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A decreasing age of menarche has been reported across the Western world. Early menarche is associated with unfavorable health outcomes. The aims of this study were to describe the age at menarche in a general population sample in Norway and the associations between body mass index (BMI) categories at preschool (approximately 6 years of age) and age at menarche. We used self-reported age at menarche among girls who participated in the population-based study Fit Futures 1 (FF 2010-2011), mostly born in 1994, to calculate age at menarche. The preschool BMI from health records was divided into BMI categories according to validated cutoffs on the basis of age and sex from the International Obesity Task Force (IOTF). We estimated the effect of preschool BMI on age at menarche via a linear regression model adjusted for socioeconomic status (SES). Among 500 girls with a mean age of 16.5 years (standard deviation (SD) ± 1.4), 497 (99%) had completed menarche. The mean age at menarche was 13.0 years (SD ± 1.2). According to the fitted linear regression model, preschool obesity was a statistically significant predictor of age at menarche and was associated with menarche 9.5 months earlier than a normal preschool BMI was. R2 estimated that preschool BMI could explain 3% of the variance in age at menarche. The mean age at menarche in Northern Norway was 13.0 (SD ± 1.2) years, similar to previous Norwegian studies. Childhood obesity was associated with earlier age at menarche.

Background Obesity is a serious childhood health problem today. Studies have shown that overweight and obesity tend to be stable (track) from birth, through childhood and adolescence, to adulthood. However, existing studies are heterogeneous; there is still no consensus on the strength of the association between high birth weight or high body mass index (BMI) early in life and overweight and obesity later in life, nor on the appropriate age or target group for intervention and prevention efforts. This study aimed to determine the presence and degree of tracking of overweight and obesity and development in BMI and BMI standard deviation scores (SDS) from childhood to adolescence in the Fit Futures cohort from North Norway. Methods Using a retrospective cohort design, data on 532 adolescents from the Fit Futures cohort were supplemented with height and weight data from childhood health records, and BMI was calculated at 2–4, 5–7, and 15–17 years of age. Participants were categorized into weight classes by BMI according to the International Obesity Taskforce’s age- and sex-specific cut-off values for children 2–18 years of age (thinness: adult BMI <18.5 kg/m 2 , normal weight: adult BMI ≥18.5- < 25 kg/m 2 , overweight: adult BMI ≥25- < 30 kg/m 2 , obesity: adult BMI ≥30 kg/m 2 ). Non-parametric tests, Cohen’s weighted Kappa statistic and logistic regression were used in the analyses. Results The prevalence of overweight and obesity combined, increased from 11.5 % at 2–4 years of age and 13.7 % at 5–7 years of age, to 20.1 % at 15–17 years of age. Children who were overweight/obese at 5–7 years of age had increased odds of being overweight/obese at 15–17 years of age, compared to thin/normal weight children (crude odds ratio: 11.1, 95 % confidence interval: 6.4–19.2). Six out of 10 children who were overweight/obese at 5–7 years of age were overweight/obese at 15–17 years of age. Conclusions The prevalence of overweight and obesity increased with age. We found a moderate indication of tracking of overweight/obesity from childhood to adolescence. Preventive and treatment initiatives among children at high risk of overweight and obesity should start before 5–7 years of age, but general preventive efforts targeting all children are most important.

ObjectivesTo investigate the longitudinal associations between tobacco use (smoking and snuff) and bone mineral density (BMD) at femoral sites and in the total body in a Norwegian adolescent cohort, aged 16–27 years.DesignProspective longitudinal cohort study.SettingA population-based study in Norwegian adolescents from the general population.ParticipantsIn total, 722 adolescents (385 females and 337 males) with a mean age of 16 years (SD: 0.5) from the Fit Futures Study (FF) were included at FF1 (2010–2011), with follow-up measures at age 18 years (FF2 (2012–2013)) and 27 years (FF3 (2021–2022)). Inclusion criteria were completed dual-energy X-ray absorptiometry (DXA) scans, serum vitamin D blood samples and information on smoking, snuff use, physical activity, height, alcohol intake, hormonal contraceptive use and puberty status, all at baseline (FF1).Primary and secondary outcome measuresAssociations between self-reported smoking and snuff use (categorised as never, sometimes or daily) and changes in BMD (g/cm²) at the total hip, femoral neck and total body, measured using DXA.ResultsTotal hip BMD (mean (g/cm2), 95% CI) slightly increased from FF1 (females: 1.066, 95% CI 1.054 to 1.079; males: 1.121, 95% CI 1.105 to 1.136) to FF2 (females: 1.076, 95% CI 1.063 to 1.089; males: 1.141, 95% CI 1.126 to 1.157; p<0.001), but thereafter decreased to FF3 (females: 1.050, 95% CI 1.036 to 1.063; males: 1.091, 95% CI 1.074 to 1.107; females and males, both p<0.001). Similar patterns were observed for the femoral neck, while total body BMD increased from FF1 through FF3 (p<0.001). We observed interactions between time and smoking and between time and snuff use in all models (all p<0.001). However, we generally observed no statistically significant differences in BMD levels across smoking and snuff use groups at different time points (all p>0.07), except in females at 18 years (FF2), where those who never smoked had higher total hip BMD than those who sometimes and never smoked (p<0.001).ConclusionsWe found no statistically significant associations between smoking or snuff use and BMD levels in Norwegian adolescents from a median age of 16 to 27 years. Notably, only 2.6% of females and 3.9% of males reported smoking daily. However, in this study, moderate tobacco use did not appear to negatively influence bone growth from adolescence to young adulthood.

Background Adolescence is associated with declining physical activity (PA) levels, and potential prevailing changes into young adulthood are indicated, but less explored. This study investigates longitudinal changes in PA from adolescence to young adulthood among males and females in a North Norwegian cohort. Methods In the population-based Fit Futures Study, PA was assessed with both questionnaires (Saltin-Grimby Physical Activity Level Scale) and accelerometers (ActiGraph) at ages ~ 16 (n self−report =936; n accelerometer =674), ~ 18 (n self−report =808; n accelerometer =507), and ~ 27 (n self−report =648; n accelerometer =466). We used mixed effects models to analyze longitudinal changes in accelerometer-measured PA and sedentary time, alongside mixed effects multinomial logistic regression for changes in self-reported leisure time PA. Results We observed a significant non-linear U-shaped trend in accelerometer-measured moderate-to-vigorous PA (MVPA) over time ( p  < 0.001), with an initial decline in minutes per day from age 16 (mean ± SD: 70.7 ± 25.2) to age 18 (62.3 ± 23.8), followed by an increase to age 27 (67.5 ± 30.4). At age 16, males exhibited higher MVPA than females. By age 18 and 27, MVPA levels were similar between sexes. Accelerometer-measured sedentary time decreased linearly across all three surveys ( p  = 0.002). We observed distributional shifts in self-reported leisure time PA over time: vigorously- and highly active proportions declined, while the moderately active proportion increased, and the proportion of sedentary participants remained stable (~ 20%). Compared to vigorously active, the odds of reporting sedentary (OR: 1.07, 95% CI: 1.03 to 1.11), moderately active (OR: 1.11, 95% CI: 1.07 to 1.15), and highly active (OR: 1.07, 95% CI: 1.03 to 1.11) increased with each year from age 16 (all p  ≤ 0.001). Compared to moderately active, the odds of reporting other categories decreased over time (ORs: 0.92 to 0.96, all p  ≤ 0.001). Conclusions We observed non-linear changes in accelerometer-measured MVPA, indicating a U-shaped trend with a decline from 16 to 18 years, followed by an increase to age 27. Self-reported leisure time PA levels declined from adolescence to young adulthood, with decreasing proportions highly and vigorously active, while the proportion moderately active increased and the proportion of sedentary was unchanged. These results indicate that from adolescence to young adulthood, not all PA changes lead exclusively to increased sedentariness.

Iodine is crucial for thyroid hormones, normal metabolism, growth and development in the foetal period. Low iodine status in women of childbearing age is particularly worrying since iodine deficiency continues into pregnancy. This study aimed to measure iodine status in non-pregnant and pregnant women in Northern Norway and investigate group differences and determinants of urine iodine concentrations (UICs) based on dietary factors and participants' knowledge about iodine. This cross-sectional study included pregnant ( = 131) and non-pregnant ( = 493) women from the Northern Norway Mother-and-Child Contaminant Cohort Study 2 study (2017-2021) and the Fit Futures 3 study (2020-2021). UIC was measured in spot urine, and dietary iodine intake was calculated from food frequency questionnaires. Group differences in median UIC were explored using non-parametric tests. Associations between independent variables and median UIC were estimated through quantile regression, adjusting for relevant covariates. Median UIC was 91 μg/L in non-pregnant and 134 μg/L in pregnant women, thus below the World Health Organization definition of insufficient iodine status of < 100 μg/L and 150 μg/L, respectively. Dairy products and lean fish were the most important dietary iodine sources, but the median estimated intake did not reach the recommended intake. Taking iodine supplements was the strongest determinant of UIC in both groups ( < 0.01), and users had adequate iodine status at a group level. A high proportion of the non-pregnant women (84%) were not taking iodine supplements. Poor knowledge about iodine in the participant groups was observed but was not associated with UIC. Pregnant and non-pregnant women not using iodine supplements had inadequate iodine status and insufficient iodine intake. Supplement use or interventions at the societal level are essential to ensure adequate status in these vulnerable groups.

ObjectivesChildhood overweight/obesity is associated with later overweight/obesity. However, the association between birth weight and later overweight/obesity has not been established. The aim of this study was to investigate the relation between both birth weight and childhood body mass index (BMI), and adolescent overweight/obesity in a Norwegian population.MethodsThe Tromsø Study – Fit Futures is a population-based cohort study conducted in 2010–2011 and 2012–2013 in Tromsø, Norway. A representative sample of 961 adolescents participated. Longitudinal anthropometric data were obtained from the Medical Birth Registry of Norway, childhood health records at 2–4 and 5–7 years of age, and repeated measurements at 15–18 and 18–20 years of age. Outcome was defined as normal weight (adult BMI <25 kg/m2) or overweight/obese (adult BMI ≥2 5 kg/m2) at 15–20 years of age according to international age- and sex-specific cut-off values for children. Associations were investigated using generalised estimating equations.ResultsIn adjusted analyses, a 1-SD (586 g) higher birth weight was associated with a higher OR for overweight/obesity at 15–20 years of age (OR 1.25, 95% CI 1.06 to 1.48). Childhood BMI was also associated with overweight/obesity at 15–20 years of age: a 1-SD (1.35 kg/m2) increase in BMI at age 2–4 years rendered an OR of 1.66 (95% CI 1.40 to 1.96); a 1-SD (1.83 kg/m2) increase in BMI at age 5–7 years rendered an OR of 3.23 (95% CI 2.56 to 4.07). When compared with normal-weight children, those with severe overweight/obesity in childhood (adult BMI ≥27 kg/m2) showed stronger associations with overweight/obesity at 15–20 years of age: OR 3.01 (95% CI 1.47 to 6.18) and OR 11.51 (95% CI 6.63 to 19.99) at ages 2–4 and 5–7, respectively.ConclusionAssociations between birth weight and overweight/obesity at 15–20 years of age were modest, whereas the influence of BMI at 2–4 and 5–7 years on overweight/obesity at 15–20 years was moderate to strong.

Determinants of bone acquisition in late adolescence and early adulthood are not well‐described. This 2‐year follow‐up study explored the associations of body weight (BW), body mass index (BMI), and changes in weight status with adolescent bone accretion in a sample of 651 adolescents (355 girls and 296 boys) between 15 and 19 years of age from The Tromsø Study: Fit Futures. This Norwegian population‐based cohort study was conducted from 2010 to 2011 and was repeated from 2012 to 2013. We measured femoral neck, total hip, and total body bone mineral content and areal bone mineral density (aBMD) by dual‐energy X‐ray absorptiometry. We measured height, BW, calculated BMI (kg/m 2), and collected information on lifestyle at both surveys. Mean BMI (SD) at baseline was 22.17 (3.76) and 22.18 (3.93) in girls and boys, respectively. Through multiple linear regression, baseline BW and BMI were positively associated with ∆aBMD over 2 years of follow‐up at all skeletal sites in boys ( p < 0.05), but not in girls. ∆BW and ∆BMI predicted ∆aBMD and ∆BMC in both sexes, but the strength of the associations was moderate. Individuals who lost weight during follow‐up demonstrated a slowed progression of aBMD accretion compared with those gaining weight, but loss of BW or reduction of BMI during 2 years was not associated with net loss of aBMD. In conclusion, our results confirm that adequate BW for height in late adolescence is important for bone health. Associations between change in weight status and bone accretion during follow‐up were moderate and unlikely to have any clinical implication on adolescents of normal weight. Underweight individuals, particularly boys, are at risk of not reaching optimal peak bone mass and could benefit from an increase in BMI. © 2019 The Authors. JBMR Plus is published by Wiley Periodicals, Inc. on behalf of the American Society for Bone and Mineral Research.

Summary In a Norwegian youth cohort followed from adolescence to young adulthood, bone mineral density (BMD) levels declined at the femoral neck and total hip from 16 to 27 years but continued to increase at the total body indicating a site-specific attainment of peak bone mass. Purpose To examine longitudinal trends in bone mineral density (BMD) levels in Norwegian adolescents into young adulthood. Method In a prospective cohort design, we followed 980 adolescents (473 (48%) females) aged 16–19 years into adulthood (age of 26–29) on three occasions: 2010–2011 (Fit Futures 1 (FF1)), 2012–2013 (FF2), and 2021–2022 (FF3), measuring BMD (g/cm 2 ) at the femoral neck, total hip, and total body with dual x-ray absorptiometry (DXA). We used linear mixed models to examine longitudinal BMD changes from FF1 to FF3. Results From the median age of 16 years (FF1), femoral neck BMD (mean g/cm 2 (95% CI)) slightly increased in females from 1.070 (1.059–1.082) to 1.076 (1.065–1.088, p  = 0.015) at the median age of 18 years (FF2) but declined to 1.041 (1.029–1.053, p  < 0.001) at the median age of 27 years (FF3). Similar patterns were observed in males: 16 years, 1.104 (1.091–1.116); 27 years, 1.063 (1.050–1.077, p  < 0.001); and for the total hip in both sexes (both p  < 0.001). Total body BMD increased from age 16 to 27 years in both sexes (females: 16 years, 1.141 (1.133–1.148); 27 years, 1.204 (1.196–1.212), p  < 0.001; males: 16 years, 1.179 (1.170–1.188); 27 years, 1.310 (1.296–1.315), p  < 0.001). Conclusion BMD levels increased from 16 to 18 years at the femoral and total hip sites in young Norwegian females and males, and a small decline was observed at the femoral sites when the participants were followed up to 27 years. Total body BMD continued to increase from adolescence to young adulthood.

The effect of birth weight and childhood body mass index (BMI) on adolescents’ bone parameters is not established. The aim of this longitudinal, population‐based study was to investigate the association of birth weight, childhood BMI, and growth, with adolescent bone mass and bone density in a sample of 633 adolescents (48% girls) from The Tromsø Study: Fit Futures. This population‐based cohort study was conducted in 2010–2011 and 2012–2013 in Tromsø, Norway. Bone mineral content (BMC) and areal BMD (aBMD) were measured at total hip (TH) and total body (TB) by dual‐energy X‐ray absorptiometry (DXA) and converted to internal Z‐scores. Birth weight and childhood anthropometric measurements were retrospectively obtained from the Medical Birth Registry of Norway and childhood health records. Associations between birth weight, BMI, and growth were evaluated by fitting linear mixed models with repeated measures of BMC and aBMD at ages 15 to 17 and 18 to 20 years as the outcome. In crude analysis, a significant positive association (p < 0.05) with TB BMC was observed per 1 SD score increase in birth weight, observed in both sexes. Higher rate of length growth, conditioned on earlier size, from birth to age 2.5 years, and higher rate of weight gain from ages 6.0 to 16.5 years, conditioned on earlier size and concurrent height growth, revealed stronger associations with bone accrual at ages 15 to 20 years compared with other ages. Compared with being normal weight, overweight/obesity at age 16.5 years was associated with higher aBMD Z‐scores: β coefficient (95% confidence interval [CI]) of 0.78 (0.53, 1.03) and 1.08 (0.85, 1.31) in girls, 0.63 (0.42, 0.85) and 0.74 (0.54, 0.95) in boys at TH and TB, respectively. Similar associations were found for BMC. Being underweight was consistently negatively associated with bone parameters in adolescence. In conclusion, birth weight influences adolescent bone mass but less than later growth and BMI in childhood and adolescence. © 2018 The Authors. JBMR Plus Published by Wiley Periodicals, Inc. on behalf of the American Society for Bone and Mineral Research