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  • 1.
    Ahorsu, Daniel K.
    et al.
    Department of Rehabilitation Sciences, the Hong Kong Polytechnic University, Hung Hom, Hong Kong.
    Lin, Chung-Ying
    Department of Rehabilitation Sciences, the Hong Kong Polytechnic University, Hung Hom, Hong Kong.
    Imani, Vida
    Pediatric Health Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
    Griffiths, Mark D.
    International Gaming Research Unit, Psychology Department, Nottingham Trent University, Nottingham, UK.
    Su, Jian-An
    Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan.
    Latner, Janet D.
    Department of Psychology, University of Hawaii at Manoa, Honolulu, Hawaii.
    Marshall, Rachel D.
    Department of Psychology, University of Hawaii at Manoa, Honolulu, Hawaii.
    Pakpour, Amir H.
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Avd. för omvårdnad. Social Determinants of Health Research Center, Research Institute for Prevention of Non-Communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran.
    A prospective study on the link between weight-related self-stigma and binge eating: Role of food addiction and psychological distress2020Ingår i: International Journal of Eating Disorders, ISSN 0276-3478, E-ISSN 1098-108XArtikel i tidskrift (Refereegranskat)
    Abstract [en]

    OBJECTIVES: This prospective study investigated the link between weight-related self-stigma and binge eating by (a) examining the temporal association between weight-related self-stigma and binge eating; (b) investigating the mediating role of food addiction in the association between weight-related self-stigma and binge eating; and (c) examining the mediating role of psychological distress in the association between weight-related self-stigma and binge eating.

    METHOD: Participants comprised 1,497 adolescents (mean = 15.1 years; SD = 6.0). Body mass index and weight bias were assessed at baseline; psychological distress (i.e., depression, anxiety, and stress) assessed and food addiction at 3 months; and binge eating at 6 months. The mediation model was analyzed using Model 4 in the PROCESS macro for SPSS with 10,000 bootstrapping resamples.

    RESULTS: There was no significant direct association between weight-related self-stigma and binge eating. However, food addiction and psychological distress significantly mediated the association between weight-related self-stigma and binge eating.

    DISCUSSION: These findings highlight the indirect association between weight-related self-stigma and binge eating via food addiction and psychological distress. Consequently, intervention programs targeting food addiction and psychological distress among adolescents may have significant positive effects on outcomes for weight-related self-stigma and binge eating. The findings will be beneficial to researchers and healthcare professionals working with adolescents during this critical developmental period.

  • 2.
    Johansson, Linda
    et al.
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Avd. för omvårdnad. Högskolan i Jönköping, Hälsohögskolan, HHJ, Institutet för gerontologi. Högskolan i Jönköping, Hälsohögskolan, HHJ. ARN-J (Aging Research Network - Jönköping).
    Wijk, Helle
    Sahlgrenska Academy, Institute of Health and Care Sciences, Gothenburg, Sweden.
    Christensson, Lennart
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Avd. för omvårdnad. Högskolan i Jönköping, Hälsohögskolan, HHJ. ARN-J (Aging Research Network - Jönköping).
    Improving Nutritional Status of Older Persons with Dementia Using a National Preventive Care Program2017Ingår i: The Journal of Nutrition, Health & Aging, ISSN 1279-7707, E-ISSN 1760-4788, Vol. 21, nr 3, s. 292-298Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    OBJECTIVE: The aim of the study was to investigate the outcome of change in body weight associated with use of a structured preventive care process among persons with dementia assessed as at risk of malnutrition or malnourished. The preventive care process is a pedagogical model used in the Senior Alert (SA) quality register, where nutrition is one of the prioritized areas and includes four steps: assessment, analysis of underlying causes, actions performed and outcome.

    DESIGN: An analysis of data from SA with a pre-post design was performed.

    SETTING: The participants were living in ordinary housing or special housing in Sweden.

    PARTICIPANTS: 1912 persons, 65 years and older, registered in both SA and the dementia quality register Svedem were included.

    INTERVENTION: A national preventive care program including individualized actions.

    MEASUREMENTS: The Mini Nutritional Assessment-Short Form was used to assess nutritional status at baseline. Body weight was measured during baseline and follow-up (7-106 days after baseline).

    RESULTS: 74.3% persons were malnourished or at risk of malnutrition. Those at risk of malnutrition or malnourished who were registered in all four steps of the preventive care process, increased in body weight from baseline (Md 60.0 kg) to follow-up (Md 62.0 kg) (p=0.013). In those with incomplete registration no increase in body weight was found.

    CONCLUSION: Using all steps in the structured preventive care process seems to improve nutritional status of persons with dementia assessed as at risk of malnutrition or malnourished. This study contributes to the development of evidence-based practice regarding malnutrition and persons with dementia.

  • 3.
    Miri, Seyedeh Fatemeh
    et al.
    Qazvin University of Medical Sciences, Qazvin, Iran.
    Javadi, Maryam
    Qazvin University of Medical Sciences, Qazvin, Iran.
    Lin, Chung-Ying
    Hong Kong Polytechnic University, Kowloon, Hong Kong.
    Griffiths, Mark D.
    Nottingham Trent University, Nottingham, United Kingdom.
    Björk, Maria
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Avd. för omvårdnad. Högskolan i Jönköping, Hälsohögskolan, HHJ. CHILD.
    Pakpour, Amir H.
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Avd. för omvårdnad. Social Determinants of Health Research Center, Qazvin University of Medical Sciences, Qazvin, Iran.
    Effectiveness of cognitive-behavioral therapy on nutrition improvement and weight of overweight and obese adolescents: A randomized controlled trial2019Ingår i: Diabetes & Metabolic syndrome: clinical Research & Reviews, ISSN 1871-4021, E-ISSN 1878-0334, Vol. 13, nr 3, s. 2190-2197Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Aim: To assess the effectiveness of a cognitive-behavioral treatment (CBT) program on weight reduction among Iranian adolescents who are overweight. Methods: Using a randomized controlled trial design, 55 adolescents who were overweight (mean [SD] age = 14.64 [1.69] years; zBMI = 2.18 [0.65]) were recruited in the CBT program and 55 in the treatment as usual (TAU; mean age = 14.88 [1.50]; zBMI = 2.09 [0.57]) group. All the participants completed several questionnaires (Child Dietary Self-Efficacy Scale; Weight Efficacy Lifestyle questionnaire; Physical Exercise Self-Efficacy Scale; Pediatric Quality of Life Inventory; and self-reported physical activity and diet) and had their anthropometrics measured (height, weight, waist and hip circumferences, and body fat). Results: The CBT group consumed significantly more fruits and juice, vegetables, and dairy in the 6-month follow-up as compared with the TAU group (p-values <0.001). The CBT group consumed significantly less sweet snacks, salty snacks, sweet drinks, sausages/processed meat, and oils in the six-month follow-up compared with the TAU group (p-values<0.001). Additionally, the waist circumference, BMI, waist-hip ratio, and fat mass were significantly decreased in the CBT group in the six-month follow-up compared with the TAU group (p-values<0.005). The CBT group significantly improved their psychosocial health, physical activity, and health-related quality of life (p-values<0.001). Conclusion: The CBT program showed its effectiveness in reducing weight among Iranian adolescents who were overweight. Healthcare providers may want to adopt this program to treat excess weight problems among adolescents. 

    Publikationen är tillgänglig i fulltext från 2020-05-22 00:00
  • 4.
    Pakpour, Amir H.
    et al.
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Avd. för omvårdnad. Social Determinants of Health Research Center, Qazvin University of Medical Sciences, Qazvin, Iran.
    Tsai, Mengche
    National Cheng Kung University Hospital, Tainan, Taiwan.
    Lin, Yi Ching
    National Taipei University of Education, Taipei, Taiwan.
    Strong, Carol
    National Cheng Kung University, Tainan, Taiwan.
    Latner, Janet D.
    University of Hawaii at Manoa, Honolulu, United States.
    Fung, Xavier C.C.
    Hong Kong Polytechnic University, Kowloon, Hong Kong.
    Lin, Chung-Ying
    Hong Kong Polytechnic University, Kowloon, Hong Kong.
    Tsang, Hector W.H.
    Hong Kong Polytechnic University, Kowloon, Hong Kong.
    Psychometric properties and measurement invariance of the Weight Self-Stigma Questionnaire and Weight Bias Internalization Scale in children and adolescents2019Ingår i: International Journal of Clinical and Health Psychology, ISSN 1697-2600, E-ISSN 2174-0852, Vol. 19, nr 2, s. 150-159Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background/Objective: Given the negative consequences of weight bias, including internalized weight stigma, on health outcomes, two instruments—the Weight Self-Stigma Questionnaire (WSSQ) and Weight Bias Internalization Scale (WBIS)—have been developed. However, their psychometric properties are yet to be tested for Asian pediatric populations.

    Method: Participants aged 8 to 12 years (N = 287; 153 boys) completed the WSSQ and the WBIS, and they were classified into either a group with overweight or a group without overweight based on self-reported weight and height.

    Results: Both WSSQ and WBIS had their factor structures supported by confirmatory factor analyses (CFAs). The measurement invariance of two-factor structure was further supported for WSSQ across gender and weight status. The measurement invariance of single-factor structure was supported for WBIS across gender but not across weight status.

    Conclusions: WSSQ and WBIS were both valid to assess the internalization of weight bias. However, the two instruments demonstrated different properties and should be applied in different situations. 

  • 5. Silventoinen, K.
    et al.
    Jelenkovic, A.
    Sund, R.
    Yokoyama, Y.
    Hur, Y. -M
    Cozen, W.
    Hwang, A. E.
    Mack, T. M.
    Honda, C.
    Inui, F.
    Iwatani, Y.
    Watanabe, M.
    Tomizawa, R.
    Pietilainen, K. H.
    Rissanen, A.
    Siribaddana, S. H.
    Hotopf, M.
    Sumathipala, A.
    Rijsdijk, F.
    Tan, Q.
    Zhang, D.
    Pang, Z.
    Piirtola, M.
    Aaltonen, S.
    Oncel, S. Y.
    Aliev, F.
    Rebato, E.
    Hjelmborg, J. B.
    Christensen, K.
    Skytthe, A.
    Kyvik, K. O.
    Silberg, J. L.
    Eaves, L. J.
    Cutler, T. L.
    Ordonana, J. R.
    Sanchez-Romera, J. F.
    Colodro-Conde, L.
    Song, Y. -M
    Yang, S.
    Lee, K.
    Franz, C. E.
    Kremen, W. S.
    Lyons, M. J.
    Busjahn, A.
    Nelson, T. L.
    Whitfield, K. E.
    Kandler, C.
    Jang, K. L.
    Gatz, M.
    Butler, D. A.
    Stazi, M. A.
    Fagnani, C.
    D'Ippolito, C.
    Duncan, G. E.
    Buchwald, D.
    Martin, N. G.
    Medland, S. E.
    Montgomery, G. W.
    Jeong, H. -U
    Swan, G. E.
    Krasnow, R.
    Magnusson, P. K. E.
    Pedersen, N. L.
    Dahl Aslan, Anna K.
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Institutet för gerontologi. Högskolan i Jönköping, Hälsohögskolan, HHJ. ARN-J (Aging Research Network - Jönköping). Departments of Social Research, Research Programs Unit, University of Helsinki, Helsinki, Finland.
    McAdams, T. A.
    Eley, T. C.
    Gregory, A. M.
    Tynelius, P.
    Baker, L. A.
    Tuvblad, C.
    Bayasgalan, G.
    Narandalai, D.
    Spector, T. D.
    Mangino, M.
    Lachance, G.
    Burt, S. A.
    Klump, K. L.
    Harris, J. R.
    Brandt, I.
    Nilsen, T. S.
    Krueger, R. F.
    McGue, M.
    Pahlen, S.
    Corley, R. P.
    Huibregtse, B. M.
    Bartels, M.
    Van Beijsterveldt, C. E. M.
    Willemsen, G.
    Goldberg, J. H.
    Rasmussen, F.
    Tarnoki, A. D.
    Tarnoki, D. L.
    Derom, C. A.
    Vlietinck, R. F.
    Loos, R. J. F.
    Hopper, J. L.
    Sung, J.
    Maes, H. H.
    Turkheimer, E.
    Boomsma, D. I.
    Sørensen, T. I. A.
    Kaprio, J.
    Differences in genetic and environmental variation in adult BMI by sex, age, time period, and region: An individual-based pooled analysis of 40 twin cohorts2017Ingår i: American Journal of Clinical Nutrition, ISSN 0002-9165, E-ISSN 1938-3207, Vol. 106, nr 2, s. 457-466Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Genes and the environment contribute to variation in adult body mass index [BMI (in kg/m2)], but factors modifying these variance components are poorly understood.

    Objective: We analyzed genetic and environmental variation in BMI between men and women from young adulthood to old age from the 1940s to the 2000s and between cultural-geographic regions representing high (North America and Australia), moderate (Europe), and low (East Asia) prevalence of obesity.

    Design: We used genetic structural equation modeling to analyze BMI in twins ≥20 y of age from 40 cohorts representing 20 countries (140,379 complete twin pairs).

    Results: The heritability of BMI decreased from 0.77 (95% CI: 0.77, 0.78) and 0.75 (95% CI: 0.74, 0.75) in men and women 20-29 y of age to 0.57 (95% CI: 0.54, 0.60) and 0.59 (95% CI: 0.53, 0.65) in men 70-79 y of age and women 80 y of age, respectively. The relative influence of unique environmental factors correspondingly increased. Differences in the sets of genes affecting BMI in men and women increased from 20-29 to 60-69 y of age. Mean BMI and variances in BMI increased from the 1940s to the 2000s and were greatest in North America and Australia, followed by Europe and East Asia. However, heritability estimates were largely similar over measurement years and between regions. There was no evidence of environmental factors shared by co-twins affecting BMI.

    Conclusions: The heritability of BMI decreased and differences in the sets of genes affecting BMI in men and women increased from young adulthood to old age. The heritability of BMI was largely similar between cultural-geographic regions and measurement years, despite large differences in mean BMI and variances in BMI. Our results show a strong influence of genetic factors on BMI, especially in early adulthood, regardless of the obesity level in the population.

  • 6.
    Sindi, Shireen
    et al.
    Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
    Kåreholt, Ingemar
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Institutet för gerontologi. Högskolan i Jönköping, Hälsohögskolan, HHJ. ARN-J (Aging Research Network - Jönköping). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
    Eskelinen, Marjo
    Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, Kuopio, Finland.
    Hooshmand, Babak
    Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
    Lehtisalo, Jenni
    Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland.
    Soininen, Hilkka
    Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, Kuopio, Finland.
    Ngandu, Tiia
    Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
    Kivipelto, Miia
    Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
    Healthy dietary changes in midlife are associated with reduced dementia risk later in life2018Ingår i: Nutrients, ISSN 2072-6643, E-ISSN 2072-6643, Vol. 10, nr 11, artikel-id 1649Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Diet is an important modifiable lifestyle factor related to dementia risk. Yet, the role of midlife dietary changes is unclear. The goal is to investigate whether midlife healthy dietary changes are associated with late-life dementia risk. Data were collected within the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) population-based cohort study (n = 2000) (mean baseline age = 56 years). Participants returned for two late-life re-examinations (mean age = 70 and 78 years). Self-reported midlife diet was measured in a sub-sample (n = 341) (mean total follow-up = 16.8 years). Changes in specific dietary components (fats, vegetables, sugar, salt) were measured in midlife. Dementia diagnoses were ascertained with detailed examinations. Analyses adjusted for potential confounders. Total midlife healthy dietary changes (improving quality of fats, increasing vegetables, decreasing sugar and salt) were associated with a reduced risk of dementia (fully adjusted odds ratio (OR) 0.41, 95% confidence interval (CI) = 0.20–0.85). In contrast, when each factor was assessed individually, associations were not significant. This study is the first to show that beneficial midlife dietary changes are associated with a reduced dementia risk later in life. The results highlight the importance of targeting dietary patterns, where various food items may have synergistic effects. 

  • 7.
    Virtanen, M.
    et al.
    School of Educational Sciences and Psychology, University of Eastern Finland, Joensuu, Finland.
    Jokela, M.
    Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.
    Lallukka, T.
    Finnish Institute of Occupational Health, Helsinki, Finland.
    Magnusson Hanson, L.
    Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Pentti, J.
    Department of Public Health, Clinicum, University of Helsinki, Helsinki, Finland.
    Nyberg, S. T.
    Department of Public Health, Clinicum, University of Helsinki, Helsinki, Finland.
    Alfredsson, L.
    Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
    Batty, G. D.
    Department of Epidemiology & Public Health, University College London, London, United Kingdom.
    Casini, A.
    IPSY, Université catholique de Louvain (UCLouvain), Louvain-la-Neuve & School of Public Health, Université libre de Bruxelles (ULB), Brussels, Belgium.
    Clays, E.
    Department of Public Health, Ghent University, Ghent, Belgium.
    DeBacquer, D.
    Department of Public Health, Ghent University, Ghent, Belgium.
    Ervasti, J.
    Finnish Institute of Occupational Health, Helsinki, Finland.
    Fransson, Eleonor I.
    Högskolan i Jönköping, Hälsohögskolan, HHJ, Avd. för naturvetenskap och biomedicin. Högskolan i Jönköping, Hälsohögskolan, HHJ. ADULT. Högskolan i Jönköping, Hälsohögskolan, HHJ. ARN-J (Aging Research Network - Jönköping). Högskolan i Jönköping, Hälsohögskolan, HHJ, Institutet för gerontologi. Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Halonen, J. I.
    Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Head, J.
    Department of Epidemiology & Public Health, University College London, London, United Kingdom.
    Kittel, F.
    IPSY, Université catholique de Louvain (UCLouvain), Louvain-la-Neuve & School of Public Health, Université libre de Bruxelles (ULB), Brussels, Belgium.
    Knutsson, A.
    Department of Health Sciences, Mid Sweden University, Sundsvall, Sweden.
    Leineweber, C.
    Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Nordin, M.
    Department of Psychology, Umeå University, Umeå, Sweden.
    Oksanen, T.
    Finnish Institute of Occupational Health, Helsinki, Finland.
    Pietiläinen, O.
    Department of Public Health, Clinicum, University of Helsinki, Helsinki, Finland.
    Rahkonen, O.
    Department of Public Health, Clinicum, University of Helsinki, Helsinki, Finland.
    Salo, P.
    Finnish Institute of Occupational Health, Helsinki, Finland.
    Singh-Manoux, A.
    Department of Epidemiology & Public Health, University College London, London, United Kingdom.
    Stenholm, S.
    Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland.
    Suominen, S. B.
    Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland.
    Theorell, T.
    Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Vahtera, J.
    Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland.
    Westerholm, P.
    Occupational and Environmental Medicine, Uppsala University, Uppsala, Sweden.
    Westerlund, H.
    Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Kivimäki, M.
    Department of Public Health, Clinicum, University of Helsinki, Helsinki, Finland.
    Long working hours and change in body weight: analysis of individual-participant data from 19 cohort studies2019Ingår i: International Journal of Obesity, ISSN 0307-0565, E-ISSN 1476-5497Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objective:

    To examine the relation between long working hours and change in body mass index (BMI).

    Methods:

    We performed random effects meta-analyses using individual-participant data from 19 cohort studies from Europe, US and Australia (n = 122,078), with a mean of 4.4-year follow-up. Working hours were measured at baseline and categorised as part time (&lt;35 h/week), standard weekly hours (35–40 h, reference), 41–48 h, 49–54 h and ≥55 h/week (long working hours). There were four outcomes at follow-up: (1) overweight/obesity (BMI ≥ 25 kg/m2) or (2) overweight (BMI 25–29.9 kg/m2) among participants without overweight/obesity at baseline; (3) obesity (BMI ≥ 30 kg/m2) among participants with overweight at baseline, and (4) weight loss among participants with obesity at baseline.

    Results:

    Of the 61,143 participants without overweight/obesity at baseline, 20.2% had overweight/obesity at follow-up. Compared with standard weekly working hours, the age-, sex- and socioeconomic status-adjusted relative risk (RR) of overweight/obesity was 0.95 (95% CI 0.90–1.00) for part-time work, 1.07 (1.02–1.12) for 41–48 weekly working hours, 1.09 (1.03–1.16) for 49–54 h and 1.17 (1.08–1.27) for long working hours (P for trend &lt;0.0001). The findings were similar after multivariable adjustment and in subgroup analyses. Long working hours were associated with an excess risk of shift from normal weight to overweight rather than from overweight to obesity. Long working hours were not associated with weight loss among participants with obesity.

    Conclusions:

    This analysis of large individual-participant data suggests a small excess risk of overweight among the healthy-weight people who work long hours. 

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