This paper reviews studies performed to date that have employed cluster or factor analysis to empirically derive eating patterns. Since 1980, at least 93 studies were published that used cluster or factor analysis to define dietary exposures, of which 65 were used to test hypotheses or examine associations between patterns and disease outcomes or biomarkers. Studies were conducted in diverse populations across many countries and continents and suggest that patterns are associated with many different biomarkers and disease outcomes, whether measured by cluster or factor analysis. Despite clear differences in approaches and interpretations, there is some evidence that underlying eating patterns are revealed by either method. Although the research considered herein has created a meaningful body of literature, refining both the factor and cluster analysis methods will help to further establish eating patterns as a sound dietary assessment method.

BackgroundSelf-monitoring of blood pressure (BP) appears to reduce BP in hypertension but important questions remain regarding effective implementation and which groups may benefit most. This individual patient data (IPD) meta-analysis was performed to better understand the effectiveness of BP self-monitoring to lower BP and control hypertension.Methods and findingsMedline, Embase, and the Cochrane Library were searched for randomised trials comparing self-monitoring to no self-monitoring in hypertensive patients (June 2016). Two reviewers independently assessed articles for eligibility and the authors of eligible trials were approached requesting IPD. Of 2,846 articles in the initial search, 36 were eligible. IPD were provided from 25 trials, including 1 unpublished study. Data for the primary outcomes—change in mean clinic or ambulatory BP and proportion controlled below target at 12 months—were available from 15/19 possible studies (7,138/8,292 [86%] of randomised participants). Overall, self-monitoring was associated with reduced clinic systolic blood pressure (sBP) compared to usual care at 12 months (−3.2 mmHg, [95% CI −4.9, −1.6 mmHg]). However, this effect was strongly influenced by the intensity of co-intervention ranging from no effect with self-monitoring alone (−1.0 mmHg [−3.3, 1.2]), to a 6.1 mmHg (−9.0, −3.2) reduction when monitoring was combined with intensive support. Self-monitoring was most effective in those with fewer antihypertensive medications and higher baseline sBP up to 170 mmHg. No differences in efficacy were seen by sex or by most comorbidities. Ambulatory BP data at 12 months were available from 4 trials (1,478 patients), which assessed self-monitoring with little or no co-intervention. There was no association between self-monitoring and either lower clinic or ambulatory sBP in this group (clinic −0.2 mmHg [−2.2, 1.8]; ambulatory 1.1 mmHg [−0.3, 2.5]). Results for diastolic blood pressure (dBP) were similar. The main limitation of this work was that significant heterogeneity remained. This was at least in part due to different inclusion criteria, self-monitoring regimes, and target BPs in included studies.ConclusionsSelf-monitoring alone is not associated with lower BP or better control, but in conjunction with co-interventions (including systematic medication titration by doctors, pharmacists, or patients; education; or lifestyle counselling) leads to clinically significant BP reduction which persists for at least 12 months. The implementation of self-monitoring in hypertension should be accompanied by such co-interventions.

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Few studies have evaluated risk factors for bone loss in elderly women and men. Thus, we examined risk factors for 4-year longitudinal change in bone mineral density (BMD) at the hip, radius, and spine in elders. Eight hundred elderly women and men from the population-based Framingham Osteoporosis Study had BMD assessed in 1988 -1989 and again in 1992-1993. BMD was measured at femoral neck, trochanter, Ward's area, radial shaft, ultradistal radius, and lumbar spine using Lunar densitometers. We examined the relation of the following factors at baseline to percent BMD loss: age, weight, change in weight, height, smoking, caffeine, alcohol use, physical activity, serum 25-OH vitamin D, calcium intake, and current estrogen replacement in women. Multivariate regression analyses were conducted with simultaneous adjustment for all variables. Mean age at baseline was 74 years ؎ 4.5 years (range, 67-90 years). Average 4-year BMD loss for women (range, 3.4 -4.8%) was greater than the loss for men (range, 0.2-3.6%) at all sites; however, BMD fell with age in both elderly women and elderly men. For women, lower baseline weight, weight loss in interim, and greater alcohol use were associated with BMD loss. Women who gained weight during the interim gained BMD or had little change in BMD. For women, current estrogen users had less bone loss than nonusers; at the femoral neck, nonusers lost up to 2.7% more BMD. For men, lower baseline weight and weight loss also were associated with BMD loss. Men who smoked cigarettes at baseline lost more BMD at the trochanter site. Surprisingly, bone loss was not affected by caffeine, physical activity, serum 25-OH vitamin D, or calcium intake. Risk factors consistently associated with bone loss in elders include female sex, thinness, and weight loss, while weight gain appears to protect against bone loss for both men and women. This population-based study suggests that current estrogen use may help to maintain bone in women, whereas current smoking was associated with bone loss in men. Even in the elderly years, potentially modifiable risk factors, such as weight, estrogen use, and cigarette smoking are important components of bone health. (J Bone Miner Res 2000;15:710 -720)