不同代谢肥胖表型与缺血性卒中的相关性研究

目的探讨不同代谢肥胖表型与缺血性卒中(ischemic stroke,IS)的关系,以期对不同风险人群提供更有针对性的干预措施。方法采用横断面研究设计,对北京市社区居民进行问卷调查,血生化等指标检测。根据代谢正常或异常及体重正常或肥胖组合形成的四种代谢肥胖表型将居民进行表型分类,分析不同表型与IS的相关性。结果共纳入3159名研究对象,其中有1106人患有IS。多因素Logistic回归显示,调整潜在混杂因素后,与代谢正常体重正常组相比,代谢异常体重正常和代谢异常肥胖组的IS风险增加,OR分别为1.76(95%CI:1.33~2.34)和2.03(95%CI:1.52~2.72);而代谢正常肥胖组与其差异不具有统计学意义。结论代谢异常体重正常表型和代谢异常肥胖表型可能是IS的危险因素,而代谢正常肥胖表型与代谢正常体重正常表型的IS风险无差异,提示代谢异常相较肥胖可能对IS风险影响更大。     

中国中老年人肥胖表型与高血压风险关联队列研究

目的探讨肥胖表型与我国中老年人高血压发病风险的关联性，为我国中老年人群高血压的防治提供参考依据。方法基于中国健康与养老追踪调查（CHALRS）数据，将参加2011年和2015年2次调查且基线年龄≥45岁的中老年人群纳入研究对象。肥胖表型根据体重和代谢状态分为代谢正常非超重/肥胖组（MHNO）、代谢正常超重/肥胖组（MHO）、代谢异常非超重/肥胖组（MANO）及代谢异常超重/肥胖组（MAO）。采用Cox比例风险回归模型分析各肥胖表型与高血压发病风险的关联性。结果共纳入3 781个研究对象，其中男性1 775人（46.95%），平均年龄为（57.76±8.57）岁。经过4年随访，高血压发病率为22.59%，控制性别、年龄等混杂因素后，MHO、MANO和MAO组高血压的发病风险显著高于MHNO组（均P<0.01），其HR值和95%CI分别为1.35（1.11~1.63）、1.51（1.15~1.97）、2.00（1.68~2.38）。结论MHO表型和代谢不健康表型（MAO/MANO）均会显著增加中老年人高血压发病风险。     

西安市成年肥胖人群膳食多样化与肥胖代谢表型的关联性

  目的  了解西安市成年肥胖人群的膳食多样化与肥胖代谢表型的关系。  方法  数据来源于西北区域自然人群队列中西安城市队列人群的基线调查,选择具有血样且反映代谢表型指标完整的肥胖人群(BMI≥28 kg/m2)1 069例。根据代谢综合征联合国际多学会联合声明的标准定义肥胖代谢表型。参考膳食多样化得分的评价规则,结合中国居民膳食指南构建膳食多样化指标。运用logistic回归分析模型探讨膳食多样化与肥胖代谢表型关系。  结果  研究对象的膳食多样化存在性别差异,不同肥胖代谢表型者的膳食多样化总分差异有统计学意义。与代谢正常肥胖者相比,代谢异常者膳食多样化得分较低[(4.20±1.88)vs.(4.51±1.97), P=0.010],其畜禽肉、鱼虾、蛋、奶及奶制品的摄入较低。控制混杂因素后,与膳食多样化得分最低的肥胖者相比,得分最高者患代谢异常的风险降低38%(OR=0.62, 95% CI: 0.40~0.96),膳食多样化得分每增加一个单位,肥胖者的代谢异常风险降低10% (OR=0.90, 95%CI: 0.82~0.99),这种关联在女性和强体力活动的肥胖人群中更明显。  结论  膳食多样化增加与成年肥胖人群代谢异常风险减少有关联。采取多样化膳食可能是预防和控制肥胖人群代谢异常的重要营养干预措施。     

无锡市社区人群不同肥胖和代谢类型现患情况及影响因素北大核心

目的探究江苏省无锡市社区人群中不同肥胖和代谢类型的现患情况及其影响因素。方法以整群随机抽样方法抽取无锡市18周岁及以上、居住满6个月及以上常住居民为研究对象,进行问卷调查、体格检查和血生化检测,分析4种不同肥胖和代谢类型患病情况,采用Logistic回归分析不同肥胖和代谢类型患病的影响因素。结果本研究共纳入研究对象8102人,体重正常代谢正常(MHNW)占37.33%,体重正常代谢肥胖(MONW)、代谢正常性超重/肥胖(MHO)和代谢异常性超重/肥胖(MAO)的年龄标化患病率分别为8.43%、23.78%、23.93%。在体重正常人群中,MONW的患病与年龄增大、水果摄入不足(OR=1.44,95%CI:1.14~1.82)以及豆制品摄入不足(OR=1.28,95%CI:1.08~1.51)有关。在超重/肥胖人群中,年龄增大、过度饮酒(OR=1.25,95%CI:1.05~1.48)、吸烟(OR=1.31,95%CI:1.09~1.58)是MAO人群的患病的影响因素。结论加强对戒烟、限酒、增加豆制品和水果摄入的健康促进,体重正常者应加强豆制品和水果摄入以防向MONW转变;超重/肥胖者更要戒烟、限酒以防转变为MAO。     

高血压儿童青少年肥胖与颈动脉内中膜厚度的关系

探讨儿童青少年肥胖与颈动脉内中膜厚度(carotid intima-media thickness,cIMT)的关系,为儿童青少年心血管疾病预防提供依据.方法 采用方便整群抽样方法选取济南市城区289名6~17岁中小学生,测量身高、体重、血压和cIMT,并采用Logistic回归模型分析肥胖和cIMT的关系.结果 男生肥胖组cIMT水平和增厚检出率均高于非肥胖组(P值均<0.05);女生肥胖组与非肥胖组cIMT水平和增厚检出率差异无统计学意义(P值均>0.05);调整性别、年龄和血压后,多因素Logistic回归分析表明,总人群肥胖组cIMT增厚风险OR值及95%CI为3.03(95%CI=1.11~8.28);男女生肥胖组OR值及95%CI为4.32(95%CI=1.23~15.21),1.45(95% CI=0.23~9.37).结论 肥胖可能增加儿童青少年的cI-MT水平和cIMT增厚检出率.应采取有效措施预防和控制儿童青少年肥胖,降低儿童青少年血管结构异常风险.     

儿童期超重肥胖与血管结构损害关系

目的探讨儿童期超重肥胖与血管结构损害的关系,为成人心血管病儿童期危险因素的防控提供科学依据。方法于2017年11月—2018年1月采用方便整群抽样方法,在山东省淄博市桓台县抽取1所公立小学共1 319名6～11岁儿童作为研究对象,根据体质指数(BMI)将其分为正常体重组、超重组和肥胖组;采用协方差分析比较不同BMI分组儿童的颈动脉内–中膜厚度(carotid intima-media thickness,cIMT)差异,并应用多因素非条件logistic回归模型分析儿童期超重肥胖对血管结构损害的影响。结果在调整了性别、年龄、每日睡眠时间、每日视屏时间、每日蔬菜水果摄入频率、每周碳酸饮料摄入频率、每日体力活动时间、收缩压和舒张压等混杂因素后,协方差分析结果显示,超重组和肥胖组儿童的cIMT分别为(0.469±0.083)和(0.502±0.093)mm,均高于正常体重组儿童的(0.453±0.068)mm(均P 0.05);超重组和肥胖组男童的cIMT分别为(0.485±0.082)和(0.521±0.092)mm,均高于正常体重组男童的(0.467±0.070)mm(均P 0.05);超重组和肥胖组女童的c IMT分别为(0.449±0.077)和(0.480±0.088)mm,均高于正常体重组女童的(0.437±0.064)mm(均P 0.05)。多因素非条件logistic回归分析结果显示,超重组和肥胖组儿童发生cIMT增厚的风险分别为正常体重组儿童的3.38倍(OR=3.38,95%CI=1.67～6.86)和17.39倍(OR=17.39,95%CI=9.97～30.35);超重组和肥胖组男童发生c IMT增厚的风险分别为正常体重组男童的6.41倍(OR=6.41,95%CI=1.61～25.56)和41.73倍(OR=41.73,95%CI=12.58～138.41);超重组和肥胖组女童发生cIMT增厚的风险分别为正常体重组女童的3.02倍(OR=3.02,95%CI=1.24～7.36)和12.38倍(OR=12.38,95%CI=6.16～24.86)。结论超重和肥胖可能是儿童期血管结构损害的重要危险因素,预防和控制儿童期超重肥胖可能会降低早期血管结构的损害。     

济南市儿童青少年不同肥胖类型与代谢异常的关系

探讨儿童青少年不同肥胖类型与代谢异常的关系,为儿童青少年心血管病危险因素的防制提供科学依据.方法 选取济南市城区1 170名7~17岁儿童青少年,测量身高、体重、腰围(WC)和血压,同时测定空腹血糖、三酰甘油、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇等血生化指标,分析不同肥胖类型与代谢异常的关系.结果 儿童青少年各类生化指标平均水平(血糖、总胆固醇除外)和代谢异常检出率(高血糖除外)在不同肥胖类型组的差异均有统计学意义(P值均<0.05),且表现为复合型肥胖组>全身性肥胖或中心性肥胖组>体质量指数(BMI)和WC均正常组.以BMI与WC均正常为对照组,任意肥胖类型组以及复合型肥胖组罹患各类代谢异常的风险均较高.以预测代谢异常≥2个为例,任意肥胖类型的风险OR值为1.50(95%CI=0.78~ 2.90),复合型肥胖的风险OR值为7.84(95%CI=5.00~ 12.30).结论 在学生体检工作中,应联合使用BMI和WC来判定儿童肥胖,从而更有效地防控儿童青少年心血管病危险因素.     

高血压合并肥胖影响因素分析

目的探讨高血压合并肥胖者的主要影响因素,为高血压合并肥胖的防治提供理论依据。方法以社区医院门诊病人为基础进行病例对照研究,其中以门诊收治的高血压合并肥胖患者372人为病例组,在同一社区人群中选择血压和体重均正常者437人为对照组;对研究对象进行问卷调查和实验室检查。运用单因素与多因素分析方法,探讨高血压合并肥胖者的主要影响因素。结果高血压合并肥胖的发病危险随着年龄的增长而增加,男性高于女性;有家族遗传倾向者发病风险明显增高,父亲肥胖（OR=5.04,95%CI=3.12～8.14）,父亲高血压（OR=2.46,95%CI=1.81～3.35）,母亲肥胖（OR=2.55,95%CI=1.78～3.64）,母亲高血压（OR=2.14,95%CI=1.60～2.86）;膳食口味偏咸（OR=2.45,95%CI=1.82～3.29）与饮酒（OR=1.92,95%CI=1.37～2.68）等行为可以增加发病风险,而坚持骑车或步行上班（OR=0.64,95%CI=0.46～0.89）、饮用牛奶（OR=0.73,95%CI=0.55～0.97）等行为则可降低发病风险。病例组血脂异常率高于对照组（P〈0.01）,提示高血压合并肥胖可增加血脂紊乱的风险。结论将戒烟限酒、减少食盐的摄入量,适量运动、合理膳食作为高血压合并肥胖人群的主要预防措施;家族遗传倾向是高血压与肥胖发病的主要危险因素,应对此类高危人群加强一、二级预防。     

瘦素受体基因Gln223Arg多态性与肥胖的关联研究

目的探讨瘦素受体基因多态性与肥胖发生的关系。方法采用PCR-RFLP对502例肥胖患者、400例体重正常者进行瘦素受体基因Gln223Arg多态性检测。结果肥胖组瘦素受体基因Gln223Arg的GG、GA和AA基因型表达频率分别为0.777、0.197及0.026。单因素分析显示携带AA基因型与携带GG基因型相比,发生肥胖的风险为OR=0.478,P=0.043。多因素分析表明,瘦素受体基因多态性、年龄>65岁、吸烟以及口味偏重与肥胖发生的相对危险度分别为:OR=1.36,95%CI:0.999~1.849,P=0.05;OR=0.55,95%CI:0.366~0.825,P=0.004;OR=1.475,95%CI:1.064~2.045,P=0.02;OR=1.506,95%CI:1.042~2.176,P=0.029。结论瘦素受体基因Gln223Arg多态性可能与肥胖发生有关。     

黔东南侗族人群骨密度调查及相关影响因素研究

目的 了解当地居民骨密度流行现状及影响因素。方法 多阶段抽样方法抽取黔东南侗族居民5792名进行问卷调查、身高、体重测量，并采用超声骨密度仪测量骨密度。使用SPSS22.0对数据进行描述性分析、x2检验和多因素非条件logistic回归分析，探讨骨密度影响因素。结果 最终纳入5322人，黔东南侗族人群骨量减少、骨质疏松检出率分别为33.84%、2.76%，男性均高于女性。不同性别、年龄、文化程度、生活习惯、职业的居民骨质情况检出率不同（P<0.05）。经logistic回归分析，高龄（OR=1.746，95%CI=1.635~1.864）、男性（OR=2.213，95%CI=1.829~2.679）、初中（OR=1.395，95%CI=1.069~1.798）和高中文化（OR=1.292，95%CI=1.066~1.565）检出骨量减少的风险高，离退休（OR=0.681，95%CI=0.508~0.911）、体力劳动人员（OR=0.702，95%CI=0.595~0.828）、超重者（OR=0.782，95%CI=0.681~0.898）、戒烟者（OR=0.695，95%CI=0.494~0.977）检出骨量减少风险低；高龄（OR=1.903，95%CI=1.567~2.311）、男性（OR=8.744，95%CI=5.290~14.451）、体重过低（OR=3.046，95%CI=1.622~5.718）、体重肥胖（OR=3.285，95%CI=1.975~5.464）检出骨质疏松风险高，初中文化（OR=0.511，95%CI=0.287~0.910）骨质疏松检出风险低。结论 贵州省黔东南侗族人群的骨量减少检出率较高，年龄、BMI、性别、文化程度可能是骨质疏松和骨量减少的影响因素。     

代谢性肥胖与高血压发病的队列研究

  目的  探讨代谢性肥胖与高血压发病的关系,为人群高血压防制提供理论依据。  方法  采用前瞻性队列研究设计,于2009年在江苏省宜兴市官林、徐舍2个乡镇采用整群抽样方法纳入4 128名成人进行流行病学基线调查。排除基线2 012名高血压病例,截至2020年7月对2 116名非高血压对象进行高血压发病随访。根据体重和代谢状态将研究对象分为4组:代谢正常体重正常(metabolically healthy and normal weight, MHNW)、代谢正常超重/肥胖(metabolically healthy overweight/obesity, MHO)、代谢异常体重正常(metabolically unhealthy and normal weight, MUNW)、代谢异常超重/肥胖(metabolically unhealthy overweight/obesity, MUO)。采用Cox比例风险回归模型对代谢性肥胖与高血压发病关联进行分析,进一步做分层分析、异质性检验及相加与相乘交互作用分析;排除随访第一年发病的高血压对象、排除偏瘦人群进行敏感性分析。  结果  共随访到新发高血压637例,超重肥胖及代谢异常联合相较于体重正常代谢正常的人群归因危险度(population attributable risk, PAR)及PAR%分别为17.4%、57.93%。Cox回归分析结果显示:与MHNW相比,MHO、MUNW、MUO三组的高血压发病风险增加均有统计学意义,调整后的HR(95% CI)值分别为1.29(1.08~1.56)、1.48(1.09~2.01)、1.70(1.37~2.11),并呈风险递增的趋势(均有P < 0.001)。分层分析和异质性检验结果显示:女性MUO的高血压发病风险(调整HR:2.14)高于男性MUO(调整HR:1.22),P_{异质性检验}= 0.017。相乘交互作用分析结果显示:性别与代谢状态之间存在相乘交互作用,调整后的HR(95% CI)值为1.53(1.06~2.22),P=0.024。排除随访第一年高血压发病的对象或排除偏瘦人群进行敏感性分析,关联强度无明显变化。  结论  代谢性肥胖增加人群高血压发病风险,尤其在女性人群中风险更高。因此,对超重肥胖及代谢异常相关人群进行主动健康干预预防高血压具有十分重要意义。     

Metabolically healthy overweight/obesity and cancer risk: A representative cohort study in Taiwan

ObjectiveMany cancers are caused by overweight; however, cancer risk varies among individuals with obesity. Few studies are addressing the relationship between metabolic obesity phenotypes and cancer. This study investigates the association between metabolically healthy overweight (MHOW) or metabolically healthy obesity (MHO) and cancer incidence.MethodsIn a nationwide, representative community-based prospective cohort study, 5734 Taiwanese adults were classified into eight phenotypes according to body mass index (underweight <18.5; normal weight 18.5–23.9; overweight 24–26.9; and obese ≥27 kg/m²) and metabolic status (healthy/unhealthy). Participants with healthy cardiometabolic blood profiles included in the metabolic syndrome criteria and an absence of hypertension, diabetes, and hyperlipidemia were considered metabolically healthy. We used the Cox proportional hazards models to estimate the adjusted hazard ratio (HR) and 95% confidence intervals (95% CI).ResultsDuring 73,389 person-years of follow-up, 428 incident cancers were identified. Compared to the participants with metabolically healthy normal weight, participants with MHOW (adjusted HR 1.39, 95% CI, 0.90–2.13) or MHO (adjusted HR 1.07, 95% CI, 0.51–2.22) had a tendency toward a higher risk of cancer. These associations were stronger in MHOW (adjusted HR 1.77, 95% CI, 1.09–2.86) or MHO (adjusted HR 1.39, 95% CI, 0.66–2.93) participants younger than 65 years.ConclusionsThis study was the first to investigate the impact of metabolic obesity phenotype on the incidence of cancer in the Taiwanese population. Even in the absence of metabolic abnormalities, overweight, and obesity may cause a modest increase in the risk of developing cancer.     

Adherence to the DASH,MeDi, and MIND diet scores and the incidence of metabolically unhealthy phenotypes

BackgroundA metabolically unhealthy phenotype is associated with the risk of cardiometabolic events and can be prevented by adherence to healthy dietary patterns. The present study was designed to investigate the association between high adherence to the Dietary Approaches to Stop Hypertension (DASH), Mediterranean (MeDi), and Mediterranean-DASH intervention for neurodegenerative delay (MIND) diet scores and the incidence of metabolically unhealthy phenotypes in adults across body mass index (BMI) categories.MethodsIn this cohort study, 512 subjects with metabolically healthy normal weight (MHNW) at baseline and 787 subjects with metabolically healthy overweight/obesity (MHOW/MHO) at baseline were included. Dietary intake was collected by a validated food frequency questionnaire, and DASH, MeDi, and MIND scores were calculated. The Joint Interim Statement (JIS) criteria were used to define a metabolically unhealthy status.ResultsA total of 137 and 388 subjects with metabolically unhealthy normal weight (MUNW) and metabolically unhealthy overweight/obesity (MUOW/MUO) phenotypes, respectively, were observed, over a mean of 5.91 years of follow-up. The Cox proportional hazard regression indicated participants in the third tertile of the DASH score had a lower risk of the MUNW phenotype (HR: 0.59; 95% CI: 0.37–0.92) than those in the lowest tertile. Similarly, the highest adherence to the MeDi and MIND scores was also linked to a 46% (HR: 0.54; 95% CI: 0.36–0.81) and 47% (HR: 0.53; 95% CI: 0.34–0.83) lower risk of the MUNW phenotype, respectively. As well, there was an inverse relationship between the highest adherence to the DASH (HR: 0.66; 95% CI: 0.50–0.86), MeDi (HR: 0.74; 95% CI: 0.58–0.93), and MIND (HR: 0.57; 95% CI: 0.43–0.74) scores and the risk of MUOW/MUO. There was no interaction between age and the three dietary patterns in relation to a metabolically unhealthy phenotype.ConclusionHigh compliance with the DASH, MeDi, and MIND scores was associated with a lower risk of MUNW. An inverse relationship between these three dietary patterns and the incidence of the metabolically unhealthy phenotype was also observed in individuals who had MHOW/MHO at baseline.     

Body weight dissatisfaction by socioeconomic status among obese, preobese and normal weight women and men: results of the cross-sectional KORA Augsburg S4 population survey

ABSTRACT: BACKGROUND: Body weight dissatisfaction is an important factor in preventing weight gain and promoting weight loss or maintenance. This study focuses on differences in the rates of body weight dissatisfaction among obese, preobese and normal weight women and men by socioeconomic status within a general adult population in Germany. METHODS: Data were analyzed from 4186 adults aged 25 to 74 who participated in a cross-sectional, representative population-based health survey (KORA S4, 1999-2001, Augsburg region/Germany). Body mass was measured anthropometrically and indexed following international standards. Among the 2123 women participating in the survey, 40.3% had a normal weight, 34.9% were preobese, and 24.8% were obese (compared to 25.9%, 51.4% and 22.6% among men, respectively). Body weight dissatisfaction, educational level, household income and occupational status were assessed by computer-aided personal interviewing. An index for socioeconomic status was calculated and categorized into quintiles. Multiple logistic regressions were performed to test for differences in the odds of body weight dissatisfaction across socioeconomic strata in normal weight, preobese and obese groups. Body mass index, age, family status, place of residence and health behaviors were adjusted for. RESULTS: Overall, being dissatisfied with one's body weight was more prevalent in women (48.3%) than in men (33.2%). In the normal weight group, no significant differences in the odds of being dissatisfied were found across socioeconomic groups among women or men. Among preobese men, compared to the lowest socioeconomic stratum, increased odds of being dissatisfied with one's body weight were associated with the highest socioeconomic index group (OR=2.3, 95% CI: 1.4-3.8), middle and high educational level (OR=1.6, 95% CI: 1.1-2.3, and OR=1.9, 95% CI: 1.3-3.7), high income (OR=1.8, 95% CI: 1.2-2.7), and middle and high occupational status (both OR=1.8, 95% CI: 1.2-2.6). Among preobese women, the odds of being dissatisfied were only significantly elevated in those with a middle educational level (OR=1.6, 95% CI: 1.1-2.3). Among obese men, elevated odds were found in the highest socioeconomic index group (OR=3.7, 95% CI: 1.8-7.5) and in those with a high educational level (OR=2.3, 95% CI: 1.3-4.1), high income (OR=2.6, 95% CI: 1.4-4.7), and middle and high occupational status (both OR=2.2, 95% CI: 1.3-3.6). The odds of dissatisfaction among obese women were not associated with socioeconomic status as a whole, but were associated with a high educational level, albeit with a comparatively large confidence interval (OR=3.6, 95% CI: 1.0-12.8). CONCLUSIONS: In Germany, body weight dissatisfaction is more prevalent among obese and preobese men in high socioeconomic status groups, a pattern not found in women. The exception to this is a greater prevalence of dissatisfaction among obese and preobese women with a high educational level (albeit inconsistently). Moreover, there is a social gradient in body weight dissatisfaction, especially in obese men, which may partly explain why obesity is more prevalent in men with low socioeconomic status. It also suggests that they are a target group for obesity care in which body weight satisfaction is an important topic.     

Association of metabolic phenotypes,grip strength and diabetes risk: The 15-year follow-up of The North West Adelaide Health Study,Australia

BackgroundThe association of diabetes risk in the long-term, metabolic phenotypes (MP) and muscle strength is unclear. We aimed to investigate the association between strictly defined MP, grip strength (GS) and diabetes.Material and methodsMP were defined according to BMI and presence of any individual metabolic abnormality for ≥18 years, in participants of the North West Adelaide Health Study (Australia) free of diabetes at baseline. The association of MP and dominant hand GS with incident diabetes over 15-years follow-up and the moderation effect of GS on the association between diabetes and MP were investigated by logistic regression models.ResultsOf 3039 participants followed over 13.3 years (SD 2.6), 236 (7.8%) developed diabetes. Compared to the metabolically healthy (MH) normal weight phenotype, the metabolically unhealthy (MU) overweight (OR 6.15, 95%CI 2.43–15.59) and obese (OR 12.32, 95%CI 4.97–30.52) phenotypes were associated with a high risk of diabetes, but not the MU normal weight (OR 1.73, 95%CI 0.57–5.25), MH overweight (OR 1.15, 95%CI 0.31–4.31) or MH obese phenotypes (OR 0.77, 0.07–8.89). GS was inversely associated with diabetes (OR 0.97, 95% CI 0.95–0.99) and attenuated the risk associated with MU overweight (beta = −0.296, p = 0.039) and MU normal weight (beta = −0.773; p for interaction = 0.009).ConclusionStrictly defined MP (rather than based on metabolic syndrome criteria) and GS, a proxy of muscle strength, might be useful for stratifying the risk of diabetes in the long-term. Improving muscle strength might be an important strategy to reduce diabetes risk.     

Predictors of changes in physical activity in a prospective cohort study of the Danish adult population

AIM: To investigate predictors of changes in physical activity, in a prospective population-based study. METHODS: Data were from the Danish Health Interview Surveys in 1994 and 2000, and included persons between 16 and 64 years of age who answered the questions on physical activity and various covariates in 1994, and who were re-interviewed in 2000. In total 2,957 subjects participated (62% of the original sample). Data were analysed using logistic regression. RESULTS: Predictors of physical inactivity were, for men and women respectively, heavy smoking (odds ratio (OR) 2.07, 95% confidence interval (CI) 1.24-3.48, and OR 2.23, 95% CI 1.34-3.71), poor self-rated health (OR 2.11, 95% CI 1.25-3.58, and OR 1.75, 95% CI 1.10-2.80), and believing that one's own effort has no effect on health (OR 1.86, 95% CI 1.20-2.88, and OR 1.63, 95% CI 1.00-2.65). For men, further predictors for physical inactivity were obesity as compared to normal weight (OR 2.10, 95% CI 1.11-3.98), and being unmarried as compared to being married (OR 2.22, 95% CI 1.40-3.51). The only predictor for becoming physically active among initially sedentary respondents was meeting often with family (p=0.011). CONCLUSIONS: Our results show a number of strong predictors for physical inactivity. Variables of an unhealthy lifestyle tend to cluster in some individuals, and physical inactivity interventions may therefore be more successful if they also address smoking, self-belief, and obesity. Interventions tailored to raise inactive people's level of activity should focus on social support from the family.     

Relationship between various physical activity domains and self-perceived health and obesity in women

The purpose of this study was to determine the relationship between self-perceived health and obesity and recreational, occupational, commuting, and total physical activity in women. The sample included 956 Estonian women aged 18-50. Cross-sectional data were collected in the Estonian Women Physical Activity Study via a mail-out survey in 2008 using the Global Physical Activity Questionnaire and self-reported measures of health indicators. The associations between physical activity and health indicators were examined using multiple logistic regression and were adjusted for potential confounding factors (age, education, and income). The women in the highest occupational physical activity group were significantly less likely to have good health (OR 0.51; CI 0.33-0.77) compared to women with no occupational physical activity. A significant association was observed, however, between being in the highest recreational physical activity group and having better self-perceived health (OR = 2.09, 95% CI 1.36-3.21) and not being obese (BMI ≥ 30) (OR = 0.42, 95% CI 0.21-0.86). A higher total amount of physical activity was not related to better health status or obesity. These findings suggest that the specific domains of physical activity may be more important for self-perceived health and obesity among women than the total amount of physical activity.     

Relationship Between Various Physical Activity Domains and Self-Perceived Health and Obesity in Women

The purpose of this study was to determine the relationship between self-perceived health and obesity and recreational, occupational, commuting, and total physical activity in women. The sample included 956 Estonian women aged 18–50. Cross-sectional data were collected in the Estonian Women Physical Activity Study via a mail-out survey in 2008 using the Global Physical Activity Questionnaire and self-reported measures of health indicators. The associations between physical activity and health indicators were examined using multiple logistic regression and were adjusted for potential confounding factors (age, education, and income). The women in the highest occupational physical activity group were significantly less likely to have good health (OR 0.51; CI 0.33–0.77) compared to women with no occupational physical activity. A significant association was observed, however, between being in the highest recreational physical activity group and having better self-perceived health (OR = 2.09, 95% CI 1.36–3.21) and not being obese (BMI ≥ 30) (OR = 0.42, 95% CI 0.21–0.86). A higher total amount of physical activity was not related to better health status or obesity. These findings suggest that the specific domains of physical activity may be more important for self-perceived health and obesity among women than the total amount of physical activity.     

The Relationship between Dietary Patterns and Metabolic Health in a Representative Sample of Adult Australians

Studies assessing dietary intake and its relationship to metabolic phenotype are emerging, but limited. The aims of the study are to identify dietary patterns in Australian adults, and to determine whether these dietary patterns are associated with metabolic phenotype and obesity. Cross-sectional data from the Australian Bureau of Statistics 2011 Australian Health Survey was analysed. Subjects included adults aged 45 years and over (n = 2415). Metabolic phenotype was determined according to criteria used to define metabolic syndrome (0–2 abnormalities vs. 3–7 abnormalities), and additionally categorized for obesity (body mass index (BMI) ≥30 kg/m² vs. BMI <30 kg/m²). Dietary patterns were derived using factor analysis. Multivariable models were used to assess the relationship between dietary patterns and metabolic phenotype, with adjustment for age, sex, smoking status, socio-economic indexes for areas, physical activity and daily energy intake. Twenty percent of the population was metabolically unhealthy and obese. In the fully adjusted model, for every one standard deviation increase in the Healthy dietary pattern, the odds of having a more metabolically healthy profile increased by 16% (odds ratio (OR) 1.16; 95% confidence interval (CI): 1.04, 1.29). Poor metabolic profile and obesity are prevalent in Australian adults and a healthier dietary pattern plays a role in a metabolic and BMI phenotypes. Nutritional strategies addressing metabolic syndrome criteria and targeting obesity are recommended in order to improve metabolic phenotype and potential disease burden.     

Do Temporal Eating Patterns Differ in Healthy versus Unhealthy Overweight/Obese Individuals?

This study examined whether the temporal patterns of energy and macronutrient intake in early and late eating windows were associated with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) among non-shift workers. A total of 299 overweight/obese non-shift workers (Age: 40.3 ± 6.9 years; 73.6% women; BMI: 31.7 ± 5.0 kg/m²) were recruited in the Klang Valley area of Malaysia. The biochemical parameters were determined from fasting blood samples, whereas information on dietary intake and timing was obtained from a 7-day diet history questionnaire. The midpoint of eating was used to determine the early and late windows. Compared to MHO non-shift workers (n = 173), MUO non-shift workers (n = 126) had lower energy intake from carbohydrates and protein during the early window. In contrast, MUO participants had greater energy intake from carbohydrates and fat during the late window. Participants with unhealthy metabolic status (regardless of their chronotypes) had similar temporal patterns of energy intake characterized by smaller energy intake during the early window and greater energy intake during the late window compared with participants with healthier metabolic status. Overall, the lowest percentile of energy intake during the early window was associated with an increased risk of MUO, after adjustment for potential confounders [odds ratio (OR) = 4.30, 95% confidence interval (CI) 1.41–13.11]. The greater the energy intake during the late window, the greater the risk of MUO (OR = 2.38, 95% CI 1.11–5.13) (OR = 2.33, 95% CI 1.03–5.32) (OR = 4.45, 95% CI 1.71–11.56). In summary, consuming less energy earlier in the day and more energy and carbohydrate later in the day was associated with a greater risk of MUO. Thus, a prospective study is needed to explore the potential role of chrono-nutrition practices in modifying risk factors to delay the transition of MHO to MUO.