23.5 doses/week for males, ≥ 14 doses/week for females.. Without adjustments, female and male participants with stable obesity had a higher probability of having PHC costs than those with stable healthy weight (OR = 3.53, 95% CI 1.39–8.92 for females; OR = 3.47, 95% CI 1.34–8.96 for males). These results were robust to adjustments (OR = 3.15, 95% CI 1.23–8.02 for females; OR = 3.77, 95% CI 1.31–10.85 for males). Table 3 reports the results from the GLM concerning the associations of the BMI and PA categories at ages 31 and 46, along with their joint associations, with individual-level outpatient PHC costs levels among those who had such costs. Table 3 The associations of physical activity and BMI at ages 31 and 46 with the primary healthcare cost levels according to generalized linear analysis. OR (95%CI) unadjusted adjusted Females Males Females Males BMI at ages 31 & 46 Stable obesity 1.29 (0.98–1.70) 0.95 (0.67–1.36) 1.33 * (1.01–1.75) 0.98 (0.66–1.44) Weight gain 1.25 * (1.06–1.48) 1.05 (0.85–1.29) 1.22 * (1.03–1.44) 1.06 (0.84–1.33) Stable overweight 1.23 (0.93–1.63) 1.01 (0.80–1.28) 1.27 (0.96–1.70) 1.00 (0.77–1.29) PA at ages 31 & 46 Turned inactive 0.79 (0.60–1.04) 0.94 (0.65–1.38) 0.79 (0.60–1.04) 0.97 (0.65–1.46) Stable active 1.03 (0.79–1.34) 0.74 (0.54–1.01) 1.08 (0.83–1.41) 0.72 (0.51–1.02) Turned active 0.78 * (0.62–0.97) 0.92 (0.65–1.30) 0.81 (0.65–1.02) 0.98 (0.68–1.42) Interaction terms between BMI and PA at ages 31 & 46 Stable obesity * Turned inactive 1.16 (0.54–2.49) 1.41 (0.64–3.13) 1.10 (0.50–2.40) 1.06 (0.44–2.54) Stable obesity * Stable active 1.26 (0.42–3.80) 0.88 (0.38–2.06) 1.29 (0.44–3.76) 0.89 (0.37–2.17) Stable obesity * Turned active 1.13 (0.56–2.26) 0.99 (0.41–2.41) 1.03 (0.51–2.06) 0.75 (0.29–2.17) Weight gain * Turned inactive 0.95 (0.64–1.42) 1.16 (0.72–1.88) 1.03 (0.69–1.54) 1.14 (0.69–1.92) Weight gain * Stable active 0.90 (0.58–1.41) 1.06 (0.67–1.67) 0.93 (0.60–1.45) 1.08 (0.66–1.77) Weight gain * Turned active 1.34 (0.96–1.88) 1.22 (0.78–1.91) 1.36 (0.97–1.90) 1.20 (0.74–1.93) Stable overweight * Turned inactive 0.99 (0.46–2.13) 1.00 (0.60–1.69) 0.97 (0.45–2.10) 0.98 (0.57–1.70) Stable overweight * Stable active 1.32 (0.61–2.82) 1.31 (0.80–2.13) 1.20 (0.57–2.55) 1.41 (0.84–2.36) Stable overweight * Turned active 0.89 (0.53–1.51) 0.86 (0.53–1.40) 0.89 (0.52–1.52) 0.88 (0.52–1.49) Married 0.92 (0.82–1.05) 0.84 * (0.73–0.98) High education 0.91 (0.81–1.03) 0.86 * (0.74–0.99) Unemployed 1.16 (0.89–1.53) 0.94 (0.72–1.23) Health behavior Ex-smoker 1.12 (0.96–1.30) 1.07 (0.91–1.26) Current smoker 1.02 (0.86–1.20) 1.07 (0.88–1.30) Risk-level alcohol use 1.18 (0.85–1.64) 1.01 (0.74–1.36) Daily consumption of fresh vegetables 0.92 (0.81–1.04) 1.04 (0.88–1.22) Weekly consumption of fast food 0.99 (0.83–1.18) 0.99 (0.85–1.15) Physically active at age 14 1.03 (0.90–1.17) 0.99 (0.82–1.20) Constant 388.21 *** (344–438) 347.38 *** (296–407) 407.02 *** (335–494) 398.82 *** (302–526) N 2 221 1 575 2 083 1 446 Log likelihood -15 612.87 -10 762.62 -14 608.87 -9 869.91 Robust standard errors are in parentheses. The level of statistical significance: ***p < 0.001, **p < 0.01, *p < 0.05. Base category: Stable healthy weight (BMI 18.5–24.9 kg/m 2 both at ages 31 and 46) - Stable inactive (MVPA < 150 min/week at ages 31 and 46). BMI = body mass index; PA = physical activity; stable obesity = BMI ≥ 30 kg/m 2 at ages 31 and 46; weight gain = any change to a higher BMI category (i.e. change from healthy weight to overweight or obesity or from overweight to obesity) from age 31 to 46; stable overweight = BMI 25–29.9 kg/m 2 at ages 31 and 46; turned inactive = MVPA ≥ 150 min/week at age 31, but < 150 min/week at age; stable active = MVPA ≥ 150 min/week at ages 31 and 46; turned active = MVPA < 150 min/week at age 31, but ≥ 150 min/week at age 46; high education = bachelor’s degree or higher education; risk-level alcohol use: ≥23.5 doses/week for males, ≥ 14 doses/week for females. Without adjustments, female participants who gained weight between ages 31 and 46 had higher individual-level outpatient PHC costs (OR = 1.25, 95% CI 1.06–1.48) than those with stable healthy weight, and females who turned active between ages 31 and 46 had lower PHC costs (OR = 0.78, 95% CI 0.62–0.97) than those who were stable inactive. After adjustments, female participants who gained weight (OR = 1.22, 95% CI 1.03–1.44) and females with stable obesity (OR = 1.33, 95% CI 1.01–1.75) had higher PHC costs than those with stable healthy weight. Table 4 reports the adjusted predicted individual annual outpatient PHC costs at age 46 according to the combined PA–BMI change categories between ages 31 and 46 based on GLM. Table 4 Average adjusted predicted outpatient primary healthcare costs (€) in 2011 stratified by physical activity and BMI at ages 31 and 46. PA at ages 31 & 46 Females Turned inactive Stable inactive Stable active Turned active BMI at ages 31 & 46 Mean 95% CI N Mean 95% CI N Mean 95% CI N Mean 95% CI N Stable obesity 436 [135–738] 16 503 [380–626] 125 700 [-5–1405] 7 420 [164–677] 19 Weight gain 374 [275–474] 115 458 [404–513] 566 459 [305–614] 71 507 [394–620] 161 Stable overweight 369 [123–614] 18 480 [355–605] 122 624 [216–1032] 18 349 [207–490] 47 Stable healthy weight 298 [223–372] 123 377 [331–423] 541 407 [310–504] 147 307 [249–365] 228 Males Turned inactive Stable inactive Stable active Turned active BMI at ages 31 & 46 Mean 95% CI N Mean 95% CI N Mean 95% CI N Mean 95% CI N Stable obesity 342 [104–580] 15 333 [216–450] 59 214 [55–374] 15 246 [44–448] 12 Weight gain 404 [288–519] 98 361 [309–414] 387 283 [190–376] 80 424 [310–538] 104 Stable overweight 326 [219–434] 74 341 [278–404] 243 346 [225–467] 64 295 [201–389] 74 Stable healthy weight 332 [212–453] 62 342 [281–402] 285 247 [175–319] 95 335 [226–443] 85 The adjusted predicted levels of individual annual outpatient primary healthcare costs in 2011 were calculated using estimated generalized linear models explaining the healthcare costs. The predictions were calculated with the values of the covariates, marital status, education level, employment status, smoking, risk-level alcohol use, daily consumption of fresh vegetables, weekly consumption of fast food, and PA at age 14, at their means. The costs were predicted individual healthcare costs of a person with average characteristics. PA = physical activity; BMI = body mass index; stable obesity = BMI ≥ 30 kg/m 2 at ages 31 and 46; weight gain = any change to a higher BMI category (i.e. change from healthy weight to overweight or obesity or from overweight to obesity) from age 31 to 46; stable overweight = BMI 25–29.9 kg/m 2 at ages 31 and 46; stable healthy weight = BMI 18.5–24.9 kg/m 2 at ages 31 and 46; turned inactive = MVPA (= moderate-to-vigorous PA, ≥3MET) ≥ 150 min/week at age 31, but < 150 min/week at age; stable inactive = MVPA < 150 min/week at ages 31 and 46; stable active = MVPA ≥ 150 min/week at ages 31 and 46; turned active = MVPA < 150 min/week at age 31, but ≥ 150 min/week at age 46. Regarding the BMI categories, among female participants who had stable obesity, those who were stable active had the highest adjusted predicted annual PHC costs. However, the predicted PHC costs did not differ statistically significantly from 0 (€700 [95% CI €-5–1405]). Among females with weight gain between ages 31 and 46, the highest predicted annual PHC costs (€507 [95% CI €394–620]) were for those who turned active. The highest predicted costs in the categories of stable overweight (€624 [95% CI €216–1032]) and stable healthy weight (€407 [95% CI €310–504]) were for females who were stable active. Among males with stable obesity, the highest predicted costs were for those who turned inactive between ages 31 and 46 (€342 [95% CI €104–580]). Among male participants with weight gain, those who turned active had the highest predicted costs (€424 [95% CI €310–538]). Among males with stable overweight, those who were stable active had the highest predicted costs (€346 [95% CI €225–467]). Finally, among males with healthy weight, those who were stable inactive had the highest predicted costs (€342 [95% CI €175–319]. Regarding the PA categories, the highest predicted PHC costs were among female participants with stable obesity among all other PA categories, but among those who turned active, those with weight gain had the highest predicted costs. For males, the highest predicted PHC costs were for those with weight gain, except among stable active males, those with stable overweight had the highest predicted costs. The results of the tests for statistical significance of the differences in the predicted outpatient PHC costs between different BMI categories within different PA categories and between different PA categories within different BMI categories are presented in Tables S1 and S2 in Supplementary Digital Content 4. Among stable inactive females, those who gained weight had 25% (€81 [95% CI €10–153]) higher predicted PHC costs than those with stable healthy weight. Among females who turned active, those who gained weight had 65% (€200 [95% CI €73–327]) higher predicted PHC costs than those with stable healthy weight. For males, among those with stable healthy weight, those who were stable inactive had 38% (€95 [95% CI €1–277]) higher predicted PHC costs than those who were stable active. DISCUSSION The present population-based birth cohort study, for the first time, evaluated the association between PA and adjusted individual-level outpatient PHC costs related to sustained healthy weight, overweight, and obesity and weight gain in midlife. In addition, the two-part model allowed us to separately estimate the probability of incurring any outpatient PHC costs, and among those who used outpatient PHC services, the level of costs, and to compare the results according to the changes in the participants’ PA and BMI. Obesity was found to be associated with a higher probability of having outpatient PHC costs in both sexes, and among females, weight gain and sustained obesity were associated with higher outpatient PHC cost level. Contrary to our hypothesis, sustained PA reaching the current recommendations or becoming physically active did not mitigate the impact of obesity or weight gain on outpatient PHC costs. The adjusted predicted individual annual outpatient PHC costs were found to be the highest for females with stable obesity, weight gain, and stable overweight regardless of the PA category, and mostly for males as well, although only a few of the differences in adjusted predicted PHC costs between the BMI categories within a fixed PA category and between the PA categories within a fixed BMI category were found to be statistically significant. Reaching the current PA recommendations predicted PHC costs only among males with stable healthy weight, among whom those who were stable inactive had 38% higher predicted costs than those who were stable active. Our findings of a higher probability of having healthcare costs for individuals with obesity and among females, and the association of having obesity and weight gain with healthcare cost levels are in line with the findings of previous studies ( 6 , 9 , 10 ). We did not find any association between having stable overweight and PHC costs, which supports the previous finding of Finkelstein et al. ( 10 ) that healthcare costs for individuals with overweight do not significantly differ from those for individuals with healthy weight. We found that female participants had 32% higher mean individual-level outpatient PHC costs than male participants. This is in line with previous studies ( 21 ). According to our results, female participants had lower MVPA volume at age 31 than male participants. However, between ages 31 and 46, more females than males became physically active and the MVPA volume of females increased by 29 minutes/week on average, while that of males increased by only 8 minutes/week. Living with children has been reported to have a negative impact on engagement in PA ( 37 ), especially among females ( 38 ). Children growing up and easing household work between ages 31 and 46 for mothers may enable them to become physically active at middle age. Persistent PA health benefits have been reported to require sustained PA ( 17 ). Among females, the impact of increased PA on healthcare costs may not be seen within the time-period used in the present study because recent PA increase and short-lived PA may not be enough to provide healthcare cost benefits. The predicted average annual individual-level healthcare costs in the present study were significantly lower than those in a recent Finnish study ( 9 ), which reported €2 665 total annual healthcare costs (consisting of the costs of healthcare visits, hospital stays and prescribed medicines) for individuals with obesity, and €1 799 for individuals with healthy weight or overweight in Finland. The difference is explained by the fact that the outpatient PHC costs used in the present study represented only a fraction of the total healthcare costs due to the lack of data on the costs of outpatient hospital care, inpatient services, and medications. For example, Cawley et al. ( 1 ) reported that obesity raises the costs in all major categories of healthcare, with particularly large increases in inpatient services and prescription drug expenditures. Wang et al. ( 20 ) reported pharmaceutical costs and inpatient costs, but not outpatient costs, to be significantly higher for retirees over age 65 with overweight and obesity compared to retirees with healthy weight. The interactions between BMI, PA, and related healthcare costs may be quite complex. BMI has been reported to be associated with PA ( 39 – 41 ). In the past decades, studies have suggested that obesity may be a driver of physical inactivity, instead of the previous assumption that low PA leads to obesity ( 39 , 40 ), or at least that the relation might be bidirectional ( 39 , 41 ). Physical inactivity itself is known to be associated with higher disease burden ( 42 ), which may lead to higher additional healthcare costs in the long run if PA remains low ( 7 ), in addition to obesity-related increased healthcare costs ( 7 , 43 ). Stable inactivity may also reflect poor health status, which may prevent engagement in PA. Health status is one of the strongest previously reported correlates and a suggested determinant of engagement in PA ( 39 , 44 ). Obesity itself has a significant independent negative impact on health ( 12 , 45 – 47 ). Additionally, shifting from physical inactivity to activity may increase the use of healthcare services through, for example, exercise-related injuries, pain, or other problems, especially in the early stages of physically active lifestyle ( 48 – 51 ), and in individuals with obesity ( 49 , 50 , 52 , 53 ). In addition, one form of complex interaction between BMI, PA, and healthcare costs is possible curvilinear shape of the association between PA and healthcare service use and healthcare costs across BMI categories ( 19 , 20 , 22 ). In our previous study ( 54 ) we found curvilinear association between adulthood accelerometer-measured PA and future income. The numbers of stable active participants with obesity, overweight, and a history of weight gain were too low to enable the evaluation of the possible curvilinear associations of PA with healthcare costs in the present study. The present study had several strengths. The unselected population-based data represented both sexes and individuals from all sectors of the economy, occupational statuses, and education levels. Additionally, the participants in the present study were born around the same year in the same geographical area in Finland and were still living in Finland at the time of the study; thus, the risk of bias arising from the effect of age, race, and culture on PHC costs was low. The fact that all the participants in the present study were living in Finland also made the healthcare cost calculations reliable and made the obtained cost values comparable to each other. Furthermore, using individual-level data, we were able to capture the outpatient PHC costs of all health conditions leading to outpatient PHC service use, whether associated with obesity or not, so the possible outpatient PHC costs from PA-related injuries and diseases were also included. We also had a longitudinal perspective, as opposed to the previous cross-sectional studies ( 19 – 21 ). Despite the foregoing, the present study also had some limitations. For example, the self-reported data concerning PA and healthcare service use in the year before age 46 might have led to recall bias. In addition, the data on self-reported PA used in the study reflected leisure time PA and did not include, for example, work-related PA. The standard unit costs reported by the Finnish Institute for Health and Welfare ( 30 ) that were used in the calculations also did not reveal the real healthcare service costs. Thus, the calculated and predicted individual-level outpatient PHC costs in the present study were underestimations. Additionally, we had no information about the participants’ reasons for healthcare service use, and we do not know if they had some health-related reasons for decrease or increase PA. For example, some disease or injury between ages 31 and 46 could have affected both PHC costs and PA. However, the effects of these factors on the main study results and conclusions were limited because the study aimed to compare the individual-level PHC costs according to the changes in PA and BMI, not to reveal the exact cost level. The classification of the participants as physically inactive or physically active was based on PA recommendations ( 17 ). The shift from physical inactivity to physically active or vice versa could have been caused by a change in MVPA as minimal as 1 min/week, because individuals with ≤ 149 minutes/week MVPA were categorized as physically inactive and those with ≥ 150 minutes/week MVPA as physically active. In addition, we did not have any information on the possible fluctuations in BMI and PA between ages 32 and 45. Moreover, in some subgroups, the numbers of participants were quite low, only 7 at the lowest. The number of individuals with weight loss between ages 31 and 46 among NFBC1966 cohort members was so low that we were not able to statistically analyze the associations of weight loss and PA categories with PHC costs. It is also well known that dietary factors and other healthy life habits (i.e. PA), BMI, and education level may interact with each other. Individual-level healthcare expenditures have also been found to increase with age ( 21 , 55 ), obesity duration has been reported to increase functional limitations and disability in the long run ( 56 , 57 ), and persistent PA health benefits have been reported to require continuing PA ( 17 ). Thus, the relatively young (46 years) age cohort in the present study might not be optimal for revealing the longitudinal associations of obesity and PA with healthcare costs. The complex interactions between BMI, PA, and healthcare costs could not be recognized in the study protocol that we used, and we were not able to distinguish the effects of different components of health behavior on healthcare costs. As conclusion, this study shows that obesity is associated with a higher probability of having outpatient primary healthcare costs, and among females, obesity and weight gain are also associated with higher outpatient PHC cost levels. Reaching the current PA recommendations did not mitigate the impact of obesity and weight gain on outpatient PHC costs in midlife. Reaching the current PA recommendations alone is insufficient when aiming to decrease obesity-related PHC costs in midlife. Long-term effects of PA on outpatient PHC costs should be evaluated in future studies. Declarations ACKNOWLEDGMENTS We are grateful for all the cohort members and researchers who participated in the 31- and 46-year follow-up studies and for the work of the NFBC project center. AUTHOR CONTRIBUTIONS HEJ contributed to the design of the study protocol and methods; interpretation of the study results; writing, review, and editing of the original paper draft; and creation of Figure 1. She also reviewed the literature, edited the tables, and had full access to the study data and final responsibility for the decision to submit the paper for publication. MMV contributed to the design of the study methods, curation and analysis of the study data, review and editing of the draft paper, and creation of Table 1. IJSN contributed to the design of the study methods and the review and editing of the draft paper. SMH contributed to the design of the study methods, analysis of the study data, interpretation of the study results, creation of Tables 2–4, S1, and S2, and review and editing of the draft paper. JTK, AML, and SMN contributed to the review and editing of the draft paper and provided feedback regarding it. RK contributed to the design of the study protocol, curation of the PA and other data, review and editing of the draft paper, resources, project supervision/administration, and funding acquisition. MJK contributed to the design of the study protocol and methods, interpretation of the study results, review and editing of the draft paper, and project supervision/administration. All the authors have read and approved the final manuscript and have agreed to be accountable for all aspects of the work, ensuring that all questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. DECLARATION OF COMPETING INTEREST None. DATA AVAILABILITY STATEMENT The data for this article were obtained from the population-based Northern Finland Birth Cohort 1966 (NFBC1966). The NFBC1966 data set comprises health-related participant data, and their use is therefore restricted under the regulations on professional secrecy (Act on the Openness of Government Activities, 612/1999) and sensitive personal data (Personal Data Act, 523/1999, implementing the EU data protection directive 95/46/EC). Due to these legal restrictions, the data from this study cannot be stored in public repositories or otherwise be made publicly available. However, data access may be permitted on a case-by-case basis upon request. Data-sharing outside the research group is done in collaboration with the NFBC1966 group and requires a data-sharing agreement with the NFBC1966 representatives (NFBC1966, University of Oulu, https://www.oulu.fi/en/university/faculties-and-units/faculty-medicine/northern-finland-birth-cohorts-and-arctic-biobank). ETHICS APPROVAL STATEMENT The results of the study are presented honestly, and without fabrication, falsification, or inappropriate data manipulation. All participants provided written informed consent, and the Ethical Committee of the Northern Ostrobothnia Hospital District in Oulu, Finland approved the Northern Finland Birth Cohort study (§94/2011), which was conducted according to the Declaration of Helsinki of 1983. The results of the study are presented honestly, and without fabrication, falsification, or inappropriate data manipulation. COMPETING INTERESTS The authors declare no competing financial interests. FUNDING NFBC1966 data collection for 31- and 46-year follow-ups received financial support from the University of Oulu (grant no. 24000692), Oulu University Hospital (grant no. 24301140), and the European Regional Development Fund (grant no.539/2010 A31592). The study has been financially supported by the Ministry of Education and Culture (OKM/86/626/2014, OKM/43/626/2015, OKM/17/626/2016, OKM/54/626/2019, OKM/85/626/2019, OKM/1096/626/2020, OKM/64/626/2020, OKM/1105/626/2020, OKM/91/626/2021, OKM/20/626/2022). M.N. has received funding from Fibrobesity-project, a strategic profiling project at the University of Oulu, which is supported by the Academy of Finland Profi6 336449. The funding organizations had no role in the study design, the collection, analysis, and interpretation of data, the writing of the article, or the decision to submit it for publication. No funding was received for this manuscript. 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Junttila","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYBACAxiDsQHMtWDgZz4IZjKwNxPWwthwwECCQbItsQEswXOYgBawrgMMEgwGxxIgEjwHsGsxZz977MEPBhsG5hm5xx9/KJCQNz7G3Lq5oOIPAw87di2WPXnphj0MaQyMM/ISQQ4z3HaMse32jDNAW5hxOOxAjpkED8NhoJYcQ5AWxm33G9tu87YZMNjj0nL+jZnkH4b/cC32m9uAtvD+w2PLjRwzaR6GA3AtiRvYQFoa8Gl5YyYtY5DMw9jzxhDoA4nkGSC/8Bwz5sGp5XyOmeSbCjs5w/Ycgw8Vf2xs+9vYn93mqZGT4+E/gF0PRCMDj2EDmhgPHvUQIE9QxSgYBaNgFIxYAACZsFd6Jjf7OAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-7030-9615","institution":"Oulu Deaconess Institute Foundation sr.","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Hanna","middleName":"","lastName":"Junttila","suffix":""},{"id":235922736,"identity":"0c670a7f-681d-45f9-bb78-fac38253f5b1","order_by":1,"name":"Mikko Vaaramo","email":"","orcid":"","institution":"Oulu Deaconess Institute Foundation sr.","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mikko","middleName":"","lastName":"Vaaramo","suffix":""},{"id":235922737,"identity":"9a2991d7-8b42-44a8-aa04-49f7d2aca9f6","order_by":2,"name":"Iiro Nerg","email":"","orcid":"","institution":"University of Oulu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Iiro","middleName":"","lastName":"Nerg","suffix":""},{"id":235922738,"identity":"689891a3-71d9-4cc6-95de-44791691e251","order_by":3,"name":"Sanna Huikari","email":"","orcid":"","institution":"University of Oulu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sanna","middleName":"","lastName":"Huikari","suffix":""},{"id":235922739,"identity":"69259d30-0bc9-443c-975a-76a9aa78c3c1","order_by":4,"name":"Jaana Kari","email":"","orcid":"","institution":"University of Jyväskylä","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jaana","middleName":"","lastName":"Kari","suffix":""},{"id":235922740,"identity":"a35fe5d1-a98f-4498-ab77-215558eaff62","order_by":5,"name":"Anna-Maiju Leinonen","email":"","orcid":"","institution":"Oulu Deaconess Institute Foundation sr.","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Anna-Maiju","middleName":"","lastName":"Leinonen","suffix":""},{"id":235922741,"identity":"4bc67a06-7411-4516-a0bd-0ab0883b6813","order_by":6,"name":"Marjukka Nurkkala","email":"","orcid":"","institution":"Oulu Deaconess Institute Foundation sr","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marjukka","middleName":"","lastName":"Nurkkala","suffix":""},{"id":235922742,"identity":"5c9274b0-2212-4931-8795-367493a45b11","order_by":7,"name":"Raija Korpelainen","email":"","orcid":"","institution":"Oulu Deaconess Institute Foundation sr., University of Oulu, and Oulu University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Raija","middleName":"","lastName":"Korpelainen","suffix":""},{"id":235922743,"identity":"1b47c4e1-fc1c-46f5-9e5a-209a022d7997","order_by":8,"name":"Marko Korhonen","email":"","orcid":"","institution":"University of Oulu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marko","middleName":"","lastName":"Korhonen","suffix":""}],"badges":[],"createdAt":"2023-09-20 16:55:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3373605/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3373605/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":44047424,"identity":"d04f95b3-7429-4c89-80b7-45b7267aad51","added_by":"auto","created_at":"2023-10-03 23:01:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20275,"visible":true,"origin":"","legend":"\u003cp\u003eConstruction of the study sample of Northern Finland Birth Cohort 1966 (NFBC1966).\u003c/p\u003e","description":"","filename":"F1.png","url":"https://assets-eu.researchsquare.com/files/rs-3373605/v1/5f1798823245e4f2e9b38580.png"},{"id":44987532,"identity":"c6fd5efb-b37e-4e2b-9a6c-e434fc6e3a11","added_by":"auto","created_at":"2023-10-20 13:29:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":401116,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3373605/v1/08aada42-9d1f-44e1-8e1b-e231d0111fb2.pdf"},{"id":44046574,"identity":"ae08ed33-b8e8-42de-9213-ce51d926033a","added_by":"auto","created_at":"2023-10-03 22:53:55","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":14745,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryDigitalContent1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3373605/v1/2f2d371433d57c6cb8bbfb27.docx"},{"id":44046573,"identity":"4fe2e821-1d5e-4295-ace6-cf9401d66c93","added_by":"auto","created_at":"2023-10-03 22:53:55","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":17657,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryDigitalContent2.docx","url":"https://assets-eu.researchsquare.com/files/rs-3373605/v1/c8c1f71df4cf5e3c1dbb1661.docx"},{"id":44046577,"identity":"ab35bbd0-d092-4cc1-a13d-481ee2b6af35","added_by":"auto","created_at":"2023-10-03 22:53:55","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":17525,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryDigitalContent3.docx","url":"https://assets-eu.researchsquare.com/files/rs-3373605/v1/143dbbc8586e320adfe6637c.docx"},{"id":44046576,"identity":"a38ccdc3-3f77-45d3-a89f-2a570d285265","added_by":"auto","created_at":"2023-10-03 22:53:55","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":28843,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryDigitalContent4.docx","url":"https://assets-eu.researchsquare.com/files/rs-3373605/v1/9bf659e319da38e9115058a5.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Association between physical activity and healthcare costs by weight status in middle age: Evidence from the Northern Finland Birth Cohort 1966","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eObesity-related healthcare costs have been rising over the past decades (\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) and have been predicted to further rise (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). National spending on direct medical costs related to overweight and obesity has been estimated to be around 4.9\u0026ndash;10% of the total healthcare expenditures (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), and that related to obesity alone around 0.7\u0026ndash;2.8% (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Individuals with obesity have been estimated to have approximately 30\u0026ndash;100% higher medical costs than those with healthy weight (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrevious research has shown that the health-related risks of obesity can be considerably reduced by physical activity (PA) (\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Increasing PA to meet the current recommendations (\u0026ge;\u0026thinsp;150 min/week moderate-to-vigorous PA [MVPA]) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) has been reported to eliminate much of the increased mortality risk associated with obesity (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). PA and cardiorespiratory fitness have been suggested to be more important than weight loss in preventing mortality (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBetter cardiorespiratory fitness was reported to be associated with lower healthcare costs in a 6-year follow-up study, particularly among individuals with obesity (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In cross-sectional settings, mean annual unadjusted (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and adjusted healthcare costs (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) were reported to be lower for those with at least low physical activity compared to sedentary ones among manufacturing employees with obesity (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and among randomly sampled middle-aged females (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and retirees (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) with as well healthy weight, overweight, as obesity. Among 18\u0026ndash;65 years old university and tertiary care medical center employees, increasing frequency of at least 30 minutes lasting aerobic PA up to four to five weekly exercises were associated with lower healthcare costs across all weight categories (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is no longitudinal birth cohort based large-scale evidence of the impact of PA on obesity-related healthcare costs. Thus, in the present study, we addressed the aforementioned research gap by employing a two-part model that has been shown to fit healthcare expenditures very well (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The two-part model allowed us to separately estimate the probability of incurring any outpatient primary healthcare (PHC) costs and, among those who used PHC services, the level of PHC costs, and to compare the results according to the changes in the participants\u0026rsquo; PA and body mass index (BMI). The use of individual-level data obtained from a large, unselected, population-based birth cohort and linked to the well-validated national register data gave the present study an advantage over selected populations. Our hypothesis was that reaching the current PA recommendations is associated with lower obesity-related PHC costs.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eThe study sample consisted of 4 076 (2 324 females and 1 752 males) participants from the population-based Northern Finland Birth Cohort 1966 (NFBC1966) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)31- (in 1997) and 46-year (in 2012) follow-ups (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents construction of the study sample. Detailed information about the follow-ups, attrition analyses, and representativeness of NFBC1966 have been reported previously (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Pregnant females at 31-year follow-up were excluded from the study. The participants gave written informed consent before participating in the NFBC1966 study. The Ethical Committee of the Northern Ostrobothnia Hospital District in Oulu, Finland approved the Northern Finland Birth Cohort study (\u0026sect;\u0026nbsp;94/2011), which was performed according to the Declaration of Helsinki 1983.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u0026lt;FIGURE \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026gt;\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eOverweight and obesity\u003c/h2\u003e \u003cp\u003eBMI at ages 31 and 46 was calculated by dividing the measured weight (kg) by the measured height in meters squared (m\u003csup\u003e2\u003c/sup\u003e) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). If measured parameters were not available, self-reported weight and height were used for the calculations at ages 31 and 46 (see Supplementary Digital Content 1(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)). The participants were categorized as follows, according to their BMI (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e): (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) stable obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) weight gain (any change to a higher BMI category; that is, change from healthy weight to overweight or obesity, or from overweight to obesity from age 31 to 46); (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) stable overweight (BMI 25\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46); and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) stable healthy weight (BMI 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003ePhysical activity\u003c/h2\u003e \u003cp\u003eSelf-reported leisure-time PA was assessed through the same questionnaire at ages 31 and 46. The participants were asked about the frequency and duration of their engagement in brisk PA (at least some sweating and getting out of breath, corresponding MVPA, \u0026ge; 3 metabolic equivalent of tasks [MET]) (see Supplementary Digital Content 2). The answers were transformed into total weekly minutes of MVPA by multiplying the frequency by the duration.\u003c/p\u003e \u003cp\u003eFor the analyses, the participants were categorized as follows: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) turned inactive (MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at age 31, but \u0026lt;\u0026thinsp;150 min/week at age 46); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) stable inactive (MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at ages 31 and 46); (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) stable active (MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at ages 31 and 46); and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) turned active (MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at age 31, but \u0026ge;\u0026thinsp;150 min/week at age 46).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eHealthcare costs\u003c/h2\u003e \u003cp\u003eIndividual-level outpatient PHC costs at age 46 (in 2012) were calculated utilizing the self-reported use of both public and private sector outpatient PHC services in the previous year. The numbers of visits to public sector PHC and occupational healthcare centers to avail of nurse, physiotherapist, physician, and psychology services; to private healthcare to avail of physiotherapist and physician services; and to mental health and substance abuse centers; and the number of physician home visits were asked. The outpatient PHC costs were calculated by multiplying the number of visits to each previously mentioned PHC services and physician home visits with the standard unit costs of those services reported by the Finnish Institute for Health and Welfare (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), and summing up the costs. All monetary values were converted into 2011 euros, utilizing the monetary value multiplier from Statistics Finland (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eInformation on the participants\u0026rsquo; marital status, employment status, and the highest educational achievement at age 46 was obtained from Statistics Finland (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Marital status was dichotomized as \u0026ldquo;married\u0026rdquo; (married or in a registered relationship at age 46) and \u0026ldquo;not married\u0026rdquo; (others). Employment status was dichotomized as \u0026ldquo;unemployed\u0026rdquo; (\u0026ge;\u0026thinsp;6 months unemployment) and \u0026ldquo;employed\u0026rdquo; at age 46. Education level was dichotomized according to the International Standard Classification of Education 2011 (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e); those with at least a bachelor\u0026rsquo;s degree were included in the high education group. Based on to the participants\u0026rsquo; self-reported PA at age 14, they were classified as \u0026ldquo;physically active\u0026rdquo; or \u0026ldquo;physically inactive\u0026rdquo;(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). The information on smoking (never smoked/ex-smoker/current smoker), risk-level alcohol use (\u0026ge;\u0026thinsp;23.5 doses/week for males, \u0026ge; 14 doses/week for females; one dose\u0026thinsp;=\u0026thinsp;12 g alcohol (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)), daily consumption of fresh vegetables, and weekly consumption of fast food (pizzas and hamburgers) was self-reported at age 46.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eA high proportion of the participants had no outpatient PHC costs at all, and among those who had such costs, the expenditures were highly skewed; that is, a small number of participants had very high PHC costs. This shape of medical expenditures is common (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), and to account for the shape of the healthcare cost distribution, we used a two-part healthcare cost model (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The first part of the model is a logit model that estimates the probability of incurring healthcare costs. The second part estimates the level of healthcare costs conditional on having such costs and is specified as a generalized linear model (GLM) with a gamma variance structure and log link. Both parts of the two-part model included PA categories, BMI categories, and their joint interactions. The analyses were adjusted for covariates listed above and were conducted separately for females and males (for the detailed model specifications, see Supplementary Digital Content 3). Finally, the adjusted predicted levels of individual annual outpatient PHC costs of a person with average characteristics were calculated for the combined BMI and PA categories. All analyses were conducted using Stata version 16.0 (StataCorp LLC, College Station, Texas 77845, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eDescriptive statistics\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the descriptive characteristics of all the participants of the NFBC1966 31-year and 46-year follow-ups and the study sample.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of all the participants of the Northern Finland Birth Cohort 1966 (NFBC1966) 31-year (1997) and 46-year (2012) follow-ups and the study sample.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAll the participants of NFBC1966,\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStudy sample, N\u0026thinsp;=\u0026thinsp;4 076\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003estill alive in 2012, N\u0026thinsp;=\u0026thinsp;9 284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(39.45% of those who were alive and living\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(77.0% of total NFBC1966 cohort population)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ein Finland with known address in 2012)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;4 809 (51.8%)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;4\u0026nbsp;475 (48.2%)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;2 324 (57.02) \u003csup\u003ea\u003c/sup\u003e %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1 752 (42.98)\u003csup\u003ea\u003c/sup\u003e %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried at age 46, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 777 (57.25)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 477 (55.35)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 436 (61.79)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 098 (62.67)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh education at age 46, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 448 (50.90)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 631 (36.45)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 381 (59.42)\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e824 (47.03)\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed at age 46, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e309 (6.75)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e442 (10.28)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128 (5.51)\u003csup\u003eb,d\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e142 (8.11)\u003csup\u003eb,d\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHealth behavior\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-smoker, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 111 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 381 (45.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 414 (60.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e872 (49.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEx-smoker, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e808 (22.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e860 (28.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e515 (22.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e515 (29.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent smoker at age 46, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e702 (19.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e796 (26.21)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e395 (17)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e365 (20.83)\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRisk-level alcohol use at age 46, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e133 (3.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e206 (6.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (3.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97 (5.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaily use of fresh vegetables at age 46, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 540 (41.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e736 (23.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e946 (40.71)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e460 (26.26)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeekly fast-food consumption at age 46, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e508 (13.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e907 (29.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e307 (13.21)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e494 (28.2)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysically active at age 14, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 186 (69.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 435 (82.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1652 (71.08)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 476 (84.25)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean primary healthcare costs at age 46, \u0026euro; (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e399.53 (689.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e289.50 (443.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e374.75\u003csup\u003ec\u003c/sup\u003e (575.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e284.44\u003csup\u003ec\u003c/sup\u003e (443.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMVPA at age 31, mean min/w (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.40 (101.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e102.33 (123.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89.66\u003csup\u003ec\u003c/sup\u003e (103.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105.58\u003csup\u003ec\u003c/sup\u003e (121.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMVPA at age 46, mean min/w (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117.22 (120.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109.92 (121.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118.80 (119.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e113.10 (118.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean change in MVPA from age 31 to 46, min/w (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.24 (132.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.05 (138.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.14\u003csup\u003ec\u003c/sup\u003e (130.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.52\u003csup\u003ec\u003c/sup\u003e (135.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean weight change from age 31 to 46, kg (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.11 (8.63)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.50 (8.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.60\u003csup\u003ea,c\u003c/sup\u003e (8.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.8\u003csup\u003ec\u003c/sup\u003e (7.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePA change from 31 to 46\u0026nbsp;year\u003c/em\u003e, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 238 (67.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 592 (57.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 324 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026nbsp;752 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTurned inactive, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e368 (11.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e363 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e272 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e249 (14.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable inactive, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 915 (59.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 471 (56.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 354 (58.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e974 (55.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable active, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e324 (10.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e352 (13.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e243 (10.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e254 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTurned active, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e631 (19.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e406 (15.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e455 (19.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e275 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBMI change from 31 to 46\u0026nbsp;year\u003c/em\u003e, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 238 (66.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 592 (59.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 324 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026nbsp;752 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e243 (7.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e181 (6.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167 (7.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101 (5.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 258 (39.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 030 (38.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e913 (38.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e669 (38.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e289 (8.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e686 (25.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e205 (8.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e455 (25.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable healthy weight, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 425 (44.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e782 (29.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 039 (45.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e527 (30.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eHigh education\u0026thinsp;=\u0026thinsp;bachelor\u0026rsquo;s degree or higher education; risk-level alcohol use: \u0026ge;23.5 doses/week for males, \u0026ge;\u0026thinsp;14 doses/week for females; MVPA\u0026thinsp;=\u0026thinsp;moderate-to-vigorous physical activity (\u0026ge;\u0026thinsp;3MET); PA\u0026thinsp;=\u0026thinsp;physical activity; min/w\u0026thinsp;=\u0026thinsp;minutes/week; kg\u0026thinsp;=\u0026thinsp;kilogram; turned inactive\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at age 31, but \u0026lt;\u0026thinsp;150 min/week at age 46; stable inactive\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at ages 31 and 46; stable active\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at ages 31 and 46; turned active\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at age 31, but \u0026ge;\u0026thinsp;150 min/week at age 46; BMI\u0026thinsp;=\u0026thinsp;body mass index; stable obesity\u0026thinsp;=\u0026thinsp;BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; weight gain\u0026thinsp;=\u0026thinsp;any change to a higher BMI category (i.e. change from healthy weight to overweight or obesity or from overweight to obesity) from age 31 to 46; stable overweight\u0026thinsp;=\u0026thinsp;BMI 25\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; stable healthy weight\u0026thinsp;=\u0026thinsp;BMI 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003e Difference between the study sample and those who participated in the 31- or 46-year follow-up and were still alive in 2012 at 5% significance level, t-test\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003csup\u003eb\u003c/sup\u003e Difference between the study sample and those who participated in the 31- or 46-year follow-up and were still alive in 2012 at 5% significance level, Pearson Chi-squared test\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003csup\u003ec\u003c/sup\u003e The level of statistical significance for the difference between females and males p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003csup\u003ed\u003c/sup\u003e The level of statistical significance for the difference between females and males p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\u0026lt;Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026gt;\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003cp\u003eThe study participants were more often married, highly educated, and employed; males of the study sample were more often non-smokers, and females with higher mean weight change from age 31 to 46 than the all NFBC1966 members attended to 31-year and 46-year follow-ups. There were no differences in MVPA, or frequency of different PA and BMI change categories from age 31 to 46.\u003c/p\u003e\n \u003cp\u003eAmong the study participants, females had higher average individual-level outpatient PHC costs in the previous year than males at age 46 (mean \u0026euro;375/year vs. \u0026euro;284/year, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Females had lower MVPA than males at age 31 (mean 89.66 min/week, SD 103.18 vs. 105.58 min/week, SD 121.77, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but there was no difference at age 46 (mean 118.80 min/week, SD 119.71 vs. 113.10 min/week SD 118.47, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.065). The MVPA volume increased by 29 min/week (SD\u0026thinsp;=\u0026thinsp;130.4) on average in females and 8 min/week (SD\u0026thinsp;=\u0026thinsp;135.45) in males, and weight increased by 7.6 kg (SD\u0026thinsp;=\u0026thinsp;8.08) on average in females and 6.8 kg (SD\u0026thinsp;=\u0026thinsp;7.44) in males between ages 31 and 46 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively).\u003c/p\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e reports the results of the multivariate logistic regression analyses conducted concerning the associations of the BMI and PA categories at ages 31 and 46, along with their joint associations, with the probability of having any outpatient PHC costs.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eThe associations of physical activity and BMI at ages 31 and 46 with the probability of having outpatient primary healthcare costs according to multivariate logistic regressions analysis. OR (95%CI)\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eunadjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eadjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI change from 31 to 46 yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.53\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(1.39\u0026ndash;8.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.47\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(1.34\u0026ndash;8.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.15\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(1.23\u0026ndash;8.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.77\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(1.31\u0026ndash;10.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003cp\u003e(0.83\u0026ndash;1.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003cp\u003e(0.91\u0026ndash;1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003cp\u003e(0.78\u0026ndash;1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003cp\u003e(0.86\u0026ndash;1.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003cp\u003e(0.48\u0026ndash;1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003cp\u003e(0.87\u0026ndash;2.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003cp\u003e(0.46\u0026ndash;1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003cp\u003e(0.81\u0026ndash;1.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePA change from 31 to 46 yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTurned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003cp\u003e(0.99\u0026ndash;4.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003cp\u003e(0.59\u0026ndash;2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003cp\u003e(0.84\u0026ndash;3.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003cp\u003e(0.64\u0026ndash;2.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003cp\u003e(0.52\u0026ndash;1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003cp\u003e(0.77\u0026ndash;2.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003cp\u003e(0.43\u0026ndash;1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003cp\u003e(0.81\u0026ndash;2.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTurned active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003cp\u003e(0.66\u0026ndash;1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003cp\u003e(0.45\u0026ndash;1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003cp\u003e(0.60\u0026ndash;1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003cp\u003e(0.48\u0026ndash;1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eInteraction terms between BMI and PA at ages 31 \u0026amp; 46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity * Turned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003cp\u003e(0.03\u0026ndash;3.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003cp\u003e(0.11\u0026ndash;11.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003cp\u003e(0.03\u0026ndash;3.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003cp\u003e(0.07\u0026ndash;8.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity * Stable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003cp\u003e(0.04\u0026ndash;1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003cp\u003e(0.04\u0026ndash;1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity * Turned active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003cp\u003e(0.07\u0026ndash;1.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003cp\u003e(0.06\u0026ndash;2.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain * Turned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003cp\u003e(0.14\u0026ndash;0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003cp\u003e(0.44\u0026ndash;2.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003cp\u003e(0.15\u0026ndash;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003cp\u003e(0.36\u0026ndash;2.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain * Stable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003cp\u003e(0.47\u0026ndash;3.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003cp\u003e(0.26\u0026ndash;1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003cp\u003e(0.51\u0026ndash;3.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003cp\u003e(0.22\u0026ndash;1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain * Turned active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003cp\u003e(0.53\u0026ndash;2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003cp\u003e(0.96\u0026ndash;5.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003cp\u003e(0.53\u0026ndash;2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003cp\u003e(0.82\u0026ndash;4.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight * Turned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003cp\u003e(0.12\u0026ndash;3.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003cp\u003e(0.33\u0026ndash;2.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003cp\u003e(0.12\u0026ndash;4.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003cp\u003e(0.31\u0026ndash;2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight * Stable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003cp\u003e(0.38\u0026ndash;27.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003cp\u003e(0.37\u0026ndash;2.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.51\u003c/p\u003e\n \u003cp\u003e(0.41\u0026ndash;30.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003cp\u003e(0.33\u0026ndash;2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight * Turned active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003cp\u003e(0.54\u0026ndash;6.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003cp\u003e(0.84\u0026ndash;5.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003cp\u003e(0.48\u0026ndash;5.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003cp\u003e(0.81\u0026ndash;5.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003cp\u003e(0.72\u0026ndash;1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003cp\u003e(0.93\u0026ndash;1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003cp\u003e(0.82\u0026ndash;1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003cp\u003e(0.72\u0026ndash;1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003cp\u003e(0.36\u0026ndash;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(0.39\u0026ndash;0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEx-smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e(0.70\u0026ndash;1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003cp\u003e(0.94\u0026ndash;1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003cp\u003e(0.80\u0026ndash;1.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003cp\u003e(0.73\u0026ndash;1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRisk-level alcohol use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003cp\u003e(0.49\u0026ndash;2.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003cp\u003e(0.73\u0026ndash;1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaily consumption of fresh vegetables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003cp\u003e(0.95\u0026ndash;1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003cp\u003e(0.80\u0026ndash;1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeekly consumption of fast food\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003cp\u003e(0.60\u0026ndash;1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003cp\u003e(0.85\u0026ndash;1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysically active at age 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003cp\u003e(0.59\u0026ndash;1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003cp\u003e(0.63\u0026ndash;1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.31\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(5.70\u0026ndash;9.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.63\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(2.78\u0026ndash;4.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.42\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(5.36\u0026ndash;13.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.28\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(2.02\u0026ndash;5.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLog likelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-817.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-865.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-758.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-793.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLR chi2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;chi2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePseudo R2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eRobust standard errors are in parentheses. The level of statistical significance: ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Base category: Stable healthy weight (BMI 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46) - Stable inactive (MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at ages 31 and 46). BMI\u0026thinsp;=\u0026thinsp;body mass index; PA\u0026thinsp;=\u0026thinsp;physical activity; stable obesity\u0026thinsp;=\u0026thinsp;BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; weight gain\u0026thinsp;=\u0026thinsp;any change to a higher BMI category (i.e. change from healthy weight to overweight or obesity or from overweight to obesity) from age 31 to 46; stable overweight\u0026thinsp;=\u0026thinsp;BMI 25\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; turned inactive\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at age 31, but \u0026lt;\u0026thinsp;150 min/week at age; stable active\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at ages 31 and 46; turned active\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at age 31, but \u0026ge;\u0026thinsp;150 min/week at age 46; high education\u0026thinsp;=\u0026thinsp;bachelor\u0026rsquo;s degree or higher education; risk-level alcohol use: \u0026ge;23.5 doses/week for males, \u0026ge;\u0026thinsp;14 doses/week for females..\u003cbr\u003e\u0026lt;Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e \u0026gt;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003cp\u003eWithout adjustments, female and male participants with stable obesity had a higher probability of having PHC costs than those with stable healthy weight (OR\u0026thinsp;=\u0026thinsp;3.53, 95% CI 1.39\u0026ndash;8.92 for females; OR\u0026thinsp;=\u0026thinsp;3.47, 95% CI 1.34\u0026ndash;8.96 for males). These results were robust to adjustments (OR\u0026thinsp;=\u0026thinsp;3.15, 95% CI 1.23\u0026ndash;8.02 for females; OR\u0026thinsp;=\u0026thinsp;3.77, 95% CI 1.31\u0026ndash;10.85 for males).\u003c/p\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e reports the results from the GLM concerning the associations of the BMI and PA categories at ages 31 and 46, along with their joint associations, with individual-level outpatient PHC costs levels among those who had such costs.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe associations of physical activity and BMI at ages 31 and 46 with the primary healthcare cost levels according to generalized linear analysis. OR (95%CI)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eunadjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eadjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI at ages 31 \u0026amp; 46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003cp\u003e(0.98\u0026ndash;1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003cp\u003e(0.67\u0026ndash;1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.33\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(1.01\u0026ndash;1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e(0.66\u0026ndash;1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.25\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(1.06\u0026ndash;1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003cp\u003e(0.85\u0026ndash;1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(1.03\u0026ndash;1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003cp\u003e(0.84\u0026ndash;1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003cp\u003e(0.93\u0026ndash;1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003cp\u003e(0.80\u0026ndash;1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003cp\u003e(0.96\u0026ndash;1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e(0.77\u0026ndash;1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePA at ages 31 \u0026amp; 46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTurned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003cp\u003e(0.60\u0026ndash;1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003cp\u003e(0.65\u0026ndash;1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003cp\u003e(0.60\u0026ndash;1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003cp\u003e(0.65\u0026ndash;1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003cp\u003e(0.79\u0026ndash;1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003cp\u003e(0.54\u0026ndash;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003cp\u003e(0.83\u0026ndash;1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003cp\u003e(0.51\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTurned active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(0.62\u0026ndash;0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003cp\u003e(0.65\u0026ndash;1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003cp\u003e(0.65\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e(0.68\u0026ndash;1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eInteraction terms between BMI and PA at ages 31 \u0026amp; 46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity * Turned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003cp\u003e(0.54\u0026ndash;2.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003cp\u003e(0.64\u0026ndash;3.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003cp\u003e(0.50\u0026ndash;2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003cp\u003e(0.44\u0026ndash;2.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity * Stable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003cp\u003e(0.42\u0026ndash;3.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003cp\u003e(0.38\u0026ndash;2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003cp\u003e(0.44\u0026ndash;3.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003cp\u003e(0.37\u0026ndash;2.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity * Turned active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003cp\u003e(0.56\u0026ndash;2.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e(0.41\u0026ndash;2.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003cp\u003e(0.51\u0026ndash;2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003cp\u003e(0.29\u0026ndash;2.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain * Turned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003cp\u003e(0.64\u0026ndash;1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003cp\u003e(0.72\u0026ndash;1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003cp\u003e(0.69\u0026ndash;1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003cp\u003e(0.69\u0026ndash;1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain * Stable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003cp\u003e(0.58\u0026ndash;1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003cp\u003e(0.67\u0026ndash;1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003cp\u003e(0.60\u0026ndash;1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003cp\u003e(0.66\u0026ndash;1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain * Turned active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003cp\u003e(0.96\u0026ndash;1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003cp\u003e(0.78\u0026ndash;1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003cp\u003e(0.97\u0026ndash;1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003cp\u003e(0.74\u0026ndash;1.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight * Turned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e(0.46\u0026ndash;2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e(0.60\u0026ndash;1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003cp\u003e(0.45\u0026ndash;2.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e(0.57\u0026ndash;1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight * Stable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003cp\u003e(0.61\u0026ndash;2.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003cp\u003e(0.80\u0026ndash;2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003cp\u003e(0.57\u0026ndash;2.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003cp\u003e(0.84\u0026ndash;2.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight * Turned active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003cp\u003e(0.53\u0026ndash;1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003cp\u003e(0.53\u0026ndash;1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003cp\u003e(0.52\u0026ndash;1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003cp\u003e(0.52\u0026ndash;1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003cp\u003e(0.82\u0026ndash;1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(0.73\u0026ndash;0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003cp\u003e(0.81\u0026ndash;1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(0.74\u0026ndash;0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003cp\u003e(0.89\u0026ndash;1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003cp\u003e(0.72\u0026ndash;1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEx-smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003cp\u003e(0.96\u0026ndash;1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003cp\u003e(0.91\u0026ndash;1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003cp\u003e(0.86\u0026ndash;1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003cp\u003e(0.88\u0026ndash;1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRisk-level alcohol use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003cp\u003e(0.85\u0026ndash;1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003cp\u003e(0.74\u0026ndash;1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaily consumption of fresh vegetables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003cp\u003e(0.81\u0026ndash;1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003cp\u003e(0.88\u0026ndash;1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeekly consumption of fast food\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e(0.83\u0026ndash;1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e(0.85\u0026ndash;1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysically active at age 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003cp\u003e(0.90\u0026ndash;1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e(0.82\u0026ndash;1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e388.21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(344\u0026ndash;438)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e347.38\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(296\u0026ndash;407)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e407.02\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(335\u0026ndash;494)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e398.82\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(302\u0026ndash;526)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLog likelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-15 612.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-10 762.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-14 608.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9 869.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eRobust standard errors are in parentheses. The level of statistical significance: ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Base category: Stable healthy weight (BMI 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e both at ages 31 and 46) - Stable inactive (MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at ages 31 and 46). BMI\u0026thinsp;=\u0026thinsp;body mass index; PA\u0026thinsp;=\u0026thinsp;physical activity; stable obesity\u0026thinsp;=\u0026thinsp;BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; weight gain\u0026thinsp;=\u0026thinsp;any change to a higher BMI category (i.e. change from healthy weight to overweight or obesity or from overweight to obesity) from age 31 to 46; stable overweight\u0026thinsp;=\u0026thinsp;BMI 25\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; turned inactive\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at age 31, but \u0026lt;\u0026thinsp;150 min/week at age; stable active\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at ages 31 and 46; turned active\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at age 31, but \u0026ge;\u0026thinsp;150 min/week at age 46; high education\u0026thinsp;=\u0026thinsp;bachelor\u0026rsquo;s degree or higher education; risk-level alcohol use: \u0026ge;23.5 doses/week for males, \u0026ge;\u0026thinsp;14 doses/week for females.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026lt;Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026gt;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003cp\u003eWithout adjustments, female participants who gained weight between ages 31 and 46 had higher individual-level outpatient PHC costs (OR\u0026thinsp;=\u0026thinsp;1.25, 95% CI 1.06\u0026ndash;1.48) than those with stable healthy weight, and females who turned active between ages 31 and 46 had lower PHC costs (OR\u0026thinsp;=\u0026thinsp;0.78, 95% CI 0.62\u0026ndash;0.97) than those who were stable inactive. After adjustments, female participants who gained weight (OR\u0026thinsp;=\u0026thinsp;1.22, 95% CI 1.03\u0026ndash;1.44) and females with stable obesity (OR\u0026thinsp;=\u0026thinsp;1.33, 95% CI 1.01\u0026ndash;1.75) had higher PHC costs than those with stable healthy weight.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e reports the adjusted predicted individual annual outpatient PHC costs at age 46 according to the combined PA\u0026ndash;BMI change categories between ages 31 and 46 based on GLM.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAverage adjusted predicted outpatient primary healthcare costs (\u0026euro;) in 2011 stratified by physical activity and BMI at ages 31 and 46.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"16\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"15\"\u003e\n \u003cp\u003ePA at ages 31 \u0026amp; 46\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTurned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eStable inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eStable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTurned active\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI at ages 31 \u0026amp; 46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[135\u0026ndash;738]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[380\u0026ndash;626]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[-5\u0026ndash;1405]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[164\u0026ndash;677]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[275\u0026ndash;474]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[404\u0026ndash;513]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[305\u0026ndash;614]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[394\u0026ndash;620]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[123\u0026ndash;614]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[355\u0026ndash;605]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[216\u0026ndash;1032]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[207\u0026ndash;490]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable healthy weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[223\u0026ndash;372]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[331\u0026ndash;423]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[310\u0026ndash;504]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[249\u0026ndash;365]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTurned inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eStable inactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eStable active\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTurned active\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI at ages 31 \u0026amp; 46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[104\u0026ndash;580]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[216\u0026ndash;450]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[55\u0026ndash;374]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[44\u0026ndash;448]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[288\u0026ndash;519]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[309\u0026ndash;414]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[190\u0026ndash;376]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[310\u0026ndash;538]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable overweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[219\u0026ndash;434]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[278\u0026ndash;404]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[225\u0026ndash;467]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[201\u0026ndash;389]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable healthy weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[212\u0026ndash;453]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[281\u0026ndash;402]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[175\u0026ndash;319]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[226\u0026ndash;443]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"16\"\u003eThe adjusted predicted levels of individual annual outpatient primary healthcare costs in 2011 were calculated using estimated generalized linear models explaining the healthcare costs. The predictions were calculated with the values of the covariates, marital status, education level, employment status, smoking, risk-level alcohol use, daily consumption of fresh vegetables, weekly consumption of fast food, and PA at age 14, at their means. The costs were predicted individual healthcare costs of a person with average characteristics. PA\u0026thinsp;=\u0026thinsp;physical activity; BMI\u0026thinsp;=\u0026thinsp;body mass index; stable obesity\u0026thinsp;=\u0026thinsp;BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; weight gain\u0026thinsp;=\u0026thinsp;any change to a higher BMI category (i.e. change from healthy weight to overweight or obesity or from overweight to obesity) from age 31 to 46; stable overweight\u0026thinsp;=\u0026thinsp;BMI 25\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; stable healthy weight\u0026thinsp;=\u0026thinsp;BMI 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e at ages 31 and 46; turned inactive\u0026thinsp;=\u0026thinsp;MVPA (=\u0026thinsp;moderate-to-vigorous PA, \u0026ge;3MET)\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at age 31, but \u0026lt;\u0026thinsp;150 min/week at age; stable inactive\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at ages 31 and 46; stable active\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026ge;\u0026thinsp;150 min/week at ages 31 and 46; turned active\u0026thinsp;=\u0026thinsp;MVPA\u0026thinsp;\u0026lt;\u0026thinsp;150 min/week at age 31, but \u0026ge;\u0026thinsp;150 min/week at age 46.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026lt;Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026gt;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003cp\u003eRegarding the BMI categories, among female participants who had stable obesity, those who were stable active had the highest adjusted predicted annual PHC costs. However, the predicted PHC costs did not differ statistically significantly from 0 (\u0026euro;700 [95% CI \u0026euro;-5\u0026ndash;1405]). Among females with weight gain between ages 31 and 46, the highest predicted annual PHC costs (\u0026euro;507 [95% CI \u0026euro;394\u0026ndash;620]) were for those who turned active. The highest predicted costs in the categories of stable overweight (\u0026euro;624 [95% CI \u0026euro;216\u0026ndash;1032]) and stable healthy weight (\u0026euro;407 [95% CI \u0026euro;310\u0026ndash;504]) were for females who were stable active. Among males with stable obesity, the highest predicted costs were for those who turned inactive between ages 31 and 46 (\u0026euro;342 [95% CI \u0026euro;104\u0026ndash;580]). Among male participants with weight gain, those who turned active had the highest predicted costs (\u0026euro;424 [95% CI \u0026euro;310\u0026ndash;538]). Among males with stable overweight, those who were stable active had the highest predicted costs (\u0026euro;346 [95% CI \u0026euro;225\u0026ndash;467]). Finally, among males with healthy weight, those who were stable inactive had the highest predicted costs (\u0026euro;342 [95% CI \u0026euro;175\u0026ndash;319].\u003c/p\u003e\n \u003cp\u003eRegarding the PA categories, the highest predicted PHC costs were among female participants with stable obesity among all other PA categories, but among those who turned active, those with weight gain had the highest predicted costs. For males, the highest predicted PHC costs were for those with weight gain, except among stable active males, those with stable overweight had the highest predicted costs.\u003c/p\u003e\n \u003cp\u003eThe results of the tests for statistical significance of the differences in the predicted outpatient PHC costs between different BMI categories within different PA categories and between different PA categories within different BMI categories are presented in Tables S1 and S2 in Supplementary Digital Content 4. Among stable inactive females, those who gained weight had 25% (\u0026euro;81 [95% CI \u0026euro;10\u0026ndash;153]) higher predicted PHC costs than those with stable healthy weight. Among females who turned active, those who gained weight had 65% (\u0026euro;200 [95% CI \u0026euro;73\u0026ndash;327]) higher predicted PHC costs than those with stable healthy weight. For males, among those with stable healthy weight, those who were stable inactive had 38% (\u0026euro;95 [95% CI \u0026euro;1\u0026ndash;277]) higher predicted PHC costs than those who were stable active.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe present population-based birth cohort study, for the first time, evaluated the association between PA and adjusted individual-level outpatient PHC costs related to sustained healthy weight, overweight, and obesity and weight gain in midlife. In addition, the two-part model allowed us to separately estimate the probability of incurring any outpatient PHC costs, and among those who used outpatient PHC services, the level of costs, and to compare the results according to the changes in the participants\u0026rsquo; PA and BMI. Obesity was found to be associated with a higher probability of having outpatient PHC costs in both sexes, and among females, weight gain and sustained obesity were associated with higher outpatient PHC cost level. Contrary to our hypothesis, sustained PA reaching the current recommendations or becoming physically active did not mitigate the impact of obesity or weight gain on outpatient PHC costs. The adjusted predicted individual annual outpatient PHC costs were found to be the highest for females with stable obesity, weight gain, and stable overweight regardless of the PA category, and mostly for males as well, although only a few of the differences in adjusted predicted PHC costs between the BMI categories within a fixed PA category and between the PA categories within a fixed BMI category were found to be statistically significant. Reaching the current PA recommendations predicted PHC costs only among males with stable healthy weight, among whom those who were stable inactive had 38% higher predicted costs than those who were stable active.\u003c/p\u003e \u003cp\u003eOur findings of a higher probability of having healthcare costs for individuals with obesity and among females, and the association of having obesity and weight gain with healthcare cost levels are in line with the findings of previous studies (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). We did not find any association between having stable overweight and PHC costs, which supports the previous finding of Finkelstein et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) that healthcare costs for individuals with overweight do not significantly differ from those for individuals with healthy weight.\u003c/p\u003e \u003cp\u003e We found that female participants had 32% higher mean individual-level outpatient PHC costs than male participants. This is in line with previous studies (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). According to our results, female participants had lower MVPA volume at age 31 than male participants. However, between ages 31 and 46, more females than males became physically active and the MVPA volume of females increased by 29 minutes/week on average, while that of males increased by only 8 minutes/week. Living with children has been reported to have a negative impact on engagement in PA (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), especially among females (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Children growing up and easing household work between ages 31 and 46 for mothers may enable them to become physically active at middle age. Persistent PA health benefits have been reported to require sustained PA (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Among females, the impact of increased PA on healthcare costs may not be seen within the time-period used in the present study because recent PA increase and short-lived PA may not be enough to provide healthcare cost benefits.\u003c/p\u003e \u003cp\u003eThe predicted average annual individual-level healthcare costs in the present study were significantly lower than those in a recent Finnish study (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), which reported \u0026euro;2 665 total annual healthcare costs (consisting of the costs of healthcare visits, hospital stays and prescribed medicines) for individuals with obesity, and \u0026euro;1 799 for individuals with healthy weight or overweight in Finland. The difference is explained by the fact that the outpatient PHC costs used in the present study represented only a fraction of the total healthcare costs due to the lack of data on the costs of outpatient hospital care, inpatient services, and medications. For example, Cawley et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) reported that obesity raises the costs in all major categories of healthcare, with particularly large increases in inpatient services and prescription drug expenditures. Wang et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) reported pharmaceutical costs and inpatient costs, but not outpatient costs, to be significantly higher for retirees over age 65 with overweight and obesity compared to retirees with healthy weight.\u003c/p\u003e \u003cp\u003eThe interactions between BMI, PA, and related healthcare costs may be quite complex. BMI has been reported to be associated with PA (\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). In the past decades, studies have suggested that obesity may be a driver of physical inactivity, instead of the previous assumption that low PA leads to obesity (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), or at least that the relation might be bidirectional (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Physical inactivity itself is known to be associated with higher disease burden (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), which may lead to higher additional healthcare costs in the long run if PA remains low (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), in addition to obesity-related increased healthcare costs (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Stable inactivity may also reflect poor health status, which may prevent engagement in PA. Health status is one of the strongest previously reported correlates and a suggested determinant of engagement in PA (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Obesity itself has a significant independent negative impact on health (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Additionally, shifting from physical inactivity to activity may increase the use of healthcare services through, for example, exercise-related injuries, pain, or other problems, especially in the early stages of physically active lifestyle (\u003cspan additionalcitationids=\"CR49 CR50\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), and in individuals with obesity (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). In addition, one form of complex interaction between BMI, PA, and healthcare costs is possible curvilinear shape of the association between PA and healthcare service use and healthcare costs across BMI categories (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In our previous study (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e) we found curvilinear association between adulthood accelerometer-measured PA and future income. The numbers of stable active participants with obesity, overweight, and a history of weight gain were too low to enable the evaluation of the possible curvilinear associations of PA with healthcare costs in the present study.\u003c/p\u003e \u003cp\u003eThe present study had several strengths. The unselected population-based data represented both sexes and individuals from all sectors of the economy, occupational statuses, and education levels. Additionally, the participants in the present study were born around the same year in the same geographical area in Finland and were still living in Finland at the time of the study; thus, the risk of bias arising from the effect of age, race, and culture on PHC costs was low. The fact that all the participants in the present study were living in Finland also made the healthcare cost calculations reliable and made the obtained cost values comparable to each other. Furthermore, using individual-level data, we were able to capture the outpatient PHC costs of all health conditions leading to outpatient PHC service use, whether associated with obesity or not, so the possible outpatient PHC costs from PA-related injuries and diseases were also included. We also had a longitudinal perspective, as opposed to the previous cross-sectional studies (\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the foregoing, the present study also had some limitations. For example, the self-reported data concerning PA and healthcare service use in the year before age 46 might have led to recall bias. In addition, the data on self-reported PA used in the study reflected leisure time PA and did not include, for example, work-related PA. The standard unit costs reported by the Finnish Institute for Health and Welfare (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) that were used in the calculations also did not reveal the real healthcare service costs. Thus, the calculated and predicted individual-level outpatient PHC costs in the present study were underestimations. Additionally, we had no information about the participants\u0026rsquo; reasons for healthcare service use, and we do not know if they had some health-related reasons for decrease or increase PA. For example, some disease or injury between ages 31 and 46 could have affected both PHC costs and PA. However, the effects of these factors on the main study results and conclusions were limited because the study aimed to compare the individual-level PHC costs according to the changes in PA and BMI, not to reveal the exact cost level. The classification of the participants as physically inactive or physically active was based on PA recommendations (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The shift from physical inactivity to physically active or vice versa could have been caused by a change in MVPA as minimal as 1 min/week, because individuals with \u0026le;\u0026thinsp;149 minutes/week MVPA were categorized as physically inactive and those with \u0026ge;\u0026thinsp;150 minutes/week MVPA as physically active. In addition, we did not have any information on the possible fluctuations in BMI and PA between ages 32 and 45. Moreover, in some subgroups, the numbers of participants were quite low, only 7 at the lowest. The number of individuals with weight loss between ages 31 and 46 among NFBC1966 cohort members was so low that we were not able to statistically analyze the associations of weight loss and PA categories with PHC costs. It is also well known that dietary factors and other healthy life habits (i.e. PA), BMI, and education level may interact with each other. Individual-level healthcare expenditures have also been found to increase with age (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e), obesity duration has been reported to increase functional limitations and disability in the long run (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e), and persistent PA health benefits have been reported to require continuing PA (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Thus, the relatively young (46 years) age cohort in the present study might not be optimal for revealing the longitudinal associations of obesity and PA with healthcare costs. The complex interactions between BMI, PA, and healthcare costs could not be recognized in the study protocol that we used, and we were not able to distinguish the effects of different components of health behavior on healthcare costs.\u003c/p\u003e \u003cp\u003eAs conclusion, this study shows that obesity is associated with a higher probability of having outpatient primary healthcare costs, and among females, obesity and weight gain are also associated with higher outpatient PHC cost levels. Reaching the current PA recommendations did not mitigate the impact of obesity and weight gain on outpatient PHC costs in midlife. Reaching the current PA recommendations alone is insufficient when aiming to decrease obesity-related PHC costs in midlife. Long-term effects of PA on outpatient PHC costs should be evaluated in future studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eACKNOWLEDGMENTS\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe are grateful for all the cohort members and researchers who participated in the 31- and 46-year follow-up studies and for the work of the NFBC project center.\u003c/p\u003e\n\u003cp\u003eAUTHOR CONTRIBUTIONS\u003c/p\u003e\n\u003cp\u003eHEJ contributed to the design of the study protocol and methods; interpretation of the study results; writing, review, and editing of the original paper draft; and creation of Figure 1. She also reviewed the literature, edited the tables, and had full access to the study data and final responsibility for the decision to submit the paper for publication. MMV contributed to the design of the study methods, curation and analysis of the study data, review and editing of the draft paper, and creation of Table 1. IJSN contributed to the design of the study methods and the review and editing of the draft paper. SMH contributed to the design of the study methods, analysis of the study data, interpretation of the study results, creation of Tables 2\u0026ndash;4, S1, and S2, and review and editing of the draft paper. JTK, AML, and SMN contributed to the review and editing of the draft paper and provided feedback regarding it. RK contributed to the design of the study protocol, curation of the PA and other data, review and editing of the draft paper, resources, project supervision/administration, and funding acquisition. MJK contributed to the design of the study protocol and methods, interpretation of the study results, review and editing of the draft paper, and project supervision/administration. All the authors have read and approved the final manuscript and have agreed to be accountable for all aspects of the work, ensuring that all questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003eDECLARATION OF COMPETING INTEREST\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003eDATA AVAILABILITY STATEMENT\u003c/p\u003e\n\u003cp\u003eThe data for this article were obtained from the population-based Northern Finland Birth Cohort 1966 (NFBC1966). The NFBC1966 data set comprises health-related participant data, and their use is therefore restricted under the regulations on professional secrecy (Act on the Openness of Government Activities, 612/1999) and sensitive personal data (Personal Data Act, 523/1999, implementing the EU data protection directive 95/46/EC). Due to these legal restrictions, the data from this study cannot be stored in public repositories or otherwise be made publicly available. However, data access may be permitted on a case-by-case basis upon request. Data-sharing outside the research group is done in collaboration with the NFBC1966 group and requires a data-sharing agreement with the NFBC1966 representatives (NFBC1966, University of Oulu, https://www.oulu.fi/en/university/faculties-and-units/faculty-medicine/northern-finland-birth-cohorts-and-arctic-biobank).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eETHICS APPROVAL STATEMENT\u003c/p\u003e\n\u003cp\u003eThe results of the study are presented honestly, and without fabrication, falsification, or inappropriate data manipulation.\u0026nbsp;All participants provided written informed consent, and the Ethical Committee of the Northern Ostrobothnia Hospital District in Oulu, Finland approved the Northern Finland Birth Cohort study (\u0026sect;94/2011), which was conducted according to the Declaration of Helsinki of 1983.\u003c/p\u003e\n\u003cp\u003eThe results of the study are presented honestly, and without fabrication, falsification, or inappropriate data manipulation.\u003c/p\u003e\n\u003cp\u003eCOMPETING INTERESTS\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003eFUNDING\u003c/p\u003e\n\u003cp\u003eNFBC1966 data collection for 31- and 46-year follow-ups received financial support from the University of Oulu (grant no. 24000692), Oulu University Hospital (grant no. 24301140), and the European Regional Development Fund (grant no.539/2010 A31592). The study has been financially supported by the Ministry of Education and Culture (OKM/86/626/2014, OKM/43/626/2015, OKM/17/626/2016, OKM/54/626/2019, OKM/85/626/2019, OKM/1096/626/2020, OKM/64/626/2020, OKM/1105/626/2020, OKM/91/626/2021, OKM/20/626/2022). M.N. has received funding from Fibrobesity-project, a strategic profiling project at the University of Oulu, which is supported by the Academy of Finland Profi6 336449.\u003c/p\u003e\n\u003cp\u003eThe funding organizations had no role in the study design, the collection, analysis, and interpretation of data, the writing of the article, or the decision to submit it for publication. No funding was received for this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCawley J, Biener A, Meyerhoefer C, Ding Y, Zvenyach T, Smolarz BG, et al. Direct medical costs of obesity in the United States and the most populous states. 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Obesity. 2015;23(2):443\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3373605/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3373605/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo study the association of physical activity (PA) with individual-level outpatient primary healthcare (PHC) costs in midlife according to body mass index (BMI) categories.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population comprised 4 076 participants from the Northern Finland Birth Cohort 1966. The probability of having PHC costs and the previous year PHC cost levels at age 46 according to BMI and self-reported PA and their joint interactions were estimated using a two-part model. The BMI categories were healthy weight, overweight, and obesity at ages 31 and 46, and weight gain between such ages. The PA categories were inactive and active at ages 31 and 46, and turning inactive and turning active between such ages. The adjusted predicted annual individual-level PHC costs (€) for the combined BMI and PA categories were estimated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participants with obesity had a significantly higher probability of having PHC costs (OR = 3.15, 95%CI 1.23–8.02 for females; OR = 3.77, 95%CI 1.31–10.85 for males) than the participants with healthy weight. The participants with obesity (OR = 1.33, 95%CI 1.01–1.75), and those with weight gain (OR = 1.22, 95%CI 1.03–1.44) had significantly higher PHC costs than the participants with healthy weight among females, but not among males. Joint associations of any of the BMI and PA categories with the probability of having PHC costs or cost levels were not found. Among females, the inactive participants with weight gain had 25% higher predicted costs than the inactive participants with healthy weight; and among the participants who turned active, those with weight gain had 65% higher predicted costs than those with healthy weight. Among males with healthy weight, the inactive ones had 38% higher predicted costs than the active participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReaching the current PA recommendations does not mitigate the impact of obesity and weight gain on outpatient PHC costs in midlife.\u003c/p\u003e","manuscriptTitle":"Association between physical activity and healthcare costs by weight status in middle age: Evidence from the Northern Finland Birth Cohort 1966","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-10-03 22:53:50","doi":"10.21203/rs.3.rs-3373605/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"84779eb4-1d16-482f-9061-e2db2b936998","owner":[],"postedDate":"October 3rd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":24986347,"name":"Health sciences/Health care/Health policy"},{"id":24986348,"name":"Health sciences/Medical research/Epidemiology"},{"id":24986349,"name":"Health sciences/Health care/Public health/Epidemiology"},{"id":24986350,"name":"Health sciences/Health care/Weight management"},{"id":24986351,"name":"Health sciences/Health care/Diagnosis/Body mass index"}],"tags":[],"updatedAt":"2023-10-20T13:21:47+00:00","versionOfRecord":[],"versionCreatedAt":"2023-10-03 22:53:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3373605","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3373605","identity":"rs-3373605","version":["v1"]},"buildId":"ApUGefWb6u5IBVtyqm6d5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}